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Guo Y, Ma S, Wang D, Mei F, Guo Y, Heng BC, Zhang S, Huang Y, Wei Y, He Y, Liu W, Xu M, Zhang X, Chen L, Deng X. HtrA3 paves the way for MSC migration and promotes osteogenesis. Bioact Mater 2024; 38:399-410. [PMID: 38774457 PMCID: PMC11107107 DOI: 10.1016/j.bioactmat.2024.05.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 05/06/2024] [Accepted: 05/07/2024] [Indexed: 05/24/2024] Open
Abstract
Mesenchymal stem cell (MSC) migration determines the healing capacity of bone and is crucial in promoting bone regeneration. Migration of MSCs is highly dependent on degradation of extracellular matrix by proteolytic enzymes. However, the underlying mechanisms of how enzymolysis paves the way for MSCs to migrate from their niche to the defect area is still not fully understood. Here, this study shows that high-temperature requirement A3 (HtrA3) overcomes the physical barrier and provides anchor points through collagen IV degradation, paving the way for MSC migration. HtrA3 is upregulated in MSCs at the leading edge of bone defect during the early stage of healing. HtrA3 degrades the surrounding collagen IV, which increases the collagen network porosity and increases integrin β1 expression. Subsequently, integrin β1 enhances the mechanotransduction of MSCs, thus remodeling the cytoskeleton, increasing cellular stiffness and nuclear translocation of YAP, eventually promoting the migration and subsequent osteogenic differentiation of MSCs. Local administration of recombinant HtrA3 in rat cranial bone defects significantly increases new bone formation and further validates the enhancement of MSC migration. This study helps to reveal the novel roles of HtrA3, explore potential targets for regenerative medicine, and offer new insights for the development of bioactive materials.
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Affiliation(s)
- Yaru Guo
- Department of Geriatric Dentistry, Peking University School and Hospital of Stomatology, Beijing, 100081, China
| | - Siqin Ma
- Department of Stomatology, PLA General Hospital, First Affiliated Hospital (304 Hospital), Beijing, 100081, China
| | - Dandan Wang
- Department of Pediatric Dentistry, Peking University School and Hospital of Stomatology, Beijing, 100081, China
| | - Feng Mei
- Department of Stomatology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
- School of Stomatology, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Yusi Guo
- Department of Geriatric Dentistry, Peking University School and Hospital of Stomatology, Beijing, 100081, China
| | - Boon Chin Heng
- Central Laboratory, Peking University School and Hospital of Stomatology, Beijing, 100081, China
| | - Shihan Zhang
- Department of Geriatric Dentistry, Peking University School and Hospital of Stomatology, Beijing, 100081, China
| | - Ying Huang
- Department of Geriatric Dentistry, Peking University School and Hospital of Stomatology, Beijing, 100081, China
| | - Yan Wei
- Department of Geriatric Dentistry, Peking University School and Hospital of Stomatology, Beijing, 100081, China
| | - Ying He
- Department of Geriatric Dentistry, Peking University School and Hospital of Stomatology, Beijing, 100081, China
| | - Wenwen Liu
- Department of Geriatric Dentistry, Peking University School and Hospital of Stomatology, Beijing, 100081, China
| | - Mingming Xu
- Department of Geriatric Dentistry, Peking University School and Hospital of Stomatology, Beijing, 100081, China
| | - Xuehui Zhang
- NMPA Key Laboratory for Dental Materials, Department of Dental Materials & Dental Medical Devices Testing Center, Peking University School and Hospital of Stomatology, Beijing, 100081, China
- National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Beijing Laboratory of Biomedical Materials, Peking University School and Hospital of Stomatology, Beijing, 100081, China
| | - Lili Chen
- Department of Stomatology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
- School of Stomatology, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Xuliang Deng
- Department of Geriatric Dentistry, Peking University School and Hospital of Stomatology, Beijing, 100081, China
- NMPA Key Laboratory for Dental Materials, Department of Dental Materials & Dental Medical Devices Testing Center, Peking University School and Hospital of Stomatology, Beijing, 100081, China
- National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Beijing Laboratory of Biomedical Materials, Peking University School and Hospital of Stomatology, Beijing, 100081, China
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Guo Q, Liu W, Zhao L, Sui Y, Zhao H, Liu Y, Mu C, Wang X. Fermented bile acids improved growth performance and intestinal health by altering metabolic profiles and intestinal microbiome in Micropterus salmoides. Fish Shellfish Immunol 2024; 149:109593. [PMID: 38697374 DOI: 10.1016/j.fsi.2024.109593] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 04/25/2024] [Accepted: 04/28/2024] [Indexed: 05/05/2024]
Abstract
A type of fermented bile acids (FBAs) has been produced through a biological method, and its effects on growth performance, metabolism, and intestinal microbiota in largemouth bass were investigated. The results demonstrated that incorporating 0.03 %-0.05 % FBAs diet could improve the final weight, weight gain and specific growth rate, and decrease the feed conversion ratio. Dietary FBAs did not significantly affect the levels of high-density lipoprotein, low-density lipoprotein, and triglycerides, but decreased the activities of α-amylase in most groups. Adding FBAs to the diet significantly increased the integrity of the microscopic structure of the intestine, thickened the muscular layer of the intestine, and notably enhanced its intestinal barrier function. The addition of FBAs to the diet increased the diversity of the gut microbiota in largemouth bass. At the phylum level, there was an increase in the abundance of Proteobacteria, Firmicutes, Tenericutes and Cyanobacteria and a significant decrease in Actinobacteria and Bacteroidetes. At the genus level, the relative abundance of beneficial bacteria Mycoplasma in the GN6 group and Coprococcus in the GN4 group significantly increased, while the pathogenic Enhydrobacter was inhibited. Meanwhile, the highest levels of AKP and ACP were observed in the groups treated with 0.03 % FBAs, while the highest levels of TNF-α and IL-10 were detected in the group treated with 0.04 % FBAs. Additionally, the highest levels of IL-1β, IL-8T, GF-β, IGF-1, and IFN-γ were noted in the group treated with 0.06 % FBAs. These results suggested that dietary FBAs improved growth performance and intestinal wall health by altering lipid metabolic profiles and intestinal microbiota in largemouth bass.
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Affiliation(s)
- Qing Guo
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention & Shandong Provincial Engineering Technology Research Center of Animal Disease Control and Prevention, Shandong Agricultural University, Taian, 271018, PR China; Anhui Chem-Bright Bioengineering Co., Ltd, Huaibei, 235025, PR China
| | - Wenwen Liu
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention & Shandong Provincial Engineering Technology Research Center of Animal Disease Control and Prevention, Shandong Agricultural University, Taian, 271018, PR China
| | - Lu Zhao
- Anhui Chem-Bright Bioengineering Co., Ltd, Huaibei, 235025, PR China
| | - Yiming Sui
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention & Shandong Provincial Engineering Technology Research Center of Animal Disease Control and Prevention, Shandong Agricultural University, Taian, 271018, PR China; Jining Leyuhui Ecological Agriculture Development Co., Ltd, Jining, 272000, PR China
| | - Houfa Zhao
- Anhui Chem-Bright Bioengineering Co., Ltd, Huaibei, 235025, PR China
| | - Yining Liu
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention & Shandong Provincial Engineering Technology Research Center of Animal Disease Control and Prevention, Shandong Agricultural University, Taian, 271018, PR China; Jining Leyuhui Ecological Agriculture Development Co., Ltd, Jining, 272000, PR China
| | - Cuimin Mu
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention & Shandong Provincial Engineering Technology Research Center of Animal Disease Control and Prevention, Shandong Agricultural University, Taian, 271018, PR China.
| | - Xuepeng Wang
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention & Shandong Provincial Engineering Technology Research Center of Animal Disease Control and Prevention, Shandong Agricultural University, Taian, 271018, PR China.
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Wang H, Du X, Liu W, Zhang C, Li Y, Hou J, Yu Y, Li G, Wang Q. Combination of betulinic acid and EGFR-TKIs exerts synergistic anti-tumor effects against wild-type EGFR NSCLC by inducing autophagy-related cell death via EGFR signaling pathway. Respir Res 2024; 25:215. [PMID: 38764025 PMCID: PMC11103851 DOI: 10.1186/s12931-024-02844-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2024] [Accepted: 05/09/2024] [Indexed: 05/21/2024] Open
Abstract
BACKGROUND Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) have revolutionized the treatment of lung cancer patients with mutated EGFR. However, the efficacy of EGFR-TKIs in wild-type EGFR tumors has been shown to be marginal. Methods that can sensitize EGFR-TKIs to EGFR wild-type NSCLC remain rare. Hence, we determined whether combination treatment can maximize the therapeutic efficacy of EGFR-TKIs. METHODS We established a focused drug screening system to investigate candidates for overcoming the intrinsic resistance of wild-type EGFR NSCLC to EGFR-TKIs. Molecular docking assays and western blotting were used to identify the binding mode and blocking effect of the candidate compounds. Proliferation assays, analyses of drug interactions, colony formation assays, flow cytometry and nude mice xenograft models were used to determine the effects and investigate the molecular mechanism of the combination treatment. RESULTS Betulinic acid (BA) is effective at targeting EGFR and synergizes with EGFR-TKIs (gefitinib and osimertinib) preferentially against wild-type EGFR. BA showed inhibitory activity due to its interaction with the ATP-binding pocket of EGFR and dramatically enhanced the suppressive effects of EGFR-TKIs by blocking EGFR and modulating the EGFR-ATK-mTOR axis. Mechanistic studies revealed that the combination strategy activated EGFR-induced autophagic cell death and that the EGFR-AKT-mTOR signaling pathway was essential for completing autophagy and cell cycle arrest. Activation of the mTOR pathway or blockade of autophagy by specific chemical agents markedly attenuated the effect of cell cycle arrest. In vivo administration of the combination treatment caused marked tumor regression in the A549 xenografts. CONCLUSIONS BA is a potential wild-type EGFR inhibitor that plays a critical role in sensitizing EGFR-TKI activity. BA combined with an EGFR-TKI effectively suppressed the proliferation and survival of intrinsically resistant lung cancer cells via the inhibition of EGFR as well as the induction of autophagy-related cell death, indicating that BA combined with an EGFR-TKI may be a potential therapeutic strategy for overcoming the primary resistance of wild-type EGFR-positive lung cancers.
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Affiliation(s)
- Han Wang
- The Second Hospital of Dalian Medical University, Dalian, 116023, China
- Guangzhou women and children's medical center, Guangzhou Medical University, Guangzhou, 510623, China
| | - Xiaohui Du
- The Second Hospital of Dalian Medical University, Dalian, 116023, China
| | - Wenwen Liu
- The Second Hospital of Dalian Medical University, Dalian, 116023, China
| | - Congcong Zhang
- The Second Hospital of Dalian Medical University, Dalian, 116023, China
| | - Ying Li
- The Second Hospital of Dalian Medical University, Dalian, 116023, China
| | - Jingwen Hou
- The Second Hospital of Dalian Medical University, Dalian, 116023, China
| | - Yi Yu
- The Second Hospital of Dalian Medical University, Dalian, 116023, China
| | - Guiru Li
- The Second Hospital of Dalian Medical University, Dalian, 116023, China.
| | - Qi Wang
- The Second Hospital of Dalian Medical University, Dalian, 116023, China.
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Huang M, Zhang Q, Jiao J, Shi J, Xu Y, Zhang C, Zhou R, Liu W, Liang Y, Chen H, Wang Y, Xu Z, Hu P. Comprehensive genetic analysis of facioscapulohumeral muscular dystrophy by Nanopore long-read whole-genome sequencing. J Transl Med 2024; 22:451. [PMID: 38741136 DOI: 10.1186/s12967-024-05259-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Accepted: 04/29/2024] [Indexed: 05/16/2024] Open
Abstract
BACKGROUND Facioscapulohumeral muscular dystrophy (FSHD) is a high-prevalence autosomal dominant neuromuscular disease characterized by significant clinical and genetic heterogeneity. Genetic diagnosis of FSHD remains a challenge because it cannot be detected by standard sequencing methods and requires a complex diagnosis workflow. METHODS We developed a comprehensive genetic FSHD detection method based on Oxford Nanopore Technologies (ONT) whole-genome sequencing. Using a case-control design, we applied this procedure to 29 samples and compared the results with those from optical genome mapping (OGM), bisulfite sequencing (BSS), and whole-exome sequencing (WES). RESULTS Using our ONT-based method, we identified 59 haplotypes (35 4qA and 24 4qB) among the 29 samples (including a mosaic sample), as well as the number of D4Z4 repeat units (RUs). The pathogenetic D4Z4 RU contraction identified by our ONT-based method showed 100% concordance with OGM results. The methylation levels of the most distal D4Z4 RU and the double homeobox 4 gene (DUX4) detected by ONT sequencing are highly consistent with the BSS results and showed excellent diagnostic efficiency. Additionally, our ONT-based method provided an independent methylation profile analysis of two permissive 4qA alleles, reflecting a more accurate scenario than traditional BSS. The ONT-based method detected 17 variations in three FSHD2-related genes from nine samples, showing 100% concordance with WES. CONCLUSIONS Our ONT-based FSHD detection method is a comprehensive method for identifying pathogenetic D4Z4 RU contractions, methylation level alterations, allele-specific methylation of two 4qA haplotypes, and variations in FSHD2-related genes, which will all greatly improve genetic testing for FSHD.
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Affiliation(s)
- Mingtao Huang
- Department of Prenatal Diagnosis, Women's Hospital of Nanjing Medical University, Nanjing Women and Children's Healthcare Hospital, 123 Tianfei Alley, Mochou Road, Nanjing, Jiangsu, 210004, People's Republic of China
| | - Qinxin Zhang
- Department of Prenatal Diagnosis, Women's Hospital of Nanjing Medical University, Nanjing Women and Children's Healthcare Hospital, 123 Tianfei Alley, Mochou Road, Nanjing, Jiangsu, 210004, People's Republic of China
| | - Jiao Jiao
- Department of Prenatal Diagnosis, Women's Hospital of Nanjing Medical University, Nanjing Women and Children's Healthcare Hospital, 123 Tianfei Alley, Mochou Road, Nanjing, Jiangsu, 210004, People's Republic of China
| | - Jianquan Shi
- Department of Neurology, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, 210006, People's Republic of China
| | - Yiyun Xu
- Department of Prenatal Diagnosis, Women's Hospital of Nanjing Medical University, Nanjing Women and Children's Healthcare Hospital, 123 Tianfei Alley, Mochou Road, Nanjing, Jiangsu, 210004, People's Republic of China
| | - Cuiping Zhang
- Department of Prenatal Diagnosis, Women's Hospital of Nanjing Medical University, Nanjing Women and Children's Healthcare Hospital, 123 Tianfei Alley, Mochou Road, Nanjing, Jiangsu, 210004, People's Republic of China
| | - Ran Zhou
- Department of Prenatal Diagnosis, Women's Hospital of Nanjing Medical University, Nanjing Women and Children's Healthcare Hospital, 123 Tianfei Alley, Mochou Road, Nanjing, Jiangsu, 210004, People's Republic of China
| | - Wenwen Liu
- Department of Prenatal Diagnosis, Women's Hospital of Nanjing Medical University, Nanjing Women and Children's Healthcare Hospital, 123 Tianfei Alley, Mochou Road, Nanjing, Jiangsu, 210004, People's Republic of China
| | - Yixuan Liang
- Department of Prenatal Diagnosis, Women's Hospital of Nanjing Medical University, Nanjing Women and Children's Healthcare Hospital, 123 Tianfei Alley, Mochou Road, Nanjing, Jiangsu, 210004, People's Republic of China
| | - Hao Chen
- Department of Prenatal Diagnosis, Women's Hospital of Nanjing Medical University, Nanjing Women and Children's Healthcare Hospital, 123 Tianfei Alley, Mochou Road, Nanjing, Jiangsu, 210004, People's Republic of China
| | - Yan Wang
- Department of Prenatal Diagnosis, Women's Hospital of Nanjing Medical University, Nanjing Women and Children's Healthcare Hospital, 123 Tianfei Alley, Mochou Road, Nanjing, Jiangsu, 210004, People's Republic of China.
| | - Zhengfeng Xu
- Department of Prenatal Diagnosis, Women's Hospital of Nanjing Medical University, Nanjing Women and Children's Healthcare Hospital, 123 Tianfei Alley, Mochou Road, Nanjing, Jiangsu, 210004, People's Republic of China.
| | - Ping Hu
- Department of Prenatal Diagnosis, Women's Hospital of Nanjing Medical University, Nanjing Women and Children's Healthcare Hospital, 123 Tianfei Alley, Mochou Road, Nanjing, Jiangsu, 210004, People's Republic of China.
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Tang M, Xu M, Wang J, Liu Y, Liang K, Jin Y, Duan W, Xia S, Li G, Chu H, Liu W, Wang Q. Brain Metastasis from EGFR-Mutated Non-Small Cell Lung Cancer: Secretion of IL11 from Astrocytes Up-Regulates PDL1 and Promotes Immune Escape. Adv Sci (Weinh) 2024:e2306348. [PMID: 38696655 DOI: 10.1002/advs.202306348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 03/24/2024] [Indexed: 05/04/2024]
Abstract
Patients who have non-small cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR) mutations are more prone to brain metastasis (BM) and poor prognosis. Previous studies showed that the tumor microenvironment of BM in these patients is immunosuppressed, as indicated by reduced T-cell abundance and activity, although the mechanism of this immunosuppression requires further study. This study shows that reactive astrocytes play a critical role in promoting the immune escape of BM from EGFR-mutated NSCLC by increasing the apoptosis of CD8+ T lymphocytes. The increased secretion of interleukin 11(IL11) by astrocytes promotes the expression of PDL1 in BM, and this is responsible for the increased apoptosis of T lymphocytes. IL11 functions as a ligand of EGFR, and this binding activates EGFR and downstream signaling to increase the expression of PDL1, culminating in the immune escape of tumor cells. IL11 also promotes immune escape by binding to its intrinsic receptor (IL11Rα/glycoprotein 130 [gp130]). Additional in vivo studies show that the targeted inhibition of gp130 and EGFR suppresses the growth of BM and prolongs the survival time of mice. These results suggest a novel therapeutic strategy for treatment of NSCLC patients with EGFR mutations.
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Affiliation(s)
- Mengyi Tang
- the Second Affiliated Hospital of Dalian Medical University, 467 Zhongshan Road, Dalian, 116027, China
| | - Mingxin Xu
- the Second Affiliated Hospital of Dalian Medical University, 467 Zhongshan Road, Dalian, 116027, China
| | - Jian Wang
- the Second Affiliated Hospital of Dalian Medical University, 467 Zhongshan Road, Dalian, 116027, China
| | - Ye Liu
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Science, 457 Zhongshan Road, Dalian, 116023, China
| | - Kun Liang
- the Second Affiliated Hospital of Dalian Medical University, 467 Zhongshan Road, Dalian, 116027, China
| | - Yinuo Jin
- the Second Affiliated Hospital of Dalian Medical University, 467 Zhongshan Road, Dalian, 116027, China
| | - Wenzhe Duan
- the Second Affiliated Hospital of Dalian Medical University, 467 Zhongshan Road, Dalian, 116027, China
| | - Shengkai Xia
- the Second Affiliated Hospital of Dalian Medical University, 467 Zhongshan Road, Dalian, 116027, China
| | - Guohui Li
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Science, 457 Zhongshan Road, Dalian, 116023, China
| | - Huiying Chu
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Science, 457 Zhongshan Road, Dalian, 116023, China
| | - Wenwen Liu
- the Second Affiliated Hospital of Dalian Medical University, 467 Zhongshan Road, Dalian, 116027, China
- Cancer Translational Medicine Research Center, The Second Hospital, Dalian, Medical University, 467 Zhongshan Road, Dalian, 116027, China
| | - Qi Wang
- the Second Affiliated Hospital of Dalian Medical University, 467 Zhongshan Road, Dalian, 116027, China
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Li J, Fan H, Liu W, Zhang J, Xiao Y, Peng Y, Yang W, Liu W, He Y, Qin L, Ma X, Li J. Mesenchymal stem cells promote ovarian reconstruction in mice. Stem Cell Res Ther 2024; 15:115. [PMID: 38650029 PMCID: PMC11036642 DOI: 10.1186/s13287-024-03718-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Accepted: 04/07/2024] [Indexed: 04/25/2024] Open
Abstract
BACKGROUND Studies have shown that chemotherapy and radiotherapy can cause premature ovarian failure and loss of fertility in female cancer patients. Ovarian cortex cryopreservation is a good choice to preserve female fertility before cancer treatment. Following the remission of the disease, the thawed ovarian tissue can be transplanted back and restore fertility of the patient. However, there is a risk to reintroduce cancer cells in the body and leads to the recurrence of cancer. Given the low success rate of current in vitro culture techniques for obtaining mature oocytes from primordial follicles, an artificial ovary with primordial follicles may be a good way to solve this problem. METHODS In the study, we established an artificial ovary model based on the participation of mesenchymal stem cells (MSCs) to evaluate the effect of MSCs on follicular development and oocyte maturation. P2.5 mouse ovaries were digested into single cell suspensions and mixed with bone marrow derived mesenchymal stem cells (BM-MSCs) at a 1:1 ratio. The reconstituted ovarian model was then generated by using phytohemagglutinin. The phenotype and mechanism studies were explored by follicle counting, immunohistochemistry, immunofluorescence, in vitro maturation (IVM), in vitro fertilization (IVF), real-time quantitative polymerase chain reaction (RT-PCR), and Terminal-deoxynucleotidyl transferase mediated nick end labeling(TUNEL) assay. RESULTS Our study found that the addition of BM-MSCs to the reconstituted ovary can enhance the survival of oocytes and promote the growth and development of follicles. After transplanting the reconstituted ovaries under kidney capsules of the recipient mice, we observed normal folliculogenesis and oocyte maturation. Interestingly, we found that BM-MSCs did not contribute to the formation of follicles in ovarian aggregation, nor did they undergo proliferation during follicle growth. Instead, the cells were found to be located around growing follicles in the reconstituted ovary. When theca cells were labeled with CYP17a1, we found some overlapped staining with green fluorescent protein(GFP)-labeled BM-MSCs. The results suggest that BM-MSCs may participate in directing the differentiation of theca layer in the reconstituted ovary. CONCLUSIONS The presence of BM-MSCs in the artificial ovary was found to promote the survival of ovarian cells, as well as facilitate follicle formation and development. Since the cells didn't proliferate in the reconstituted ovary, this discovery suggests a potential new and safe method for the application of MSCs in clinical fertility preservation by enhancing the success rate of cryo-thawed ovarian tissues after transplantation.
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Affiliation(s)
- Jiazhao Li
- State Key Laboratory of Reproductive Medicine and Offspring health, Nanjing Medical University, 210029, Nanjing, China
- Scientific Research Department, Wannan Medical College, 241002, Wuhu, China
| | - Haonan Fan
- State Key Laboratory of Reproductive Medicine and Offspring health, Nanjing Medical University, 210029, Nanjing, China
| | - Wei Liu
- State Key Laboratory of Reproductive Medicine and Offspring health, Nanjing Medical University, 210029, Nanjing, China
| | - Jing Zhang
- State Key Laboratory of Reproductive Medicine and Offspring health, Nanjing Medical University, 210029, Nanjing, China
| | - Yue Xiao
- State Key Laboratory of Reproductive Medicine and Offspring health, Nanjing Medical University, 210029, Nanjing, China
- Center of Reproductive Medicine, The First Affiliated Hospital of Zhejiang University School of Medicine, 310003, Hangzhou, China
| | - Yue Peng
- State Key Laboratory of Reproductive Medicine and Offspring health, Nanjing Medical University, 210029, Nanjing, China
- Pathology Department, Nanjing Kingmed Medical Laboratory Co.,Ltd., 210032, Nanjing, China
| | - Weijie Yang
- State Key Laboratory of Reproductive Medicine and Offspring health, Nanjing Medical University, 210029, Nanjing, China
- Assisted Reproduction Unit, Department of Obstetrics and Gynecology, Sir Run Run Shaw Hospital, Key Laboratory of Reproductive Dysfunction Management of Zhejiang Province, Zhejiang University School of Medicine, 310016, Hangzhou, China
| | - Wenwen Liu
- State Key Laboratory of Reproductive Medicine and Offspring health, Nanjing Medical University, 210029, Nanjing, China
- Women's Hospital of Nanjing Medical University (Nanjing Maternity and Child Health Care Hospital), 21003, Nanjing, China
| | - Yuanlin He
- State Key Laboratory of Reproductive Medicine and Offspring health, Nanjing Medical University, 210029, Nanjing, China
| | - Lianju Qin
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center of Clinical Reproductive Medicine, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical University, 210029, Nanjing, China.
| | - Xiang Ma
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center of Clinical Reproductive Medicine, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical University, 210029, Nanjing, China.
- Prenatal Diagnosis Department, First Affiliated Hospital, Nanjing Medical University, 210029, Nanjing, China.
| | - Jing Li
- State Key Laboratory of Reproductive Medicine and Offspring health, Nanjing Medical University, 210029, Nanjing, China.
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Liu L, Zhang M, Cui N, Liu W, Di G, Wang Y, Xi X, Li H, Shen Z, Gu M, Wang Z, Jiang S, Liu B. Integration of single-cell RNA-seq and bulk RNA-seq to construct liver hepatocellular carcinoma stem cell signatures to explore their impact on patient prognosis and treatment. PLoS One 2024; 19:e0298004. [PMID: 38635528 PMCID: PMC11025768 DOI: 10.1371/journal.pone.0298004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 01/11/2024] [Indexed: 04/20/2024] Open
Abstract
BACKGROUND Liver hepatocellular carcinoma (LIHC) is a prevalent form of primary liver cancer. Research has demonstrated the contribution of tumor stem cells in facilitating tumor recurrence, metastasis, and treatment resistance. Despite this, there remains a lack of established cancer stem cells (CSCs)-associated genes signatures for effectively predicting the prognosis and guiding the treatment strategies for patients diagnosed with LIHC. METHODS The single-cell RNA sequencing (scRNA-seq) and bulk RNA transcriptome data were obtained based on public datasets and computerized firstly using CytoTRACE package and One Class Linear Regression (OCLR) algorithm to evaluate stemness level, respectively. Then, we explored the association of stemness indicators (CytoTRACE score and stemness index, mRNAsi) with survival outcomes and clinical characteristics by combining clinical information and survival analyses. Subsequently, weighted co-expression network analysis (WGCNA) and Cox were applied to assess mRNAsi-related genes in bulk LIHC data and construct a prognostic model for LIHC patients. Single-sample gene-set enrichment analysis (ssGSEA), Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) and Tumor Immune Estimation Resource (TIMER) analysis were employed for immune infiltration assessment. Finally, the potential immunotherapeutic response was predicted by the Tumor Immune Dysfunction and Exclusion (TIDE), and the tumor mutation burden (TMB). Additionally, pRRophetic package was applied to evaluate the sensitivity of high and low-risk groups to common chemotherapeutic drugs. RESULTS A total of four genes (including STIP1, H2AFZ, BRIX1, and TUBB) associated with stemness score (CytoTRACE score and mRNAsi) were identified and constructed a risk model that could predict prognosis in LIHC patients. It was observed that high stemness cells occurred predominantly in the late stages of LIHC and that poor overall survival in LIHC patients was also associated with high mRNAsi scores. In addition, pathway analysis confirmed the biological uniqueness of the two risk groups. Personalized treatment predictions suggest that patients with a low risk benefited more from immunotherapy, while those with a high risk group may be conducive to chemotherapeutic drugs. CONCLUSION The current study developed a novel prognostic risk signature with genes related to CSCs, which provides novel ideas for the diagnosis, prognosis and treatment of LIHC.
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Affiliation(s)
- Lixia Liu
- Department of Ultrasound and Hebei Key Laboratory of Precise Imaging of Inflammation Related Tumors, Affiliated Hospital of Hebei University, Baoding, 071052, China
| | - Meng Zhang
- Department of Hepatobiliary Surgery, Affiliated Hospital of Hebei University, Baoding, 071052, China
| | - Naipeng Cui
- Department of Breast Surgery, Affiliated Hospital of Hebei University, Baoding, 071052, China
| | - Wenwen Liu
- Department of Breast Surgery, Affiliated Hospital of Hebei University, Baoding, 071052, China
| | - Guixin Di
- Department of Ultrasound, Affiliated Hospital of Hebei University, Baoding, 071052, China
| | - Yanan Wang
- Department of Pathology, Affiliated Hospital of Hebei University, Baoding, 071052, China
| | - Xin Xi
- Central Laboratory, Hebei Key Laboratory of Cancer Radiotherapy and Chemotherapy, Affiliated Hospital of Hebei University, Baoding, 071052, China
| | - Hao Li
- Central Laboratory, Hebei Key Laboratory of Cancer Radiotherapy and Chemotherapy, Affiliated Hospital of Hebei University, Baoding, 071052, China
| | - Zhou Shen
- Central Laboratory, Hebei Key Laboratory of Cancer Radiotherapy and Chemotherapy, Affiliated Hospital of Hebei University, Baoding, 071052, China
| | - Miaomiao Gu
- Department of Ultrasound, Affiliated Hospital of Hebei University, Baoding, 071052, China
| | - Zichao Wang
- Department of Ultrasound, Affiliated Hospital of Hebei University, Baoding, 071052, China
| | - Shan Jiang
- Central Laboratory, Hebei Key Laboratory of Cancer Radiotherapy and Chemotherapy, Affiliated Hospital of Hebei University, Baoding, 071052, China
| | - Bin Liu
- Central Laboratory, Hebei Key Laboratory of Cancer Radiotherapy and Chemotherapy, Affiliated Hospital of Hebei University, Baoding, 071052, China
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8
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Zhao S, Jiang H, Miao Y, Liu W, Li Y, Zhang Y, Wang A, Cui X. Effects of implementing non-nutritive sucking on oral feeding progression and outcomes in preterm infants: A systematic review and meta-analysis. PLoS One 2024; 19:e0302267. [PMID: 38626172 PMCID: PMC11020483 DOI: 10.1371/journal.pone.0302267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2023] [Accepted: 03/29/2024] [Indexed: 04/18/2024] Open
Abstract
BACKGROUND Preterm infants have imperfect neurological development, uncoordinated sucking-swallowing-breathing, which makes it difficult to realize effective oral feeding after birth. How to help preterm infants achieve complete oral feeding as soon as possible has become an important issue in the management of preterm infants. Non-nutritive sucking (NNS), as a useful oral stimulation, can improve the effect of oral feeding in preterm infants. This review aimed to explore the effect of NNS on oral feeding progression through a meta-analysis. METHODS We systematically searched PubMed, CINHAL, Web of Science, Embase, Cochrane databases, China's National Knowledge Infrastructure (CNKI), Wanfang and VIP database from inception to January 20, 2024. Search terms included 'non-nutritive sucking' 'oral feeding' and 'premature.' Eligibility criteria involved randomized controlled studies in English or Chinese. Studies were excluded if they were reviews, case reports, or observational studies from which valid data could not be extracted or outcome indicators were poorly defined. The meta-analysis will utilize Review Manager 5.3 software, employing either random-effects or fixed-effects models based on observed heterogeneity. We calculated the mean difference (MD) and 95% confidence interval (CI) for continuous data, and estimated pooled odds ratios (ORs) for dichotomous data. Sensitivity and publication bias analyses were conducted to ensure robust and reliable findings. We evaluated the methodological quality of randomized controlled trials (RCTs) utilizing the assessment tool provided by the Cochrane Collaboration. RESULTS A total of 23 randomized controlled trials with 1461 preterm infants were included. The results of the meta-analysis showed that NNS significantly shortened time taken to achieve exclusive oral feeding (MD = -5.37,95%CI = -7.48 to-3.26, p<0.001), length of hospital stay(MD = -4.92, 95% CI = -6.76 to -3.09, p<0.001), time to start oral feeding(MD = -1.41, 95% CI = -2.36 to -0.45, p = 0.004), time to return to birth weight(MD = -1.72, 95% CI = -2.54 to -0.91, p<0.001). Compared to the NNS group, the control group had significant weight gain in preterm infants, including weight of discharge (MD = -61.10, 95% CI = -94.97 to -27.23, p = 0.0004), weight at full oral feeding (MD = -86.21, 95% CI = -134.37 to -38.05, p = 0.0005). In addition, NNS reduced the incidence of feeding intolerance (OR = 0.22, 95% CI = 0.14 to 0.35, p<0.001) in preterm infants. CONCLUSION NNS improves oral feeding outcomes in preterm infants and reduces the time to reach full oral feeding and hospitalization length. However, this study was limited by the relatively small sample size of included studies and did not account for potential confounding factors. There was some heterogeneity and bias between studies. More studies are needed in the future to validate the effects on weight gain and growth in preterm infants. Nevertheless, our meta-analysis provides valuable insights, updating existing evidence on NNS for improving oral feeding in preterm infants and promoting evidence-based feeding practices in this population.
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Affiliation(s)
- Shuliang Zhao
- Nursing Department, Affiliated Hospital of Shandong Second Medical University, Weifang, China
- School of Nursing, Shandong Second Medical University, Weifang, China
| | - Huimin Jiang
- School of Nursing, Shandong Second Medical University, Weifang, China
| | - Yiqun Miao
- School of Nursing, Capital Medical University, Beijing, China
| | - Wenwen Liu
- Xiangya School of Nursing, Central South University, Changsha, China
| | - Yanan Li
- School of Nursing, Shandong Second Medical University, Weifang, China
| | - Yuanyuan Zhang
- School of Nursing, Shandong Second Medical University, Weifang, China
| | - Aihua Wang
- School of Nursing, Shandong Second Medical University, Weifang, China
| | - Xinghui Cui
- Nursing Department, Affiliated Hospital of Shandong Second Medical University, Weifang, China
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9
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Jia Y, Liu W, Wang J, Zhang R, Li M, Liu S. A pair of twins with multicystic dysplastic kidney and hydrocephalus caused by a novel homozygous mutation in SPATA33 and CDK10. QJM 2024; 117:302-303. [PMID: 38180891 DOI: 10.1093/qjmed/hcad289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Indexed: 01/07/2024] Open
Affiliation(s)
- Y Jia
- Medical Genetic Department, The Affiliated Hospital of Qingdao University, NO.16 Jiang Su Road, Qingdao 266071, China
- Prenatal Diagnosis Center, The Affiliated Hospital of Qingdao University, NO.16 Jiang Su Road, Qingdao 266071, China
| | - W Liu
- Medical Genetic Department, The Affiliated Hospital of Qingdao University, NO.16 Jiang Su Road, Qingdao 266071, China
- Prenatal Diagnosis Center, The Affiliated Hospital of Qingdao University, NO.16 Jiang Su Road, Qingdao 266071, China
| | - J Wang
- Medical Genetic Department, The Affiliated Hospital of Qingdao University, NO.16 Jiang Su Road, Qingdao 266071, China
- Prenatal Diagnosis Center, The Affiliated Hospital of Qingdao University, NO.16 Jiang Su Road, Qingdao 266071, China
| | - R Zhang
- Medical Genetic Department, The Affiliated Hospital of Qingdao University, NO.16 Jiang Su Road, Qingdao 266071, China
- Prenatal Diagnosis Center, The Affiliated Hospital of Qingdao University, NO.16 Jiang Su Road, Qingdao 266071, China
| | - M Li
- Department of Urology, Qingdao Municipal Hospital Group, NO.5 Middle Dong Hai Road, Qingdao 266071, China
| | - S Liu
- Medical Genetic Department, The Affiliated Hospital of Qingdao University, NO.16 Jiang Su Road, Qingdao 266071, China
- Prenatal Diagnosis Center, The Affiliated Hospital of Qingdao University, NO.16 Jiang Su Road, Qingdao 266071, China
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10
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Rosenberg E, Andersen TI, Samajdar R, Petukhov A, Hoke JC, Abanin D, Bengtsson A, Drozdov IK, Erickson C, Klimov PV, Mi X, Morvan A, Neeley M, Neill C, Acharya R, Allen R, Anderson K, Ansmann M, Arute F, Arya K, Asfaw A, Atalaya J, Bardin JC, Bilmes A, Bortoli G, Bourassa A, Bovaird J, Brill L, Broughton M, Buckley BB, Buell DA, Burger T, Burkett B, Bushnell N, Campero J, Chang HS, Chen Z, Chiaro B, Chik D, Cogan J, Collins R, Conner P, Courtney W, Crook AL, Curtin B, Debroy DM, Barba ADT, Demura S, Di Paolo A, Dunsworth A, Earle C, Faoro L, Farhi E, Fatemi R, Ferreira VS, Burgos LF, Forati E, Fowler AG, Foxen B, Garcia G, Genois É, Giang W, Gidney C, Gilboa D, Giustina M, Gosula R, Dau AG, Gross JA, Habegger S, Hamilton MC, Hansen M, Harrigan MP, Harrington SD, Heu P, Hill G, Hoffmann MR, Hong S, Huang T, Huff A, Huggins WJ, Ioffe LB, Isakov SV, Iveland J, Jeffrey E, Jiang Z, Jones C, Juhas P, Kafri D, Khattar T, Khezri M, Kieferová M, Kim S, Kitaev A, Klots AR, Korotkov AN, Kostritsa F, Kreikebaum JM, Landhuis D, Laptev P, Lau KM, Laws L, Lee J, Lee KW, Lensky YD, Lester BJ, Lill AT, Liu W, Locharla A, Mandrà S, Martin O, Martin S, McClean JR, McEwen M, Meeks S, Miao KC, Mieszala A, Montazeri S, Movassagh R, Mruczkiewicz W, Nersisyan A, Newman M, Ng JH, Nguyen A, Nguyen M, Niu MY, O'Brien TE, Omonije S, Opremcak A, Potter R, Pryadko LP, Quintana C, Rhodes DM, Rocque C, Rubin NC, Saei N, Sank D, Sankaragomathi K, Satzinger KJ, Schurkus HF, Schuster C, Shearn MJ, Shorter A, Shutty N, Shvarts V, Sivak V, Skruzny J, Smith WC, Somma RD, Sterling G, Strain D, Szalay M, Thor D, Torres A, Vidal G, Villalonga B, Heidweiller CV, White T, Woo BWK, Xing C, Yao ZJ, Yeh P, Yoo J, Young G, Zalcman A, Zhang Y, Zhu N, Zobrist N, Neven H, Babbush R, Bacon D, Boixo S, Hilton J, Lucero E, Megrant A, Kelly J, Chen Y, Smelyanskiy V, Khemani V, Gopalakrishnan S, Prosen T, Roushan P. Dynamics of magnetization at infinite temperature in a Heisenberg spin chain. Science 2024; 384:48-53. [PMID: 38574139 DOI: 10.1126/science.adi7877] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 03/01/2024] [Indexed: 04/06/2024]
Abstract
Understanding universal aspects of quantum dynamics is an unresolved problem in statistical mechanics. In particular, the spin dynamics of the one-dimensional Heisenberg model were conjectured as to belong to the Kardar-Parisi-Zhang (KPZ) universality class based on the scaling of the infinite-temperature spin-spin correlation function. In a chain of 46 superconducting qubits, we studied the probability distribution of the magnetization transferred across the chain's center, [Formula: see text]. The first two moments of [Formula: see text] show superdiffusive behavior, a hallmark of KPZ universality. However, the third and fourth moments ruled out the KPZ conjecture and allow for evaluating other theories. Our results highlight the importance of studying higher moments in determining dynamic universality classes and provide insights into universal behavior in quantum systems.
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Affiliation(s)
- E Rosenberg
- Google Research, Mountain View, CA, USA
- Department of Physics, Cornell University, Ithaca, NY, USA
| | | | - R Samajdar
- Department of Physics, Princeton University, Princeton, NJ, USA
- Princeton Center for Theoretical Science, Princeton University, Princeton, NJ, USA
| | | | - J C Hoke
- Department of Physics, Stanford University, Stanford, CA, USA
| | - D Abanin
- Google Research, Mountain View, CA, USA
| | | | - I K Drozdov
- Google Research, Mountain View, CA, USA
- Department of Physics, University of Connecticut, Storrs, CT, USA
| | | | | | - X Mi
- Google Research, Mountain View, CA, USA
| | - A Morvan
- Google Research, Mountain View, CA, USA
| | - M Neeley
- Google Research, Mountain View, CA, USA
| | - C Neill
- Google Research, Mountain View, CA, USA
| | - R Acharya
- Google Research, Mountain View, CA, USA
| | - R Allen
- Google Research, Mountain View, CA, USA
| | | | - M Ansmann
- Google Research, Mountain View, CA, USA
| | - F Arute
- Google Research, Mountain View, CA, USA
| | - K Arya
- Google Research, Mountain View, CA, USA
| | - A Asfaw
- Google Research, Mountain View, CA, USA
| | - J Atalaya
- Google Research, Mountain View, CA, USA
| | - J C Bardin
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, USA
| | - A Bilmes
- Google Research, Mountain View, CA, USA
| | - G Bortoli
- Google Research, Mountain View, CA, USA
| | | | - J Bovaird
- Google Research, Mountain View, CA, USA
| | - L Brill
- Google Research, Mountain View, CA, USA
| | | | | | - D A Buell
- Google Research, Mountain View, CA, USA
| | - T Burger
- Google Research, Mountain View, CA, USA
| | - B Burkett
- Google Research, Mountain View, CA, USA
| | | | - J Campero
- Google Research, Mountain View, CA, USA
| | - H-S Chang
- Google Research, Mountain View, CA, USA
| | - Z Chen
- Google Research, Mountain View, CA, USA
| | - B Chiaro
- Google Research, Mountain View, CA, USA
| | - D Chik
- Google Research, Mountain View, CA, USA
| | - J Cogan
- Google Research, Mountain View, CA, USA
| | - R Collins
- Google Research, Mountain View, CA, USA
| | - P Conner
- Google Research, Mountain View, CA, USA
| | | | - A L Crook
- Google Research, Mountain View, CA, USA
| | - B Curtin
- Google Research, Mountain View, CA, USA
| | | | | | - S Demura
- Google Research, Mountain View, CA, USA
| | | | | | - C Earle
- Google Research, Mountain View, CA, USA
| | - L Faoro
- Google Research, Mountain View, CA, USA
| | - E Farhi
- Google Research, Mountain View, CA, USA
| | - R Fatemi
- Google Research, Mountain View, CA, USA
| | | | | | - E Forati
- Google Research, Mountain View, CA, USA
| | | | - B Foxen
- Google Research, Mountain View, CA, USA
| | - G Garcia
- Google Research, Mountain View, CA, USA
| | - É Genois
- Google Research, Mountain View, CA, USA
| | - W Giang
- Google Research, Mountain View, CA, USA
| | - C Gidney
- Google Research, Mountain View, CA, USA
| | - D Gilboa
- Google Research, Mountain View, CA, USA
| | | | - R Gosula
- Google Research, Mountain View, CA, USA
| | | | - J A Gross
- Google Research, Mountain View, CA, USA
| | | | - M C Hamilton
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, USA
| | - M Hansen
- Google Research, Mountain View, CA, USA
| | | | | | - P Heu
- Google Research, Mountain View, CA, USA
| | - G Hill
- Google Research, Mountain View, CA, USA
| | | | - S Hong
- Google Research, Mountain View, CA, USA
| | - T Huang
- Google Research, Mountain View, CA, USA
| | - A Huff
- Google Research, Mountain View, CA, USA
| | | | - L B Ioffe
- Google Research, Mountain View, CA, USA
| | | | - J Iveland
- Google Research, Mountain View, CA, USA
| | - E Jeffrey
- Google Research, Mountain View, CA, USA
| | - Z Jiang
- Google Research, Mountain View, CA, USA
| | - C Jones
- Google Research, Mountain View, CA, USA
| | - P Juhas
- Google Research, Mountain View, CA, USA
| | - D Kafri
- Google Research, Mountain View, CA, USA
| | - T Khattar
- Google Research, Mountain View, CA, USA
| | - M Khezri
- Google Research, Mountain View, CA, USA
| | - M Kieferová
- Google Research, Mountain View, CA, USA
- QSI, Faculty of Engineering & Information Technology, University of Technology Sydney, Ultimo, NSW, Australia
| | - S Kim
- Google Research, Mountain View, CA, USA
| | - A Kitaev
- Google Research, Mountain View, CA, USA
| | - A R Klots
- Google Research, Mountain View, CA, USA
| | - A N Korotkov
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of California, Riverside, CA, USA
| | | | | | | | - P Laptev
- Google Research, Mountain View, CA, USA
| | - K-M Lau
- Google Research, Mountain View, CA, USA
| | - L Laws
- Google Research, Mountain View, CA, USA
| | - J Lee
- Google Research, Mountain View, CA, USA
- Department of Chemistry, Columbia University, New York, NY, USA
| | - K W Lee
- Google Research, Mountain View, CA, USA
| | | | | | - A T Lill
- Google Research, Mountain View, CA, USA
| | - W Liu
- Google Research, Mountain View, CA, USA
| | | | - S Mandrà
- Google Research, Mountain View, CA, USA
| | - O Martin
- Google Research, Mountain View, CA, USA
| | - S Martin
- Google Research, Mountain View, CA, USA
| | | | - M McEwen
- Google Research, Mountain View, CA, USA
| | - S Meeks
- Google Research, Mountain View, CA, USA
| | - K C Miao
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - M Newman
- Google Research, Mountain View, CA, USA
| | - J H Ng
- Google Research, Mountain View, CA, USA
| | - A Nguyen
- Google Research, Mountain View, CA, USA
| | - M Nguyen
- Google Research, Mountain View, CA, USA
| | - M Y Niu
- Google Research, Mountain View, CA, USA
| | | | - S Omonije
- Google Research, Mountain View, CA, USA
| | | | - R Potter
- Google Research, Mountain View, CA, USA
| | - L P Pryadko
- Department of Physics and Astronomy, University of California, Riverside, CA, USA
| | | | | | - C Rocque
- Google Research, Mountain View, CA, USA
| | - N C Rubin
- Google Research, Mountain View, CA, USA
| | - N Saei
- Google Research, Mountain View, CA, USA
| | - D Sank
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - A Shorter
- Google Research, Mountain View, CA, USA
| | - N Shutty
- Google Research, Mountain View, CA, USA
| | - V Shvarts
- Google Research, Mountain View, CA, USA
| | - V Sivak
- Google Research, Mountain View, CA, USA
| | - J Skruzny
- Google Research, Mountain View, CA, USA
| | | | - R D Somma
- Google Research, Mountain View, CA, USA
| | | | - D Strain
- Google Research, Mountain View, CA, USA
| | - M Szalay
- Google Research, Mountain View, CA, USA
| | - D Thor
- Google Research, Mountain View, CA, USA
| | - A Torres
- Google Research, Mountain View, CA, USA
| | - G Vidal
- Google Research, Mountain View, CA, USA
| | | | | | - T White
- Google Research, Mountain View, CA, USA
| | - B W K Woo
- Google Research, Mountain View, CA, USA
| | - C Xing
- Google Research, Mountain View, CA, USA
| | | | - P Yeh
- Google Research, Mountain View, CA, USA
| | - J Yoo
- Google Research, Mountain View, CA, USA
| | - G Young
- Google Research, Mountain View, CA, USA
| | - A Zalcman
- Google Research, Mountain View, CA, USA
| | - Y Zhang
- Google Research, Mountain View, CA, USA
| | - N Zhu
- Google Research, Mountain View, CA, USA
| | - N Zobrist
- Google Research, Mountain View, CA, USA
| | - H Neven
- Google Research, Mountain View, CA, USA
| | - R Babbush
- Google Research, Mountain View, CA, USA
| | - D Bacon
- Google Research, Mountain View, CA, USA
| | - S Boixo
- Google Research, Mountain View, CA, USA
| | - J Hilton
- Google Research, Mountain View, CA, USA
| | - E Lucero
- Google Research, Mountain View, CA, USA
| | - A Megrant
- Google Research, Mountain View, CA, USA
| | - J Kelly
- Google Research, Mountain View, CA, USA
| | - Y Chen
- Google Research, Mountain View, CA, USA
| | | | - V Khemani
- Department of Physics, Stanford University, Stanford, CA, USA
| | | | - T Prosen
- Faculty of Mathematics and Physics, University of Ljubljana, Ljubljana, Slovenia
| | - P Roushan
- Google Research, Mountain View, CA, USA
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11
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Xia S, Duan W, Xu M, Li M, Tang M, Wei S, Lin M, Li E, Liu W, Wang Q. Mesothelin promotes brain metastasis of non-small cell lung cancer by activating MET. J Exp Clin Cancer Res 2024; 43:103. [PMID: 38570866 PMCID: PMC10988939 DOI: 10.1186/s13046-024-03015-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Accepted: 03/18/2024] [Indexed: 04/05/2024] Open
Abstract
BACKGROUND Brain metastasis (BM) is common among cases of advanced non-small cell lung cancer (NSCLC) and is the leading cause of death for these patients. Mesothelin (MSLN), a tumor-associated antigen expressed in many solid tumors, has been reported to be involved in the progression of multiple tumors. However, its potential involvement in BM of NSCLC and the underlying mechanism remain unknown. METHODS The expression of MSLN was validated in clinical tissue and serum samples using immunohistochemistry and enzyme-linked immunosorbent assay. The ability of NSCLC cells to penetrate the blood-brain barrier (BBB) was examined using an in vitro Transwell model and an ex vivo multi-organ microfluidic bionic chip. Immunofluorescence staining and western blotting were used to detect the disruption of tight junctions. In vivo BBB leakiness assay was performed to assess the barrier integrity. MET expression and activation was detected by western blotting. The therapeutic efficacy of drugs targeting MSLN (anetumab) and MET (crizotinib/capmatinib) on BM was evaluated in animal studies. RESULTS MSLN expression was significantly elevated in both serum and tumor tissue samples from NSCLC patients with BM and correlated with a poor clinical prognosis. MSLN significantly enhanced the brain metastatic abilities of NSCLC cells, especially BBB extravasation. Mechanistically, MSLN facilitated the expression and activation of MET through the c-Jun N-terminal kinase (JNK) signaling pathway, which allowed tumor cells to disrupt tight junctions and the integrity of the BBB and thereby penetrate the barrier. Drugs targeting MSLN (anetumab) and MET (crizotinib/capmatinib) effectively blocked the development of BM and prolonged the survival of mice. CONCLUSIONS Our results demonstrate that MSLN plays a critical role in BM of NSCLC by modulating the JNK/MET signaling network and thus, provides a potential novel therapeutic target for preventing BM in NSCLC patients.
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Affiliation(s)
- Shengkai Xia
- Department of Respiratory Medicine, The Second Hospital, Dalian Medical University, Dalian, China
| | - Wenzhe Duan
- Department of Respiratory Medicine, The Second Hospital, Dalian Medical University, Dalian, China
| | - Mingxin Xu
- Department of Respiratory Medicine, The Second Hospital, Dalian Medical University, Dalian, China
| | - Mengqi Li
- Department of Respiratory Medicine, The Second Hospital, Dalian Medical University, Dalian, China
| | - Mengyi Tang
- Department of Respiratory Medicine, The Second Hospital, Dalian Medical University, Dalian, China
| | - Song Wei
- Department of Oncology, Beijing Chest Hospital, Capital Medical University, Beijing, China
| | - Manqing Lin
- Department of Respiratory Medicine, The Second Hospital, Dalian Medical University, Dalian, China
| | - Encheng Li
- Department of Respiratory Medicine, The Second Hospital, Dalian Medical University, Dalian, China.
| | - Wenwen Liu
- Department of Respiratory Medicine, The Second Hospital, Dalian Medical University, Dalian, China.
- Department of Scientific Research Center, The Second Hospital, Dalian Medical University, Dalian, China.
| | - Qi Wang
- Department of Respiratory Medicine, The Second Hospital, Dalian Medical University, Dalian, China.
- Department of Scientific Research Center, The Second Hospital, Dalian Medical University, Dalian, China.
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12
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Yu X, Xiang J, Zhang Q, Chen S, Tang W, Li X, Sui Y, Liu W, Kong Q, Guo Y. Corrigendum to Triple-negative breast cancer: predictive model of early recurrence based on MRI features [78 (11) e798-e807]. Clin Radiol 2024; 79:e640. [PMID: 38316571 DOI: 10.1016/j.crad.2024.01.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2024]
Affiliation(s)
- X Yu
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - J Xiang
- Guangdong Women and Children Hospital, No. 13 West Guangyuan Road, Guangzhou, Guangdong, 510010, China
| | - Q Zhang
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - S Chen
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - W Tang
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - X Li
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - Y Sui
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - W Liu
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China.
| | - Q Kong
- Department of Radiology, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510630, China.
| | - Y Guo
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China.
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13
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Qi W, Cui L, Jiajue R, Pang Q, Chi Y, Liu W, Jiang Y, Wang O, Li M, Xing X, Tong A, Xia W. Deteriorated bone microarchitecture caused by sympathetic overstimulation in pheochromocytoma and paraganglioma. J Endocrinol Invest 2024; 47:843-856. [PMID: 37872466 DOI: 10.1007/s40618-023-02198-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 09/12/2023] [Indexed: 10/25/2023]
Abstract
PURPOSE Despite the potentially destructive effect of sympathetic activity on bone metabolism, its impact on bone microarchitecture, a key determinant of bone quality, has not been thoroughly investigated. This study aims to evaluate the impact of sympathetic activity on bone microarchitecture and bone strength in patients with pheochromocytoma and paraganglioma (PPGL). METHODS A cross-sectional study was conducted in 38 PPGL patients (15 males and 23 females). Bone turnover markers serum procollagen type 1 N-terminal propeptide (P1NP) and β-carboxy-terminal crosslinked telopeptide of type 1 collagen (β-CTX) were measured. 24-h urinary adrenaline (24hUE) and 24-h urinary norepinephrine levels (24hUNE) were measured to indicate sympathetic activity. High-resolution peripheral quantitative computed tomography (HR-pQCT) was conducted to evaluate bone microarchitecture in PPGL patients and 76 age-, sex-matched healthy controls (30 males and 46 females). Areal bone mineral density (aBMD) was measured by dual-energy X-ray absorptiometry (DXA) simultaneously. RESULTS PPGL patients had a higher level of β-CTX. HR-pQCT assessment revealed that PPGL patients had notably thinner and more sparse trabecular bone (decreased trabecular number and thickness with increased trabecular separation), significantly decreased volume BMD (vBMD), and bone strength at both the radius and tibia compared with healthy controls. The deterioration of Tt.vBMD, Tb.Sp, and Tb.1/N.SD was more pronounced in postmenopausal patients compared with the premenopausal subjects. Moreover, subjects in the highest 24hUNE quartile (Q4) showed markedly lower Tb.N and higher Tb.Sp and Tb.1/N.SD at the tibia than those in the lowest quartile (Q1). Age-related bone loss was also exacerbated in PPGL patients to a certain extent. CONCLUSIONS PPGL patients had significantly deteriorated bone microarchitecture and strength, especially in the trabecular bone, with an increased bone resorption rate. Our findings provide clinical evidence that sympathetic overstimulation may serve as a secondary cause of osteoporosis, especially in subjects with increased sympathetic activity.
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Affiliation(s)
- W Qi
- Department of Endocrinology, Key Laboratory of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Dongcheng District, National Commission of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Beijing, 100730, China
| | - L Cui
- Department of Endocrinology, Key Laboratory of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Dongcheng District, National Commission of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Beijing, 100730, China
| | - R Jiajue
- Department of Endocrinology, Key Laboratory of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Dongcheng District, National Commission of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Beijing, 100730, China
| | - Q Pang
- Department of Endocrinology, Key Laboratory of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Dongcheng District, National Commission of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Beijing, 100730, China
| | - Y Chi
- Department of Endocrinology, Key Laboratory of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Dongcheng District, National Commission of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Beijing, 100730, China
| | - W Liu
- Department of Endocrinology, Key Laboratory of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Dongcheng District, National Commission of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Beijing, 100730, China
| | - Y Jiang
- Department of Endocrinology, Key Laboratory of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Dongcheng District, National Commission of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Beijing, 100730, China
| | - O Wang
- Department of Endocrinology, Key Laboratory of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Dongcheng District, National Commission of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Beijing, 100730, China
| | - M Li
- Department of Endocrinology, Key Laboratory of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Dongcheng District, National Commission of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Beijing, 100730, China
| | - X Xing
- Department of Endocrinology, Key Laboratory of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Dongcheng District, National Commission of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Beijing, 100730, China
| | - A Tong
- Department of Endocrinology, Key Laboratory of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Dongcheng District, National Commission of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Beijing, 100730, China.
| | - W Xia
- Department of Endocrinology, Key Laboratory of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Dongcheng District, National Commission of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Beijing, 100730, China.
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14
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Wen X, Zhao C, Zhao B, Yuan M, Chang J, Liu W, Meng J, Shi L, Yang S, Zeng J, Yang Y. Application of deep learning in radiation therapy for cancer. Cancer Radiother 2024; 28:208-217. [PMID: 38519291 DOI: 10.1016/j.canrad.2023.07.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 07/17/2023] [Accepted: 07/18/2023] [Indexed: 03/24/2024]
Abstract
In recent years, with the development of artificial intelligence, deep learning has been gradually applied to clinical treatment and research. It has also found its way into the applications in radiotherapy, a crucial method for cancer treatment. This study summarizes the commonly used and latest deep learning algorithms (including transformer, and diffusion models), introduces the workflow of different radiotherapy, and illustrates the application of different algorithms in different radiotherapy modules, as well as the defects and challenges of deep learning in the field of radiotherapy, so as to provide some help for the development of automatic radiotherapy for cancer.
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Affiliation(s)
- X Wen
- Cancer Institute of the Affiliated Hospital of Qingdao University and Qingdao Cancer Institute, Qingdao University, Qingdao, China; Department of Radiotherapy, Yunnan Cancer Hospital, the Third Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - C Zhao
- School of Biomedical Engineering, Shanghai Jiao Tong University, No. 800, Dongchuan Road, Minhang District, Shanghai, China
| | - B Zhao
- Department of Radiotherapy, Yunnan Cancer Hospital, the Third Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - M Yuan
- Department of Radiotherapy, Yunnan Cancer Hospital, the Third Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - J Chang
- Cancer Institute of the Affiliated Hospital of Qingdao University and Qingdao Cancer Institute, Qingdao University, Qingdao, China; School of Basic Medicine, Qingdao University, Qingdao, China
| | - W Liu
- Cancer Institute of the Affiliated Hospital of Qingdao University and Qingdao Cancer Institute, Qingdao University, Qingdao, China; School of Basic Medicine, Qingdao University, Qingdao, China
| | - J Meng
- Cancer Institute of the Affiliated Hospital of Qingdao University and Qingdao Cancer Institute, Qingdao University, Qingdao, China; School of Basic Medicine, Qingdao University, Qingdao, China
| | - L Shi
- Cancer Institute of the Affiliated Hospital of Qingdao University and Qingdao Cancer Institute, Qingdao University, Qingdao, China; School of Basic Medicine, Qingdao University, Qingdao, China
| | - S Yang
- Cancer Institute of the Affiliated Hospital of Qingdao University and Qingdao Cancer Institute, Qingdao University, Qingdao, China; School of Basic Medicine, Qingdao University, Qingdao, China
| | - J Zeng
- Cancer Institute of the Affiliated Hospital of Qingdao University and Qingdao Cancer Institute, Qingdao University, Qingdao, China; School of Basic Medicine, Qingdao University, Qingdao, China
| | - Y Yang
- Department of Radiotherapy, Yunnan Cancer Hospital, the Third Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China.
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15
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Yang Q, Yi SH, Fu BS, Zhang T, Zeng KN, Feng X, Yao J, Tang H, Li H, Zhang J, Zhang YC, Yi HM, Lyu HJ, Liu JR, Luo GJ, Ge M, Yao WF, Ren FF, Zhuo JF, Luo H, Zhu LP, Ren J, Lyu Y, Wang KX, Liu W, Chen GH, Yang Y. [Clinical application of split liver transplantation: a single center report of 203 cases]. Zhonghua Wai Ke Za Zhi 2024; 62:324-330. [PMID: 38432674 DOI: 10.3760/cma.j.cn112139-20231225-00297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 03/05/2024]
Abstract
Objective: To investigate the safety and therapeutic effect of split liver transplantation (SLT) in clinical application. Methods: This is a retrospective case-series study. The clinical data of 203 consecutive SLT, 79 living donor liver transplantation (LDLT) and 1 298 whole liver transplantation (WLT) performed at the Third Affiliated Hospital of Sun Yat-sen University from July 2014 to July 2023 were retrospectively analyzed. Two hundred and three SLT liver grafts were obtained from 109 donors. One hundred and twenty-seven grafts were generated by in vitro splitting and 76 grafts were generated by in vivo splitting. There were 90 adult recipients and 113 pediatric recipients. According to time, SLT patients were divided into two groups: the early SLT group (40 cases, from July 2014 to December 2017) and the mature SLT technology group (163 cases, from January 2018 to July 2023). The survival of each group was analyzed and the main factors affecting the survival rate of SLT were analyzed. The Kaplan-Meier method and Log-rank test were used for survival analysis. Results: The cumulative survival rates at 1-, 3-, and 5-year were 74.58%, 71.47%, and 71.47% in the early SLT group, and 88.03%, 87.23%, and 87.23% in the mature SLT group, respectively. Survival rates in the mature SLT group were significantly higher than those in the early SLT group (χ2=5.560,P=0.018). The cumulative survival rates at 1-, 3- and 5-year were 93.41%, 93.41%, 89.95% in the LDLT group and 87.38%, 81.98%, 77.04% in the WLT group, respectively. There was no significant difference among the mature SLT group, the LDLT group and the WLT group (χ2=4.016, P=0.134). Abdominal hemorrhage, infection, primary liver graft nonfunction,and portal vein thrombosis were the main causes of early postoperative death. Conclusion: SLT can achieve results comparable to those of WLT and LDLT in mature technology liver transplant centers, but it needs to go through a certain time learning curve.
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Affiliation(s)
- Q Yang
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
| | - S H Yi
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
| | - B S Fu
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
| | - T Zhang
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
| | - K N Zeng
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
| | - X Feng
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
| | - J Yao
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
| | - H Tang
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
| | - H Li
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
| | - J Zhang
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
| | - Y C Zhang
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
| | - H M Yi
- Organ transplant Intensive Care Unit, the Third Affiliated Hospital of Sun Yat-sen University,Guangzhou 510630
| | - H J Lyu
- Organ transplant Intensive Care Unit, the Third Affiliated Hospital of Sun Yat-sen University,Guangzhou 510630
| | - J R Liu
- Organ transplant Intensive Care Unit, the Third Affiliated Hospital of Sun Yat-sen University,Guangzhou 510630
| | - G J Luo
- Anesthesia & Surgery Center, the Third Affiliated Hospital of Sun Yat-sen University ,Guangzhou 510630
| | - M Ge
- Anesthesia & Surgery Center, the Third Affiliated Hospital of Sun Yat-sen University ,Guangzhou 510630
| | - W F Yao
- Anesthesia & Surgery Center, the Third Affiliated Hospital of Sun Yat-sen University ,Guangzhou 510630
| | - F F Ren
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
| | - J F Zhuo
- Organ transplant Intensive Care Unit, the Third Affiliated Hospital of Sun Yat-sen University,Guangzhou 510630
| | - H Luo
- Anesthesia & Surgery Center, the Third Affiliated Hospital of Sun Yat-sen University ,Guangzhou 510630
| | - L P Zhu
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
| | - J Ren
- Ultrasound Department of the Third Affiliated Hospital of Sun Yat-sen University,Guangzhou 510630
| | - Y Lyu
- Ultrasound Department of the Third Affiliated Hospital of Sun Yat-sen University,Guangzhou 510630
| | - K X Wang
- Organ Donation Department of the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China
| | - W Liu
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
| | - G H Chen
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
| | - Y Yang
- Liver Surgery & Liver Transplantation Center, the Third Affiliated Hospital of Sun Yat-sen University, Institute of Organ Transplantation, Sun Yat-sen University, Guangdong Organ Transplantation Research Center, Guangdong Transplantation Medical Engineering Laboratory, Guangdong Provincial Key Laboratory of Liver Diseases, Guangzhou 510630
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Liu W, Zhao Z, Hou S, Lu Y. Alkaline liquid-derived Na xTi11.5MoVO x/C-40 material with controlled electron transfer rate for sensitive electrochemical detection of dopamine. Talanta 2024; 270:125540. [PMID: 38096738 DOI: 10.1016/j.talanta.2023.125540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Revised: 12/05/2023] [Accepted: 12/08/2023] [Indexed: 01/27/2024]
Abstract
The neurotransmitter dopamine (DA) is associated with many physiological and pathological processes, so the importance of low detection limits and high sensitivity analysis cannot be overstated, especially for early disease detection. Here, 2 M NaOH aqueous solution is used to precipitate metal ions in an ethanol solution containing carbon black (CB), and then nanocomposite catalysts (NaxTi11.5MoVOx/C-40 (40 denoted as 40 mg CB)) were obtained by calcining the precipitation. When used for DA detection, NaxVOx acts as the main active site for electrochemical oxidation of DA and NaxTi11.5MoOx plays a role in facilitating the binding of DA to the active site and stabilizing the active site. The NaxTi11.5MoVOx/C-40 electrochemical biosensor has a limit of detection (LOD) of 0.003 μM with a linear range of 0.005-51.665 μM for DA. This sensor can be used to sensitively identify the concentration of DA in human blood and urine. Catalysts containing varying amounts of CB exhibit diverse electron transfer rates, and surprisingly, we found that the appropriate electron transfer rate is optimal for the detection of low concentrations of DA. Because the performance of the electrochemical biosensors is affected by both the activity of the catalysts and the accuracy of the electrochemical testing instrumentation. To better explain this phenomenon, we propose the concept of resolution (Rn) and present the formula to derive it, offering a new approach to evaluating the performance of electrochemical biosensors.
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Affiliation(s)
- Wenwen Liu
- School of Material Science and Engineering, University of Jinan, Jinan, 250022, Shandong, China.
| | - Zhenlu Zhao
- School of Material Science and Engineering, University of Jinan, Jinan, 250022, Shandong, China; Anhui Laboratory of Functional Coordinated Complexes for Materials Chemistry and Application, School of Chemical and Environmental Engineering, Anhui Polytechnic University, Wuhu, 241000, China.
| | - Shuping Hou
- State Key Lab of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, 130022, Jilin, China.
| | - Yizhong Lu
- School of Material Science and Engineering, University of Jinan, Jinan, 250022, Shandong, China.
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17
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Miled MB, Liu W, Liu Y. Adaptive Unsupervised Learning-Based 3D Spatiotemporal Filter for Event-Driven Cameras. Research (Wash D C) 2024; 7:0330. [PMID: 38562525 PMCID: PMC10981976 DOI: 10.34133/research.0330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Accepted: 02/06/2024] [Indexed: 04/04/2024]
Abstract
In the evolving landscape of robotics and visual navigation, event cameras have gained important traction, notably for their exceptional dynamic range, efficient power consumption, and low latency. Despite these advantages, conventional processing methods oversimplify the data into 2 dimensions, neglecting critical temporal information. To overcome this limitation, we propose a novel method that treats events as 3D time-discrete signals. Drawing inspiration from the intricate biological filtering systems inherent to the human visual apparatus, we have developed a 3D spatiotemporal filter based on unsupervised machine learning algorithm. This filter effectively reduces noise levels and performs data size reduction, with its parameters being dynamically adjusted based on population activity. This ensures adaptability and precision under various conditions, like changes in motion velocity and ambient lighting. In our novel validation approach, we first identify the noise type and determine its power spectral density in the event stream. We then apply a one-dimensional discrete fast Fourier transform to assess the filtered event data within the frequency domain, ensuring that the targeted noise frequencies are adequately reduced. Our research also delved into the impact of indoor lighting on event stream noise. Remarkably, our method led to a 37% decrease in the data point cloud, improving data quality in diverse outdoor settings.
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Affiliation(s)
- Meriem Ben Miled
- Department of Mechanical Engineering,
University College London, London, UK
| | - Wenwen Liu
- School of Automation,
Nanjing University of Information, Science and Technology, Nanjing, China
| | - Yuanchang Liu
- Department of Mechanical Engineering,
University College London, London, UK
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18
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Cao Z, Aharonian F, Axikegu, Bai YX, Bao YW, Bastieri D, Bi XJ, Bi YJ, Bian W, Bukevich AV, Cao Q, Cao WY, Cao Z, Chang J, Chang JF, Chen AM, Chen ES, Chen HX, Chen L, Chen L, Chen L, Chen MJ, Chen ML, Chen QH, Chen S, Chen SH, Chen SZ, Chen TL, Chen Y, Cheng N, Cheng YD, Cui MY, Cui SW, Cui XH, Cui YD, Dai BZ, Dai HL, Dai ZG, Danzengluobu, Dong XQ, Duan KK, Fan JH, Fan YZ, Fang J, Fang JH, Fang K, Feng CF, Feng H, Feng L, Feng SH, Feng XT, Feng Y, Feng YL, Gabici S, Gao B, Gao CD, Gao Q, Gao W, Gao WK, Ge MM, Geng LS, Giacinti G, Gong GH, Gou QB, Gu MH, Guo FL, Guo XL, Guo YQ, Guo YY, Han YA, Hasan M, He HH, He HN, He JY, He Y, Hor YK, Hou BW, Hou C, Hou X, Hu HB, Hu Q, Hu SC, Huang DH, Huang TQ, Huang WJ, Huang XT, Huang XY, Huang Y, Ji XL, Jia HY, Jia K, Jiang K, Jiang XW, Jiang ZJ, Jin M, Kang MM, Karpikov I, Kuleshov D, Kurinov K, Li BB, Li CM, Li C, Li C, Li D, Li F, Li HB, Li HC, Li J, Li J, Li K, Li SD, Li WL, Li WL, Li XR, Li X, Li YZ, Li Z, Li Z, Liang EW, Liang YF, Lin SJ, Liu B, Liu C, Liu D, Liu DB, Liu H, Liu HD, Liu J, Liu JL, Liu MY, Liu RY, Liu SM, Liu W, Liu Y, Liu YN, Luo Q, Luo Y, Lv HK, Ma BQ, Ma LL, Ma XH, Mao JR, Min Z, Mitthumsiri W, Mu HJ, Nan YC, Neronov A, Ou LJ, Pattarakijwanich P, Pei ZY, Qi JC, Qi MY, Qiao BQ, Qin JJ, Raza A, Ruffolo D, Sáiz A, Saeed M, Semikoz D, Shao L, Shchegolev O, Sheng XD, Shu FW, Song HC, Stenkin YV, Stepanov V, Su Y, Sun DX, Sun QN, Sun XN, Sun ZB, Takata J, Tam PHT, Tang QW, Tang R, Tang ZB, Tian WW, Wang C, Wang CB, Wang GW, Wang HG, Wang HH, Wang JC, Wang K, Wang K, Wang LP, Wang LY, Wang PH, Wang R, Wang W, Wang XG, Wang XY, Wang Y, Wang YD, Wang YJ, Wang ZH, Wang ZX, Wang Z, Wang Z, Wei DM, Wei JJ, Wei YJ, Wen T, Wu CY, Wu HR, Wu QW, Wu S, Wu XF, Wu YS, Xi SQ, Xia J, Xiang GM, Xiao DX, Xiao G, Xin YL, Xing Y, Xiong DR, Xiong Z, Xu DL, Xu RF, Xu RX, Xu WL, Xue L, Yan DH, Yan JZ, Yan T, Yang CW, Yang CY, Yang F, Yang FF, Yang LL, Yang MJ, Yang RZ, Yang WX, Yao YH, Yao ZG, Yin LQ, Yin N, You XH, You ZY, Yu YH, Yuan Q, Yue H, Zeng HD, Zeng TX, Zeng W, Zha M, Zhang BB, Zhang F, Zhang H, Zhang HM, Zhang HY, Zhang JL, Zhang L, Zhang PF, Zhang PP, Zhang R, Zhang SB, Zhang SR, Zhang SS, Zhang X, Zhang XP, Zhang YF, Zhang Y, Zhang Y, Zhao B, Zhao J, Zhao L, Zhao LZ, Zhao SP, Zhao XH, Zheng F, Zhong WJ, Zhou B, Zhou H, Zhou JN, Zhou M, Zhou P, Zhou R, Zhou XX, Zhou XX, Zhu BY, Zhu CG, Zhu FR, Zhu H, Zhu KJ, Zou YC, Zuo X. Measurements of All-Particle Energy Spectrum and Mean Logarithmic Mass of Cosmic Rays from 0.3 to 30 PeV with LHAASO-KM2A. Phys Rev Lett 2024; 132:131002. [PMID: 38613275 DOI: 10.1103/physrevlett.132.131002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 01/23/2024] [Accepted: 02/12/2024] [Indexed: 04/14/2024]
Abstract
We present the measurements of all-particle energy spectrum and mean logarithmic mass of cosmic rays in the energy range of 0.3-30 PeV using data collected from LHAASO-KM2A between September 2021 and December 2022, which is based on a nearly composition-independent energy reconstruction method, achieving unprecedented accuracy. Our analysis reveals the position of the knee at 3.67±0.05±0.15 PeV. Below the knee, the spectral index is found to be -2.7413±0.0004±0.0050, while above the knee, it is -3.128±0.005±0.027, with the sharpness of the transition measured with a statistical error of 2%. The mean logarithmic mass of cosmic rays is almost heavier than helium in the whole measured energy range. It decreases from 1.7 at 0.3 PeV to 1.3 at 3 PeV, representing a 24% decline following a power law with an index of -0.1200±0.0003±0.0341. This is equivalent to an increase in abundance of light components. Above the knee, the mean logarithmic mass exhibits a power law trend towards heavier components, which is reversal to the behavior observed in the all-particle energy spectrum. Additionally, the knee position and the change in power-law index are approximately the same. These findings suggest that the knee observed in the all-particle spectrum corresponds to the knee of the light component, rather than the medium-heavy components.
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Affiliation(s)
- Zhen Cao
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - F Aharonian
- Dublin Institute for Advanced Studies, 31 Fitzwilliam Place, 2 Dublin, Ireland
- Max-Planck-Institut for Nuclear Physics, P.O. Box 103980, 69029 Heidelberg, Germany
| | - Axikegu
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - Y X Bai
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Y W Bao
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - D Bastieri
- Center for Astrophysics, Guangzhou University, 510006 Guangzhou, Guangdong, China
| | - X J Bi
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Y J Bi
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - W Bian
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - A V Bukevich
- Institute for Nuclear Research of Russian Academy of Sciences, 117312 Moscow, Russia
| | - Q Cao
- Hebei Normal University, 050024 Shijiazhuang, Hebei, China
| | - W Y Cao
- University of Science and Technology of China, 230026 Hefei, Anhui, China
| | - Zhe Cao
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - J Chang
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - J F Chang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - A M Chen
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - E S Chen
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - H X Chen
- Research Center for Astronomical Computing, Zhejiang Laboratory, 311121 Hangzhou, Zhejiang, China
| | - Liang Chen
- Key Laboratory for Research in Galaxies and Cosmology, Shanghai Astronomical Observatory, Chinese Academy of Sciences, 200030 Shanghai, China
| | - Lin Chen
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - Long Chen
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - M J Chen
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - M L Chen
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - Q H Chen
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - S Chen
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - S H Chen
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - S Z Chen
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - T L Chen
- Key Laboratory of Cosmic Rays (Tibet University), Ministry of Education, 850000 Lhasa, Tibet, China
| | - Y Chen
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - N Cheng
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Y D Cheng
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - M Y Cui
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - S W Cui
- Hebei Normal University, 050024 Shijiazhuang, Hebei, China
| | - X H Cui
- National Astronomical Observatories, Chinese Academy of Sciences, 100101 Beijing, China
| | - Y D Cui
- School of Physics and Astronomy (Zhuhai) and School of Physics (Guangzhou) and Sino-French Institute of Nuclear Engineering and Technology (Zhuhai), Sun Yat-sen University, 519000 Zhuhai and 510275 Guangzhou, Guangdong, China
| | - B Z Dai
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - H L Dai
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - Z G Dai
- University of Science and Technology of China, 230026 Hefei, Anhui, China
| | - Danzengluobu
- Key Laboratory of Cosmic Rays (Tibet University), Ministry of Education, 850000 Lhasa, Tibet, China
| | - X Q Dong
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - K K Duan
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - J H Fan
- Center for Astrophysics, Guangzhou University, 510006 Guangzhou, Guangdong, China
| | - Y Z Fan
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - J Fang
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - J H Fang
- Research Center for Astronomical Computing, Zhejiang Laboratory, 311121 Hangzhou, Zhejiang, China
| | - K Fang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - C F Feng
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - H Feng
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
| | - L Feng
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - S H Feng
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - X T Feng
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - Y Feng
- Research Center for Astronomical Computing, Zhejiang Laboratory, 311121 Hangzhou, Zhejiang, China
| | - Y L Feng
- Key Laboratory of Cosmic Rays (Tibet University), Ministry of Education, 850000 Lhasa, Tibet, China
| | - S Gabici
- APC, Université Paris Cité, CNRS/IN2P3, CEA/IRFU, Observatoire de Paris, 119 75205 Paris, France
| | - B Gao
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - C D Gao
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - Q Gao
- Key Laboratory of Cosmic Rays (Tibet University), Ministry of Education, 850000 Lhasa, Tibet, China
| | - W Gao
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - W K Gao
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - M M Ge
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - L S Geng
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - G Giacinti
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - G H Gong
- Department of Engineering Physics, Tsinghua University, 100084 Beijing, China
| | - Q B Gou
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - M H Gu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - F L Guo
- Key Laboratory for Research in Galaxies and Cosmology, Shanghai Astronomical Observatory, Chinese Academy of Sciences, 200030 Shanghai, China
| | - X L Guo
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - Y Q Guo
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Y Y Guo
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - Y A Han
- School of Physics and Microelectronics, Zhengzhou University, 450001 Zhengzhou, Henan, China
| | - M Hasan
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - H H He
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - H N He
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - J Y He
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - Y He
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - Y K Hor
- School of Physics and Astronomy (Zhuhai) and School of Physics (Guangzhou) and Sino-French Institute of Nuclear Engineering and Technology (Zhuhai), Sun Yat-sen University, 519000 Zhuhai and 510275 Guangzhou, Guangdong, China
| | - B W Hou
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - C Hou
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - X Hou
- Yunnan Observatories, Chinese Academy of Sciences, 650216 Kunming, Yunnan, China
| | - H B Hu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Q Hu
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - S C Hu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- China Center of Advanced Science and Technology, Beijing 100190, China
| | - D H Huang
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - T Q Huang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - W J Huang
- School of Physics and Astronomy (Zhuhai) and School of Physics (Guangzhou) and Sino-French Institute of Nuclear Engineering and Technology (Zhuhai), Sun Yat-sen University, 519000 Zhuhai and 510275 Guangzhou, Guangdong, China
| | - X T Huang
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - X Y Huang
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - Y Huang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - X L Ji
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - H Y Jia
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - K Jia
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - K Jiang
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - X W Jiang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Z J Jiang
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - M Jin
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - M M Kang
- College of Physics, Sichuan University, 610065 Chengdu, Sichuan, China
| | - I Karpikov
- Institute for Nuclear Research of Russian Academy of Sciences, 117312 Moscow, Russia
| | - D Kuleshov
- Institute for Nuclear Research of Russian Academy of Sciences, 117312 Moscow, Russia
| | - K Kurinov
- Institute for Nuclear Research of Russian Academy of Sciences, 117312 Moscow, Russia
| | - B B Li
- Hebei Normal University, 050024 Shijiazhuang, Hebei, China
| | - C M Li
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - Cheng Li
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - Cong Li
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - D Li
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - F Li
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - H B Li
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - H C Li
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Jian Li
- University of Science and Technology of China, 230026 Hefei, Anhui, China
| | - Jie Li
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - K Li
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - S D Li
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Key Laboratory for Research in Galaxies and Cosmology, Shanghai Astronomical Observatory, Chinese Academy of Sciences, 200030 Shanghai, China
| | - W L Li
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - W L Li
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - X R Li
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Xin Li
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - Y Z Li
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Zhe Li
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Zhuo Li
- School of Physics, Peking University, 100871 Beijing, China
| | - E W Liang
- Guangxi Key Laboratory for Relativistic Astrophysics, School of Physical Science and Technology, Guangxi University, 530004 Nanning, Guangxi, China
| | - Y F Liang
- Guangxi Key Laboratory for Relativistic Astrophysics, School of Physical Science and Technology, Guangxi University, 530004 Nanning, Guangxi, China
| | - S J Lin
- School of Physics and Astronomy (Zhuhai) and School of Physics (Guangzhou) and Sino-French Institute of Nuclear Engineering and Technology (Zhuhai), Sun Yat-sen University, 519000 Zhuhai and 510275 Guangzhou, Guangdong, China
| | - B Liu
- University of Science and Technology of China, 230026 Hefei, Anhui, China
| | - C Liu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - D Liu
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - D B Liu
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - H Liu
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - H D Liu
- School of Physics and Microelectronics, Zhengzhou University, 450001 Zhengzhou, Henan, China
| | - J Liu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - J L Liu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - M Y Liu
- Key Laboratory of Cosmic Rays (Tibet University), Ministry of Education, 850000 Lhasa, Tibet, China
| | - R Y Liu
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - S M Liu
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - W Liu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Y Liu
- Center for Astrophysics, Guangzhou University, 510006 Guangzhou, Guangdong, China
| | - Y N Liu
- Department of Engineering Physics, Tsinghua University, 100084 Beijing, China
| | - Q Luo
- School of Physics and Astronomy (Zhuhai) and School of Physics (Guangzhou) and Sino-French Institute of Nuclear Engineering and Technology (Zhuhai), Sun Yat-sen University, 519000 Zhuhai and 510275 Guangzhou, Guangdong, China
| | - Y Luo
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - H K Lv
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - B Q Ma
- School of Physics, Peking University, 100871 Beijing, China
| | - L L Ma
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - X H Ma
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - J R Mao
- Yunnan Observatories, Chinese Academy of Sciences, 650216 Kunming, Yunnan, China
| | - Z Min
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - W Mitthumsiri
- Department of Physics, Faculty of Science, Mahidol University, Bangkok 10400, Thailand
| | - H J Mu
- School of Physics and Microelectronics, Zhengzhou University, 450001 Zhengzhou, Henan, China
| | - Y C Nan
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - A Neronov
- APC, Université Paris Cité, CNRS/IN2P3, CEA/IRFU, Observatoire de Paris, 119 75205 Paris, France
| | - L J Ou
- Center for Astrophysics, Guangzhou University, 510006 Guangzhou, Guangdong, China
| | - P Pattarakijwanich
- Department of Physics, Faculty of Science, Mahidol University, Bangkok 10400, Thailand
| | - Z Y Pei
- Center for Astrophysics, Guangzhou University, 510006 Guangzhou, Guangdong, China
| | - J C Qi
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - M Y Qi
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - B Q Qiao
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - J J Qin
- University of Science and Technology of China, 230026 Hefei, Anhui, China
| | - A Raza
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - D Ruffolo
- Department of Physics, Faculty of Science, Mahidol University, Bangkok 10400, Thailand
| | - A Sáiz
- Department of Physics, Faculty of Science, Mahidol University, Bangkok 10400, Thailand
| | - M Saeed
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - D Semikoz
- APC, Université Paris Cité, CNRS/IN2P3, CEA/IRFU, Observatoire de Paris, 119 75205 Paris, France
| | - L Shao
- Hebei Normal University, 050024 Shijiazhuang, Hebei, China
| | - O Shchegolev
- Institute for Nuclear Research of Russian Academy of Sciences, 117312 Moscow, Russia
- Moscow Institute of Physics and Technology, 141700 Moscow, Russia
| | - X D Sheng
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - F W Shu
- Center for Relativistic Astrophysics and High Energy Physics, School of Physics and Materials Science and Institute of Space Science and Technology, Nanchang University, 330031 Nanchang, Jiangxi, China
| | - H C Song
- School of Physics, Peking University, 100871 Beijing, China
| | - Yu V Stenkin
- Institute for Nuclear Research of Russian Academy of Sciences, 117312 Moscow, Russia
- Moscow Institute of Physics and Technology, 141700 Moscow, Russia
| | - V Stepanov
- Institute for Nuclear Research of Russian Academy of Sciences, 117312 Moscow, Russia
| | - Y Su
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - D X Sun
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - Q N Sun
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - X N Sun
- Guangxi Key Laboratory for Relativistic Astrophysics, School of Physical Science and Technology, Guangxi University, 530004 Nanning, Guangxi, China
| | - Z B Sun
- National Space Science Center, Chinese Academy of Sciences, 100190 Beijing, China
| | - J Takata
- School of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
| | - P H T Tam
- School of Physics and Astronomy (Zhuhai) and School of Physics (Guangzhou) and Sino-French Institute of Nuclear Engineering and Technology (Zhuhai), Sun Yat-sen University, 519000 Zhuhai and 510275 Guangzhou, Guangdong, China
| | - Q W Tang
- Center for Relativistic Astrophysics and High Energy Physics, School of Physics and Materials Science and Institute of Space Science and Technology, Nanchang University, 330031 Nanchang, Jiangxi, China
| | - R Tang
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - Z B Tang
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - W W Tian
- University of Chinese Academy of Sciences, 100049 Beijing, China
- National Astronomical Observatories, Chinese Academy of Sciences, 100101 Beijing, China
| | - C Wang
- National Space Science Center, Chinese Academy of Sciences, 100190 Beijing, China
| | - C B Wang
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - G W Wang
- University of Science and Technology of China, 230026 Hefei, Anhui, China
| | - H G Wang
- Center for Astrophysics, Guangzhou University, 510006 Guangzhou, Guangdong, China
| | - H H Wang
- School of Physics and Astronomy (Zhuhai) and School of Physics (Guangzhou) and Sino-French Institute of Nuclear Engineering and Technology (Zhuhai), Sun Yat-sen University, 519000 Zhuhai and 510275 Guangzhou, Guangdong, China
| | - J C Wang
- Yunnan Observatories, Chinese Academy of Sciences, 650216 Kunming, Yunnan, China
| | - Kai Wang
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - Kai Wang
- School of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
| | - L P Wang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - L Y Wang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - P H Wang
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - R Wang
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - W Wang
- School of Physics and Astronomy (Zhuhai) and School of Physics (Guangzhou) and Sino-French Institute of Nuclear Engineering and Technology (Zhuhai), Sun Yat-sen University, 519000 Zhuhai and 510275 Guangzhou, Guangdong, China
| | - X G Wang
- Guangxi Key Laboratory for Relativistic Astrophysics, School of Physical Science and Technology, Guangxi University, 530004 Nanning, Guangxi, China
| | - X Y Wang
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - Y Wang
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - Y D Wang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Y J Wang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Z H Wang
- College of Physics, Sichuan University, 610065 Chengdu, Sichuan, China
| | - Z X Wang
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - Zhen Wang
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - Zheng Wang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - D M Wei
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - J J Wei
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - Y J Wei
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - T Wen
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - C Y Wu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - H R Wu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Q W Wu
- School of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
| | - S Wu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - X F Wu
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - Y S Wu
- University of Science and Technology of China, 230026 Hefei, Anhui, China
| | - S Q Xi
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - J Xia
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - G M Xiang
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Key Laboratory for Research in Galaxies and Cosmology, Shanghai Astronomical Observatory, Chinese Academy of Sciences, 200030 Shanghai, China
| | - D X Xiao
- Hebei Normal University, 050024 Shijiazhuang, Hebei, China
| | - G Xiao
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Y L Xin
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - Y Xing
- Key Laboratory for Research in Galaxies and Cosmology, Shanghai Astronomical Observatory, Chinese Academy of Sciences, 200030 Shanghai, China
| | - D R Xiong
- Yunnan Observatories, Chinese Academy of Sciences, 650216 Kunming, Yunnan, China
| | - Z Xiong
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - D L Xu
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - R F Xu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - R X Xu
- School of Physics, Peking University, 100871 Beijing, China
| | - W L Xu
- College of Physics, Sichuan University, 610065 Chengdu, Sichuan, China
| | - L Xue
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - D H Yan
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - J Z Yan
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - T Yan
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - C W Yang
- College of Physics, Sichuan University, 610065 Chengdu, Sichuan, China
| | - C Y Yang
- Yunnan Observatories, Chinese Academy of Sciences, 650216 Kunming, Yunnan, China
| | - F Yang
- Hebei Normal University, 050024 Shijiazhuang, Hebei, China
| | - F F Yang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - L L Yang
- School of Physics and Astronomy (Zhuhai) and School of Physics (Guangzhou) and Sino-French Institute of Nuclear Engineering and Technology (Zhuhai), Sun Yat-sen University, 519000 Zhuhai and 510275 Guangzhou, Guangdong, China
| | - M J Yang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - R Z Yang
- University of Science and Technology of China, 230026 Hefei, Anhui, China
| | - W X Yang
- Center for Astrophysics, Guangzhou University, 510006 Guangzhou, Guangdong, China
| | - Y H Yao
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Z G Yao
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - L Q Yin
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - N Yin
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - X H You
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Z Y You
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Y H Yu
- University of Science and Technology of China, 230026 Hefei, Anhui, China
| | - Q Yuan
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - H Yue
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - H D Zeng
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - T X Zeng
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - W Zeng
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - M Zha
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - B B Zhang
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - F Zhang
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - H Zhang
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - H M Zhang
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - H Y Zhang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - J L Zhang
- National Astronomical Observatories, Chinese Academy of Sciences, 100101 Beijing, China
| | - Li Zhang
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - P F Zhang
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - P P Zhang
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - R Zhang
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - S B Zhang
- University of Chinese Academy of Sciences, 100049 Beijing, China
- National Astronomical Observatories, Chinese Academy of Sciences, 100101 Beijing, China
| | - S R Zhang
- Hebei Normal University, 050024 Shijiazhuang, Hebei, China
| | - S S Zhang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - X Zhang
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - X P Zhang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Y F Zhang
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - Yi Zhang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - Yong Zhang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - B Zhao
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - J Zhao
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - L Zhao
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - L Z Zhao
- Hebei Normal University, 050024 Shijiazhuang, Hebei, China
| | - S P Zhao
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - X H Zhao
- Yunnan Observatories, Chinese Academy of Sciences, 650216 Kunming, Yunnan, China
| | - F Zheng
- National Space Science Center, Chinese Academy of Sciences, 100190 Beijing, China
| | - W J Zhong
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - B Zhou
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - H Zhou
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - J N Zhou
- Key Laboratory for Research in Galaxies and Cosmology, Shanghai Astronomical Observatory, Chinese Academy of Sciences, 200030 Shanghai, China
| | - M Zhou
- Center for Relativistic Astrophysics and High Energy Physics, School of Physics and Materials Science and Institute of Space Science and Technology, Nanchang University, 330031 Nanchang, Jiangxi, China
| | - P Zhou
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - R Zhou
- College of Physics, Sichuan University, 610065 Chengdu, Sichuan, China
| | - X X Zhou
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - X X Zhou
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - B Y Zhu
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - C G Zhu
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - F R Zhu
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - H Zhu
- National Astronomical Observatories, Chinese Academy of Sciences, 100101 Beijing, China
| | - K J Zhu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - Y C Zou
- School of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
| | - X Zuo
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
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Mi X, Michailidis AA, Shabani S, Miao KC, Klimov PV, Lloyd J, Rosenberg E, Acharya R, Aleiner I, Andersen TI, Ansmann M, Arute F, Arya K, Asfaw A, Atalaya J, Bardin JC, Bengtsson A, Bortoli G, Bourassa A, Bovaird J, Brill L, Broughton M, Buckley BB, Buell DA, Burger T, Burkett B, Bushnell N, Chen Z, Chiaro B, Chik D, Chou C, Cogan J, Collins R, Conner P, Courtney W, Crook AL, Curtin B, Dau AG, Debroy DM, Del Toro Barba A, Demura S, Di Paolo A, Drozdov IK, Dunsworth A, Erickson C, Faoro L, Farhi E, Fatemi R, Ferreira VS, Burgos LF, Forati E, Fowler AG, Foxen B, Genois É, Giang W, Gidney C, Gilboa D, Giustina M, Gosula R, Gross JA, Habegger S, Hamilton MC, Hansen M, Harrigan MP, Harrington SD, Heu P, Hoffmann MR, Hong S, Huang T, Huff A, Huggins WJ, Ioffe LB, Isakov SV, Iveland J, Jeffrey E, Jiang Z, Jones C, Juhas P, Kafri D, Kechedzhi K, Khattar T, Khezri M, Kieferová M, Kim S, Kitaev A, Klots AR, Korotkov AN, Kostritsa F, Kreikebaum JM, Landhuis D, Laptev P, Lau KM, Laws L, Lee J, Lee KW, Lensky YD, Lester BJ, Lill AT, Liu W, Locharla A, Malone FD, Martin O, McClean JR, McEwen M, Mieszala A, Montazeri S, Morvan A, Movassagh R, Mruczkiewicz W, Neeley M, Neill C, Nersisyan A, Newman M, Ng JH, Nguyen A, Nguyen M, Niu MY, O'Brien TE, Opremcak A, Petukhov A, Potter R, Pryadko LP, Quintana C, Rocque C, Rubin NC, Saei N, Sank D, Sankaragomathi K, Satzinger KJ, Schurkus HF, Schuster C, Shearn MJ, Shorter A, Shutty N, Shvarts V, Skruzny J, Smith WC, Somma R, Sterling G, Strain D, Szalay M, Torres A, Vidal G, Villalonga B, Heidweiller CV, White T, Woo BWK, Xing C, Yao ZJ, Yeh P, Yoo J, Young G, Zalcman A, Zhang Y, Zhu N, Zobrist N, Neven H, Babbush R, Bacon D, Boixo S, Hilton J, Lucero E, Megrant A, Kelly J, Chen Y, Roushan P, Smelyanskiy V, Abanin DA. Stable quantum-correlated many-body states through engineered dissipation. Science 2024; 383:1332-1337. [PMID: 38513021 DOI: 10.1126/science.adh9932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 02/13/2024] [Indexed: 03/23/2024]
Abstract
Engineered dissipative reservoirs have the potential to steer many-body quantum systems toward correlated steady states useful for quantum simulation of high-temperature superconductivity or quantum magnetism. Using up to 49 superconducting qubits, we prepared low-energy states of the transverse-field Ising model through coupling to dissipative auxiliary qubits. In one dimension, we observed long-range quantum correlations and a ground-state fidelity of 0.86 for 18 qubits at the critical point. In two dimensions, we found mutual information that extends beyond nearest neighbors. Lastly, by coupling the system to auxiliaries emulating reservoirs with different chemical potentials, we explored transport in the quantum Heisenberg model. Our results establish engineered dissipation as a scalable alternative to unitary evolution for preparing entangled many-body states on noisy quantum processors.
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Affiliation(s)
- X Mi
- Google Research, Mountain View, CA, USA
| | - A A Michailidis
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
| | - S Shabani
- Google Research, Mountain View, CA, USA
| | - K C Miao
- Google Research, Mountain View, CA, USA
| | | | - J Lloyd
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
| | | | - R Acharya
- Google Research, Mountain View, CA, USA
| | - I Aleiner
- Google Research, Mountain View, CA, USA
| | | | - M Ansmann
- Google Research, Mountain View, CA, USA
| | - F Arute
- Google Research, Mountain View, CA, USA
| | - K Arya
- Google Research, Mountain View, CA, USA
| | - A Asfaw
- Google Research, Mountain View, CA, USA
| | - J Atalaya
- Google Research, Mountain View, CA, USA
| | - J C Bardin
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA, USA
| | | | - G Bortoli
- Google Research, Mountain View, CA, USA
| | | | - J Bovaird
- Google Research, Mountain View, CA, USA
| | - L Brill
- Google Research, Mountain View, CA, USA
| | | | | | - D A Buell
- Google Research, Mountain View, CA, USA
| | - T Burger
- Google Research, Mountain View, CA, USA
| | - B Burkett
- Google Research, Mountain View, CA, USA
| | | | - Z Chen
- Google Research, Mountain View, CA, USA
| | - B Chiaro
- Google Research, Mountain View, CA, USA
| | - D Chik
- Google Research, Mountain View, CA, USA
| | - C Chou
- Google Research, Mountain View, CA, USA
| | - J Cogan
- Google Research, Mountain View, CA, USA
| | - R Collins
- Google Research, Mountain View, CA, USA
| | - P Conner
- Google Research, Mountain View, CA, USA
| | | | - A L Crook
- Google Research, Mountain View, CA, USA
| | - B Curtin
- Google Research, Mountain View, CA, USA
| | - A G Dau
- Google Research, Mountain View, CA, USA
| | | | | | - S Demura
- Google Research, Mountain View, CA, USA
| | | | | | | | | | - L Faoro
- Google Research, Mountain View, CA, USA
| | - E Farhi
- Google Research, Mountain View, CA, USA
| | - R Fatemi
- Google Research, Mountain View, CA, USA
| | | | | | - E Forati
- Google Research, Mountain View, CA, USA
| | | | - B Foxen
- Google Research, Mountain View, CA, USA
| | - É Genois
- Google Research, Mountain View, CA, USA
| | - W Giang
- Google Research, Mountain View, CA, USA
| | - C Gidney
- Google Research, Mountain View, CA, USA
| | - D Gilboa
- Google Research, Mountain View, CA, USA
| | | | - R Gosula
- Google Research, Mountain View, CA, USA
| | - J A Gross
- Google Research, Mountain View, CA, USA
| | | | - M C Hamilton
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, USA
| | - M Hansen
- Google Research, Mountain View, CA, USA
| | | | | | - P Heu
- Google Research, Mountain View, CA, USA
| | | | - S Hong
- Google Research, Mountain View, CA, USA
| | - T Huang
- Google Research, Mountain View, CA, USA
| | - A Huff
- Google Research, Mountain View, CA, USA
| | | | - L B Ioffe
- Google Research, Mountain View, CA, USA
| | | | - J Iveland
- Google Research, Mountain View, CA, USA
| | - E Jeffrey
- Google Research, Mountain View, CA, USA
| | - Z Jiang
- Google Research, Mountain View, CA, USA
| | - C Jones
- Google Research, Mountain View, CA, USA
| | - P Juhas
- Google Research, Mountain View, CA, USA
| | - D Kafri
- Google Research, Mountain View, CA, USA
| | | | - T Khattar
- Google Research, Mountain View, CA, USA
| | - M Khezri
- Google Research, Mountain View, CA, USA
| | - M Kieferová
- Google Research, Mountain View, CA, USA
- Centre for Quantum Software and Information (QSI), Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW, Australia
| | - S Kim
- Google Research, Mountain View, CA, USA
| | - A Kitaev
- Google Research, Mountain View, CA, USA
| | - A R Klots
- Google Research, Mountain View, CA, USA
| | - A N Korotkov
- Google Research, Mountain View, CA, USA
- Department of Electrical and Computer Engineering, University of California, Riverside, CA, USA
| | | | | | | | - P Laptev
- Google Research, Mountain View, CA, USA
| | - K-M Lau
- Google Research, Mountain View, CA, USA
| | - L Laws
- Google Research, Mountain View, CA, USA
| | - J Lee
- Google Research, Mountain View, CA, USA
- Department of Chemistry, Columbia University, New York, NY, USA
| | - K W Lee
- Google Research, Mountain View, CA, USA
| | | | | | - A T Lill
- Google Research, Mountain View, CA, USA
| | - W Liu
- Google Research, Mountain View, CA, USA
| | | | | | - O Martin
- Google Research, Mountain View, CA, USA
| | | | - M McEwen
- Google Research, Mountain View, CA, USA
| | | | | | - A Morvan
- Google Research, Mountain View, CA, USA
| | | | | | - M Neeley
- Google Research, Mountain View, CA, USA
| | - C Neill
- Google Research, Mountain View, CA, USA
| | | | - M Newman
- Google Research, Mountain View, CA, USA
| | - J H Ng
- Google Research, Mountain View, CA, USA
| | - A Nguyen
- Google Research, Mountain View, CA, USA
| | - M Nguyen
- Google Research, Mountain View, CA, USA
| | - M Y Niu
- Google Research, Mountain View, CA, USA
| | | | | | | | - R Potter
- Google Research, Mountain View, CA, USA
| | - L P Pryadko
- Google Research, Mountain View, CA, USA
- Department of Physics and Astronomy, University of California, Riverside, CA, USA
| | | | - C Rocque
- Google Research, Mountain View, CA, USA
| | - N C Rubin
- Google Research, Mountain View, CA, USA
| | - N Saei
- Google Research, Mountain View, CA, USA
| | - D Sank
- Google Research, Mountain View, CA, USA
| | | | | | | | | | | | - A Shorter
- Google Research, Mountain View, CA, USA
| | - N Shutty
- Google Research, Mountain View, CA, USA
| | - V Shvarts
- Google Research, Mountain View, CA, USA
| | - J Skruzny
- Google Research, Mountain View, CA, USA
| | - W C Smith
- Google Research, Mountain View, CA, USA
| | - R Somma
- Google Research, Mountain View, CA, USA
| | | | - D Strain
- Google Research, Mountain View, CA, USA
| | - M Szalay
- Google Research, Mountain View, CA, USA
| | - A Torres
- Google Research, Mountain View, CA, USA
| | - G Vidal
- Google Research, Mountain View, CA, USA
| | | | | | - T White
- Google Research, Mountain View, CA, USA
| | - B W K Woo
- Google Research, Mountain View, CA, USA
| | - C Xing
- Google Research, Mountain View, CA, USA
| | - Z J Yao
- Google Research, Mountain View, CA, USA
| | - P Yeh
- Google Research, Mountain View, CA, USA
| | - J Yoo
- Google Research, Mountain View, CA, USA
| | - G Young
- Google Research, Mountain View, CA, USA
| | - A Zalcman
- Google Research, Mountain View, CA, USA
| | - Y Zhang
- Google Research, Mountain View, CA, USA
| | - N Zhu
- Google Research, Mountain View, CA, USA
| | - N Zobrist
- Google Research, Mountain View, CA, USA
| | - H Neven
- Google Research, Mountain View, CA, USA
| | - R Babbush
- Google Research, Mountain View, CA, USA
| | - D Bacon
- Google Research, Mountain View, CA, USA
| | - S Boixo
- Google Research, Mountain View, CA, USA
| | - J Hilton
- Google Research, Mountain View, CA, USA
| | - E Lucero
- Google Research, Mountain View, CA, USA
| | - A Megrant
- Google Research, Mountain View, CA, USA
| | - J Kelly
- Google Research, Mountain View, CA, USA
| | - Y Chen
- Google Research, Mountain View, CA, USA
| | - P Roushan
- Google Research, Mountain View, CA, USA
| | | | - D A Abanin
- Google Research, Mountain View, CA, USA
- Department of Theoretical Physics, University of Geneva, Geneva, Switzerland
- Department of Physics, Princeton University, Princeton, NJ, USA
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20
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Liu W, Zhou W, Zhang Y, Ge X, Qi W, Lin T, Cao Q, Cao L. Strictureplasty may lead to increased preference in the surgical management of Crohn's disease: a case-matched study. Tech Coloproctol 2024; 28:40. [PMID: 38507096 DOI: 10.1007/s10151-024-02915-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Accepted: 03/05/2024] [Indexed: 03/22/2024]
Abstract
BACKGROUND Resection and strictureplasty are the two surgical modalities used in the management of Crohn's disease (CD). The objective of this study was to compare morbidity and clinical recurrence between patients who underwent strictureplasty and patients who underwent resection. METHODS Patients with CD who underwent strictureplasty between January 2012 and December 2022 were enrolled. The patients were well matched with patients who underwent resection without strictureplasty. Patient- and disease-specific characteristics, postoperative morbidity, and clinical recurrence were also analyzed. RESULTS A total of 118 patients who underwent a total of 192 strictureplasties were well matched to 118 patients who underwent resection. The strictureplasty group exhibited significantly less blood loss (30 ml versus 50 ml, p < 0.001) and stoma creation (2.5% versus 16.9%, p < 0.001). No significant difference was found regarding postoperative complications or length of postoperative stay. At the end of the follow-up, the overall rate of clinical recurrence was 39.4%, and no difference was observed between the two groups. Postoperative prophylactic use of biologics (odds ratio = 0.2, p < 0.001) was the only protective factor against recurrence. CONCLUSION Strictureplasty does not increase the risk of complications or recurrence compared with resection. It represents a viable alternative to resection in selected patients, and as such, it should have a broader scope of indications and greater acceptance among surgeons.
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Affiliation(s)
- W Liu
- Department of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, 3 East Qingchun Road, Hangzhou, 310016, Zhejiang Province, People's Republic of China
- Inflammatory Bowel Disease Center, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, People's Republic of China
| | - W Zhou
- Department of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, 3 East Qingchun Road, Hangzhou, 310016, Zhejiang Province, People's Republic of China.
- Inflammatory Bowel Disease Center, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, People's Republic of China.
| | - Y Zhang
- School of Medicine, Shantou University, Shantou, 515063, Guangdong Province, China
| | - X Ge
- Department of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, 3 East Qingchun Road, Hangzhou, 310016, Zhejiang Province, People's Republic of China
- Inflammatory Bowel Disease Center, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, People's Republic of China
| | - W Qi
- Department of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, 3 East Qingchun Road, Hangzhou, 310016, Zhejiang Province, People's Republic of China
- Inflammatory Bowel Disease Center, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, People's Republic of China
| | - T Lin
- Department of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, 3 East Qingchun Road, Hangzhou, 310016, Zhejiang Province, People's Republic of China
| | - Q Cao
- Inflammatory Bowel Disease Center, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, People's Republic of China
| | - L Cao
- Department of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, 3 East Qingchun Road, Hangzhou, 310016, Zhejiang Province, People's Republic of China.
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21
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Yang R, Wu Z, Sun Y, Liu Y, Hang Y, Liu M, Liu Y, Wang X, Liu W, Fu C. miR156-PvSPL2 controls culm development by transcriptional repression of switchgrass CYTOKININ OXIDASE/DEHYDROGENASE4. Plant J 2024. [PMID: 38507513 DOI: 10.1111/tpj.16728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Revised: 02/07/2024] [Accepted: 03/09/2024] [Indexed: 03/22/2024]
Abstract
Culm development in grasses can be controlled by both miR156 and cytokinin. However, the crosstalk between the miR156-SPL module and the cytokinin metabolic pathway remains largely unknown. Here, we found CYTOKININ OXIDASE/DEHYDROGENASE4 (PvCKX4) plays a negative regulatory role in culm development of the bioenergy grass Panicum virgatum (switchgrass). Overexpression of PvCKX4 in switchgrass reduced the internode diameter and length without affecting tiller number. Interestingly, we also found that PvCKX4 was always upregulated in miR156 overexpressing (miR156OE) transgenic switchgrass lines. Additionally, upregulation of either miR156 or PvCKX4 in switchgrass reduced the content of isopentenyl adenine (iP) without affecting trans-zeatin (tZ) accumulation. It is consistent with the evidence that the recombinant PvCKX4 protein exhibited much higher catalytic activity against iP than tZ in vitro. Furthermore, our results showed that miR156-targeted SPL2 bound directly to the promoter of PvCKX4 to repress its expression. Thus, alleviating the SPL2-mediated transcriptional repression of PvCKX4 through miR156 overexpression resulted in a significant increase in cytokinin degradation and impaired culm development in switchgrass. On the contrary, suppressing PvCKX4 in miR156OE transgenic plants restored iP content, internode diameter, and length to wild-type levels. Most strikingly, the double transgenic lines retained the same increased tiller numbers as the miR156OE transgenic line, which yielded more biomass than the wild type. These findings indicate that the miR156-SPL module can control culm development through transcriptional repression of PvCKX4 in switchgrass, which provides a promising target for precise design of shoot architecture to yield more biomass from grasses.
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Affiliation(s)
- Ruijuan Yang
- CAS Key Laboratory of Biofuels, Shandong Provincial Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
| | - Zhenying Wu
- CAS Key Laboratory of Biofuels, Shandong Provincial Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
- College of Life Science, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Ying Sun
- CAS Key Laboratory of Biofuels, Shandong Provincial Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Yangzhou University, Yangzhou, 225009, China
| | - Yuchen Liu
- CAS Key Laboratory of Biofuels, Shandong Provincial Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
| | - Yuqing Hang
- CAS Key Laboratory of Biofuels, Shandong Provincial Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
| | - Min Liu
- CAS Key Laboratory of Biofuels, Shandong Provincial Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
| | - Yajun Liu
- CAS Key Laboratory of Biofuels, Shandong Provincial Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
- College of Life Science, University of Chinese Academy of Sciences, Beijing, 100049, China
| | | | - Wenwen Liu
- CAS Key Laboratory of Biofuels, Shandong Provincial Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
| | - Chunxiang Fu
- CAS Key Laboratory of Biofuels, Shandong Provincial Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
- College of Life Science, University of Chinese Academy of Sciences, Beijing, 100049, China
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Wang T, Peng X, Liu W, Ji M, Sun J. Identification and validation of KIF23 as a hypoxia-regulated lactate metabolism-related oncogene in uterine corpus endometrial carcinoma. Life Sci 2024; 341:122490. [PMID: 38336274 DOI: 10.1016/j.lfs.2024.122490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 02/01/2024] [Accepted: 02/04/2024] [Indexed: 02/12/2024]
Abstract
AIMS The "Warburg effect" has been developed from the discovery that hypoxia-inducible factor 1α (HIF-1α) could promote the conversion of pyruvate to lactate. However, no studies have linked hypoxia and lactate metabolism to uterine corpus endometrial carcinoma (UCEC). MAIN METHODS Sequencing and clinical data of patients with UCEC were extracted from The Cancer Genome Atlas (TCGA) database. Hypoxia-related lactate metabolism genes (HRLGs) were screened using Spearman's correlation analysis. A prognostic signature based on HRLGs was developed using the least absolute shrinkage and selection operator (LASSO) algorithm. A comprehensive analysis was conducted on the molecular features, immune environment, mutation patterns, and response to drugs between different risk groups. In vitro and in vivo experiments were performed to verify the function of KIF23. KEY FINDINGS A five HRLG-based prognostic signature was identified. The prognostic outcome was unfavorable for the high-risk subgroup. Observation of increased pathway activities associated with cell proliferation and DNA damage repair was noted in the high-risk subgroup. Additionally, notable correlations were observed between risk score and immune microenvironment, mutational features, and drug responsiveness. Further, we confirmed KIF23 as a novel oncogene in UCEC, whose silencing decreased proliferation and promoted apoptosis of cancer cells. KIF23 knockdown reduced tumor growth in nude mice. We demonstrated that KIF23 was upregulated under hypoxic stress in a HIF-1α dependent manner. Moreover, KIF23 regulated lactate dehydrogenase A expression. SIGNIFICANCE The developed HRLG-related signature was associated with prognosis, immune microenvironment, and drug sensitivity in UCEC. We also revealed KIF23 as a hypoxia-regulated lactate metabolism-related oncogene.
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Affiliation(s)
- Tao Wang
- The Gynecology Department, Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai 200092, China
| | - Xiaotong Peng
- The Gynecology Department, Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai 200092, China
| | - Wenwen Liu
- The Gynecology Department, Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai 200092, China
| | - Mei Ji
- The Gynecology Department, Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai 200092, China
| | - Jing Sun
- The Gynecology Department, Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai 200092, China.
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Liu W, Zhao TT, Feng S, Ma H, Sun JC, Wei MH. [Follicular dendritic cell sarcoma of the tonsil: a case report]. Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi 2024; 59:260-262. [PMID: 38561267 DOI: 10.3760/cma.j.cn115330-20230921-00109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Affiliation(s)
- W Liu
- Department of Head and Neck Surgery, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzheng Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen 518116, China
| | - T T Zhao
- Department of Head and Neck Surgery, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzheng Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen 518116, China
| | - S Feng
- Department of Pathology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzheng Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen 518116, China
| | - H Ma
- Department of Head and Neck Surgery, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzheng Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen 518116, China
| | - J C Sun
- Department of Head and Neck Surgery, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzheng Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen 518116, China
| | - M H Wei
- Department of Head and Neck Surgery, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzheng Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen 518116, China
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24
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Shi L, Huang S, Liu W. Infection prevention in induction chemotherapy for childhood acute leukaemia. J Hosp Infect 2024; 145:226-227. [PMID: 38103693 DOI: 10.1016/j.jhin.2023.11.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 10/28/2023] [Accepted: 11/06/2023] [Indexed: 12/19/2023]
Affiliation(s)
- L Shi
- Key Laboratory of Paediatric Haematology, Children's Hospital Affiliated to Zhengzhou University/Henan Children's Hospital, Zhengzhou, People's Republic of China.
| | - S Huang
- Department of Hematology and Oncology, Children's Hospital Affiliated to Zhengzhou University/Henan Children's Hospital, Zhengzhou, People's Republic of China
| | - W Liu
- Department of Hematology and Oncology, Children's Hospital Affiliated to Zhengzhou University/Henan Children's Hospital, Zhengzhou, People's Republic of China
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25
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Han X, Tang S, Ma X, Liu W, Yang R, Zhang S, Wang N, Song X, Fu C, Yang R, Cao X. Blocking miR528 function promotes tillering and regrowth in switchgrass. Plant Biotechnol J 2024; 22:712-721. [PMID: 37929781 PMCID: PMC10893936 DOI: 10.1111/pbi.14218] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2023] [Revised: 09/28/2023] [Accepted: 10/17/2023] [Indexed: 11/07/2023]
Abstract
MiRNAs have been reported to be the key regulators involving a wide range of biological processes in diverse plant species, but their functions in switchgrass, an important biofuel and forage crop, are largely unknown. Here, we reported the novel function of miR528, which has expanded to four copies in switchgrass, in controlling biomass trait of tillering number and regrowth rate after mowing. Blocking miR528 activity by expressing short tandem target mimic (STTM) increased tiller number and regrowth rate after mowing. The quadruple pvmir528 mutant lines derived from genome editing also showed such improved traits. Degradome and RNA-seq analysis, combined with in situ hybridization assay revealed that up-regulation of two miR528 targets coding for Cu/Zn-SOD enzymes, might be responsible for the improved traits of tillering and regrowth in pvmir528 mutant. Additionally, natural variations in the miR528-SOD interaction exist in C3 and C4 monocot species, implying the distinct regulatory strength of the miR528-SOD module during monocot evolution. Overall, our data illuminated a novel role of miR528 in controlling biomass traits and provided a new target for genetic manipulation-mediated crop improvement.
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Affiliation(s)
- Xiangyan Han
- Department of Plant Biology and Ecology, Tianjin Key Laboratory of Protein Sciences, College of Life SciencesNankai UniversityTianjinChina
- Institute of Genetics and Developmental BiologyChinese Academy of SciencesBeijingChina
| | - Shanjie Tang
- Institute of Genetics and Developmental BiologyChinese Academy of SciencesBeijingChina
- College of Life SciencesUniversity of the Chinese Academy of SciencesBeijingChina
| | - Xuan Ma
- College of Life Sciences, Tianjin Key Laboratory of Animal and Plant ResistanceTianjin Normal UniversityTianjinChina
| | - Wenwen Liu
- CAS Key Laboratory of Biofuels, Shandong Provincial Key Laboratory of Synthetic Biology, Qingdao Institute of Bioenergy and Bioprocess TechnologyChinese Academy of SciencesQingdaoChina
- Shandong Energy InstituteQingdaoChina
- Qingdao New Energy Shandong LaboratoryQingdaoChina
| | - Ruijuan Yang
- CAS Key Laboratory of Biofuels, Shandong Provincial Key Laboratory of Synthetic Biology, Qingdao Institute of Bioenergy and Bioprocess TechnologyChinese Academy of SciencesQingdaoChina
- Shandong Energy InstituteQingdaoChina
- Qingdao New Energy Shandong LaboratoryQingdaoChina
| | - Shuaibin Zhang
- Institute of Genetics and Developmental BiologyChinese Academy of SciencesBeijingChina
| | - Ningning Wang
- Department of Plant Biology and Ecology, Tianjin Key Laboratory of Protein Sciences, College of Life SciencesNankai UniversityTianjinChina
| | - Xianwei Song
- Institute of Genetics and Developmental BiologyChinese Academy of SciencesBeijingChina
| | - Chunxiang Fu
- CAS Key Laboratory of Biofuels, Shandong Provincial Key Laboratory of Synthetic Biology, Qingdao Institute of Bioenergy and Bioprocess TechnologyChinese Academy of SciencesQingdaoChina
- Shandong Energy InstituteQingdaoChina
- Qingdao New Energy Shandong LaboratoryQingdaoChina
| | - Rongxin Yang
- Institute of Genetics and Developmental BiologyChinese Academy of SciencesBeijingChina
- Key Laboratory of Molecular Biology and Gene Engineering in Jiangxi Province, College of Life ScienceNanchang UniversityJiangxiChina
| | - Xiaofeng Cao
- Institute of Genetics and Developmental BiologyChinese Academy of SciencesBeijingChina
- College of Life SciencesUniversity of the Chinese Academy of SciencesBeijingChina
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26
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Zhao S, Jiang H, Miao Y, Liu W, Li Y, Liu H, Wang A, Cui X, Zhang Y. Factors influencing necrotizing enterocolitis in premature infants in China: a systematic review and meta-analysis. BMC Pediatr 2024; 24:148. [PMID: 38418993 PMCID: PMC10903018 DOI: 10.1186/s12887-024-04607-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 01/31/2024] [Indexed: 03/02/2024] Open
Abstract
BACKGROUND Necrotizing enterocolitis (NEC) is a multifactorial gastrointestinal disease with high morbidity and mortality among premature infants. However, studies with large samples on the factors of NEC in China have not been reported. This meta-analysis aims to systematically review the literature to explore the influencing factors of necrotizing enterocolitis in premature infants in China and provide a reference for the prevention of NEC. METHODS PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure (CNKI), China Biomedical Literature Database (CBM), Wanfang and VIP databases were systematically searched from inception to February 2023. We used Stata14.0 software to perform the systematic review and meta-analysis. We used fixed or random effects models with combined odds ratios (ORs) and 95% confidence intervals (CIs), and quality was evaluated using the Newcastle‒Ottawa Scale (NOS). RESULTS The total sample was 8616 cases, including 2456 cases in the intervention group and 6160 cases in the control group. It was found that 16 risk factors and 3 protective factors were related to necrotizing enterocolitis in premature infants. Septicemia (OR = 3.91), blood transfusion (OR = 2.41), neonatal asphyxia (OR = 2.46), pneumonia (OR = 6.17), infection (OR = 5.99), congenital heart disease (OR = 4.80), intrahepatic cholestasis of pregnancy (ICP) (OR = 2.71), mechanical ventilation (OR = 1.44), gestational diabetes mellitus (GDM) (OR = 3.08), respiratory distress syndrome (RDS) (OR = 3.28), hypoalbuminemia (OR = 2.80), patent ductus arteriosus (PDA) (OR = 3.10), respiratory failure (OR = 7.51), severe anemia (OR = 2.86), history of antibiotic use (OR = 2.12), and meconium-stained amniotic fluid (MSAF) (OR = 3.14) were risk factors for NEC in preterm infants in China. Breastfeeding (OR = 0.31), oral probiotics (OR = 0.36), and prenatal use of glucocorticoids (OR = 0.38) were protective factors for NEC in preterm infants. CONCLUSIONS Septicemia, blood transfusion, neonatal asphyxia, pneumonia, infection, congenital heart disease, ICP, GDM, RDS, hypoproteinemia, PDA, respiratory failure, severe anemia, history of antibiotic use and MSAF will increase the risk of NEC in premature infants, whereas breastfeeding, oral probiotics and prenatal use of glucocorticoids reduce the risk. Due to the quantity and quality of the included literature, the above findings need to be further validated by more high-quality studies.
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Affiliation(s)
- Shuliang Zhao
- School of Nursing, Shandong Second Medical University, Weifang, 261053, China
- Nursing Department Affiliated Hospital of Shandong Second Medical University, Weifang, 261031, China
| | - Huimin Jiang
- School of Nursing, Shandong Second Medical University, Weifang, 261053, China
| | - Yiqun Miao
- School of Nursing, Capital Medical University, Beijing, 100071, China
| | - Wenwen Liu
- Xiangya School of Nursing, Central South University, Changsha, 410000, China
| | - Yanan Li
- School of Nursing, Shandong Second Medical University, Weifang, 261053, China
| | - Hui Liu
- School of Nursing, Shandong Second Medical University, Weifang, 261053, China
| | - Aihua Wang
- School of Nursing, Shandong Second Medical University, Weifang, 261053, China.
| | - Xinghui Cui
- Nursing Department Affiliated Hospital of Shandong Second Medical University, Weifang, 261031, China.
| | - Yuanyuan Zhang
- School of Nursing, Shandong Second Medical University, Weifang, 261053, China
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27
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Liu W, Li H, Tay RY. Recent progress of high-performance in-plane zinc ion hybrid micro-supercapacitors: design, achievements, and challenges. Nanoscale 2024; 16:4542-4562. [PMID: 38299713 DOI: 10.1039/d3nr06120e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/02/2024]
Abstract
With the increasing demand for wearable and miniature electronics, in-plane zinc (Zn) ion hybrid micro-supercapacitors (ZIHMSCs), as a promising and compatible energy power source, have attracted tremendous attention due to their unique merits. Despite enormous development and breakthroughs in this field, there is still a lack of a systematic and comprehensive review to update the recent progress of in-plane ZIHMSCs in the design and fabrication of both micro-anodes and micro-cathodes, the exploration and optimization of new electrolytes, and the investigation of related-energy storage mechanisms. This minireview summarizes the key breakthroughs and recent advances in the construction of high-performance in-plane ZIHMSCs. First, the background and fundamentals of in-plane ZIHMSCs are briefly introduced. Then, new concepts, strategies, and latest exciting developments in the preparation and interfacial engineering of Zn metal micro-anodes, the fabrication of advanced micro-cathodes, and the exploration of new electrolyte systems are discussed, respectively. Finally, the key challenges and future directions for the development of high-performance in-plane ZIHMSCs are presented as well. This review not only accounts for the recent research progress in the field of the in-plane ZIHMSCs, but also provides important new insights into the design of next-generation miniaturized energy storage devices.
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Affiliation(s)
- Wenwen Liu
- School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore.
| | - Hongling Li
- School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore.
| | - Roland Yingjie Tay
- School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore.
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Zhu M, Wu N, Zhong J, Chen C, Liu W, Ren Y, Wang X, Jin H. N 6-methyladenosine modification of the mRNA for a key gene in purine nucleotide metabolism regulates virus proliferation in an insect vector. Cell Rep 2024; 43:113821. [PMID: 38368611 DOI: 10.1016/j.celrep.2024.113821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 01/10/2024] [Accepted: 02/02/2024] [Indexed: 02/20/2024] Open
Abstract
The titer of viruses that persist and propagate in their insect vector must be high enough for transmission yet not harm the insect, but the mechanism of this dynamic balance is unclear. Here, expression of inosine monophosphate dehydrogenase (LsIMPDH), a rate-limiting enzyme for guanosine triphosphate (GTP) synthesis, is shown to be downregulated by increased levels of N6-methyladenosine (m6A) on LsIMPDH mRNA in rice stripe virus (RSV)-infected small brown planthoppers (SBPHs; Laodelphax striatellus), the RSV vector, which decreases GTP content, thus limiting viral proliferation. Moreover, planthopper methyltransferase-like protein 3 (LsMETTL3) and m6A reader protein LsYTHDF3 are found to catalyze and recognize the m6A on LsIMPDH mRNA, respectively, and cooperate in destabilizing LsIMPDH transcripts. Co-silencing assays show that negative regulation of viral proliferation by both LsMETTL3 and LsYTHDF3 is partially dependent on LsIMPDH. This distinct mechanism limits virus replication in an insect vector, providing a potential gene target to block viral transmission.
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Affiliation(s)
- Mengjie Zhu
- State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Nan Wu
- State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Jiayi Zhong
- State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Chen Chen
- State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Wenwen Liu
- State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Yingdang Ren
- Institute of Plant Protection, Henan Academy of Agricultural Sciences, Zhengzhou 450002, China
| | - Xifeng Wang
- State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
| | - Huaibing Jin
- State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
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Lai FTT, Liu W, Hu Y, Wei C, Chu RYK, Lum DH, Leung JCN, Cheng FWT, Chui CSL, Li X, Wan EYF, Wong CKH, Cheung CL, Chan EWY, Hung IFN, Wong ICK. Elevated risk of multimorbidity post-COVID-19 infection: protective effect of vaccination. QJM 2024; 117:125-132. [PMID: 37824396 DOI: 10.1093/qjmed/hcad236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Revised: 10/05/2023] [Indexed: 10/14/2023] Open
Abstract
BACKGROUND It is unclear how the coronavirus disease 2019 (Covid-19) pandemic has affected multimorbidity incidence among those with one pre-existing chronic condition, as well as how vaccination could modify this association. AIM To examine the association of Covid-19 infection with multimorbidity incidence among people with one pre-existing chronic condition, including those with prior vaccination. DESIGN Nested case-control study. METHODS We conducted a territory-wide nested case-control study with incidence density sampling using Hong Kong electronic health records from public healthcare facilities and mandatory Covid-19 reports. People with one listed chronic condition (based on a list of 30) who developed multimorbidity during 1 January 2020-15 November 2022 were selected as case participants and randomly matched with up to 10 people of the same age, sex and with the same first chronic condition without having developed multimorbidity at that point. Conditional logistic regression was used to estimate adjusted odds ratios (aORs) of multimorbidity. RESULTS In total, 127 744 case participants were matched with 1 230 636 control participants. Adjusted analysis showed that there were 28%-increased odds of multimorbidity following Covid-19 [confidence interval (CI) 22% to 36%] but only 3% (non-significant) with prior full vaccination with BNT162b2 or CoronaVac (95% CI -2% to 7%). Similar associations were observed in men, women, older people aged 65 or more, and people aged 64 or younger. CONCLUSIONS We found a significantly elevated risk of multimorbidity following a Covid-19 episode among people with one pre-existing chronic condition. Full vaccination significantly reduced this risk increase.
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Affiliation(s)
- F T T Lai
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, Centre for Safe Medication Practice and Research, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
- Department of Family Medicine and Primary Care, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
- Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, Sha Tin, Hong Kong SAR, China
| | - W Liu
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, Centre for Safe Medication Practice and Research, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - Y Hu
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, Centre for Safe Medication Practice and Research, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - C Wei
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, Centre for Safe Medication Practice and Research, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - R Y K Chu
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, Centre for Safe Medication Practice and Research, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - D H Lum
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, Centre for Safe Medication Practice and Research, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - J C N Leung
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, Centre for Safe Medication Practice and Research, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - F W T Cheng
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, Centre for Safe Medication Practice and Research, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - C S L Chui
- Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, Sha Tin, Hong Kong SAR, China
- School of Nursing, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - X Li
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, Centre for Safe Medication Practice and Research, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
- Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, Sha Tin, Hong Kong SAR, China
- Department of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - E Y F Wan
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, Centre for Safe Medication Practice and Research, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
- Department of Family Medicine and Primary Care, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
- Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, Sha Tin, Hong Kong SAR, China
| | - C K H Wong
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, Centre for Safe Medication Practice and Research, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
- Department of Family Medicine and Primary Care, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
- Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, Sha Tin, Hong Kong SAR, China
| | - C L Cheung
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, Centre for Safe Medication Practice and Research, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
- Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, Sha Tin, Hong Kong SAR, China
| | - E W Y Chan
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, Centre for Safe Medication Practice and Research, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
- Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, Sha Tin, Hong Kong SAR, China
| | - I F N Hung
- Department of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - I C K Wong
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, Centre for Safe Medication Practice and Research, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
- Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, Sha Tin, Hong Kong SAR, China
- Aston Pharmacy School, Aston University, Birmingham, England, UK
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Liu W, He G, Deng XW. Toward understanding and utilizing crop heterosis in the age of biotechnology. iScience 2024; 27:108901. [PMID: 38533455 PMCID: PMC10964264 DOI: 10.1016/j.isci.2024.108901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/28/2024] Open
Abstract
Heterosis, a universal phenomenon in nature, mainly reflected in the superior productivity, quality, and fitness of F1 hybrids compared with their inbred parents, has been exploited in agriculture and greatly benefited human society in terms of food security. However, the flexible and efficient utilization of heterosis has remained a challenge in hybrid breeding systems because of the limitations of "three-line" and "two-line" methods. In the past two decades, rapidly developed biotechnologies have provided unprecedented conveniences for both understanding and utilizing heterosis. Notably, "third-generation" (3G) hybrid breeding technology together with high-throughput sequencing and gene editing greatly promoted the efficiency of hybrid breeding. Here, we review emerging ideas about the genetic or molecular mechanisms of heterosis and the development of 3G hybrid breeding system in the age of biotechnology. In addition, we summarized opportunities and challenges for optimal heterosis utilization in the future.
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Affiliation(s)
- Wenwen Liu
- School of Advanced Agricultural Sciences and School of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China
- National Key Laboratory of Wheat Improvement, Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Weifang, Shandong 261325, China
| | - Guangming He
- School of Advanced Agricultural Sciences and School of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China
| | - Xing Wang Deng
- School of Advanced Agricultural Sciences and School of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China
- National Key Laboratory of Wheat Improvement, Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Weifang, Shandong 261325, China
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Liu S, Li M, Liu W, Zhang Z, Wang X, Dong H. Structure and properties of acidic polysaccharides isolated from Massa Medicata Fermentata: Neuroprotective and antioxidant activity. Int J Biol Macromol 2024; 259:129128. [PMID: 38176512 DOI: 10.1016/j.ijbiomac.2023.129128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 12/27/2023] [Accepted: 12/27/2023] [Indexed: 01/06/2024]
Abstract
Massa Medicata Fermentata (MMF) is a fermented food with therapeutic effects. Previous studies suggested that after stir-frying, the uronic acid content in MMF crude polysaccharides increases, and the pH value decreases, which is caused by the change in acidic polysaccharides. However, the detailed physicochemical properties and structure-activity correlation of the acidic polysaccharides in MMF have not been fully explored. In this study, two acidic polysaccharides (SMMFAP and CMMFAP) were isolated from the MMF and its stir-fried product, respectively. Their structural characteristics and bioactivities were comparatively studied, and the structure-activity correlation was examined. Our findings revealed that the SMMFAP had a higher average Mw and higher Gal and Man content than the CMMFAP. Both the SMMFAP and CMMFAP were mainly composed of Xyl, Man, and Gal residues, whereas the CMMFAP had fewer linkage types. Additionally, the CMMFAP exhibited stronger neuroprotective activity than the SMMFAP owing to its higher content of 1,6-linked-Galp, while the SMMFAP exhibited better antioxidant activity, which might be related to its higher average Mw. Our findings suggest that acidic polysaccharides may be the active substances that cause differences in effectiveness between the sheng and chao MMF. Furthermore, the research qualified the SMMFAP and CMMFAP with different potential applications.
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Affiliation(s)
- Shuang Liu
- Key Laboratory for Applied Technology of Sophisticated Analytical Instruments of Shandong Province, Shandong Analysis and Test Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China; Key Laboratory for Natural Active Pharmaceutical Constituents Research in Universities of Shandong Province, School of Pharmaceutical Sciences, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China
| | - Meng Li
- Key Laboratory for Applied Technology of Sophisticated Analytical Instruments of Shandong Province, Shandong Analysis and Test Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China; Key Laboratory for Natural Active Pharmaceutical Constituents Research in Universities of Shandong Province, School of Pharmaceutical Sciences, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China
| | - Wenwen Liu
- Key Laboratory for Applied Technology of Sophisticated Analytical Instruments of Shandong Province, Shandong Analysis and Test Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China; College of pharmacy, Shandong University of Traditional Chinese Medicine, Jinan 250300, China
| | - Zhe Zhang
- College of pharmacy, Shandong University of Traditional Chinese Medicine, Jinan 250300, China
| | - Xiao Wang
- Key Laboratory for Applied Technology of Sophisticated Analytical Instruments of Shandong Province, Shandong Analysis and Test Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China; Key Laboratory for Natural Active Pharmaceutical Constituents Research in Universities of Shandong Province, School of Pharmaceutical Sciences, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China
| | - Hongjing Dong
- Key Laboratory for Applied Technology of Sophisticated Analytical Instruments of Shandong Province, Shandong Analysis and Test Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China; Key Laboratory for Natural Active Pharmaceutical Constituents Research in Universities of Shandong Province, School of Pharmaceutical Sciences, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China.
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Ding WH, Li YF, Liu W, Li W, Wu N, Hu SY, Shi JJ. Effect of occlusal stabilisation splint with or without arthroscopic disc repositioning on condylar bone remodelling in adolescent patients. Int J Oral Maxillofac Surg 2024; 53:156-164. [PMID: 37357072 DOI: 10.1016/j.ijom.2023.06.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 06/03/2023] [Accepted: 06/06/2023] [Indexed: 06/27/2023]
Abstract
The aim of this study was to investigate the treatment effects of a stabilisation splint (SS) with and without arthroscopic disc repositioning (ADR) on condylar bone remodelling in adolescent patients with anterior disc displacement without reduction (ADDwoR). Cone beam computed tomography and magnetic resonance imaging were used to analyse condylar bone remodelling, condyle position, and disc position. Twenty-two temporomandibular joints of 14 patients who underwent ADR (age range 12-20 years; mean follow-up 12.5 ± 7.8 months) and 21 temporomandibular joints of 14 patients who did not undergo ADR (age range 13-20 years; mean follow-up 11.1 ± 5.1 months) were included. The change in bone volume (P < 0.001), rate of bone volume change (P < 0.001), and change in condyle height (P = 0.031) were significantly greater in patients with ADR than in those without ADR. The changes in posterior joint space (P = 0.013), superior joint space (P = 0.020), and ratio of condyle sagittal position (P = 0.013) were significantly greater in patients with ADR than in those without ADR. All discs in patients who underwent ADR and one disc in those who did not undergo ADR were backward repositioned. In conclusion, in adolescent patients with ADDwoR, ADR with SS therapy achieved better condyle and disc position than SS therapy alone, and also induced bone generation.
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Affiliation(s)
- W H Ding
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou, Zhejiang, China
| | - Y F Li
- The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, Zhejiang, China
| | - W Liu
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou, Zhejiang, China
| | - W Li
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou, Zhejiang, China
| | - N Wu
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou, Zhejiang, China
| | - S Y Hu
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou, Zhejiang, China
| | - J J Shi
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou, Zhejiang, China.
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Liu W, Cai L, Li Y. Application of natural language processing to post-structuring of rectal cancer MRI reports. Clin Radiol 2024; 79:e204-e210. [PMID: 38042740 DOI: 10.1016/j.crad.2023.10.032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 10/20/2023] [Accepted: 10/26/2023] [Indexed: 12/04/2023]
Abstract
AIM To evaluate a natural language processing (NLP) system for extracting structured information from the free-form text of rectal cancer magnetic resonance imaging (MRI) reports written in Chinese. MATERIALS AND METHODS A rule-based NLP model that could extract 11 key image features of rectal cancer was constructed using 358 MRI reports of rectal cancer written between 2015 and 2021. Fifty reports written before 2015 and 50 written after 2021 were used as test datasets, and the reference standard was determined by manual extraction of information by two radiologists. The length and reporting rate of image features in pre-2015 and post-2021 datasets, as well as the accuracy, precision, recall, and F1 score of feature extraction by the NLP system, were compared. The time required for the NLP to extract data was compared with that required by the radiologists. RESULTS Reports written after 2021 had longer diagnostic impression sections than reports written before 2015. The reporting rate of key imaging features of rectal cancer was 36.55% before 2015 and 79.82% after 2021. The accuracy, precision, recall, and F1 score of NLP for correct extraction of values from reports were 93.82%, 95.63%, 87.06%, and 91.15%, respectively, for pre-2015 reports, and 92.55%, 98.53%, 94.15%, and 96.29%, respectively, for post-2021 reports. NLP generated all the structured information in <1 second. CONCLUSIONS The NLP system with rule-based pattern matching achieved rapid and accurate structured processing of rectal cancer MRI reports. MRI reports with structured templates are more suitable for NLP-based extraction of information.
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Affiliation(s)
- W Liu
- Department of Radiology, Aerospace Center Hospital, Beijing, 100049, China; Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, China
| | - L Cai
- School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, China
| | - Y Li
- Department of General Surgery, Aerospace Center Hospital, Beijing, 100049, China.
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Gao Z, Su Y, Chang L, Jiao G, Ou Y, Yang M, Xu C, Liu P, Wang Z, Qi Z, Liu W, Sun L, He G, Deng XW, He H. Increased long-distance and homo-trans interactions related to H3K27me3 in Arabidopsis hybrids. J Integr Plant Biol 2024; 66:208-227. [PMID: 38326968 DOI: 10.1111/jipb.13620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Accepted: 01/04/2024] [Indexed: 02/09/2024]
Abstract
In plants, the genome structure of hybrids changes compared with their parents, but the effects of these changes in hybrids remain elusive. Comparing reciprocal crosses between Col × C24 and C24 × Col in Arabidopsis using high-throughput chromosome conformation capture assay (Hi-C) analysis, we found that hybrid three-dimensional (3D) chromatin organization had more long-distance interactions relative to parents, and this was mainly located in promoter regions and enriched in genes with heterosis-related pathways. The interactions between euchromatin and heterochromatin were increased, and the compartment strength decreased in hybrids. In compartment domain (CD) boundaries, the distal interactions were more in hybrids than their parents. In the hybrids of CURLY LEAF (clf) mutants clfCol × clfC24 and clfC24 × clfCol , the heterosis phenotype was damaged, and the long-distance interactions in hybrids were fewer than in their parents with lower H3K27me3. ChIP-seq data revealed higher levels of H3K27me3 in the region adjacent to the CD boundary and the same interactional homo-trans sites in the wild-type (WT) hybrids, which may have led to more long-distance interactions. In addition, the differentially expressed genes (DEGs) located in the boundaries of CDs and loop regions changed obviously in WT, and the functional enrichment for DEGs was different between WT and clf in the long-distance interactions and loop regions. Our findings may therefore propose a new epigenetic explanation of heterosis in the Arabidopsis hybrids and provide new insights into crop breeding and yield increase.
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Affiliation(s)
- Zhaoxu Gao
- School of Advanced Agriculture Sciences and School of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Peking University, Beijing, 100871, China
| | - Yanning Su
- School of Advanced Agriculture Sciences and School of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Peking University, Beijing, 100871, China
| | - Le Chang
- School of Advanced Agriculture Sciences and School of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Peking University, Beijing, 100871, China
| | - Guanzhong Jiao
- School of Advanced Agriculture Sciences and School of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Peking University, Beijing, 100871, China
| | - Yang Ou
- School of Advanced Agriculture Sciences and School of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Peking University, Beijing, 100871, China
| | - Mei Yang
- School of Advanced Agriculture Sciences and School of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Peking University, Beijing, 100871, China
| | - Chao Xu
- School of Advanced Agriculture Sciences and School of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Peking University, Beijing, 100871, China
| | - Pengtao Liu
- School of Advanced Agriculture Sciences and School of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Peking University, Beijing, 100871, China
| | - Zejia Wang
- School of Advanced Agriculture Sciences and School of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Peking University, Beijing, 100871, China
| | - Zewen Qi
- College of Grassland Science, Beijing Forestry University, Beijing, 100083, China
| | - Wenwen Liu
- School of Advanced Agriculture Sciences and School of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Peking University, Beijing, 100871, China
| | - Linhua Sun
- School of Advanced Agriculture Sciences and School of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Peking University, Beijing, 100871, China
| | - Guangming He
- School of Advanced Agriculture Sciences and School of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Peking University, Beijing, 100871, China
| | - Xing Wang Deng
- School of Advanced Agriculture Sciences and School of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Peking University, Beijing, 100871, China
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Weifang 261325, China
| | - Hang He
- School of Advanced Agriculture Sciences and School of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Peking University, Beijing, 100871, China
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Weifang 261325, China
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Lu J, Wang M, Wang X, Meng Y, Chen F, Zhuang J, Han Y, Wang H, Liu W. A basement membrane extract-based three-dimensional culture system promotes the neuronal differentiation of cochlear Sox10-positive glial cells in vitro. Mater Today Bio 2024; 24:100937. [PMID: 38269057 PMCID: PMC10805941 DOI: 10.1016/j.mtbio.2023.100937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 12/14/2023] [Accepted: 12/27/2023] [Indexed: 01/26/2024] Open
Abstract
Spiral ganglion neurons (SGNs) in the mammalian cochleae are essential for the delivery of acoustic information, and damage to SGNs can lead to permanent sensorineural hearing loss as SGNs are not capable of regeneration. Cochlear glial cells (GCs) might be a potential source for SGN regeneration, but the neuronal differentiation ability of GCs is limited and its properties are not clear yet. Here, we characterized the cochlear Sox10-positive (Sox10+) GCs as a neural progenitor population and developed a basement membrane extract-based three-dimensional (BME-3D) culture system to promote its neuronal generation capacity in vitro. Firstly, the purified Sox10+ GCs, isolated from Sox10-creER/tdTomato mice via flow cytometry, were able to form neurospheres after being cultured in the traditional suspension culture system, while significantly more neurospheres were found and the expression of stem cell-related genes was upregulated in the BME-3D culture group. Next, the BME-3D culture system promoted the neuronal differentiation ability of Sox10+ GCs, as evidenced by the increased number, neurite outgrowth, area of growth cones, and synapse density as well as the promoted excitability of newly induced neurons. Notably, the BME-3D culture system also intensified the reinnervation of newly generated neurons with HCs and protected the neurospheres and derived-neurons against cisplatin-induced damage. Finally, transcriptome sequencing analysis was performed to identify the characteristics of the differentiated neurons. These findings suggest that the BME-3D culture system considerably promotes the proliferation capacity and neuronal differentiation efficiency of Sox10+ GCs in vitro, thus providing a possible strategy for the SGN regeneration study.
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Affiliation(s)
- Junze Lu
- Department of Otolaryngology-Head and Neck Surgery, Shandong Provincial ENT Hospital, Shandong University, Jinan, 250022, China
- Shandong Institute of Otorhinolaryngology, Jinan, 250022, China
| | - Man Wang
- Department of Otolaryngology-Head and Neck Surgery, Shandong Provincial ENT Hospital, Shandong University, Jinan, 250022, China
- Shandong Institute of Otorhinolaryngology, Jinan, 250022, China
| | - Xue Wang
- Department of Otolaryngology-Head and Neck Surgery, Shandong Provincial ENT Hospital, Shandong University, Jinan, 250022, China
- Shandong Institute of Otorhinolaryngology, Jinan, 250022, China
| | - Yu Meng
- Department of Otolaryngology-Head and Neck Surgery, Shandong Provincial ENT Hospital, Shandong University, Jinan, 250022, China
- Shandong Institute of Otorhinolaryngology, Jinan, 250022, China
| | - Fang Chen
- Department of Otolaryngology-Head and Neck Surgery, Shandong Provincial ENT Hospital, Shandong University, Jinan, 250022, China
- Shandong Institute of Otorhinolaryngology, Jinan, 250022, China
| | - Jinzhu Zhuang
- Department of Otolaryngology-Head and Neck Surgery, Shandong Provincial ENT Hospital, Shandong University, Jinan, 250022, China
- Shandong Institute of Otorhinolaryngology, Jinan, 250022, China
| | - Yuechen Han
- Department of Otolaryngology-Head and Neck Surgery, Shandong Provincial ENT Hospital, Shandong University, Jinan, 250022, China
- Shandong Institute of Otorhinolaryngology, Jinan, 250022, China
| | - Haibo Wang
- Department of Otolaryngology-Head and Neck Surgery, Shandong Provincial ENT Hospital, Shandong University, Jinan, 250022, China
- Shandong Institute of Otorhinolaryngology, Jinan, 250022, China
| | - Wenwen Liu
- Department of Otolaryngology-Head and Neck Surgery, Shandong Provincial ENT Hospital, Shandong University, Jinan, 250022, China
- Shandong Institute of Otorhinolaryngology, Jinan, 250022, China
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Long Q, Cao S, Huang G, Wang X, Liu Z, Liu W, Wang Y, Xiao H, Peng Y, Zhou Y. Population comparative genomic analyses unveil gene gain and loss during grapevine domestication. Plant Physiol 2024:kiae039. [PMID: 38285049 DOI: 10.1093/plphys/kiae039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 12/06/2023] [Accepted: 01/01/2024] [Indexed: 01/30/2024]
Abstract
Plant domestication shapes gene contents between the cultivars and their wild progenitors. Previously, short-reads and small variants (SNPs, indels and microsatellites) were mostly used to study grapevine (Vitis vinifera) domestication processes. Due to the lack of population-level assemblies for both the crop and its wild progenitors, capturing gene gain and loss caused by large structural variants remains a challenge. Here, we applied comparative genomic analyses to discover gene gain and loss during grapevine domestication using long-read assemblies of representative population samples for both domesticated grapevines (V. vinifera ssp. vinifera) and their wild progenitors (V. vinifera ssp. sylvestris). Only ∼7% of gene families were shared by 16 Vitis genomes while ∼8% of gene families were specific to each accession, suggesting dramatic variations of gene contents in grapevine genomes. Compared to wild progenitors, the domesticated accessions possessed more genes involved in asexual reproduction, while the wild progenitors harbored more genes related to pollination, revealing the transition from sexual reproduction to clonal propagation during domestication processes. Moreover, the domesticated accessions harbored fewer disease-resistance genes than wild progenitors. The structural variants occurred frequently in aroma and disease-resistance related genes between domesticated grapevines and wild progenitors, indicating the rapid diversification of these genes during domestication. Our study provides insights and resources for biological studies and breeding programs in grapevine.
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Affiliation(s)
- Qiming Long
- National Key Laboratory of Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Shuo Cao
- National Key Laboratory of Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Key Laboratory of Horticultural Plant Biology Ministry of Education, Huazhong Agricultural University, Wuhan, China
| | - Guizhou Huang
- National Key Laboratory of Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Xu Wang
- National Key Laboratory of Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- School of Agriculture and Food Science, University College Dublin, Belfield, Dublin, Ireland
| | - Zhongjie Liu
- National Key Laboratory of Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Wenwen Liu
- National Key Laboratory of Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Yiwen Wang
- National Key Laboratory of Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Hua Xiao
- National Key Laboratory of Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Yanling Peng
- National Key Laboratory of Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Yongfeng Zhou
- National Key Laboratory of Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- National Key Laboratory of Tropical Crop Breeding, Tropical Crops Genetic Resources Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou, China
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Liu X, Onda M, Schlomer J, Bassel L, Kozlov S, Tai CH, Zhou Q, Liu W, Tsao HE, Hassan R, Ho M, Pastan I. Tumor resistance to anti-mesothelin CAR-T cells caused by binding to shed mesothelin is overcome by targeting a juxtamembrane epitope. Proc Natl Acad Sci U S A 2024; 121:e2317283121. [PMID: 38227666 PMCID: PMC10823246 DOI: 10.1073/pnas.2317283121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Accepted: 11/27/2023] [Indexed: 01/18/2024] Open
Abstract
Despite many clinical trials, CAR-T cells are not yet approved for human solid tumor therapy. One popular target is mesothelin (MSLN) which is highly expressed on the surface of about 30% of cancers including mesothelioma and cancers of the ovary, pancreas, and lung. MSLN is shed by proteases that cleave near the C terminus, leaving a short peptide attached to the cell. Most anti-MSLN antibodies bind to shed MSLN, which can prevent their binding to target cells. To overcome this limitation, we developed an antibody (15B6) that binds next to the membrane at the protease-sensitive region, does not bind to shed MSLN, and makes CAR-T cells that have much higher anti-tumor activity than a CAR-T that binds to shed MSLN. We have now humanized the Fv (h15B6), so the CAR-T can be used to treat patients and show that h15B6 CAR-T produces complete regressions in a hard-to-treat pancreatic cancer patient derived xenograft model, whereas CAR-T targeting a shed epitope (SS1) have no anti-tumor activity. In these pancreatic cancers, the h15B6 CAR-T replicates and replaces the cancer cells, whereas there are no CAR-T cells in the tumors receiving SS1 CAR-T. To determine the mechanism accounting for high activity, we used an OVCAR-8 intraperitoneal model to show that poorly active SS1-CAR-T cells are bound to shed MSLN, whereas highly active h15B6 CAR-T do not contain bound MSLN enabling them to bind to and kill cancer cells.
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Affiliation(s)
- X.F. Liu
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, MD20892
| | - M. Onda
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, MD20892
| | - J. Schlomer
- Center for Advanced Preclinical Research, Frederick National Lab for Cancer Research Center for Cancer Research, National Cancer Institute, NIH, Frederick, MD 21701
| | - L. Bassel
- Center for Advanced Preclinical Research, Frederick National Lab for Cancer Research Center for Cancer Research, National Cancer Institute, NIH, Frederick, MD 21701
| | - S. Kozlov
- Center for Advanced Preclinical Research, Frederick National Lab for Cancer Research Center for Cancer Research, National Cancer Institute, NIH, Frederick, MD 21701
| | - C.-H. Tai
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, MD20892
| | - Q. Zhou
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, MD20892
| | - W. Liu
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, MD20892
| | - H.-E. Tsao
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, MD20892
| | - R. Hassan
- Thoracic and Gastrointestinal Malignancies Branch, National Cancer Institute, NIH, Bethesda, MD20892
| | - M. Ho
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, MD20892
| | - I. Pastan
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, MD20892
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Parshina EY, Liu W, Yusipovich AI, Gvozdev DA, He Y, Pirutin SK, Klimanova EA, Maksimov EG, Maksimov GV. Spectral and conformational characteristics of phycocyanin associated with changes of medium pH. Photosynth Res 2024:10.1007/s11120-023-01068-0. [PMID: 38224422 DOI: 10.1007/s11120-023-01068-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/01/2023] [Accepted: 12/09/2023] [Indexed: 01/16/2024]
Abstract
C-phycocyanin (C-PC) is the main component of water-soluble light-harvesting complexes (phycobilisomes, PBS) of cyanobacteria. PBS are involved in the absorption of quantum energy and the transfer of electronic excitation energy to the photosystems. A specific environment of C-PC chromophoric groups is provided by the protein matrix structure including protein-protein contacts between different subunits. Registration of C-PC spectral characteristics and the fluorescence anisotropy decay have revealed a significant pH influence on the chromophore microenvironment: at pH 5.0, a chromophore is more significantly interacts with the solvent, whereas at pH 9.0 the chromophore microenvironment becomes more viscous. Conformations of chromophores and the C-PC protein matrix have been studied by Raman and infrared spectroscopy. A decrease in the medium pH results in changes in the secondary structure either the C-PC apoproteins and chromophores, the last one adopts a more folded conformation.
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Affiliation(s)
- E Yu Parshina
- Faculty of Biology, Shenzhen MSU-BIT University, Shenzhen, 518172, China.
- Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia, 119991.
| | - W Liu
- Faculty of Biology, Shenzhen MSU-BIT University, Shenzhen, 518172, China
| | - A I Yusipovich
- Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia, 119991
| | - D A Gvozdev
- Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia, 119991
| | - Y He
- Faculty of Biology, Shenzhen MSU-BIT University, Shenzhen, 518172, China
| | - S K Pirutin
- Faculty of Biology, Shenzhen MSU-BIT University, Shenzhen, 518172, China
- Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia, 119991
- Institute of Theoretical and Experimental Biophysics of Russian Academy of Sciences, Institutskaya St. 3, Pushchino, Russia, 142290
| | - E A Klimanova
- Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia, 119991
| | - E G Maksimov
- Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia, 119991
| | - G V Maksimov
- Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia, 119991
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Lu J, Wang M, Meng Y, An W, Wang X, Sun G, Wang H, Liu W. Current advances in biomaterials for inner ear cell regeneration. Front Neurosci 2024; 17:1334162. [PMID: 38282621 PMCID: PMC10811200 DOI: 10.3389/fnins.2023.1334162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Accepted: 12/28/2023] [Indexed: 01/30/2024] Open
Abstract
Inner ear cell regeneration from stem/progenitor cells provides potential therapeutic strategies for the restoration of sensorineural hearing loss (SNHL), however, the efficiency of regeneration is low and the functions of differentiated cells are not yet mature. Biomaterials have been used in inner ear cell regeneration to construct a more physiologically relevant 3D culture system which mimics the stem cell microenvironment and facilitates cellular interactions. Currently, these biomaterials include hydrogel, conductive materials, magneto-responsive materials, photo-responsive materials, etc. We analyzed the characteristics and described the advantages and limitations of these materials. Furthermore, we reviewed the mechanisms by which biomaterials with different physicochemical properties act on the inner ear cell regeneration and depicted the current status of the material selection based on their characteristics to achieve the reconstruction of the auditory circuits. The application of biomaterials in inner ear cell regeneration offers promising opportunities for the reconstruction of the auditory circuits and the restoration of hearing, yet biomaterials should be strategically explored and combined according to the obstacles to be solved in the inner ear cell regeneration research.
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Affiliation(s)
- Junze Lu
- Department of Otolaryngology-Head and Neck Surgery, Shandong Provincial ENT Hospital, Shandong University, Jinan, China
- Shandong Institute of Otorhinolaryngology, Jinan, China
| | - Man Wang
- Department of Otolaryngology-Head and Neck Surgery, Shandong Provincial ENT Hospital, Shandong University, Jinan, China
- Shandong Institute of Otorhinolaryngology, Jinan, China
| | - Yu Meng
- Department of Otolaryngology-Head and Neck Surgery, Shandong Provincial ENT Hospital, Shandong University, Jinan, China
- Shandong Institute of Otorhinolaryngology, Jinan, China
| | - Weibin An
- Department of Otolaryngology-Head and Neck Surgery, Shandong Provincial ENT Hospital, Shandong University, Jinan, China
- Shandong Institute of Otorhinolaryngology, Jinan, China
| | - Xue Wang
- Department of Otolaryngology-Head and Neck Surgery, Shandong Provincial ENT Hospital, Shandong University, Jinan, China
- Shandong Institute of Otorhinolaryngology, Jinan, China
| | - Gaoying Sun
- Department of Otolaryngology-Head and Neck Surgery, Shandong Provincial ENT Hospital, Shandong University, Jinan, China
- Shandong Institute of Otorhinolaryngology, Jinan, China
| | - Haibo Wang
- Department of Otolaryngology-Head and Neck Surgery, Shandong Provincial ENT Hospital, Shandong University, Jinan, China
- Shandong Institute of Otorhinolaryngology, Jinan, China
| | - Wenwen Liu
- Department of Otolaryngology-Head and Neck Surgery, Shandong Provincial ENT Hospital, Shandong University, Jinan, China
- Shandong Institute of Otorhinolaryngology, Jinan, China
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Ji J, Qin J, Wang X, Lv M, Hou X, Jing A, Zhou J, Zuo L, Liu W, Feng J, Qian Q, Liu Y, Wang X, Liu B. JHD205, A Novel Abemaciclib Derivative, Exerts Antitumor Effects on Breast Cancer by CDK4/6. Anticancer Agents Med Chem 2024; 24:ACAMC-EPUB-137080. [PMID: 38192142 DOI: 10.2174/0118715206265751231204190204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 10/09/2023] [Accepted: 10/16/2023] [Indexed: 01/10/2024]
Abstract
BACKGROUND Efficient targeted molecular therapeutics are needed for the treatment of triple-negative breast cancer (TNBC), a highly invasive and difficult-to-treat form of breast cancer associated with a poor prognosis. OBJECTIVES This study aims to evaluate the potential of selective CDK4/6 inhibitors as a therapeutic option for TNBC by impairing the cell cycle G1 phase through the inhibition of retinoblastoma protein (Rb) phosphorylation. METHODS In this study, we synthesized a compound called JHD205, derived from the chemical structure of Abemaciclib, and examined its inhibitory effects on the malignant characteristics of TNBC cells. RESULTS Our results demonstrated that JHD205 exhibited superior tumor growth inhibition compared to Abemaciclib in breast cancer xenograft chicken embryo models. Western blot analysis revealed that JHD205 could dosedependently degrade CDK4 and CDK6 while also causing abnormal changes in other proteins associated with CDK4/6, such as p-Rb, Rb, and E2F1. Moreover, JHD205 induced apoptosis and DNA damage and inhibited DNA repair by upregulating Caspase3 and p-H2AX protein levels. CONCLUSION Collectively, our findings suggest that JHD205 holds promise as a potential treatment for breast carcinoma.
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Affiliation(s)
- Jing Ji
- Jiangsu Key Laboratory of Marine Pharmaceutical Compound Screening, College of Pharmacy, Jiangsu Ocean University, Lianyungang, China
| | - Jingting Qin
- Jiangsu Key Laboratory of Marine Pharmaceutical Compound Screening, College of Pharmacy, Jiangsu Ocean University, Lianyungang, China
| | - Xiaoshuo Wang
- Jiangsu Key Laboratory of Marine Pharmaceutical Compound Screening, College of Pharmacy, Jiangsu Ocean University, Lianyungang, China
| | - Mingxiao Lv
- Jiangsu Key Laboratory of Marine Pharmaceutical Compound Screening, College of Pharmacy, Jiangsu Ocean University, Lianyungang, China
| | - Xiao Hou
- Jiangsu Key Laboratory of Marine Pharmaceutical Compound Screening, College of Pharmacy, Jiangsu Ocean University, Lianyungang, China
| | - Aixin Jing
- Jiangsu Key Laboratory of Marine Pharmaceutical Compound Screening, College of Pharmacy, Jiangsu Ocean University, Lianyungang, China
| | - Jiaojiao Zhou
- Jiangsu Key Laboratory of Marine Pharmaceutical Compound Screening, College of Pharmacy, Jiangsu Ocean University, Lianyungang, China
| | - Lingyi Zuo
- Jiangsu Key Laboratory of Marine Pharmaceutical Compound Screening, College of Pharmacy, Jiangsu Ocean University, Lianyungang, China
| | - Wenwen Liu
- Jiangsu Key Laboratory of Marine Pharmaceutical Compound Screening, College of Pharmacy, Jiangsu Ocean University, Lianyungang, China
| | - Jing Feng
- Jiangsu Key Laboratory of Marine Pharmaceutical Compound Screening, College of Pharmacy, Jiangsu Ocean University, Lianyungang, China
| | - Qilan Qian
- Jiangsu Key Laboratory of Marine Pharmaceutical Compound Screening, College of Pharmacy, Jiangsu Ocean University, Lianyungang, China
| | - Yuanyuan Liu
- Jiangsu Key Laboratory of Marine Pharmaceutical Compound Screening, College of Pharmacy, Jiangsu Ocean University, Lianyungang, China
| | - Xiujun Wang
- Jiangsu Key Laboratory of Marine Pharmaceutical Compound Screening, College of Pharmacy, Jiangsu Ocean University, Lianyungang, China
| | - Bin Liu
- Jiangsu Key Laboratory of Marine Pharmaceutical Compound Screening, College of Pharmacy, Jiangsu Ocean University, Lianyungang, China
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Ren H, Wang Z, Shang X, Zhang X, Ma L, Bian Y, Wang D, Liu W. Involvement of GA3-oxidase in inhibitory effect of nitric oxide on primary root growth in Arabidopsis. Plant Biol (Stuttg) 2024; 26:117-125. [PMID: 38014496 DOI: 10.1111/plb.13600] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 11/13/2023] [Indexed: 11/29/2023]
Abstract
Both NO and GAs are essential for regulating various physiological processes and stress responses in plants. However, the interaction between these two molecules remains unclear. We investigated the distinct response patterns of Arabidopsis thaliana Col-0 and GA synthesis functional deficiency mutants to NO by measuring root length. To investigate underlying mechanisms, we detected bioactive GA content using UHPLC-ESI-MS/MS, assessed the accumulation of ROS by chemical staining Arabidopsis roots. We also conducted RNA-seq analysis and compared results between Col-0 and ga3ox1, with and without SNP (as NO donor) treatment. Phenotypic results revealed that the inhibitory effect of NO on primary roots of Arabidopsis was primarily mediated by GA3-oxidase, rather than GA20-oxidase or GA2-oxidase. The content of GA3 decreased in Col-0 treated with SNP, whereas this decrease was not observed in ga3ox1. The deficiency of GA3-oxidase alleviated the buildup of H2 O2 in roots when treated with SNP. We identified 222 DEGs. GO annotation of these DEGs revealed that all top 20 GO terms were related to stress responses. Moreover, three DEGs were annotated to GA-related processes (DDF1, DDF2, EXPA1), and seven DEGs were associated with root development (RAV1, RGF2, ERF71, ZAT6, MYB77, XT1, and DTX50). In summary, NO inhibits primary root growth partially by repressing GA3-oxidase catalysed GA3 synthesis in Arabidopsis. ROS, Ca2+ , DDF1, DDF2, EXPA1 and seven root development-related genes may be involved in crosstalk between NO and GAs.
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Affiliation(s)
- H Ren
- Shanxi Normal University, Taiyuan, Shanxi, China
| | - Z Wang
- Shanxi Normal University, Taiyuan, Shanxi, China
| | - X Shang
- Shanxi Normal University, Taiyuan, Shanxi, China
| | - X Zhang
- Shanxi Normal University, Taiyuan, Shanxi, China
| | - L Ma
- Shanxi Normal University, Taiyuan, Shanxi, China
| | - Y Bian
- Shanxi Normal University, Taiyuan, Shanxi, China
| | - D Wang
- Shanxi Normal University, Taiyuan, Shanxi, China
| | - W Liu
- Shanxi Normal University, Taiyuan, Shanxi, China
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Zeng HQ, Li G, Zhou KX, Li AD, Liu W, Zhang Y. Causal link between gut microbiota and osteoporosis analyzed via Mendelian randomization. Eur Rev Med Pharmacol Sci 2024; 28:542-555. [PMID: 38305631 DOI: 10.26355/eurrev_202401_35052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 02/03/2024]
Abstract
OBJECTIVE Osteoporosis (OP) is closely associated with gut microbiota (GM), yet the nature of their causal relationship remains elusive. Therefore, this study aims to reverse causality between GM and OP by using population cohorts and two-sample MR (TSMR) analysis. MATERIALS AND METHODS In this study, we conducted an extensive genome-wide association study (GWAS) using publicly accessible summary statistics data for GM and OP. Employing rigorous criteria (p < 1*e-5), we identified independent genetic loci that exhibited significant associations with GM relative abundances as instrumental variables (IVs). A causal evaluation was primarily carried out using the inverse variance-weighted (IVW) method, supplemented by additional analyses such as MR-Egger, weighted median, simple mode, and weighted mode. RESULTS We unveiled that increased abundances of the family Pasteurellaceae, order Pasteurellales, and genus Ruminococcaceae UCG004 were linked to an increased risk of OP. Conversely, the family Oxalobacteraceae, unknown family id.1000006161, genus Lachnospiraceae NK4A136 group, unknown genus id.1000006162, and order NB1n were associated with a reduced risk of OP. To ensure the reliability of our findings, we conducted quality assessments through Cochrane's Q test and a leave-one-out analysis. Furthermore, the stability and consistency of the results were confirmed by the MR-Egger intercept test, Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) global test, and sensitivity analysis (p > 0.05). Our study reveals the causal relationships between 211 GM taxa and OP, pinpointing specific GM taxa associated with the risk of OP. This research sheds light on the genetic mechanisms that underlie GM-mediated OP and opens up promising avenues for identifying valuable biomarkers and potential therapeutic targets in future OP research. CONCLUSIONS This study establishes a substantial GM-OP link with specific taxa being identified, offering biomarkers for early detection, tailored interventions, and improved patient education. These findings enhance OP diagnosis, prevention, and treatment, promising more effective, individualized care and inspiring future research.
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Affiliation(s)
- H-Q Zeng
- Traditional Chinese Medicine Department of Rheumatism, Women and Children Health Institute Futian Shenzhen, Shenzhen, China.
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Liu W, Yu Y, Wang Y, Yang T, Kong Y, Xie X, Zhang J. Deciphering the genetic basis of resistome and virulome diversity among multidrug-resistant Mycoplasma hominis. Drug Resist Updat 2024; 72:101029. [PMID: 38071861 DOI: 10.1016/j.drup.2023.101029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 11/12/2023] [Accepted: 11/24/2023] [Indexed: 01/08/2024]
Abstract
Mycoplasma hominis, a commensal bacterium that commonly inhabits the genital tract, leading to infections in both the genitourinary and extragenital regions. However, the antimicrobial resistance and pathogenic mechanisms of M. hominis isolated from extra-urogenital cystic abscess is largely unknown. This study reports the genomic epidemiological characteristics of a M. hominis isolate recovered from a pelvic abscess sample in China. Genomic DNA was extracted and sequenced using Illumina HiSeq X Ten platform. De novo assembly was performed and in silico analysis was accomplished by multiple bioinformatics tools. For phylogenomic analysis, publicly available M. hominis genomes were retrieved from NCBI GenBank database. Whole genome sequencing data showed that the genome size of M. hominis MH4246 was calculated as 679,746 bp, with 558 protein-coding sequences and a G + C content of 26.9%. M. hominis MH4246 is resistant to fluoroquinolones and macrolides, harboring mutations in the quinolone resistance-determining regions (QRDRs) (GyrA S153L, ParC S91I and ParE V417I) and 23S rRNA gene (G280A, C1500T, T1548C and T2218C). Multiple virulence determinants, such as tuf, hlyA, vaa, oppA, MHO_0730 and alr genes, were identified. Phylogenetic analysis showed that the closest relative of M. hominis MH4246 was the strain MH-1 recovered from China, which differed by 3490 SNPs. Overall, this study contributes to the comprehension of genomic characteristics, antimicrobial resistance patterns, and the mechanisms underlying the pathogenicity of this pathogen.
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Affiliation(s)
- Wenwen Liu
- Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China; Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, Hangzhou, China
| | - Yawen Yu
- Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yuting Wang
- Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Ting Yang
- Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China; Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, Hangzhou, China
| | - Yingying Kong
- Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China; Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, Hangzhou, China
| | - Xinyou Xie
- Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China; Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, Hangzhou, China.
| | - Jun Zhang
- Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China; Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, Hangzhou, China.
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Nian Z, Zhao Q, He Y, Xie R, Liu W, Chen T, Huang S, Dong L, Huang R, Yang L. Efficacy and Safety of First-line Therapies for Advanced Unresectable Oesophageal Squamous Cell Cancer: a Systematic Review and Network Meta-analysis. Clin Oncol (R Coll Radiol) 2024; 36:30-38. [PMID: 37827946 DOI: 10.1016/j.clon.2023.09.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 08/27/2023] [Accepted: 09/21/2023] [Indexed: 10/14/2023]
Abstract
AIM To compare the clinical efficacy and safety of first-line treatments for advanced unresectable oesophageal squamous cell cancer. MATERIALS AND METHODS A systematic review and network meta-analysis was carried out by retrieving and retaining relevant literature from databases. The studies were randomised controlled trials comparing first-line treatments for advanced unresectable oesophageal squamous cell cancer. A Bayesian network meta-analysis was used to assess clinical outcomes. RESULTS Nine studies including 4499 patients receiving first-line treatments were analysed. For all populations, toripalimab plus chemotherapy tended to provide the best overall survival (hazard ratio 0.58, 95% confidence intervals 0.43-0.78) and sintilimab plus chemotherapy provided the best progression-free survival (0.56, 0.46-0.68). Nivolumab plus chemotherapy presented the best objective response rate (odds ratio 2.45, 1.78-3.42) and camrelizumab plus chemotherapy (0.47, 0.29-0.74) appeared to be the safest. Sintilimab plus chemotherapy (0.55, 0.40-0.75) and nivolumab (0.54, 0.37-0.80) plus chemotherapy had the best overall survival in programmed death ligand 1 (PD-L1) tumour proportion score <1% and ≥1% subgroups. Toripalimab plus chemotherapy (0.61, 0.40-0.93) and pembrolizumab (0.57, 0.43-0.75) were the best in overall survival in combined positive score <10 and ≥10 subgroups, respectively. Toripalimab plus chemotherapy showed the best overall survival in the Asian group; pembrolizumab presented better overall survival in the Asian population than the non-Asian group. CONCLUSION Most immunotherapy combined with chemotherapy showed superior clinical benefits and sintilimab plus chemotherapy, toripalimab plus chemotherapy and tislelizumab plus chemotherapy had better comprehensive clinical efficacy. PD-L1 expression detection and ethnicity differences are still of great significance and most suitable regimens varied from each subgroup.
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Affiliation(s)
- Z Nian
- School of Pharmacy, Fujian Medical University, Fuzhou, China
| | - Q Zhao
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China
| | - Y He
- School of Pharmacy, Fujian Medical University, Fuzhou, China
| | - R Xie
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China
| | - W Liu
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China
| | - T Chen
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China
| | - S Huang
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China
| | - L Dong
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China
| | - R Huang
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China
| | - L Yang
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.
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45
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Ji Q, Lian W, Meng Y, Liu W, Zhuang M, Zheng N, Karlsson IK, Zhan Y. Cytomegalovirus Infection and Alzheimer's Disease: A Meta-Analysis. J Prev Alzheimers Dis 2024; 11:422-427. [PMID: 38374748 DOI: 10.14283/jpad.2023.126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/21/2024]
Abstract
BACKGROUND Evidence on the association of cytomegalovirus (CMV) infection with Alzheimer's disease (AD) is scarce and the results are inconsistent. OBJECTIVE To investigate the association of CMV infection with the risk of AD. METHODS Observational studies on the relationship between CMV infection and AD were identified from PubMed, Embase, Web of Science, and the Cochrane Library until September 30, 2022. The quality of included studies was assessed using the Newcastle-Ottawa Scale. Random-effect meta-analysis was performed using a generic inverse-variance method, followed by sensitivity analyses and subgroup analyses based on study designs, regions, adjustments, and population types. RESULTS Our search yielded 870 articles, of which 200 were duplicates and 663 did not meet the inclusion criteria, and finally yielded seven studies with 6,772 participants. No strong evidence was observed in the summary analysis for the association of CMV infection and risk of AD (odds ratio [OR] = 1.33; 95% confidence interval [CI]: 0.88, 2.03, I2 =69.9%). However, subgroup analysis showed that an increased risk of AD was detected in East Asians (OR = 2.39; 95% CI: 1.63, 3.50, I2 = 0.00%), cohort studies (OR = 1.99; 95% CI: 1.35, 2.94, I2 = 28.20%), and studies with confounder adjustment (OR = 2.05; 95% CI: 1.52, 2.77, I2 = 0.00%). CONCLUSIONS This meta-analysis provides evidence to support the heterogeneity of the associations between CMV infection and AD. Future studies with larger sample sizes and multi-ethnic populations are necessary.
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Affiliation(s)
- Q Ji
- Yiqiang Zhan, Department of Epidemiology, School of Public Health (Shenzhen), Sun Yat-Sen University, Shenzhen, China; Tel: 0755-23260106; E-mail:
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46
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Ji L, Ahmann AJ, Ahrén B, Capehorn MS, Hu P, Lingvay I, Liu W, Rodbard HW, Shen Z, Sorli C. Proportion of participants with type 2 diabetes achieving a metabolic composite endpoint with once-weekly semaglutide treatment versus comparators: Post hoc pooled analysis from SUSTAIN 1-5, 7-10 and SUSTAIN China. Diabetes Obes Metab 2024; 26:233-241. [PMID: 37822270 DOI: 10.1111/dom.15309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 09/05/2023] [Accepted: 09/15/2023] [Indexed: 10/13/2023]
Abstract
AIM To compare the proportion of participants with type 2 diabetes (T2D) treated with once-weekly (OW) subcutaneous (SC) semaglutide versus comparators who achieved a composite metabolic endpoint. MATERIALS AND METHODS SUSTAIN 1-5, 7-10 and SUSTAIN China trial data were pooled. Participants with T2D (aged ≥18 years) and glycated haemoglobin ≥7.0% (≥53 mmol/mol) who had been randomized to OW SC semaglutide (0.5 or 1.0 mg) or comparator in addition to background medication. Using patient-level data pooled by treatment, proportions of participants achieving the metabolic composite endpoint, defined as glycated haemoglobin <7% (<53 mmol/mol), blood pressure <140/90 mmHg and non-high-density lipoprotein cholesterol <130 mg/dl (<3.37 mmol/L), were evaluated following baseline adjustments. Endpoints were analysed per trial using a binomial logistic regression model with treatment, region/country and stratification factor as fixed effects and baseline value as covariate. Pooled analysis used logistic regression with treatment and trial as fixed effects and baseline value as covariate. RESULTS This post hoc analysis included data from 7633 participants across 10 trials. The proportion of participants who achieved the metabolic composite endpoint was significantly higher with OW SC semaglutide 0.5 and 1.0 mg versus comparators (23.7% and 32.0% vs. 11.5%, respectively; p < .0001). Likewise, when the OW SC semaglutide doses were pooled, significantly higher proportions of patients receiving semaglutide achieved the composite metabolic endpoint versus comparators (29.1% vs. 11.4%, respectively; p < .0001). CONCLUSIONS Treatment with OW SC semaglutide versus comparators was associated with increased proportions of participants with T2D meeting the composite metabolic endpoint.
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Affiliation(s)
- Linong Ji
- Peking University People's Hospital, Beijing, China
| | - A J Ahmann
- Oregon Health and Science University, Portland, Oregon, USA
| | - B Ahrén
- Lund University, Lund, Sweden
| | | | - P Hu
- Novo Nordisk (Shanghai) Pharma Trading Co., Ltd, Beijing, China
| | - I Lingvay
- University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - W Liu
- Novo Nordisk (Shanghai) Pharma Trading Co., Ltd, Beijing, China
| | - H W Rodbard
- Endocrine and Metabolic Consultants, Rockville, Maryland, USA
| | - Z Shen
- Novo Nordisk (Shanghai) Pharma Trading Co., Ltd, Beijing, China
| | - C Sorli
- Acerus Pharma, Toronto, Ontario, Canada
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47
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Chen L, Tan H, Feng R, Ma L, Zhang Y, Yi H, Yin L, Liu W, Hu L, Zhu W. Effect of modified starches on the quality of skins of glutinous rice dumplings. Int J Biol Macromol 2023; 253:127139. [PMID: 37793518 DOI: 10.1016/j.ijbiomac.2023.127139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 09/17/2023] [Accepted: 09/27/2023] [Indexed: 10/06/2023]
Abstract
This study aimed to investigate the influence of modified starches on the quality of skins of glutinous rice dumplings (SGRDs), including changes in textural properties, pasting parameters, microstructure, color, transparency, and sensory quality. The results showed that the addition of a single acetylated-modified cassava or potato starch or composite modified cassava and potato starch in a ratio of 2:1 can improve the quality of SGRDs. The springiness and lightness of SGRDs increased, and the transparency increased from 3.22 % to 6.18 %. The cooked samples had delicate mouth-feel, uniform color and luster, good transparency, no depression, and low weight loss and did not stick to the teeth. Moreover, the total consumer acceptability score increased from 60.67 to 89.33, indicating that these products were widely accepted by consumers. However, the addition of hydroxypropyl-modified cassava starch or its composite with other two modified starches had no apparent effect on the quality of SGRDs. In conclusion, the quality of SGRDs were significantly improved by the addition of single or composite acetylated-modified starches. This study provides a theoretical basis for improving the quality of SGRDs.
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Affiliation(s)
- Lu Chen
- Faculty of Agriculture, Forestry and Food Engineering, Yibin University, Yibin 643000, China; Solid-state Fermentation Resource Utilization Key Laboratory of Sichuan Province, Yibin 643000, China; Sichuan Province Engineering Technology Research Center of Oil Cinnamon, Yibin 643000, China
| | - Hongxia Tan
- College of Food Science, Southwest University, Chongqing 400715, China
| | - Ruizhang Feng
- Faculty of Agriculture, Forestry and Food Engineering, Yibin University, Yibin 643000, China; Sichuan Province Engineering Technology Research Center of Oil Cinnamon, Yibin 643000, China
| | - Liang Ma
- College of Food Science, Southwest University, Chongqing 400715, China
| | - Yuhao Zhang
- College of Food Science, Southwest University, Chongqing 400715, China
| | - Haitao Yi
- Faculty of Agriculture, Forestry and Food Engineering, Yibin University, Yibin 643000, China
| | - Liguo Yin
- Faculty of Agriculture, Forestry and Food Engineering, Yibin University, Yibin 643000, China; Solid-state Fermentation Resource Utilization Key Laboratory of Sichuan Province, Yibin 643000, China
| | - Wenwen Liu
- Faculty of Agriculture, Forestry and Food Engineering, Yibin University, Yibin 643000, China; Sichuan Province Engineering Technology Research Center of Oil Cinnamon, Yibin 643000, China
| | - Lianqing Hu
- Faculty of Agriculture, Forestry and Food Engineering, Yibin University, Yibin 643000, China; Sichuan Province Engineering Technology Research Center of Oil Cinnamon, Yibin 643000, China
| | - Wenyou Zhu
- Solid-state Fermentation Resource Utilization Key Laboratory of Sichuan Province, Yibin 643000, China.
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Zhang Z, Tian J, Liu W, Zhou J, Zhang Y, Ding L, Sun H, Yan G, Sheng X. Perfluorooctanoic acid exposure leads to defect in follicular development through disrupting the mitochondrial electron transport chain in granulosa cells. Sci Total Environ 2023; 905:166954. [PMID: 37722425 DOI: 10.1016/j.scitotenv.2023.166954] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 08/21/2023] [Accepted: 09/08/2023] [Indexed: 09/20/2023]
Abstract
Perfluorooctanoic acid (PFOA) is a persistent environmental pollutant that can impair ovarian function, while the underlying mechanism is not fully understood, and effective treatments are lacking. In this study, we established a mouse model of PFOA exposure induced by drinking water and found that PFOA exposure impaired follicle development, increased apoptosis of granulosa cells (GCs), and hindered normal follicular development in a 3D culture system. RNA-seq analysis revealed that PFOA disrupted oxidative phosphorylation in ovaries by impairing the mitochondrial electron transport chain. This resulted in reduced mitochondrial membrane potential and increased mitochondrial reactive oxygen species (mtROS) in isolated GCs or KGN cells. Resveratrol, a mitochondrial nutrient supplement, could improve mitochondrial function and restore normal follicular development by activating FoxO1 through SIRT1/PI3K-AKT pathway. Our results indicate that PFOA exposure impairs mitochondrial function in GCs and affects follicle development. Resveratrol can be a potential therapeutic agent for PFOA-induced ovarian dysfunction.
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Affiliation(s)
- Zhe Zhang
- Department of Reproductive Medicine and Obstetrics and Gynecology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China; State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China; Center for Molecular Reproductive Medicine, Nanjing University, Nanjing, China
| | - Jiao Tian
- Department of Reproductive Medicine and Obstetrics and Gynecology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China; State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China; Center for Molecular Reproductive Medicine, Nanjing University, Nanjing, China
| | - Wenwen Liu
- Department of Reproductive Medicine and Obstetrics and Gynecology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China; State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China; Center for Molecular Reproductive Medicine, Nanjing University, Nanjing, China
| | - Jidong Zhou
- Department of Reproductive Medicine and Obstetrics and Gynecology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China; State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China; Center for Molecular Reproductive Medicine, Nanjing University, Nanjing, China
| | - Yang Zhang
- Department of Reproductive Medicine and Obstetrics and Gynecology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China; State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China; Center for Molecular Reproductive Medicine, Nanjing University, Nanjing, China
| | - Lijun Ding
- Department of Reproductive Medicine and Obstetrics and Gynecology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China; State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China; Center for Molecular Reproductive Medicine, Nanjing University, Nanjing, China
| | - Haixiang Sun
- Department of Reproductive Medicine and Obstetrics and Gynecology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China; State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China; Center for Molecular Reproductive Medicine, Nanjing University, Nanjing, China.
| | - Guijun Yan
- Department of Reproductive Medicine and Obstetrics and Gynecology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China; Center for Molecular Reproductive Medicine, Nanjing University, Nanjing, China; State Key Laboratory of Pharmaceutical Biotechnology, Nanjing University, Nanjing, China.
| | - Xiaoqiang Sheng
- Center for Reproductive Medicine, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.
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Liu W, Li RY. [Enlightenment of World Health Organization fungal priority pathogens list]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:1984-1987. [PMID: 38129157 DOI: 10.3760/cma.j.cn112338-20230701-00410] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 12/23/2023]
Abstract
The WHO established the first fungal priority pathogens list (FPPL) in October 2022 to focus on and promote further research and policy interventions to strengthen the global response to fungal infections and antifungal resistance. The FPPL and its formulation process provide new significant insights for managing pathogenic fungi and invasive fungal disease (IFD) in China, necessitating the following key actions: Strengthen public health interventions for IFD. Further, it improves the ability of laboratory testing and clinical supervision for IFD and pathogenic fungi. Increase targeted investment and support for innovative research and development in IFD diagnosis, treatment, and prevention.
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Affiliation(s)
- W Liu
- Department of Dermatology, Peking University First Hospital/National Clinical Research Center for Skin and Immune Diseases/Research Center for Medical Mycology, Peking University/Beijing Key Laboratory of Molecular Diagnosis on Dermatoses/Peking University First Hospital-National Institute for Communicable Disease Control and Prevention Joint Laboratory of Pathogenic Fungi, Beijing 100034, China
| | - R Y Li
- Department of Dermatology, Peking University First Hospital/National Clinical Research Center for Skin and Immune Diseases/Research Center for Medical Mycology, Peking University/Beijing Key Laboratory of Molecular Diagnosis on Dermatoses/Peking University First Hospital-National Institute for Communicable Disease Control and Prevention Joint Laboratory of Pathogenic Fungi, Beijing 100034, China
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50
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Gong J, Geng YY, Zhang S, Liu W, Wu WW, Li RY, Zhang JZ. [Analysis of public health risks associated with pathogenic fungi in China]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:1977-1983. [PMID: 38129156 DOI: 10.3760/cma.j.cn112338-20230615-00376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 12/23/2023]
Abstract
At present, the public health risks caused by pathogenic fungi are greater in China and have attracted great attention from disease control departments. Due to the difficulty in diagnosing fungal infections, the public health risk of pathogenic fungi is currently hidden in the unexplained pneumonia/encephalitis/fever syndrome and is not effectively appreciated. From the public health perspective, the mainly focused fungal pathogens include highly pathogenic fungi (including dimorphic fungi and dematiaceous fungi), pathogenic fungi that cause regional aggregation infections, and drug-resistant pathogenic fungi. However, due to the lack of systematic monitoring data, the disease burden related to pathogenic fungi cannot be accurately quantified and evaluated. Therefore, to effectively reduce the serious harm of fungal infections to the public, systematic monitoring of pathogenic fungi should be carried out nationally.
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Affiliation(s)
- J Gong
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention/Peking University First Hospital-National Institute for Communicable Disease Control and Prevention Joint Laboratory of Pathogenic Fungi, Beijing 102206, China
| | - Y Y Geng
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention/Peking University First Hospital-National Institute for Communicable Disease Control and Prevention Joint Laboratory of Pathogenic Fungi, Beijing 102206, China
| | - S Zhang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention/Peking University First Hospital-National Institute for Communicable Disease Control and Prevention Joint Laboratory of Pathogenic Fungi, Beijing 102206, China
| | - W Liu
- Department of Dermatology, Peking University First Hospital/National Clinical Research Center for Skin and Immune Diseases/Research Center for Medical Mycology, Peking University/Beijing Key Laboratory of Molecular Diagnosis on Dermatoses/Peking University First Hospital-National Institute for Communicable Disease Control and Prevention Joint Laboratory of Pathogenic Fungi, Beijing 100034, China
| | - W W Wu
- Derpartment of Plastic and Dermatologic Surgery, the Fifth People's Hospital of Hainan Province, Haikou 570102, China
| | - R Y Li
- Department of Dermatology, Peking University First Hospital/National Clinical Research Center for Skin and Immune Diseases/Research Center for Medical Mycology, Peking University/Beijing Key Laboratory of Molecular Diagnosis on Dermatoses/Peking University First Hospital-National Institute for Communicable Disease Control and Prevention Joint Laboratory of Pathogenic Fungi, Beijing 100034, China
| | - J Z Zhang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention/Peking University First Hospital-National Institute for Communicable Disease Control and Prevention Joint Laboratory of Pathogenic Fungi, Beijing 102206, China
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