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Yang W, Wang Y, Han D, Tang W, Sun L. Recent advances in application of computer-aided drug design in anti-COVID-19 Virials Drug Discovery. Biomed Pharmacother 2024; 173:116423. [PMID: 38493593 DOI: 10.1016/j.biopha.2024.116423] [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: 12/08/2023] [Revised: 03/05/2024] [Accepted: 03/08/2024] [Indexed: 03/19/2024] Open
Abstract
Corona Virus Disease 2019 (COVID-19) is a global pandemic epidemic caused by severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), which poses a serious threat to human health worldwide and results in significant economic losses. With the continuous emergence of new virus strains, small molecule drugs remain the most effective treatment for COVID-19. The traditional drug development process usually requires several years; however, the development of computer-aided drug design (CADD) offers the opportunity to develop innovative drugs quickly and efficiently. The literature review describes the general process of CADD, the viral proteins that play essential roles in the life cycle of SARS-CoV-2 and can serve as therapeutic targets, and examples of drug screening of viral target proteins by applying CADD methods. Finally, the potential of CADD in COVID-19 therapy, the deficiency, and the possible future development direction are discussed.
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Affiliation(s)
- Weiying Yang
- Department of Emergency Medicine, First Hospital of Jilin University, Changchun 130021, China
| | - Ye Wang
- School of Life Sciences, Jilin University, Changchun 130012, China
| | - Dongfeng Han
- Department of Emergency Medicine, First Hospital of Jilin University, Changchun 130021, China
| | - Wenjing Tang
- Department of Emergency Medicine, First Hospital of Jilin University, Changchun 130021, China
| | - Lichao Sun
- Department of Emergency Medicine, First Hospital of Jilin University, Changchun 130021, China.
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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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Zong W, Song Y, Xiao D, Guo X, Li F, Sun K, Tang W, Xie W, Luo Y, Liang S, Zhou J, Xie X, Liu D, Chen L, Wang H, Liu YG, Guo J. Dominance complementation of parental heading date alleles of Hd1, Ghd7, DTH8, and PRR37 confers transgressive late maturation in hybrid rice. Plant J 2024. [PMID: 38526880 DOI: 10.1111/tpj.16732] [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: 10/03/2023] [Revised: 01/11/2024] [Accepted: 03/05/2024] [Indexed: 03/27/2024]
Abstract
Rice (Oryza sativa L.) is a short-day plant whose heading date is largely determined by photoperiod sensitivity (PS). Many parental lines used in hybrid rice breeding have weak PS, but their F1 progenies have strong PS and exhibit an undesirable transgressive late-maturing phenotype. However, the genetic basis for this phenomenon is unclear. Therefore, effective methods are needed for selecting parents to create F1 hybrid varieties with the desired PS. In this study, we used bulked segregant analysis with F1 Ningyou 1179 (strong PS) and its F2 population, and through analyzing both parental haplotypes and PS data for 918 hybrid rice varieties, to identify the genetic basis of transgressive late maturation which is dependent on dominance complementation effects of Hd1, Ghd7, DTH8, and PRR37 from both parents rather than from a single parental genotype. We designed a molecular marker-assisted selection system to identify the genotypes of Hd1, Ghd7, DTH8, and PRR37 in parental lines to predict PS in F1 plants prior to crossing. Furthermore, we used CRISPR/Cas9 technique to knock out Hd1 in Ning A (sterile line) and Ning B (maintainer line) and obtained an hd1-NY material with weak PS while retaining the elite agronomic traits of NY. Our findings clarified the genetic basis of transgressive late maturation in hybrid rice and developed effective methods for parental selection and gene editing to facilitate the breeding of hybrid varieties with the desired PS for improving their adaptability.
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Affiliation(s)
- Wubei Zong
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangdong Laboratory for Lingnan Modern Agriculture, College of Life Sciences, South China Agricultural University, Guangzhou, 510642, China
| | - Yingang Song
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangdong Laboratory for Lingnan Modern Agriculture, College of Life Sciences, South China Agricultural University, Guangzhou, 510642, China
| | - Dongdong Xiao
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangdong Laboratory for Lingnan Modern Agriculture, College of Life Sciences, South China Agricultural University, Guangzhou, 510642, China
| | - Xiaotong Guo
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangdong Laboratory for Lingnan Modern Agriculture, College of Life Sciences, South China Agricultural University, Guangzhou, 510642, China
| | - Fuquan Li
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangdong Laboratory for Lingnan Modern Agriculture, College of Life Sciences, South China Agricultural University, Guangzhou, 510642, China
| | - Kangli Sun
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangdong Laboratory for Lingnan Modern Agriculture, College of Life Sciences, South China Agricultural University, Guangzhou, 510642, China
| | - Wenjing Tang
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangdong Laboratory for Lingnan Modern Agriculture, College of Life Sciences, South China Agricultural University, Guangzhou, 510642, China
| | - Wenhao Xie
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangdong Laboratory for Lingnan Modern Agriculture, College of Life Sciences, South China Agricultural University, Guangzhou, 510642, China
| | - Yanqiu Luo
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangdong Laboratory for Lingnan Modern Agriculture, College of Life Sciences, South China Agricultural University, Guangzhou, 510642, China
| | - Shan Liang
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangdong Laboratory for Lingnan Modern Agriculture, College of Life Sciences, South China Agricultural University, Guangzhou, 510642, China
| | - Jingyao Zhou
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangdong Laboratory for Lingnan Modern Agriculture, College of Life Sciences, South China Agricultural University, Guangzhou, 510642, China
| | - Xianrong Xie
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangdong Laboratory for Lingnan Modern Agriculture, College of Life Sciences, South China Agricultural University, Guangzhou, 510642, China
| | - Dilin Liu
- Key Laboratory of Genetics and Breeding of High Quality Rice in Southern China (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Guangdong Key Laboratory of New Technology in Rice, Breeding-Guangdong Rice Engineering Laboratory, Rice Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640, China
| | - Letian Chen
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangdong Laboratory for Lingnan Modern Agriculture, College of Life Sciences, South China Agricultural University, Guangzhou, 510642, China
| | - Haiyang Wang
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangdong Laboratory for Lingnan Modern Agriculture, College of Life Sciences, South China Agricultural University, Guangzhou, 510642, China
| | - Yao-Guang Liu
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangdong Laboratory for Lingnan Modern Agriculture, College of Life Sciences, South China Agricultural University, Guangzhou, 510642, China
| | - Jingxin Guo
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangdong Laboratory for Lingnan Modern Agriculture, College of Life Sciences, South China Agricultural University, Guangzhou, 510642, China
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Wu S, Tang W, Wang Z, Tang Z, Zheng P, Chen Z, Zhu JJ. High Dynamic Range Probing of Single-Molecule Mechanical Force Transitions at Cell-Matrix Adhesion Bonds by a Plasmonic Tension Nanosensor. JACS Au 2024; 4:1155-1165. [PMID: 38559721 PMCID: PMC10976601 DOI: 10.1021/jacsau.4c00002] [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] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Revised: 01/30/2024] [Accepted: 02/01/2024] [Indexed: 04/04/2024]
Abstract
Mechanical signals in animal tissues are complex and rapidly changed, and how the force transduction emerges from the single-cell adhesion bonds remains unclear. DNA-based molecular tension sensors (MTS), albeit successful in cellular force probing, were restricted by their detection range and temporal resolution. Here, we introduced a plasmonic tension nanosensor (PTNS) to make straight progress toward these shortcomings. Contrary to the fluorescence-based MTS that only has specific force response thresholds, PTNS enabled the continuous and reversible force measurement from 1.1 to 48 pN with millisecond temporal resolution. We used the PTNS to visualize the high dynamic range single-molecule force transitions at cell-matrix adhesions during adhesion formation and migration. Time-resolved force traces revealed that the lifetime and duration of stepwise force transitions of molecular clutches are strongly modulated by the traction force through filamentous actin. The force probing technique is sensitive, fast, and robust and constitutes a potential tool for single-molecule and single-cell biophysics.
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Affiliation(s)
| | | | - Ziyi Wang
- State Key Laboratory of Analytical
Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, P. R. China
| | - Zhuodong Tang
- State Key Laboratory of Analytical
Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, P. R. China
| | - Peng Zheng
- State Key Laboratory of Analytical
Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, P. R. China
| | - Zixuan Chen
- State Key Laboratory of Analytical
Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, P. R. China
| | - Jun-Jie Zhu
- State Key Laboratory of Analytical
Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, P. R. China
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Wu S, Tang W, Liu L, Wei K, Tang Y, Ma J, Li H, Ao Y. Obesity-induced downregulation of miR-192 exacerbates lipopolysaccharide-induced acute lung injury by promoting macrophage activation. Cell Mol Biol Lett 2024; 29:36. [PMID: 38486141 PMCID: PMC10938800 DOI: 10.1186/s11658-024-00558-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] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 02/29/2024] [Indexed: 03/17/2024] Open
Abstract
BACKGROUND Macrophage activation may play a crucial role in the increased susceptibility of obese individuals to acute lung injury (ALI). Dysregulation of miRNA, which is involved in various inflammatory diseases, is often observed in obesity. This study aimed to investigate the role of miR-192 in lipopolysaccharide (LPS)-induced ALI in obese mice and its mechanism of dysregulation in obesity. METHODS Human lung tissues were obtained from obese patients (BMI ≥ 30.0 kg/m2) and control patients (BMI 18.5-24.9 kg/m2). An obese mouse model was established by feeding a high-fat diet (HFD), followed by intratracheal instillation of LPS to induce ALI. Pulmonary macrophages of obese mice were depleted through intratracheal instillation of clodronate liposomes. The expression of miR-192 was examined in lung tissues, primary alveolar macrophages (AMs), and the mouse alveolar macrophage cell line (MH-S) using RT-qPCR. m6A quantification and RIP assays helped determine the cause of miR-192 dysregulation. miR-192 agomir and antagomir were used to investigate its function in mice and MH-S cells. Bioinformatics and dual-luciferase reporter gene assays were used to explore the downstream targets of miR-192. RESULTS In obese mice, depletion of macrophages significantly alleviated lung tissue inflammation and injury, regardless of LPS challenge. miR-192 expression in lung tissues and alveolar macrophages was diminished during obesity and further decreased with LPS stimulation. Obesity-induced overexpression of FTO decreased the m6A modification of pri-miR-192, inhibiting the generation of miR-192. In vitro, inhibition of miR-192 enhanced LPS-induced polarization of M1 macrophages and activation of the AKT/ NF-κB inflammatory pathway, while overexpression of miR-192 suppressed these reactions. BIG1 was confirmed as a target gene of miR-192, and its overexpression offset the protective effects of miR-192. In vivo, when miR-192 was overexpressed in obese mice, the activation of pulmonary macrophages and the extent of lung injury were significantly improved upon LPS challenge. CONCLUSIONS Our study indicates that obesity-induced downregulation of miR-192 expression exacerbates LPS-induced ALI by promoting macrophage activation. Targeting macrophages and miR-192 may provide new therapeutic avenues for obesity-associated ALI.
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Affiliation(s)
- Siqi Wu
- Department of Anesthesiology, The First Affiliated Hospital of Chongqing Medical University, No 1. YouYi Road, Yuzhong District, Chongqing, 400016, China
| | - Wenjing Tang
- Department of Anesthesiology, The First Affiliated Hospital of Chongqing Medical University, No 1. YouYi Road, Yuzhong District, Chongqing, 400016, China
| | - Ling Liu
- Department of Anesthesiology, The First Affiliated Hospital of Chongqing Medical University, No 1. YouYi Road, Yuzhong District, Chongqing, 400016, China.
| | - Ke Wei
- Department of Anesthesiology, The First Affiliated Hospital of Chongqing Medical University, No 1. YouYi Road, Yuzhong District, Chongqing, 400016, China.
| | - Yin Tang
- Department of Anesthesiology, The First Affiliated Hospital of Chongqing Medical University, No 1. YouYi Road, Yuzhong District, Chongqing, 400016, China
| | - Jingyue Ma
- Department of Anesthesiology, The First Affiliated Hospital of Chongqing Medical University, No 1. YouYi Road, Yuzhong District, Chongqing, 400016, China
| | - Hongbin Li
- Department of Anesthesiology, The First Affiliated Hospital of Chongqing Medical University, No 1. YouYi Road, Yuzhong District, Chongqing, 400016, China
| | - Yichan Ao
- Department of Anesthesiology, The First Affiliated Hospital of Chongqing Medical University, No 1. YouYi Road, Yuzhong District, Chongqing, 400016, China
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Liu L, Tang W, Wu S, Ma J, Wei K. Pulmonary succinate receptor 1 elevation in high-fat diet mice exacerbates lipopolysaccharides-induced acute lung injury via sensing succinate. Biochim Biophys Acta Mol Basis Dis 2024; 1870:167119. [PMID: 38479484 DOI: 10.1016/j.bbadis.2024.167119] [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: 11/16/2023] [Revised: 02/23/2024] [Accepted: 03/06/2024] [Indexed: 04/05/2024]
Abstract
BACKGROUND Individuals with obesity have higher level of circulating succinate, which acts as a signaling factor that initiates inflammation. It is obscure whether succinate and succinate receptor 1 (SUCNR1) are involved in the process of obesity aggravating acute lung injury (ALI). METHODS The lung tissue and blood samples from patients with obesity who underwent lung wedgectomy or segmental resection were collected. Six-week-old male C57BL/6J mice were fed a high-fat diet for 12 weeks to induce obesity and lipopolysaccharides (LPS) were injected intratracheally (100 μg, 1 mg/ml) for 24 h to establish an ALI model. The pulmonary SUCNR1 expression and succinate level were measured. Exogenous succinate was supplemented to assess whether succinate exacerbated the LPS-induced lung injury. We next examined the cellular localization of pulmonary SUCNR1. Furthermore, the role of the succinate-SUCNR1 pathway in LPS-induced inflammatory responses in MH-s macrophages and obese mice was investigated. RESULT The pulmonary SUCNR1 expression and serum succinate level were significantly increased in patients with obesity and in HFD mice. Exogenous succinate supplementation significantly increased the severity of ALI and inflammatory response. SUCNR1 was mainly expressed on lung macrophages. In LPS-stimulated MH-s cells, knockdown of SUCNR1 expression significantly inhibited pro-inflammatory cytokines' expression, the increase of hypoxia-inducible factor-1α (HIF-1α) expression, inhibitory κB-α (IκB-α) phosphorylation, p65 phosphorylation and p65 translocation to nucleus. In obese mice, SUCNR1 inhibition significantly alleviated LPS-induced lung injury and decreased the HIF-1α expression and IκB-α phosphorylation. CONCLUSION The high expression of pulmonary SUCNR1 and serum succinate accumulation at least partly participate in the process of obesity aggravating LPS-induced lung injury.
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Affiliation(s)
- Ling Liu
- Department of Anesthesiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Wenjing Tang
- Department of Anesthesiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Siqi Wu
- Department of Anesthesiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Jingyue Ma
- Department of Anesthesiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Ke Wei
- Department of Anesthesiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.
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Lu G, Xiao S, Meng F, Zhang L, Chang Y, Zhao J, Gao N, Su W, Guo X, Liu Y, Li C, Tang W, Zou L, Yu S, Liu R. AMPK activation attenuates central sensitization in a recurrent nitroglycerin-induced chronic migraine mouse model by promoting microglial M2-type polarization. J Headache Pain 2024; 25:29. [PMID: 38454376 PMCID: PMC10921743 DOI: 10.1186/s10194-024-01739-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] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Accepted: 02/27/2024] [Indexed: 03/09/2024] Open
Abstract
BACKGROUND Energy metabolism disorders and neurogenic inflammation play important roles in the central sensitization to chronic migraine (CM). AMP-activated protein kinase (AMPK) is an intracellular energy sensor, and its activation regulates inflammation and reduces neuropathic pain. However, studies on the involvement of AMPK in the regulation of CM are currently lacking. Therefore, this study aimed to explore the mechanism underlying the involvement of AMPK in the central sensitization to CM. METHODS Mice with recurrent nitroglycerin (NTG)-induced CM were used to detect the expression of AMPK protein in the trigeminal nucleus caudalis (TNC). Following intraperitoneal injection of the AMPK activator 5-aminoimidazole-4-carboxyamide ribonucleoside (AICAR) and inhibitor compound C, the mechanical pain threshold, activity level, and pain-like behaviors in the mice were measured. The expression of calcitonin gene-related peptide (CGRP) and cytokines, M1/M2 microglia, and NF-κB pathway activation were detected after the intervention. RESULTS Repeated NTG injections resulted in a gradual decrease in AMPK protein expression, and the negative regulation of AMPK by increased ubiquitin-like plant homeodomain and RING finger domain 1 (UHRF1) expression may counteract AMPK activation by increasing ADP/ATP. AICAR can reduce the hyperalgesia and pain-like behaviors of CM mice, improve the activity of mice, reduce the expression of CGRP, IL-1β, IL-6, and TNF-α in the TNC region, and increase the expression of IL-4 and IL-10. Moreover, AMPK in TNC was mainly located in microglia. AICAR could reduce the expression of inducible NO synthase (iNOS) in M1 microglia and increase the expression of Arginase 1 (Arg1) in M2 microglia by inhibiting the activation of NF-κB pathway. CONCLUSIONS AMPK was involved in the central sensitization of CM, and the activation of AMPK reduced neuroinflammation in NTG-induced CM mice. AMPK may provide new insights into interventions for energy metabolism disorders and neurogenic inflammation in migraine.
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Affiliation(s)
- Guangshuang Lu
- Medical School of Chinese PLA, Beijing, 100853, China
- Department of Neurology, International Headache Center, The First Medical Center of Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, China
- Department of Pediatrics, The Lu'an Hospital Affiliated to Anhui Medical University, The Lu'an People's Hospital, Lu'an, China
| | - Shaobo Xiao
- Medical School of Chinese PLA, Beijing, 100853, China
- Department of Neurology, International Headache Center, The First Medical Center of Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, China
| | - Fanchao Meng
- Medical School of Chinese PLA, Beijing, 100853, China
- Department of Neurology, International Headache Center, The First Medical Center of Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, China
| | - Leyi Zhang
- Medical School of Chinese PLA, Beijing, 100853, China
- Department of Neurology, International Headache Center, The First Medical Center of Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, China
| | - Yan Chang
- Medical School of Chinese PLA, Beijing, 100853, China
- Department of Neurology, International Headache Center, The First Medical Center of Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, China
| | - Jinjing Zhao
- Medical School of Chinese PLA, Beijing, 100853, China
- Department of Neurology, International Headache Center, The First Medical Center of Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, China
| | - Nan Gao
- Department of Neurology, International Headache Center, The First Medical Center of Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, China
- School of Medicine, Nankai University, Tianjin, 300071, China
| | - Wenjie Su
- Medical School of Chinese PLA, Beijing, 100853, China
- Department of Neurology, International Headache Center, The First Medical Center of Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, China
| | - Xinghao Guo
- Medical School of Chinese PLA, Beijing, 100853, China
- Department of Neurology, International Headache Center, The First Medical Center of Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, China
| | - Yingyuan Liu
- Medical School of Chinese PLA, Beijing, 100853, China
- Department of Neurology, International Headache Center, The First Medical Center of Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, China
| | - Chenhao Li
- Medical School of Chinese PLA, Beijing, 100853, China
- Department of Neurology, International Headache Center, The First Medical Center of Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, China
| | - Wenjing Tang
- Medical School of Chinese PLA, Beijing, 100853, China
- Department of Neurology, International Headache Center, The First Medical Center of Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, China
| | - Liping Zou
- Medical School of Chinese PLA, Beijing, 100853, China
- Department of Pediatrics, The First Medical Center of Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, China
| | - Shengyuan Yu
- Medical School of Chinese PLA, Beijing, 100853, China.
- Department of Neurology, International Headache Center, The First Medical Center of Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, China.
| | - Ruozhuo Liu
- Medical School of Chinese PLA, Beijing, 100853, China.
- Department of Neurology, International Headache Center, The First Medical Center of Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, China.
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Tang W, Zong SM, Du PY, Xiao HJ. [Auditory brainstem implant: current states and future prospects]. Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi 2024; 59:266-270. [PMID: 38561269 DOI: 10.3760/cma.j.cn115330-20230725-00017] [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] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Affiliation(s)
- W Tang
- Department of Otorhinolaryngology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - S M Zong
- Department of Otorhinolaryngology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - P Y Du
- Department of Otorhinolaryngology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - H J Xiao
- Department of Otorhinolaryngology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
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Li B, Cao Y, Yuan H, Yu Z, Miao S, Yang C, Gong Z, Xie W, Li C, Bai W, Tang W, Zhao D, Yu S. The crucial role of locus coeruleus noradrenergic neurons in the interaction between acute sleep disturbance and headache. J Headache Pain 2024; 25:31. [PMID: 38443795 PMCID: PMC10913606 DOI: 10.1186/s10194-024-01714-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 01/07/2024] [Indexed: 03/07/2024] Open
Abstract
BACKGROUND Both epidemiological and clinical studies have indicated that headache and sleep disturbances share a complex relationship. Although headache and sleep share common neurophysiological and anatomical foundations, the mechanism underlying their interaction remains poorly understood. The structures of the diencephalon and brainstem, particularly the locus coeruleus (LC), are the primary sites where the sleep and headache pathways intersect. To better understand the intricate nature of the relationship between headache and sleep, our study focused on investigating the role and function of noradrenergic neurons in the LC during acute headache and acute sleep disturbance. METHOD To explore the relationship between acute headache and acute sleep disturbance, we primarily employed nitroglycerin (NTG)-induced migraine-like headache and acute sleep deprivation (ASD) models. Initially, we conducted experiments to confirm that ASD enhances headache and that acute headache can lead to acute sleep disturbance. Subsequently, we examined the separate roles of the LC in sleep and headache. We observed the effects of drug-induced activation and inhibition and chemogenetic manipulation of LC noradrenergic neurons on ASD-induced headache facilitation and acute headache-related sleep disturbance. This approach enabled us to demonstrate the bidirectional function of LC noradrenergic neurons. RESULTS Our findings indicate that ASD facilitated the development of NTG-induced migraine-like headache, while acute headache affected sleep quality. Furthermore, activating the LC reduced the headache threshold and increased sleep latency, whereas inhibiting the LC had the opposite effect. Additional investigations demonstrated that activating LC noradrenergic neurons further intensified pain facilitation from ASD, while inhibiting these neurons reduced this pain facilitation. Moreover, activating LC noradrenergic neurons exacerbated the impact of acute headache on sleep quality, while inhibiting them alleviated this influence. CONCLUSION The LC serves as a significant anatomical and functional region in the interaction between acute sleep disturbance and acute headache. The involvement of LC noradrenergic neurons is pivotal in facilitating headache triggered by ASD and influencing the effects of headache on sleep quality.
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Affiliation(s)
- Bozhi Li
- Department of Neurology, the First Medical Center, Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, People's Republic of China
- Neurology Institute of Chinese PLA General Hospital, the First Medical Center, Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, People's Republic of China
| | - Ya Cao
- Department of Neurology, the First Medical Center, Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, People's Republic of China
- Neurology Institute of Chinese PLA General Hospital, the First Medical Center, Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, People's Republic of China
- Medical School of Chinese PLA, Beijing, 100853, People's Republic of China
| | - Huijuan Yuan
- Department of Neurology, the First Medical Center, Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, People's Republic of China
- Neurology Institute of Chinese PLA General Hospital, the First Medical Center, Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, People's Republic of China
- School of Medicine, Nankai University, Tianjin, China
| | - Zhe Yu
- Department of Neurology, the First Medical Center, Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, People's Republic of China
| | - Shuai Miao
- Department of Neurology, the First Medical Center, Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, People's Republic of China
- Neurology Institute of Chinese PLA General Hospital, the First Medical Center, Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, People's Republic of China
| | - Chunxiao Yang
- Department of Neurology, the First Medical Center, Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, People's Republic of China
- Neurology Institute of Chinese PLA General Hospital, the First Medical Center, Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, People's Republic of China
- School of Medicine, Nankai University, Tianjin, China
| | - Zihua Gong
- Department of Neurology, the First Medical Center, Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, People's Republic of China
- Neurology Institute of Chinese PLA General Hospital, the First Medical Center, Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, People's Republic of China
- Medical School of Chinese PLA, Beijing, 100853, People's Republic of China
| | - Wei Xie
- Department of Neurology, the First Medical Center, Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, People's Republic of China
| | - Chenhao Li
- Department of Neurology, the First Medical Center, Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, People's Republic of China
- Neurology Institute of Chinese PLA General Hospital, the First Medical Center, Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, People's Republic of China
- Medical School of Chinese PLA, Beijing, 100853, People's Republic of China
| | - Wenhao Bai
- Department of Neurology, the First Medical Center, Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, People's Republic of China
- Neurology Institute of Chinese PLA General Hospital, the First Medical Center, Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, People's Republic of China
| | - Wenjing Tang
- Department of Neurology, the First Medical Center, Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, People's Republic of China
- Neurology Institute of Chinese PLA General Hospital, the First Medical Center, Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, People's Republic of China
| | - Dengfa Zhao
- Department of Neurology, the First Medical Center, Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, People's Republic of China
- Neurology Institute of Chinese PLA General Hospital, the First Medical Center, Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, People's Republic of China
| | - Shengyuan Yu
- Department of Neurology, the First Medical Center, Chinese PLA General Hospital, Fuxing Road 28, Haidian District, Beijing, 100853, People's Republic of China.
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10
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Tang W, Wu S, Tang Y, Ma J, Ao Y, Liu L, Wei K. Microarray analysis identifies lncFirre as a potential regulator of obesity-related acute lung injury. Life Sci 2024; 340:122459. [PMID: 38307237 DOI: 10.1016/j.lfs.2024.122459] [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: 11/08/2023] [Revised: 01/21/2024] [Accepted: 01/22/2024] [Indexed: 02/04/2024]
Abstract
AIMS The inflammatory response in acute lung injury/acute respiratory distress syndrome (ALI/ARDS) is heightened in obesity. The aim of this study was to investigate whether lncRNAs are involved in the effects of obesity on acute lung injury and to find possible effector lncRNAs. MAIN METHODS Microarray analysis was used to assess the transcriptional profiles of lncRNAs and mRNAs in lung tissues from normal (CON), high-fat diet induced obese (DIO), and obese ALI mice (DIO-ALI). GO and KEGG analyses were employed to explore the biological functions of differentially expressed genes. A lncRNA-mRNA co-expression network was constructed to identify specific lncRNA. Lung tissues and peripheral blood samples from patients with obesity and healthy lean donors were utilized to confirm the expression characteristics of lncFirre through qRT-PCR. lncFirre was knocked down in MH-S macrophages to explore its function. ELISA and Griess reagent kit were used to detect PGE2 and NO. Flow cytometry was used to detect macrophages polarization. KEY FINDINGS There were 475 lncRNAs and 404 mRNAs differentially expressed between DIO and CON, while 1348 lncRNAs and 1349 mRNAs between DIO-ALI and DIO. Obesity increased lncFirre expression in both mice and patients, and PA elevated lncFirre in MH-S. PA exacerbated the inflammation and proinflammatory polarization of MH-S induced by LPS. LncFirre knockdown inhibited the secretion of PGE2 and NO, M1 differentiation while promoted the M2 differentiation in PA and LPS co-challenged MH-S. SIGNIFICANCE Interfering with lncFirre effectively inhibit inflammation in MH-S, lncFirre can serve as a promising target for treating obesity-related ALI.
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Affiliation(s)
- Wenjing Tang
- Department of Anesthesiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Siqi Wu
- Department of Anesthesiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Yin Tang
- Department of Anesthesiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Jingyue Ma
- Department of Anesthesiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Yichan Ao
- Department of Anesthesiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Ling Liu
- Department of Anesthesiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.
| | - Ke Wei
- Department of Anesthesiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.
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11
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Tang W, Li L, Li XB, Qiu XT, Ger DL. [The accuracy and feasibility study of freehand pedicle screw insertion for subaxial cervical spine assisted with safe core-referred technique]. Zhonghua Wai Ke Za Zhi 2024; 62:202-209. [PMID: 38291665 DOI: 10.3760/cma.j.cn112139-20230820-00052] [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: 02/01/2024]
Abstract
Objectives: To construct the "safe core" of the pedicle screw trajectory using CT imaging data of the subaxial cervical spine in adults, and to assess the accuracy and feasibility of the pedicle screw insertion assisted with the "safe core-referred technique" for subaxial cervical spine with a cadaver specimen study. Methods: This is an experimental study. From January 2015 to March 2020,60 adults' CT images data of the cervical spine were collected from the database of the First Affiliated Hospital of Gannan Medical University,and were imported into Mimics 20.0 software. Virtual cervical pedicle trajectory and safe core were constructed according to the self-designed "virtual construction method of pedicle in the subaxial cervical spine". The success rate of the construction and the spatial position data of the virtual safe core of was recorded,including the distance between the safe core and the tangent line of the upper and lower outer edge of Luschka's joint on coronal plane,and the distance between the safe core and the posterior edge of the vertebral body on sagittal plane.The 3.5 mm column was used to simulate the pedicle screw placement,using the safe core as the only hub in pedicle screw trajectory.The length of the anterior pedicle screw trajectory,the interval of the abductive angle of the pedicle screw in axial plane, and the projection area of the entry area on periapical radiograph was calculated.In addition,8 adult cervical cadaver specimens were collected for the pedicle screw insertion experiment.The left side group used the "safe core-referred technique" for pedicle screw insertion,while the right side group used the Abumi method for pedicle screw insertion.The accuracy of pedicle screw placement was verified by CT scan.The difference between the accuracy of subjective judgment based on X-ray monitoring of operator and the actual accuracy of pedicle screw insertion verified by CT scan was compared between the two groups.The chi-square test was used to compare the intergroup data. Results: The total success rate of the virtual construction method for the safe core of the subaxial cervical spine was 97.0% (291/300); The distance between the safe core and the tangent line of the upper and lower outer edge of Luschka's joint on coronal plane was (M(IQR)) 0.91 (0.98) mm (range: 0 to 1.85 mm);The distance between the safe core and the posterior wall on the sagittal plane of the vertebral body was (2.01±0.86) mm (range: 0.67 to 3.53 mm). The distance (anterior pedicle screw trajectory) from the posterior cortex to the central point of the safe core was (11.58±1.00)mm (range: 8.27 to 14.93 mm).The projection area of the entry point on the coronal plane was (36.18±11.67) mm2 (range: 13.38 to 83.11 mm2). Pedicle screw insertion experiment in cervical cadaver specimen showed the rate of intraoperative correction of the pedicle screw trajectory was 7.5% (3/40) in the experimental group and 12.5% (5/40) in the control group (χ2=0.139,P=0.709). The operator 's correct rate of subjective judgment on CT in the stage of pedicle screw trajectory preparation was 100% (40/40) in the experimental group and 82.5% (33/40) in the control group, the difference was statistically significant (χ2=5.638,P=0.018). The actual correct rate of CT verification in the stage of pedicle screw insertion was 100% (40/40) in the experimental group and 90.0% (36/40) in the control group, the difference was statistically significant (χ2=2.368,P=0.124); The operator 's correct rate of subjective judgment in the stage of pedicle screw insertion completion was 100% (83/83) in the experimental group and 92.9% (79/85) in the control group (χ2=4.199,P=0.040). Conclusions: The virtual safe-core of subaxial cervical spine can be use as a reliable anatomical fluoroscopy landmark for freehand pedicle screw insertion."Safe core-referred technique" can improve the accuracy rate of the operator's subjective judgment on the intraoperative fluoroscopy monitoring,and hence improve the accuracy of freehand pedicle screw insertion technology for subaxial cervical spine. And it still needs to be further verified in clinical practice.
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Affiliation(s)
- W Tang
- Department of Orthopaedics,Trauma Center, the First Affiliated Hospital of Gannan Medical University,Ganzhou 341000,China
| | - L Li
- Department of Spine Surgery, 903 Hospital,Jiangyou 621700,China
| | - X B Li
- Center for Information Technology and Network Management,Gannan Medical University,Ganzhou 341000,China
| | - X T Qiu
- Department of Medical Imaging,the First Affiliated Hospital of Gannan Medical University,Ganzhou 341000,China
| | - D L Ger
- Gannan Medical University, Ganzhou 341000, China
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12
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Yau YK, Su Q, Xu Z, Tang W, Ching JYL, Cheung CP, Fung M, Ip M, Chan PKS, Chan FKL, Ng SC. Faecal microbiota transplantation for patients with irritable bowel syndrome: abridged secondary publication. Hong Kong Med J 2024; 30 Suppl 1:34-38. [PMID: 38413211] [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] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/29/2024] Open
Affiliation(s)
- Y K Yau
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Microbiota I-Center (MagIC), Hong Kong SAR, China
- Li Ka Shing Institute of Health Sciences, State Key Laboratory of Digestive Disease, Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Q Su
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Microbiota I-Center (MagIC), Hong Kong SAR, China
- Li Ka Shing Institute of Health Sciences, State Key Laboratory of Digestive Disease, Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Z Xu
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Microbiota I-Center (MagIC), Hong Kong SAR, China
- Li Ka Shing Institute of Health Sciences, State Key Laboratory of Digestive Disease, Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - W Tang
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Microbiota I-Center (MagIC), Hong Kong SAR, China
- Li Ka Shing Institute of Health Sciences, State Key Laboratory of Digestive Disease, Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - J Y L Ching
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Microbiota I-Center (MagIC), Hong Kong SAR, China
| | - C P Cheung
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Microbiota I-Center (MagIC), Hong Kong SAR, China
- Li Ka Shing Institute of Health Sciences, State Key Laboratory of Digestive Disease, Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - M Fung
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Microbiota I-Center (MagIC), Hong Kong SAR, China
- Li Ka Shing Institute of Health Sciences, State Key Laboratory of Digestive Disease, Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - M Ip
- Department of Microbiology, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - P K S Chan
- Department of Microbiology, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - F K L Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Microbiota I-Center (MagIC), Hong Kong SAR, China
- Li Ka Shing Institute of Health Sciences, State Key Laboratory of Digestive Disease, Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - S C Ng
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Microbiota I-Center (MagIC), Hong Kong SAR, China
- Li Ka Shing Institute of Health Sciences, State Key Laboratory of Digestive Disease, Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong SAR, China
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13
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Abratenko P, Alterkait O, Andrade Aldana D, Arellano L, Asaadi J, Ashkenazi A, Balasubramanian S, Baller B, Barr G, Barrow D, Barrow J, Basque V, Benevides Rodrigues O, Berkman S, Bhanderi A, Bhat A, Bhattacharya M, Bishai M, Blake A, Bogart B, Bolton T, Book JY, Brunetti MB, Camilleri L, Cao Y, Caratelli D, Cavanna F, Cerati G, Chappell A, Chen Y, Conrad JM, Convery M, Cooper-Troendle L, Crespo-Anadón JI, Cross R, Del Tutto M, Dennis SR, Detje P, Devitt A, Diurba R, Djurcic Z, Dorrill R, Duffy K, Dytman S, Eberly B, Englezos P, Ereditato A, Evans JJ, Fine R, Finnerud OG, Foreman W, Fleming BT, Franco D, Furmanski AP, Gao F, Garcia-Gamez D, Gardiner S, Ge G, Gollapinni S, Gramellini E, Green P, Greenlee H, Gu L, Gu W, Guenette R, Guzowski P, Hagaman L, Hen O, Hilgenberg C, Horton-Smith GA, Imani Z, Irwin B, Ismail M, James C, Ji X, Jo JH, Johnson RA, Jwa YJ, Kalra D, Kamp N, Karagiorgi G, Ketchum W, Kirby M, Kobilarcik T, Kreslo I, Leibovitch MB, Lepetic I, Li JY, Li K, Li Y, Lin K, Littlejohn BR, Liu H, Louis WC, Luo X, Mariani C, Marsden D, Marshall J, Martinez N, Martinez Caicedo DA, Martynenko S, Mastbaum A, Mawby I, McConkey N, Meddage V, Micallef J, Miller K, Mogan A, Mohayai T, Mooney M, Moor AF, Moore CD, Mora Lepin L, Moudgalya MM, Mulleriababu S, Naples D, Navrer-Agasson A, Nayak N, Nebot-Guinot M, Nowak J, Oza N, Palamara O, Pallat N, Paolone V, Papadopoulou A, Papavassiliou V, Parkinson HB, Pate SF, Patel N, Pavlovic Z, Piasetzky E, Pophale I, Qian X, Raaf JL, Radeka V, Rafique A, Reggiani-Guzzo M, Ren L, Rochester L, Rodriguez Rondon J, Rosenberg M, Ross-Lonergan M, Rudolf von Rohr C, Safa I, Scanavini G, Schmitz DW, Schukraft A, Seligman W, Shaevitz MH, Sharankova R, Shi J, Snider EL, Soderberg M, Söldner-Rembold S, Spitz J, Stancari M, St John J, Strauss T, Szelc AM, Tang W, Taniuchi N, Terao K, Thorpe C, Torbunov D, Totani D, Toups M, Tsai YT, Tyler J, Uchida MA, Usher T, Viren B, Weber M, Wei H, White AJ, Wolbers S, Wongjirad T, Wospakrik M, Wresilo K, Wu W, Yandel E, Yang T, Yates LE, Yu HW, Zeller GP, Zennamo J, Zhang C. Search for Heavy Neutral Leptons in Electron-Positron and Neutral-Pion Final States with the MicroBooNE Detector. Phys Rev Lett 2024; 132:041801. [PMID: 38335355 DOI: 10.1103/physrevlett.132.041801] [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: 10/12/2023] [Accepted: 11/30/2023] [Indexed: 02/12/2024]
Abstract
We present the first search for heavy neutral leptons (HNLs) decaying into νe^{+}e^{-} or νπ^{0} final states in a liquid-argon time projection chamber using data collected with the MicroBooNE detector. The data were recorded synchronously with the NuMI neutrino beam from Fermilab's main injector corresponding to a total exposure of 7.01×10^{20} protons on target. We set upper limits at the 90% confidence level on the mixing parameter |U_{μ4}|^{2} in the mass ranges 10≤m_{HNL}≤150 MeV for the νe^{+}e^{-} channel and 150≤m_{HNL}≤245 MeV for the νπ^{0} channel, assuming |U_{e4}|^{2}=|U_{τ4}|^{2}=0. These limits represent the most stringent constraints in the mass range 35
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Affiliation(s)
- P Abratenko
- Tufts University, Medford, Massachusetts 02155, USA
| | - O Alterkait
- Tufts University, Medford, Massachusetts 02155, USA
| | - D Andrade Aldana
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - L Arellano
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Asaadi
- University of Texas, Arlington, Texas 76019, USA
| | - A Ashkenazi
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - S Balasubramanian
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - B Baller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Barr
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - D Barrow
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - J Barrow
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - V Basque
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | | | - S Berkman
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
- Michigan State University, East Lansing, Michigan 48824, USA
| | - A Bhanderi
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - A Bhat
- University of Chicago, Chicago, Illinois 60637, USA
| | - M Bhattacharya
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Bishai
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Blake
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - B Bogart
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - T Bolton
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - J Y Book
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - M B Brunetti
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - L Camilleri
- Columbia University, New York, New York 10027, USA
| | - Y Cao
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - D Caratelli
- University of California, Santa Barbara, California 93106, USA
| | - F Cavanna
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Cerati
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - A Chappell
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - Y Chen
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J M Conrad
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - M Convery
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | | | - J I Crespo-Anadón
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid E-28040, Spain
| | - R Cross
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - M Del Tutto
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S R Dennis
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - P Detje
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - A Devitt
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - R Diurba
- Universität Bern, Bern CH-3012, Switzerland
| | - Z Djurcic
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - R Dorrill
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - K Duffy
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - S Dytman
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - B Eberly
- University of Southern Maine, Portland, Maine 04104, USA
| | - P Englezos
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - A Ereditato
- University of Chicago, Chicago, Illinois 60637, USA
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J J Evans
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - R Fine
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O G Finnerud
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - W Foreman
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - B T Fleming
- University of Chicago, Chicago, Illinois 60637, USA
| | - D Franco
- University of Chicago, Chicago, Illinois 60637, USA
| | - A P Furmanski
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - F Gao
- University of California, Santa Barbara, California 93106, USA
| | | | - S Gardiner
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Ge
- Columbia University, New York, New York 10027, USA
| | - S Gollapinni
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - E Gramellini
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - P Green
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - H Greenlee
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L Gu
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - W Gu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - R Guenette
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - P Guzowski
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Hagaman
- University of Chicago, Chicago, Illinois 60637, USA
| | - O Hen
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - C Hilgenberg
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - Z Imani
- Tufts University, Medford, Massachusetts 02155, USA
| | - B Irwin
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - M Ismail
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - C James
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - X Ji
- Nankai University, Nankai District, Tianjin 300071, China
| | - J H Jo
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - R A Johnson
- University of Cincinnati, Cincinnati, Ohio 45221, USA
| | - Y-J Jwa
- Columbia University, New York, New York 10027, USA
| | - D Kalra
- Columbia University, New York, New York 10027, USA
| | - N Kamp
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - G Karagiorgi
- Columbia University, New York, New York 10027, USA
| | - W Ketchum
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Kirby
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Kobilarcik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - I Kreslo
- Universität Bern, Bern CH-3012, Switzerland
| | - M B Leibovitch
- University of California, Santa Barbara, California 93106, USA
| | - I Lepetic
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - J-Y Li
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - K Li
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Y Li
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - K Lin
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - B R Littlejohn
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - H Liu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - W C Louis
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - X Luo
- University of California, Santa Barbara, California 93106, USA
| | - C Mariani
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Viriginia 24061, USA
| | - D Marsden
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Marshall
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - N Martinez
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - D A Martinez Caicedo
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - S Martynenko
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Mastbaum
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - I Mawby
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - N McConkey
- University College London, London WC1E 6BT, United Kingdom
| | - V Meddage
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - J Micallef
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
- Tufts University, Medford, Massachusetts 02155, USA
| | - K Miller
- University of Chicago, Chicago, Illinois 60637, USA
| | - A Mogan
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - T Mohayai
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
- Indiana University, Bloomington, Indiana 47405, USA
| | - M Mooney
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - A F Moor
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - C D Moore
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L Mora Lepin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - M M Moudgalya
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | | | - D Naples
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Navrer-Agasson
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - N Nayak
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Nebot-Guinot
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - J Nowak
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - N Oza
- Columbia University, New York, New York 10027, USA
| | - O Palamara
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - N Pallat
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - V Paolone
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Papadopoulou
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - V Papavassiliou
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - H B Parkinson
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - S F Pate
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - N Patel
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - Z Pavlovic
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Piasetzky
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - I Pophale
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - X Qian
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - J L Raaf
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - V Radeka
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Rafique
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - M Reggiani-Guzzo
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Ren
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - L Rochester
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Rodriguez Rondon
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - M Rosenberg
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Ross-Lonergan
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | | | - I Safa
- Columbia University, New York, New York 10027, USA
| | - G Scanavini
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - D W Schmitz
- University of Chicago, Chicago, Illinois 60637, USA
| | - A Schukraft
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Seligman
- Columbia University, New York, New York 10027, USA
| | - M H Shaevitz
- Columbia University, New York, New York 10027, USA
| | - R Sharankova
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Shi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - E L Snider
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Soderberg
- Syracuse University, Syracuse, New York 13244, USA
| | | | - J Spitz
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - M Stancari
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J St John
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Strauss
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - A M Szelc
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - W Tang
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - N Taniuchi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - K Terao
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C Thorpe
- Lancaster University, Lancaster LA1 4YW, United Kingdom
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - D Torbunov
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - D Totani
- University of California, Santa Barbara, California 93106, USA
| | - M Toups
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y-T Tsai
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Tyler
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - M A Uchida
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - T Usher
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - B Viren
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Weber
- Universität Bern, Bern CH-3012, Switzerland
| | - H Wei
- Louisiana State University, Baton Rouge, Louisiana 70803, USA
| | - A J White
- University of Chicago, Chicago, Illinois 60637, USA
| | - S Wolbers
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Wongjirad
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Wospakrik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - K Wresilo
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - W Wu
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - E Yandel
- University of California, Santa Barbara, California 93106, USA
| | - T Yang
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L E Yates
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - H W Yu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - G P Zeller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Zennamo
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - C Zhang
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
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Xie B, Tang W, Wen S, Chen F, Yang C, Wang M, Yang Y, Liang W. GDF-15 Inhibits ADP-Induced Human Platelet Aggregation through the GFRAL/RET Signaling Complex. Biomolecules 2023; 14:38. [PMID: 38254638 PMCID: PMC10813690 DOI: 10.3390/biom14010038] [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: 11/01/2023] [Revised: 12/13/2023] [Accepted: 12/18/2023] [Indexed: 01/24/2024] Open
Abstract
Growth differentiation factor-15 (GDF-15) is proposed to be strongly associated with several cardiovascular diseases, such as heart failure and atherosclerosis. Moreover, some recent studies have reported an association between GDF-15 and platelet activation. In this study, we isolated peripheral blood platelets from healthy volunteers and evaluated the effect of GDF-15 on adenosine diphosphate (ADP)-induced platelet activation using the platelet aggregation assay. Subsequently, we detected the expression of GDF-15-related receptors on platelets, including the epidermal growth factor receptor (EGFR), human epidermal growth factor receptor 2 (HER2), human epidermal growth factor receptor 3 (HER3), transforming growth factor-beta receptor I (TGF-βRI), transforming growth factor-beta receptor II (TGF-βRII), glial-cell-line-derived neurotrophic factor family receptor α-like (GFRAL), and those rearranged during transfection (RET). Then, we screened for GDF-15 receptors using the GDF-15-related receptor microarray comprising these recombinant proteins. We also performed the immunoprecipitation assay to investigate the interaction between GDF-15 and the receptors on platelets. For the further exploration of signaling pathways, we investigated the effects of GDF-15 on the extracellular signal-regulated kinase (ERK), protein kinase B (AKT), and Janus kinase 2 (JAK2) pathways. We also investigated the effects of GDF-15 on the ERK and AKT pathways and platelet aggregation in the presence or absence of RET agonists or inhibition. Our study revealed that GDF-15 can dose-independently inhibit ADP-induced human platelet aggregation and that the binding partner of GDF-15 on platelets is GFRAL. We also found that GDF-15 inhibits ADP-induced AKT and ERK activation in platelets. Meanwhile, our results revealed that the inhibitory effects of GDF-15 can be mediated by the GFRAL/RET complex. These findings reveal the novel inhibitory mechanism of ADP-induced platelet activation by GDF-15.
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Affiliation(s)
- Baikang Xie
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; (B.X.); (W.T.); (F.C.); (M.W.)
- Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- Hubei Provincial Engineering Research Center of Immunological Diagnosis and Therapy for Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Wenjing Tang
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; (B.X.); (W.T.); (F.C.); (M.W.)
- Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- Hubei Provincial Engineering Research Center of Immunological Diagnosis and Therapy for Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Shuang Wen
- Department of Emergency Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China;
| | - Fen Chen
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; (B.X.); (W.T.); (F.C.); (M.W.)
- Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- Hubei Provincial Engineering Research Center of Immunological Diagnosis and Therapy for Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Chao Yang
- Department of Vascular Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China;
| | - Min Wang
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; (B.X.); (W.T.); (F.C.); (M.W.)
- Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- Hubei Provincial Engineering Research Center of Immunological Diagnosis and Therapy for Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Yong Yang
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; (B.X.); (W.T.); (F.C.); (M.W.)
- Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- Hubei Provincial Engineering Research Center of Immunological Diagnosis and Therapy for Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Wei Liang
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; (B.X.); (W.T.); (F.C.); (M.W.)
- Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- Hubei Provincial Engineering Research Center of Immunological Diagnosis and Therapy for Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
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Zhang H, Du Y, Tang W, Chen M, Yu W, Ke Z, Dong S, Cheng Q. Eldecalcitol prevents muscle loss and osteoporosis in disuse muscle atrophy via NF-κB signaling in mice. Skelet Muscle 2023; 13:22. [PMID: 38115079 PMCID: PMC10729577 DOI: 10.1186/s13395-023-00332-0] [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] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Accepted: 11/29/2023] [Indexed: 12/21/2023] Open
Abstract
We investigated the effect of eldecalcitol on disuse muscle atrophy. C57BL/6J male mice aged 6 weeks were randomly assigned to control, tail suspension (TS), and TS-eldecalcitol-treated groups and were injected intraperitoneally twice a week with either vehicle (control and TS) or eldecalcitol at 3.5 or 5 ng for 3 weeks. Grip strength and muscle weights of the gastrocnemius (GAS), tibialis anterior (TA), and soleus (SOL) were determined. Oxidative stress was evaluated by malondialdehyde, superoxide dismutase, glutathione peroxidase, and catalase. Bone microarchitecture was analyzed using microcomputed tomography. The effect of eldecalcitol on C2C12 myoblasts was analyzed by measuring myofibrillar protein MHC and the atrophy markers Atrogin-1 and MuRF-1 using immunofluorescence. The influence of eldecalcitol on NF-κB signaling pathway and vitamin D receptor (VDR) was assessed through immunofluorescence, (co)-immunoprecipitation, and VDR knockdown studies. Eldecalcitol increased grip strength (P < 0.01) and restored muscle loss in GAS, TA, and SOL (P < 0.05 to P < 0.001) induced by TS. An improvement was noted in bone mineral density and bone architecture in the eldecalcitol group. The impaired oxidative defense system was restored by eldecalcitol (P < 0.05 to P < 0.01 vs. TS). Eldecalcitol (10 nM) significantly inhibited the expression of MuRF-1 (P < 0.001) and Atrogin-1 (P < 0.01), increased the diameter of myotubes (P < 0.05), inhibited the expression of P65 and P52 components of NF-κB and P65 nuclear location, thereby inhibiting NF-κB signaling. Eldecalcitol promoted VDR binding to P65 and P52. VDR signaling is required for eldecalcitol-mediated anti-atrophy effects. In conclusion, eldecalcitol exerted its beneficial effects on disuse-induced muscle atrophy via NF-κB inhibition.
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Affiliation(s)
- Haichao Zhang
- Department of Osteoporosis and Bone Disease, Huadong Hospital Affiliated to Fudan University, Research Section of Geriatric Metabolic Bone Disease, Shanghai Geriatric Institute, Shanghai, 200040, People's Republic of China
| | - Yanping Du
- Department of Osteoporosis and Bone Disease, Huadong Hospital Affiliated to Fudan University, Research Section of Geriatric Metabolic Bone Disease, Shanghai Geriatric Institute, Shanghai, 200040, People's Republic of China
| | - Wenjing Tang
- Department of Osteoporosis and Bone Disease, Huadong Hospital Affiliated to Fudan University, Research Section of Geriatric Metabolic Bone Disease, Shanghai Geriatric Institute, Shanghai, 200040, People's Republic of China
| | - Minmin Chen
- Department of Osteoporosis and Bone Disease, Huadong Hospital Affiliated to Fudan University, Research Section of Geriatric Metabolic Bone Disease, Shanghai Geriatric Institute, Shanghai, 200040, People's Republic of China
| | - Weijia Yu
- Department of Osteoporosis and Bone Disease, Huadong Hospital Affiliated to Fudan University, Research Section of Geriatric Metabolic Bone Disease, Shanghai Geriatric Institute, Shanghai, 200040, People's Republic of China
| | - Zheng Ke
- Medical Division, Chugai Pharma China Co., Ltd., Shanghai, 200021, People's Republic of China
| | - Shuangshuang Dong
- Medical Division, Chugai Pharma China Co., Ltd., Shanghai, 200021, People's Republic of China
| | - Qun Cheng
- Department of Osteoporosis and Bone Disease, Huadong Hospital Affiliated to Fudan University, Research Section of Geriatric Metabolic Bone Disease, Shanghai Geriatric Institute, Shanghai, 200040, People's Republic of China.
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Tang W, Zhou LJ, Zhang WQ, Jia YJ, Ge MW, Hu FH, Chen HL. Association of radiotherapy for prostate cancer and second primary colorectal cancer: a US population-based analysis. Tech Coloproctol 2023; 28:14. [PMID: 38095784 DOI: 10.1007/s10151-023-02883-2] [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: 08/18/2023] [Accepted: 11/17/2023] [Indexed: 12/18/2023]
Abstract
BACKGROUND Radiotherapy (RT) is a common treatment for prostate cancer, yet the risk of second primary colorectal cancer (SPCRC) in patients with prostate cancer undergoing RT has not been adequately studied. METHODS This study employed a population-based cohort design using the US Surveillance, Epidemiology, and End Results (SEER) database to identify individuals diagnosed between January 1975 and December 2015. The cumulative incidence of SPCRC was estimated using Fine-Gray competing risk regression. Poisson regression analysis was used to estimate the risk associated with RT. Survival outcomes of patients with SPCRC were evaluated using the Kaplan-Meier method. RESULTS A total of 287,607 patients diagnosed with prostate cancer were identified. The cumulative incidences were higher in patients who did not receive RT (2.00%) compared to those who underwent RT (2.47%) after 25 years. After adjustment for multiple variables, RT was associated with an increased risk of developing combined SPCRC (adjusted HR 1.590). Additionally, the overall survival was significantly lower in patients who developed colorectal cancer after receiving RT as compared to those who did not receive RT. CONCLUSION These findings underscore the need for diligent long-term monitoring and effective management strategies to detect SPCRC in patients treated with RT for prostate cancer.
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Affiliation(s)
- W Tang
- Medical School, Nantong University, Nantong, China
| | - L-J Zhou
- Nursing Department, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou School of Clinical Medicine, Nanjing Medical University, Taizhou, China
| | - W-Q Zhang
- Medical School, Nantong University, Nantong, China
| | - Y-J Jia
- Medical School, Nantong University, Nantong, China
| | - M-W Ge
- Medical School, Nantong University, Nantong, China
| | - F-H Hu
- Medical School, Nantong University, Nantong, China
| | - H-L Chen
- School of Public Health, Nantong University, 9#Seyuan Road, Nantong, 226000, Jiangsu, China.
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Chen S, Sui Y, Ding S, Chen C, Liu C, Zhong Z, Liang Y, Kong Q, Tang W, Guo Y. A simple and convenient model combining multiparametric MRI and clinical features to predict tumour-infiltrating lymphocytes in breast cancer. Clin Radiol 2023; 78:e1065-e1074. [PMID: 37813758 DOI: 10.1016/j.crad.2023.08.029] [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] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Revised: 08/30/2023] [Accepted: 08/31/2023] [Indexed: 10/11/2023]
Abstract
AIM To develop a simple and convenient method based on multiparametric magnetic resonance imaging (MRI) and clinical features to non-invasively predict tumour-infiltrating lymphocytes (TILs) in breast cancer (BC) and to explore the relationship between TIL levels and disease-free survival (DFS). MATERIALS AND METHODS A total of 172 BC patients were enrolled between November 2017 and June 2021 in this retrospective study. The patients were divided into high (≥10%) and low (<10%) TIL groups. Clinicopathological data were collected. MRI features were reviewed by two radiologists. Predictors associated with TILs were determined by using multivariable logistic regression analyses. Kaplan-Meier survival curves based on TIL levels were used to estimate DFS. RESULTS A total of 102 patients with low TILs and 70 patients with high TILs were included in the study. Tumour size (odds ratio [OR], 1.040; 95% confidence interval [CI]: 1.006, 1.075; p=0.020), apparent diffusion coefficient (ADC; OR, 1.003; 95% CI: 1.001, 1.005; p=0.015), clinical axillary lymph node status (CALNS; OR, 3.222; 95% CI: 1.372,7.568; p=0.007), and enhancement pattern (OR, 0.284; 95% CI: 0.143, 0.563; p<0.001) were independently associated with TIL levels. These features were used in the ALSE model (where A is ADC, L is CALNS, S is size, and E is enhancement pattern). High TILs were associated with better DFS (p=0.016). CONCLUSION The ALSE model derived from multiparametric MRI and clinical features could non-invasively predict TIL levels in BC, and high TILs were associated with longer DFS, especially in human epidermal growth factor receptor 2 (HER2)-positive BC and triple-negative BC (TNBC).
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Affiliation(s)
- S Chen
- Department of Radiology, Guangzhou First People's Hospital, South China University of Technology, Guangzhou, 510180, China
| | - Y Sui
- Department of Radiology, Guangzhou First People's Hospital, South China University of Technology, Guangzhou, 510180, China; Department of Radiology, Guangzhou Women and Children's Medical Center, Guangzhou, 510005, China
| | - S Ding
- Department of Radiology, Liuzhou People's Hospital, Guangxi Medical University, Liuzhou, 545006, China
| | - C Chen
- Department of Pathology, Guangzhou First People's Hospital, South China University of Technology, Guangzhou, 510180, China
| | - C Liu
- Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China
| | - Z Zhong
- Department of Radiology, Guangzhou First People's Hospital, South China University of Technology, Guangzhou, 510180, China
| | - Y Liang
- Department of Pathology, Guangzhou First People's Hospital, South China University of Technology, Guangzhou, 510180, China
| | - Q Kong
- Department of Radiology, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510630, China.
| | - W Tang
- Department of Radiology, Guangzhou First People's Hospital, South China University of Technology, Guangzhou, 510180, China.
| | - Y Guo
- Department of Radiology, Guangzhou First People's Hospital, South China University of Technology, Guangzhou, 510180, China.
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18
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Peng Q, Wu N, Huang Y, Zhao SJ, Tang W, Liang M, Ran YL, Xiao T, Yang L, Liang X. [Diagnostic values of conventional tumor markers and their combination with chest CT for patients with stageⅠA lung cancer]. Zhonghua Zhong Liu Za Zhi 2023; 45:934-941. [PMID: 37968078 DOI: 10.3760/cma.j.cn112152-20220208-00082] [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] [Subscribe] [Scholar Register] [Indexed: 11/17/2023]
Abstract
Objective: To investigate the diagnostic efficiency of conventional serum tumor markers and their combination with chest CT for stage ⅠA lung cancer. Methods: A total of 1 155 patients with stage ⅠA lung cancer and 200 patients with benign lung lesions (confirmed by surgery) treated at the Cancer Hospital, Chinese Academy of Medical Sciences from January 2016 to October 2020 were retrospectively enrolled in this study. Six conventional serum tumor markers [carcinoembryonic antigen (CEA), carbohydrate antigen 125 (CA125), squamous cell carcinoma associated antigen (SCCA), cytokeratin 19 fragment (CYFRA21-1), neuron-specific enolase (NSE), and gastrin-releasing peptide precursor (ProGRP)] and chest thin-slice CT were performed on all patients one month before surgery. Pathology was taken as the gold standard to analyze the difference of positivity rates of tumor markers between the lung cancer group and the benign group, the moderate/poor differentiation group and the well differentiation group, the adenocarcinoma group and the squamous cell carcinoma group, the lepidic and non-lepidic predominant adenocarcinoma groups, the solid nodule group and the subsolid nodule group based on thin-slice CT, and subgroups of ⅠA1 to ⅠA3 lung cancers. The diagnostic performance of tumor markers and tumor markers combined with chest CT was analyzed using the receiver operating characteristic curve. Results: The positivity rates of six serum tumor markers in the lung cancer group and the benign group were 2.32%-20.08% and 0-13.64%, respectively; only the SCCA positivity rate in the lung cancer group was higher than that in the benign group (10.81% and 0, P=0.022). There were no significant differences in the positivity rates of other serum tumor markers between the two groups (all P>0.05). The combined detection of six tumor markers showed that the positivity rate of the lung cancer group was higher than that of the benign group (40.93% and 18.18%, P=0.004), and the positivity rate of the adenocarcinoma group was lower than that of the squamous cell carcinoma group (35.66% and 47.41%, P=0.045). The positivity rates in the poorly differentiated group and moderately differentiated group were higher than that in the well differentiated group (46.48%, 43.75% and 22.73%, P=0.025). The positivity rate in the non-lepidic adenocarcinoma group was higher than that in lepidic adenocarcinoma group (39.51% and 21.74%, P=0.001). The positivity rate of subsolid nodules was lower than that of solid nodules (30.01% vs 58.71%, P=0.038), and the positivity rates of stageⅠA1, ⅠA2 and ⅠA3 lung cancers were 33.33%, 48.96% and 69.23%, respectively, showing an increasing trend (P=0.005). The sensitivity and specificity of the combined detection of six tumor markers in the diagnosis of stage ⅠA lung cancer were 74.00% and 56.30%, respectively, and the area under the curve (AUC) was 0.541. The sensitivity and specificity of the combined detection of six serum tumor markers with CT in the diagnosis of stage ⅠA lung cancer were 83.0% and 78.3%, respectively, and the AUC was 0.721. Conclusions: For stage ⅠA lung cancer, the positivity rates of commonly used clinical tumor markers are generally low. The combined detection of six markers can increase the positivity rate. The positivity rate of markers tends to be higher in poorly differentiated lung cancer, squamous cell carcinoma, or solid nodules. Tumor markers combined with thin-slice CT showed limited improvement in diagnostic efficiency for early lung cancer.
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Affiliation(s)
- Q Peng
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - N Wu
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Y Huang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - S J Zhao
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - W Tang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - M Liang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Y L Ran
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - T Xiao
- State Key Laboratory of Molecular Oncology, Beijing Key Laboratory for Carcinogenesis and Cancer Prevention, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - L Yang
- Department of Pathology Diagnosis, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - X Liang
- Medical Statistics Office, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
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Tang W, Dong Z, Gao L, Wang X, Li T, Sun C, Chu Z, Cui D. Genetic diversity and population structure of modern wheat (Triticum aestivum L.) cultivars in Henan Province of China based on SNP markers. BMC Plant Biol 2023; 23:542. [PMID: 37924000 PMCID: PMC10625233 DOI: 10.1186/s12870-023-04537-9] [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] [Subscribe] [Scholar Register] [Received: 06/10/2023] [Accepted: 10/18/2023] [Indexed: 11/06/2023]
Abstract
BACKGROUND Henan is the province with the greatest wheat production in China. Although more than 100 cultivars are used for production, many cultivars are still insufficient in quality, disease resistance, adaptability and yield potential. To overcome these limitations, it is necessary to constantly breed new cultivars to maintain the continuous and stable growth of wheat yield and quality. To improve breeding efficiency, it is important to evaluate the genetic diversity and population genetic structure of its cultivars. However, there are no such reports from Henan Province. Therefore, in this study, single nucleotide polymorphism (SNP) markers were used to study the population genetic structure and genetic diversity of 243 wheat cultivars included in a comparative test of wheat varieties in Henan Province, aiming to provide a reference for the utilization of backbone parents and the selection of hybrid combinations in the genetic improvement of wheat cultivars. RESULTS In this study, 243 wheat cultivars from Henan Province of China were genotyped by the Affymetrix Axiom Wheat660K SNP chip, and 21 characteristics were investigated. The cultivars were divided into ten subgroups; each subgroup had distinct characteristics and unique utilization value. Furthermore, based on principal component analysis, Zhoumai cultivars were the main hybrid parents, followed by Aikang 58, high-quality cultivars, and Shandong cultivars. Genetic diversity analysis showed that 61.3% of SNPs had a high degree of genetic differentiation, whereas 33.4% showed a moderate degree. The nucleotide diversity of subgenome B was relatively high, with an average π value of 3.91E-5; the nucleotide diversity of subgenome D was the lowest, with an average π value of 2.44E-5. CONCLUSION The parents used in wheat cross-breeding in Henan Province are similar, with a relatively homogeneous genetic background and low genetic diversity. These results will not only contribute to the objective evaluation and utilization of the tested cultivars but also provide insights into the current conditions and existing challenges of wheat cultivar breeding in Henan Province, thereby facilitating the scientific formulation of breeding objectives and strategies to improve breeding efficiency.
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Affiliation(s)
- Wenjing Tang
- College of Agronomy/Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou, 450046, China
- Henan Agricultural Remote Sensing Monitoring Center, Zhengzhou, 450002, China
| | - Zhongdong Dong
- College of Agronomy/Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou, 450046, China
| | - Lifeng Gao
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Xicheng Wang
- Henan Academy of Agricultural Sciences, Zhengzhou, 450002, China
| | - Tianbao Li
- College of Agronomy/Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou, 450046, China
| | - Congwei Sun
- College of Agronomy/Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou, 450046, China
| | - Zongli Chu
- College of Agronomy, Xinyang Agriculture and Forestry University, Xinyang, 464000, China
| | - Dangqun Cui
- College of Agronomy/Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou, 450046, China.
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Yu M, Tang W, Liang W, Xie B, Gao R, Ding P, Gu X, Wang M, Wen S, Sun P. PCSK9 inhibition ameliorates experimental autoimmune myocarditis by reducing Th17 cell differentiation through LDLR/STAT-3/ROR-γt pathway. Int Immunopharmacol 2023; 124:110962. [PMID: 37776771 DOI: 10.1016/j.intimp.2023.110962] [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: 04/27/2023] [Revised: 08/16/2023] [Accepted: 09/15/2023] [Indexed: 10/02/2023]
Abstract
Proprotein convertase subtilisin kexin type 9 (PCSK9) was characterized as a protein regulating circulating cholesterol metabolism; however, recent studies demonstrated a role for PCSK9 in inflammatory and autoimmune diseases unrelated to cholesterol alterations. The implication of PCSK9 in myocarditis is unclear and we aim at investigating the roles and mechanisms of PCSK9 in myocarditis. Male BALB/c mice received subcutaneous immunization with MyHC-α peptide on days 0 and 7 to establish the experimental autoimmune myocarditis (EAM) model. PCSK9 inhibitor, evolocumab, was administered subcutaneously once a week starting on day 0 and all mice were euthanized on day 21. Our results showed that PCSK9 inhibition ameliorated the cardiac inflammation of EAM mice. PCSK9 inhibition reduced both the levels of cardiac and peripheral blood PCSK9. We found that CD4+ T cells, CD8+ T cells, macrophages, and cardiomyocytes in the heart of EAM mice could express PCSK9. PCSK9 inhibition decreased the differentiation of cardiac Th17 cells by lowering ROR-γt levels but had no effects on Th1, Th2, and Treg cell differentiation. In vitro experiments of CD4+ T cells, we found that PCSK9 directly promoted Th17 cell differentiation through LDLR/STAT3/ROR-γt pathway. Collectively, we demonstrated that PCSK9 inhibition ameliorated the severity of EAM mice by reducing Th17 cell differentiation. PCSK9 is a promising target for treating myocarditis.
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Affiliation(s)
- Miao Yu
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Hubei Provincial Engineering Research Center of Immunological Diagnosis and Therapy for Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Wenjing Tang
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Hubei Provincial Engineering Research Center of Immunological Diagnosis and Therapy for Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Wei Liang
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Hubei Provincial Engineering Research Center of Immunological Diagnosis and Therapy for Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Baikang Xie
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Hubei Provincial Engineering Research Center of Immunological Diagnosis and Therapy for Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Ran Gao
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Hubei Provincial Engineering Research Center of Immunological Diagnosis and Therapy for Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Peiwu Ding
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Hubei Provincial Engineering Research Center of Immunological Diagnosis and Therapy for Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Xiaoying Gu
- Department of Emergency Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430022, China
| | - Min Wang
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Hubei Provincial Engineering Research Center of Immunological Diagnosis and Therapy for Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Shuang Wen
- Department of Emergency Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430022, China.
| | - Peng Sun
- Department of Emergency Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430022, China.
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Yu X, Xiang J, Zhang Q, Chen S, Tang W, Li X, Sui Y, Liu W, Kong Q, Guo Y. Triple-negative breast cancer: predictive model of early recurrence based on MRI features. Clin Radiol 2023; 78:e798-e807. [PMID: 37596179 DOI: 10.1016/j.crad.2023.07.008] [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: 05/03/2023] [Revised: 07/13/2023] [Accepted: 07/18/2023] [Indexed: 08/20/2023]
Abstract
AIM To develop an integrated model based on preoperative magnetic resonance imaging (MRI) features for predicting early recurrence in patients with triple-negative breast cancer (TNBC). MATERIALS AND METHODS Women with TNBC who underwent breast MRI and surgery between 2009 and 2019 were evaluated retrospectively. Two breast radiologists reviewed MRI images independently based on the Breast Imaging Reporting and Data System Lexicon (BI-RADS), and classified the breast oedema scores on T2-weighted imaging (WI) as no oedema, peritumoural oedema, prepectoral oedema, or subcutaneous oedema. The relationship between disease-free survival (DFS) and MRI features was analysed by Cox regression, and a nomogram model was generated based on the results. RESULTS 150 patients with TNBC were included and divided into a training cohort (n=78) and validation cohort (n=72). MRI features including subcutaneous oedema and rim enhancement showed a tendency to worsen DFS in univariate analysis. Multivariate analysis showed that subcutaneous oedema (p=0.049, HR [95% confidence interval {CI} = 8.24 [1.01-67.52]) and rim enhancement (p=0.016, HR [95% CI] = 4.38 [1.32-14.54]) were independent predictors for DFS. In the nomogram, the areas under the curves (AUCs) of the training cohort was 0.808, and that of the validation cohort was 0.875. CONCLUSION The presence of subcutaneous oedema or rim enhancement on preoperative breast MRI was shown to be a good predictor of poor survival outcomes in patients with TNBC.
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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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Wang Y, Li X, Chen Y, Li Y, Liu Z, Fang C, Wu T, Niu H, Li Y, Sun W, Tang W, Xia W, Song K, Liu H, Zhou W. Pulsed-Laser-Triggered Piezoelectric Photocatalytic CO 2 Reduction over Tetragonal BaTiO 3 Nanocubes. Adv Mater 2023; 35:e2305257. [PMID: 37530983 DOI: 10.1002/adma.202305257] [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: 06/01/2023] [Revised: 07/23/2023] [Indexed: 08/03/2023]
Abstract
The recombination of photoinduced carriers in photocatalysts is considered one of the biggest barriers to the increase of photocatalytic efficiency. Piezoelectric photocatalysts open a new route to realize rapid carrier separation by mechanically distorting the lattice of piezoelectric nanocrystals to form a piezoelectric potential within the nanocrystals, generally requiring external force (e.g., ultrasonic radiation, mechanical stirring, and ball milling). In this study, a low-power UV pulsed laser (PL) (3 W, 355 nm) as a UV light source can trigger piezoelectric photocatalytic CO2 reduction of tetragonal BaTiO3 (BTO-T) in the absence of an applied force. The tremendous transient light pressure (5.7 × 107 Pa, 2.7 W) of 355 nm PL not only bends the energy band of BTO-T, thus allowing reactions that cannot theoretically occur to take place, but also induces a pulsed built-in electric field to determine an efficient photoinduced carrier separation. On that basis, the PL-triggered piezoelectric photocatalytic CO2 reduction realizes the highest reported performance, reaching a millimole level CO yield of 52.9 mmol g-1 h-1 and achieving efficient photocatalytic CO2 reduction in the continuous catalytic system. The method in this study is promising to contribute to the design of efficient piezoelectric photocatalytic reactions.
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Affiliation(s)
- Yijie Wang
- Institute for Advanced Interdisciplinary Research (iAIR), School of Chemistry and Chemical Engineering, University of Jinan, Jinan, 250022, P. R. China
| | - Xiao Li
- Institute for Advanced Interdisciplinary Research (iAIR), School of Chemistry and Chemical Engineering, University of Jinan, Jinan, 250022, P. R. China
| | - Yuke Chen
- Institute for Advanced Interdisciplinary Research (iAIR), School of Chemistry and Chemical Engineering, University of Jinan, Jinan, 250022, P. R. China
| | - Yue Li
- Institute for Advanced Interdisciplinary Research (iAIR), School of Chemistry and Chemical Engineering, University of Jinan, Jinan, 250022, P. R. China
| | - Zhen Liu
- Institute for Advanced Interdisciplinary Research (iAIR), School of Chemistry and Chemical Engineering, University of Jinan, Jinan, 250022, P. R. China
| | - Chaoqiong Fang
- Institute for Advanced Interdisciplinary Research (iAIR), School of Chemistry and Chemical Engineering, University of Jinan, Jinan, 250022, P. R. China
| | - Tong Wu
- Institute for Advanced Interdisciplinary Research (iAIR), School of Chemistry and Chemical Engineering, University of Jinan, Jinan, 250022, P. R. China
| | - Hongsen Niu
- School of Information Science and Engineering, University of Jinan, Jinan, 250022, P. R. China
| | - Yang Li
- School of Information Science and Engineering, University of Jinan, Jinan, 250022, P. R. China
| | - Wanggen Sun
- School of Physics and Technology, University of Jinan, Jinan, 250022, P. R. China
| | - Wenjing Tang
- School of Physics and Technology, University of Jinan, Jinan, 250022, P. R. China
| | - Wei Xia
- School of Physics and Technology, University of Jinan, Jinan, 250022, P. R. China
| | - Kepeng Song
- Electron Microscopy Center, Shandong University, Jinan, Shandong, 250100, P. R. China
| | - Hong Liu
- Institute for Advanced Interdisciplinary Research (iAIR), School of Chemistry and Chemical Engineering, University of Jinan, Jinan, 250022, P. R. China
- State Key Laboratory of Crystal Materials, Shandong University, Jinan, 250100, P. R. China
| | - Weijia Zhou
- Institute for Advanced Interdisciplinary Research (iAIR), School of Chemistry and Chemical Engineering, University of Jinan, Jinan, 250022, P. R. China
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Hou Y, Wang L, Luo C, Tang W, Dai R, An Y, Tang X. Clinical characteristics of early-onset paediatric systemic lupus erythematosus in a single centre in China. Rheumatology (Oxford) 2023; 62:3373-3381. [PMID: 36810668 DOI: 10.1093/rheumatology/kead086] [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: 10/04/2022] [Revised: 01/31/2023] [Accepted: 02/07/2023] [Indexed: 02/24/2023] Open
Abstract
OBJECTIVES We sought to investigate the sex distribution, clinical presentations, disease outcomes and genetic background of early-onset paediatric SLE (eo-pSLE) in a single centre in China to help enable early diagnosis and timely treatment. METHODS The clinical data of children aged less than 5 years old with SLE (n = 19) from January 2012 to December 2021 were reviewed and analysed. We performed DNA sequencing in 11 out of 19 patients to survey the genetic aetiologies. RESULTS Our study included 6 males and 13 females. The mean age at onset was 3.73 years. The median diagnostic delay was 9 months and was longer in male patients (P = 0.02). Four patients had an SLE-relevant family history. The most common clinical manifestations at diagnosis were fever, rash and hepatosplenomegaly. ANA positivity and low C3 were identified in all children. The renal (94.74%), mucocutaneous (94.74%), haematological (89.47%), respiratory (89.47%), digestive (84.21%), cardiovascular (57.89%) and neuropsychiatric (52.63%) systems were involved to varying degrees. We identified 13 SLE-associated gene mutations in 9 out of 11 patients: TREX1, PIK3CD, LRBA, KRAS, STAT4, C3, ITGAM, CYBB, TLR5, RIPK1, BACH2, CFHR5 and SYK. One male patient showed a 47, XXY chromosomal abnormality. CONCLUSION Early-onset (<5 years) pSLE is characterized by an insidious onset, typical immunological patterns, and the involvement of multiple organs. Immunological screening and genetic testing should be performed as soon as feasible in patients with an early onset of multisystemic autoimmune diseases to confirm the diagnosis.
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Affiliation(s)
- Yipei Hou
- Department of Rheumatology and Immunology, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Paediatrics, Chongqing Key Laboratory of Child Infection and Immunity, Chongqing, China
| | - Li Wang
- Department of Rheumatology and Immunology, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Paediatrics, Chongqing Key Laboratory of Child Infection and Immunity, Chongqing, China
| | - Chong Luo
- Department of Rheumatology and Immunology, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Paediatrics, Chongqing Key Laboratory of Child Infection and Immunity, Chongqing, China
| | - Wenjing Tang
- Department of Rheumatology and Immunology, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Paediatrics, Chongqing Key Laboratory of Child Infection and Immunity, Chongqing, China
| | - Rongxin Dai
- Department of Rheumatology and Immunology, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Paediatrics, Chongqing Key Laboratory of Child Infection and Immunity, Chongqing, China
| | - Yunfei An
- Department of Rheumatology and Immunology, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Paediatrics, Chongqing Key Laboratory of Child Infection and Immunity, Chongqing, China
| | - Xuemei Tang
- Department of Rheumatology and Immunology, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Paediatrics, Chongqing Key Laboratory of Child Infection and Immunity, Chongqing, China
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Tang W, Guo Q, Chen J, Wu Q, Zhang T, Wang Q, Zhang X, Xie P. The Predictive Value of Circulating Exosomal PD-L1 in Cervical Cancer Immunotherapy. Int J Radiat Oncol Biol Phys 2023; 117:e548-e549. [PMID: 37785688 DOI: 10.1016/j.ijrobp.2023.06.1851] [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] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Programmed death ligand 1 (PD-L1) expression was wildly used as a predictor of immune Check-Point Inhibitors (ICIs) efficiency. However, emerging results showed that PD-L1 was of great heterogeneity in sampling time and site. Recently, some studies found that exosomal PD-L1(ExoPD-L1) was related to ICIs response. In this study, we aimed to explore the predictive value of ExoPD-L1 in ICIs treatment of cervical cancer (CC) for the first time. MATERIALS/METHODS A total of 40 primarily diagnosed CC patients who accepted radical radiotherapy (RT) from March 2021 to October 2022 were included. The consecutive tumor sample were collected before and during RT. Another 37 advanced CC patients who accepted ICIs combination therapy from June 2020 to October 2022 were enrolled in this study. Blood samples were collected from each participant before and during treatment. Exosomes were derived by differential centrifugation, which was further identified by Western blot (WB) (CD9/TSG101/Calnexin), transmission electron microscope analysis and nanoparticle tracking analysis. ExoPD-L1 detection was conducted by enzyme-linked immuno-sorbent assay (ELISA). The knockout of PD-L1 was conducted via CRISPR/Cas9 assay and the overexpress of PD-L1 was conducted by lentiviral transfection. CD8+ T cells were extracted from murine spleen by CD8+ T Cell Isolation Kit. Immune cells and cytokines markers were detected by multicolor flow cytometry. RESULTS The consecutive detection of PD-L1 showed a dynamic change during RT. Compared with the level before RT, PD-L1 expression elevated in most patients (87.5%, 35/40) after RT. And the responders (n = 18) had elevated ExoPD-L1 level at the first two circles in the ICIs combination therapy (P<0.001). Whereas the level of pre-treatment ExoPD-L1 couldn't stratified clinical responders and non-responders (P = 0.181). The median follow-up time was 14.13 months. The mPFS in increased group vs. decreased group: not reach vs.11.02 months (P = 0.025, HR: 0.218, 0.052-0.913). Continuous blood sampling of mice models also found that effective therapeutic intervention could increase ExoPD-L1 in the early stage. The combination of exosome inhibitor GW4869 and anti-PD-1 further inhibited tumor growth. Mice were injected with external ExoPD-L1OE and ExoPD-L1KO. The results showed that ExoPD-L1OE suppressed body immunity and promoted tumor growth. The results of flow cytometry showed that ExoPD-L1OE inhibited CD8+ T cells from releasing interferon-and granzyme B. And ExoPD-L1OE also suppressed the CD8+ T cells proliferation in murine spleen. The coculture of CD8+ T cells and exosomes in vitro also confirmed the above conclusion. CONCLUSION Compared with unstable and impressionable tumoral PD-L1, ExoPD-L1 seems to be better predictor for the efficacy of immunotherapy in CC, which was with easy accessibility and continuation. Exosome PD-L1 played an immunosuppressive role by inhibiting the proliferation and functional factor release of CD8+ T cell.
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Affiliation(s)
- W Tang
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Q Guo
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - J Chen
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Q Wu
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - T Zhang
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Q Wang
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - X Zhang
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - P Xie
- Shandong Cancer Hospital and Institute, Jinan, Shandong, China
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Zhuo X, Xia L, Tang W, He W. A practical nomogram and risk stratification system for predicting survival outcomes in neuroblastoma patients: a SEER population-based study. J Cancer Res Clin Oncol 2023; 149:12285-12296. [PMID: 37430162 PMCID: PMC10465685 DOI: 10.1007/s00432-023-05110-5] [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] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 06/30/2023] [Indexed: 07/12/2023]
Abstract
BACKGROUND Neuroblastoma (NB) is a childhood malignancy with marked heterogeneity, resulting in highly variable outcomes among patients. This study aims to establish a novel nomogram and risk stratification system to predict the overall survival (OS) for patients with NB. METHODS We analyzed neuroblastoma patients from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015. The nomogram was constructed using independent risk factors for OS, identified through univariate and multivariate Cox regression analyses. The accuracy of this nomogram was evaluated with the concordance index, receiver operating characteristic curve, calibration curve, and decision curve analysis. In addition, we developed a risk stratification system based on the total score of each patient in the nomogram. RESULTS A total of 2185 patients were randomly assigned to the training group and the testing group. Six risk factors, including age, chemotherapy, brain metastases, primary site, tumor stage, and tumor size, were identified in the training group. Using these factors, a nomogram was constructed to predict 1-, 3-, and 5-year OS of NB patients. This model exhibited superior accuracy in the training and testing groups, exceeding traditional tumor stage prediction. Subgroup analysis suggested worse prognosis for retroperitoneal origin in the intermediate-risk group and adrenal gland origin in the high-risk group compared to other sites. Additionally, the prognosis for high-risk patients significantly improved after surgery. We also developed a web application to make the nomogram more user-friendly in clinical practices. CONCLUSION This nomogram demonstrates excellent accuracy and reliability, offering more precise personalized prognostic predictions to clinical patients.
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Affiliation(s)
- Xiaoyu Zhuo
- Department of Pediatric Hematology and Oncology, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Liangfeng Xia
- Department of Pediatric Surgery, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Wenjing Tang
- Department of Pediatric Hematology and Oncology, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Wenqi He
- Department of Pediatric Surgery, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, China.
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Wang S, Tang W, Luo H, Jin F. Incidence and Risk Factors for Brain Metastases in Patients with Lung Cancer: A Systematic Review and Meta-Analysis. Int J Radiat Oncol Biol Phys 2023; 117:e71-e72. [PMID: 37786078 DOI: 10.1016/j.ijrobp.2023.06.804] [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] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Brain metastases (BM) are a very common metastatic site in lung cancer, but the exact rate of metastasis is still controversial. Risk factors for BM development are also largely lacking, hampering personalized treatment strategies. This study aimed to identify the incidence and possible risk factors for BM in lung cancer. MATERIALS/METHODS A systematic review, based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guide-lines, was conducted using PubMed, Medline databases and Cochrane Library databases from inception until February 2023. Two investigators independently searched and selected literature, included in randomized controlled trials and cohort studies. Heterogeneity was assessed using the χ2 test and the I2 statistic. Significant heterogeneity was indicated by P <0.05 in Cochrane Q tests and a ratio greater than 40% in I2 statistics. The review is registered on PROSPERO, number: CRD42022370173. RESULTS Forty-nine studies were included in the meta-analysis. The results showed that the incidence rate of BM in non-small cell lung cancer (NSCLC) was 0.24 (95% confidence interval [CI]: 0.23-0.25; I2 = 97.1%). The incidence rate in early NSCLC was 0.11 (95% CI: 0.10-0.13), locally advanced NSCLC was 0.32 (95% CI: 0.29-0.34), and advanced NSCLC was 0.37 (95% CI: 0.35-0.38). Lung adenocarcinoma was more prone to BM in NSCLC (risk ratio [RR] = 3.59, 95% CI: 1.97-6.54; P<0.001). The BM rate of NSCLC with EGFR mutation was also higher (hazard ratio [HR] = 1.49, 95% CI: 1.14-1.94; P = 0.004). Sex and smoking had no significant effect on the incidence of BM in NSCLC. Prophylactic Cranial Irradiation (PCI) could significantly reduce BM in NSCLC (HR = 0.36, 95% CI: 0.23-0.56; P<0.001), but chemotherapy had no obvious effect on decreasing the rate of BM (HR = 0.91, 95% CI: 0.54-1.54; P = 0.73). The incidence rate of BM in small cell lung cancer (SCLC) was 0.28 (95% CI: 0.27-0.30; I2 = 95.9%), and 0.23 (95% CI: 0.20-0.25) in the limited-stage SCLC. Older age (≥65) (HR = 0.70, 95% CI: 0.54-0.92; P = 0.01) were associated with less BM in SCLC. A higher T stage (≥T3) (HR = 1.72, 95% CI: 1.16-2.56; P = 0.007) was a significant risk factor for BM, while sex, smoking dose were not. PCI could also significantly decreased BM in SCLC (HR = 0.47, 95% CI: 0.38-0.58; P<0.001). CONCLUSION This study is the first meta-analysis of BM incidence rate in lung cancer, and further explores the factors affecting BM, providing some suggestions for clinical decision-making of BM prevention in patients with lung cancer.
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Affiliation(s)
- S Wang
- Department of Radiation Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - W Tang
- Department of Rehabilitation, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - H Luo
- Department of Radiation Oncology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, China
| | - F Jin
- Department of Radiation Oncology, Chongqing University Cancer Hospital, Chongqing, China
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Abratenko P, Alterkait O, Andrade Aldana D, Anthony J, Arellano L, Asaadi J, Ashkenazi A, Balasubramanian S, Baller B, Barr G, Barrow J, Basque V, Benevides Rodrigues O, Berkman S, Bhanderi A, Bhattacharya M, Bishai M, Blake A, Bogart B, Bolton T, Book JY, Camilleri L, Caratelli D, Caro Terrazas I, Cavanna F, Cerati G, Chen Y, Cohen EO, Conrad JM, Convery M, Cooper-Troendle L, Crespo-Anadón JI, Del Tutto M, Dennis SR, Detje P, Devitt A, Diurba R, Djurcic Z, Dorrill R, Duffy K, Dytman S, Eberly B, Ereditato A, Evans JJ, Fine R, Finnerud OG, Foreman W, Fleming BT, Foppiani N, Franco D, Furmanski AP, Garcia-Gamez D, Gardiner S, Ge G, Gollapinni S, Goodwin O, Gramellini E, Green P, Greenlee H, Gu W, Guenette R, Guzowski P, Hagaman L, Hen O, Hicks R, Hilgenberg C, Horton-Smith GA, Irwin B, Itay R, James C, Ji X, Jiang L, Jo JH, Johnson RA, Jwa YJ, Kalra D, Kamp N, Karagiorgi G, Ketchum W, Kirby M, Kobilarcik T, Kreslo I, Leibovitch MB, Lepetic I, Li JY, Li K, Li Y, Lin K, Littlejohn BR, Louis WC, Luo X, Mariani C, Marsden D, Marshall J, Martinez N, Martinez Caicedo DA, Mason K, Mastbaum A, McConkey N, Meddage V, Miller K, Mills J, Mogan A, Mohayai T, Mooney M, Moor AF, Moore CD, Mora Lepin L, Mousseau J, Mulleriababu S, Naples D, Navrer-Agasson A, Nayak N, Nebot-Guinot M, Nowak J, Oza N, Palamara O, Pallat N, Paolone V, Papadopoulou A, Papavassiliou V, Parkinson HB, Pate SF, Patel N, Pavlovic Z, Piasetzky E, Ponce-Pinto ID, Pophale I, Prince S, Qian X, Raaf JL, Radeka V, Rafique A, Reggiani-Guzzo M, Ren L, Rochester L, Rodriguez Rondon J, Rosenberg M, Ross-Lonergan M, Rudolf von Rohr C, Scanavini G, Schmitz DW, Schukraft A, Seligman W, Shaevitz MH, Sharankova R, Shi J, Snider EL, Soderberg M, Söldner-Rembold S, Spitz J, Stancari M, John JS, Strauss T, Sword-Fehlberg S, Szelc AM, Tang W, Taniuchi N, Terao K, Thorpe C, Torbunov D, Totani D, Toups M, Tsai YT, Tyler J, Uchida MA, Usher T, Viren B, Weber M, Wei H, White AJ, Williams Z, Wolbers S, Wongjirad T, Wospakrik M, Wresilo K, Wright N, Wu W, Yandel E, Yang T, Yates LE, Yu HW, Zeller GP, Zennamo J, Zhang C. First Double-Differential Measurement of Kinematic Imbalance in Neutrino Interactions with the MicroBooNE Detector. Phys Rev Lett 2023; 131:101802. [PMID: 37739352 DOI: 10.1103/physrevlett.131.101802] [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: 01/11/2023] [Revised: 05/09/2023] [Accepted: 07/14/2023] [Indexed: 09/24/2023]
Abstract
We report the first measurement of flux-integrated double-differential quasielasticlike neutrino-argon cross sections, which have been made using the Booster Neutrino Beam and the MicroBooNE detector at Fermi National Accelerator Laboratory. The data are presented as a function of kinematic imbalance variables which are sensitive to nuclear ground-state distributions and hadronic reinteraction processes. We find that the measured cross sections in different phase-space regions are sensitive to different nuclear effects. Therefore, they enable the impact of specific nuclear effects on the neutrino-nucleus interaction to be isolated more completely than was possible using previous single-differential cross section measurements. Our results provide precision data to help test and improve neutrino-nucleus interaction models. They further support ongoing neutrino-oscillation studies by establishing phase-space regions where precise reaction modeling has already been achieved.
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Affiliation(s)
- P Abratenko
- Tufts University, Medford, Massachusetts 02155, USA
| | - O Alterkait
- Tufts University, Medford, Massachusetts 02155, USA
| | - D Andrade Aldana
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - J Anthony
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - L Arellano
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Asaadi
- University of Texas, Arlington, Texas 76019, USA
| | - A Ashkenazi
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - S Balasubramanian
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - B Baller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Barr
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - J Barrow
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - V Basque
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - O Benevides Rodrigues
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
- Syracuse University, Syracuse, New York 13244, USA
| | - S Berkman
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - A Bhanderi
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - M Bhattacharya
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Bishai
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Blake
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - B Bogart
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - T Bolton
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - J Y Book
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - L Camilleri
- Columbia University, New York, New York 10027, USA
| | - D Caratelli
- University of California, Santa Barbara, California 93106, USA
| | - I Caro Terrazas
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - F Cavanna
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Cerati
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y Chen
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - E O Cohen
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - J M Conrad
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - M Convery
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - L Cooper-Troendle
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - J I Crespo-Anadón
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid E-28040, Spain
| | - M Del Tutto
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S R Dennis
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - P Detje
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - A Devitt
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - R Diurba
- Universität Bern, Bern CH-3012, Switzerland
| | - Z Djurcic
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - R Dorrill
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - K Duffy
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - S Dytman
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - B Eberly
- University of Southern Maine, Portland, Maine 04104, USA
| | | | - J J Evans
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - R Fine
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O G Finnerud
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - W Foreman
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - B T Fleming
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - N Foppiani
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - D Franco
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - A P Furmanski
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - S Gardiner
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Ge
- Columbia University, New York, New York 10027, USA
| | - S Gollapinni
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - O Goodwin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - E Gramellini
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - P Green
- The University of Manchester, Manchester M13 9PL, United Kingdom
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - H Greenlee
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Gu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - R Guenette
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - P Guzowski
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Hagaman
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - O Hen
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - R Hicks
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - C Hilgenberg
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - B Irwin
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - R Itay
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C James
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - X Ji
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - L Jiang
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - J H Jo
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - R A Johnson
- University of Cincinnati, Cincinnati, Ohio 45221, USA
| | - Y-J Jwa
- Columbia University, New York, New York 10027, USA
| | - D Kalra
- Columbia University, New York, New York 10027, USA
| | - N Kamp
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - G Karagiorgi
- Columbia University, New York, New York 10027, USA
| | - W Ketchum
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Kirby
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Kobilarcik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - I Kreslo
- Universität Bern, Bern CH-3012, Switzerland
| | - M B Leibovitch
- University of California, Santa Barbara, California 93106, USA
| | - I Lepetic
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - J-Y Li
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - K Li
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Y Li
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - K Lin
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - B R Littlejohn
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - W C Louis
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - X Luo
- University of California, Santa Barbara, California 93106, USA
| | - C Mariani
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - D Marsden
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Marshall
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - N Martinez
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - D A Martinez Caicedo
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - K Mason
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mastbaum
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - N McConkey
- The University of Manchester, Manchester M13 9PL, United Kingdom
- University College London, London WC1E 6BT, United Kingdom
| | - V Meddage
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - K Miller
- University of Chicago, Chicago, Illinois 60637, USA
| | - J Mills
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mogan
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - T Mohayai
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Mooney
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - A F Moor
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - C D Moore
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L Mora Lepin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Mousseau
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | | | - D Naples
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Navrer-Agasson
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - N Nayak
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Nebot-Guinot
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - J Nowak
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - N Oza
- Columbia University, New York, New York 10027, USA
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O Palamara
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - N Pallat
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - V Paolone
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Papadopoulou
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - V Papavassiliou
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - H B Parkinson
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - S F Pate
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - N Patel
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - Z Pavlovic
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Piasetzky
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - I D Ponce-Pinto
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - I Pophale
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - S Prince
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - X Qian
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - J L Raaf
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - V Radeka
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Rafique
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - M Reggiani-Guzzo
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Ren
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - L Rochester
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Rodriguez Rondon
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - M Rosenberg
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Ross-Lonergan
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | | | - G Scanavini
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - D W Schmitz
- University of Chicago, Chicago, Illinois 60637, USA
| | - A Schukraft
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Seligman
- Columbia University, New York, New York 10027, USA
| | - M H Shaevitz
- Columbia University, New York, New York 10027, USA
| | - R Sharankova
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Shi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - E L Snider
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Soderberg
- Syracuse University, Syracuse, New York 13244, USA
| | | | - J Spitz
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - M Stancari
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J St John
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Strauss
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S Sword-Fehlberg
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - A M Szelc
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - W Tang
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - N Taniuchi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - K Terao
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C Thorpe
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - D Torbunov
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - D Totani
- University of California, Santa Barbara, California 93106, USA
| | - M Toups
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y-T Tsai
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Tyler
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - M A Uchida
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - T Usher
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - B Viren
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Weber
- Universität Bern, Bern CH-3012, Switzerland
| | - H Wei
- Louisiana State University, Baton Rouge, Louisiana 70803, USA
| | - A J White
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Z Williams
- University of Texas, Arlington, Texas 76019, USA
| | - S Wolbers
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Wongjirad
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Wospakrik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - K Wresilo
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - N Wright
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - W Wu
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Yandel
- University of California, Santa Barbara, California 93106, USA
| | - T Yang
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L E Yates
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - H W Yu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - G P Zeller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Zennamo
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - C Zhang
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
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Xie W, Li R, Tang W, Ma Z, Miao S, Li C, Yang C, Li B, Wang T, Gong Z, Zhou Y, Yu S. Proteomics profiling reveals mitochondrial damage in the thalamus in a mouse model of chronic migraine. J Headache Pain 2023; 24:122. [PMID: 37667199 PMCID: PMC10478405 DOI: 10.1186/s10194-023-01646-6] [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: 04/01/2023] [Accepted: 08/08/2023] [Indexed: 09/06/2023] Open
Abstract
BACKGROUND Migraine, a complex brain disorder, is regarded as a possible clinical manifestation of brain energy dysfunction. The trigeminovascular system is considered the basis for the pathogenesis of migraine, hence we depicted the proteomics profiling of key regions in this system, then focusing on protein alterations related to mitochondrial function. The aim of this study is to illustrate the role of mitochondria in migraine. METHODS A mouse model of chronic migraine (CM) was established by repeated nitroglycerin (NTG) stimulation and evaluated by von-Frey filaments, a hot plate and a light-dark box. Differentially expressed proteins (DEPs) in some subcortical brain regions of the trigeminovascular system were screened through liquid chromatography-tandem mass spectrometry (LC‒MS/MS) to analyse the specificity of key signaling pathways in different brain regions. And then mitochondrial function, structure and dynamics were determined by qPCR, ELISA, and transmission electron microscope (TEM). Finally, the effect of mitochondrial intervention-Urolithin A (UA) on CM was investigated. RESULTS Repeated NTG injection triggered photophobia, periorbital and hind paw allodynia in mice. The proteomics profiling of CM model showed that 529, 109, 163, 152 and 419 DEPs were identified in the thalamus, hypothalamus, periaqueductal grey (PAG), trigeminal ganglion (TG) and trigeminocervical complex (TCC), respectively. The most significant changes in the brain region-specific pathways pointed to thalamic mitochondrial impairment. NTG induced mitochondrial structural disruption, dysfunction and homeostatic dysregulation, which could be partially attenuated by UA intervention. CONCLUSION Our findings highlight the involvement of mitochondrial damage in the thalamus in central sensitization of CM, which provides evidence of possible metabolic mechanisms in migraine pathophysiology.
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Affiliation(s)
- Wei Xie
- Department of Neurology, the First Medical Center, Chinese PLA General Hospital, Beijing, China
- Medical School of Chinese PLA, Beijing, China
| | - Ruibing Li
- Department of Laboratory Medicine, the First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Wenjing Tang
- Department of Neurology, the First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Zhenjie Ma
- Department of Neurology, the First Medical Center, Chinese PLA General Hospital, Beijing, China
- Medical School of Chinese PLA, Beijing, China
| | - Shuai Miao
- Department of Neurology, the First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Chenhao Li
- Department of Neurology, the First Medical Center, Chinese PLA General Hospital, Beijing, China
- Medical School of Chinese PLA, Beijing, China
| | - Chunxiao Yang
- Department of Neurology, the First Medical Center, Chinese PLA General Hospital, Beijing, China
- School of Medicine, Nankai University, Tianjin, China
| | - Bozhi Li
- Department of Neurology, the First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Tao Wang
- Department of Neurology, the First Medical Center, Chinese PLA General Hospital, Beijing, China
- Medical School of Chinese PLA, Beijing, China
| | - Zihua Gong
- Department of Neurology, the First Medical Center, Chinese PLA General Hospital, Beijing, China
- Medical School of Chinese PLA, Beijing, China
| | - Yue Zhou
- College of Life Science, Northwest University, Xi'an, Shanxi, China.
| | - Shengyuan Yu
- Department of Neurology, the First Medical Center, Chinese PLA General Hospital, Beijing, China.
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Jia J, Shuai M, Yan W, Tang Q, Wang B, Tang W, Wang P, Zhang T, Yang S, Zhang Y, Liu Q, Fu Y, Cai W, Zheng JS. Conserved Covarying Gut Microbial Network in Preterm Infants and Childhood Growth During the First 5 Years of Life: A Prospective Cohort Study. Am J Clin Nutr 2023; 118:561-571. [PMID: 37517614 DOI: 10.1016/j.ajcnut.2023.07.019] [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: 05/06/2023] [Revised: 07/19/2023] [Accepted: 07/24/2023] [Indexed: 08/01/2023] Open
Abstract
BACKGROUND Longitudinally conserved microbe-microbe interactions may provide insights to understand the complex dynamic system of early-life gut microbiota among preterm infants. OBJECTIVES We aimed to profile the covarying network of gut microbiota among preterm infants and investigate its potential influence on host growth (2-5 y). METHODS We collected time-series stool samples (n = 717 from children and n = 116 from mothers) among 51 preterm and 51 full-term infants from birth up to 5 y of age and among 53 mothers. The included infants underwent time-series measurements of early-life gut microbiota (0-5 y) and growth (2-5 y) from June 2014 to April 2017. The covarying taxa that exhibited consistent covariation from day 1 to year 5 were defined as conserved features in the development of gut microbiota. Childrens' height-for-age z score (HAZ) and weight-for-age z score were calculated according to World Health Organization Child Growth Standards. RESULTS We observed distinct dynamic patterns of both microbial alpha and beta diversity comparing preterm infants with full-term controls during the very early stage (<3 mo). Moreover, we identified a covarying network containing 10 taxa as a conserved gut microbial feature of these preterm infants from birth to 5 y old. This covarying network was distinctive between preterm and full-term infants before 3 mo of age (P < 0.001) and tended to be similar as the infants grew up. Several covarying taxa of the network during early life (<3 mo) were associated with childhood growth (2-5 y) (eg, Clostridium_sensu_stricto_1 with HAZ, β = -0.32, q < 0.01), and the human milk feeding duration was a main modulating factor. CONCLUSIONS Preterm born children possess conserved and distinct covarying microbiota during very early life, which may have a profound influence on their growth later in life. This trial was registered at clinicaltrials.gov as NCT03373721.
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Affiliation(s)
- Jie Jia
- Department of Clinical Nutrition, Xin Hua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Key Laboratory of Pediatric Gastroenterology and Nutrition, Shanghai, China; Shanghai Institute of Pediatric Research, Shanghai, China
| | - Menglei Shuai
- School of Life Sciences, Westlake University, Hangzhou, China; Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Weihui Yan
- Shanghai Key Laboratory of Pediatric Gastroenterology and Nutrition, Shanghai, China; Shanghai Institute of Pediatric Research, Shanghai, China; Division of Pediatric Gastroenterology and Nutrition, Xin Hua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qingya Tang
- Department of Clinical Nutrition, Xin Hua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Bei Wang
- Department of Obstetrics & Gynecology, Xin Hua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Wenjing Tang
- Department of Clinical Nutrition, Xin Hua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Panliang Wang
- Shanghai Key Laboratory of Pediatric Gastroenterology and Nutrition, Shanghai, China; Shanghai Institute of Pediatric Research, Shanghai, China
| | - Tian Zhang
- Shanghai Key Laboratory of Pediatric Gastroenterology and Nutrition, Shanghai, China; Shanghai Institute of Pediatric Research, Shanghai, China
| | - Shihan Yang
- College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yimeng Zhang
- College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qianruo Liu
- College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuanqing Fu
- School of Life Sciences, Westlake University, Hangzhou, China; Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China.
| | - Wei Cai
- Shanghai Key Laboratory of Pediatric Gastroenterology and Nutrition, Shanghai, China; Shanghai Institute of Pediatric Research, Shanghai, China; Division of Pediatric Gastroenterology and Nutrition, Xin Hua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Ju-Sheng Zheng
- School of Life Sciences, Westlake University, Hangzhou, China; Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
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30
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Zhang Y, Chen C, Cui Y, Du Q, Tang W, Yang W, Kou G, Tang W, Chen H, Gong R. Potential regulatory genes of light induced anthocyanin accumulation in sweet cherry identified by combining transcriptome and metabolome analysis. Front Plant Sci 2023; 14:1238624. [PMID: 37662172 PMCID: PMC10469515 DOI: 10.3389/fpls.2023.1238624] [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: 06/12/2023] [Accepted: 07/26/2023] [Indexed: 09/05/2023]
Abstract
Anthocyanins exist widely in various plant tissues and organs, and they play an important role in plant reproduction, disease resistance, stress resistance, and protection of human vision. Most fruit anthocyanins can be induced to accumulate by light. Here, we shaded the "Hong Deng" sweet cherry and performed an integrated analysis of its transcriptome and metabolome to explore the role of light in anthocyanin accumulation. The total anthocyanin content of the fruit and two of its anthocyanin components were significantly reduced after the shading. Transcriptome and metabolomics analysis revealed that PAL, 4CL, HCT, ANS and other structural genes of the anthocyanin pathway and cyanidin 3-O-glucoside, cyanidin 3-O-rutinoside, and other metabolites were significantly affected by shading. Weighted total gene network analysis and correlation analysis showed that the upstream and middle structural genes 4CL2, 4CL3, and HCT2 of anthocyanin biosynthesis may be the key genes affecting the anthocyanin content variations in fruits after light shading. Their expression levels may be regulated by transcription factors such as LBD, ERF4, NAC2, NAC3, FKF1, LHY, RVE1, and RVE2. This study revealed for the first time the possible role of LBD, FKF1, and other transcription factors in the light-induced anthocyanin accumulation of sweet cherry, thereby laying a preliminary foundation for further research on the role of light in anthocyanin accumulation of deep red fruit varieties and the genetic breeding of sweet cherry.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Ronggao Gong
- College of Horticulture, Sichuan Agricultural University, Chengdu, China
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31
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Ouyang Y, Zhang J, Sun W, Li M, Chen T, Zhang H, Tang W, Xia W. Picosecond dissipative soliton generation from an ytterbium-doped fiber laser based on a BP/SnSe 2-PVA mixture saturable absorber. Front Optoelectron 2023; 16:19. [PMID: 37466763 DOI: 10.1007/s12200-023-00074-3] [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] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 06/01/2023] [Indexed: 07/20/2023]
Abstract
Stable picosecond dissipative soliton pulses were observed in an ytterbium-doped fiber laser employing a high-quality mixture of BP/SnSe2-PVA saturable absorber (SA). The modulation depth, saturation intensity, and non-saturable loss of the mixture of BP/SnSe2-PVA SA were measured with values of 5.98%, 18.37 MW/cm2, and 33%, respectively. Within the pump power range of 150-270 mW, stable dissipative soliton pulses were obtained with an output power of 1.68-4 mW. When the minimum pulse duration is 1.28 ps, a repetition rate of 0.903 MHz, center wavelength of 1064.38 nm and 3 dB bandwidth of 2 nm were obtained. The maximum pulse energy of 4.43 nJ and the signal-to-noise ratio up to 72 dB were achieved at pump power of 270 mW. The results suggest that the BP/SnSe2-PVA mixture SA has outstanding nonlinear saturable absorption characteristics and broad ultrafast laser applications.
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Affiliation(s)
- Yuting Ouyang
- School of Physics and Technology, University of Jinan, Jinan, 250022, China
| | - Jiayu Zhang
- School of Physics and Technology, University of Jinan, Jinan, 250022, China
| | - Wanggen Sun
- Shandong Huaguang Optoelectronics Co. Ltd., Jinan, 250101, China
| | - Mengxiao Li
- School of Physics and Technology, University of Jinan, Jinan, 250022, China
| | - Tao Chen
- School of Physics and Technology, University of Jinan, Jinan, 250022, China
| | - Haikun Zhang
- School of Physics and Technology, University of Jinan, Jinan, 250022, China.
| | - Wenjing Tang
- School of Physics and Technology, University of Jinan, Jinan, 250022, China.
| | - Wei Xia
- School of Physics and Technology, University of Jinan, Jinan, 250022, China
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Tao X, Yang C, He J, Liu Q, Wu S, Tang W, Wang J. Serum alkaline phosphatase was independently associated with depression in patients with cerebrovascular disease. Front Psychiatry 2023; 14:1184673. [PMID: 37469359 PMCID: PMC10352498 DOI: 10.3389/fpsyt.2023.1184673] [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] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 06/16/2023] [Indexed: 07/21/2023] Open
Abstract
Background and purpose Blood markers have important value in the diagnosis of depressive disorders. Serum alkaline phosphatase (ALP) not only predicts stroke recurrence and poor functional prognosis in cerebrovascular disease (CVD) patients but also increases significantly in middle-aged women with depression. Thus, it has not been reported whether serum ALP is associated with the development of depression and/or vascular depression (VDe) in CVD patients. Methods This was a cross-sectional study of 353 CVD patients (stroke patients, n = 291; cerebral small vessel disease (CSVD) patients, n = 62). Baseline demographic information, fasting blood markers (such as blood counts, liver function, kidney function and lipids), and brain CT/MRI scans were collected. CVD patients were divided into non-depression, suspected vascular depression (SVD), and positive vascular depression (PVD) groups according to their Hamilton Rating Scale for Depression (HAMD) scores. Univariate analysis of baseline data, blood markers, and the prevalence of lesions (> 1.5 cm) was performed. Subsequently, the diagnostic performance of the univariate and combined variables for SVD and PVD was analyzed using binary logistic regression. The diagnostic value of the multivariate model for VDe was analyzed by ordinal logistic regression. Results (1) Serum ALP (p = 0.003) and hypersensitive C-reactive protein (hs-CRP, p = 0.001) concentrations increased as HAMD scores increased, and the prevalence of brain atrophy (p = 0.016) and lesions in the basal ganglia (p = 0.001) and parietal (p = 0.001), temporal (p = 0.002), and frontal lobes (p = 0.003) also increased, whereas the concentrations of hemoglobin (Hb, p = 0.003), cholinesterase (ChE, p = 0.001), and high-density lipoprotein cholesterol (HDL-C, p = 0.005) declined. Among these variables, hs-CRP (r = 0.218, p < 0.001) had a weak positively association with HAMD scores, and ChE (r = -0.226, p < 0.001) had a weak negative association. (2) The combination of Hb, hs-CRP, ChE, ALP, and HDL-C improved diagnostic performance for VDe [AUC = 0.775, 95% CI (0.706, 0.844), p < 0.001]. (3) Hb (OR = 0.986, p = 0.049), ChE (OR = 0.999, p = 0.020), ALP (OR = 1.017, p = 0.003), and basal ganglia lesions (OR = 2.197, p < 0.001) were important factors impacting VDe development. After adjusting for Hb, hs-CRP, ChE, HDL-C, lesions in the above mentioned four locations, sex, age and the prevalence of CSVD and brain atrophy, ALP [OR = 1.016, 95% CI (1.005, 1.027), p = 0.004] was independently associated with VDe. Conclusion Hb, hs-CRP, ChE, ALP, and HDL-C concentrations are potential blood markers of depression in CVD patients and, when combined, may improve diagnostic performance for VDe. Serum ALP was independently associated with VDe in patients with CVD.
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Affiliation(s)
- Xi Tao
- Department of Neurological Rehabilitation, Hunan Provincial People’s Hospital, Hunan Normal University, Changsha, Hunan Province, China
- Clinical Research Center for Cerebrovascular Disease Rehabilitation in Hunan Province, Changsha, Hunan Province, China
- Hunan Provincical Key Laboratory of Neurorestoratology, Hunan Normal University, Changsha, Hunan, China
| | - Chen Yang
- Department of Neurological Rehabilitation, Hunan Provincial People’s Hospital, Hunan Normal University, Changsha, Hunan Province, China
| | - Juan He
- Department of Neurosurgery, Hunan Provincial People’s Hospital, Hunan Normal University, Changsha, Hunan Province, China
| | - Qianrong Liu
- Department of Neurological Rehabilitation, Hunan Provincial People’s Hospital, Hunan Normal University, Changsha, Hunan Province, China
- Clinical Research Center for Cerebrovascular Disease Rehabilitation in Hunan Province, Changsha, Hunan Province, China
| | - Siyuan Wu
- Department of Neurological Rehabilitation, Hunan Provincial People’s Hospital, Hunan Normal University, Changsha, Hunan Province, China
| | - Wenjing Tang
- Department of Rehabilitation, Rehabilitation Hospital of Hunan Province, Changsha, Hunan Province, China
| | - Jia Wang
- Department of Scientific Research, Hunan Provincial People’s Hospital, Hunan Normal University, Changsha, Hunan Province, China
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Sun G, Wu M, Lv Q, Yang X, Wu J, Tang W, Dai R, Zhou L, Ding Y, Zhang Z, An Y, Tang X, Zheng X, Wang Z, Sun L, Xie Y, Zhao X, Du H. A Multicenter Cohort Study of Immune Dysregulation Disorders Caused by ELF4 Variants in China. J Clin Immunol 2023; 43:933-939. [PMID: 36823308 DOI: 10.1007/s10875-023-01453-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [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: 12/30/2022] [Accepted: 02/15/2023] [Indexed: 02/25/2023]
Abstract
Patients with DEX (deficiency in ELF4, X-linked) were recently reported by our team and others, and cases are very limited worldwide. Our knowledge of this new disease is currently preliminary. In this study, we described 5 more cases presenting mainly with oral ulcer, inflammatory bowel disease-like symptoms, fever of unknown origin, anemia, or systemic lupus erythematosus. Whole exome sequencing identified potential pathogenic ELF4 variants in all cases. The pathogenicity of these variants was confirmed by the detection of ELF4 expression in peripheral blood mononuclear cells from patients and utilizing a simple IFN-b luciferase reporter assay, as previously reported. Our findings significantly contribute to the current understanding of DEX.
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Affiliation(s)
- Gan Sun
- National Clinical Research Center for Child Health and Disorders (Chongqing), Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Infection and Immunity, Department of Rheumatology & Immunology, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Maolan Wu
- Department of Pediatrics, Xiangya Hospital, Central South University, Changsha, China
| | - Qianying Lv
- Department of Rheumatology, Children's Hospital of Fudan University, National Pediatric Medical Center of China, Shanghai, China
| | - Xi Yang
- National Clinical Research Center for Child Health and Disorders (Chongqing), Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Infection and Immunity, Department of Rheumatology & Immunology, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Junfeng Wu
- National Clinical Research Center for Child Health and Disorders (Chongqing), Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Infection and Immunity, Department of Rheumatology & Immunology, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Wenjing Tang
- National Clinical Research Center for Child Health and Disorders (Chongqing), Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Infection and Immunity, Department of Rheumatology & Immunology, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Rongxin Dai
- National Clinical Research Center for Child Health and Disorders (Chongqing), Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Infection and Immunity, Department of Rheumatology & Immunology, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Lina Zhou
- National Clinical Research Center for Child Health and Disorders (Chongqing), Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Infection and Immunity, Department of Rheumatology & Immunology, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Yuan Ding
- National Clinical Research Center for Child Health and Disorders (Chongqing), Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Infection and Immunity, Department of Rheumatology & Immunology, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Zhiyong Zhang
- National Clinical Research Center for Child Health and Disorders (Chongqing), Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Infection and Immunity, Department of Rheumatology & Immunology, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Yunfei An
- National Clinical Research Center for Child Health and Disorders (Chongqing), Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Infection and Immunity, Department of Rheumatology & Immunology, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Xuemei Tang
- National Clinical Research Center for Child Health and Disorders (Chongqing), Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Infection and Immunity, Department of Rheumatology & Immunology, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Xiangrong Zheng
- Department of Pediatrics, Xiangya Hospital, Central South University, Changsha, China.
| | - Zhaoxia Wang
- Department of Gastroenterology, Shenzhen Children's Hospital, Shenzhen, China.
| | - Li Sun
- Department of Rheumatology, Children's Hospital of Fudan University, National Pediatric Medical Center of China, Shanghai, China.
| | - Yongmei Xie
- Department of Pediatrics, West China Second University Hospital, Sichuan University, Sichuan province, Chengdu, China.
| | - Xiaodong Zhao
- National Clinical Research Center for Child Health and Disorders (Chongqing), Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Infection and Immunity, Department of Rheumatology & Immunology, Children's Hospital of Chongqing Medical University, Chongqing, China.
- The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
| | - Hongqiang Du
- National Clinical Research Center for Child Health and Disorders (Chongqing), Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Infection and Immunity, Department of Rheumatology & Immunology, Children's Hospital of Chongqing Medical University, Chongqing, China.
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Abratenko P, Andrade Aldana D, Anthony J, Arellano L, Asaadi J, Ashkenazi A, Balasubramanian S, Baller B, Barr G, Barrow J, Basque V, Benevides Rodrigues O, Berkman S, Bhanderi A, Bhattacharya M, Bishai M, Blake A, Bogart B, Bolton T, Book JY, Camilleri L, Caratelli D, Caro Terrazas I, Cavanna F, Cerati G, Chen Y, Conrad JM, Convery M, Cooper-Troendle L, Crespo-Anadón JI, Del Tutto M, Dennis SR, Detje P, Devitt A, Diurba R, Djurcic Z, Dorrill R, Duffy K, Dytman S, Eberly B, Ereditato A, Evans JJ, Fine R, Finnerud OG, Foreman W, Fleming BT, Foppiani N, Franco D, Furmanski AP, Garcia-Gamez D, Gardiner S, Ge G, Gollapinni S, Goodwin O, Gramellini E, Green P, Greenlee H, Gu W, Guenette R, Guzowski P, Hagaman L, Hen O, Hicks R, Hilgenberg C, Horton-Smith GA, Irwin B, Itay R, James C, Ji X, Jiang L, Jo JH, Johnson RA, Jwa YJ, Kalra D, Kamp N, Karagiorgi G, Ketchum W, Kirby M, Kobilarcik T, Kreslo I, Leibovitch MB, Lepetic I, Li JY, Li K, Li Y, Lin K, Littlejohn BR, Louis WC, Luo X, Mariani C, Marsden D, Marshall J, Martinez N, Martinez Caicedo DA, Mason K, Mastbaum A, McConkey N, Meddage V, Miller K, Mills J, Mogan A, Mohayai T, Mooney M, Moor AF, Moore CD, Mora Lepin L, Mousseau J, Mulleriababu S, Naples D, Navrer-Agasson A, Nayak N, Nebot-Guinot M, Nowak J, Nunes M, Oza N, Palamara O, Pallat N, Paolone V, Papadopoulou A, Papavassiliou V, Parkinson HB, Pate SF, Patel N, Pavlovic Z, Piasetzky E, Ponce-Pinto ID, Pophale I, Prince S, Qian X, Raaf JL, Radeka V, Rafique A, Reggiani-Guzzo M, Ren L, Rochester L, Rodriguez Rondon J, Rosenberg M, Ross-Lonergan M, Rudolf von Rohr C, Scanavini G, Schmitz DW, Schukraft A, Seligman W, Shaevitz MH, Sharankova R, Shi J, Snider EL, Soderberg M, Söldner-Rembold S, Spitz J, Stancari M, John JS, Strauss T, Sword-Fehlberg S, Szelc AM, Tang W, Taniuchi N, Terao K, Thorpe C, Torbunov D, Totani D, Toups M, Tsai YT, Tyler J, Uchida MA, Usher T, Viren B, Weber M, Wei H, White AJ, Williams Z, Wolbers S, Wongjirad T, Wospakrik M, Wresilo K, Wright N, Wu W, Yandel E, Yang T, Yates LE, Yu HW, Zeller GP, Zennamo J, Zhang C. First Measurement of Quasielastic Λ Baryon Production in Muon Antineutrino Interactions in the MicroBooNE Detector. Phys Rev Lett 2023; 130:231802. [PMID: 37354393 DOI: 10.1103/physrevlett.130.231802] [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: 12/16/2022] [Revised: 04/07/2023] [Accepted: 04/28/2023] [Indexed: 06/26/2023]
Abstract
We present the first measurement of the cross section of Cabibbo-suppressed Λ baryon production, using data collected with the MicroBooNE detector when exposed to the neutrinos from the main injector beam at the Fermi National Accelerator Laboratory. The data analyzed correspond to 2.2×10^{20} protons on target running in neutrino mode, and 4.9×10^{20} protons on target running in anti-neutrino mode. An automated selection is combined with hand scanning, with the former identifying five candidate Λ production events when the signal was unblinded, consistent with the GENIE prediction of 5.3±1.1 events. Several scanners were employed, selecting between three and five events, compared with a prediction from a blinded Monte Carlo simulation study of 3.7±1.0 events. Restricting the phase space to only include Λ baryons that decay above MicroBooNE's detection thresholds, we obtain a flux averaged cross section of 2.0_{-1.7}^{+2.2}×10^{-40} cm^{2}/Ar, where statistical and systematic uncertainties are combined.
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Affiliation(s)
- P Abratenko
- Tufts University, Medford, Massachusetts 02155, USA
| | - D Andrade Aldana
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - J Anthony
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - L Arellano
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Asaadi
- University of Texas, Arlington, Texas 76019, USA
| | - A Ashkenazi
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - S Balasubramanian
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - B Baller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Barr
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - J Barrow
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - V Basque
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | | | - S Berkman
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - A Bhanderi
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - M Bhattacharya
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Bishai
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Blake
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - B Bogart
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - T Bolton
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - J Y Book
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - L Camilleri
- Columbia University, New York, New York 10027, USA
| | - D Caratelli
- University of California, Santa Barbara, California 93106, USA
| | - I Caro Terrazas
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - F Cavanna
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Cerati
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y Chen
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J M Conrad
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - M Convery
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - L Cooper-Troendle
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - J I Crespo-Anadón
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid E-28040, Spain
| | - M Del Tutto
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S R Dennis
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - P Detje
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - A Devitt
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - R Diurba
- Universität Bern, Bern CH-3012, Switzerland
| | - Z Djurcic
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - R Dorrill
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - K Duffy
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - S Dytman
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - B Eberly
- University of Southern Maine, Portland, Maine 04104, USA
| | | | - J J Evans
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - R Fine
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O G Finnerud
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - W Foreman
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - B T Fleming
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - N Foppiani
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - D Franco
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - A P Furmanski
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - S Gardiner
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Ge
- Columbia University, New York, New York 10027, USA
| | - S Gollapinni
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - O Goodwin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - E Gramellini
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - P Green
- The University of Manchester, Manchester M13 9PL, United Kingdom
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - H Greenlee
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Gu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - R Guenette
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - P Guzowski
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Hagaman
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - O Hen
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - R Hicks
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - C Hilgenberg
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - B Irwin
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - R Itay
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C James
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - X Ji
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - L Jiang
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - J H Jo
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - R A Johnson
- University of Cincinnati, Cincinnati, Ohio 45221, USA
| | - Y-J Jwa
- Columbia University, New York, New York 10027, USA
| | - D Kalra
- Columbia University, New York, New York 10027, USA
| | - N Kamp
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - G Karagiorgi
- Columbia University, New York, New York 10027, USA
| | - W Ketchum
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Kirby
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Kobilarcik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - I Kreslo
- Universität Bern, Bern CH-3012, Switzerland
| | - M B Leibovitch
- University of California, Santa Barbara, California 93106, USA
| | - I Lepetic
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - J-Y Li
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - K Li
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Y Li
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - K Lin
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - B R Littlejohn
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - W C Louis
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - X Luo
- University of California, Santa Barbara, California 93106, USA
| | - C Mariani
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - D Marsden
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Marshall
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - N Martinez
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - D A Martinez Caicedo
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - K Mason
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mastbaum
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - N McConkey
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - V Meddage
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - K Miller
- University of Chicago, Chicago, Illinois 60637, USA
| | - J Mills
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mogan
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - T Mohayai
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Mooney
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - A F Moor
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - C D Moore
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L Mora Lepin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Mousseau
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | | | - D Naples
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Navrer-Agasson
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - N Nayak
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Nebot-Guinot
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - J Nowak
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - M Nunes
- Syracuse University, Syracuse, New York 13244, USA
| | - N Oza
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O Palamara
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - N Pallat
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - V Paolone
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Papadopoulou
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - V Papavassiliou
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - H B Parkinson
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - S F Pate
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - N Patel
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - Z Pavlovic
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Piasetzky
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - I D Ponce-Pinto
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - I Pophale
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - S Prince
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - X Qian
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - J L Raaf
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - V Radeka
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Rafique
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - M Reggiani-Guzzo
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Ren
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - L Rochester
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Rodriguez Rondon
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - M Rosenberg
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Ross-Lonergan
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | | | - G Scanavini
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - D W Schmitz
- University of Chicago, Chicago, Illinois 60637, USA
| | - A Schukraft
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Seligman
- Columbia University, New York, New York 10027, USA
| | - M H Shaevitz
- Columbia University, New York, New York 10027, USA
| | - R Sharankova
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Shi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - E L Snider
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Soderberg
- Syracuse University, Syracuse, New York 13244, USA
| | | | - J Spitz
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - M Stancari
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J St John
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Strauss
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S Sword-Fehlberg
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - A M Szelc
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - W Tang
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - N Taniuchi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - K Terao
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C Thorpe
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - D Torbunov
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - D Totani
- University of California, Santa Barbara, California 93106, USA
| | - M Toups
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y-T Tsai
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Tyler
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - M A Uchida
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - T Usher
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - B Viren
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Weber
- Universität Bern, Bern CH-3012, Switzerland
| | - H Wei
- Louisiana State University, Baton Rouge, Louisiana 70803, USA
| | - A J White
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Z Williams
- University of Texas, Arlington, Texas 76019, USA
| | - S Wolbers
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Wongjirad
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Wospakrik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - K Wresilo
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - N Wright
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - W Wu
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Yandel
- University of California, Santa Barbara, California 93106, USA
| | - T Yang
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L E Yates
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - H W Yu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - G P Zeller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Zennamo
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - C Zhang
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
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Xu B, Jin Z, Shi L, Zhang H, Liu Q, Qin P, Jiang K, Wang J, Tang W, Xia W. Two types of ultrafast mode-locking operations from an Er-doped fiber laser based on germanene nanosheets. Front Optoelectron 2023; 16:13. [PMID: 37284945 DOI: 10.1007/s12200-023-00068-1] [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] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 04/17/2023] [Indexed: 06/08/2023]
Abstract
As a member of Xenes family, germanene has excellent nonlinear saturable absorption characteristics. In this work, we prepared germanene nanosheets by liquid phase exfoliation and measured their saturation intensity as 0.6 GW/cm2 with a modulation depth of 8%. Then, conventional solitons with a pulse width of 946 fs and high-energy noise-like pulses with a pulse width of 784 fs were obtained by using germanene nanosheet as a saturable absorber for a mode-locked Erbium-doped fiber laser. The characteristics of the two types of pulses were investigated experimentally. The results reveal that germanene has great potential for modulation devices in ultrafast lasers and can be used as a material for creation of excellent nonlinear optical devices to explore richer applications in ultrafast photonics.
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Affiliation(s)
- Baohao Xu
- School of Physics and Technology, University of Jinan, Jinan, 250022, China
| | - Zhiyuan Jin
- School of Physics and Technology, University of Jinan, Jinan, 250022, China
| | - Lie Shi
- School of Physics and Technology, University of Jinan, Jinan, 250022, China
| | - Huanian Zhang
- School of Physics and Optoelectronic Engineering, Shandong University of Technology, Zibo, 255049, China
| | - Qi Liu
- Shandong Huaguang Optoelectronics Co., Ltd., Jinan, 250101, China
| | - Peng Qin
- Shandong Huaguang Optoelectronics Co., Ltd., Jinan, 250101, China
| | - Kai Jiang
- School of Physics and Technology, University of Jinan, Jinan, 250022, China
| | - Jing Wang
- School of Physics and Technology, University of Jinan, Jinan, 250022, China
| | - Wenjing Tang
- School of Physics and Technology, University of Jinan, Jinan, 250022, China.
| | - Wei Xia
- School of Physics and Technology, University of Jinan, Jinan, 250022, China.
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Zeng W, Zhou SL, Guo JX, Tang W. [Metal artifact reduction and clinical verification in oral and maxillofacial region based on deep learning]. Zhonghua Kou Qiang Yi Xue Za Zhi 2023; 58:542-548. [PMID: 37271998 DOI: 10.3760/cma.j.cn112144-20230302-00067] [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] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Objective: To construct a kind of neural network for eliminating the metal artifacts in CT images by training the generative adversarial networks (GAN) model, so as to provide reference for clinical practice. Methods: The CT data of patients treated in the Department of Radiology, West China Hospital of Stomatology, Sichuan University from January 2017 to June 2022 were collected. A total of 1 000 cases of artifact-free CT data and 620 cases of metal artifact CT data were obtained, including 5 types of metal restorative materials, namely, fillings, crowns, titanium plates and screws, orthodontic brackets and metal foreign bodies. Four hundred metal artifact CT data and 1 000 artifact-free CT data were utilized for simulation synthesis, and 1 000 pairs of simulated artifacts and metal images and simulated metal images (200 pairs of each type) were constructed. Under the condition that the data of the five metal artifacts were equal, the entire data set was randomly (computer random) divided into a training set (800 pairs) and a test set (200 pairs). The former was used to train the GAN model, and the latter was used to evaluate the performance of the GAN model. The test set was evaluated quantitatively and the quantitative indexes were root-mean-square error (RMSE) and structural similarity index measure (SSIM). The trained GAN model was employed to eliminate the metal artifacts from the CT data of the remaining 220 clinical cases of metal artifact CT data, and the elimination results were evaluated by two senior attending doctors using the modified LiKert scale. Results: The RMSE values for artifact elimination of fillings, crowns, titanium plates and screws, orthodontic brackets and metal foreign bodies in test set were 0.018±0.004, 0.023±0.007, 0.015±0.003, 0.019±0.004, 0.024±0.008, respectively (F=1.29, P=0.274). The SSIM values were 0.963±0.023, 0.961±0.023, 0.965±0.013, 0.958±0.022, 0.957±0.026, respectively (F=2.22, P=0.069). The intra-group correlation coefficient of 2 evaluators was 0.972. For 220 clinical cases, the overall score of the modified LiKert scale was (3.73±1.13), indicating a satisfactory performance. The scores of modified LiKert scale for fillings, crowns, titanium plates and screws, orthodontic brackets and metal foreign bodies were (3.68±1.13), (3.67±1.16), (3.97±1.03), (3.83±1.14), (3.33±1.12), respectively (F=1.44, P=0.145). Conclusions: The metal artifact reduction GAN model constructed in this study can effectively remove the interference of metal artifacts and improve the image quality.
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Affiliation(s)
- W Zeng
- Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University & State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases, Chengdu 610041, China
| | - S L Zhou
- Department of Oral and Maxillofacial Surgery, School of Stomatology, The Fourth Military Medical University & State Key Laboratory of Military Stomatology & National Clinical Research Center for Oral Diseases & Shaanxi Clinical Research Center for Oral Diseases, Xi'an 710032, China
| | - J X Guo
- Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu 610041, China
| | - W Tang
- Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University & State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases, Chengdu 610041, China
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Zong W, Ren D, Huang M, Sun K, Feng J, Zhao J, Xiao D, Xie W, Liu S, Zhang H, Qiu R, Tang W, Yang R, Chen H, Xie X, Chen L, Liu YG, Guo J. Corrigendum. New Phytol 2023; 238:2247-2250. [PMID: 37002836 PMCID: PMC10479992 DOI: 10.1111/nph.18843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
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Tang W, Zhu D, Wu F, Xu JF, Yang JP, Deng ZP, Chen XB, Papi A, Qu JM. Intravenous N-acetylcysteine in respiratory disease with abnormal mucus secretion. Eur Rev Med Pharmacol Sci 2023; 27:5119-5127. [PMID: 37318485 DOI: 10.26355/eurrev_202306_32628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
OBJECTIVE Evidence for the mucolytic and expectorant efficacy of intravenous (IV) N-acetylcysteine (NAC) is limited. This study aimed to evaluate in a large, multicenter, randomized, controlled, subject, and rater-blinded study whether IV NAC is superior to placebo and non-inferior to ambroxol in improving sputum viscosity and expectoration difficulty. PATIENTS AND METHODS A total of 333 hospitalized subjects from 28 centers in China with respiratory disease (such as acute bronchitis, chronic bronchitis and exacerbations, emphysema, mucoviscidosis, and bronchiectasis) and abnormal mucus secretion were randomly allocated in a 1:1:1 ratio to receive NAC 600 mg, ambroxol hydrochloride 30 mg, or placebo as an IV infusion twice daily for 7 days. Mucolytic and expectorant efficacy was assessed by ordinal categorical 4-point scales and analyzed by stratified and modified Mann-Whitney U statistics. RESULTS NAC showed consistent and statistically significant superiority to placebo and non-inferiority to ambroxol in change from baseline to day 7 in both sputum viscosity scores [mean (SD) difference 0.24 (0.763), p<0.001 vs. placebo] and expectoration difficulty score [mean (SD) difference 0.29 (0.783), p=0.002 vs. placebo]. Safety findings confirm the good tolerability profile of IV NAC reported from previous small studies, and no new safety concerns were identified. CONCLUSIONS This is the first large, robust study of the efficacy of IV NAC in respiratory diseases with abnormal mucus secretion. It provides new evidence for IV NAC administration in this indication in clinical situations where the IV route is preferred.
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Affiliation(s)
- W Tang
- Department of Pulmonary and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
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Tang W, Xu W, Zhong M, Zhang Z. Slightly doped hydroxyapatite pigments of subtractive color with high near-infrared reflectance. J SOLID STATE CHEM 2023. [DOI: 10.1016/j.jssc.2023.123947] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/03/2023]
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Wu W, Wang A, Zhan Q, Hu Z, Tang W, Zhang L, Luo J. A Molecularly Engineered Cathode Lithium Compensation Agent for High Energy Density Batteries. Small 2023:e2301737. [PMID: 37191324 DOI: 10.1002/smll.202301737] [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: 02/27/2023] [Revised: 05/03/2023] [Indexed: 05/17/2023]
Abstract
Prelithiating cathode is considered as one of the most promising lithium compensation strategies for practical high energy density batteries. Whereas most of reported cathode lithium compensation agents are deficient owing to their poor air-stability, residual insulating solid, or formidable Li-extracting barrier. Here, this work proposes molecularly engineered 4-Fluoro-1,2-dihydroxybenzene Li salt (LiDF) with high specific capacity (382.7 mAh g-1 ) and appropriate delithiation potential (3.6-4.2 V) as an air-stable cathode Li compensation agent. More importantly, the charged residue 4-Fluoro-1,2-benzoquinone (BQF) can synergistically work as an electrode/electrolyte interface forming additive to build uniform and robust LiF-riched cathode/anode electrolyte interfaces (CEI/SEI). Consequently, less Li loss and retrained electrolyte decomposition are achieved. With 2 wt% 4-Fluoro-1,2-dihydroxybenzene Li salt initially blended within the cathode, 1.3 Ah pouch cells with NCM (Ni92) cathode and SiO/C (550 mAh g-1 ) anode can keep 91% capacity retention after 350 cycles at 1 C rate. Moreover, the anode free of NCM622+LiDF||Cu cell achieves 78% capacity retention after 100 cycles with the addition of 15 wt% LiDF. This work provides a feasible sight for the rational designing Li compensation agent at molecular level to realize high energy density batteries.
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Affiliation(s)
- Wei Wu
- State Key Laboratory of Metal Matrix Composites, School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
- Key Laboratory for Green Chemical Technology of Ministry of Education, School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072, China
| | - Aoxuan Wang
- Key Laboratory for Green Chemical Technology of Ministry of Education, School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072, China
| | - Qiushe Zhan
- CAS Key Laboratory of Green Process and Engineering, Institute of Process Engineering, Chinese Academy of Sciences, Beijing, 100190, China
| | - Zhenglin Hu
- Key Laboratory for Green Chemical Technology of Ministry of Education, School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072, China
| | - Wenjing Tang
- State Key Laboratory of Metal Matrix Composites, School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Lan Zhang
- CAS Key Laboratory of Green Process and Engineering, Institute of Process Engineering, Chinese Academy of Sciences, Beijing, 100190, China
| | - Jiayan Luo
- State Key Laboratory of Metal Matrix Composites, School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
- Global Institute of Future Technology, Shanghai Jiao Tong University, Shanghai, 200240, China
- Zhangjiang Institute for Advanced Study, Shanghai Jiao Tong University, Shanghai, 200240, China
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Zhou L, Sun G, Chen R, Chen J, Fang S, Xu Q, Tang W, Dai R, Zhang Z, An Y, Tang X, Zhao X. An early-onset SLE patient with a novel paternal inherited BACH2 mutation. J Clin Immunol 2023:10.1007/s10875-023-01506-7. [PMID: 37148421 DOI: 10.1007/s10875-023-01506-7] [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: 02/26/2023] [Accepted: 04/27/2023] [Indexed: 05/08/2023]
Abstract
BACH2-related immunodeficiency and autoimmunity (BRIDA) is an inborn error of immunity, newly reported in 2017, presenting with symptoms of immunoglobulin deficiency and ongoing colitis. Studies using a mouse model have demonstrated that BACH2 deficiency predisposes individuals to systemic lupus erythematosus (SLE); however, no BACH2 deficiency has been reported in SLE patients. Here we describe a patient with BRIDA presenting with early-onset SLE, juvenile dermatomyositis, and IgA deficiency. Whole exome sequencing analysis of the patient and her parents revealed a novel heterozygous point mutation in BACH2, c.G1727T, resulting in substitution of a highly conserved arginine with leucine (R576L), which is predicted to be deleterious, in the patient and her father. Reduced BACH2 expression and deficient transcriptional repression of the BACH2 target, BLIMP1, were detected in PBMCs or lymphoblastoid cell lines of our patient. Notably, extreme reduction of memory B cells was detected in the patient's father, although he had no obvious symptoms. SLE symptoms and recurrent fever were relieved by treatment with prednisone combined with tofacitinib. Thus, we present the second report of BRIDA and demonstrate that BACH2 may be a monogenic cause of SLE.
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Affiliation(s)
- Lina Zhou
- National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Infection and Immunity, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Gan Sun
- National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Infection and Immunity, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Ran Chen
- National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Infection and Immunity, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Junjie Chen
- National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Infection and Immunity, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Shuyu Fang
- National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Infection and Immunity, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Qiling Xu
- National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Infection and Immunity, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Wenjing Tang
- National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Infection and Immunity, Children's Hospital of Chongqing Medical University, Chongqing, China
- Division of Rheumatology and Immunology, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Rongxin Dai
- National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Infection and Immunity, Children's Hospital of Chongqing Medical University, Chongqing, China
- Division of Rheumatology and Immunology, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Zhiyong Zhang
- National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Infection and Immunity, Children's Hospital of Chongqing Medical University, Chongqing, China
- Division of Rheumatology and Immunology, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Yunfei An
- National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Infection and Immunity, Children's Hospital of Chongqing Medical University, Chongqing, China
- Division of Rheumatology and Immunology, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Xuemei Tang
- National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Infection and Immunity, Children's Hospital of Chongqing Medical University, Chongqing, China
- Division of Rheumatology and Immunology, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Xiaodong Zhao
- National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Infection and Immunity, Children's Hospital of Chongqing Medical University, Chongqing, China.
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42
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Hofmeyer M, Haas G, Kransdorf E, Ewald G, Morris A, Owens A, Lowes B, Stoller D, Tang W, Garg S, Trachtenberg B, Shah P, Pamboukian S, Sweitzer N, Wheeler M, Wilcox J, Katz S, Pan S, Jimenez J, Smart F, Wang J, Gottlieb S, Judge D, Moore C, Huggins G, Jordan E, Kinnamon D, Ni H, Hershberger R. Genetic Signature of Dilated Cardiomyopathy Severity: The DCM Precision Medicine Study. J Heart Lung Transplant 2023. [DOI: 10.1016/j.healun.2023.02.1674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/05/2023] Open
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43
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Longinow J, Il'Giovine Z, Martens P, Higgins A, Soltesz E, Tong M, Estep J, Starling R, Tang W, Hanna M, Lee R. Hemodynamic Response after Intra-Aortic Balloon Counter-Pulsation in Cardiac Amyloidosis and Cardiogenic Shock. J Heart Lung Transplant 2023. [DOI: 10.1016/j.healun.2023.02.821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/05/2023] Open
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44
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Jiang DH, Tang W. [The theory of unresponsive pulse by Wang Ji : The historical position of his Yun Qi Yi Lan]. Zhonghua Yi Shi Za Zhi 2023; 53:67-73. [PMID: 37183619 DOI: 10.3760/cma.j.cn112155-20221025-00153] [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] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
Wang Ji (1463-1539) was a well-known doctor of the Xin An Medical School in the Ming Dynasty. He and his representative masterpiece Yun Qi Yi Lan are particularly important in the medical history of Yunqi, which refers to the principles of Air (Qi) regulation, influencing almost all life in nature. In terms of the theory "nonresponsive pulse matching the South and the North in the ten Stem years" (Nan Bei Zheng Bu Ying Mai), Wang Ji differentiated and analysed the changes of this theory after the Jin and Yuan Dynasties and traced it back to the classics the Inner canon of Huangdi (Huang Di Nei Jing), based on Su Wen Ru Shi Yun Qi Lun Ao, Huang Di Nei Jing and other relevant reference materials. This paper examined the evolution of the theory of unresponsive pulse in the ancient and modern literature. It was found that after the Song Dynasty, the theory of nonresponsive pulse in the South-North in the ten Stem years was developed into two main schools. One was represented by Cheng Wuji and Liu Wansu, followed with Zhang Jingyue, Li Yanshi, Yao Zhian, Lu Guanquan, Wu Qian, Huang Yuanyu, Xue Fuchen and Zhou Xuehai, who argued that the nonresponsive pulse was determined by the position of Shaoyin. Another was represented by Liu Wenshu, followed with Wang Ji, Li Zhongzi, Zhang Zhicong and Ren Yingqiu, who believed that Shaoyin always stands in the middle, Jueyin and Taiyin are always on the two sides of Shaoyin.
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Affiliation(s)
- D H Jiang
- College of Acupuncture and Moxibustion, Anhui University of Chinese Medicine, Hefei 230038, China
| | - W Tang
- College of Acupuncture and Moxibustion, Anhui University of Chinese Medicine, Hefei 230038, China
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45
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Liang M, Zhao SJ, Zhou LN, Xu XJ, Wang YW, Niu L, Wang HH, Tang W, Wu N. [The performance of digital chest radiographs in the detection and diagnosis of pulmonary nodules and the consistency among readers]. Zhonghua Zhong Liu Za Zhi 2023; 45:265-272. [PMID: 36944548 DOI: 10.3760/cma.j.cn112152-20220304-00150] [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] [Subscribe] [Scholar Register] [Indexed: 03/23/2023]
Abstract
Objective: To investigate the detection and diagnostic efficacy of chest radiographs for ≤30 mm pulmonary nodules and the factors affecting them, and to compare the level of consistency among readers. Methods: A total of 43 patients with asymptomatic pulmonary nodules who consulted in Cancer Hospital, Chinese Academy of Medical Sciences from 2012 to 2014 and had chest CT and X-ray chest radiographs during the same period were retrospectively selected, and one nodule ≤30 mm was visible on chest CT images in the whole group (total 43 nodules in the whole group). One senior radiologist with more than 20 years of experience in imaging diagnosis reviewed CT images and recording the size, morphology, location, and density of nodules was selected retrospectively. Six radiologists with different levels of experience (2 residents, 2 attending physicians and 2 associate chief physicians independently reviewed the chest images and recorded the time of review, nodule detection, and diagnostic opinion. The CT imaging characteristics of detected and undetected nodules on X images were compared, and the factors affecting the detection of nodules on X-ray images were analyzed. Detection sensitivity and diagnosis accuracy rate of 6 radiologists were calculated, and the level of consistency among them was compared to analyze the influence of radiologists' seniority and reading time on the diagnosis results. Results: The number of nodules detected by all 6 radiologists was 17, with a sensitivity of detection of 39.5%(17/43). The number of nodules detected by ≥5, ≥4, ≥3, ≥2, and ≥1 physicians was 20, 21, 23, 25, and 28 nodules, respectively, with detection sensitivities of 46.5%, 48.8%, 53.5%, 58.1%, and 65.1%, respectively. Reasons for false-negative result of detection on X-ray images included the size, location, density, and morphology of the nodule. The sensitivity of detecting ≤30 mm, ≤20 mm, ≤15 mm, and ≤10 mm nodules was 46.5%-58.1%, 45.9%-54.1%, 36.0%-44.0%, and 36.4% for the 6 radiologists, respectively; the diagnosis accuracy rate was 19.0%-85.0%, 16.7%-6.5%, 18.2%-80.0%, and 0%-75.0%, respectively. The consistency of nodule detection among 6 doctors was good (Kappa value: 0.629-0.907) and the consistency of diagnostic results among them was moderate or poor (Kappa value: 0.350-0.653). The higher the radiologist's seniority, the shorter the time required to read the images. The reading time and the seniority of the radiologists had no significant influence on the detection and diagnosis results (P>0.05). Conclusions: The ability of radiographs to detect lung nodules ≤30 mm is limited, and the ability to determine the nature of the nodules is not sufficient, and the increase in reading time and seniority of the radiologists will not improve the diagnostic accuracy. X-ray film exam alone is not suitable for lung cancer diagnosis.
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Affiliation(s)
- M Liang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - S J Zhao
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - L N Zhou
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - X J Xu
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Y W Wang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - L Niu
- Radiology Department, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100020, China
| | - H H Wang
- Radiology Department, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100020, China
| | - W Tang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - N Wu
- Department of Nuclear Medicine (PET-CT Center), National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Hebei Cancer Hospital, Chinese Academy of Medical Sciences, Langfang 065001, China
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46
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Jiang C, Tang W, Hou X, Li H. Recurrent syncope in an 84-year-old man. J Postgrad Med 2023; 69:111-113. [PMID: 36861546 DOI: 10.4103/jpgm.jpgm_414_22] [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] [Indexed: 02/25/2023] Open
Abstract
An 84-year-old man with hypertension and type 2 diabetes presented with recurrent transient loss of consciousness within 2 hours after dinner at home. Physical examination, electrocardiogram, and laboratory studies were unremarkable except hypotension. Blood pressures were measured in different postures and within 2 hours after meal, but neither orthostatic hypotension nor postprandial hypotension was detected. Further, history taking revealed that the patient was tube-fed with a fluid food pump with an inappropriate rapid infusion rate of 1500 mL per minute at home. He was eventually diagnosed as having syncope due to postprandial hypotension, which was caused by the inappropriate way of tube feeding. The family was educated about appropriate way of tube-feeding and the patient did not develop any episode of syncope during a two-year follow-up. This case highlights the importance of careful history taking in the diagnostic evaluation of syncope and the increased risk of syncope due to postprandial hypotension in the elderly.
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Affiliation(s)
- C Jiang
- Department of Internal Medicine and Geriatrics, Beijing Friendship Hospital, Capital Medical University, Beijing, India
| | - W Tang
- Department of Internal Medicine and Geriatrics, Beijing Friendship Hospital, Capital Medical University, Beijing, India
| | - X Hou
- Department of Internal Medicine and Geriatrics, Beijing Friendship Hospital, Capital Medical University, Beijing, India
| | - H Li
- Department of Internal Medicine and Geriatrics, Beijing Friendship Hospital, Capital Medical University, Beijing, India
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47
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Yu YX, Wu ZJ, Tang W, Liao R. [A comparison of current guidelines for the management of intrahepatic cholangiocarcinoma worldwide]. Zhonghua Wai Ke Za Zhi 2023; 61:297-304. [PMID: 36822586 DOI: 10.3760/cma.j.cn112139-20221125-00495] [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] [Subscribe] [Scholar Register] [Indexed: 02/25/2023]
Abstract
Intrahepatic cholangiocarcinoma (ICC) is the second most common human liver malignancy and its incidence rate has been gradually increasing worldwide over the past decades. Surgical resection (R0 resection) is the preferred potentially curative treatment for ICC patients. However, due to its conceal clinical features and high invasiveness, most patients have lost the opportunity for surgical resection at the time of diagnosis. In recent years, with the rapid development of targeted therapy and immunotherapy, which is represented by immune checkpoint inhibitors, clinicians are expected to provide more effective treatment options for patients with mid-stage or advanced ICC. At present, there are still controversial opinions on different guidelines regarding preoperative biliary drainage, the extent of hepatectomy, the definition of R0 resection, the width of the resection margin, lymph node dissection, postoperative recurrence, adjuvant therapy, etc. In this review, 12 guidelines or expert consensus published worldwide from 2012 to 2022 (including 4 Chinese guidelines, 4 European guidelines, 2 American guidelines and 2 Japanese guidelines) were retrieved. Focusing on sorting and comparing the current views on clinical management of ICC in different guidelines, this review aims to provide reference information for ICC clinical management and decision-making.
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Affiliation(s)
- Y X Yu
- Department of Hepatobiliary Surgery, the First Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Z J Wu
- Department of Hepatobiliary Surgery, the First Hospital of Chongqing Medical University, Chongqing 400016, China
| | - W Tang
- National Center for Global Health and Medicine, Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, the University of Tokyo Hospital, Tokyo 162-8655, Japan
| | - R Liao
- Department of Hepatobiliary Surgery, the First Hospital of Chongqing Medical University, Chongqing 400016, China
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48
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Ji MM, Shen YG, Gong JC, Tang W, Xu XQ, Zheng Z, Chen SY, He Y, Zheng X, Zhao LD, Zhao WL, Wu W. [Efficiency and safety analysis of Plerixafor combined with granulocyte colony-stimulating factor on autologous hematopoietic stem cell mobilization in lymphoma]. Zhonghua Xue Ye Xue Za Zhi 2023; 44:112-117. [PMID: 36948864 PMCID: PMC10033277 DOI: 10.3760/cma.j.issn.0253-2727.2023.02.005] [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] [Grants] [Subscribe] [Scholar Register] [Indexed: 03/24/2023]
Abstract
Objective: To evaluate the advantages and safety of Plerixafor in combination with granulocyte colony-stimulating factor (G-CSF) in autologous hematopoietic stem cell mobilization of lymphoma. Methods: Lymphoma patients who received autologous hematopoietic stem cell mobilization with Plerixafor in combination with G-CSF or G-CSF alone were obtained. The clinical data, the success rate of stem cell collection, hematopoietic reconstitution, and treatment-related adverse reactions between the two groups were evaluated retrospectively. Results: A total of 184 lymphoma patients were included in this analysis, including 115 cases of diffuse large B-cell lymphoma (62.5%) , 16 cases of classical Hodgkin's lymphoma (8.7%) , 11 cases of follicular non-Hodgkin's lymphoma (6.0%) , 10 cases of angioimmunoblastic T-cell lymphoma (5.4%) , 6 cases of mantle cell lymphoma (3.3%) , and 6 cases of anaplastic large cell lymphoma (3.3%) , 6 cases of NK/T-cell lymphoma (3.3%) , 4 cases of Burkitt's lymphoma (2.2%) , 8 cases of other types of B-cell lymphoma (4.3%) , and 2 cases of other types of T-cell lymphoma (1.1%) ; 31 patients had received radiotherapy (16.8%) . The patients in the two groups were recruited with Plerixafor in combination with G-CSF or G-CSF alone. The baseline clinical characteristics of the two groups were basically similar. The patients in the Plerixafor in combination with the G-CSF mobilization group were older, and the number of recurrences and third-line chemotherapy was higher. 100 patients were mobilized with G-CSF alone. The success rate of the collection was 74.0% for one day and 89.0% for two days. 84 patients in the group of Plerixafor combined with G-CSF were recruited successfully with 85.7% for one day and 97.6% for two days. The success rate of mobilization in the group of Plerixafor combined with G-CSF was substantially higher than that in the group of G-CSF alone (P=0.023) . The median number of CD34(+) cells obtained in the mobilization group of Plerixafor combined with G-CSF was 3.9×10(6)/kg. The median number of CD34(+) cells obtained in the G-CSF Mobilization group alone was 3.2×10(6)/kg. The number of CD34(+) cells collected by Plerixafor combined with G-CSF was considerably higher than that in G-CSF alone (P=0.001) . The prevalent adverse reactions in the group of Plerixafor combined with G-CSF were grade 1-2 gastrointestinal reactions (31.2%) and local skin redness (2.4%) . Conclusion: The success rate of autologous hematopoietic stem cell mobilization in lymphoma patients treated with Plerixafor combined with G-CSF is significantly high. The success rate of collection and the absolute count of CD34(+) stem cells were substantially higher than those in the group treated with G-CSF alone. Even in older patients, second-line collection, recurrence, or multiple chemotherapies, the combined mobilization method also has a high success rate of mobilization.
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Affiliation(s)
- M M Ji
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Y G Shen
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - J C Gong
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - W Tang
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - X Q Xu
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Z Zheng
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - S Y Chen
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Y He
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - X Zheng
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - L D Zhao
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - W L Zhao
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - W Wu
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
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49
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Wang Y, Tao H, Tang W, Wu S, Tang Y, Liu L. Succinate level is increased and succinate dehydrogenase exerts forward and reverse catalytic activities in lipopolysaccharides-stimulated cardiac tissue: The protective role of dimethyl malonate. Eur J Pharmacol 2023; 940:175472. [PMID: 36549501 DOI: 10.1016/j.ejphar.2022.175472] [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: 08/08/2022] [Revised: 12/09/2022] [Accepted: 12/15/2022] [Indexed: 12/24/2022]
Abstract
This study aimed to investigate the alterations of myocardial succinate and fumarate levels with or without succinate dehydrogenase (SDH) inhibitor dimethyl malonate during 24 h of lipopolysaccharides (LPS) challenge, as well as the effects of dimethyl malonate on the impaired cardiac tissue. Myocardial succinate and fumarate levels were increased in the initial 9 h of LPS challenge. During this time, dimethyl malonate increased the succinate level, decreased the fumarate level, aggravated the cardiac dysfunction, reduced the oxidative stress, had little effect on interleukin-1β production, promoted interleukin-10 production and bothered the ATP production. Co-treatment with exogenous succinate significantly increased interleukin-1β production in this period. After 12 h of LPS challenge, myocardial the succinate level increased sharply, while the fumarate level gradually decreased. During 12-24 h of LPS challenge, dimethyl malonate effectively reduced the succinate level, increased the fumarate level, improved cardiac dysfunction, inhibited interleukin-1β production, and had little effect on oxidative stress, interleukin-10 production, and ATP production. LPS challenge also significantly increased the myocardial succinate receptor 1 expression and circulating succinate level. Inhibition of succinate receptor 1 significantly reduced the mRNA expression of interleukin-1β. In conclusion, the current study suggests that myocardial succinate accumulates during LPS challenge, and that SDH activity may be transformed (from forward to reversed) and involved in a line of stress response. Dimethyl malonate inhibits SDH and, depending on the time of treatment, reduces LPS-induced cardiac impairment. Furthermore, accumulated succinate exerts pro-inflammatory effects partly via succinate receptor 1 signaling.
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Affiliation(s)
- Yu Wang
- Department of Cardiovascular Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China
| | - Hongmei Tao
- Department of Cardiovascular Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China
| | - Wenjing Tang
- Department of Anesthesiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China
| | - Siqi Wu
- Department of Anesthesiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China
| | - Yin Tang
- Department of Anesthesiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China
| | - Ling Liu
- Department of Anesthesiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China.
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50
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Zhou X, Tang W, He M, Xiao X, Wang T, Cheng S, Zhang L. Combined removal of SO 3 and HCl by modified Ca(OH) 2 from coal-fired flue gas. Sci Total Environ 2023; 857:159466. [PMID: 36257446 DOI: 10.1016/j.scitotenv.2022.159466] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [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: 09/06/2022] [Revised: 10/01/2022] [Accepted: 10/12/2022] [Indexed: 06/16/2023]
Abstract
As treatments for mainstream pollutants in coal-fired power plants have been established, the control of non-conventional pollutants, such as SO3 and HCl, is gradually gaining attention. In this study, combined SO3 and HCl removal is proposed based on SO3 removal by absorber injection. However, it is challenging to selectively absorb SO3 and HCl from SO2-rich atmospheres. Therefore, Ca(OH)2 was modified via ball milling and doping with CuO for the combined removal of SO3 and HCl. The results showed that ball milling reduced the particle and grain sizes of Ca(OH)2, which increased the active sites of Ca(OH)2 and prolonged reaction time. After modification by ball milling, SO3 absorption per mg of Ca(OH)2 increased by 40 %. However, HCl removal efficiency was difficult to improve by modifying Ca(OH)2 using only ball milling under SO3 and SO2 atmospheres. Therefore, the dechlorination capacity of Ca(OH)2 was improved by adding ions during the ball milling process. Doping of Ca(OH)2 with Cu2+ changed its crystal structure, weakened the diffusion resistance of HCl, and improved Ca(OH)2 utilization. Additionally, it increased the energy of Ca(OH)2 to adsorb HCl.
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Affiliation(s)
- Xiaohan Zhou
- National Engineering Laboratory of Coal-fired Pollutants Emission Reduction, School of Energy and Power Engineering, Shandong University, Jinan 250061, China
| | - Wenjing Tang
- National Engineering Laboratory of Coal-fired Pollutants Emission Reduction, School of Energy and Power Engineering, Shandong University, Jinan 250061, China
| | - Minqiang He
- Xi'an Thermal Power Research Institute Co., Ltd., China
| | - Xia Xiao
- National Engineering Laboratory of Coal-fired Pollutants Emission Reduction, School of Energy and Power Engineering, Shandong University, Jinan 250061, China
| | - Tao Wang
- National Engineering Laboratory of Coal-fired Pollutants Emission Reduction, School of Energy and Power Engineering, Shandong University, Jinan 250061, China
| | - Shanjie Cheng
- National Engineering Laboratory of Coal-fired Pollutants Emission Reduction, School of Energy and Power Engineering, Shandong University, Jinan 250061, China
| | - Liqiang Zhang
- National Engineering Laboratory of Coal-fired Pollutants Emission Reduction, School of Energy and Power Engineering, Shandong University, Jinan 250061, China.
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