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Chen P, Wang J, Tang G, Chen G, Xiao S, Guo Z, Qi Z, Wang J, Wang Y. Large-scale network abnormality in behavioral addiction. J Affect Disord 2024; 354:743-751. [PMID: 38521138 DOI: 10.1016/j.jad.2024.03.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 03/01/2024] [Accepted: 03/09/2024] [Indexed: 03/25/2024]
Abstract
BACKGROUND Researchers have endeavored to ascertain the network dysfunction associated with behavioral addiction (BA) through the utilization of resting-state functional connectivity (rsFC). Nevertheless, the identification of aberrant patterns within large-scale networks pertaining to BA has proven to be challenging. METHODS Whole-brain seed-based rsFC studies comparing subjects with BA and healthy controls (HC) were collected from multiple databases. Multilevel kernel density analysis was employed to ascertain brain networks in which BA was linked to hyper-connectivity or hypo-connectivity with each prior network. RESULTS Fifty-six seed-based rsFC publications (1755 individuals with BA and 1828 HC) were included in the meta-analysis. The present study indicate that individuals with BAs exhibit (1) hypo-connectivity within the fronto-parietal network (FN) and hypo- and hyper-connectivity within the ventral attention network (VAN); (2) hypo-connectivity between the FN and regions of the VAN, hypo-connectivity between the VAN and regions of the FN and default mode network (DMN), hyper-connectivity between the DMN and regions of the FN; (3) hypo-connectivity between the reward system and regions of the sensorimotor network (SS), DMN and VAN; (4) hypo-connectivity between the FN and regions of the SS, hyper-connectivity between the VAN and regions of the SS. CONCLUSIONS These findings provide impetus for a conceptual framework positing a model of BA characterized by disconnected functional coordination among large-scale networks.
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Affiliation(s)
- Pan Chen
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Junjing Wang
- Department of Applied Psychology, Guangdong University of Foreign Studies, Guangzhou 510006, China
| | - Guixian Tang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Guanmao Chen
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Shu Xiao
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Zixuan Guo
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Zhangzhang Qi
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Jurong Wang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Ying Wang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China.
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Guo Z, Wang H, Deng H, Xu W, Baghaei N, Lo CH, Liang HN. Breaking the Isolation: Exploring the Impact of Passthrough in Shared Spaces on Player Performance and Experience in VR Exergames. IEEE Trans Vis Comput Graph 2024; 30:2580-2590. [PMID: 38437094 DOI: 10.1109/tvcg.2024.3372114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/06/2024]
Abstract
VR exergames offer an engaging solution to combat sedentary behavior and promote physical activity. However, challenges emerge when playing these games in shared spaces, particularly due to the presence of bystanders. VR's passthrough functionality enables players to maintain awareness of their surrounding environment while immersed in VR gaming, rendering it a promising solution to improve users' awareness of the environment. This study investigates the passthrough's impact on player performance and experiences in shared spaces, involving an experiment with 24 participants that examines Space (Office vs. Corridor) and Passthrough Function (With vs. Without). Results reveal that Passthrough enhances game performance and environmental awareness while reducing immersion. Players prefer an open area to an enclosed room, whether with or without Passthrough, finding it more socially acceptable. Additionally, Passthrough appears to encourage participation among players with higher self-consciousness, potentially alleviating their concerns about being observed by bystanders. Our findings provide valuable insights for designing VR experiences in shared spaces, underscoring the potential of VR's passthrough to enhance user experiences and promote VR adoption in these environments.
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Guo Z, Han X, Kong T, Wu Y, Kang Y, Liu Y, Wang F. The mediation effects of nightmares and depression between insomnia and suicidal ideation in young adults. Sci Rep 2024; 14:9577. [PMID: 38670978 DOI: 10.1038/s41598-024-58774-5] [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] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Accepted: 04/03/2024] [Indexed: 04/28/2024] Open
Abstract
Suicide is prevalent among young adults, and epidemiological studies indicate that insomnia, nightmares, and depression are significantly associated with a high incidence of suicidal ideation (SI). However, the causal relationship between these factors and SI remains unclear. Therefore, the purpose of this study was to examine the association between nightmares and depression and insomnia and SI in young adults, as well as to develop a mediation model to investigate the causal relationship between insomnia, nightmare, depression, and SI. We assessed insomnia, nightmares, depression, and SI in 546 young adults using the Insomnia Severity Scale (ISI), Disturbing Dream and Nightmare Severity Scale (DDNSI), Depression Study Scale (CESD-20), and Columbia-Suicide Severity Rating Scale (C-SSRS). Using the Bootstrap method, the mediation effects of nightmares and depression between insomnia and SI were calculated. The results demonstrated that nightmares and depression fully mediated the relationship between insomnia and SI, including the chain-mediation of insomnia and SI between nightmare and depression with an effect value of 0.02, 95% CI 0.01-0.04, and depression as a mediator between insomnia and SI with an effect value of 0.22, 95% CI 0.15-0.29. This study found that depression and nightmares may be risk and predictive factors between insomnia and SI, which implies that the assessment and treatment of depression and the simple or linked effect of nightmares play crucial roles in preventing SI in young adults.
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Affiliation(s)
- Zixuan Guo
- Medical Neurobiology Lab, Inner Mongolia Medical University, Huhhot, 010110, China
- Beijing Hui-Long-Guan Hospital, Peking University, Beijing, 100096, China
| | - Xiaoli Han
- Clinical Nutrition Department, Friendship Hospital of Urumqi, Urumqi, 830049, China
| | - Tiantian Kong
- Xinjiang Key Laboratory of Neurological Disorder Research, The Second Affiliated Hospital of Xinjiang Medical University, Urumqi, 830063, China
| | - Yan Wu
- Beijing Hui-Long-Guan Hospital, Peking University, Beijing, 100096, China
| | - Yimin Kang
- Medical Neurobiology Lab, Inner Mongolia Medical University, Huhhot, 010110, China.
| | - Yanlong Liu
- School of Mental Health, Wenzhou Medical University, Wenzhou, 325035, China.
| | - Fan Wang
- Beijing Hui-Long-Guan Hospital, Peking University, Beijing, 100096, China.
- Xinjiang Key Laboratory of Neurological Disorder Research, The Second Affiliated Hospital of Xinjiang Medical University, Urumqi, 830063, China.
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Li X, Guo Z, Zhang X, Yang G. Layered Hydride LiH 4 with a Pressure-Insensitive Superconductivity. Inorg Chem 2024. [PMID: 38662198 DOI: 10.1021/acs.inorgchem.4c00520] [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: 04/26/2024]
Abstract
For hydride superconductors, each significant advance is built upon the discovery of novel H-based structural units, which in turn push the understanding of the superconducting mechanism to new heights. Based on first-principles calculations, we propose a metastable LiH4 with a wavy H layer composed of the edge-sharing pea-like H18 rings at high pressures. Unexpectedly, it exhibits pressure-insensitive superconductivity manifested by an extremely small pressure coefficient (dTc/dP) of 0.04 K/GPa. This feature is attributed to the slightly weakened electron-phonon coupling with pressure, caused by the reduced charge transfer from Li atoms to wavy H layers, significantly suppressing the substantial increase in the contribution of phonons to Tc. Its superconductivity originates from the strong coupling between the H 1s electrons and the high-frequency phonons associated with the H layer. Our study extends the list of H-based structural units and enhances the in-depth understanding of pressure-related superconductivity.
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Affiliation(s)
- Xing Li
- State Key Laboratory of Metastable Materials Science & Technology and Key Laboratory for Microstructural Material Physics of Hebei Province, School of Science, Yanshan University, Qinhuangdao 066004, China
| | - Zixuan Guo
- State Key Laboratory of Metastable Materials Science & Technology and Key Laboratory for Microstructural Material Physics of Hebei Province, School of Science, Yanshan University, Qinhuangdao 066004, China
| | - Xiaohua Zhang
- State Key Laboratory of Metastable Materials Science & Technology and Key Laboratory for Microstructural Material Physics of Hebei Province, School of Science, Yanshan University, Qinhuangdao 066004, China
| | - Guochun Yang
- State Key Laboratory of Metastable Materials Science & Technology and Key Laboratory for Microstructural Material Physics of Hebei Province, School of Science, Yanshan University, Qinhuangdao 066004, China
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Guo Z, Guillen DP, Grimm JR, Renteria C, Marsico C, Nikitin V, Arola D. High Throughput Automated Characterization of Enamel Microstructure using Synchrotron Tomography and Optical Flow Imaging. Acta Biomater 2024:S1742-7061(24)00216-2. [PMID: 38677636 DOI: 10.1016/j.actbio.2024.04.033] [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: 10/10/2023] [Revised: 04/18/2024] [Accepted: 04/22/2024] [Indexed: 04/29/2024]
Abstract
The remarkable damage-tolerance of enamel has been attributed to its hierarchical microstructure and the organized bands of decussated rods. A thorough characterization of the microscale rod evolution within the enamel is needed to elucidate this complex structure. While prior efforts in this area have made use of single particle tracking to track a single rod evolution to various degrees of success, such a process can be both computationally and labor intensive, limited to the evolution path of a single rod, and is therefore prone to error from potentially tracking outliers. Particle image velocimetry (PIV) is a well-established algorithm to derive field information from image sequences for processes that are time-dependent, such as fluid flows and structural deformation. In this work, we demonstrate the use of PIV in extracting the full-field microstructural distribution of rods within the enamel. Enamel samples from a wild African lion were analyzed using high-energy synchrotron X-ray micro-tomography. Results from the PIV analysis provide sufficient full-field information to reconstruct the growth of individual rods that can potentially enable rapid analysis of complex microstructures from high resolution synchrotron datasets. Such information can serve as a template for designing damage-tolerant bioinspired structures for advanced manufacturing. STATEMENT OF SIGNIFICANCE: Thorough characterization and analysis of biological microstructures (viz. dental enamel) allows us to understand the basis of their excellent mechanical properties. Prior efforts have successfully replicated these microstructures via single particle tracking, but the process is computationally and labor intensive. In this work, optical flow imaging algorithms were used to extract full-field microstructural distribution of enamel rods from synchrotron X-ray computed tomography datasets, and a field method was used to reconstruct the growth of individual rods. Such high throughput information allows for the rapid production/prototyping and advanced manufacturing of damage-tolerant bioinspired structures for specific engineering applications. Furthermore, the algorithms used herein are freely available and open source to broaden the availability of the proposed workflow to the general scientific community.
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Affiliation(s)
- Z Guo
- Idaho National Laboratory, Idaho Falls, ID, USA.
| | - D P Guillen
- Idaho National Laboratory, Idaho Falls, ID, USA
| | - J R Grimm
- Materials Science and Engineering, University of Washington, Seattle, WA USA
| | - C Renteria
- Materials Science and Engineering, University of Washington, Seattle, WA USA
| | - C Marsico
- Idaho National Laboratory, Idaho Falls, ID, USA; Materials Science and Engineering, University of Washington, Seattle, WA USA
| | - V Nikitin
- Argonne National Laboratory, Lemont, IL USA
| | - D Arola
- Materials Science and Engineering, University of Washington, Seattle, WA USA; Mechanical Engineering, University of Washington, Seattle, WA USA; Department of Restorative Dentistry, School of Dentistry, University of Washington, Seattle, WA USA
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6
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Guo Z, Zhu M, Li X, Xu H, Lv Y. Primary goose kidney tubular epithelial cells for goose astrovirus genotype 2 infection: establishment and RNA sequencing analysis. Poult Sci 2024; 103:103774. [PMID: 38669820 DOI: 10.1016/j.psj.2024.103774] [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: 03/05/2024] [Revised: 04/03/2024] [Accepted: 04/13/2024] [Indexed: 04/28/2024] Open
Abstract
Goose astrovirus genotype 2 (GAstV-2) mainly causes gout in goslings; therefore, it is a major pathogen threatening to goose flocks. However, the mechanisms underlying host-GAstV-2 interactions remain unclear because host cells suitable for GAstV-2 replication have been unavailable. We previously noted that GAstV-2 is primarily located in goose renal epithelial cells, where it causes kidney damage. Therefore, here, we derived goose primary renal tubular epithelial (RTE) cells (GRTE cells) from the kidneys of goose embryos after collagenase I digestion. After culture in Dulbecco's modified Eagle medium/Nutrient mixture F-12 with 10% fetal bovine serum (FBS), the isolated cells had polygonal with roadstone-like morphology; they were identified to be epithelial cells based on the presence of cytokeratin 18 expression detected through immunofluorescence assay (IFA). GAstV-2 infection in GRTE cells led to no obvious cytopathic effects; the maximum amounts of infectious virions were observed 48 h post infection through IFA and quantitative PCR. Next, RNA-seq was performed to identify and map post-GAstV-2 infection differentially expressed genes. The downregulated pathways were mainly related to metabolism, including tryptophan metabolism, drug metabolism by cytochrome P450, xenobiotic metabolism by cytochrome P450, retinol metabolism, butanoate metabolism, starch and sucrose metabolism, ascorbate and aldarate metabolism, and drug metabolism by other enzymes and peroxisome. In contrast, the upregulated pathways were mostly related to the host cell defense and proliferation, including extracellular matrix-receptor interaction, complement and coagulation cascades, phagosome, PI3K-Akt signaling pathway, human T-lymphotropic virus 1 infection, lysosome, and tumor necrosis factor signaling pathway. In conclusion, we developed a GRTE cell line for GAstV-2 replication and analyzed the potential host-GAstV-2 interactions through RNA-seq; our results may aid in further investigating the pathogenic mechanisms underlying GAstV-2 infection and provide strategies for its prevention and control.
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Affiliation(s)
- Zixuan Guo
- College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, 210095, China
| | - Ming Zhu
- College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, 210095, China
| | - Xinyang Li
- College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, 210095, China
| | - Haoran Xu
- College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, 210095, China
| | - Yingjun Lv
- College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, 210095, China.
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7
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Guo Z, Fan Y, Yu C, Lu H, Zhang Z. GCMSFormer: A Fully Automatic Method for the Resolution of Overlapping Peaks in Gas Chromatography-Mass Spectrometry. Anal Chem 2024; 96:5878-5886. [PMID: 38560891 DOI: 10.1021/acs.analchem.3c05772] [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: 04/04/2024]
Abstract
Gas chromatography-mass spectrometry (GC-MS) is one of the most important instruments for analyzing volatile organic compounds. However, the complexity of real samples and the limitations of chromatographic separation capabilities lead to coeluting compounds without ideal separation. In this study, a Transformer-based automatic resolution method (GCMSFormer) is proposed to resolve mass spectra from GC-MS peaks in an end-to-end manner, predicting the mass spectra of components directly from the raw overlapping peaks data. Furthermore, orthogonal projection resolution (OPR) was integrated into GCMSFormer to resolve minor components. The GCMSFormer model was trained, validated, and tested using 100,000 augmented data. It achieves 99.88% of the bilingual evaluation understudy (BLEU) value on the test set, significantly higher than the 97.68% BLEU value of the baseline sequence-to-sequence model long short-term memory (LSTM). GCMSFormer was also compared with two nondeep learning resolution tools (MZmine and AMDIS) and two deep learning resolution tools (PARAFAC2 with DL and MSHub/GNPS) on a real plant essential oil GC-MS data set. Their resolution results were compared on evaluation metrics, including the number of compounds resolved, mass spectral match score, correlation coefficient, explained variance, and resolution speed. The results demonstrate that GCMSFormer has better resolution performance, higher automation, and faster resolution speed. In summary, GCMSFormer is an end-to-end, fast, fully automatic, and accurate method for analyzing GC-MS data of complex samples.
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Affiliation(s)
- Zixuan Guo
- College of Chemistry and Chemical Engineering, Central South University, Hunan, Changsha 410083, China
| | - Yingjie Fan
- College of Chemistry and Chemical Engineering, Central South University, Hunan, Changsha 410083, China
| | - Chuanxiu Yu
- College of Chemistry and Chemical Engineering, Central South University, Hunan, Changsha 410083, China
| | - Hongmei Lu
- College of Chemistry and Chemical Engineering, Central South University, Hunan, Changsha 410083, China
| | - Zhimin Zhang
- College of Chemistry and Chemical Engineering, Central South University, Hunan, Changsha 410083, China
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Guo Z, Tang X, Xiao S, Yan H, Sun S, Yang Z, Huang L, Chen Z, Wang Y. Systematic review and meta-analysis: multimodal functional and anatomical neural alterations in autism spectrum disorder. Mol Autism 2024; 15:16. [PMID: 38576034 PMCID: PMC10996269 DOI: 10.1186/s13229-024-00593-6] [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: 11/08/2023] [Accepted: 03/13/2024] [Indexed: 04/06/2024] Open
Abstract
BACKGROUND This meta-analysis aimed to explore the most robust findings across numerous existing resting-state functional imaging and voxel-based morphometry (VBM) studies on the functional and structural brain alterations in individuals with autism spectrum disorder (ASD). METHODS A whole-brain voxel-wise meta-analysis was conducted to compare the differences in the intrinsic functional activity and gray matter volume (GMV) between individuals with ASD and typically developing individuals (TDs) using Seed-based d Mapping software. RESULTS A total of 23 functional imaging studies (786 ASD, 710 TDs) and 52 VBM studies (1728 ASD, 1747 TDs) were included. Compared with TDs, individuals with ASD displayed resting-state functional decreases in the left insula (extending to left superior temporal gyrus [STG]), bilateral anterior cingulate cortex/medial prefrontal cortex (ACC/mPFC), left angular gyrus and right inferior temporal gyrus, as well as increases in the right supplementary motor area and precuneus. For VBM meta-analysis, individuals with ASD displayed decreased GMV in the ACC/mPFC and left cerebellum, and increased GMV in the left middle temporal gyrus (extending to the left insula and STG), bilateral olfactory cortex, and right precentral gyrus. Further, individuals with ASD displayed decreased resting-state functional activity and increased GMV in the left insula after overlapping the functional and structural differences. CONCLUSIONS The present multimodal meta-analysis demonstrated that ASD exhibited similar alterations in both function and structure of the insula and ACC/mPFC, and functional or structural alterations in the default mode network (DMN), primary motor and sensory regions. These findings contribute to further understanding of the pathophysiology of ASD.
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Affiliation(s)
- Zixuan Guo
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Xinyue Tang
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Shu Xiao
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Hong Yan
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Shilin Sun
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Zibin Yang
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Li Huang
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Zhuoming Chen
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China
| | - Ying Wang
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou, China.
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Zhu M, Guo Z, Xu H, Li X, Chen H, Cao R, Lv Y. Aminoguanidine alleviates gout in goslings experimentally infected with goose astrovirus-2 by reducing kidney lesions. Poult Sci 2024; 103:103484. [PMID: 38306918 PMCID: PMC10847692 DOI: 10.1016/j.psj.2024.103484] [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: 11/11/2023] [Revised: 01/16/2024] [Accepted: 01/17/2024] [Indexed: 02/04/2024] Open
Abstract
Goose astrovirus (GAstV)-2, a novel pathogen identified in 2018, mainly causes visceral gout in goslings, leading to approximately 50% mortality. At present, no commercial veterinary products are available to prevent and treat the disease. Our previous studies showed that nitric oxide (NO) and inducible NO synthase (iNOS) were markedly higher in the kidney and spleen of goslings infected with GAstV-2, but their effects during GAstV-2 infection remain unclear. In the present study, goslings were intraperitoneally injected with aminoguanidine (AG)-an iNOS inhibitor-to examine the role of NO during GAstV-2 infection. AG significantly decreased the serum NO concentration and iNOS mRNA expression in the kidney. Moreover, AG reduced the mortality, serum uric acid and creatinine content, and urate deposition in visceral organs and joints. Histopathological analysis demonstrated that AG reduced renal tubular cell necrosis, inflammatory cell infiltration, glycogen deposition in glomerular mesangium, and interstitial fibrosis, suggesting alleviation of kidney lesions. Furthermore, AG decreased the expression of renal injury markers such as KIM-1 and desmin; inflammatory cytokine-related genes such as IL-1β, IL-8, and MMP-9; and autophagy-related genes and proteins such as LC3II, ATG5, and Beclin1. However, quantitative real-time PCR and immunohistochemistry showed that treatment with AG did not affect the kidney and liver viral load. These findings suggest that AG decreases the mortality rate and kidney lesions in goslings infected with GAstV-2 through mechanisms associated with autophagy and inhibition of inflammatory cytokine production in the kidney but not with GAstV-2 replication.
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Affiliation(s)
- Ming Zhu
- MOE Joint International Research Laboratory of Animal Health and Food Safety, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, 210095, China
| | - Zixuan Guo
- MOE Joint International Research Laboratory of Animal Health and Food Safety, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, 210095, China
| | - Haoran Xu
- MOE Joint International Research Laboratory of Animal Health and Food Safety, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, 210095, China
| | - Xinyang Li
- MOE Joint International Research Laboratory of Animal Health and Food Safety, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, 210095, China
| | - Hongbo Chen
- Engineering Research Center for the Prevention and Control of Animal Original Zoonosis of Fujian Province University, College of Life Science, Longyan University, Longyan, 364012, Fujian, China
| | - Ruibing Cao
- MOE Joint International Research Laboratory of Animal Health and Food Safety, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, 210095, China
| | - Yingjun Lv
- MOE Joint International Research Laboratory of Animal Health and Food Safety, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, 210095, China.
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Ke J, Wu J, Zhao W, Wang Y, Zhang Z, Tong Q, Guo Z, Wen Y, Li N, Yu F, Xie S, Zhu C, Wang K, Zhang L. Childhood maltreatment and engaging in NSSI for automatic-negative reinforcement: The mediating role of alexithymia and moderating role of help-seeking attitudes. J Affect Disord 2024; 350:295-303. [PMID: 38211755 DOI: 10.1016/j.jad.2024.01.068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 12/21/2023] [Accepted: 01/04/2024] [Indexed: 01/13/2024]
Abstract
BACKGROUND There is evidence indicating that childhood maltreatment is linked to the occurrence of non-suicidal self-injury (NSSI). Nevertheless, the association between childhood maltreatment and the automatic-negative reinforcement aspect of NSSI remains understudied. Chapman's (2006) experiential avoidance model posits that the main factor in sustaining NSSI is negative reinforcement, specifically through the avoidance or escape from distressful emotional experiences. The current study examines a conceptual framework based on this theory and the available literature that explores the potential mediation role of alexithymia in the relation between childhood maltreatment and the automatic-negative reinforcement of NSSI. Additionally, this study investigates how this process may be influenced by individuals' attitudes toward seeking professional help. METHODS 3657 adolescents (1616 females) completed questionnaires regarding childhood maltreatment, alexithymia, help-seeking attitudes, the NSSI, and its functions. RESULTS The findings of the study exposed a positive link between childhood maltreatment and the automatic-negative reinforcement of NSSI, with the mediating role of alexithymia. Interestingly, it was unexpected to discover that individuals with high help-seeking attitudes experienced an intensification of the relationship between childhood maltreatment and both alexithymia and the automatic-negative reinforcement of NSSI. LIMITATION The study's cross-sectional design hindered the inference of causality. CONCLUSION The present study demonstrated that it is crucial to consider the impact of both alexithymia and help-seeking attitudes in adolescents who have experienced maltreatment. These findings hold implications for preventive interventions that target the reduction of NSSI behaviors driven by automatic-negative reinforcement.
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Affiliation(s)
- Jing Ke
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China
| | - Jiayi Wu
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China
| | - Weixiang Zhao
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China
| | - Yuebing Wang
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China
| | - Ze Zhang
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China
| | - Qing Tong
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China
| | - Zixuan Guo
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China
| | - Yan Wen
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China
| | - Nan Li
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China; Department of Neurology, The First Affiliated Hospital of Anhui Medical University, The School of Mental Health and Psychological Sciences, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center for Neuropsychiatric Disorders and Mental Health, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Affective Computing & Advanced Intelligent Machine, Hefei, China
| | - Fengqiong Yu
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China
| | - Sisi Xie
- Anhui Mental Health Center, Hefei, China
| | - Chunyan Zhu
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China
| | - Kai Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, The School of Mental Health and Psychological Sciences, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center for Neuropsychiatric Disorders and Mental Health, Anhui Medical University, Hefei, China.
| | - Lei Zhang
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China; Research Center for Translational Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China; Key Laboratory of Philosophy and Social Science of Anhui Province on Adolescent Mental Health and Crisis Intelligence Intervention, Hefei, China.
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Wu Y, Guo Z, Zhang D, Wang Y, Wang S. Sleep Quality and Suicidal Ideation in Adolescent Depression: A Chain Mediation Effect of Perceived Social Support and Resilience. Clin Psychol Psychother 2024; 31:e2990. [PMID: 38659274 DOI: 10.1002/cpp.2990] [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: 03/23/2024] [Revised: 04/04/2024] [Accepted: 04/08/2024] [Indexed: 04/26/2024]
Abstract
BACKGROUND The prevalence of suicide is high among major depressive adolescents. Poor sleep quality has been documented as a significant risk factor for suicide, influencing perceived social support. Enhanced social support acts as a buffer against suicidal ideation and positively impacts resilience, reducing the prevalence of suicidal ideation. This reciprocal relationship between sleep quality, social support and resilience forms the basis for understanding the mechanisms contributing to suicidal ideation in major depressive adolescents. METHODS A total of 585 major depressive adolescents aged 11 to 24 years was conducted to explore these associations. Assessments included the Pittsburgh Sleep Quality Index, Multidimensional Scale of Perceived Social Support, Connor-Davidson Resilience Scale and Beck Scale for Suicide Ideation. Pearson correlation and Model 6 in the SPSS program were employed for chain mediating tests. RESULTS Better sleep quality positively predicted decreased suicide ideation (β = 0.207, p < 0.01) and predicted lower perceived social support (β = -0.226, p < 0.01) and resilience (β = -0.355, p < 0.01). Perceived social support positively predicted increased resilience (β = 0.422, p < 0.01) and negatively predicted suicide ideation (β = -0.288, p < 0.01). Resilience negatively predicted suicide ideation (β = -0.187, p < 0.01). Sleep quality indirectly predicted suicide ideation through perceived social support and resilience, with a mediation value of 0.0678 (95% CI [0.0359, 0.1060]), constituting 10.65% of the total effect. CONCLUSIONS This study establishes that sleep quality indirectly predicts suicide ideation in major depressive adolescents, mediated independently by perceived social support and resilience.
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Affiliation(s)
- Yan Wu
- Beijing Hui-Long-Guan Hospital, Peking University, Beijing, China
| | - Zixuan Guo
- Beijing Hui-Long-Guan Hospital, Peking University, Beijing, China
| | - Dawei Zhang
- Beijing Hui-Long-Guan Hospital, Peking University, Beijing, China
| | - Yongna Wang
- Beijing Hui-Long-Guan Hospital, Peking University, Beijing, China
| | - Shufen Wang
- Beijing Hui-Long-Guan Hospital, Peking University, Beijing, China
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Tang X, Guo Z, Chen G, Sun S, Xiao S, Chen P, Tang G, Huang L, Wang Y. A Multimodal Meta-Analytical Evidence of Functional and Structural Brain Abnormalities Across Alzheimer's Disease Spectrum. Ageing Res Rev 2024; 95:102240. [PMID: 38395200 DOI: 10.1016/j.arr.2024.102240] [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: 01/05/2024] [Accepted: 02/18/2024] [Indexed: 02/25/2024]
Abstract
BACKGROUND Numerous neuroimaging studies have reported that Alzheimer's disease (AD) spectrum have been linked to alterations in intrinsic functional activity and cortical thickness (CT) of some brain areas. However, the findings have been inconsistent and the correlation with the transcriptional profile and neurotransmitter systems remain largely unknown. METHODS We conducted a meta-analysis to identify multimodal differences in the amplitude of low-frequency fluctuation (ALFF)/fractional ALFF (fALFF) and CT in patients with AD and preclinical AD compared to healthy controls (HCs), using the Seed-based d Mapping with Permutation of Subject Images software. Transcriptional data were retrieved from the Allen Human Brain Atlas. The atlas-based nuclear imaging-derived neurotransmitter maps were investigated by JuSpace toolbox. RESULTS We included 26 ALFF/fALFF studies comprising 884 patients with AD and 1,020 controls, along with 52 studies comprising 2,046 patients with preclinical AD and 2,336 controls. For CT, we included 11 studies comprising 353 patients with AD and 330 controls. Overall, compared to HCs, patients with AD showed decreased ALFF/fALFF in the bilateral posterior cingulate gyrus (PCC)/precuneus and right angular gyrus, as well as increased ALFF/fALFF in the bilateral parahippocampal gyrus (PHG). Patients with peclinical AD showed decreased ALFF/fALFF in the left precuneus. Additionally, patients with AD displayed decreased CT in the bilateral PHG, left PCC, bilateral orbitofrontal cortex, sensorimotor areas and temporal lobe. Furthermore, gene sets related to brain structural and functional changes in AD and preclincal AD were enriched for G protein-coupled receptor signaling pathway, ion gated channel activity, and components of biological membrane. Functional and structural alterations in AD and preclinical AD were spatially associated with dopaminergic, serotonergic, and GABAergic neurotransmitter systems. CONCLUSIONS The multimodal meta-analysis demonstrated that patients with AD exhibited convergent functional and structural alterations in the PCC/precuneus and PHG, as well as cortical thinning in the primary sensory and motor areas. Furthermore, patients with preclinical AD showed reduced functional activity in the precuneus. AD and preclinical AD showed genetic modulations/neurotransmitter deficits of brain functional and structural impairments. These findings may provide new insights into the pathophysiology of the AD spectrum.
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Affiliation(s)
- Xinyue Tang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Zixuan Guo
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Guanmao Chen
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Shilin Sun
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Shu Xiao
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Pan Chen
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Guixian Tang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Li Huang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Ying Wang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China.
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13
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Qi J, Liu H, Zhou Z, Jiang Y, Fan W, Hu J, Li J, Guo Z, Xie M, Huang W, Zhang Q, Hou S. Genome-wide association study identifies multiple loci influencing duck serum biochemical indicators in the laying period. Br Poult Sci 2024; 65:8-18. [PMID: 38284741 DOI: 10.1080/00071668.2023.2272982] [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: 10/24/2022] [Accepted: 09/12/2023] [Indexed: 01/30/2024]
Abstract
1. Laying performance is an important economic trait in poultry. The blood is essential in transporting nutrients to the yolk and albumen and is necessary for egg formation.2. This study calculated the phenotypic relationships of duck egg quality, egg production efficiency and 22 serum parameters in the egg-laying stage. Using a variety of methodologies, a genome-wide association study (GWAS) was carried out to uncover the genetic foundations of the 22 serum biochemical markers of laying ducks.3. Spearman correlation coefficients between the egg production (226-329 per day) and the serum parameters were all weak, being less than 0.3. This analysis was done on 22 serum parameters, with total protein (TP), total triglycerides (TG), calcium (Ca) and phosphorous (P) having the highest correlation coefficients (r = 0.56-0.88). The coefficients for blood markers, such as total cholesterol (CHOL), total bilirubin (TBIL), low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C) varied from 0.70-0.94.4. Based on single-marker single-trait genome-wide analyses by a mixed linear model program of EMMAX, nine candidate genes were associated with enzyme traits (AST/ALT aspartate transaminase/glutamic-pyruvic transaminase, creatine kinase) and 19 candidate genes were associated with metabolism and protein-related serum parameters (glucose, total bile acid, uric acid (UA), albumin (ALB).5. The mvLMM (multivariate linear mixed model) of GEMMA software was used to carry out multiple trait integrated GWAS. Two candidate genes were found in the TP-TG-CA-P analysis and seven candidate genes in the CHOL_LDL-C_HDL-C_TBIL study. There was a high genetic correlation between the two groups.
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Affiliation(s)
- J Qi
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - H Liu
- State Key Laboratory of Animal Nutrition, Ministry of Agriculture and Rural Affairs, Beijing, China
- Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Beijing, China
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Z Zhou
- State Key Laboratory of Animal Nutrition, Ministry of Agriculture and Rural Affairs, Beijing, China
- Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Beijing, China
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Y Jiang
- State Key Laboratory of Animal Nutrition, Ministry of Agriculture and Rural Affairs, Beijing, China
- Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Beijing, China
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - W Fan
- State Key Laboratory of Animal Nutrition, Ministry of Agriculture and Rural Affairs, Beijing, China
- Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Beijing, China
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - J Hu
- State Key Laboratory of Animal Nutrition, Ministry of Agriculture and Rural Affairs, Beijing, China
- Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Beijing, China
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - J Li
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - Z Guo
- State Key Laboratory of Animal Nutrition, Ministry of Agriculture and Rural Affairs, Beijing, China
- Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Beijing, China
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - M Xie
- State Key Laboratory of Animal Nutrition, Ministry of Agriculture and Rural Affairs, Beijing, China
- Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Beijing, China
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - W Huang
- State Key Laboratory of Animal Nutrition, Ministry of Agriculture and Rural Affairs, Beijing, China
- Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Beijing, China
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Q Zhang
- State Key Laboratory of Animal Nutrition, Ministry of Agriculture and Rural Affairs, Beijing, China
- Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Beijing, China
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - S Hou
- State Key Laboratory of Animal Nutrition, Ministry of Agriculture and Rural Affairs, Beijing, China
- Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Beijing, China
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
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Guo Y, Kang X, Huang Y, Guo Z, Wang Y, Ma S, Li H, Chao N, Liu L. Functional characterization of MaEXPA11 and its roles in response to biotic and abiotic stresses in mulberry. Plant Physiol Biochem 2024; 206:108289. [PMID: 38154294 DOI: 10.1016/j.plaphy.2023.108289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 12/06/2023] [Accepted: 12/15/2023] [Indexed: 12/30/2023]
Abstract
Mulberry is a traditional economic tree with various values in sericulture, ecology, food industry and medicine. Expansins (EXPs) are known as cell wall expansion related proteins and have been characterized to involve in plant development and responses to diverse stresses. In present study, twenty EXP and expansin-like (EXL) genes were identified in mulberry. RNA-seq results indicated that three EXP and EXL genes showed up-regulated expression level under sclerotiniose pathogen infection in three independent RNA-seq datasets. The most significant upregulated EXPA11 was selected as key EXP involving in response to sclerotiniose pathogen infection in mulberry. Furthermore, a comprehensive functional analysis was performed to reveal subcellular location, tissue expression profile of MaEXPA11 in mulberry. Down-regulation of MaEXPA11 using virus induced gene silence (VIGS) was performed to explore the function of MaEXPA11 in Morus alba. Results showed that MaEXPA11 can positively regulate mulberry resistance to Ciboria shiraiana infection and negatively regulate mulberry resistance to cold or drought stress.
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Affiliation(s)
- Yangyang Guo
- Jiangsu Key Laboratory of Sericultural Biology and Biotechnology, School of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212100, China
| | - Xiaoru Kang
- Jiangsu Key Laboratory of Sericultural Biology and Biotechnology, School of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212100, China
| | - Yajiang Huang
- Jiangsu Key Laboratory of Sericultural Biology and Biotechnology, School of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212100, China
| | - Zixuan Guo
- Jiangsu Key Laboratory of Sericultural Biology and Biotechnology, School of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212100, China
| | - Yuqiong Wang
- Jiangsu Key Laboratory of Sericultural Biology and Biotechnology, School of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212100, China
| | - Shuwen Ma
- Jiangsu Key Laboratory of Sericultural Biology and Biotechnology, School of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212100, China
| | - Hua Li
- Jiangsu Key Laboratory of Sericultural Biology and Biotechnology, School of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212100, China
| | - Nan Chao
- Jiangsu Key Laboratory of Sericultural Biology and Biotechnology, School of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212100, China; Key Laboratory of Silkworm and Mulberry Genetic Improvement, Ministry of Agriculture and Rural Affairs, Sericultural Research Institute, Chinese Academy of Agricultural Sciences, Zhenjiang, Jiangsu 212100, China.
| | - Li Liu
- Jiangsu Key Laboratory of Sericultural Biology and Biotechnology, School of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212100, China; Key Laboratory of Silkworm and Mulberry Genetic Improvement, Ministry of Agriculture and Rural Affairs, Sericultural Research Institute, Chinese Academy of Agricultural Sciences, Zhenjiang, Jiangsu 212100, China.
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Sun S, Xiao S, Guo Z, Gong J, Tang G, Huang L, Wang Y. Meta-analysis of cortical thickness reduction in adult schizophrenia. J Psychiatry Neurosci 2023; 48:E461-E470. [PMID: 38123240 PMCID: PMC10743639 DOI: 10.1503/jpn.230081] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 08/17/2023] [Accepted: 09/11/2023] [Indexed: 12/23/2023] Open
Abstract
BACKGROUND Numerous neuroimaging studies using surface-based morphometry analyses have reported altered cortical thickness among patients with schizophrenia, but the results have been inconsistent. We sought to provide a whole-brain meta-analysis, which may help enhance the spatial accuracy of identification. METHODS We conducted a meta-analysis of whole-brain studies that explored cortical thickness alteration among adult patients with schizophrenia, including first-episode patients with schizophrenia, and patients with chronic schizophrenia, compared with healthy controls by using the seed-based d mapping with permutation of subject images (SDM-PSI) software. RESULTS A systematic literature search identified 25 studies (33 data sets) of cortical thickness, including 2008 patients with schizophrenia and 2004 healthy controls. Overall, patients with schizophrenia showed decreased cortical thickness in the right inferior frontal gyrus (IFG) and bilateral insula extending to the superior temporal gyrus (STG). Subgroup meta-analysis reported that patients with chronic schizophrenia showed decreased cortical thickness in the right insula extending to the right IFG. There was no significant cortical thickness difference between first-episode patients with schizophrenia and healthy controls. LIMITATIONS The results of meta-regression analyses should be viewed cautiously since they were driven by a small number of studies or did not overlap with the between-group differences found in the primary analyses. CONCLUSION The meta-analysis suggested robust cortical thickness reduction in the IFG, insula and STG among adult patients with schizophrenia, particularly in those with chronic schizophrenia. The results provide useful insights to understanding the underlying pathophysiology of schizophrenia.
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Affiliation(s)
- Shilin Sun
- From the Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, China (Sun, Xiao, Guo, Tang, Huang, Wang); the Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, China (Sun, Xiao, Guo, Gong, Tang, Huang, Wang); the Department of Radiology, Six Affiliated Hospital of Sun Yat-sen University, Guangzhou, China (Gong)
| | - Shu Xiao
- From the Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, China (Sun, Xiao, Guo, Tang, Huang, Wang); the Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, China (Sun, Xiao, Guo, Gong, Tang, Huang, Wang); the Department of Radiology, Six Affiliated Hospital of Sun Yat-sen University, Guangzhou, China (Gong)
| | - Zixuan Guo
- From the Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, China (Sun, Xiao, Guo, Tang, Huang, Wang); the Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, China (Sun, Xiao, Guo, Gong, Tang, Huang, Wang); the Department of Radiology, Six Affiliated Hospital of Sun Yat-sen University, Guangzhou, China (Gong)
| | - Jiaying Gong
- From the Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, China (Sun, Xiao, Guo, Tang, Huang, Wang); the Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, China (Sun, Xiao, Guo, Gong, Tang, Huang, Wang); the Department of Radiology, Six Affiliated Hospital of Sun Yat-sen University, Guangzhou, China (Gong)
| | - Guixian Tang
- From the Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, China (Sun, Xiao, Guo, Tang, Huang, Wang); the Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, China (Sun, Xiao, Guo, Gong, Tang, Huang, Wang); the Department of Radiology, Six Affiliated Hospital of Sun Yat-sen University, Guangzhou, China (Gong)
| | - Li Huang
- From the Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, China (Sun, Xiao, Guo, Tang, Huang, Wang); the Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, China (Sun, Xiao, Guo, Gong, Tang, Huang, Wang); the Department of Radiology, Six Affiliated Hospital of Sun Yat-sen University, Guangzhou, China (Gong)
| | - Ying Wang
- From the Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, China (Sun, Xiao, Guo, Tang, Huang, Wang); the Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, China (Sun, Xiao, Guo, Gong, Tang, Huang, Wang); the Department of Radiology, Six Affiliated Hospital of Sun Yat-sen University, Guangzhou, China (Gong)
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Wang Y, Wang Y, Li X, Zhao C, Ma N, Guo Z. A Comparative Study of the Typing Performance of Two Mid-Air Text Input Methods in Virtual Environments. Sensors (Basel) 2023; 23:6988. [PMID: 37571771 PMCID: PMC10422554 DOI: 10.3390/s23156988] [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: 05/14/2023] [Revised: 07/09/2023] [Accepted: 07/19/2023] [Indexed: 08/13/2023]
Abstract
Inputting text is a prevalent requirement among various virtual reality (VR) applications, including VR-based remote collaboration. In order to eliminate the need for complex rules and handheld devices for typing within virtual environments, researchers have proposed two mid-air input methods-the trace and tap methods. However, the specific impact of these input methods on performance in VR remains unknown. In this study, typing tasks were used to compare the performance, subjective report, and cognitive load of two mid-air input methods in VR. While the trace input method was more efficient and novel, it also entailed greater frustration and cognitive workload. Fortunately, the levels of frustration and cognitive load associated with the trace input method could be reduced to the same level as those of the tap input method via familiarity with VR. These findings could aid the design of virtual input methods, particularly for VR applications with varying text input demands.
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Affiliation(s)
- Yueyang Wang
- The School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China;
| | - Yahui Wang
- The School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China;
| | - Xiaoqiong Li
- The School of Life Science, Beijing Institute of Technology, Beijing 100081, China;
| | - Chengyi Zhao
- Faculty of Psychology, Beijing Normal University, Beijing 100875, China; (C.Z.); (Z.G.)
| | - Ning Ma
- Department of Design, Kyiv National University of Technologies and Design, 01011 Kyiv, Ukraine;
| | - Zixuan Guo
- Faculty of Psychology, Beijing Normal University, Beijing 100875, China; (C.Z.); (Z.G.)
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Lv C, Wang R, Li S, Yan S, Wang Y, Chen J, Wang L, Liu Y, Guo Z, Wang J, Pei Y, Yu L, Wu N, Lu F, Gao F, Chen J, Liu Y, Wang X, Li S, Han B, Zhang L, Ma Y, Ding L, Wang Y, Yuan X, Yang Y. Randomized phase II adjuvant trial to compare two treatment durations of icotinib (2 years versus 1 year) for stage II-IIIA EGFR-positive lung adenocarcinoma patients (ICOMPARE study). ESMO Open 2023; 8:101565. [PMID: 37348348 PMCID: PMC10515286 DOI: 10.1016/j.esmoop.2023.101565] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 03/30/2023] [Accepted: 04/24/2023] [Indexed: 06/24/2023] Open
Abstract
BACKGROUND Despite the prolonged median disease-free survival (DFS) by adjuvant targeted therapy in non-small-cell lung cancer patients with epidermal growth factor receptor (EGFR) mutations, the relationship between the treatment duration and the survival benefits in patients remains unknown. PATIENTS AND METHODS In this multicenter, randomized, open-label, phase II trial, eligible patients aged 18-75 years with EGFR-mutant, stage II-IIIA lung adenocarcinoma and who had not received adjuvant chemotherapy after complete tumor resection were enrolled from eight centers in China. Patients were randomly assigned (1 : 1) to receive either 1-year or 2-year icotinib (125 mg thrice daily). The primary endpoint was DFS assessed by investigator. The secondary endpoints were overall survival (OS) and safety. This study was registered at ClinicalTrials.gov (NCT01929200). RESULTS Between September 2013 and October 2018, 109 patients were enrolled (1-year group, n = 55; 2-year group, n = 54). Median DFS was 48.9 months [95% confidence interval (CI) 33.1-70.1 months] in the 2-year group and 32.9 months (95% CI 26.6-44.8 months) in the 1-year group [hazard ratio (HR) 0.51; 95% CI 0.28-0.94; P = 0.0290]. Median OS for patients was 75.8 months [95% CI 64.4 months-not evaluable (NE)] in the 2-year group and NE (95% CI 66.3 months-NE) in the 1-year group (HR 0.34; 95% CI 0.13-0.95; P = 0.0317). Treatment-related adverse events (TRAEs) were observed in 41 of 55 (75%) patients in the 1-year group and in 36 of 54 (67%) patients in the 2-year group. Grade 3-4 TRAEs occurred in 4 of 55 (7%) patients in the 1-year group and in 3 of 54 (6%) patients in the 2-year group. No treatment-related deaths or interstitial lung disease was reported. CONCLUSIONS Two-year adjuvant icotinib was shown to significantly improve DFS and provide an OS benefit in EGFR-mutant, stage II-IIIA lung adenocarcinoma patients compared with 1-year treatment in this exploratory phase II study.
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Affiliation(s)
- C Lv
- Department of Thoracic Surgery II, Beijing Cancer Hospital, Beijing
| | - R Wang
- Department of Thoracic Surgery, The Fourth Hospital of Hebei Medical University, Hebi
| | - S Li
- Department of Thoracic Surgery II, Beijing Cancer Hospital, Beijing
| | - S Yan
- Department of Thoracic Surgery II, Beijing Cancer Hospital, Beijing
| | - Y Wang
- Department of Thoracic Surgery II, Beijing Cancer Hospital, Beijing
| | - J Chen
- Department of Thoracic Surgery II, Beijing Cancer Hospital, Beijing
| | - L Wang
- Department of Thoracic Surgery II, Beijing Cancer Hospital, Beijing
| | - Y Liu
- Department of Thoracic Surgery II, Beijing Cancer Hospital, Beijing
| | - Z Guo
- Department of Thoracic Surgery, The Affiliated Hospital of Inner Mongolia Medical University, Inner Mongolia
| | - J Wang
- Department of Thoracic Surgery II, Beijing Cancer Hospital, Beijing
| | - Y Pei
- Department of Thoracic Surgery II, Beijing Cancer Hospital, Beijing
| | - L Yu
- Department of Thoracic Surgery, Beijing Tongren Hospital, CMU, Beijing
| | - N Wu
- Department of Thoracic Surgery II, Beijing Cancer Hospital, Beijing
| | - F Lu
- Department of Thoracic Surgery II, Beijing Cancer Hospital, Beijing
| | - F Gao
- Department of Thoracic Surgery, The Fourth Hospital of Hebei Medical University, Hebi
| | - J Chen
- Thoracic Neoplasms Surgical Department, Tianjing Medical University General Hospital, Tianjing
| | - Y Liu
- Thoracic Neoplasms Surgical Department, Inner Mongolia People's Hospital, Inner Mongolia
| | - X Wang
- Department of Thoracic Surgery II, Beijing Cancer Hospital, Beijing
| | - S Li
- Department of Thoracic Surgery, Peking Union Medical College Hospital, Beijing
| | - B Han
- Department of Thoracic Surgery, PLA Pocket Force Characteristic Medical Center, Beijing
| | - L Zhang
- Department of Thoracic Surgery II, Beijing Cancer Hospital, Beijing
| | - Y Ma
- Department of Thoracic Surgery II, Beijing Cancer Hospital, Beijing
| | - L Ding
- Betta Pharmaceuticals Co., Ltd, Hangzhou, China
| | - Y Wang
- Betta Pharmaceuticals Co., Ltd, Hangzhou, China
| | - X Yuan
- Betta Pharmaceuticals Co., Ltd, Hangzhou, China
| | - Y Yang
- Department of Thoracic Surgery II, Beijing Cancer Hospital, Beijing.
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Cheng H, Teng J, Jia L, Xu L, Yang F, Li H, Ling C, Liu W, Li J, Li Y, Guo Z, Geng X, Guo J, Zhang D. Association between morphologic features of intracranial distal arteries and brain atrophy indexes in cerebral small vessel disease: a voxel-based morphometry study. Front Neurol 2023; 14:1198402. [PMID: 37396753 PMCID: PMC10313400 DOI: 10.3389/fneur.2023.1198402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2023] [Accepted: 05/24/2023] [Indexed: 07/04/2023] Open
Abstract
Background Brain atrophy represents a final common pathway for pathological processes in patients with cerebral small vessel disease (CSVD) and is now recognized as a strong independent predictor of clinical status and progression. The mechanism underlying brain atrophy in patients with CSVD is not yet fully comprehended. This study aims to investigate the association of morphologic features of intracranial distal arteries (A2, M2, P2 and more distal) with different brain structures [gray matter volume (GMV), white matter volume (WMV), and cerebrospinal fluid volume (CSFV)]. Furthermore, we also examined whether a correlation existed between these cerebrovascular characteristics and GMV in different brain regions. Method A total of 39 participants were eventually enrolled. The morphologic features of intracranial distal arteries based on TOF-MRA were extracted and quantified using the intracranial artery feature extraction technique (iCafe). The brain 3D-T1 images were segmented into gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) using the "Segment" tool in CAT12 for the voxel-based morphometry (VBM) analysis. Univariable and multivariable linear regression models were used to investigate the relationship between these cerebrovascular features and different brain structures. Partial correlation analysis with a one-tailed method was used to evaluate the relationship between these cerebrovascular features and GMV in different brain regions. Results Our findings indicate that both distal artery length and density were positively correlated with GM fraction in CSVD patients, regardless of whether univariable or multivariable linear regression analyses were performed. In addition, distal artery length (β = -0.428, p = 0.007) and density (β = -0.337, p = 0.036) were also found to be negative associated with CSF fraction, although this relationship disappeared after adjusting for potential confounders. Additional adjustment for the effect of WMHs volume did not change these results. In subgroup anasysis, we found that participants in the highest distal artery length tertile had significantly higher GM fraction and lower CSF fraction level than participants in the lowest distal artery length tertile. In partial correlation analysis, we also found that these cerebrovascular characteristics associated with regional GMV, especially subcortical nuclear. Conclusion The morphologic features of intracranial distal arteries, including artery length, density and average tortuosity, measured from 3D-TOF MRA, are associated with generalized or focal atrophy indexes of CSVD.
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Affiliation(s)
- Hongjiang Cheng
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Junfang Teng
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Longbin Jia
- Department of Neurology, Jincheng People’s Hospital, Jincheng, Shanxi, China
| | - Lina Xu
- Department of Neurology, Jincheng People’s Hospital, Jincheng, Shanxi, China
| | - Fengbing Yang
- Department of Neurology, Jincheng People’s Hospital, Jincheng, Shanxi, China
| | - Huimin Li
- Department of Neurology, Jincheng People’s Hospital, Jincheng, Shanxi, China
| | - Chen Ling
- Graduate School, Changzhi Medical College, Changzhi, Shanxi, China
| | - Wei Liu
- Department of Neurology, Jincheng People’s Hospital, Jincheng, Shanxi, China
| | - Jinna Li
- Department of Neurology, Jincheng People’s Hospital, Jincheng, Shanxi, China
| | - Yujuan Li
- Department of Neurology, Jincheng People’s Hospital, Jincheng, Shanxi, China
| | - Zixuan Guo
- Department of Neurology, Jincheng People’s Hospital, Jincheng, Shanxi, China
| | - Xia Geng
- Department of Neurology, Jincheng People’s Hospital, Jincheng, Shanxi, China
| | - Jiaying Guo
- Department of Neurology, Jincheng People’s Hospital, Jincheng, Shanxi, China
| | - Dandan Zhang
- Department of Neurology, Jincheng People’s Hospital, Jincheng, Shanxi, China
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An FP, Bai WD, Balantekin AB, Bishai M, Blyth S, Cao GF, Cao J, Chang JF, Chang Y, Chen HS, Chen HY, Chen SM, Chen Y, Chen YX, Cheng J, Cheng J, Cheng YC, Cheng ZK, Cherwinka JJ, Chu MC, Cummings JP, Dalager O, Deng FS, Ding YY, Diwan MV, Dohnal T, Dolzhikov D, Dove J, Dugas KV, Duyang HY, Dwyer DA, Gallo JP, Gonchar M, Gong GH, Gong H, Gu WQ, Guo JY, Guo L, Guo XH, Guo YH, Guo Z, Hackenburg RW, Han Y, Hans S, He M, Heeger KM, Heng YK, Hor YK, Hsiung YB, Hu BZ, Hu JR, Hu T, Hu ZJ, Huang HX, Huang JH, Huang XT, Huang YB, Huber P, Jaffe DE, Jen KL, Ji XL, Ji XP, Johnson RA, Jones D, Kang L, Kettell SH, Kohn S, Kramer M, Langford TJ, Lee J, Lee JHC, Lei RT, Leitner R, Leung JKC, Li F, Li HL, Li JJ, Li QJ, Li RH, Li S, Li SC, Li WD, Li XN, Li XQ, Li YF, Li ZB, Liang H, Lin CJ, Lin GL, Lin S, Ling JJ, Link JM, Littenberg L, Littlejohn BR, Liu JC, Liu JL, Liu JX, Lu C, Lu HQ, Luk KB, Ma BZ, Ma XB, Ma XY, Ma YQ, Mandujano RC, Marshall C, McDonald KT, McKeown RD, Meng Y, Napolitano J, Naumov D, Naumova E, Nguyen TMT, Ochoa-Ricoux JP, Olshevskiy A, Park J, Patton S, Peng JC, Pun CSJ, Qi FZ, Qi M, Qian X, Raper N, Ren J, Morales Reveco C, Rosero R, Roskovec B, Ruan XC, Russell B, Steiner H, Sun JL, Tmej T, Treskov K, Tse WH, Tull CE, Tung YC, Viren B, Vorobel V, Wang CH, Wang J, Wang M, Wang NY, Wang RG, Wang W, Wang X, Wang Y, Wang YF, Wang Z, Wang Z, Wang ZM, Wei HY, Wei LH, Wen LJ, Whisnant K, White CG, Wong HLH, Worcester E, Wu DR, Wu Q, Wu WJ, Xia DM, Xie ZQ, Xing ZZ, Xu HK, Xu JL, Xu T, Xue T, Yang CG, Yang L, Yang YZ, Yao HF, Ye M, Yeh M, Young BL, Yu HZ, Yu ZY, Yue BB, Zavadskyi V, Zeng S, Zeng Y, Zhan L, Zhang C, Zhang FY, Zhang HH, Zhang JL, Zhang JW, Zhang QM, Zhang SQ, Zhang XT, Zhang YM, Zhang YX, Zhang YY, Zhang ZJ, Zhang ZP, Zhang ZY, Zhao J, Zhao RZ, Zhou L, Zhuang HL, Zou JH. Improved Measurement of the Evolution of the Reactor Antineutrino Flux and Spectrum at Daya Bay. Phys Rev Lett 2023; 130:211801. [PMID: 37295075 DOI: 10.1103/physrevlett.130.211801] [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: 10/03/2022] [Revised: 02/10/2023] [Accepted: 04/27/2023] [Indexed: 06/12/2023]
Abstract
Reactor neutrino experiments play a crucial role in advancing our knowledge of neutrinos. In this Letter, the evolution of the flux and spectrum as a function of the reactor isotopic content is reported in terms of the inverse-beta-decay yield at Daya Bay with 1958 days of data and improved systematic uncertainties. These measurements are compared with two signature model predictions: the Huber-Mueller model based on the conversion method and the SM2018 model based on the summation method. The measured average flux and spectrum, as well as the flux evolution with the ^{239}Pu isotopic fraction, are inconsistent with the predictions of the Huber-Mueller model. In contrast, the SM2018 model is shown to agree with the average flux and its evolution but fails to describe the energy spectrum. Altering the predicted inverse-beta-decay spectrum from ^{239}Pu fission does not improve the agreement with the measurement for either model. The models can be brought into better agreement with the measurements if either the predicted spectrum due to ^{235}U fission is changed or the predicted ^{235}U, ^{238}U, ^{239}Pu, and ^{241}Pu spectra are changed in equal measure.
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Affiliation(s)
- F P An
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - W D Bai
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | | | - M Bishai
- Brookhaven National Laboratory, Upton, New York 11973
| | - S Blyth
- Department of Physics, National Taiwan University, Taipei
| | - G F Cao
- Institute of High Energy Physics, Beijing
| | - J Cao
- Institute of High Energy Physics, Beijing
| | - J F Chang
- Institute of High Energy Physics, Beijing
| | - Y Chang
- National United University, Miao-Li
| | - H S Chen
- Institute of High Energy Physics, Beijing
| | - H Y Chen
- Department of Engineering Physics, Tsinghua University, Beijing
| | - S M Chen
- Department of Engineering Physics, Tsinghua University, Beijing
| | - Y Chen
- Sun Yat-Sen (Zhongshan) University, Guangzhou
- Shenzhen University, Shenzhen
| | - Y X Chen
- North China Electric Power University, Beijing
| | - J Cheng
- North China Electric Power University, Beijing
| | - J Cheng
- North China Electric Power University, Beijing
| | - Y-C Cheng
- Department of Physics, National Taiwan University, Taipei
| | - Z K Cheng
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | | | - M C Chu
- Chinese University of Hong Kong, Hong Kong
| | | | - O Dalager
- Department of Physics and Astronomy, University of California, Irvine, California 92697
| | - F S Deng
- University of Science and Technology of China, Hefei
| | - Y Y Ding
- Institute of High Energy Physics, Beijing
| | - M V Diwan
- Brookhaven National Laboratory, Upton, New York 11973
| | - T Dohnal
- Charles University, Faculty of Mathematics and Physics, Prague
| | - D Dolzhikov
- Joint Institute for Nuclear Research, Dubna, Moscow Region
| | - J Dove
- Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - K V Dugas
- Department of Physics and Astronomy, University of California, Irvine, California 92697
| | | | - D A Dwyer
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - J P Gallo
- Department of Physics, Illinois Institute of Technology, Chicago, Illinois 60616
| | - M Gonchar
- Joint Institute for Nuclear Research, Dubna, Moscow Region
| | - G H Gong
- Department of Engineering Physics, Tsinghua University, Beijing
| | - H Gong
- Department of Engineering Physics, Tsinghua University, Beijing
| | - W Q Gu
- Brookhaven National Laboratory, Upton, New York 11973
| | - J Y Guo
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - L Guo
- Department of Engineering Physics, Tsinghua University, Beijing
| | - X H Guo
- Beijing Normal University, Beijing
| | - Y H Guo
- Department of Nuclear Science and Technology, School of Energy and Power Engineering, Xi'an Jiaotong University, Xi'an
| | - Z Guo
- Department of Engineering Physics, Tsinghua University, Beijing
| | | | - Y Han
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - S Hans
- Brookhaven National Laboratory, Upton, New York 11973
| | - M He
- Institute of High Energy Physics, Beijing
| | - K M Heeger
- Wright Laboratory and Department of Physics, Yale University, New Haven, Connecticut 06520
| | - Y K Heng
- Institute of High Energy Physics, Beijing
| | - Y K Hor
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - Y B Hsiung
- Department of Physics, National Taiwan University, Taipei
| | - B Z Hu
- Department of Physics, National Taiwan University, Taipei
| | - J R Hu
- Institute of High Energy Physics, Beijing
| | - T Hu
- Institute of High Energy Physics, Beijing
| | - Z J Hu
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - H X Huang
- China Institute of Atomic Energy, Beijing
| | - J H Huang
- Institute of High Energy Physics, Beijing
| | | | - Y B Huang
- Guangxi University, No. 100 Daxue East Road, Nanning
| | - P Huber
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061
| | - D E Jaffe
- Brookhaven National Laboratory, Upton, New York 11973
| | - K L Jen
- Institute of Physics, National Chiao-Tung University, Hsinchu
| | - X L Ji
- Institute of High Energy Physics, Beijing
| | - X P Ji
- Brookhaven National Laboratory, Upton, New York 11973
| | - R A Johnson
- Department of Physics, University of Cincinnati, Cincinnati, Ohio 45221
| | - D Jones
- Department of Physics, College of Science and Technology, Temple University, Philadelphia, Pennsylvania 19122
| | - L Kang
- Dongguan University of Technology, Dongguan
| | - S H Kettell
- Brookhaven National Laboratory, Upton, New York 11973
| | - S Kohn
- Department of Physics, University of California, Berkeley, California 94720
| | - M Kramer
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
- Department of Physics, University of California, Berkeley, California 94720
| | - T J Langford
- Wright Laboratory and Department of Physics, Yale University, New Haven, Connecticut 06520
| | - J Lee
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - J H C Lee
- Department of Physics, The University of Hong Kong, Pokfulam, Hong Kong
| | - R T Lei
- Dongguan University of Technology, Dongguan
| | - R Leitner
- Charles University, Faculty of Mathematics and Physics, Prague
| | - J K C Leung
- Department of Physics, The University of Hong Kong, Pokfulam, Hong Kong
| | - F Li
- Institute of High Energy Physics, Beijing
| | - H L Li
- Institute of High Energy Physics, Beijing
| | - J J Li
- Department of Engineering Physics, Tsinghua University, Beijing
| | - Q J Li
- Institute of High Energy Physics, Beijing
| | - R H Li
- Institute of High Energy Physics, Beijing
| | - S Li
- Dongguan University of Technology, Dongguan
| | - S C Li
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061
| | - W D Li
- Institute of High Energy Physics, Beijing
| | - X N Li
- Institute of High Energy Physics, Beijing
| | - X Q Li
- School of Physics, Nankai University, Tianjin
| | - Y F Li
- Institute of High Energy Physics, Beijing
| | - Z B Li
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - H Liang
- University of Science and Technology of China, Hefei
| | - C J Lin
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - G L Lin
- Institute of Physics, National Chiao-Tung University, Hsinchu
| | - S Lin
- Dongguan University of Technology, Dongguan
| | - J J Ling
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - J M Link
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061
| | - L Littenberg
- Brookhaven National Laboratory, Upton, New York 11973
| | - B R Littlejohn
- Department of Physics, Illinois Institute of Technology, Chicago, Illinois 60616
| | - J C Liu
- Institute of High Energy Physics, Beijing
| | - J L Liu
- Department of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai Laboratory for Particle Physics and Cosmology, Shanghai
| | - J X Liu
- Institute of High Energy Physics, Beijing
| | - C Lu
- Joseph Henry Laboratories, Princeton University, Princeton, New Jersey 08544
| | - H Q Lu
- Institute of High Energy Physics, Beijing
| | - K B Luk
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
- Department of Physics, University of California, Berkeley, California 94720
- The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong
| | - B Z Ma
- Shandong University, Jinan
| | - X B Ma
- North China Electric Power University, Beijing
| | - X Y Ma
- Institute of High Energy Physics, Beijing
| | - Y Q Ma
- Institute of High Energy Physics, Beijing
| | - R C Mandujano
- Department of Physics and Astronomy, University of California, Irvine, California 92697
| | - C Marshall
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - K T McDonald
- Joseph Henry Laboratories, Princeton University, Princeton, New Jersey 08544
| | - R D McKeown
- California Institute of Technology, Pasadena, California 91125
- College of William and Mary, Williamsburg, Virginia 23187
| | - Y Meng
- Department of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai Laboratory for Particle Physics and Cosmology, Shanghai
| | - J Napolitano
- Department of Physics, College of Science and Technology, Temple University, Philadelphia, Pennsylvania 19122
| | - D Naumov
- Joint Institute for Nuclear Research, Dubna, Moscow Region
| | - E Naumova
- Joint Institute for Nuclear Research, Dubna, Moscow Region
| | - T M T Nguyen
- Institute of Physics, National Chiao-Tung University, Hsinchu
| | - J P Ochoa-Ricoux
- Department of Physics and Astronomy, University of California, Irvine, California 92697
| | - A Olshevskiy
- Joint Institute for Nuclear Research, Dubna, Moscow Region
| | - J Park
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061
| | - S Patton
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - J C Peng
- Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - C S J Pun
- Department of Physics, The University of Hong Kong, Pokfulam, Hong Kong
| | - F Z Qi
- Institute of High Energy Physics, Beijing
| | - M Qi
- Nanjing University, Nanjing
| | - X Qian
- Brookhaven National Laboratory, Upton, New York 11973
| | - N Raper
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - J Ren
- China Institute of Atomic Energy, Beijing
| | - C Morales Reveco
- Department of Physics and Astronomy, University of California, Irvine, California 92697
| | - R Rosero
- Brookhaven National Laboratory, Upton, New York 11973
| | - B Roskovec
- Charles University, Faculty of Mathematics and Physics, Prague
| | - X C Ruan
- China Institute of Atomic Energy, Beijing
| | - B Russell
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - H Steiner
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
- Department of Physics, University of California, Berkeley, California 94720
| | - J L Sun
- China General Nuclear Power Group, Shenzhen
| | - T Tmej
- Charles University, Faculty of Mathematics and Physics, Prague
| | - K Treskov
- Joint Institute for Nuclear Research, Dubna, Moscow Region
| | - W-H Tse
- Chinese University of Hong Kong, Hong Kong
| | - C E Tull
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - Y C Tung
- Department of Physics, National Taiwan University, Taipei
| | - B Viren
- Brookhaven National Laboratory, Upton, New York 11973
| | - V Vorobel
- Charles University, Faculty of Mathematics and Physics, Prague
| | - C H Wang
- National United University, Miao-Li
| | - J Wang
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - M Wang
- Shandong University, Jinan
| | - N Y Wang
- Beijing Normal University, Beijing
| | - R G Wang
- Institute of High Energy Physics, Beijing
| | - W Wang
- Sun Yat-Sen (Zhongshan) University, Guangzhou
- College of William and Mary, Williamsburg, Virginia 23187
| | - X Wang
- College of Electronic Science and Engineering, National University of Defense Technology, Changsha
| | - Y Wang
- Nanjing University, Nanjing
| | - Y F Wang
- Institute of High Energy Physics, Beijing
| | - Z Wang
- Institute of High Energy Physics, Beijing
| | - Z Wang
- Department of Engineering Physics, Tsinghua University, Beijing
| | - Z M Wang
- Institute of High Energy Physics, Beijing
| | - H Y Wei
- Brookhaven National Laboratory, Upton, New York 11973
| | - L H Wei
- Institute of High Energy Physics, Beijing
| | - L J Wen
- Institute of High Energy Physics, Beijing
| | | | - C G White
- Department of Physics, Illinois Institute of Technology, Chicago, Illinois 60616
| | - H L H Wong
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
- Department of Physics, University of California, Berkeley, California 94720
| | - E Worcester
- Brookhaven National Laboratory, Upton, New York 11973
| | - D R Wu
- Institute of High Energy Physics, Beijing
| | - Q Wu
- Shandong University, Jinan
| | - W J Wu
- Institute of High Energy Physics, Beijing
| | - D M Xia
- Chongqing University, Chongqing
| | - Z Q Xie
- Institute of High Energy Physics, Beijing
| | - Z Z Xing
- Institute of High Energy Physics, Beijing
| | - H K Xu
- Institute of High Energy Physics, Beijing
| | - J L Xu
- Institute of High Energy Physics, Beijing
| | - T Xu
- Department of Engineering Physics, Tsinghua University, Beijing
| | - T Xue
- Department of Engineering Physics, Tsinghua University, Beijing
| | - C G Yang
- Institute of High Energy Physics, Beijing
| | - L Yang
- Dongguan University of Technology, Dongguan
| | - Y Z Yang
- Department of Engineering Physics, Tsinghua University, Beijing
| | - H F Yao
- Institute of High Energy Physics, Beijing
| | - M Ye
- Institute of High Energy Physics, Beijing
| | - M Yeh
- Brookhaven National Laboratory, Upton, New York 11973
| | - B L Young
- Iowa State University, Ames, Iowa 50011
| | - H Z Yu
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - Z Y Yu
- Institute of High Energy Physics, Beijing
| | - B B Yue
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - V Zavadskyi
- Brookhaven National Laboratory, Upton, New York 11973
- Joint Institute for Nuclear Research, Dubna, Moscow Region
| | - S Zeng
- Institute of High Energy Physics, Beijing
| | - Y Zeng
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - L Zhan
- Institute of High Energy Physics, Beijing
| | - C Zhang
- Brookhaven National Laboratory, Upton, New York 11973
| | - F Y Zhang
- Department of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai Laboratory for Particle Physics and Cosmology, Shanghai
| | - H H Zhang
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | | | - J W Zhang
- Institute of High Energy Physics, Beijing
| | - Q M Zhang
- Department of Nuclear Science and Technology, School of Energy and Power Engineering, Xi'an Jiaotong University, Xi'an
| | - S Q Zhang
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - X T Zhang
- Institute of High Energy Physics, Beijing
| | - Y M Zhang
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - Y X Zhang
- China General Nuclear Power Group, Shenzhen
| | - Y Y Zhang
- Department of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai Laboratory for Particle Physics and Cosmology, Shanghai
| | - Z J Zhang
- Dongguan University of Technology, Dongguan
| | - Z P Zhang
- University of Science and Technology of China, Hefei
| | - Z Y Zhang
- Institute of High Energy Physics, Beijing
| | - J Zhao
- Institute of High Energy Physics, Beijing
| | - R Z Zhao
- Institute of High Energy Physics, Beijing
| | - L Zhou
- Institute of High Energy Physics, Beijing
| | - H L Zhuang
- Institute of High Energy Physics, Beijing
| | - J H Zou
- Institute of High Energy Physics, Beijing
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Shen Y, Yuan H, Guo Z, Li XQ, Yang Z, Zong C. Exonuclease III Can Efficiently Cleave Linear Single-Stranded DNA: Reshaping Its Experimental Applications in Biosensors. Biosensors (Basel) 2023; 13:581. [PMID: 37366946 DOI: 10.3390/bios13060581] [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: 04/06/2023] [Revised: 05/18/2023] [Accepted: 05/24/2023] [Indexed: 06/28/2023]
Abstract
Exonuclease III (Exo III) has been generally used as a double-stranded DNA (dsDNA)-specific exonuclease that does not degrade single-stranded DNA (ssDNA). Here, we demonstrate that Exo III at concentrations above 0.1 unit/μL can efficiently digest linear ssDNA. Moreover, the dsDNA specificity of Exo III is the foundation of many DNA target recycling amplification (TRA) assays. We demonstrate that with 0.3 and 0.5 unit/μL Exo III, the degradation of an ssDNA probe, free or fixed on a solid surface, was not discernibly different, regardless of the presence or absence of target ssDNA, indicating that Exo III concentration is critical in TRA assays. The study has expanded the Exo III substrate scope from dsDNA to both dsDNA and ssDNA, which will reshape its experimental applications.
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Affiliation(s)
- Yi Shen
- State Key Laboratory of Marine Resource Utilization in South China Sea, Key Laboratory of Tropical Biological Resources of Ministry of Education, School of Pharmaceutical Sciences, Hainan University, Haikou 570228, China
| | - Haoyu Yuan
- State Key Laboratory of Marine Resource Utilization in South China Sea, Key Laboratory of Tropical Biological Resources of Ministry of Education, School of Pharmaceutical Sciences, Hainan University, Haikou 570228, China
| | - Zixuan Guo
- State Key Laboratory of Marine Resource Utilization in South China Sea, Key Laboratory of Tropical Biological Resources of Ministry of Education, School of Pharmaceutical Sciences, Hainan University, Haikou 570228, China
| | - Xiu-Qing Li
- Fredericton Research and Development Centre, Agriculture and Agri-Food Canada, Fredericton, NB E3B 4Z7, Canada
- NutraHealth Products and Technologies Inc., Fredericton, NB E3B 6J5, Canada
| | - Zhiqing Yang
- State Key Laboratory of Marine Resource Utilization in South China Sea, Key Laboratory of Tropical Biological Resources of Ministry of Education, School of Pharmaceutical Sciences, Hainan University, Haikou 570228, China
- Rizhao Science and Technology Innovation Service Center, Rizhao 276825, China
| | - Chengli Zong
- State Key Laboratory of Marine Resource Utilization in South China Sea, Key Laboratory of Tropical Biological Resources of Ministry of Education, School of Pharmaceutical Sciences, Hainan University, Haikou 570228, China
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An FP, Bai WD, Balantekin AB, Bishai M, Blyth S, Cao GF, Cao J, Chang JF, Chang Y, Chen HS, Chen HY, Chen SM, Chen Y, Chen YX, Chen ZY, Cheng J, Cheng ZK, Cherwinka JJ, Chu MC, Cummings JP, Dalager O, Deng FS, Ding YY, Ding XY, Diwan MV, Dohnal T, Dolzhikov D, Dove J, Duyang HY, Dwyer DA, Gallo JP, Gonchar M, Gong GH, Gong H, Gu WQ, Guo JY, Guo L, Guo XH, Guo YH, Guo Z, Hackenburg RW, Han Y, Hans S, He M, Heeger KM, Heng YK, Hor YK, Hsiung YB, Hu BZ, Hu JR, Hu T, Hu ZJ, Huang HX, Huang JH, Huang XT, Huang YB, Huber P, Jaffe DE, Jen KL, Ji XL, Ji XP, Johnson RA, Jones D, Kang L, Kettell SH, Kohn S, Kramer M, Langford TJ, Lee J, Lee JHC, Lei RT, Leitner R, Leung JKC, Li F, Li HL, Li JJ, Li QJ, Li RH, Li S, Li SC, Li WD, Li XN, Li XQ, Li YF, Li ZB, Liang H, Lin CJ, Lin GL, Lin S, Ling JJ, Link JM, Littenberg L, Littlejohn BR, Liu JC, Liu JL, Liu JX, Lu C, Lu HQ, Luk KB, Ma BZ, Ma XB, Ma XY, Ma YQ, Mandujano RC, Marshall C, McDonald KT, McKeown RD, Meng Y, Napolitano J, Naumov D, Naumova E, Nguyen TMT, Ochoa-Ricoux JP, Olshevskiy A, Pan HR, Park J, Patton S, Peng JC, Pun CSJ, Qi FZ, Qi M, Qian X, Raper N, Ren J, Morales Reveco C, Rosero R, Roskovec B, Ruan XC, Russell B, Steiner H, Sun JL, Tmej T, Treskov K, Tse WH, Tull CE, Viren B, Vorobel V, Wang CH, Wang J, Wang M, Wang NY, Wang RG, Wang W, Wang X, Wang Y, Wang YF, Wang Z, Wang Z, Wang ZM, Wei HY, Wei LH, Wei W, Wen LJ, Whisnant K, White CG, Wong HLH, Worcester E, Wu DR, Wu Q, Wu WJ, Xia DM, Xie ZQ, Xing ZZ, Xu HK, Xu JL, Xu T, Xue T, Yang CG, Yang L, Yang YZ, Yao HF, Ye M, Yeh M, Young BL, Yu HZ, Yu ZY, Yue BB, Zavadskyi V, Zeng S, Zeng Y, Zhan L, Zhang C, Zhang FY, Zhang HH, Zhang JL, Zhang JW, Zhang QM, Zhang SQ, Zhang XT, Zhang YM, Zhang YX, Zhang YY, Zhang ZJ, Zhang ZP, Zhang ZY, Zhao J, Zhao RZ, Zhou L, Zhuang HL, Zou JH. Precision Measurement of Reactor Antineutrino Oscillation at Kilometer-Scale Baselines by Daya Bay. Phys Rev Lett 2023; 130:161802. [PMID: 37154643 DOI: 10.1103/physrevlett.130.161802] [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: 12/01/2022] [Accepted: 02/24/2023] [Indexed: 05/10/2023]
Abstract
We present a new determination of the smallest neutrino mixing angle θ_{13} and the mass-squared difference Δm_{32}^{2} using a final sample of 5.55×10^{6} inverse beta-decay (IBD) candidates with the final-state neutron captured on gadolinium. This sample is selected from the complete dataset obtained by the Daya Bay reactor neutrino experiment in 3158 days of operation. Compared to the previous Daya Bay results, selection of IBD candidates has been optimized, energy calibration refined, and treatment of backgrounds further improved. The resulting oscillation parameters are sin^{2}2θ_{13}=0.0851±0.0024, Δm_{32}^{2}=(2.466±0.060)×10^{-3} eV^{2} for the normal mass ordering or Δm_{32}^{2}=-(2.571±0.060)×10^{-3} eV^{2} for the inverted mass ordering.
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Affiliation(s)
- F P An
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - W D Bai
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | | | - M Bishai
- Brookhaven National Laboratory, Upton, New York 11973
| | - S Blyth
- Department of Physics, National Taiwan University, Taipei
| | - G F Cao
- Institute of High Energy Physics, Beijing
| | - J Cao
- Institute of High Energy Physics, Beijing
| | - J F Chang
- Institute of High Energy Physics, Beijing
| | - Y Chang
- National United University, Miao-Li
| | - H S Chen
- Institute of High Energy Physics, Beijing
| | - H Y Chen
- Department of Engineering Physics, Tsinghua University, Beijing
| | - S M Chen
- Department of Engineering Physics, Tsinghua University, Beijing
| | - Y Chen
- Sun Yat-Sen (Zhongshan) University, Guangzhou
- Shenzhen University, Shenzhen
| | - Y X Chen
- North China Electric Power University, Beijing
| | - Z Y Chen
- Institute of High Energy Physics, Beijing
| | - J Cheng
- North China Electric Power University, Beijing
| | - Z K Cheng
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | | | - M C Chu
- Chinese University of Hong Kong, Hong Kong
| | | | - O Dalager
- Department of Physics and Astronomy, University of California, Irvine, California 92697
| | - F S Deng
- University of Science and Technology of China, Hefei
| | - Y Y Ding
- Institute of High Energy Physics, Beijing
| | | | - M V Diwan
- Brookhaven National Laboratory, Upton, New York 11973
| | - T Dohnal
- Charles University, Faculty of Mathematics and Physics, Prague
| | - D Dolzhikov
- Joint Institute for Nuclear Research, Dubna, Moscow Region
| | - J Dove
- Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | | | - D A Dwyer
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - J P Gallo
- Department of Physics, Illinois Institute of Technology, Chicago, Illinois 60616
| | - M Gonchar
- Joint Institute for Nuclear Research, Dubna, Moscow Region
| | - G H Gong
- Department of Engineering Physics, Tsinghua University, Beijing
| | - H Gong
- Department of Engineering Physics, Tsinghua University, Beijing
| | - W Q Gu
- Brookhaven National Laboratory, Upton, New York 11973
| | - J Y Guo
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - L Guo
- Department of Engineering Physics, Tsinghua University, Beijing
| | - X H Guo
- Beijing Normal University, Beijing
| | - Y H Guo
- Department of Nuclear Science and Technology, School of Energy and Power Engineering, Xi'an Jiaotong University, Xi'an
| | - Z Guo
- Department of Engineering Physics, Tsinghua University, Beijing
| | | | - Y Han
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - S Hans
- Brookhaven National Laboratory, Upton, New York 11973
| | - M He
- Institute of High Energy Physics, Beijing
| | - K M Heeger
- Wright Laboratory and Department of Physics, Yale University, New Haven, Connecticut 06520
| | - Y K Heng
- Institute of High Energy Physics, Beijing
| | - Y K Hor
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - Y B Hsiung
- Department of Physics, National Taiwan University, Taipei
| | - B Z Hu
- Department of Physics, National Taiwan University, Taipei
| | - J R Hu
- Institute of High Energy Physics, Beijing
| | - T Hu
- Institute of High Energy Physics, Beijing
| | - Z J Hu
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - H X Huang
- China Institute of Atomic Energy, Beijing
| | - J H Huang
- Institute of High Energy Physics, Beijing
| | | | - Y B Huang
- Guangxi University, No.100 Daxue East Road, Nanning
| | - P Huber
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061
| | - D E Jaffe
- Brookhaven National Laboratory, Upton, New York 11973
| | - K L Jen
- Institute of Physics, National Chiao-Tung University, Hsinchu
| | - X L Ji
- Institute of High Energy Physics, Beijing
| | - X P Ji
- Brookhaven National Laboratory, Upton, New York 11973
| | - R A Johnson
- Department of Physics, University of Cincinnati, Cincinnati, Ohio 45221
| | - D Jones
- Department of Physics, College of Science and Technology, Temple University, Philadelphia, Pennsylvania 19122
| | - L Kang
- Dongguan University of Technology, Dongguan
| | - S H Kettell
- Brookhaven National Laboratory, Upton, New York 11973
| | - S Kohn
- Department of Physics, University of California, Berkeley, California 94720
| | - M Kramer
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
- Department of Physics, University of California, Berkeley, California 94720
| | - T J Langford
- Wright Laboratory and Department of Physics, Yale University, New Haven, Connecticut 06520
| | - J Lee
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - J H C Lee
- Department of Physics, The University of Hong Kong, Pokfulam, Hong Kong
| | - R T Lei
- Dongguan University of Technology, Dongguan
| | - R Leitner
- Charles University, Faculty of Mathematics and Physics, Prague
| | - J K C Leung
- Department of Physics, The University of Hong Kong, Pokfulam, Hong Kong
| | - F Li
- Institute of High Energy Physics, Beijing
| | - H L Li
- Institute of High Energy Physics, Beijing
| | - J J Li
- Department of Engineering Physics, Tsinghua University, Beijing
| | - Q J Li
- Institute of High Energy Physics, Beijing
| | - R H Li
- Institute of High Energy Physics, Beijing
| | - S Li
- Dongguan University of Technology, Dongguan
| | - S C Li
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061
| | - W D Li
- Institute of High Energy Physics, Beijing
| | - X N Li
- Institute of High Energy Physics, Beijing
| | - X Q Li
- School of Physics, Nankai University, Tianjin
| | - Y F Li
- Institute of High Energy Physics, Beijing
| | - Z B Li
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - H Liang
- University of Science and Technology of China, Hefei
| | - C J Lin
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - G L Lin
- Institute of Physics, National Chiao-Tung University, Hsinchu
| | - S Lin
- Dongguan University of Technology, Dongguan
| | - J J Ling
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - J M Link
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061
| | - L Littenberg
- Brookhaven National Laboratory, Upton, New York 11973
| | - B R Littlejohn
- Department of Physics, Illinois Institute of Technology, Chicago, Illinois 60616
| | - J C Liu
- Institute of High Energy Physics, Beijing
| | - J L Liu
- Department of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai Laboratory for Particle Physics and Cosmology, Shanghai
| | - J X Liu
- Institute of High Energy Physics, Beijing
| | - C Lu
- Joseph Henry Laboratories, Princeton University, Princeton, New Jersey 08544
| | - H Q Lu
- Institute of High Energy Physics, Beijing
| | - K B Luk
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
- Department of Physics, University of California, Berkeley, California 94720
- The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong
| | - B Z Ma
- Shandong University, Jinan
| | - X B Ma
- North China Electric Power University, Beijing
| | - X Y Ma
- Institute of High Energy Physics, Beijing
| | - Y Q Ma
- Institute of High Energy Physics, Beijing
| | - R C Mandujano
- Department of Physics and Astronomy, University of California, Irvine, California 92697
| | - C Marshall
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - K T McDonald
- Joseph Henry Laboratories, Princeton University, Princeton, New Jersey 08544
| | - R D McKeown
- California Institute of Technology, Pasadena, California 91125
- College of William and Mary, Williamsburg, Virginia 23187
| | - Y Meng
- Department of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai Laboratory for Particle Physics and Cosmology, Shanghai
| | - J Napolitano
- Department of Physics, College of Science and Technology, Temple University, Philadelphia, Pennsylvania 19122
| | - D Naumov
- Joint Institute for Nuclear Research, Dubna, Moscow Region
| | - E Naumova
- Joint Institute for Nuclear Research, Dubna, Moscow Region
| | - T M T Nguyen
- Institute of Physics, National Chiao-Tung University, Hsinchu
| | - J P Ochoa-Ricoux
- Department of Physics and Astronomy, University of California, Irvine, California 92697
| | - A Olshevskiy
- Joint Institute for Nuclear Research, Dubna, Moscow Region
| | - H-R Pan
- Department of Physics, National Taiwan University, Taipei
| | - J Park
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061
| | - S Patton
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - J C Peng
- Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - C S J Pun
- Department of Physics, The University of Hong Kong, Pokfulam, Hong Kong
| | - F Z Qi
- Institute of High Energy Physics, Beijing
| | - M Qi
- Nanjing University, Nanjing
| | - X Qian
- Brookhaven National Laboratory, Upton, New York 11973
| | - N Raper
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - J Ren
- China Institute of Atomic Energy, Beijing
| | - C Morales Reveco
- Department of Physics and Astronomy, University of California, Irvine, California 92697
| | - R Rosero
- Brookhaven National Laboratory, Upton, New York 11973
| | - B Roskovec
- Charles University, Faculty of Mathematics and Physics, Prague
| | - X C Ruan
- China Institute of Atomic Energy, Beijing
| | - B Russell
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - H Steiner
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
- Department of Physics, University of California, Berkeley, California 94720
| | - J L Sun
- China General Nuclear Power Group, Shenzhen
| | - T Tmej
- Charles University, Faculty of Mathematics and Physics, Prague
| | - K Treskov
- Joint Institute for Nuclear Research, Dubna, Moscow Region
| | - W-H Tse
- Chinese University of Hong Kong, Hong Kong
| | - C E Tull
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - B Viren
- Brookhaven National Laboratory, Upton, New York 11973
| | - V Vorobel
- Charles University, Faculty of Mathematics and Physics, Prague
| | - C H Wang
- National United University, Miao-Li
| | - J Wang
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - M Wang
- Shandong University, Jinan
| | - N Y Wang
- Beijing Normal University, Beijing
| | - R G Wang
- Institute of High Energy Physics, Beijing
| | - W Wang
- Sun Yat-Sen (Zhongshan) University, Guangzhou
- College of William and Mary, Williamsburg, Virginia 23187
| | - X Wang
- College of Electronic Science and Engineering, National University of Defense Technology, Changsha
| | - Y Wang
- Nanjing University, Nanjing
| | - Y F Wang
- Institute of High Energy Physics, Beijing
| | - Z Wang
- Institute of High Energy Physics, Beijing
| | - Z Wang
- Department of Engineering Physics, Tsinghua University, Beijing
| | - Z M Wang
- Institute of High Energy Physics, Beijing
| | - H Y Wei
- Brookhaven National Laboratory, Upton, New York 11973
| | - L H Wei
- Institute of High Energy Physics, Beijing
| | - W Wei
- Shandong University, Jinan
| | - L J Wen
- Institute of High Energy Physics, Beijing
| | | | - C G White
- Department of Physics, Illinois Institute of Technology, Chicago, Illinois 60616
| | - H L H Wong
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
- Department of Physics, University of California, Berkeley, California 94720
| | - E Worcester
- Brookhaven National Laboratory, Upton, New York 11973
| | - D R Wu
- Institute of High Energy Physics, Beijing
| | - Q Wu
- Shandong University, Jinan
| | - W J Wu
- Institute of High Energy Physics, Beijing
| | - D M Xia
- Chongqing University, Chongqing
| | - Z Q Xie
- Institute of High Energy Physics, Beijing
| | - Z Z Xing
- Institute of High Energy Physics, Beijing
| | - H K Xu
- Institute of High Energy Physics, Beijing
| | - J L Xu
- Institute of High Energy Physics, Beijing
| | - T Xu
- Department of Engineering Physics, Tsinghua University, Beijing
| | - T Xue
- Department of Engineering Physics, Tsinghua University, Beijing
| | - C G Yang
- Institute of High Energy Physics, Beijing
| | - L Yang
- Dongguan University of Technology, Dongguan
| | - Y Z Yang
- Department of Engineering Physics, Tsinghua University, Beijing
| | - H F Yao
- Institute of High Energy Physics, Beijing
| | - M Ye
- Institute of High Energy Physics, Beijing
| | - M Yeh
- Brookhaven National Laboratory, Upton, New York 11973
| | - B L Young
- Iowa State University, Ames, Iowa 50011
| | - H Z Yu
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - Z Y Yu
- Institute of High Energy Physics, Beijing
| | - B B Yue
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - V Zavadskyi
- Joint Institute for Nuclear Research, Dubna, Moscow Region
| | - S Zeng
- Institute of High Energy Physics, Beijing
| | - Y Zeng
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - L Zhan
- Institute of High Energy Physics, Beijing
| | - C Zhang
- Brookhaven National Laboratory, Upton, New York 11973
| | - F Y Zhang
- Department of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai Laboratory for Particle Physics and Cosmology, Shanghai
| | - H H Zhang
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | | | - J W Zhang
- Institute of High Energy Physics, Beijing
| | - Q M Zhang
- Department of Nuclear Science and Technology, School of Energy and Power Engineering, Xi'an Jiaotong University, Xi'an
| | - S Q Zhang
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - X T Zhang
- Institute of High Energy Physics, Beijing
| | - Y M Zhang
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - Y X Zhang
- China General Nuclear Power Group, Shenzhen
| | - Y Y Zhang
- Department of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai Laboratory for Particle Physics and Cosmology, Shanghai
| | - Z J Zhang
- Dongguan University of Technology, Dongguan
| | - Z P Zhang
- University of Science and Technology of China, Hefei
| | - Z Y Zhang
- Institute of High Energy Physics, Beijing
| | - J Zhao
- Institute of High Energy Physics, Beijing
| | - R Z Zhao
- Institute of High Energy Physics, Beijing
| | - L Zhou
- Institute of High Energy Physics, Beijing
| | - H L Zhuang
- Institute of High Energy Physics, Beijing
| | - J H Zou
- Institute of High Energy Physics, Beijing
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Si TG, Li L, Guo Z, Xu B. [Chinese expert consensus on perioperative management of renal tumor cryoablation (2022 edition)]. Zhonghua Nei Ke Za Zhi 2023; 62:363-368. [PMID: 37032130 DOI: 10.3760/cma.j.cn112138-20221024-00780] [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: 04/11/2023]
Abstract
In recent years, the incidence of renal cancer has been increasing continuously. Surgical resection is the "gold standard" for the treatment of small renal cancer. However, local ablation therapy of renal cancer is undoubtedly the best choice for patients with short life expectancy, other complications, and impaired renal function who are not suitable for surgery. In recent years, with the development of ablation techniques and long-term follow-up, local ablation has shown good therapeutic effects. As many domestic hospitals are performing or planning to perform renal tumor cryoablation to improve the clinical cure rate and surgical safety of renal tumor cryoablation, it is necessary to standardize the surgical indications, contraindications, perioperative management, efficacy evaluation, and other common problems. Currently, there is no expert consensus regarding perioperative renal tumor cryoablation in China. To standardize the perioperative management of renal tumor cryoablation and related technical operations in clinical practice, and improve the effectiveness and safety of cryoablation, the expert committee of Tumor Interventional and Minimally Invasive Diagnosis and Treatment Continuing Education Base of the Chinese Anti-Cancer Association convened experts in related fields to discuss and formulate this consensus, which is hereby published, for clinical reference and application.
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Affiliation(s)
- T G Si
- Department of Interventional Therapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China
| | - L Li
- Department of Urology, Shanghai Ninth People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 200011, China
| | - Z Guo
- Department of Interventional Therapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China
| | - B Xu
- Department of Urology, Shanghai Ninth People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 200011, China
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23
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Ju Y, Liu K, Ma G, Zhu B, Wang H, Hu Z, Zhao J, Zhang L, Cui K, He XR, Huang M, Li Y, Xu S, Gao Y, Liu K, Liu H, Zhuo Z, Zhang G, Guo Z, Ye Y, Zhang L, Zhou X, Ma S, Qiu Y, Zhang M, Tao Y, Zhang M, Xian L, Xie W, Wang G, Wang Y, Wang C, Wang DH, Yu K. Bacterial antibiotic resistance among cancer inpatients in China: 2016-20. QJM 2023; 116:213-220. [PMID: 36269193 DOI: 10.1093/qjmed/hcac244] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 09/16/2022] [Accepted: 10/10/2022] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND The incidence of infections among cancer patients is as high as 23.2-33.2% in China. However, the lack of information and data on the number of antibiotics used by cancer patients is an obstacle to implementing antibiotic management plans. AIM This study aimed to investigate bacterial infections and antibiotic resistance in Chinese cancer patients to provide a reference for the rational use of antibiotics. DESIGN This was a 5-year retrospective study on the antibiotic resistance of cancer patients. METHODS In this 5-year surveillance study, we collected bacterial and antibiotic resistance data from 20 provincial cancer diagnosis and treatment centers and three specialized cancer hospitals in China. We analyzed the resistance of common bacteria to antibiotics, compared to common clinical drug-resistant bacteria, evaluated the evolution of critical drug-resistant bacteria and conducted data analysis. FINDINGS Between 2016 and 2020, 216 219 bacterial strains were clinically isolated. The resistance trend of Escherichia coli and Klebsiella pneumoniae to amikacin, ciprofloxacin, cefotaxime, piperacillin/tazobactam and imipenem was relatively stable and did not significantly increase over time. The resistance of Pseudomonas aeruginosa strains to all antibiotics tested, including imipenem and meropenem, decreased over time. In contrast, the resistance of Acinetobacter baumannii strains to carbapenems increased from 4.7% to 14.7%. Methicillin-resistant Staphylococcus aureus (MRSA) significantly decreased from 65.2% in 2016 to 48.9% in 2020. CONCLUSIONS The bacterial prevalence and antibiotic resistance rates of E. coli, K. pneumoniae, P. aeruginosa, A. baumannii, S. aureus and MRSA were significantly lower than the national average.
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Affiliation(s)
- Y Ju
- From the Department of Critical Care Medicine, Harbin Medical University Cancer Hospital, Harbin, China
| | - K Liu
- Department of Critical Care Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - G Ma
- Department of Critical Care Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - B Zhu
- Department of Critical Care Medicine, Fudan University Shanghai Cancer Center, Shanghai, China
| | - H Wang
- Department of Critical Care Medicine, Peking University Cancer Hospital & Institute, Beijing, China
| | - Z Hu
- Department of Critical Care Medicine, Hebei Tumor Hospital, Shijiazhuang, China
| | - J Zhao
- Department of Critical Care Medicine, Hunan Cancer Hospital, Changsha, China
| | - L Zhang
- Department of Critical Care Medicine, Hubei Cancer Hospital, Wuhan, China
| | - K Cui
- Department of Critical Care Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - X-R He
- Department of Critical Care Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - M Huang
- Department of Critical Care Medicine, Shanxi Tumor Hospital, Taiyuan, China
| | - Y Li
- Department of Critical Care Medicine, Guangxi Medical University Cancer Hospital, Nanning, China
| | - S Xu
- Department of Critical Care Medicine, Sichuan Cancer Hospital, Chengdu, China
| | - Y Gao
- Department of Critical Care Medicine, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, China
| | - K Liu
- Department of Critical Care Medicine, Zhejiang Cancer Hospital, Hangzhou, China
| | - H Liu
- From the Department of Critical Care Medicine, Harbin Medical University Cancer Hospital, Harbin, China
| | - Z Zhuo
- From the Department of Critical Care Medicine, Harbin Medical University Cancer Hospital, Harbin, China
| | - G Zhang
- Department of Critical Care Medicine, Jilin Tumor Hospital, Changchun, China
| | - Z Guo
- Department of Critical Care Medicine, Shandong Cancer Hospital and Institute, Shandong, China
| | - Y Ye
- Department of Critical Care Medicine, Fujian Cancer Hospital, Fuzhou, China
| | - L Zhang
- Department of Critical Care Medicine, Anhui Provincial Cancer Hospital, Hefei, China
| | - X Zhou
- Department of Critical Care Medicine, Gansu Provincial Cancer Hospital, Lanzhou, China
| | - S Ma
- Department of Critical Care Medicine, Jiangsu Cancer Hospital, Nanjing, China
| | - Y Qiu
- Department of Critical Care Medicine, Jiangxi Cancer Hospital, Nanchang, China
| | - M Zhang
- Department of Critical Care Medicine, Hangzhou Cancer Hospital, Hangzhou, China
| | - Y Tao
- Department of Critical Care Medicine, Nantong Tumor Hospital, Nantong, China
| | - M Zhang
- Department of Critical Care Medicine, Baotou Cancer Hospital, Baotou, China
| | - L Xian
- Department of Critical Care Medicine, Affiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou, China
| | - W Xie
- Department of Critical Care Medicine, The Affiliated Cancer Hospital of Guizhou Medical University, Guiyang, China
| | - G Wang
- Department of Critical Care Medicine, The First Hospital of Jilin University, Changchun, China
| | - Y Wang
- Department of Critical Care Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - C Wang
- From the Department of Critical Care Medicine, Harbin Medical University Cancer Hospital, Harbin, China
| | - D-H Wang
- Department of Critical Care Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - K Yu
- Department of Critical Care Medicine, The First Affiliated Hospital of Harbin Medical University, Harbin, China
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Guo Z, Wang Z, Ji W. [Selection of classic laryngeal mask airway size based on ideal body mass in patients with low body mass index: a randomized trial]. Nan Fang Yi Ke Da Xue Xue Bao 2023; 43:460-465. [PMID: 37087592 PMCID: PMC10122727 DOI: 10.12122/j.issn.1673-4254.2023.03.17] [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] [Indexed: 04/24/2023]
Abstract
OBJECTIVE To compare the effect of laryngeal mask airway (LMA) size selection based on ideal and actual body mass on the success rate of first insertion in patients with low body mass index (BMI). METHODS This study was performed in 137 patients aged 18-60 years with BMI below 18.5 kg/m2, in whom discrepancies occurred in the selection of LMA size based on their actual body mass and the ideal body mass. The patients were randomized divided into ideal body mass group and actual body mass group, in which the size of LMA was selected based on the ideal body mass and their actual body mass, respectively. The success rate of first LMA insertion, overall success rate, fiberoptic visual field grade, leakage pressure, and LMA-related complications of the patients were recorded during the maintenance and recovery of anesthesia. RESULTS The success rate of first LMA insertion was significantly higher in ideal body mass group than in the actual body mass group (86.8% vs 68.1%, P=0.016). Compared with those in the actual body mass group, the patients in the ideal body mass group used larger LMA (P < 0.005) and had better fiberoptic field scores (P=0.001) and higher airway seal pressure (P < 0.005). The peak inspiratory pressure (P=0.154) or the incidence of LMA-related complications during anesthesia maintenance and recovery did not differ significantly between the two groups (P>0.05). CONCLUSION The size selection of LMA based on the ideal body mass of the patients, determined according to their height and sex, can significantly improve the success rate of first LMA insertion in patients with low BMI.
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Affiliation(s)
- Z Guo
- Department of Anesthesiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080, China
| | - Z Wang
- Department of Anesthesiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080, China
| | - W Ji
- Department of Anesthesiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080, China
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Wang K, Tao J, Hu Z, Guo Z, Li J, Guo W. Association Between Gastric Antral Cross-sectional Area and Postoperative Nausea and Vomiting in Patients Undergoing Laparoscopic Cholecystectomy. J Coll Physicians Surg Pak 2023; 33:249-253. [PMID: 36945151 DOI: 10.29271/jcpsp.2023.03.249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Accepted: 02/24/2023] [Indexed: 03/23/2023]
Abstract
OBJECTIVE To explore the predictive value of gastric antral cross-sectional area (CSA) in the occurrence of postoperative nausea and vomiting (PONV) by analysing the association between gastric antral CSA measured by ultrasound and frequency of PONV after laparoscopic cholecystectomy. STUDY DESIGN Observational study. Place and Duration of the Study: Department of Anaesthesiology, The First Hospital of Wannan Medical College, Yijishan Hospital of Wannan Medical College, from October 2021 to February 2022. METHODOLOGY Gastric antral ultrasound (US) was performed in 266 patients undergoing laparoscopic cholecystectomy (LC) before anaesthesia induction, after it, and after surgery. The data obtained were used to evaluate the relationship between gastric antral CSA and PONV. RESULTS The gastric antral CSA in Semi-recumbent decubitus (SRD) position >398.85 mm2 (AUC=0.623) highly indicated the occurrence of PONV. In addition, the subject performance characteristic curve of a binary logistics retrospective model for predicting PONV (AUC=0.805) highly indicated the occurrence of PONV. CONCLUSION Gastric US assessment of gastric antral CSA might change the current assessment model of PONV risk. This study showed that the gastric antral CSA in the SRD position after anaesthesia induction and a binary logistics retrospective model could be used to predict the occurrence of PONV, which could be helpful to adjust intraoperative and postoperative interventions and accelerate the recovery of patients. KEY WORDS Postoperative nausea and vomiting, Gastric ultrasound, Gastric cross-sectional area, Perioperative period.
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Affiliation(s)
- Kai Wang
- Department of Anaesthesiology, The First Affiliated Hospital of Wannan Medical College, Wuhu, Anhui Province, China
| | - Junyu Tao
- Department of Anaesthesiology, The First Affiliated Hospital of Wannan Medical College, Wuhu, Anhui Province, China
| | - Zhangrui Hu
- Department of Anaesthesiology, The First Affiliated Hospital of Wannan Medical College, Wuhu, Anhui Province, China
| | - Zixuan Guo
- Department of Anaesthesiology, The First Affiliated Hospital of Wannan Medical College, Wuhu, Anhui Province, China
| | - Jing Li
- Department of Anaesthesiology, The First Affiliated Hospital of Wannan Medical College, Wuhu, Anhui Province, China
| | - Wenjun Guo
- Department of Anaesthesiology, The First Affiliated Hospital of Wannan Medical College, Wuhu, Anhui Province, China
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Gu X, Guo Z, Cai M, Shi Y, Wang S, Xie F. Paced breathing and respiratory movement responses evoked by bidirectional constant current stimulation in anesthetized rabbits. Front Bioeng Biotechnol 2023; 10:1109892. [PMID: 36714628 PMCID: PMC9877234 DOI: 10.3389/fbioe.2022.1109892] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Accepted: 12/30/2022] [Indexed: 01/13/2023] Open
Abstract
Objective: Diaphragm pacing (DP) is a long-term and effective respiratory assist therapy for patients with central alveolar hypoventilation and high cervical spinal cord injury. The existing DP system has some limitations, especially high price, inconvenience preoperative evaluation methods and diaphragm fatigue easily. Our objective was to develop a DP system and evaluated reliability through hardware testing and animal experiments. Methods: A DP system with bidirectional constant current was designed, manufactured and tested. Effects of a wide range of stimulus amplitudes (range: .5-2.5 mA) and frequencies (range: 10-250 Hz) on airflow and corresponding inspired volume were investigated during DP. Differences in airflow characteristics under various stimulation parameters were evaluated using power function. ECG interference in diaphragm electromyography (EMGdi) was filtered out using stationary wavelet transform to obtain pure EMGdi (EMGdip). 80-min period with a tendency for diaphragm fatigue by root mean square (RMS) and centroid frequency (f c ) of EMGdip was studied. Results: The increase of stimulus frequency and amplitude in animals resulted in different degrees of increase in envoked volume. Significant difference in Airflow Index (b) between anesthesia and DP provided a simple, non-invasive and feasible solution for phrenic nerve conduction function test. Increased stimulation duration with the developed DP system caused less diaphragm fatigue. Conclusion: A modular, inexpensive and reliable DP was successfully developed. Its effectiveness was confirmed in animal experiments. Significance: This study is useful for design of future implantable diaphragmatic pacemakers for improving diaphragm fatigue and convenient assessment of respiratory activity in experiments.
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Affiliation(s)
- Xiaoyu Gu
- School of Biology and Medical Engineering, Beihang University, Beijing, China
| | - Zixuan Guo
- Medical School of Chinese PLA, Beijing, China
| | - Maolin Cai
- School of Automation Science and Electrical Engineering, Beihang University, Beijing, China
| | - Yan Shi
- School of Automation Science and Electrical Engineering, Beihang University, Beijing, China,*Correspondence: Yan Shi, ; Fei Xie,
| | - Shoukun Wang
- School of Automation, Beijing Institute of Technology, Beijing, China
| | - Fei Xie
- Department of Pulmonary and Critical Care Medicine, Chinese PLA General Hospital, Beijing, China,*Correspondence: Yan Shi, ; Fei Xie,
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Guo Z, Tan X, Yuan H, Zhang L, Wu J, Yang Z, Qu K, Wan Y. Bis-enzyme cascade CRISPR-Cas12a platform for miRNA detection. Talanta 2023; 252:123837. [DOI: 10.1016/j.talanta.2022.123837] [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] [Received: 03/09/2022] [Revised: 07/23/2022] [Accepted: 08/08/2022] [Indexed: 11/17/2022]
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Mu R, Meng Z, Guo Z, Qin X, Huang G, Yang X, Jin H, Yang P, Deng M, Zhang X, Zhu X. Diagnostic value of dual-layer spectral detector CT in differentiating lung adenocarcinoma from squamous cell carcinoma. Front Oncol 2022; 12:868216. [DOI: 10.3389/fonc.2022.868216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 11/14/2022] [Indexed: 12/03/2022] Open
Abstract
Background and objectiveThe pathological type of non–small cell lung cancer is considered to be an important factor affecting the treatment and prognosis. The purpose of this study was to investigate the diagnostic value of spectral parameters of dual-layer spectral detector computed tomography (DLCT) in determining efficacy to distinguish adenocarcinoma (AC) and squamous cell carcinoma (SC), and their combined diagnostic efficacy was also analyzed.MethodsThis is a single-center prospective study, and we collected 70 patients with lung SC and 127 patients with lung AC confirmed by histopathological examination. Morphological parameters, plain scan CT value, biphasic enhanced CT value, and spectral parameters were calculated. The diagnostic efficiency of morphological parameters, spectral parameters, and spectral parameters combined with morphological parameters was obtained by statistical analysis.ResultsIn univariate analysis, seven morphological CT features differed significantly between SC and AC: tumor location (distribution), lobulation, spicule, air bronchogram, vacuole sign, lung atelectasis and/or obstructive pneumonia, and vascular involvement (all p < 0.05). In the arterial phase and the venous phase, the spectral parameters of AC were higher than those of SC (AP-Zeff: 8.07 ± 0.23 vs. 7.85 ± 0.16; AP-ID: 1.41 ± 0.47 vs. 0.94 ± 0.28; AP-NID: 0.13 ± 0.04 vs. 0.09 ± 0.03; AP-λ: 3.42 ± 1.10 vs. 2.33 ± 0.96; VP-Zeff: 8.26 ± 0.23 vs. 7.96 ± 0.16; VP-ID: 1.18 ± 0.51 vs. 1.16 ± 0.30; VP-NID: 0.39 ± 0.13 vs. 0.29 ± 0.08; VP-λ: 4.42 ± 1.28 vs. 2.85 ± 0.72; p < 0.001). When conducting multivariate analysis combining CT features and DLCT parameters with the best diagnostic efficacy, the independent predictors of AC were distribution on peripheral (OR, 4.370; 95% CI, 1.485–12.859; p = 0.007), presence of air bronchogram (OR, 5.339; 95% CI, 1.729–16.484; p = 0.004), and presence of vacuole sign ( OR, 7.330; 95% CI, 1.030–52.184; p = 0.047). Receiver operating characteristic curves of the SC and AC showed that VP-λ had the best diagnostic performance, with an area under the curve (AUC) of 0.864 and sensitivity and specificity rates of 85.8% and 74.3%, respectively; the AUC was increased to 0.946 when morphological parameters were combined, and sensitivity and specificity rates were 89.8% and 87.1%, respectively.ConclusionThe quantitative parameters of the DLCT spectrum are of great value in the diagnosis of SC and AC, and the combination of morphological parameters and spectral parameters is helpful to distinguish SC from AC.
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Manickam A, Peterson J, Mei W, Murdoch D, Margolis D, Oesterling A, Guo Z, Rudin C, Jiang Y, Browne E. PP 1.33 – 00167 Integrated single-cell multi-omic profiling of HIV latency reversal. J Virus Erad 2022. [DOI: 10.1016/j.jve.2022.100137] [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: 12/24/2022] Open
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Guo Z, Li L, Han W, Guo Z. SF 6 High-Voltage Circuit Breaker Contact Status Detection at Different Currents. Sensors (Basel) 2022; 22:8490. [PMID: 36366185 PMCID: PMC9657242 DOI: 10.3390/s22218490] [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] [Figures] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 10/31/2022] [Accepted: 11/01/2022] [Indexed: 06/16/2023]
Abstract
Currently, the online non-destructive testing (NDT) methods to measure the contact states of high-voltage circuit breakers (HVCBs) with SF6 gas as a quenching medium are lacking. This paper aims to put forward a novel method to detect the contact state of an HVCB based on the vibrational signal. First, for a 40.5-kV SF6 HVCB prototype, a mechanical vibration detection system along with a high-current generator to provide the test current is designed. Given this, vibration test experiments are carried out, and the vibration signal data under various currents and corresponding contact states are obtained. Afterward, a feature extraction method based on the frequency is designed. The state of the HVCB contacts is then determined using optimized deep neural networks (DNNs) along with the method of adaptive moment estimation (Adam) on the obtained experimental data. Finally, the hyperparameters for the DNNs are tuned using the Bayesian optimization (BO) technique, and a global HVCB contact state recognition model at various currents is proposed. The obtained results clearly depict that the proposed recognition model can accurately identify five various contact states of HVCBs for the currents between 1000 A and 3500 A, and the recognition accuracy rate is above 96%. The designed experimental and theoretical analysis in our study will provide the references for future monitoring and diagnosis of faults in HVCBs.
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Affiliation(s)
- Ze Guo
- State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300401, China
- Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, Hebei University of Technology, Tianjin 300401, China
| | - Linjing Li
- State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300401, China
- Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, Hebei University of Technology, Tianjin 300401, China
| | - Weimeng Han
- State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300401, China
- Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, Hebei University of Technology, Tianjin 300401, China
| | - Zixuan Guo
- State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300401, China
- Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, Hebei University of Technology, Tianjin 300401, China
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Guo Z, Qin X, Mu R, Lv J, Meng Z, Zheng W, Zhuang Z, Zhu X. Amide Proton Transfer Could Provide More Accurate Lesion Characterization in the Transition Zone of the Prostate. J Magn Reson Imaging 2022; 56:1311-1319. [PMID: 35429190 DOI: 10.1002/jmri.28204] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Revised: 04/04/2022] [Accepted: 04/04/2022] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND There is an overlap comparing transition zone prostate cancer (TZ PCa) and benign prostatic hyperplasia (BPH) on T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI), creating additional challenges for assessment of TZ tumors on MRI. PURPOSE To evaluate whether amide proton transfer-weighted (APTw) imaging provides new diagnostic ideas for TZ PCa. STUDY TYPE Prospective. POPULATION A total of 51 TZ PCa patients (age, 49-89), 44 stromal BPH (age, 57-92), and 45 glandular BPH patients (age, 56-92). FIELD STRENGTH/SEQUENCE A 3 T; T2WI turbo spin echo (TSE), quantitative T2*-weighted imaging, DWI echo planar imaging, 3D APTw TSE. ASSESSMENT Differences in APTw, apparent diffusion coefficient (ADC), and T2* among three lesions were compared by one-way analysis of variance (ANOVA). Regions of interest were drawn by two radiologists (X.Q.Z. and X.Y.Q., with 21 and 15 years of experience, respectively). STATISTICAL TESTS Multivariable logistic regression analyses; ANOVA with post hoc testing; receiver operator characteristic curve analysis; Delong test. Significance level: P < 0.05. RESULTS APTw among TZ PCa, stromal BPH, and glandular BPH (3.48% ± 0.83% vs. 2.76% ± 0.49% vs. 2.72% ± 0.45%, respectively) were significantly different except between stromal BPH and glandular BPH (P > 0.99). Significant differences were found in ADC (TZ PCa 0.76 ± 0.16 × 10-3 mm2 /sec vs. stromal BPH 0.91 ± 0.14 × 10-3 mm2 /sec vs. glandular BPH 1.08 ± 0.18 × 10-3 mm2 /sec) among three lesions. APTw (OR = 12.18, 11.80, respectively) and 1/ADC (OR = 703.87, 181.11, respectively) were independent predictors of TZ PCa from BPH and stromal BPH. The combination of APTw and ADC had better diagnostic performance in the identification of TZ PCa from BPH and stromal BPH. DATA CONCLUSION APTw imaging has the potential to be of added value to ADC in differentiating TZ PCa from BPH and stromal BPH. EVIDENCE LEVEL 2 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Zixuan Guo
- Department of Medical Imaging, Guilin Medical University, Guilin, China
- Department of Medical Imaging, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China
| | - Xiaoyan Qin
- Department of Medical Imaging, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China
| | - Ronghua Mu
- Department of Medical Imaging, Guilin Medical University, Guilin, China
- Department of Medical Imaging, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China
| | - Jian Lv
- Department of Medical Imaging, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China
| | - Zhuoni Meng
- Department of Medical Imaging, Guilin Medical University, Guilin, China
- Department of Medical Imaging, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China
| | - Wei Zheng
- Department of Medical Imaging, Guilin Medical University, Guilin, China
- Department of Medical Imaging, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China
| | - Zeyu Zhuang
- Department of Medical Imaging, Guilin Medical University, Guilin, China
- Department of Medical Imaging, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China
| | - Xiqi Zhu
- Department of Medical Imaging, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China
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Bao J, Guo Z, He J, Leng T, Wei Z, Wang C, Chen F. Semen parameters and sex hormones as affected by SARS-CoV-2 infection: A systematic review. Prog Urol 2022; 32:1431-1439. [PMID: 36153222 PMCID: PMC9468308 DOI: 10.1016/j.purol.2022.09.004] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 07/31/2022] [Accepted: 09/05/2022] [Indexed: 11/23/2022]
Abstract
Background Impaired semen quality and reproductive hormone levels were observed in patients during and after recovery from coronavirus disease 2019 (COVID-19), which raised concerns about negative effects on male fertility. Therefore, this study systematically reviews available data on semen parameters and sex hormones in patients with COVID-19. Methods Systematic search was performed on PubMed and Google Scholar until July 18th, 2022. We identified relevant articles that discussed the effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on male fertility. Results A total number of 1,684 articles were identified by using a suitable keyword search strategy. After screening, 26 articles were considered eligible for inclusion in this study. These articles included a total of 1,960 controls and 2,106 patients. When all studies were considered, the results showed that the semen parameters and sex hormone levels of patients infected with SARS-CoV-2 exhibited some significant differences compared with controls. Fortunately, these differences gradually disappear as patients recover from COVID-19. Conclusion While present data show the negative effects of SARS-CoV-2 infection on male fertility, this does not appear to be long-term. Semen quality and hormone levels will gradually increase to normal as patients recover.
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Affiliation(s)
- J Bao
- Jining Medical University, 133, Hehua Road, 272067 Jining, China.
| | - Z Guo
- Jining Medical University, 133, Hehua Road, 272067 Jining, China.
| | - J He
- Jining Medical University, 133, Hehua Road, 272067 Jining, China.
| | - T Leng
- Jining Medical University, 133, Hehua Road, 272067 Jining, China.
| | - Z Wei
- Jining Medical University, 133, Hehua Road, 272067 Jining, China.
| | - C Wang
- Jining Medical University, 133, Hehua Road, 272067 Jining, China.
| | - F Chen
- Jining Medical University, 133, Hehua Road, 272067 Jining, China.
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Zhu P, Zhao X, Zhang Y, Liu Y, Zhao Z, Yang Z, Liu X, Zhang W, Guo Z, Wang X, Niu Y, Xu M. Mn3+/Mn4+ ion-doped carbon dots as fenton-like catalysts for fluorescence dual-signal detection of dopamine. Front Bioeng Biotechnol 2022; 10:964814. [PMID: 36159685 PMCID: PMC9490222 DOI: 10.3389/fbioe.2022.964814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 07/26/2022] [Indexed: 11/13/2022] Open
Abstract
Carbon dots (CDs), a new zero-dimensional material, have ignited a revolution in the fields of sensing, bioimaging, and biomedicine. However, the difficulty of preparing CDs with Fenton-like catalytic properties has seriously hindered their application in the diagnosis of oxidation/reduction biomolecules or metal ions. Here, an innovative method was successfully established to synthesize Mn3+/Mn4+ ion-doped blue-green fluorescent CDs with Fenton-like catalytic properties using manganese acetate as the manganese source. Specifically, the CDs prepared here were equipped with functional groups of -COOH, NH2, C=O, and Mn-O, offering the possibility to function as a fluorescence sensor. More importantly, the introduction of manganese acetate resulted in the preparation of CDs with Fenton-like catalytic properties, and the dual-signal fluorescence detection of dopamine (DA) was realized with linear ranges of 100–275 nM and 325–525 nM, and the detection limits were 3 and 12 nM, respectively. In addition, due to the Fenton-like catalytic activity of Mn3+/Mn4+ ion-doped CDs, the material has broad application prospects in the detection of oxidation/reduction biomolecules or metal ions related to disease diagnosis and prevention.
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Affiliation(s)
- Peide Zhu
- State Key Laboratory of Heavy Oil Processing, China University of Petroleum-Beijing, Beijing, China
| | - Xuelin Zhao
- Department of Musculoskeletal Tumor, Senior Department of Orthopedics, Fourth Medical Center of PLA General Hospital, Beijing, China
- Medical School of Chinese PLA, Beijing, China
| | - Yuqi Zhang
- State Key Laboratory of Heavy Oil Processing, China University of Petroleum-Beijing, Beijing, China
| | - Yinping Liu
- State Key Laboratory of Heavy Oil Processing, China University of Petroleum-Beijing, Beijing, China
| | - Ziyi Zhao
- Department of Musculoskeletal Tumor, Senior Department of Orthopedics, Fourth Medical Center of PLA General Hospital, Beijing, China
| | - Ziji Yang
- State Key Laboratory of Heavy Oil Processing, China University of Petroleum-Beijing, Beijing, China
| | - Xinzhu Liu
- Senior Department of Burns and Plastic Surgery, Fourth Medical Center of PLA General Hospital, Beijing, China
| | - Weiye Zhang
- State Key Laboratory of Heavy Oil Processing, China University of Petroleum-Beijing, Beijing, China
| | - Zixuan Guo
- Department of Musculoskeletal Tumor, Senior Department of Orthopedics, Fourth Medical Center of PLA General Hospital, Beijing, China
| | - Xiao Wang
- Medical School of Chinese PLA, Beijing, China
| | - Yingchun Niu
- State Key Laboratory of Heavy Oil Processing, China University of Petroleum-Beijing, Beijing, China
- *Correspondence: Yingchun Niu, ; Meng Xu,
| | - Meng Xu
- Department of Musculoskeletal Tumor, Senior Department of Orthopedics, Fourth Medical Center of PLA General Hospital, Beijing, China
- *Correspondence: Yingchun Niu, ; Meng Xu,
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Wu D, Lan S, Guo Z, Niu N, Zhang Y, Gui J. 1501P Preliminary analysis of a single-arm, multi-center study of anlotinib combined with toripalimab in first-line treatment of unresectable or metastatic undifferentiated pleomorphic sarcoma. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.07.1604] [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: 11/01/2022] Open
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Mu R, Meng Z, Guo Z, Qin X, Huang G, Yang X, Jin H, Yang P, Zhang X, Zhu X. Dual-layer spectral detector computed tomography parameters can improve diagnostic efficiency of lung adenocarcinoma grading. Quant Imaging Med Surg 2022; 12:4601-4611. [PMID: 36060598 PMCID: PMC9403580 DOI: 10.21037/qims-22-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2022] [Accepted: 06/23/2022] [Indexed: 11/06/2022]
Abstract
Background Methods Results Conclusions
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Affiliation(s)
- Ronghua Mu
- Department of Radiology, Graduate School of Guilin Medical University, Guilin, China
| | - Zhuoni Meng
- Department of Radiology, Graduate School of Guilin Medical University, Guilin, China
| | - Zixuan Guo
- Department of Radiology, Graduate School of Guilin Medical University, Guilin, China
| | - Xiaoyan Qin
- Department of Radiology, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China
| | - Guangyi Huang
- Department of Radiology, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China
| | - Xuri Yang
- Department of Radiology, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China
| | - Hui Jin
- Department of Radiology, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China
| | - Peng Yang
- Department of Radiology, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China
| | - Xiaodi Zhang
- Philips (China) Investment Co., Ltd., Chengdu Branch, Chengdu, China
| | - Xiqi Zhu
- Department of Radiology, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China
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Pappalardo A, Vasilikos P, Nathaniel M, Guo Z, Abaci H, Christiano A. 602 An in vitro psoriasis model for high throughput screening. J Invest Dermatol 2022. [DOI: 10.1016/j.jid.2022.05.611] [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: 10/17/2022]
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Song X, Song Y, Guo Z, Tan M. Influence of protein coronas between carbon nanoparticles extracted from roasted chicken and pepsin on the digestion of soy protein isolate. Food Chem 2022; 385:132714. [DOI: 10.1016/j.foodchem.2022.132714] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Revised: 03/10/2022] [Accepted: 03/13/2022] [Indexed: 01/18/2023]
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He Z, Xin Z, Yang Q, Wang C, Li M, Rao W, Du Z, Bai J, Guo Z, Ruan X, Zhang Z, Fang X, Zhao H. Mapping the single-cell landscape of acral melanoma and analysis of the molecular regulatory network of the tumor microenvironments. eLife 2022; 11:78616. [PMID: 35894206 PMCID: PMC9398445 DOI: 10.7554/elife.78616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 07/25/2022] [Indexed: 12/02/2022] Open
Abstract
Acral melanoma (AM) exhibits a high incidence in Asian patients with melanoma, and it is not well treated with immunotherapy. However, little attention has been paid to the characteristics of the immune microenvironment in AM. Therefore, in this study, we collected clinical samples from Chinese patients with AM and conducted single-cell RNA sequencing to analyze the heterogeneity of its tumor microenvironments (TMEs) and the molecular regulatory network. Our analysis revealed that genes, such as TWIST1, EREG, TNFRSF9, and CTGF could drive the deregulation of various TME components. The molecular interaction relationships between TME cells, such as MIF-CD44 and TNFSF9-TNFRSF9, might be an attractive target for developing novel immunotherapeutic agents. Acral melanoma is a type of cancer that affects the hands and feet. It tends to form on the palms, soles, and under the nails. It is rare in people of European descent, but in Asian populations it makes up more than half of all melanoma cases. Unlike other types of skin cancer, it does not respond well to immunotherapy, but scientists did not understand why. Historically, cancer research has focused on the genetics of whole tumors. But cancer is complicated. Malignant cells recruit other cells to help them survive and grow, and to protect them from attacks by the immune system. Together, they create their own ecosystem, called the tumor microenvironment. The exact makeup of the tumor microenvironment differs depending on the type of cancer and on the genetics of the individual. Investigating the cells that ‘support’ the tumor could help to explain how acral melanoma develops and why it does not respond to treatment. To address these questions, He et al. collected samples from six patients with acral melanoma and examined the genes used by more than 60,000 individual cells. This revealed nine different types of cells in the tumor microenvironment. Most were cancer cells, but there were also immune cells, blood vessel cells, skin cells, and a type of cell that makes connective tissue. He et al. also identified four genes that most likely shape the tumor microenvironment, and two gene pairs that may control some of the interactions between the cells. Investigating these early findings in more detail could open new treatment avenues for acral melanoma. The number of samples in this study was small, but it provides a starting point for future investigation. With more data, researchers could start to develop treatments that target the unique tumor microenvironment of this type of cancer.
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Affiliation(s)
- Zan He
- Department of Dermatology, General Hospital of People's Liberation Army, Beijing, China
| | - Zijuan Xin
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Qiong Yang
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Chen Wang
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Meng Li
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Wei Rao
- Department of Dermatology, General Hospital of People's Liberation Army, Beijing, China
| | - Zhimin Du
- Department of Dermatology, General Hospital of People's Liberation Army, Beijing, China
| | - Jia Bai
- Department of Dermatology, General Hospital of People's Liberation Army, Beijing, China
| | - Zixuan Guo
- Department of Dermatology, General Hospital of People's Liberation Army, Beijing, China
| | - Xiuyan Ruan
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Zhaojun Zhang
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Xiangdong Fang
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Hua Zhao
- Department of Dermatology, General Hospital of People's Liberation Army, Beijing, China
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An FP, Bai WD, Balantekin AB, Bishai M, Blyth S, Cao GF, Cao J, Chang JF, Chang Y, Chen HS, Chen HY, Chen SM, Chen Y, Chen YX, Cheng J, Cheng ZK, Cherwinka JJ, Chu MC, Cummings JP, Dalager O, Deng FS, Ding YY, Diwan MV, Dohnal T, Dolzhikov D, Dove J, Dwyer DA, Gallo JP, Gonchar M, Gong GH, Gong H, Gu WQ, Guo JY, Guo L, Guo XH, Guo YH, Guo Z, Hackenburg RW, Hans S, He M, Heeger KM, Heng YK, Hor YK, Hsiung YB, Hu BZ, Hu JR, Hu T, Hu ZJ, Huang HX, Huang JH, Huang XT, Huang YB, Huber P, Jaffe DE, Jen KL, Ji XL, Ji XP, Johnson RA, Jones D, Kang L, Kettell SH, Kohn S, Kramer M, Langford TJ, Lee J, Lee JHC, Lei RT, Leitner R, Leung JKC, Li F, Li HL, Li JJ, Li QJ, Li RH, Li S, Li SC, Li WD, Li XN, Li XQ, Li YF, Li ZB, Liang H, Lin CJ, Lin GL, Lin S, Ling JJ, Link JM, Littenberg L, Littlejohn BR, Liu JC, Liu JL, Liu JX, Lu C, Lu HQ, Luk KB, Ma BZ, Ma XB, Ma XY, Ma YQ, Mandujano RC, Marshall C, McDonald KT, McKeown RD, Meng Y, Napolitano J, Naumov D, Naumova E, Nguyen TMT, Ochoa-Ricoux JP, Olshevskiy A, Pan HR, Park J, Patton S, Peng JC, Pun CSJ, Qi FZ, Qi M, Qian X, Raper N, Ren J, Morales Reveco C, Rosero R, Roskovec B, Ruan XC, Steiner H, Sun JL, Tmej T, Treskov K, Tse WH, Tull CE, Viren B, Vorobel V, Wang CH, Wang J, Wang M, Wang NY, Wang RG, Wang W, Wang X, Wang Y, Wang YF, Wang Z, Wang Z, Wang ZM, Wei HY, Wei LH, Wen LJ, Whisnant K, White CG, Wong HLH, Worcester E, Wu DR, Wu Q, Wu WJ, Xia DM, Xie ZQ, Xing ZZ, Xu HK, Xu JL, Xu T, Xue T, Yang CG, Yang L, Yang YZ, Yao HF, Ye M, Yeh M, Young BL, Yu HZ, Yu ZY, Yue BB, Zavadskyi V, Zeng S, Zeng Y, Zhan L, Zhang C, Zhang FY, Zhang HH, Zhang JL, Zhang JW, Zhang QM, Zhang SQ, Zhang XT, Zhang YM, Zhang YX, Zhang YY, Zhang ZJ, Zhang ZP, Zhang ZY, Zhao J, Zhao RZ, Zhou L, Zhuang HL, Zou JH. First Measurement of High-Energy Reactor Antineutrinos at Daya Bay. Phys Rev Lett 2022; 129:041801. [PMID: 35939015 DOI: 10.1103/physrevlett.129.041801] [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: 03/17/2022] [Revised: 06/05/2022] [Accepted: 06/28/2022] [Indexed: 06/15/2023]
Abstract
This Letter reports the first measurement of high-energy reactor antineutrinos at Daya Bay, with nearly 9000 inverse beta decay candidates in the prompt energy region of 8-12 MeV observed over 1958 days of data collection. A multivariate analysis is used to separate 2500 signal events from background statistically. The hypothesis of no reactor antineutrinos with neutrino energy above 10 MeV is rejected with a significance of 6.2 standard deviations. A 29% antineutrino flux deficit in the prompt energy region of 8-11 MeV is observed compared to a recent model prediction. We provide the unfolded antineutrino spectrum above 7 MeV as a data-based reference for other experiments. This result provides the first direct observation of the production of antineutrinos from several high-Q_{β} isotopes in commercial reactors.
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Affiliation(s)
- F P An
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - W D Bai
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | | | - M Bishai
- Brookhaven National Laboratory, Upton, New York 11973
| | - S Blyth
- Department of Physics, National Taiwan University, Taipei
| | - G F Cao
- Institute of High Energy Physics, Beijing
| | - J Cao
- Institute of High Energy Physics, Beijing
| | - J F Chang
- Institute of High Energy Physics, Beijing
| | - Y Chang
- National United University, Miao-Li
| | - H S Chen
- Institute of High Energy Physics, Beijing
| | - H Y Chen
- Department of Engineering Physics, Tsinghua University, Beijing
| | - S M Chen
- Department of Engineering Physics, Tsinghua University, Beijing
| | - Y Chen
- Sun Yat-Sen (Zhongshan) University, Guangzhou
- Shenzhen University, Shenzhen
| | - Y X Chen
- North China Electric Power University, Beijing
| | - J Cheng
- North China Electric Power University, Beijing
| | - Z K Cheng
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | | | - M C Chu
- Chinese University of Hong Kong, Hong Kong
| | | | - O Dalager
- Department of Physics and Astronomy, University of California, Irvine, California 92697
| | - F S Deng
- University of Science and Technology of China, Hefei
| | - Y Y Ding
- Institute of High Energy Physics, Beijing
| | - M V Diwan
- Brookhaven National Laboratory, Upton, New York 11973
| | - T Dohnal
- Charles University, Faculty of Mathematics and Physics, Prague
| | - D Dolzhikov
- Joint Institute for Nuclear Research, Dubna, Moscow Region
| | - J Dove
- Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - D A Dwyer
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - J P Gallo
- Department of Physics, Illinois Institute of Technology, Chicago, Illinois 60616
| | - M Gonchar
- Joint Institute for Nuclear Research, Dubna, Moscow Region
| | - G H Gong
- Department of Engineering Physics, Tsinghua University, Beijing
| | - H Gong
- Department of Engineering Physics, Tsinghua University, Beijing
| | - W Q Gu
- Brookhaven National Laboratory, Upton, New York 11973
| | - J Y Guo
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - L Guo
- Department of Engineering Physics, Tsinghua University, Beijing
| | - X H Guo
- Beijing Normal University, Beijing
| | - Y H Guo
- Department of Nuclear Science and Technology, School of Energy and Power Engineering, Xi'an Jiaotong University, Xi'an
| | - Z Guo
- Department of Engineering Physics, Tsinghua University, Beijing
| | | | - S Hans
- Brookhaven National Laboratory, Upton, New York 11973
| | - M He
- Institute of High Energy Physics, Beijing
| | - K M Heeger
- Wright Laboratory and Department of Physics, Yale University, New Haven, Connecticut 06520
| | - Y K Heng
- Institute of High Energy Physics, Beijing
| | - Y K Hor
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - Y B Hsiung
- Department of Physics, National Taiwan University, Taipei
| | - B Z Hu
- Department of Physics, National Taiwan University, Taipei
| | - J R Hu
- Institute of High Energy Physics, Beijing
| | - T Hu
- Institute of High Energy Physics, Beijing
| | - Z J Hu
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - H X Huang
- China Institute of Atomic Energy, Beijing
| | - J H Huang
- Institute of High Energy Physics, Beijing
| | | | - Y B Huang
- Guangxi University, No. 100 Daxue East Road, Nanning
| | - P Huber
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061
| | - D E Jaffe
- Brookhaven National Laboratory, Upton, New York 11973
| | - K L Jen
- Institute of Physics, National Chiao-Tung University, Hsinchu
| | - X L Ji
- Institute of High Energy Physics, Beijing
| | - X P Ji
- Brookhaven National Laboratory, Upton, New York 11973
| | - R A Johnson
- Department of Physics, University of Cincinnati, Cincinnati, Ohio 45221
| | - D Jones
- Department of Physics, College of Science and Technology, Temple University, Philadelphia, Pennsylvania 19122
| | - L Kang
- Dongguan University of Technology, Dongguan
| | - S H Kettell
- Brookhaven National Laboratory, Upton, New York 11973
| | - S Kohn
- Department of Physics, University of California, Berkeley, California 94720
| | - M Kramer
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
- Department of Physics, University of California, Berkeley, California 94720
| | - T J Langford
- Wright Laboratory and Department of Physics, Yale University, New Haven, Connecticut 06520
| | - J Lee
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - J H C Lee
- Department of Physics, The University of Hong Kong, Pokfulam, Hong Kong
| | - R T Lei
- Dongguan University of Technology, Dongguan
| | - R Leitner
- Charles University, Faculty of Mathematics and Physics, Prague
| | - J K C Leung
- Department of Physics, The University of Hong Kong, Pokfulam, Hong Kong
| | - F Li
- Institute of High Energy Physics, Beijing
| | - H L Li
- Institute of High Energy Physics, Beijing
| | - J J Li
- Department of Engineering Physics, Tsinghua University, Beijing
| | - Q J Li
- Institute of High Energy Physics, Beijing
| | - R H Li
- Institute of High Energy Physics, Beijing
| | - S Li
- Dongguan University of Technology, Dongguan
| | - S C Li
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061
| | - W D Li
- Institute of High Energy Physics, Beijing
| | - X N Li
- Institute of High Energy Physics, Beijing
| | - X Q Li
- School of Physics, Nankai University, Tianjin
| | - Y F Li
- Institute of High Energy Physics, Beijing
| | - Z B Li
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - H Liang
- University of Science and Technology of China, Hefei
| | - C J Lin
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - G L Lin
- Institute of Physics, National Chiao-Tung University, Hsinchu
| | - S Lin
- Dongguan University of Technology, Dongguan
| | - J J Ling
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - J M Link
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061
| | - L Littenberg
- Brookhaven National Laboratory, Upton, New York 11973
| | - B R Littlejohn
- Department of Physics, Illinois Institute of Technology, Chicago, Illinois 60616
| | - J C Liu
- Institute of High Energy Physics, Beijing
| | - J L Liu
- Department of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai Laboratory for Particle Physics and Cosmology, Shanghai
| | - J X Liu
- Institute of High Energy Physics, Beijing
| | - C Lu
- Joseph Henry Laboratories, Princeton University, Princeton, New Jersey 08544
| | - H Q Lu
- Institute of High Energy Physics, Beijing
| | - K B Luk
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
- Department of Physics, University of California, Berkeley, California 94720
| | - B Z Ma
- Shandong University, Jinan
| | - X B Ma
- North China Electric Power University, Beijing
| | - X Y Ma
- Institute of High Energy Physics, Beijing
| | - Y Q Ma
- Institute of High Energy Physics, Beijing
| | - R C Mandujano
- Department of Physics and Astronomy, University of California, Irvine, California 92697
| | - C Marshall
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - K T McDonald
- Joseph Henry Laboratories, Princeton University, Princeton, New Jersey 08544
| | - R D McKeown
- California Institute of Technology, Pasadena, California 91125
- College of William and Mary, Williamsburg, Virginia 23187
| | - Y Meng
- Department of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai Laboratory for Particle Physics and Cosmology, Shanghai
| | - J Napolitano
- Department of Physics, College of Science and Technology, Temple University, Philadelphia, Pennsylvania 19122
| | - D Naumov
- Joint Institute for Nuclear Research, Dubna, Moscow Region
| | - E Naumova
- Joint Institute for Nuclear Research, Dubna, Moscow Region
| | - T M T Nguyen
- Institute of Physics, National Chiao-Tung University, Hsinchu
| | - J P Ochoa-Ricoux
- Department of Physics and Astronomy, University of California, Irvine, California 92697
| | - A Olshevskiy
- Joint Institute for Nuclear Research, Dubna, Moscow Region
| | - H-R Pan
- Department of Physics, National Taiwan University, Taipei
| | - J Park
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061
| | - S Patton
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - J C Peng
- Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - C S J Pun
- Department of Physics, The University of Hong Kong, Pokfulam, Hong Kong
| | - F Z Qi
- Institute of High Energy Physics, Beijing
| | - M Qi
- Nanjing University, Nanjing
| | - X Qian
- Brookhaven National Laboratory, Upton, New York 11973
| | - N Raper
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - J Ren
- China Institute of Atomic Energy, Beijing
| | - C Morales Reveco
- Department of Physics and Astronomy, University of California, Irvine, California 92697
| | - R Rosero
- Brookhaven National Laboratory, Upton, New York 11973
| | - B Roskovec
- Charles University, Faculty of Mathematics and Physics, Prague
| | - X C Ruan
- China Institute of Atomic Energy, Beijing
| | - H Steiner
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
- Department of Physics, University of California, Berkeley, California 94720
| | - J L Sun
- China General Nuclear Power Group, Shenzhen
| | - T Tmej
- Charles University, Faculty of Mathematics and Physics, Prague
| | - K Treskov
- Joint Institute for Nuclear Research, Dubna, Moscow Region
| | - W-H Tse
- Chinese University of Hong Kong, Hong Kong
| | - C E Tull
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - B Viren
- Brookhaven National Laboratory, Upton, New York 11973
| | - V Vorobel
- Charles University, Faculty of Mathematics and Physics, Prague
| | - C H Wang
- National United University, Miao-Li
| | - J Wang
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - M Wang
- Shandong University, Jinan
| | - N Y Wang
- Beijing Normal University, Beijing
| | - R G Wang
- Institute of High Energy Physics, Beijing
| | - W Wang
- Sun Yat-Sen (Zhongshan) University, Guangzhou
- College of William and Mary, Williamsburg, Virginia 23187
| | - X Wang
- College of Electronic Science and Engineering, National University of Defense Technology, Changsha
| | - Y Wang
- Nanjing University, Nanjing
| | - Y F Wang
- Institute of High Energy Physics, Beijing
| | - Z Wang
- Institute of High Energy Physics, Beijing
| | - Z Wang
- Department of Engineering Physics, Tsinghua University, Beijing
| | - Z M Wang
- Institute of High Energy Physics, Beijing
| | - H Y Wei
- Brookhaven National Laboratory, Upton, New York 11973
| | - L H Wei
- Institute of High Energy Physics, Beijing
| | - L J Wen
- Institute of High Energy Physics, Beijing
| | | | - C G White
- Department of Physics, Illinois Institute of Technology, Chicago, Illinois 60616
| | - H L H Wong
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
- Department of Physics, University of California, Berkeley, California 94720
| | - E Worcester
- Brookhaven National Laboratory, Upton, New York 11973
| | - D R Wu
- Institute of High Energy Physics, Beijing
| | - Q Wu
- Shandong University, Jinan
| | - W J Wu
- Institute of High Energy Physics, Beijing
| | - D M Xia
- Chongqing University, Chongqing
| | - Z Q Xie
- Institute of High Energy Physics, Beijing
| | - Z Z Xing
- Institute of High Energy Physics, Beijing
| | - H K Xu
- Institute of High Energy Physics, Beijing
| | - J L Xu
- Institute of High Energy Physics, Beijing
| | - T Xu
- Department of Engineering Physics, Tsinghua University, Beijing
| | - T Xue
- Department of Engineering Physics, Tsinghua University, Beijing
| | - C G Yang
- Institute of High Energy Physics, Beijing
| | - L Yang
- Dongguan University of Technology, Dongguan
| | - Y Z Yang
- Department of Engineering Physics, Tsinghua University, Beijing
| | - H F Yao
- Institute of High Energy Physics, Beijing
| | - M Ye
- Institute of High Energy Physics, Beijing
| | - M Yeh
- Brookhaven National Laboratory, Upton, New York 11973
| | - B L Young
- Iowa State University, Ames, Iowa 50011
| | - H Z Yu
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - Z Y Yu
- Institute of High Energy Physics, Beijing
| | - B B Yue
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - V Zavadskyi
- Joint Institute for Nuclear Research, Dubna, Moscow Region
| | - S Zeng
- Institute of High Energy Physics, Beijing
| | - Y Zeng
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - L Zhan
- Institute of High Energy Physics, Beijing
| | - C Zhang
- Brookhaven National Laboratory, Upton, New York 11973
| | - F Y Zhang
- Department of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai Laboratory for Particle Physics and Cosmology, Shanghai
| | - H H Zhang
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | | | - J W Zhang
- Institute of High Energy Physics, Beijing
| | - Q M Zhang
- Department of Nuclear Science and Technology, School of Energy and Power Engineering, Xi'an Jiaotong University, Xi'an
| | - S Q Zhang
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - X T Zhang
- Institute of High Energy Physics, Beijing
| | - Y M Zhang
- Sun Yat-Sen (Zhongshan) University, Guangzhou
| | - Y X Zhang
- China General Nuclear Power Group, Shenzhen
| | - Y Y Zhang
- Department of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai Laboratory for Particle Physics and Cosmology, Shanghai
| | - Z J Zhang
- Dongguan University of Technology, Dongguan
| | - Z P Zhang
- University of Science and Technology of China, Hefei
| | - Z Y Zhang
- Institute of High Energy Physics, Beijing
| | - J Zhao
- Institute of High Energy Physics, Beijing
| | - R Z Zhao
- Institute of High Energy Physics, Beijing
| | - L Zhou
- Institute of High Energy Physics, Beijing
| | - H L Zhuang
- Institute of High Energy Physics, Beijing
| | - J H Zou
- Institute of High Energy Physics, Beijing
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Ning S, He C, Guo Z, Zhang H, Mo Z. [VIPR1 promoter methylation promotes transcription factor AP-2 α binding to inhibit VIPR1 expression and promote hepatocellular carcinoma cell growth in vitro]. Nan Fang Yi Ke Da Xue Xue Bao 2022; 42:957-965. [PMID: 35869757 DOI: 10.12122/j.issn.1673-4254.2022.07.01] [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] [Indexed: 11/24/2022]
Abstract
OBJECTIVE To explore the transcriptional regulation mechanism and biological function of low expression of vasoactive intestinal peptide receptor 1 (VIPR1) in hepatocellular carcinoma (HCC). METHODS We constructed plasmids carrying wild-type VIPR1 promoter or two mutant VIPR1 promoter sequences for transfection of the HCC cell lines Hep3B and Huh7, and examined the effect of AP-2α expression on VIPR1 promoter activity using dual-luciferase reporter assay. Pyrosequencing was performed to detect the changes in VIPR1 promoter methylation level in HCC cells treated with a DNA methyltransferase inhibitor (DAC). Chromatin immunoprecipitation was used to evaluate the binding ability of AP-2α to VIPR1 promoter. Western blotting was used to assess the effect of AP-2α knockdown on VIPR1 expression and examine the differential expression of VIPR1 in the two cell lines. The effects of VIPR1 overexpression and knockdown on the proliferation, cell cycle and apoptosis of HCC cells were analyzed using CCK8 assay and flow cytometry. We also observed the growth of HCC xenograft with lentivirus-mediated over-expression of VIPR1 in nude mice. RESULTS Compared with the wild-type VIPR1 promoter group, co-transfection with the vector carrying two promoter mutations and the AP-2α-over-expressing plasmid obviously restored the luciferase activity in HCC cells (P < 0.05). DAC treatment of the cells significantly decreased the methylation level of VIPR1 promoter and inhibited the binding of AP-2α to VIPR1 promoter (P < 0.01). The HCC cells with AP-2α knockdown showed increased VIPR1 expression, which was lower in Huh7 cells than in Hep3B cells. VIPR1 overexpression in HCC cells caused significant cell cycle arrest in G2/M phase (P < 0.01), promoted cell apoptosis (P < 0.001), and inhibited cell proliferation (P < 0.001), while VIPR1 knockdown produced the opposite effects. In the tumor-bearing nude mice, VIPR1 overexpression in the HCC cells significantly suppressed the increase of tumor volume (P < 0.001) and weight (P < 0.05). CONCLUSION VIPR1 promoter methylation in HCC promotes the binding of AP-2α and inhibits VIPR1 expression, while VIPR1 overexpression causes cell cycle arrest, promotes cell apoptosis, and inhibits cell proliferation and tumor growth.
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Affiliation(s)
- S Ning
- School of Intelligent Medicine and Biotechnology, Guilin Medical University, Guilin 541199, China
| | - C He
- Faculty of Basic Medical Sciences, Guilin Medical University, Guilin 541199, China
| | - Z Guo
- School of Intelligent Medicine and Biotechnology, Guilin Medical University, Guilin 541199, China
| | - H Zhang
- School of Intelligent Medicine and Biotechnology, Guilin Medical University, Guilin 541199, China
| | - Z Mo
- School of Intelligent Medicine and Biotechnology, Guilin Medical University, Guilin 541199, China
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Guo Z, Wang J, Tian X, Fang Z, Gao Y, Ping Z, Liu L. Body mass index increases the recurrence risk of breast cancer: a dose-response meta-analysis from 21 prospective cohort studies. Public Health 2022; 210:26-33. [PMID: 35868141 DOI: 10.1016/j.puhe.2022.06.014] [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: 12/14/2021] [Revised: 05/09/2022] [Accepted: 06/13/2022] [Indexed: 10/17/2022]
Abstract
OBJECTIVE The purpose of this study was to investigate the effect of body mass index (BMI) on the recurrence risk of breast cancer. STUDY DESIGN Dose-response meta-analysis. METHODS Cohort studies that included BMI and the recurrence of breast cancer were selected through various databases including PubMed, Web of Science, the China National Knowledge Infrastructure (CNKI), Chinese Scientific Journals (VIP), and Wanfang Data Knowledge Service Platform (WanFang) until November 30, 2021. The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of literature. A two-stage random-effects meta-analysis was performed to assess the dose-response relationship between BMI and breast cancer recurrence risk. Heterogeneity between studies is assessed using I2. RESULTS The relative risk (RR) of BMI <25 kg/m2 vs BMI ≥25 kg/m2, BMI <30 kg/m2 vs BMI ≥30 kg/m2 were 1.09 (95% CI: 1.00-1.19) and 1.15 (95% CI: 1.04-1.27), suggesting that BMI had a significant effect on the recurrence risk of breast cancer, and there might be a dose-response relationship between them. A total of 21 studies were included in dose-response meta-analysis, which showed that there was a positive linear correlation between BMI and the risk of recurrence (RR = 1.02, 95% CI: 1.01-1.03). For every 1 kg/m2 increment of BMI, the risk of recurrence increased by approximately 2%. In subgroup analyses, positive linear dose-response relationships between BMI and recurrence risk were observed among Asian and study period >10 years groups. For every 1 kg/m2 increment of BMI, the risk of recurrence increased by 3.41% and 1.87%, respectively. CONCLUSIONS The recurrence risk of breast cancer increases with BMI, which is most obvious among Asian women.
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Affiliation(s)
- Z Guo
- College of Public Health, Zhengzhou University, Zhengzhou, Henan, China.
| | - J Wang
- College of Public Health, Zhengzhou University, Zhengzhou, Henan, China.
| | - X Tian
- College of Public Health, Zhengzhou University, Zhengzhou, Henan, China.
| | - Z Fang
- College of Public Health, Zhengzhou University, Zhengzhou, Henan, China.
| | - Y Gao
- College of Public Health, Zhengzhou University, Zhengzhou, Henan, China.
| | - Z Ping
- College of Public Health, Zhengzhou University, Zhengzhou, Henan, China.
| | - L Liu
- School of Basic Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China.
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Guo Z, Zhou J, Guo H, Liu LK. Radiotherapy-induced abscopal effect on the metastatic carcinoma of unknown primary origin: a case report and literature review. Eur Rev Med Pharmacol Sci 2022; 26:4634-4637. [PMID: 35856353 DOI: 10.26355/eurrev_202207_29185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
OBJECTIVE Abscopal effect of radiotherapy refers to a clinical phenomenon that is characterized by the eradication of distant metastatic tumors following localized irradiation. Reports on the abscopal effect following pure radiotherapy have been relatively rare. CASE REPORT Herein, we reported a 70-year-old male patient, who has been subjected to swelling and pain in the left neck. Computed tomography examination presented a metastatic lymph node of the left cervical and an intra-abdominal mass which was located in hepatogastric space, upward of the pancreatic head. Histopathology of the left cervical lymph node further ensured a poorly-moderately differentiated form of squamous cell carcinoma. But the primary origin was not defined. This patient received radiotherapy on the metastatic lymph nodes of the left cervical (dose: 60 Gray in 30 fractions) only. After treatment, the pain in the left neck dramatically improved and the swelling of the radiation exposure site diminished gradually. Computed tomography examination also confirmed that the abdominal mass was significantly reduced. CONCLUSIONS The abscopal effect, in this case, may help us to get a better understanding of the impact of radiotherapy.
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Affiliation(s)
- Z Guo
- Department of Oncology, Shanxi Province Academy of Traditional Chinese Medicine, Shanxi Province Hospital of Traditional Chinese Medicine, Taiyuan, Shanxi, China.
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Yang G, Guo Z, Wang P, Wang W, Liao H, Ding T, Chen H. Research and validation on the numerical algorithm of mechanical module in a transient fuel rod performance code for fast reactor. ANN NUCL ENERGY 2022. [DOI: 10.1016/j.anucene.2022.108991] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Liu X, Jin G, Tang Q, Huang S, Zhang Y, Sun Y, Liu T, Guo Z, Yang C, Wang B, Jiang K, Zhong W, Cao H. Early life Lactobacillus rhamnosus GG colonisation inhibits intestinal tumour formation. Br J Cancer 2022; 126:1421-1431. [PMID: 35091695 PMCID: PMC9090826 DOI: 10.1038/s41416-021-01562-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 08/04/2021] [Accepted: 09/17/2021] [Indexed: 01/30/2023] Open
Abstract
BACKGROUND Gut microbiota dysbiosis is closely related to the progression of colorectal cancer. Our previous study revealed that early life colonisation with Lactobacillus rhamnosus GG (LGG) had long-term positive effects on health. We sought to investigate whether early life LGG colonisation could inhibit intestinal tumour formation in offspring. METHODS Adult C57BL/6 female mice were mated with Apcmin/+ male mice. Pregnant mice with the same conception date received 108 cfu live or fixed LGG from day 18 of pregnancy until natural delivery. After genotyping, offspring mice received 107 cfu of live or fixed LGG for 0-5 days after birth. RESULTS Early life LGG colonisation significantly promoted intestinal development, inhibited low-grade intestinal inflammation and altered the gut microbiota composition of offspring in the weaning period (3 week old). Notably, early life LGG colonisation reduced the multiplicity of intestinal tumours in adulthood (12 week old), possibly due to inhibition of Wnt signalling and promotion of tumour cell apoptosis. Importantly, at the genus level, Bifidobacterium and Anaeroplasma with potential anti-tumour effects were increased in adulthood, while Peptostreptococcus, which potentially contributes to tumour formation, was decreased. CONCLUSIONS Early life LGG colonisation inhibited the intestinal tumour formation of offspring in adulthood.
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Affiliation(s)
- Xiang Liu
- Department of Gastroenterology and Hepatology, General Hospital, Tianjin Medical University, Tianjin Institute of Digestive Diseases, Tianjin Key Laboratory of Digestive Diseases, Tianjin, China
| | - Ge Jin
- Department of Gastroenterology and Hepatology, General Hospital, Tianjin Medical University, Tianjin Institute of Digestive Diseases, Tianjin Key Laboratory of Digestive Diseases, Tianjin, China
| | - Qiang Tang
- Department of Gastroenterology and Hepatology, General Hospital, Tianjin Medical University, Tianjin Institute of Digestive Diseases, Tianjin Key Laboratory of Digestive Diseases, Tianjin, China
| | - Shumin Huang
- Department of Gastroenterology and Hepatology, General Hospital, Tianjin Medical University, Tianjin Institute of Digestive Diseases, Tianjin Key Laboratory of Digestive Diseases, Tianjin, China
| | - Yujie Zhang
- Department of Pathology, General Hospital, Tianjin Medical University, Tianjin, China
| | - Yue Sun
- Department of Gastroenterology and Hepatology, General Hospital, Tianjin Medical University, Tianjin Institute of Digestive Diseases, Tianjin Key Laboratory of Digestive Diseases, Tianjin, China
| | - Tianyu Liu
- Department of Gastroenterology and Hepatology, General Hospital, Tianjin Medical University, Tianjin Institute of Digestive Diseases, Tianjin Key Laboratory of Digestive Diseases, Tianjin, China
| | - Zixuan Guo
- Department of Gastroenterology and Hepatology, General Hospital, Tianjin Medical University, Tianjin Institute of Digestive Diseases, Tianjin Key Laboratory of Digestive Diseases, Tianjin, China
| | - Cheng Yang
- Tianjin Key Laboratory of Early Druggability Evaluation of Innovative Drugs and Tianjin Key Laboratory of Molecular Drug Research, Tianjin International Joint Academy of Biomedicine, Tianjin, China
| | - Bangmao Wang
- Department of Gastroenterology and Hepatology, General Hospital, Tianjin Medical University, Tianjin Institute of Digestive Diseases, Tianjin Key Laboratory of Digestive Diseases, Tianjin, China
| | - Kui Jiang
- Department of Gastroenterology and Hepatology, General Hospital, Tianjin Medical University, Tianjin Institute of Digestive Diseases, Tianjin Key Laboratory of Digestive Diseases, Tianjin, China.
| | - Weilong Zhong
- Department of Gastroenterology and Hepatology, General Hospital, Tianjin Medical University, Tianjin Institute of Digestive Diseases, Tianjin Key Laboratory of Digestive Diseases, Tianjin, China.
| | - Hailong Cao
- Department of Gastroenterology and Hepatology, General Hospital, Tianjin Medical University, Tianjin Institute of Digestive Diseases, Tianjin Key Laboratory of Digestive Diseases, Tianjin, China.
- Tianjin Key Laboratory of Early Druggability Evaluation of Innovative Drugs and Tianjin Key Laboratory of Molecular Drug Research, Tianjin International Joint Academy of Biomedicine, Tianjin, China.
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Zhao HF, Zhang Y, Dang LX, Liang JL, Chen SX, Guo Z, Li YL, Zu RR, Gui XD, Wei YP, Song Y. [Analysis the influence factors of treatment free remission outcome with chronic myeloid leukemia patients who discontinued tyrosine kinase inhibitors]. Zhonghua Yi Xue Za Zhi 2022; 102:1523-1529. [PMID: 35692068 DOI: 10.3760/cma.j.cn112137-20220112-00074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Objective: To explore the related factors affecting the outcome of treatment free remission (TFR) in patients with chronic myeloid leukemia (CML). Methods: Clinical data of CML patients with automatic discontinuation of tyrosine kinase inhibitor (TKI) from the CML cooperative organization of Henan province between June 2, 2013 to March 27, 2021 and the follow-up time was ≥ 6 months were retrospectively analyzed. Log-rank test was used for univariate analysis and Cox proportional risk regression model was used for multivariate analysis. Results: A total of 135 patients were enrolled, and 69 patients (51.1%) were femal and 66 patients (48.9%)were male. Median age was[M(Q1,Q3)] 49 years (38, 58)at discontinuation.Before discontinuation, 72 patients (53.3%) were on treatment with second-generation TKI, 63 patients (46.7%) were on treatment with IM, 17patients (12.6%) had a history of TKI reduction/withdrawal;median duration of treatment was months 84 (68, 108) for all patients;median time of TKI treatment to DMR was months 12(8, 26);median duration of DMR was months 65 (54, 84), and 9 patients (6.7%) had unsustained DMR.The median follow-up time was months 16(6-96), 35 patients (25.9%) lost MMR at a median months 3(1-22), overall estimated TFR was 74.1%.The univariate analysis results showed that:second-generation TKI was used, the time of TKI treatment to DMR was ≤12 months, DMR duration time ≥48 months, had sustained DMR, without TKI reduction/withdrawal history were favorable factors affecting of TFR in patients with TKI discontinuation (all P<0.05).The TFR rate of the second-generation TKI therapy group was significantly higher than the IM therapy group (81.9% vs 65.1%, P=0.019).The multivariate analysis results showed that second-generation TKI treatment[RR=0.451, 95%CI (0.227-0.896), P=0.023] and had sustained DMR [RR=0.120, 95%CI (0.053-0.271), P<0.001] were the protective factors of TFR in patients with TKI discontinuation. Conclusions: Treated with second-generation TKI and had sustained DMR are the protective factors of TFR in patients with TKI discontinuation.The CML patients who had sustained DMR more≥48 months before TKI discontinuation showed a better TFR.
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Affiliation(s)
- H F Zhao
- Department of Hematology, Henan Cancer Hospital, the Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou 450008, China
| | - Yanli Zhang
- Department of Hematology, Henan Cancer Hospital, the Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou 450008, China
| | - L X Dang
- Department of Hematology, the first Affiliated Hospital of Nanyang Medical College, Nanyang 473000, China
| | - J L Liang
- Department of Hematology, Sanmenxia Central Hospital, Sanmenxia 472000, China
| | - S X Chen
- Department of Hematology, Pingdingshan Second People's Hospital, Pingdingshan 467000, China
| | - Z Guo
- Department of Hematology, Zhengzhou People's Hospital, Zhengzhou 450000, China
| | - Y L Li
- Department of Hematology, Henan Cancer Hospital, the Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou 450008, China
| | - R R Zu
- Department of Hematology, Henan Cancer Hospital, the Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou 450008, China
| | - X D Gui
- Department of Hematology, Henan Cancer Hospital, the Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou 450008, China
| | - Y P Wei
- Department of Hematology, Henan Cancer Hospital, the Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou 450008, China
| | - Yongping Song
- Department of Hematology, Henan Cancer Hospital, the Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou 450008, China
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Wang G, Guan J, Yang Q, Wu F, Shao J, Zhou Q, Guo Z, Ren Y, Zhu H, Chen Z. Development of a Bile Acid-Related Gene Signature for Predicting Survival in Patients with Hepatocellular Carcinoma. Comput Math Methods Med 2022; 2022:9076175. [PMID: 35592684 PMCID: PMC9113879 DOI: 10.1155/2022/9076175] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Revised: 04/07/2022] [Accepted: 04/13/2022] [Indexed: 12/24/2022]
Abstract
Background Hepatocellular carcinoma (HCC) is one of the most common diseases that threaten millions of lives annually. Evidence supports that bile acid (BA) affects HCC through inflammation, DNA damage, or other mechanisms. Methods A total of 127 BA-associated genes were analyzed in HCC tumor and nontumor samples using The Cancer Genome Atlas data. Genes correlated to the prognosis of patients with HCC were identified using univariate and multivariate Cox regression analyses. Furthermore, a prediction model with identified genes was constructed to evaluate the risk of patients with HCC for prognosis. Results Out of 26 genes with differential expressions between the HCC and nontumor samples, 19 and 7 genes showed upregulated and downregulated expressions, respectively. Three genes, NPC1, ABCC1, and SLC51B, were extrapolated to construct a prediction model for the prognosis of patients with HCC. Conclusion The three-gene prediction model was more reliable than the pathological staging characters of the tumor for the prognosis and survival of patients with HCC. In addition, the upregulated genes facilitating the transport of BAs are associated with poor prognosis of patients with HCC, and genes of de novo synthesis of BAs benefit patients with HCC.
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Affiliation(s)
- Gang Wang
- Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jun Guan
- Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Qin Yang
- Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Fengtian Wu
- Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Junwei Shao
- Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Qihui Zhou
- Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Zixuan Guo
- Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yanli Ren
- Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Haihong Zhu
- Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Zhi Chen
- Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
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Cescon D, Schmid P, Rugo H, Im SA, Md Yusof M, Gallardo C, Lipatov O, Barrios C, Perez Garcia J, Iwata H, Masuda N, Torregroza Otero M, Gokmen E, Loi S, Haiderali A, Zhou X, Guo Z, Martin Nguyen A, Cortés J. 164O Health-related quality of life (HRQoL) with pembrolizumab (pembro) + chemotherapy (chemo) vs placebo (pbo) + chemo as 1L treatment for advanced triple-negative breast cancer (TNBC): Results from KEYNOTE-355. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.03.183] [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: 11/01/2022] Open
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Liu Y, Ma Q, Liu H, Guo Z. Public attitudes and influencing factors toward COVID-19 vaccination for adolescents/children: a scoping review. Public Health 2022; 205:169-181. [PMID: 35303534 PMCID: PMC8825307 DOI: 10.1016/j.puhe.2022.02.002] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 01/30/2022] [Accepted: 02/01/2022] [Indexed: 11/19/2022]
Abstract
OBJECTIVE This study aimed to systematically clarify attitudes and influencing factors of the public toward COVID-19 vaccination for children or adolescents. STUDY DESIGN This was a scoping review. METHODS This scoping review screened, included, sorted, and analyzed relevant studies on COVID-19 vaccination for children or adolescents before December 31, 2021, in databases, including PubMed, Elsevier, Web of Science, Cochrane Library, and Wiley. RESULTS A total of 34 studies were included. The results showed that the public's acceptance rate toward COVID-19 vaccination for children or adolescents ranged from 4.9% (southeast Nigerian mothers) to 91% (Brazilian parents). Parents' or adolescents' age, gender, education level, and cognition and behavior characteristics for the vaccines were the central factors affecting vaccination. The vaccine's safety, effectiveness, and potential side-effects were the main reasons affecting vaccination. CONCLUSIONS Realizing current public attitudes of COVID-19 vaccination for adolescents or children can effectively develop intervention measures and control the pandemic as soon as possible through herd immunity.
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Affiliation(s)
- Y Liu
- School of Nursing, University of South China, Hengyang, China
| | - Q Ma
- School of Nursing, University of South China, Hengyang, China
| | - H Liu
- School of Nursing, University of South China, Hengyang, China
| | - Z Guo
- School of Nursing, University of South China, Hengyang, China; Institute of Pharmacy and Pharmacology, University of South China, Hengyang, China.
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Jiang W, Dong W, Li M, Guo Z, Wang Q, Liu Y, Bi Y, Zhou H, Wang Y. Nitric Oxide Induces Immunogenic Cell Death and Potentiates Cancer Immunotherapy. ACS Nano 2022; 16:3881-3894. [PMID: 35238549 DOI: 10.1021/acsnano.1c09048] [Citation(s) in RCA: 44] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Tumor cells undergoing immunogenic cell death (ICD) release immunogenic damage-associated molecular patterns (DAMPs) to trigger a long-term protective antitumor response. ICD can be induced by certain pathogens, chemotherapeutics, and physical modalities. In this work, we demonstrate that a gaseous molecule, specifically nitric oxide (NO), can induce a potent ICD effect. NO exerts cytotoxic effects that are accompanied by the emission of DAMPs based on the endoplasmic reticulum stress and mitochondrial dysfunction pathways. Released DAMPs elicit immunological protection against a subsequent rechallenge of syngeneic tumor cells in immunocompetent mice. We prepare polynitrosated polyesters with high NO storage capacity through a facile polycondensation reaction followed by a postsynthetic modification. The polynitrosated polyesters-based NO nanogenerator (NanoNO) that enables efficient NO delivery and controlled NO release in tumors induces a sufficient ICD effect. In different immune-intact models of tumors, the NanoNO exhibits significant tumor growth suppression and increases the local dose of immunogenic signals and T cell infiltrations, ultimately prolonging survival. In addition, the NanoNO synergizes with the PD-1 blockade to prevent metastasis. We conclude not only that NO is a potent ICD inducer for cancer immunotherapy but also that it expands the range of ICD inducers into the field of gaseous molecules.
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Affiliation(s)
- Wei Jiang
- Intelligent Nanomedicine Institute, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230001, China
| | - Wang Dong
- Intelligent Nanomedicine Institute, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230001, China
| | - Min Li
- The CAS Key Laboratory of Innate Immunity and Chronic Disease, School of Life Sciences and Medical Center, University of Science and Technology of China, Hefei, Anhui 230027, China
| | - Zixuan Guo
- The CAS Key Laboratory of Innate Immunity and Chronic Disease, School of Life Sciences and Medical Center, University of Science and Technology of China, Hefei, Anhui 230027, China
| | - Qin Wang
- The CAS Key Laboratory of Innate Immunity and Chronic Disease, School of Life Sciences and Medical Center, University of Science and Technology of China, Hefei, Anhui 230027, China
| | - Yi Liu
- The CAS Key Laboratory of Innate Immunity and Chronic Disease, School of Life Sciences and Medical Center, University of Science and Technology of China, Hefei, Anhui 230027, China
| | - Yihui Bi
- The CAS Key Laboratory of Innate Immunity and Chronic Disease, School of Life Sciences and Medical Center, University of Science and Technology of China, Hefei, Anhui 230027, China
| | - Han Zhou
- The CAS Key Laboratory of Innate Immunity and Chronic Disease, School of Life Sciences and Medical Center, University of Science and Technology of China, Hefei, Anhui 230027, China
| | - Yucai Wang
- The CAS Key Laboratory of Innate Immunity and Chronic Disease, School of Life Sciences and Medical Center, University of Science and Technology of China, Hefei, Anhui 230027, China
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Mu R, Meng Z, Zhang X, Guo Z, Zheng W, Zhuang Z, Zhu X. Parameters of Dual-Layer Spectral Detector CT could be Used to Differentiate Non-Small Cell Lung Cancer from Small Cell Lung Cancer. Curr Med Imaging 2022; 18:1070-1078. [PMID: 35260059 DOI: 10.2174/1573405618666220308105359] [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: 08/31/2021] [Revised: 12/20/2021] [Accepted: 12/31/2021] [Indexed: 11/22/2022]
Abstract
BACKGROUND AND OBJECTIVE Differentiating non-small cell lung cancer (NSCLC) from small cell lung cancer (SCLC) remains a substantial challenge. This study aimed at evaluating the performance of dual-layer spectral detector CT (DLCT) in differentiating NSCLC from SCLC. METHODS Spectral images of 247 cancer patients confirmed by pathology were retrospectively analyzed in both the arterial phase (AP) and the venous phase (VP), which includes 197 cases of NSCLC and 50 cases of SCLC. Effective atomic umber (Z-eff), Spectral CT-Mono Energetic (MonoE [40keV~90keV]), iodine density (ID) and thoracic aorta iodine density (IDaorta) in contrast-enhanced images were calculated and compared between the SCLC and NSCLC subgroups of tumors. Slope of spectral curve (λ, interval of 10 keV) and normalized iodine density (NID) was calculated between the SCLC and NSCLC too. Through statistical analysis, the diagnostic efficiency of each spectral parameter was calculated, and the difference of their efficiency was analyzed. RESULTS Both in NSCLS and SCLC, all parameters in VP were significantly higher than those in AP (p<0.001), except for λ90. There were significant differences in all spectral parameters between NSCLS and SCLC, both in AP and VP (p < 0.001). Except VP-λ90, there was no significant difference in ROC curves of all spectral parameters. VP-NID has the best diagnostic performance with AUC value of 0.917 (95%[CI]: 0.870~0.965), sensitivity and specificity of 92.9%, 80%, and diagnostic threshold of 0.217. CONCLUSION All parameters of DLCT have high diagnostic efficiency in differentiating NSCLC from SCLC except for VP-λ90, and VP-NID has the highest diagnostic efficiency.
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Affiliation(s)
- Ronghua Mu
- Graduate School of Guilin Medical University,541004,China
| | - Zhuoni Meng
- Graduate School of Guilin Medical University,541004,China
| | - Xiaodi Zhang
- Philips (China) Investment Co., Ltd. Chengdu Branch,610000,China
| | - Zixuan Guo
- Graduate School of Guilin Medical University,541004,China
| | - Wei Zheng
- Graduate School of Guilin Medical University,541004,China
| | - Zeyu Zhuang
- Graduate School of Guilin Medical University,541004,China
| | - Xiqi Zhu
- Department of Medical Imaging, Nanxishan Hospital of Guangxi Zhuang Autonomous Region,541004 , China
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