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Guo Z, Zhao Z, Wang X, Zhou J, Liu J, Plunet W, Ren W, Tian L. Identification of mitophagy-related hub genes during the progression of spinal cord injury by integrated multinomial bioinformatics analysis. Biochem Biophys Rep 2024; 38:101654. [PMID: 38375420 PMCID: PMC10875195 DOI: 10.1016/j.bbrep.2024.101654] [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: 11/21/2023] [Revised: 01/24/2024] [Accepted: 01/25/2024] [Indexed: 02/21/2024] Open
Abstract
Spinal cord injury (SCI) is a disturbance of peripheral and central nerve conduction that causes disability in sensory and motor function. Currently, there is no effective treatment for SCI. Mitophagy plays a vital role in mitochondrial quality control during various physiological and pathological processes. The study aimed to elucidate the role of mitophagy and identify potential mitophagy-related hub genes in SCI pathophysiology. Two datasets (GSE15878 and GSE138637) were analyzed. Firstly, the differentially expressed genes (DEGs) were identified and mitophagy-related genes were obtained from GeneCards, then the intersection between SCI and mitophagy-related genes was determined. Next, we performed gene set enrichment analysis (GSEA), weighted gene co-expression network analysis (WGCNA), protein-protein interaction network (PPI network), least absolute shrinkage and selection operator (LASSO), and cluster analysis to identify and define the hub genes in SCI. Finally, the link between hub genes and infiltrating immune cells was investigated and the potential transcriptional regulation/small molecular compounds to target hub genes were predicted. In total, SKP1 and BAP1 were identified as hub genes of mitophagy-related DEGs during SCI development and regulatory T cells (Tregs)/resting NK cells/activated mast cells may play an essential role in the progression of SCI. LINC00324 and SNHG16 may regulate SKP1 and BAP1, respectively, through miRNAs. Eleven and eight transcriptional factors (TFs) regulate SKP1 and BAP1, respectively, and six small molecular compounds target BAP1. Then, the mRNA expression levels of BAP1 and SKP1 were detected in the injured sites of spinal cord of SD rats at 6 h and 72 h after injury using RT-qPCR, and found that the level were decreased. Therefore, the pathways of mitophagy are downregulated during the pathophysiology of SCI, and SKP1 and BAP1 could be accessible targets for diagnosing and treating SCI.
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Affiliation(s)
- Zhihao Guo
- The Department of Orthopedics, The Third Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China
| | - Zihui Zhao
- Institute of Trauma & Orthopedics, The Third Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China
| | - Xiaoge Wang
- Institute of Trauma & Orthopedics, The Third Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China
| | - Jie Zhou
- The Department of Orthopedics, The Third Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China
| | - Jie Liu
- Institute of Trauma & Orthopedics, The Third Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China
- Clinical Medical Center of Tissue Engineering and Regeneration, Xinxiang Medical University, Xinxiang, Henan, China
| | - Ward Plunet
- International Collaboration on Repair Discoveries (ICORD), Blusson Spinal Cord Center, Vancouver, British Columbia, Canada
| | - Wenjie Ren
- Institute of Trauma & Orthopedics, The Third Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China
- Clinical Medical Center of Tissue Engineering and Regeneration, Xinxiang Medical University, Xinxiang, Henan, China
| | - Linqiang Tian
- The Department of Orthopedics, The Third Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China
- Institute of Trauma & Orthopedics, The Third Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China
- Clinical Medical Center of Tissue Engineering and Regeneration, Xinxiang Medical University, Xinxiang, Henan, China
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Ye L, Liu X, Ni Y, Xu Y, Zheng Z, Chen K, Hu Q, Tan L, Guo Z, Wai CK, Chan EWC, Li R, Chen S. Comprehensive genomic and plasmid characterization of multidrug-resistant bacterial strains by R10.4.1 nanopore sequencing. Microbiol Res 2024; 283:127666. [PMID: 38460283 DOI: 10.1016/j.micres.2024.127666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 01/17/2024] [Accepted: 02/25/2024] [Indexed: 03/11/2024]
Abstract
The escalating prevalence of multidrug-resistant (MDR) bacteria pose a significant public health threat. Understanding the genomic features and deciphering the antibiotic resistance profiles of these pathogens is crucial for development of effective surveillance and treatment strategies. In this study, we employed the R10.4.1 nanopore sequencing technology, specifically through the use of the MinION platform, to analyze eight MDR bacterial strains originating from clinical, ecological and food sources. A single 72-hour sequencing run could yield approximately 12 million reads which covered a total of 34 gigabases (Gbp). The nanopore R10.4.1 data was processed using the Flye assembler, successfully assembling the genomes of eight bacterial strains and their 18 plasmids. Notably, the assemblies generated solely from R10.4.1 nanopore data closely matched those from next-generation sequencing data. Diverse antibiotic resistance patterns and specific resistance genes in the test strains were identified. Hospital strains that exhibited multidrug resistance were found to harbor various resistance genes that encode efflux pumps and extended-spectrum β-lactamases. Environmental and food sources were found to display resistance profiles in a species-specific manner. The composition of structurally complex plasmids in the test strains could also be revealed by analysis of nanopore long reads, which also suggested evidence of horizontal transfer of plasmids between different bacterial species. These findings provide valuable insights into the genetic characteristics of MDR bacteria and demonstrating the practicality of nanopore sequencing technology for detecting of resistance elements in bacterial pathogens.
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Affiliation(s)
- Lianwei Ye
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon, Hong Kong, SAR China; State Key Lab of Chemical Biology and Drug Discovery and the Department of Food Science and Nutrition, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, SAR China
| | - Xudong Liu
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon, Hong Kong, SAR China
| | - Ying Ni
- Department of Biomedical Sciences and Tung Biomedical Sciences Centre, City University of Hong Kong, Hong Kong, Hong Kong, SAR China; Department of Precision Diagnostic and Therapeutic Technology, City University of Hong Kong Shenzhen Futian Research Institute, Shenzhen, Guangdong, China
| | - Yating Xu
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon, Hong Kong, SAR China; State Key Lab of Chemical Biology and Drug Discovery and the Department of Food Science and Nutrition, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, SAR China
| | - Zhiwei Zheng
- State Key Lab of Chemical Biology and Drug Discovery and the Department of Food Science and Nutrition, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, SAR China; Shenzhen Key Lab for Biological Safety Control, The Hong Kong Polytechnic University Shenzhen Research Institute, Shenzhen, China
| | - Kaichao Chen
- State Key Lab of Chemical Biology and Drug Discovery and the Department of Food Science and Nutrition, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, SAR China
| | - Qiao Hu
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon, Hong Kong, SAR China; State Key Lab of Chemical Biology and Drug Discovery and the Department of Food Science and Nutrition, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, SAR China
| | - Lu Tan
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon, Hong Kong, SAR China
| | - Zhihao Guo
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon, Hong Kong, SAR China
| | - Chan Kwan Wai
- State Key Lab of Chemical Biology and Drug Discovery and the Department of Food Science and Nutrition, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, SAR China
| | - Edward Wai Chi Chan
- State Key Lab of Chemical Biology and Drug Discovery and the Department of Food Science and Nutrition, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, SAR China
| | - Runsheng Li
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon, Hong Kong, SAR China; Department of Precision Diagnostic and Therapeutic Technology, City University of Hong Kong Shenzhen Futian Research Institute, Shenzhen, Guangdong, China.
| | - Sheng Chen
- State Key Lab of Chemical Biology and Drug Discovery and the Department of Food Science and Nutrition, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, SAR China; Shenzhen Key Lab for Biological Safety Control, The Hong Kong Polytechnic University Shenzhen Research Institute, Shenzhen, China; Animal Health Research Center, City University of Hong Kong Chengdu Research Institute, Chengdu, China.
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Ye L, Zheng Z, Wang Y, Hu Q, Zhong L, Heng H, Guo Z, Li R, Chan EWC, Chen S. Integrating metagenomic and isolation strategies revealed high contamination of pathogenies and resistome in market shrimps. Sci Total Environ 2024; 926:171924. [PMID: 38522537 DOI: 10.1016/j.scitotenv.2024.171924] [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: 01/27/2024] [Revised: 03/21/2024] [Accepted: 03/21/2024] [Indexed: 03/26/2024]
Abstract
This study employs a comprehensive approach combining metagenomic analysis and bacterial isolation to elucidate the microbial composition, antibiotic resistance genes (ARGs), and virulence factors (VFGs) present in shrimps from market and supermarket. Metagenomic analysis of shrimps revealed a dominance of Proteobacteria and Bacteroidetes with Firmicutes notably enriched in some samples. On the other hand, the dominant bacteria isolated included Citrobacter portucalensis, Escherichia coli, Salmonella enterica, Vibrio species and Klebsiella pneumonaie. Metagenomic analysis unveiled a diverse spectrum of 23 main types and 380 subtypes of ARGs in shrimp samples including many clinical significant ARGs such as blaKPC, blaNDM, mcr, tet(X4) etc. Genomic analysis of isolated bacterial strains identified 14 ARG types with 109 subtype genes, which complemented the metagenomic data. Genomic analysis also allowed us to identify a rich amount of MDR plasmids, which provided further insights into the dissemination of resistance genes in different species of bacteria in the same samples. Examination of VFGs and mobile genetic elements (MGEs) in both metagenomic and bacterial genomes revealed a complex landscape of factors contributing to bacterial virulence and genetic mobility. Potential co-occurrence patterns of ARGs and VFGs within human pathogenic bacteria underlined the intricate interplay between antibiotic resistance and virulence. In conclusion, this integrated analysis for the first time provides a comprehensive view and sheds new light on the potential hazards associated with shrimp products in the markets. The findings underscore the necessity of ongoing surveillance and intervention strategies to mitigate risks posed by antibiotic-resistant bacteria in the food supply chain using the novel comprehensive approaches.
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Affiliation(s)
- Lianwei Ye
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon, Hong Kong; State Key Lab of Chemical Biology and Drug Discovery and the Department of Food Science and Nutrition, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
| | - Zhiwei Zheng
- State Key Lab of Chemical Biology and Drug Discovery and the Department of Food Science and Nutrition, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong; Shenzhen Key Lab for Biological Safety Control, The Hong Kong Polytechnic University Shenzhen Research Institute, Shenzhen, China
| | - Yaling Wang
- Shenzhen Key Lab for Biological Safety Control, The Hong Kong Polytechnic University Shenzhen Research Institute, Shenzhen, China
| | - Qiao Hu
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon, Hong Kong; State Key Lab of Chemical Biology and Drug Discovery and the Department of Food Science and Nutrition, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
| | - Liang Zhong
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon, Hong Kong
| | - Heng Heng
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon, Hong Kong; State Key Lab of Chemical Biology and Drug Discovery and the Department of Food Science and Nutrition, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
| | - Zhihao Guo
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon, Hong Kong
| | - Runsheng Li
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon, Hong Kong
| | - Edward Wai Chi Chan
- State Key Lab of Chemical Biology and Drug Discovery and the Department of Food Science and Nutrition, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
| | - Sheng Chen
- State Key Lab of Chemical Biology and Drug Discovery and the Department of Food Science and Nutrition, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong; Shenzhen Key Lab for Biological Safety Control, The Hong Kong Polytechnic University Shenzhen Research Institute, Shenzhen, China.
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Ma B, Khan KS, Xu T, Xeque Amada J, Guo Z, Huang Y, Yan Y, Lam H, Cheng ASL, Ng BWL. Targeted Protein O-GlcNAcylation Using Bifunctional Small Molecules. J Am Chem Soc 2024; 146:9779-9789. [PMID: 38561350 PMCID: PMC11009946 DOI: 10.1021/jacs.3c14380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 03/13/2024] [Accepted: 03/13/2024] [Indexed: 04/04/2024]
Abstract
Protein O-linked β-N-acetylglucosamine modification (O-GlcNAcylation) plays a crucial role in regulating essential cellular processes. The disruption of the homeostasis of O-GlcNAcylation has been linked to various human diseases, including cancer, diabetes, and neurodegeneration. However, there are limited chemical tools for protein- and site-specific O-GlcNAc modification, rendering the precise study of the O-GlcNAcylation challenging. To address this, we have developed heterobifunctional small molecules, named O-GlcNAcylation TArgeting Chimeras (OGTACs), which enable protein-specific O-GlcNAcylation in living cells. OGTACs promote O-GlcNAcylation of proteins such as BRD4, CK2α, and EZH2 in cellulo by recruiting FKBP12F36V-fused O-GlcNAc transferase (OGT), with temporal, magnitude, and reversible control. Overall, the OGTACs represent a promising approach for inducing protein-specific O-GlcNAcylation, thus enabling functional dissection and offering new directions for O-GlcNAc-targeting therapeutic development.
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Affiliation(s)
- Bowen Ma
- School
of Pharmacy, Faculty of Medicine, The Chinese
University of Hong Kong, Sha Tin, Hong Kong
| | - Khadija Shahed Khan
- School
of Pharmacy, Faculty of Medicine, The Chinese
University of Hong Kong, Sha Tin, Hong Kong
- School
of Biomedical Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Sha Tin, Hong Kong
| | - Tongyang Xu
- School
of Pharmacy, Faculty of Medicine, The Chinese
University of Hong Kong, Sha Tin, Hong Kong
| | - Josefina Xeque Amada
- School
of Pharmacy, Faculty of Medicine, The Chinese
University of Hong Kong, Sha Tin, Hong Kong
| | - Zhihao Guo
- School
of Pharmacy, Faculty of Medicine, The Chinese
University of Hong Kong, Sha Tin, Hong Kong
| | - Yunpeng Huang
- School
of Pharmacy, Faculty of Medicine, The Chinese
University of Hong Kong, Sha Tin, Hong Kong
| | - Yu Yan
- School
of Pharmacy, Faculty of Medicine, The Chinese
University of Hong Kong, Sha Tin, Hong Kong
| | - Henry Lam
- Department
of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Sai Kung, Hong Kong
| | - Alfred Sze-Lok Cheng
- School
of Biomedical Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Sha Tin, Hong Kong
| | - Billy Wai-Lung Ng
- School
of Pharmacy, Faculty of Medicine, The Chinese
University of Hong Kong, Sha Tin, Hong Kong
- Li Ka
Shing Institute of Health Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Sha Tin, Hong
Kong
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Yao Y, Wang X, Zhao B, Mo J, Guo Z, Yang B, Li Z, Fan X, Cai D, Sang L, Zheng Z, Shao X, Ai L, Hu W, Zhang C, Zhang K. Hypometabolic patterns are related to post-surgical seizure outcomes in focal cortical dysplasia: A semi-quantitative study. Epilepsia Open 2024; 9:653-664. [PMID: 38265725 PMCID: PMC10984320 DOI: 10.1002/epi4.12903] [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: 05/11/2023] [Revised: 12/25/2023] [Accepted: 01/06/2024] [Indexed: 01/25/2024] Open
Abstract
OBJECTIVE Fluorine-18-fluorodeoxyglucose-positron emission tomography (FDG-PET) is routinely used for presurgical evaluation in many epilepsy centers. Hypometabolic characteristics have been extensively examined in prior studies, but the metabolic patterns associated with specific pathological types of drug-resistant epilepsy remain to be fully defined. This study was developed to explore the relationship between metabolic patterns or characteristics and surgical outcomes in type I and II focal cortical dysplasia (FCD) patients based on results from a large cohort. METHODS Data from individuals who underwent epilepsy surgery from 2014 to 2019 with a follow-up duration of over 3 years and a pathological classification of type I or II FCD in our hospital were retrospectively analyzed. Hypometabolic patterns were quantitatively identified via statistical parametric mapping (SPM) and qualitatively analyzed via visual examination of PET-MRI co-registration images. Univariate analyses were used to explore the relationship between metabolic patterns and surgical outcomes. RESULTS In total, this study included data from 210 patients. Following SPM calculations, four hypometabolic patterns were defined including unilobar, multi-lobar, and remote patterns as well as cases where no pattern was evident. In type II FCD patients, the unilobar pattern was associated with the best surgical outcomes (p = 0.014). In visual analysis, single gyrus (p = 0.032) and Clear-cut hypometabolism edge (p = 0.040) patterns exhibited better surgery outcomes in the type II FCD group. CONCLUSIONS PET metabolic patterns are well-correlated with the prognosis of type II FCD patients. However, similar correlations were not observed in type I FCD, potentially owing to the complex distribution of the epileptogenic region. PLAIN LANGUAGE SUMMARY In this study, we demonstrated that FDG-PET was a crucial examination for patients with FCD, which was a common cause of epilepsy. We compared the surgical prognosis for patients with different hypometabolism distribution patterns and found that clear and focal abnormal region in PET was correlated with good surgical outcome in type II FCD patients.
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Affiliation(s)
- Yuan Yao
- Department of NeurosurgeryBeijing TianTan Hospital, Capital Medical UniversityBeijingChina
| | - Xiu Wang
- Department of NeurosurgeryBeijing TianTan Hospital, Capital Medical UniversityBeijingChina
| | - Baotian Zhao
- Department of NeurosurgeryBeijing TianTan Hospital, Capital Medical UniversityBeijingChina
| | - Jiajie Mo
- Department of NeurosurgeryBeijing TianTan Hospital, Capital Medical UniversityBeijingChina
| | - Zhihao Guo
- Department of NeurosurgeryBeijing TianTan Hospital, Capital Medical UniversityBeijingChina
| | - Bowen Yang
- Department of NeurosurgeryBeijing TianTan Hospital, Capital Medical UniversityBeijingChina
| | - Zilin Li
- Department of NeurosurgeryBeijing TianTan Hospital, Capital Medical UniversityBeijingChina
| | - Xiuliang Fan
- Department of NeurosurgeryBeijing TianTan Hospital, Capital Medical UniversityBeijingChina
| | - Du Cai
- Department of NeurosurgeryBeijing TianTan Hospital, Capital Medical UniversityBeijingChina
| | - Lin Sang
- Department of NeurosurgeryBeijing FengTai HospitalBeijingChina
| | - Zhong Zheng
- Department of NeurosurgeryBeijing FengTai HospitalBeijingChina
| | - Xiaoqiu Shao
- Department of NeurologyBeijing TianTan Hospital, Capital Medical UniversityBeijingChina
| | - Lin Ai
- Department of Nuclear MedicineBeijing TianTan Hospital, Capital Medical UniversityBeijingChina
| | - Wenhan Hu
- Beijing Neurosurgical InstituteCapital Medical UniversityBeijingChina
| | - Chao Zhang
- Department of NeurosurgeryBeijing TianTan Hospital, Capital Medical UniversityBeijingChina
| | - Kai Zhang
- Department of NeurosurgeryBeijing TianTan Hospital, Capital Medical UniversityBeijingChina
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Tan L, Guo Z, Wang X, Kim DY, Li R. Utilization of nanopore direct RNA sequencing to analyze viral RNA modifications. mSystems 2024; 9:e0116323. [PMID: 38294229 PMCID: PMC10878088 DOI: 10.1128/msystems.01163-23] [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: 11/02/2023] [Accepted: 12/19/2023] [Indexed: 02/01/2024] Open
Abstract
Modifications on viral RNAs (vRNAs), either genomic RNAs or RNA transcripts, have complex effects on the viral life cycle and cellular responses to viral infection. The advent of Oxford Nanopore Technologies Direct RNA Sequencing provides a new strategy for studying RNA modifications. To this end, multiple computational tools have been developed, but a systemic evaluation of their performance in mapping vRNA modifications is lacking. Here, 10 computational tools were tested using the Sindbis virus (SINV) RNAs isolated from infected mammalian (BHK-21) or mosquito (C6/36) cells, with in vitro-transcribed RNAs serving as modification-free control. Three single-mode approaches were shown to be inapplicable in the viral context, and three out of seven comparative methods required cutoff adjustments to reduce false-positive predictions. Utilizing optimized cutoffs, an integrated analysis of comparative tools suggested that the intersected predictions of Tombo_com and xPore were significantly enriched compared with the background. Consequently, a pipeline integrating Tombo_com and xPore was proposed for vRNA modification detection; the performance of which was supported by N6-methyladenosine prediction in severe acute respiratory syndrome coronavirus 2 RNAs using publicly available data. When applied to SINV RNAs, this pipeline revealed more intensive modifications in subgenomic RNAs than in genomic RNAs. Modified uridines were frequently identified, exhibiting substantive overlapping between vRNAs generated in different cell lines. On the other hand, the interpretation of other modifications remained unclear, underlining the limitations of the current computational tools despite their notable potential.IMPORTANCEComputational approaches utilizing Oxford Nanopore Technologies Direct RNA Sequencing data were almost exclusively designed to map eukaryotic epitranscriptomes. Therefore, extra caution must be exercised when using these tools to detect vRNA modifications, as in most cases, vRNA modification profiles should be regarded as unknown epitranscriptomes without prior knowledge. Here, we comprehensively evaluated the performance of 10 computational tools in detecting vRNA modification sites. All tested single-mode methods failed to differentiate native and in vitro-transcribed samples. Using optimized cutoff values, seven tested comparative tools generated very different predictions. An integrated analysis showed significant enrichment of Tombo_com and xPore predictions against the background. A pipeline for vRNA modification detection was proposed accordingly and applied to Sindbis virus RNAs. In conclusion, our study underscores the need for the careful application of computational tools to analyze viral epitranscriptomics. It also offers insights into alphaviral RNA modifications, although further validation is required.
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Affiliation(s)
- Lu Tan
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, China
| | - Zhihao Guo
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, China
| | - Xiaoming Wang
- College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China
| | - Dal Young Kim
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, China
| | - Runsheng Li
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, China
- Tung Biomedical Sciences Centre, City University of Hong Kong, Hong Kong, China
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Zhang Z, Guo Z, Tan Y, Li L, Wang Z, Wen Y, Huang S, Shang D. Population pharmacokinetic approach to guide personalized sertraline treatment in Chinese patients. Heliyon 2024; 10:e25231. [PMID: 38352761 PMCID: PMC10861969 DOI: 10.1016/j.heliyon.2024.e25231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 01/23/2024] [Accepted: 01/23/2024] [Indexed: 02/16/2024] Open
Abstract
Object: Sertraline is a first-line SSRI for the treatment of depression and has the same effectiveness along with a superior safety profile compared to other medications. There are few population pharmacokinetic (PPK) studies of sertraline and a lack of studies in the Chinese population. Therefore, we performed a PPK analysis of Chinese patients treated with sertraline to identify factors that can influence drug exposure. In addition, the dosing and discontinuation regimen of sertraline when applied to adolescents was explored. Methods: Sertraline serum drug concentration data were collected from 140 hospitalized patients to generate a sertraline PPK dataset, and data evaluation and examination of the effects of covariates on drug exposure in the final model were performed using nonlinear mixed-effects models (NONMEM) and first-order conditional estimation with interaction (FOCE-I). Examining rational medication administration and rational withdrawal of sertraline based on significant covariates and final modeling. Results: A one-compartment model with first-order absorption and elimination of sertraline was developed for Chinese patients with psychiatric disorders. Analysis of covariates revealed that age was a covariate that significantly affected sertraline CL/F (P < 0.01) and that sertraline clearance decreased progressively with aging, whereas other factors had no effect on CL/F and V/F of sertraline. In the age range of 11-79, there were 54 adolescent patients (about 1/3) aged 13-18 years, and the safe and effective optimal daily dose for adolescent patients based on the final model simulations was 50-250 mg/d. For adolescent patients, serum concentration fluctuations were moderate for OD doses of 50 mg and 100 mg, using a fixed dose-descent regimen. For patients with OD doses of 150-200 mg and BID doses of 100-200 mg, a more gradual decrease in serum concentration was achieved with a fixed dose interval of 7 or 14 days for 25 mg as the regimen of descent. Conclusions: To our knowledge, this may be the first PPK study of sertraline in Chinese patients. We found that age was an important factor affecting clearance in Chinese patients taking sertraline. Patients taking sertraline may be exposed to increased amounts of sertraline due to decreased clearance with increasing age. The rational dosing and safe discontinuation of sertraline in adolescent patients can be appropriately referenced to the results of the model simulation, thus providing assistance for individualized dosing in adolescents.
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Affiliation(s)
- Zi Zhang
- Department of Pharmacy, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, 510000, China
| | - Zhihao Guo
- Department of Pharmacy, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, 510000, China
| | - Yaqian Tan
- Department of Pharmacy, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, 510000, China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510000, China
| | - Lu Li
- Department of Pharmacy, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, 510000, China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510000, China
| | - Zhanzhang Wang
- Department of Pharmacy, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, 510000, China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510000, China
| | - Yuguan Wen
- Department of Pharmacy, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, 510000, China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510000, China
| | - Shanqing Huang
- Department of Pharmacy, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, 510000, China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510000, China
| | - Dewei Shang
- Department of Pharmacy, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, 510000, China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510000, China
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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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Yang B, Zhao B, Li C, Mo J, Guo Z, Li Z, Yao Y, Fan X, Cai D, Sang L, Zheng Z, Gao D, Zhao X, Wang X, Zhang C, Hu W, Shao X, Zhang J, Zhang K. Localizing seizure onset zone by a cortico-cortical evoked potentials-based machine learning approach in focal epilepsy. Clin Neurophysiol 2024; 158:103-113. [PMID: 38218076 DOI: 10.1016/j.clinph.2023.12.135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 12/03/2023] [Accepted: 12/19/2023] [Indexed: 01/15/2024]
Abstract
OBJECTIVE We aimed to develop a new approach for identifying the localization of the seizure onset zone (SOZ) based on corticocortical evoked potentials (CCEPs) and to compare the connectivity patterns in patients with different clinical phenotypes. METHODS Fifty patients who underwent stereoelectroencephalography and CCEP procedures were included. Logistic regression was used in the model, and six CCEP metrics were input as features: root mean square of the first peak (N1RMS) and second peak (N2RMS), peak latency, onset latency, width duration, and area. RESULTS The area under the curve (AUC) for localizing the SOZ ranged from 0.88 to 0.93. The N1RMS values in the hippocampus sclerosis (HS) group were greater than that of the focal cortical dysplasia (FCD) IIa group (p < 0.001), independent of the distance between the recorded and stimulated sites. The sensitivity of localization was higher in the seizure-free group than in the non-seizure-free group (p = 0.036). CONCLUSIONS This new method can be used to predict the SOZ localization in various focal epilepsy phenotypes. SIGNIFICANCE This study proposed a machine-learning approach for localizing the SOZ. Moreover, we examined how clinical phenotypes impact large-scale abnormality of the epileptogenic networks.
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Affiliation(s)
- Bowen Yang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Baotian Zhao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Chao Li
- Department of Radiology, Third Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Guangzhou, China
| | - Jiajie Mo
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zhihao Guo
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zilin Li
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yuan Yao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xiuliang Fan
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Du Cai
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Lin Sang
- Department of Neurosurgery, Beijing Fengtai Hospital, Beijing, China
| | - Zhong Zheng
- Department of Neurosurgery, Beijing Fengtai Hospital, Beijing, China
| | - Dongmei Gao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xuemin Zhao
- Department of Neurophysiology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Xiu Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Stereotactic and Functional Neurosurgery Laboratory, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Chao Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Stereotactic and Functional Neurosurgery Laboratory, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Wenhan Hu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Stereotactic and Functional Neurosurgery Laboratory, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Xiaoqiu Shao
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jianguo Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Stereotactic and Functional Neurosurgery Laboratory, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Kai Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Stereotactic and Functional Neurosurgery Laboratory, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
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Heng H, Yang X, Ye L, Tang Y, Guo Z, Li J, Chan EWC, Zhang R, Chen S. Global genomic profiling of Klebsiella pneumoniae: A spatio-temporal population structure analysis. Int J Antimicrob Agents 2024; 63:107055. [PMID: 38081547 DOI: 10.1016/j.ijantimicag.2023.107055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 11/30/2023] [Accepted: 12/05/2023] [Indexed: 01/15/2024]
Abstract
Klebsiella pneumoniae is an important clinical bacterial pathogen that has hypervirulent and multidrug-resistant variants. Uniform Manifold Approximation and Projection (UMAP) was used to cluster genomes of 16 797 K. pneumoniae strains collected, based on core genome distance, in over 100 countries during the period 1937 to 2021. A total of 60 high-density genetic clusters of strains representing the major epidemic strains were identified among these strains. Using UMAP bedding, the relationship between genetic cluster, capsular polysaccharide (KL) types and sequence type (ST) of the strains was clearly demonstrated, with some important STs, such as ST11 and ST258, found to contain multiple clusters. Strains within the same cluster often exhibited significant diverse features, such as originating from different areas and being isolated in different years, as well as carriage of different resistance and virulence genes. These data enable the routes of evolution of the globally prevalent K. pneumoniae strains to be traced. Alarmingly, carbapenem-resistant K. pneumoniae strains accounted for 51.7% of the test strains and worldwide transmission was observed. Carbapenem-resistant and hypervirulent K. pneumoniae strains are mainly reported in China; however, these strains are increasingly reported in other parts of the world. Also identified in this study were several key genetic loci that facilitate development of a new K. pneumoniae typing method to differentiate between high- and low-risk strains. In particular, the acrR, ompK35 and hha genes were predicted to play a key role in expression of the resistance and virulence phenotypes.
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Affiliation(s)
- Heng Heng
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon, Hong Kong SAR; State Key Lab of Chemical Biology and Drug Discovery and the Department of Food Science and Nutrition, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR
| | - Xuemei Yang
- State Key Lab of Chemical Biology and Drug Discovery and the Department of Food Science and Nutrition, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR; Shenzhen Key Laboratory of Food Biological Safety Control, The Hong Kong Polytechnic University Shenzhen Research Institute, Shenzhen, China
| | - Lianwei Ye
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon, Hong Kong SAR; State Key Lab of Chemical Biology and Drug Discovery and the Department of Food Science and Nutrition, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR
| | - Yang Tang
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon, Hong Kong SAR; State Key Lab of Chemical Biology and Drug Discovery and the Department of Food Science and Nutrition, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR
| | - Zhihao Guo
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon, Hong Kong SAR
| | - Jun Li
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon, Hong Kong SAR
| | - Edward Wai-Chi Chan
- State Key Lab of Chemical Biology and Drug Discovery and the Department of Food Science and Nutrition, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR
| | - Rong Zhang
- Department of Clinical Laboratory, Second Affiliated Hospital of Zhejiang University, School of Medicine, Zhejiang, Hangzhou, China
| | - Sheng Chen
- State Key Lab of Chemical Biology and Drug Discovery and the Department of Food Science and Nutrition, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR; Shenzhen Key Laboratory of Food Biological Safety Control, The Hong Kong Polytechnic University Shenzhen Research Institute, Shenzhen, China.
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Zhao X, Hu X, Guo Z, Hu W, Zhang C, Mo J, Zhang K. Deep Learning Approaches for Imaging-Based Automated Segmentation of Tuberous Sclerosis Complex. J Clin Med 2024; 13:680. [PMID: 38337374 PMCID: PMC10856546 DOI: 10.3390/jcm13030680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 10/22/2023] [Accepted: 01/17/2024] [Indexed: 02/12/2024] Open
Abstract
The present study presents a novel approach for identifying epileptogenic tubers in patients with tuberous sclerosis complex (TSC) and automating tuber segmentation using a three-dimensional convolutional neural network (3D CNN). The study retrospectively included 31 TSC patients whose lesions were manually annotated from multiparametric neuroimaging data. Epileptogenic tubers were determined via presurgical evaluation and stereoelectroencephalography recording. Neuroimaging metrics were extracted and compared between epileptogenic and non-epileptogenic tubers. Additionally, five datasets with different preprocessing strategies were used to construct and train 3D CNNs for automated tuber segmentation. The normalized positron emission tomography (PET) metabolic value was significantly lower in epileptogenic tubers defined via presurgical evaluation (p = 0.001). The CNNs showed high performance for localizing tubers, with an accuracy between 0.992 and 0.994 across the five datasets. The automated segmentations were highly correlated with clinician-based features. The neuroimaging characteristics for epileptogenic tubers were demonstrated, increasing surgical confidence in clinical practice. The validated deep learning detection algorithm yielded a high performance in determining tubers with an excellent agreement with reference clinician-based segmentation. Collectively, when coupled with our investigation of minimal input requirements, the approach outlined in this study represents a clinically invaluable tool for the management of TSC.
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Affiliation(s)
- Xuemin Zhao
- Department of Neurophysiology, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100071, China;
| | - Xu Hu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100071, China; (X.H.); (Z.G.); (W.H.); (C.Z.)
- Department of Neurosurgery, Wuxi Taihu Hospital, Wuxi Clinical College of Anhui Medical University, Wuxi 214000, China
| | - Zhihao Guo
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100071, China; (X.H.); (Z.G.); (W.H.); (C.Z.)
| | - Wenhan Hu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100071, China; (X.H.); (Z.G.); (W.H.); (C.Z.)
| | - Chao Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100071, China; (X.H.); (Z.G.); (W.H.); (C.Z.)
| | - Jiajie Mo
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100071, China; (X.H.); (Z.G.); (W.H.); (C.Z.)
| | - Kai Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100071, China; (X.H.); (Z.G.); (W.H.); (C.Z.)
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12
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Mo J, Guo Z, Wang X, Zhang J, Hu W, Shao X, Sang L, Zheng Z, Zhang C, Zhang K. Magnetic resonance-guided laser interstitial thermal therapy vs. open surgery for drug-resistant mesial temporal lobe epilepsy: a propensity score matched retrospective cohort study. Int J Surg 2024; 110:306-314. [PMID: 37800596 PMCID: PMC10793731 DOI: 10.1097/js9.0000000000000811] [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: 07/12/2023] [Accepted: 09/18/2023] [Indexed: 10/07/2023]
Abstract
BACKGROUND Magnetic resonance-guided laser interstitial thermal therapy (MRgLITT) and traditional open surgery (OS) are effective and safe options for patients with drug-resistant mesial temporal lobe epilepsy (DR-mTLE). However, their superiority in seizure control and preservation of functional abilities remains unclear. This study aimed to compare the surgical outcomes of MRgLITT and OS. MATERIALS AND METHODS This multicenter retrospective cohort study included patients with DR-mTLE who underwent MRgLITT or OS at three centres between 2015 and 2023. The data on patient demographics, presurgical non-invasive evaluation, stereoelectroencephalography (SEEG) implantation, memory alteration, and seizure outcomes were collected. Propensity score matching (PSM) analysis was conducted for the comparison of seizure control and functional preservation between two surgical approaches. RESULTS Of the 244 individuals who met the study criteria, 33 underwent MRgLITT and 211 OS. The median (interquartile range) age at seizure onset was 22.0 (13.0) and 12.3 (10.0) years in the MRgLITT and OS groups, respectively. The first PSM, based on demographic and non-invasive information, resulted in 26 matched pairs for the primary analysis. There were no significant differences in memory preservation ( P = 0.95) or surgical outcomes ( P = 0.96) between the groups. The second PSM, based on demographics and SEEG implantation, yielded 32 matched pairs for the sensitivity analysis, showing similar results. Subset analysis of early and late MRgLITT cases revealed no statistically significant differences in the proportion of patients with memory decline ( P = 0.42) or seizure control ( P = 1.00). Patients who underwent SEEG implantation were 96% less likely to achieve seizure freedom after MRgLITT ( P = 0.02). CONCLUSION Minimally invasive MRgLITT is associated with memory preservation and seizure control, similar to traditional OS. MRgLITT is effective and safe for DR-mTLE and is relevant for future prospective randomized trials on dominant-side mTLE, providing practical implications for guiding neurosurgeons in the selection of surgical approaches.
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Affiliation(s)
- Jiajie Mo
- Departments ofNeurosurgery
- Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University
| | - Zhihao Guo
- Departments ofNeurosurgery
- Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University
| | - Xiu Wang
- Departments ofNeurosurgery
- Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University
| | - Jianguo Zhang
- Departments ofNeurosurgery
- Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University
| | - Wenhan Hu
- Departments ofNeurosurgery
- Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University
| | - Xiaoqiu Shao
- Neurology, Beijing Tiantan Hospital
- China National Clinical Research Center for Neurological Disease, NCRC-ND
| | - Lin Sang
- Department of Neurosurgery, Beijing Fengtai Hospital, Beijing, China
| | - Zhong Zheng
- Department of Neurosurgery, Beijing Fengtai Hospital, Beijing, China
| | - Chao Zhang
- Departments ofNeurosurgery
- Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University
| | - Kai Zhang
- Departments ofNeurosurgery
- Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University
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Guo Z, Chen C, Deng S, Lu H, Ni X, Zhang M, Huang S, Wen Y, Shang D, Wang Z. Factors influencing concentrations of risperidone and 9-hydroxyrisperidone in psychiatric outpatients taking immediate-release formulations of risperidone. Hum Psychopharmacol 2024; 39:e2886. [PMID: 37983624 DOI: 10.1002/hup.2886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Revised: 10/10/2023] [Accepted: 11/07/2023] [Indexed: 11/22/2023]
Abstract
OBJECTIVES To analyze the factors affecting the concentrations of the active moiety of risperidone (RIS) and its active metabolite 9-hydroxyrisperidone (9-OH-RIS) in psychiatric outpatients taking immediate-release formulations. METHODS This is a retrospective study on the therapeutic drug monitoring (TDM) data regarding RIS and 9-OH-RIS in adult psychiatric outpatients. TDM data with simultaneous RIS and 9-OH-RIS monitoring from March 2018 to February 2020 and relevant medical records (including dosage, dosage form, sex, age, diagnosis, combined medication, and comorbid disease) from 399 adult psychiatric outpatients (223 males and 176 females) were included in this study. RESULTS The daily dose of RIS was 5.56 ± 2.05 mg, the concentration of total active moiety was 42.35 ± 25.46 ng/mL, and the dose-adjusted plasma concentration (C/D) of active moiety was 7.83 ± 3.87 (ng/ml)/(mg/day). Dose, sex, and age were identified as important factors influencing concentrations of RIS and 9-OH-RIS in adult psychiatric outpatients. CONCLUSIONS Individualized medication adjustments should be made according to the specific conditions of psychiatric outpatients. The findings strongly support the use of TDM to guide dosing decisions in psychiatric outpatients taking RIS.
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Affiliation(s)
- Zhihao Guo
- Department of Pharmacy, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- School of Pharmacy, Guangzhou Medical University, Guangzhou, China
| | - Chunxiu Chen
- Department of Pharmacy, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- School of Pharmacy, Guangzhou Medical University, Guangzhou, China
| | - Shuhua Deng
- Department of Pharmacy, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
| | - Haoyang Lu
- Department of Pharmacy, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
| | - Xiaojia Ni
- Department of Pharmacy, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
| | - Ming Zhang
- Department of Pharmacy, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
| | - Shanqing Huang
- Department of Pharmacy, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yuguan Wen
- Department of Pharmacy, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
| | - Dewei Shang
- Department of Pharmacy, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
| | - Zhanzhang Wang
- Department of Pharmacy, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
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Wang L, Chen P, Ding Y, Fan S, Wang G, Jia S, Guo Z, Zheng C. Effects of Kinesio taping on lower limb biomechanical characteristics during unexpected jumping in patients with chronic ankle instability. Scand J Med Sci Sports 2024; 34:e14566. [PMID: 38268069 DOI: 10.1111/sms.14566] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 12/06/2023] [Accepted: 01/05/2024] [Indexed: 01/26/2024]
Abstract
PURPOSE The current biomechanical research on the application of Kinesio taping (KT) to patients with chronic ankle instability (CAI) has focused on testing the expected movements. However, unexpected movements are more common in actual sports. Therefore, the present study aimed to investigate the effects of KT on the biomechanical characteristics of the knee and ankle joints during unexpected jumping movements. METHODS Twenty-one patients with unilateral CAI were recruited to capture the biomechanical parameters during unexpected jumping movements under different interventions: no taping (NT), placebo taping (PT), and KT. A one-way repeated measures analysis of variance was used to compare the differences in knee and ankle biomechanical characteristics among patients with CAI between the three intervention conditions. RESULTS At initial contact, the KT group demonstrated a significant decrease in ankle plantarflexion and knee flexion angles compared to the NT group (p < 0.05). At the early landing phase, the KT group had a significant increase in peak ankle dorsiflexion angle, peak ankle eversion angle, peak ankle dorsiflexion moment, and peak ankle eversion moment compared to the NT and PT groups (p < 0.05). Furthermore, the KT group had a significantly reduced peak knee flexion angle, peak knee eversion angle, and peak vertical ground reaction force (p < 0.05) compared to the NT and PT groups. CONCLUSION KT significantly improves the sprain-prone touchdown posture of patients with CAI. And reducing the risk of ankle sprains during the early landing phase by promoting ankle dorsiflexion and eversion angles and moments.
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Affiliation(s)
- Ling Wang
- School of Sports Medicine, Wuhan Sports University, Wuhan, Hubei, China
- Key Laboratory of Sports Engineering of General Administration of Sport of China, Wuhan Sports University, Wuhan, Hubei, China
| | - Peng Chen
- School of Exercise and Health, Shanghai University of Sport, Shanghai, China
| | - Yue Ding
- Taihe Hospital, Shiyan, Hubei, China
| | - Siyu Fan
- School of Sports Medicine, Wuhan Sports University, Wuhan, Hubei, China
| | - Guanglan Wang
- School of Sports Medicine, Wuhan Sports University, Wuhan, Hubei, China
| | - Shaohui Jia
- School of Sports Medicine, Wuhan Sports University, Wuhan, Hubei, China
- Hubei Provincial Key Laboratory of Sports Training and Monitoring, Wuhan Sports University, Wuhan, Hubei, China
| | - Zhihao Guo
- Key Laboratory of Sports Engineering of General Administration of Sport of China, Wuhan Sports University, Wuhan, Hubei, China
- Engineering Research Center of Sports Health Intelligent Equipment of Hubei Province, Wuhan Sports University, Wuhan, China
| | - Cheng Zheng
- Department of Sports Medicine, Affiliated Hospital, Wuhan Sports University, Wuhan, Hubei, China
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Li T, Zhou H, Liu W, Gao J, Guo Z, Su Z, Yan Y, Su S, Xie H, Peng G, Qu M. A Freestanding 3D Skeleton with Gradationally Distributed Lithiophilic Sites for Realizing Stable Lithium Anodes. Chemistry 2023; 29:e202301991. [PMID: 37610944 DOI: 10.1002/chem.202301991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 08/22/2023] [Accepted: 08/22/2023] [Indexed: 08/25/2023]
Abstract
Lithium (Li) metal anodes are drawing considerable attention owing to their ultrahigh theoretical capacities and low electrochemical reduction potentials. However, their commercialization has been hampered by safety hazards induced by continuous dendrite growth. These issues can be alleviated using the ZnO-modified 3D carbon-based host containing carbon nanotubes (CNTs) and carbon felt (CF) fabricated by electroplating in the present study (denoted as ZnO/CNT@CF). The constructed skeleton has lithiophilic ZnO that is gradationally distributed along its thickness. The utilization of an inverted ZnO/CNT@CF-Li anode obtained by flipping over the carbon skeleton after Li electrodeposition is also reported herein. The synergistic effect of the Li metal and lithiophilic sites reduces the nucleation overpotential, thus inducing Li+ to preferentially deposit inside the porous carbon-based scaffold. The composite electrode compels Li to grow away from the separator, thereby significantly improving battery safety. A symmetric cell with the inverted ZnO/CNT@CF-Li electrode operates steadily for 700 cycles at 1 mA cm-2 and 1 mAh cm-2 . Moreover, the ZnO/CNT@CF-Li|S cell exhibits an initial areal capacity of 10.9 mAh cm-2 at a S loading of 10.4 mg cm-2 and maintains a capacity of 3.0 mAh cm-2 after 320 cycles.
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Affiliation(s)
- Tianhui Li
- Chengdu Institute of Organic Chemistry, Chinese Academy of Sciences, Chengdu, Sichuan, 610041, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Hanxiao Zhou
- Chengdu Institute of Organic Chemistry, Chinese Academy of Sciences, Chengdu, Sichuan, 610041, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Wenjing Liu
- Chengdu Institute of Organic Chemistry, Chinese Academy of Sciences, Chengdu, Sichuan, 610041, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jingjing Gao
- Chengdu Institute of Organic Chemistry, Chinese Academy of Sciences, Chengdu, Sichuan, 610041, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Zhihao Guo
- Chengdu Institute of Organic Chemistry, Chinese Academy of Sciences, Chengdu, Sichuan, 610041, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Zihao Su
- Chengdu Institute of Organic Chemistry, Chinese Academy of Sciences, Chengdu, Sichuan, 610041, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yuanting Yan
- Chengdu Institute of Organic Chemistry, Chinese Academy of Sciences, Chengdu, Sichuan, 610041, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Shaoxiang Su
- Chengdu Institute of Organic Chemistry, Chinese Academy of Sciences, Chengdu, Sichuan, 610041, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Haoyu Xie
- Chengdu Institute of Organic Chemistry, Chinese Academy of Sciences, Chengdu, Sichuan, 610041, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Gongchang Peng
- Chengdu Institute of Organic Chemistry, Chinese Academy of Sciences, Chengdu, Sichuan, 610041, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Meizhen Qu
- Chengdu Institute of Organic Chemistry, Chinese Academy of Sciences, Chengdu, Sichuan, 610041, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
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Ma X, Guo W, Zhu X, Li Z, Li Y, Guo Z, Wang Y, Pang J, Yuan M, Li Z, You X, Lu X, Liu Y, Song D. Synthesis of peptidomimetics as antibiotic adjuvants for combination with aztreonam to combat MDR Pseudomonas aeruginosa. Eur J Med Chem 2023; 260:115778. [PMID: 37672933 DOI: 10.1016/j.ejmech.2023.115778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 08/28/2023] [Accepted: 08/29/2023] [Indexed: 09/08/2023]
Abstract
Pseudomonas aeruginosa is one of the multipledrug-resistant (MDR) Gram-negative pathogens with few drugs available for treatment. Antibiotic adjuvant approach provides an alternative and complementary strategy. In this study, the stereo-structure-activity relationship of monobactams against MDR Gram-negative organisms was extended. Meanwhile, a series of novel peptidemimetic derivatives as antibiotic adjuvants was synthesized and evaluated for their synergistic effects with aztreonam (AZT) against P. aeruginosa, using dipeptide PAβN as the lead. Among the analogues, compound 22j showed a significant synergistic effect against MDR P. aeruginosa in vitro and in vivo, presumably through the mechanism of affecting the permeability of outer membrane. Thus, we identified 22j as a novel peptidemimetic lead compound to potentiate the activity of AZT against MDR P. aeruginosa, which is worthy of further development as antibiotic adjuvant candidates.
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Affiliation(s)
- Xican Ma
- Beijing Key Laboratory of Antimicrobial Agents, Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Wei Guo
- Beijing Key Laboratory of Antimicrobial Agents, Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Xi Zhu
- Beijing Key Laboratory of Antimicrobial Agents, Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Zhiwen Li
- Beijing Key Laboratory of Antimicrobial Agents, Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Yinghong Li
- Beijing Key Laboratory of Antimicrobial Agents, Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Zhihao Guo
- Beijing Key Laboratory of Antimicrobial Agents, Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Yanxiang Wang
- Beijing Key Laboratory of Antimicrobial Agents, Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Jing Pang
- Beijing Key Laboratory of Antimicrobial Agents, Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Min Yuan
- State Key Laboratory for Infectious Diseases Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Disease, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China
| | - Zhenjun Li
- State Key Laboratory for Infectious Diseases Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Disease, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China
| | - Xuefu You
- Beijing Key Laboratory of Antimicrobial Agents, Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Xi Lu
- Beijing Key Laboratory of Antimicrobial Agents, Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China.
| | - Yishuang Liu
- Beijing Key Laboratory of Antimicrobial Agents, Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China.
| | - Danqing Song
- Beijing Key Laboratory of Antimicrobial Agents, Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China.
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17
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Xiao W, Chen Y, Zhang J, Guo Z, Hu Y, Yang F, Wang C. A Simplified and Ultrafast Pipeline for Site-Specific Quantitative Chemical Proteomics. J Proteome Res 2023; 22:3360-3367. [PMID: 37676756 DOI: 10.1021/acs.jproteome.3c00179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/09/2023]
Abstract
Activity-based proteome profiling (ABPP) is a powerful chemoproteomic technology for global profiling of protein activity and modifications. The tandem orthogonal proteolysis-ABPP (TOP-ABPP) strategy utilizes a clickable enrichment tag with cleavable linkers to enable direct identification of probe-labeled residue sites within the target proteins. However, such a site-specific chemoproteomic workflow requires a long operation time and complex sample preparation procedures, limiting its wide applications. In the current study, we developed a simplified and ultrafast peptide enrichment and release TOP-ABPP ("superTOP-ABPP") pipeline for site-specific quantitative chemoproteomic analysis with special agarose resins that are functionalized with azide groups and acid-cleavable linkers. The azide groups allow enrichment of peptides that are labeled by the alkynyl probe through a one-step click reaction, which can be conveniently released by acid cleavage for subsequent LC-MS/MS analysis. In comparison with the traditional TOP-ABPP method, superTOP-ABPP cuts down the averaged sample preparation time from 25 to 9 h, and significantly improves the sensitivity and coverage of site-specific cysteinome profiling. The method can also be seamlessly integrated with reductive dimethylation to enable quantitative chemoproteomic analysis with a high accuracy. The simplified and ultrafast superTOP-ABPP will become a valuable tool for site-specific quantitative chemoproteomic studies.
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Affiliation(s)
- Weidi Xiao
- Synthetic and Functional Biomolecules Center, Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Ying Chen
- Synthetic and Functional Biomolecules Center, Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Jin Zhang
- Synthetic and Functional Biomolecules Center, Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China
| | - Zhihao Guo
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Yihao Hu
- Synthetic and Functional Biomolecules Center, Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China
| | - Fan Yang
- Synthetic and Functional Biomolecules Center, Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China
| | - Chu Wang
- Synthetic and Functional Biomolecules Center, Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
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18
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Guo Z, Li Q, Li X, Wang Z, Guo H, Peng W, Li G, Yan G, Wang J. Uniform Densification of Garnet Electrolyte for Solid-State Lithium Batteries. Small Methods 2023; 7:e2300232. [PMID: 37199176 DOI: 10.1002/smtd.202300232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 04/13/2023] [Indexed: 05/19/2023]
Abstract
Highly uniformly dense garnet type solid-state electrolyte plays a significant role in determining the performance of solid-state lithium batteries. Herein, a rational powder-covering sintering strategy is proposed and demonstrated, in which narrow-particle-size-distribution fine powder and uniform sintering temperature distribution are considered as very significant factors. It is suggested that powder materials with wider particle size distribution dramatically decrease the densified level of electrolytes. Slow temperature elevating rate and the overhead structure of bearing table are found to be beneficial to uniform densification. Moreover, the uniform densification process of sintering solid-state electrolyte is studied both microscopically and macroscopically, which can be divided into three phases according to the grain growing evolution and linear shrinkage patterns. The ionic conductivity of the as-prepared Li6.4 La3 Zr1.4 Ta0.6 O12 (LLZTO) garnet electrolyte is determined to be 0.73 mS cm-1 at 303 K with an activation energy of 0.37 eV. The Li/LLZTO/Li symmetric cell exhibits a small interfacial impedance of 8.49 Ω cm2 and a high apparent critical current density of 2.15 mA cm-2 and also can be cycled for 1000 h continuously without short-circuit. Such results indicate the good feasibility of as-proposed sintering strategy to prepare uniformly dense garnet type solid-state electrolytes for solid-state lithium batteries.
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Affiliation(s)
- Zhihao Guo
- School of Metallurgy and Environment, Central South University, Changsha, 410083, China
| | - Qihou Li
- School of Metallurgy and Environment, Central South University, Changsha, 410083, China
| | - Xinhai Li
- School of Metallurgy and Environment, Central South University, Changsha, 410083, China
- Engineering Research Center of the Ministry of Education for Advanced Battery Materials, Central South University, Changsha, 410083, China
- Key Laboratory of Value-added Metallurgy of Hunan Province, Central South University, Changsha, 410083, China
| | - Zhixing Wang
- School of Metallurgy and Environment, Central South University, Changsha, 410083, China
- Engineering Research Center of the Ministry of Education for Advanced Battery Materials, Central South University, Changsha, 410083, China
- Key Laboratory of Value-added Metallurgy of Hunan Province, Central South University, Changsha, 410083, China
| | - Huajun Guo
- School of Metallurgy and Environment, Central South University, Changsha, 410083, China
- Engineering Research Center of the Ministry of Education for Advanced Battery Materials, Central South University, Changsha, 410083, China
- Key Laboratory of Value-added Metallurgy of Hunan Province, Central South University, Changsha, 410083, China
| | - Wenjie Peng
- School of Metallurgy and Environment, Central South University, Changsha, 410083, China
| | - Guangchao Li
- School of Metallurgy and Environment, Central South University, Changsha, 410083, China
| | - Guochun Yan
- School of Metallurgy and Environment, Central South University, Changsha, 410083, China
- Engineering Research Center of the Ministry of Education for Advanced Battery Materials, Central South University, Changsha, 410083, China
- Key Laboratory of Value-added Metallurgy of Hunan Province, Central South University, Changsha, 410083, China
| | - Jiexi Wang
- School of Metallurgy and Environment, Central South University, Changsha, 410083, China
- Engineering Research Center of the Ministry of Education for Advanced Battery Materials, Central South University, Changsha, 410083, China
- Key Laboratory of Value-added Metallurgy of Hunan Province, Central South University, Changsha, 410083, China
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Guo Z, Chen W, Wang H, Cai W, Qaid SMH, Zang Z. Additive Conformational Engineering To Improve the PbI 2 Framework for Efficient and Stable Perovskite Solar Cells. Inorg Chem 2023; 62:14086-14093. [PMID: 37635648 DOI: 10.1021/acs.inorgchem.3c02338] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/29/2023]
Abstract
The PbI2 framework is critical for two-step fabricated perovskite solar cells. This study investigates the effects of introducing two functional urea-based molecules, biuret (BU) and dithiobiuret (DTBU), into the PbI2 precursor solution on the absorber layer and overall device performance. BU, which contains C═O, enhanced device performance and stability, whereas DTBU, which contains C═S, had negative effects. Research analysis revealed the differences in the spatial structures of the two urea-based molecules. The introduction of symmetrical BU molecules facilitated the crystallization of PbI2, whereas the introduction of DTBU with a twisted molecular structure led to inferior crystallization performance of PbI2. The perovskite thin film, obtained by introducing BU into the PbI2 precursor solution, demonstrated superior performance, characterized by a decreased defect density and an extended carrier lifetime. The device performance and stability were enhanced, resulting in higher open-circuit voltage and fill factor. The highest achieved power conversion efficiency was 23.50%. After 1300 h of storage under unpackaged conditions at 30-40% humidity, the devices maintained 93% of their initial efficiency. Conversely, the devices prepared with DTBU doping exhibited inferior performance and stability, displaying power conversion efficiency below 10% and faster degradation under the same humidity conditions.
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Affiliation(s)
- Zhihao Guo
- Key Laboratory of Optoelectronic Technology & Systems (Ministry of Education), Chongqing University, Chongqing 400044, China
| | - Weixian Chen
- Key Laboratory of Optoelectronic Technology & Systems (Ministry of Education), Chongqing University, Chongqing 400044, China
| | - Huaxin Wang
- Key Laboratory of Optoelectronic Technology & Systems (Ministry of Education), Chongqing University, Chongqing 400044, China
| | - Wensi Cai
- Key Laboratory of Optoelectronic Technology & Systems (Ministry of Education), Chongqing University, Chongqing 400044, China
| | - Saif M H Qaid
- Department of Physics & Astronomy, College of Sciences, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia
| | - Zhigang Zang
- Key Laboratory of Optoelectronic Technology & Systems (Ministry of Education), Chongqing University, Chongqing 400044, China
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Guo Z, Mo J, Zhang J, Hu W, Zhang C, Wang X, Zhao B, Zhang K. Altered Metabolic Networks in Mesial Temporal Lobe Epilepsy with Focal to Bilateral Seizures. Brain Sci 2023; 13:1239. [PMID: 37759840 PMCID: PMC10526398 DOI: 10.3390/brainsci13091239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 08/23/2023] [Accepted: 08/24/2023] [Indexed: 09/29/2023] Open
Abstract
This study was designed to identify whether the metabolic network changes in mesial temporal lobe epilepsy (MTLE) patients with focal to bilateral tonic-clonic seizures (FBTCS) differ from changes in patients without FBTCS. This retrospective analysis enrolled 30 healthy controls and 54 total MTLE patients, of whom 27 had FBTCS. Fluorodeoxyglucose positron emission tomography (FDG-PET) data and graph theoretical analyses were used to examine metabolic connectivity. The differences in metabolic networks between the three groups were compared. Significant changes in both local and global network topology were evident in FBTCS+ patients as compared to healthy controls, with a lower assortative coefficient and altered betweenness centrality in 15 brain regions. While global network measures did not differ significantly when comparing FBTCS- patients to healthy controls, alterations in betweenness centrality were evident in 13 brain regions. Significantly altered betweenness centrality was also observed in four brain regions when comparing patients with and without FBTCS. The study revealed greater metabolic network abnormalities in MTLE patients with FBTCS as compared to FBTCS- patients, indicating the existence of distinct epileptogenic networks. These findings can provide insight into the pathophysiological basis of FBTCS.
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Affiliation(s)
- Zhihao Guo
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China; (Z.G.); (J.M.); (J.Z.); (W.H.); (C.Z.); (X.W.); (B.Z.)
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
| | - Jiajie Mo
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China; (Z.G.); (J.M.); (J.Z.); (W.H.); (C.Z.); (X.W.); (B.Z.)
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
| | - Jianguo Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China; (Z.G.); (J.M.); (J.Z.); (W.H.); (C.Z.); (X.W.); (B.Z.)
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
| | - Wenhan Hu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China; (Z.G.); (J.M.); (J.Z.); (W.H.); (C.Z.); (X.W.); (B.Z.)
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
| | - Chao Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China; (Z.G.); (J.M.); (J.Z.); (W.H.); (C.Z.); (X.W.); (B.Z.)
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
| | - Xiu Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China; (Z.G.); (J.M.); (J.Z.); (W.H.); (C.Z.); (X.W.); (B.Z.)
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
| | - Baotian Zhao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China; (Z.G.); (J.M.); (J.Z.); (W.H.); (C.Z.); (X.W.); (B.Z.)
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
| | - Kai Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China; (Z.G.); (J.M.); (J.Z.); (W.H.); (C.Z.); (X.W.); (B.Z.)
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
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21
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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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22
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Guo Z, Zhang J, Hu W, Wang X, Zhao B, Zhang K, Zhang C. Does seizure propagate within or across intrinsic brain networks? An intracranial EEG study. Neurobiol Dis 2023; 184:106220. [PMID: 37406713 DOI: 10.1016/j.nbd.2023.106220] [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: 04/28/2023] [Revised: 06/27/2023] [Accepted: 07/01/2023] [Indexed: 07/07/2023] Open
Abstract
BACKGROUND Understanding the spatiotemporal propagation profiles of seizures is crucial for the preoperative assessment of epilepsy patients. The present study aimed to investigate whether seizures exhibit propagation patterns that align with intrinsic networks (INs). METHODS A quantitative analysis was conducted to examine ictal fast activity (IFA). The Epileptogenicity Index (EI) was employed to assess the epileptogenicity, spectral features, and temporal characteristics of IFA. Intra-network and inter-network comparisons were made regarding the IFA-related metrics. Additionally, the metrics were correlated with Euclidean distance. Network connection maps were generated to visualize seizures originating from different INs, allowing for comparisons between distinct groups. RESULTS Data for 81 seizures in 43 subjects were captured using stereoelectroencephalography implantation. Three metrics were compared: EI, time involvement (TI), and energy ratio index (ERI). Intra-network channels exhibited higher EI, earlier involvement of IFA, and stronger high-frequency energy. These findings were further validated through subgroup analyses stratified by neuropathology, seizure type, and seizure origination lobe. Correlation analyses revealed a negative association between distance and both EI and ERI, while distance exhibited a positive correlation with TI. Seizures originating from different INs exhibited varying propagation characteristics. CONCLUSIONS The study findings highlight the dominant role of intra-network dynamics over inter-network during seizure propagation. These results contribute to our understanding of seizure dynamics and their relationship with INs.
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Affiliation(s)
- Zhihao Guo
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Jianguo Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Wenhan Hu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Xiu Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Baotian Zhao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Kai Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
| | - Chao Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, 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 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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Zhou H, Li T, Liu W, Guo Z, Su Z, Gao J, Qu M, Peng G. A Bifunctional Fluorine-Free Electrolyte Additive for Realizing Dendrite-Free Lithium Anodes. ChemSusChem 2023; 16:e202300186. [PMID: 36780130 DOI: 10.1002/cssc.202300186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 02/12/2023] [Accepted: 02/13/2023] [Indexed: 05/20/2023]
Abstract
Owing to the strong energy advantage of lithium anodes, the development of lithium-metal batteries has become an inevitable trend. However, plagued by the instability of solid-electrolyte interphase (SEI) films, lithium metal anodes face challenges such as lithium dendrite formation and volume expansion. Studies have proven that modulating the composition and structure of SEI films by using electrolyte additives is a convenient and valid method. Currently, it is widely accepted that fluoride is an effective additive but, based on the high cost of fluoride production and environmental concerns, the development of fluoride-free additives is of great significance. In this work, the bifunctional additive N,O-bis(trimethylsilyl)acetamide (BSA) is proposed, which can build up a SEI layer that is rich in SiOx and Li3 N on the surface of the lithium anode to control the deposition behavior of lithium and clean the electrolyte of HF to protect the electrode. The experimental results indicate that BSA suppresses the generation of lithium dendrites and controls the volume expansion of lithium anodes. Moreover, compared with the commonly used carbonate electrolytes, the battery containing BSA has the best overall performance. Methodologically, the results can be extended to other additives containing Si-O functional groups to replace the same type of fluorine-containing additives.
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Affiliation(s)
- Hanxiao Zhou
- Chengdu Institute of Organic Chemistry, Chinese Academy of Sciences Chengdu, Sichuan, 610041, P. R. China
- University of Chinese Academy of Sciences, Beijing, 100049, P. R. China
| | - Tianhui Li
- Chengdu Institute of Organic Chemistry, Chinese Academy of Sciences Chengdu, Sichuan, 610041, P. R. China
- University of Chinese Academy of Sciences, Beijing, 100049, P. R. China
| | - Wenjing Liu
- Chengdu Institute of Organic Chemistry, Chinese Academy of Sciences Chengdu, Sichuan, 610041, P. R. China
- University of Chinese Academy of Sciences, Beijing, 100049, P. R. China
| | - Zhihao Guo
- Chengdu Institute of Organic Chemistry, Chinese Academy of Sciences Chengdu, Sichuan, 610041, P. R. China
- University of Chinese Academy of Sciences, Beijing, 100049, P. R. China
| | - Zihao Su
- Chengdu Institute of Organic Chemistry, Chinese Academy of Sciences Chengdu, Sichuan, 610041, P. R. China
- University of Chinese Academy of Sciences, Beijing, 100049, P. R. China
| | - Jingjing Gao
- Chengdu Institute of Organic Chemistry, Chinese Academy of Sciences Chengdu, Sichuan, 610041, P. R. China
- University of Chinese Academy of Sciences, Beijing, 100049, P. R. China
| | - Meizhen Qu
- Chengdu Institute of Organic Chemistry, Chinese Academy of Sciences Chengdu, Sichuan, 610041, P. R. China
- University of Chinese Academy of Sciences, Beijing, 100049, P. R. China
| | - Gongchang Peng
- Chengdu Institute of Organic Chemistry, Chinese Academy of Sciences Chengdu, Sichuan, 610041, P. R. China
- University of Chinese Academy of Sciences, Beijing, 100049, P. R. China
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Ng BWL, Xu T, Guo Z. Discovery of chemical probes that perturb protein complexes using size exclusion chromatography and chemical proteomics. Mol Cell 2023; 83:1544-1546. [PMID: 37207621 DOI: 10.1016/j.molcel.2023.04.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 04/28/2023] [Accepted: 04/28/2023] [Indexed: 05/21/2023]
Abstract
Most human proteins lack small-molecule ligands, rendering these proteins "undruggable." In this issue of Molecular Cell, Lazear et al.1 develop a novel chemical proteomic screening platform and discover new chemical probes targeting previously undruggable protein complexes.
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Affiliation(s)
- Billy Wai-Lung Ng
- School of Pharmacy, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong; Li Ka Shing Institute of Health Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong.
| | - Tongyang Xu
- School of Pharmacy, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong
| | - Zhihao Guo
- School of Pharmacy, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong
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Yang B, Wang X, Mo J, Li Z, Hu W, Zhang C, Zhao B, Gao D, Zhang X, Zou L, Zhao X, Guo Z, Zhang J, Zhang K. The altered spontaneous neural activity in patients with Parkinson's disease and its predictive value for the motor improvement of deep brain stimulation. Neuroimage Clin 2023; 38:103430. [PMID: 37182459 PMCID: PMC10197096 DOI: 10.1016/j.nicl.2023.103430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Revised: 05/04/2023] [Accepted: 05/05/2023] [Indexed: 05/16/2023]
Abstract
BACKGROUND This study aims to investigate the altered spontaneous neural activity in patients with Parkinson's disease (PD) revealed by amplitudes of low-frequency fluctuations (ALFF) of resting-state fMRI, and the feasibility of using ALFF as neuroimaging predictors for motor improvement after bilateral subthalamic nucleus (STN) deep brain stimulation (DBS). METHODS Fourty-four patients and 44 healthy controls were included in this study. First, the ALFF of patients with PD was compared with that of controls; then significant clusters were correlated with motor improvement after DBS (unified Parkinson's disease rating scale (UPDRS-III)) and other clinical variables. Second, regression and classification of the machine learning models were conducted to predict motor improvement after DBS. Receiver operating characteristic (ROC) analysis was used to evaluate the performance of the classification model. RESULTS Compared with healthy controls, patients with PD showed increased ALFF in the bilateral motor area and decreased ALFF in the bilateral temporal cortex and cerebellum. The Hoehn-Yahr stages correlated with ALFF within the bilateral cerebellum (p = 0.021), and UPDRS-III improvement correlated with ALFF in the left (p < 0.001) and right (p = 0.005) motor areas. The regression model showed a significant correlation between the predicted and observed UPDRS-III changes (R = 0.65, p < 0.001). The ROC analysis revealed an area under the curve (AUC) of 0.94 which differentiated moderate and superior DBS responders. CONCLUSION The results revealed altered ALFF patterns in patients with PD and their correlations with clinical variables. Both binary and continuous ALFF can potentially serve as predictive biomarkers for DBS response.
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Affiliation(s)
- Bowen Yang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xiu Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jiajie Mo
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zilin Li
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Wenhan Hu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Stereotactic and Functional Neurosurgery Laboratory, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Chao Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Stereotactic and Functional Neurosurgery Laboratory, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Baotian Zhao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Dongmei Gao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xin Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Stereotactic and Functional Neurosurgery Laboratory, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Liangying Zou
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Stereotactic and Functional Neurosurgery Laboratory, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Xuemin Zhao
- Department of Neurophysiology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Zhihao Guo
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jianguo Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Stereotactic and Functional Neurosurgery Laboratory, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
| | - Kai Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Stereotactic and Functional Neurosurgery Laboratory, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
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Yu J, Guo Z, Yan J, Bu C, Peng C, Li C, Mao R, Zhang J, Wang Z, Chen S, Yao M, Xie Z, Yang C, Yang YY, Yuan P, Ding X. Gastric Acid-Responsive ROS Nanogenerators for Effective Treatment of Helicobacter pylori Infection without Disrupting Homeostasis of Intestinal Flora. Adv Sci (Weinh) 2023:e2206957. [PMID: 37127895 PMCID: PMC10369278 DOI: 10.1002/advs.202206957] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/24/2022] [Revised: 04/15/2023] [Indexed: 05/03/2023]
Abstract
Helicobacter pylori (H. pylori) has infected more than half of the world's population, and is the major cause of gastric cancer. The efficacy of standard antibiotic-based triple therapy is declining due to drug resistance development. Herein, a pH-responsive reactive oxygen species (ROS) nanogenerator (Fe-HMME@DHA@MPN) composed of acid-responsive metal polyphenol network (MPN) shell and mesoporous metal-organic nanostructure core [Fe-HMME (hematoporphyrin monomethyl ether, sonosensitizer)] loaded with dihydroartemisinin (DHA) is reported. These nanoparticles generate more ROS singlet oxygen than sonosensitizer HMME under ultrasonication, and this sonodynamic process is fueled by oxygen generated through Fenton/Fenton-like reactions of the degraded product in gastric acid Fe (II) and hydrogen peroxide (H2 O2 ) in the infection microenvironment. The encapsulated DHA, as a hydroperoxide source, is found to enhance the peroxidase-like activity of the Fe-HMME@DHA@MPN to generate ROS hydroxyl radical, beneficial for the microenvironment without sufficient H2 O2 . In vitro experiments demonstrate that the ROS nanogenerators are capable of killing multidrug-resistant H. pylori and removing biofilm, and ROS nanogenerators show high therapeutic efficacy in a H. pylori infection mouse model. Unlike the triple therapy, the nanogenerators display negligible side effects toward the normal gut microbiota. Taken together, these self-enhanced ROS nanogenerators have a great potential for treatment of H. pylori infection.
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Affiliation(s)
- Jiayin Yu
- School of Pharmaceutical Science (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, P. R. China
| | - Zhihao Guo
- School of Pharmaceutical Science (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, P. R. China
| | - Jiachang Yan
- School of Pharmaceutical Science (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, P. R. China
| | - Changxin Bu
- School of Pharmaceutical Science (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, P. R. China
| | - Chang Peng
- School of Pharmaceutical Science (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, P. R. China
| | - Cuie Li
- Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Science, 190 Kaiyuan Avenue, Guangzhou Science Park, Luogang District, Guangzhou, 510080, P. R. China
| | - Rui Mao
- Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Science, 190 Kaiyuan Avenue, Guangzhou Science Park, Luogang District, Guangzhou, 510080, P. R. China
| | - Jian Zhang
- Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Science, 190 Kaiyuan Avenue, Guangzhou Science Park, Luogang District, Guangzhou, 510080, P. R. China
| | - Zhi Wang
- Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Science, 190 Kaiyuan Avenue, Guangzhou Science Park, Luogang District, Guangzhou, 510080, P. R. China
| | - Shi Chen
- The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510655, P. R. China
| | - Meicun Yao
- School of Pharmaceutical Science (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, P. R. China
| | - Zhiyong Xie
- School of Pharmaceutical Science (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, P. R. China
| | - Chuan Yang
- Bioprocessing Technology Institute (BTI), Agency for Science, Technology and Research (A*STAR), 20 Biopolis Way, Centros #06-01, Singapore, 138668, Singapore
| | - Yi Yan Yang
- Bioprocessing Technology Institute (BTI), Agency for Science, Technology and Research (A*STAR), 20 Biopolis Way, Centros #06-01, Singapore, 138668, Singapore
- Department of Orthopaedic Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119288, Singapore
| | - Peiyan Yuan
- School of Pharmaceutical Science (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, P. R. China
| | - Xin Ding
- School of Pharmaceutical Science (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, P. R. China
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28
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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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29
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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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30
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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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Li Z, Guo Z, Lu X, Ma X, Wang X, Zhang R, Hu X, Wang Y, Pang J, Fan T, Liu Y, Tang S, Fu H, Zhang J, Li Y, You X, Song D. Evolution and development of potent monobactam sulfonate candidate IMBZ18g as a dual inhibitor against MDR Gram-negative bacteria producing ESBLs. Acta Pharm Sin B 2023. [PMID: 37521870 PMCID: PMC10372838 DOI: 10.1016/j.apsb.2023.03.002] [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] [Indexed: 03/09/2023] Open
Abstract
A series of new monobactam sulfonates is continuously synthesized and evaluated for their antimicrobial efficacies against Gram-negative bacteria. Compound 33a (IMBZ18G) is highly effective in vitro and in vivo against clinically intractable multi-drug-resistant (MDR) Gram-negative strains, with a highly druglike nature. The checkerboard assay reveals its significant synergistic effect with β-lactamase inhibitor avibactam, and the MIC values against MDR enterobacteria were reduced up to 4-512 folds. X-ray co-crystal and chemoproteomic assays indicate that the anti-MDR bacteria effect of 33a results from the dual inhibition of the common PBP3 and some class A and C β-lactamases. Accordingly, preclinical studies of 33a alone and 33a‒avibactam combination as potential innovative candidates are actively going on, in the treatment of β-lactamase-producing MDR Gram-negative bacterial infections.
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Nie S, Guo Z, Tian M, Sun W. Selective flotation separation of cassiterite and calcite through using cinnamohydroxamic acid as the collector and Pb2+ as the activator. Colloids Surf A Physicochem Eng Asp 2023. [DOI: 10.1016/j.colsurfa.2023.131262] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/12/2023]
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Zhang Q, Guo Z, Ma Z, Wang S, Peng B. Fabricating SU-8 Photoresist Microstructures with Controlled Convexity-Concavity and Curvature through Thermally Manipulating Capillary Action in Poly(dimethylsiloxane) Microholes. Langmuir 2023; 39:763-770. [PMID: 36598372 DOI: 10.1021/acs.langmuir.2c02614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
We present a simple, robust, and cheap microfabrication method, based on thermally manipulating capillary action in poly(dimethylsiloxane) (PDMS) microholes, for preparing SU-8 curved microstructures. The microstructure morphology including convexity-concavity and curvature can be controlled via tuning the formation temperature. The convex SU-8 microspherical crowns with a height of 40 μm were formed at 10 °C, whereas the concave SU-8 microspherical crowns with a height of 90 μm were formed at 100 °C. The morphology of the microstructures is dictated by the thermally controlled combination of the pressure difference across the interface, contact angle, and surface tension. The fabricated microstructures with a spherical surface can be used as a microlens array or a mold for producing a microlens array. The clear and uniform images were observed using the generated microlens arrays. The equilibrium morphology of the microstructures can be predicted by numerical simulation, which can lessen the number of experiments and thus the design cost. The proposed method has the potential to find applications in industrial fields.
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Affiliation(s)
- Qiushu Zhang
- School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan611731, China
| | - Zhihao Guo
- School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan611731, China
| | - Zhinan Ma
- School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan611731, China
| | - Song Wang
- School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan611731, China
| | - Bei Peng
- School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan611731, China
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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, Wang H. INFLUENCE OF CORE TRAINING ON THE ABILITY OF CONTROL AND BALANCE IN SURFERS. REV BRAS MED ESPORTE 2022. [DOI: 10.1590/1517-8692202228062022_0042] [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: 11/21/2022] Open
Abstract
ABSTRACT Introduction Surfing depends mainly on the driving force resulting from wave oscillations. Athletes need to paddle in the wave zone and complete the competition actions in the most robust section on the wave walls. This requires extreme balance skills, which can be strengthened with specific training. Among them, it is believed that core training could be beneficial. Objective To study the influence of training on a stable and unstable platform on the regulation of the surfer’s orthostatic posture under balance disturbance. Methods Members of the Hainan National Surf Training Team were volunteers for the experiment; their physical training methods, memory training, and effects evaluation were analyzed. Results 90% of athletes manage to complete the balance control in a short-term autonomous position on the balance board in 1 week; their progress also depends on the training duration, times, and intervals; the progression rule lies according to the literary theory of sports training. Conclusion With the further extension of the balance board training cycle, it is believed that athletes’ ability to control balance and real competition comprehensive capabilities will continue to increase, the overall technical level and stability of their performance will be even greater. Evidence level II; Therapeutic Studies - Investigating the results.
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Guo Z, Mo J, Zhang C, Zhang J, Hu W, Zhang K. Brain-clinical signatures for vagus nerve stimulation response. CNS Neurosci Ther 2022; 29:855-865. [PMID: 36415145 PMCID: PMC9928539 DOI: 10.1111/cns.14021] [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: 07/21/2022] [Revised: 10/18/2022] [Accepted: 10/20/2022] [Indexed: 11/25/2022] Open
Abstract
AIM Vagus nerve stimulation (VNS) is a valuable treatment for drug-resistant epilepsy (DRE) without the indication of surgical resection. The clinical heterogeneity of DRE has limited the optimal indication of choice and diagnosis prediction. The study aimed to explore the correlations of brain-clinical signatures with the clinical phenotype and VNS responsiveness. METHODS A total of 89 DRE patients, including VNS- (n = 44) and drug-treated (n = 45) patients, were retrospectively recruited. The brain-clinical signature consisted of demographic information and brain structural deformations, which were measured using deformation-based morphometry and presented as Jacobian determinant maps. The efficacy and presurgical differences between these two cohorts were compared. Then, the potential of predicting VNS response using brain-clinical signature was investigated according to the different prognosis evaluation approaches. RESULTS The seizure reduction was higher in the VNS-treated group (42.50%) as compared to the drug-treated group (12.09%) (p = 0.11). Abnormal imaging representation, showing encephalomalacia (pcorrected = 0.03), was commonly observed in the VNS-treated group (p = 0.04). In the patients treated with VNS, the mild/subtle brain abnormalities indicated higher seizure frequency (p = 0.03) and worse VNS response (p = 0.04). The partial least square regression analysis showed a moderate prediction potential of brain-clinical signature for VNS response (p < 0.01). The increase in the pre-VNS seizure frequency and structural etiology could indicate a worse prognosis (higher McHugh classification). CONCLUSION The brain-clinical signature illustrated its clinical potential in predicting the VNS response, which might allow clinicians to personalize treatment decisions for DRE patients.
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Affiliation(s)
- Zhihao Guo
- Department of NeurosurgeryBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina,Department of NeurosurgeryBeijing Neurosurgical Institute, Capital Medical UniversityBeijingChina
| | - Jiajie Mo
- Department of NeurosurgeryBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina,Department of NeurosurgeryBeijing Neurosurgical Institute, Capital Medical UniversityBeijingChina
| | - Chao Zhang
- Department of NeurosurgeryBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina,Department of NeurosurgeryBeijing Neurosurgical Institute, Capital Medical UniversityBeijingChina
| | - Jianguo Zhang
- Department of NeurosurgeryBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina,Department of NeurosurgeryBeijing Neurosurgical Institute, Capital Medical UniversityBeijingChina,Beijing Key Laboratory of NeurostimulationBeijingChina
| | - Wenhan Hu
- Department of NeurosurgeryBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina,Department of NeurosurgeryBeijing Neurosurgical Institute, Capital Medical UniversityBeijingChina,Beijing Key Laboratory of NeurostimulationBeijingChina
| | - Kai Zhang
- Department of NeurosurgeryBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina,Department of NeurosurgeryBeijing Neurosurgical Institute, Capital Medical UniversityBeijingChina,Beijing Key Laboratory of NeurostimulationBeijingChina
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Guo Z, Sui J, Li Y, Wei Q, Wei C, Xiu L, Zhu R, Sun Y, Hu J, Li JL. GE11 peptide-decorated acidity-responsive micelles for improved drug delivery and enhanced combination therapy of metastatic breast cancer. J Mater Chem B 2022; 10:9266-9279. [PMID: 36342458 DOI: 10.1039/d2tb01816k] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Nanotechnology-mediated drug delivery systems suffer from insufficient retention in tumor tissues and unreliable drug release at specific target sites. Herein, we developed an epidermal growth factor receptor-targeted multifunctional micellar nanoplatform (GE11-DOX+CEL-M) by encapsulating celecoxib into polymeric micelles based on the conjugate of GE11-poly(ethylene glycol)-b-poly(trimethylene carbonate) with doxorubicin to suppress tumor growth and metastasis. The polymeric micelles maintained stable nanostructures under physiological conditions but quickly disintegrated in a weakly acidic environment, which is conducive to controlled drug release. Importantly, GE11-DOX+CEL-M micelles effectively delivered the drug combination to tumor sites and enhanced tumor cell uptake through GE11-mediated active tumor targeting. Subsequently, GE11-DOX+CEL-M micelles dissociated in response to intracellular slightly acidic microenvironmental stimuli, resulting in rapid release of celecoxib and doxorubicin to synergistically inhibit the proliferation and migration of tumor cells. Systemic administration of GE11-DOX+CEL-M micelles into mice bearing subcutaneous 4T1 tumor models resulted in higher tumor growth suppression and decreased lung metastasis of tumor cells compared with micelles without GE11 decoration or delivering only doxorubicin. Furthermore, the micelles effectively reduced the systemic toxicity of the chemotherapy drugs. This nanotherapeutic system provides a promising strategy for safe and effective cancer therapy.
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Affiliation(s)
- Zhihao Guo
- School of Biomedical Engineering, School of Ophthalmology & Optometry, Eye Hospital, Wenzhou Medical University, 270 Xueyuan Road, Wenzhou, 325027, China. .,National Engineering Research Center for Biomaterials, Sichuan University, 29 Wangjiang Road, Chengdu, 610064, China. .,Center for Molecular Science and Engineering, College of Science, Northeastern University, 3-11 Wenhua Road, Shenyang, 110819, China
| | - Junhui Sui
- National Engineering Research Center for Biomaterials, Sichuan University, 29 Wangjiang Road, Chengdu, 610064, China. .,College of Life Science and Technology, Xinxiang Medical University, 601 Jinsui Road, Xinxiang, 453003, China
| | - Yumei Li
- School of Biomedical Engineering, School of Ophthalmology & Optometry, Eye Hospital, Wenzhou Medical University, 270 Xueyuan Road, Wenzhou, 325027, China.
| | - Qinchuan Wei
- School of Biomedical Engineering, School of Ophthalmology & Optometry, Eye Hospital, Wenzhou Medical University, 270 Xueyuan Road, Wenzhou, 325027, China.
| | - Cailing Wei
- School of Biomedical Engineering, School of Ophthalmology & Optometry, Eye Hospital, Wenzhou Medical University, 270 Xueyuan Road, Wenzhou, 325027, China.
| | - Linyun Xiu
- School of Biomedical Engineering, School of Ophthalmology & Optometry, Eye Hospital, Wenzhou Medical University, 270 Xueyuan Road, Wenzhou, 325027, China.
| | - Ruohua Zhu
- School of Biomedical Engineering, School of Ophthalmology & Optometry, Eye Hospital, Wenzhou Medical University, 270 Xueyuan Road, Wenzhou, 325027, China.
| | - Yong Sun
- National Engineering Research Center for Biomaterials, Sichuan University, 29 Wangjiang Road, Chengdu, 610064, China.
| | - Jianshe Hu
- Center for Molecular Science and Engineering, College of Science, Northeastern University, 3-11 Wenhua Road, Shenyang, 110819, China
| | - Ji-Liang Li
- School of Biomedical Engineering, School of Ophthalmology & Optometry, Eye Hospital, Wenzhou Medical University, 270 Xueyuan Road, Wenzhou, 325027, China. .,Wenzhou Institute, University of Chinese Academy of Sciences, 1 Jinlian Road, Wenzhou, 325000, China.
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Guo Z, Li L, Su Z, Peng G, Qu M, Fu Y, Wang H, Ge W. Enhancing Cyclic Performance of Lithium-rich Manganese-based Cathode via In-situ Co-doping of Magnesium and Fluorine. Electrochim Acta 2022. [DOI: 10.1016/j.electacta.2022.141525] [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: 11/12/2022]
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Abrahams BF, Commons CJ, Hudson TA, Sanchez Arlt R, Ahl R, Carajias ED, Chan JWK, Guo Z, Hill RE, McGinty A, Peters NL, Poon JYP, Qu J, Qu J, Rochette EE, Walkear C, Wang H, Wu H, Xu C, Zhang J. Complexes of 2,4,6-trihydroxybenzoic acid: effects of intramolecular hydrogen bonding on ligand geometry and metal binding modes. Acta Crystallogr C 2022; 78:653-670. [DOI: 10.1107/s2053229622009901] [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] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 10/10/2022] [Indexed: 11/10/2022]
Abstract
This article describes a series of more than 20 new compounds formed by the combination of 2,4,6-trihydroxybenzoic acid (H4thba) with metal ions in the presence of a base, with structures that include discrete molecular units, chains, and two- and three-dimensional networks. As a result of the presence of two ortho-hydroxy groups, H4thba is a relatively strong acid (pK
a1 = 1.68). The carboxylate group in H3thba− is therefore considerably less basic than most carboxylates with intramolecular hydrogen bonds, conferring a rigid planar geometry upon the anion. These characteristics of H3thba− significantly impact upon the way it interacts with metal ions. In s-block metal compounds, where the interaction of the metal centres with the carboxylate O atoms is essentially ionic, the anion bonds to up to three metal centres via a variety of binding modes. In cases where the metal ion is able to form directional coordinate bonds, however, the carboxylate group tends to bond in a monodentate mode, interacting with just one metal centre in the syn mode. A dominant influence on the structures of the complexes seems to be the face-to-face stacking of the aromatic rings, which creates networks containing layers of metal–oxygen polyhedra that participate in hydrogen bonding. This investigation was undertaken, in part, by a group of secondary school students as an educational exercise designed to introduce school students to the technique of single-crystal X-ray diffraction and enhance their understanding of primary and secondary bonding.
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Guo Z, Zhang C, Wang X, Liu C, Zhao B, Mo J, Zheng Z, Shao X, Zhang J, Zhang K, Hu W. Is intracranial electroencephalography mandatory for MRI-negative neocortical epilepsy surgery? J Neurosurg 2022:1-11. [PMID: 36242573 DOI: 10.3171/2022.8.jns22995] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [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: 05/02/2022] [Accepted: 08/18/2022] [Indexed: 11/06/2022]
Abstract
OBJECTIVE MRI-negative focal epilepsy is one of the most challenging cases in surgical epilepsy treatment. Many epilepsy centers recommend intracranial electroencephalography (EEG) for MRI-negative cases, especially neocortical epilepsy. This retrospective study aimed to explore whether intracranial monitoring is mandatory in MRI-negative neocortical epilepsy surgery and the factors that significantly influence the decision on whether to perform intracranial recording. METHODS In this study, consecutive surgical patients with focal MRI-negative neocortical epilepsy were recruited. All patients underwent routine preoperative evaluation according to the dedicated protocol of the authors' epilepsy center to determine the treatment strategy. Patients were divided into two groups according to the surgical strategy, i.e., a direct group and a stereo-EEG (SEEG)-guided group. History of epilepsy, seizure frequency, interictal and ictal EEG data, PET data, PET/MRI coregistration data, neuropathological findings, and surgical outcomes were compared between the two groups. Multivariate analysis was performed to identify factors influencing the decision to perform SEEG monitoring. RESULTS Sixty-four patients were included in this study, 19 and 45 of whom underwent direct and SEEG-guided cortical resection, respectively. At an average follow-up of 3.9 years postoperatively, 56 patients (87.5%) had Engel class I results without permanent neurological deficits. Surgical outcomes were not significantly different between the direct and SEEG-guided groups (94.7% vs 84.4%). PET hypometabolic abnormalities were detected in all patients. There were significant differences between the two groups in the extent of hypometabolism (focal vs nonfocal, p < 0.01) and pathological subtype (focal cortical dysplasia type II vs others, p = 0.03). Multivariate analysis revealed that the extent of hypometabolism (OR 0.01, 95% CI 0.00-0.15; p = 0.001) was the only independent factor affecting the treatment strategy. CONCLUSIONS Careful selection of patients with MRI-negative neocortical epilepsy may yield favorable outcomes after direct cortical resection without intracranial monitoring. PET/MRI coregistration plays an essential role in the preoperative evaluation and subsequent resection of these patients. Intracranial monitoring is not a mandatory requirement for surgery if the focal hypometabolic areas are consistent with the findings of semiology and scalp EEG.
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Affiliation(s)
| | | | - Xiu Wang
- 1Departments of Neurosurgery and
| | | | | | | | - Zhong Zheng
- 4Department of Neurosurgery, Beijing Fengtai Hospital, Beijing, China
| | - Xiaoqiu Shao
- 5Neurology, Beijing Tiantan Hospital, Capital Medical University
| | - Jianguo Zhang
- 1Departments of Neurosurgery and
- 3Beijing Key Laboratory of Neurostimulation; and
| | - Kai Zhang
- 1Departments of Neurosurgery and
- 3Beijing Key Laboratory of Neurostimulation; and
| | - Wenhan Hu
- 1Departments of Neurosurgery and
- 3Beijing Key Laboratory of Neurostimulation; and
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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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Liu C, Hu W, Zhang C, Zheng Z, Yang X, Wang X, Mo J, Guo Z, Shao X, Zhang K. Anatomical features decide the atypical seizure manifestation of parahypothalamic hamartomas. Front Neurol 2022; 13:981488. [PMID: 36172032 PMCID: PMC9510781 DOI: 10.3389/fneur.2022.981488] [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: 06/29/2022] [Accepted: 08/17/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundThe intrahypothalamic phenotype of hypothalamic hamartomas (HH) is associated with epilepsy, and the parahypothalamic phenotype usually leads to central precocious puberty but not neurological comorbidities or seizures. No study has confirmed the pathological role of parahypothalamic hamartomas in epileptogenesis, and the underlying mechanism is yet to be elucidated.ObjectiveWe aimed to investigate whether parahypothalamic hamartomas are intrinsically epileptogenic and elucidate the underlying pathway of epileptogenesis.MethodsWe reviewed 92 patients with HH-related epilepsy, categorized them by the classification system of Delalande and Fohlen, and further classified Type I (corresponding to parahypothalamic HH) into the following three groups based on the relationship between the lesion and mammillary bodies (MB): entirely invaded (Group 1), partially connected (Group 2), and not connected at all (Group 3). We examined different anatomical features with their relationship to clinical manifestations. Stereoelectroencephalography (SEEG) was implanted in both HH and extra-HH cortices in different groups to identify the epileptogenic zone. Corticocortical evoked potentials (CCEPs) were also used to determine the pathological correlation among different regions to determine the related epileptogenic network.ResultsA total of 13 patients presented with parahypothalamic HH and 10 (76.9%) presented with non-GS only, with late-onset age and normal cognitive development, which is different from classical clinical features. SEEG showed that HH is intrinsically epileptogenic in MB-involved parahypothalamic groups. No statistical difference was found in onset age (p = 0.213), and lesions horizontally oriented from the tuber cinereum without connection to MB were not involved in seizure genesis. CCEP indicated a pathological connection among HH, middle cingulate cortex, and insular cortex.ConclusionThe parahypothalamic HH can also cause epilepsy and is different from classic HH-related seizures, by non-GS only with the late-onset age and normal cognitive development. MB is proven to be related to non-GS by the mamillo-cingulate-cortex pathway.
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Affiliation(s)
- Chang Liu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Wenhan Hu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Stereotactic and Functional Neurosurgery Laboratory, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Chao Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zhong Zheng
- Epilepsy Center, Beijing Fengtai Hospital, Beijing, China
| | - Xiaoli Yang
- Epilepsy Center, Beijing Fengtai Hospital, Beijing, China
| | - Xiu Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jiajie Mo
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zhihao Guo
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xiaoqiu Shao
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Kai Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Stereotactic and Functional Neurosurgery Laboratory, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
- *Correspondence: Kai Zhang
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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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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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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, Tian M, Qian G, Zhou Y, Gao Z, Sun W. Flotation separation of bastnaesite and fluorite using styrylphosphonic acid and cinnamohydroxamic acid as collectors. J Mol Liq 2022. [DOI: 10.1016/j.molliq.2022.119766] [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: 11/27/2022]
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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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