1.A disentangled generative model for improved drug response prediction in patients via sample synthesis
Kunshi LI ; Bihan SHEN ; Fangyoumin FENG ; Xueliang LI ; Yue WANG ; Na FENG ; Zhixuan TANG ; Liangxiao MA ; Hong LI
Journal of Pharmaceutical Analysis 2025;15(6):1226-1237
Personalized drug response prediction from molecular data is an important challenge in precision medicine for treating cancer.Computational methods have been widely explored and have become increasingly accurate in recent years.However,the clinical application of prediction methods is still in its infancy due to large discrepancies between preclinial models and patients.We present a novel disentangled synthesis transfer network(DiSyn)for drug response prediction specifically designed for transfer learning from preclinical models to clinical patients.DiSyn uses a domain separation network(DSN)to disentangle drug response related features,employs data synthesis technology to increase the sample size and iteratively trains for better feature disentanglement.DiSyn is pretrained on large-scale unlabeled cancer samples and validated by three datasets,The Cancer Genome Atlas(TCGA),Investigation of Serial Studies to Predict Your Therapeutic Response With Imaging And moLecular Analysis 2(I-SPY2)and Novartis Institutes for Biomedical Research Patient-Derived Xenograft Encyclopedia(NIBR PDXE),achieving competitive performance with the state-of-the-art methods on cancer patients and mice.Furthermore,the application of DiSyn to thousands of breast cancer patients show the heterogeneity in drug responses and demonstrate its potential value in biomarker discovery and drug combination prediction.
2.Design and implementation of night vision simulation training system
Chao ZHAO ; Liang-yu ZHAO ; Jia-li WANG ; Yan WANG ; Hong-yue YANG ; Jian-fei CUI
Chinese Medical Equipment Journal 2025;46(3):21-26
Objective To design a night vision simulation training system to provide pilots with practical training on ground night vision goggles.Methods The system had its hardware composed of a control stick,a throttle lever,rudder pedals,a head-up display(HUD),a control box,a computer,a projector and a screen.The HUD and control box were designed using night vision-compatible lighting technology to simulate the ambient light conditions pilots experienced when flying with night vision goggles.The software of the system consisted of five ones developed with C++programming languge for visual scene simulation,instrument simulation,flight performance simulation,integrated management control and cockpit manage-ment.Night vision images and computer-rendered images of typical scenes with varying brightness levels were collected.Objective image evaluation metrics such as contrast and brightness were used as inputs,while subjective evaluation data served as outputs to construct and train a support vector machine(SVM)model.Totally 30 typical night vision training scenarios were selected based on model validation and optimization to evaluate the system's optical fidelity.Results The average fidelity score for the 30 typical night vision training scenarios was 8.05,indicating that the system could realistically simulate terrain and landscapes under various lighting and weather conditions during night flights and static and dynamic targets in the air,on the ground and at sea.Conclusion The system meets the desired requirements and effectively facilitates night vision training for pilots.[Chinese Medical Equipment Journal,2025,46(3):21-26]
3.Changing resistance profiles of Haemophilus influenzae and Moraxella catarrhalis isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Hui FAN ; Chunhong SHAO ; Jia WANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Yunsheng CHEN ; Qing MENG ; Hong ZHANG ; Chun WANG ; Fang DONG ; Wenqi SONG ; Kaizhen WEN ; Yirong ZHANG ; Chuanqing WANG ; Pan FU ; Chao ZHUO ; Danhong SU ; Jiangwei KE ; Shuping ZHOU ; Hua ZHANG ; Fangfang HU ; Mei KANG ; Chao HE ; Hua YU ; Xiangning HUANG ; Yingchun XU ; Xiaojiang ZHANG ; Wenen LIU ; Yanming LI ; Lei ZHU ; Jinhua MENG ; Shifu WANG ; Bin SHAN ; Yan DU ; Wei JIA ; Gang LI ; Jiao FENG ; Ping GONG ; Miao SONG ; Lianhua WEI ; Xin WANG ; Ruizhong WANG ; Hua FANG ; Sufang GUO ; Yanyan WANG ; Dawen GUO ; Jinying ZHAO ; Lixia ZHANG ; Juan MA ; Han SHEN ; Wanqing ZHOU ; Ruyi GUO ; Yan ZHU ; Jinsong WU ; Yuemei LU ; Yuxing NI ; Jingrong SUN ; Xiaobo MA ; Yanqing ZHENG ; Yunsong YU ; Jie LIN ; Ziyong SUN ; Zhongju CHEN ; Zhidong HU ; Jin LI ; Fengbo ZHANG ; Ping JI ; Yunjian HU ; Xiaoman AI ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Xuesong XU ; Chao YAN ; Yi LI ; Shanmei WANG ; Hongqin GU ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Jihong LI ; Bixia YU ; Cunshan KOU ; Jilu SHEN ; Wenhui HUANG ; Xiuli YANG ; Likang ZHU ; Lin JIANG ; Wen HE ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(1):30-38
Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91%of the total clinical isolates and 4.07%of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89%were isolated from children and 33.11%were isolated from adults.More than 90%of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79%in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06%were isolated from children and 19.94%isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0%.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.
4.Changing distribution and antimicrobial resistance profiles of clinical isolates in children:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Qing MENG ; Lintao ZHOU ; Yunsheng CHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Chuanqing WANG ; Aimin WANG ; Lei ZHU ; Jinhua MENG ; Hong ZHANG ; Chun WANG ; Fang DONG ; Zhiyong LÜ ; Shuping ZHOU ; Yan ZHOU ; Shifu WANG ; Fangfang HU ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Wei JIA ; Gang LI ; Kaizhen WEN ; Yirong ZHANG ; Yan JIN ; Chunhong SHAO ; Yong ZHAO ; Ping GONG ; Chao ZHUO ; Danhong SU ; Bin SHAN ; Yan DU ; Sufang GUO ; Jiao FENG ; Ziyong SUN ; Zhongju CHEN ; Wen'en LIU ; Yanming LI ; Xiaobo MA ; Yanping ZHENG ; Dawen GUO ; Jinying ZHAO ; Ruizhong WANG ; Hua FANG ; Lixia ZHANG ; Juan MA ; Jihong LI ; Zhidong HU ; Jin LI ; Yuxing NI ; Jingyong SUN ; Ruyi GUO ; Yan ZHU ; Yi XIE ; Mei KANG ; Yuanhong XU ; Ying HUANG ; Shanmei WANG ; Yafei CHU ; Hua YU ; Xiangning HUANG ; Lianhua WEI ; Fengmei ZOU ; Han SHEN ; Wanqing ZHOU ; Yunzhuo CHU ; Sufei TIAN ; Shunhong XUE ; Hongqin GU ; Xuesong XU ; Chao YAN ; Bixia YU ; Jinju DUAN ; Jianbang KANG ; Jiangshan LIU ; Xuefei HU ; Yunsong YU ; Jie LIN ; Yunjian HU ; Xiaoman AI ; Chunlei YUE ; Jinsong WU ; Yuemei LU
Chinese Journal of Infection and Chemotherapy 2025;25(1):48-58
Objective To understand the changing composition and antibiotic resistance of bacterial species in the clinical isolates from outpatient and emergency department(hereinafter referred to as outpatients)and inpatient children over time in various hospitals,and to provide laboratory evidence for rational antibiotic use.Methods The data on clinically isolated pathogenic bacteria and antimicrobial susceptibility of isolates from outpatients and inpatient children in the CHINET program from 2015 to 2021 were collected and analyzed.Results A total of 278 471 isolates were isolated from pediatric patients in the CHINET program from 2015 to 2021.About 17.1%of the strains were isolated from outpatients,primarily group A β-hemolytic Streptococcus,Escherichia coli,and Staphylococcus aureus.Most of the strains(82.9%)were isolated from inpatients,mainly SS.aureus,E.coli,and H.influenzae.The prevalence of methicillin-resistant S.aureus(MRSA)in outpatients(24.5%)was lower than that in inpatient children(31.5%).The MRSA isolates from outpatients showed lower resistance rates to the antibiotics tested than the strains isolated from inpatient children.The prevalence of vancomycin-resistant Enterococcus faecalis or E.faecium and penicillin-resistant S.pneumoniae was low in either outpatients or inpatient children.S.pneumoniae,β-hemolytic Streptococcus and S.viridans showed high resistance rates to erythromycin.The prevalence of erythromycin-resistant group A β-hemolytic Streptococcus was higher in outpatients than that in inpatient children.The prevalence of β-lactamase-producing H.influenzae showed an overall upward trend in children,but lower in outpatients(45.1%)than in inpatient children(59.4%).The prevalence of carbapenem-resistant Klebsiella pneumoniae(CRKpn),carbapenem-resistant Pseudomonas aeruginosa(CRPae)and carbapenem-resistant Acinetobacter baumannii(CRAba)was 14%,11.7%,47.8%in outpatients,but 24.2%,20.6%,and 52.8%in inpatient children,respectively.The prevalence of multidrug-resistant E.coli,K.pneumoniae,Proteus mirabilis,P.aeruginosa and A.baumannii strains was lower in outpatients than in inpatient children.The prevalence of fluoroquinolone-resistant E.coli,ESBLs-producing K.pneumoniae,ESBLs-producing P.mirabilis,carbapenem-resistant E.coli(CREco),CRKpn,and CRPae was lower in children in outpatients than in inpatient children,but the prevalence of CRAba in 2021 was higher than in inpatient children.Conclusions The distribution of clinical isolates from children is different between outpatients and inpatients.The prevalence of MRSA,ESBL,and CRO was higher in inpatient children than in outpatients.Antibiotics should be used rationally in clinical practice based on etiological diagnosis and antimicrobial susceptibility test results.Ongoing antimicrobial resistance surveillance and prevention and control of hospital infections are crucial to curbing bacterial resistance.
5.Surveillance of antimicrobial resistance in clinical isolates of Escherichia coli:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Shanmei WANG ; Bing MA ; Yi LI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Aimin WANG ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WEN ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(1):39-47
Objective To investigate the changing antibiotic resistance profiles of E.coli isolated from patients in the 52 hospitals participating in the CHINET program from 2015 to 2021.Methods Antimicrobial susceptibility was tested for clinical isolates of E.coli according to the unified protocol of CHINET program.WHONET 5.6 and SPSS 20.0 software were used for data analysis.Results Atotal of 289 760 nonduplicate clinical strains ofE.coli were isolated from 2015 to 2021,mainly from urine samples(44.7±3.2)%.The proportion of E.coli strains isolated from urine samples was higher in females than in males(59.0%vs 29.5%).The proportion of E.coli strains isolated from respiratory tract and cerebrospinal fluid samples was significantly higher in children than in adults(16.7%vs 7.8%,0.8%vs 0.1%,both P<0.05).The isolates from internal medicine department accounted for the largest proportion(28.9±2.8)%with an increasing trend over years.Overall,the prevalence of ESBLs-producing E.coli and carbapenem resistant E.coli(CREco)was 55.9%and 1.8%,respectively during the 7-year period.The prevalence of ESBLs-producing E.coli was the highest in tertiary hospitals each year from 2015 to 2021 compared to secondary hospitals.The prevalence of CREco was higher in children's hospitals compared to secondary and tertiary hospitals each year from 2015 to 2021.The prevalence of ESBLs-producing E.coli in tertiary hospitals and children's hospitals and the prevalence of CREco in children's hospitals showed a decreasing trend over the 7-year period.The prevalence of CREco in secondary and tertiary hospitals increased slowly.Antibiotic resistance rates changed slowly from 2015 to 2021.Carbapenem drugs(imipenem,meropenem)were the most active drugs amongβ-lactams against E.coli(resistance rate≤2.1%).The resistance rates of E.coli to β-lactam/β-lactam inhibitor combinations(piperacillin-tazobactam,cefoperazone-sulbactam),aminoglycosides(amikacin),nitrofurantoin and fosfomycin(for urinary isolates only)were all less than 10%.The resistance rate of E.coli strains to antibiotics varied with the level of hospitals and the departments where the strains were isolated,especially for cefazolin and ciprofloxacin,to which the resistance rate of E.coli strains from children in non-ICU departments was significantly lower than that of the strains isolated from other departments(P<0.05).The E.coli isolates from ICU showed higher resistance rate to most antimicrobial agents tested(excluding tigecycline)than the strains isolated from other departments.The E.coli strains isolated from tertiary hospitals showed higher resistance rates to the antimicrobial agents tested(excluding tigecycline,polymyxin B,cefepime and carbapenems)than the strains from secondary hospitals and children's hospitals.Conclusions E.coli is an important pathogen causing clinical infection.More than half of the clinical isolates produced ESBL.The prevalence of CREco is increasing in secondary and tertiary hospitals over the 7-year period even though the overall prevalence is still low.This is an issue of concern.
6.Expert consensus on the prevention and treatment of enamel demineralization in orthodontic treatment.
Lunguo XIA ; Chenchen ZHOU ; Peng MEI ; Zuolin JIN ; Hong HE ; Lin WANG ; Yuxing BAI ; Lili CHEN ; Weiran LI ; Jun WANG ; Min HU ; Jinlin SONG ; Yang CAO ; Yuehua LIU ; Benxiang HOU ; Xi WEI ; Lina NIU ; Haixia LU ; Wensheng MA ; Peijun WANG ; Guirong ZHANG ; Jie GUO ; Zhihua LI ; Haiyan LU ; Liling REN ; Linyu XU ; Xiuping WU ; Yanqin LU ; Jiangtian HU ; Lin YUE ; Xu ZHANG ; Bing FANG
International Journal of Oral Science 2025;17(1):13-13
Enamel demineralization, the formation of white spot lesions, is a common issue in clinical orthodontic treatment. The appearance of white spot lesions not only affects the texture and health of dental hard tissues but also impacts the health and aesthetics of teeth after orthodontic treatment. The prevention, diagnosis, and treatment of white spot lesions that occur throughout the orthodontic treatment process involve multiple dental specialties. This expert consensus will focus on providing guiding opinions on the management and prevention of white spot lesions during orthodontic treatment, advocating for proactive prevention, early detection, timely treatment, scientific follow-up, and multidisciplinary management of white spot lesions throughout the orthodontic process, thereby maintaining the dental health of patients during orthodontic treatment.
Humans
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Consensus
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Dental Caries/etiology*
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Dental Enamel/pathology*
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Tooth Demineralization/etiology*
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Tooth Remineralization
7.A disentangled generative model for improved drug response prediction in patients via sample synthesis.
Kunshi LI ; Bihan SHEN ; Fangyoumin FENG ; Xueliang LI ; Yue WANG ; Na FENG ; Zhixuan TANG ; Liangxiao MA ; Hong LI
Journal of Pharmaceutical Analysis 2025;15(6):101128-101128
Personalized drug response prediction from molecular data is an important challenge in precision medicine for treating cancer. Computational methods have been widely explored and have become increasingly accurate in recent years. However, the clinical application of prediction methods is still in its infancy due to large discrepancies between preclinial models and patients. We present a novel disentangled synthesis transfer network (DiSyn) for drug response prediction specifically designed for transfer learning from preclinical models to clinical patients. DiSyn uses a domain separation network (DSN) to disentangle drug response related features, employs data synthesis technology to increase the sample size and iteratively trains for better feature disentanglement. DiSyn is pretrained on large-scale unlabeled cancer samples and validated by three datasets, The Cancer Genome Atlas (TCGA), Investigation of Serial Studies to Predict Your Therapeutic Response With Imaging And moLecular Analysis 2 (I-SPY2) and Novartis Institutes for Biomedical Research Patient-Derived Xenograft Encyclopedia (NIBR PDXE), achieving competitive performance with the state-of-the-art methods on cancer patients and mice. Furthermore, the application of DiSyn to thousands of breast cancer patients show the heterogeneity in drug responses and demonstrate its potential value in biomarker discovery and drug combination prediction.
8.Methodological quality of systematic reviews on orally administered Chinese herbal medicine published in Chinese between 2021 and 2022: A cross-sectional study.
Yue JIANG ; Claire Chenwen ZHONG ; Betty Huan WANG ; Shan-Shan XU ; Fai Fai HO ; Ming Hong KWONG ; Leonard HO ; Joson Hao-Shen ZHOU ; K C LAM ; Jian-Ping LIU ; Bao-Ting ZHANG ; Vincent Chi Ho CHUNG
Journal of Integrative Medicine 2025;23(5):492-501
OBJECTIVE:
This cross-sectional study assessed the methodological quality of systematic reviews (SRs) of Chinese herbal medicine (CHM) published in Chinese between Jan 2021 and Sep 2022.
METHODS:
Chinese language CHM SRs were identified through literature searches across 3 international and 4 Chinese databases. Methodological quality was appraised using A MeaSurement Tool to Assess systematic Reviews 2. Logistic regressions were used to explore associations between bibliographical characteristics and quality.
RESULTS:
Analyses of methodological quality found that among the 213 sampled SRs, 69.5% were of critically low quality, 30.5% were of low quality, and none achieved high or moderate quality. Common shortcomings included the failure to identify the studies excluded from the analysis, failure to disclose funding sources, and limited evaluation of the potential impact of bias on conclusions. Logistic regressions revealed that SRs led by corresponding authors affiliated with universities or academic institutions tended to be of lower quality than SRs led by authors affiliated with hospitals or clinical facilities.
CONCLUSION
Recent Chinese language CHM SRs exhibited limited methodological quality, making them unlikely to support the development of clinical practice guidelines. Urgent initiatives are needed to enhance training for researchers, peer-reviewers and editors involved in the preparation and publication of SRs. Adoption of Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guidelines in Chinese language journals is crucial to improve the relevance of SRs for Chinese medicine development. Addressing deficiencies in methodology and reporting is essential for promoting evidence-based practices and informed clinical decisions in Chinese medicine. Please cite this article as: Jiang Y, Zhong CC, Wang BH, Xu SS, Ho FF, Kwong MH, Ho L, Zhou JHS, Lam KC, Liu JP, Zhang BT, Chung VCH. Methodological quality of systematic reviews on orally administered Chinese herbal medicine published in Chinese between 2021 and 2022: A cross-sectional study. J Integr Med. 2025; 23(5):492-501.
Cross-Sectional Studies
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Drugs, Chinese Herbal/administration & dosage*
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Systematic Reviews as Topic/standards*
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Humans
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China
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Administration, Oral
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Medicine, Chinese Traditional
9.Associations of White Blood Cell, Platelet Count, Platelet-to-White Blood Cell Ratio with Muscle Mass among Community-Dwelling Older Adults in China.
Zhen Wei ZHANG ; Yu Ming ZHAO ; Hong Zhou CHEN ; Li QI ; Chen CHEN ; Jun WANG ; Wen Hui SHI ; Yue Bin LYU ; Xiao Ming SHI
Biomedical and Environmental Sciences 2025;38(6):693-705
OBJECTIVE:
This study aimed to evaluate the relationships of white blood cell (WBC) count, platelet (PLT) count, and PLT-to-WBC ratio (PWR) with muscle mass in Chinese older adults.
METHODS:
This cross-sectional analysis involved 4,033 Chinese older adults aged ≥ 65 years from the Healthy Ageing and Biomarkers Cohort Study. Muscle mass and total skeletal muscle mass index (TSMI) were measured by bioelectric impedance analysis. WBC, PLT, and PWR were measured using standard methods. Multivariate linear regression was used to examine the associations of WBC count, PLT count, and PWR with TSMI.
RESULTS:
High WBC count, PLT count, and PWR were associated with low TSMI, with coefficients of -0.0091 (95% confidence interval [ CI]: -0.0142 to -0.0041), -0.0119 (95% CI: -0.0170 to -0.0068), and -0.0051 (95% CI: -0.0102 to -0.0001). The associations between the three inflammatory indices and TSMI were linear. Stratified analyses indicated that the relationship between inflammatory markers and TSMI was more evident in male participants and in individuals aged < 80 years than in their counterparts.
CONCLUSION
Elevated WBC count, PLT count, and PWR correlated with muscle mass loss. This study highlights the importance of regular monitoring of inflammatory markers as a potential strategy for the screening and management of sarcopenia in older adults.
Humans
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Aged
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Male
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Female
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China
;
Leukocyte Count
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Cross-Sectional Studies
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Platelet Count
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Aged, 80 and over
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Muscle, Skeletal/anatomy & histology*
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Independent Living
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Blood Platelets
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Leukocytes
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Sarcopenia
10.Untargeted Metabolomics of Plasma From Coronavirus Disease 2019 Patients One Year After Recovery.
Xu-Tong ZHANG ; Ye-Hong YANG ; Yue WU ; Rong HAN ; Qiao-Chu WANG ; Tao DING ; Jiang-Feng LIU ; Jun-Tao YANG
Acta Academiae Medicinae Sinicae 2025;47(4):519-526
Objective To investigate the recovery of plasma metabolism in asymptomatic and mild patients of coronavirus disease 2019(COVID-19)one year after recovery.Methods A total of 174 participants were recruited from the communities in Wuhan,including 80 healthy volunteers and the COVID-19 patients who had recovered for one year.According to the disease severity,the recovered COVID-19 patients were grouped as asymptomatic patients(n=80)and mild patients(n=14).The liquid chromatography mass spectrometry platform was employed to study the metabolomic characteristics of the plasma from all the participants.Results The plasma metabolites in asymptomatic patients and mild patients remained abnormal compared with those in healthy volunteers.Among the differential metabolites in asymptomatic patients and mild patients,some metabolites showed a downward trend only in mild patients,such as phosphatidylethanolamine[20∶3(5Z,8Z,11Z)/P-18∶0],sphingomyelin(d18∶1/24∶0),and cholesteryl(15∶0).The metabolic pathway involving the differential metabolites in mild patients was mainly glycerophospholipid metabolism.Conclusions Even one year after recovery,the mild COVID-19 patients still exhibit metabolic abnormalities.Hence,these patients may experience an extended period of time for recovery.
Humans
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COVID-19/metabolism*
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Metabolomics
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SARS-CoV-2
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Metabolome
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Female
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Male
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Adult
;
Middle Aged

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