2.Associations between statins and all-cause mortality and cardiovascular events among peritoneal dialysis patients: A multi-center large-scale cohort study.
Shuang GAO ; Lei NAN ; Xinqiu LI ; Shaomei LI ; Huaying PEI ; Jinghong ZHAO ; Ying ZHANG ; Zibo XIONG ; Yumei LIAO ; Ying LI ; Qiongzhen LIN ; Wenbo HU ; Yulin LI ; Liping DUAN ; Zhaoxia ZHENG ; Gang FU ; Shanshan GUO ; Beiru ZHANG ; Rui YU ; Fuyun SUN ; Xiaoying MA ; Li HAO ; Guiling LIU ; Zhanzheng ZHAO ; Jing XIAO ; Yulan SHEN ; Yong ZHANG ; Xuanyi DU ; Tianrong JI ; Yingli YUE ; Shanshan CHEN ; Zhigang MA ; Yingping LI ; Li ZUO ; Huiping ZHAO ; Xianchao ZHANG ; Xuejian WANG ; Yirong LIU ; Xinying GAO ; Xiaoli CHEN ; Hongyi LI ; Shutong DU ; Cui ZHAO ; Zhonggao XU ; Li ZHANG ; Hongyu CHEN ; Li LI ; Lihua WANG ; Yan YAN ; Yingchun MA ; Yuanyuan WEI ; Jingwei ZHOU ; Yan LI ; Caili WANG ; Jie DONG
Chinese Medical Journal 2025;138(21):2856-2858
3.Mechanism of Action of Huangqi Guizhi Wuwutang Against Cerebral Ischemia-reperfusion Injury Based on Bioinformatics and Experimental Validation
Jie HU ; Gaojun TANG ; Ouyang RAO ; Sha XIE ; Ying LIU
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(22):10-20
ObjectiveTo investigate the mechanism of action of Huangqi Guizhi Wuwutang (HGWT) against cerebral ischemia-reperfusion injury (CIRI) based on bioinformatics and experimental validation. MethodsBiological informatics methods were used to screen for active components of HGWT and their targets. The GEO database was utilized to obtain CIRI-related differentially expressed genes (DEGs), and platforms such as GeneCards were used to identify disease targets. Venn diagram analysis was conducted to identify overlapping targets, followed by protein-protein interaction (PPI), gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, as well as immune infiltration and immune cell differential analysis. Core genes (Hub genes) were screened using LASSO regression and ROC curves, and molecular docking was used to validate the binding efficiency between the active components of the drug and the core targets. A rat CIRI model was established, with rats randomly divided into five groups (n=10): Sham surgery group (Sham), model group (MG), and low-dose (LD,5.3 g·kg-1), medium-dose (MD,10.6 g·kg-1), and high-dose (HD,21.2 g·kg-1) HGWT groups. From 3 days before modeling to 7 days after surgery, oral administration was performed daily: Sham and MG groups received physiological saline, while each drug group received the corresponding dose of HGWT. Hematoxylin-eosin (HE) staining, Nissl staining, and terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (TUNEL staining) were used to assess the repair effects of HGWT on neural damage. Western blot analysis was used to detect B-cell lymphoma-2 protein (Bcl-2), Bcl-2-associated X protein (Bax), signal transducer and activator of transcription 3 (STAT3), phosphorylated STAT3 [p-STAT3 (Tyr705)], protein kinase B1 (Akt1), and phosphorylated Akt1 [p-Akt1 (Ser473)], among other target proteins. ResultsAfter screening, 56 common target points of DEGs-disease-drug were obtained. GO and KEGG analyses indicated that HGWT primarily functions in pathways such as apoptosis, oxidative stress, and inflammatory responses. Immune infiltration analysis revealed a significant association between HGWT's anti-CIRI activity and immune cells such as Th17 cells and myeloid-derived suppressor cells (MDSCs) (P0.01). LASSO-ROC analysis identified Akt1, Caspase-3, glycogen synthase kinase-3β (GSK-3β), and STAT3 as core genes. Molecular docking confirmed that Hub genes exhibit significant binding affinity with the active components of HGWT (binding energy ≤ -5 kJ·mol-1)(1 cal≈4.186 J). Animal experiment results showed that compared with the sham group, the MG group exhibited significant neuronal necrosis, nuclear condensation, and vacuolar degeneration in rat brains, with a significant decrease in Nissl body density (P0.01) and increased neuronal apoptosis in rat brains as indicated by TUNEL staining (P0.01). Compared with the MG, the LD, MD, and HD groups showed reduced neuronal necrosis, nuclear condensation, and vacuolar degeneration in rat brain neurons, increased Nissl body density, and reduced apoptosis (P0.01), with significant differences among the drug groups (P0.01). Western blot results showed that compared with the sham group, the MG group had reduced Bcl-2 and p-Akt1 (P0.01) and increased Bax and p-STAT3 (P0.01). Compared with the MG group, the drug groups showed increased Bcl-2 and p-Akt1 (P0.01) and decreased Bax and p-STAT3 (P0.01). There were no significant changes in total Akt1 and STAT3 protein levels among the groups. ConclusionBased on network pharmacology and experimental verification, HGWT may exert its neuroprotective effects by regulating the phosphorylation levels of Akt1 and STAT3, thereby alleviating cell apoptosis, inflammatory responses, and oxidative stress in rat brain tissue following CIRI. This provides theoretical support for the clinical treatment of CIRI.
4.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.
5.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.
6.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.
7.Construction of a pancreatic cancer prognosis model based on immune-related genes and its application in immune microenvironment
Yan-jie XU ; Yang-dong WU ; Qiang WANG ; Cun-ying ZHOU ; Xia TIAN ; Xiao HU
Chinese Journal of Current Advances in General Surgery 2025;28(7):530-537
Objective:It is of great significance to analyze the expression characteristics of immune-related genes in pancreatic cancer and their relationship with prognosis,construct and verify a reliable prognostic model,and explore prognostic methods of pancreatic cancer from the perspective of immune microenvironment.Methods:GSEA enrich-ment analysis of differentially expressed genes in pancreatic cancer was performed to identify key immune-related pathways and genes.The genes involved in the immune pathway were screened through the STRING database and combined with univariate Cox regression and LASSO regression analysis.Three key genes,RIPK2,IRAK2 and CXCL11,were finally identified to construct the prognostic model.The accuracy of the model was evaluated using ROC curves and calibration curves,and verified in an independent verification set(GSE57495).At the same time,the expression pat-terns of key genes in the immune microenvironment were analyzed by single-cell RNA sequencing,and the expression levels of these genes were verified in pancreatic cancer cell lines by RT-qPCR.Results:The expressions of RIPK2,IRAK2 and CXCL11 in pancreatic cancer cell lines were higher than those in normal pancreatic cancer cells(P<0.05).The model based on these three genes divided the patients into a high-risk group(n=87)and a low-risk group(n=89),and the difference in survival time between the high-risk group and the low-risk group was statistically significant(P<0.001).Risk score was correlated with G stage,N stage and tumor residue(P<0.01).Single-cell analysis showed that the ex-pression of these genes was highest in tumor-associated macrophages(mean>0.5)and correlated with regulatory T cells and macrophage infiltration(P<0.05).Multivariate analysis showed that risk score was correlated with overall sur-vival after adjusting for clinical factors(P=0.0014).Conclusion:Based on three key immune-related genes(RIPK2,IRAK2 and CXCL11),we successfully constructed a model to accurately predict the prognosis of pancreatic cancer pa-tients,revealing the important role of these genes in the tumor immune microenvironment,and providing new insights and theoretical basis for pancreatic cancer prognosis assessment and immunotherapy research.
8.Guideline for Adult Weight Management in China
Weiqing WANG ; Qin WAN ; Jianhua MA ; Guang WANG ; Yufan WANG ; Guixia WANG ; Yongquan SHI ; Tingjun YE ; Xiaoguang SHI ; Jian KUANG ; Bo FENG ; Xiuyan FENG ; Guang NING ; Yiming MU ; Hongyu KUANG ; Xiaoping XING ; Chunli PIAO ; Xingbo CHENG ; Zhifeng CHENG ; Yufang BI ; Yan BI ; Wenshan LYU ; Dalong ZHU ; Cuiyan ZHU ; Wei ZHU ; Fei HUA ; Fei XIANG ; Shuang YAN ; Zilin SUN ; Yadong SUN ; Liqin SUN ; Luying SUN ; Li YAN ; Yanbing LI ; Hong LI ; Shu LI ; Ling LI ; Yiming LI ; Chenzhong LI ; Hua YANG ; Jinkui YANG ; Ling YANG ; Ying YANG ; Tao YANG ; Xiao YANG ; Xinhua XIAO ; Dan WU ; Jinsong KUANG ; Lanjie HE ; Wei GU ; Jie SHEN ; Yongfeng SONG ; Qiao ZHANG ; Hong ZHANG ; Yuwei ZHANG ; Junqing ZHANG ; Xianfeng ZHANG ; Miao ZHANG ; Yifei ZHANG ; Yingli LU ; Hong CHEN ; Li CHEN ; Bing CHEN ; Shihong CHEN ; Guiyan CHEN ; Haibing CHEN ; Lei CHEN ; Yanyan CHEN ; Genben CHEN ; Yikun ZHOU ; Xianghai ZHOU ; Qiang ZHOU ; Jiaqiang ZHOU ; Hongting ZHENG ; Zhongyan SHAN ; Jiajun ZHAO ; Dong ZHAO ; Ji HU ; Jiang HU ; Xinguo HOU ; Bimin SHI ; Tianpei HONG ; Mingxia YUAN ; Weibo XIA ; Xuejiang GU ; Yong XU ; Shuguang PANG ; Tianshu GAO ; Zuhua GAO ; Xiaohui GUO ; Hongyi CAO ; Mingfeng CAO ; Xiaopei CAO ; Jing MA ; Bin LU ; Zhen LIANG ; Jun LIANG ; Min LONG ; Yongde PENG ; Jin LU ; Hongyun LU ; Yan LU ; Chunping ZENG ; Binhong WEN ; Xueyong LOU ; Qingbo GUAN ; Lin LIAO ; Xin LIAO ; Ping XIONG ; Yaoming XUE
Chinese Journal of Endocrinology and Metabolism 2025;41(11):891-907
Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.
9.Material basis of bitter taste and taste-effect relationship in Cistanche deserticola based on UPLC-Q-Orbitrap HRMS combined with molecular docking.
Li-Ying TIAN ; Ming-Jie LI ; Qiang HOU ; Zheng-Yuan WANG ; Ai-Sai-Ti GULIZIYE ; Jun-Ping HU
China Journal of Chinese Materia Medica 2025;50(6):1569-1580
Based on ultra-performance liquid chromatography-quadrupole-electrostatic field Orbitrap high-resolution mass spectrometry(UPLC-Q-Orbitrap HRMS) technology and molecular docking, the bitter-tasting substances(hereafter referred to as "bitter substances") in Cistanche deserticola extract were investigated, and the bitter taste and efficacy relationship was explored to lay the foundation for future research on de-bittering and taste correction. Firstly, UPLC-Q-Orbitrap HRMS was used for the qualitative analysis of the constituents of C. deserticola, and 69 chemical components were identified. These chemical components were then subjected to molecular docking with the bitter taste receptor, leading to the screening of 20 bitter substances, including 6 phenylethanol glycosides, 5 flavonoids, 3 phenolic acids, 2 cycloalkenyl ether terpenes, 2 alkaloids, and 2 other components. Nine batches of fresh C. deserticola samples were collected from the same origin but harvested at different months. These samples were divided into groups based on harvest month and plant part. The bitterness was quantified using an electronic tongue, and the content of six potential bitter-active compounds(pineconotyloside, trichothecene glycoside, tubulin A, iso-trichothecene glycoside, jinshihuaoside, and jingnipinoside) was determined by high-performance liquid chromatography(HPLC). The total content of phenylethanol glycosides, polysaccharides, alkaloids, flavonoids, and phenolic acids was determined using UV-visible spectrophotometry. Chemometric analyses were then conducted, including Pearson's correlation analysis, gray correlation analysis, and orthogonal partial least squares discriminant analysis(OPLS-DA), to identify the bitter components in C. deserticola. The results were consistent with the molecular docking findings, and the two methods mutually supported each other. Finally, network pharmacological predictions and analyses were performed to explore the relationship between the targets of bitter substances and their efficacy. The results indicated that key targets of the bitter substances included EGFR, PIK3CB, and PTK2. These substances may exert their bitter effects by acting on relevant disease targets, confirming that the bitter substances in C. deserticola are the material basis of its bitter taste efficacy. In conclusion, this study suggests that the phenylethanol glycosides, primarily pineconotyloside, mauritiana glycoside, and gibberellin, are the material basis for the "bitter taste" of C. deserticola. The molecular docking technique plays a guiding role in the screening of bitter substances in traditional Chinese medicine(TCM). The bitter substances in C. deserticola not only contribute to its bitter taste but also support the concept of the "taste-efficacy" relationship in TCM, providing valuable insights and references for future research in this area.
Molecular Docking Simulation
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Taste
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Chromatography, High Pressure Liquid
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Cistanche/chemistry*
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Drugs, Chinese Herbal/chemistry*
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Humans
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Mass Spectrometry
10.Clinical and Laboratory Characteristic Analysis of Patients with Newly Diagnosed Monoclonal Gammopathy Combined with Anemia.
Han QIAN ; Yue-Xia WU ; Min YANG ; Yu-Ting HU ; Yu-Jie KONG ; Qian LIU ; Ying XU
Journal of Experimental Hematology 2025;33(2):587-592
OBJECTIVE:
To study the clinical and laboratory characteristics of monoclonal gammopathy anemia and explore the risk factors associated with anemia in monoclonal gammopathy.
METHODS:
A retrospective analysis was conducted on 5 539 patients who underwent immunofixation electrophoresis at the First Affiliated Hospital of Chengdu Medical College from January 2016 to February 2024. A total of 351 newly diagnosed M protein positive patients were selected as the study subjects, including 270 in the anemia group and 81 in the non-anemia group. Laboratory test results were compared between the two groups, and logistic regression models were used to analyze the risk factors for anemia. ROC curve analysis was performed to evaluate the predictive value of risk factors for anemia in monoclonal gammopathy.
RESULTS:
The proportion of non-anemic patients was 23.1% (81/351), with a median age of 67(60-75) years; the proportion of anemic patients was 76.9% (270/351), with a median age of 70(63-75) years. The total protein, globulin, urea, creatinine, uric acid, β2-microglobulin, and ceruloplasmin levels in the anemia group were higher than those in the non-anemia group ( P < 0.05), while albumin, neutrophil count, lymphocyte count, monocyte count, complement C3, complement C4, haptoglobin, and transferrin levels were lower in the non-anemia group ( P < 0.05). After adjustment, multivariate logistic regression analysis shows that elevated GLB, increased β2-MG, decreased ANC, and reduced complement C3 were independent risk factors for anemia in monoclonal gammopathy ( P < 0.05). ROC curve analysis demonstrates that GLB, β2-MG, ANC, and complement C3 had good predictive value for anemia associated with monoclonal gammopathy.
CONCLUSION
Elevated GLB, increased β2-MG, decreased ANC, and reduced complement C3 are independent risk factors for anemia in monoclonal gammopathy (P < 0.05). The combined assessment of these four factors has good predictive value for anemia in monoclonal gammopathy.
Humans
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Retrospective Studies
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Anemia/complications*
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Aged
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Middle Aged
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Paraproteinemias/diagnosis*
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Risk Factors
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Male
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Female
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Logistic Models
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ROC Curve
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Complement C3

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