1.Longitudinal study on the relationship between DASH-style dietary pattern and allostatic load in Chinese pregnant women
Wenjuan LI ; Ziyan XU ; Min YU ; Fangfang YANG ; Hong ping ZHAO ; Yu-hong LI
Nutrition Research and Practice 2026;20(1):77-88
BACKGROUND/OBJECTIVES:
Unhealthy diets are associated with chronic stress. An allostatic load (AL) is a comprehensive physiological index that measures the chronic stress response of the body. As a healthy dietary pattern, the role of Dietary Approaches to Stop Hypertension (DASH) in the development of an AL during pregnancy remains unclear. This study examined the relationship between the DASH dietary pattern and AL during pregnancy.
SUBJECTS/METHODS:
This study was a prospective study. From January 2024 to November 2024, 134 pregnant women in the second trimester (23–27 weeks) and third trimester (32–36 weeks) of pregnancy who met the inclusion and exclusion criteria in the obstetrics clinic of a tertiary general hospital in Anhui Province were selected for a questionnaire survey, physical examination, and laboratory examination. The DASH dietary pattern was assessed using the DASH scoring tool, and the total AL score was calculated using nine biomarkers that represent the cardiovascular, metabolic, and immune systems. Logistic regression was used to analyze the relationship between the DASH score and AL.
RESULTS:
One hundred and thirty-four pregnant women were included in this study. At the second and third trimesters, 41.8% and 37% of pregnant women, respectively, were in the high AL group. The binary logistic regression results showed that the DASH score was negatively correlated with the AL in the unadjusted model (odds ratio [OR], 0.878; 95% confidence interval [CI], 0.807–0.957; P = 0.003) and adjusted model (OR, 0.878; 95% CI, 0.792–0.973; P = 0.013) in the second trimester, the DASH score was negatively correlated with the AL in the unadjusted model (OR, 0.832; 95% CI, 0.758–0.913; P < 0.001) and adjusted model (OR, 0.806; 95% CI, 0.716–0.908; P < 0.001) in the third trimester.
CONCLUSION
The DASH score was negatively correlated with the AL in pregnant women.A low DASH score may increase the risk of a high AL, which may have adverse effects on physical and mental health.
2.A preliminary exploration of influenza-like illness surveillance and influenza vaccination in Jing’an District of Shanghai, 2017‒2023
Ruijue HUA ; Lixue LYU ; Biao XU ; Jin HUANG ; Ping YU
Shanghai Journal of Preventive Medicine 2025;37(4):313-318
ObjectiveTo understand the surveillance of influenza-like illness (ILI) and influenza vaccination status in Jing’an District, Shanghai, and to provide a basis for optimizing influenza prevention and control strategies. MethodsThe sentinel surveillance data for ILI and virological surveillance data of influenza viruses in Jing’an District were collected from the Chinese influenza surveillance information system, and data for influenza vaccination were collected from Shanghai immunization information system from September 2017 to August 2023. Epidemiological characteristics of ILI, influenza etiology, and the temporal and population distributions of influenza vaccination were analyzed using descriptive epidemiological methods. ResultsILI as a percentage of total visit surveillance units (ILI%) reported by sentinel hospital was increased in Jing’an District of Shanghai from September 2017 to August 2023 (F=18.841, P=0.012). The peak of the influenza cases mainly appeared in winter-spring, but there were two peaks in winter-spring and summer from September 2019 to August 2020, from September 2020 to August 2021, and from September 2021 to August 2022. In particular, there were two peaks in winter-spring from September 2022 to August 2023, with a rebound during the descending process. The average positive rate of ILI was 21.64% (2 421/11 189) during the 6 years. There was a peak in winter-spring during every year with the exception of the period from September 2020 to August 2021. The dominant strains were B/Yamagata and A/H1N1 in winter-spring from September 2017 to August 2018. The dominant strain was A/H1N1 in winter-spring from September 2018 to August 2019 and from September 2022 to August 2023. The dominant strain was B/Victoria in winter-spring from September 2019 to August 2020 and from September 2021 to August 2022. Different subtype strains occurred alternately, and the dominant strains were A/H1N1 and A/H3N2 in recent years. The influenza vaccination coverage was 2.94% from September 2017 to August 2023, and the vaccination coverage was highest in young children. The vaccination coverage for females was higher than that for males (χ2=546.963, P<0.001), and the vaccination coverage for registered residents was higher compared to that for migrants (χ2=123.141, P<0.001). ConclusionILI% exhibits an upward trend in Jing’an District of Shanghai, and the dominant strain is A subtype. The influenza vaccination coverage is still low, which is insufficient to have an impact on the spread of influenza. It is recommended that the surveillance of ILI and variations of influenza virus strains should be improved continuously, and effective steps should be taken to promote influenza vaccination.
3.Critical care medicine under the background of digital intelligence integration:opportunities,challenges,and strategies
Tianyu XU ; Songxuan YU ; Lengchen HOU ; Mingxiao MA ; Ping HE ; Bing SHEN
Academic Journal of Naval Medical University 2025;46(1):118-122
Recently,the theoretical system and practical path for the deep integration of digitalization and traditional industrialization have gradually matured.Medical innovation and digital technology are progressing,and the deep integration of intensive care medicine and intelligence is surpassing the traditional informatization and ushering in new development opportunities.Technologies such as 5G,big data,artificial intelligence,and digital twins can help to understand more complex critical care issues,improve the diagnoses and prediction of diseases and symptoms,develop more accurate treatment strategies,and even transform the service model of critical care medicine.This paper summarizes the application and challenge of digital technology in the practical scenarios of critical care medicine,so as to further consolidate infrastructure,enrich application scenarios,accelerate implementation,improve effectiveness,and strengthen the safety and compliance with the regulations.
4.Research of miR-508-3p involvement in ovarian cancer progression by regulating ZEB1
Yu-hong XU ; Shuai-ying ZHU ; Jiang-jing SHAN ; Wei-ping ZHENG ; Hui-ya ZHANG ; Yun-gen WANG
The Chinese Journal of Clinical Pharmacology 2025;41(2):193-197
Objective To investigate the expression of microRNA-508-3p(miR-508-3p)in epithelial ovarian cancer(EOC)tissue,its impact on the migration and invasion of ovarian cancer cells,and its regulatory relationship with zinc-finger E-box-binding homeobox 1(ZEB1).Methods The surgical resection of EOC cancer tissues and paired adjacent normal tissues were collected.SKOV3 cells were divided into the NC mimic group(transfected with NC mimic),miR-508-3p mimic group(transfected with miR-508-3p mimic),si-NC group(transfected with si-NC),si-ZEB1 group(transfected with si-ZEB1)and co-transfection group(co-transfected with si-ZEB1 and miR-508-3p mimic).The mRNA expression levels of miR-508-3p and ZEB1 in EOC cancer tissues,adjacent normal tissues and five groups of cells were measured by real-time quantitative polymerase chain reaction.The Transwell assay was used to detect the cell migration and invasion abilities.Results The relative expression levels of miR-508-3p in EOC tissues and adjacent normal tissues were 0.77±0.36 and 1.07±0.40,the relative expression levels of ZEB1 mRNA in EOC tissues and adjacent normal tissues were 2.10±1.21 and 1.29±0.95,and the differences were statistically significant(all P<0.01).The migration cell number of the NC mimic,miR-508-3p mimic,si-NC,si-ZEB1 and co-transfection groups was 633.00±32.49,319.20±19.89,650.40±25.85,375.00±17.25 and 129.40±17.10;the invasion cell number was 527.20±25.01,288.60±16.68,520.00±25.83,293.40±18.37 and 76.60±8.76;the relative expression levels of miR-508-3p were 1.05±0.37,3.94±1.21,1.01±0.21,1.26±0.34 and 3.40±0.41;the relative expression levels of ZEB1 mRNA were 1.00±0.04,0.58±0.05,1.00±0.08,0.54±0.07 and 0.29±0.03,respectively.The above indicators showed statistically significant differences between the miR-508-3p mimic group and the NC mimic group,between the si-NC group and the co-transfection group(P<0.01,P<0.05).Conclusion MiR-508-3p is lowly expressed in EOC cancer tissue,and it may inhibit the migration and invasion of ovarian cancer cells by targeting ZEB1 expression.
5.Homotherapy for hetropathy of ischemic stroke and hemorrhagic stroke through common metabolites
Shaojing CHEN ; Ping JIANG ; Shujie SHEN ; Jie YU ; Ying GAO ; Mingying SHANG ; Guangxue LIU ; Shaoqing CAI ; Feng XU
Chinese Journal of Cerebrovascular Diseases 2025;22(4):277-284
Ischemic stroke and hemorrhagic stroke have different pathogenic mechanisms,but share similarities in metabolic dysregulation,inflammatory responses and oxidative stress.This paper summarized 28 metabolic markers shared between ischemic stroke and hemorrhagic stroke with consistent trends through literature review.It also provided an overview of their involvement in abnormal energy metabolism,inflammatory responses,blood-brain barrier disruption,and neural damage in relation to stroke.The aim is to provide a scientific basis for future prognosis,curative efficacy evaluation and future homotherapy of ischemic stroke and hemorrhagic stroke,and provide insights for the development of new therapies and new drugs.
6.Expert Consensus on the Ethical Requirements for Generative AI-Assisted Academic Writing
You-Quan BU ; Yong-Fu CAO ; Zeng-Yi CHANG ; Hong-Yu CHEN ; Xiao-Wei CHEN ; Yuan-Yuan CHEN ; Zhu-Cheng CHEN ; Rui DENG ; Jie DING ; Zhong-Kai FAN ; Guo-Quan GAO ; Xu GAO ; Lan HU ; Xiao-Qing HU ; Hong-Ti JIA ; Ying KONG ; En-Min LI ; Ling LI ; Yu-Hua LI ; Jun-Rong LIU ; Zhi-Qiang LIU ; Ya-Ping LUO ; Xue-Mei LV ; Yan-Xi PEI ; Xiao-Zhong PENG ; Qi-Qun TANG ; You WAN ; Yong WANG ; Ming-Xu WANG ; Xian WANG ; Guang-Kuan XIE ; Jun XIE ; Xiao-Hua YAN ; Mei YIN ; Zhong-Shan YU ; Chun-Yan ZHOU ; Rui-Fang ZHU
Chinese Journal of Biochemistry and Molecular Biology 2025;41(6):826-832
With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.
7.Changing prevalence and antibiotic resistance profiles of carbapenem-resistant Enterobacterales in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Wenxiang JI ; Tong JIANG ; Jilu SHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yuanhong XU ; Ying HUANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yingchun XU ; Xiaojiang ZHANG ; 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 ; 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 ; Shanmei WANG ; Yafei CHU ; 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 ; Hong ZHANG ; Chun WANG ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; 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(4):445-454
Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43%(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38%,9.73%,and 8.47%,respectively.The prevalence of CRE strains in Escherichia coli was 1.99%.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)%,followed by blood(20.88±3.40)%and urine(18.40±3.45)%.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)%.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.
8.Changing distribution and antibiotic resistance profiles of the respiratory bacterial isolates in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Ying FU ; Yunsong YU ; Jie LIN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; 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 ; Shanmei WANG ; Yafei CHU ; 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 ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(4):431-444
Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6%of the isolates were Gram-negative bacteria and 17.4%were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)%and(94.0±0.1)%,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P<0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9%.The prevalence of penicillin-resistant S.pneumoniae was 1.4%.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8%and 41.3%,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7%,20.8%,9.4%,29.8%,and 73.3%,respectively.The prevalence of β-lactamase was 96.1%in Moraxella catarrhalis and 60.0%in Haemophilus influenzae.The H.influenzae isolates from children(<18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P<0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.
9.Progress on antisense oligonucleotide in the field of antibacterial therapy
Jia LI ; Xiao-lu HAN ; Shi-yu SONG ; Jin-tao LIN ; Zhi-qiang TANG ; Zeng-ming WANG ; Liang XU ; Ai-ping ZHENG
Acta Pharmaceutica Sinica 2025;60(2):337-347
With the widespread use of antibiotics, drug-resistant bacterial infections have become a significant threat to human health. Finding new antibacterial strategies that can effectively control drug-resistant bacterial infections has become an urgent task. Unlike small molecule drugs that target bacterial proteins, antisense oligonucleotide (ASO) can target genes related to bacterial resistance, pathogenesis, growth, reproduction and biofilm formation. By regulating the expression of these genes, ASO can inhibit or kill bacteria, providing a novel approach for the development of antibacterial drugs. To overcome the challenge of delivering antisense oligonucleotide into bacterial cells, various drug delivery systems have been applied in this field, including cell-penetrating peptides, lipid nanoparticles and inorganic nanoparticles, which have injected new momentum into the development of antisense oligonucleotide in the antibacterial realm. This review summarizes the current development of small nucleic acid drugs, the antibacterial mechanisms, targets, sequences and delivery vectors of antisense oligonucleotide, providing a reference for the research and development of antisense oligonucleotide in the treatment of bacterial infections.
10.Changes in hepatic bile acid profile in a mouse model of metabolic-associated steatohepatitis induced by a high-fat, high-sugar, and high-cholesterol diet combined with carbon tetrachloride
Jingjing WANG ; Jinghua PENG ; Yu LIU ; Feipeng XU ; Wei LIU ; Hailin YANG ; Ping LIU
Journal of Clinical Hepatology 2025;41(4):661-669
ObjectiveTo compare the hepatic bile acid profile between a mouse model of metabolic-associated steatohepatitis (MASH) induced by a high-fat, high-sugar, and high-cholesterol diet combined with intraperitoneal injection of 10% carbon tetrachloride (CCl4) and MASH cases in clinical practice, and to investigate the feasibility of this model in studying drug interventions on bile acid profile in MASH. MethodsA total of 30 male C57BL/6J mice were randomly divided into control group and model group, with 15 mice in each group. The mice in the control group were given normal diet and drinking water and weekly injections of olive oil, and those in the model group were given a high-fat, high-sugar, and high-cholesterol diet, high-sugar drinking water, and weekly injections of CCl4+olive oil. At the end of weeks 8, 12, and 16, 5 mice were selected from each group to collect samples. Behavioral assessments were performed, and body weight and liver wet weight were measured; liver pathology and lipid deposition were evaluated by HE staining, SAF scoring, oil Red O staining, the semi-quantitative analysis of stained area, the serum levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST), and liver triglyceride (TG) content; Sirius Red staining was performed for liver tissue to assess liver fibrosis; ultra-performance liquid chromatography-tandem mass spectrometry and targeted metabolomics were used to measure the hepatic bile acid profile, including cholic acid (CA), glycocholic acid (GCA), chenodeoxycholic acid (CDCA), glycochenodeoxycholic acid (GCDCA), ursodeoxycholic acid (UDCA), tauroursodeoxycholic acid (TUDCA), hyodeoxycholic acid (HDCA), and glycodeoxycholic acid (GDCA). The independent-samples t test was used for comparison of normally distributed continuous data between two groups, and the Wilcoxon rank-sum test was used for comparison of non-normally distributed continuous data between two groups. ResultsCompared with the control group at the same time point, the model group had disheveled and dull fur, reduced activity, and relatively slow reactions at weeks 8, 12, and 16, as well as significant increases in liver wet weight (P<0.05), the serum level of ALT (P<0.05), the content of TG in the liver (P<0.05), and SAF score (P<0.05). As for the differentially expressed bile acids in liver tissue, compared with the control group at week 8, the model group had significantly higher levels of CA and CDCA and significantly lower levels of UDCA, TUDCA, HDCA, and GDCA (all P<0.05); compared with the control group at week 12, the model group had significantly higher levels of CA, GCA, CDCA, and GCDCA and significantly lower levels of UDCA and HDCA (all P<0.05); compared with the control group at week 16, the model group had significantly higher levels of CA, GCA, CDCA, GCDCA, and TUDCA and significantly lower levels of UDCA, HDCA, and GDCA (all P<0.05). As for the differentially expressed bile acids in the bile acid pool of liver tissue, compared with the control group at week 8, the model group had significantly higher levels of CA and CDCA and significantly lower levels of UDCA, TUDCA, GDCA, and HDCA (all P<0.05); compared with the control group at weeks 12 and 16, the model group had significantly higher levels of GCA and GCDCA and significantly lower levels of UDCA, GDCA, and HDCA (all P<0.05). ConclusionThere are significant changes in the hepatic bile acid profile in a mouse model of MASH induced by a high-fat, high-sugar, and high-cholesterol diet combined with CCl4, which are similar to the changes in bile acids in MASH cases in clinical practice, suggesting that this model can be used to explore the interventional effect of drugs on the bile acid profile in MASH.

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