1.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.
2.Aloin blocks the malignant behavior of lung squamous cell carcinoma cells and M2 macrophage polarization by modulating the NR3C2/MT1M axis.
Ying-Na CHEN ; Jie-Ya LU ; Cheng-Feng GAO ; Zhi-Ruo FANG ; Yan ZHOU
Journal of Integrative Medicine 2025;23(2):195-208
OBJECTIVE:
Aloin, the main active component in Aloe vera (L.) Burm. f., has shown promising anti-tumor effects. This study investigated the impact of aloin in lung squamous cell carcinoma (LUSC) and explored its functional mechanism.
METHODS:
We analyzed the viability, migration, invasion, proliferation, and apoptosis of two LUSC cell lines after treatment with aloin. Target molecules of aloin and downstream target transcripts of nuclear receptor subfamily 3 group C member 2 (NR3C2) were predicted by bioinformatics. The biological functions of NR3C2 and metallothionein 1 M (MT1M) in the malignant properties of LUSC cells were determined. A co-culture system of LUSC cells with monocyte-derived macrophages was constructed. Mouse xenograft tumor models were generated to analyze the functions of aloin and NR3C2 in the tumorigenic activity of LUSC cells and macrophage polarization in vivo.
RESULTS:
Aloin suppressed malignant properties of LUSC cells in vitro. However, these effects were negated by the silencing of NR3C2. NR3C2 was found to activate MT1M transcription by binding to its promoter. Additional upregulation of MT1M suppressed the malignant behavior of LUSC cells augmented by NR3C2 silencing. Analysis of the M1 and M2 markers/cytokines in the macrophages or the culture supernatant revealed that aloin treatment or MT1M overexpression in LUSC cells enhanced M1 polarization while suppressing M2 polarization of macrophages, whereas NR3C2 silencing led to reverse trends. Consistent findings were reproduced in vivo.
CONCLUSION
This study demonstrated that aloin activates the NR3C2/MT1M axis to suppress the malignant behavior of LUSC cells and M2 macrophage polarization. Please cite this article as: Chen YN, Lu JY, Gao CF, Fang ZR, Zhou Y. Aloin blocks the malignant behavior of lung squamous cell carcinoma cells and M2 macrophage polarization by modulating the NR3C2/MT1M axis. J Integr Med. 2025; 23(2): 195-208.
Lung Neoplasms/metabolism*
;
Humans
;
Animals
;
Cell Line, Tumor
;
Carcinoma, Squamous Cell/metabolism*
;
Mice
;
Macrophages/drug effects*
;
Emodin/analogs & derivatives*
;
Metallothionein/genetics*
;
Cell Proliferation/drug effects*
;
Cell Movement/drug effects*
;
Apoptosis/drug effects*
;
Receptors, Glucocorticoid/genetics*
3.Impact of Laboratory Analytical Indicators on Positive Blood Culture Detection Rates: A Single Center Study.
Di WANG ; Ling Li LIU ; Rui Rui MA ; Li Jun DU ; Gui Xue CHENG ; Ya Li LIU ; Qiao Lian YI ; Ying Chun XU
Biomedical and Environmental Sciences 2025;38(3):303-312
OBJECTIVE:
Blood culture remains the gold standard for diagnosing bloodstream infections. Clinical laboratories must ensure the quality of blood culture processes from receipt to obtaining definitive results. We examined laboratory analytical indicators associated with positive blood culture results.
METHODS:
Blood cultures collected from Peking Union Medical College Hospital between January 1, 2020, and December 31, 2022, were retrospectively analyzed. The mode of transportation (piping logistics delivery vs. staff), source of blood cultures (outpatient/emergency department vs. inpatient department), rotation of personnel, and time of reception (8:00-19:59 vs. 20:00-07:59) were compared between blood culture-positive and -negative results.
RESULTS:
Between 2020 and 2022, the total positive rate of blood culture was 8.07%. The positive rate of blood cultures in the outpatient/emergency department was significantly higher than that in the inpatient department (12.46% vs. 5.83%; P < 0.0001). The time-to-detection of blood cultures was significantly affected by the delivery mode and personnel rotation. The blood culture positive rate of the total pre-analytical time within 1 h was significantly higher than that within 1-2 h or > 2 h ( P < 0.0170).
CONCLUSION
Laboratory analytical indicators such as patient source, transportation mode, and personnel rotation significantly impacted the positive detection rate or time of blood culture.
Blood Culture/statistics & numerical data*
;
Humans
;
Retrospective Studies
;
Emergency Service, Hospital/statistics & numerical data*
4.Regulatory effect and molecular mechanism of circ_0044556 targeting the miR-338-3p/BRD4 axis on the malignant biological behavior of triple negative breast cancer cells
Xing-Juan DONG ; Ya-Li ZHANG ; Wei XING ; Ying-Ying ZHU ; Yong-Li CHENG ; Ping YU
Medical Journal of Chinese People's Liberation Army 2025;50(9):1146-1153
Objective To investigate the regulatory effect and molecular mechanism of circ_0044556 on the malignant biological behavior of triple negative breast cancer(TNBC)cells by targeting the miR-338-3p/bromodomain-containing protein 4(BRD4)axis.Methods The TargetScan online website was used to predict the binding sites of circ_0044556 with miR-338-3p and miR-338-3p with BRD4.Dual-luciferase reporter gene assays were performed to determine the relationship among circ_0044556,miR-338-3p,and BRD4 in MDA-MB-231 cells.Quantitative real-time PCR(qRT-PCR)and Western blotting were employed to detect the expression of circ_0044556,miR-338-3p,and BRD4 protein in human TNBC cell line MDA-MB-231 and human normal breast epithelial cells MCF-10A.MDA-MB-231 cells were divided into NC group,si-NC group(transfected with si-NC),si-circ_0044556 group(transfected with si-circ_0044556),si-circ_0044556+inhibitor NC group(transfected with si-circ_0044556 and inhibitor NC),and si-circ_0044556+miR-338-3p inhibitor group(transfected with si-circ_0044556 andmiR-338-3p inhibitor).qRT-PCR was applied to detect the expression of circ_0044556 and miR-338-3p;Western blotting was used to detect the expression of BRD4,E-cadherin,N-cadherin and Vimentin;the CCK-8 assay was applied to detect cell proliferation;flow cytometry was applied to detect cell apoptosis;and Transwell assays were used to detect cell invasion and migration.Thirty nude mice were randomly divided into NC group(tail vein injection of normal saline),si-NC group(tail vein injection of LV-NC),si-circ_0044556 group(tail vein injection of LV-circ_0044556),si-circ_0044556+inhibitor NC group(tail vein injection of LV-circ_0044556 and antiagomir NC),and si-circ_0044556+miR-338-3p inhibitor group(tail vein injection of LV-circ_0044556 and antiagomir miR-338-3p),with 6 mice per group.A xenograft tumor model was constructed by subcutaneous injection of MDA-MB-231 cells into nude mice,and tumor volume and weight were measured.Results TargetScan prediction results showed that the downstream miRNA of circ_0044556 was miR-338-3p,and the downstream target gene of miR-338-3p might be BRD4.Compared with transfecting mimic NC,transfection with miR-338-3p mimic significantly reduced the luciferase activities of WT-circ_0044556(0.34±0.03 vs.1.00±0.15,P<0.05)and WT-BRD4(0.41±0.05 vs.1.05±0.13,P<0.05)in MDA-MB-231 cells.Compared with MCF-10A cells,the expression levels of circ_0044556 and BRD4 protein in MDA-MB-231 cells were significantly increased,while the expression level of miR-338-3p was significantly decreased(P<0.05).Compared with NC group and si-NC group,the expression levels of circ_0044556,the protein expression levels of BRD4,N-cadherin,and Vimentin,and the OD450 value in MDA-MB-231 cells of si-circ_0044556 group and si-circ_0044556+inhibitor NC group were significantly decreased(P<0.05),the number of migrated and invaded cells was significantly reduced(P<0.05),and the expression level of miR-338-3p,the protein expression level of E-cadherin,and the cell apoptosis rate in MDA-MB-231 cells were significantly increased(P<0.05);downregulation of miR-338-3p rescued the inhibitory effect of circ_0044556 knockdown on invasion,migration,and proliferation of MDA-MB-231 cells.Compared with NC group and si-NC group,the tumor volume and weight in si-circ_0044556 group and si-circ_0044556+inhibitor NC group were significantly decreased(P<0.05);compared with si-circ_0044556 group and si-circ_0044556+inhibitor NC group,the tumor volume and weight in si-circ_0044556+miR-338-3p inhibitor group were significantly increased(P<0.05).Conclusion circ_0044556 may promote the malignant biological behaviors of TNBC cells through the miR-338-3p/BRD4 axis.
5.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.
6.Cross-sectional survey of healthcare-associated infection in 5 736 medical institutions across China in 2024
Cui ZENG ; Wuqiang GAO ; Fu QIAO ; Hui ZHAO ; Xu FANG ; Linping LI ; Xiuwen CHEN ; Jiansen CHEN ; Dan LI ; Yuan ZHOU ; Lingli YU ; Qinglan MENG ; Xia MOU ; Lijuan XIONG ; Weiguang LI ; Ding LIU ; Jiaqing XIAO ; Limei OU ; Baozhen LI ; Jun YIN ; Haojun ZHANG ; Qiang FU ; Qun LU ; Biao WU ; Ya-wei XING ; Shumei SUN ; Shuncai WANG ; Longmin DU ; Jingping ZHANG ; Wen-ying HE ; Gui CHENG ; Nan REN ; Xun HUANG ; Anhua WU
Chinese Journal of Infection Control 2025;24(11):1572-1583
Objective To understand the current situation of healthcare-associated infection(HAI)in China,pro-vide data support and decision-making basis for formulating scientific and effective strategies for HAI prevention and control.Methods A nationwide cross-sectional survey on HAI was conducted among various types and levels of medical institutions in China according to a unified protocol of bedside surveys and case investigations.Results In 2024,a total of 5 736 medical institutions and 2 751 765 patients were surveyed.Among them,34 889 HAI cases were identified,with a prevalence rate of 1.27%.The number of HAI episodes was 38 032,and case prevalence rate was 1.38%.The prevalence rate of HAI in medical institutions in different regions of China ranged from 0.66%to 2.35%.Among medical institutions of different scales,those with a bed capacity of ≥900 had the high-est incidence of HAI,reaching 1.65%.The most common infection site was the lower respiratory tract(44.66%),followed by the urinary tract(12.94%),surgical site(9.32%),upper respiratory tract(7.02%),and bloodstream infection(5.78%).The top 3 departments with the highest HAI rates were the general intensive care unit(10.02%),department of neurosurgery(5.51%),and department(group)of hematology(5.34%).A total of 23 238 strains of HAI pathogens were detected,with 10 714 strains(46.10%)from lower respiratory tract speci-mens.The top 5 detected strains were Klebsiella pneumoniae(14.76%),Pseudomonas aeruginosa(13.33%),Escherichia coli(12.79%),Acinetobacter baumannii(9.23%),and Staphylococcus aureus(7.88%).231 944 pa-tients underwent class Ⅰ incision surgery were monitored,with 1 647 cases experienced surgical site infection,and the prevalence rate of surgical site infection was 0.71%.The number of patients who should undergo pathogen de-tection(patients receiving therapeutic and therapeutic combined prophylactic antimicrobial agents)was 715 179,while the actual number was 480 492,with a pathogen detection rate of 67.18%.425 225 patients received patho-genic detection before treatment,with a detection rate of 59.46%.Conclusion The overall HAI prevalence in Chi-na is lower,showing disparities among medical institutions of different regions and scales.Therefore,precise imple-mentation of measures is necessary for HAI prevention and control,with a focus on high-risk institutions and high-risk departments,key areas,and critical procedures.All levels of medical institutions should continuously reduce the incidence of HAI by strengthening monitoring,standardizing the use of antimicrobial agents,and reinforcing basic HAI prevention and control measures.
7.Cross-sectional survey of healthcare-associated infection in 5 736 medical institutions across China in 2024
Cui ZENG ; Wuqiang GAO ; Fu QIAO ; Hui ZHAO ; Xu FANG ; Linping LI ; Xiuwen CHEN ; Jiansen CHEN ; Dan LI ; Yuan ZHOU ; Lingli YU ; Qinglan MENG ; Xia MOU ; Lijuan XIONG ; Weiguang LI ; Ding LIU ; Jiaqing XIAO ; Limei OU ; Baozhen LI ; Jun YIN ; Haojun ZHANG ; Qiang FU ; Qun LU ; Biao WU ; Ya-wei XING ; Shumei SUN ; Shuncai WANG ; Longmin DU ; Jingping ZHANG ; Wen-ying HE ; Gui CHENG ; Nan REN ; Xun HUANG ; Anhua WU
Chinese Journal of Infection Control 2025;24(11):1572-1583
Objective To understand the current situation of healthcare-associated infection(HAI)in China,pro-vide data support and decision-making basis for formulating scientific and effective strategies for HAI prevention and control.Methods A nationwide cross-sectional survey on HAI was conducted among various types and levels of medical institutions in China according to a unified protocol of bedside surveys and case investigations.Results In 2024,a total of 5 736 medical institutions and 2 751 765 patients were surveyed.Among them,34 889 HAI cases were identified,with a prevalence rate of 1.27%.The number of HAI episodes was 38 032,and case prevalence rate was 1.38%.The prevalence rate of HAI in medical institutions in different regions of China ranged from 0.66%to 2.35%.Among medical institutions of different scales,those with a bed capacity of ≥900 had the high-est incidence of HAI,reaching 1.65%.The most common infection site was the lower respiratory tract(44.66%),followed by the urinary tract(12.94%),surgical site(9.32%),upper respiratory tract(7.02%),and bloodstream infection(5.78%).The top 3 departments with the highest HAI rates were the general intensive care unit(10.02%),department of neurosurgery(5.51%),and department(group)of hematology(5.34%).A total of 23 238 strains of HAI pathogens were detected,with 10 714 strains(46.10%)from lower respiratory tract speci-mens.The top 5 detected strains were Klebsiella pneumoniae(14.76%),Pseudomonas aeruginosa(13.33%),Escherichia coli(12.79%),Acinetobacter baumannii(9.23%),and Staphylococcus aureus(7.88%).231 944 pa-tients underwent class Ⅰ incision surgery were monitored,with 1 647 cases experienced surgical site infection,and the prevalence rate of surgical site infection was 0.71%.The number of patients who should undergo pathogen de-tection(patients receiving therapeutic and therapeutic combined prophylactic antimicrobial agents)was 715 179,while the actual number was 480 492,with a pathogen detection rate of 67.18%.425 225 patients received patho-genic detection before treatment,with a detection rate of 59.46%.Conclusion The overall HAI prevalence in Chi-na is lower,showing disparities among medical institutions of different regions and scales.Therefore,precise imple-mentation of measures is necessary for HAI prevention and control,with a focus on high-risk institutions and high-risk departments,key areas,and critical procedures.All levels of medical institutions should continuously reduce the incidence of HAI by strengthening monitoring,standardizing the use of antimicrobial agents,and reinforcing basic HAI prevention and control measures.
8. Ligustilide delays senescence of auditory cortex in mice by inhibiting ferritinophagy
Ying-Dong ZHOU ; Meng-Xian ZHANG ; Qing-Ling WANG ; Hao-Ran KANG ; Zhi-Cheng ZHANG ; Xiang-Dong GUO ; Qing-Lin WANG ; Ya-Min LIU
Chinese Pharmacological Bulletin 2024;40(3):455-461
Aim To investigate the mechanism of ligu aged 2 months of the same strain were used as the constilide (LIG) in delaying the senescence of auditory trol (Ctrl) group. Auditory brainstem response test was cortex and treating central presbycusis. Methods used to detect the auditory threshold of mice before and Forty C57BL/6J mice aged 13 months were randomly di after treatment. Levels of serum MDA and activity of vided into ligustilide low-dose(L-LIG) group, ligustil serum SOD were detected to display the level of oxidative ide medium-dose (M-LIG) group, ligustilide high-dose stress. The pathological changes of auditory cortex were (H-LIG) group and aging (Age) group, and 10 mice observed by HE staining. Ferroptosis was observed by
9.Artificial intelligence predicts direct-acting antivirals failure among hepatitis C virus patients: A nationwide hepatitis C virus registry program
Ming-Ying LU ; Chung-Feng HUANG ; Chao-Hung HUNG ; Chi‐Ming TAI ; Lein-Ray MO ; Hsing-Tao KUO ; Kuo-Chih TSENG ; Ching-Chu LO ; Ming-Jong BAIR ; Szu-Jen WANG ; Jee-Fu HUANG ; Ming-Lun YEH ; Chun-Ting CHEN ; Ming-Chang TSAI ; Chien-Wei HUANG ; Pei-Lun LEE ; Tzeng-Hue YANG ; Yi-Hsiang HUANG ; Lee-Won CHONG ; Chien-Lin CHEN ; Chi-Chieh YANG ; Sheng‐Shun YANG ; Pin-Nan CHENG ; Tsai-Yuan HSIEH ; Jui-Ting HU ; Wen-Chih WU ; Chien-Yu CHENG ; Guei-Ying CHEN ; Guo-Xiong ZHOU ; Wei-Lun TSAI ; Chien-Neng KAO ; Chih-Lang LIN ; Chia-Chi WANG ; Ta-Ya LIN ; Chih‐Lin LIN ; Wei-Wen SU ; Tzong-Hsi LEE ; Te-Sheng CHANG ; Chun-Jen LIU ; Chia-Yen DAI ; Jia-Horng KAO ; Han-Chieh LIN ; Wan-Long CHUANG ; Cheng-Yuan PENG ; Chun-Wei- TSAI ; Chi-Yi CHEN ; Ming-Lung YU ;
Clinical and Molecular Hepatology 2024;30(1):64-79
Background/Aims:
Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy.
Methods:
We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment.
Results:
The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset.
Conclusions
Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.
10.Chemical consitituents and hypoglycemic activity of Sophora tonkinensis
Xiao-yun YAN ; Ling-feng QIN ; Rui ZHANG ; Ya-nan YANG ; Jin-ying TIAN ; Fei YE ; Xu ZHANG ; Pei-cheng ZHANG ; Guo-cheng WANG
Acta Pharmaceutica Sinica 2024;59(11):3135-3140
Eleven compounds were isolated from the ethyl acetate fraction of the 95% aqueous ethanol extract of the roots of

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