1.Harnessing Machine Learning for Personalized Care of Patients With Idiopathic Sudden Sensorineural Hearing Loss: A Multicenter Cohort Study
Yen-Ting GUO ; Ching-Ting TAN ; Chen-Chi WU ; Chun-Ying WANG ; Chein-Yu HUANG ; Tzu-Hsiang YANG ; Ting-Yi LEE ; Ting-Hua YANG ; Tien-Chen LIU ; Pey-Yu CHEN ; Pei-Hsuan LIN
Clinical and Experimental Otorhinolaryngology 2026;19(2):194-204
Objectives:
. Idiopathic sudden sensorineural hearing loss (ISSNHL) is a significant cause of hearing loss. Intratympanic steroid injection (ITSI) is commonly used as an initial or salvage treatment; however, the lack of a standardized treatment protocol has resulted in variability in clinical practice. In addition, no efficient prediction model currently exists to support personalized management. Therefore, this study aimed to develop tailored management strategies for ISSNHL using a machine-learning model.
Methods:
. This retrospective multicenter cohort study was conducted between January 2015 and December 2020, with data analysis performed between January 2021 and March 2024. Patients were selected based on the International Classification of Diseases, 10th Revision criteria for ISSNHL, along with relevant medication and procedure codes. Patients with pure-tone audiogram results not meeting ISSNHL criteria, better initial hearing in the affected ear, an identifiable etiology, no post-treatment audiogram, or delayed treatment (>6 weeks) were excluded. We included 770 patients diagnosed with ISSNHL who received ITSI. The primary outcome was the area under the receiver operating characteristic curve for prediction performance. Recovery status was determined using the last pure-tone audiogram. Modeling was conducted on the Quanta for Medical Care AI platform using five machine-learning algorithms and a nested cross-validation framework, in which feature selection and hyperparameter tuning were performed in the inner folds and model performance was evaluated in the outer folds.
Results:
. A random forest classifier outperformed the other models in predicting hearing outcomes, achieving an area under the receiver operating characteristic curve of 0.788. Time to ITSI was the most influential treatment-related factor, with ITSI administered within 10 days of hearing loss being associated with better outcomes. This model can be used to provide personalized prognostic estimates under different treatment protocols.
Conclusion
. The machine-learning-based prediction model facilitates personalized treatment strategies and timely treatment adjustments for ISSNHL, thereby optimizing the likelihood of complete recovery.
2.Divergent Small Vessel Disease Burden in Warfarin-Associated and Direct Oral Anticoagulant-Associated Intracerebral Hemorrhage
Sung-Chun TANG ; Ya-Fang CHEN ; Chih-Hao CHEN ; Ching-Hua KUO ; Yuan-Chang CHAO ; Yu-Fong PENG ; Shu-Wen LIN ; Shin-Yi LIN ; Jiann-Shing JENG
Journal of Stroke 2026;28(2):334-338
3.Changing antimicrobial resistance profiles of Burkholderia cepacia in hospitals across China:results from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Chunyue GE ; Yunjian HU ; Xiaoman AI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Hui LI ; 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 ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; 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 ; 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(5):557-562
Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1%(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5%,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3%(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1%)were isolated from sputum and respiratory secretions,followed by urine(10.7%)and blood samples(8.1%).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1%.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4%in the patients<18 years old to 20.6%in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.
4.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.
5.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.
6.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.
7.Study on mechanism of stigmasterol inhibiting hepatocellular carcinoma based on TLR4/MyD88/NF-κB signaling pathway
Chinese Pharmacological Bulletin 2025;41(5):867-873
Aim To utilize molecular docking and in vitro experiments to investigate the regulatory mecha-nism of stigmasterol on the TLR4/MyD88/NF-κB sig-naling pathway in hepatocellular carcinoma.Methods Molecular docking was performed using AutoDock to study the binding affinity of stigmasterol with TLR4,MyD88,and NF-κB.The effects on cell proliferation and migration were assessed through CCK-8,wound healing assays,and Transwell experiments,while colony formation ability was measured using a colony formation assay.Flow cytometry was employed to examine apop-tosis and cell cycle.Western blot analysis was used to evaluate the expression levels of TLR4,MyD88,and NF-κB proteins after stigmasterol treatment.Results Molecular docking indicated that stigmasterol exhibited favorable binding conformations with TLR4,MyD88,and NF-κB.In vitro,stigmasterol demonstrated inhibi-tory effects on proliferation,migration,invasion,and colony formation in hepatocellular carcinoma cells.Ad-ditionally,it promoted apoptosis,inhibited cell cycle progression,and reduced protein expression of the TLR4/MyD88/NF-κB signaling pathway(P<0.05).Conclusion Stigmasterol suppresses the activity of hepatocellular carcinoma cells by modulating the TLR4/MyD88/NF-κB signaling pathway.
8.Effects of Gynura divaricate polysaccharide on gouty nephropathy induced by dry yeast combined with adenine in rats
Chun-ting ZHI ; Yu-hua WEI ; Miao ZHANG ; Zu-ding LIU ; Hua ZHU ; Li-ba XU
Chinese Traditional Patent Medicine 2025;47(4):1137-1143
AIM To study the protective effect of Gynura divaricate polysaccharide on gouty nephropathy(GN)induced by dry yeast combined with adenine in rats.METHODS Sixty male SD rats were randomly divided into the normal group,the model group,the allopurinol group(42 mg/kg),and the low-dose,medium-dose and high-dose G.divaricate polysaccharide groups(140,280,560 mg/kg).All the rats except those of the normal group were induced into GN models by intragastrical dosing of yeast(5 g/kg)and adenine(100 mg/kg)and intervened with corresponding drug administration simultaneously.After 35 days,the rats had their levels of creatinine(Cr)and uric acid(UA)in serum and urine detected and their fraction excretion of uric acid(FEUA)value determined;their kidney mass and volume measured and their levels of kidney index and density calculated;their renal pathological changes checked by HE staining;their renal GLUT9,URAT1,ABCG2 and OAT1 mRNA expressions dectected by RT-qPCR;and their renal GLUT9,URAT1,ABCG2 and OAT1 protein expressions dectected by Western blot.RESULTS Compared with the model group,each dose of G.divaricate polysaccharide group displayed decreased levels of kidney mass,kidney volume and kidney index(P<0.01);increased levels of kidney density(P<0.05,P<0.01);decreased serum levels of UA and Cr(P<0.01);increased urine levels of UA and Cr(P<0.01);increased FEUA value(P<0.01);decreased GLUT9,URAT1 mRNA and protein expressions(P<0.05,P<0.01);and increased ABCG2,OAT1 mRNA and protein expressions(P<0.05,P<0.01);and more alleviated renal histological aberrations.CONCLUSION G.divaricate polysaccharide exerts good protective effects against yeast/adenine-induced GN in rats probably through down-regulating protein expression of GLUT9,URAT1 and up-regulating ABCG2 and OAT1.
9.Effect of tetramethylpyrazine on neuroinflammation after cerebral ischemia and hypoxia based on mannose-binding lectin
Yan-zhe DUAN ; Yu-kang SUN ; Jian-lin HUA ; Chun-li WEN ; Hao TIAN ; Yi YANG ; Xiu LOU ; Cun-gen MA ; Yu-qing YAN ; Li-juan SONG
Chinese Pharmacological Bulletin 2025;41(4):668-676
Aim To investigate the effect of tetrameth-ylpyrazine(TMP)on neuroinflammation after cerebral ischemia and hypoxia via mannose-binding lectin(MBL).Methods Patients diagnosed with ischaemic stroke at Shanxi Provincial People's Hospital were in-cluded in the study,and their clinicopathological data,as well as blood and urine samples,were collected with the consent of the patients and their families.Using these biological samples,differential proteins and tar-gets were identified by proteomic analysis and subse-quently verified with animal experiments.The mice were divided into the sham,dMCAO,and TMP(10,20,40 mg·kg-1)treatment groups.After seven days of drug administration,the modified neurological sever-ity score(mNSS)was used to assess the neurological function.TTC staining was used to detect the volume of cerebral infarction.Motor function was evaluated be-haviourally,and ELISA was used to detect MASP1,sC5b-9,TNF-α,IL-6,and IL-1β.Western blot was used to determine the expression of relevant proteins,such as MBL2,MASP2,and C3.Results Compared with the sham group,the dMCAO group exhibited in-creased neurological impairment,which was signifi-cantly ameliorated by TMP treatment.The expression levels of MBL2,C3 and MASP2 were elevated in the dMCAO group and were reduced following TMP treat-ment.Additionally,the dMCAO group showed elevat-ed expression of inflammatory factors IL-1 β,IL-6 and TNF-α,which were then suppressed by TMP treat-ment.Conclusion TMP inhibits the inflammatory re-sponse after ischemia and hypoxia by regulating MBL,thus attenuating brain injury.
10.Study on mechanism of stigmasterol inhibiting hepatocellular carcinoma based on TLR4/MyD88/NF-κB signaling pathway
Chinese Pharmacological Bulletin 2025;41(5):867-873
Aim To utilize molecular docking and in vitro experiments to investigate the regulatory mecha-nism of stigmasterol on the TLR4/MyD88/NF-κB sig-naling pathway in hepatocellular carcinoma.Methods Molecular docking was performed using AutoDock to study the binding affinity of stigmasterol with TLR4,MyD88,and NF-κB.The effects on cell proliferation and migration were assessed through CCK-8,wound healing assays,and Transwell experiments,while colony formation ability was measured using a colony formation assay.Flow cytometry was employed to examine apop-tosis and cell cycle.Western blot analysis was used to evaluate the expression levels of TLR4,MyD88,and NF-κB proteins after stigmasterol treatment.Results Molecular docking indicated that stigmasterol exhibited favorable binding conformations with TLR4,MyD88,and NF-κB.In vitro,stigmasterol demonstrated inhibi-tory effects on proliferation,migration,invasion,and colony formation in hepatocellular carcinoma cells.Ad-ditionally,it promoted apoptosis,inhibited cell cycle progression,and reduced protein expression of the TLR4/MyD88/NF-κB signaling pathway(P<0.05).Conclusion Stigmasterol suppresses the activity of hepatocellular carcinoma cells by modulating the TLR4/MyD88/NF-κB signaling pathway.

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