ObjectiveTo investigate the mechanism by which Jianpi Xiao'ai prescription （JPXAP） inhibits colorectal cancer progression by regulating the inducible nitric oxide synthase-arginase 1 （iNOS-ARG1） metabolic axis and inducing mitochondrial reactive oxygen species （mito-ROS）-mediated mitochondrial structural and functional impairment. MethodsAn arginine metabolism disorder model of human colorectal cancer HCT116 cells was established by combined treatment with recombinant human interferon-γ （IFN-γ， 10 μg·L^-1） and N（ω）-hydroxy-L-arginine （Nor-NOHA， 200 μmol·L^-1） for 24 h， followed by intervention with 5%， 10%， or 20% JPXAP-containing serum. Cell proliferation was assessed using cell counting kit-8 （CCK-8）， 5-ethynyl-2′-deoxyuridine （EdU） staining， and colony formation assays. Cell invasion and migration were evaluated using Transwell chamber and wound healing assays. Mitochondrial membrane potential （MMP） and ROS levels were assessed by JC-1 and MitoSOX staining， respectively. Mitochondrial ultrastructure was observed by transmission electron microscopy （TEM）. The expression of iNOS， ARG1， and mitochondrial dynamics-related proteins， including mitofusin 2 （MFN2） and dynamin-related protein 1 （DRP1）， was analyzed by Western blot and immunofluorescence. The levels of L-arginine， citrulline， and urea were determined by colorimetric methods and enzyme-linked immunosorbent assay （ELISA）. ResultsCompared with the blank group， the model group exhibited significantly upregulated iNOS expression， downregulated ARG1 expression， a decreased ARG1/iNOS ratio， reduced L-arginine and urea levels， and increased citrulline levels （P<0.05）. Meanwhile， mito-ROS accumulation was significantly increased， the JC-1 red/green fluorescence ratio was decreased， and mitochondria showed swelling and cristae disruption， indicating that metabolic disorder induced mitochondrial injury. Compared with the model group， all JPXAP-treated groups further decreased the ARG1/iNOS ratio， enhanced nitric oxide （NO） and reactive nitrogen species accumulation， further reduced L-arginine and urea levels， and increased citrulline levels （P<0.01）. EdU-positive rate， colony formation rate， wound healing rate， and Transwell invasion number all decreased significantly with increasing serum concentration （P<0.01）. Mito-ROS levels were further elevated， and the JC-1 red/green ratio further decreased. TEM revealed aggravated mitochondrial swelling and vacuolization. MFN2 expression was downregulated and DRP1 expression was upregulated （P<0.01），in a dose-dependent manner. ConclusionJPXAP further activates NO-mediated oxidative/nitrosative stress under arginine metabolism imbalance， inducing mito-ROS accumulation， MMP collapse， and mitochondrial dynamics imbalance， thereby inhibiting colorectal cancer cell proliferation and migration. These findings reveal an antitumor mechanism of JPXAP based on coordinated targeting of the "metabolism-mitochondria" axis.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Progressive pulmonary fibrosis (PPF) is a progressive and lethal condition with few effective treatment options. Improvements in quality of life for patients with PPF remain limited even while receiving treatment with approved antifibrotic drugs. Traditional Chinese medicine (TCM) has the potential to improve cough, dyspnea and fatigue symptoms of patients with PPF. TCM treatments are typically diverse and individualized, requiring urgent development of efficient and precise design strategies to identify effective treatment options. We designed an innovative Bayesian adaptive two-stage trial, hoping to provide new ideas for the rapid evaluation of the effectiveness of TCM in PPF. An open-label, two-stage, adaptive Bayesian randomized controlled trial will be conducted in China. Based on Bayesian methods, the trial will employ response-adaptive randomization to allocate patients to study groups based on data collected over the course of the trial. The adaptive Bayesian trial design will employ a Bayesian hierarchical model with "stopping" and "continuation" criteria once a predetermined posterior probability of superiority or futility and a decision threshold are reached. The trial can be implemented more efficiently by sharing the master protocol and organizational management mechanisms of the sub-trial we have implemented. The primary patient-reported outcome is a change in the Leicester Cough Questionnaire score, reflecting an improvement in cough-specific quality of life. The adaptive Bayesian trial design may be a promising method to facilitate the rapid clinical evaluation of TCM effectiveness for PPF, and will provide an example for how to evaluate TCM effectiveness in rare and refractory diseases. However, due to the complexity of the trial implementation, sufficient simulation analysis by professional statistical analysts is required to construct a Bayesian response-adaptive randomization procedure for timely response. Moreover, detailed standard operating procedures need to be developed to ensure the feasibility of the trial implementation. Please cite this article as: Zhang C, Nie YS, Zhang CT, Yang HJ, Zhang HR, Xiao W, Cui GF, Li J, Li SJ, Huang QS, Yan SY. An adaptive Bayesian randomized controlled trial of traditional Chinese medicine in progressive pulmonary fibrosis: Rationale and study design. J Integr Med. 2025; 23(2): 138-145.
Female ; Humans ; Male ; Bayes Theorem ; Disease Progression ; Drugs, Chinese Herbal/therapeutic use* ; Medicine, Chinese Traditional/methods* ; Pulmonary Fibrosis/therapy* ; Quality of Life ; Randomized Controlled Trials as Topic ; Research Design ; Adaptive Clinical Trials as Topic

OBJECTIVE: This study examines the sequential mediating roles of body pain and self-reported health in the association between sleep duration and self-reported life satisfaction among elderly Chinese adults. METHODS: Data from the fifth wave of the China Health and Retirement Longitudinal Survey (CHARLS) were used to analyse the relationships between sleep duration and body pain, self-reported health, and life satisfaction through logistic regression and Restricted Cubic Spline (RCS) analyses. The sequential mediation effects of body pain and self-reported health status were examined via chain mediation analysis. RESULTS: Logistic regression analysis showed that sleeping fewer than 6 hours or 6-7 hours was linked to higher risks of body pain, poor health, and dissatisfaction with life compared to sleeping 7-8 hours (all P < 0.05). Additionally, those sleeping more than 9 hours also had increased risks of poor health and dissatisfaction with life compared to those sleeping 7-8 hours (all P < 0.05). Chain mediation analysis showed that body pain and self-reported health status sequentially mediated 46.15% of the association between sleep duration and life satisfaction. CONCLUSION Body pain and self-reported health may shape the relationship between sleep duration and life satisfaction in elderly Chinese adults.
Humans ; Male ; Female ; Aged ; Personal Satisfaction ; Sleep ; Health Status ; Self Report ; China ; Middle Aged ; Longitudinal Studies ; Pain/psychology* ; Sleep Duration

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.

Objective:To evaluate the clinical utility of left atrial strain parameters and left atrioventricular global longitudinal strain（LAVGLS）in detecting cardiovascular immune-related adverse events（CV-irAEs）among non-small cell lung cancer patients receiving immune checkpoint inhibitors（ICIs）.Methods:A total of 68 patients with non-small cell lung cancer were prospectively enrolled in Tianjin Medical University Cancer Institute and Hospital from October 2023 to October 2024. All patients were treated with ICIs for 6 cycles. Electrocardiogram，cardiac serological markers and echocardiography were examined before medication（T0 stage），4 cycles after medication（T1 stage）and 6 cycles after medication（T2 stage），respectively. According to the guidelines of the American Society of Clinical Oncology，all patients were divided into the CV-irAEs group（ n=14）and the No-CV-irAEs group（ n=54）. AFI software and 4D Auto LAQ software were used to calculate LVGLS，left atrial reservoir longitudinal strain（LASr），LAVGLS and a series of left atrial parameters. Cox proportional hazards regression model was applied to find the risk factors for the occurrence of CV-irAEs. ROC curve was applied to analyze the diagnostic efficiency of these parameters for CV-irAEs. Results:Fourteen patients（20.6%）developed CV-irAEs after T2 stage. After ICIs treatment，LVGLS，LASr and LAVGLS decreased in both groups，LVGLS，LASr and LAVGLS decreased more significantly in the CV-irAEs group than those in the No-CV-irAEs group（ P=0.038，0.047，0.005）. Left ventricular ejection fraction（LVEF）decreased in the CV-irAEs group at the same time（ P=0.003）. Cox multivariate analysis showed that ΔLAVGLS（the difference between stage T0 and stage T2）was a risk factor for CV-irAEs（ HR：1.395， P=0.019）. ROC curve analysis showed the area under the curve of LVGLS，LASr，LAVGLS，ΔLVGLS，ΔLASr，ΔLAVGLS，and LVEF at the T2 stage for diagnosis of CV-irAEs were 0.68，0.67，0.75，0.79，0.73，0.82，and 0.72，respectively. Conclusions:Decline of LAVGLS is a risk factor for CV-irAEs in patients with non-small cell lung cancer receiving ICIs and can be used for early detection of CV-irAEs. LASr has potential diagnostic value for CV-irAEs，but it is less valuable than LVGLS and LAVGLS.

Objective To propose a dynamic early warning model based on machine learning methods and validate its predi-ctive efficacy so as to achieve precise assessment and early warning of mortality risk in patients with traumatic hypothermia.Methods Firstly,a total of 480 patients who met inclusion criteria were retrospectively selected from the eICU database and randomly divided into training and test sets at an 8∶2 ratio.Secondly,physiological parameters were extracted from these patients,and five machine learning algorithms including XGBoost,AdaBoost,LightGBM,logistic regression(LR)and random forest(RF)were employed respectively to develop dynamic mortality risk warning models for traumatic hypothermia patients,utilizing a 1-hour observation window.Thirdly,receiver operating characteristic curves(ROC)were plotted using the test set data and the effects of different warning windows on the model performance were analyzed by calculating the AUC.Finally,the interpretability of the models was analyzed using the SHapley Additive exPlanations(SHAP)algorithm to elucidate the contribution of each feature to predictive performance.Results The optimal warning window for the dynamic warning model constructed using the eICU database was 12 hours,and in case of 12-hour warning window the logistic regression model achieved the highest AUC of 0.935 and showed optimal predictive performance.The results of the interpretability analysis by the SHAP algorithm showed that body temperature was the feature that had the greatest impact on the model results,and its reduction was positively correlated with the increased risk of death.Conclusion The machine learning-based dynamic warning model for mortality risk in traumatic hypothermia patients enables real-time dynamic risk assessment,providing robust support for clinicians to identify the patient's condition changes at an early stage and references for the adjustment of clinical treatment programs.[Chinese Medical Equipment Journal,2025,46(3):9-14]

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.

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.

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.