Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

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.

BACKGROUND:Previous studies by our research group discovered that Jiawei Xiaoyao San has a significant anti-liver cancer effect,but the specific mechanism of action was unclear. OBJECTIVE:To investigate the regulatory effects of the traditional Chinese medicine formula Jiawei Xiaoyao San on the levels of miRNAs in plasma exosomes of rats with diethylnitrosamine chronically induced primary liver cancer,based on high-throughput sequencing combined with bioinformatics. METHODS:SD rats were randomly divided into a blank control group,a liver cancer model group,and a Jiawei Xiaoyao San treatment group.Liver cancer models were induced by continuous administration of diethylnitrosamine for 12 weeks.Starting from the 17th week,rats in the Jiawei Xiaoyao San treatment group were administered Jiawei Xiaoyao San once daily until the end of the 20th week,while rats in the blank control and liver cancer model groups were given an equivalent volume of saline.Anti-hepatocellular carcinoma effects were validated by assessing the morphological structure of rat liver tissues,along with the expression of the hepatocellular carcinoma markers,Glypican-3 protein and serum alpha-fetoprotein.Plasma exosomes from each group of rats were isolated using ultracentrifugation.High-throughput sequencing technology was used to screen for differentially expressed miRNAs in rat plasma exosomes.Bioinformatics was used to predict the potential biomarkers through which Jiawei Xiaoyao San exerts its anti-liver cancer effects via liver cancer-derived exosomal miRNAs,followed by functional analysis. RESULTS AND CONCLUSION:(1)Jiawei Xiaoyao San significantly improved the morphological structure of liver tissues in a rat model of liver cancer.Compared with the liver cancer model group,the expression of liver cancer markers Glypican-3 protein and serum alpha-fetoprotein was significantly reduced in the Jiawei Xiaoyao San treatment group.(2)Bioinformatics analysis showed that in the Jiawei Xiaoyao San group,upregulated miR-223-3p in the liver cancer model group had target binding sites with genes E2F1 and NCOA1,which were closely related to liver cancer survival and prognosis.Therefore,Jiawei Xiaoyao San has a therapeutic effect on liver cancer,possibly by targeting negative regulation of NCOA1/E2F1 through liver cancer plasma-derived exosomal miR-223-3p,thereby playing anti-liver cancer effect.

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 propose a novel identification algorithm based on ensemble learning for assessing the severity of acute respiratory distress syndrome(ARDS)to achieve continuous monitoring of the disease severity.Methods Firstly,leve-raging the open-source MIMIC-Ⅳ database,a variety of non-invasive physiological parameters of patients were extracted and subjected to preliminary preprocessing.A multivariate feature selection algorithm was employed to rank these parameters and calculate feature importance scores through weighted computation.Secondly,based on the feature importance scores,a subset search algorithm was utilized to identify the subset of features that could yield optimal performance across four machine learning algorithms:neural networks,logistic regression,AdaBoost and XGBoost.Finally,a soft voting ensemble method was designed using a generalized linear regression model to integrate the results of each single machine learning algorithm,and a multivariate ensemble learning algorithm was proposed by combining the optimal feature subsets.The algorithm proposed when used to identify the severity of ADRS was evaluated with MIMIC-Ⅳ database,and compared with the traditional algorithms.Results The sensitivity,specificity,accuracy and AUC of the algorithm were 87.15％,89.23％,88.34％and 0.923 4,respectively,all of which outperformed those of the traditional algorithms.Conclusion The ARDS severity identification algorithm based on ensemble learning is capable of achieving continuous and real-time monitoring of the severity of ARDS,thereby offering robust support for the early identification and warning of ARDS in patients.[Chinese Medical Equipment Journal,2025,46(2):1-9]

AIM:This study aimed to confirm the glycolytic inhibitory activity of 3-bromopyruvic acid(3BP)and to assess whether this inhibition could ameliorate hypoxia-induced pulmonary hypertension in rats.METHODS:PAH model rats were generated from normal SD rats via exposure to normal pressure and hypoxia.Intervention groups I and II(6 rats per group)were then intraperitoneally injected with 3BP(15 mg/kg),and the normal and hypoxia groups(6 rats per group)were given the same amount of normal saline for a total of 21 d.The average pulmonary artery pressure of the rats in each group was measured via right heart catheterisation,and hilar tissue measurements.The right ventricle(RV),left ventricle,and interventricular septum(LV+S)were weighed,and the ratio of RV/(LV+S)was calculated as an index of right ventricular hypertrophy.Right lower lung tissues were fixed in 4%paraformaldehyde-PBS buffer,sec-tioned in conventional paraffin(5 μm thick),stained with HE and Masson,photographed under a microscope.Then the thickness ratio of the tunica media and the area ratio of collagen fibres were calculated.The expression of pyruvate kinase isozyme type M2(PKM2),nucleotide-binding oligomerization domain-like receptor protein 3(NLRP3),and pyruvate de-hydrogenase(PDH)proteins in the hilar tissues of each group were detected by western blot,whereas interleukin-1β(IL-1β)and IL-18 contents were detected using ELISA,and lactic acid content was detected using a lactic acid kit.RE-SULTS:The results showed that 3-brpa effectively inhibited glycolysis and significantly improved hypoxia-induced pulmo-nary hypertension in rats.Compared with the hypoxia group,in intervention group II,PKM2 expression was decreased(P<0.05),PDH expression increased significantly(P<0.01),and NLRP3 expression was decreased(P<0.05).The IL-18 and IL-1β contents decreased(P<0.05 or P<0.01,respectively).Pulmonary hemodynamic indexes showed that the pro-portion of the right ventricle and the mean pressure of the pulmonary artery decreased(P<0.05 or P<0.01,respectively).The HE and Masson staining results showed that the thickness ratio of the tunica media and the area ratio of collagen fibres decreased significantly(P<0.01).Lactic acid content was significantly decreased(P<0.01).CONCLUSION:This study showed that 3BP can inhibit glycolysis and alleviate hypoxia-induced pulmonary hypertension in rats.

Objective:To explore the application effect of case-based learning (CBL) combined with interactive portrait in the internship teaching of nephrology nurses.Methods:A total of 52 nursing students who interned in the Department of Nephrology at Sichuan Provincial People's Hospital from March 2022 to February 2023 were selected as the research subjects. They were divided into an experimental group and a control group, with 26 students in each group. The experimental group received CBL combined with interactive portrait teaching method, while the control group received traditional teaching method. After the teaching, the two groups were compared in terms of their in-class quiz scores and questionnaire results. SPSS 27.0 was used for t test. Results:The experimental group showed a theoretical assessment score of (41.08±2.09) points, an operational practice assessment score of (42.42±2.04) points, and a total score of (83.50±2.63) points. The control group showed a theoretical assessment score of (37.69±2.80) points, an operational practice assessment score of (39.08±3.06) points, and a total score of (76.78±4.26) points. The experimental group outperformed the control group in all scores, and the differences were statistically significant ( P<0.05). The experimental group also scored higher than the control group in both learning evaluation and teaching evaluation questionnaires, and the differences were statistically significant ( P<0.05). Conclusions:The CBL combined with interactive portrait teaching method is conducive to improving students' comprehensive clinical ability and mastering the basic theory and clinical skills of nephrology nursing. This method is widely recognized by students and is worthy of clinical promotion.

Early screening of tumors is crucial for prevention and treatment of cancer,thus identifying effective biomarkers is of great importance for early diagnosis of tumors.In recent years,tumor-secreted exosomes(Exos)have attracted widespread attention as a novel biomarker for tumor liquid biopsy.Especially,some specific proteins contained in Exos play important roles in the occurrence,development,metastasis and microenvironment regulation of tumors,indicating their enormous potential as potential diagnostic biomarkers for tumors.Compared to traditional biopsy sample testing,exosome-based protein detection methods exhibit significant advantages in liquid biopsy,including rapid sampling,easy operation,non-invasiveness,and feasibility for early detection,holding important application value for clinical diagnosis of tumors.This review aimed to comprehensively summarize and discuss various detection strategies for exosomal proteins in liquid biopsy for tumors,while comprehensively evaluating the analytical performance of these methods.Meanwhile,new perspectives and strategies for early diagnosis and treatment of tumors were discussed.Additionally,the unique advantages of exosomal proteins as a new generation of non-invasive diagnostic biomarkers and insights into their promising prospects for future clinical applications were emphasized.

Background/Aims: Treatment indications for patients with chronic hepatitis B (CHB) remain contentious, particularly for patients with mild alanine aminotransferase (ALT) elevation. We aimed to evaluate treatment effects in this patient population. Methods: This rollover study extended a placebo-controlled trial that enrolled non-cirrhotic patients with CHB and ALT levels below two times the upper limit of normal. Following 3 years of randomized intervention with either tenofovir disoproxil fumarate (TDF) or placebo, participants were rolled over to open-label TDF for 3 years. Liver biopsies were performed before and after the treatment to evaluate histopathological changes. Virological, biochemical, and serological outcomes were also assessed (NCT02463019). Results: Of 146 enrolled patients (median age 47 years, 80.8% male), 123 completed the study with paired biopsies. Overall, the Ishak fibrosis score decreased in 74 (60.2%), remained unchanged in 32 (26.0%), and increased in 17 (13.8%) patients (p<0.0001). The Knodell necroinflammation score decreased in 58 (47.2%), remained unchanged in 29 (23.6%), and increased in 36 (29.3%) patients (p=0.0038). The proportion of patients with an Ishak score ≥ 3 significantly decreased from 26.8% (n=33) to 9.8% (n=12) (p=0.0002). Histological improvements were more pronounced in patients switching from placebo. Virological and biochemical outcomes also improved in placebo switchers and remained stable in patients who continued TDF. However, serum HBsAg levels did not change and no patient cleared HBsAg. Conclusions In CHB patients with minimally raised ALT, favorable histopathological, biochemical, and virological outcomes were observed following 3-year TDF treatment, for both treatment-naïve patients and those already on therapy.