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.

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.

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 construct a tripartite game model involving the government,the public,and the pharmaceutical industry alliance during public health emergencies,revealing the dynamic mechanisms of health-related information quality regulation and exploring effective strategies to optimize the informa-tion dissemination environment through reward-punishment mechanisms.Methods:Based on evolutionary game theory,a tripartite evolutionary game model was established,integrating strategy spaces,payoff functions,and parameter definitions for each stakeholder.The pharmaceutical industry alliance's strate-gies included publishing high-or low-quality information(α),the public's strategies encompassed ration-al analysis or passive response(β),and the government's strategies involved regulatory enforcement or inaction(γ).Key parameters,such as economic benefits(Iyy),regulatory costs(Czf),penalties(Fyy),and incentives(Pyy),were quantified to reflect real-world scenarios.Replicator dynamic equa-tions and Jacobian matrices were derived to analyze the stability of equilibrium points,while MATLAB 2016a simulations were conducted to validate the model under varying initial conditions(e.g.,Iyy=100,150,200;Pyy=0,20,35;Fyy=0,10,20).Sensitivity analyses examined the impact of critical pa-rameters on system evolution,by 50 iterative simulations to observe convergence patterns.Results:The study revealed three key findings:(1)Public rational discernment(β)significantly influenced the phar-maceutical industry's strategy.Simulations demonstrated that increasing Iqz(benefits of information acqui-sition)reduced Cqz(cognitive costs),elevating β from 0.4 to 0.8 and driving α(high-quality information probability)to stabilize at 1.(2)Government regulatory intensity(γ)correlated positively with the so-cial hazards of low-quality information.When Fyy+Pyy＞Iyy,speculative behaviors decreased,achieving equilibrium at α=1.(3)Dual stable equilibria emerged:a high-quality equilibrium(α=1,β=1,γ=0)with lower regulatory costs and a low-quality equilibrium(α=0,β=0,γ=1)associated with higher social risks.Phase diagrams illustrated path dependency,where initial α＜0.5 led to the low-quality equilibrium unless dynamic penalties(Fyy＞20)and incentives(Pyy＞30)were enforced.Conclusion:A"carrot-stick"collaborative governance framework is proposed,emphasizing categorized regulation,AI-enabled auditing,and dynamic penalty systems.Future research should integrate emotional utility func-tions to address irrational decision-making impacts,thereby enhancing the adaptability of health informa-tion regulatory systems.

Objective:To observe the effects of ear acupressure combined with acupoint application on serum inflammatory factors,pain and psychological status of children with limb fractures.Methods:By using random number table method,60 children with limb fracture who were admitted to Qiantang Campus of Zhejiang Provincial Traditional Chinese Medicine Hospital from February 2022 to August 2024 were divided into control group(received conventional treatment combined with acupoint application)and experimental group(combined with ear acupressure based on the control group),with 30 cases in each group.Pain and swelling degree of the affected limb,anxiety and depression[Screening Checklist for Childhood Anxiety Disorders(SCARED),Depression self-rating scale for children(DSRSC)],inflammatory factors[High sensitivity C-reactive protein(hs-CRP),tumor necrosis factor-α(TNF-α),interleukin-6(IL-6),interleukin-1(IL-1)]and family satisfaction rate were compared between the two groups.Results:The scores of visual analogue scale(VAS),SCARED and DSRSC in the experimental group were lower than those in the control group at 1 week and 4 weeks after treatment(P＜0.05).Swelling degree of the affected limb in the experimental group was better than that in the control group at 4 weeks after treatment(P＜0.05).hs-CRP,IL-1,IL-6 and TNF-α in the experimental group were lower than those in the control group at 4 weeks after treatment(P＜0.05).The family satisfaction rate in the experimental group was higher than that in the control group(P＜0.05).Conclusion:Ear acupressure combined with acupoint application therapy for children with limb fractures can significantly alleviate postoperative pain,promote swelling reduction,effectively reduce inflammation,and improve anxiety and depression,with high treatment satisfaction.

Objective To explore the clinical characteristics, treatment methods, and prognostic risk factors of cesarean scar endometriosis (CSE), and to provide evidence for standardized management. Methods A retrospective analysis was conducted on the clinical data of patients with postoperatively pathologically confirmed CSE who underwent primary surgical treatment at the Obstetrics and Gynecology Hospital of Fudan University from January 1, 2015, to June 30, 2024. According to the deepest tissue involved as determined during intraoperative exploration, patients were classified into three types: typeⅠ(fascia type), typeⅡ(anterior sheath muscle type), and type Ⅲ (peritoneal type). Differences in general patient characteristics among the subtypes were compared, and recurrence was followed up. Results A total of 321 patients were included, with age of (31.82±3.82) years. 95.6% patients had Pfannenstiel incision. The latent period was (34.45±26.43) months, patients younger than 35 years (P＝0.005), with lactation duration less than 6 months (P＜0.001), and with maximum lesion diameter less than 4 cm (P＝0.011) had shorter latent periods. Typical symptoms of cyclical pain with mass enlargement at the scar site were present in 84.4% of patients. Preoperative ultrasound and magnetic resonance imaging (MRI) both had a positive predictive value of 100% for CSE, but MRI was superior to ultrasound in accuracy rate of assessing lesion infiltration depth (96.9% vs 50.5%) and measuring lesion size. Patients with type Ⅲ lesions had the highest proportion with maximum lesion diameter ＞3 cm (52.8%) and requiring mesh repair (25.0%). The follow-up period was (21.3±12.6) months, and the recurrence rate was 1.82%. Younger age (P＝0.030) and multiple lesions (P＝0.048) were influencing factors for postoperative recurrence. Conclusions The latent period of CSE is correlated with age, lactation duration and lesion size. Younger patients and those with multiple lesions have a higher risk of recurrence.

Objective To develop the value of machine learning(ML)models based on contrast-transthoracic echocardiography(cTTE)and transesophageal echocardiography(TEE)combined with clinical and laboratory indicators for predicting patent foramen ovale-associated stroke(PFO-AS).Methods Totally 313 patients with PFO diagnosed with cTTE and TEE were retrospectively enrolled.Among them,65 cases were found complicated with ischemic stroke and confirmed as PFO-AS(PFO-AS group),and the rest 248 cases without ischemic stroke were classified as non-PFO-AS group.The patients were divided into training set(n=219,including 48 cases of PFO-AS and 171 cases of non-PFO-AS)and test set(n=94,including 17 cases of PFO-AS and 77 cases of non-PFO-AS)at the ratio of 7∶3.Univariable and multivariable logistic regression(LR)were used to analyze clinical and laboratory indicators as well as cTTE and TEE parameters in training set to screen independent predictive factors of PFO-AS.ML models,including LR,K-nearest neighbor(KNN),support vector machine(SVM),random forest(RF),decision tree(DT),back propagation neural network(BPNN)and gradient boosting machine(GBM)were constructed,and the predictive efficacy of the models for predicting PFO-AS was evaluated,then the optimal model was selected.Results Patient's age＞49-69 years,with smoking history,plasma albumin≥43.8 g/L,significant right-to-left shunt at rest shown on cTTE and complicated atrial septal aneurysm shown on TEE were all independent predictors of PFO-AS,which were used to construct ML models.The area under the curve(AUC)of LR,KNN,SVM,RF,DT,BPNN and GBM models in training set was 0.779-0.853,while in test set was 0.730-0.877.RF model had relatively high and comparable sensitivity,specificity and AUC in both training and test sets,also higher precision and smaller Brier score in test set,hence was regarded as the optimal ML model.Conclusion RF model based on cTTE and TEE combined with clinical and laboratory indicators could be used to effectively predict PFO-AS.

AIM To investigate the effects of Jisuishang Formula on neurological function and ferroptosis in a rat model of cervical spondylotic myelopathy(CSM).METHODS The CSM rat models were established and randomly assigned to the model group,the Fer-1 group(2 g/kg Ferrostatin-1 via intraperitoneal injection),the low-dose(9.7 g/kg,intragastrically),medium-dose(19.4 g/kg,intragastrically)and high-dose(38.8 g/kg,intragastrically)Jisuishang Formula groups,and the sham operation group,with 6 rats in each group.Following 4 weeks of treatment administration,BBB locomotor scores and oblique plate test result were recorded to assess their neurological function in rats.Histopathological evaluation utilized HE staining for spinal cord tissue pathology,Nissl staining for Nissl body visualization,and Prussian blue staining for iron ion deposition analysis.Protein expressions of Nrf2,SLC7A11,GPX4,HO-1,TFRC and Cox2 in spinal cord tissues was detected by immunofluorescence and Western blot,while mRNA expressions were quantified using RT-qPCR.RESULTS Compared to the sham group,the CSM model group exhibited significantly reduced BBB locomotor scores and inclined plane test performance at 1,2 and 4 weeks post-operation(P＜0.05);obvious tissue cavitation,cellular edema and Prussian blue positive iron deposition in spinal cord tissues;downregulated protein and mRNA expressions of Nrf2,SLC7A11,GPX4,HO-1(P＜0.05);and upregulated protein and mRNA expressions of TFRC and Cox2(P＜0.05).Compared to the model group,the Jisuishang Formula and Fer-1 intervention groups showed significantly improved BBB scores and inclined plane test result at 1,2 and 4 weeks post-operation(P＜0.05);reduced tissue cavitation,attenuated cellular edema and decreased Prussian blue positive iron deposition in spinal cord tissues;upregulated protein and mRNA expression of Nrf2,SLC7A11,GPX4 and HO-1 in spinal cord tissues(P＜0.05);and downregulated protein and mRNA expressions of TFRC and Cox2(P＜0.05).CONCLUSION Targeting the Nrf2/SLC7A11/GPX4 signaling pathway,Jisuishang Formula potentially suppresses ferroptosis and alleviates iron accumulation in spinal cord neurons,thereby improving neurological recovery in CSM rats.

Objective: To retrospectively compare the safety and efficacy of ultrasound-guided radiofrequency ablation (RFA) with parotidectomy for superficial pleomorphic adenoma (PA). Materials and Methods: From March 2022 to October 2023, 88 patients diagnosed with superficial parotid PA underwent either RFA (n = 12; mean age, 47.1 years) or parotidectomy (n = 76; mean age, 47.8 years). Patients in the RFA group were matched to those in the surgery group in a 1:1 ratio using propensity scores based on age, sex, tumor volume, diameter, location, and comorbidities. Ultrasound characteristics, cosmetic scores (0–4), numerical rating scale scores (0–10), and complications were assessed before the procedures and at 1-, 3-, and 6-month follow-ups. Outcomes were compared between baseline and follow-up in the RFA group and between the RFA and surgery groups. Results: In the RFA group, significant reductions in tumor volume were observed between baseline (median, 2.02 cm 3 ) and the 1-month follow-up (median, 1.21 cm 3 ; P = 0.015), between the 1-month and 3-month follow-ups (median, 0.53 cm 3 ; P= 0.002), and between the 3- and 6-month follow-ups (median, 0.23 cm 3 ; P = 0.003). The volume reduction ratios at 1, 3, and 6 months were 39.7%, 79.9%, and 88.0%, respectively. The cosmetic score was significantly lower at 3- and 6-month followup compared to baseline (median 1 and 1 vs. 4, P = 0.04). The numerical rating scale scores did not differ significantly from baseline throughout follow-up. In the propensity score-matched analysis (12 patients per group), RFA was associated with a shorter median procedure time (61.5 vs. 253.3 minutes; P < 0.001), shorter hospital stay (0 vs. 4 days; P < 0.001), and lower cost (1859.9 vs. 3512.4 USD; P < 0.001) than parotidectomy, with no significant difference in overall complication rates (33.3% [4/12] vs. 41.7% [5/12]; P = 1.000). Conclusion RFA may be a safe and effective alternative to surgery for superficial parotid PA, offering a shorter median procedure time, shorter hospital stay, and lower costs.

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.