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.

Objective:To evaluate the clinical outcomes of combined complete preservation of chordal structure mitral valve replacement (C-MVR) with total anatomical arterial myocardial revascularization (TACR) in coronary patients with moderate-to-severe or severe ischemic mitral regurgitation (IMR).Methods:This is a retrospective multi-center case series study. Data were retrospectively collected from 127 patients with coronary artery disease with moderate to severe or severe IMR who received TACR with C-MVR from July 2015 to April 2024 in 13 hospitals in China. There were 90 males and 37 females, aged (56.5±10.7) years (range: 33 to 74 years). Perioperative data and follow-up data including left ventricular ejection fraction, left ventricular end-diastolic diameter, and patency rate of arterial grafts of patients were collected. Comparisons were made using paired sample t-test or χ2 test. Results:In this cohort of 127 patients, 67 underwent concurrent tricuspid valve repair. During surgery, 113 grafts of the left internal mammary artery (LIMA), 127 grafts of the left radial artery, 80 grafts of the right radial artery, and 110 grafts of the right internal mammary artery (RIMA) were harvested. The number of the distal anastomosis was 4.2±0.4 (range: 3 to 5). The aortic cross-clamp time and cardiopulmonary bypass time were (97.5±23.4) minutes (range: 90 to 161 minutes) and (145.4±19.2) minutes (range: 101 to 210 minutes), respectively. There was one operative death. Intraoperative placement of an intra-aortic balloon pump was performed in 21 patients to improve the left ventricular ejection. No sternal ischemic occurred. All patients completed follow-up, with a mean follow-up period of (64.3±7.5) months (range: 4 to 110 months). No major cerebrovascular events occurred during the follow-up period, and all patients survived. Left ventricular ejection fraction improved postoperatively (55.0%±5.3% vs. 41.0%±15.3%, t=17.23, P<0.01). The proportion of patients with New York Heart Association functional class ≤2 increased postoperatively (23.6% (30/127) vs. 87.3% (110/126), χ2=103.77, P<0.01). The proportion of patients with Canadian Cardiovascular Society Angina Classification ≤3 decreased postoperatively (4.8% (6/126) vs. 78.7% (100/127), χ2=142.19, P<0.01). The left ventricular end-diastolic diameter decreased postoperatively ((5.70±4.50) cm vs. (6.10±0.23) cm, t=12.15, P<0.01). Coronary multi-detector computed tomography angiography (MDCTA) follow-up was conducted for (60.5±11.7) months (range: 6 to 109 months) postoperatively. MDCTA confirmed the patency rates of the grafts: 96.4% (108/112) for the LIMA grafts, 88.9% (112/126) for the left radial artery grafts, 93.7% (74/79) for the right radial artery grafts, and 90.9% (100/110) for the free RIMA grafts. No significant differences in graft patency rates were observed between the arterial grafts ( χ2=5.24, P=0.155). Conclusion:The results of this multi-centre study demonstrate satisfactory mid-term results of C-MVR with TACR for the treatment of coronary artery disease with moderate to severe or severe IMR.

Objective:To evaluate the clinical outcomes of combined complete preservation of chordal structure mitral valve replacement (C-MVR) with total anatomical arterial myocardial revascularization (TACR) in coronary patients with moderate-to-severe or severe ischemic mitral regurgitation (IMR).Methods:This is a retrospective multi-center case series study. Data were retrospectively collected from 127 patients with coronary artery disease with moderate to severe or severe IMR who received TACR with C-MVR from July 2015 to April 2024 in 13 hospitals in China. There were 90 males and 37 females, aged (56.5±10.7) years (range: 33 to 74 years). Perioperative data and follow-up data including left ventricular ejection fraction, left ventricular end-diastolic diameter, and patency rate of arterial grafts of patients were collected. Comparisons were made using paired sample t-test or χ2 test. Results:In this cohort of 127 patients, 67 underwent concurrent tricuspid valve repair. During surgery, 113 grafts of the left internal mammary artery (LIMA), 127 grafts of the left radial artery, 80 grafts of the right radial artery, and 110 grafts of the right internal mammary artery (RIMA) were harvested. The number of the distal anastomosis was 4.2±0.4 (range: 3 to 5). The aortic cross-clamp time and cardiopulmonary bypass time were (97.5±23.4) minutes (range: 90 to 161 minutes) and (145.4±19.2) minutes (range: 101 to 210 minutes), respectively. There was one operative death. Intraoperative placement of an intra-aortic balloon pump was performed in 21 patients to improve the left ventricular ejection. No sternal ischemic occurred. All patients completed follow-up, with a mean follow-up period of (64.3±7.5) months (range: 4 to 110 months). No major cerebrovascular events occurred during the follow-up period, and all patients survived. Left ventricular ejection fraction improved postoperatively (55.0%±5.3% vs. 41.0%±15.3%, t=17.23, P<0.01). The proportion of patients with New York Heart Association functional class ≤2 increased postoperatively (23.6% (30/127) vs. 87.3% (110/126), χ2=103.77, P<0.01). The proportion of patients with Canadian Cardiovascular Society Angina Classification ≤3 decreased postoperatively (4.8% (6/126) vs. 78.7% (100/127), χ2=142.19, P<0.01). The left ventricular end-diastolic diameter decreased postoperatively ((5.70±4.50) cm vs. (6.10±0.23) cm, t=12.15, P<0.01). Coronary multi-detector computed tomography angiography (MDCTA) follow-up was conducted for (60.5±11.7) months (range: 6 to 109 months) postoperatively. MDCTA confirmed the patency rates of the grafts: 96.4% (108/112) for the LIMA grafts, 88.9% (112/126) for the left radial artery grafts, 93.7% (74/79) for the right radial artery grafts, and 90.9% (100/110) for the free RIMA grafts. No significant differences in graft patency rates were observed between the arterial grafts ( χ2=5.24, P=0.155). Conclusion:The results of this multi-centre study demonstrate satisfactory mid-term results of C-MVR with TACR for the treatment of coronary artery disease with moderate to severe or severe IMR.

OBJECTIVE To study the safety of Shuangshu decoction in rats and its efficacy in improving functional dyspepsia （FD） in rats. METHODS In safety test， 40 rats were divided into blank control group， Shuangshu decoction low-dose， medium- dose and high-dose groups [108， 216， 324 g/（kg·d）， calculated by raw medicine， the same applies below]； they were given relevant medicine intragastrically， for continuous 14 days. The mortality and toxic reactions of rats were recorded， and the organ indexes of the liver， kidney， spleen， lung and heart of rats were calculated； the pathological morphological changes in the liver， kidney， spleen， lung， heart， stomach， duodenum， and colon were observed to evaluate the acute toxicity of Shuangshu decoction. Another 40 rats were grouped and administered in the same way for 30 consecutive days. The mortality and toxic reactions of the rats were recorded， and the corresponding organ indexes were calculated. The pathological morphological changes in the corresponding organs were observed， and blood routine and serum biochemical indicators were measured， in order to assess the subacute toxicity of Shuangshu decoction. In pharmacodynamic experiments: 50 rats were divided into blank control group， model group， and Shuangshu decoction low-， medium-， and high-dose groups （9.45， 18.9， 37.8 g/kg）， with 10 rats in each group. Except for blank control group， rats in all other groups were used to establish the FD rat model by subcutaneous injection of loperamide （3.5 mg/kg）. Rats in each group were administered the corresponding drug solution/normal saline intragastrically， once a day， for 14 consecutive days. After the last medication， fecal moisture content， intestinal propulsion rate， gastric emptying rate and serum level of motilin were all detected， and interstitial cell of Cajal （ICC） ultrastructure of rats was observed in colon tissue. RESULTS The safety experiments showed that no death occurred in each dose group， and no significant difference was found in organ coefficient， routine blood and serum biological index， compared to blank control group （P＞0.05）； no abnormality was found in organ appearance and pathological sections. The results of the pharmacodynamic experiments showed that， compared with the blank control group， the fecal moisture content， gastric emptying rate， intestinal propulsion rate， and serum motilin levels in the model group were significantly decreased （P＜0.05）； in the colonic tissue， the mitochondria in the ICC exhibited severe swelling with the disappearance of cristae， and the endoplasmic reticulum was dilated. Compared with model group， the rats in Shuangshu decoction high-dose group showed significant increases in the above quantitative indicators （P＜ 0.05）； additionally， there was a large number of mitochondria in the ICC of the colonic tissue， with clear cristae and regular arrangement. CONCLUSIONS Shuangshu decoction is safe and has a beneficial improving effect on FD rats； its mechanism of action may be related to the regulation of gastrointestinal hormone expression to promote gastric emptying and intestinal propulsion， as well as the repair of mitochondrial structure in ICCs to restore gastrointestinal function.

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.

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.

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.

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.

ObjectiveTraditional Chinese medicine (TCM) constitutes a valuable cultural heritage and an important source of antitumor compounds. Poria (Poria cocos (Schw.) Wolf), the dried sclerotium of a polyporaceae fungus, was first documented in Shennong’s Classic of Materia Medica and has been used therapeutically and dietarily in China for millennia. Traditionally recognized for its diuretic, spleen-tonifying, and sedative properties, modern pharmacological studies confirm that Poria exhibits antioxidant, anti-inflammatory, antibacterial, and antitumor activities. Pachymic acid (PA; a triterpenoid with the chemical structure 3β-acetyloxy-16α-hydroxy-lanosta-8,24(31)-dien-21-oic acid), isolated from Poria, is a principal bioactive constituent. Emerging evidence indicates PA exerts antitumor effects through multiple mechanisms, though these remain incompletely characterized. Neuroblastoma (NB), a highly malignant pediatric extracranial solid tumor accounting for 15% of childhood cancer deaths, urgently requires safer therapeutics due to the limitations of current treatments. Although PA shows multi-mechanistic antitumor potential, its efficacy against NB remains uncharacterized. This study systematically investigated the potential molecular targets and mechanisms underlying the anti-NB effects of PA by integrating network pharmacology-based target prediction with experimental validation of multi-target interactions through molecular docking, dynamic simulations, and in vitro assays, aimed to establish a novel perspective on PA’s antitumor activity and explore its potential clinical implications for NB treatment by integrating computational predictions with biological assays. MethodsThis study employed network pharmacology to identify potential targets of PA in NB, followed by validation using molecular docking, molecular dynamics (MD) simulations, MM/PBSA free energy analysis, RT-qPCR and Western blot experiments. Network pharmacology analysis included target screening via TCMSP, GeneCards, DisGeNET, SwissTargetPrediction, SuperPred, and PharmMapper. Subsequently, potential targets were predicted by intersecting the results from these databases via Venn analysis. Following target prediction, topological analysis was performed to identify key targets using Cytoscape software. Molecular docking was conducted using AutoDock Vina, with the binding pocket defined based on crystal structures. MD simulations were performed for 100 ns using GROMACS, and RMSD, RMSF, SASA, and hydrogen bonding dynamics were analyzed. MM/PBSA calculations were carried out to estimate the binding free energy of each protein-ligand complex. In vitro validation included RT-qPCR and Western blot, with GAPDH used as an internal control. ResultsThe CCK-8 assay demonstrated a concentration-dependent inhibitory effect of PA on NB cell viability. GO analysis suggested that the anti-NB activity of PA might involve cellular response to chemical stress, vesicle lumen, and protein tyrosine kinase activity. KEGG pathway enrichment analysis suggested that the anti-NB activity of PA might involve the PI3K/AKT, MAPK, and Ras signaling pathways. Molecular docking and MD simulations revealed stable binding interactions between PA and the core target proteins AKT1, EGFR, SRC, and HSP90AA1. RT-qPCR and Western blot analyses further confirmed that PA treatment significantly decreased the mRNA and protein expression of AKT1, EGFR, and SRC while increasing the HSP90AA1 mRNA and protein levels. ConclusionIt was suggested that PA may exert its anti-NB effects by inhibiting AKT1, EGFR, and SRC expression, potentially modulating the PI3K/AKT signaling pathway. These findings provide crucial evidence supporting PA’s development as a therapeutic candidate for NB.

Objective: To understand the incidence risk and risk factors of tuberculosis (TB) among middle school students in Chongqing, so as to provide a basis for formulating TB prevention and control strategies. Methods: From September to December 2022, 32 181 middle school students were selected as the study cohort from 15 administrative districts in Chongqing by using the stratified cluster random sampling method. All cohort members were screened with the tuberculin skin test (TST), and relevant information was collected from January 1, 2023 to December 31, 2024. On the basis of active screening, the follow up data of the participants were compared with the National Tuberculosis Management Information System to obtain the incidence status of the study subjects. The Log rank test was used to compare the TB incidence rates among students with different characteristics, and a Cox proportional hazards model was established to analyze the incidence risk and risk factors of TB. Results: The TST screening rate of the cohort members was 93.0%. During the 2 year follow up period, a total of 36 TB cases occurred, with a cumulative incidence rate of 111.87/100 000 and an incidence density of 55.95/100 000. Among them, the cumulative incidence rate of students from public schools (170.44/ 100 000 ) was higher than that of students from private schools (41.16/100 000), the cumulative incidence rate of students in schools located in high epidemic areas (153.95/100 000) was higher than that in medium epidemic areas (69.00/100 000), and the difference was statistically significant ( χ 2=11.49, 4.73, both P <0.05). The Log-rank test for different TST results showed that the difference in TB comulative incidence rate between students with strongly positive TST results (216.55/ 100 000 ) and those with negative TST results (81.40/100 000) was statistically significant ( χ 2=5.85, P <0.05). Univariate analysis using the Cox proportional hazards model revealed that the risk of TB was lower in students from private schools ( HR=0.25, 95% CI = 0.10-0.59) and students in medium epidemic areas ( HR=0.46, 95%CI =0.23-0.94); whereas the risk of TB was increased in students with strongly positive TST results ( HR=1.39, 95%CI =1.05-1.84) (all P <0.05). Multivariate Cox regression analysis showed that the risk of TB in students from private schools was lower than that of students from public schools ( HR=0.23, 95%CI=0.08-0.62, P <0.05). Conclusions The annual average incidence rate of TB among middle school students in Chongqing is at a relatively high level. It is necessary to strengthen the management and intervention for student groups, including those in public schools, those in schools located in high epidemic areas, and those with strongly positive TST results, so as to reduce the incidence rate of TB.