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.

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.

Aim To investigate the regulatory mecha-nism of butin on the proliferation,migration,cycle blockage and pyroptosis related inflammatory factors in human fibroblast-like synoviocytes of rheumatoid arthri-tis(HFLS-RA).Methods Cell proliferation,migra-tion and invasion were studied using cell migration and invasion assays.Cell cycle was detected by flow cytom-etry,and the expression of the pyroptosis-associated in-flammatory factors IL-1β,IL-18,caspase-1 and caspase-3 was detected by ELISA,RT-qPCR and West-ern blot.Results Migration and invasion experiments showed that the cell proliferation rate of the butin group was lower than that of the blank control group(P＜0.05).Cell cycle analysis demonstrated that in the G0/G1 phase,the DNA expression was elevated in the medium and high-dose groups of butin(P＜0.05),while in the G2 and S phases,the DNA expression was reduced in the medium and high-dose groups of butin(P＜0.05).The results of ELISA,RT-qPCR and Western blot assay revealed that the expression of IL-1β,IL-1 8,caspase-1,and caspase-3 decreased in the butin group compared with the IL-1β+caspase-3 in-hibitor group(P＜0.05).Conclusions Butin inhib-its HFLS-RA proliferation by inhibiting the synthesis of inflammatory vesicles by caspase-1 in the pyroptosis pathway,thereby reducing the production and release of inflammatory factors such as IL-1β and IL-18 down-stream of the pathway,and also inhibits HFLS-RA pro-liferation by exerting a significant blocking effect in the G1 phase,which may be one of the potential mecha-nisms of butin in the treatment of RA.

Objective To retrospectively analyze the ultra-fast track anesthesia(UFTA)methods and perioperative anesthesia management experiences of transcatheter mitral valve edge-to-edge repair(TEER)in the treatment of functional mitral regurgitant.Methods In this retrospective study,patients underwent the TEER procedure and received UFTA in Fuwai Yunnan Hospital,from May 2022 to September 2022 for heart failure combined with moderate to severe or severe functional mitral regurgitant were included.Baseline,preoperative complications,cardial function and anesthesia classification,amino-terminal probrain natriuretic peptide(NT-proBNP),ultrasound examination results,surgery time,extubation time,intraoperative anesthetic and vasoactive drug,complications related to TEER and UFTA,perioperative,and postoperative 30-day and one-year follow-up data were collected.All perioperative clinical data were recorded and analyzed.Results A total of 30 patients were enrolled,11 patients(36.7％)were female,mean age was(63.6±6.1)years,NYHA classification IV 14 patients(46.7％),left ventricular ejection fraction(LVEF)(36.0±8.1)％,the end-diastolic volume of the left ventricle(66.0±8.2)mm,mitral regurgitation 4+14 patients(56.7％),3+17 patients(43.3％),NT-proBNP(1 934.1±1 973.5)pg/ml,1 patient(3.3％)used high-dose vasoactive drugs during surgery.All patients did not experience nausea,vomiting,delirium,respiratory depression,perioperative transesophageal echocardiography-related gastrointestinal bleeding,pericardial effusion,cerebrovascular accidents,emergency surgery or secondary intervention,or other serious adverse events within 24 hours after surgery.No 30-day all-cause death occurred;the mean postoperative hospital stay was(7.4±2.8)days.All patients completed one-year follow-up,LVEF(37.6±11.1)％,the end-diastolic volume of the left ventricle(63.2±8.6)mm,mitral regurgitation 2+7 patients(23.3％),1+23 patients(76.7％),NT-proBNP(1 949.2±2 576.6)pg/ml.Conclusions Ultra-fast track anesthesia can be safely applied to TEER in treating functional mitral regurgitant patients.

Objective:To evaluate the safety and efficiency of robotic visualization system(RVS)-assisted microsurgical re-construction of the reproductive tract in male rats and the satisfaction of the surgeons.Methods:We randomly divided 8 adult male SD rats into an experimental and a control group,the former treated by RVS-assisted microsurgical vasoepididymostomy(VE)or vaso-vasostomy(VV),and the latter by VE or VV under the standard operating microscope(SOM).We compared the operation time,me-chanical patency and anastomosis leakage immediately after surgery,and the surgeons'satisfaction between the two groups.Results:No statistically significant difference was observed the operation time between the experimental and the control groups,and no anasto-mosis leakage occurred after VV in either group.The rate of mechanical patency immediately after surgery was 100％in both groups,and that of anastomosis leakage after VE was 16.7％in the experimental group and 14.3％in the control.Compared with the control group,the experimental group achieved dramatically higher scores on visual comfort(3.00±0.76 vs 4.00±0.53,P＜0.05),neck/back comfort(2.75±1.16 vs 4.38±1.06,P＜0.01)and man-machine interaction(3.88±1.55 va 4.88±0.35,P＜0.05).There were no statistically significant differences in the scores on image definition and operating room suitability between the two groups.Conclusion:RVS can be used in microsurgical reconstruction of the reproductive tract in male rats and,with its advantages over SOM in ergonomic design and image definition,has a potential application value in male reproductive system micosurgery.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

Objective:This investigation sought to delineate the associations among colorectal adenomatous polyps, diabetes, and biomolecules involved in glucose metabolism.Method:Data were collected from 40 patients who underwent endoscopic polypectomy at the Endoscopy Department of Shandong Cancer Hospital between June 2019 and September 2021. This cohort included 27 patients with inflammatory polyps and 13 with adenomatous polyps. We assessed fasting insulin (Fins), fasting blood glucose (FBG), and the mRNA expressions of fibroblast growth factor 19 (FGF-19) and insulin-like growth factor 1 (IGF-1) in the polyp tissues. Both univariate and multivariate logistic regression analyses were employed to ascertain the determinants influencing the emergence of adenomatous polyps. From these analyses, a predictive nomogram was constructed to forecast the occurrence of adenomatous polyps, and evaluations on the discriminative capacity, calibration, and clinical utility of the model were conducted.Results:The adenomatous polyp group exhibited markedly elevated levels of glucose, insulin, FGF-19, and IGF-1, with respective concentrations of (8.67±2.70) mmol/L, (12.72±7.69) μU/L, 2.20±1.88, and 1.36±0.69. These figures were significantly higher compared to the inflammatory polyp group, which showed levels of (5.51±0.72) mmol/L, (5.49±2.68) μU/L, 0.53±0.97, and 0.41±0.46, respectively, P=0.001. Multivariate logistic regression revealed that the relative expression of IGF-1 served as an independent risk factor for the development of colorectal adenomatous polyps ( OR=5.622, 95% CI:1.085-29.126). The nomogram displayed a C-index of 0.849, indicating substantial discriminative capability. The calibration curve affirmed the model's accuracy in aligning predicted probabilities with actual outcomes, and the clinical decision curve demonstrated thepractical clinical applicability of the model. Conclusions:There was a significant correlation between the occurrence of colorectal adenomatous polyps and glucose metabolic pathways. Individuals with diabetes showed a higher propensity to develop such polyps.