Varicocele (VC) is a common cause of male infertility, yet there is a lack of molecular information for VC-associated male infertility. This study investigated alterations in the seminal plasma metabolomic and lipidomic profiles of infertile male VC patients. Twenty infertile males with VC and twenty-three age-matched healthy controls (HCs) were recruited from Peking Union Medical College Hospital (Beijing, China) between October 2019 and April 2021. Untargeted metabolite and lipid profiles from seminal plasma were analyzed using mass spectrometry. Four hundred and seventy-six metabolites and seventeen lipids were significantly different in infertile male VC patients compared to HCs. The top enriched pathways among these significantly different metabolites are protein digestion and absorption, aminoacyl-transfer RNA (tRNA) biosynthesis, and biosynthesis of amino acids. Different key lipid species, including triglyceride (TG), diacylglycerol (DG), ceramides (Cer), and phosphatidylserine (PS), varied between VC and HC groups. The distinct metabolites and lipids were moderately correlated. DL-3-phenyllactic acid is a potential diagnostic biomarker for VC-related male infertility (area under the curve [AUC] = 0.893), positively correlating with sperm count, concentration, and motility. Furthermore, DL-3-phenyllactic acid is the only metabolite shared by all four comparisons (VC vs HC, VC-induced oligoasthenospermia [OAS] vs VC-induced asthenospermia [AS], OAS vs HC, and AS vs HC). DL-3-phenyllactic acid significantly decreased in OAS than AS. Metabolite-targeting gene analysis revealed carbonic anhydrase 9 (CA9) might be the strongest candidate associated with the onset and severity of VC. The seminal plasma metabolite and lipid profiles of infertile males with VC differ significantly from those of HCs. DL-3-phenyllactic acid could be a promising biomarker.
Humans ; Male ; Varicocele/complications* ; Infertility, Male/etiology* ; Semen/metabolism* ; Lipidomics ; Adult ; Metabolomics ; Case-Control Studies ; Biomarkers/metabolism*

BACKGROUND: Medical informatics accumulated vast amounts of data for clinical diagnosis and treatment. However, limited access to follow-up data and the difficulty in integrating data across diverse platforms continue to pose significant barriers to clinical research progress. In response, our research team has embarked on the development of a specialized clinical research database for cardiology, thereby establishing a comprehensive digital platform that facilitates both clinical decision-making and research endeavors. METHODS: The database incorporated actual clinical data from patients who received treatment at the Cardiovascular Medicine Department of Chinese PLA General Hospital from 2012 to 2021. It included comprehensive data on patients' basic information, medical history, non-invasive imaging studies, laboratory test results, as well as peri-procedural information related to interventional surgeries, extracted from the Hospital Information System. Additionally, an innovative artificial intelligence (AI)-powered interactive follow-up system had been developed, ensuring that nearly all myocardial infarction patients received at least one post-discharge follow-up, thereby achieving comprehensive data management throughout the entire care continuum for high-risk patients. RESULTS: This database integrates extensive cross-sectional and longitudinal patient data, with a focus on higher-risk acute coronary syndrome patients. It achieves the integration of structured and unstructured clinical data, while innovatively incorporating AI and automatic speech recognition technologies to enhance data integration and workflow efficiency. It creates a comprehensive patient view, thereby improving diagnostic and follow-up quality, and provides high-quality data to support clinical research. Despite limitations in unstructured data standardization and biological sample integrity, the database's development is accompanied by ongoing optimization efforts. CONCLUSION The cardiovascular specialty clinical database is a comprehensive digital archive integrating clinical treatment and research, which facilitates the digital and intelligent transformation of clinical diagnosis and treatment processes. It supports clinical decision-making and offers data support and potential research directions for the specialized management of cardiovascular diseases.

Mycophenolic acid (MPA), the active moiety of both mycophenolate mofetil (MMF) and enteric-coated mycophenolate sodium (EC-MPS), serves as a primary immunosuppressant for maintaining solid organ transplants. Therapeutic drug monitoring (TDM) enhances treatment outcomes through tailored approaches. This study aimed to develop an evidence-based guideline for MPA TDM, facilitating its rational application in clinical settings. The guideline plan was drawn from the Institute of Medicine and World Health Organization (WHO) guidelines. Using the Delphi method, clinical questions and outcome indicators were generated. Systematic reviews, Grading of Recommendations Assessment, Development, and Evaluation (GRADE) evidence quality evaluations, expert opinions, and patient values guided evidence-based suggestions for the guideline. External reviews further refined the recommendations. The guideline for the TDM of MPA (IPGRP-2020CN099) consists of four sections and 16 recommendations encompassing target populations, monitoring strategies, dosage regimens, and influencing factors. High-risk populations, timing of TDM, area under the curve (AUC) versus trough concentration (C₀), target concentration ranges, monitoring frequency, and analytical methods are addressed. Formulation-specific recommendations, initial dosage regimens, populations with unique considerations, pharmacokinetic-informed dosing, body weight factors, pharmacogenetics, and drug‍-‍drug interactions are covered. The evidence-based guideline offers a comprehensive recommendation for solid organ transplant recipients undergoing MPA therapy, promoting standardization of MPA TDM, and enhancing treatment efficacy and safety.
Mycophenolic Acid/administration & dosage* ; Drug Monitoring/methods* ; Humans ; Organ Transplantation ; Immunosuppressive Agents/administration & dosage* ; Delphi Technique

Hearing loss is the most prevalent disabling disease. Cochlear implantation（CI） serves as the primary intervention for severe to profound hearing loss. This consensus systematically explores the value of genetic diagnosis in the pre-operative assessment and efficacy prognosis for CI. Drawing upon domestic and international research and clinical experience, it proposes an evidence-based medicine three-tiered prognostic classification system（Favorable, Marginal, Poor）. The consensus focuses on common hereditary non-syndromic hearing loss（such as that caused by mutations in genes like GJB2, SLC26A4, OTOF, LOXHD1） and syndromic hereditary hearing loss（such as Jervell & Lange-Nielsen syndrome and Waardenburg syndrome）, which are closely associated with congenital hearing loss, analyzing the impact of their pathological mechanisms on CI outcomes. The consensus provides recommendations based on multiple round of expert discussion and voting. It emphasizes that genetic diagnosis can optimize patient selection, predict prognosis, guide post-operative rehabilitation, offer stratified management strategies for patients with different genotypes, and advance the application of precision medicine in the field of CI.
Humans ; Cochlear Implantation ; Prognosis ; Hearing Loss/surgery* ; Consensus ; Connexin 26 ; Mutation ; Sulfate Transporters ; Connexins/genetics*

OBJECTIVES: To develop an early atrial fibrillation (AF) risk prediction model based on large-scale electrocardiogram (ECG) data from the Chinese population. METHODS: The data of multiple ECG records of 30 383 patients admitted in the Chinese PLA General Hospital between 2009 and 2023 were randomly divided into the training set and the internal testing set in a 7:3 ratio. The predictive factors were selected based on the training set using univariate analysis, LASSO regression, and the Boruta algorithm. Cox proportional hazards regression was used to establish the ECG model and the composite model incorporating age, gender, and ECG model score. The discrimination power, calibration, and clinical net benefits of the models were evaluated using the area under the receiver operating characteristic curve (AUROC), calibration curves, and decision curves. RESULTS: The cohort included 51.1% male patients with a median age of the patients of 51 (36, 62) years and an AF incidence of 4.5% (1370/30 383). In the ECG model, the parameters related to the P wave and QRS complex were identified as significant predictors. In the testing set, the AUROC of the ECG model for predicting 5-year AF risk was 0.77 (95% CI: 0.74-0.80), which was increased to 0.81 (95% CI: 0.78-0.83) after incorporating age and gender, with a net reclassification improvement of 0.123 and an integrated discrimination improvement of 0.04 (P<0.05). The calibration curve of the model was close to the diagonal line. Decision curve analysis showed that the clinical net benefit of the composite model was higher than that of the ECG model across the majority of threshold probability. CONCLUSIONS The composite model incorporating quantitative ECG features during sinus rhythm, along with age and gender, can effectively predict AF risk in the Chinese population, thus providing a low-cost screening tool for early AF risk assessment and management.
Humans ; Atrial Fibrillation/epidemiology* ; Electrocardiography ; Middle Aged ; Male ; Female ; China/epidemiology* ; Proportional Hazards Models ; Adult ; Risk Factors ; Risk Assessment ; East Asian People

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

The human gut is inhabited by a large number and variety of microorganisms, which constitute the intestinal microecosystem with the intestinal environment where they reside. After oral administration, Chinese medicine undergoes metabolism by these intestinal microorganisms within the gastrointestinal tract. The resulting metabolites are absorbed into the bloodstream to produce pharmacological effects. This paper provides a comprehensive review of the characteristics and influencing factors related to the mediation of Traditional Chinese Medicine (TCM) metabolism by intestinal flora. Additionally, recent progress in the microbial-mediated metabolism of TCM components such as flavonoids, saponins, iridoids, and lignans is summarized. This serves as a foundation for understanding the connection between intestinal bacteria and the chemical structural alterations of TCM components. It also offers insight into the regulations and mechanisms governing the intestinal bacterial metabolism of TCM constituents.

Objective Viral encephalitis is an infectious disease severely affecting human health.It is caused by a wide variety of viral pathogens,including herpes viruses,flaviviruses,enteroviruses,and other viruses.The laboratory diagnosis of viral encephalitis is a worldwide challenge.Recently,high-throughput sequencing technology has provided new tools for diagnosing central nervous system infections.Thus,In this study,we established a multipathogen detection platform for viral encephalitis based on amplicon sequencing. Methods We designed nine pairs of specific polymerase chain reaction(PCR)primers for the 12 viruses by reviewing the relevant literature.The detection ability of the primers was verified by software simulation and the detection of known positive samples.Amplicon sequencing was used to validate the samples,and consistency was compared with Sanger sequencing. Results The results showed that the target sequences of various pathogens were obtained at a coverage depth level greater than 20×,and the sequence lengths were consistent with the sizes of the predicted amplicons.The sequences were verified using the National Center for Biotechnology Information BLAST,and all results were consistent with the results of Sanger sequencing. Conclusion Amplicon-based high-throughput sequencing technology is feasible as a supplementary method for the pathogenic detection of viral encephalitis.It is also a useful tool for the high-volume screening of clinical samples.

Objective To investigate the value of computer-assisted quantification of pulmonary embolism volume(PEV)in identifying mild-to-high-risk acute pulmonary embolism(APE).Methods We retrospectively enrolled 143 patients with suspected APE confirmed by computed tomography pulmonary angiography(CTPA)at Yan'an University Affiliated Hospital from January 2017 to December 2020.According to the 2018 Chinese Guidelines for Diagnosis,Treatment and Prevention of Pulmonary Thromboembolism,all the patients were divided into low-risk group(n=88)and mild-to-high-risk group(n=55).We collected the patients'basic demographic data,clinical manifestations,and serum levels of N-terminal-B type natriuretic peptide precursor(NT-proBNP)and D-dimer.Based on CTPA images,the degree of pulmonary thromboembolism was artificially evaluated to obtain the pulmonary artery occlusion index(PAOI).The thrombus was segmented using the pulmonary embolism detection tool based on digital lung,and PEV was calculated.We compared the differences in clinical and laboratory indicators and PAOI and PEV between the two risk groups.We analyzed the value of PAOI and PEV in identifying mild-to-high-risk APE using receiver operating characteristic(ROC)curves,and used Logistic regression analysis to identify independent risk factors in predicting mild-to-high-risk APE.Different models were established.Results Compared with the low-risk group,APE patients in the mild-to-high-risk group were older(P＜0.05),had lower diastolic blood pressure(P＜0.05),higher levels of D-dimer and NT-proBNP(P＜0.05),lower levels of platelet count,arterial oxygen partial pressure and arterial carbon dioxide partial pressure(P＜0.05),and higher levels of PAOI and PEV(P＜0.001).ROC curve analysis showed that the area under the curve for PEV in identifying mild-to-high-risk APE was 0.809(95％CI:0.734-0.884),while that for PAOI was 0.753(95％CI:0.667-0.839).Logistic regression analysis showed that PEV and NT-proBNP were independent risk factors for mild-to-high-risk APE(P＜0.05).Conclusion PEV and NT-proBNP are independent risk factors for mild-to-high-risk APE.

Paroxysmal nocturnal hemoglobinuria (PNH) is an acquired clonal hematopoietic stem cell disease caused by abnormal expression of glycosylphosphatidylinositol (GPI) on the cell membrane due to mutations in the phosphatidylinositol glycan class A(PIGA) gene. It is commonly characterized by intravascular hemolysis, repeated thrombosis, and bone marrow failure, as well as multiple systemic involvement symptoms such as renal dysfunction, pulmonary hypertension, swallowing difficulties, chest pain, abdominal pain, and erectile dysfunction. Due to the rarity of PNH and its strong heterogeneity in clinical manifestations, multidisciplinary collaboration is often required for diagnosis and treatment. Peking Union Medical College Hospital, relying on the rare disease diagnosis and treatment platform, has invited multidisciplinary clinical experts to form a unified opinion on the diagnosis and treatment of PNH, and formulated the Expert Consensus of Multidisciplinary Diagnosis and Treatment for Paroxysmal Nocturnal Hemoglobinuria (2024), with the hope of promoting the standardization of PNH diagnosis and treatment.