BACKGROUND: The primary limitation to kidney transplantation is organ shortage. Recent progress in gene editing and immunosuppressive regimens has made xenotransplantation with porcine organs a possibility. However, evidence in pig-to-human xenotransplantation remains scarce, and antibody-mediated rejection (AMR) is a major obstacle to clinical applications of xenotransplantation. METHODS: We conducted a kidney xenotransplantation in a brain-dead human recipient using a porcine kidney with five gene edits (5GE) on March 25, 2024 at Xijing Hospital, China. Clinical-grade immunosuppressive regimens were employed, and the observation period lasted 22 days. We collected and analyzed the xenograft function, ultrasound findings, sequential protocol biopsies, and immune surveillance of the recipient during the observation. RESULTS: The combination of 5GE in the porcine kidney and clinical-grade immunosuppressive regimens prevented hyperacute rejection. The xenograft kidney underwent delayed graft function in the first week, but urine output increased later and the single xenograft kidney maintained electrolyte and pH homeostasis from postoperative day (POD) 12 to 19. We observed AMR at 24 h post-transplantation, due to the presence of pre-existing anti-porcine antibodies and cytotoxicity before transplantation; this AMR persisted throughout the observation period. Plasma exchange and intravenous immunoglobulin treatment mitigated the AMR. We observed activation of latent porcine cytomegalovirus toward the end of the study, which might have contributed to coagulation disorder in the recipient. CONCLUSIONS 5GE and clinical-grade immunosuppressive regimens were sufficient to prevent hyperacute rejection during pig-to-human kidney xenotransplantation. Pre-existing anti-porcine antibodies predisposed the xenograft to AMR. Plasma exchange and intravenous immunoglobulin were safe and effective in the treatment of AMR after kidney xenotransplantation.
Transplantation, Heterologous/methods* ; Kidney Transplantation/methods* ; Heterografts/pathology* ; Immunoglobulins, Intravenous/administration & dosage* ; Graft Survival/immunology* ; Humans ; Animals ; Sus scrofa ; Graft Rejection/prevention & control* ; Kidney/pathology* ; Gene Editing ; Species Specificity ; Immunosuppression Therapy/methods* ; Plasma Exchange ; Brain Death ; Biopsy ; Male ; Aged

BACKGROUND: Over 20 million colonoscopies are performed in China annually. An automatic clinical decision support system (CDSS) with accurate semantic recognition of colonoscopy reports and guideline-based is helpful to relieve the increasing medical burden and standardize the healthcare. In this study, the CDSS was built under a hierarchical-label interpretable classification framework, trained by a state-of-the-art transformer-based model, and validated in a multi-center style. METHODS: We conducted stratified sampling on a previously established dataset containing 302,965 electronic colonoscopy reports with pathology, identified 2041 patients' records representative of overall features, and randomly divided into the training and testing sets (7:3). A total of five main labels and 22 sublabels were applied to annotate each record on a network platform, and the data were trained respectively by three pre-training models on Chinese corpus website, including bidirectional encoder representations from transformers (BERT)-base-Chinese (BC), the BERT-wwm-ext-Chinese (BWEC), and ernie-3.0-base-zh (E3BZ). The performance of trained models was subsequently compared with a randomly initialized model, and the preferred model was selected. Model fine-tuning was applied to further enhance the capacity. The system was validated in five other hospitals with 3177 consecutive colonoscopy cases. RESULTS: The E3BZ pre-trained model exhibited the best performance, with a 90.18% accuracy and a 69.14% Macro-F1 score overall. The model achieved 100% accuracy in identifying cancer cases and 99.16% for normal cases. In external validation, the model exhibited favorable consistency and good performance among five hospitals. CONCLUSIONS The novel CDSS possesses high-level semantic recognition of colonoscopy reports, provides appropriate recommendations, and holds the potential to be a powerful tool for physicians and patients. The hierarchical multi-label strategy and pre-training method should be amendable to manage more medical text in the future.
Humans ; Colonoscopy/methods* ; Deep Learning ; Decision Support Systems, Clinical ; Female ; Male

This study explored the drying kinetics of Salviae Miltiorrhizae Radix et Rhizoma(SM), established the suitable models simulating the drying kinetics, and then analyzed the dynamic changes of active components during the drying processes with different methods, aiming to provide a basis for the establishment of suitable drying methods and the quality control of SM. The drying kinetics were studied based on the drying curve, drying rate, moisture effective diffusion coefficient, and drying activation energy, and the appropriate drying kinetics model of SM was established. The drying performance of different methods, such as hot air drying, infrared drying, and microwave drying of SM was evaluated, and the changes in the content of 10 salvianolic acids and 6 tanshinones during drying were analyzed by UPLC-TQ-MS. The Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS) was employed to evaluate the quality of SM dried with different methods. The results showed that the drying rate and moisture effective diffusion coefficient of SM increased with the rise in drying temperature, and the maximum drying rates of different methods were in the order of microwave drying > infrared drying > hot air drying, slice > whole root. The drying rate decreased with the rise in temperature and the extension of drying time. The activation energy of hot air drying was higher than that of infrared drying in SM. The most suitable model for simulating the drying process of SM was the Page model. The TOPSIS results suggested infrared drying at 50 ℃ was the optimal drying method for SM. During the drying process, the content of salvianolic acids increased in different degrees with the loss of moisture, among which salvianolic acid B showed the largest increase of 44 times compared with that in the fresh medicinal material. Tanshinones also existed in the fresh herb of SM, and the content of tanshinone Ⅱ_A increased by 3 times after drying. The results provided a basis for the establishment of suitable drying methods and the quality control of SM.
Salvia miltiorrhiza/chemistry* ; Desiccation/methods* ; Drugs, Chinese Herbal/chemistry* ; Rhizome/chemistry* ; Kinetics ; Quality Control ; Abietanes

With the rise of data-intensive research, data literacy has become a critical capability for improving scientific data quality and achieving artificial intelligence (AI) readiness. In the biomedical domain, data are characterized by high complexity and privacy sensitivity, calling for robust and systematic data management skills. This paper reviews current trends in scientific data governance and the evolving policy landscape, highlighting persistent challenges such as inconsistent standards, semantic misalignment, and limited awareness of compliance. These issues are largely rooted in the lack of structured training and practical support for researchers. In response, this study builds on existing data literacy frameworks and integrates the specific demands of biomedical research to propose a comprehensive, lifecycle-oriented data literacy competency model with an emphasis on ethics and regulatory awareness. Furthermore, it outlines a tiered training strategy tailored to different research stages-undergraduate, graduate, and professional, offering theoretical foundations and practical pathways for universities and research institutions to advance data literacy education.
Artificial Intelligence ; Humans ; Biomedical Research

OBJECTIVE: To explore the current research status and hotspots in the field of biomechanics of diabetic foot by bibliometric analysis methods. METHODS: Literatures related to biomechanics of diabetic foot published in the Web of Scienc Core Collection (WoSCC) from 1981 to 2024 were searched. CiteSpace software and R language bibliometrics plugin were used to conduct a visual analysis of annual publication volume of the literature, including publication volume of each country and region, the publication situation of authors and institutions, the citation situation of individual literature, and the co-occurrence network of keywords. RESULTS: Totally 996 literatures were included, and the number of published papers increased steadily. The United States (261 papers) and China (89 papers) were the top two countries in terms of the number of published papers. The mediating centrality of the United States was 0.94, and that of China was 0.01. Scholars such as Cavanagh and institutions like the Cleveland Clinic were at the core of research in this field. High-frequency keywords include plantar pressure (plantar pressure), diabetic foot (diabetic foot), ulceration (ulcer), etc. The research focuses on plantar pressure, ulcer formation and prevention, etc. CONCLUSION Biomechanical research on diabetic foot mainly focuses on the pressure distribution on the sole of the foot, callus formation, mechanical analysis of soft tissues on the sole of the foot, and the study of plantar decompression caused by Achilles tendon elongation. The research trend has gradually shifted from focusing on joint range of motion to gait and the design of braces and assistive devices, and has begun to pay attention to muscle strength, gait imbalance and proprioception abnormalities.
Humans ; Diabetic Foot/physiopathology* ; Biomechanical Phenomena ; Bibliometrics

Objective： The aim of this study is to explore the predictive value of biparametric magnetic resonance imaging(bpMRI)for pelvic lymph node metastasis in prostate cancer patients with PSA≤20 μg/L and establish a nomogram. Methods： The imaging data and clinical data of 363 patients undergoing radical prostatectomy and pelvic lymph node dissection in the First Affiliated Hospital of Nanjing Medical University from July 2018 to December 2023 were retrospectively analyzed. Univariate analysis and multivariate logistic regression were used to screen independent risk factors for pelvic lymph node metastasis in prostate cancer, and a nomogram of the clinical prediction model was established. Calibration curves were drawn to evaluate the accuracy of the model. Results： Multivariate logistic regression analysis showed extrocapusular extension (OR=8.08,95%CI=2.62－24.97, P<0.01), enlargement of pelvic lymph nodes (OR=4.45,95%CI=1.16－17.11,P=0.030), and biopsy ISUP grade(OR=1.97,95%CI=1.12－3.46, P=0.018)were independent risk factors for pelvic lymph node metastasis. The C-index of the prediction model was 0.834, which indicated that the model had a good prediction ability. The actual value of the model calibration curve and the prediction probability of the model fitted well, indicating that the model had a good accuracy. Further analysis of DCA curve showed that the model had good clinical application value when the risk threshold ranged from 0.05 to 0.70.Conclusion： For prostate cancer patients with PSA≤20 μg/L, bpMRI has a good predictive value for the pelvic lymph node metastasis of prostate cancer with extrocapusular extension, enlargement of pelvic lymph nodes and ISUP grade≥4.
Humans ; Male ; Prostatic Neoplasms/diagnostic imaging* ; Lymphatic Metastasis ; Retrospective Studies ; Nomograms ; Prostate-Specific Antigen/blood* ; Lymph Nodes/pathology* ; Pelvis ; Predictive Value of Tests ; Prostatectomy ; Lymph Node Excision ; Risk Factors ; Magnetic Resonance Imaging ; Logistic Models ; Middle Aged ; Aged

OBJECTIVE: To investigate the clinical effect of transposition of gracilis muscle flap in repairing urethral perineal fistula after Miles operation. METHODS: The clinical data of 3 patients with urethral perineal fistula treated in the Second Affiliated Hospital of Zhejiang University from September 2023 to November 2024 were analyzed retrospectively. All patients were male, aged from 59 to 68 years (mean 63 years). All patients underwent Miles operation because of low rectal cancer. Urethral perineal fistula occurred after 2 months to 13 years of the operation. The underlying comorbidities included diabetes (2/3), preoperative chemoradiotherapy (1/3), and chemotherapy alone (1/3). The endourethral fistula was located in the apical and membranous part of the prostate, with a diameter of 1.5-2.0 cm and a mean of 1.7 cm. Suprapubic cystostomy was performed one month before operation. In all 3 cases, perineal inverted "Y" incision was taken under general anesthesia to expose urethral fistula, cut off necrotic tissue and suture urethral fistula. The gracilis muscle of the right thigh was taken and turned through the perineal subcutaneous tunnel. and 6 stitches were suture at the urethral fistula. RESULTS: The operations of all 3 patients were completed successfully. The follow-up period ranged from 2 months to 12 months, with an average of 8 months. There was no case of urinary incontinence after removal of catheter 3 weeks after operation. In two patients, urethrography was reviewed 1 month after surgery to show no fistula residue and urethral stenosis, and the fistula was removed. In one patient with a history of radiotherapy, urethrography was reviewed 1 month after surgery to show a small amount of contrast overflow around the urethra, and urethrography was reviewed again 3 months after surgery to show no contrast overflow around the urethra. All the 3 patients had no disturbance of movement of the right lower limb, and the pain of different degrees of thigh incision was acceptable and basically relieved half a month after operation. CONCLUSION Gracilis muscle flap is one of the effective methods for repairing urethral perineal fistula after Miles operation，which has a precise surgical result and few complications.
Humans ; Male ; Middle Aged ; Aged ; Gracilis Muscle/transplantation* ; Urinary Fistula/surgery* ; Retrospective Studies ; Surgical Flaps ; Perineum/surgery* ; Rectal Neoplasms/surgery* ; Postoperative Complications/surgery* ; Urethral Diseases/surgery* ; Urethra/surgery*

Ovarian tumor (OT) is the most lethal form of gynecologic malignancy, with minimal improvements in patient outcomes over the past several decades. Metastasis is the leading cause of ovarian cancer-related deaths, yet the underlying mechanisms remain poorly understood. Psychological stress is known to activate the glucocorticoid receptor (NR3C1), a factor associated with poor prognosis in OT patients. However, the precise mechanisms linking NR3C1 signaling and metastasis have yet to be fully elucidated. In this study, we demonstrate that chronic restraint stress accelerates epithelial-mesenchymal transition (EMT) and metastasis in OT through an NR3C1-dependent mechanism involving nuclear protein 1 (NUPR1). Mechanistically, NR3C1 directly regulates the transcription of NUPR1, which in turn increases the expression of snail family transcriptional repressor 2 (SNAI2), a key driver of EMT. Clinically, elevated NR3C1 positively correlates with NUPR1 expression in OT patients, and both are positively associated with poorer prognosis. Overall, our study identified the NR3C1/NUPR1 axis as a critical regulatory pathway in psychological stress-induced OT metastasis, suggesting a potential therapeutic target for intervention in OT metastasis.

Objective: To investigate morphological differences between obstructive and non-obstructive coronary artery disease (CAD) patients using computer-aided image analysis, and identify color and texture features for traditional Chinese medicine (TCM) syndrome differentiation. Methods: This prospective study enrolled patients undergoing coronary computed tomography angiography (CTA) at the Affiliated Hospital of Liaoning University of Traditional Chinese Medicine between May 1, 2024 and August 7, 2025. Based on CTA results, patients were categorized into obstructive CAD and non-obstructive CAD groups. Standardized tongue images were acquired using a dedicated mobile application (Traditional Chinese Medicine Tongue Image-Assisted Diagnosis System) and analyzed for the overall tongue surface and three macroscopic features (tooth marks, fissures, and red dots) from which high-dimensional color and texture parameters were extracted. Multi-scale texture features were derived using spatial-domain Laplacian pyramid and frequency-domain wavelet transform methods. Dimensionality reduction and feature selection were performed using principal component analysis (PCA) and random forest with 5-fold cross-validation. Feature stability was assessed using Hodges-Lehmann estimator and Cliff’s δ. A multi-view XGBoost model was developed to differentiate the two groups and evaluated on a temporally independent validation set using accuracy and the area under the receiver operating characteristic curve (AUC). SHapley Additive exPlanations (SHAP) analysis was applied to interpret model decisions. Results: This study analyzed 373 CAD patients, including 167 with obstructive CAD and 206 with non-obstructive CAD according to CTA results. The whole cohort was divided into training set (n = 316, obstructive : non-obstructive = 142 : 174 ) and validation set (n = 57, obstructive : non-obstructive = 25 : 32), with balanced baseline characteristics (P > 0.05). Macroscopic tongue analysis revealed that patients with obstructive CAD had fewer tooth marks [odds ratio (OR) = 0.43, P < 0.05] and red dots (OR = 0.46, P < 0.05). High-dimensional color analysis identified pronounced intergroup differences, most notably a reduction in hue values in the hue-saturation-intensity (HSI) color space among obstructive CAD patients (Cliff’s δ = – 0.31, P = 2.72 × 10–6; Hodges-Lehmann estimator: – 0.31). PCA results suggested that tongue surface features explained the highest proportion of variance (48.2%). Random forest screening identified 77 stable features across all tongue regions, with wavelet-transformed texture features demonstrating the highest importance. The multi-view XGBoost fusion model achieved an accuracy of 75% and an AUC of 0.779 in the independent validation set. SHAP analysis identified the wavelet-based feature—left-handed lower-level gray-level size zone matrix zone variance (LHL_glszm_ZoneVariance) as the top predictor, accounting for 40.6% of the model's decision variance, and indicated that 85.3% of the predictive power came from wavelet-based texture features. Conclusion This study has provided objective evidence for the TCM concept that “the tongue reflects the heart” by identifying distinct morphological and colorimetric tongue patterns in patients with obstructive CAD through artificial intelligence (AI)-driven image analysis, and the promising performance of the computational model suggests its potential as a non-invasive adjunctive tool for CAD assessment.