This paper proposes a two-stage method integrating visual foundation models （VFM） and diffusion models. The segment anything model （SAM） as VFM is combined with the SegRefiner diffusion model to construct the SAM-SegRefiner framework for automated segmentation of edema， inflammation， and thrombus regions in histopathological images of hemorrhoidal tissue， providing a reproducible technical tool for the objective quantification of pathological morphology and its application in traditional Chinese medicine （TCM） syndrome research. Trained and validated on multi-center retrospective data， the SAM-SegRefiner model achieved an average pixel accuracy of 95.32% and a mean intersection over union （mIoU） of 66.81% on an independent test set， significantly outperfor-ming comparative models such as U-Net， MixU-Net， and SAM-Med2D， and also demonstrating robust cross-center generalization capability. Furthermore， by correlating the quantitatively segmented results from the model with the patients' TCM syndrome types， the potential associations between pathomorphological features and TCM syndrome differentiation have been explored. The analysis revealed no statistically significant differences in the degree of inflammatory infiltration and thrombus formation among different syndrome types， suggesting a complex relationship between local pathological changes and systemic syndrome manifestations.

The initiation of adaptive immune responses relies on the precise recognition and interpretation of antigenic information. In this process, the specific binding of T cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules represents one of the key molecular events in the initiation of adaptive immune responses. Accordingly, the structural features of TCR-pMHC complexes provide a fundamental basis for dissecting antigen recognition mechanisms and support rational vaccine design, therapeutic target discovery in TCR-based immunotherapy, and TCR identification and optimization. However, experimental determination of TCR-pMHC structures remains costly, time-consuming, and limited in coverage, making computational approaches essential for rapidly obtaining reliable structural information. Computational methods for predicting the structures of TCR-pMHC complexes have advanced rapidly in recent years, driven by progress in deep learning-based modeling frameworks and the increasing availability of structural and sequence resources. Despite these developments, most existing tools do not adequately distinguish the key structural and biophysical differences between MHC class I (MHC-I) and MHC class II (MHC-II) complexes during model construction. As a consequence, their predictive performance differs substantially between class I and class II complexes. In general, structural predictions for class I complexes outperform those for class II complexes. This discrepancy may be related to several fundamental differences between the two systems, including the architecture of the peptide-binding groove, the distribution of peptide lengths, and the properties of peptide flanking residues (PFRs). Compared with MHC-I molecules, MHC-II molecules usually bind longer antigenic peptides, which typically range from 13 to 25 amino acids in length. PFRs at both termini of these peptides participate in regulating the overall conformation of TCR-pMHC class II complexes and exert a pronounced effect on the geometric and physicochemical characteristics of the TCR-pMHC binding interface. Furthermore, within the TCR recognition interface, the complementarity-determining regions (CDRs) consist of segments that differ markedly in conformational behavior. They commonly include regions that are relatively rigid and structurally stable, together with highly flexible segments exhibiting substantial conformational plasticity. These rigidity-flexibility features constitute an essential structural basis enabling TCRs to recognize diverse peptide-MHC ligands and to accommodate conformational heterogeneity at the interface. However, many current modeling tools, in an effort to enforce global conformational stability or reduce structural noise, tend to over-constrain intrinsically flexible regions. Such oversimplification may lead to inappropriate rigidification of flexible CDR loops, resulting in local structural distortions, compromised interface geometry, or even complete modeling failure for specific complexes. Against this background, the review approaches the field from the perspective of computational differences between MHC-I and MHC-II complexes. We first systematically organize and summarize available resources related to TCRs and pMHCs, including structural datasets, sequence databases, prediction tools, and benchmarking studies. We then focus on five representative tools capable of predicting both class I and class II complexes—AlphaFold2, AlphaFold3, TCRmodel2, tFold-TCR, and TCR-pHLA_ModellerS. After excluding structures present in the training sets of these tools, we constructed a benchmark dataset comprising 25 class I and 10 class II TCR-pMHC complexes in the bound state and conducted a systematic evaluation using this dataset. We first employ widely used general evaluation metrics, including All-Atom Root Mean Square Deviation (All-Atom RMSD), Backbone RMSD, Template Modeling score (TM-score), and DockQ, to assess the global conformational accuracy and interface modeling quality of class I and class II complexes. For class II complexes, we propose for the first time a peptide flanking residue deviation index, including the PFRs-Deviation Index (PFRs-DI), N-PFR-Deviation Index (N-PFR-DI), and C-PFR-Deviation Index (C-PFR-DI), to quantitatively characterize conformational deviations in PFRs. In addition, we propose the CDR conformational consistency index (CCC) designed to qualitatively evaluate the ability of prediction tools to capture TCR CDR conformational flexibility. These metrics collectively assess a tool’s ability to model both overall conformation and critical functional regions, thereby addressing the limitations of existing evaluation criteria that overemphasize global structure while inadequately capturing modeling quality in key functional areas. This establishes a unified analytical framework for MHC-I and MHC-II complexes to guide data resource selection, modeling strategy formulation, and evaluation system development. The framework further advances computational modeling and provides crucial support for multi-scale analysis of TCR-pMHC recognition mechanisms and their biological functions.

The initiation of adaptive immune responses relies on the precise recognition and interpretation of antigenic information. In this process, the specific binding of T cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules represents one of the key molecular events in the initiation of adaptive immune responses. Accordingly, the structural features of TCR-pMHC complexes provide a fundamental basis for dissecting antigen recognition mechanisms and support rational vaccine design, therapeutic target discovery in TCR-based immunotherapy, and TCR identification and optimization. However, experimental determination of TCR-pMHC structures remains costly, time-consuming, and limited in coverage, making computational approaches essential for rapidly obtaining reliable structural information. Computational methods for predicting the structures of TCR-pMHC complexes have advanced rapidly in recent years, driven by progress in deep learning-based modeling frameworks and the increasing availability of structural and sequence resources. Despite these developments, most existing tools do not adequately distinguish the key structural and biophysical differences between MHC class I (MHC-I) and MHC class II (MHC-II) complexes during model construction. As a consequence, their predictive performance differs substantially between class I and class II complexes. In general, structural predictions for class I complexes outperform those for class II complexes. This discrepancy may be related to several fundamental differences between the two systems, including the architecture of the peptide-binding groove, the distribution of peptide lengths, and the properties of peptide flanking residues (PFRs). Compared with MHC-I molecules, MHC-II molecules usually bind longer antigenic peptides, which typically range from 13 to 25 amino acids in length. PFRs at both termini of these peptides participate in regulating the overall conformation of TCR-pMHC class II complexes and exert a pronounced effect on the geometric and physicochemical characteristics of the TCR-pMHC binding interface. Furthermore, within the TCR recognition interface, the complementarity-determining regions (CDRs) consist of segments that differ markedly in conformational behavior. They commonly include regions that are relatively rigid and structurally stable, together with highly flexible segments exhibiting substantial conformational plasticity. These rigidity-flexibility features constitute an essential structural basis enabling TCRs to recognize diverse peptide-MHC ligands and to accommodate conformational heterogeneity at the interface. However, many current modeling tools, in an effort to enforce global conformational stability or reduce structural noise, tend to over-constrain intrinsically flexible regions. Such oversimplification may lead to inappropriate rigidification of flexible CDR loops, resulting in local structural distortions, compromised interface geometry, or even complete modeling failure for specific complexes. Against this background, the review approaches the field from the perspective of computational differences between MHC-I and MHC-II complexes. We first systematically organize and summarize available resources related to TCRs and pMHCs, including structural datasets, sequence databases, prediction tools, and benchmarking studies. We then focus on five representative tools capable of predicting both class I and class II complexes—AlphaFold2, AlphaFold3, TCRmodel2, tFold-TCR, and TCR-pHLA_ModellerS. After excluding structures present in the training sets of these tools, we constructed a benchmark dataset comprising 25 class I and 10 class II TCR-pMHC complexes in the bound state and conducted a systematic evaluation using this dataset. We first employ widely used general evaluation metrics, including All-Atom Root Mean Square Deviation (All-Atom RMSD), Backbone RMSD, Template Modeling score (TM-score), and DockQ, to assess the global conformational accuracy and interface modeling quality of class I and class II complexes. For class II complexes, we propose for the first time a peptide flanking residue deviation index, including the PFRs-Deviation Index (PFRs-DI), N-PFR-Deviation Index (N-PFR-DI), and C-PFR-Deviation Index (C-PFR-DI), to quantitatively characterize conformational deviations in PFRs. In addition, we propose the CDR conformational consistency index (CCC) designed to qualitatively evaluate the ability of prediction tools to capture TCR CDR conformational flexibility. These metrics collectively assess a tool’s ability to model both overall conformation and critical functional regions, thereby addressing the limitations of existing evaluation criteria that overemphasize global structure while inadequately capturing modeling quality in key functional areas. This establishes a unified analytical framework for MHC-I and MHC-II complexes to guide data resource selection, modeling strategy formulation, and evaluation system development. The framework further advances computational modeling and provides crucial support for multi-scale analysis of TCR-pMHC recognition mechanisms and their biological functions.

ObjectiveTo develop and validate a nomogram based on the albumin-bilirubin （ALBI） score for predicting the risk of severe perioperative complications in patients undergoing hepatectomy for hepatolithiasis. MethodsA retrospective analysis was conducted on the clinical data of 163 hepatolithiasis patients who underwent hepatectomy. Univariate and multivariate logistic regression analyses were used to identify independent risk factors for severe perioperative complications. A nomogram prediction model was constructed and its performance was evaluated. ResultsAmong the 163 patients， 66 and 97 were classified into the low-grade and high-grade ALBI groups， respectively. Significant intergroup differences were observed in gender， total bilirubin， albumin levels， and the incidence of severe complications （P0.05）. Severe complications occurred in 40 patients. Independent risk factors included age 60 years （OR=5.49， P0.001）， high-grade ALBI （OR=8.30， P0.001）， history of biliary surgery （OR=2.60， P=0.035）， hepatectomy （segmentectomy）≥3 （OR=2.75， P=0.028）， and open surgical approach （OR=4.00， P=0.009）. A nomogram for predicting severe perioperative complications was successfully established. Internal validation showed that the model had an area under the ROC curve （AUC） of 0.865， which outperformed traditional single predictors. The calibration curve closely aligned with the ideal curve， with a mean absolute error （MAE） of 0.027. Decision curve analysis （DCA） demonstrated a net clinical benefit when the threshold probability exceeded 10%， superior to that of traditional predictors. ConclusionThe ALBI score-based nomogram is successfully developed and validated to predict the risk of severe perioperative complications in hepatolithiasis patients undergoing hepatectomy. The model demonstrated favorable predictive performance and high clinical utility， serving as an effective tool for both preoperative risk assessment and postoperative risk stratification.

Background/Aims: Liver transplantation (LT) following total hepatectomy is a life-saving treatment for hepatocellular carcinoma (HCC). The HCC recurrence after LT hinders the effectiveness of the procedure. The objective of this study is to develop a pre-operative risk stratification model based on a liquid biopsy. Methods: We conducted a comprehensive multi-omics study of 260 HCC patients from three centers, including clinical data, low-coverage whole-genome sequencing of cell-free DNA (cfDNA) from plasma, as well as whole-exome, single-nucleus RNA, and spatial transcriptomics from matched tumor and non-tumor tissues. Results: We identified cfDNA-derived copy number alteration (CNA) signatures associated with post-transplant recurrence. By integrating cfDNA-derived CNA profiles with single-cell transcriptomic data, we traced recurrence-associated cfDNA to a distinct subpopulation of malignant cells within the primary tumor. These cells were embedded in a pro-metastatic microenvironment of specialized endothelial subtypes and cancer-associated fibroblasts. Notably, most recurrence-associated lesions were detectable in cfDNA prior to liver transplantation (LT). Building on these insights, we developed the ZJU Criteria based on CNA fragments and tumor markers, a pre-LT risk prediction tool that integrates conventional clinical factors with cfDNA-derived CNA signatures, and validated it using internal and independent external cohorts. Conclusion Our findings suggest that post-transplant recurrence commonly originates from advanced subclones that emerge late during tumor evolution. The ZJU Criteria provides an accurate, non-invasive strategy that significantly improves pre-LT risk stratification and clinical decision-making for patients with HCC.

Objective To study the pathogenic bacteria infection in hospitalized diabetic foot patients in the Third People's Hospital of Yunnan Province and its correlation with different Wagner grades,to understand the the characteristics of pathogenic bacteria and related risk factors in hospitalized diabetic foot patients in the Third People's Hospital of Yunnan Province,and to further provide theoretical guidance for anti-infection treatment of these patients.Methods A retrospective analysis was conducted on the demographic data,severity of foot ulcers,and related laboratory test results of 536 patients with diabetic foot who were detected to have bacterial infection in the Third People's Hospital of Yunnan Province from January 2019 to January 2023.Results Among the 536 diabetic foot patients,pathogenic bacteria were cultured from 268 cases(50.0%)of Gram-positive bacterial infections,214 cases(39.9%)of gram-negative bacterial infections,2 cases(0.4%)of fungal infections,and 52 cases(9.7%)of mixed bacterial infections.The main pathogens among gram-positive bacteria were Staphylococcus aureus,Staphylococcus epidermidis and Enterococcus faecalis.for Gram-negative bacteria,the main pathogens were Escherichia coli,Enterobacter cloacae and Klebsiella pneumoniae.There were 31 cases of multi-drug resistant bacteria,and the multi-drug resistance rate was(5.78%).Among Gram-positive bacteria,all multidrug-resistant strains were Staphylococcus aureus,while among Gram-negative bacteria,the multi-drug resistant strains included Acinetobacter baumannii(1 case),Klebsiella pneumoniae(2 cases),Proteus common(2 cases),Pseudomonas aeruginosa(5 cases),Proteus mirabilis(1 case)and Enterobacter cloacae(1 case).The 536 patients were divided into Wagner grade 1 and 2 groups(78 cases),Wagner grade 3 group(274 cases),and Wagner grade 4 and 5 groups(184 cases).There were 73 cases of single bacterial infections and 5 cases of mixed bacterial infections in Wagner grade 1 and 2 group,including 51 cases(65.4%)of gram-positive bacteria,21 cases(26.9%)of gram-negative bacteria and 1 case(1.3%)of fungi.There were 248 cases of single bacterial infections and 26 cases of mixed bacterial infections in Wagner3 group,with 144 cases(52.6%)of gram-positive bacteria,103 cases(37.6%)of gram-negative bacteria,and 1 case(0.4%)with fungi.In the Wagner grade 4 and 5 groups,there were 163 cases of single bacterial infections and 21 cases of mixed bacterial infection,with 73 strains(39.7%)of gram-positive bacteria,90 strains(48.9%)of gram-negative bacteria and 0 strain(0%)of fungi.The predominant infectious pathogens in Wagner grades 1,2 and 3 were gram-positive bacteria,while those in Wagner grades 4 and 5 patients were mainly gram-negative bacteria.There were statistically significant differences in white blood cell counts,neutrophil percentage,bacterial classification,length of hospital stay,erythrocyte sedimentation rate and albumin levels among diabetic foot patients with different Wagner grades(P<0.01).With the increase of Wagner grade,patients had higher white blood cell counts and hypersensitive C-reactive protein levels,longer hospital stays,and lower albumin levels;however,there were no statistically significant differences in age,sex,duration of diabetes,smoking history,alcohol consumption history and history of hypertension(P>0.05).Conclusion The bacterial infection situation in patients with diabetic foot ulcers is related to different Wagner grades.The higher the Wagner grades,the greater the likelihood of infection with gram-negative bacteria.Antibiotics can be reasonably selected according to the Wagner grades of patients upon admission,actively controlling infection,while also enhancing,shortening hospital stays,and reducing amputation rates,thereby improving the prognosis of diabetic foot patients.

Objective:To investigate the efficacy of laparoscopic versus open hepatectomy for intrahepatic bile duct stones based on propensity score matching. Methods:This study used a case-control design to retrospectively analyze 163 patients with intrahepatic bile duct stones who were treated at The Second Hospital of Anhui Medical University between February 2014 and February 2024. Based on the surgical approach, the patients were divided into two groups: the laparoscopic hepatectomy group ( n = 72) and the open hepatectomy group ( n = 91). Using 1:1 PSM, two groups with similar baseline clinical characteristics were created to compare perioperative outcomes, stone residual rates, and recurrence rates. Results:After PSM, a total of 52 matched pairs were successfully obtained. Compared with the laparoscopic hepatectomy group, the open hepatectomy group demonstrated a significantly shorter operative time [233.00 (180.00, 315.00) minutes vs. 313.00 (222.25, 405.75) minutes, Z = 3.41, P = 0.01]. However, no statistically significant differences were observed between the open hepatectomy and laparoscopic hepatectomy groups in terms of pre- to postoperative hemoglobin change [(22.69 ± 14.27) g/L vs. (20.63 ± 14.36) g/L, t = 0.73, P = 0.465], postoperative bile leakage [5.77% (3/52) vs. 11.54% (6/52), χ2 = 1.10, P = 0.25], hypoalbuminemia [82.69% (43/52) vs. 84.62% (44/52), χ2 = 0.07, P = 0.791], pulmonary infection [28.85% (15/52) vs. 40.38% (21/52), χ2 = 1.53, P = 0.216], surgical site infection [5.77% (3/52) vs. 1.92% (1/52), χ2 = 1.04, P = 0.308], intra-abdominal infection [1.92% (1/52) vs. 5.77% (3/52), χ2 = 1.04, P = 0.308], postoperative drainage tube removal time [8.00 (6.00, 11.75) days vs. 8.00 (6.25, 10.00) days, t = 0.05, P = 0.958], postoperative hospital stay [8.00 (9.00, 15.00) days vs. 9.00 (7.00, 12.50) days, t = -1.22, P = 0.222], residual stone rate [11.54% (6/52) vs. 9.62% (5/52), χ2 = 0.10, P = 0.750], and stone recurrence rate [13.46% (7/52) vs. 3.85% (2/52), χ2 = 3.04, P = 0.081]. All differences were statistically significant (all P > 0.05). Conclusions:Laparoscopic hepatectomy and open hepatectomy have comparable efficacy in the treatment of intrahepatic bile duct stones.

This consensus was developed by the Orthodontic Society of the Chinese Stomatological Association to provide a systematic, scientific, and practical guideline for informed consent in orthodontic care. Orthodontic treatment is typically lengthy, highly individualized, and involves multiple factors such as growth and development, occlusal function, and facial esthetics. Rapid technological advances and diverse risk profiles make the traditional reliance on orthodontist experience or institutional templates insufficient to ensure patients′ full understanding and autonomous decision-making. To address this, the expert panel conducted extensive reviews of domestic and international guidelines, analyzed representative dispute cases, and performed multicenter patient-clinician surveys. Using a multi-round Delphi method, the group established a standardized informed consent framework covering the initial consultation, treatment, and retention phases. The consensus emphasizes that informed consent is not only a fundamental legal and ethical requirement but also a key step in building trust, improving patient compliance, and enhancing treatment satisfaction. Orthodontists should clearly and comprehensively explain treatment plans, potential risks, uncertainties, and associated costs, while respecting the autonomy of patients or guardians, and maintain continuous communication and dynamic evaluation throughout the treatment process. The release of this consensus provides unified and authoritative guidance for clinical orthodontics, helping to standardize informed consent, enhance its transparency, safeguard patient rights, reduce medical risks, and promote high-quality, sustainable development of orthodontic practice.

Objective:To analyze the efficacy and safety of a fully biodegradable occluder for the treatment of ventricular septal defects through percutaneous and transthoracic strategies.Methods:A case series study was conducted.The clinical data of 38 pediatric patients with a ventricular septal defect treated with a fully biodegradable occluder at Central China Fuwai Hospital from January 2023 to July 2024 were retrospectively analyzed.Among these patients, 15 received the percutaneous approach(percutaneous approach group) and the other 23 adopted the transthoracic approach(transthoracic approach group).The diagnosis was confirmed by transthoracic echocardiography before operation in all patients.The percutaneous approach was defined as establishing a venous-arterial track through X-ray and then placing an occluder under the guidance of transthoracic echocardiograph.The transthoracic approach was achieved by establishing a delivery track with a special hollow bougie through a small right subaxillary incision under the real-time guidance of esophageal ultrasound and then delivery and put an occluder.The clinical data of the patients, including general characteristics, electrocardiograms, echocardiograms and the biodegradable occluder system were collected and analyzed.Categorical variables were tested using the chi-square or Fisher′s exact test.Continuous variables were verified using the t-test or Mann-Whitney U test. Results:The patients were aged (5.7±3.9) years on average, with an average weight of 19.5(14.9, 25.9) kg.There were 39.5%(15 cases) of males among the patients included.The average size of the ventricular septal defect was 4.1(4.0, 5.0) mm.A simple perimembrane ventricular septal defect was detected in 29 patients (76.3%), concomitant membranous aneurysm in 4 patients (10.5%), an intracristal ventricular septal defect in 3 patients (7.9%), and a muscular ventricular septal defect in 2 patients (5.3%).Preoperative aortic and tricuspid valve regurgitations accounted for 5.3%(2/38) and 81.6%(31/38), respectively.The average age was (9.0±3.9) years in the percutaneous approach group and (3.6±1.9) years in the transthoracic approach group.In terms of the cardiac structure, the percutaneous approach group had smaller Z values of the left atrial anterior-to-posterior diameter (-0.5±0.6 vs.0.5±1.0, P<0.01) and the left ventricular end-diastolic diameter (-0.5±1.1 vs.0.8±0.8, P<0.01), and a smaller ventricular septal defect [4.0(3.9, 4.2) mm vs.4.5(4.0, 5.5) mm, P=0.01] than the transthoracic approach group.Regarding the operation, the percutaneous approach group had a larger difference between the waist diameter of the selected occluder and the diameter of the ventricular septal defect [2.8(2.0, 3.0) mm vs.2.0(1.5, 2.5) mm, P=0.02], shorter operative time [(61.5±27.3) minutes vs.(91.5±31.4) minutes, P=0.01], and a shorter hospital stay [8(5, 9) days vs.12(9, 15) days, P<0.01] than the transthoracic approach group.Both groups achieved immediate occlusion postoperatively, with no residual shunts and no grade Ⅲ atrioventricular conduction block.Five new cases of bundle branch blocks and 1 case of trivial aortic valve regurgitation occurred in the transthoracic approach group. Conclusions:Both percutaneous and transthoracic approaches are safe and effective in interventional closure of ventricular septal defects, but the former is more applicable to slightly older or heavier patients with a smaller ventricular septal defect, who need a larger occluder.

Targeting T-cell is a strategy to control allogeneic response disorders, such as acute graft-versus-host disease (GVHD) which is an important cause of therapy-failure after allogeneic hematopoietic cell transplants. Free fatty acid receptor-4 (FFAR4) is a regulator of obesity but its role in T-cell and allogeneic reactions is unknown. Here, we found knockout of Ffar4 in donor T-cells in a mouse allograft model increased acute GVHD whereas the natural FFAR4 ligands and the synthetic FFAR4 agonists decreased it. FFAR4 agonist-mediated anti-acute GVHD effects depended on FFAR4-expression in donor T-cells. The FFAR4 agonist CpdA suppressed donor T-cell-mediated alloreaction by activating an aryl hydrocarbon receptor (AhR) pathway. CpdA recruited β-Arrestin2 to FFAR4 which facilitated nuclear translocation of AhR and upregulation of IL-22. The CpdA-mediated anti-acute GVHD effect was absent in mice receiving Ahr-knockout or Il22-knockout T-cells. Recipient-expressing Ffar4 was also important for the anti-acute GVHD effect of CpdA which inhibited activation of antigen presenting cells. Importantly, CpdA decreased acute GVHD in obese mice, an effect also depended on Ffar4-expression in donor T-cells and recipients. Our study shows the immunoregulatory effect of FFAR4 in T-cell, and targeting FFAR4 might be a relative option for controlling allogeneic reactions in obese patients.