Objective To explore the visiting behavior and health management strategy of patients with cardiovascular disease (CVD) and the industry management strategies under the family doctor contract service model. Methods A total of 351 patients with CVD from January 2022 to January 2025 were included in the case investigation by random sampling. Taking the number of visits in community health service institutions/total number of visits ≥90% as high compliance, the influencing factors of the visiting behavior of CVD patients were analyzed. Results Finally, 344 valid questionnaires were collected, with an effective recovery rate of 98.01%. The study subjects were categorized into high compliance group (271 cases) and low compliance group (73 cases). The scores of policy cognition understanding, institutional trust and medical service understanding in the high compliance group were higher compared with those in the low compliance group (P<0.05). There was no significant difference in the understanding of medical expenses between the two groups (P>0.05). Multivariate logistic regression model analysis revealed that CVD duration [OR (95% CI): 1.72 (1.21-2.44)], policy cognition understanding [OR (95% CI): 2.16 (1.20-3.89)] and institutional trust [OR (95% CI): 1.88 (1.08-3.25)] were independently associated with medical treatment behavior in CVD patients (P<0.05). Conclusion Enhancing the policy cognition understanding and institutional trust of CVD patients on family doctor contract service can promote patients to seek medical treatment and promote the high-quality development of family doctor contract service.

Primary biliary cholangitis （PBC） is a cholestatic autoimmune liver disease characterized by the injury of small intrahepatic bile ducts， and at present， the pathogenesis of PBC remains unclear. Recent studies have shown that bile acid metabolism disorder and gut microbiota imbalance play a key role in the development and progression of PBC， and they form a complex and dynamic interaction network via the “gut-liver axis” and regulate core physiopathological processes such as immune response， metabolic homeostasis， and inflammatory response in a synergistic manner. This article systematically elaborates on the abnormal features of bile acid metabolism and gut microbiota in PBC， discusses their synergistic mechanisms in PBC， and then proposes a combined strategy of targeting bile acid receptors and modulating gut microbiota， in order to overcome the limitations of current treatment modalities and provide new insights and directions for the clinical management of PBC.

Purpose: Metastatic rectal cancer (mRC) is a highly lethal and complex disease that demands a multidisciplinary treatment approach. However, the clinical effectiveness of radiotherapy (RT) for de novo mRC remains controversial and uncertain. Methods: This retrospective cohort study examined medical records from Kaohsiung Chang Gung Memorial Hospital for patients with histologically confirmed de novo mRC diagnosed between January 2015 and December 2020. All patients received standard systemic therapy and radical surgery when feasible. The primary outcome, overall survival (OS), was assessed using the Kaplan-Meier method. Multivariable analysis was performed using a Cox regression model. Results: Among 271 patients included in the analysis, 117 received RT and 154 did not. The median OS was significantly longer in the RT group compared with the non-RT group (27.8 months vs. 21.9 months; P=0.046). Multivariate analysis identified several independent predictors of OS: age ≥65 years (hazard ratio [HR], 1.69; 95% confidence interval [CI], 1.26–2.27; P=0.001), primary tumor resection (HR, 2.62; 95% CI, 1.90–3.61; P<0.001), M1b or M1c disease (HR, 1.97; 95% CI, 1.44–2.69; P<0.001), and receipt of RT (HR, 1.41; 95% CI, 1.02–1.94; P=0.036). Conclusion RT significantly improves OS in patients with mRC, underscoring its role in treatment strategies. These findings support its inclusion in therapeutic protocols and highlight the need for larger, multicenter trials to confirm and extend these results.

Malignant tumors represent a major threat to global health. Conventional anti-tumor pharmacotherapy often encounters challenges such as drug resistance, highlighting an urgent need for the development of novel therapeutic strategies. Fatty acid synthase (FASN), the key enzyme catalyzing de novo fatty acid synthesis, is subject to precise regulation at multiple levels, including transcriptional control, various post-translational modifications such as ubiquitination and phosphorylation, as well as modulation by diverse signaling pathways. Recent studies have revealed that FASN is aberrantly overexpressed in various malignant tumors and is closely associated with tumor progression and poor patient prognosis. FASN is a homodimer composed of seven functional domains that catalyzes the NADPH-dependent condensation of acetyl-CoA and malonyl-CoA to generate saturated fatty acids, primarily palmitic acid. Its stability is regulated by multiple ubiquitin ligases and deubiquitinating enzymes. Additionally, FASN is subject to upstream regulation via neural precursor cell-expressed developmentally downregulated 8 (Nedd8) modification and the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) pathway, thereby establishing a metabolic-signaling positive feedback loop. As a core executor of metabolic reprogramming, FASN promotes tumorigenesis through dual mechanisms. First, its fatty acid synthesis product, palmitate, participates in membrane phospholipid synthesis, lipid raft formation, and protein palmitoylation, thereby activating several key oncogenic signaling pathways, including PI3K/AKT/mTOR, wingless-type MMTV integration site family member (Wnt)/β‑catenin, and signal transducer and activator of transcription 3 (STAT3)/matrix metalloproteinase (MMP), leading to tumor development and progression. Second, FASN plays a pivotal role in modulating the anti-tumor functions of immune cells and remodeling the tumor immune microenvironment. Specifically, FASN enhances immune checkpoint inhibition by inducing programmed death-ligand 1 (PD-L1) palmitoylation, suppresses the activation of cytotoxic T lymphocytes and natural killer cells, and promotes the polarization of M2-type macrophages, consequently facilitating tumor immune evasion and malignant progression. Precisely due to its significant overexpression in tumor cells, its critical functional role, and its differential expression compared to normal cells, FASN has emerged as a highly promising target for anti-tumor drug development. Highly selective small-molecule inhibitors, notably represented by TVB-2640, have advanced to clinical trial stages and demonstrated favorable anti-tumor activity. Furthermore, the combination of FASN inhibitors with other chemotherapeutic agents or targeted drugs can overcome the limitations of monotherapy through synergistic effects or by resensitizing tumor cells to conventional drugs, achieving a “1+1>2” therapeutic outcome. With the advancement of modern traditional Chinese medicine (TCM), numerous active ingredients derived from TCM have been confirmed to exert anti-tumor effects by modulating FASN-related pathways. This integrated approach leverages the precision of Western medicine while simultaneously harnessing the holistic regulatory benefits of TCM to alleviate the side effects of radiotherapy and chemotherapy. Despite the promising prospects of FASN-targeted therapies, challenges remain, including tumor cell metabolic plasticity, tumor context-dependent responses, and heterogeneity. This review systematically summarizes the molecular structure, physiological functions, and mechanisms of FASN in tumorigenesis, as well as recent advances in targeted therapies. Future directions—including the precise identification of responsive patient populations using spatial transcriptomics, the development of novel combination regimens, and the active exploration of integrative strategies combining traditional Chinese and Western medicine—will facilitate the clinical translation of FASN-targeted therapies and open new avenues for improving the quality of life and prognosis of cancer patients.

Mammalian male germline development depends on a specialized gonadal somatic microenvironment. However, itsin vitro reconstruction remains challenging. Major barriers include the generation of appropriate supporting-cell lineages, organized tissue architecture, and culture conditions that sustain germ-cell maturation. Yoshino et al. established a mouse pluripotent stem cell-derived testicular organoid model. This model reconstitutes the sex-determining region Y (Sry)-SRY-box transcription factor 9 (Sox9)‑mediated sex-determination program and generates testicular somatic cell-like cells (TesLCs). When assembled with primordial germ cell-like cells (PGCLCs), TesLCs formed seminiferous tubule-like structures and supported male germline progression toward prospermatogonia and germline stem cell-like cells (GSCLCs). After transplantation into infertile recipient testes, organoid-derived GSCLCs produced fertilization-competent sperm and generated fertile offspring. The major significance of this work extends beyond sperm production. It integrates sex determination, germ-cell fate transition, and testicular niche self-organization into an experimentally tractable organoid system. This commentary discusses the technical strategy, sex-determination mechanism, value of testicular niche reconstruction, and translational limitations of this study. It also highlights its implications for in vitro gametogenesis, male infertility modeling, and reproductive medicine.

The 2024 National Education Work Conference pointed out that at the current juncture of the critical period for achieving the goals and tasks of the 14th Five-Year Plan,the implementation of the Education Powerhouse Construction Plan Outline should be taken as the main line of work,and building first-class disciplines is an crucial task for a higher education powerhouse.In 2022,forensic medicine was officially listed as a first-level discipline under the medical category,presenting an un-precedented historical opportunity for the development of forensic medicine.The forensic medicine dis-cipline of Southern Medical University comprehensively improves the quality of talent cultivation and facilitates the construction of first-class disciplines as its main direction.It aims to initiate and imple-ment a high-level faculty team building plan featuring"combining recruitment and cultivation,inter-disciplinary integration";make vigorous efforts to establish a first-level doctoral program,refine advan-tageous second-level disciplines and research directions;and establish an innovative research platform from a high starting point with deep integration.The discipline adheres to moral cultivation and the Five Domains of Education simultaneous development,to build a high-quality talent joint training model.Guided by the construction of the national legal system and industry needs,the discipline will enhance social service capabilities.The forensic medicine construction in our university will continue to contribute to the rule of law in China and educational power.

Objective To explore a deep learning-based automatic bone age estimation model for elbow joint X-ray images of Chinese Han adolescents and children and evaluate its performance.Methods A total of 943(517 males and 426 females)elbow joint frontal view X-ray images of Chinese Han ado-lescents and children aged 6.00 to<16.00 years were collected from East,South,Central and North-west China.Three experimental schemes were adopted for bone age estimation.Scheme 1:Directly in-put preprocessed images into the regression model;Scheme 2:Train a segmentation network using"key elbow joint bone annotations"as labels,then input segmented images into the regression model;Scheme 3:Train a segmentation network using"full elbow joint bone annotations"as labels,then in-put segmented images into the regression model.For segmentation,the optimal model was selected from U-Net,UNet++and TransUNet.For regression,VGG16,VGG19,InceptionV2,InceptionV3,ResNet34,ResNet50,ResNet101 and DenseNet121 models were selected for bone age estimation.The dataset was randomly split into 80%(754 samples)for training and validation for model fitting and hyperparameter tuning,and 20%(189 samples)as an internal test set to test the performance of the trained model.An additional 104 elbow joint X-ray images from the same demographic and age group were col-lected and used as an external test set.Model performance was evaluated by comparing the mean ab-solute error(MAE),root mean square error(RMSE),accuracies within±0.7 years(P±0.7 years)and±1.0 years(P±1.0 years)between the estimated age and the actual age,and by drawing radar charts,scat-ter plots,and heatmaps.Results When segmented with Scheme 3,the UNet++model achieved good segmentation performance with a segmentation loss of 0.000 4 and an accuracy of 93.8%at a learning rate of 0.000 1.In the internal test set,the DenseNet121 model with Scheme 3 yielded the best results with MAE,P±0.7 years and P±1.0 years being 0.83 years,70.03%,and 84.30%,respectively.In the external test set,the DenseNet121 model with Scheme 3 also performed best,with an average MAE of 0.89 years and an average RMSE of 1.00 years.Conclusion When performing automatic bone age estima-tion using elbow joint X-ray images in Chinese Han adolescents and children,it is recommended to use the UNet++model for segmentation.The DenseNet121 model with Scheme 3 achieves optimal per-formance.Using segmentation networks,especially that trained with annotation areas encompassing the full elbow joint including the distal humerus,proximal radius,and proximal ulna,can improve the ac-curacy of bone age estimation based on elbow joint X-ray images.

Objective To explore a deep learning network model suitable for bone age estimation using shoulder joint X-ray images in Chinese Han adolescents.Methods A retrospective collection of 1 286 shoulder joint X-ray images of Chinese Han adolescents aged 12.0 to<18.0 years(708 males and 578 females)was conducted.Using random sampling,approximately 80%of the samples(1 032 cases)were selected as the training and validation sets for model learning,selection and optimization,and the other 20%samples(254 cases)were used as the test set to evaluate the model's generalization ability.The original single-channel shoulder joint X-ray images and dual-channel inputs combining original images with segmentation labels(manually annotated shoulder joint regions multiplied pixel-by-pixel with original images,followed by segmentation via the U-Net++network to retain only key shoulder joint region information)were respectively input into four network models,namely VGG16,ResNet18,ResNet50 and DenseNet121 for bone age estimation.Additionally,manual bone age estimation was con-ducted on the test set data,and the results were compared with the four network models.The mean absolute error(MAE),root mean square error(RMSE),coefficient of determination(R2),and Pear-son correlation coefficient(PCC)were used as main evaluation indicators.Results In the test set,the bone age estimation results of the four models with dual-channel input of shoulder joint X-ray images outperformed those with single-channel input in all four evaluation indicators.Among them,DenseNet121 with dual-channel input achieved best results with MAE of 0.54 years,RMSE of 0.82 years,R2 of 0.76,and PCC(r)of 0.88.Manual estimation yielded an MAE of 0.82 years,ranking second only to dual-channel DenseNet121.Conclusion The DenseNet121 model with dual-channel input combined with original images and segmentation labels is superior to manual evaluation results,and can effectively estimate the bone age of Chinese Han adolescents.

Objective To establish a rapid analysis method for cyanide based on a ratiometric fluores-cent probe,providing a quantitative strategy for on-site visual and rapid detection of cyanide.Methods A dual-emission ratiometric fluorescent probe(AuNCs-FL)was constructed by using bovine serum al-bumin(BSA)-stabilized gold nanoclusters(AuNCs,fluorescence emission at 660 nm)as the responsive signal unit and fluorescein(FL,emission at 515 nm)as the internal reference.Results The etching effect of cyanide on AuNCs resulted in fluorescence quenching at 660 nm,while the fluorescence inten-sity of FL at 515 nm remained unchanged,enabling a rapid response analysis of cyanide shift from red to green fluorescence.The developed probe enabled rapid analysis of cyanide within 3 min,with a limit of detection(LOD)of 3.4 mg/L and a visual detection range of 10-100 mg/L.Conclusion The AuNCs-FL fluorescent probe is structurally simple,low-cost,and easy to operate,delivering rapid and accurate results.It also avoids the interference from sulfides encountered in commercial cyanide test kits,making it suitable for the on-site rapid detection of suspected powder samples in cyanide poisoning cases.

Complications such as pancreatic leakage,biliary leakage and abdominal infection may occur after pancreaticoduodenectomy.Previous surgeons have recommended routine preventive drainage for early detection and treatment of complications.In recent years,with the rise of the idea of accelerated rehabilitation,this view has been questioned and disputed.In this paper,five aspects of drainage tube placement after pancreaticoduodenectomy,drainage mode,drainage placement area,when to remove the drainage tube,and re-catheter drainage after surgery are reviewed.