Objective:Patients with decompensated hepatitis B virus (HBV)- and hepatitis C virus (HCV)-related cirrhosis are at high risk of first variceal bleeding, yet etiology-specific and stage-specific prediction models remain limited. This study aimed to develop and internally validate nomogram models for predicting the risk of first variceal bleeding in this population. Methods:This retrospective cohort study included 451 patients with decompensated HBV- or HCV-related cirrhosis (331 HBV-related and 120 HCV-related), of whom 230 experienced first variceal bleeding. Random Forest and XGBoost algorithms were used for feature selection, followed by multivariable logistic regression to develop etiology-specific nomogram models. Internal validation was performed using a training-testing split. Model discrimination, calibration, and clinical utility were assessed using the area under the receiver operating characteristic curve (AUC), bootstrap resampling, and decision curve analysis, respectively. Partial Dependence Plots (PDPs) midpoint risk (≈0.5) set clinical thresholds. Results:Seven predictors were retained for HBV (Hemoglobin, Ascites Depth, Total Protein, Prothrombin Activity [PTA], Total Bile Acid [TBA], D-dimer, and White Blood Cell Count [WBC]) and three for HCV (Hemoglobin, PTA, and TBA), with an AUC of 0.9239 (95% CI 0.8941-0.9537) and 0.9127 (95% CI 0.8646-0.9609), respectively. The models showed good calibration and clinical utility on decision curve analysis. PDPs indicated 0.5-risk thresholds at 96.12 g/L (Hemoglobin), 60.75 g/L (Total Protein), 30.58 mm (Ascites Depth), 49.2% (PTA), 25.78 µmol/L (TBA), 2.24 mg/L (D-dimer), and 5.33×109/L (WBC) for HBV, and 46.81% (PTA), 82.4 g/L (Hemoglobin), 47.51 µmol/L (TBA) for HCV. Conclusion:Etiology-specific nomogram models were developed to predict first variceal bleeding in patients with decompensated HBV- and HCV-related cirrhosis. The models showed good discriminative performance in internal validation and may assist in risk stratification. However, further prospective multicenter studies with external validation are needed before clinical implementation.
Yu Zeng,1,2 Li Bao,3 Jian Li,4 Yanyan Hong11Department of Nursing, Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine, Nanjing, Jiangsu, People’s Republic of China; 2School of Nursing, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, People’s Republic of China; 3Department of Oncology, Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine, Nanjing, Jiangsu, People’s Republic of China; 4Department of Proctology, Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine, Nanjing, Jiangsu, People’s Republic of ChinaCorrespondence: Yanyan Hong, Email yyhong197503@163.comBackground: Early mucosal edema is a common and burdensome complication following prophylactic ileostomy in elderly rectal cancer patients, yet effective tools for its pre-operative prediction are lacking. This study aimed to develop and validate an interpretable, machine learning-guided logistic regression model for this specific outcome.Patients and Methods: In this retrospective cohort study, 296 eligible patients were included. The cohort was randomly split into a training set (n=207) for model development and an internal test set (n=89) for validation. A consensus machine learning approach, integrating Least Absolute Shrinkage and Selection Operator (LASSO) regression, stepwise forward logistic regression, and Random Forest with Recursive Feature Elimination (RF-RFE), was employed to select core predictors from comprehensive clinical data. The final predictive model is a standard multivariable logistic regression. Model performance was validated via internal bootstrap resampling, ten-fold cross-validation, and external dataset testing, and assessed by discrimination, calibration, and decision curve analysis, with interpretability enhanced using SHAP (SHapley Additive exPlanations) values. Generalizability was tested in an external cohort (n=40).Results: Five variables were consistently selected as core predictors: the Prognostic Nutritional Index (PNI), preoperative neutrophil-to-lymphocyte ratio (NLR), intraoperative fluid intake, abdominal wall opening size, and time to first postoperative bowel movement. The model incorporates early postoperative variables and is intended for early perioperative risk stratification, not solely preoperative prediction. The final multivariable logistic regression model, presented as a nomogram, demonstrated good discriminatory ability in the training (AUC=0.838, 95% CI: 0.706– 0.845) and test (AUC=0.826, 95% CI: 0.743– 0.910) sets. Internal robustness was supported by ten-fold cross-validation (mean AUC=0.813, 95% CI: 0.680– 0.960). The model maintained acceptable performance in the external validation cohort (AUC=0.820), though some miscalibration was noted. Subgroup analysis suggested that a smaller abdominal opening and delayed bowel function were specifically associated with progression to severe edema.Conclusion: We developed and validated an interpretable, machine learning-guided logistic regression model for early mucosal edema, incorporating five readily available clinical variables. The model, available as an online nomogram, provides a practical tool for perioperative risk stratification, potentially guiding individualized patient counseling and targeted management strategies to mitigate this complication.Keywords: early mucosal edema, machine learning, nomogram, predictive model, prophylactic ileostomy, rectal cancer
Background:Cervical spondylosis frequently recurs after conservative treatment, but its predictors remain unclear. This study aimed to identify factors associated with recurrence and develop a predictive nomogram. Methods:This retrospective analysis used data from a multicenter cross-sectional survey (six Chinese cities, March-November 2025). We identified 668 patients who reported remission after systematic conservative treatment and retrospectively collected their post-treatment recurrence status via self-report. Potential predictors included demographics, lifestyle, clinical history, and radiographic findings. The sam ple was randomly split into training (70%) and validation (30%) sets. Multivariable logistic regression identified independent predictors, and a nomogram was constructed. Model performance was evaluated using AUC, calibration, and decision curve analysis. Supplementary analyses examined episode frequency and time to recurrence. Results:Six independent predictors were identified: exercise duration per session (OR=0.992), neck length (OR=0.850), disc space narrowing (OR=0.478), disease duration (overall P<0.001), pre-treatment attack frequency (overall P<0.001), and PCS score (OR=0.943). Compared with disease duration <3 months, 3-11 months increased risk (OR=2.691); pre-treatment attacks ≥6/month raised risk (OR=4.608). The nomogram showed good discrimination (training AUC=0.760) and net benefit. Longer exercise was associated with delayed recurrence, while longer disease duration and frequent prior episodes increased recurrence risk; disc narrowing paradoxically predicted lower recurrence. Conclusion:Post-treatment recurrence is associated with multifactorial factors, including modifiable elements like exercise and physical health, as well as disease chronicity. Imaging changes may prompt protective behaviors. These findings support individualized risk stratification, but causal inference requires prospective validation.
Background:Hypertension is frequently accompanied by metabolic abnormalities that increase cardiovascular risk. The triglyceride-glucose (TyG) index is a practical surrogate marker of insulin resistance. This study aimed to compare TyG index values and related metabolic parameters between patients receiving RAAS blockers plus thiazide/thiazide-like diuretics and those receiving RAAS blockers plus calcium channel blockers (CCBs) as antihypertensive regimens. Methods:In this retrospective observational study, 157 of 189 screened patients met eligibility criteria and were included (RAAS blocker plus thiazide/thiazide-like diuretic, n=95; RAAS blocker plus CCB, n=62). Multivariable linear regression models and inverse probability of treatment weighting (IPTW) analyses were performed to assess the independence of findings from clinical confounders. Results:The TyG index was significantly higher in the diuretic group than in the CCB group [9.21 (9.01-9.73) vs 8.95 (8.66-9.40); p<0.001], as were triglyceride [186.00 vs 142.35 mg/dL; p<0.001] and uric acid levels [5.70 vs 5.00 mg/dL; p=0.004]. Blood pressure control rates were similar. The treatment group effect remained significant across all adjusted models, including IPTW-weighted regression (β=0.385, p=0.0003). A significant treatment group × diabetes mellitus interaction was observed (p=0.042), suggesting a stronger association in diabetic patients. A dose-stratified analysis within the diuretic group showed a significant dose-response relationship: higher hydrochlorothiazide (25 vs 12.5 mg/day) and indapamide (2.5 vs 1.25 mg/day) doses were both associated with significantly higher TyG index, fasting glucose, and uric acid levels. In an exploratory diuretic subgroup analysis, urea and BUN levels were higher with hydrochlorothiazide than indapamide; however, this analysis was underpowered (indapamide n=24) and should be interpreted with caution. Conclusions:RAAS blocker plus thiazide/thiazide-like diuretic regimens were associated with a significantly higher TyG index and a less favorable metabolic profile than RAAS blocker plus CCB regimens, independent of multiple clinical confounders. Metabolic risk profiles should be considered when selecting antihypertensive combination therapy; prospective studies are needed to establish causality.
Background:Remote mountainous areas face severe challenges regarding medical resource scarcity and delayed emergency treatment. While the "Walking Hospital" model has physically descended medical hardware to the village level, the efficacy of these interventions is bottlenecked by the limited diagnostic capabilities of grassroots doctors. Methods:This narrative review synthesizes literature identified through searches in PubMed, IEEE Xplore, and Web of Science, focusing on articles published between January 2017 and March 2026. Keywords included "mobile health", "artificial intelligence", "telemedicine", "rural health", "drone logistics", and "edge computing". We prioritized peer-reviewed articles, clinical trials, and policy analyses relevant to resource-limited settings. Due to the heterogeneity of study designs and the emerging nature of the topic, a formal meta-analysis was not conducted; instead, a qualitative synthesis of technological models and operational frameworks is presented. Results:The review finds that the deep integration of edge computing, natural language processing (NLP), and computer vision (CV) empowers village doctors with specialist-level diagnostic capabilities offline. Technically, lightweight AI models enable real-time ECG interpretation and ultrasound guidance in network dead zones. Operationally, a closed-loop ecosystem integrating Low-Earth-Orbit (LEO) satellite communications, medical drone logistics, and county-level medical consortia is identified as a sustainable framework. Global case studies from Rwanda, India, and Australia validate the feasibility of AI-optimized aerial logistics and edge-based diagnostics in resource-limited settings. However, critical barriers remain, including algorithmic generalization deficits (domain shift) and ambiguous liability frameworks. Conclusion:AI-empowered "Walking Hospitals" represent a paradigm shift from hardware distribution to capability enhancement. Future research must prioritize resolving domain shift through techniques like Federated Learning, establishing sustainable reimbursement models, and developing community-level data governance frameworks to transition these innovations from pilot projects to scalable global solutions.
Plasma cell mastitis (PCM) is a predominant form of non-lactational mastitis with an increasing incidence worldwide. The condition is characterized by a complex pathogenesis, difficulties in differential diagnosis, and a high rate of recurrence, thereby presenting significant challenges in clinical management. Conventional Western medicine is limited by high postoperative recurrence, difficulty in distinguishing PCM from breast cancer, and unsatisfactory long-term efficacy of single anti-inflammatory or hormone therapy. Against these clinical bottlenecks, Traditional Chinese medicine (TCM) shows unique advantages and accumulated extensive clinical experience for the treatment of PCM. This review systematically delineates the epidemiological characteristics and key pathophysiological mechanisms, including activation of the IL-6/STAT3 signaling pathway, immune cell dysregulation, autoimmune responses, distinctive plasma cell infiltration, and diagnostic methodologies such as imaging techniques, histopathological examination as the diagnostic gold standard, and emerging biomarkers. In addition, the theoretical foundations, contemporary pharmacological mechanisms, and clinical applications of comprehensive TCM therapy for PCM are summarized. Evidence indicates that TCM interventions, guided by syndrome differentiation and targeting liver qi stagnation, phlegm-stasis congealing, and heat-toxin accumulation, exert therapeutic effects by modulating inflammatory signaling pathways, correcting immune dysfunction, and restoring the mammary gland microecological balance. Clinical trials have demonstrated that combining TCM with surgical procedures or western medical treatments significantly improves clinical outcomes, reduces inflammatory mediator levels, and lowers recurrence rates. However, there remains a need for standardization in TCM syndrome differentiation, therapeutic evaluation criteria, and high-quality randomized controlled trials. In summary, integrated TCM therapy constitutes a safe and effective approach for managing PCM, and further rigorous research is warranted to enhance its clinical application and facilitate international recognition of TCM in PCM treatment.
Objective:To investigate serum myeloperoxidase-DNA (MPO-DNA) and C-C motif chemokine ligand 26 (CCL26) levels in pediatric multidrug-resistant organism (MDRO)-associated pneumonia and their association with 28-day prognosis. Methods:In this single-center prospective cohort study, 220 pediatric patients hospitalized for MDRO-associated pneumonia (February 2022-February 2025) were enrolled. Serum MPO-DNA, CCL26, C-reactive protein (CRP), and procalcitonin (PCT) were measured by ELISA within 24 h of admission. Patients were classified into good-prognosis (clinical improvement, ≥50% pulmonary lesion absorption, no severe complications) and poor-prognosis (treatment failure, severe complications, or death within 28 days) groups. Multivariable logistic regression and ROC analysis were performed. Results:Of 220 patients, 68 (30.9%) had poor prognosis. The poor-prognosis group showed significantly elevated CRP, PCT, MPO-DNA, and CCL26 (all P < 0.05). MPO-DNA and CCL26 were positively correlated (r = 0.507, P < 0.001). Multivariable analysis indicated elevated CRP (OR = 1.714, 95% CI: 1.389-2.116), PCT (OR = 1.739, 95% CI: 1.497-2.021), MPO-DNA (OR = 1.007, 95% CI: 1.003-1.011), and CCL26 (OR = 1.002, 95% CI: 1.001-1.004) as independent risk factors (all P < 0.05). ROC analysis showed AUC values for MPO-DNA, CCL26, and their combination of 0.799, 0.816, and 0.872, respectively, with the combined model significantly superior to either alone (all P < 0.05). Conclusion:Elevated serum MPO-DNA and CCL26 levels are associated with 28-day poor prognosis in pediatric MDRO pneumonia. Combined detection shows favorable discriminative performance. However, given the single-center design and lack of external validation, clinical utility requires further multicenter confirmation.
Background:Inflammatory chemokines may participate in the progression of diabetic kidney disease (DKD). However, the clinical value of macrophage inflammatory protein-1β (MIP-1β) for identifying macroalbuminuria in DKD remains insufficiently defined. This study aims to construct a nomogram-based prediction model to evaluate MIP-1β level in predicting DKD progression. Methods:In this prospective, single-center observational study, 198 DKD patients and 198 type 2 diabetes mellitus patients without DKD were consecutively recruited from July 2021 to July 2023. DKD patients were stratified into microalbuminuria (A2, n=146) and macroalbuminuria (A3, n=52) groups. Multivariate logistic regression identified risk factors for macroalbuminuria. A nomogram incorporating significant variables was constructed and internally validated using bootstrap method. Model performance was evaluated via receiver operating characteristic (ROC) analysis and decision curve analysis. Results:MIP-1β levels were significantly higher in the DKD group than non-DKD group (78.88±21.18 vs 67.75±16.25 pg/mL, P<0.001). For predicting DKD, MIP-1β had an area under the ROC curve of 0.711 (95% CI: 0.661-0.762), with 62.6% sensitivity and 74.2% specificity. Independent risk factors for macroalbuminuria included MIP-1β (adjusted odds ratio=1.089, 95% CI: 1.052-1.127), urea nitrogen (1.694, 95% CI: 1.142-2.513), and cystatin C (7.728, 95% CI: 1.843-32.400). The nomogram incorporating these predictors achieved 88.5% sensitivity and 91.1% specificity, with C-index of 0.852 and good calibration. Conclusion:MIP-1β level is independently associated with macroalbuminuria in DKD patients. The nomogram model demonstrates high predictive value for macroalbuminuria and may assist risk stratification in DKD patients; however, external validation is required.
Background:Carotid plaque calcification is an active multicellular process with heterogeneous clinical implications. However, endothelial cell (EC) heterogeneity and plaque-region-specific EC states associated with calcified lesions remain incompletely characterized. Methods:We performed an exploratory integrative analysis of the public single-cell RNA sequencing dataset GSE159677, comprising paired calcified core (AC) and proximal adjacent (PA) tissues from three patients, together with a single-center proteomic cohort of three additional patients with paired AC and PA samples. Major plaque cell populations and EC subclusters were identified by unsupervised clustering and canonical markers. Calcium signaling activity, pathway enrichment, ligand-receptor communication, and Monocle2 pseudotime trajectories were analyzed. Transcriptomic findings were compared with differentially expressed proteins to identify cross-omics candidate molecules. Results:A total of 35,890 cells were classified into seven major cell types. AC and PA tissues showed distinct cellular compositions and signaling patterns. Re-clustering of 4,925 ECs identified six subclusters, including a calcium signaling-high EC cluster enriched for extracellular matrix organization, inflammatory signaling, cytoskeletal regulation, and endothelial-to-mesenchymal transition-related programs. CellChat analysis indicated plaque-region-specific communication networks involving ECs, immune cells, fibroblasts, and smooth muscle cells. Pseudotime analysis suggested heterogeneous EC state transitions rather than a definitive longitudinal progression. Cross-omics comparison identified eight candidate molecules, FABP4, FABP5, MYL12A, POSTN, S100A10, SERPINB1, SOD2, and TMSB10, with concordant changes across transcriptomic and preliminary proteomic analyses. Conclusion:These exploratory findings characterize plaque-region-specific EC heterogeneity associated with carotid plaque calcification and nominate candidate pathways and molecules for further validation in larger cohorts and functional models.
Metabolic dysfunction-associated steatohepatitis (MASH) is a progressive form of metabolic dysfunction-associated steatotic liver disease (MASLD) characterized by steatosis, inflammation, hepatocellular injury, and fibrosis. The pathogenesis of MASH is complex and involves multiple factors, such as lipotoxicity, insulin resistance (IR), genetic susceptibility, endoplasmic reticulum (ER) stress, mitochondrial dysfunction, and dysregulation of the hepatic immune microenvironment. Currently, the clinical treatment for MASH remains challenging. Traditional Chinese medicine (TCM) has shown broad prospects in the prevention and treatment of MASH owing to its multi-target and multi-pathway regulation. This review summarizes the pathophysiological basis of MASH relevant to TCM intervention and discusses the effects of TCM formulas, active compounds, and comprehensive treatment strategies on lipid metabolism, IR, inflammation, autophagy and ferroptosis, intestinal barrier function, immune regulation, fibrosis, and clinical outcomes. We also discuss current clinical evidence, safety considerations, and remaining limitations, with the aim of providing a clearer basis for the clinical application and further investigation of TCM in MASH management.
Objective:Traumatic spinal cord injury (TSCI) is a severe neurological urgency. Neuritin is a neurotrophic factor. This study aimed to explore prognostic predictive value of serum neuritin levels in TSCI. Methods:In this prospective cohort study, serum neuritin levels were quantified at admission of 126 patients and at study entry of 126 controls. The American Spinal Injury Association Impairment Scale (AIS) was used as the severity index. Poor prognosis was defined as no improvement in AIS grade at six months post TSCI versus admission. The results were analyzed using multivariate regression method. Results:Serum neuritin levels were significantly higher in patients with TSCI than in controls. No significant departure from linearity was detected between serum neuritin levels, AIS grade and poor prognosis in the restricted cubic spline. AIS grade was independently correlated with serum neuritin levels. Age, AIS grade, and serum neuritin levels were independently associated with poor prognosis. Receiver operating characteristic (ROC) curve analysis showed that poor prognosis was effectively predicted by serum neuritin levels. The results of the regression analysis were robust via sensitivity analysis, variance inflation factor estimation, the Hosmer-Lemeshow test, and Brier score calculation. The prognosis model incorporating AIS grade, age, and serum neuritin levels was visualized by nomogram, had satisfactory goodness of fit under the calibration curve, showed substantially high discrimination efficiency through the ROC curve approach, and displayed good clinical validity as demonstrated by the decision curve through internal validation. Serum neuritin levels partially mediated the association between AIS grade and poor prognosis. Conclusions:Elevated serum neuritin levels are closely associated with TSCI severity and poor prognosis following TSCI, indicating that serum neuritin may serve as a potential prognostic biomarker of TSCI.
Yuchang Ma, Shiyu Tian, Yaowen Zhang, Chenxu Jiao, Haiyong YeThe First School of Clinical Medicine, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou City, Zhejiang Province, People’s Republic of ChinaCorrespondence: Haiyong Ye, Email 104514118@qq.comAbstract: Osteoporosis has traditionally been viewed as a bone remodeling disorder characterized by excessive bone resorption and inadequate bone formation. However, this paradigm does not fully explain its systemic heterogeneity, persistent progression, or variable therapeutic responses. This review reconceptualizes osteoporosis as a systemic remodeling disorder driven by immunometabolic dysregulation within the bone marrow microenvironment. Upstream risk factors, including estrogen deficiency, inflammaging, gut microbiota dysbiosis, lipid dysmetabolism, and chronic low-grade inflammation, do not act solely on terminal osteoblasts or osteoclasts; instead, they are hierarchically translated within the marrow niche. These perturbations reshape hematopoietic lineage commitment, redirect Bone Marrow Mesenchymal Stem Cells(BMSC) osteogenic-adipogenic fate, promote pathological marrow adipose tissue expansion, and establish a pro-inflammatory, osteoclastogenic milieu through T helper 17 (Th17)/regulatory T (Treg) imbalance, monocyte/macrophage remodeling, inflammasome activation, and osteoclast metabolic reprogramming. Consequently, the marrow niche shifts from an osteogenesis-supportive state toward a self-reinforcing pathological ecosystem marked by enhanced resorption, impaired formation, and marrow adiposity. We further discuss emerging strategies involving microecological remodeling, immune phenotype correction, metabolic checkpoint modulation, BMSC fate regulation, and biomaterial-based niche repair. Importantly, the current evidence base is derived predominantly from postmenopausal osteoporosis and ovariectomized animal models, whereas validation across other osteoporosis subtypes and in prospective human studies remains limited. Accordingly, the broader applicability of this immunometabolic framework should be regarded as an emerging hypothesis requiring further clinical validation. Nevertheless, it may provide a conceptual basis for understanding osteoporosis heterogeneity and developing subtype-stratified precision interventions beyond conventional anti-resorptive and anabolic therapies.Keywords: osteoporosis, immunometabolic dysregulation, bone marrow niche, precision therapy
Jialin Shao,1,2 Haibin Zhao,1 Wanli Ding,1,2 Yiwei Gui,1,2 Wantong Wang,1,2 Junqing Wang,1,2 Chao Wang11Department of Cardiology, Dongfang Hospital, Beijing University of Chinese Medicine, Beijing, People’s Republic of China; 2The Second Clinical Medical College, Beijing University of Chinese Medicine, Beijing, People’s Republic of ChinaCorrespondence: Chao Wang, Department of Cardiology, Dongfang Hospital, Beijing University of Chinese Medicine, No. 6 Fangxingyuan 1st District, Fangzhuang, Fengtai District, Beijing, 100078, People’s Republic of China, Email wangchaozhongyi@sina.cn Haibin Zhao, Email bucmsxktz@163.comBackground: Pericoronary adipose tissue (PCAT) radiomics provides a CT-derived phenotype of perivascular inflammation and tissue heterogeneity. This review evaluated the predictive performance, validation, incremental value, and methodological quality of PCAT radiomics-based prediction models for cardiovascular events.Methods: This PROSPERO-registered systematic review (CRD420261417591) followed PRISMA 2020. PubMed and Web of Science Core Collection were searched for original human studies from 1 January 2014 to 8 June 2026. Data were extracted on populations, outcomes, region of interest definitions, radiomics workflows, model structure, performance, validation, calibration, clinical utility, and incremental value. Risk of bias and applicability were assessed using PROBAST.Results: Eighteen studies reported 74 prediction models, including 44 incorporating PCAT radiomics. Populations, outcomes, prediction horizons, region-of-interest strategies, and modelling workflows were heterogeneous, limiting comparison of AUCs and C-indices. Most outcomes were study-defined composite major adverse cardiovascular events; cardiovascular death and myocardial infarction were rarely evaluated separately. PCAT radiomics features were assessed as standalone signatures or incorporated into clinical-radiomics and multimodal models. Among studies with comparator models, most reported improved discrimination after adding PCAT radiomics, but formal incremental-value assessment was uncommon. Four studies (22.2%) reported external validation, external testing, or cohort-wide prognostic testing. Calibration was reported in 13 studies and decision-curve analysis in 15, but reporting was often incomplete or graphical. NRI or IDI was reported in 3 studies, and 7 assessed reproducibility or applied ICC-based feature filtering. PROBAST identified high overall risk of bias in 11 studies and unclear risk in 7; none had low overall risk.Conclusion: The use of PCAT radiomics for cardiovascular event prediction warrants further investigation as a potential adjunct to CT-based risk stratification. However, methodological heterogeneity, limited external validation, incomplete incremental-value assessment, and risk of bias mean that improvement in routine risk stratification remains unestablished. Standardized workflows and external validation are required before implementation.Keywords: pericoronary adipose tissue, radiomics, coronary computed tomography angiography, cardiovascular events, prediction model
Chen Li,1 Xinyu Cui,2 Yong Yang,2 Xiaoyang Li,2 Junyu Zhang,1 Bo Gao,1 Yingying Niu21Department of Medical Imaging, Mudanjiang Medical University, Mudanjiang, People’s Republic of China; 2Department of Public Health, Mudanjiang Medical University, Mudanjiang, People’s Republic of ChinaCorrespondence: Yingying Niu, Department of Public Health, Mudanjiang Medical University, Mudanjiang, People’s Republic of China, Email niuyingying@mdjmu.edu.cnBackground: Melanoma is highly invasive with poor advanced-stage prognosis and remarkable heterogeneity of the tumor immune microenvironment. Lysine crotonylation regulates tumor progression and immune processes, yet its role in melanoma remains unclear.Purpose: This study aims to explore the value of crotonylation-related genes in melanoma.Patients and Methods: Transcriptomic data of 471 melanoma samples from the TCGA database were utilized. Consensus clustering was performed based on 2971 crotonylation-related genes. Differential analysis, WGCNA and LASSO regression were combined to construct a prognostic model, followed by analyses of the immune microenvironment and drug sensitivity. Molecular docking and cellular experiments were adopted to investigate the core gene SEPTIN1.Results: Melanoma patients were classified into two subtypes (C1 and C2). Patients in the high-risk group of the established prognostic model exhibited shorter overall survival. SEPTIN1 was correlated with prognosis, immune microenvironment and TMZ response. TMZ could downregulate the expression of SEPTIN1, and overexpression of SEPTIN1 reversed the anti-tumor effect of TMZ.Conclusion: Expression signatures of crotonylation-related genes can be applied to molecular subtyping, immune microenvironment dissection and prognostic stratification of melanoma, providing potential clues for individualized diagnosis and treatment of melanoma.Keywords: melanoma, lysine crotonylation, SEPTIN1, tumor immune microenvironment, prognostic model
Xin Xiong,1 Yingqi Xiong,2 Songjiang Liu31Graduate School, Heilongjiang University of Chinese Medicine, Harbin, People’s Republic of China; 2Traditional Chinese Medicine Department, West Nanjing Road Sub-District Community Health Service Center, Shanghai, People’s Republic of China; 3Department of Oncology, The First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, People’s Republic of ChinaCorrespondence: Songjiang Liu, The First Affiliated Hospital of Heilongjiang University of Chinese Medicine, No. 26, Heping Road, Xiangfang District, Harbin, Heilongjiang, 150000, People’s Republic of China, Email hljzylsj@126.comAbstract: Gastric cancer remains one of the most common malignant tumors worldwide and is associated with a high disease burden. Its treatment is still challenged by multidrug resistance, an immunosuppressive tumor microenvironment, and suboptimal postoperative recovery. Traditional Chinese Medicine (TCM) has shown potential in the prevention, treatment, and rehabilitation of gastric cancer. Herein, this review aims to discuss the basic theory, clinical practice, technical progress, epidemiological research, controversies and challenges, and future prospects of TCM in gastric cancer treatment. Literature from the past five years was retrieved from PubMed and China National Knowledge Infrastructure (CNKI) using English and Chinese search terms related to gastric cancer, TCM, Chinese herbal medicine, integrated traditional Chinese and Western medicine, clinical outcomes, mechanisms, network pharmacology, metabolomics, immunotherapy, chemotherapy resistance, postoperative recovery, and translational research. Experimental studies, clinical studies, cohort studies, randomized trials, meta-analyses, guideline-related studies, and technical studies were considered only if they were relevant to the scope of this narrative review. Based on these, we discuss how TCM may exert potential anti-gastric cancer effects through the regulation of apoptotic pathways, modulation of signaling networks, and improvement of immune function. Currently, clinical studies indicate that TCM combined with chemotherapy may prolong survival in patients with advanced gastric cancer, while perioperative interventions such as transcutaneous electrical acupoint stimulation and herbal formulations may alleviate postoperative pain, promote gastrointestinal recovery, and regulate inflammatory responses. Technological advances such as network pharmacology, metabolomics, and nano-preparation technologies have been used to help clarify the molecular mechanisms of TCM and improve drug delivery efficiency. In addition, observational and real-world evidence suggest that TCM use is associated with survival-related outcomes, patient acceptance, and regional differences in clinical application patterns. Despite these findings, challenges remain, including insufficient high-quality clinical evidence, lack of standardization in syndrome differentiation and efficacy evaluation, and the need for more rigorous safety assessment. Overall, TCM may serve as a complementary component of integrated gastric cancer management, particularly in supportive care, postoperative recovery, and treatment tolerance, but its clinical value remains dependent on the quality of supporting evidence. Future studies should use standardized protocols, rigorous clinical designs, reproducible quality-control systems, and appropriate safety assessment to define its role within modern precision oncology.Keywords: gastric cancer, TCM, integrated traditional Chinese and western medicine, postoperative rehabilitation, immune regulation
Childhood asthma is a common but biologically heterogeneous disease, and this heterogeneity limits the performance of one-size-fits-all biomarkers for diagnosis, risk stratification, and disease monitoring. Microbiome and metabolome profiling are attractive in pediatric asthma because they reflect host-environment interactions at mucosal surfaces and may capture clinically relevant variation not fully explained by conventional markers. However, their translational value in children remains uncertain. This review critically examines the current evidence on microbiome- and metabolome-based biomarkers in childhood asthma from a clinically oriented perspective, with emphasis on four settings of practical relevance: early-life risk and disease development, allergic and non-allergic asthma, severe, uncontrolled, or exacerbation-prone disease, and lung-function or inflammatory phenotypes. Current data suggest that composite and phenotype-linked signatures are more informative than isolated taxa or single metabolites. The most convincing signals arise in early-life microbial maturation trajectories and in unstable disease, where upper-airway microbial patterns and integrated metabolic profiles show the greatest potential for clinical stratification. Allergic burden appears to be reflected more consistently by metabolomic than microbiome findings, whereas lung-function and inflammatory phenotypes currently show stronger metabolite-trait associations than reproducible airway microbial correlates. Across phenotypes, pathway-level convergence is more robust than single-marker reproducibility, with recurring signals involving microbial fermentation and short-chain fatty acid biology, bile acid metabolism, tryptophan and histamine pathways, and lipid remodeling. Nevertheless, most pediatric studies remain cross-sectional, modest in size, and heterogeneous in phenotype definitions, sampling matrices, and analytical platforms. No microbiome- or metabolome-based signature is currently ready for routine pediatric clinical use. The most realistic near-term translational direction is the development of age-contextualized, phenotype-oriented reduced panels that are prospectively validated in multicenter cohorts and shown to provide clinical value beyond existing tools for childhood asthma diagnosis, risk stratification, and monitoring.
Meixia Du,1,* Tao Li,1,* Huai Li,1,* Xiaochun Zhang,1 Binqing Xiao,1 Mengni Zhen,1 Yongzhong Li,1 Yi Ouyang1,21Center for Infectious Diseases, Hunan University of Medicine General Hospital, Huaihua, Hunan, 418000, People’s Republic of China; 2Department of Infectious Diseases, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yi Ouyang; Yongzhong Li, Email chuyi_1993@163.com; liyz2008@163.comObjective: Patients with decompensated hepatitis B virus (HBV)- and hepatitis C virus (HCV)-related cirrhosis are at high risk of first variceal bleeding, yet etiology-specific and stage-specific prediction models remain limited. This study aimed to develop and internally validate nomogram models for predicting the risk of first variceal bleeding in this population.Methods: This retrospective cohort study included 451 patients with decompensated HBV- or HCV-related cirrhosis (331 HBV-related and 120 HCV-related), of whom 230 experienced first variceal bleeding. Random Forest and XGBoost algorithms were used for feature selection, followed by multivariable logistic regression to develop etiology-specific nomogram models. Internal validation was performed using a training-testing split. Model discrimination, calibration, and clinical utility were assessed using the area under the receiver operating characteristic curve (AUC), bootstrap resampling, and decision curve analysis, respectively. Partial Dependence Plots (PDPs) midpoint risk (≈ 0.5) set clinical thresholds.Results: Seven predictors were retained for HBV (Hemoglobin, Ascites Depth, Total Protein, Prothrombin Activity [PTA], Total Bile Acid [TBA], D-dimer, and White Blood Cell Count [WBC]) and three for HCV (Hemoglobin, PTA, and TBA), with an AUC of 0.9239 (95% CI 0.8941– 0.9537) and 0.9127 (95% CI 0.8646– 0.9609), respectively. The models showed good calibration and clinical utility on decision curve analysis. PDPs indicated 0.5-risk thresholds at 96.12 g/L (Hemoglobin), 60.75 g/L (Total Protein), 30.58 mm (Ascites Depth), 49.2% (PTA), 25.78 μmol/L (TBA), 2.24 mg/L (D-dimer), and 5.33× 109/L (WBC) for HBV, and 46.81% (PTA), 82.4 g/L (Hemoglobin), 47.51 μmol/L (TBA) for HCV.Conclusion: Etiology-specific nomogram models were developed to predict first variceal bleeding in patients with decompensated HBV- and HCV-related cirrhosis. The models showed good discriminative performance in internal validation and may assist in risk stratification. However, further prospective multicenter studies with external validation are needed before clinical implementation.Keywords: esophageal and gastric varices, decompensated liver cirrhosis, hepatitis B, hepatitis C, machine learning, risk assessment, nomograms
Objective:Oral frailty (OF) is defined as an age-related decline in physiological reserve resulting from the accumulation of oral functional deterioration and oral health problems, typically manifested as impairments in mastication, swallowing, tongue pressure, and salivary secretion. This study aimed to investigate the relationship between self-perceived aging (SPA) and OF in elderly Chinese patients with ischemic stroke. Methods:A total of 500 elderly ischemic stroke patients were included from the neurology outpatient clinic and inpatient ward of the Affiliated Hospital of Jiangnan University from January to September 2025. Patients completed general demographic questionnaires, the Brief Ageing Perceptions Questionnaire (B-APQ), and the Oral Frailty Index-8 (OFI-8). Participants were classified into OF and Non-OF groups. Baseline demographics, clinical data, B-APQ and OFI-8 scores were compared between groups. Logistic regression analysis identified independent risk factors for OF, while Pearson correlation analysis assessed the relationship between SPA and OF. Results:488 elderly patients with ischemic stroke were ultimately included in this study. The average B-APQ score among elderly ischemic stroke patients was 53.18±11.16. The prevalence of OF was 74.6%, with an average OFI-8 score of 6.14±3.53. Logistic multivariate regression analysis identified age (OR=1.156), score of National Institutes of Health Stroke Scale (OR=1.298), infarct area (OR=2.340), high-sensitivity C-reactive protein (OR=1.183), and B-APQ score (OR=1.423) were factors significantly associated with OF (P<0.05). Spearman correlation analysis demonstrated a negative correlation between B-APQ and OFI-8 scores (P<0.05). Conclusion:Elderly Chinese patients with ischemic stroke have a relatively high prevalence of OF. Advanced age, severity of baseline illness, and SPA significantly influence OF. Higher SPA levels correspond to more severe OF.
Objective:To evaluate diagnostic delay, referral pathways, presenting symptoms, and clinical characteristics among patients with axial spondyloarthritis (axSpA) managed at a Malaysian tertiary rheumatology centre. Methods:This retrospective observational study included adults with consultant-confirmed axSpA attending the Rheumatology Clinic, Universiti Malaya Medical Centre. Demographics, axSpA subtype, diagnostic delay, presenting symptoms, laboratory profiles, HLA‑B27 status, referral pathways, and treatments before and 6 months after diagnosis were recorded. Results:A total of 141 adults were included. This consisted of 87 males (61.7%) and was predominantly Chinese (n=83, 58.9%), followed by Malay (n=45, 31.9%), Indian (n=12, 8.5%), and other ethnicities (n=1, 0.7%). Radiographic axSpA and non‑radiographic axSpA accounted for 103 (73.0%) and 38 (27.0%) patients, respectively. Median age at symptom onset and diagnosis were 28 and 35 years. Median diagnostic delay was 48 months, and radiographic patients experienced longer delays (60 vs 36 months). Back pain was the commonest presenting symptom, with subtype‑specific variations in neck, shoulder, and peripheral joint involvement. External referrals had longer delays than internal referrals. Before diagnosis, 76.5% received NSAIDs, and 31.2% commenced biologic therapy within six months. Conclusion:In this Malaysian tertiary-care cohort, axSpA was associated with a median diagnostic delay of 48 months, with longer delays observed in radiographic disease and external referrals. Delayed recognition may reflect non-classical presentations and pathway-level barriers in referral coordination and specialist access. Greater awareness among primary care and non-rheumatology specialties, supported by structured referral criteria, minimum referral datasets, shared imaging pathways, and streamlined external referral processes, may improve timely rheumatology assessment.
Background:Malnutrition is related to adverse outcomes across a wide range of diseases. This study aimed to examine the relationship between the Geriatric Nutritional Risk Index (GNRI) and prognosis in elderly patients with acute ischemic stroke (AIS) following intravenous thrombolysis. Methods:This single-center cohort study recruited elderly patients with AIS who received intravenous alteplase thrombolysis, and GNRI was used to evaluate their nutritional status. All-cause mortality was the primary outcome. The relationship between GNRI and prognosis was investigated using Cox proportional hazards models and restricted cubic spline. Results:Three hundred eighteen elderly patients with AIS who underwent intravenous thrombolysis were included and stratified into tertiles based on GNRI. The mean age was 73.05 ± 8.10 years. During a median follow-up of 17.6 months (IQR, 10.8-23.4 months), 38 (12.0%) patients died. Multivariable Cox analysis showed that GNRI (HR 0.944, 95% CI 0.912-0.978, P=0.001) was significantly related to a reduced risk of all-cause death in AIS. T3 group (HR: 0.349; 95% CI: 0.133-0.914, p=0.032) was associated with lower all-cause mortality rates, using T1 group as the reference. Additionally, a linear association between GNRI and all-cause mortality was found using RCS (nonlinear p-value = 0.478). Conclusion:This study found that among older patients with AIS, lower levels of GNRI were linked to all-cause mortality following intravenous thrombolysis.The GNRI could potentially be used to predict all-cause mortality; however, further multicenter studies are needed to confirm the generalizability of these findings.
