OBJECITVE: To investigate the effectiveness of three-dimensional (3D) printing-assisted vascularized fibular graft for repairing metatarsal defects. METHODS: Between November 2021 and February 2024, 11 patients with varying degrees of metatarsal defects caused by trauma were treated. There were 10 males and 1 female, aged 22-67 years, with a mean age of 51.2 years. The defect locations were as follows: the first metatarsal in 4 cases, the fifth metatarsal in 2 cases, the first and the second metatarsals in 1 case, the first to third metatarsals in 1 case, the third and the fourth metatarsals in 1 case, the third to fifth metatarsals in 1 case, and the first to fifth metatarsals in 1 case. The preoperative American Orthopaedic Foot & Ankle Society (AOFAS) score was 67.0 (48.5, 72.5). Based on 3D-printed bilateral feet models and mirrored healthy-side foot arch angles for preoperative planning and design, the vascularized fibular graft was performed to repair the metatarsal defects. At last follow-up, the medial and lateral longitudinal arches of bilateral feet were measured on weight-bearing X-ray films, and functional assessment was conducted using the AOFAS score. RESULTS: All operations were successfully completed, with an operation time ranging from 180 to 465 minutes (mean, 246.8 minutes). All incisions healed by first intention, with no occurrence of osteomyelitis. All patients were followed up 6-22 months (mean, 10 months). X-ray film reviews showed bone graft healing in all cases, with a healing time of 3-6 months (mean, 5 months). All patients underwent internal fixator removal at 6-12 months after operation. At last follow-up, no significant difference was observed in the medial and lateral longitudinal arches between the healthy and affected feet ( P>0.05). The AOFAS score of the affected foot was 78.0 (73.5, 84.0), showing a significant improvement compared to the preoperative score ( P<0.05). The effectiveness was rated as excellent in 1 case, good in 7 cases, fair in 2 cases, and poor in 1 case. Linear scarring remained at the donor site, with no functional impairment in adjacent joint movement. CONCLUSION 3D printing-assisted vascularized fibular graft for repairing metatarsal defects can effectively restore the physiological angle of the foot arch, facilitate the recovery of weight-bearing alignment, promote good bone healing, and yield satisfactory clinical outcomes.
Humans ; Printing, Three-Dimensional ; Middle Aged ; Male ; Fibula/blood supply* ; Female ; Metatarsal Bones/injuries* ; Adult ; Bone Transplantation/methods* ; Aged ; Plastic Surgery Procedures/methods* ; Young Adult ; Treatment Outcome

BACKGROUND: Based on the China-VHD database, this study sought to develop and validate a Valvular Heart Disease- specific Age-adjusted Comorbidity Index (VHD-ACI) for predicting mortality risk in patients with VHD. METHODS & RESULTS: The China-VHD study was a nationwide, multi-centre multi-centre cohort study enrolling 13,917 patients with moderate or severe VHD across 46 medical centres in China between April-June 2018. After excluding cases with missing key variables, 11,459 patients were retained for final analysis. The primary endpoint was 2-year all-cause mortality, with 941 deaths (10.0%) observed during follow-up. The VHD-ACI was derived after identifying 13 independent mortality predictors: cardiomyopathy, myocardial infarction, chronic obstructive pulmonary disease, pulmonary artery hypertension, low body weight, anaemia, hypoalbuminaemia, renal insufficiency, moderate/severe hepatic dysfunction, heart failure, cancer, NYHA functional class and age. The index exhibited good discrimination (AUC, 0.79) and calibration (Brier score, 0.062) in the total cohort, outperforming both EuroSCORE II and ACCI (P < 0.001 for comparison). Internal validation through 100 bootstrap iterations yielded a C statistic of 0.694 (95% CI: 0.665-0.723) for 2-year mortality prediction. VHD-ACI scores, as a continuous variable (VHD-ACI score: adjusted HR (95% CI): 1.263 (1.245-1.282), P < 0.001) or categorized using thresholds determined by the Yoden index (VHD-ACI ≥ 9 vs. < 9, adjusted HR (95% CI): 6.216 (5.378-7.184), P < 0.001), were independently associated with mortality. The prognostic performance remained consistent across all VHD subtypes (aortic stenosis, aortic regurgitation, mitral stenosis, mitral regurgitation, tricuspid valve disease, mixed aortic/mitral valve disease and multiple VHD), and clinical subgroups stratified by therapeutic strategy, LVEF status (preserved vs. reduced), disease severity and etiology. CONCLUSION The VHD-ACI is a simple 13-comorbidity algorithm for the prediction of mortality in VHD patients and providing a simple and rapid tool for risk stratification.

OBJECTIVE: To identify prognostic genes associated with lysosome-dependent cell death (LDCD) in patients with gastric cancer (GC). METHODS: Differentially expressed genes (DEGs) were identified using The Cancer Genome Atlas - Stomach Adenocarcinoma. Weighted gene co-expression network analysis was performed to identify the key module genes associated with LDCD score. Candidate genes were identified by DEGs and key module genes. Univariate Cox regression analysis, and least absolute shrinkage and selection operator regression and multivariate Cox regression analyses were performed for the selection of prognostic genes, and risk module was established. Subsequently, key cells were identified in the single-cell dataset (GSE183904), and prognostic gene expression was analyzed. Cell proliferation and migration were assessed using the Cell Counting Kit-8 assay and the wound healing assay. RESULTS: A total of 4,465 DEGs, 95 candidate genes, and 4 prognostic genes, including C19orf59, BATF2, TNFAIP2, and TNFSF18, were identified in the analysis. Receiver operating characteristic curves indicated the excellent predictive power of the risk model. Three key cell types (B cells, chief cells, and endothelial/pericyte cells) were identified in the GSE183904 dataset. C19orf59 and TNFAIP2 exhibited predominant expression in macrophage species, whereas TNFAIP2 evolved over time in endothelial/pericyte cells and chief cells. Functional experiments confirmed that interfering with C19orf59 inhibited proliferation and migration in GC cells. CONCLUSION C19orf59, BATF2, TNFAIP2, and TNFSF18 are prognostic genes associated with LDCD in GC. Furthermore, the risk model established in this study showed robust predictive power.
Stomach Neoplasms/pathology* ; Humans ; Prognosis ; Lysosomes/physiology* ; RNA-Seq ; Cell Death ; Single-Cell Analysis ; Gene Expression Regulation, Neoplastic ; Cell Proliferation ; Single-Cell Gene Expression Analysis

Objective:To investigate the clinical and genetic characteristics of a Henan Han family with pontine autosomal dominant microangiopathy and leukoencephalopathy (PADMAL), aiming to enhance understanding of this disease.Methods:The proband was first admitted to the Department of Neurology, Henan Provincial People′s Hospital, Fuwai Central China Cardiovascular Hospital in December 2019 due to cerebral infarction and unilateral limb numbness and weakness. Detailed medical history collection, pedigree mapping, whole-exome sequencing screening, and Sanger sequencing validation were performed for the proband and family members. The patients′ clinical manifestations, imaging features, neuropsychological scale assessment results, and pathological changes were summarized, and genetic analysis was conducted on the gene variant site. Relevant literature was reviewed to summarize the characteristics of PADMAL.Results:The proband was a 47-year-old female, with 3 generations of family members affected, including 7 patients, 3 of whom had died. The clinical features of the patients were similar, with the first stroke occurring around the age of 40, without vascular risk factors such as hypertension or diabetes. The main clinical manifestation was unilateral limb numbness and weakness. The proband and her niece sought medical attention due to stroke symptoms. Brain magnetic resonance imaging revealed acute infarct lesions located in the pons, accompanied by multiple oval infarct foci (the "raisin bread sign") and white matter hyperintensity changes. Genetic testing showed that 4 patients carried a heterozygous c. *34GT mutation in the 3′-untranslated region (3′-UTR) of the COL4A1 gene, while the other 4 unaffected family members did not carry this variant, consistent with genotype- phenotype co-segregation in the family. Conclusions:PADMAL is an extremely rare monogenic cerebral small vessel disease caused by pathogenic variants in the 3′-UTR of the COL4A1 gene. The "raisin bread sign" in the pons is a relatively specific imaging feature that distinguishes it from other cerebral small vessel diseases. For patients with this sign, genetic testing for PADMAL should be considered.

Objective To develop a machine learning model integrating preoperative chest CT radiomic features with clinical data for predicting 5-year postoperative recurrence risk in stage Ⅰ non-small cell lung cancer(NSCLC)patients undergoing surgical resection.Methods A total of 217 patients with pathologically confirmed stage Ⅰ NSCLC(selected from 778 initially screened cases based on our inclusion and exclusion criteria)treated in Army Medical Center of PLA between January 2014 and December 2019 were retrospectively enrolled,including 53 recurrence cases and 164 non-recurrence cases within 5-year follow-up.They were randomly divided into a training set(n=173)and a validation set(n=44)in a ratio of 8:2.Radiomic models were established based on extracted features from tumor-dominant regions of interest(ROI)on CT images,while clinical models were developed using demographic characteristics and preoperative laboratory examinations.A combined model was further constructed by integrating both feature sets,and model performance was compared to identify the optimal predictive model.Results This study screened the features from non-contrast CT images and ultimately selected 7 radiomic features for constructing radiomic model.Among 6 machine learning algorithms,the adaptive boosting(Adaboost)model demonstrated the best overall predictive performance,with an area under the curve(AUC)of 0.866(95%CI:0.808～0.923;accuracy:0.832,specificity:0.884)in the training set and of 0.806(95%CI:0.630～0.983;accuracy:0.795,specificity:0.971)in the validation set.Univariate and multivariate logistic regression analyses identified 4 clinical features for clinical model construction.The clinical model achieved an AUC value of 0.874(95%CI:0.821～0.928;accuracy:0.827,specificity:0.891)in the training set and 0.813(95%CI:0.677～0.948;accuracy:0.636,specificity:0.600)in the validation set.By integrating the 7 radiomic features and 4 clinical features using a feature-level fusion strategy,the combined model exhibited further improved predictive performance,with an AUC value of 0.953(95%CI:0.924～0.983;accuracy:0.884,specificity:0.860)and 0.852(95%CI:0.729～0.976;accuracy:0.682,specificity:0.629),respectively in the training set and the validation set.Conclusion The combined model integrating preoperative CT radiomic features with clinical risk factors may provide an evidence-based framework for evaluating 5-year postoperative recurrence risk in stage Ⅰ NSCLC patients.

Under the background of forensic medicine becoming a first-level discipline,the opportuni-ties and challenges of discipline development coexist.Starting from the actual situation and characteris-tics of local medical colleges and universities,this paper discusses the problems and solutions for the development of forensic medicine discipline from the perspective of building a regional high-level medical university.Combined with the experiences of carrying out forensic medicine education in our college,this paper supplies our thoughts and practices on improving the discipline system,enhancing the ability to serve society,perfecting the talent cultivation model and promoting forensic culture,to provide reference and inspiration for the development of forensic medicine in other universities,jointly promote the advancement of forensic medicine in China to a new stage,and contribute the wisdom and strength of forensic medical experts to the construction of a law-based China,a safe China and a healthy China.

Objective To explore the mechanism of myocardial toxicity caused by N-methyl-3,4-methyle-nedioxyamphetamine(MDMA),the changes of intracellular calcium oscillation mode and calcium han-dling proteins during acute exposure to different concentrations of MDMA were detected,and the in-volvement of nuclear factor κB(NF-κB)and its effect on calcium handling proteins were investigated.Methods Primary rat cardiomyocytes were cultured to establish MDMA acute exposure model,and a control group was set up.The MDMA poisoning model was divided into three concentration groups of 10,100 and 1 000 μmol/L.After 1 h of exposure,the morphological changes of cardiomyocytes were ob-served,the cytotoxicity and changes in calcium signals were measured,and the changes in calcium handling proteins RyR2,SERCA2a,PLN,NCX1 and Cav1.2 were detected.The changes of NF-κB activity and the expression of nucleoprotein p-p65(Ser311)and PKCζ after MDMA exposure,and the intervention of NF-κB inhibitors pyrrolidine dithiocarbamate ammonium(PDTC)and protein kinase C(PKC)inhibitor chelerythrine(CHE)were detected by electrophoretic mobility shift assay(EMSA)and Western blotting.The effects of PDTC intervention on calcium signals,and the expressions of RyR2,SERCA2a,PLN,NCX1 and Cav1.2 after acute MDMA exposure were also observed.Results No obvious changes were observed in the morphology of cardiomyocytes after acute exposure to MDMA,whereas the oscillation waveform of intracytoplasmic calcium ion showed irregular changes with increased oscillation amplitude,intense fluctuations,irregular frequency,and increased fluctuation range of relative optical density values.The expression of RyR2,SERCA2a and NCX1 increased,while the expression of Cav1.2 and PLN de-creased.Acute MDMA exposure could increase NF-κB activity,while PDTC and CHE intervention could inhibit NF-κB activity.In MDMA exposed group,the expression of PKCζ and nucleoprotein p-p65(Ser311)both increased and could be inhibited by CHE.After the intervention of PDTC to block NF-κB,the amplitude of calcium oscillation was lower than that of the MDMA exposed group,and the expres-sion of RyR2,SERCA2a and NCX1 decreased.There was no significant change in PLN,while the ex-pression of Cav1.2 increased.Conclusion MDMA can lead to an increase of calcium ion concentration in cardiomyocytes.Calcium ions are involved in myocardial toxicity of MDMA.The mechanism is re-lated to changes in calcium handling proteins,mainly associated with the increased expression of RyR2.MDMA can up-regulate the intracellular activity of NF-κB through the PKCζ-NF-κB pathway and affect calcium handling proteins,which aggravate intracellular calcium overload during acute MDMA exposure.

Objective To analyze the relationship between the visceral adiposity index(VAI)and nocturia in the US adult population.Methods A cross-sectional study was performed.Data from subjects aged≥20 years in the National Health and Nutrition Examination Survey(NHANES)database from 2007 to 2020 were collected,including waist circumference,triglyceride,body mass index(BMI),high-density lipoprotein,age,gender,race,poverty income ratio,education level,marital status,smoking,alcohol consumption,sleep disorders,depression,occupation,hypertension,diabetes,congestive heart failure,cancer,and nocturnal urination frequency.Weighted analysis,multivariate logistic regression,generalized additive model(GAM),and curve fitting were employed to evaluate the association between VAI and nocturia,adjusting for age,gender,race,poverty income ratio,education level,marital status,smoking,alcohol consumption,sleep disorders,depression,occupation,hypertension,diabetes,congestive heart failure,and cancer.Subgroup analyses were conducted based on age,gender,race,hypertension and diabetes to further evaluate the relationship between VAI and the risk of nocturia.Results A total of 29,196 American adults were included.All subjects were divided into 4 groups based on VAI quartiles:Q1 group(0.32≤VAI<1.01),Q2 group(1.01≤VAI<1.70),Q3 group(1.70≤VAI<2.95),and Q4 group(2.95≤VAI<13.59),with nocturia prevalence rates of 28.5%,31.4%,33.3%,and 34.9%,respectively.In subgroup analyses,the risk of nocturia significantly increased with higher VAI in the 20-40 age group,females and other Hispanics(OR=1.04,95%CI 1.01-1.08,P=0.006;OR=1.02,95%CI 1.00-1.04,P=0.035;OR=1.05,95%CI 1.01-1.09,P=0.026).GAM analysis results showed a nonlinear relationship between VAI and nocturia.Conclusion VAI is positively associated with the risk of nocturia,and may be an effective indicator for predicting the risk of nocturia occurrence.

Objective To design a digital intelligence-driven critical treatment platform to implement integrated treatment procedure inside and outside the hospital and intelligent whole-course managment from pre-hospital emergency care to discharge for critically ill patients.Methods The platform was designed with 5G,IoT,big data and aritificial intelligence techniques and developed with Java language,which adopted Oracle database-based data management and front-end and back-end separation mode,with the front end realized by Vue.js framework and the back end by microservice architecture.There were five functional modules for pre-hospital emergency care,multidisciplinary joint diagnosis and treatment,critical care,quality control management and post-discharge follow-up involved in the platform.Results The platform developed simplified the treatment procedure,enhanced the timeliness of emergency care,decreased the workload of nursing staffs and improved medical service efficiency and working efficiency effectively.Conclusion The platform increases first aid quality and treatment efficiency and provides critically ill patients with high-quality medical experience.[Chinese Medical Equipment Journal,2025,46(1):38-43]

Objective To explore the application value of CT-based radiomics in differentiating pneumonia-type mucinous adenocarcinoma(PTMA)from organizing pneumonia(OP).Methods A total of 52 PTMA patients and 102 OP patients were retrospectively included and randomly divided into training set(n=124)and test set(n=30)in an 8∶2 ratio.Eight PTMA patients and 22 OP patients from another hospital during the same period were included as external validation set(n=30).Clinical characteristics and CT signs of the patients were selected to construct the clinical model.Radiomics features were extracted and dimensionality reduction was performed through the least absolute shrinkage and selection operator(LASSO)algorithm.A radiomics model was constructed and the Radiomics score(Radscore)was calculated.The Radscore was combined with clinical factors to establish the combined model and a nomogram was illustrated.The models' fitting degree was analyzed by the calibration curve,while their efficacy was evaluated by the receiver operating characteristic(ROC)curve and decision curve analysis(DCA).Results The clinical model,established based on the border,cystic space and bronchial leafless tree sign,achieved area under the curve(AUC)of 0.850,0.782,and 0.759 in the training set,test set,and external validation set,respectively.Thirteen features were obtained to construct the radiomics model,with AUC of 0.925,0.865,and 0.830,respectively.The AUC of the combined model were 0.970,0.905,and 0.864,respectively,in which the calibration curve demonstrated good model fitting.DCA indicated that the combined model had the greatest clinical net benefit.Conclusion The combined model based on CT radiomics can effectively distinguish PTMA from OP.