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.

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 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.

In response to the new requirements for course instruction outlined in the revised training program for medical imaging program, this study integrated medical imaging technology courses based on the principle of outcome-oriented education and by leveraging self-developed digital resources, with imaging methods as the entry point. The core elements of the course teaching were re-optimized and reorganized to transcend the temporal and spatial limitations of course delivery, enabling the rational application of diverse teaching methods. This approach facilitated the integration of knowledge across three specialized courses, namely medical imaging physics, medical imaging equipment, and medical imaging examination techniques, and achieved full-dimensional and whole-process teaching evaluation. While reducing the number of hours allocated to theoretical instruction, the teaching objectives were achieved with high quality, providing a reference for the integration of digital technologies into the teaching of medical imaging and related disciplines.

Objective:To explore the predictive value of atherogenic index of plasma(AIP)combined with neutro-phil/HDL-C ratio(NHR),lymphocyte/HDL-C ratio(LHR)and monocyte/HDL-C ratio(MHR)for major adverse cardiovascular events(MACE)in patients with acute coronary syndrome(ACS).Methods:This retrospec-tive study enrolled 320 patients underwent coronary angiography in Department of Cardiovascular Medicine,Harri-son International Peace Hospital between January 2021 and December 2022,including 215 ACS patients and 105 pa-tients without ACS;according to Gensini score,ACS patients were divided into low risk group(n=50),medium risk group(n=70)and high risk group(n=95).According to the presence of MACE within 1 year,patients were divided into MACE group(n=55)and no MACE group(n=160).After admission,blood routine,blood lipids,C-reactive protein(CRP)and endothelin-1(ET-1)levels were measured,then NHR,LHR,MHR and AIP were calculated.Spearman method was used to analyze the association of above-mentioned indexes with Gensini score;stepwise Logistic regression was used to analyze the influencing factors of MACE within 1 year in ACS patients;and ROC curve was used to analyze the predictive value of single and combined detection of above indexes for MACE within 1 year in ACS patients.Results:Compared to patients in no ACS group,those in ACS group had significantly higher BMI[(23.59±0.85)kg/m2 vs.(21.57±1.16)kg/m2],proportions of hypertension(57.67％vs.13.33％),diabetes(23.26％vs.8.57％),NHR[(12.09±3.46)vs.(3.81±1.29)],MHR[(0.70±0.18)vs.(0.33±0.10)],LHR[(0.79±0.21)vs.(0.40±0.09)],AIP[(0.21±0.06)vs.(0.11±0.02)],CRP[(9.82±3.09)mg/L vs.(2.20±0.58)mg/L],ET-1[(31.25±10.34)μg/L vs.(10.60±1.96)μg/L](P＜0.001 all).Compared to those in no MACE group,patients in MACE group had significantly higher NHR[(17.33±3.87)vs.(10.12±2.68)],MHR[(0.93±0.24)vs.(0.61±0.13)],LHR[(1.05±0.27)vs.(0.71±0.16)],AIP[(0.28±0.04)vs.(0.17±0.02)],CRP[(15.52±3.83)mg/L vs.(7.69±2.40)mg/L],ET-1[(46.68±9.51)μg/L vs.(25.47±4.66)μg/L]levels(P＜0.001 all).Spearman correlation analysis showed that NHR,MHR,LHR and AIP were significant positively correlated with Gensini score(r=0.837～0.868,P＜0.001 all).Stepwise Logistic regression analysis showed that NHR(OR=1.225,95％CI 1.016～1.550,P=0.035),AIP(OR=2.632,95％CI 1.055～6.566,P=0.038)were independent risk factors for MACE within 1 year in ACS patients.ROC curve shows that AUC of AIP combined with NHR,MHR and LHR predicting MACE within 1 year in ACS patients was 0.786(95％CI 0.725～0.839),which was significantly higher than those of NHR(AUC 0.768,95％CI 0.706～0.823),LHR(AUC 0.749,95％CI 0.686～0.806)and AIP(AUC 0.764,95％CI 0.701～0.819)alone(Z=2.597,2.687,1.965,P＜0.05 or＜0.01).Conclusion:AIP combined with NHR,MHR and LHR have certain predictive value for MACE within 1 year in ACS patients.

Objective:To explore the predictive value of atherogenic index of plasma(AIP)combined with neutro-phil/HDL-C ratio(NHR),lymphocyte/HDL-C ratio(LHR)and monocyte/HDL-C ratio(MHR)for major adverse cardiovascular events(MACE)in patients with acute coronary syndrome(ACS).Methods:This retrospec-tive study enrolled 320 patients underwent coronary angiography in Department of Cardiovascular Medicine,Harri-son International Peace Hospital between January 2021 and December 2022,including 215 ACS patients and 105 pa-tients without ACS;according to Gensini score,ACS patients were divided into low risk group(n=50),medium risk group(n=70)and high risk group(n=95).According to the presence of MACE within 1 year,patients were divided into MACE group(n=55)and no MACE group(n=160).After admission,blood routine,blood lipids,C-reactive protein(CRP)and endothelin-1(ET-1)levels were measured,then NHR,LHR,MHR and AIP were calculated.Spearman method was used to analyze the association of above-mentioned indexes with Gensini score;stepwise Logistic regression was used to analyze the influencing factors of MACE within 1 year in ACS patients;and ROC curve was used to analyze the predictive value of single and combined detection of above indexes for MACE within 1 year in ACS patients.Results:Compared to patients in no ACS group,those in ACS group had significantly higher BMI[(23.59±0.85)kg/m2 vs.(21.57±1.16)kg/m2],proportions of hypertension(57.67％vs.13.33％),diabetes(23.26％vs.8.57％),NHR[(12.09±3.46)vs.(3.81±1.29)],MHR[(0.70±0.18)vs.(0.33±0.10)],LHR[(0.79±0.21)vs.(0.40±0.09)],AIP[(0.21±0.06)vs.(0.11±0.02)],CRP[(9.82±3.09)mg/L vs.(2.20±0.58)mg/L],ET-1[(31.25±10.34)μg/L vs.(10.60±1.96)μg/L](P＜0.001 all).Compared to those in no MACE group,patients in MACE group had significantly higher NHR[(17.33±3.87)vs.(10.12±2.68)],MHR[(0.93±0.24)vs.(0.61±0.13)],LHR[(1.05±0.27)vs.(0.71±0.16)],AIP[(0.28±0.04)vs.(0.17±0.02)],CRP[(15.52±3.83)mg/L vs.(7.69±2.40)mg/L],ET-1[(46.68±9.51)μg/L vs.(25.47±4.66)μg/L]levels(P＜0.001 all).Spearman correlation analysis showed that NHR,MHR,LHR and AIP were significant positively correlated with Gensini score(r=0.837～0.868,P＜0.001 all).Stepwise Logistic regression analysis showed that NHR(OR=1.225,95％CI 1.016～1.550,P=0.035),AIP(OR=2.632,95％CI 1.055～6.566,P=0.038)were independent risk factors for MACE within 1 year in ACS patients.ROC curve shows that AUC of AIP combined with NHR,MHR and LHR predicting MACE within 1 year in ACS patients was 0.786(95％CI 0.725～0.839),which was significantly higher than those of NHR(AUC 0.768,95％CI 0.706～0.823),LHR(AUC 0.749,95％CI 0.686～0.806)and AIP(AUC 0.764,95％CI 0.701～0.819)alone(Z=2.597,2.687,1.965,P＜0.05 or＜0.01).Conclusion:AIP combined with NHR,MHR and LHR have certain predictive value for MACE within 1 year in ACS patients.

In response to the new requirements for course instruction outlined in the revised training program for medical imaging program, this study integrated medical imaging technology courses based on the principle of outcome-oriented education and by leveraging self-developed digital resources, with imaging methods as the entry point. The core elements of the course teaching were re-optimized and reorganized to transcend the temporal and spatial limitations of course delivery, enabling the rational application of diverse teaching methods. This approach facilitated the integration of knowledge across three specialized courses, namely medical imaging physics, medical imaging equipment, and medical imaging examination techniques, and achieved full-dimensional and whole-process teaching evaluation. While reducing the number of hours allocated to theoretical instruction, the teaching objectives were achieved with high quality, providing a reference for the integration of digital technologies into the teaching of medical imaging and related disciplines.

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.