Cardiotoxicity is a critical issue in drug development that poses serious health risks,including potentially fatal arrhythmias.The human ether-à-go-go related gene(hERG)potassium channel,as one of the pri-mary targets of cardiotoxicity,has garnered widespread attention.Traditional cardiotoxicity testing methods are expensive and time-consuming,making computational virtual screening a suitable alter-native.In this study,we employed machine learning techniques utilizing molecular fingerprints and descriptors to predict the cardiotoxicity of compounds,with the aim of improving prediction accuracy and efficiency.We used four types of molecular fingerprints and descriptors combined with machine learning and deep learning algorithms,including Gaussian naive Bayes(NB),random forest(RF),support vector machine(SVM),K-nearest neighbors(KNN),eXtreme gradient boosting(XGBoost),and Trans-former models,to build predictive models.Our models demonstrated advanced predictive performance.The best machine learning model,XGBoost Morgan,achieved an accuracy(ACC)value of 0.84,and the deep learning model,Transformer_Morgan,achieved the best ACC value of 0.85,showing a high ability to distinguish between toxic and non-toxic compounds.On an external independent validation set,it achieved the best area under the curve(AUC)value of 0.93,surpassing ADMETlab3.0,Cardpred,and CardioDPi.In addition,we explored the integration of molecular descriptors and fingerprints to enhance model performance and found that ensemble methods,such as voting and stacking,provided slight improvements in model stability.Furthermore,the SHapley Additive exPlanations(SHAP)explanations revealed the relationship between benzene rings,fluorine-containing groups,NH groups,oxygen in ether groups,and cardiotoxicity,highlighting the importance of these features.This study not only improved the predictive accuracy of cardiotoxicity models but also promoted a more reliable and scientifically interpretable method for drug safety assessment.Using computational methods,this study facilitates a more efficient drug development process,reduces costs,and improves the safety of new drug candidates,ultimately benefiting medical and public health.

Objective:To develop a blockchain-based clinical configuration management model for medical equipment and evaluate its application value in optimizing clinical configuration management of hospital emergency and life-support devices.Methods:A data traceability management model was implemented.The Spatial Durbin Model(SDM)was used to identify issues in equipment configuration,and a blockchain-enabled review framework was established for procurement management of emergency and life-support devices.From January 2019 to December 2022,57 emergency and life-support devices deployed in Shaanxi Provincial People's Hospital were retrospectively analyzed.Among them,26 devices(January 2019-December 2020)were managed via conventional expert evaluation,while 31 devices(January 2021-December 2022)were managed using blockchain-based review.In the conventional mode,four traceability parameters-procurement declaration,supplier qualification,transaction records,and after-sales support-were randomly sampled 128,85,119,and 100 times,respectively;in the blockchain mode,these parameters were sampled 145,94,124,and 105 times.Procurement process compliance was evaluated across device categories:emergency,monitoring,therapeutic,and others required 25,40,30,and 35 review steps(conventional mode)versus 30,45,45,and 35 steps(blockchain mode).Comparative metrics included data traceability rates,process compliance rates,and procurement performance target achievement rates.Results:The blockchain mode demonstrated superior traceability rates:92.41%(134/145)for declarations,100.00%(94/94)for suppliers,97.58%(121/124)for transactions,and 97.14%(102/105)for after-sales support-all significantly higher than the conventional mode(x2=5.898,4.525,9.185,8.362,P＜0.05).Process compliance rates reached 100.00%(30/30)for emergency devices,95.56%(43/45)for monitoring devices,97.78%(44/45)for therapeutic devices,and 97.14%(34/35)for others,with statistically significant improvements(x2=5.176,4.936,5.103,3.968,P＜0.05).Procurement performance targets for progress,benefit,quality,and satisfaction were achieved at 96.77%(30/31),100.00%(31/31),100.00%(31/31),and 93.55%(29/31),respectively,surpassing the conventional mode(x2=6.581,6.535,5.129,5.780,P＜0.05).Conclusion:The blockchain-based clinical configuration management model enhances data traceability,standardizes procurement workflows,and improves performance goal attainment in hospital emergency and life-support device deployment.

Objectives:To evaluate the safety and feasibility of endovascular aortic repair without contrast agent under branch artery guidewire marking(FLARE technique).Methods:The clinical data of 7 patients who underwent contrast-free endovascular aortic repair with branch artery guidewire marking in Fuwai Hospital from 2024 to 2025 were retrospectively analyzed.The criteria for patient selection included renal insufficiency,history of contrast agent allergy,high risk of high-pressure angiography due to extensive calcification of the aortic arch,and patients'strong personal wishes,all patients merited with anatomically friendly and anchored area criteria.The patients were evaluated by preoperative computed tomography or color Doppler ultrasound,and the occlusive stent anchor point was located by branch artery guidewire marking combined with bone marking during surgery.The primary endpoints were early stage of postoperative renal function changes(comparison of preoperative and postoperative serum creatinine)and surgical technique success rate,and the secondary endpoints included the incidence of internal leakage,re-intervention rates,and incidence of aneurysm and kidney-related adverse events during follow-up.Results:Among the seven patients who underwent endovascular aortic repair without contrast using a branch artery guidewire,four were male,with an average age of(72.0±5.9)years.Six of these patients had infrarenal abdominal aortic aneurysms,two of them with bilateral renal artery severe stenosis and renal insufficiency underwent renal artery stenting combined with endovascular aortic repair,one patient had isolated chronic renal insufficiency,one had a history of iodine contrast skin allergy,and the remaining two cases wished this surgery option.The seventh patient had a penetrating ulcer in the aortic arch and descending aorta,along with extensive thrombosis and calcification in the ascending aorta,aortic arch and descending aorta.All the patients achieved surgical technique success.No iodine contrast agent was used during the procedure for endovascular aortic repair.In patients with chronic renal insufficiency and renal artery stenosis before surgery,serum creatinine levels were significantly improved after surgery.All patients did not need hemodialysis,there was no allergic reaction,and no graft-related or perioperative complications.The average follow-up was(5.8±3.0)months,all patients recovered well without re-intervention or complications.The creatinine levels did not fluctuate significantly after surgery.Conclusions:Branch artery guidewire marked contrast-free aortic endovascular repair may be a safe and feasible treatment option in selected patients,especially in patients with contraindications to contrast agents.

Objective:To examine the near-complete genomic analysis of norovirus (NoV) subtype GⅡ.17 [P17] outbreaks in Beijing Chaoyang District from 2014 to 2024.Methods:Data and specimens related to outbreaks of the NoV aggregation in Beijing′s Chaoyang District from 2014 to 2024 were collected. The NoV was identified using real-time fluorescence reverse transcription polymerase chain reaction (RT-PCR). Specimens with positive nucleic acid were amplified by standard PCR, whole genome sequencing and evolutionary analysis. Amino acid site variations were compared.Results:In Chaoyang District, from 2014 to 2024, a total of 637 aggregated outbreaks caused by the NoV infection were reported, of which 584 were successfully typed. The epidemic caused by the GⅡ.17 [P17] subtype accounted for 8.79% (56/637), which was the dominant epidemic gene subtype in 2014-2015, sporadic in 2016-2019, reappeared in 2022, and significantly increased in 2024 (27.27%, 24/88). Outbreaks caused by the GⅡ.17 [P17] subtype occurred mainly from October to December, with the main sites of occurrence in primary schools and kindergartens. This study yielded 53 near-complete genome sequences of the GⅡ.17 [P17] subtype from 46 incidents in Chaoyang District. The GⅡ.17 [P17] subtype sequences of Chaoyang District from 2014 to 2024 were segmented into three subgroups on the evolutionary tree, with sequences from 2014 to 2019, 2022 to April 2024, and May to December 2024 clustered into the d, e, and b subgroups, respectively. In the VP1 region′s P2 area, particularly at the HBGA binding site, subgroups b and e exhibited mutations in 22 and two sites, while subgroups b and e showed mutations in four and one sites, predominantly in the RdRp region.Conclusion:The outbreak caused by the NoV GⅡ.17 [P17] subtype in Chaoyang District from 2014 to 2024 continues, with a significant increase in 2024, and it becomes the dominant gene subtype from October to December. The sequence formation of the NoV GⅡ.17 [P17] subtype in Chaoyang District from January to April 2022 and from May to December 2024 shows two different evolutions, with specific mutation sites, requiring continuous monitoring of the NoV GⅡ.17 [P17] subtype.

Cardiotoxicity is a critical issue in drug development that poses serious health risks, including potentially fatal arrhythmias. The human ether-à-go-go related gene (hERG) potassium channel, as one of the primary targets of cardiotoxicity, has garnered widespread attention. Traditional cardiotoxicity testing methods are expensive and time-consuming, making computational virtual screening a suitable alternative. In this study, we employed machine learning techniques utilizing molecular fingerprints and descriptors to predict the cardiotoxicity of compounds, with the aim of improving prediction accuracy and efficiency. We used four types of molecular fingerprints and descriptors combined with machine learning and deep learning algorithms, including Gaussian naive Bayes (NB), random forest (RF), support vector machine (SVM), K-nearest neighbors (KNN), eXtreme gradient boosting (XGBoost), and Transformer models, to build predictive models. Our models demonstrated advanced predictive performance. The best machine learning model, XGBoost Morgan, achieved an accuracy (ACC) value of 0.84, and the deep learning model, Transformer_Morgan, achieved the best ACC value of 0.85, showing a high ability to distinguish between toxic and non-toxic compounds. On an external independent validation set, it achieved the best area under the curve (AUC) value of 0.93, surpassing ADMETlab3.0, Cardpred, and CardioDPi. In addition, we explored the integration of molecular descriptors and fingerprints to enhance model performance and found that ensemble methods, such as voting and stacking, provided slight improvements in model stability. Furthermore, the SHapley Additive exPlanations (SHAP) explanations revealed the relationship between benzene rings, fluorine-containing groups, NH groups, oxygen in ether groups, and cardiotoxicity, highlighting the importance of these features. This study not only improved the predictive accuracy of cardiotoxicity models but also promoted a more reliable and scientifically interpretable method for drug safety assessment. Using computational methods, this study facilitates a more efficient drug development process, reduces costs, and improves the safety of new drug candidates, ultimately benefiting medical and public health.

Objective To investigate the effects of scoparone(Sco)on proliferation and invasion of colon cancer cell line HCT116,and its effect on the expression of epidermal growth factor receptor(EGFR).Methods 1)HCT116 cells were divided into control group,50Sco group,100Sco group and 200Sco group.The cells in con-trol group were incubated with culture medium for 48 hrs.The 50Sco group,100Sco group and 200Sco group were incubated with 50,100 and 200 μmol/L scoparone for 48 hrs respectively.2)HCT116 cells were divided into con-trol group,NC-200Sco group,NC-LV+200Sco group and EGFR-LV+200Sco group.The control group was incuba-ted with normal culture medium for 48 hrs.NC-200Sco group was incubated with 200 μmol/L scoparone for 48 hrs.NC-LV and EGFR-LV were infected into HCT116 cells in NC-LV+200Sco group and EGFR-LV+200Sco group,then incubated with 200 μmol/L scoparone for 48 hrs.Cell proliferation was detected by MTT assay and EdU stai-ning,cell apoptosis was detected by flow cytometry and cell invasion was detected by Transwell assay.EGFR mRNA was detected by RT-qPCR,the level of EGFR,Bcl-2,Bax,matrix metalloproteinase(MMP)-2 and MMP-9 protein was detected by Western blot.Results Compared to the control group,the cell viability,proportion of EdU positive cells and counting number of invasive cells in 50Sco group,100Sco group and 200Sco group all decreased(P＜0.05).Cell apoptosis rate and Bax protein expression increased(P＜0.05),the protein expression of Bcl-2,MMP-2 and MMP-9 decreased(P＜0.05).mRNA and protein expression of EGFR were de-creased(P＜0.05).Compared with NC-200 Sco group and NC-LV+200Sco group,the expression level of mRNA and protein of EGFR in EGFR-LV+200Sco group was increased(P＜0.05).Cell viability,proportion of EdU posi-tive cells and counting number of invasive cells all increased(P＜0.05).The cell apoptosis rate and Bax protein expression level were decreased(P＜0.05).The protein expression of Bcl-2,MMP-2 and MMP-9 was increased(P＜0.05).Conclusions Scoparone has anti-colon cancer cell activity and inhibits proliferation as well as invasion of colon cancer cells through inhibition of EGFR.

Objective To investigate the susceptibility of Cryptococcus neoformans strains to antifungal drugs and examine the relevant clinical manifestations and laboratory test results in a tertiary hospital in Shanghai during the period from 2019 to 2023.Methods The isolates were identified by MALDI-TOF and biochemical identification cards.The minimum inhibitory concentration(MIC)values of 5-fluorocytosine,amphotericin B,fluconazole,voriconazole,and itraconazole against C.neoformans strains were measured using broth microdilution method.The corresponding clinical data were reviewed and compared.Results Majority(78.7％)of the 75 strains of C.neoformans were isolated from cerebrospinal fluid(CSF).The prevalence of wild type(WT)strains was the lowest(36.0％)for itraconazole and the highest(94.7％)for voriconazole.Cryptococcus capsular antigen test was positive in 62 strains.The results of Cryptococcus capsular antigen test was consistent with fungal culture in 96.9％of the cases.Conclusions Most of the C.neoformans strains were isolated from CSF.The prevalence of non-WT C.neoformans strains was the highest for itraconazole.The prevalence of WT C.neoformans strains was the highest for voriconazole.

Objective To explore the CT diagnosis and differential diagnosis of perivascular epithelioid cell neoplasms (PEComa), improve the accuracy of PEComa diagnosis, and reduce misdiagnosis. Methods CT findings of 8 cases of PEComa confirmed by pathology in Jining First People’s Hospital from January 2020 to April 2024 were retrospectively analyzed for the location, shape, size, boundary, plain scan density, and enhancement characteristics of the lesions. Results All 8 tumors were solitary, with 5 located in the kidney, 1 in the liver, 1 in the extraperitoneal space, and 1 in the retroperitoneal space. The tumors were round in 3 cases, oval in 1 case, and irregular in 4 cases. Seven cases were benign with clear boundaries and 1 case was malignant with unclear boundaries. On plain CT, 2 cases showed slightly low density, 3 cases showed slightly high density, and 3 cases showed low density. One tumor had uniform density, and 7 tumors had nonuniform density with internal necrosis and cystic changes. Contrast-enhanced CT revealed diverse enhancement patterns. Four cases showed a “fast in and fast out” enhancement pattern, with significant arterial-phase enhancement and reduced portal venous-phase enhancement. Three cases showed a “fast-in and slow-out” enhancement pattern, with significant enhancement in the arterial phase, persistent enhancement in the portal venous phase, and slightly reduced density in the delayed phase. One case showed mild enhancement in the arterial phase and significant enhancement in the portal venous phase. In 3 cases, multiple tortuous and thickened blood vessels were observed around the tumors, while 3 cases showed tortuous vascular shadows within the tumors. Conclusion PEComa demonstrates characteristic CT features, predominantly with “fast in and fast out” or “fast in and slow out” enhancement patterns. When thickened and tortuous blood vessels are observed within or around the tumor, PEComa should be considered in combination with clinical findings.

Background China is a major coal producer and consumer country in the world. Coal workers' pneumoconiosis (CWP) is a primary factor endangering the occupational health of coal miners. Research on the disease burden of CWP and its changing trend is significant for disease prevention & control and associated policies. Objective To analyze the disease burden of CWP in China from 1990 to 2021 and its changing trend, and predict the disease burden from 2022 to 2035. Methods Using the Global Burden of Disease Study (GBD) database of 2021, numbers ofincident cases, prevalent cases, deaths, and disability-adjusted life years (DALYs) as well as crude and age-standardized rates of CWP in China were retrieved. Linear regression model was used to calculate the estimated annual percentage change (EAPC) of the age-standardized rates. Joinpoint regression model was used to analyze the temporal trend of disease burden and the disease burden of different sexes and age groups, and Bayesian age-period-cohort (BAPC) model was used to forecast the trend of CWP disease burden. Results In 1990, the incident, prevalent, and deaths cases of CWP in China were 3266, 18872, and 1561, respectively, and the DALYs of CWP were 44614.718 person-years. In 2021, the incident, prevalent, and deaths cases of CWP were 3446, 23975, and 1229, respectively, and the DALYs of CWP were 29610.754 person-years. From 1990 to 2021, the age-standardized incidence, prevalence, mortality, and DALYs rates of CWP in China all showed a downward trend, with the EAPCs of −3.121%, −2.532%, −4.018%, and −4.268%, respectively. The disease burden of CWP in China was mainly concentrated in the male population. The annual average percent change analysis indicated that each standardized rate showed a fluctuating downward trend in different periods. The BAPC model showed that from 2022 to 2035, the age-standardized rates of CWP in China would continue to decline steadily. In 2035, the age-standardized incidence, prevalence, mortality, and DALYs rates of CWP would be reduced to 0.10 per 100000, 0.74 per 100000, 0.03 per 100000, and 0.74 per 100000, respectively. Conclusion The disease burden contributed by CWP in China generally show a downward trend from 1990 to 2021, and it is expected that the age-standardized rates will continue to decline steadily from 2022 to 2035.