Patients with Takayasu arteritis combined with aortic valve disease often have a poor prognosis following surgical valve replacement, frequently encountering complications such as perivalvular leakage, valve detachment, and anastomotic aneurysm. This article presents a high-risk case wherein severe aortic valve insufficiency associated with Takayasu arteritis was successfully managed through transcatheter aortic valve implantation via the transapical approach. The patient had satisfactory valve function with no complications observed during the six-month postoperative follow-up. This case provides a minimally invasive and feasible alternative for the clinical management of such high-risk patients.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Monkeypox is a viral zoonotic disease,and there is currently a lack of safe and effective vac-cines against the monkeypox virus.Therefore,screening and developing vaccine candidates is of signifi-cant practical importance.With the rapid advancement of molecular biology and plant genetic engineer-ing,plant bioreactors offer promising potential for producing vaccine proteins due to their advantages,in-cluding safety,cost-effectiveness,and scalability.In this study,we focused on the monkeypox protein B6R.The recombinant expression plasmid pFolia40108-B6R-Fer was successfully constructed using am-plification,enzyme digestion,and flexible linker tandem ferritin technology.A complete transient expres-sion system in Nicotiana benthamiana and a purification system for the recombinant monkeypox protein were established.The optimal expression time was determined to be 12-14 days,with a final purified pro-tein concentration of approximately 1 mg/mL and a yield of 0.85 mg/kg fresh weight.The purified B6R-Fer recombinant protein self-assembled into spherical virus-like particles(VLPs)with an average particle size of 24 nm.The B6R-Fer recombinant protein from this study shows promising potential for use in the development and screening of plant-derived monkeypox vaccine candidates.

Monkeypox is a viral zoonotic disease,and there is currently a lack of safe and effective vac-cines against the monkeypox virus.Therefore,screening and developing vaccine candidates is of signifi-cant practical importance.With the rapid advancement of molecular biology and plant genetic engineer-ing,plant bioreactors offer promising potential for producing vaccine proteins due to their advantages,in-cluding safety,cost-effectiveness,and scalability.In this study,we focused on the monkeypox protein B6R.The recombinant expression plasmid pFolia40108-B6R-Fer was successfully constructed using am-plification,enzyme digestion,and flexible linker tandem ferritin technology.A complete transient expres-sion system in Nicotiana benthamiana and a purification system for the recombinant monkeypox protein were established.The optimal expression time was determined to be 12-14 days,with a final purified pro-tein concentration of approximately 1 mg/mL and a yield of 0.85 mg/kg fresh weight.The purified B6R-Fer recombinant protein self-assembled into spherical virus-like particles(VLPs)with an average particle size of 24 nm.The B6R-Fer recombinant protein from this study shows promising potential for use in the development and screening of plant-derived monkeypox vaccine candidates.

Aim To investigate the anti-Zika virus(ZIKV)mechanism of diterpenoid compound 9 from Euphorbia helioscopia in vitro.Methods The cytotox-icity of compound 9 was evaluated using the CCK-8 as-say.A ZIKV-infected Vero cell model was established,and the antiviral activity was assessed through RT-qPCR,plaque assay,Western blot,and immunofluores-cence.Furthermore,the mechanism of action was elu-cidated using multi-cell line validation,nanoparticle tracking analysis,cellular thermal shift assay,and mo-lecular docking.Results In Vero cells,compound 9 exhibited an EC50 of(3.95±0.15)μmol·L-1 and a CC50 of(272.12±8.56)μmol·L-1,demonstrating significantly higher antiviral efficacy than the positive control drug ribavirin(RBV).Its virus inactivation effect was time-dependent and could significantly re-duce viral load and plaque formation.Studies revealed that compound 9 altered the physicochemical properties of ZIKV particles,including reducing surface charge and increasing particle size distribution.Additionally,it significantly enhanced the thermal stability of the prM protein.Molecular docking analysis indicated that compound 9 formed a high-affinity interaction with the prM protein(binding energy:-38.52 kJ·mol-1)and stabilized its structure through hydrophobic interac-tions.Conclusion Compound 9 exerts in vitro anti-ZIKV activity by directly inactivating the virus,disrup-ting viral particle integrity,and targeting the prM pro-tein.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: To identify the spatio-temporal clustering analysis of mumps in Wenzhou City, Zhejiang Province from 2010 to 2023, so as to provide the basis for improving mumps prevention and control strategies. Methods: Data of mumps cases in Wenzhou City from 2010 to 2023 were collected from the Monitoring and Reporting Management System of Chinese Disease Prevention and Control Information System. The spatio-temporal clustering characteristics of mumps incidence were identified using spatial autocorrelation analysis and spatio-temporal scan analysis. Results: A total of 20 455 mumps cases were reported in Wenzhou City from 2010 to 2023, with an average annual incidence of 17.54/105. There were 12 919 male and 7 536 female cases, with a male-to-female ratio of 1.71∶1. The children aged 5-<10 years had the highest incidence of mumps at 135.29/105. The incidence of mumps showed a downward trend from 46.82/105 in 2010 to 3.59/105 in 2023 (P<0.05). The incidence of mumps peaked from May to July and from November to January during 2010 and 2012, the winter peak became less evident after 2013, and no seasonal trends were observed after 2020. Spatial autocorrelation analysis showed there was a positive spatial correlation of mumps of other years, with the exception of 2018 (all Moran's I >0, all P<0.05). Lucheng District, Longwan District, Ouhai District, Cangnan County and Rui'an City were high-high clustering sites. Spatio-temporal scan analysis showed that the primary clustering area was centered in Nanbaixiang Street, Ouhai District, covering 50 towns (streets), with the clustering time from April 2010 to August 2013; the secondary clustering area was centered in Zaoxi Town, Cangnan County, covering 24 towns (streets), with the clustering time from January 2010 to June 2013. Conclusions The incidence of mumps in Wenzhou City from 2010 to 2023 showed a downward trend. The urban areas, Cangnan County and Rui'an City were the clustering areas.

ObjectiveTo explore the clinical safety of Feilike Mixture （FLK） in the real world. MethodsThe safety of all children who received FLK from 29 institutions in 12 provinces between January 21，2021 and December 25，2021 was evaluated through prospective centralized surveillance and a nested case control study. ResultsA total of 3 035 juveniles were included. There were 29 research centers involved，which are distributed across 12 provinces，including one traditional Chinese medicine （TCM） hospital and 28 general hospitals. The average age among the juveniles was （4.77±3.56） years old，and the average weight was （21.81±12.97） kg. Among them，119 cases （3.92%） of juveniles had a history of allergies. Acute bronchitis was the main diagnosis for juveniles，with 1 656 cases （54.46%）. FLK was first used in 2 016 cases （66.43%），and 142 juvenile patients had special dosages，accounting for 4.68%. Among them，92 adverse drug reactions （ADRs） occurred，including 73 cases of gastrointestinal system disorders，10 cases of metabolic and nutritional disorders，eight cases of skin and subcutaneous tissue diseases，two cases of vascular and lymphatic disorders，and one case of systemic diseases and various reactions at the administration site. The manifestations of ADRs were mainly diarrhea，stool discoloration，and vomiting，and no serious ADRs occurred. The results of multi-factor analysis indicated that special dosages （the use of FLK）［odds ratio （OR） of 2.642， 95% confidence interval （CI） of 1.105-6.323］，combined administration： spleen aminopeptide （OR of 4.978， 95%CI of 1.200-20.655），and reason for combined administration： anti-infection （OR of 1.814， 95%CI of 1.071-3.075） were the risk factors for ADRs caused by FLK. Conclusion92 ADRs occurred among 3 035 juveniles using FLK. The incidence of ADRs caused by FLK was 3.03%，and the severity was mainly mild or moderate. Generally，the prognosis was favorable after symptomatic treatment such as drug withdrawal or dosage reduction，suggesting that FLK has good clinical safety.

OBJECTIVE: This study reports the first imported case of Lassa fever (LF) in China. Laboratory detection and molecular epidemiological analysis of the Lassa virus (LASV) from this case offer valuable insights for the prevention and control of LF. METHODS: Samples of cerebrospinal fluid (CSF), blood, urine, saliva, and environmental materials were collected from the patient and their close contacts for LASV nucleotide detection. Whole-genome sequencing was performed on positive samples to analyze the genetic characteristics of the virus. RESULTS: LASV was detected in the patient's CSF, blood, and urine, while all samples from close contacts and the environment tested negative. The virus belongs to the lineage IV strain and shares the highest homology with strains from Sierra Leone. The variability in the glycoprotein complex (GPC) among different strains ranged from 3.9% to 15.1%, higher than previously reported for the seven known lineages. Amino acid mutation analysis revealed multiple mutations within the GPC immunogenic epitopes, increasing strain diversity and potentially impacting immune response. CONCLUSION The case was confirmed through nucleotide detection, with no evidence of secondary transmission or viral spread. The LASV strain identified belongs to lineage IV, with broader GPC variability than previously reported. Mutations in the immune-related sites of GPC may affect immune responses, necessitating heightened vigilance regarding the virus.
Humans ; China/epidemiology* ; Genome, Viral ; Lassa Fever/virology* ; Lassa virus/classification* ; Molecular Epidemiology ; Phylogeny

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.