ObjectiveTo understand the whole genome characteristics and the information for genetic evolution in the two coxsackievirus A2 (CVA2) strains isolated from patients with herpangina in Shanghai, and to provide a scientific basis for the prevention and treatment of herpetic angina. MethodsTwo CAV2 strains isolated from patients with herpetic angina in Shanghai were performed whole genome sequencing and analysis for phylogenetics, nucleotide homology, and evolution. ResultsA phylogenetic analysis of the VP1 region revealed that the two Shanghai strains both belonged to CVA2 genotype D, with the highest homology to OL357660, a strain from Yunnan. The average nucleotide identity (ANI) of the whole genome between the two Shanghai strains was 98.88%, and the ANI of the whole genome comparisons to other CVA2 genotype D strains and CVA2 genotypes A-C strains ranged from 84.64% to 97.42% and from 79.21% to 84.20%, respectively. The two Shanghai strains had low homology in the 3D region compared to the existing CVA2 strains. The phylogenetic analysis and sliding window nucleotide similarity analysis indicated that the two Shanghai strains and the Yunnan OL357660 strain might constitute a new genetic lineage. ConclusionThe two CVA2 strains isolated for the first time in Shanghai are assigned to genotype D (GenBank: PQ130039 and PQ130040), which is identical to the existing subtype prevalent in China. As represented by the Shanghai strains, a new CVA2 genetic lineage is been identified. This study has enriched the data on genetic evolution and genetic variation of CVA2 in Shanghai, indicating the requirement to strengthen surveillance for the epidemiological pattern of CVA2.

Glioblastoma (GBM) is a highly aggressive primary brain tumor characterized by poor prognosis. Conventional chemo-radiotherapy demonstrates limited therapeutic efficacy and is often accompanied by significant side effects, largely due to factors such as drug resistance, radiation resistance, the presence of the blood-brain barrier (BBB), and the activation of DNA damage repair mechanisms. There is a pressing need to enhance treatment efficacy, with BRD4 identified as a promising target for increasing GBM sensitivity to therapy. Lacking small molecule inhibitors, BRD4 can be degraded using PROteolysis Targeting Chimera (PROTAC), thereby inhibiting DNA damage repair. To deliver PROTAC, SIAIS171142 (SIS) effectively, we designed a responsive nanocapsule, MPL_(SS)P@SIS, featuring GBM-targeting and GSH-responsive drug release. Modified with 1-methyl-l-tryptophan (MLT), nanocapsules facilitate targeted delivery of SIS, downregulating BRD4 and sensitizing GBM cells to radiotherapy and chemotherapy. After intravenous administration, MPL_(SS)P@SIS selectively accumulates in tumor tissue, enhancing the effects of radiotherapy and temozolomide (TMZ) by increasing DNA damage and oxidative stress. GSH activates the nanocapsules, triggering BRD4 degradation and hindering DNA repair. In mouse models, the nanosensitizer, combined with TMZ and X-ray irradiation, efficiently inhibited the growth of GBM. These findings demonstrate a novel PROTAC-based sensitization strategy targeting BRD4, offering a promising approach for effective GBM therapy.

Temporomandibular disorders (TMD), a common condition in oral and maxillofacial surgery, significantly impairs patients' quality of life. Early prediction and appropriate treatment of TMD are therefore critically important. Research on TMD prediction models has evolved from traditional statistical methods to machine learning and subsequently to deep learning, each offering unique advantages and limitations. Traditional statistical methods can effectively identify independent risk factors influencing treatment outcomes but generally rely on substantial prior knowledge and assumptions. Machine learning techniques can process large-scale, high-dimensional data and autonomously learning patterns and regularities within datasets. However, they exhibit strong dependence on data quality and limited model generalization capabilities. Deep learning approaches excel at automatically extracting temporal patterns and trends from time-series data while effectively capturing complex nonlinear relationships, yet they require extensive training datasets and suffer from interpretability challenges due to their inherent black-box testing. This review comprehensively evaluates the implementation and performance of these computational approaches in TMD prediction, critically analyzes their respective strengths and constraints, and discusses promising future research directions.

Objective:To delineate clinical characteristics of infantile myofibroma/myofibromatosis (IM) .Methods:A retrospective analysis was conducted on histologically confirmed IM cases from Beijing Children's Hospital, Henan Children's Hospital, and Maternity and Child Health Care of Guangxi Zhuang Autonomous Region between August 2014 and July 2021. The clinical, pathological, imaging features, and outcomes were analyzed and summarized.Results:A total of 44 IM patients were included, comprising 28 males (63.6%) and 16 females (36.4%). Their ages at onset ( M[ Q1, Q3]) were 14.8 (4.7, 42.4) months, and 26 patients (59.1%) developed IM before the age of 1 year. Seven patients (15.9%) were initially diagnosed with IM. Skin involvement occurred in 42 patients (95.5%), of whom 30 (71.4%) presented with a solitary lesion and 12 (28.6%) with multiple lesions. Skin lesions mainly manifested as painless, firm nodules or masses. The most commonly involved extracutaneous site was the skeletal system (21/44, 47.7%). Histopathological examination of all 44 IM cases revealed a biphasic architecture pattern, characterized by the coexistence of two distinct morphologies or cell types within the tumor tissues (including spindle cell areas composed of fascicularly and densely arranged myofibroblasts, and primitive mesenchymal cell areas composed of small, round undifferentiated cells. Immunohistochemical study was performed in 42 cases; 40 (95.2%) were positive for smooth muscle actin, and 20 (47.6%) were positive for CD34. Genetic testing was conducted in 3 cases, and NOTCH mutations were identified in 2. Among the 44 patients, 30 patients (68.2%) underwent surgical excision, 5 patients (11.4%) received intralesional injections of triamcinolone acetonide, 1 patient (2.3%) received chemotherapy for intestinal involvement, and 8 patients were managed expectantly. During the follow-up of 49 (36, 60) months, lesions completely resolved in 42 cases (95.5%), while 2 cases died of pulmonary infection following chemotherapy or postoperative airway compression. Conclusions:IM predominantly affected infants and young children, with the skin and skeletal system being the most commonly involved sites. Skin lesions often manifested as firm nodules or masses, and histopathological examination was crucial for definitive diagnoses. Most IM cases exhibited favorable outcomes.

Objective To investigate the incidence and economic burden of healthcare-associated infection(HAI)in patients after liver transplant.Methods Basic clinical information,infection status,and related medical expenses of liver transplant patients in the department of hepatobiliary surgery in a tertiary first-class hospital from November 2012 to December 2023 were investigated retrospectively.A case-control study design was employed,with post-li-ver transplant patients who developed HAI as the infection group and those without HAI during the same period as the control group.The 1∶1 propensity score matching(PSM)method was adopted(caliper value was set at 0.05,employing sampling without replacement).Length of hospital stay and hospitalization expenses between patients in the infection group and the control group were compared using Wilcoxon rank-sum test,and the economic burden due to HAI was calculated.Results A total of 336 liver transplant patients were included in study,out of which 48 had HAI,with an incidence of 14.29％.44 pairs were successfully matched by PSM.After matching,the median hospitalization expense for patients in the infection group was 334 473.73 Yuan,while that of the control group was 285 824.82 Yuan,with a statistically significant difference(Z=-3.430,P＜0.05).The direct economic burden of HAI in liver transplant patients was 48 648.91 Yuan.After matching,the median length of hospital stay in the in-fection group(37.0 days)was 12.5 days longer than that in the control group(24.5 days),with statistically sig-nificnat difference(Z=-3.630,P＜0.001).Conclusion HAI after liver transplant increases patients' hospitaliza-tion expense and prolongs their hospital stay,thus brings huge economic burdens to the patients.

As a critical component of global agriculture,the dairy industry is essential for the food security and economic development.In China,the dairy sector in plateau regions plays an important role in addressing the nutritional needs of residents,boosting farmers' incomes,and fostering re-gional economic growth.However,the harsh high-altitude conditions,such as low oxygen,low at-mospheric pressure,and severe climate,pose significant challenges to the health and survival of dairy cows.This article summarizes the changes in physiological characteristics,metabolic perform-ance,production performance,and health status of dairy under high altitude areas,providing in-sights for the identification of adaptive traits in dairy to plateau.Also,the genetic and epigenetic mechanisms behind these phenotypic adaptations are discussed,and future directions and strategies for enhancing adaptability of dairy of dairy n plateau regions are outlined,thereby guiding re-searchers in adaptation evolution and breeding of dairy cattle.

Objective To preoperatively predict microvascular invasion(MVI)in intrahepatic cholangiocarcinoma(ICC)using clinical data and computed tomography(CT)signs.Methods A retrospective analysis was conducted on the preoperative clinical data and CT images of 173 ICC patients with complete surgical pathological results.Among them,102 were MVI-negative and 71 were MVI-positive.Results Statistically significant differences were observed between the MVI-positive and MVI-negative groups in liver cirrhosis,alpha-fetoprotein,alanine aminotransferase(ALT),margin,and capsule(P<0.05).Univariate analysis identified liver cirrhosis(OR=0.530,95%CI:0.286-0.983,P=0.044),unsmooth tumor margin(OR=19.362,95%CI:5.717-65.575,P<0.001),and incomplete capsule(OR=2.983,95%CI:1.544-5.760,P=0.001)as risk factors for predicting MVI.Multivariate analysis revealed that elevated ALT(OR=0.164,95%CI:0.030-0.884,P=0.035),unsmooth tumor margin(OR=35.816,95%CI:7.486-171.36,P<0.001),and incomplete capsule(OR=4.234,95%CI:1.211-14.801,P=0.024)were independent predictors of MVI.Conclusion Elevated ALT,unsmooth tumor margin,and incomplete capsule are highly correlated with MVI in ICC patients.

Temporomandibular disorders (TMD), a common condition in oral and maxillofacial surgery, significantly impairs patients' quality of life. Early prediction and appropriate treatment of TMD are therefore critically important. Research on TMD prediction models has evolved from traditional statistical methods to machine learning and subsequently to deep learning, each offering unique advantages and limitations. Traditional statistical methods can effectively identify independent risk factors influencing treatment outcomes but generally rely on substantial prior knowledge and assumptions. Machine learning techniques can process large-scale, high-dimensional data and autonomously learning patterns and regularities within datasets. However, they exhibit strong dependence on data quality and limited model generalization capabilities. Deep learning approaches excel at automatically extracting temporal patterns and trends from time-series data while effectively capturing complex nonlinear relationships, yet they require extensive training datasets and suffer from interpretability challenges due to their inherent black-box testing. This review comprehensively evaluates the implementation and performance of these computational approaches in TMD prediction, critically analyzes their respective strengths and constraints, and discusses promising future research directions.