Background::Hepatitis B poses a heavy burden for children in China, however, the national studies on the distributional characteristics and health care costs of children with severe hepatitis B is still lacking. This study aimed to analyze the disease characteristics, health economic effects, and medical cost for children with severe hepatitis B in China.Methods::Based on patient information in the Hospital Quality Monitoring System, cases with severe hepatitis B were divided into four groups according to age, and the etiology and symptoms of each group were quantified. The cost of hospitalization was calculated for cases with different disease processes, and severity of disease. The spatial aggregation of cases and the relationship with health economic factors were analyzed by Moran’s I analysis. Results::The total number of children discharged with hepatitis B from January 2016 to April 2022 was 1603, with an average age of 10.5 years. Liver failure cases accounted for 43.48% (697/1603) of total cases and cirrhosis cases accounted for 11.23% (180/1603). According to the grouping of disease progression, there were 1292 cases without associated complications, and the median hospitalization cost was $818.12. According to the spatial analysis, the aggregation of cases was statistically significant at the prefectural and provincial levels in 2019, 2020, and 2021 (all P <0.05). The number of severe cases was negatively correlated with gross domestic product (Moran’s I <0) and percentage of urban population (Moran’s I <0), and positively correlated with the number of pediatric beds per million population (Moran’s I >0). Conclusion::The number of severe hepatitis B cases is low in areas with high gross domestic product levels and high urban population ratios, and health care costs have been declining over the years.

Objective To observe the value of pituitary radiomics and MRI features combined model for predicting growth hormone(GH)status in pediatric short stature.Methods Totally 300 children with short stature were enrolled as training set,while other 73 cases were taken as external validation set.Based on growth hormone stimulation test,the children were divided into GH deficiency(GHD)group(n=228)and non-GHD group(n=145).The training set included 196 cases in GHD subgroup and 104 cases in non-GHD subgroup,while the validation set included 32 cases in GHD subgroup and 41 cases in non-GHD subgroup.Radiomics features of pituitary were extracted from T1WI.The key features were selected using least absolute shrinkage and selection operator(LASSO)regression,and machine learning models were subsequently constructed using support vector machine(SVM),logistic regression(LR),naive Bayes(NB)and K-nearest neighbor(KNN),respectively.Then combined models were constructed combining with MRI features,and the efficacy of each model was evaluated.Results The area under the curve(AUC)of SVM,LR,NB,and KNN radiomics model for predicting GH status in pediatric short stature was 0.860,0.831,0.838 and 0.901 in training set,0.788,0.829,0.823 and 0.770 in validation set,while of the relative combined SVM,LR,NB and KNN model was 0.924,0.903,0.859 and 0.920 in training set,and 0.827,0.881,0.836 and 0.718 in validation set.LRcombined model had the best overall performance,with sensitivity of 84.94％,specificity of 80.56％and accuracy of 83.61％in training set,and 80.95％,72.22％and 80.00％in validation set,respectively.Conclusion Pituitary radiomics and MRI features combined model could effectively predict GH status in pediatric short stature.

Cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is a non-atherosclerotic, non-amyloidogenic inherited cerebral small vessel disease caused by mutations in the NOTCH3 gene, typically manifesting in middle age. The diagnosis can be confirmed through the detection of granular osmiophilic material in skin biopsies and NOTCH3 gene mutations identified by genetic testing. However, the pathogenesis of this disease remains unclear, and treatment options are limited. A major contributing factor is that currently available preclinical animal models fail to adequately recapitulate the characteristic pathological features and clinical phenotypes of the disease. Therefore, a comprehensive review of recent advances in CADASIL animal models was conducted, and the advantages and limitations of existing models were systematically analyzed, aiming to offer guidance for selecting appropriate animal models in fundamental research and to propose future directions for developing experimental models.

Purpose To investigate the independent risk factors for early recurrence of solitary hepatocellular carcinoma after radiofrequency ablation based on gadoxetic acid disodium(Gd-EOB-DTPA)-enhanced MRI combined with clinical features.Materials and Methods Clinical and imaging data of hepatocellular carcinoma patients who underwent radiofrequency ablation at the First Affiliated Hospital of Henan University of Chinese Medicine from January 2019 to June 2022 were retrospectively collected.All patients underwent preoperative Gd-EOB-DTPA-enhanced MRI and were followed up for up to two years post-surgery.Univariate and multivariate Cox proportional hazards regression were performed to identify independent risk factors for recurrence after radiofrequency ablation.Results A total of 58 patients were finally included,including early recurrence group(n=22)and non-early recurrence group(n=36).Multivariate Cox regression analysis revealed that preoperative alpha-fetoprotein(AFP)levels(HR=1.103,95%CI 1.008-1.206,P=0.033),arterial-phase irregular margin enhancement(HR=4.647,95%CI 1.527-14.110,P=0.007),peritumoral arterial-phase enhancement(HR=11.575,95%CI 3.575-37.478,P=0.001)and peritumoral hepatobiliary phase hypointensity(HR=5.058,95%CI 1.129-22.668,P=0.034)were independent risk factors for early recurrence.The area under the curve for AFP combined with arterial-phase irregular margin enhancement,peritumoral arterial-phase enhancement and peritumoral hepatobiliary phase hypointensity were 0.896,0.842 and 0.860,with accuracy rates of 81.0%,84.5%and 82.8%,respectively.Conclusion Preoperative serum AFP levels,arterial-phase irregular margin enhancement,peritumoral arterial-phase enhancement and peritumoral hepatobiliary phase hypointensity are independent risk factors for early recurrence after radiofrequency ablation in hepatocellular carcinoma patients.The combination of AFP and any of these MRI features significantly improves predictive efficacy.

The development and validation of clinical prediction models based on artificial intelligence (AI) and machine learning methods have become increasingly widespread. However, the prediction model bias risk and applicability evaluation tool developed in 2019 (i.e., PROBAST-2019) has shown significant limitations. Therefore, an expanded and updated version of the PROBAST-2019 tool was released in 2025, known as the PROBAST+AI tool. The tool is divided into two parts including model development and model evaluation. It aims to comprehensively and systematically evaluate potential methodological quality issues in model development, bias risks in model evaluation, and the applicability of models, regardless of the modeling method used. This paper provides a systematic interpretation of the PROBAST+AI tool's items and case analyses, with the aim of guiding and assisting researchers engaged in related studies and promoting the high-quality development of clinical predictive model research.

Objective To observe the value of pituitary radiomics and MRI features combined model for predicting growth hormone(GH)status in pediatric short stature.Methods Totally 300 children with short stature were enrolled as training set,while other 73 cases were taken as external validation set.Based on growth hormone stimulation test,the children were divided into GH deficiency(GHD)group(n=228)and non-GHD group(n=145).The training set included 196 cases in GHD subgroup and 104 cases in non-GHD subgroup,while the validation set included 32 cases in GHD subgroup and 41 cases in non-GHD subgroup.Radiomics features of pituitary were extracted from T1WI.The key features were selected using least absolute shrinkage and selection operator(LASSO)regression,and machine learning models were subsequently constructed using support vector machine(SVM),logistic regression(LR),naive Bayes(NB)and K-nearest neighbor(KNN),respectively.Then combined models were constructed combining with MRI features,and the efficacy of each model was evaluated.Results The area under the curve(AUC)of SVM,LR,NB,and KNN radiomics model for predicting GH status in pediatric short stature was 0.860,0.831,0.838 and 0.901 in training set,0.788,0.829,0.823 and 0.770 in validation set,while of the relative combined SVM,LR,NB and KNN model was 0.924,0.903,0.859 and 0.920 in training set,and 0.827,0.881,0.836 and 0.718 in validation set.LRcombined model had the best overall performance,with sensitivity of 84.94％,specificity of 80.56％and accuracy of 83.61％in training set,and 80.95％,72.22％and 80.00％in validation set,respectively.Conclusion Pituitary radiomics and MRI features combined model could effectively predict GH status in pediatric short stature.

Homo- or heterodimeric compounds that affect dimeric protein function through interaction between monomeric moieties and protein subunits can serve as valuable sources of potent and selective drug candidates. Here, we screened an in-house dimeric natural product collection, and panepocyclinol A (PecA) emerged as a selective and potent STAT3 inhibitor with profound anti-tumor efficacy. Through cross-linking C712/C718 residues in separate STAT3 monomers with two distinct Michael receptors, PecA inhibits STAT3 DNA binding affinity and transcription activity. Molecular dynamics simulation reveals the key conformation changes of STAT3 dimers upon the di-covalent binding with PecA that abolishes its DNA interactions. Furthermore, PecA exhibits high efficacy against anaplastic large T cell lymphoma in vitro and in vivo, especially those with constitutively activated STAT3 or STAT3^Y640F. In summary, our study describes a distinct and effective di-covalent modification for the dimeric compound PecA to disrupt STAT3 function.

This study aims to investigate the isolate and identify of infectious bronchitis virus(IBV)in chickens,and study its genetic variation and pathogenicity.In 2023,two strains named CK/CH/HN/SQ202301 and CK/CH/HN/SQ202302 were obtained from suspected infectious bronchitis(IB)infected materials collected in a region of Henan Province,China.Further analysis showed that the two isolates belong to the G Ⅰ-13 and GⅥ genotypes,respectively.The cleavage sites of S protein were all RRSRR.The prediction of glycosylation sites showed that the two isolates had 18 and 12 N-glycosylation sites respectively,but no O-glycosylation site.Recombinant analysis shows that C2023-1 was a recombinant strain.Pathogenicity was assessed by infecting 1-day-old SPF chicks with the two isolates,and the results showed that C2023-1 strain infection could cause clini-cal symptoms such as depression and head shaking,as well as death in chicks,with a mortality rate of 37.5％.There were no clinical symptoms or deaths after infection with C2023-2 strain.Viral load test results showed that both isolates continued to detoxify until the 10th day,and had strong rep-lication capacity in the kidney,trachea and bursa of Fabricius.The results indicate significant differences in the genetic characteristics and pathogenicity of the two isolates due to their different genotypes.This study not only provides new epidemiological data on IB,which contributes to a bet-ter understanding of IBV's epidemiological features and control challenges,but also adds valuable bioinformatics resources for IBV by analyzing its variation mechanisms and biological information.

Background::Hepatitis B poses a heavy burden for children in China, however, the national studies on the distributional characteristics and health care costs of children with severe hepatitis B is still lacking. This study aimed to analyze the disease characteristics, health economic effects, and medical cost for children with severe hepatitis B in China.Methods::Based on patient information in the Hospital Quality Monitoring System, cases with severe hepatitis B were divided into four groups according to age, and the etiology and symptoms of each group were quantified. The cost of hospitalization was calculated for cases with different disease processes, and severity of disease. The spatial aggregation of cases and the relationship with health economic factors were analyzed by Moran’s I analysis. Results::The total number of children discharged with hepatitis B from January 2016 to April 2022 was 1603, with an average age of 10.5 years. Liver failure cases accounted for 43.48% (697/1603) of total cases and cirrhosis cases accounted for 11.23% (180/1603). According to the grouping of disease progression, there were 1292 cases without associated complications, and the median hospitalization cost was $818.12. According to the spatial analysis, the aggregation of cases was statistically significant at the prefectural and provincial levels in 2019, 2020, and 2021 (all P <0.05). The number of severe cases was negatively correlated with gross domestic product (Moran’s I <0) and percentage of urban population (Moran’s I <0), and positively correlated with the number of pediatric beds per million population (Moran’s I >0). Conclusion::The number of severe hepatitis B cases is low in areas with high gross domestic product levels and high urban population ratios, and health care costs have been declining over the years.

Cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is a non-atherosclerotic, non-amyloidogenic inherited cerebral small vessel disease caused by mutations in the NOTCH3 gene, typically manifesting in middle age. The diagnosis can be confirmed through the detection of granular osmiophilic material in skin biopsies and NOTCH3 gene mutations identified by genetic testing. However, the pathogenesis of this disease remains unclear, and treatment options are limited. A major contributing factor is that currently available preclinical animal models fail to adequately recapitulate the characteristic pathological features and clinical phenotypes of the disease. Therefore, a comprehensive review of recent advances in CADASIL animal models was conducted, and the advantages and limitations of existing models were systematically analyzed, aiming to offer guidance for selecting appropriate animal models in fundamental research and to propose future directions for developing experimental models.