Objective: To analyze the epidemiological characteristics of category C intestinal infectious diseases among children and adolescents in Shenzhen from 2012 to 2024 and the association with meteorological factors, so as to provide a scientific basis for the targeted prevention and control of infectious diseases for children and adolescents. Methods: Using data from the "Infectious Disease Reporting Information Management System" of the "China Disease Prevention and Control Information System" covering the period from January 1, 2012 to December 31, 2024, the study analyzed clinical and confirmed cases of hand, foot, and mouth disease, other infectious diarrhea, and acute hemorrhagic conjunctivitis among individuals aged 6-19 years old to describe demographic and temporal characteristics. It used Joinpoint regression to calculate the average annual percent change (AAPC) and annual percent change (APC) to analyze incidence trends, and Spearman s correlation was combined to generalize linear models so as to assess the association between category C intestinal infectious diseases and meteorological factors. Results: From 2012 to 2024, a cumulative total of 61 019 cases of hand, foot, and mouth disease among children and adolescents, 58 498 cases of other infectious diarrhea, and 6 377 cases of acute hemorrhagic conjunctivitis were reported. The AAPC in the incidence rates of these three diseases was 19.19%, 31.03% and 31.48 %, respectively(all P <0.05). Notably, the incidence of hand, foot, and mouth disease increased significantly after 2022 (APC= 133.66 %, P <0.01). The temporal distribution showed that hand,foot,and mouth disease was most prevalent in May,June and July (seasonal index of 2.39,3.64,1.97), other infectious diarrhea was most prevalent in February,March and December (seasonal index of 1.22,1.25,1.47), and acute hemorrhagic conjunctivitis peaked in September and October (seasonal index of 4.22,2.16). Monthly average temperature could increase the risk of hand,foot,and mouth disease( β = 0.18 ,95% CI =0.11-0.25); as monthly average wind speed increased, the incidence of other infectious diarrhea ( β =-0.86, 95% CI = -1.50 to -0.22) and acute hemorrhagic conjunctivitis ( β =-1.32, 95% CI =-2.60 to -0.05) both decreased (all P < 0.05 ). Conclusions Among children and adolescents in Shenzhen, category C intestinal infectious diseases remain prevalent throughout the year；the number of reported hand, foot, and mouth disease cases has shown an upward trend in recent years.Temperature and wind speed significantly affect the number of reported cases of three types with category C intestinal infectious diseases.

ObjectiveTo investigate the effects of Xinfeng capsules combined with chronic disease management of traditional Chinese medicine （TCM） on rapid disease control and short-term prognosis of patients with rheumatoid arthritis （RA）. MethodsA total of 80 RA patients hospitalized in the Department of Rheumatology of The First Affiliated Hospital of Anhui University of Chinese Medicine from January 2022 to March 2024 were enrolled and randomly divided into an observation group （40 cases） and a control group （40 cases）. The control group was treated with conventional methotrexate combined with standard chronic disease management， while the observation group was additionally treated with Xinfeng Capsules combined with TCM chronic disease management. The treatment course lasted 24 weeks. The outcomes were compared between two groups， including disease activity ［28-joint disease activity score （DAS28）， clinical disease activity index （CDAI）， simplified disease activity index （SDAI）］， visual analogue scale （VAS） for pain， TCM syndrome score， tender joint count （TJC）， swollen joint count （SJC）， morning stiffness duration， Health Assessment Questionnaire （HAQ）， Self-Rating Anxiety Scale （SAS）， Self-Rating Depression Scale （SDS）， American College of Rheumatology （ACR） 20%， 50% and 70% response rates （ACR20/50/70）， erythrocyte sedimentation rate （ESR）， high-sensitivity C-reactive protein （hs-CRP）， rheumatoid factor （RF）， anti-cyclic citrullinated peptide antibody （CCP-Ab）， interleukin （IL）-6， IL-1β， tumor necrosis factor-α （TNF-α）， and serum immunoglobulin G （IgG）. The Chronic Disease Self-Management Scale （CDSMS） was used to evaluate patients’ self-management ability， self-care ability， and nursing satisfaction. Patients were followed up for 12 weeks to assess prognosis， and COX regression analysis was performed to determine the impact on short-term prognosis. ResultsAfter treatment， TJC， SJC， morning stiffness duration， DAS28， CDAI， SDAI， VAS， TCM syndrome score， ESR， hs-CRP， RF， CCP-Ab， IL-6， IL-1β， TNF-α， IgG， HAQ， SAS， SDS， chronic disease self-management behavior， self-efficacy， and self-care ability all improved significantly in both groups compared with baseline （P<0.05，P<0.01）. Compared with the control group， the observation group showed more significant improvements in TJC， SJC， morning stiffness duration， DAS28， CDAI， SDAI， VAS， TCM syndrome score， ESR， IL-1β， IgG， HAQ， SAS， SDS， self-care ability， chronic disease self-management behavior， and self-efficacy （P<0.05 or P<0.01）. The ACR70 response rate and nursing satisfaction were significantly higher in the observation group than in the control group （P<0.01）. COX regression analysis showed that Xinfeng capsules combined with TCM chronic disease management reduced the risk of poor short-term prognosis in RA patients. ConclusionXinfeng capsules combined with TCM chronic disease management facilitates rapid disease control in RA patients， effectively improves short-term prognosis， and plays an important role in the treatment of the disease.

Hepatocellular carcinoma (HCC) is one of the fastest growing cancers in the world, ranking fourth among the causes of cancer-induced death in the world. At present, the field of HCC treatment is developing rapidly, and immunotherapy has been recognized as a promising treatment method, in which T cells play a key role in HCC immunotherapy. However, in the case of virus infection or in tumor microenvironment (TME), T cells will be continuously stimulated by antigens and then fall into the state of T cell exhaustion (Tex). This state will not only reduce the immunity of patients but also lead to poor efficacy of immunotherapy. Therefore, to deeply analyze the mechanism of Tex and to explore effective strategies to reverse Tex is the key point in the immunotherapy for HCC. This review aims to summarize the mechanism of Tex in HCC patients, and the current situation and shortcomings of drug research and development to reverse Tex at this stage, in order to provide theoretical basis for the optimization of immunotherapy regimen for HCC patients.
Humans ; Carcinoma, Hepatocellular/therapy* ; Liver Neoplasms/therapy* ; Immunotherapy/methods* ; T-Lymphocytes/immunology* ; Tumor Microenvironment/immunology* ; Animals ; T-Cell Exhaustion

Alzheimer's disease (AD) is characterized by cognitive and functional deterioration, with pathological features such as amyloid-beta (Aβ) aggregates in the extracellular spaces of parenchymal neurons and intracellular neurofibrillary tangles formed by the hyperphosphorylation of tau protein. Despite a thorough investigation, current treatments targeting the reduction of Aβ production, promotion of its clearance, and inhibition of tau protein phosphorylation and aggregation have not met clinical expectations, posing a substantial obstacle in the development of drugs for AD. Recently, artificial intelligence (AI), computational biology (CB), and systems biology (SB) have emerged as promising methodologies in AD research. Their capacity to analyze extensive and varied datasets facilitates the identification of intricate patterns, thereby enriching our comprehension of AD pathology. This paper provides a comprehensive examination of the utilization of AI, CB, and SB in the diagnosis of AD, including the use of imaging omics for early detection, drug discovery methods such as lecanemab, and complementary therapies like phototherapy. This review offers novel perspectives and potential avenues for further research in the realm of translational AD studies.

Objective:To explore the genetic etiology for a Chinese pedigree affected with X-linked cardiac valve dysplasia (CVDPX) and chronic idiopathic intestinal pseudo-obstruction (CIIPX).Methods:A pedigree presented at the First Hospital of Lanzhou University in June 2024 for CVDPX combined with CIIPX was selected as the study subject. Whole exome sequencing (Trio-WES) was carried out, and the candidate variant was verified by Sanger sequencing. This study has been approved by the Medical Ethics Committee of the First Hospital of Lanzhou University (Ethics No. LDYYSZLLKH2024-15).Results:Both the proband and his affected younger brother were found to harbor a hemizygous c. 443A>G (p.Tyr148Cys) variant of the FLNA gene, for which their mother was heterozygous and their father was not a carrier, suggesting an X-linked recessive inheritance pattern. The variant was not recorded by the OMIM and ClinVar databases, and was determined to be likely pathogenic (PM2+ PS4+ PP2+ PP3) based on the guidelines from the American College of Medical Genetics and Genomics (ACMG). The patients had presented with typical CVDPX/CIIPX phenotype, including multiple valve dysplasia and chronic pseudo intestinal obstruction, in addition with gallbladder wall edema and thickening. Bioinformatic analysis showed that the variant site is highly conserved, and multiple algorithms had predicted its pathogenicity. Conclusion:This study confirmed the diagnosis of CVDPX/CIIPX in a Chinese pedigree, expanded the phenotype spectrum of FLNA gene variants, and provided a basis for genetic counseling and prenatal diagnosis for the pedigree.

Objective:To develop PixelSIFT-UNet, a novel semantic segmentation model that integrates deep learning with scale-invariant feature transform (SIFT) algorithm to improve the segmentation accuracy of oral mucosal lesions.Methods:This investigation utilized 838 standard clinical white light images of oral mucosal diseases acquired from January 2020 to December 2022 at the Stomatology Hospital Zhejiang University School of Medicine. Randomization was achieved through Python′s random.seed function implementation. The random sample function was subsequently applied for sampling distribution. The dataset was stratified into three subsets with a 6∶2∶2 ratio: training ( n=506), validation ( n=166), and testing ( n=166). Lesion boundaries were annotated using Labelme software, and a PixelSIFT-UNet-based deep learning model was developed with VGG-16 and ResNet-50 backbone networks. Model parameters were optimized using the validation set, and performance metrics [including Dice coefficient, mean intersection over union (mIoU), mean pixel accuracy (mPA), and Precision] were assessed on the test set. The model′s performance was benchmarked against conventional semantic segmentation frameworks (U-Net and PSPNet). Results:The developed PixelSIFT-UNet model could achieve precise segmentation of three common oral mucosal lesions: oral lichen planus, oral leukoplakia, and oral submucous fibrosis. Utilizing VGG-16 as the backbone network, the model achieved Dice coefficient, mIoU, mPA, and Precision values of 0.642, 0.699, 0.836, and 0.792, respectively. Implementation with ResNet-50 backbone network yielded metrics of 0.668, 0.733, 0.872 and 0.817, demonstrating significant improvements across all performance indicators compared to conventional U-Net model (relevant metrics: 0.662, 0.717, 0.861 and 0.809) and PSPNet model (relevant metrics: 0.671, 0.721, 0.858 and 0.813).Conclusions:The proposed PixelSIFT-UNet architecture demonstrates superior performance in oral mucosal lesion segmentation tasks, surpassing conventional semantic segmentation models and providing robust quantitative improvements in segmentation accuracy.

In the general population, obesity (high BMI) is often considered as an important risk factor for many diseases and premature death. However, in patients with a certain disease, the risk of death in people with obesity was lower than that in people with normal weight. This abnormal correlation has caused widespread discussion, and different explanations have been given by physiology and epidemiology. Based on causal inference theory, this study used directed acyclic graphs to introduce the collision bias (also called collision-stratification bias). Through example demonstrations, this study explored whether and why the abnormal correlation between obesity and higher survival rates in patients with hyperglycemia exists. Finally, it was concluded that this abnormal correlation among patients with a certain disease (e.g., hyperglycemia in the current analysis) was partly or even totally caused by collider bias.

Objective:To analyze the epidemiological characteristics and natural focus distribution of marburg virus disease (MVD), and provide evidence for the prevention and control of MVD.Methods:A systematic literature retrieval was conducted, and descriptive epidemiological method was used to analyze the temporal, spatial, and population distributions of MVD as well as its natural hosts. The case fatality rate of MVD was evaluated through Meta-analysis, and the phylogenetic analysis of viral genomes was done by using software IQ-TREE 2.3.6.Results:Marburg virus has endemic spread in Africa and can be detected in various animals such as primates and bats. The positive rate is higher in Egyptian fruit bats, and the disease epidemic areas continue to expand. The human infections occur frequently. As of December 20, 2024, a total of 18 MVD outbreaks had been reported worldwide, resulting in 722 reported cases and 548 deaths. Meta- analysis showed a case fatality rate of about 65.19% (95% CI: 48.07%-80.50%). Populations are generally susceptible, with a higher proportion of the cases in miners and medical workers. Marburg virus specific antibody can be detected in populations and animals in some countries and regions where no cases have been reported in Africa, indicating the potential of virus transmission. Conclusion:The transmission capacity of Marburg virus shows no significant changes, but the areas affected by the virus transmission expands, indicating increased risk for MVD outbreak.

Objective To develop a virtual reality rehabilitation support system and evaluate its effects on improving discharge readiness in caregivers of laryngectomy patients.Methods The system is equipped with a virtual reality-based home nursing skills guidance module for post-laryngectomy patients and an evidence-based artificial intelligence Q&A module.A convenience sampling method was adopted to select 64 caregivers of patients who underwent laryngectomy for the first time in the otorhinolaryngology head and neck surgery department of a tertiary A hospital in Beijing from July 2024 to January 2025 for a systematic study on application effects.To avoid cross-contamination between an experimental group and a control group,ward-based grouping was applied.A coin toss was used to assign Ward 1 to an experimental group and Ward 2 to a control group,with 32 cases in each group.The experimental group received discharge guidance based on the virtual reality technology,while the control group was provided with conventional verbal and written discharge instructions.The readiness for hospital discharge and the quality of discharge teaching scores of caregivers were compared between the 2 groups after the intervention.Results No sample detachment.After the intervention,the patient caregivers in the experimental group scored significantly higher than those in the control group in terms of discharge readiness and quality of discharge guidance,with a statistically significant difference(P＜0.001).Conclusion This study developed the virtual reality rehabilitation system for laryngeal cancer patients demonstrated good feasibility and effectiveness.The application of this system for discharge education significantly improved discharge readiness of caregivers and quality of discharge guidance for post-laryngectomy patients.It also helped with the optimization of health education models,enhancement of nursing resource utilization efficiency,and improvement of transitional care.

Objective:To explore the differences in sociodemographic and clinical characteristics between pa-tients with unipolar depression bipolar depression and to establish a nomogram for identifying bipolar depression.Methods:Using data from the China Mental Disorders Cohort Study,the sociodemographic and clinical characteristics of 2 643 patients with unipolar depression and 250 patients with bipolar depression diagnosed accord-ing to the criteria of the Diagnostic and Statistical Manual of Mental Disorders,Fifth Edition(DSM-5)were includ-ed to compare their sociodemographic and clinical characteristics.These characteristics included general demograph-ic information,disease-related information,clinical examination results,and the severity of the disease assessed with the Global Assessment of Functioning(GAF)and Hamilton Depression Rating Scale.Logistic regression analysis was employed to identify factors influencing bipolar depression,and a nomogram was constructed for its identifica-tion.Results:The risk factors for bipolar depression included being male(OR=1.48),being employed(OR=1.38),having non-melancholic features during episodes(OR=2.33),a Body Mass Index ranging from normal to obese(OR=2.48,2.49,4.65),psychotic features(OR=2.14),mixed episode(OR=9.36),comorbid physical diseases(OR=2.47),four or more depressive episodes(OR=1.67),earlier age of onset(OR=0.95),longer ill-ness duration(OR=1.03),and higher GAF scores(OR=1.02).The nomogram model achieved an AUC of 0.81(95％CI:0.78-0.84).The Hosmer-Lemeshow test result was x2=6.96(P＞0.05),indicating good model fit.The calibration curve showed good performance.The decision curve analysis revealed that the nomogram pro-vides significant clinical benefit when the risk of bipolar depression was within the range of 0 to 0.9.Conclusion:The nomogram established based on the identified sociodemographic and clinical factors can accurately assess the risk of bipolar depression,providing a useful tool for early identification and intervention.