OBJECTIVE To confirm trigger items for adverse drug reaction （ADR） induced by bevacizumab， to identify and analyze the occurrence of related ADR， and to establish a predictive model for severe adverse reaction （SAR） caused by this drug. METHODS Based on the global trigger tool （GTT） theory， and referencing the GTT White Paper， drug package inserts and relevant literature， trigger items for bevacizumab-related ADR were confirmed using a single-round Delphi method. Utilizing these established items， electronic medical records of relevant patients at Guilin People’s Hospital from January 2020 to September 2024 were actively screened via the China Hospital Pharmacovigilance System. Pharmacists then identified and tallied the occurrence of bevacizumab-induced ADR. Data from patients with any positive trigger item served as the study subjects （divided into training and test sets at a ratio of 7∶3）， candidate feature variables were selected from 39 related variables using the Boruta algorithm， and the multivariable Logistic regression analysis was performed with the occurrence of SAR as the dependent variable. Based on these candidate features， Logistic Regression， Extreme Gradient Boosting， Light Gradient Boosting Machine， Random Forest， and Categorical Boosting models were constructed. Model performance was evaluated using metrics including the area under the curve （AUC） of receiver operating characteristic curve and recall rate. The Shapley Additive exPlanations （SHAP） method was applied to analyze and interpret the contribution of each variable. A nomogram was constructed based on the optimal model. RESULTS A total of 38 trigger items for active monitoring of bevacizumab-related ADR were determined， comprising 17 laboratory indicators， 13 clinical manifestations， and 8 intervention measures. In total， 483 patients with positive trigger items were included， and 318 patients with bevacizumab-induced ADR were identified， including 83 SARs. The positive predictive values for the trigger items and cases were 43.57% （708/1 625） and 63.84% （318/483）， respectively. Bevacizumab-induced ADR involved 7 systems/organs， with the hematological system being the most frequently involved （64.15%）. The Boruta algorithm selected 7 vari ables： serum potassium， hematocrit， albumin-to-globulin ratio， prealbumin， hypertension history， age and red blood cell count. Multivariable Logistic regression showed that elevated serum potassium levels were associated with a decreased risk of bevacizumab-induced SAR （OR＝0.234， P ＝0.002）， while a history of hypertension （OR＝2.642， P ＝0.006） and increased age （OR＝1.040， P ＝0.025） were associated with an increased risk. The Logistic Regression model demonstrated superior performance with higher AUC， F1 score and recall rate （0.761， 0.447， 0.607）， compared to other models. SHAP evaluation results indicated that variables such as serum potassium， hematocrit， and age ranked highest in importance. CONCLUSIONS Totally 38 trigger entries have been successfully identified for active screening of bevacizumab-related ADR. Elevated serum potassium levels are a protective factor against bevacizumab-induced SAR， whereas the hypertension history and increased age are risk factors. The Logistic Regression model is the optimal predictive model.

ObjectiveThis paper aims to conduct a secondary analysis of a randomized controlled trial on the treatment of myelodysplastic syndrome （MDS） with deficiency of both the spleen and kidney and blockage of toxin and blood stasis with an arsenic-containing traditional Chinese medicine compound， by applying the mixed model for repeated measure （MMRM） and the method of stratified composite outcome with win ratio. The analysis includes the assessment of hematological efficacy and the composite outcome evaluation of adverse reactions， so as to more comprehensively assess the therapy of this regimen. MethodsThe MMRM and win ratio methods were used to evaluate the efficacy of a prospective，multi-center，double-blind，randomized controlled study. The blood routine （hemoglobin concentration，neutrophil count， and platelet count） and biochemical indexes （aspartate aminotransferase，alanine aminotransferase，serum creatinine，and serum ferritin） of the patients were detected at the time of enrollment and at the end of each course of treatment in the laboratory department of Xiyuan Hospital. The patients' syndromes at the time of enrollment and after treatment were recorded and scored according to the therapy standard of traditional Chinese medicine for diseases and syndromes. MMRM was used to analyze the blood routine indexes of the experimental group and the control group. This method has the advantages of high data reliability and dynamic efficacy under intervention and time. The win ratio method was used to evaluate the composite outcome of traditional Chinese medicine syndrome scores and biochemical indexes according to the priority and to verify the clinical safety of arsenic-containing traditional Chinese medicine compound. ResultsThe results of MMRM analysis showed that the hemoglobin concentration of patients in the group with arsenic-containing traditional Chinese medicine compound increased significantly compared with that before treatment in the group，while that in the placebo group decreased significantly （P<0.01）. When compared with that after treatment in the placebo group，the hemoglobin concentration of patients in the group with arsenic-containing traditional Chinese medicine compound increased significantly，and the mean difference of least squares （LS） was statistically significant （P<0.01）. When compared with those before treatment in the group，there were no statistically significant differences in the neutrophil count and platelet count in both groups. After treatment，there were no statistically significant differences in the neutrophil count， platelet count， and the mean difference of LS between the two groups. The analysis results of win ratio showed that the group with arsenic-containing traditional Chinese medicine compound had a significant advantage in the comparison of composite outcomes，with a win ratio （95% CI） of 2.01 （1.24-3.27） （P<0.01），and that the possibility of "winning" in terms of safety was 2.01 times that of the placebo group. The safety advantage of the group with arsenic-containing traditional Chinese medicine compound mainly came from the traditional Chinese medicine syndrome scores，renal function indexes， and iron reserve capacity indexes，and the number of winning times was less than that of losing times in the comparison of liver function outcomes. ConclusionThe MMRM analysis proves that the arsenic-containing traditional Chinese medicine compound can significantly improve the hemoglobin concentration of patients with myelodysplastic syndrome with refractory cytopenia and multilineage dysplasia （MDS-RCMD） of the type of deficiency of both the spleen and kidney and blockage of toxin and blood stasis. This conclusion is not interfered with by time trends and individual relationships and methodologically improves the credibility of the therapy of the arsenic-containing traditional Chinese medicine compound in treating MDS. Four outcomes are evaluated by the win ratio method，namely traditional Chinese medicine syndromes，liver function，renal function， and iron reserve capacity，proving that the arsenic-containing traditional Chinese medicine compound has the comprehensive advantages of improving the survival quality of the patients and reducing adverse reactions. The win ratio outcome provides clear comparative indexes for the evaluation of adverse reactions，making it easier for regulatory authorities，medical staff， and patients to understand the safety of the arsenic-containing traditional Chinese medicine compound in clinical application.

Metabolic associated fatty liver disease （MAFLD） is a common chronic liver disease worldwide， and timely and precise intervention can delay disease progression and significantly reduce the risk of serious complications such as liver fibrosis， liver cirrhosis， and liver cancer. Although traditional liver biopsy combined with metabolic markers is the gold standard， it may cause complications such as pain and bleeding as an invasive examination， which has promoted scientific research to shift its focus to the construction of noninvasive assessment systems. In recent years， noninvasive diagnostic technologies based on multi-dimensional detection strategies have been continuously updated， including serological models， imaging techniques， and clinical algorithms. This article systematically reviews the screening methods for MAFLD during the fibrotic stages F1—F3， especially deep learning models based on artificial intelligence， in order to provide ideas for the early screening of MAFLD， as well as a scientific reference for optimizing disease management strategies.

ObjectiveTo systematically evaluate the effectiveness of music therapy in reducing children’s dental anxiety by summarizing relevant literature， and to provide application references for the clinical practice of pediatric dentistry in China. MethodsA systematic literature search was conducted using the Cochrane Library and Medline databases. Clinical trials， systematic reviews， and cohort studies on the effectiveness of music in children’s dental anxiety both domestically and internationally were included. A detailed retrospective analysis of the included literature was conducted to extract relevant evidence and conclusions. ResultsThrough extensive literature screening and quality assessment， multiple studies showed that music therapy could positively influence emotions through biological and psychological mechanisms. In clinical practice， music was confirmed to be an effective auxiliary means that significantly reduced children’s dental anxiety levels. ConclusionMusic therapy can not only effectively alleviate children’s anxiety during medical visits but also improve the effectiveness of diagnosis and treatment， promoting harmonious doctor-patient relationships. Therefore， hospitals should actively explore and implement specific pathways to music therapy， including multiple specific suggestions such as music selection， optimization of playback environment， and interaction strategies with children， with a view to achieving the goals of being people-oriented and pursuing goodness and beauty in medical humanities， and thus achieving the ultimate goal of health humanities.

Objective To systematically review the studies on predictive models for delayed graft function (DGF) after kidney transplantation. Methods Databases including China Biology Medicine Database, China National Knowledge Infrastructure, Wanfang Database, VIP Database, PubMed, Web of Science and CINAHL were searched to collect studies on predictive models for DGF after kidney transplantation published from the establishment of each database to June 29, 2025. Two researchers screened the literatures according to the inclusion and exclusion criteria, evaluated the quality of the literatures using the prediction model risk of bias assessment tool (PROBAST), and conducted a meta-analysis of the common predictors of the models using R software. Results A total of 12 literatures were included, involving 14 predictive models with sample sizes ranging from 103 to 24 653 cases. Donor serum creatinine level, cold ischemia time, donor age and donor body mass index were the top four common predictors. All the predictive models were at high risk of bias and low in applicability. The results of meta-analysis showed that abnormal donor body mass index, advanced donor age, prolonged cold ischemia time and elevated donor serum creatinine level were all associated with an increased risk of DGF after transplantation (all P<0.01), but there was high heterogeneity among the studies. Fixed-effect model and random-effect model were used to re-pool the effect sizes separately. The results indicated that the fixed-effect model and random-effect model had good consistency in terms of donor body mass index, donor age and cold ischemia time, while there was a significant difference in the effect sizes of the two models for donor serum creatinine level. Conclusions The predictive models for DGF risk after kidney transplantation have good predictive performance, but the overall risk of bias is high. In the future, large-sample, multicenter and high-quality prospective clinical studies should be carried out to optimize the predictive models, so as to improve their predictive ability and clinical application value.

In-depth study of the components of polymyxins is the key to controlling the quality of this class of antibiotics.Similarities and variations of components present significant analytical challenges.A two-dimensional(2D)liquid chromatography-mass spectrometry(LC-MS)method was established for screening and comprehensive profiling of compositions of the antibiotic colistimethate sodium(CMS).A high concentration of phosphate buffer mobile phase was used in the first-dimensional LC system to get the components well separated.For efficient and high-accuracy screening of CMS,a targeted method based on a self-constructed high resolution(HR)mass spectrum database of CMS components was established.The database was built based on the commercial MassHunter Personal Compound Database and Library(PCDL)software and its accuracy of the compound matching result was verified with six known components before being applied to genuine sample screening.On this basis,the unknown peaks in the CMS chromatograms were deduced and assigned.The molecular formula,group composition,and origins of a total of 99 compounds,of which the combined area percentage accounted for more than 95％of CMS components,were deduced by this 2D-LC-MS method combined with the MassHunter PCDL.This profiling method was highly efficient and could distinguish hundreds of components within 3 h,providing reliable results for quality control of this kind of complex drugs.

BackgroundSevere mental disorders represent a major public health concern due to the high disability rates and substantial disease burden， which has garnered significant national attention and prompted their inclusion in public health project management systems. However， credible evidence regarding the current status of disease management and factors influencing disease stabilization among patients with severe mental disorders in Luzhou City， Sichuan Province， remains limited. ObjectiveTo investigate the current management status of patients with severe mental disorders in Luzhou City， Sichuan Province， and to analyze influencing factors of disease stabilization among patients under standardized care， so as to provide evidence-based insights for developing targeted management strategies to optimize clinical interventions for this patient population. MethodsIn March 2023， data were extracted from the Sichuan Mental Health Service Comprehensive Management Platform for patients with severe mental disorders in Luzhou City who received management between December 2017 and December 2022. Information on mental health service utilization and clinical status changes was collected. Trend analysis was conducted to evaluate temporal changes in key management indicators for severe mental disorders in Luzhou City. Logistic regression analysis was employed to identify factors influencing the disease stabilization or fluctuation of these patients. ResultsThis study enrolled a total of 20 232 patients. In Luzhou City， the stabilization rate and standardized management rate of severe mental disorders were 94.89% and 79.36% in 2017， respectively， which increased to 95.33% and 96.92% by 2022. The regular medication adherence rate rose from 34.42% in 2018 to 86.81% in 2022. In 2022， the regular medication adherence rate was 71.80% for schizophrenia， 55.26% for paranoid psychosis， and 51.43% for schizoaffective disorder. Multivariate analysis identified the following protective factors for disease stabilization： age of 18~39 years （OR=0.613， 95% CI： 0.409~0.918）， age of 40~65 years （OR=0.615， 95% CI： 0.407~0.931）， urban residence （OR=0.587， 95% CI： 0.478~0.720）， and regular medication adherence （OR=0.826， 95% CI： 0.702~0.973）. Risk factors for disease fluctuation included poor （OR=1.712， 95% CI： 1.436~2.040）， non-inclusion in care-support programs （OR=1.928， 95% CI： 1.694~2.193）， non-participation in community rehabilitation （OR=2.255， 95% CI： 1.930~2.634）， and intermittent medication adherence （OR=3.893， 95% CI： 2.548~5.946）. ConclusionThe stability rate， standardized management rate， and regular medication adherence rate of patients with severe mental disorders in Luzhou City have shown a year-by-year increase. Age， household registration status， economic condition， medication compliance， and community-based rehabilitation were identified as influencing factors for disease fluctuation in these patients. ［Funded by Luzhou Science and Technology Plan Project （number， 2022-ZRK-186）］

BACKGROUND: Regulatory dendritic cell (DCreg) subset exhibits a unique capacity for inducing immune tolerance among the variety subsets of dendritic cells (DCs) within gut-associated lymphoid tissues (GALTs). Fms-like tyrosine kinase 3 ligand (FLT3L) is involved in the differentiation of DCregs and the subsequent expansion of regulatory T-cells (Tregs) mediated by DCregs, though the precise mechanism remains poorly understood. This study aimed to explore the expansion mechanism of Treg induced by DCreg and the role of FLT3L in this process. METHODS: DCregs were distinguished from other DC subsets isolated from GALTs of BALB/c mice through a mixed lymphocyte reaction assay. The functions and mechanisms by which FLT3L promoted Treg expansion via DCregs were investigated in vitro through co-culture experiments involving DCregs and either CD4 + CD25 - T-cells or CD4 + CD25 + T-cells. Additionally, an in vivo experiment was conducted using a dextran sulfate sodium (DSS)-induced colitis model in mice. RESULTS: CD103 + CD11b + DC exhibited DCreg-like functionality and was identified as DCreg for subsequent investigation. Analysis of Foxp3 + Treg percentages within a co-culture system of CD4 + CD25 - T-cells and DCregs, with or without FLT3L, demonstrated the involvement of the FLT3/FLT3L axis in driving the differentiation of precursor T-cells into Foxp3 + Tregs induced by DCregs. Cell migration and co-culture assays revealed that the FLT3/FLT3L axis enhanced DCreg migration toward Tregs via the Rho pathway. Additionally, it was observed that DCregs could promote Treg proliferation through the Notch pathway, as inhibition of Notch signaling by DAPT (N-[N-(3,5-difluorophenacetyl)-l-alanyl]-S-phenylglycine t-butyl ester) suppressed Treg expansion within the co-culture system of DCregs and CD4 + T-cells or CD4 + CD25 + T-cells. Furthermore, the FLT3/FLT3L axis influenced JAG1 expression in DCregs, indirectly modulating Treg expansion. In vivo experiments further established that FLT3L promoted DCreg expansion and restored Treg balance in DSS-induced colitis models, thereby ameliorating colitis symptoms in mice. CONCLUSION The FLT3/FLT3L axis is integral to the maintenance of DCreg function in Treg expansion.
Animals ; T-Lymphocytes, Regulatory/immunology* ; Dendritic Cells/immunology* ; Mice ; Mice, Inbred BALB C ; Membrane Proteins/metabolism* ; Receptors, Notch/metabolism* ; Lymphoid Tissue/metabolism* ; Signal Transduction/physiology* ; Coculture Techniques ; Flow Cytometry

Alzheimer's disease (AD), a prototypical neurodegenerative disorder, encompasses multifaceted pathological processes. As pivotal cellular structures within the central nervous system, ion channels play critical roles in regulating neuronal excitability, synaptic transmission, and neurotransmitter release. Extensive research has revealed significant alterations in the expression and function of ion channels in AD, implicating an important role of ion channels in the pathogenesis of abnormal Aβ deposition, neuroinflammation, oxidative stress, and disruptions in calcium homeostasis and neural network functionality. This review systematically summarizes the crucial roles and underlying mechanisms of ion channels in the onset and progression of AD, highlighting how these channel abnormalities contribute to AD pathophysiology. We also discuss the therapeutic potential of ion channel modulation in AD treatment, emphasizing the importance of addressing multifactorial nature and heterogeneity of AD. The development of multi-target drugs and precision therapies is proposed as a future direction of scientific research.
Alzheimer Disease/therapy* ; Humans ; Ion Channels/physiology* ; Oxidative Stress ; Animals ; Amyloid beta-Peptides/metabolism* ; Synaptic Transmission ; Calcium/metabolism*