ObjectiveTo investigate the present situation of input, output, outcome and impact of all registered community-based rehabilitation stations in Inner Mongolia in China, and analyze how the input predict the output, outcome and impact. MethodsFrom March 1st to April 30th, 2025, a questionnaire survey was conducted on all registered community-based rehabilitation stations in Inner Mongolia, covering four dimensions: input, output, outcome and impact. A total of 1 365 questionnaires were distributed. The input included four items: laws and policies, human resources, equipment and facilities, and rehabilitation information management. The output included two items: technical paths and benefits/effectiveness. The outcome included three items: coverage rates, rehabilitation interventions and functional results. The impact included two items: health and sustainability. Each item contained several questions, all of which were described in a positive way. Each question was scored from one to five. A lower score indicated that the situation of the community-based rehabilitation station was more in line with the content described in the question. Regression analysis was performed using the total score of each item of input dimension as independent variables, and the total scores of the output, outcome and impact dimensions as dependent variables. ResultsA total of 1 262 valid questionnaires were collected. The mean values of input, output, outcome and impact of community-based rehabilitation stations were 1.827 to 1.904, with coefficient of variation of 45.892% to 49.239%. The regression analysis showed that, rehabilitation information management, human resources, and laws and policies significantly predicted the output dimension (R² = 0.910, P < 0.001). Meanwhile, all four items in the input dimension predicted both the outcome (R² = 0.850, P < 0.001) and impact dimensions (R² = 0.833, P < 0.001). ConclusionInput, output, outcome and impact of the community-based rehabilitation stations in Inner Mongolia were generally in line with the content of the questions, although some imbalances were observed. Additionally, the input of community-based rehabilitation stations could significantly predict their output, outcome and impact.

Objective: To investigate the factors influencing intraoperative blood transfusion in patients with hip fractures and to develop a machine learning (ML) model for predicting this risk. Methods: A total of 424 patients with hip fractures who underwent surgical treatment between November 2022 and March 2025 in our hospital were selected. Key feature variables of intraoperative blood transfusion risk were identified using the Boruta algorithm. Four different ML algorithms—support vector machine (SVM), linear discriminant analysis (LDA), mixed discriminant analysis (MDA), and extreme gradient boosting (XGBoost)—were used to develop predictive models for intraoperative blood transfusion risk. The predictive performance of the four ML models were evaluated using accuracy, precision, receiver operating characteristic (ROC) curves, precision-recall curves (PRC), precision-recall gain curves (PRGC), and F1 scores. Shapley additive interpretation (SHAP) was used to interpret the final model. Results: Among the 424 patients, 77(18.2%) received intraoperative blood transfusion. The Boruta algorithm identified albumin (ALB), activated partial thromboplastin time (APTT), types of anesthesia, types of fracture, and hemoglobin (Hb) as key feature variables for predicting intraoperative blood transfusion risk. In model evaluation, the SVM model outperforms the other three models across multiple metrics, including the area under the receiver operating characteristic curve (AUC), recall, recall gain, accuracy, precision, F1 score, and the area under the precision-recall curve (PRC-AUC). The SVM model, interpreted and visualized based on SHAP values, effectively predicted intraoperative blood transfusion risk in patients with hip fracture. A visual online application was developed based on the SVM model (https://pbo-nomogram.shinyapps.io/blood/). Conclusion: Preoperative low ALB and Hb levels, prolonged APTT, general anesthesia, and intertrochanteric fractures are risk factors for intraoperative blood transfusion in hip fracture patients. The risk prediction model for intraoperative blood transfusion constructed based on the SVM algorithm has optimal performance, which provides new ideas and methods for the clinical early identification of hip fracture patients with high transfusion risk and the implementation of targeted interventions.

ObjectiveTo explore the potential mechanisms by which Myristica fragrans prevents and treats atherosclerosis （AS）. MethodsThe major active components of Myristica fragrans and their shared targets with AS were obtained from databases. The shared targets were subjected to pathway enrichment analysis and PPI network construction using the ClusterProfile package and the STRING database. Molecular docking between key targets and major active components was performed using AutoDock. Gene expression data from early and late， as well as stable and unstable AS plaques， were used to validate changes of key targets and major pathways during AS progression. Western blot， flow cytometry， YO-PRO-1/PI staining， and TUNEL staining were applied to verify the main mechanisms. ResultsNine active components of Myristica fragrans interacted with 293 AS-related targets， among which eight components acted on an average of 57.0% of the shared targets. Gene ontology （GO） and Kyoto encyclopedia of genes and genomes （KEGG） enrichment analyses indicated that the anti-AS effects mainly involved oxidative stress， inflammation， lipid metabolism， fluid shear stress， and apoptosis pathways. PPI network revealed JUN， CASP3， MAPK3， and AKT1 as key targets mainly involved in regulating apoptosis. Molecular docking showed stable binding conformations and high affinities between major components and these targets. Integrated analysis of gene expression in early and late， as well as stable and unstable AS plaques， showed significant enrichment of leukocyte apoptosis pathways in late and unstable plaques. Cell experiments further confirmed that Myristica fragrans significantly reduced Cleaved-CASP3（P=0.04）and p-MAPK3（P=0.000 3）levels， increased p-AKT1（P=0.004）levels， and inhibited macrophage apoptosis. ConclusionMyristica fragrans potentially interferes with AS development by modulating pathways related to oxidative stress， inflammation， lipid metabolism， fluid shear stress， and apoptosis， with CASP3， MAPK3， and AKT1 serving as key targets mediating its anti-apoptotic and anti-AS effects.

Objective To explore the medicinal mechanism of Actinidia Chinensis Planch Radix(ACPR)in the treatment of colorectal cancer(CRC)by network pharmacology and molecular docking technology.Methods The genes involved in the effects of the main chemical components and disease genes of ACPR were screened from the TCM database and disease database.The main genes were analyzed through protein interaction network analysis,and molecular docking was performed on the main chemical components and key targets.The effects of the drug on tumor cells were measured,and the levels of key proteins in the signaling pathway were detected.Results The primary components of ACPR for treating CRC include quercetin,β-sitosterol,aloe baicalin,and catechin.It targets 144 protein interaction sites and were involved in the protein interaction network,with key genes including AKT1,TP53,MAPK1,JUN,and TNF.The recognition network includes five modules that were involved in various biological processes and signaling pathways.The main components exhibited excellent or good activity when interacting with these targets.At a certain concentration,the drug could inhibit the proliferation,invasion,and migration of colorectal cancer cells and affect the PI3K/AKT signaling pathway.Conclusion ACPR has been used to treat colorectal cancer through multiple pathways and multiple targets,among which the PI3K/AKT signaling pathway may be the mechanism.

OBJECTIVE To explore the molecular mechanism of Xijiao Dihuang Decoction(XJDHT)in inhibiting inflammatory response in sepsis based on network pharmacology,molecular docking and in vitro and in vivo experiments.METHODS Active com-ponents of XJDHT were screened using the TCMSP and HERB databases.Sepsis-related targets and histone H3K36 trimethylation(H3K36me3)-associated targets were retrieved from GeneCard,OMIM,and DisGeNet databases.A protein-protein interaction(PPI)network was constructed using the STRING database,and core targets were identified via Cytoscape 3.9.1.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analyses were performed to predict potential mechanisms.Mo-lecular docking validated ligand-receptor binding affinity.A cecal ligation and puncture(CLP)model was established in mice to evalu-ate 24-hour sepsis scores(MSS)and survival rates.Blood routine parameters were analyzed using an automated hematology analyzer.Serum IL-1β and TNF-α levels were measured by ELISA.Liver histopathology was assessed via HE staining,and H3K36me3 expression in Kupffer cells was detected by immunofluorescence.In vitro,LPS-induced THP-1 cells were used as an in-flammatory model.ChIP-qPCR evaluated H3K36me3 enrichment at IL-1β and TNF-α gene loci.Western blot analyzed HIF-1α,EGFR,and AKT1 pathway proteins.RESULTS A total of 28 active components of XJDHT were identified,corresponding to 987 gene targets,with 189 overlapping sepsis-related targets.Core targets included TNF,IL1B,and GAPDH.Enriched pathways includ-ed EGFR tyrosine kinase inhibitor resistance.Molecular docking confirmed strong binding between core components and key targets.In vivo,compared to the sham group,the CLP group exhibited significantly reduced 24-hour survival(P<0.01),elevated MSS(P<0.01),immune imbalance,and increased serum IL-1β and TNF-α levels(P<0.01).High-and low-dose XJDHT intervention im-proved survival(P<0.01),reduced MSS(P<0.01),restored immune homeostasis,and dose-dependently suppressed IL-1β and TNF-α(P<0.01).CLP mice showed elevated H3K36me3 in Kupffer cells and severe hepatic inflammation,while XJDHT dose-de-pendently reduced H3K36me3(P<0.05)and attenuated liver injury.In peritoneal macrophages,CLP upregulated H3K36me3,IL-1β,TNF-α,HIF-1α,p-AKT1/AKT1,and EGFR(P<0.01),which were reversed by XJDHT(P<0.05,P<0.01).In vitro,LPS increased H3K36me3 and IL-1β and TNF-α expression(P<0.01),with ChIP-qPCR confirming H3K36me3 enrichment at IL-1β lo-ci(P<0.01).Treatment with 15%XJDHT-containing serum for 24 h reduced H3K36me3(P<0.01),diminished its recruitment to IL-1β loci(P<0.01),and inhibited LPS-induced activation of EGFR,HIF-1α,and p-AKT1/AKT1(P<0.05,P<0.01).HIF-1α agonist Dimethyloxallyl Glycine(DMOG)further validated that XJDHT suppressed H3K36me3-mediated epigenetic remodeling via HIF-1α-related pathways.CONCLUSION XJDHT inhibits inflammatory responses,regulates immune homeostasis,and improves sepsis prognosis,potentially by modulating H3K36me3 epigenetic modifications at IL-1β loci.

Gastric cancer with peritoneal metastasis (GCPM) is a common and lethal manifestation of advanced gastric cancer, with a median survival of only 5-11 months. This consensus was developed by 30 experts from Asia (China, Japan, Korea, and Singapore) using the Delphi method and the GRADE evidence grading system. A total of 29 statements were formulated, covering the diagnosis and assessment of GCPM, indications for laparoscopic exploration and NIPS (normothermic intraperitoneal and systemic treatment), treatment regimens, prevention and management of complications, criteria for conversion surgery, and postoperative intraperitoneal therapy. The consensus aims to standardize clinical practice and improve the prognosis of patients with GCPM.

Objective To develop a machine learning-based risk prediction model for postoperative acute kidney injury(AKI)and a model for mortality in obese patients admitted to intensive care unit(ICU)in order to improve early warning and prognostic evaluation to support clinical decision-making.Methods Data of obese postoperative ICU patients were retrospectively retrieved from the MIMIC-Ⅳ and eICU databases for statistical analysis.Ultimately,2 520 patients(670 from MIMIC-Ⅳ and 1 850 from eICU databases)were included to build the risk prediction models for AKI and mortality.The data included demographic information,vital signs,laboratory findings,surgical types,comorbidities,and medication use.After data cleaning and preprocessing,Boruta feature selection was applied,followed by the construction of prediction models using 7 machine learning algorithms,that is,Gradient Boosting Machine(GBM),Generalized Linear Model(GLM),k-Nearest Neighbors(KNN),Na?ve Bayes(NB),Neural Network(NNET),Support Vector Machine(SVM),and XGBoost.Model performance was evaluated through cross-validation and external validation.Results In the risk prediction models of AKI,the SVM model achieved the highest AUC value of 0.80 in the testing set and 0.71 in the external validation test.For the risk prediction models of mortality,the GBM model outperformed others in the prediction,attaining an AUC value of 0.91 in the testing set.Conclusion Risk predictive models for postoperative AKI and mortality in obese ICU patients are successfully constructed,and are valuable tools for clinicians to optimize early intervention and improve clinical outcomes for the patients.

Haloacetic acids(HAAs),as a class of disinfection byproducts in drinking water,pose potential threats to human health,so the rapid,accurate and simultaneous detection of HAAs is of great significance for ensuring drinking water safety.Aiming at the challenges in HAAs detection and risk analysis,a novel method for synchronous rapid detection of seven kinds of HAAs in drinking water based on in situ derivatization technology and headspace gas chromatography was developed in this study.Through single-factor optimization experiments,the optimal reaction parameters for in situ derivatization were determined,including the type and dosage of salting-out agent,the acidity of reaction system,the amount of phase transfer catalyst,the dosage of derivatization agent,and the extraction solvent volume.Methodologic validation showed that the seven kinds of HAAs exhibited excellent linear relationships within their respective detection concentration ranges(R2>0.998).The method detection limits(MDLs)ranged from 0.04 to 0.33 μg/L,and the limits of quantification(LOQs)were between 0.14 and 1.34 μg/L.For real water samples,the average spiked recoveries of the seven HAAs ranged from 90.9%to 107.7%,with relative standard deviation(RSDs)between 1.55%and 6.49%,and the HAAs contents in all tested samples were below the limits specified in the Standards for Drinking Water Quality(GB 5749-2022)of China.This method was featured with simple operation,fast analysis speed,high sensitivity,and good accuracy,providing an efficient and reliable technical support for routine monitoring of HAAs contaminants in drinking water and showing promising application value for widespread promotion.

Objective:To investigate the efficacy and toxicity of blinatumomab in the first-line and second-line treatment of pediatric B-cell acute lymphoblastic leukemia (B-ALL).Methods:A multi-center retrospective cohort study was conducted to analyze clinical data from 323 pediatric B-ALL patients treated with blinatumomab across 14 hospitals in China from May 2021 to July 2023. Patients were divided into four groups based on the treatment phase and disease status when blinatumomab was used: relapsed/refractory group, post-consolidation minimal residual disease (MRD)-positive group, early MRD-positive group, and MRD-negative group. Blinatumomab for the relapsed/refractory group was considered as second-line treatment, while the other 3 groups as first-line treatment. The MRD negativity rate after treatment, the survival rates and the incidence of severe adverse events were compared across these groups. Patients who received blinatumomab for more than 7 days were included in the efficacy analysis. Survival analysis was performed using the Kaplan-Meier method, and Log-Rank test was used to compare the survival rates among groups.Results:Among the 323 patients, 191 (59.1%) were male, with the age of 6.2 (3.9, 10.5) years. There were 117 patients in the relapsed/refractory group, 62 cases in the post-consolidation MRD-positive group, 43 cases in the early MRD-positive group, and 101 cases in the MRD negative group. In the relapsed/refractory group, the complete remission rate and MRD negativity rate after one course of blinatumomab were 71.4% (35/49) and 81.5% (75/92) for the 49 children without complete remission and the 92 children with flow cytometry-positive MRD, respectively. In the post-consolidation MRD-positive group, the MRD negativity rates after one course of blinatumomab were 100.0% (27/27), 12/16 and 9/19 for patients with MRD positivity detected by flow cytometry, polymerase chain reaction and next-generation sequencing, respectively. In the early MRD-positive group, the MRD negativity rates were 96.7% (29/30) and 9/9 for flow cytometry and next-generation sequencing, respectively. The 2-year overall survival rate and event-free survival rate for the 319 children evaluable for efficacy were (90.6±1.7)% and (87.6±1.9)%, respectively, with the relapsed/refractory group showing significantly lower overall survival rates and event-free survival rate compared to the other groups ( χ2=21.40, 26.21,both P<0.001). Grade 3 or higher adverse events occurred in 128 cases (39.6%), with hematological toxicity observed in 101 cases, while cytokine release syndrome (CRS), infection, and neurotoxicity occurred in 11, 26 and 8 cases, respectively. In addition, there were statistically significant differences in the grade 3 or higher CRS among the four groups ( χ2=8.03, P<0.05). Conclusion:Blinatumomab can clear MRD more effectively and achieve superior survival outcomes when used as first-line treatment for pediatric B-ALL, with less CRS.

Objective:To investigate the clinical characteristics and independent risk factors of severe disease in patients with anti-nuclear matrix protein (NXP) 2 antibody-positive juvenile dermatomyositis (JDM).Methods:A retrospective cohort study was conducted, including 219 anti-NXP2 antibody-positive JDM patients admitted to 23 children′s hospitals across China from July 2011 to July 2023. Patients were classified into severe and non-severe groups based on classification criteria for severe dermatomyositis. Demographic characteristics, clinical manifestations, and laboratory parameters were compared between the 2 groups using independent sample t-test, Mann-Whitney U test, or χ2 test. Univariate and multivariate Logistic regression analyses were performed to identify risk factors for severe disease. The receiver operating characteristic curve was employed to calculate optimal cut-off values. Results:Among the 219 patients, 108 were male and 111 were female, with an age at onset of 6.3 (3.5, 9.4) years. The severe group comprised 69 patients, and the non-severe group 150 patients. The severe group had significantly higher rates of fever, heliotrope rash, subcutaneous edema, periorbital edema, anti-Ro52 antibody positivity, as well as elevated levels of ferritin-to-albumin ratio (FAR), creatine kinase (CK), aspartate aminotransferase (AST), and lactate dehydrogenase (LDH) (all P<0.05). Multivariate analysis identified anti-Ro52 antibody positivity ( OR=13.26, 95% CI 1.37-128.29) and elevated FAR ( OR=1.90, 95% CI 1.09-2.31) as independent risk factors for severe anti-NXP2 antibody-positive JDM (both P<0.05). Receiver operating characteristic curve analysis revealed that a FAR cutoff value of 6.82 predicted severe disease with an area under the curve of 0.87 (95% CI 0.81-0.94, P<0.001), sensitivity of 0.85, and specificity of 0.70. All patients received glucocorticoid therapy, and the severe group received higher proportions of steroid pulse therapy, cyclophosphamide, mycophenolate mofetil, intravenous immunoglobulin, biologics, and adjuvant treatments compared to the non-severe group (all P<0.05). In terms of outcomes, 2 patients (2.9%) in the severe group died (due to neurological involvement and intestinal perforation, respectively), while the remaining patients achieved complete clinical response or remission. All patients in the non-severe group achieved remission. Conclusions:The primary clinical features of anti-NXP2 antibody-positive JDM included fever, heliotrope rash, subcutaneous edema, periorbital edema, anti-Ro52 antibody positivity, and elevated levels of CK, AST, LDH, and FAR. Furthermore, anti-Ro52 antibody positivity and a FAR>6.82 were identified as independent risk factors.