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.

Acute lung injury （ALI） is one of the most common and critical diseases in clinical practice， with extremely high morbidity and mortality， seriously threatening human life and health. The pathogenesis of ALI is complex， in which the inflammatory response is a key factor. Studies have shown that NOD-like receptor protein 3 （NLRP3） inflammasomes are involved in ALI through mechanisms such as inflammation induction， increased microvascular permeability， recruitment of neutrophils， oxidative stress， and pyroptosis， playing a key role in the occurrence and progression of ALI. Therefore， regulating NLRP3 inflammasomes and inhibiting the release of inflammatory factors can alleviate the damage in ALI. At present， ALI is mainly treated by mechanical ventilation and oxygen therapy， which have problems such as high costs and poor prognosis. In recent years， studies have shown that traditional Chinese medicine （TCM） can reduce the inflammatory response and the occurrence of oxidative stress and pyroptosis by regulating the NLRP3 inflammasome， thus alleviating the damage and decreasing the mortality of ALI. Based on the relevant literature in recent years， this article reviews the research progress in TCM treatment of ALI by regulating NLRP3 inflammasomes， discusses how NLRP3 inflammasomes participate in ALI， and summarizes the active ingredients， extracts， and compound prescriptions of TCM that regulate NLRP3 inflammasomes， aiming to provide new ideas for the clinical treatment of ALI and the development of relevant drugs.

A growing body of research points out that gut microbiota plays a key role in tumor immunotherapy. By optimizing the composition of intestinal microbiota, it is possible to effectively improve immunotherapy resistance and enhance its therapeutic effect. This article comprehensively analyzes the mechanism of intestinal microbiota influencing tumor immunotherapy resistance, expounds the current strategies for targeted regulation of intestinal microbiota, such as traditional Chinese medicine and plant components, fecal microbiota transplantation, probiotics, prebiotics and dietary therapy, and explores the potential mechanisms of these strategies to improve patients' resistance to tumor immunotherapy. At the same time, the article also briefly discusses the prospects and challenges of targeting intestinal microbiota to improve tumor immunotherapy resistance, which provides a reference for related research to help the strategy research of reversing tumor immunotherapy resistance.

Objective: To analyze respiratory syncytial virus(RSV) outbreaks surveillance results and the epidemiological characteristics in kindergarten and school in Shenzhen during 2017-2023 , so as to provide a scientific reference for control and prevention of RSV. Methods: Epidemiological data and surveillance results of RSV outbreaks in kindergarten and school from 2017 to 2023 were collected for descriptive analyses. Results: A total of 31 RSV outbreaks were identified in kindergarten and school in 2017-2023 in Shenzhen, 346 cases were reported, the average incidence rate was 22.02%. The most annual RSV outbreaks were reported in 2020 with 14 outbreaks, followed by 8 outbreaks in 2023. A total of 64.52% of RSV outbreaks were identified in kindergarten with rest occurring in primary school or middle school. The greatest monthly count of outbreak was 18 (58.06%) in September, followed by 3 outbreaks (9.68%) in March and October. A total of 244 swab samples were collected, 169 samples were positive for respiratory viruses, the positive rate was 69.26%, 121 samples were positive for RSV,from 31 respiratory syncytical virus outbreaks 57 and samples were positive for other respiratory viruses(9 samples were positive for two respiratory viruses). A toral of 14(45.16%) outbreaks are caused by RSV alone, 17 outbreaks (54.84%) were caused by RSV and other respiratory viruses. Conclusions Most RSV outbreaks in kindergarten and school are reported after 2020 in Shenzhen, most RSV outbreaks occur in kindergarten, peak seasons of RSV outbreaks are autumn and spring.

Abnormal expression of CMTM4 protein is closely related to tumour occurrence,development and prognosis.Although the important role of CMTM4 in tumours has been gradually manifested,its spe-cific mechanism of action in cervical cancer remains unclear.The aim of this study was to investigate the relationship between CMTM4 expression and clinicopathological features in cervical cancer and study its mechanism.Immunohistochemistry and Western blot were used to detect the expression level of CMTM4 in cancer tissues and paracancerous tissues,and it was found that CMTM4 was significantly under-ex-pressed in cervical cancer tissues(P＜0.001).The chi-square test analysed the relationship between high and low CMTM4 expression and the clinical and pathological characteristics of cervical cancer pa-tients and results found that CMTM4 expression was correlated with the number of births,HPV infection status,pathological type,FIGO stage and lymph node metastasis.Data from Western blot and RT-qPCR found that CMTM4 protein and mRNA levels in HaCaT cells were significantly higher than that of C-33A cells,HeLa cells,U14 cells,and HT-3 cells.Among them,the most significant change in CMTM4 ex-pression was observed in C-33A cells,so the C-33A cell line was selected for subsequent overexpression experiments.CCK-8 analysis found that the proliferation ability of C-33A cervical cancer cells in the pcDNA-CMTM4 group was significantly lower than that in the pcDNA-NC group(P＜0.001).Flow cy-tometry and Western blot results indicated that CMTM4 overexpression promoted apoptosis(P＜0.001),significantly increased Bax(P＜0.001)and cleaved caspase 3(P＜0.05)protein levels,and significant-ly decreased Bcl-2 protein level(P＜0.01).Western blot results further found that CMTM4 overexpres-sion significantly reduced the protein levels of p-PI3K(P＜0.001)and p-AKT(P＜0.01),but did not affect the protein levels of PI3K and AKT(P＞0.05).The above findings indicated that CMTM4 gene expression was down-regulated in cervical cancer,and CMTM4 overexpression inhibited cervical cancer cell proliferation and induced apoptosis by inhibiting the PI3K/AKT pathway.Therefore,CMTM4 may be used as a biological marker for screening cervical cancer.

Objective To understand the current situation of healthcare-associated infection(HAI)in China,pro-vide data support and decision-making basis for formulating scientific and effective strategies for HAI prevention and control.Methods A nationwide cross-sectional survey on HAI was conducted among various types and levels of medical institutions in China according to a unified protocol of bedside surveys and case investigations.Results In 2024,a total of 5 736 medical institutions and 2 751 765 patients were surveyed.Among them,34 889 HAI cases were identified,with a prevalence rate of 1.27％.The number of HAI episodes was 38 032,and case prevalence rate was 1.38％.The prevalence rate of HAI in medical institutions in different regions of China ranged from 0.66％to 2.35％.Among medical institutions of different scales,those with a bed capacity of ≥900 had the high-est incidence of HAI,reaching 1.65％.The most common infection site was the lower respiratory tract(44.66％),followed by the urinary tract(12.94％),surgical site(9.32％),upper respiratory tract(7.02％),and bloodstream infection(5.78％).The top 3 departments with the highest HAI rates were the general intensive care unit(10.02％),department of neurosurgery(5.51％),and department(group)of hematology(5.34％).A total of 23 238 strains of HAI pathogens were detected,with 10 714 strains(46.10％)from lower respiratory tract speci-mens.The top 5 detected strains were Klebsiella pneumoniae(14.76％),Pseudomonas aeruginosa(13.33％),Escherichia coli(12.79％),Acinetobacter baumannii(9.23％),and Staphylococcus aureus(7.88％).231 944 pa-tients underwent class Ⅰ incision surgery were monitored,with 1 647 cases experienced surgical site infection,and the prevalence rate of surgical site infection was 0.71％.The number of patients who should undergo pathogen de-tection(patients receiving therapeutic and therapeutic combined prophylactic antimicrobial agents)was 715 179,while the actual number was 480 492,with a pathogen detection rate of 67.18％.425 225 patients received patho-genic detection before treatment,with a detection rate of 59.46％.Conclusion The overall HAI prevalence in Chi-na is lower,showing disparities among medical institutions of different regions and scales.Therefore,precise imple-mentation of measures is necessary for HAI prevention and control,with a focus on high-risk institutions and high-risk departments,key areas,and critical procedures.All levels of medical institutions should continuously reduce the incidence of HAI by strengthening monitoring,standardizing the use of antimicrobial agents,and reinforcing basic HAI prevention and control measures.

Objective:To establish an arsenic free fully automatic online digestion iodine analyzer detection method for urinary iodine (hereinafter referred to as the method).Methods:Based on the principle of iodine catalyzed antimony cerium redox reaction, a fully automatic online digestion iodine analyzer was used to determine the iodine content in urine. The effectiveness of the method in terms of detection limit, precision, accuracy (determination of urinary iodine primary standard reference materials GBW09108z and GBW09110f and spiked recovery experiment), and interference experiments was validated. The method was compared with the arsenic cerium catalytic spectrophotometry method recommended by the National Reference Laboratory for Iodine Deficiency Disorders.Results:The linear range of the method was 0 - 300 μg/L, with a correlation coefficient │ r│> 0.999 5. The qualitative and quantitative detection limits were 7.41 and 18.01 μg/L, respectively. The relative standard deviation ( RSD) of urine samples with different iodine concentrations ranged from 1.0% to 1.7%. The results of the determination of iodine concentrations in urine using standard substances GBW09108z and GBW09110f were within the given standard range, with RSD < 2.5%. The range of spiked recovery rates for urine samples with different iodine concentrations was 101.3% to 104.8%, with an overall average spiked recovery rate of 103.0%. The average concentration of the baseline iodine standard solution was determined to be 116.21 μg/L, and the relative error of the concentration determination with the addition of interfering substances was less than 5.0%. The comparison results showed that there was no statistically significant difference in the measurement results between the two methods ( t = - 0.06, P = 0.952). Conclusions:The method adopts automated detection, which is simple to operate, labor-saving, and does not require the use of arsenic trioxide. It has high precision and accuracy, and is suitable for detection of large quantities of samples.

Objective To investigate the changes of brain structure and functional connectivity by multimodal magnetic resonance imaging(MRI)in patients with type 2 diabetes mellitus(T2DM)and mild cognitive impairment(MCI).Methods A total of 120 patients with T2DM who were treated in the our hospital were enrolled in this study from April 2023 to April 2024.All the patients were divided into simple T2DM group(n=62)and MCI group(n=58)according to whether they were complicated with MCI.The general data and cognitive function related indicators were compared between the two groups,and the volume of MRI subcortical structures were analyzed.The fractional amplitude of low-frequency fluctuation(fALFF)values were compared between the two groups,and the brain regions with different fALFF values were used as seed points for voxel-based functional connectivity analysis.Pearson correlation analysis was used to analyze the correlation between MRI subcortical structure volume and abnormal functional connectivity brain regions and cognitive function in T2DM patients with MCI.Results Connection test A(TMT-A),TMT-B scores and bilateral temporal angle width of ventricles were higher,while Dorsal number span test(FDST),dorsal number span test(BDST),Wechsler adult intelligence scale(WAIS-RC)arithmetic,WAIS-RC knowledge,Montreal cognitive assessment scale(MoCA)score,bilateral caudate nucleus,putamen,hippocampal volume and subcutaneous gray matter volume were lower in MCI group than in T2DM group(P<0.05).The fALFF values increased in the left pericallosal cortex,right lingual gyrus,corpus callosum and right medial and parascingulate gyrus,while fALFF values decreased in the right inferior temporal gyrus,fusiform gyrus,left suboccipital gyrus,left parietal gyrus,left anterior cuneiform lobe,left parietal lobule and left supplementary motor area.Whole brain voxel functional connectivity analysis showed that the functional connectivity of right inferior temporal gyrus and left inferior parietal gyrus was stronger,while the functional connectivity of right lingual gyrus was weaker in MCI group than in T2DM group.Pearson correlation analysis showed that FDST,BDST,WAIS-RC arithmetic,WAIS-RC knowledge,and MoCA score were positively correlated with bilateral caudate nucleus,putamen nucleus,hippocampus volume,subcortical gray matter volume,and right inferior temporal gyrus and left inferior parietal gyrus functions(P<0.05),and negatively correlated with temporal angle width of bilateral ventricles and right superior frontal gyrus function(P<0.05).TMT-a and TMT-B scores were positively correlated with bilateral temporal angle width and right superior frontal gyrus function(P<0.05),and negatively correlated with bilateral caudate nucleus,putamen nucleus,hippocampus volume,subcortical gray matter volume,right inferior temporal gyrus and left inferior parietal gyrus function(P<0.05).Conclusions The volume of subcortical structures is changed in patients with T2DM and MCI,and there are multiple brain regions with abnormal functional connectivity.These alterations demonstrate varying degrees of correlation with MCI,providing partial insight into its neuropathological basis.

Objective To explore the effect of endoscopic ultrasonography(EUS)with different probes on the measurement of gastrointestinal submucosal tumor(SMT)diameter.Methods The clinical data of 356 patients(with a total of 372 lesions)initially diagnosed as SMT by EUS at the Second Affiliated Hospital of Army Medical University from January 2023 to June 2024 were analyzed retrospectively.The basic characteristics of the origin layers and pathological distribution of SMT were analyzed.The differences between the EUS-measured diameters and the actual diameters of SMT at different diameter ranges of lesions were compared.Taking the postoperative pathological diagnosis results as the gold standard,the effects of different clinicopathological features and probe types on the relative error in EUS-measured diameters of SMT were analyzed.Results Among the 372 gastrointestinal SMT lesions,lesions were more frequent in female patients,gastric lesions was the most common,and leiomyoma was the predominant pathological type.The accuracy of EUS in diagnosing SMT was 94.4%.A statistically significant difference was observed between the EUS-measured diameters and the actual diameters of SMT(P<0.05).There were significantly differences in various ranges of lesions between the EUS-measured diameters and the actual diameters(P<0.05).The gender,age,lesion location,and pathological type had no significant effect on the relative error of EUS-measured diameters(P>0.05);while probe types had a significant effect on the relative error of EUS-measured diameters(P<0.05).For lesions with an actual diameter of 2.0 to 3.9 cm,the relative error of SMT diameters measured by small-probe EUS was significantly greater than that by large-probe EUS(P<0.05).Conclusion Large-probe EUS exhibits a smaller relative error in measuring the diameter of SMT with a diameter of≥2.0 cm.Therefore,large-probe EUS is recommended for the examination of SMT with an estimated diameter exceeding 2.0 cm.

Objective:To develop and validate machine learning models for predicting the cumulative live birth rate (CLBR) following in vitro fertilization (IVF) and to analyze key predictive features using SHAP values. Methods:This retrospective study included data from patients who underwent IVF-embryo transfer at the Department of Reproductive Medicine, Baoding Maternal and Child Health Hospital, between January 2017 and December 2022. Patients were categorized into two groups based on live birth outcome: the live birth group ( n=1 036) and the non-live birth group ( n=756). The dataset was randomly divided into a training set and a validation set in a ratio of 7∶3. Five algorithms were utilized for model development: logistic regression, random forest, extreme gradient boosting (XGBoost), support vector machine, and neural networks. Model performance was assessed using the area under the receiver operating characteristic (AUC) curve, F1 score, and calibration curves. Clinical decision curve analysis (DCA) was employed to evaluate the clinical utility of the models. SHAP values were used to interpret feature importance in the XGBoost model and enhance its explainability. Results:The XGBoost model demonstrated the best performance in predicting CLBR,with accuracy of 72.44%, AUC of 0.775, and F1 score of 0.654, accuracy and F1 score outperforming logistic regression (accuracy was 70.02%, F1 score was 0.585), random forest (accuracy was 71.69%, F1 score was 0.606), support vector machine (accuracy was 70.20%, F1 score was 0.607), and neural network (accuracy was 68.72%, F1 score was 0.560). The calibration curve of XGBoost closely aligned with the diagonal line, indicating that the predicted probabilities were very close to the actual outcomes, demonstrating good calibration. DCA indicated that the XGBoost model provided higher net benefits across a wide range of clinical decision thresholds. SHAP value analysis identified number of previous IVF failures, antral follicle count, anti-Müllerian hormone level, percentage of normal sperm morphology, and sperm DNA fragmentation index as key predictors of CLBR.Conclusion:The XGBoost model exhibits excellent predictive performance and calibration for CLBR, with SHAP values providing important insights into feature importance. This model has the potential to support the development of personalized treatment strategies in clinical practice. However, its generalizability needs to be validated using external datasets to ensure its applicability to diverse populations.