OBJECTIVE To investigate the current status of informatization tools applied to antimicrobial stewardship in county hospitals in China， and to provide a reference for promoting the informatization development of antimicrobial stewardship in county hospitals.METHODS From August to September 2025， an online questionnaire survey was conducted among 1 007 county hospitals across 31 provinces（autonomous regions， and municipalities） in China. The survey focused on the application of four types of informatization tools：the real-time monitoring system for antimicrobial use， the pre-prescription review system， the irrational use warning system， and the electronic prescription evaluation system（hereinafter referred to as the “monitoring system”“review system”“warning system”“evaluation system”，respectively）. Correlation analysis and binary Logistic regression analysis were employed to explore the influencing factors.RESULTS Of the county hospitals， 80.83% were equipped with at least one type of informatization tool for antimicrobial stewardship， while 19.17% had no relevant tool. Only 18.87% of the hospitals were equipped with all four types of tools. The monitoring system exhibited the highest equipped rate （70.80%）， whereas the warning system was equipped in only 33.96% of the hospitals. Four types of tools are evenly and adequately deployed in the eastern region， the central and western regions have far lower deployment rates of intervention tools including review system and warning system， accompanied by prominent intra-provincial gaps. The total number of the health technicians， hospital grade， and prescription review rate of outpatient antibacterial drug were significantly and positively correlated with the deployment rates of the four informatization tools （ P ＜0.05）. The results of the Logistic regression model fitting indicated that the model of the review system was rated “excellent” [area under the receiver operating characteristic curve （AUC）＝0.81]， and the model of the warning system was rated “further improvement” （AUC＝0.67）. The total number of health technicians was significantly positively correlated with the deployment rates of all four types of informatization tools （all P ＜0.05）.CONCLUSIONS The informatization of antimicrobial stewardship in county hospitals in China remains in the initial stage of transitioning from “passive statistics” to “active prevention and control”， with challenges such as structural imbalance and regional disparities. In the future， differentiated support strategies should be implemented， the allocation of resources should be optimized， to enhance the level of refined antimicrobial stewardship.

AIM:To analyze the association between mobile phone addiction and high myopia among college students.METHODS:We conducted a cross-sectional questionnaire survey in December 2022 on all students of a university in Shaanxi Province, and the questionnaire included socio-demographic characteristics, mobile phone addiction, high myopia, and lifestyle. Binary Logistic regression model was used to analyze the association between mobile phone addiction and high myopia among college students.RESULTS:A total of 19 952 college students were included. The prevalence of high myopia was 7.31%. The rate of mobile phone addiction was 25.68%, and the mobile phone addiction score was 37.59±13.38. The incidence of high myopia among college students with mobile phone addiction was higher than non-mobile phone addiction(P<0.001). After adjusting for socio-demographic characteristics and lifestyle, the risk of high myopia among college students with mobile phone addiction was 1.274 times(95%CI:1.131-1.434)higher than non-mobile phone addiction. For each point increase of total mobile phone addiction score, withdrawal symptoms score, salience score, social comfort score, and mood changes score, the risk of high myopia among college students increased by 0.9%(95%CI:1.005-1.013), 2.0%(95%CI:1.010-1.030), 2.6%(95%CI:1.010-1.043), 4.8%(95%CI:1.030-1.066), and 3.3%(95%CI:1.014-1.052), respectively.CONCLUSION:Mobile phone addiction is significantly associated with the increased risk of high myopia among college students, and early intervention of mobile phone use may reduce the risk of high myopia among college students.

OBJECTIVE To investigate the effects of calcitriol on sepsis-induced immunosuppression and its potential mechanism. METHODS A sepsis-induced immunosuppression mice model was established using cecal ligation and puncture （CLP）. The 7-day survival rate， serum levels of tumor necrosis factor- α （TNF- α）， interleukin-6 （IL-6）， and IL-1β were determined in sham operation group， CLP group and calcitriol group （1 μg/kg）； the morphological changes of lung tissue in mice were observed. Lipopolysaccharide （LPS） tolerance macrophage models （representing sepsis-induced immunosuppression） were established using mice macrophage cell line RAW264.7 cells. The levels of TNF-α and IL-6 in cell supernatants as well as mRNA expressions of IL-1β， nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 （NLRP3）， IL-18 and caspase-1 were assessed in culture medium group， LPS group， LPS tolerance group， and calcitriol （5 μmol/L） group. The following parameters were measured： propidium iodide （PI）-positive cell ratio， caspase-1 activity， lactate dehydrogenase （LDH） release， and Ca2+ levels. RESULTS Compared with CLP group， 7-day survival rate and serum levels of TNF-α， IL-6 and IL-1β were increased significantly in calcitriol group （P＜0.05）. Additionally， pulmonary tissue damage was markedly attenuated in calcitriol group. Compared with LPS tolerance group， the levels of TNF-α and IL-6 in cell supernatants， mRNA expressions of IL- 1β， NLRP3， IL-18 and caspase-1， PI-positive cell ratio， caspase-1 activity， LDH release， and Ca2+ levels were all increased significantly in calcitriol group （P＜0.05）. CONCLUSIONS Calcitriol can reverse sepsis-induced immunosuppression， and the mechanism of action may be E-mail：yarfwy@163.com achieved by the binding of calcitriol to vitamin D receptor，which promotes the release of Ca2+ from the endoplasmic reticulum， thereby driving the NLRP3/caspase-1-mediated pyroptosis pathway.

Objective: To investigate the distribution characteristics of previous infection of human parvovirus B19(HPV B19) among blood donors in Xi 'an, and to provide data support and theoretical basis for formulating individualized and precise blood screening strategies. Methods: A total of 970 qualified blood samples tested at Shaanxi Blood Center from August to September 2024 were randomly selected. The levels of HPV B19 IgG antibodies in the serum were detected by enzyme-linked immunosorbent assay (ELISA). The distribution characteristics of the samples were analyzed from the perspectives of age, gender, education level, occupation, blood type and region. Results: The positive rate of HPV B19 IgG antibodies among blood donors in Xi 'an was 25.26%(245/970), which increased gradually with age (P<0.05). There was no significant difference in the positive rate of HPV B19 IgG antibodies among blood donors of different genders, education levels, occupations, or blood types (P>0.05). Univariate logistic regression analysis showed that past HPV B19 infection was only related to age (P<0.05). The distribution of positive blood samples in 13 districts and counties of Xi 'an was counted based on the blood collection sites. The results showed that there was no significant global spatial autocorrelation in the distribution of positive samples. Among them, the Weiyang District and Beilin District exhibited a "high-high" cluster (P<0.05), while Chang'an District exhibited a "low-high" cluster (P<0.01). Conclusion: A certain proportion of blood donors in Xi'an showed past infection with HPV B19, which was only correlated with age and demonstrated an upward trend. It is recommended to continue expanding the screening scope and incorporate screening for this virus in blood transfusion processes involving susceptible populations.

BACKGROUND: Lung cancer is one of the most common malignant tumors worldwide and a major cause of cancer-related deaths. Early-stage lung cancer is often manifested as pulmonary nodules, and accurate assessment of the malignancy risk is crucial for prolonging survival and avoiding overtreatment. This study aims to construct a model based on image feature parameters automatically extracted by artificial intelligence (AI) to evaluate its effectiveness in predicting the malignancy of part-solid nodule (PSN). METHODS: This retrospective study analyzed 229 PSN from 222 patients who underwent pulmonary nodule resection at Lanzhou University Second Hospital between October 2020 and February 2025. According to pathological results, 45 cases of benign lesions and precursor glandular lesion were categorized into the non-malignant group, and 184 cases of pulmonary malignancies were categorized into the malignant group. All patients underwent preoperative chest computed tomography (CT), and AI software was used to extract imaging feature parameters. Univariate analysis was used to screen significant variables; variance inflation factor (VIF) was calculated to exclude highly collinear variables, and LASSO regression was further applied to identify key features. Multivariate Logistic regression was used to determine independent risk factors. Based on the selected variables, five models were constructed: Logistic regression, random forest, XGBoost, LightGBM, and support vector machine (SVM). Receiver operating characteristic (ROC) curves were used to assess the performance of the models. RESULTS: The independent risk factors for the malignancy of PSN include roughness (ngtdm), dependence variance (gldm), and short run low gray-level emphasis (glrlm). Logistic regression achieved area under the curves ( AUCs) of 0.86 and 0.89 in the training and testing sets, respectively, showing good performance. XGBoost had AUCs of 0.78 and 0.77, respectively, demonstrating relatively balanced performance, but with lower accuracy. SVM showed an AUC of 0.93 in the training set, which decreased to 0.80 in the testing set, indicating overfitting. LightGBM performed excellently in the training set with an AUC of 0.94, but its performance declined in the testing set, with an AUC of 0.88. In contrast, random forest demonstrated stable performance in both the training and testing sets, with AUCs of 0.89 and 0.91, respectively, exhibiting high stability and excellent generalizability. CONCLUSIONS The random forest model constructed based on independent risk factors demonstrated the best performance in predicting the malignancy of PSN and could provide effective auxiliary predictions for clinicians, supporting individualized treatment decisions.
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Humans ; Male ; Female ; Lung Neoplasms/pathology* ; Middle Aged ; Retrospective Studies ; Artificial Intelligence ; Aged ; Tomography, X-Ray Computed ; Adult ; Solitary Pulmonary Nodule/diagnostic imaging* ; ROC Curve

Hepatic stellate cells (HSCs) are the primary fibrogenic cells in the liver, and their activation plays a crucial role in the development and progression of hepatic fibrosis. Here, we report that retinoid X receptor-alpha (RXRα), a unique member of the nuclear receptor superfamily, is a key modulator of HSC activation and liver fibrosis. RXRα exerts its effects by modulating calcium/calmodulin-dependent protein kinase kinase β (CaMKKβ)-mediated activation of AMP-activated protein kinase-alpha (AMPKα). In addition, we demonstrate that K-80003, which binds RXRα by a unique mechanism, effectively suppresses HSC activation, proliferation, and migration, thereby inhibiting liver fibrosis in the CCl₄ and amylin liver NASH (AMLN) diet animal models. The effect is mediated by AMPKα activation, promoting mitophagy in HSCs. Mechanistically, K-80003 activates AMPKα by inducing RXRα to form condensates with CaMKKβ and AMPKα via a two-phase process. The formation of RXRα condensates is driven by its N-terminal intrinsic disorder region and requires phosphorylation by CaMKKβ. Our results reveal a crucial role of RXRα in liver fibrosis regulation through modulating mitochondrial activities in HSCs. Furthermore, they suggest that K-80003 and related RXRα modulators hold promise as therapeutic agents for fibrosis-related diseases.

Osteoarthritis (OA) causes chronic pain that significantly impairs quality of life, with current treatments often proving insufficient and accompanied by adverse effects. Recent research has identified the dorsal root ganglion (DRG) and its resident macrophages as crucial mediators of chronic OA pain through neuroinflammation driven by macrophage polarization. We present a novel injectable thermo-sensitive hydrogel system, KAF@PLEL, designed to deliver an anti-inflammatory peptide (KAF) specifically to the DRG. This biodegradable hydrogel enables sustained KAF release, promoting the reprogramming of DRG macrophages from pro-inflammatory to anti-inflammatory phenotypes. Through comprehensive in vitro and in vivo studies, we evaluated the hydrogel's biocompatibility, effects on macrophage polarization, and therapeutic efficacy in chronic OA pain management. The system demonstrated significant capabilities in preserving macrophage mitochondrial function, suppressing neuroinflammation, alleviating chronic OA pain, reducing cartilage degradation, and improving motor function in OA rat models. The sustained-release properties of KAF@PLEL enabled prolonged therapeutic effects while minimizing systemic exposure and side effects. These findings suggest that KAF@PLEL represents a promising therapeutic approach for improving outcomes in OA patients through targeted, sustained treatment.

Objective To observe the value of machine learning model based on MR T2WI and diffusion weighted imaging(DWI)radiomics for predicting perineural invasion(PNI)of rectal cancer.Methods Totally 343 patients with rectal cancer were retrospectively collected and divided into training set(n=275,92 PNI[+]and 183 PNI[-])and test set(n=68,23 PNI[+]and 45 PNI[-])at the ratio of 8∶2.Univariate and multivariate logistic regression(LR)were used to analyze clinical data and screen the independent predictors of PNI in rectal cancer,so as to construct a clinical model.The best radiomics features were extracted and screened based on preoperative T2WI and DWI.Then extremely randomized trees,multilayer perceptron,light gradient boosting machine,extreme gradient boosting,support vector machine(SVM),LR,K-nearest neighbor and random forest algorithms were used to construct ML models,respectively,and the optimal ML model was selected to establish a clinical-radiomics ML model combined with clinical relevant independent predictors.The predictive efficacy and clinical value of each model were evaluated.Results Patients' age was the independent predictor of PNI of rectal cancer(OR=0.988,P＜0.001),and the area under the curve(AUC)of the clinical model constructed based on it was 0.435 and 0.458 in training and test sets,respectively.SVM model was the best one among 8 ML models,with AUC in training and test set of 0.887 and 0.854,respectively.The AUC of clinical-radiomics ML model in training and test sets was 0.887 and 0.860,respectively,not different with AUC of SVM model(both P＞0.05).Decision curve analysis showed that when the threshold value was 0.20-0.45,clinical net benefit of SVM model was higher than that of other models.Conclusion SVM model based on T2WI and DWI radiomics could effectively predict PNI of rectal cancer.

Objective To compare five time series models and predict the monthly incidence of bacillary dysentery in Qinghai Province in 2024,and provide reference for the prevention and control.Methods The epidemic charac-teristics of bacterial dysentery in Qinghai Province from 2014 to 2023 were analyzed.R4.3.1 software was used for establishing seasonal autoregressive integrated moving average(SARIMA)model,Holt-Winters triple exponential smoothing(Holt Winters)model,exponential smoothing(ETS)model,neural network autoregression(NNAR)model,and trigonometric seasonality,Box-Cox transformation,ARMA errors,trend and seasonal components(TBATS)model.Fitting effect of the models was analyzed and accuracy was compared.Results From 2014 to 2023,a total of 5 833 cases of bacterial dysentery were reported in Qinghai Province,without deaths,male to fe-male ratio being 1.23∶1.The highest incidence was reported in 2016(15.45 per 100 000 people),and the lowest in-cidence was reported in 2023(3.68 per 100 000 people).Incidence increased from 2014 to 2016,then decreased,showing an obvious overall downward trend.Case number in＜5 years age group was the highest,accounting for 29.76％of the total cases(n=1 736).Regarding population distribution,the top three were children in childcare institutions and scattered children(35.56％),farmers(24.65％),and students(12.62％).Except the additive Holt-Winters model,the predicted trends of the other four models were consistent with actuality.The ETS model had the best fitting effect,with a relatively balanced overall performance(training set:MAE=0.13,RMSE=0.21,MAPE=19.55％;testing set:MAE=0.11,RMSE=0.16,MAPE=28.66％).It is recommended to pre-dict the incidence of bacillary dysentery in Qinghai Province based on ETS model.Conclusion From 2014 to 2023,bacterial dysentery in Qinghai Province showed a downward trend,with the peak of the epidemic from June to Au-gust.Preschool and scattered children were high-risk groups.Among the five prediction models,ETS model has the best fitting effect,and can be used to predict the incidence of bacillary dysentery.

Objective:To explore the factors influencing the success rate of culturing patient-derived gastric and colorectal cancer organoids.Methods:From Feb 2022 to Oct 2023, 398 tumor tissue specimens from patients who underwent gastric cancer and colorectal cancer resection at the Department of Gastrointestinal Surgery, the Affiliated Hospital of Qingdao University, were used for organoid culture. The clinicopathological factors affecting the success rate of organoid culture were analyzed.Results:The overall success rate of organoid culture in this group was 75.1% (299/398), with the success rate of gastric cancer organoid culture being 79.8%(154/193) and that of colorectal cancer being 70.7% (145/205). Different clinicopathological T stage ( χ2=4.765, P<0.05),histological type ( χ2=11.248, P<0.05), and tumor regression grade (TRG) grade after neoadjuvant chemotherapy ( χ2=7.797, P<0.05) were related to the success rate of organoid culture . Multivariate analysis showed that the TRG grade was an independent influencing factor( P=0.040). For colorectal cancer, different pathological T stage ( χ2=5.108, P<0.05), histological type ( χ2=11.270, P<0.05), and TRG grade after neoadjuvant chemotherapy ( χ2=6.797, P<0.05) were related to the success rate of organoidculture . Different from gastric cancer, the results of multivariate analysis of colorectal cancer showed that the histological type was an independent influencing factor ( P=0.018). Conclusions:The pathologic T stage, histological type of tumors, and TRG of cancer patients all have a significant impact on the success rate of establishing tumor organoids. Among them, the TRG grade is an independent influencing factor for the culture of gastric cancer organoids, and the histological type is an independent influencing factor for colorectal cancer organoids.