Objective To investigate changes in the distribution of Oncomelania hupensis snails in Yixing City, Jiangsu Province, from 2008 to 2024, and to provide insights to guide formulation of O. hupensis snail investigation and surveillance programs. Methods Data from O. hupensis snail surveys in Yixing City from 2008 to 2024 were collected. Trends in snail habitat site numbers, snail-infested areas, proportion of total area with snail habitats, occurrence of frames with living snails, and density of living snails in snail habitats in hilly regions of Yixing City were evaluated from 2008 to 2024 by applying a Joinpoint regression model to collect annual percent change (APC) and average annual percent change (AAPC) data. Results From 2008 to 2024, a total of 193.815 hm2 of snail-infested area was found within Yixing City, of which 191.765 hm2 (accounting for 98.94%) was distributed in hilly regions. A total of 344 snail infestation sites in hilly regions were identified. The average occurrence rate of living snail frames in snail habitats was 8.650% and the average living snail density in snail habitats was 0.246 per 0.1 m2. No Oncomelania snails were positively identified. The number of snail habitat sites in hilly regions of Yixing City showed no significant decreasing trend (AAPC=-2.8%, P=0.527). Similarly, no significant increasing trend in snail-infested area (APC=AAPC=5.7%, P=0.328) was found. The occurrence rate of living snail frames in snail habitats showed no significant increasing trend (APC=AAPC=5.1%, P=0.583). Living snail density in snail habitats also showed no significant increasing trend (APC=AAPC=3.2%, P=0.598). Conclusions From 2008 to 2024, snail infestation has persisted in the hilly areas of Yixing City with an unclear variation trend. The quality of snail investigation and snail surveillance system should be strengthened to permit timely identification of hidden dangers and rapid risk responses, thereby preventing schistosomiasis outbreaks.

Objective: To establish a prediction model for high-risk cardiovascular disease (CVD) among residents aged 35 to 75 years, so as to provide the basis for improving CVD prevention and control measures. Methods: Permanent residents aged 35 to 75 years were selected from Dongcheng District, Beijing Municipality using the stratified random sampling method from 2018 to 2023. Demographic information, lifestyle, waist circumference and blood biochemical indicators were collected through questionnaire surveys, physical examinations and laboratory tests. Influencing factors for high-risk CVD among residents aged 35 to 75 years were identified using a multivariable logistic regression model, and a prediction model for high-risk CVD was established. The predictive effect was evaluated using the receiver operating characteristic (ROC) curve. Results: A total of 6 968 individuals were surveyed, including 2 821 males (40.49%) and 4 147 females (59.51%), and had a mean age of (59.92±9.33) years. There were 1 155 high-risk CVD population, with a detection rate of 16.58%. Multivariable logistic regression analysis showed that gender, age, smoking, central obesity, systolic blood pressure, fasting blood glucose, triglyceride and low-density lipoprotein cholesterol were influencing factors for high-risk CVD among residents aged 35 to 75 years (all P<0.05). The area under the ROC curve of the established prediction model was 0.849 (95%CI: 0.834-0.863), with a sensitivity of 0.693 and a specificity of 0.863, indicating good discrimination. Conclusion The model constructed by eight factors including demographic characteristics, lifestyle and blood biochemical indicators has good predictive value for high-risk CVD among residents aged 35 to 75 years.

Objective To investigate the protective effect and its mechanism of low-dose interleukin-2(IL-2)against hepatocyte injury in Concanavalin A(Con A)-induced autoimmune hepatitis(AIH)mice.Methods Eighteen SPF female C57BL/6 mice were randomly divided into normal group,model group and treatment group,each group with 6 mice.Mice in the treatment group were subcutaneously injected with 300 μl 10,000 U IL-2 for 12 d,once a day.2 h after the last dose,Con A(15 mg/kg)was injected through the tail vein in the model group and treatment group.After 8 h of modeling,the histopathological changes in the mouse liver were observed using HE staining,and the serum levels of aspartate aminotransferase(AST),alanine aminotransferase(ALT),tumor necrosis factor-α(TNF-α),and interferon-γ(IFN-γ)were detected using ELISA method;the expression of apoptotic protein caspase 8/9/3 was detected by Western blotting;and the percentages of Treg and Th1 cells were observed by flow cytometry.Results Compared with normal group,the liver index,spleen index,the percentage of necrotic area of liver tissue,the serum levels of ALT,AST,TNF-α and IFN-γ,and the expression of apoptosis protein caspase 8/9/3 significantly increased in the model group(P<0.05 or P<0.01);Compared with model group,the liver index,spleen index,the percentage of necrotic area of liver tissue,the serum levels of ALT,TNF-α and IFN-γ,and the expression of apoptosis protein caspase 8/9/3 significantly decreased in the treatment group(P<0.05 or P<0.01).The flow cytometry results showed that compared with normal group,the percentages of Treg and Th1 cells and Th1/Treg ratio increased in the model group(P<0.05 or P<0.01);Compared with the model group,the percentage of Treg cells further increased(P<0.01),Th1/Treg ratio decreased significantly in the treatment group(P<0.05),but there was no significant difference in the percentage of Th1 cells between two groups(P>0.05).Conclusion Low-dose of IL-2 can effectively improve liver injury in AIH mice,and the mechanism of action may be related to inducible Treg cell activation.

A strategy combining a tailored database and high-throughput activity screening that discover bioactive metabolites derived from Magnoliae Officinalis Cortex(MOC)was developed and implemented to rapidly profile and discover bioactive metabolites in vivo derived from traditional Chinese medicine(TCM).The strategy possessed four characteristics:1)The tailored database consisted of metabolites derived from big data-originated reference compound,metabolites predicted in silico,and MOC chemical profile-based pseudomolecular ions.2)When profiling MOC-derived metabolites in vivo,attentions were paid not only to prototypes of MOC compounds and metabolites directly derived from MOC compounds,as reported by most papers,but also to isomerized metabolites and the degradation products of MOC compounds as well as their derived metabolites.3)Metabolite traceability was performed,especially to distinguish isomeric prototypes-derived metabolites,prototypes of MOC compounds as well as phase Ⅰ metabolites derived from other MOC compounds.4)Molecular docking was utilized for high-throughput activity screening and molecular dynamic simulation as well as zebrafish model were used for verification.Using this strategy,134 metabolites were swiftly characterized after the oral administration of MOC to rats,and several metabolites were reported for the first time.Furthermore,17 potential active metabolites were discovered by targeting the motilin,dopamine D2,and the serotonin type 4(5-HT4)receptors,and part bioactivities were verified using molecular dynamic simulation and a zebrafish constipation model.This study extends the application of mass spectrometry(MS)to rapidly profile TCM-derived metabolites in vivo,which will help pharmacologists rapidly discover potent metabolites from a complex matrix.

Objective:To investigate the value of biparametric-MRI (bpMRI) based peritumoral radiomics for preoperative prediction of extraprostatic extension (EPE) in prostate cancer (PCa).Methods:In this cross-sectional study, consecutive bpMRI of patients undergoing prostatectomy for PCa were retrospectively collected from the First Medical Center (center 1) and the Third Medical Center (center 2) of Chinese PLA General Hospital. A total of 274 patients were finally enrolled. Patients at center 1 from January 2020 to December 2022 were randomly divided into a training set (149 cases) and an internal validation set (63 cases) by stratified random sampling. Patients at center 2 from January 2023 to March 2024 were assigned to the external test set (62 cases). Patients were categorized into EPE-positive group and EPE-negative group according to pathological assessment postoperatively. In the training set, there were 49 cases in EPE-positive group and 100 cases in EPE-negative group. In the internal validation set, there were 26 cases in EPE-positive group and 37 cases in EPE-negative group. In the external test set, there were 22 cases in EPE-positive group and 40 cases in EPE-negative group. Axial T 2WI and apparent diffusion coefficient (ADC) images were manually annotated to obtain index lesion regions of interest (ROIs), with the peritumoral ROIs subsequently delineated by semi-automatic segmentation technique. Radiomics features were extracted from intra-tumoral, peri-tumoral, and intra-tumoral plus peri-tumoral ROIs. The training set data was employed to select and optimize features to build the radiomics models. The logistic regression analysis was used to develop radiomics, clinical, and integrated models. The predictive performance was assessed by the area under the receiver operating characteristic curve (AUC) in the external test set, and compared by the DeLong test. The sensitivity and specificity were compared by the exact McNemar test. Results:In the external test set, the peri-tumoral radiomics model based on bpMRI showed the highest performance in evaluating EPE, with an AUC of 0.739 (95% CI 0.611-0.842), which was identified as the optimal radiomics model. EPE grade ( OR=6.151, 95% CI 3.371-11.226, P<0.001) was incorporated into the clinical model, with an AUC of 0.780 (95% CI 0.657-0.875) in the external test set. The integrated model had an AUC of 0.817 (95% CI 0.698-0.904) in the external test set. There was no statistically significant difference in comparisons of AUCs among the three models (all P>0.05). The sensitivity of the integrated model (68.2%) showed no significant difference from those of the clinical model and the optimal radiomics model (77.3% and 86.4%, respectively; P=0.500 and P=0.289). However, the specificity of the integrated model (85.0%) was significantly higher than those of the clinical model (67.5%, P=0.016) and the optimal radiomics model (50.0%, P<0.001). Conclusion:A bpMRI-based peritumoral radiomics integrating clinical model demonstrates high performance for preoperative prediction of EPE in PCa.

Objective:To localize the Oncofertility Barrier Scale and examine its reliability and validity, thereby providing an effective tool for assessing and measuring barriers encountered by healthcare professionals in oncofertility care.Methods:After obtaining authorization from the original scale author, the scale was translated following Brislin's translation model and underwent cultural adaptation and a pre-survey to develop and adjust the localized Chinese version of the Oncofertility Barrier Scale. A questionnaire survey was conducted using the Chinese version of the Oncofertility Barrier Scale among 210 healthcare professionals selected via convenience sampling from Yichang Central People's Hospital, Tongji Hospital affiliated to Tongji Medical College of Huazhong University of Science & Technology, and Taihe Hospital. The reliability and validity of the scale were analyzed.Results:The Chinese version of the Oncofertility Barrier Scale demonstrated an average scale-level content validity index of 0.97. Exploratory factor analysis extracted six common factors, with a cumulative variance contribution rate of 69.415%. The final scale consisted of 26 items across five dimensions. The Cronbach α coefficient was 0.940, and the split-half reliability coefficient was 0.867. Conclusions:The Chinese version of the Oncofertility Barrier Scale exhibits good reliability and validity and can serve as an effective tool for evaluating factors hindering healthcare professionals in providing oncofertility care.

Objective To explore the distribution patterns of traditional Chinese medicine(TCM)syndromes in patients with metabolic syndrome caused by antipsychotic drugs.Methods A standardized TCM syndrome survey was performed to collect diagnostic information from 160 patients diagnosed with metabolic syndrome due to antipsychotic drug use.Subsequent frequency analysis,cluster analysis,and Bayesian network analysis were carried out.The syndrome pattern distribution was ultimately determined through relevant literatures and expert opinions.Results Five TCM syndromes were identified through frequency,cluster,and Bayesian network analyses.The most common syndrome was qi deficiency with phlegm-dampness(30％),followed by spleen deficiency with phlegm-Heat(23.75％),qi and yin deficiency Pattern(21.88％),yin deficiency with damp-heat(17.50％),and stomach fire hyperactivity pattern(6.88％).Conclusion The pathogenesis of antipsychotics-induced metabolic syndrome involves a complex interplay of deficiency and excess factors.The primary disease is mainly located at the spleen and stomach,with involvement of the liver,kidney,and heart.Pathogenic factors include qi deficiency,yin deficiency,dampness,heat,pathogenic fire,and phlegm.

Time rhythm and the immune system play crucial roles in the pathogenesis of allergic rhinitis.Traditional Chinese medicine(TCM)believes that the circulation of qi and blood in lung meridian follows the principle of"yang during the day,yin at night",which has a defensive function to protect the body from external pathogens.Qi stagnation in lung meridian and impaired qi and blood circulation can lead to the invasion of external pathogens,exacerbating allergic reactions,especially during the active period of the lung meridian,when the immune system is most sensitive to allergens.Based on this,this paper proposes the concept of"bidirectional regulation among meridian,time rhythm,and immune system",and in combination with TCM theory of midnight-noon and ebb-flow doctrine,analyzes the fluctuations of allergic rhinitis symptoms and the temporal changes of meridian qi and blood,and reveals the rhythmic relationship between meridian activity and immune response.This paper combines existing clinical and experimental studies to support this hypothesis,integrating the time dimension into traditional TCM syndrome differentiation and treatment,offering a more individualized treatment approach.This concept not only provides novel scientific evidence for TCM treatment of allergic rhinitis,but also offers theoretical support for optimizing treatment timing and intervention strategies.

OBJECTIVE: Blood culture remains the gold standard for diagnosing bloodstream infections. Clinical laboratories must ensure the quality of blood culture processes from receipt to obtaining definitive results. We examined laboratory analytical indicators associated with positive blood culture results. METHODS: Blood cultures collected from Peking Union Medical College Hospital between January 1, 2020, and December 31, 2022, were retrospectively analyzed. The mode of transportation (piping logistics delivery vs. staff), source of blood cultures (outpatient/emergency department vs. inpatient department), rotation of personnel, and time of reception (8:00-19:59 vs. 20:00-07:59) were compared between blood culture-positive and -negative results. RESULTS: Between 2020 and 2022, the total positive rate of blood culture was 8.07%. The positive rate of blood cultures in the outpatient/emergency department was significantly higher than that in the inpatient department (12.46% vs. 5.83%; P < 0.0001). The time-to-detection of blood cultures was significantly affected by the delivery mode and personnel rotation. The blood culture positive rate of the total pre-analytical time within 1 h was significantly higher than that within 1-2 h or > 2 h ( P < 0.0170). CONCLUSION Laboratory analytical indicators such as patient source, transportation mode, and personnel rotation significantly impacted the positive detection rate or time of blood culture.
Blood Culture/statistics & numerical data* ; Humans ; Retrospective Studies ; Emergency Service, Hospital/statistics & numerical data*