Objective To evaluate the effectiveness of schistosomiasis surveillance in Jiangsu Province during the stage moving from transmission control to transmission interruption, and to analyze the current risk and challenges, so as to provide the evidence for achieving the target of schistosomiasis elimination. Methods Schistosomiasis surveillance data were collected from Jiangsu Province from 2012 to 2024, and the endemic areas, Schistosoma japonicum infections in humans and livestock, Oncomelania hupensis snail distribution and implementation of integrated interventions were descriptively analyzed. In addition, the trends in areas with snails, seroprevalence of human S. japonicum infections and numbers of advanced schistosomiasis cases were assessed using a Joinpoint regression model. Results The endemic areas of schistosomiasis continued to shrink in Jiangsu Province from 2012 to 2024, with the number of schistosomiasis-eliminated counties (cities, districts) increasing from 53 (75.71%) to 63 (96.92%), and interruption of schistosomiasis transmission was achieved across the province. A total of 4 600 300 person-times were tested for serum antibodies against S. japonicum, with 28 719 person-times positive detected; and 616 500 person-times were tested S. japonicum infections among local residents in Jiangsu Province from 2012 to 2024, with only 3 egg-positives detected, and no egg-positives found since 2017. A total of 187 600 herd-times were tested for schistosomiasis in livestock, and no S. japonicum infections were found. O. hupensis snail survey was performed covering 1 018 408.97 hm², and a total of 35 556.35 hm² was found with snail-infested habitats, including 174.40 hm2 of emerging snail-infested habitats. A total of 1 102 800 O. hupensis snails were identified for S. japonicum infections, and no infections were found. The areas of snail-infested habitats appeared a tendency towards a rise in Jiangsu Province from 2019 to 2023 (APC = 23.67%, P < 0.05), and the actual areas of snail-infested habitats appeared a tendency towards a decline from 2012 to 2015 (APC = −22.77%, P < 0.05), and towards a rise from 2015 to 2023 (APC = 9.76%, P < 0.01). The seroprevalence of anti-S. japonicum antibodies appeared a tendency towards a decline among residents in Jiangsu Province from 2017 to 2023 (APC = −14.92%, P < 0.01). In addition, the number of newly diagnosed advanced schistosomiasis cases appeared a tendency towards a decline from 2012 to 2024 (APC = −12.02%, P < 0.01), and the numbers of advanced schistosomiasis patients requiring treatment showed a tendency towards a decline from 2012 to 2021 (APC = −10.56%, P < 0.01) and from 2021 to 2023 (APC = −20.06%, P < 0.01). Conclusions Great progresses had been achieved in schistosomiasis control in Jiangsu Province following transmission control, and transmission interruption had been achieved; however, there are still snail-infested habitats. High-intensity surveillance and integrated control are required to be maintained to advance the achievement of the target of schistosomiasis elimination in Jiangsu Province.

BackgroundThe violent aggressive behaviors of patients with schizophrenia usually have the characteristics of suddenness， unpredictability， high severity， and great difficulty in prevention. Early identification and accurate assessment of their risk of violent aggression have significant clinical significance. ObjectiveTo construct a predictive model for the violence risk in hospitalized patients with schizophrenia， to identify the key factors influencing the occurrence of violent behavior in these patients， so as to provide references for clinical precise quantitative assessment and early intervention. MethodsA total of 200 patients with schizophrenia who were hospitalized at Taiyuan Psychiatric Hospital from March 2022 to September 2024 and met the diagnostic criteria of the International Classification of Diseases， eleventh edition （ICD-11） were collected to form the modeling cohort. They were randomly divided into a training set （n=140） and a test set （n=60） at a ratio of 7∶3. Based on the least absolute shrinkage and selection operator （LASSO） regression algorithm， the feature variables were screened and dimension-reduced. The support vector machine （SVM） from machine learning was selected for model training and prediction. The discrimination efficacy of the model was evaluated by the area under the receiver operating characteristic （ROC） curve （AUC）， accuracy， precision， sensitivity， specificity， F1 value， and Brier value. ResultsLASSO regression screening identified 16 feature variables. Pearson correlation analysis revealed a positive correlation between prior violent behavior frequency and clinical psychiatric symptom scores （r=0.580， P<0.01）， a positive correlation between hospitalization compliance and current disease status （r=0.550， P=0.003）， and a positive correlation between educational level and family per capita monthly income （r=0.367， P<0.01）. The SVM model achieved an AUC of 0.853， accuracy of 0.800， precision of 0.810， sensitivity of 0.895， specificity of 0.636， F1 value of 0.850， and Brier value of 0.168. ConclusionThe SVM model has a relatively high level of applicability and overall predictive performance in the assessment of violent risk in schizophrenia patients， which is helpful for the early identification of violent risks in such patients. ［Funded by Specialized Research Project for Enhancing the Competence of Health Professionals in Taiyuan City （number， Y2023006）］

Objective To develop a predictive model for postoperative pulmonary complications (PPC) following video-assisted thoracic surgery (VATS) in lung cancer patients by integrating cardiopulmonary exercise testing (CPET) parameters and machine learning techniques. Methods A retrospective analysis was conducted on patients with early-stage non-small cell lung cancer who underwent CPET and VATS at Guangdong Provincial People’s Hospital between October 2021 and July 2023. Patients were divided into a PPC group and a non-PPC group. The least absolute shrinkage and selection operator (LASSO) regression was used to select important features associated with PPC. Six machine learning algorithms were utilized to construct prediction models, including logistic regression, support vector machine, k-nearest neighbors, random forest, gradient boosting machine, and extreme gradient boosting. The optimal model was interpreted using SHapley Additive exPlanations (SHAP). Results A total of 325 patients were included, with an average age of 60.36 years, and 55.1% were male. Significant differences were observed between the PPC and non-PPC groups in age, diabetes, coronary heart disease, surgical approach, forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), FVC% predicted, peak oxygen uptake (peak VO2), anaerobic threshold (AT), and ventilatory equivalent for carbon dioxide slope (VE/VCO2 slope) (P<0.05). In the predictive model constructed by selecting 7 key features using LASSO regression, the random forest model demonstrated the best overall performance across various metrics, with an area under the receiver operating curve of 0.930, an F1 score of 0.836, and a Brier score of 0.133 in the training set. It also exhibited good predictive ability and calibration in the test set. SHAP analysis ranked feature importance as follows: peak VO2, VE/VCO2 slope, age, FEV1, smoking history, diabetes, and surgical approach. Conclusion Integrating CPET parameters, the random forest model can effectively identify high-risk patients for PPC and has the potential for clinical application.

OBJECTIVE To develope a predictive model for medication deviation risks during the hospital-to-home transition period in coronary heart disease （CHD） patients with initial treatment， aiming to assist medical staff in rapidly identifying high-risk groups for medication deviation. METHODS A total of 462 CHD patients with initial treatment from the Affiliated Hospital of North China University of Science and Technology （hereinafter referred to as “our hospital”） between January and July 2024 were enrolled. The patients were randomly divided into a modeling group and an internal validation group. The modeling group was further categorized into a medication deviation group and a non-medication deviation group based on whether medication deviations occurred. Similarly， 57 CHD patients with initial treatment from the cardiology department of our hospital between June and September 2025 were collected as an external validation group. Univariate analysis was used to screen predictive factors， followed by multivariate Logistic regression to construct the predictive model. Internal validation methods were employed to evaluate model performance， while external validation methods were used to test the model’s generalizability. RESULTS The 462 patients were divided into a modeling group （319 cases） and an internal validation group （143 cases）. In the modeling group， the medication deviation group （192 cases， 60.19%） and the non-medication deviation group （127 cases， 39.81%） were identified. Multivariate Logistic regression analysis revealed that age， medication type， medication adherence， and self-efficacy in rational medication use were predictive factors for medication deviations in CHD patients with initial treatment （ P ＜0.05）. The predictive model equation was logit P ＝ln[ P /（1－ P ） ] ＝1.321+1.732×age+4.091×medication type －4.360×medication adherence －3.081×self-efficacy in rational medication use. The model demonstrated good discrimination， with a Hosmer-Lemeshow goodness-of-fit test P -value of 0.439， an area under the receiver operating characteristic curve （AUC） of 0.870， sensitivity of 0.970， and specificity of 0.607. A risk nomogram with a total score of 350 points and a cutoff value of 110 points was plotted. The internal validation group showed an AUC o f 0.787 and a prediction accuracy of 77.6%， while the external validation group exhibited an AUC of 0.802 and a prediction accuracy of 73.7%. CONCLUSIONS This study successfully developed a predictive model for medication deviation risks during the hospital-to-home transition period in CHD patients with initial treatment. The model demonstrates excellent discrimination and predictive accuracy， effectively identifying high-risk populations for medication deviations. Age （＞70 years）， number of drug types≥5， poor medication adherence， and poor self-efficacy in rational medication use are independent risk factors for medication deviations.

ObjectiveTo investigate the molecular mechanisms related to angiogenesis during the development and progression of diabetic retinopathy （DR）. MethodsAngiogenesis-related genes were obtained from the Gencard website and intersected with differentially expressed genes from DR datasets （GSE60436 and GSE94019）. Functional enrichment and protein-protein interaction （PPI） networks were then used to screen candidate genes and evaluate their diagnostic value. Gene set enrichment analysis （GSEA） was used to explore potential pathways underlying candidate genes， and immune infiltration analysis revealed associations between candidate genes and immune cells. Cellular experiments were conducted to validate the role of fibronectin 1 （FN1） in human retinal microvascular endothelial cells （HRMECs） under high glucose （HG） conditions. ResultsA total of 237 differentially expressed genes related to angiogenesis were identified， enriched in pathways such as phosphoinositide 3-kinase/protein kinase B signaling pathway （PI3K-Akt）， tumor suppressor protein 53 （P53）， tumor necrosis factor （TNF）， and Janus kinase （JAK）/signal transducer and activator of transcription signaling pathway （STAT）. Among them， collagen type I alpha 1 chain （COL1A1）， COL1A2， FN1， TNF， and tumor protein p53 （TP53） were key genes with high diagnostic value. GSEA indicated that these genes were involved in multiple signaling pathways， including P53. CIBERSORTx analysis revealed significant associations with the infiltration of multiple immune cells. HG treatment led to the upregulation of FN1. In HG-induced HRMECs， compared with the si-NC control group， si-FN1 significantly reduced cell proliferation， migration， and tube formation， while P53 protein expression was increased. ConclusionThis study reveals the important role of FN1 in angiogenesis in DR and suggests that it may be a potential diagnostic and therapeutic target.

Objective To evaluate the effect of low-dose ¹⁸F-fluorodeoxyglucose (FDG) injection on image quality in pediatric patients, calculate the whole-body effective dose and absorbed doses to critical organs, and provide a reference for clinical protection in pediatric low-dose positron emission tomography/computed tomography (PET/CT) examination. Methods A total of 67 pediatric patients aged 4-14 years who underwent ¹⁸F-FDG whole-body PET/CT imaging in the Department of Nuclear Medicine, The First Affiliated Hospital of Shandong First Medical University between January 2024 and December 2025 were enrolled in a retrospective study. According to the injected ¹⁸F-FDG dose, patients were divided into a full-dose group (37 cases, 2.96-3.7 MBq/kg, PET acquisition duration of 10 min) and a low-dose group (30 cases, 1.85-2.4 MBq/kg, PET acquisition duration of 15 min). All scans were performed using a uEXPLORER PET/CT scanner. The standardized uptake value, standard deviation, and signal-to-noise ratio were measured for the liver and mediastinal blood pool. Image quality was compared between the two groups. The PET effective dose was calculated based on body mass index, and the total effective dose was obtained by combining PET effective dose with CT effective dose. The doses to critical organs were calculated according to ICRP Publication 128. Statistical analysis was performed using SPSS 26.0 and Prism 9.0 software. Differences were compared between groups. Results There were no significant differences in age, sex, weight, height, or body mass index between the two groups (P>0.05), while the injected dose showed a significant difference (P<0.001). In terms of image quality, there were no significant differences in standardized uptake value, standard deviation, and signal-to-noise ratio between the two groups. In terms of radiation dose, compared with the full-dose group, the low-dose group showed a 35.13% reduction in PET effective dose and a 15.22% reduction in total effective dose (P<0.05), whereas the CT effective dose was reduced by 2.4% and the difference was not significant (P=0.0892). The doses to critical organs (gonads, breasts, thyroid, red bone marrow, lungs) in the low-dose group were significantly lower than those in the full-dose group (P<0.01). Conclusion Under the premise of meeting clinical diagnostic requirements, low-dose ¹⁸F-FDG whole-body PET/CT imaging in pediatric patients can reduce the overall radiation exposure by 15%, and decrease the doses to critical organs, including the gonads, by more than 20%.

Objective To evaluate the effect of low-dose ¹⁸F-fluorodeoxyglucose (FDG) injection on image quality in pediatric patients, calculate the whole-body effective dose and absorbed doses to critical organs, and provide a reference for clinical protection in pediatric low-dose positron emission tomography/computed tomography (PET/CT) examination. Methods A total of 67 pediatric patients aged 4-14 years who underwent ¹⁸F-FDG whole-body PET/CT imaging in the Department of Nuclear Medicine, The First Affiliated Hospital of Shandong First Medical University between January 2024 and December 2025 were enrolled in a retrospective study. According to the injected ¹⁸F-FDG dose, patients were divided into a full-dose group (37 cases, 2.96-3.7 MBq/kg, PET acquisition duration of 10 min) and a low-dose group (30 cases, 1.85-2.4 MBq/kg, PET acquisition duration of 15 min). All scans were performed using a uEXPLORER PET/CT scanner. The standardized uptake value, standard deviation, and signal-to-noise ratio were measured for the liver and mediastinal blood pool. Image quality was compared between the two groups. The PET effective dose was calculated based on body mass index, and the total effective dose was obtained by combining PET effective dose with CT effective dose. The doses to critical organs were calculated according to ICRP Publication 128. Statistical analysis was performed using SPSS 26.0 and Prism 9.0 software. Differences were compared between groups. Results There were no significant differences in age, sex, weight, height, or body mass index between the two groups (P>0.05), while the injected dose showed a significant difference (P<0.001). In terms of image quality, there were no significant differences in standardized uptake value, standard deviation, and signal-to-noise ratio between the two groups. In terms of radiation dose, compared with the full-dose group, the low-dose group showed a 35.13% reduction in PET effective dose and a 15.22% reduction in total effective dose (P<0.05), whereas the CT effective dose was reduced by 2.4% and the difference was not significant (P=0.0892). The doses to critical organs (gonads, breasts, thyroid, red bone marrow, lungs) in the low-dose group were significantly lower than those in the full-dose group (P<0.01). Conclusion Under the premise of meeting clinical diagnostic requirements, low-dose ¹⁸F-FDG whole-body PET/CT imaging in pediatric patients can reduce the overall radiation exposure by 15%, and decrease the doses to critical organs, including the gonads, by more than 20%.

Objective To evaluate the effect of low-dose ¹⁸F-fluorodeoxyglucose (FDG) injection on image quality in pediatric patients, calculate the whole-body effective dose and absorbed doses to critical organs, and provide a reference for clinical protection in pediatric low-dose positron emission tomography/computed tomography (PET/CT) examination. Methods A total of 67 pediatric patients aged 4-14 years who underwent ¹⁸F-FDG whole-body PET/CT imaging in the Department of Nuclear Medicine, The First Affiliated Hospital of Shandong First Medical University between January 2024 and December 2025 were enrolled in a retrospective study. According to the injected ¹⁸F-FDG dose, patients were divided into a full-dose group (37 cases, 2.96-3.7 MBq/kg, PET acquisition duration of 10 min) and a low-dose group (30 cases, 1.85-2.4 MBq/kg, PET acquisition duration of 15 min). All scans were performed using a uEXPLORER PET/CT scanner. The standardized uptake value, standard deviation, and signal-to-noise ratio were measured for the liver and mediastinal blood pool. Image quality was compared between the two groups. The PET effective dose was calculated based on body mass index, and the total effective dose was obtained by combining PET effective dose with CT effective dose. The doses to critical organs were calculated according to ICRP Publication 128. Statistical analysis was performed using SPSS 26.0 and Prism 9.0 software. Differences were compared between groups. Results There were no significant differences in age, sex, weight, height, or body mass index between the two groups (P>0.05), while the injected dose showed a significant difference (P<0.001). In terms of image quality, there were no significant differences in standardized uptake value, standard deviation, and signal-to-noise ratio between the two groups. In terms of radiation dose, compared with the full-dose group, the low-dose group showed a 35.13% reduction in PET effective dose and a 15.22% reduction in total effective dose (P<0.05), whereas the CT effective dose was reduced by 2.4% and the difference was not significant (P=0.0892). The doses to critical organs (gonads, breasts, thyroid, red bone marrow, lungs) in the low-dose group were significantly lower than those in the full-dose group (P<0.01). Conclusion Under the premise of meeting clinical diagnostic requirements, low-dose ¹⁸F-FDG whole-body PET/CT imaging in pediatric patients can reduce the overall radiation exposure by 15%, and decrease the doses to critical organs, including the gonads, by more than 20%.

Polycystic ovary syndrome（PCOS） and its resulting infertility is one of the common diseases of gynecology and reproductive endocrinology. The phosphatidylinositol 3-kinase/protein kinase B（PI3K/Akt） signaling pathway is relatively well-studied in the development of intervention in PCOS， and the experiments on PCOS in rats conducted by traditional Chinese medicine through this signaling pathway is also the main direction of mechanistic research. In this paper， 20 articles published in academic journals in the past 5 years were selected through the corresponding criteria， and the objective situation and existing problems of the selected research projects were analyzed from five aspects， namely， baseline data， modeling and treatment， grouping， evaluative indexes， and pharmacodynamic indexes. It is found that there were different degrees of problems in each research project， such as the observation indicators of modeling， criteria for judging the success of the model， the treatment period， the calculation of dosage of prescription/active ingredients and specific dosage were not clearly defined， which could easily lead the bias of the results or reduce the validity of experimental data. Based on this， the list of PCOS rat experimental research operations was formed， involving five categories of experimental rats， model construction， study implementation， outcome measures and analysis and report with a total of 21 operation lists， with a view to provide a reference for the subsequent PCOS experiments related to scientific research and helping to form high-quality results.

BACKGROUND:Currently,there have been studies on three-dimensional digitalization and visualization systems for adult acupoints,but there are not many reports on the visualization of pediatric acupoints based on real pediatric digital sectional anatomical datasets. OBJECTIVE:To design and develop a digital three-dimensional visualization system for children's neck acupoints,to provide a basis for acupuncture and moxibustion,meridian and acupoint science teaching,clinical practice,acupuncture manipulation practice,and acupuncture safety research,and to provide a basis for the development of children's acupoint simulation system. METHODS:Based on a real cross-sectional anatomical dataset of pre-school boys,a three-dimensional digital virtual anatomical model of the neck region of children and internal multi-organ three-dimensional reconstruction were completed using PhotoShop 2021 and Digihuman Reconstruction System software.A database of 11 acupoints was compiled,including Fengfu and Fengchi,using the Unity database language.A three-dimensional model of children's neck anatomy,acupoint database,and writing acupuncture operation codes were integrated in Unity3D software.A three-dimensional digital visualization system for children's neck acupoints was successfully created,which integrated simulation acupoint positioning,three-dimensional acupoint anatomy,acupuncture training,clinical teaching,and acupuncture safety research. RESULTS AND CONCLUSION:(1)This study was based on real child specimens.Manual layer by layer segmentation of cross-sectional images was used to ensure the accuracy of the three-dimensional model to the greatest extent possible.The 3D software Digihuman Reconstruction System was utilized to extract and save independent segmentation data.PhotoShop 2021 software was collaborated with to complete dozens of three-dimensional reconstruction anatomical models of the outer skin of the neck and its internal bone structure,cervical spinal cord,blood vessels and nerves,muscles,and ligaments in children.The basic morphology and overall contour integrity verification of each independent structure were completed in MeshLab software.The 3-material research 13.0 software was applied for final fine tuning and anatomical position confirmation,successfully simulating and restoring the true anatomical morphology of the neck of preschool children.(2)Based on and referring to the national standards of the People's Republic of China,a database of commonly used acupoints in children's neck region was collected and organized,including their names,meridians,positioning,local anatomy,needle insertion levels,acupuncture methods,acupuncture accidents and prevention,acupoint indications,and two-dimensional anatomical sectional images.(3)Unity3D software was employed to integrate the three-dimensional model of children's neck,acupuncture simulation operation,and acupoint database,and a three-dimensional digital children's neck acupoint acupuncture visualization system was successfully constructed.The system displayed information on children's neck acupoints,two-dimensional and three-dimensional anatomical structures,and achieved two-dimensional and three-dimensional acupuncture simulation functions and acupuncture safety research functions for children's neck acupoints.Based on the ultra-thin sectional anatomical dataset of real child specimens,the first three-dimensional digital and visualization system for acupoints in the neck region of children had been constructed.Compared with previous acupoint acupuncture systems,it is more in line with the anatomical and morphological development characteristics of Asian children and has high application value in the fields of acupuncture safety research,clinical teaching,and acupuncture simulation training.