Objective To investigate the prevalence of pinworm infections among kindergarten children and the effectiveness of health interventions among teachers and parents in Gaoyou City, so as to provide insights into optimization of enterobiasis control strategies. Methods From September to November each year from 2023 to 2025, Gaoyou City’s 57 kindergartens were divided into five zones based on the five cardinal directions: east, west, south, north, and center. At least one kindergarten was randomly selected as a survey site in each zone, with a minimum of 200 children surveyed per site. The transparent adhesive tape anal swab method was used to detect pinworm infection in the surveyed children, while the transparent adhesive tape sticking method was employed to assess pinworm egg contamination in the children’s home and classroom environments. Concurrently, health education interventions were conducted for kindergarten teachers and parents. Additionally, self-administered questionnaires were administered to teachers and parents to evaluate children’s hygiene behaviors and the awareness rates of pinworm prevention knowledge among teachers and parents before and after the health education interventions. Results From 2023 to 2025, a total of 1 939 children from nine kindergartens in Gaoyou City were tested for pinworm infection, with two cases detected, resulting in an overall infection rate of 0.10% (2/1 939). No pinworm eggs were found in the samples from the children’s families or classroom environments. In public kindergartens, the proportions of children practicing the four hygiene habits, namely “handwashing after defecation” [96.10% (1 305/1 358) vs. 74.65% (212/284); χ² = 153.646, P < 0.05], “regular nail trimming” [92.93% (1 262/1 358) vs. 77.82% (221/284); χ² = 61.349, P < 0.05], “not biting toys or pencils” [88.14% (1 197/1 358) vs. 76.76% (218/284); χ² = 25.549, P < 0.05], and “showering twice or more per week” [89.03% (1 209/1 358) vs. 74.65% (212/284); χ² = 41.699, P < 0.05], were all higher than those in private kindergartens. Before health education intervention, the awareness rates of pinworm prevention knowledge among teachers in public and private kindergartens were 86.89% (53/61) and 75.00% (21/28), respectively, with no statistically significant difference (χ² = 1.935, P > 0.05). The awareness rates among parents of children in public and private kindergartens were 64.73% (879/1 358) and 57.39% (163/284), respectively, showing a statistically significant difference (χ² = 5.447, P < 0.05). After the intervention, the awareness rates among teachers in public and private kindergartens increased to 96.72% (59/61) and 82.14% (23/28), respectively, while those among parents rose to 88.95% (1 208/1 358) and 77.81% (221/284), both with statistically significant differences (χ² = 5.628 and 25.808, both P < 0.05). Among the questionnaire items, teachers [32.58% (29/89)] and parents [26.00% (427/1 642)] had the lowest overall awareness rate regarding the “main reasons for the difficulty in preventing and controlling pinworm disease”. After the intervention, these rates increased to 77.53% (69/89) and 70.77% (1 162/1 642), respectively. Conclusions The prevalence of pinworm infection in kindergarten children in Gaoyou City is at a low level. Health intervention can effectively improve the knowledge level of teachers and parents on the prevention and treatment of pinworm disease, but further efforts are needed to strengthen the health education and management of pinworm disease in private kindergartens.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective:To evaluate the relationship between postoperative changes in femoral head coverage (FHC) after S 2-Alar-Iliac (S 2AI) screw fixation and the development of sagittal imbalance during follow-up in patients with adult spinal deformity (ASD), providing insights for clinical assessment and treatment strategies. Methods:A consecutive cohort of 98 ASD patients who underwent S2AI fixation between September 2019 and September 2021 was retrospectively analyzed. Patients were divided into two groups based on changes in femoral head coverage (ΔFHC): the FHC-C group (upper quartile ΔFHC, 25 cases) and the FHC-NC group (lower quartile ΔFHC, 24 cases). Additionally, patients were classified into proximal junctional kyphosis (PJK) and non-PJK groups based on their clinical outcomes at the last follow-up. Standing full-spine anteroposterior and lateral X-rays were taken preoperatively, postoperatively, and at the two-year follow-up to measure and document the following spinal parameters: Cobb angle, proximal lumbar lordosis (PLL), distal lumbar lordosis (DLL), lumbar lordosis (LL), lordosis distribution index (LDI), sagittal vertical axis (SVA), coronal balance distance (CBD), thoracic kyphosis (TK), T 1 pelvic angle (T 1PA), pelvic incidence (PI), pelvic tilt (PT), sacral slope (SS), PI-LL, and proximal junctional angle (PJA). Parameters related to hip joint coverage included: femoral head coverage (FHC), lateral center-edge angle (LCE angle), acetabular index (AI), Sharp angle, and extrusion index (EI). Comparisons of radiographic indicators between the two groups were performed at preoperative, postoperative, and final follow-up assessments. The visual analogue scale (VAS) was used to evaluate the hip pain and back pain. Results:At final follow-up, the incidence of PJK was significantly higher in the FHC-NC group [37.5% (9/24)] compared to the FHC-C group [16.0% (4/25)] (χ 2=3.952, P=0.042). Moreover, the increase in sagittal vertical axis (ΔSVA) was significantly greater in the FHC-NC group (35.9±44.7 mm vs. 14.6±31.8 mm, t=2.216, P=0.031). Patients with PJK had significantly higher preoperative T 1PA (36.8°±10.8° vs. 31.9°±18.4°, t=2.150, P=0.034) and lower immediate postoperative ΔFHC (1.7%±1.5% vs. 3.3%±2.5%, t=2.987, P=0.004), as well as lower changes in lateral center-edge angle during follow-up (0.3°±3.0° vs. 1.1°±8.9°, t=2.334, P=0.022). Pearson correlation analysis revealed significant negative correlations between postoperative ΔFHC and both ΔSVA ( r=-0.374, P=0.008) and proximal junctional angle changes (ΔPJA, r=-0.429, P=0.006). Additionally, increases in VAS leg pain scores correlated negatively with immediate postoperative FHC ( r=-0.314, P=0.025) and ΔFHC ( r=-0.298, P=0.031). Logistic regression indicated that immediate postoperative ΔFHC was a protective factor against PJK [ OR=0.722, 95% CI (0.541, 0.963), P=0.009), with a ROC-determined optimal ΔFHC cut-off of 3.90% (AUC=0.723, Youden index=0.847). Conclusions:Postoperative evaluation of femoral head coverage is clinically important for ASD patients undergoing S2AI screw fixation. A pre-to-post ΔFHC below 3.90% may indicate reduced hip compensation capacity, increasing risks for hip pain, sagittal imbalance progression, and PJK postoperatively.

This study was aimed at establishing a sensitive and specific sandwich ELISA detection method for Brucella.We screened monoclonal capture antibodies and detection antibodies for Brucella detection,and optimized and determined the opti-mal antibody coating time and concentration,as well as the optimal blocking solution,blocking time,and yin-yang critical val-ue.The specificity of this method was verified by examination of other bacteria prone to cross-reacting with Brucella.The sen-sitivity of the method was verified by detection of a gradient dilution of inactivated Brucella.Moreover,the sandwich ELISA detection results were compared with test tube agglutination and qPCR results.The selected capture antibody was 4A12,and the selected detection antibody was 6C12.Experimental analysis indicated that the optimal coating concentration for the 4A12 capture antibody was 5 μg/mL,and the optimal dilution ratio for the 6C12 detection antibody was 1∶2000.The optimal coating conditions were overnight at 4℃,and blocking with 5％skim milk powder for 2 hours.The established double antibody sand-wich ELISA method reacted with only Brucella but not other bacteria,thus demonstrating the method's good specificity.Inac-tivated Brucella solution was still detectable after dilution to 1 × 105 CFU/mL,thus demonstrating the method's good sensitiv-ity.The intra-and inter batch coefficients of variation were both below 10％,thus indicating the method's good repeatability.Thus,this study successfully established a dual antibody sandwich ELISA method for Brucella detection,which has good spe-cificity and sensitivity,and might provide an effective approach for the precise diagnosis and effective prevention and control of brucellosis.

Integrated metabolomic and lipidomic profiling,utilizing liquid chromatography coupled with high-resolution mass spectrometry(LC-HRMS),has emerged as a pivotal strategy for biomarker discovery.However,the inherent polarity disparity between metabolites and lipids complicates simultaneous analysis.To address this,a dual-stationary phase polarity-extended liquid chromatography(PELC)system was developed,which surpassed conventional one-dimensional LC(1D-LC)by enabling comprehensive coverage of both polar and non-polar compounds within a single injection.This system enhanced chromatographic resolution,peak capacity,and throughput while minimizing analytical variability.Extracellular vesicles(EVs),lipid bilayer-enclosed nanoparticles ubiquitously present in biofluids,had gained prominence as reservoirs of cancer biomarkers due to their cargo stability and pathophysiological relevance.Herein,the application of PELC-HRMS for concurrent metabolome-lipidome profiling in EVs was pioneered.A total of 193 metabolites were identified using this technique coupled with MS-DIAL software and Human Metabolome Database.Subsequently,this technique was employed to explore potential biomarkers for prostate cancer(PCa).Multivariate analysis identified 17 differentially abundant metabolites in PCa,implicating dysregulated pathways including purine metabolism,starch and sucrose metabolism,galactose metabolism,cysteine and methionine metabolism,and biosynthesis of unsaturated fatty acids.Notably,creatine(AUC=0.92)and DG 42:5(AUC=0.80)demonstrated robust diagnostic efficacy,attributable to their broad polarity ranges and EV-specific enrichment.This study established PELC as a high-fidelity platform for multi-omics integration in complex biospecimens,advancing mechanistic insights into metabolic rewiring and disease pathophysiology.

This study was aimed at establishing a sensitive and specific sandwich ELISA detection method for Brucella.We screened monoclonal capture antibodies and detection antibodies for Brucella detection,and optimized and determined the opti-mal antibody coating time and concentration,as well as the optimal blocking solution,blocking time,and yin-yang critical val-ue.The specificity of this method was verified by examination of other bacteria prone to cross-reacting with Brucella.The sen-sitivity of the method was verified by detection of a gradient dilution of inactivated Brucella.Moreover,the sandwich ELISA detection results were compared with test tube agglutination and qPCR results.The selected capture antibody was 4A12,and the selected detection antibody was 6C12.Experimental analysis indicated that the optimal coating concentration for the 4A12 capture antibody was 5 μg/mL,and the optimal dilution ratio for the 6C12 detection antibody was 1∶2000.The optimal coating conditions were overnight at 4℃,and blocking with 5％skim milk powder for 2 hours.The established double antibody sand-wich ELISA method reacted with only Brucella but not other bacteria,thus demonstrating the method's good specificity.Inac-tivated Brucella solution was still detectable after dilution to 1 × 105 CFU/mL,thus demonstrating the method's good sensitiv-ity.The intra-and inter batch coefficients of variation were both below 10％,thus indicating the method's good repeatability.Thus,this study successfully established a dual antibody sandwich ELISA method for Brucella detection,which has good spe-cificity and sensitivity,and might provide an effective approach for the precise diagnosis and effective prevention and control of brucellosis.

Objective:To evaluate the relationship between postoperative changes in femoral head coverage (FHC) after S 2-Alar-Iliac (S 2AI) screw fixation and the development of sagittal imbalance during follow-up in patients with adult spinal deformity (ASD), providing insights for clinical assessment and treatment strategies. Methods:A consecutive cohort of 98 ASD patients who underwent S2AI fixation between September 2019 and September 2021 was retrospectively analyzed. Patients were divided into two groups based on changes in femoral head coverage (ΔFHC): the FHC-C group (upper quartile ΔFHC, 25 cases) and the FHC-NC group (lower quartile ΔFHC, 24 cases). Additionally, patients were classified into proximal junctional kyphosis (PJK) and non-PJK groups based on their clinical outcomes at the last follow-up. Standing full-spine anteroposterior and lateral X-rays were taken preoperatively, postoperatively, and at the two-year follow-up to measure and document the following spinal parameters: Cobb angle, proximal lumbar lordosis (PLL), distal lumbar lordosis (DLL), lumbar lordosis (LL), lordosis distribution index (LDI), sagittal vertical axis (SVA), coronal balance distance (CBD), thoracic kyphosis (TK), T 1 pelvic angle (T 1PA), pelvic incidence (PI), pelvic tilt (PT), sacral slope (SS), PI-LL, and proximal junctional angle (PJA). Parameters related to hip joint coverage included: femoral head coverage (FHC), lateral center-edge angle (LCE angle), acetabular index (AI), Sharp angle, and extrusion index (EI). Comparisons of radiographic indicators between the two groups were performed at preoperative, postoperative, and final follow-up assessments. The visual analogue scale (VAS) was used to evaluate the hip pain and back pain. Results:At final follow-up, the incidence of PJK was significantly higher in the FHC-NC group [37.5% (9/24)] compared to the FHC-C group [16.0% (4/25)] (χ 2=3.952, P=0.042). Moreover, the increase in sagittal vertical axis (ΔSVA) was significantly greater in the FHC-NC group (35.9±44.7 mm vs. 14.6±31.8 mm, t=2.216, P=0.031). Patients with PJK had significantly higher preoperative T 1PA (36.8°±10.8° vs. 31.9°±18.4°, t=2.150, P=0.034) and lower immediate postoperative ΔFHC (1.7%±1.5% vs. 3.3%±2.5%, t=2.987, P=0.004), as well as lower changes in lateral center-edge angle during follow-up (0.3°±3.0° vs. 1.1°±8.9°, t=2.334, P=0.022). Pearson correlation analysis revealed significant negative correlations between postoperative ΔFHC and both ΔSVA ( r=-0.374, P=0.008) and proximal junctional angle changes (ΔPJA, r=-0.429, P=0.006). Additionally, increases in VAS leg pain scores correlated negatively with immediate postoperative FHC ( r=-0.314, P=0.025) and ΔFHC ( r=-0.298, P=0.031). Logistic regression indicated that immediate postoperative ΔFHC was a protective factor against PJK [ OR=0.722, 95% CI (0.541, 0.963), P=0.009), with a ROC-determined optimal ΔFHC cut-off of 3.90% (AUC=0.723, Youden index=0.847). Conclusions:Postoperative evaluation of femoral head coverage is clinically important for ASD patients undergoing S2AI screw fixation. A pre-to-post ΔFHC below 3.90% may indicate reduced hip compensation capacity, increasing risks for hip pain, sagittal imbalance progression, and PJK postoperatively.

Osteoporotic fractures(OPF) refer to the fractures caused by minor violence in the state of osteoporosis, seriously threatening the life and health of elderly patients. Drug and surgical therapies have limitations such as single targets, diverse adverse reactions, and poor prognosis. Kidney-tonifying traditional Chinese medicine(TCM) has good potential in the treatment of OPF. TCM can promote the healing of OPF by promoting angiogenesis in the early stage of bone healing, promoting osteogenic differentiation of bone marrow mesenchymal stem cells in the stage of bone repair, maintaining the balance of osteogenic and osteoclastic system in the stage of bone remodeling, and regulating the oxidative stress responses throughout the process of OPF healing. TCM can alleviate the pathological state of osteoporosis and promote fracture healing in OPF patients via multiple pathways and targets, demonstrating the advantages and potential of biphasic regulation.
Humans ; Drugs, Chinese Herbal/therapeutic use* ; Osteoporotic Fractures/metabolism* ; Animals ; Fracture Healing/drug effects* ; Medicine, Chinese Traditional ; Kidney/metabolism* ; Osteogenesis/drug effects*

In this paper, near-infrared spectroscopy(NIRS) was employed to analyze 129 batches of commercial products of Reduning Injection. The batch reporting rate was estimated according to the report of Reduning Injection in the direct adverse drug reaction(ADR) reporting system of the drug marketing authorization holder of the Center for Drug Reevaluation of the National Medical Products Administration(National Center for ADR Monitoring) from August 2021 to August 2022. According to the batch reporting rate, the samples of Reduning Injection were classified into those with potential risks and those being safe. No processing, random oversampling(ROS), random undersampling(RUS), and synthetic minority over-sampling technique(SMOTE) were then employed to balance the unbalanced data. After the samples were classified according to appropriate sampling methods, competitive adaptive reweighted sampling(CARS), successive projections algorithm(SPA), uninformative variables elimination(UVE), and genetic algorithm(GA) were respectively adopted to screen the features of spectral data. Then, support vector machine(SVM), logistic regression(LR), k-nearest neighbors(KNN), naive bayes(NB), random forest(RF), and artificial neural network(ANN) were adopted to establish the risk prediction models. The effects of the four feature extraction methods on the accuracy of the models were compared. The optimal method was selected, and bayesian optimization was performned to optimize the model parameters to improve the accuracy and robustness of model prediction. To explore the correlations between potential risks of clinical use and quality test data, TreeNet was employed to identify potential quality parameters affecting the clinical safety of Reduning Injection. The results showed that the models established with the SVM, LR, KNN, NB, RF, and ANN algorithms had the F1 scores of 0.85, 0.85, 0.86, 0.80, 0.88, and 0.85 and the accuracy of 88%, 88%, 88%, 85%, 91%, and 88%, respectively, and the prediction time was less than 5 s. The results indicated that the established models were accurate and efficient. Therefore, near infrared spectroscopy combined with machine learning algorithms can quickly predict the potential risks of clinical use of Reduning Injection in batches. Three key quality parameters that may affect clinical safety were identified by TreeNet, which provided a scientific basis for improving the safety standards of Reduning Injection.
Spectroscopy, Near-Infrared/methods* ; Drugs, Chinese Herbal/administration & dosage* ; Machine Learning ; Algorithms ; Humans ; Quality Control

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.