Objective: To investigate the epidemiological and spatio-temporal characteristics of influenza in Jiaxing City, Zhejiang Province, so as to provide insights into perfecting the prevention and control strategies of influenza. Methods: Data of influenza in Jiaxing City from 2019 to 2023 were collected from the Chinese Disease Prevention and Control Information System. Population data of the same period were collected from the Zhejiang Health Information Network Reporting System. The epidemiological characteristics of influenza were analyzed using descriptive analysis. Vector map information was collected from the Open Street Map, and the spatio-temporal clustering characteristics of influenza were analyzed using spatial autocorrelation and spatio-temporal scanning. Results: A total of 181 501 cases of influenza were reported in Jiaxing City from 2019 to 2023, with an average annual reported incidence of 653.93/105. The majority of cases were aged 5 to <15 years (59 785 cases, 32.94%). The majority of the occupations were students (78 239 cases, 43.11%) and pre-school children (33 715 cases, 18.58%). The county (city, district) with the highest reported incidence was Haining City (1 451.70/105), and the town (street) with the highest reported incidence was Chang'an Town (1 932.78/105). Spatial autocorrelation analysis showed that the incidence of influenza in Jiaxing City from 2019 to 2023 had positive spatial correlations (all Moran's I>0, all P<0.05), with a high-high clustering in the southern region. Spatio-temporal scanning analysis showed that there was a spatio-temporal clustering of influenza in Jiaxing City from 2019 to 2023, with the southern region being the primary-type clustering area and the period between November and January of the following year being the clustering time. Conclusion There was a significant spatio-temporal clustering of influenza in Jiaxing City from 2019 to 2023, with winter being the peak season and the southern region being the primary area.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: To explore the relative importance of different food attributes and levels in food decision making of school aged children, and to understand their meal preferences, so as to provide the evidence for formulating precise intervention strategies for dietary behaviours of school aged children. Methods: From May to June 2024, a total of 854 children aged 11 to 15 years old were selected from 2 middle schools (each school in urban and rural areas) in both Hubei Province and Anhui Province by stratified cluster random sampling method to conduct a D-optimal discrete choice experiment. The mixed Logit model was used to analyze children s preference for meal attributes and different levels, and to calculate the relative importance (RI) of attributes and willingness to pay (WTP) in meal choices. Results: The included five food attributes had statistical significance on meal choice of school aged children ( P <0.05). The relative importance of food attributes affecting the meal choices of school aged children in descending order were dining mode ( RI =31.26%), food varieties ( RI =30.56%), cooking method( RI =23.84%), taste( RI =8.06%) and price ( RI =6.27%). Among them, school aged children preferred home cooked meals ( β =0.74) (WTP=86.3 yuan),varied foods(grain/tubers+vegetables+fish, meat, eggs and beans) ( β =0.61) (WTP=71.9 yuan), fried/roasted cooking ( β =0.51) and spicy taste ( β =0.33).Price was negatively correlated with meal choices( β =-0.01) ( P <0.05). Based on residential area and body mass index (BMI), the stratified analysis showed that dining mode was highest in the relative importance for rural children with overweight and obese children ( RI =31.28%,34.17%), both of whom preferred home cooked meals ( β =0.76, 0.91), and meals containing fish, meat, eggs and beans with grain/tubers or grain/tubers and vegetables in terms of food choice (area: β =0.53, 0.53 ; BMI: β =0.55, 0.56) ( P <0.05). Conclusions School aged children have different preferences for different attributes of meals. The quality of school meals should be improved,the cost of buying healthy meals should be reduced,targeted family health education should be carried out,and healthy cooking methods should be advocated.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

ObjectiveTo investigate the intervention effects and mechanisms of the flavonoid hyperoside （Hyp） on lipopolysaccharide （LPS）-induced inflammation in the zebrafish model. MethodsZebrafish larvae were either microinjected with 0.5 g·L^-1 LPS or immersed in 1 g·L^-1 LPS for the modeling of inflammation. The larvae were then treated with Hyp at 25， 50， and 100 mg·L^-1 through immersion for four consecutive days. The inflammatory phenotypes were assessed by analyzing the mortality rate， malformation rate， body length， and yolk sac area ratio. Behavioral tests were conducted to evaluate the inflammatory stress responses， and macrophage migration was observed by fluorescence microscopy. Additionally， the mRNA levels of inflammation-related genes， including interleukin-1β （IL-1β）， interleukin-6 （IL-6）， chemokine C-C motif ligand 2 （CCL2）， chemokine C-X3-C motif receptor 1 （CX3CR1）， chemokine C-C motif receptor 2 （CCR2）， and genes associated with the Toll-like receptor 4 （TLR4）/myeloid differentiation factor 88 （MyD88）/nuclear factor-kappa B （NF-κB） signaling pathway， were measured by Real-time quantitative polymerase chain reaction（Real-time PCR）. ResultsCompared with the pure water injection group， the model group exhibited increased mortality， malformation rates and yolk sac area ratio （P0.01）， reduced body length （P0.01）， increased total swimming distance and high-speed swimming duration （P0.01）， and up-regulated mRNA levels of TLR4， MyD88， NF-κB， IL-1β， IL-6， CCL2， CX3CR1， and CCR2 （P0.01）. Hyp at low， medium and high doses， as well as aspirin， reduced the mortality and malformation rates （P0.05，P0.01）， increased the body length （P0.05，P0.01）， decreased the yolk sac area ratio （P0.01）， reduced the high-speed swimming duration （P0.01）， and down-regulated the mRNA levels of TLR4， MyD88， NF-κB， IL-1β， IL-6， CCL2， CX3CR1， and CCR2 （P0.05，P0.01） compared with the model group. ConclusionHyp may modulate the TLR4/MyD88/NF-κB pathway to ameliorate inflammatory phenotypes and alleviate stress conditions in zebrafish， thereby exerting the anti-inflammatory effect.

Objective To analyze the characteristics of males with autologous sperm preservation(ASP)in Anhui human sperm bank,and to explore the future direction of ASP in human sperm bank.Methods The basic infor-mation of males applied for ASP in Anhui human sperm bank from January 2019 to December 2023 was retrospec-tively analyzed.Results During this period,there were 424 males applied for ASP.93.40％(396/424)came from Anhui Province,of which 46.46％(197/424)came from Hefei.The age range of them was 15 to 59 years old.66.04％(280/424)had a college degree or above.23.11％(98/424)were employees of public institutions or enterprises.26.89％(114/424)were unmarried and 89.39％(379/424)were childless.67.45％(286/424)patients applied for ASP because of assisted reproductive technology treatment.15.33％(65/424)patients did it due to tumors,among which testicular cancer,lymphoma,leukemia and seminoma were the main reasons.A total of 1 163 semen samples were saved,and 53 males had used their sperm.Conclusion Only a few people applied for ASP,and the characteristics of males with ASP can be used to further strengthen publicity for key groups,espe-cially cancer patients,so as to benefit more people with autologous sperm preservation.

Objective: To analyze the spatio-temporal distribution characteristics of pulmonary tuberculosis incidence in Xinjiang, and to provide reference for the prevention and control of pulmonary tuberculosis. Methods: The reported incidence numbers of tuberculosis and population data from various counties, cities(prefectures), and districts in Xinjiang from 2010 to 2022 were collected. Based on spatial-temporal scan statistics, standard deviational ellipse analysis, and centroid migration models, the clustering and migration trends of tuberculosis incidence were evaluated. Utilizing Kriging interpolation techniques, an interpolation analysis of the 2022 incidence rate was conducted on an annual scale, with the reported incidence rate in 2018 serving as a temporal control, to identify hotspots of the spatio-temporal distribution. ArcGIS software was employed to visualize the continuous spatial trends of incidence rate changes. Results: The annual reported incidence rate of tuberculosis in Xinjiang from 2010 to 2022 varied year by year, with fluctuations and increases prior to 2018, peaking in 2018, and then declining annually thereafter. The spatial distribution of the incidence rate exhibited a trend of initial clustering followed by diffusion, with the centroid of incidence shifting towards the northeast, yet the epicenter of the epidemic remained in Aksu Prefecture. The results of spatiotemporal scan statistics analysis revealed that the three-level aggregated areas of the epidemic encompassed a total of 41 prefectures, counties, and cities, with the tuberculosis incidence risk in the primary and secondary aggregated areas being significantly higher than that in other regions(P<0.01). The Kriging interpolation prediction map suggested that the four prefectures in southern Xinjiang continued to be high-risk regions for tuberculosis(incidence rate>300/100 000). The overall incidence rate in the northern region was relatively low, with the lowest rate observed in Urumqi, radiating outwards. Conclusion The incidence rate of tuberculosis in Xinjiang shows an upward trend before 2018, followed by a year-on-year decrease. The centroid of the incidence rate shifts towards the northeast. From 2010 to 2022, the tuberculosis epidemic in Xinjiang exhibits a notable spatiotemporal clustering, particularly prominent in the southwestern region, where the four prefectures constitute high-risk areas for tuberculosis. The prevention and control efforts of tuberculosis in Xinjiang should prioritize the regions with high tuberculosis incidence, intensifying prevention and control measures as well as policy support.