ObjectiveTo explore the possible mechanisms by which ligustilide （LIG） exerts neuroprotective effects on ischemic stroke （IS） by inhibiting the release of neutrophil extracellular traps （NETs）， promoting blood-brain barrier repair， and alleviating post-ischemic neuroinflammation， thereby providing a new direction for IS treatment. MethodsA middle cerebral artery occlusion （MCAO） model was established in rats. The rats were divided into the sham operation （Sham） group， model （Model） group， low- and high-dose LIG groups （20， 40 mg·kg^-1）， and the NET inhibitor CI-amidine group （CI-amidine， 10 mg·kg^-1）. Drug treatments were administered for 3 days. Neurological injury after ischemia was evaluated by 2，3，5-triphenyltetrazolium chloride （TTC） staining， neurological deficit scoring， and brain index measurement. Flow cytometry and Western blot were used to analyze changes in neutrophil expression. Immunofluorescence was used to observe the fluorescence intensity of the NET marker citrullinated histone H3 （H3Cit）. Western blot was performed to detect the expression of blood-brain barrier tight junction-related proteins and inflammatory factors， including interleukin-18 （IL-18） and interleukin-1β （IL-1β）. ResultsCompared with the Sham group， the Model group exhibited significant brain tissue injury （P<0.05）， significantly increased neutrophil numbers and NET expression （P<0.05）， significantly impaired blood-brain barrier permeability （P<0.05）， and significantly increased expression of inflammatory factors （P<0.05）. Compared with the Model group， both low- and high-dose LIG significantly alleviated brain tissue injury in rats （P<0.01）， inhibited neutrophil numbers and NET expression （P<0.01）， reduced blood-brain barrier damage （P<0.01）， and suppressed the expression of inflammatory factors IL-18 and IL-1β （P<0.01）， thereby ultimately exerting a neuroprotective effect. ConclusionThe neuroprotective effect of LIG in rats with cerebral ischemia-reperfusion injury may be related to inhibition of neutrophils and the NETs induced by them.

ObjectiveTo explore the possible mechanisms by which ligustilide （LIG） exerts neuroprotective effects on ischemic stroke （IS） by inhibiting the release of neutrophil extracellular traps （NETs）， promoting blood-brain barrier repair， and alleviating post-ischemic neuroinflammation， thereby providing a new direction for IS treatment. MethodsA middle cerebral artery occlusion （MCAO） model was established in rats. The rats were divided into the sham operation （Sham） group， model （Model） group， low- and high-dose LIG groups （20， 40 mg·kg^-1）， and the NET inhibitor CI-amidine group （CI-amidine， 10 mg·kg^-1）. Drug treatments were administered for 3 days. Neurological injury after ischemia was evaluated by 2，3，5-triphenyltetrazolium chloride （TTC） staining， neurological deficit scoring， and brain index measurement. Flow cytometry and Western blot were used to analyze changes in neutrophil expression. Immunofluorescence was used to observe the fluorescence intensity of the NET marker citrullinated histone H3 （H3Cit）. Western blot was performed to detect the expression of blood-brain barrier tight junction-related proteins and inflammatory factors， including interleukin-18 （IL-18） and interleukin-1β （IL-1β）. ResultsCompared with the Sham group， the Model group exhibited significant brain tissue injury （P<0.05）， significantly increased neutrophil numbers and NET expression （P<0.05）， significantly impaired blood-brain barrier permeability （P<0.05）， and significantly increased expression of inflammatory factors （P<0.05）. Compared with the Model group， both low- and high-dose LIG significantly alleviated brain tissue injury in rats （P<0.01）， inhibited neutrophil numbers and NET expression （P<0.01）， reduced blood-brain barrier damage （P<0.01）， and suppressed the expression of inflammatory factors IL-18 and IL-1β （P<0.01）， thereby ultimately exerting a neuroprotective effect. ConclusionThe neuroprotective effect of LIG in rats with cerebral ischemia-reperfusion injury may be related to inhibition of neutrophils and the NETs induced by them.

Abstract The prevention and control of myopia in Chinese children and adolescents has become a major public health issue. While maintaining increased outdoor activity as a cornerstone intervention, there is an urgent need to explore new complementary approaches that can be effectively implemented in both indoor and outdoor settings. In recent years, environmental spatial frequency has gained increasing attention as one of the key environmental factors influencing the development and progression of myopia. Both animal studies and human research have confirmed that indoor environments lacking mid to high spatial frequency components, often characterized as "visually impoverished", can promote axial elongation and myopia through mechanisms such as disruption of retinal neural signaling, impaired accommodative function, and altered expression of related molecules. Based on the scientific consensus, it is recommended that "enriching of environmental spatial frequency" should be integrated into the myopia prevention and control framework. Following the principles of schoolled organization, family cooperation, community involvement, and student participation, specific measures are put forward in three areas：optimizing school visual settings, improving home spatial environments, and promoting healthy visual behavior. The aim is to create "visually friendly" indoor environments as an important supplement to outdoor activity, thereby providing a novel perspective and strategy for comprehensively advancing myopia prevention and control among children and adolescents.

Objective: To explore the relationship between social jetlag and depressive symptoms in junior high school students, as well as the potential gender differences, so as to provide a reference for developing effective interventions for depressive symptoms and promoting adolescents mental health. Methods: In October 2024, a total of 3 516 students from grades 7 to 9 were recruited from 4 junior high schools in Chongqing Municipality using a combination of cluster sampling and convenience sampling. A questionnaire survey was conducted using the Center for Epidemiologic Studies Depression Scale (CES-D) and the Munich Chronotype Questionnaire (MCTQ). Statistical analyses included the χ 2 test, binary Logistic regression analysis, and stratified Logistic regression analysis. Results: The detection rate of depressive symptoms among the junior high school students was 34.3%. The number of students with social jetlag >2 h was 714 (20.3%), >1-2 h was 1 455(41.4%), and ≤1 h was 1 347(38.3%). Results from the binary Logistic regression analysis showed that compared to the group with social jetlag ≤1 h, the risk of depressive symptoms in the group with social jetlag >2 h was higher ( OR=1.59, 95%CI=1.28-1.98, P <0.01). Gender stratified analysis revealed that among females, the risk of depressive symptoms was higher in the groups with social jetlag of >1-2 h and >2 h compared to the ≤1 h group ( OR = 1.34 and 2.05, 95% CI =1.03-1.75 and 1.48-2.83, both P <0.05). However, among males, the associations were not statistically significant ( OR =1.11 and 1.29, 95% CI =0.86-1.43 and 0.95-1.77, both P >0.05). Conclusions Social jetlag is positively associated with depressive symptoms in junior high school students, demonstrating a threshold effect and gender differences. The findings suggest that reducing social jetlag may decrease the risk of depressive symptoms in adolescents, and targeted intervention measures should be developed considering different gender characteristics.

Objective: To investigate the current status of refractive errors and insufficient hyperopia reserve in preschool children aged 3-6 years in Hefei and to analyze influencing factors, so as to provide a scientific basis for formulating targeted myopia prevention policies and comprehensive interventions. Methods: In May 2022, a stratified cluster random sampling method was used to select 897 preschool children from 8 kindergartens across four districts (Baohe, Yaohai, Shushan, and Economic and Technological Development Zone) in Hefei, and Children’s Visual Health related Behavior Assessment Scale was used to collect personal information and environmental factors. Pre and post cycloplegic refraction tests were conducted to assess insufficient hyperopic reserve and refractive development levels. Group comparisons were conducted using 2 test, t-test or analysis of variance. Multivariate regression analysis was performed to identify key factors influencing hyperopic reserve, axial length and spherical equivalent in preschool children. Results: The detection rates of refractive errors among preschool children were 6.8% for hyperopia, 1.6% for myopia, and 11.1% for astigmatism. Notably, the prevalence of myopia was significantly higher in boys (2.3%) than in girls (0.7%) ( χ 2=3.88, P <0.05). Additionally, 8.8% of the children exhibited insufficient hyperopic reserve. The results of multiple regression analysis showed that preschool children with high myopia in the father, high myopia in the mother, longer daily duration of near work, and longer daily electronic product use time had increased risks of axial growth ( β =0.12, 0.09, 0.15, 0.11), SE reduction ( β =-0.10, -0.07, -0.18, -0.13), and insufficient hyperopic reserve ( OR=1.87, 2.22, 1.40, 1.28) (P <0.05). While, preschool children with longer sleep time and daily outdoor activity duration had lower risks of axial growth ( β =-0.11, -0.10 ), SE reduction ( β =0.39, 0.51), and insufficient hyperopia reserve ( OR =0.54, 0.51) in preschool children ( P <0.05). Conclusions The rates of refractive errors and insufficient hyperopia reserve in preschool children in Hefei are relatively low, which are influenced by many factors. Parents, kindergartens and relevant departments should implement early vision monitoring and intervention for preschool children, and cultivate their scientific eye use habits.

Objective: To explore the mediating role of balanced time perspective in the relationship between social jetlag and depressive symptom among junior high school students, so as to privide a basis for improving their mental health. Methods: In October 2024, a method of combining convenient sampling with cluster sampling was used to select 3 438 junior high school students from two districts(Yubei District and Kaizhou District) in Chongqing. The Center for Epidemiological Studies Depression Scale (CES-D), Munich Chronotype Questionnaire (MCTQ), and Balanced Time Perspective Inventory (BTPI) were administered for the survey. Statistical analyses included t-test, ANOVA, and Spearman correlation analysis, and conduct a mediation effect analysis using the Process program. Results: The mean score of depressive symptom among junior high school students was 15.00(9.00, 23.00 ), social jetlag was 1.18(0.72, 1.83) hours, and balanced time perspective score was -0.18(-2.82, 2.93). Social jetlag among junior high school students was positively correlated with depressive symptom score ( r =0.17), while balanced time perspective was negatively correlated with social jetlag ( r =-0.15) and depressive symptom score ( r =-0.68) (all P <0.01). Mediation analysis showed that balanced time perspective partially mediated the relationship between social jetlag and depressive symptom ( β=0.68, P <0.01) among junior high school students, accounting for 53.97% of the total effect. Conclusions Social jetlag of junior high school students influences depressive symptoms by affecting balanced time perspective. Efforts should be made to improve adolescents balanced time perspective for reducing the impact of social jetlag on depressive symptom.

Objective Heart failure(HF)complicated by acute kidney injury(AKI)significantly impacts patient outcomes,and it is crucial to make early predictions of short-term mortality.This study is focused on developing an interpretable machine learning model to enhance early prediction accuracy in such clinical scenarios.Methods This retrospective cohort study utilized data from the Medical Information Mart for Intensive Care Ⅳ(MIMIC-Ⅳ,version 2.0)database.Data from the first 24 hours after admission to the ICU were extracted and divided into a training set(70％)and a validation set(30％).We utilized the SHapley Additive exPlanation(SHAP)method to interpret the workings of an extreme gradient boosting(XGBoost)model and identify key prognostic factors.The XGBoost model's predictive ability was evaluated against three other machine learning models using the area under the curve(AUC)metric,and its interpretation was enhanced using the SHAP method.Results The study included 8 028 patients with HF complicated by AKI.The XGBoost model outperformed the other models,achieving an AUC of 0.93(95％confidence interval[CI]:0.78-0.94;accuracy=0.89),while neural network model showed the worst performance(AUC=0.79,95％CI:0.77-0.82;accuracy=0.82).Decision curve analysis showed the superior net benefit of the XGBoost model within the 9％to 60％threshold probabilities.SHAP analysis was performed to identify the top 20 predictors,with age(mean SHAP value 1.29)and Glasgow Coma Scale score(mean SHAP value 1.24)emerging as significant factors.Conclusions Our interpretable model offers an enhanced ability to predict mortality risk in HF patients with AKI in ICUs.This model can be used to assist in formulating effective treatment plans and optimizing resource allocation.

With the aggravation of population aging in our country,the prevalence of osteoporosis(OP)has surged dramatically.Currently,the diagnosis of OP primarily relies on bone mineral density(BMD),and the precise measurement of BMD is crucial in the diagnosis and treatment of spinal surgical diseases.In recent years,computed tomography(CT)has gained widespread attention in clinical diagnosis and treatment due to its unique advantages.Vertebral CT values not only enhance the diagnostic rate of OP but also effectively predict the occurrence of postoperative complications such as adjacent vertebral fractures,fusion device subsidence,and pedicle screw loosening.This article summarizes the research progress of vertebral CT value in the field of spine surgery,and discusses its feasibility in guiding spinal surgery and its correlation with postoperative complications of spine.Additionally,it elaborates on the progress of combining CT with artificial intelligence(AI)to assist in disease diagnosis and treatment,aiming to better promote the clinical application of vertebral CT values.

Objective To explore the behavioral patterns and hippocampal neurogenesis of CHD8+mice,and to provide behavioral and morphological basis for improving autism like behavior and neurogenesis.Methods Genotype of wild type(WT)and CHD8+/-mice was identified.Weight measurement was conducted on both male and female mice of the WT and CHD8+/-strains.Subsequently,a battery of behavioral tests was administered,which included three-chamber test,self-grooming test,nesting test,Y-maze spontaneous alternation test,food burial test,open-field test and light-dark transition test.Afterwards,the mice were administered 2％pentobarbital sodium(2 ml/kg)to induce anesthesia.Their brains were frozen with 4％paraformaldehyde,removed for photography and analysis to identify any alterations in brain size.Western blotting and immunofluorescent labeling were used to detect changes in the process of hippocampus neurogenesis.Results Western blotting analysis demonstrated a decrease in the amounts of chromodomain helicase DNA binding protein 8(CHD8)protein in both male and female mice with CHD8+genotype,as compared to WT mice.There were no notable disparities in body weight between male and female WT and CHD8+mice,as well as in brain size.The three-chamber social behavior test revealed that both male and female CHD8+/-mice had social deficiencies(P＜0.05).During the open field test,there was no significant difference in the total distance moved by male and female WT and CHD8+/-mice.However,the amount of time spent in the central region was considerably lower in CHD8+/-mice compared to the WT mice(P＜0.01).Furthermore,the light-dark transition test revealed that both male and female CHD8+/-mice spent considerably less time investigating the white box compared to the WT mice(P＜0.05).Nevertheless,there were no notable alterations found in self-grooming,nesting,spontaneous alternation of Y-maze,and food burial experiments.In addition,Western blotting result demonstrated a significant drop in doublecortin(DCX)expression(P＜0.001),and immunofluorescent staining revealed a notable reduction in the number of DCX+cells(P＜0.01)in the hippocampus of CHD8+/-mice.Conclusion CHD8+/-mice exhibit social disorders and anxiety-like behaviors,with a decrease in the number of newly generated neurons in the hippocampus and neurogenesis disorders.

Microfluidic chips have revolutionized analytical sciences through miniaturization and high-throughput capabilities.However,conventional static devices are constrained by fixed architectures,functional rigidity,and high customization costs.In recent years,,the emerging configurable and reconfigurable microfluidic technologies have provided solutions for these limitations through dynamic adaptability.Configurable systems enable post-fabrication customization via modular assembly or boundary modification,offering cost-effective functional versatility.Reconfigurable microfluidics represents a more advanced paradigm,incorporating real-time decision-making and dynamic control through physical/virtual boundary adjustments during operation.These adaptive systems enable precise manipulation of microenvironments for applications ranging from single-cell manipulation to dynamic biochemical synthesis.In this review,a ″static-dynamic boundary″ framework to systematically analyze both technologies was proposed,and the design rationales,operational mechanisms,and implementation strategies were compared.The development history of these two techniques was introduced,and the applications demonstrated their transformative potential in developing intelligent lab-on-chip systems,while technical challenges in standardization and control interfaces were critically assessed.The development trend on integrating smart materials and AI-driven automation to advance next-generation adaptive microfluidic platforms was prospected.