Objective: To investigate the prevalence and associated factors of depressive symptoms among junior and senior high school students in Beijing from 2019 to 2023, in order to provide a scientific basis for interventions targeting high risk groups. Methods: From 2019 to 2023, a stratified cluster random sampling method was used to select 88 927 junior and senior high school students from 16 districts in Beijing. The Center for Epidemiologic Studies Depression Scale(CES-D) was conducted to assess depressive symptoms. The Chi square test was used to compare the detection rates of depressive symptoms among different student groups, and the trend Chi square test was employed for trend analysis of detection rates across the years. Multivariate Logistic regression analysis was applied to examine the association between the detection of depressive symptoms and related factors among junior and senior high school students. Results: From 2019 to 2023, the prevalence rates of depressive symptoms among junior and senior high school students in Beijing were 20.45%, 18.19%, 16.64%, 17.89% and 18.17%, respectively, with an overall downward trend ( χ 2 trend =27.51, P <0.01). Multivariate Logistic regression analysis revealed that after adjusting for gender, monitoring year, educational stage,family structure,boarding status and has taken a medical leave of absence in the past year unhealthy dietary behaviors ( OR=1.80, 95%CI =1.73-1.87), physical inactivity ( OR=1.24, 95%CI =1.19-1.29), try smoking ( OR=1.46, 95%CI =1.35-1.58), try alcohol( OR=1.96, 95%CI =1.88-2.05), Internet addiction ( OR=3.88, 95%CI =3.57-4.22), and adverse ear related behavior ( OR=1.82, 95%CI =1.71-1.93) were all associated with an increased risk of depressive symptoms among junior and senior high school students (all P <0.05). Conclusions The prevalence depression symptoms among middle school students in Beijing showed a fluctuating downward trend from 2019 to 2023. Targeted interventions should be adopted to reduce the occurrence of depression symptoms among junior and senior high school students.

Objective: To understand the trends of classroom lighting and illumination of primary and secondary schools in Beijing from 2016 to 2023, so as to provide a scientific basis for targeted improvement measures. Methods: A sampling survey was conducted on the lighting and illumination indicators of 8 390 classrooms in primary and secondary schools in Beijing from 2016 to 2023. The survey included classroom daylight factor, window to floor area ratio, average illuminance and illuminance uniformity on the desks, average illuminance and illuminance uniformity on blackboards, as well as classroom lighting and blackboard illumination sources. Intergroup comparisons were performed using the Kruskal-Wallis H test and the Chi square test, and Spearman correlation analysis was used to examine the trend of classroom lighting and illumination changes. Results: Except the window to floor area ratio, the measured values and compliance rates of all lighting and illumination indicators showed an overall upward trend from 2016 to 2023 (daylight factor r = 0.27, χ 2 trend =206.80, average illuminance on the desk surface r =0.30, χ 2 trend =87.97, illuminance uniformity on the desk surface r =0.14, χ 2 trend =73.59, average illuminance on the blackboard r =0.33, χ 2 trend =477.43, illuminance uniformity on the blackboard r = 0.09, χ 2 trend =50.76) (all P ＜0.01). The lighting and illumination indicators of classrooms (included classroom daylight factor, average illuminance and illuminance uniformity on the desks, average illuminance and illuminance uniformity on blackboards) in urban schools, primary schools, and secondary schools from 2016 to 2023 showed an upward trend (urban r =0.23-0.40, χ 2 trend =88.66-392.18; primary school r =0.12-0.36, χ 2 trend =39.50-281.44; secondary schools r =0.06-0.31, χ 2 trend =11.79-213.73) (all P ＜ 0.01 ). The illuminance uniformity on the blackboard in suburban schools showed a downward trend ( r = -0.09, χ 2 trend =31.53, both P ＜0.01). The illuminance uniformity on the desk surface in suburban schools showed no significant change ( r =0.03, χ 2 trend =1.23, both P ＞0.05). The other indicators showed an upward trend (daylight factor r =0.28, χ 2 trend =40.69, average illuminance on the desk surface r =0.24, χ 2 trend =16.35, average illuminance on the blackboard r =0.25, χ 2 trend =118.05, all P ＜0.01). The trends of classroom and blackboard illumination sources were that fluorescent lamps decreased year by year and LED lamps increased by year (classroom illumination sources χ 2 trend =1 059.82, blackboard illumination sources χ 2 trend =1 070.25, both P ＜0.01). Conclusions The classroom lighting and illumination in primary and secondary schools in Beijing has shown an overall improving trend from 2016 to 2023. However, problems remain, such as limited improvement of illuminance uniformity indicators, late start and poor effect of reconstruction in suburban schools. Further improvements are still needed.

Objective: To investigate the prevalence of undernutrition and its associated factors among left behind and non left behind primary and secondary school students in the Nutrition Improvement Program for Rural Compulsory Education Students (NIPRCES) areas of central and western China, so as to provide evidence for improving the nutritional status of children and adolescents. Methods: A survey was conducted among 123 782 students selected by random cluster sampling method in grades 3-9 from NIPRCES in central (Hebei, Shanxi, Heilongjiang, Jilin, Anhui, Jiangxi, Henan, Hunan, Hubei, and Hainan) and western (Gansu, Guangxi, Inner Mongolia, Ningxia, Tibet, Shaanxi, Guizhou, Sichuan, Xinjiang, the Xinjiang Production and Construction Corps, Yunnan, Qinghai, and Chongqing) China in 2023. Anthropometric measurements and questionnaires were used to assess nutritional and dietary status. The prevalence of undernutrition was compared between left behind and non left behind students by Chi square test, and associated factors were analyzed by three level Logistic mixed effects model. Results: The prevalence of undernutrition was 8.5% (4 326) in left behind students and 8.1% (5 905) in non left behind students. Three level Logistic mixed effect model analysis showed that whether left behind or non left behind, the undernutrition rates of primary and secondary students in western regions were higher than those of students in central regions [ OR (95% CI )=1.72(1.57-1.87),2.25(2.07- 2.43 )]; the undernutrition risk was lower for those whose fathers had a cultural level of high school or above [ OR (95% CI )=0.69(0.62-0.77),0.90(0.82-0.98)] or junior high school [ OR (95% CI )=0.72(0.66-0.79),0.92(0.85-0.99)] compared to those with primary school or below; picky eating or selective eating increased the risk of undernutrition [ OR (95% CI )=2.36(2.07-2.68),2.28(2.04-2.55)], and primary and secondary school students without nutritional content in health education classes had higher rates of undernutrition [ OR (95% CI )=1.12(1.03-1.23),1.09(1.01-1.17)](all P <0.05). Conclusion The prevalence of undernutrition is slightly higher in left behind primary and secondary students than in non left behind primary and secondary students in central and western NIPRCES areas, with variations across different characteristics.

Objective: To analyze the trends of the frequency of meat, egg, and milk consumption among rural primary and junior high school students in central and western China covered by the Nutrition Improvement Program for Rural Compulsory Education Students (NIPRCES) from 2015 to 2023, so as to provide basis for formulating more targeted nutrition intervention policies and health education strategies. Methods: Using data from six rounds of monitoring and evaluation (2015-2021 and 2023), the study included 323 870 students from grade 3 to 9 across 22 provinces (autonomous regions and municipalities) in central and western China. The consumption frequencies of meat, egg, and milk over the past week were collected via questionnaires. The Cochran-Armitage trend test was used to analyze temporal trends, and multivariable Logistic regression models were employed to analyze factors associated with the frequency of meat, egg and milk consumption and to test for interaction effects between the year and gender, region, and grade level. Results: From 2015 to 2023, the proportion of students consuming meat, egg, and milk ≥1 time/day increased from 23.20 %, 10.71%, and 0.74% to 35.53%, 22.09%, and 26.63%, respectively. Trend tests indicated a significant upward trend for the daily intake of all three food categories for meat, egg and milk over the years ( Z =67.18, 64.90, 93.14, all P <0.01). Multivariable Logistic regression analysis showed that the daily meat intake was lower in the central region than in the western region ( OR=0.77, 95%CI =0.76-0.78), whereas the daily intake of eggs ( OR=1.19, 95%CI =1.17-1.22) and milk ( OR= 1.27 , 95%CI =1.24-1.29) was higher in the central region (all P <0.05). Compared with grade 3-4 students, junior high school students had lower daily intake of meat, eggs, and milk≥1 time/day ( OR =0.95, 0.77, 0.77, all P <0.05), with a declining trend as grade increased. Girls also had lower daily intake of meat, eggs, and milk ≥1 time/day than boys ( OR =0.95，0.93，0.91, all P < 0.05). Significant interactions were observed between year and region, as well as between year and grade (all P <0.05). Conclusion From 2015 to 2023, the NIPRCES improved the intake level of among rural students, but the situation of relatively insufficient intake of egg and milk among females, junior high school students and those in the western region still exists.

Neurological disorders, including Alzheimer’s disease (AD), Parkinson’s disease (PD), cerebral ischemia, and multiple sclerosis (MS), impose an escalating global health burden and remain largely incurable. These disorders arise from multifactorial and interconnected pathological processes, such as chronic neuroinflammation, oxidative stress, protein misfolding and aggregation, demyelination, and neurovascular dysfunction. Despite substantial advances in elucidating disease-associated molecular mechanisms, current therapeutic strategies are predominantly symptomatic and fail to effectively halt or reverse disease progression. This limitation highlights the urgent need to identify endogenous regulatory molecules capable of coordinating neuronal survival, synaptic maintenance, inflammatory control, and tissue repair within the central nervous system (CNS). Pleiotrophin (PTN) is a heparin-binding, growth-associated cytokine that has emerged as a key regulator of neural development, plasticity, and regeneration. Structurally, PTN contains multiple high-affinity heparin-binding domains that facilitate interactions with extracellular matrix components and cell surface proteoglycans, enabling spatially restricted and context-dependent signaling. Through these molecular properties, PTN functions as a multifunctional organizer of neural growth, plasticity, and tissue remodeling across developmental and adult stages. Its diverse biological effects are executed through a multi-receptor signaling system that integrates extracellular cues with intracellular programs governing cellular survival, migration, and differentiation. Notably, PTN displays a highly dynamic and cell type-specific expression pattern in the central nervous system, being enriched in neural progenitor cells during development and later restricted to discrete neuronal populations, neural stem cells, and non-neuronal niche cells—including astrocytes, pericytes, and vascular endothelial cells—which serve as critical sources of PTN under physiological and pathological conditions. PTN expression is tightly regulated during development and exhibits pronounced plasticity in response to pathological stimuli. Under physiological conditions, PTN is transiently expressed during critical windows of neural growth and synaptogenesis, supporting neuron-glia interactions and myelin formation. In contrast, in pathological contexts such as amyloid β-protein (Aβ) accumulation in AD, dopaminergic neuron degeneration in PD, demyelination in MS, and ischemic brain injury, PTN expression is frequently dysregulated, suggesting an active role in disease-associated remodeling rather than a passive bystander effect. Importantly, accumulating evidence indicates that PTN exerts a dual and context-dependent influence on neurological disorders. On the one hand, aberrant PTN signaling may contribute to maladaptive responses, including sustained glial activation, dysregulated neuroinflammation, extracellular matrix remodeling, and enhanced Aβ deposition. On the other hand, PTN displays robust neuroprotective and reparative functions by promoting neuronal survival, enhancing oligodendrocyte maturation and remyelination, and stimulating post-injury angiogenesis, thereby facilitating tissue repair and functional recovery. At the mechanistic level, PTN signaling is characterized by extensive cross-talk among receptor-dependent pathways. Activation of anaplastic lymphoma kinase (ALK) triggers canonical PI3K-AKT-mTOR and MAPK cascades that support neuronal survival and axonal integrity. PTN binding to protein tyrosine phosphatase receptor type Z1 (PTPRZ1) induces conformational inhibition of its phosphatase activity, resulting in increased phosphorylation of downstream effectors such as β-catenin, Fyn, and Src, which regulate neuronal migration and synaptic stabilization. Syndecan-3 (SDC3) functions as both a co-receptor and an independent signaling mediator by capturing extracellular PTN, amplifying ALK- and PTPRZ1-dependent signaling, and directly modulating cytoskeletal dynamics through PKC and ERK pathways. In parallel, PTN interaction with αVβ3 integrin contributes to remodeling of the neurovascular niche, linking angiogenesis with neurogenesis and neural repair. From a translational perspective, therapeutic strategies targeting PTN can be broadly classified into 3 categories: direct enhancement of PTN signaling through exogenous protein supplementation or gene therapy-mediated upregulation, pharmacological modulation of PTN-associated receptor pathways and downstream signaling nodes, and exploitation of PTN as a dynamic biomarker to inform disease stratification and therapeutic responsiveness. These complementary approaches underscore the growing interest in PTN-centered interventions across a spectrum of neurological disorders. In summary, PTN functions not merely as a classical trophic factor but as a central signaling hub integrating inflammatory regulation, neural regeneration, and vascular remodeling within the CNS. This review aims to synthesize current insights into PTN’s molecular architecture, multi-receptor signaling mechanisms, and disease-specific functions, and to highlight emerging therapeutic strategies targeting PTN. By conceptualizing PTN as a dynamic modulator of neuronal resilience rather than a static biomarker, we propose that precise modulation of PTN signaling may offer promising avenues for therapeutic development in neurodegenerative and neuroinflammatory diseases.

Objective: To systematically evaluate the performance of machine learning (ML) models in predicting non suicidal self injury (NSSI) behavior among adolescents, providing an evidence based foundation for the development of clinically applicable risk assessment tools. Methods: A comprehensive search was conducted in PubMed, Embase, Web of Science, CNKI, and Wanfang databases for relevant studies from their inception to July 21, 2025. The Prediction Model Risk of Bias Assessment Tool (PROBAST) was used to evaluate the methodological quality of the included studies. Stata 18 software was used to calculate the area under the receiver operating characteristic curve (AUC) of the models, and publication bias assessment, sensitivity analysis, and Egger s test were performed. Results: The total of 12 studies (42 prediction models) involving 58 070 adolescents were included. There were 15 machine learning algorithms in total, among which Random Forest, Logistic Regression, XGBoost, and Support Vector Machines were the most frequently utilized. The most common predictors were gender (female), family function, depression, emotion regulation, and age. All 12 included studies exhibited a high risk of bias. The pooled AUC was 0.80 (95% CI =0.78-0.82), although heterogeneity was substantial ( I 2=95.8%, P <0.01). Sensitivity analysis confirmed the robustness of these findings (no overlap in 95% CI ), while Egger s test indicated the presence of publication bias ( P <0.05). Conclusions Machine learning demonstrates potential in the risk prediction of adolescent NSSI, but existing models have a high risk of bias. Future research should focus on improving methodological quality and optimizing model reliability through rigorous external validation.

Objective: To develop a RHCE genotyping assay based on kompetitive allele-specific PCR (KASP) and assess its clinical accuracy for RhCE blood group determination. Methods: KASP primers were designed to interrogate three RHCE loci: the 109 bp insertion/deletion in intron 2, c. 307T>C, and c. 676C>G. A total of 1 194 RhD-positive inpatients from Chengdu were typed by both KASP genotyping and manual tube serology. Discordant samples (n=10) were retested by both methods and further resolved by Sanger sequencing. An additional 377 cases were tested for the c. 48C>G locus to evaluate the predictive accuracy of individual loci and combined locus testing for RhC antigen. Results: Genotyping concordance with serology was 100.0% for both the c. 676C>G locus (RhE/Rhe) and the c. 307T>C locus (Rhc). For RhC prediction using the 109 bp insertion, overall accuracy was 99.7% (1 191/1 194); the 3 discordant cases were confirmed by Sanger sequencing to be false negatives attributable to 109 bp deletion in intron 2. Testing the c. 48C>G allele for RhC prediction yielded 7 false positives, with an accuracy of 98.1% (370/377). RhC antigen status was determined by combining the 109 bp insertion and the c. 48C allele. After excluding 10 samples with inconsistent results between the two loci, the accuracy reached 100% in the remaining 367 samples. When both loci were applied in combination, accuracy reached 100% in the 367 cases with concordant results. Among the 1 194 patients, CCee (45.8%) and CcEe (31.7%) were the most common RhCE phenotypes. The e antigen had the highest positivity rate (92.2%), and the Ce haplotype was the most frequent (66.9%). Conclusion: The KASP-based RHCE genotyping method achieves high accuracy for clinical RhCE typing. Combining the 109 bp insertion/deletion with the c. 48C allele significantly improves RhC antigen prediction compared with either locus alone. This method was applied to RhCE genotyping of 1 194 RhD-positive inpatients in Chengdu, providing local RhCE phenotype and haplotype distribution data to support RhCE-matched transfusion practice.

Health economics evidence plays an important role in linking clinical value evidence with health resource allocation decisions in the development of clinical practice guidelines. It can not only effectively balance clinical effectiveness and economic feasibility but also avoid forming "idealized" recommendations that are detached from the affordability of the healthcare system or the burden-bearing capacity of patients. To promote guideline developers to use health economics evidence more standardizedly and fully, this paper conducts an in-depth analysis of the current application status, existing challenges, access channels, and application processes of health economics evidence in current guidelines, and on this basis, puts forward considerations and suggestions for strengthening and standardizing the application of health economics evidence in China's clinical practice guidelines.

Objective To investigate the epidemiological survey of pulmonary Aspergillus infection in a district of Hefei City, Anhui Province, from 2019 to 2023. Methods The data of 302 patients who attended and were treated in the respiratory department, thoracic surgery department, oncology department, tuberculosis department and RICU ward of Anhui Chest Hospital from January 2019 to September 2023 were selected, and patients with Aspergillus infections were taken as the observation group, patients with Candida infections were taken as the control group, and bacterial infections were taken as the blank group. The general information of patients, pre-treatment infection, underlying diseases, and use of antifungal drugs were analyzed. Compare the data of observation group and control group, and analyze the risk factors affecting pulmonary Aspergillus infection. Results Pulmonary Aspergillus infection 100 cases, accounting for 33.11%. Pulmonary Candida infection was 80 cases, accounting for 26.49%. The other 122 cases were other lung diseases, accounting for 40.40%. The most common causative agent of pulmonary Aspergillus infection was Aspergillus fumigatus (57.00%), cough, sputum and occasional blood were found in most of the patients (88.00%), most of the lesions were located in the right upper lobe of the lungs (55.00%), and most of the single or multiple cavities were seen on imaging (47.00%). Specimens mostly originated from the deep airways of hospitalized patients and there was a predominance of male patients. Risk factors for pulmonary Aspergillus infection were history of hospital transfer, ICU admission, mechanical ventilation, extracorporeal catheterization (intravenous catheter and urinary catheter), history of surgery within 15 days, history of diabetes mellitus, history of respiratory chronic disease, history of antifungal prophylaxis and abnormal serum indicators. History of hospital transfer (OR=2.951, P=0.008), history of diabetes mellitus (OR=5.073, P=0.018), history of chronic respiratory disease (OR=7.523 , P=0.028), extracorporeal catheterization (OR=3.142, P=0.022), and history of anti-fungal prophylaxis (OR=6.334, P<0.001) were Aspergillus pulmonaryis infection independent risk factors for infection. Conclusion Aspergillus fumigatus and Aspergillus flavus are the main pathogens of pulmonary Aspergillus infections in the region, and a history of nosocomial transfer, extracorporeal tubes, diabetes mellitus, chronic respiratory disease, and antifungal prophylaxis are independent risk factors for pulmonary Aspergillus infections.