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.

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.

Myopia is a common eye disease among children and adolescents, and it is also a major and common public health problem for children and adolescents worldwide. Although the myopia rate among children and adolescents in different provinces , cities , and regions varies , the incidence of myopia is generally high , showing a trend of high incidence and younger age. Myopia in children and adolescents is closely related to sleep conditions . The sleep time of most children and adolescents in China does not reach the recommended length of time for this age group, and their sleep quality is poor, which affects their study and life. The biological connection and molecular mechanism between sleep and myopia are hot topics in clinical research . This article reviews the epidemiological characteristics of myopia and sleep status in children and adolescents , as well as the biological mechanisms between sleep and myopia , with the aim of providing a theoretical basis for preventing myopia in children and adolescents.

Electroencephalogram (EEG) is a non-invasive, high temporal-resolution technique for monitoring brain activity. However, affected by the volume conduction effect, EEG has a low spatial resolution and is difficult to locate brain neuronal activity precisely. The surface Laplacian (SL) technique obtains the Laplacian EEG (LEEG) by estimating the second-order spatial derivative of the scalp potential. LEEG can reflect the radial current activity under the scalp, with positive values indicating current flow from the brain to the scalp (“source”) and negative values indicating current flow from the scalp to the brain (“sink”). It attenuates signals from volume conduction, effectively improving the spatial resolution of EEG, and is expected to contribute to breakthroughs in neural engineering. This paper provides a systematic overview of the principles and development of SL technology. Currently, there are two implementation paths for SL technology: current source density algorithms (CSD) and concentric ring electrodes (CRE). CSD performs the Laplace transform of the EEG signals acquired by conventional disc electrodes to indirectly estimate the LEEG. It can be mainly classified into local methods, global methods, and realistic Laplacian methods. The global method is the most commonly used approach in CSD, which can achieve more accurate estimation compared with the local method, and it does not require additional imaging equipment compared with the realistic Laplacian method. CRE employs new concentric ring electrodes instead of the traditional disc electrodes, and measures the LEEG directly by differential acquisition of the multi-ring signals. Depending on the structure, it can be divided into bipolar CRE, quasi-bipolar CRE, tripolar CRE, and multi-pole CRE. The tripolar CRE is widely used due to its optimal detection performance. While ensuring the quality of signal acquisition, the complexity of its preamplifier is relatively acceptable. Here, this paper introduces the study of the SL technique in resting rhythms, visual-related potentials, movement-related potentials, and sensorimotor rhythms. These studies demonstrate that SL technology can improve signal quality and enhance signal characteristics, confirming its potential applications in neuroscientific research, disease diagnosis, visual pathway detection, and brain-computer interfaces. CSD is frequently utilized in applications such as neuroscientific research and disease detection, where high-precision estimation of LEEG is required. And CRE tends to be used in brain-computer interfaces, that have stringent requirements for real-time data processing. Finally, this paper summarizes the strengths and weaknesses of SL technology and envisages its future development. SL technology boasts advantages such as reference independence, high spatial resolution, high temporal resolution, enhanced source connectivity analysis, and noise suppression. However, it also has shortcomings that can be further improved. Theoretically, simulation experiments should be conducted to investigate the theoretical characteristics of SL technology. For CSD methods, the algorithm needs to be optimized to improve the precision of LEEG estimation, reduce dependence on the number of channels, and decrease computational complexity and time consumption. For CRE methods, the electrodes need to be designed with appropriate structures and sizes, and the low-noise, high common-mode rejection ratio preamplifier should be developed. We hope that this paper can promote the in-depth research and wide application of SL technology.

ObjectiveTo investigate the protective effect and mechanism of action of flavonoid combination of Alpiniae Officinarum Rhizoma （A. officinarum） against Helicobacter pylori （H. pylori） gastritis in mice. MethodsAfter acclimatization for one week， 56 SPF-grade healthy C57BL/6J mice were gavaged with mixed antibiotics for three consecutive days. They were randomly divided into a normal group， model group， positive drug group （triple therapy group）， and low- and high-dose groups （100， 200 mg·kg^-1） of flavonoid combination of A. officinarum. The H. pylori gastritis mice model was established by gavage with H. pylori bacterial suspension in each group except for the normal group. After successful modeling， mice were administrated with corresponding drugs once a day for two weeks. Hematoxylin-eosin （HE） staining was used to observe the pathological changes in gastric tissue. Rapid urease test paper was used to detect the positive rate of H. pylori. Silver staining was used to observe the H. pylori adherence on the surface of gastric tissue. Immunohistochemistry was used to detect the protein expression of interleukin-8 （IL）-8 and myeloid differentiation factor （MyD88） in gastric tissue. The serum levels of IL-6， tumor necrosis factor-α （TNF-α）， IL-8， and IL-1β were detected by enzyme-linked immunosorbent assay （ELISA）. The expressions of phosphatidylinositol 3-kinase/protein kinase B （PI3K/Akt） protein were detected by Western blot. ResultsCompared with those in the normal group， mice in the model group had lower gastric weight coefficients， higher pH of gastric juice， 100% H. pylori infection rate， and significantly changed gastric histopathology. The expressions of IL-8 and MyD88 proteins in the gastric tissue of mice in the model group were significantly elevated， and the serum levels of inflammatory factors IL-6， TNF-α， IL-8， and IL-1β were significantly up-regulated in mice. Compared with that in the model group， the gastric weight coefficient of mice in each treatment group of the flavonoid combinations of A. officinarum was elevated （P<0.01）， and the pH of gastric juice was reduced （P<0.01）. The infection rate of H. pylori was reduced. The expressions of IL-8 and MyD88 proteins in the gastric tissue of mice in the treatment groups were significantly reduced （P<0.01）， and the serum levels of inflammatory factors IL-6， TNF-α， IL-8， and IL-1β were significantly reduced in a dose-dependent manner （P<0.01）. The flavonoid combinations of A. officinarum down-regulated the expression of PI3K and Akt proteins in H. pylori gastritis-infected cells （P<0.01）. ConclusionThe protective effect of flavonoid combinations of A. officinarum against H. pylori gastritis is associated with the inhibition of H. pylori infection rate and regulation of PI3K/Akt signaling pathway， resulting in inhibiting the release of inflammatory factors.

ObjectiveTo explore the current situation of forensic ethics practice and education by designing a questionnaire on forensic ethics， with a view to exploring the path of forensic ethics education construction. MethodsA total of 667 valid questionnaires were collected using the online survey method， basically covering various regions across the country and all sub-specialties of forensic medicine. Descriptive analysis was used to analyze the relevant data. ResultsMost practitioners had relevant ethical reflections in the process of forensic practice. 69.12% of the respondents indicated that they had studied the relevant rules， but approximately half stated that there were no corresponding ethical norms or standard operating manuals. The specific behaviors violating ethics in different units were diverse. 23.04% of the respondents reported that they had encountered unethical behaviors， but only 4.9% of them reported such violations. In terms of forensic ethics education， 87.75% of the respondents believed that there were issues with the current model of forensic ethics education. Meanwhile， the respondents showed a high degree of recognition for receiving forensic ethics education， with 84.15% of respondents expressing willingness to participate in relevant courses. More than half of respondents were willing to participate in forensic ethics education during undergraduate studies， new employee training， and regular post-employment training. ConclusionCurrently， there is a problem of ethical neglect in forensic work in China. Combining ethics courses with professional courses at the practitioner training stage and providing regular training at the practice stage are effective measures to popularize forensic ethics knowledge， enhance ethical awareness， and improve the quality of practice.

Cell models can simulate a variety of life states and disease developments, including single cells, two-dimensional (2D) cell cultures, three-dimensional (3D) multicellular spheroids, and organoids. They are essential tools for addressing complex biochemical questions. With continuous advancements in biological and cellular analysis technologies, in vitro cellular models designed to answer scientific questions have evolved rapidly. Early in vitro models primarily relied on 2D systems, which failed to accurately replicate the complex cellular compositions and microenvironmental interactions observed in vivo, let alone support sophisticated investigations into cellular biological functions. Subsequent improvements in cell culture techniques led to the development of 3D culture-based models, such as cellular spheroids. The advent of pluripotent stem cell technology further advanced the development of organoid systems, which closely mimic human organ development. Compared to traditional 2D models, both 3D cellular models and organoids offer significant advantages, including personalization and enhanced physiological relevance, making them particularly suitable for exploring molecular mechanisms of disease progression, discovering novel cellular and biomolecular functions, and conducting related studies. The imaging analysis of common cellular models primarily employs labeling-based methods for in situ imaging of targeted genes, proteins, and small-molecule metabolites, enabling further research on cell types, states, metabolism, and drug efficacy. However, these approaches have drawbacks such as poor labeling specificity and complex experimental procedures. By using cells as experimental models, mass spectrometry technology combined with morphological analysis can reveal quantitative changes and spatial distributions of various biological substances at the spatiotemporal level, including metabolites, proteins, lipids, peptides, drugs, environmental pollutants, and metals. This allows for the investigation of cell-cell interactions, tumor microenvironments, and cellular bioinformational heterogeneity. The application of these cutting-edge imaging technologies generates vast amounts of cellular data, necessitating the development of rapid, efficient, and highly accurate image data algorithms for precise segmentation and identification of single cells, multi-organelle structures, rare cell subpopulations, and complex cellular morphologies. A critical focus lies in creating deep learning models and algorithms that enhance the accuracy of cellular visualization. At the same time, establishing more robust data integration tools is essential not only for analyzing and interpreting outputs but also for effectively uncovering the biological significance of spatially resolved mass spectrometry data. Developing a cell imaging platform with high versatility, operational stability, and specificity to enable data interoperability will significantly enhance its utility in clinical research, thereby advancing investigations into disease molecular mechanisms and supporting precision diagnostics and therapeutics. In contrast to genomic, transcriptomic, and proteomic information, the metabolome can rapidly respond to external stimuli and cellular physiological changes within a short timeframe. This rapid and precise reflection of ongoing cellular state alterations has positioned spatial metabolomics as a pivotal approach for exploring the molecular mechanisms underlying physiological and pathological processes in cells, tissues, and organisms. In this review, we summarize research on cell imaging based on mass spectrometry technologies, including the selection and preparation of cell models, morphological analysis of cell models, spatial omics techniques based on mass spectrometry, mass cytometry, and their applications. We also discuss the current challenges and propose future directions for development in this field.