Green prescription is a written prescription aimed at improving health by promoting physical activity and improving diet， with advantages such as high cost-effectiveness， strong feasibility， and minimal harm to patients. The theory of traditional Chinese medicine （TCM） green prescription integrates the health philosophy of "following rule of yin and yang， and adjusting ways to cultivating health"， the exercise philosophy of balancing yin-yang and the five elements， and the dietary philosophy of moderation and balance， which embody core TCM concepts such as treating disease before its onset and harmony between humans and nature. It has also developed traditional exercise practices like Tai Chi， Baduanjin， Wuqinxi， Yi-Gin-Ching， and Qigong， as well as dietary adjustments like medicated diet and herbal wines. However， it is believed that the TCM green prescription currently suffers from insufficient evidence-based research， low patient awareness and acceptance， and weak basic research. Based on this， it is proposed that large-sample clinical trials should be conducted in the future to improve the quality of evidence-based medicine， basic research can be carried out with the help of artificial intelligence and other methods in research design， the hospital information system （HIS） can be used for control at the implementation level， and publicity and patient education can be strengthened through the new media， so as to promote the development and application of the TCM green prescriptions in the field of global health treatment.

This article is based on modern psychology and TCM emotional theory,combined with facial expression recognition technology,to apply deep learning methods to the digital research of TCM emotions to more accurately capture and analyze patients'emotional states.A cross-disciplinary framework was established by synthesizing facial expression-emotion correlations from psychological and TCM perspectives.The methodology included:Data annotation of TCM-defined emotional expressions using standardized coding systems;Facial expression acquisition,spatiotemporal feature extraction and emotion classification through a 3D convolutional neural network(3D CNN).The framework achieved 91.43%accuracy in video-based emotion classification.High-arousal emotional states demonstrated superior recognition performance,with anger showing optimal recall(1.000 0)and F1-score(0.946 3),while surprise attained the highest precision(0.976 0).These findings aligned with TCM pathological characteristic of"anger induces qi ascending,surprise disrupts qi flow".The digital recognition framework for TCM emotional quantification based on facial expression recognition technology exhibits strong alignment with TCM observation diagnosis,providing clinicians with an objective tool to assess the"seven emotions"and elucidating emotion-facial correlations in classical TCM theory.Future research should focus on longitudinal validation across diverse populations and establish development pathways for AI-assisted TCM diagnostic systems.

Objective:To express,purify,prepare antibodies,and analyze the subcellular localization of Toxoplasma gondii thioredoxin 20(Trx20),and to provide the reference for the development of Toxoplasma gondii vaccine.Methods:Bioinformatics-related websites and software were used to perform bioinformatics analysis of the Trx20 protein;specific primers were designed to amplify the target fragment and construct the prokaryotic expression vector;the protein was expressed in vitro and purified;experimental animals were immunized to prepare antibodies;enzyme-linked immunosorbent assay(ELISA)method was used to detect the titer of the polyclonal antibodies;Western blotting method was used to verify the specificity and sensitivity of the antibodies and to determine the natural expression of the protein;immunofluorescence assay(IFA)was used to analyze the subcellular localization of the protein.Results:The bioinformatics analysis results showed that Trx20 protein was a relatively stable hydrophilic protein with a molecular formula of C2172H3412N548O616S20,containing 424 amino acids,a predicted relative molecular mass of 47 700,and a theoretical isoelectric point of 8.55;it was predicted that the protein had one signal peptide,no transmembrane region,contained one domain named"Thioredoxin like Superfamily",and had 35 phosphorylation sites,one N-glycosylation site,and 17 antigenic determinants;in the secondary structure,alpha-helices accounted for 41.51％of the total amino acids,and random coils accounted for 39.86％;the recombinant plasmids pET-28a-Trx20 and pGEX-4T-1-Trx20 were successfully constructed,and the soluble recombinant protein was expressed and purified;polyclonal antibodies were successfully prepared with a titer as high as 1:64 000,and they specifically recognized the endogenous Trx20 protein in Toxoplasma gondii;the subcellular localization results showed that Trx20 protein was widely distributed in the cytoplasm of the parasite.Conclusion:Toxoplasma gondii Trx20 protein is a secretory protein containing phosphorylation/glycosylation modification sites and a thioredoxin domain,and it is localized in the cytoplasm of the parasite.

Traditional scientific research management suffers from problems such as scattered archives,lack of effective dynamic process supervision for projects,weak data analysis capabilities,and low sharing,making it difficult to meet the unified management of multiple hospital areas in medical groups and the independent management of each branch.The group has devel-oped an intelligent scientific research management system based on artificial big data by constructing the framework and designing the content of various demand modules for scientific research management.This system achieves full coverage management of sci-entific research activities,designing interrelated information data networks for scientific research project process management,a-chievement management,academic(specialized)construction management,postdoctoral management,etc.,realizing informa-tionization and refined management of multiple campuses within the group.Analyze the technological values of each hospital,de-partment,and personnel to provide powerful reference for decision-makers.The information-based scientific research manage-ment system is an important guarantee for hospital groups to intelligently manage and efficiently carry out scientific research work.

This article is based on modern psychology and TCM emotional theory,combined with facial expression recognition technology,to apply deep learning methods to the digital research of TCM emotions to more accurately capture and analyze patients'emotional states.A cross-disciplinary framework was established by synthesizing facial expression-emotion correlations from psychological and TCM perspectives.The methodology included:Data annotation of TCM-defined emotional expressions using standardized coding systems;Facial expression acquisition,spatiotemporal feature extraction and emotion classification through a 3D convolutional neural network(3D CNN).The framework achieved 91.43%accuracy in video-based emotion classification.High-arousal emotional states demonstrated superior recognition performance,with anger showing optimal recall(1.000 0)and F1-score(0.946 3),while surprise attained the highest precision(0.976 0).These findings aligned with TCM pathological characteristic of"anger induces qi ascending,surprise disrupts qi flow".The digital recognition framework for TCM emotional quantification based on facial expression recognition technology exhibits strong alignment with TCM observation diagnosis,providing clinicians with an objective tool to assess the"seven emotions"and elucidating emotion-facial correlations in classical TCM theory.Future research should focus on longitudinal validation across diverse populations and establish development pathways for AI-assisted TCM diagnostic systems.

Traditional scientific research management suffers from problems such as scattered archives,lack of effective dynamic process supervision for projects,weak data analysis capabilities,and low sharing,making it difficult to meet the unified management of multiple hospital areas in medical groups and the independent management of each branch.The group has devel-oped an intelligent scientific research management system based on artificial big data by constructing the framework and designing the content of various demand modules for scientific research management.This system achieves full coverage management of sci-entific research activities,designing interrelated information data networks for scientific research project process management,a-chievement management,academic(specialized)construction management,postdoctoral management,etc.,realizing informa-tionization and refined management of multiple campuses within the group.Analyze the technological values of each hospital,de-partment,and personnel to provide powerful reference for decision-makers.The information-based scientific research manage-ment system is an important guarantee for hospital groups to intelligently manage and efficiently carry out scientific research work.

Purpose To investigate the 18F-FDG PET/CT metabolic characteristics and the accuracy of diagnosis in post-traumatic osteomyelitis. Materials and Methods A total of 64 patients with post-traumatic fracture nonunion and suspected infection in Beijing Jishuitan Hospital were retrospectively analyzed. The PET/CT examinations were performed from May 2019 to April 2020. Qualitative and semi-quantitative evaluation methods were used to evaluate the diagnostic accuracy of 18F-FDG PET/CT in post-traumatic osteomyelitis. The diagnostic efficiency was compared among different laboratory indexes,such as erythrocyte sedimentation rate,C-reactive protein and leukocyte. Logistic regression was used to analyze parameters with diagnostic significance. Results Among 64 patients with post-traumatic fracture nonunion,37 were ultimately diagnosed with post-traumatic osteomyelitis. Among them,23 were confirmed through positive microbial cultures during surgery,and 14 were diagnosed based on clinical symptoms and follow-up results. The remaining 27 patients showed no signs of infection based on intraoperative microbial cultures (n=10) or clinical follow-up of more than six months (n=17). PET/CT correctly identified infections in 34 of the 37 infected cases and accurately ruled out infections in 23 of the 27 non-infected cases. The sensitivity,specificity,positive predictive value,negative predictive value and overall diagnostic accuracy of PET/CT were 91.89％,85.19％,89.47％,88.46％ and 89.06％,respectively. The maximum standardized uptake value (SUVmax) of PET/CT semi-quantitative parameter in the infection group (6.23±2.16) was higher than that in the non-infection group (4.24±1.86),showing a statistically significant difference (t=3.864,P<0.01). Logistic regression analysis revealed that SUVmax and C-reactive protein had diagnostic significance for distinguishing between groups,and SUVmax demonstrated higher diagnostic accuracy than C-reactive protein (x2=27.245,P<0.001). Conclusion The metabolic imaging features provided by 18F-FDG PET/CT imaging help to provide a more accurate reference for the diagnosis of post-traumatic osteomyelitis,which is worthy of clinical application.

Purpose To investigate the 18F-FDG PET/CT metabolic characteristics and the accuracy of diagnosis in post-traumatic osteomyelitis. Materials and Methods A total of 64 patients with post-traumatic fracture nonunion and suspected infection in Beijing Jishuitan Hospital were retrospectively analyzed. The PET/CT examinations were performed from May 2019 to April 2020. Qualitative and semi-quantitative evaluation methods were used to evaluate the diagnostic accuracy of 18F-FDG PET/CT in post-traumatic osteomyelitis. The diagnostic efficiency was compared among different laboratory indexes,such as erythrocyte sedimentation rate,C-reactive protein and leukocyte. Logistic regression was used to analyze parameters with diagnostic significance. Results Among 64 patients with post-traumatic fracture nonunion,37 were ultimately diagnosed with post-traumatic osteomyelitis. Among them,23 were confirmed through positive microbial cultures during surgery,and 14 were diagnosed based on clinical symptoms and follow-up results. The remaining 27 patients showed no signs of infection based on intraoperative microbial cultures (n=10) or clinical follow-up of more than six months (n=17). PET/CT correctly identified infections in 34 of the 37 infected cases and accurately ruled out infections in 23 of the 27 non-infected cases. The sensitivity,specificity,positive predictive value,negative predictive value and overall diagnostic accuracy of PET/CT were 91.89％,85.19％,89.47％,88.46％ and 89.06％,respectively. The maximum standardized uptake value (SUVmax) of PET/CT semi-quantitative parameter in the infection group (6.23±2.16) was higher than that in the non-infection group (4.24±1.86),showing a statistically significant difference (t=3.864,P<0.01). Logistic regression analysis revealed that SUVmax and C-reactive protein had diagnostic significance for distinguishing between groups,and SUVmax demonstrated higher diagnostic accuracy than C-reactive protein (x2=27.245,P<0.001). Conclusion The metabolic imaging features provided by 18F-FDG PET/CT imaging help to provide a more accurate reference for the diagnosis of post-traumatic osteomyelitis,which is worthy of clinical application.

OBJECTIVE Cognitive deficit is a com-mon comorbidity in temporal lobe epilepsy(TLE)and that is not well controlled by current therapeutics.Currently,how epileptic seizure affects cognitive performance remains largely unclear.The subiculum is the major out-put of the hippocampus,which projects to entorhinal cor-tex and other more distinct brain regions.Physiologically,the subiculum codes spatial working memory and naviga-tion information including place,speed,and trajectory.Importantly,prior studies have noted the importance of the subiculum in the beginning,spreading,and generaliz-ing process of hippocampal seizure.How seizure-activated neurons in subiculum participate in cognitive impairment remains largely elusive.METHODS In this study,we sought to label the subicular seizure-activated c-fos+ neu-rons with a special promoter with enhanced synaptic activity-responsive element E-SARE in the subiculum,combined with chemogenetics and designer receptors exclusively activated by designer drugs(DREADDs),Ca2+ fiber photometry approaches,and behavioral tasks,to reveal the role of these neurons in cognitive impairment in epilepsy.RESULTS We found that chemogenetic inhibi-tion of subicular seizure-tagged c-fos+ neurons(mainly CaMK Ⅱ α+ glutamatergic neurons)alleviates seizure generalization and improves cognitive performance in the hippocampal CA3 kindling TLE model.While inhibition of seizure-labeled c-fos+ GABAergic interneuron shows no effect on seizure and cognition.As a comparison,che-mogenetic inhibition of the whole subicular CaMK Ⅱ α+ neuron impairs cognitive function in na?ve mice in basal condition.Notably,inhibition of subicular seizure-tagged c-fos+ neurons enhances the recruitment of cognition-responsive c-fos+ neurons via increasing neural excitability during cognition tasks.CONCLUSION Our results dem-onstrate that subicular seizure-activated c-fos+ neurons contribute to cognitive impairment in TLE,suggesting sei-zure-tagged c-fos+ neurons as the potential therapeutic target to alleviate cognitive impairment in TLE.

Abstract Comprehensive sexuality education is an important part of quality education, primary and secondary schools are the most suitable places for sex education. This paper sorts out the current status of sexuality education for primary and secondary school students in developed countries after presenting the overall significance of school based sexuality education, and further points out the problems and urgency of sexuality education for primary and secondary school students in China. It also put forward the way to new directions for advocacy, including the comphrehensive sexuality education curriculum system, training of sexuality education teachers, the positive and active role of families, as well as social and community support for sexuality education in schools.