Objective: To analyze the school tuberculosis (TB) outbreaks and preventive treatment in Hefei from 2022 to 2024, so as to provide reference for TB prevention and control in schools. Methods: Data were collected on all school based TB outbreaks occurring during 2022-2024 in Hefei, defined as ≥2 epidemiologically linked TB cases within the same school during a single semester. Statistical analyses were performed using the Chi square test. Results: Close contacts exhibited significantly higher TB incidence (2.88%) and latent mycobacterium tuberculosis infection (LTBI) rates (13.80%) in the school TB outbreaks, compared to non close contacts (0.12% and 2.63%, respectively). Among close contacts, secondary school students showed lower TB incidence (0.48%) and LTBI prevalence (3.42%) than both primary school or younger children (0.68%, 6.95%) and college students ( 0.78% , 6.50%), with statistically significant differences ( χ 2=360.91, 6.37; 791.71, 102.03, all P <0.05). The proportion of LTBI individuals recommended for preventive therapy was higher in primary school or younger groups (98.59%) than in secondary (95.25%) or college students (86.34%) ( χ 2=25.86, P <0.01). However, among those recommended, close contacts had higher uptake (85.82%) and completion rates (87.25%) of preventive therapy than non close contacts (69.63% and 70.57%); similarly, secondary school students demonstrated higher uptake (91.21%) and completion rates (86.45%) compared to primary school or younger (88.57%, 83.87%) and college students (57.28%, 64.08%) ( χ 2=30.52, 26.72; 125.17, 38.84, all P <0.01). Subsequent TB incidence among LTBI close contacts (13.30%) and among those who did not complete preventive therapy (22.73%) were significantly higher than among non close contacts (2.80%, 2.41%), respectively ( χ 2=32.19, 13.87, both P <0.05). Conclusions In school TB outbreaks, close contacts face higher LTBI prevalence and subsequent TB risk than non close contacts. College students show notably low adherence to preventive therapy. It is necessary to take targeted measures to improve the compliance of preventive measures among students.

ObjectiveTo investigate the functional role and underlying molecular mechanisms of fumarylacetoacetate hydrolase （FAH） in the progression of glioblastoma （GBM）. MethodsDifferential expression analysis was performed on the TCGA-GBM， GSE4290， and GSE116520 datasets. Weighted gene co-expression network analysis （WGCNA） was used to identify key modules， and Cox regression and risk modeling were used to screen prognostic genes. Immune infiltration analysis of prognostic genes was carried out by using single-cell RNA sequencing panels. The clinical expression signature of FAH in GBM was analyzed in the TCGA and HPA databases. The functional role of FAH was validated by in vitro and in vivo experiments， and pathway analysis was performed to explore the underlying mechanisms. ResultsA total of 152 overlapping genes were identified across the three GBM datasets （P<0.05）. WGCNA revealed that the turquoise module was most strongly associated with tumor purity， stromal score， immune score， and ESTIMATE score （P<0.001）. Compared with normal tissues， three prognostic genes （CTSD， FAH， and THBD） were upregulated in GBM and correlated with immune infiltration （P<0.05）. FAH mRNA and protein levels were elevated in GBM tissues relative to normal tissues， and its expression was significantly associated with age stratification and TP53 mutation （P<0.05）. CCK-8 assay results showed that， compared with the shNC group， the proliferative activity of GBM cells in the shFAH group was reduced （P<0.001）. Transwell migration and invasion assays demonstrated that， relative to the shNC group， the numbers of migrated and invaded cells in the shFAH group decreased （P<0.05）. Western blot analysis revealed that the protein expression levels of PI3K， p-AKT， and p-mTOR in the shFAH group decreased compared with those in the shNC group （P<0.05）. In vivo subcutaneous xenograft experiments further confirmed that tumor volume and weight significantly decreased in the shFAH group compared with the shNC group （P<0.001）. ConclusionFAH promotes GBM progression by activating the PI3K/AKT/mTOR signaling pathway and may serve as a potential therapeutic target for GBM.

Atherosclerosis (AS) remains the core pathological basis underlying the high incidence and high rates of mortality and disability associated with cardiovascular disease (CVD) worldwide. Its essence is not merely lipid deposition, but rather an immune-mediated disease of the vascular wall characterized by an interplay of lipid metabolism disorders and chronic inflammation, with damage to vascular endothelial cells serving as the initiating event. As the disease progresses, it involves complex synergistic interactions among various cellular components, including endothelial cells, macrophages, and inflammatory cells, ultimately leading to plaque formation, instability, and even fatal thrombotic events. In recent years, the central driving role of lipid metabolic reprogramming in the progression of AS has garnered increasing attention from the scientific community. Among the vast array of lipid molecules, long-chain fatty acids (LCFAs) have become a primary focus of research due to their exceptional physiological functions. Traditional views have primarily emphasized the basic physiological functions of LCFAs: serving as highly efficient energy substrates through mitochondrial β-oxidation and acting as key structural components of cellular phospholipid membranes. However, emerging evidence clearly indicates that the functions of LCFAs extend far beyond those of mere metabolic fuel. They also act as potent bioactive signaling molecules, playing an indispensable multidimensional role in the pathogenesis of AS. Equally noteworthy and representing a paradigm shift in cardiovascular research is the emerging theory of the “gut-heart axis”. This theoretical framework views the human gut microbiota—comprising trillions of microorganisms—as a critical and metabolically active “bioreactor”. A wealth of clinical and multi-cohort epidemiological studies have conclusively demonstrated that imbalances in the composition and function of the gut microbiota are highly correlated with the clinical risk and severity of AS. Within this axis, the gut microbiota serves as the primary processing hub for dietary lipids. It actively participates in the digestion and biochemical remodeling of LCFAs, thereby altering their saturation and chemical structure and generating a wide variety of gut microbial metabolites. The effects of these gut-derived lipid metabolites extend far beyond the local intestinal microenvironment. Upon entering the bloodstream, these circulating microbiota metabolites act as endocrine signals. Given the extreme complexity of the underlying mechanisms, a comprehensive elucidation of the synergistic and bidirectional interactions between LCFAs and the gut microbiota in vascular pathology is particularly urgent. Therefore, this article aims to provide a systematic review of the multidimensional regulatory mechanisms of LCFAs and their associated gut microbiota metabolites in the onset, progression, and clinical manifestations of AS. By thoroughly exploring the interaction patterns within the “LCFAs-gut microbiota-AS” triad, this review seeks to fundamentally expand our understanding of the pathogenesis of CVDs. More importantly, translating these mechanistic insights into clinical practice holds tremendous promise. We hope to provide a solid theoretical foundation for the future development of novel AS prevention and treatment strategies based on non-traditional approaches. These include precision nutritional interventions (i.e., dietary lipid intake plans tailored to an individual’s unique microbiome profile) and targeted microbiome modulation therapies (such as next-generation probiotics, prebiotics, or specific metabolite supplements). Targeting the gut as a “reactor” to treat vascular wall lesions represents a promising direction for future cardiovascular medicine.

ObjectiveThis study aims to develop a prediction model for the compatibility of Chinese medicinal pairs based on Graph Convolutional Networks （GCN）， named HC-GCN. The model integrates the properties of herbs with modern pharmacological mechanisms to predict pairs with specific therapeutic effects. It serves as a demonstration by applying the model to predict and validate the efficacy of blood-activating herb pairs. MethodsThe training dataset for herb pair prediction was constructed by systematically collecting commonly used herb pairs along with their characteristic data， including Qi， flavor， meridian tropism， and target genes. Integrating traditional characteristics of herb with modern bioinformatics， we developed an efficacy-oriented herb pair compatibility prediction model （HC-GCN） using graph convolutional networks （GCN）. This model leverages machine learning to capture the complex relationships in herb pair compatibility， weighted by efficacy features. The performance of the HC-GCN model was evaluated using accuracy （ACC）， recall， precision， F1 score （F1）， and area under the ROC curve （AUC）. Its predictive effectiveness was then compared to five other machine learning models： eXtreme Gradient Boosting （XGBoost）， logistic regression （LR）， Naive Bayes， K-nearest neighbor （KNN）， and support vector machine （SVM）. ResultsUsing herb pairs with blood-activating effects as a demonstration， a prediction model was constructed based on a foundational dataset of 46 blood-activating herb pairs， incorporating their Qi， flavor， meridian tropism， and target gene characteristics. The HC-GCN model outperforms other commonly used machine learning models in key performance metrics， including ACC， recall， precision， F1 score， and AUC. Through the predictive analysis of the HC-GCN model， 60 herb pairs with blood-activating effects were successfully identified. Among of these potential herb pairs， 44 include at least one herb with blood-activating effects. ConclusionIn this study， we established an efficacy-oriented compatibility prediction model for herb pairs based on GCN by integrating the unique characteristics of traditional herbs with modern pharmacological mechanisms. This model demonstrated high predictive performance， offering a novel approach for the intelligent screening and optimization of traditional Chinese medicine prescriptions， as well as their clinical applications.

Nine compounds were isolated and purified from 90% ethanol extract of Alstonia mairei Lévl by using various chromatographic methods, including silica gel, SephadexLH-20, MCI Gel and ODS column chromatography, combined with semi-preparative liquid phase separation methods. Modern spectroscopic methods (1D and 2D NMR, UV, IR, MS, etc.) were used to identify the structures of the isolated compounds. They were identified as mairoside A (1), 3′,6-di-O-sinaloylsucrose (2), myristic acid (3), methyl myristate (4), ethyl myristate (5), 3,4,5-trimethoxycinnamic acid (6), 3,4,5-trimethoxybenzoic acid (7), vinoline (8), kaempferol-3-O-rutinoside (9), among which compound 1 is a new glycoside, compounds 4 and 5 are new natural products, and the nuclear magnetic data of compound 4 were reported for the first time.

In today's society， depression is a kind of highly prevalent chronic mental illness. It leads to a high disability rate and a heavy economic burden. Depression is defined by fundamental symptoms of low mood and diminished pleasure. Its causes and mechanisms remain unclear， and it presents a broad spectrum of symptoms and a persistent nature that significantly impacts both physical and mental well-being. Treatment in Western medicine primarily focuses on alleviating symptoms， yet it entails numerous adverse effects and contraindications. Traditional Chinese medicine （TCM） treatment is based on resolving depression， which is often accompanied by soothing liver， and the key medicine is Bupleuri Radix. Bupleuri Radix associated prescriptions refer to a class of prescriptions using Bupleuri Radix as the sovereign medicinal or having a high dose of Bupleuri Radix， which are widely used in the field of anti-depression. Previous studies from animal experiments， clinical research， and modern pharmacological research have confirmed that Bupleuri Radix associated prescriptions have precise anti-depression efficacy in multiple ways and at multiple levels， but lack a comprehensive and systematic summarization. This paper summarized and analyzed the literature related to the clinical application and mechanism of action of Bupleuri Radix associated prescriptions in anti-depression treatment. The results showed that the anti-depression mechanism of the Bupleuri Radix associated prescriptions （such as Xiaochaihu Tang， Xiaoyao San， Sini San， Chaihu Shugan San， and Chaihu jia Longgu Muli San） was associated with the effects of regulating monoamine neurotransmitters， the brain-derived neurotrophic factor （BDNF）， intestinal flora， and the hypothalamic-pituitary-adrenal （HPA） axis， inhibiting inflammatory responses， and modulating related signaling pathways. Applying them in clinical practice can effectively alleviate patient symptoms， lower the TCM syndrome score and the severity of depression， and also reduce adverse reactions. This underscores advantages of TCM in depression treatment， which offers patients a secure， effective， and more individualized alternative treatment regimen. On this basis， the shortcomings of current studies and the future trend were analyzed. This study aimed to provide an evidence-based medicine basis for the research and development of novel antidepressant medications.

As a cheap and effective antibiotic,sulfonamides are often used in animal husbandry.However,their residues in animal-derived foodstuffs will threaten human health.Consequently,a high-performance liquid chromatography(HPLC)method integrated with supramolecular solvent microextraction was successfully established for simultaneous quantification of sulfonamide residues sulfachlorpyridazine,sulfamethoxazole,sulfamethoxypyridazine and sulfadimethoxine in milk matrices.This approach exhibited prominent characteristics of operational simplicity,environmental sustainability,and high extraction efficiency.The supramolecular solvents prepared by tributyl octylphosphine tetrafluoroborate and tetrahydrofuran were employed as extraction solvents.The analytes underwent isolation and concentration via dispersive liquid-liquid microextraction(DLLME)prior to quantitative determination using high-performance liquid chromatography(HPLC).The composition and microscopic morphology of the supramolecular solvent were characterized through a series of analytical techniques,including phase diagram,Fourier transform infrared spectroscopy,scanning electron microscopy,and inverted fluorescence microscopy and so on.The density and pH value of supramolecular solvents were determined.The extraction conditions were optimized through the one-factor experiments.The experimental results demonstrated that under the optimal extraction conditions,the four kinds of sulfonamide antibiotics exhibited excellent linearity within respective detection range(R2 ≥ 0.9998)and the limits of detection(LOD)were 0.67-1.45 μg/L.Compared with literature methods,this approach offered some advantages such as simplicity of operation and less reagent consumption,and could be used for analysis and detection of sulfonamide antibiotic residues in milk samples.The present method provided technical support for food safety regulation and paved a new way for the application of supramolecular solvents in the field of extraction and separation.

With reference to the Information and Documentation-Resource Description (GB/T 3792-2021) and Bibliographical Description for Ancient Chinese Books (GB/T 3792.7-2008) and other cataloging standards and rules, drawing on the practical experience of cataloging ancient TCM books, Bibliographical Cataloging for Ancient TCM Books was formulated. This standard specifies the entry items and their order of ancient TCM books, cataloging identifier, cataloging text, cataloging information source, and cataloging item details. The standard can provide standardized and unified guiding principles and methods for the work of ancient TCM books, and promote the sharing and utilization of ancient TCM books.

Objective:To explore the differences in active components between Hedysari Radix and Astragali Radix; To explore the material basis and therapeutic functions of Hedysari Radix in promoting blood circulation and nourishing blood.Methods:The research materials used in this study were Hedysari Radix and Astragali Radix from Wudu District, Longnan City, Gansu Province. The contents of seven resource-based components-total sugars, total polyphenols, total flavonoids, crude proteins, total saponins, total alkaloids, and total dietary fiber were measured according to standard methods. Additionally, an HPLC method was established to quantify 21 active compounds. In vitro antioxidant experiments were conducted to assess the scavenging ability of DPPH and ABTS free radicals.Results:The contents of resource-based components in Hedysari Radix were higher than in Astragali Radix. Among the 21 active components, the characteristic active components of Astragali Radix, such as calycosin, formononetin, calycosin glucoside and so on, were high in contents. The contents of paeoniflorin and Medicinol in Astragali Radix were low or not detected, and the contents in Hedysari Radix were 98.828 μg/g and 103.986 μg/g, and the antioxidant capacity was also better than Astragali Radix.Conclusions:The basic components of Hedysari Radix for promoting blood circulation and nourishing blood are paeoniflorin, Medilac, vanillic acid, ferulic acid and formononetin, which can provide a scientific basis for the determination of the characteristic components and the improvement of the main functions of Hedysari Radix.

OBJECTIVES: To study the incidence and disease burden of congenital birth defects in children under five in China from 1990 to 2021 and to predict the incidence of congenital birth defects in this population from 2022 to 2036, providing a reference for the prevention of congenital birth defects in children. METHODS: Using the Global Burden of Disease Study 2021 (GBD 2021) database, the incidence and disability-adjusted life years (DALY) were employed to describe the disease burden. The Joinpoint regression model was used to analyze the trends in incidence and DALY rates of congenital birth defects in children under five. A grey prediction model GM(1,1) was applied to fit the trend of incidence rates of congenital birth defects in this age group and to predict the incidence from 2022 to 2036. RESULTS: In 2021, the incidence rate of congenital birth defects among children under five in China was 737.28 per 100 000. Among these, congenital musculoskeletal and limb deformities had the highest incidence rate at 307.15 per 100 000, followed by congenital heart defects (223.53 per 100 000), congenital urinary and genital tract malformations (74.99 per 100 000), and congenital gastrointestinal malformations (62.61 per 100 000). From 1990 to 2021, the incidence rate and DALY rate of congenital birth defects in children under five in China decreased at an average annual rate of 1.73% and 5.42%, respectively. The prediction analysis indicated a decreasing trend in the incidence of congenital birth defects among children under five in China from 2022 to 2036, with the incidence rate dropping from 892.36 per 100 000 in 2022 to 783.35 per 100 000 in 2036. CONCLUSIONS The incidence and disease burden of congenital birth defects in children under five in China showed a significant declining trend from 1990 to 2021. It is predicted that this incidence will continue to decrease until 2036.
Humans ; Congenital Abnormalities/epidemiology* ; China/epidemiology* ; Incidence ; Infant ; Infant, Newborn ; Child, Preschool ; Female ; Male ; Forecasting ; Disability-Adjusted Life Years