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.

Objective: To study the correlation between short sleep duration and screening myopia among primary and middle school students in Beijing, so as to provide a scientific basis for the comprehensive prevention and control of myopia among students. Methods: Using a stratified cluster random sampling, 25 593 primary and middle school students from 16 districts of Beijing were selected from September to November 2023. The National Common Diseases and Health Influencing Factors Monitoring Survey Questionnaire was used to conduct a questionnaire survey, and visual acuity was tested according to the Specification for the Screening of Refractive Error in Primary and Middle School Students. The reporting rates of short sleep duration and detection rates of screening myopia among primary and middle school students were compared using the Chi square test. Binary Logistic regression was used to analyze the correlation between short sleep duration and screening myopia. Results: About 68.63% of students reported short sleep duration. There was a statistically significant difference in the reporting rate of short sleep duration among students in different school stages ( χ 2=981.18, P <0.01), with the lowest reporting rate of vocational high school students (47.07%) and the highest reporting rate of ordinary high school students (76.17%). The detection rates of screening myopia among primary school students ( 57.09% ) and middle school students (76.53%) who reported short sleep duration were higher than those who reported enough sleep duration (52.65%, 71.94%), with satistically significant differences ( χ 2=14.83, 17.96, P <0.01). The results of binary Logistic regression analysis showed that primary and middle school students with short sleep duration had a higher risk of developing screening myopia, compared to students with enough sleep duration ( OR =1.25); after adjusting for confounding factors such as educational stage, gender, region, boarding situation, primary and secondary school students with short sleep duration still had a higher risk of screening myopia ( OR =1.26) ( P <0.01). The analysis results stratified by educational stage showed that primary school students from grades 4-6 and middle school students with short sleep duration had a higher risk of screening myopia ( OR=1.18, 1.20, P <0.01). Conclusions Primary and secondary school students in Beijing with short sleep duration sleep have a higher risk of developing screening myopia. Families, schools, and society should ensure enough sleep duration to reduce the occurrence of myopia among students.

Objective: To explore the association between CDKAL1 rs35261542, FAIM2 rs 3205718, and VGLL4 rs 2574704 polymorphisms with childhood obesity and related metabolic phenotypes to provide evidence for personalized prevention and management strategies. Methods: Based on the 2023 Long term Nutritional Health Effects of Early Childhood Nutrition Package Intervention project, the study enrolled 1 078 children aged 5-7 years from four counties in Henan (Songxian and Ruyang countries) and Guizhou (Guiding and Fuquan countries) provinces. Using BMI Z scores, 87 overweight and obese(OVOB) children were selected and matched by sex, age, and BMI Z score with 117 normal weight controls. Participants were further stratified into four metabolic phenotype groups: metabolically healthy normal weight (MHNW, n =51), metabolically unhealthy normal weight (MUNW, n =66), metabolically healthy obesity (MHO, n =31) and metabolically unhealthy obesity (MUO, n =56) based on four conventional cardiometabolic risk factor (CR) criteria. Data were collected through questionnaires, anthropometric measurements, serum biochemical tests, and KASP genotyping. The distribution of three genetic polymorphisms ( CDKAL1 rs35261542, FAIM2 rs3205718, VGLL4 rs 2574704) across metabolic subgroups was analyzed. Multivariate Logistic regression models assessed associations between these polymorphisms and obesity/metabolic phenotypes. Results: Multivariate Logistic regression analysis showed that Homozygous mutant AA genotype of CDKAL1 rs 35261542 was positively associated with OVOB( OR =3.63), MHO ( OR =11.04), MUO ( OR = 4.88 ) ( P <0.05). Homozygous TT genotype of FAIM2 rs 3205718 increased OVOB risk ( OR =4.44, P <0.05) but showed no association with metabolic phenotypes ( P >0.05). Homozygous mutant TT of VGLL4 rs 2574704 reduced the risks of MHO and MUO ( OR = 0.30, 0.24， P <0.05). Cumulative genetic effects analysis demonstrated carriers of 1 or 2 risk genotypes of rs 35261542 and rs 3205718 had progressively higher OVOB risk ( OR =2.53, 20.79), and the combination of rs 35261542 and rs 2574704 increased risks for both MHO ( OR =8.50) and MUO ( OR =5.00) ( P <0.05). Conclusions The AA genotype of rs 35261542 ( CDKAL1 ) positively correlates with childhood obesity and metabolic abnormalities. The TT genotype of rs 3205718 ( FAIM 2) increases obesity risk but not metabolic phenotypes. The TT genotype of rs 2574704 ( VGLL 4) shows protective effects against metabolic dysfunction. Risk genotypes exhibit dosedependent cumulative effects on obesity and metabolic outcomes.

The continuous emergence of SARS-CoV-2 variants as well as other potential future coronavirus has challenged the effectiveness of current COVID-19 vaccines. Therefore, there remains a need for alternative antivirals that target processes less susceptible to mutations, such as the formation of six-helix bundle (6-HB) during the viral fusion step of host cell entry. In this study, a novel high-throughput screening (HTS) assay employing a yeast-two-hybrid (Y2H) system was established to identify inhibitors of HR1/HR2 interaction. The compound IMB-9C, which achieved single-digit micromolar inhibition of SARS-CoV-2 and its Omicron variants with low cytotoxicity, was selected. IMB-9C effectively blocks the HR1/HR2 interaction in vitro and inhibits SARS-CoV-2-S-mediated cell-cell fusion. It binds to both HR1 and HR2 through non-covalent interaction and influences the secondary structure of HR1/HR2 complex. In addition, virtual docking and site-mutagenesis results suggest that amino acid residues A930, I931, K933, T941, and L945 are critical for IMB-9C binding to HR1. Collectively, in this study, we have developed a novel screening method for HR1/HR2 interaction inhibitors and identified IMB-9C as a potential antiviral small molecule against COVID-19 and its variants.

OBJECTIVE: To explore the clinical features of the sepsis in immunocompromised hosts and establish an early warning equation. METHODS: A retrospective study was conducted on sepsis patients admitted to the intensive care unit (ICU) of Binzhou Medical University Hospital from October 2011 to October 2022. General information, infection site, etiology results and drug susceptibility, clinical symptoms, inflammatory indicators, acute physiology and chronic health status evaluation II (APACHE II), sequential organ failure assessment (SOFA), incidence of immune paralysis, and outcome during hospitalization were collected. Based on whether they met the diagnostic criteria for immunocompromised hosts, patients were divided into immunocompromised group and immune normal group. The clinical information of the two groups were compared. Multivariate Logistic regression was used to analyze the risk factors of patients with immunocompromised sepsis and the regression equation model was initially established. Omnibus test and Hosmer-Lemeshow test were used to evaluate the model. RESULTS: A total of 169 patients with sepsis were included, including 61 in the immunocompromised group and 108 in the normal immune group. The top 3 infection sites in the immunocompromised group were bloodstream infection, pulmonary infection and abdominal infection. The top 3 infection sites in the normal immune group were pulmonary infection, bloodstream infection and abdominal infection. The infection rate of Gram-negative bacteria in the immunocompromised group was significantly lower than that in the normal group [49.2% (30/61) vs. 64.8% (70/108), P < 0.05]. The infection rate of Gram-positive bacteria [27.9% (17/61) vs. 13.9% (15/108)] and multidrug-resistant bacteria [54.1% (33/61) vs. 29.6% (32/108)] were significantly higher than those in normal immune group (both P < 0.05). In terms of clinical symptoms, the proportion of fever in the immunocompromised group was significantly lower than that in the immune normal group [49.2% (30/61) vs. 66.7% (72/108), P < 0.05]. Neutrophil count (NEU) and neutrophil percentage (NEU%) in the immunocompromised group were significantly lower than those in the normal immune group. Lymphocyte percentage (LYM%), neutrophil/lymphocyte ratio (NLR), C-reactive protein (CRP), procalcitonin (PCT), APACHE II score, combined shock rate, incidence of immune paralysis, and mortality during hospitalization in the immunocompromised group were significantly higher than those in the normal immune group. Logistic regression analysis showed that NLR, CRP and PCT were risk factors for patients with immunocompromised sepsis (all P < 0.05). The above indicators were used as covariables to construct a Logistic regression equation, that was, Logit (P) = 0.025X₁+0.010X₂+0.013X₃-2.945, where X₁, X₂ and X₃ represent NLR, CRP and PCT respectively. Omnibus test and Hosmer-Lemeshow test show that the model fits well and has certain early warning value. CONCLUSIONS Patients with immunocompromised sepsis have more intense inflammatory response, with Gram-negative bacteria being the predominant pathogen, and a higher incidence of Gram-positive bacterial infections and multi-drug resistant infections. The severity of the disease, in-hospital mortality, the incidence of shock and the incidence of immune paralysis after sepsis were significantly higher. NLR, CRP and PCT were independent risk factors for sepsis in immunocompromised hosts. The regression equation constructed based on this may have early warning significance for patients with immunocompromised sepsis.
Humans ; Sepsis/immunology* ; Immunocompromised Host ; Retrospective Studies ; Risk Factors ; Intensive Care Units ; Logistic Models ; Male ; APACHE ; Female ; Middle Aged ; Aged

The research on the cardiovascular toxicity of air pollutants is in urgent need of collaborative innovation across multiple models. This paper systematically reviewed the advantages and limitations of four principal research models of cardiotoxicity, including epidemiological model, mammalian model, zebrafish model, and in vitro model. Epidemiological models have been used to demonstrate a significant correlation between exposure to PM_2.5 and both the incidence and mortality of cardiovascular diseases within populations; however, these models face challenges in establishing causal inferences and interpreting individual mechanisms. Mammalian models have been applied to elucidate the pathogenic mechanisms of PM_2.5 at both the systemic and organ-specific levels, yet they encounter difficulties related to interspecies differences and throughput constraints. Zebrafish models, with their transparent embryos and observable development, offer a distinctive opportunity for high-throughput screening and mechanistic investigation of PM_2.5-induced cardiac developmental toxicity. Nonetheless, their cardiac physiological structure diverges from that of mammals, limiting their capacity to accurately model chronic conditions such as coronary heart disease. In vitro models, particularly human heart organoids and chip technologies, have provided profound insights into the direct toxic mechanisms of PM_2.5, including disruptions in calcium homeostasis, cellular senescence, and electrophysiological irregularities at the cellular and molecular levels. Despite these advancements, the complexity and developmental maturity of these models present challenges to their broader application. This paper proposed that the key to overcoming the bottlenecks of single models lies in the construction of an integrated evaluation system that combines “epidemiological studies, mammalian models, zebrafish models, and in vitro models”. By focusing on three aspects, namely model integration, technological convergence, and policy support, it is intended to collaboratively address issues such as standardization of multi-model data, simulation of complex exposure scenarios and susceptible life stages, and transformation pathways. This will provide innovative methodological support for the analysis of the cardiotoxic mechanisms of air pollutants, the assessment of environmental health impacts, and the formulation of precise prevention and control strategies.

Objective: To assess the nutritional status of primary and secondary school students in Beijing City and to analyze the related factors, so as to provide a scientific basis for improving the nutritional status of primary and secondary school students in a targeted manner. Methods: Based on the 2021 Beijing Student Common Diseases and Health Influencing Factors Surveillance Project, a stratified random cluster sampling method was used to conduct a physical examination and questionnaire survey on 25 487 primary and secondary school students from September to November 2021. The Chi square test was used for comparison of nutritional status detection rates, and disordered multi classification Logistic regression analysis was used to explore the factors associated with students nutritional status. Results: The detection rates of malnutrition, overweight and obesity among primary and secondary school students in Beijing City were 4.7%, 18.0% and 23.8% respectively. The detection rates of malnutrition, overweight and obesity were higher among male students (5.1%, 20.4%, 29.7%) than female students (4.2%, 15.5%, 17.4%) ( χ 2= 12.23, 101.71, 526.99, P <0.01). The detection rate of obesity was higher in the suburbs than urban areas(26.6%, 19.8%), and the detection rate of malnutrition was lower in the suburbs than urban areas (4.2%,5.5%)( χ 2=157.25, 23.61, P <0.01). The results of disordered multi classification Logistic regression showed that the related factors for malnutrition, overweight and obesity were gender, residence, moderate to vigorous exercise ≥60 min per day and lack of sleep( OR =1.70, 1.88,2.48; 1.14, 0.87, 0.67; 0.85, 0.92, 0.81 ; 0.83, 1.08, 1.07); frequency of fried food intake daily was a related factor for overweight ( OR =0.70); whether eating breakfast daily or not was a related factor for overweight and obesity ( OR =0.91, 0.84); academic level (middle and high school) was a related factor for malnutrition and obesity ( OR =1.38, 1.37; 0.77, 1.40)( P <0.05). Conclusions The problem of overweight and obesity among primary and secondary school students in Beijing City continues to be serious, especially among boys and suburban areas. It is recommended that society, schools, families and individuals should work together to improve the nutritional status of primary and secondary school students by adopting a graded and classified approach.

Acute pancreatitis （AP） is one of the most clinically common acute digestive disorders characterized by quick onset，rapid progression，severe condition，and high mortality. If the disease is not timely intervened in the early stage，it can develop into severe AP in the later stage，which damages the long-term quality of life and brings serious economic burden to patients and their families. However， the pathogenesis of this disease is complex and has not been fully explained. The generation and development of AP is closely related to many signaling pathways. Among them，Toll-like receptor 4（TLR4），as a transmembrane signal transduction receptor，can mediate immune response and inflammatory response，and play a key role in the occurrence and development of AP. Traditional Chinese medicine（TCM）can regulate the TLR4 signaling pathway with multiple targets，multiple effects，and multiple administration methods to inhibit inflammatory response，and effectively intervene in the progression of AP， which has gradually become a new craze for preventing and treating AP. Many studies have shown that TCM has obvious advantages in the prevention and treatment of AP. It can effectively treat AP by regulating TLR4 signaling pathway，strengthening immune resistance and defense，and inhibiting inflammatory response. Despite of the research progress，there is still a lack of comprehensive review on TCM regulation of TLR4 signaling pathway in the treatment of AP. Therefore，the literature on TCM regulation of TLR4 signaling pathway published in recent years was systematically reviewed and elaborated，aiming to provide new ideas for the treatment of AP and further drug development.

Abstract: The differential expression and subcellular localization of single-cell proteins are closely related to the physiological state and pathological mechanisms of the body. The development of single-cell protein in situ imaging methods provides powerful tools for spatial single-cell proteomics research and single-cell protein profiling. This article summarizes the single-cell protein imaging methods developed in recent years, including the circulating immunofluorescence imaging methods based on ordered multi-round antibody incubation, mass spectrometry imaging based on metal element labeled antibodies, fluorescence imaging based on DNA-barcoded antibody, gene encoded fluorescence protein imaging and spectral imaging based on Raman spectroscopy or X-ray spectroscopy, with brief explanation of the imaging principles of these methods. It focuses on the multiple performance, imaging resolution and signal amplification performance of these methods, and analyzes their application characteristics in practical scientific research and clinical work, in the hope of providing some reference for the development of more revolutionary single-cell imaging methods, and promoting the development of biomedical and precision medicine.