ObjectiveTo study the pharmacological substances and mechanisms through which sesquiterpene ZH-13 from Aquilariae Lignum Resinatum improves neuroinflammation. MethodsBV-2 microglial cells were stimulated with lipopolysaccharide （LPS） to induce neuroinflammation. The cells were divided into the normal group， the model group， and the ZH-13 low- and high-dose treatment groups （10， 20 μmol·L^-1）. The model group was treated with 1 μmol·L^-1 LPS. Cell viability was assessed using the cell proliferation and activity assay （CCK-8 kit）. Nitric oxide （NO） release in the cell supernatant was measured using a nitric oxide kit （Griess method）. The mRNA expression levels of interleukin-1β （IL-1β）， tumor necrosis factor-α （TNF-α）， inducible nitric oxide synthase （iNOS）， and interleukin-6 （IL-6） were detected by real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）. The phosphorylation of mitogen-activated protein kinase （MAPK） pathway proteins was assessed by Western blot. ResultsCompared with the model group， ZH-13 dose-dependently reduced NO release from BV-2 cells under LPS stimulation （P<0.05， P<0.01）. In the 20 μmol·L^-1 ZH-13 treatment group， the mRNA expression levels of IL-1β， TNF-α， iNOS， and IL-6 were significantly reduced compared to the model group （P<0.05， P<0.01）. In both the low- and high-dose ZH-13 groups， the expression of the inflammatory factor TNF-α and the phosphorylation of c-Jun N-terminal kinase （JNK） in the upstream MAPK pathway were significantly reduced （P<0.05）. After stimulation with the JNK agonist anisomycin （Ani）， both low- and high-dose ZH-13 treatment groups showed reduced phosphorylation of JNK proteins compared to the Ani-treated group （P<0.01）. ConclusionThe sesquiterpene compound ZH-13 from Aquilariae Lignum Resinatum significantly ameliorates LPS-induced neuroinflammatory responses in BV-2 cells by inhibiting excessive JNK phosphorylation and reducing TNF-α expression. These findings elucidate the pharmacological substances and mechanisms underlying the sedative and calming effects of Aquilariae Lignum Resinatum.

Objective To understand the application effect of early screening scale and behavioral intervention effect in children with autism spectrum disorder (ASD). Methods A total of 348 children with suspected ASD were selected and evaluated using the Modified Checklist for Autism in Toddlers (M-CHAT) and Autism Behavior Checklist (ABC). The evaluation results were compared with those from the Diagnostic and Statistical Manual of Mental Disorders (DSM-V). Children enrolled were given Early start Denver model (ESDM) intervention. The evaluation results of Gesell Developmental Scale and Autism Treatment Evaluation Checklist (ATEC) scores were compared before and after intervention. Results The sensitivity, specificity, accuracy and Kappa value of M-CHAT for evaluating ASD in children aged 1-3 years were 89.53%, 90.70%, 89.92% and 0.78. The corresponding values of ABC were 78.49%, 81.40%, 79.46% and 0.56. The sensitivity, specificity, accuracy and Kappa value of M-CHAT for evaluating children aged >3-6 years were 87.30%, 77.78%, 84.44% and 0.64. The corresponding values of ABC were 85.71%, 77.78%, 83.33% and 0.62. The sensitivity and accuracy of M-CHAT were higher than ABC for evaluating ASD in children aged 1-3 years (P<0.05). There were no significant differences in sensitivity, specificity and accuracy between M-CHAT and ABC for evaluating ASD in children aged 3-6 years (P>0.05). After intervention, development quotients (DQ) of personal-social aspects, adaptability, language, gross motor, and fine motor of children with ASD were higher than those before intervention (P<0.05). ATEC scores for language, behavior, sensation, and social contact of children with ASD were lower than those before intervention (P<0.05). Conclusion M-CHAT and ABC both can be used for early screening of ASD in children, especially M-CHAT. Early behavioral intervention can effectively improve the condition and developmental level of children with ASD.

ObjectiveTo analyze the epidemiological characteristics of long COVID and to investigate its main influencing factors by examining individuals infected with SARS-CoV-2 between March and June 2022 in two communities in Shanghai, to lay the foundation for further research on the mechanism and clinical treatment of long COVID, and to provide the basis for the development of inexpensive, convenient, and feasible prevention and intervention strategies. MethodsA cross-sectional study was conducted, enrolling 6 410 individuals infected with SARS-CoV-2. Data were collected through a questionnaire survey. The incidence and common symptoms of long COVID were analyzed, along with their associations with demographic characteristics, medical history, and behavioral factors. A logistic regression model was used to identify the major factors associated with the development of long COVID symptoms. ResultsThe overall incidence rate of long COVID among the study population was 13.9%. The most commonly reported symptoms included fatigue (65.1%), attention disorders (23.1%), and cough (16.9%). The analysis showed that having underlying chronic diseases (OR=2.580, 95%CI: 2.165‒3.074), a history of allergies (OR=1.418, 95%CI: 1.003‒1.971), current smoking (OR=1.461, 95%CI: 1.013‒2.079), ever smoking (OR=2.462, 95%CI: 1.687‒3.551), a greater number of symptoms during the acute phase [1 symptom (OR=1.778, 95%CI: 1.459‒2.162), 2 symptoms (OR=2.749, 95%CI: 2.209‒3.409), ≥3 symptoms (OR=7.792, 95%CI: 6.333‒9.593)] and aggravated symptoms during the acute phase (OR=1.082, 95%CI: 1.070‒1.094) were factors associated with a higher risk of developing long COVID symptoms. Additionally, individuals who had consumed alcohol in the past year (OR=1.914, 95%CI: 1.344‒2.684) were more prone to objective long COVID symptoms. Among individuals under 50 years of age, females (OR=1.427, 95%CI: 1.052‒1.943) were more likely to develop objective long COVID symptoms. ConclusionThis study has identified the diversity of long COVID symptoms, which involve multiple organs and systems, including fatigue, attention disorders, cough, and joint pain. It has also revealed associations between long COVID and various demographic factors (e.g., age, gender), personal medical history (e.g., underlying chronic diseases, history of allergies), acute-phase characteristics (e.g., number and severity of symptoms), and behavioral factors (e.g., smoking, alcohol consumption). These findings highlight the need for further research and ongoing surveillance of long COVID and may inform the development of more targeted health management strategies for specific populations.

The quality of traditional Chinese medicine (TCM) prescriptions (TCMPs) is critical to clinical efficacy; however, evaluating their consistency and identifying sources of variability remain challenging. This study proposes an integrated strategy to assess the quality of 100 widely sold TCMPs. A "one-for-all" chromatographic method was employed to analyze 645 sample batches. This large-scale data collection enabled statistical evaluations, such as hierarchical cluster analysis (HCA) and similarity heatmap, to identify quality inconsistencies. The introduction of a TCM-specific mass spectrometry (MS) database allowed for rapid, automated annotation of chemicals across 100 prescriptions and facilitated the tracing of raw material sources. Results indicate that 19% of prescriptions exhibited chemical inconsistencies, which are associated with high market value, low pricing, and substantial price disparities. The MS database allowed rapid annotation of 761 and 673 compounds in positive and negative modes, respectively, in 100 TCMPs, with 73 prescriptions reported for the first time. The tracing efforts succeeded in identifying >40% of the raw material sources for 51 prescriptions. P93 (Yinianjin (YNJ)) is a case in which the chromatographic profiles from three manufacturers displayed inconsistencies. Analysis using the database traced divergent peaks to Rhei Radix et R hizoma (RRER). Verification with self-prepared samples confirmed that manufacturers utilized three distinct botanical sources. This integrated strategy provides a scalable framework for quality control in TCMPs.

Objective To explore the therapeutic mechanism of Modified Lugen Formula(Phragmitis Rhizoma,Cicadae Periostracum,Batryticatus Bombyx,Lonicerae Japonicae Flos,Glycyrrhiza,Menthae Haplocalycis Herba,Notopterygii Rhizoma et Radix,Puerariae Lobatae Radix,Bupleuri Radix)in treating influenza from the virus-host interaction interface.Methods The phytocompounds were first collected from the HERB database,and then potential active compounds were screened out by Lipinski's rules of five.The targets of active compounds were further predicted through the SwissTargetPrediction platform.Differentially expressed genes(DEGs)were determined from the human H1N1 influenza dataset GSE90732 available in the Gene Expression Omnibus database(GEO).H1N1-Homo sapiens-related protein-protein interactions(PPIs)were gathered from the Pathogen-Host Interaction Search Tool(PHISTO).The above mentioned bioinformatic datasets were integrated.Then a PPI network and a Formula-virus-host interaction network were constructed using Cytoscape.Functional enrichment analyses were performed by using R software.Finally,molecular docking was carried out to evaluate the binding activities between the key compounds and targets.Results A total of 1 252 active compounds,1 415 targets,951 influenza-related DEGs,and 10 142 H1N1-Homo sapiens-related PPIs were obtained.There were 72 intersection targets between the Modified Lugen Formula and influenza.Functional enrichment analyses showed that these targets are closely related to host defense and programmed cell death.The network topological analysis showed that active compounds in the Modified Lugen Formula,such as oleanolic acid,γ-undecalactone,and longispinogenin,regulate viral proteins M2,NA,NS1,and HA and/or the host factors HSP90AA1,NRAS,and ITGB1,thus exert therapeutic effect.Molecular docking results confirmed that these compounds had a good binding ability with the targets.Conclusion Multiple active ingredients in Modified Lugen Formula directly target influenza virus proteins and/or host factors,thereby play an anti-influenza role in multiple dimensions,including inhibiting virus replication,regulating host defense and cell death.This study provides a theoretical basis for further experimental analysis of the action mechanism of the Modified Lugen Formula in treating influenza.

[Objective]To investigate the association between screen content and the frequency of screen exposure at the age of one and a half years and hyperactive behavior in preschool,and to explore how the association is affected by the interaction between outdoor activities and screen behaviors,which could provide theoretical basis and feasible solutions for the prevention and intervention of behavioral problems in childhoood.[Methods]The survey was conducted from June 2022 to June 2023 in Huicheng District,Huizhou (China) stratified by whole cluster sampling methods. Parents and teachers of 5648 children in 61 kindergartens were sampled for questionnaire surveys. The Conners Teacher Rating Scale (TRS) was used to investigate hyperactive behavior. A self-administered questionnaire was used to investigate basic demographic information of children,screen content,frequency of screen exposure and outdoor activities at the age of one and a half years. Multivariate logistic regression was used to explore the association between video screen behavior and hyperactive behavior and its interaction with outdoor activities by controlling for covariates such as children's age,gender,and parental education.[Results]Result showed the overall prevalence of 3.2％ for hyperactive behavior,2.1％ for conduct problems,2.1％ for hyperactivity problems,1.3％ for inattention-passivity problems,and 0.9％ for hyperactivity index. After adjusting for confounding factors,multiple logistic regression analysis showed that screen exposure of "two to four times a week" at one and a half years old was associated with an increased detection rate of hyperactive behaviors in preschool children,with an estimated ORs (95％ CI) of 1.682 (1.141,2.480). Daily screen exposure was associated with increased detection rates of hyperactive behavior,conduct problems,hyperactivity issues,inattention-passivity problems,and hyperactivity index in pre-school age. The estimated ORs (95％ CI) were 2.136 (1.218,3.746),2.321 (1.185,4.546),2.300 (1.208,4.380),2.776 (1.267,6.085) and 3.640 (1.525,8.687),respectively. But the above associations were not found in children who were engaged in daily outdoor activities at the age of one and a half years (P value for interaction<0.001). No association was found between screen content and hyperactive behavior (P>0.05).[Conclusions]Frequency of screen exposure in early childhood is significantly associated with hyperactive behavior problems in preschool,and outdoor activities could weaken the correlation between high-frequency screen exposure and hyperactive behavior,suggesting that parents and schools should prioritize scientifically guiding children's video viewing behavior and outdoor activities,ensuring a well-arranged daily life,to lay a good foundation for the healthy development of children's behavior.

Objective:To explore the association between insulin resistance (IR) and genome-wide DNA methylation based on Shanghai twin study.Methods:Monozygotic twins (MZ) from Shanghai were recruited during 2012-2013, 2017-2018, and 2022-2023. Data were collected by questionnaire survey, physical examination and laboratory tests. Genome-wide DNA methylation was quantified. Generalized linear mixed effect model was applied to analyze the association between methylation level at each site and homeostatic model assessment 2-insulin resistance (HOMA2-IR). Non-paired and paired designs were used to assess the association between DNA methylation and phenotype of IR. Cluster analysis was conducted to identify the clusters of top significant sites. Generalized linear regression was performed to examine the differential methylation patterns from clusters.Results:A total of 100 MZ pairs were included in this study. Hypermethylated cg10535199-2q23.1 ( β=0.74%, P=1.51×10 -7, OR=1.06, 95% CI: 1.03-1.09) and ch.17.49619327- SPOP ( β=0.23%, P=7.54×10 -7, OR=1.17, 95% CI: 1.08-1.28) were identified with suggestive significance. After correcting for multiple testing, no sites reached genome-wide significance. There was no statistical significance in the paired analysis. Two clusters with hypomethylated ( β=-0.39%, P<0.001) and hypermethylated ( β=0.47%, P<0.001) patterns were observed for HOMA2-IR. Conclusions:IR was significantly associated with DNA methylation, and genetic factors might contribute to the association.

Objective:To analyze the survival of pneumoconiosis patients in Guangzhou from 1958 to 2018, explore the factors affecting the survival of pneumoconiosis, and provide scientific basis for formulating the guidelines and policies for treatment and assistance of pneumoconiosis.Methods:From July 2019 to January 2020, 1194 cases of occupational pneumoconiosis patients diagnosed by institutions qualified for pneumoconiosis diagnosis in Guangzhou from June 1, 1958 to December 31, 2018 were studied. Excluding 258 patients who lacked survival data, 936 patients were included in the pneumoconiosis survival analysis. Life table method was used to estimate the survival rate, Kaplan-Meier method was used to draw the survival curve, log-rank test was used to compare the groups, and Cox proportional risk regression model was used to analyze the influencing factors of survival.Results:The 10, 20 and 30 years cumulative survival rates of pneumoconiosis patients in Guangzhou were 62.8%, 35.2% and 15.4%, respectively. The median survival time was 19.4 years. log-rank test showed that there were statistically significant differences in the survival curves of pneumoconiosis patients between group without tuberculosis and group with tuberculosis ( P<0.001), and there were statistically significant differences among different stages and categories of pneumoconiosis ( P<0.001). Age of exposure to dust ( HR=1.03, 95% CI: 1.01-1.05), age of diagnosis ( HR=1.02, 95% CI: 1.00-1.04), combined pulmonary tuberculosis ( HR=1.46, 95% CI: 1.18-1.81), stage of pneumoconiosis (stage Ⅲ vs. stage Ⅰ, HR=2.26, 95% CI: 1.47-3.48) and categories of pneumoconiosis (fibrogenic mineral dust pneumoconiosis and metallogenic pneumoconiosis, HR=2.45, 95% CI: 1.61-3.74; non-fibrogenic mineral pneumoconiosis and metallogenic pneumoconiosis, HR=2.67, 95% CI: 1.47-4.87; mixed pneumoconiosis and metallogenic pneumoconiosis, HR=2.25, 95% CI: 1.11-4.56) were the factors affecting the survival time of pneumoconiosis patients ( P<0.05) . Conclusion:Pulmonary tuberculosis may increase the risk of death in patients with pneumoconiosis. Mineral dust pneumoconiosis, mixed pneumoconiosis and stage Ⅲ pneumoconiosis may also have higher risk of death.

Innate immunity is the front line of the antiviral immune response and the bridge to a-daptive immunity.Porcine reproductive and respiratory syndrome virus(PRRSV)has evolved mul-tiple strategies to evade the host's innate immunity and thus establish persistent infections,which is one of the biggest obstacles to control PRRSV infection.In antiviral innate immunity,type Ⅰ in-terferons,interferon-stimulated genes(ISGs),and other antiviral proteins are the main perform-ers,cellular autophagy and programmed cell death are important components,noncoding RNAs are key regulators.Studies on evasion mechanisms of innate immune by PRRSV have emerged in re-cent years,greatly expanding our understandings of the PRRSV-host interaction network.In this paper,we outline the latest researches on PRRSV inhibition of type Ⅰ interferon production and its signaling transduction as well as antagonism of ISGs and other antiviral proteins,and focus on summarizing the researches on PRRSV evade the innate immunity through the modulation of cel-lular autophagy,programmed cell death,and non-coding RNAs,with a view to providing ideas for subsequent research and anti-PRRSV vaccine and drug development.

Objective The goals of this study were to identify early warning markers of severe dengue based on bioinformatics com-bined with machine learning,and explore the evaluation system of the risk of occurrence of severe dengue.Methods Based on the Gene Expression Omnibus database,the differentially expressed genes between dengue and severe dengue were analyzed,and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were conducted.Early warning genes of severe dengue were screened using a random forest model,and the accuracy of the genes was verified using receiver operating characteristic(ROC)curves.Finally,nomograms were constructed to quantify the warning genes and predict the risk of progression from dengue to severe dengue based on the expression level of these genes.Results A total of 817 differentially expressed genes were identified,along with the associated biolo-gical processes that may be closely related to the occurrence and development of severe dengue,namely,antimicrobial humoral response,humoral immune response,serine hydrolase activity,and arachidonic acid metabolism.Based on this analysis,five early warning genes were isolated:AZU1,PDCD4,COL4A3BP,TRPM4,and ATP4A.Among these,ATP4A,COL4A3BP,and TRPM4 showed low expression levels,whereas AZU1and PDCD4were highly expressed.The ROC curves indicated that these genes were accurate pre-dictors of severe dengue.The nomograms indicated good predictive accuracy,clinical benefit rate,and clinical effectiveness of the model.Conclusion Measuring the expression levels of five warning genes(AZU1,PDCD4,COL4A3BP,TRPM4,and ATP4A)may help to evaluate the risk of severe dengue.