ObjectiveTraditional Chinese medicine (TCM) constitutes a valuable cultural heritage and an important source of antitumor compounds. Poria (Poria cocos (Schw.) Wolf), the dried sclerotium of a polyporaceae fungus, was first documented in Shennong’s Classic of Materia Medica and has been used therapeutically and dietarily in China for millennia. Traditionally recognized for its diuretic, spleen-tonifying, and sedative properties, modern pharmacological studies confirm that Poria exhibits antioxidant, anti-inflammatory, antibacterial, and antitumor activities. Pachymic acid (PA; a triterpenoid with the chemical structure 3β-acetyloxy-16α-hydroxy-lanosta-8,24(31)-dien-21-oic acid), isolated from Poria, is a principal bioactive constituent. Emerging evidence indicates PA exerts antitumor effects through multiple mechanisms, though these remain incompletely characterized. Neuroblastoma (NB), a highly malignant pediatric extracranial solid tumor accounting for 15% of childhood cancer deaths, urgently requires safer therapeutics due to the limitations of current treatments. Although PA shows multi-mechanistic antitumor potential, its efficacy against NB remains uncharacterized. This study systematically investigated the potential molecular targets and mechanisms underlying the anti-NB effects of PA by integrating network pharmacology-based target prediction with experimental validation of multi-target interactions through molecular docking, dynamic simulations, and in vitro assays, aimed to establish a novel perspective on PA’s antitumor activity and explore its potential clinical implications for NB treatment by integrating computational predictions with biological assays. MethodsThis study employed network pharmacology to identify potential targets of PA in NB, followed by validation using molecular docking, molecular dynamics (MD) simulations, MM/PBSA free energy analysis, RT-qPCR and Western blot experiments. Network pharmacology analysis included target screening via TCMSP, GeneCards, DisGeNET, SwissTargetPrediction, SuperPred, and PharmMapper. Subsequently, potential targets were predicted by intersecting the results from these databases via Venn analysis. Following target prediction, topological analysis was performed to identify key targets using Cytoscape software. Molecular docking was conducted using AutoDock Vina, with the binding pocket defined based on crystal structures. MD simulations were performed for 100 ns using GROMACS, and RMSD, RMSF, SASA, and hydrogen bonding dynamics were analyzed. MM/PBSA calculations were carried out to estimate the binding free energy of each protein-ligand complex. In vitro validation included RT-qPCR and Western blot, with GAPDH used as an internal control. ResultsThe CCK-8 assay demonstrated a concentration-dependent inhibitory effect of PA on NB cell viability. GO analysis suggested that the anti-NB activity of PA might involve cellular response to chemical stress, vesicle lumen, and protein tyrosine kinase activity. KEGG pathway enrichment analysis suggested that the anti-NB activity of PA might involve the PI3K/AKT, MAPK, and Ras signaling pathways. Molecular docking and MD simulations revealed stable binding interactions between PA and the core target proteins AKT1, EGFR, SRC, and HSP90AA1. RT-qPCR and Western blot analyses further confirmed that PA treatment significantly decreased the mRNA and protein expression of AKT1, EGFR, and SRC while increasing the HSP90AA1 mRNA and protein levels. ConclusionIt was suggested that PA may exert its anti-NB effects by inhibiting AKT1, EGFR, and SRC expression, potentially modulating the PI3K/AKT signaling pathway. These findings provide crucial evidence supporting PA’s development as a therapeutic candidate for NB.

Objective To investigate the ameliorative effect of Lentinan (LNT) on sodium arsenite (SA)-induced hepatic lipid deposition in mice. Methods C57BL/6 mice were used as the experimental subjects, which were divided into control group, SA-exposed group, LNT + SA-exposed group and LNT control group. Blood and liver tissue samples were collected at the end of the experiment, and serum glutathione transaminase (ALT) and glutathione aminotransferase (AST) levels were detected by enzyme-linked immunosorbent assay (ELISA). A part of liver tissues was stained with hematoxylin-eosin (HE) or oil red O to observe the characteristics of liver pathological damage and lipid deposition, and another part of liver tissues was used to detect triglyceride (TG) and Adiponectin (APN) levels by ELISA. Results Compared with control group or LNT control group, SA-exposed group showed the increased levels of AST and ALT, showing the characteristics of liver histopathological damage and lipid deposition, and the APN level decreased while the TG level increased (P<0.05). Compared with SA-exposed group, the levels of AST and ALT decreased in LNT + SA-exposed group, showing the reduced degree of liver tissue damage and lipid deposition, and APN level upregulated while TG level downregulated (P<0.05). Conclusion Chronic SA exposure induces liver function damage, APN downregulation and lipid deposition in C57BL/6 mice, while LNT intervention leads to the significantly improvement of hepatic damage and lipid deposition, which may be related to the elevated APN level in liver.

Background and Objectives: Acute myocardial infarction (AMI) often occurs suddenly and leads to fatal consequences. Ferroptosis is closely related to the progression of AMI.However, the specific mechanism of ferroptosis in AMI remains unclear. Methods: We constructed a cell model of AMI using AC16 cells under oxygen and glucose deprivation (OGD) conditions and a mice model of AMI using the left anterior descending (LAD) ligation. The 3-(4, 5-dimethylthiazol-2-yl)-2, 5 diphenyltetrazolium bromide was employed to determine cell viability. The levels of lactate dehydrogenase, creatine kinase, reactive oxygen species (ROS), glutathione (GSH), malondialdehyde (MDA), and iron were measured using corresponding kits. Dual luciferase reporter gene assay, RNAbinding protein immunoprecipitation, and RNA pull-down were performed to validate the correlations among AC005332.7, miR-331-3p, and cyclin D2 (CCND2). Hematoxylin and eosin staining was employed to evaluate myocardial damage. Results: AC005332.7 and CCND2 were lowly expressed, while miR-331-3p was highly expressed in vivo and in vitro models of AMI. AC005332.7 sufficiency reduced ROS, MDA, iron, and ACSL4 while boosting the GSH and GPX4, indicating that AC005332.7 sufficiency impeded ferroptosis to improve cardiomyocyte injury in AMI. Mechanistically, AC005332.7 interacted with miR-331-3p, and miR-331-3p targeted CCND2. Additionally, miR-331-3p overexpression or CCND2 depletion abolished the suppressive impact of AC005332.7 on ferroptosis in OGD-induced AC16 cells. Moreover, AC005332.7 overexpression suppressed ferroptosis in mice models of AMI. Conclusions AC005332.7 suppressed ferroptosis in OGD-induced AC16 cells and LAD ligation-operated mice through modulating miR-331-3p/CCND2 axis, thereby mitigating the cardiomyocyte injury in AMI, which proposed novel targets for AMI treatment.

Aim To investigate the potential mechanism of osthole promoting autophagy in cervical cancer HeLa cells. Methods HeLa cells were treated with various concentrations of Osthole(0,10,20,40,80,160,240,320 mg·L-1). MTT was used to detect cell vitality. Transmission electron microscopy(TEM)was used to observe the morphology of HeLa cells after osthole intervention. Mondane sulfonyl cadaverine(MDC)staining was used to dectect the level of autophagy. Western blot was employed to analyze the expression levels of mitochondrial protein MFN1 and DPR1. JC-1 flourescence probe was applied to detect mitochondrial membrane potential. Flow cytometry was used to deteminet the release of reactive oxygen species(ROS). A transplanted tumor model of cervical cancer was established in vivo in nude mice. Western blot was used to detect the protein expression levels of PINK1,Parkin and LC3Ⅱ/. Results Osthole could inhibit the proliferation of HeLa cells significantly. Transmission electron microscopy showed that typical autophagosomes were formed in HeLa cells after osthole intervention. The fluorescence intensity of MDC was enhanced. The expression of mitochondrial fusion protein MFN1 was down-regulated after HeLa cells pretreated with osthole,and mitochondrial fission protein DRP1 was up-regulated. Mitochondrial membrane potential decreased. ROS production of HeLa cells was increased by flow cytometry,which could be reversed by autophagy inhibitor 3-MA. Tumor weight in nude mice was inhibited by osthole obviously,which might restrain cervical cancer. Western blot result indicated that the key factors of mitochondrial autophagy PINK1,Parkin and LC3Ⅱ/ratio were up-regulated in HeLa cells. Conclusions Osthole could induce autophagy in HeLa cells and its mechanism may be related to ROS production and PINK1/Parkin pathway.

Objective To investigate the relationship between occupational noise exposure and glycated hemoglobin (HbA1c) levels, as well as prediabetes diagnosed by HbA1c. Methods A total of 1 181 workers from a cigarette factory were selected as the research subjects using a judgment sampling method. Workers were divided into control, low-level noise exposure and high-level noise exposure groups, consisting of 236, 359, and 586 individuals, respectively. The blood sample was collected for HbA1c test and occupation noise exposure intensity in workplace was detected by an area-sampling method. Results There were no statistical significant differences in HbA1c levels and prediabetes prevalence among the three groups of workers (all P>0.05). After adjusting for potential confounding factors such as years of service, gender, smoking, pack-years of smoking, alcohol consumption, and body mass index, multiple linear regression analysis showed that the high-level noise exposure group had higher HbA1c level than the control group (P<0.05). Multivariable logistic regression analysis results showed that the high-level noise exposure group had higher risk of prediabetes compared with the control group (P<0.05). Conclusion Occupational noise exposure could be a risk factor for the increased HbA1c levels and prediabetes incidence among the occupational population. More attention should be paid to the effects of occupational noise exposure on the HbA1c level in occupational health surveillance.

Objective:To detect the expression of interleukin 2 (IL-2)/Janus kinase 3/signal transduction and transcriptional activator 5 (JAK3/STAT5) signaling pathway in peripheral blood of patients with ankylosing spondylitis (AS) and explore its mechanism in the development and progression of AS.Methods:Clinical data, peripheral blood and laboratory tests of 30 patients with active AS (ASA), 30 patients with stable AS (ASS) and 50 healthy subjects (HC) were collected. The mRNA expression levels of JAK3, signal transduction and transcription activator 5a (STAT5a) and signal transduction and transcription activator 5b (STAT5b) were detected by quantitative real-time-polymerase chain reaction (RT-qPCR). The expression levels of JAK3, STAT5a and STAT5b proteins and phosphorylated proteins were detected by Western-blot. Plasma IL-2 concentration was determined by enzyme-linked immunosorbent assay (ELISA). Two independent samples t-test or one-way analysis of variance were used for measurement data consistent with normal distribution, LSD- t test was used for pairwise comparison between the three groups, Mann-Whitney U test or Kruskal-Wallis H test was used for non-normal distribution, χ2 test was used for correlation analysis of categorical variables. Spearman correlation analysis was used for correlation analysis between variables, and receiver operating characteristic (ROC) curve was used to evaluate the value of JAK3, STAT5a and STAT5b mRNA expression levels in monitoring AS activity. Results:① The mRNA expression levels of JAK3, STAT5a and STAT5b were significantly different among the three groups ( F=65.98, P<0.001; F=21.15, P<0.001; F=13.67, P<0.001). JAK3 mRNA expression in ASA group (2.5±0.9) was significantly higher than that in ASS group (1.1±0.4) and healthy subjects (1.0±0.5), the difference was statistically significant (both P<0.001). The mRNA expression level of STAT5a in ASA group (1.4±0.3) was significantly higher than that in ASS group (0.9±0.3) and healthy subjects group (1.0±0.3), the difference was statistically significant (both P<0.001). STAT5b mRNA expression level in ASA group (1.5±0.6) was significantly higher than that in ASS group (1.0±0.4) and healthy subjects (1.0±0.4), the difference was statistically significant (both P<0.001). The expression level of JAK3 mRNA in HLA-B27 positive group (1.9±1.0) was higher than that in HLA-B27 negative group (1.4±0.6), and the difference was statistically significant ( t=-2.22, P=0.032). The phosphorylation levels of JAK3, STAT5a and STAT5b showed statistically significant differences among the three groups ( F=91.56, P<0.001; F=25.15, P< 0.001; F=178.59, P<0.001). The phosphorylation level of JAK3 protein in ASA group (1.04±0.08) was significantly higher than that in ASS group (0.568±0.019) and healthy subjects (0.536±0.064), the difference was statistically significant (both P<0.001). The phosphorylation level of STAT5a protein in ASA group (1.166±0.096) was significantly higher than that in ASS group (0.923±0.018) and healthy subjects (0.911±0.017), the difference was statistically significant (both P<0.001). The phosphorylation level of STAT5b protein in ASA group (0.81±0.05) was significantly higher than that in ASS group (0.21±0.03) and healthy subjects (0.24± 0.07), the difference was statistically significant (both P<0.001). The difference of plasma IL-2 concentration among the three groups was statistically significant ( F=3.32, P=0.040). The IL-2 concentration in the ASA group [(110±40) pg/ml] was significantly higher than that in the ASS group [(89±40) pg/ml] and the healthy group [(88±39) pg/ml], the difference was statistically significant ( P=0.044, P=0.016). ② Spearman correlation analysis showed that STAT5a mRNA expression level was positively correlated with platelets in AS patients ( r=0.353, P=0.006). JAK3 mRNA expression level in ASA group was positively correlated with IL-2 concentration ( r=0.766, P<0.001), and negatively correlated with estimated glomerular filtration rate ( r=-0.485, P=0.007). STAT5a mRNA expression level was positively correlated with erythrocyte sedimentation rate ( r= 0.680, P<0.001), and STAT5b mRNA expression level was positively correlated with hypersensitive C-reactive protein (CRP) ( r=0.823, P<0.001). ③ The ROC curve showed that JAK3 mRNA expression level predicted the area under ROC curve (AUC) of ASA with a 95% CI of 0.920 (0.853, 0.987), sensitivity and specificity of 86.7% and 90.0%, respectively. STAT5a mRNA expression level predicted the AUC 95% CI of ASA was 0.874 (0.787, 0.961), and the sensitivity and specificity were 96.7% and 66.7%, respectively. STAT5b mRNA expression level predicted the AUC 95% CI of ASA was 0.749 (0.617, 0.881), and the sensitivity and specificity were 73.3% and 80.0%, respectively. Conclusion:This study suggests that IL-2/JAK3/STAT5 may be involved in the pathogenesis of AS, and JAK3 mRNA can be used as a biological indicator to monitor the activity of AS disease.

Gram-positive bacteria secrete virulence factors into host cells and cause suppurative inflammation, which leads to the emergence of diseases, therefore poses a great threat to human health. Identifying secreted proteins is beneficial to understand the secretion system and pathogenic mechanism of bacteria, and lays the foundation for further screening of pathogenic factors. Due to the lack of classical signal peptide sequence in non-classical secreted proteins, it is relatively difficult and time-consuming to identify such proteins in large-scale experiments. At present, some computational prediction methods have been proposed, but their performance in predicting non-classical secreted proteins of Gram-positive bacteria is not satisfactory. This paper proposed an ensemble learning model - SPNG+, which integrates six machine learning algorithms including naive bayes, random forest, support vector machine, two gradient promotion trees XGBoost and LightGBM, and K-nearest neighbor through stacking strategy. The results of 5-fold cross validation and independent dataset test show that the SPNG+ is superior to the single machine learning model, the simple integrated learning model and the existing prediction tools in predicting non-classical secreted proteins of Gram-positive bacteria. Compared with the predictors constructed by limited feature coding methods or single machine learning algorithms in the past, the proposed method is a useful supplement to the study of non-classical secreted proteins in Gram-positive bacteria. The source code of SPNG+ is available from https: / / github.com / weidai00 / SPNG.

Objective:To investigation the situation of occupational noise exposure and hearing loss among workers in automobile manufacturing enterprise during 2017-2019 in Wuhan.Methods:Workers in automobile manufacturing who underwent physical examination in Wuhan Hospital for the Prevention and Treatment of Occupational Diseases from 2017 to 2019 were included as subjects in the cross-sectional survey. Questionnaire survey, noise detection and pure tone threshold test were used. Excluding individuals with working time less than 3 years and information deficiency, 3 948 individuals were finally included in the study.Results:Among 3 948 workers, 128 workers had hearing loss and the rate of hearing loss was 3.24%, among which 101 workers had high-frequency hearing loss and 27 workers were diagnosed as occupational noise deafness. The prevalence of hearing loss among workers previously exposed to noise was significantly higher than that without prior exposure (12.10%, 0.96%, P<0.05) . The prevalence of hearing loss among workers with occupational noise exposure <80 dB (A) , 80~<85 dB (A) and ≥85 dB (A) was 1.83%, 2.69% and 5.09%, respectively. The prevalence of high frequency hearing loss was 1.60%, 2.05% and 3.71%, respectively. The prevalence of occupational noise deafness was 0.23%, 0.64% and 1.38%, respectively. The prevalence of hearing loss and high frequency hearing loss among workers exposed to different occupational noise was statistically significant ( P<0.05) , while the prevalence of occupational noise deafness was not statistically significant ( P>0.05) . There were statistically significant differences in the prevalence of hearing loss (2.88%, 4.45%) and occupational noise deafness (0.46%, 1.41%) between those who used protective equipment and those who did not ( P<0.05) . Compared with workers exposed to occupational noise <80 dB (A) , workers exposed to occupational noise ≥85 dB (A) had A 3.16-fold increased risk of hearing loss ( OR=3.16, 95% CI: 1.44~6.95, P<0.05) . Compared to workers using hearing protective equipment, the risk of hearing loss ( OR=1.96, 95% CI: 1.25~3.06, P<0.05) and occupational noise deafness ( OR=3.46, 95% CI: 1.51-7.96, P<0.05) significantly increased among those without using hearing protective equipment. Conclusion:The risk of hearing loss in automobile manufacturing workers is significantly associated with occupational noise exposure and the use of hearing protective equipment. Good hearing protection may reduce the risk of occupational noise-induced hearing loss and occupational noise deafness.

Objective:To investigation the situation of occupational noise exposure and hearing loss among workers in automobile manufacturing enterprise during 2017-2019 in Wuhan.Methods:Workers in automobile manufacturing who underwent physical examination in Wuhan Hospital for the Prevention and Treatment of Occupational Diseases from 2017 to 2019 were included as subjects in the cross-sectional survey. Questionnaire survey, noise detection and pure tone threshold test were used. Excluding individuals with working time less than 3 years and information deficiency, 3 948 individuals were finally included in the study.Results:Among 3 948 workers, 128 workers had hearing loss and the rate of hearing loss was 3.24%, among which 101 workers had high-frequency hearing loss and 27 workers were diagnosed as occupational noise deafness. The prevalence of hearing loss among workers previously exposed to noise was significantly higher than that without prior exposure (12.10%, 0.96%, P<0.05) . The prevalence of hearing loss among workers with occupational noise exposure <80 dB (A) , 80~<85 dB (A) and ≥85 dB (A) was 1.83%, 2.69% and 5.09%, respectively. The prevalence of high frequency hearing loss was 1.60%, 2.05% and 3.71%, respectively. The prevalence of occupational noise deafness was 0.23%, 0.64% and 1.38%, respectively. The prevalence of hearing loss and high frequency hearing loss among workers exposed to different occupational noise was statistically significant ( P<0.05) , while the prevalence of occupational noise deafness was not statistically significant ( P>0.05) . There were statistically significant differences in the prevalence of hearing loss (2.88%, 4.45%) and occupational noise deafness (0.46%, 1.41%) between those who used protective equipment and those who did not ( P<0.05) . Compared with workers exposed to occupational noise <80 dB (A) , workers exposed to occupational noise ≥85 dB (A) had A 3.16-fold increased risk of hearing loss ( OR=3.16, 95% CI: 1.44~6.95, P<0.05) . Compared to workers using hearing protective equipment, the risk of hearing loss ( OR=1.96, 95% CI: 1.25~3.06, P<0.05) and occupational noise deafness ( OR=3.46, 95% CI: 1.51-7.96, P<0.05) significantly increased among those without using hearing protective equipment. Conclusion:The risk of hearing loss in automobile manufacturing workers is significantly associated with occupational noise exposure and the use of hearing protective equipment. Good hearing protection may reduce the risk of occupational noise-induced hearing loss and occupational noise deafness.

Metabolomics, which inherits the ideas of genomics and proteomics, has been widely applied in clinical medical research. In the field of kidney transplantation, changes, which occur in the concentration of small molecule metabolites in blood or urine, can be used to identify organs at risk of acute rejection, locate organ damage, and monitor graft function. This article reviews the problems in the field of kidney transplantation, the concepts, characteristics and research methods of metabolomics, as well as the progress in the application of kidney transplantation and the biomarkers that have been discovered.