Background Co-exposure to noise and microwave radiation occurs frequently. The central nervous system has been identified as a sensitive target organ for both noise and microwave exposure individually, and the underlying mechanisms remain poorly understood. The specific biological effects resulting from co-exposure to these two factors have yet to be fully elucidated. Objective To clarify the effects of co-exposure to noise and microwave on neurobehavior and hippocampal tissue structure, and to explore the underlying mechanism through the assessment of serum cytokines. Methods C57BL/6N mice were selected and randomly assigned to a blank control group, a noise group, a microwave group, and a combined noise & microwave exposure group. To establish the exposure models, the noise group was subjected to broadband noise at 100 dB for 2 h, while the microwave group received radiation at a central frequency of 9.375 GHz with an average power density of 12 mW·cm⁻² and a specific absorption rate of 2.58 W·kg⁻¹ for 15 min. Open field and tail suspension tests assessed anxiety-like emotional behaviour; novel object recognition and Y-maze tests evaluated cognitive function. Histological changes in hippocampal tissue were examined using haematoxylin and eosin (HE) staining, and Nissl staining under light microscopy. Serum cytokine levels were measured using radioimmunoassay and enzyme-linked immunosorbent assay (ELISA). Results After 3 d of exposure, the noise, microwave, and combined exposure groups showed significant reductions in exploration frequency, duration, and distance within the central zone of the open field test compared to the control group (P < 0.01); the combined exposure group exhibited increased ratios of peripheral-to-central exploration time and distance (P < 0.05). After 7 d of exposure, compared with the control group, the noise group maintained a decrease in central zone exploration time (P < 0.01), while the combined exposure group showed persistent decline across all central zone metrics (P < 0.05) and elevated peripheral-to-central ratios (P < 0.05); compared to the microwave group, the combined exposure group showed significant less time in the central zone (P < 0.05) and higher peripheral-to-central ratios (P < 0.05). Regarding behaviour and cognition, compared with the control group, the combined exposure group showed increased immobility time in the tail suspension test after 3 d of exposure (P < 0.01). At this interval, all exposure groups demonstrated reduced frequency and duration of novel object recognition (P < 0.05), with the combined exposure group showing a marked decrease in novel arm exploration time (P < 0.01). After 7 d of exposure, compared with the control group, the noise group showed reduced novel object recognition frequency (P < 0.05), and both the noise and microwave groups exhibited decreased novel arm exploration time (P < 0.05). Pathological alterations including an increased number of hyperchromatic nuclei and depleted Nissl bodies were observed in the CA3 and DG regions across all exposure groups with the most severe lesions observed in the combined exposure group. Serum levels of central nervous system-specific protein β (S-100β), glial fibrillary acidic protein (GFAP), and corticosterone (CORT) were significantly elevated in all exposure groups compared with the control group (P < 0.05). Aquaporin-4 (AQP4) levels increased in the combined exposure group (P < 0.05), while CXC chemokine ligand 10 (CXCL10) levels rose in both the noise and combined groups compared with the control group (P < 0.05). Specifically, S-100β and CXCL10 levels in the combined exposure group were higher than those in the microwave group (P < 0.05); moreover, levels of S-100β, GFAP, CORT, AQP4, and CXCL10 in the combined exposure group were significantly higher than those in the noise group (P < 0.05). Conclusion Combined exposure to noise and microwave radiation induces pathological changes in the hippocampus of mice, increases levels of serum stress hormones and neuro-specific biomarkers. These impairments are more severe than those observed following single-factor exposure. The underlaying mechanism may be related to systemic stress response, neuronal damage, astrocyte activation, and changes in blood-brain barrier permeability, leading to emotional behavioral abnormalities and cognitive decline.

Sishen Pills and its separated prescriptions are classic prescriptions of traditional Chinese medicine to treat intestinal diseases. In this study, a high-performance liquid chromatography-electrospray ionization tandem mass spectrometry(HPLC-ESI-MS/MS) technology was used to identify the components of Sishen Pills, Ershen Pills, and Wuweizi Powder. The positive and negative ion sources of electrospray ionization were simultaneously collected by mass spectrometry. A total of 11 effective components were detected in Sishen Pills, with four effective components detected in Ershen Pills and eight effective components detected in Wuweizi Powder, respectively. To explore the effects of Sishen Pills and its separated prescriptions on the human intestinal flora, an in vitro anaerobic fermentation model was established, and the human intestinal flora was incubated with Sishen Pills, Ershen Pills, and Wuweizi Powder in vitro. The 16S rDNA sequencing technology was used to analyze the changes in the intestinal flora. The results showed that compared with the control group, Sishen Pills, and its separated prescriptions could decrease the intestinal flora abundance and increase the Shannon index after fermentation. The abundance of Bifidobacterium was significantly increased in the Sishen Pills and Ershen Pills groups. However, the abundance of Lactobacillus, Weissella, and Pediococcus was significantly increased in the Wuweizi Powder group. After fermentation for 12 h, the pH of the fermentation solution of three kinds of liquids with feces gradually decreased and was lower than that of the control group. The decreasing amplitude in the Wuweizi Powder group was the most obvious. The single-bacteria fermentation experiments further confirmed that Sishen Pills and Wuweizi Powder had inhibitory effects on Escherichia coli, Staphylococcus aureus, and Enterococcus faecalis, and the antibacterial activity of Wuweizi Powder was stronger than that of Sishen Pills. Both Sishen Pills and Ershen Pills could promote the growth of Lactobacillus brevis, and Ershen Pills could promote the growth of Bifidobacterium adolescentis. This study provided a more sufficient theoretical basis for the clinical application of Sishen Pills and its separated prescriptions.
Humans ; Gastrointestinal Microbiome/drug effects* ; Drugs, Chinese Herbal/chemistry* ; Fermentation/drug effects* ; Bacteria/drug effects* ; Chromatography, High Pressure Liquid ; Tandem Mass Spectrometry ; Intestines/microbiology*

Objective To mine and analyze the routine blood test data of children with allergic rhinitis (AR), identify routine blood parameters related to childhood allergic rhinitis, establish an effective diagnostic model, and evaluate the performance of the model. Methods This study was a retrospective study of clinical cases. The experimental group comprised a total of 1110 children diagnosed with AR at the First Affiliated Hospital of Air Force Medical University during the period from December 12, 2020 to December 12, 2021, while the control group included 1109 children without a history of allergic rhinitis or other allergic diseases who underwent routine physical examinations during the same period. Information such as age, sex and routine blood test results was collected for all subjects. The levels of routine blood test indicators were compared between AR children and healthy children using comprehensive intelligent baseline analysis, with indicators of P≥0.05 excluded; variables were screened by Lasso regression. Binary Logistic regression was used to further evaluate the influence of multiple routine blood indexes on the results. Five kinds of machine model algorithms were used, namely extreme value gradient lift (XGBoost), logistic regression (LR), gradient lift decision tree (LGBMC), Random forest (RF) and adaptive lift algorithm (AdaBoost), to establish the diagnostic models. The receiver operating characteristic (ROC) curve was used to screen the optimal model. The best LightGBM algorithm was used to build an online patient risk assessment tool for clinical application. Results Statistically significant differences were observed between the AR group and the control group in the following routine blood test indicators: mean cellular hemoglobin concentration (MCHC), hemoglobin (HGB), absolute value of basophils (BASO), absolute value of eosinophils (EOS), large platelet ratio (P-LCR), mean platelet volume (MPV), platelet distribution width (PDW), platelet count (PLT), absolute values of leukocyte neutrophil (W-LCC), leukocyte monocyte (W-MCC), leukocyte lymphocyte (W-SCC), and age. Lasso regression identified these variables as important predictors, and binary Logistic regression further analyzed the significant influence of these variables on the results. The optimal machine learning algorithm LightGBM was used to establish a multi-index joint detection model. The model showed robust prediction performance in the training set, with AUC values of 0.8512 and 0.8103 in the internal validation set. Conclusion The identified routine blood parameters can be used as potential biomarkers for early diagnosis and risk assessment of AR, which can improve the accuracy and efficiency of diagnosis. The established model provides scientific basis for more accurate diagnostic tools and personalized prevention strategies. Future studies should prospectively validate these findings and explore their applicability in other related diseases.
Humans ; Male ; Female ; Rhinitis, Allergic/blood* ; Child ; Biomarkers/blood* ; Retrospective Studies ; Early Diagnosis ; Child, Preschool ; ROC Curve ; Logistic Models ; Hematologic Tests ; Algorithms ; Adolescent ; Machine Learning

OBJECTIVE: To investigate the Wnt signaling pathway and miRNAs mechanism of extracts of Plastrum Testudinis (PT) in the treatment of osteoporosis (OP). METHODS: Thirty female Sprague Dawley rats were randomly divided into 5 groups by random number table method, including sham group, ovariectomized group (OVX), ovariectomized groups treated with high-, medium-, and low-dose PT (160, 80, 40 mg/kg per day, respectively), with 6 rats in each group. Except for the sham group, the other rats underwent bilateral ovariectomy to simulate OP and received PT by oral gavage for 10 consecutive weeks. After treatment, bone mineral density was measured by dual-energy X-ray absorptiometry; bone microstructure was analyzed by micro-computed tomography and hematoxylin and eosin staining; and the expressions of osteogenic differentiation-related factors were detected by immunochemistry, Western blot, and quantitative polymerase chain reaction. In addition, Dickkopf-1 (Dkk-1) was used to inhibit the Wnt signaling pathway in bone marrow mesenchymal stem cells (BMSCs) and miRNA overexpression was used to evaluate the effect of miR-214 on the osteogenic differentiation of BMSCs. Subsequently, PT extract was used to rescue the effects of Dkk-1 and miR-214, and its impacts on the osteogenic differentiation-related factors of BMSCs were evaluated. RESULTS: PT-M and PT-L significantly reduced the weight gain in OVX rats (P<0.05). PT also regulated the bone mass and bone microarchitecture of the femur in OVX rats, and increased the expressions of bone formation-related factors including alkaline phosphatase, bone morphogenetic protein type 2, collagen type I alpha 1, and runt-related transcription factor 2 when compared with the OVX group (P<0.05 or P<0.01). Meanwhile, different doses of PT significantly rescued the inhibition of Wnt signaling pathway-related factors in OVX rats, and increased the mRNA or protein expressions of Wnt3a, β-catenin, glycogen synthase kinase-3β, and low-density lipoprotein receptor-related protein 5 (P<0.05 or P<0.01). PT stimulated the osteogenic differentiation of BMSCs inhibited by Dkk-1 and activated the Wnt signaling pathway. In addition, the expression of miR-214 was decreased in OVX rats (P<0.01), and it was negatively correlated with the osteogenic differentiation of BMSCs (P<0.01). MiR-214 mimic inhibited Wnt signaling pathway in BMSCs (P<0.05 or P<0.01). Conversely, PT effectively counteracted the effect of miR-214 mimic, thereby activating the Wnt signaling pathway and stimulating osteogenic differentiation in BMSCs (P<0.05 or P<0.01). CONCLUSION PT stimulates bone formation in OVX rats through β-catenin-mediated Wnt signaling pathway, which may be related to inhibiting miR-214 in BMSCs.
Animals ; MicroRNAs/genetics* ; Female ; Rats, Sprague-Dawley ; Wnt Signaling Pathway/genetics* ; Osteogenesis/genetics* ; Mesenchymal Stem Cells/cytology* ; Cell Differentiation/drug effects* ; Bone Density/drug effects* ; Ovariectomy ; Osteoporosis/drug therapy* ; beta Catenin/metabolism* ; Rats ; Intercellular Signaling Peptides and Proteins/metabolism* ; Drugs, Chinese Herbal/pharmacology*

Natural product-based drug combinations (NPDCs) present distinctive advantages in treating complex diseases. While high-throughput screening (HTS) and conventional computational methods have partially accelerated synergistic drug combination discovery, their applications remain constrained by experimental data fragmentation, high costs, and extensive combinatorial space. Recent developments in artificial intelligence (AI), encompassing traditional machine learning and deep learning algorithms, have been extensively applied in NPDC identification. Through the integration of multi-source heterogeneous data and autonomous feature extraction, prediction accuracy has markedly improved, offering a robust technical approach for novel NPDC discovery. This review comprehensively examines recent advances in AI-driven NPDC prediction, presents relevant data resources and algorithmic frameworks, and evaluates current limitations and future prospects. AI methodologies are anticipated to substantially expedite NPDC discovery and inform experimental validation.
Artificial Intelligence ; Biological Products/chemistry* ; Humans ; Drug Combinations ; Drug Discovery/methods* ; Machine Learning ; Algorithms

Cuproptosis, a recently identified form of regulated cell death triggered by excess intracellular copper, has emerged as a promising cytotoxic strategy for cancer therapy. However, the therapeutic efficacy of copper ionophores such as elesclomol (ES) is often hindered by cellular copper homeostasis mechanisms that limit copper influx and cuproptosis induction. To address this challenge, we developed a nanoagent utilizing outer membrane vesicle (OMV) derived from Akkermansia muciniphila (Akk) for co-delivery of antioxidant 1 copper chaperone (Atox1)-targeting siRNA and ES (siAtox1/ES@OMV) to tumors. In vitro, we demonstrated that Atox1 knockdown via siRNA significantly disrupted copper export mechanisms, resulting in elevated intracellular copper levels. Simultaneously, ES facilitated efficient copper influx and mitochondrial transport, leading to Fe-S cluster depletion, increased proteotoxic stress, and robust cuproptosis. In vivo, siAtox1/ES@OMV achieved targeted tumor delivery and induced pronounced cuproptosis. Furthermore, leveraging the immunomodulatory properties of OMVs, siAtox1/ES@OMV promoted T-cell infiltration and the activation of tumor-reactive cytotoxic T cells, enhancing tumor immune responses. The combination of siAtox1/ES-induced cuproptosis and immunogenic cell death synergistically suppressed tumor growth in both subcutaneous breast cancer and orthotopic rectal cancer mouse models. This study highlights the potential of integrating copper homeostasis disruption with a copper ionophore using an immunomodulatory OMV-based vector, offering a promising combinatorial strategy for cancer therapy.

AIM:To investigate the preventive and therapeutic effects of sesamin(SES)on fatty liver disease in rats with hypertension combined with dyslipidemia,and to explore the potential mecha-nisms based on mRNA-seq.METHODS:Spontane-ously hypertensive rats(SHRs)were fed a high-fat,high-cholesterol diet to establish a rat model of hy-pertension combined with dyslipidemia,and then treated with SES for 16 weeks continuously.The ex-periment was divided into four groups:WKY,SHR,Model,and Model+SES(160 mg·kg-1·d-1).Blood pressure was measured using the tail-cuff method.Body weight was monitored,and body mass index was calculated.Liver morphology was detected by ultrasound,and liver thickness was measured.Liver wet weight was weighed,and liver index was calcu-lated.Liver volume was detected by the water dis-placement method.Serum triglycerides(TG),total cholesterol(TC),low-density lipoprotein cholesterol(LDL-C),high-density lipoprotein cholesterol(HDL-C),alanine aminotransferase(ALT),aspartate amino-transferase(AST),and total bile acids(TBA)were de-tected by ELISA.Liver sequencing analysis was per-formed using mRNA-seq.Liver histomorphological changes were observed by HE staining.The degree of hepatic steatosis was observed by Oil Red O stain-ing,and the degree of hepatic fibrosis was observed by MASSON staining.The mRNA expression of Al-dh1a7,Nnmt,Irs2,Pltp,and Scd was detected by q-PCR.The protein expression of Scd,Nnmt,AMPK,p-AMPK,PPARα,and PPARγ was detected by Western blotting.RESULTS:After 16 weeks of continuous SES administration to rats with hypertension combined with dyslipidemia,blood pressure was significantly reduced(P＜0.01),and body weight was decreased.Serum TG,TC,and LDL-C levels were decreased,while HDL-C levels were increased.Serum ALT and AST levels were decreased.Liver weight,organ in-dex,liver thickness,and liver volume were de-creased.The degree of hepatic steatosis and hepat-ic fibrosis was improved.A total of 545 differentially expressed mRNAs were identified in the livers of rats in each group,of which 278 were upregulated and 267 were downregulated.Among the 27 com-monly differentially expressed mRNAs,five mRNAs related to lipid metabolism were screened,namely Aldh1a7,Nnmt,Irs2,Pltp,and Scd.KEGG enrich-ment analysis showed that the enriched pathways were AMPK and PPAR.Further validation revealed that in the SES-treated group,the mRNA expression of Scd in the liver was decreased,while the mRNA expression of Nnmt was increased.The protein ex-pression of Scd was decreased,while the protein ex-pression of Nnmt,AMPK,p-AMPK,PPARα,and PPARγ was increased.CONCLUSION:SES has preven-tive and therapeutic effects on fatty liver disease in rats with hypertension combined with dyslipidemia,and its mechanism of action may be related to the reduction of Scd expression levels in the liver and the increase in the expression of Nnmt,AMPK,p-AMPK,PPARα,and PPARγ.

Objective To understand the implementation of WS/T 508-2016 and the status of washing and disin-fection of medical textiles in China,and provide basis for the revision of the standard.Methods A questionnaire survey was conducted on the management of medical institutions and washing and disinfection workplace,building layout,personnel protection,equipment and supplies,washing and disinfection principles,and hygiene quality mo-nitoring of medical textiles in 323 medical institutions and 31 washing institutions in China.Meanwhile,microbio-logical index sampling was conducted on 234 pieces of medical textiles in 9 medical institutions and 8 washing insti-tutions in Hubei,Shanxi,Shanghai,and Sichuan Provinces before and after washing and disinfection.Results The awareness rates of WS/T 508-2016 among medical institutions and washing institutions were 96.90％and 96.77％,respectively,and the implementation rates were 94.12％and 96.77％,respectively.47.99％medical in-stitutions use purchasing services for washing and disinfecting medical textiles,and the higher the level of the medi-cal institution was,the higher the proportion of purchasing services was(x2=15.312,P＜0.001).85.16％medi-cal institutions have conducted risk assessments on service providers,and 52.99％were responsible for or participa-ted in pre-job training by the medical institution.Washing institutions were higher than medical institutions in terms of system soundness rate,pre-job training rate,proportion of quality management leaders and full-time(part-time)quality inspectors,setting rate of hand-washing facilities in zones,passages,isolation barriers,dressing(buffer)room,and toilets,configuration rate of hygiene isolation washing equipment,tunnel washing unit,washing equip-ment with heating functions,drying equipment and mechanical ventilation facilities,and specialty machine washing rate.Among 234 medical textiles specimens,11.97％were detected fungi,and the total fungal colonies in 5 clean textiles exceeded 100 CFU/100 cm2.Conclusion WS/T 508-2016 can further standardize the washing and disin-fection of medical textiles in China through strengthening institutional management,improving the supervision level of service providers,perfecting hardware facilities and layout,introducing new technologies,and increasing the mo-nitoring on fungi in clean textiles.

Objective:To analyze the factors influencing the lung function of coal miners, identify the optimal combination of indicators for evaluating lung function, develop a risk assessment model using machine learning, and offer personalized risk assessment for workers.Methods:In June 2023, through cluster sampling, male underground workers who participated in occupational health examinations at a coal mine in North China from July to August 2018 were selected as the research subjects. Their health examination results and occupational environmental data were collected. A total of 3, 320 coal miners were included. Randomly divide the research subjects into a training set (2324 people) and a validation set (996 people) in a ratio of 7∶3, and the balance of the two sets was tested. Perform LASSO regression analysis using R 4.2.2 software to select relevant important variables, and determine the model's input variables by combining them with relevant literature. Utilize Python 3.8 to construct logistic regression, random forest, support vector machine, and XG Boost models, assess the models' discriminative ability using metrics like accuracy, sensitivity, specificity, F1 score, ROC curve, and AUC, evaluate the models' calibration using Brier score, Log loss score, and calibration curve, and further analyze the clinical performance of the developed models through DCA decision curve analysis.Results:Among the 3 320 coal miners, 856 had abnormal lung function (25.78%). The XG Boost model was identified as the optimal model, achieving a training set accuracy of 87.39%, sensitivity of 86.60%, specificity of 87.67%, F1 score of 0.779, AUC of 0.945, Brier score of 0.071, Log loss of 0.267 and demonstrated good calibration curve consistency.Conclusion:The XG Boost model exhibits superior predictive performance compared to other models, and the model has high application value. The Shapley Additive Explanation (SHAP) method is employed for interpretation, making it a reliable basis for preventing abnormal lung function in coal miners.