ObjectiveTo evaluate the antitumor activity of Periplaneta americana extract（PAE） against human-derived lung adenocarcinoma organoids（LUAD-PDOs） and to elucidate its potential mechanism based on transcriptomics. MethodsFresh tumor and adjacent normal tissues from patients with LUAD were collected to construct LUAD-PDOs and normal lung organoid（Nor-PDOs） models using 3D organoid culture technology. The effective intervention concentration of PAE was determined using the cell counting kit-8（CCK-8） assay. Experimental groups included the model group（LUAD-PDOs）， normal group， model administration group（LUAD-PDOs+PAE）， and normal administration group（Nor-PDOs+PAE）. Hematoxylin-eosin（HE） staining was used to observe the pathological structures of PDOs， immunohistochemistry（IHC） was performed to detect the expressions of the proliferation marker Ki-67 and lung adenocarcinoma differentiation markers cytokeratin-7（CK-7） and Napsin A， TUNEL staining was applied to detect cell apoptosis. RNA sequencing（RNA-Seq） was conducted to identify differentially expressed genes（DEGs）， followed by Gene Ontology（GO）， Kyoto Encyclopedia of Genes and Genomes（KEGG）， and Gene Set Enrichment Analysis（GSEA）， alongside protein-protein interaction（PPI） network analysis to screen core mechanisms. Finally， key targets were validated by integrating external database analysis with immunofluorescence（IF）. ResultsNor-PDOs and LUAD-PDOs that highly recapitulated the pathological characteristics of the primary tissues were successfully established. The CCK-8 assay determined that the effective intervention concentration of PAE was 16 g·L^-1. Morphological observation showed that Nor-PDOs exhibited lumen-forming structures， whereas LUAD-PDOs displayed dense， solid structures. CCK-8 and TUNEL assays revealed that， compared with the model group， PAE intervention inhibited the proliferation of LUAD-PDOs and promoted apoptosis in LUAD cells， while showing no significant effect on the viability of Nor-PDOs. Transcriptomic analysis identified 719 DEGs that were significantly reversed after PAE intervention（347 up-regulated and 372 down-regulated）（P<0.05）. GO enrichment analysis indicated that DEGs in the model administration group were significantly enriched in biological processes related to cell cycle regulation compared to the model group. KEGG pathway analysis revealed that PAE affected pathways related to proliferation and metabolism， including pathways in cancer and the p53 signaling pathway. GSEA further confirmed that PAE significantly enhanced the activity of the p53 signaling pathway（P<0.05）. PPI network analysis indicated that breast cancer type 1 susceptibility protein（BRCA1） and checkpoint kinase 1（CHEK1） were the core down-regulated targets in the p53 pathway. IF verified the high expression of BRCA1 and CHEK1 in LUAD-PDOs and their significant downregulation after PAE intervention（P<0.05）. Furthermore， survival analysis based on The Cancer Genome Atlas（TCGA） database indicated that low expression of BRCA1 and CHEK1 was significantly associated with prolonged overall survival in patients with LUAD（P<0.05）. ConclusionPAE effectively inhibits proliferation of LUAD-PDOs and promotes their apoptosis， its anti-tumor mechanism is potentially associated with the activation of the p53 signaling pathway， with BRCA1 and CHEK1 genes likely serving as key downstream targets for the effects of PAE.

Olfactory receptors (ORs) form the largest superfamily of G protein-coupled receptors (GPCRs). Traditionally recognized for their role in the nasal olfactory epithelium, where they mediate the sense of smell, accumulating evidence has firmly established their ectopic expression in non-olfactory tissues, including the intestine, lungs, and kidneys. The intestine, as the primary site for nutrient digestion and absorption, harbors a highly complex chemical environment. To adapt to this environment, the gut employs a sophisticated network of “chemosensors” to monitor luminal contents and maintain homeostasis. Among these sensors, intestinal ORs have emerged as crucial functional components, serving as a molecular bridge that connects environmental chemical signals—such as food-derived odorants—to specific physiological responses. This discovery has significantly deepened our understanding of how dietary flavors and compounds influence intestinal physiology at the molecular level. This review systematically summarizes the expression profiles, ligand classification, and biological functions of ORs within the gastrointestinal tract. Studies indicate that intestinal ORs exhibit distinct spatial distribution patterns across different gut segments and display cell-type specificity, particularly within enterocytes and enteroendocrine cells. These receptors function as versatile sensors capable of recognizing a wide variety of ligands, including exogenous dietary components, gut microbiota metabolites such as short-chain fatty acids, and endogenous small molecules like azelaic acid. Upon activation by specific ligands, intestinal ORs trigger intracellular signaling cascades, primarily involving the AC-cAMP-PKA pathway or calcium influx channels. A major focus of this review is to elucidate the molecular mechanisms by which these receptors regulate the secretion of gut hormones. Activation of specific ORs in enteroendocrine cells has been shown to stimulate the release of hormones such as glucagon-like peptide-1 (GLP-1), peptide YY (PYY), and serotonin (5-HT), thereby modulating systemic energy metabolism, glucose homeostasis, and gastrointestinal motility. Furthermore, the review addresses the critical roles of ORs in immune regulation and pathology. Evidence suggests that specific ORs contribute to the maintenance of intestinal immune homeostasis and may offer protection against inflammation. Beyond their involvement in inflammatory responses, ORs such as Olfr78 have been shown to regulate the differentiation and function of intestinal endocrine cells. Similarly, Olfr544 has been demonstrated to alleviate intestinal inflammation by remodeling the gut microbiome and metabolome. These findings collectively suggest that specific ORs hold promise as therapeutic targets for mitigating intestinal inflammation and maintaining gut homeostasis. Additionally, the review explores the emerging role of ORs in cancer. Although OR expression is often downregulated in tumor tissues compared to normal mucosa, activation of specific ORs by certain ligands can inhibit tumor cell proliferation and migration and induce apoptosis via pathways such as MEK/ERK and p38 MAPK. Conversely, other receptors, such as OR7C1, may serve as biomarkers for cancer-initiating cells. In conclusion, intestinal ORs represent a vital component of the gut’s sensory network. The review also discusses the translational potential of these findings. By elucidating the precise pairing relationships between dietary components and specific ORs, novel therapeutic strategies could be developed. Intestinal ORs may thus emerge as promising targets for nutritional and pharmacological interventions in metabolic diseases, inflammatory bowel diseases, and malignancies.

Metabolic dysfunction-associated steatotic liver disease (MASLD) has become the most prevalent chronic liver disease worldwide, affecting approximately 32%-38% of the adult population and posing a growing public health burden. MASLD represents a continuous disease spectrum ranging from simple steatosis to metabolic dysfunction-associated steatohepatitis (MASH), progressive hepatic fibrosis, cirrhosis, and ultimately hepatocellular carcinoma (HCC). The pathological core of MASLD lies in disruption of hepatic lipid metabolic homeostasis, characterized by an imbalance among de novo lipogenesis, fatty acid β-oxidation, and very-low-density lipoprotein (VLDL)-mediated lipid export. This metabolic disequilibrium subsequently drives inflammatory injury and fibrotic progression. Among the multiple regulatory pathways involved, thyroid hormone (TH) signaling has emerged as a central regulator of hepatic metabolic homeostasis. The liver is a major peripheral target organ of TH action, where TH predominantly exerts its metabolic effects through thyroid hormone receptor β (TRβ). Large-scale epidemiological studies and meta-analyses have demonstrated that hypothyroidism is significantly associated with increased MASLD prevalence, more severe histological injury, and advanced hepatic fibrosis, suggesting that dysregulation of TH signaling may participate throughout the entire MASLD disease spectrum. At the molecular level, TH regulates hepatic lipid metabolism by coordinating suppression of lipogenesis, enhancement of mitochondrial fatty acid oxidation, and promotion of VLDL assembly and secretion through integrated genomic actions of the T3-TRβ axis and non-genomic signaling pathways. Across different stages of MASLD, TH signaling exerts stage-dependent protective effects. In the steatosis stage, TH improves metabolic flexibility by modulating insulin sensitivity, glucose metabolism, and lipid droplet clearance, thereby alleviating early lipotoxic stress. During progression to MASH, TH attenuates inflammatory amplification by improving mitochondrial homeostasis, suppressing activation of the NOD-like receptor family pyrin domain containing 3 (NLRP3) inflammasome, and modulating the gut-liver axis microenvironment. In advanced stages, TH signaling influences hepatic stellate cell activation and extracellular matrix deposition, partly through interaction with the transforming growth factor-β (TGF-β)/SMAD pathway, while alterations in intrahepatic TH availability, mediated by dynamic changes in iodothyronine deiodinase 1 (DIO1), contribute to fibrosis progression and hepatocellular dedifferentiation. In hepatocellular carcinoma, coordinated downregulation of TRβ and DIO1 establishes a tumor-associated hypothyroid state that promotes metabolic reprogramming and tumor progression. The clinical relevance of TH signaling in MASLD has been underscored by the recent approval of Resmetirom, a liver-targeted TRβ‑selective agonist, for the treatment of non-cirrhotic MASH with moderate-to-severe fibrosis (F2-F3). This approval represents a landmark transition from mechanistic understanding to metabolism-centered precision therapy in MASLD. Clinical trials have demonstrated that Resmetirom not only improves key histological endpoints, including MASH resolution and fibrosis regression, but also favorably modulates atherogenic lipid profiles, highlighting the therapeutic potential of selectively targeting hepatic TH pathways. This review systematically summarizes the multidimensional regulatory roles of TH across the MASLD disease spectrum and discusses emerging diagnostic and therapeutic implications of TH-based interventions, aiming to inform future mechanistic research and optimize clinical management strategies.

ObjectiveTo explore the vascular endothelial injury in male mice caused by exposure to polystyrene microplastics （PS-MPs） and the intervention effect of luteolin on vascular remodeling. Additionally， to investigate the mechanism through the oxidative system and metabolomics. MethodsThirty-two C57BL/6 mice （6-8 weeks old） were randomly divided into the saline group （saline group）， the 0.1 mg/kg PS-MPs exposure group （0.1PS-MPs group）， the 1 mg/kg PS-MPs exposure group （1PS-MPs group）， and the 1 mg/kg PS-MPs + luteolin treatment group （1PS-MPs + Lut group）， with 8 mice in each group. After 8 weeks of intervention， the body weight， blood pressure， aortic organ coefficient， and aortic histopathological changes of mice in each group were detected； the total cholesterol （TC）， triglyceride （TG）， and high-density lipoprotein cholesterol （HDL-C） lipid metabolism-related indicators in the aorta of mice were detected； the reactive oxygen species （ROS）， glutathione （GSH）， and malondialdehyde （MDA） oxidative stress-related indicators were detected； the endothelin （ET-1）， nitric oxide （NO）， vascular endothelial growth factor A （VEGF-A）， vascular cell adhesion molecule-1 （VCAM-1/CD106）， and intercellular adhesion molecule-1 （ICAM-1/CD54） endothelial function-related indicators and serum metabolomics were detected. ResultsCompared to the saline group， exposure to PS-MPs resulted in pathological thickening of the mouse aorta， increased aortic organ coefficient， and elevated blood pressure. Lipid metabolism-related indicators， including TC and TG， were elevated， while HDL-C was reduced， indicating lipid metabolism disorder in mice. Oxidative stress markers such as ROS and MDA increased， whereas GSH decreased， demonstrating oxidative damage. Vascular endothelial inflammation and injury markers， including ET-1， VEGF-A， VCAM-1， and ICAM-1， were upregulated， while the vasodilatory substance NO was downregulated， confirming endothelial injury. Furthermore， serum metabolomics results revealed that PS-MPs exposure induced endothelial damage by disrupting metabolic pathways such as the citrate cycle. Compared to the PS-MPs group， luteolin significantly reversed these effects， attenuating oxidative stress and lipid metabolism disorders， and effectively repairing endothelial injury. ConclusionPS-MPs induce vascular toxicity through oxidative stress and lipid metabolism. Luteolin effectively alleviates endothelial damage and vascular remodeling.

Objective To analyze the infection status and epidemic trends of soil-borne nematode infections in Yubei, Chongqing City, in 2010,2021, and 2022. Methods The local populations from four survey sites of four towns in 2010 and five sites of five towns in 2021 and 2022 were surveyed regarding their basic information using a unified form. Fecal samples of the participants were collected and tested for soil-borne nematode infections using the modified Kato-Katz thick smear method. Results In 2010, 2 049 participants were surveyed, followed by 1 000 participants in 2021 and 2022. The overall prevalence of parasitic infections declined significantly from 3.86% to 0.20%. In 2010, soil-transmitted nematode included hookworms(3.81%) and roundworms(0.29%). In 2021, the infection rates of roundworms and hookworms were 1.70% and 0.10% respectively. Notably, only Ascaris was identified in 2022(0.20%). The≥60 age group consistently exhibited the highest infection rates across all surveys, followed by the 40-59 age group. The infection rates of males in the three surveys were 3.31%,1.92%, and 0.20% respectively, and those of females were 4.37%, 1.46%, and 0.20% respectively. There was no statistically significant difference in the infection rates between males and females. Educational attainment was inversely associated with infection; in 2010, the highest prevalence was observed among those with primary education or below, whereas in 2021, illiterate or semi-literate individuals showed the highest susceptibility. The occupational distribution of infections in 2010 indicated that retirees (8.33%), farmers(4.86%), and homemakers or unemployed individuals(3.45%)were the most affected. However, in 2021 and 2022, farmers emerged as the predominant occupational group with soil-transmitted nematode infections. Conclusions The infection rate of soil-borne nematodes showed a decreasing trend in Yubei, and the infection species changed from hookworms in 2010 to Ascaris in 2022. Farmers, the elderly, and people with low education levels should continue to be the focus of preventive and control efforts.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective To investigate the differences in demographic characteristics,reproductive health status,and the distribution of pregnancy-related diseases between couples conceived via assisted reproductive technology(ART)and naturally conceived couples,and to analyze the impact of ART treatment on the incidence of preterm birth(PTB)in singleton and twin and multiple pregnancies.Methods We conducted a retrospective analysis of the maternal and infant cohort data of Jing'an District from 2013 to 2020.Based on the conception method,the subjects were categorized into two groups:the ART group and the natural conception group.Chi-square test was applied to compare baseline characteristics and disease distributions differences between the two groups,and logistic regression models were used to evaluate the association between ART and the PTB risks.A causal mediation model was used to evaluate the mediating effect of twin and multiple pregnancy in the relationship between ART and PTB.Results A total of 117 717 parturients were included,6 265 in the ART group and 111 452 in the natural conception group.Compared with the natural conception group,couples in the ART group were significantly older and had a higher prevalence of reproductive system diseases.The incidences of diabetes and hypertensive disorders during pregnancy in ART parturient were 13.76%and 9.99%,respectively,which were significantly higher than 7.88%and 4.75%in the natural conception group(both P<0.001).The overall PTB rate in the ART group was 14.81%,higher than 5.35%in the natural conceptions group(P<0.001).The PTB rate in ART for singleton pregnancies in the ART group was 6.40%,higher than 4.83%in the natural conception group(P<0.001),while the PTB rate in ART for twin and multiple pregnancies in the ART group was 53.97%,lower than 60.42%in the natural conception group(P<0.05).Mediation analysis showed that 97.99%of the effect of ART on PTB was mediated by twin and multiple pregnancy,with ART increasing the PTB risk by 3.44 times through multiple pregnancy.Conclusion The overall PTB rate of ART recipients is higher than that of natural recipients,but ART does not increase the PTB risk in singleton and twin and multiple pregnancies.Twin and multiple pregnancy is the key mediating factor contributing to PTB in ART-conceived recipients.Compared with naturally conceived couples,ART conception couples own more advanced maternal age,and have higher risks of suffering gestational diabetes,gestational hypertension,and PTB.

Objective To evaluate the safety and efficacy of valve-in-valve transcatheter mitral valve replacement(ViV-TMVR)in patients with bioprosthetic valve degeneration who are at high surgical risk.Methods This study is a multi-center,retrospective cohort analysis of 20 consecutive patients who underwent transseptal ViV-TMVR using the Edwards SAPIEN 3 transcatheter heart valve(THV).The primary endpoints include technical success and procedural success,both defined according to the Mitral Valve Academic Research Consortium(MVARC)criteria,as well as mortality and functional change assessed based on New York Heart Association(NYHA)classification at 30-days and six months post-procedure.Clinical follow-up assessments are conducted at 30-days and six months.Results From February 2021 to October 2022,a total of 20 patients with symptoms of bioprosthetic valve degeneration were enrolled across nine sites in China.The patients had a mean age of(73.5±5.5)years,with 85.0％being females and 70.0％classified as NYHA class Ⅲ/Ⅳ.The study achieved a 100.0％technical success rate and a 90.0％procedural success rate finally.All patients remained alive during the 30-day follow-up period.However,six months post-intervention,two patients(10.0％)were re-hospitalized due to heart failure,and sadly,one of them(5.0％)died.None of the patients reported any adverse events related to ViV-TMVR during the follow-up period.Notably,there was a significant improvement in NYHA class compared to baseline(P=0.0004)at six-month follow-ups.Conclusions The transseptal ViV-TMVR technique proved to be highly successful and was associated with significant improvement in NYHA class function.These findings strongly suggest that it serves as a safe and efficient treatment alternative for high-risk patients suffering from bioprosthetic valve degeneration.

Aim To explore the mechanism of baicalin combined with heat stimulation in treating acute lym-phoblastic leukemia(ALL)based on network pharma-cology and in vitro experiments.Methods The CCK-8 assay was used to screen the suitable conditions for heat stimulation to interfere ALL cell lines Jurkat,CCRF-CEM,Hut-78 and a normal lymphocyte HMy2.CIR,and the effects of baicalin combined with heat stimulation on the proliferation of three ALL cell lines and a normal lymphocyte were tested.The key targets of baicalin combined with fever stimulation for the treatment of ALL were obtained based on network phar-macological analysis,and the potential mechanisms were predicted by gene ontology(GO)annotation and kyoto encyclopedia of genes and genomes(KEGG)en-richment.The expression levels of TNF-α,AKT1,TYMS and CASP3 mRNA in ALL cell lines Jurkat and CCRF-CEM were examined by RT-qPCR with baicalin alone and baicalin combined with heat stimulation.Results The optimal conditions for heat stimulation to intervene ALL cells were 41 ℃ for 24 h,and heat stimulation combined with baicalin synergistically inhibited the growth of ALL cell lines and effectively reduced the cy-totoxicity of baicalin.Based on the network pharmaco-logical analysis,55 intersecting targets of baicalin with ALL diseases and 77 intersecting targets of baicalin with fever were obtained.The results of GO annotation and KEGG enrichment suggested that baicalin com-bined with fever stimulation to intervene ALL might be associated with influencing intracellular reactive oxygen species metabolism,DNA transcription and apoptotic processes involved in cysteine enzymes.Apoptosis,TNF and IL-17 signaling pathways were the key pathways for baicalin combined with heat stimulation in treating ALL.Under heat stimulation at 41 ℃ using SDHA gene as housekeeping gene,in vitro experiments showed that baicalin significantly up-regulated the expression of TNF-α and CASP3,and down-regulated the expression of TYMS in ALL cells.Conclusions Based on net-work pharmacologic analyses and in vitro experiments,baicalin combined with heat stimulation can regulate TNF-α and CASP3 gene levels in ALL cells and de-stroy cellular structure to promote cell apoptosis,thus synergistically treating ALL.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.