As the intricate interplay between microbiota and the host garners increasing research attention, a significant parallel surge has emerged in the investigation of intestinal bacterial extracellular vesicles (BEVs). Most intestinal bacteria secrete BEVs, which harbor specific cargo molecules and exhibit diverse functions, encompassing interactions among bacteria themselves and between bacteria and the host. These interactions can either bolster host health or contribute to various pathologies. By integrating the characteristics of BEVs, we summarized the current research landscape, delving into the intricate interplay between BEVs and different diseases. Furthermore, we offer a succinct overview of the challenges faced in BEVs-based research, encompassing separation, detection, engineering for drug purposes, clinical diagnostics, safety, and future study. In essence, these summaries may serve as invaluable guides for BEVs as communication tools between the gut microbiome and host, ultimately propelling the discovery of novel studies and drug discovery.

Liraglutide (Lira), a glucagon-like peptide-1 (GLP-1) receptor agonist approved for diabetes and obesity, has shown significant potential in treating metabolic dysfunction-associated steatotic liver disease (MASLD). However, its systematic molecular regulation and mechanisms remain underexplored. In this study, a mouse model of MASLD was developed using a high-fat diet (HFD), followed by Lira administration. Proteomics and glycoproteomics were analyzed using label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS), while potential molecular target analysis was conducted via quantitative real-time polymerase chain reaction (qPCR) and Western blotting. Our results revealed that Lira treatment significantly reduced liver weight and serum markers, including alanine aminotransferase (ALT) and others, with glycosylation changes playing a more significant role than overall protein expression. The glycoproteome identified 255 independent glycosylation sites, emphasizing the impact of Lira on amino acid, carbohydrate metabolism, and ferroptosis. Simultaneously, proteomic analysis highlighted its effects on lipid metabolism and fibrosis pathways. 21 signature molecules, including 7 proteins and 14 N-glycosylation sites (N-glycosites), were identified as potential targets. A Lira hydrogel formulation (Lira@fibrin (Fib) Gel) was developed to extend drug dosing intervals, offering enhanced therapeutic efficacy in managing chronic metabolic diseases. Our study demonstrated the importance of glycosylation regulation in the therapeutic effects of Lira on MASLD, identifying potential molecular targets and advancing its clinical application for MASLD treatment.

Alopecia areata （AA） is a common hair loss disorder， and the core pathogenesis is the internal gene-ration of turbid toxin caused by qi movement disorder in the liver， spleen， and kidney. Turbid toxin serves as both a pivotal etiological trigger and a pathological driver of disease exacerbation. Clinically， AA can be classified into four principal patterns， including liver constraint with spleen deficiency， internal accumulation of damp-heat， liver-kidney depletion， and qi-blood depletion. Therapeutic strategies prioritize clearing and resolving turbid toxin while regulating the qi movement of the liver， spleen， and kidney. Accordingly， different formulas were applied. Self-formulated Shugan Jianpi Huazhuo Formula （疏肝健脾化浊方） is suggested to drain dampness， resolve turbidity， and unblock qi movement. Self-formulated Sanjiao Fenxiao Jiedu Formula （三焦分消解毒方） can be used to clear heat， drain dampness and resolve toxin. Self-formulated Zishen Yanggan Toudu Decoction （滋肾养肝透毒汤） can clear and vent latent toxins， while Self-formulated Guiqi Shengfa Didu Formula （归芪生发涤毒方） is employed to tonify qi and blood， purge toxins， and regenerate vitality. By differentiating and treating AA based on the functional patterns of the liver， spleen， and kidney， this approach expands the application scope of the turbid toxin theory and provides valuable insights for treatment of AA.

The development of novel point-to-point drugs targeting resistance mechanisms is a critical and popular research field; nevertheless, success remains challenging. Therefore, given the short survival time and heightened expectations of patients with advanced NSCLC, the design of various combination therapy strategies––integrating preclinical, clinical, and real-world evidence (such as radiotherapy, chemotherapy, targeted therapy, antibody–drug conjugates, oncolytic viruses, and cell therapy)––may be a wise and practical choice to address the disease. Resistance to immunotherapy involves almost all cell types in the body, primarily cancer cells and T cells involved in immune surveillance. As a result of space limitations, this article focuses on the progress and challenges of various combined strategies for directly eliminating cancer cells. We also emphasize the realignment of treatment goals, shifting from primarily focusing on eliminating cancer cells (via chemotherapy and radiotherapy) to fully utilizing immune regulation to overcome resistance to immune checkpoint inhibitors.

Objective To investigate the expression of SLC35A2 and PFDN2 in breast cancer and their relationship with clinical indicators and prognosis.Methods TCGA database and TIMER 2.0 database were used to analyze the differences of SLC35A2 and PFDN2 expression in breast cancer tissues and paracancerous tissues;K-M database was used to create the survival curves of patients in the high and low expression groups of the two.qRT-PCR and immunohistochemistry were used to detect the expression of SLC35A2 and PFDN2 in the cancerous and paracancerous tissues,and the expression differences,the relationship between their expression levels and the clinical observation indexes were statistically analyzed,and the independent prognostic factors of breast cancer were screened out;K-M survival analysis was used to compare the prognostic differences between the groups and create the survival curves.Results The expression levels of SLC35A2 and PFDN2 in breast cancer tissues were significantly higher than those in paracancerous tissues according to the results of biopsy,qRT-PCR and immuno-histochemistry,and the expression levels of SLC35A2 were significantly correlated with lymph node metastasis,while the expression of PFDN2 was significantly correlated with the diameter of the tumor and the metastasis of lymph nodes,and the expression of SLC35A2 and PFDN2 was an independent prognostic factor for breast cancer.patients had the worst prognosis.Conclusion The expression of SLC35A2 and PFDN2 in breast cancer tissues was closely related to clinical indicators and prognosis of breast cancer,and could be used as a potential target for breast cancer treatment.

Objective:To investigate the role of TcpC, a virulence factor of uropathogenic Escherichia coli (UPEC), in immune evasion, and analyze its related pathogenic mechanism. Methods:C57BL/6 mice were injected with 10 9 colony-forming unit of wild-type (CFT073 wt) or tcpc gene-knockout (CFT073 Δ tcpc) UPEC CFT073 strains from urethra into bladder to construct a mouse model of pyelonephritis. These mice were sacrificed 5 d after infection and their kidneys were taken to observe the gross pathological changes. Hematoxylin-eosin staining was used to observe histopathological changes in kidney tissues and immunohistochemistry was performed to locate TcpC in kidney tissues. The bacterial loads in urine samples of UPEC infected-mice were counted by ten-fold dilution method, and the presence of tcpc gene in the genomic DNA of bacteria from CFT073-infected mouse kidney or urine samples was measured by PCR. The expression of TcpC at mRNA level was detected by qRT-PCR after infecting dendritic cells with CFT073 wt strains. The influences of UPEC infection on the activation of NF-κB signaling pathway and the secretion of proinflammatory factors by dendritic cells were analyzed by Western blot and ELISA, respectively. The viability of UPEC strains in dendritic cells were observed by laser confocal microscope. Results:Compared with the CFT073 Δ tcpc group, the mice in the CFT073 wt group had obvious abscess in the kidneys as well as massive neutrophil infiltration and abundant TcpC in kidney tissues. The bacterial loads in the urine of CFT073 wt-infected mice were significantly higher than those in the urine of CFT073 Δ tcpc mice. PCR results showed that tcpc gene was successfully amplified from mouse kidney and urine samples. Increased expression of TcpC at both mRNA and protein levels was detected in CFT073 wt-infected dendritic cells. CFT073 wt infection inhibited the phosphorylation of NF-κB p50 and the production of proinflammatory factors in dendritic cells. TcpC promoted the survival of CFT073 wt in dendritic cells. Conclusions:TcpC expression increases significantly during CFT073 wt infection or in mice with CFT073 wt-induced pyelonephritis. It promotes the survival of CFT073 wt in dendritic cells by inhibiting the activation of NF-κB signaling pathway and reducing the secretion of pro-inflammatory cytokines. TcpC is involved in the pathogenesis of UPEC and immune evasion.

To investigate the differences in methylation levels of cuproptosis related genes in cervical cancer and their effects on clinical prognosis.Methods:The methylation data of 310 cervical tissue specimens were acquired from public databases. The UALCAN database was used to analyze the methylation level differences of 12 cuproptosis-related genes and study their level in different stages or grades of cervical cancer. Genes with statistically significant differences were selected for prognosis analysis using the EWAS datahub. Finally, gene-enrichment analysis, pathway analysis, immune infiltration analysis, the mutation rate and tumor mutation burden (TMB) of the genes in cervical cancer were analyzed using the cBioportal database. Two independent samples rank-sum test was used for differences in methylation levels and immune cell infiltration; comparative analyses of overall survival were performed using KM survival curves and Log-rank two-sided tests. TMB analyses were performed using the Wilcoxon Test for statistical analyses; Pearson correlation analysis was used for assessment in GSEA and pathway analyses.Results:The methylationβvalue of Cyclin Dependent Kinase Inhibitor 2A (CDKN2A gene) in the cervical cancer tissues of patients was 0.075 which was significantly higher than the methylationβvalue of 0.049 in normal human tissues ( P=0.008). Dihydrolipoamide S-Acetyltransferase (DLAT gene) methylation with a β value of 0.102 was significantly higher than normal human tissue methylation with a β value of 0.08 ( P=0.002), and the methylation level β value of Lipoyltransferase 1 (LIPT1 gene) in cervical cancer tissues was 0.06,which was significantly lower than normal human tissue methylation value of 0.092 ( P=0.009). Patients with CDKN2A gene methylation levels≥0.199 had an overall survival of 14.75 years, which was lower than that of patients with methylation levels<0.199 (17.56 years) ( P=0.034).The results of gene enrichment analysis indicated that it mainly involves biological processes such as the response to type I interferon and DNA replication. The expression of CDKN2A gene is positively correlated with the number of neutrophils and dendritic cells in the tumor microenvironment( P<0.05), and negatively correlated with the number ofmacrophages( P<0.05). TMB was higher in the group of variants of the CDKN2A gene than in the group of non-variants ( P=0.019). Conclusion:CDKN2A methylation is a potential biomarker for predicting the prognosis of cervical cancer.

Objective To predict the potential geographic distribution of Oncomelania hupensis in Yunnan Province using random forest (RF) and maximum entropy (MaxEnt) models, so as to provide insights into O. hupensis surveillance and control in Yunnan Province. Methods The O. hupensis snail survey data in Yunnan Province from 2015 to 2016 were collected and converted into O. hupensis snail distribution site data. Data of 22 environmental variables in Yunnan Province were collected, including twelve climate variables (annual potential evapotranspiration, annual mean ground surface temperature, annual precipitation, annual mean air pressure, annual mean relative humidity, annual sunshine duration, annual mean air temperature, annual mean wind speed, ≥ 0 ℃ annual accumulated temperature, ≥ 10 ℃ annual accumulated temperature, aridity and index of moisture), eight geographical variables (normalized difference vegetation index, landform type, land use type, altitude, soil type, soil textureclay content, soil texture-sand content and soil texture-silt content) and two population and economic variables (gross domestic product and population). Variables were screened with Pearson correlation test and variance inflation factor (VIF) test. The RF and MaxEnt models and the ensemble model were created using the biomod2 package of the software R 4.2.1, and the potential distribution of O. hupensis snails after 2016 was predicted in Yunnan Province. The predictive effects of models were evaluated through cross-validation and independent tests, and the area under the receiver operating characteristic curve (AUC), true skill statistics (TSS) and Kappa statistics were used for model evaluation. In addition, the importance of environmental variables was analyzed, the contribution of environmental variables output by the models with AUC values of > 0.950 and TSS values of > 0.850 were selected for normalization processing, and the importance percentage of environmental variables was obtained to analyze the importance of environmental variables. Results Data of 148 O. hupensis snail distribution sites and 15 environmental variables were included in training sets of RF and MaxEnt models, and both RF and MaxEnt models had high predictive performance, with both mean AUC values of > 0.900 and all mean TSS values and Kappa values of > 0.800, and significant differences in the AUC (t = 19.862, P < 0.05), TSS (t = 10.140, P < 0.05) and Kappa values (t = 10.237, P < 0.05) between two models. The AUC, TSS and Kappa values of the ensemble model were 0.996, 0.954 and 0.920, respectively. Independent data verification showed that the AUC, TSS and Kappa values of the RF model and the ensemble model were all 1, which still showed high performance in unknown data modeling, and the MaxEnt model showed poor performance, with TSS and Kappa values of 0 for 24%(24/100) of the modeling results. The modeling results of 79 RF models, 38 MaxEnt models and their ensemble models with AUC values of > 0.950 and TSS values of > 0.850 were included in the evaluation of importance of environmental variables. The importance of annual sunshine duration (SSD) was 32.989%, 37.847% and 46.315% in the RF model, the MaxEnt model and their ensemble model, while the importance of annual mean relative humidity (RHU) was 30.947%, 15.921% and 28.121%, respectively. Important environment variables were concentrated in modeling results of the RF model, dispersed in modeling results of the MaxEnt model, and most concentrated in modeling results of the ensemble model. The potential distribution of O. hupensis snails after 2016 was predicted to be relatively concentrated in Yunnan Province by the RF model and relatively large by the MaxEnt model, and the distribution of O. hupensis snails predicted by the ensemble model was mostly the joint distribution of O. hupensis snails predicted by RF and MaxEnt models. Conclusions Both RF and MaxEnt models are effective to predict the potential distribution of O. hupensis snails in Yunnan Province, which facilitates targeted O. hupensis snail control.

Unplanned readmission is one of the adverse outcomes of patients after left ventricular assist device implantation,which seriously affects the prognosis of patients.This article reviews the incidence,causes,influencing factors and intervention measures of unplanned readmission of patients after left ventricular assist device implantation,in order to improve the attention of nursing staff,early identify high-risk groups of unplanned readmission of patients after left ventricular assist device implantation and provide references for formulating personalized intervention measures.

Objective To investigate the predictive value of serum lipoprotein-associated phospho-lipase A2(Lp-PLA2)for long-term prognosis of elderly patients with stable coronary heart dis-ease(CHD).Methods A retrospective trial was conducted on 198 patients with stable CHD ad-mitted to our hospital from January 2016 to December 2018.All of them were followed up for 5 years,and divided into adverse cardiovascular event group(n=42)and control group(n=156)according to whether adverse cardiovascular events occurred during follow-up.Clinical features and Lp-PLA2 level were compared between the two groups.The predictive value of Lp-PLA2 for adverse cardiovascular events was analyzed in elderly patients with stable CHD within 5 years.Re-sults The adverse cardiovascular event group had significantly older age(74.95±7.02 vs 70.17±6.30 years,P=0.000),larger proportions of diabetes(54.76％vs 27.56％,P=0.001),of coronary artery stenosis ≥75％(69.05％vs 47.44％,P=0.013)and of left ventricular ejection fraction(LVEF)＜50％(50.00％vs 28.21％,P=0.008),and higher Lp-PLA2 level(478.38±187.54 U/L vs 308.17±126.73 U/L,P=0.000)when compared with the control group.The AUC value of age and Lp-PLA2 was 0.683(95％CI:0.590--0.776,P＜0.001)and 0.763(95％CI:0.677--0.848,P=0.763),respectively,in predicting the long-term prognosis in elderly patients with stable CHD.Multivariate logistic regression analysis showed that age,diabetes,coronary artery stenosis ≥75％,LVEF＜50％and Lp-PLA2 were independent influencing factors for adverse cardiovascular events within 5 years in elderly patients with stable CHD(P＜0.05,P＜0.01).Con-clusion Increased Lp-PLA2 level is associated with adverse cardiovascular events within 5 years in patients with stable CHD.