The genesis and development of renal fibrosis involve a variety of pathways closely related to inflammation, cytokines, oxidative stress and metabolic abnormalities. Renal fibrosis is the result of a complex combination of a variety of lesions. Epithelial-mesenchymal transdifferentiation (EMT) of renal tubular epithelial cells is considered the key to renal fibrosis. Losartan is a typical Angiotensin II (ANG II) receptor antagonist and relaxes blood vessels. In this study, we investigated the effects of losartan on Unilateral Ureteral Obstruction (UUO) model mice by studying the changes in the TGF-β/Smad and metabolomics. Male C57BL/6 J mice were intervened with the UUO model and given losartan (10, 20, 30 mg/kg/d) for 28 consecutive days. The results showed that losartan could reduce UUO-induced abnormal serum metabolic spectrum and renal function. It could also improve renal tubular-interstitial injury and fibrosis by reducing tubulointerstitial dilation and collagen deposition. In addition, losartan promoted the expression of Smurf2 and Smurf1, i.e., Smad7 and E3 ubiquitin-linked enzymes, in the nucleus to degrade the type I receptor of TGF-β1 (TβR-I) and P-Smad2/3 to inhibit renal tubular epithelial cells EMT. In summary, these findings indicated that losartan could regulate the TGF-β/Smad and metabolic pathway in UUO model mice through ubiquitination to reduce renal fibrosis.

Purpose: Non-alcoholic fatty liver disease (NAFLD) represents a significant global health burden, exhibiting a strong correlation with insulin resistance, obesity, and type 2 diabetes (T2DM). Despite the severity of hepatic steatosis in T2DM patients, no specific drugs have been approved for clinical treatment of the disease. Tangerine peel is one kind of popular functional food and reported to possess hypoglycemic and lipid-lowering potential. In this study, we investigated the effects of Tangerine-peel-derived exosome-like nanovesicles (TNVs) on hepatic lipotoxicity associated with T2DM. Methods: The TNVs was prepared by differential centrifugation of the aqueous extract of Tangerine and chemical properties were characterized using transmission electron microscopy (TEM), nanoparticle tracking analysis (NTA) and LC-MS/MS. The hypoglycemic and lipid-lowering potential of TNVs were possessed by biochemical measurement, RT-PCR, 16S rRNA sequencing, GC/MS, UHPLC-MS/MS, in vivo small animal imaging assay and HE staining. Subsequently, effects of TNVs on lipid accumulation and glycolysis were investigated on 3T3-L1 and AML-12 cells. Results: TNVs significantly inhibited insulin resistance, reduced hepatic lipid accumulation, facilitate intestinal mucosal repair, rescued gut microbiota dysbiosis, regulated colonic SCFA and liver bile acid metabolism in db/db mice. Furthermore, TNVs restored the expression of key genes in glucose and lipid metabolism (ACC, AMPK, CD36, LXRα, PPAR-γ, SREBP-1) while activating the expression of genes related to glycolysis (G6Pase, GLUT2, PCK1, PEPCK) in db/db mice. Further cell-based mechanistic studies revealed that TNVs reduced lipid accumulation in 3T3-L1 and AML-12 cells via regulation of glucose and lipid metabolism-related genes (UCP1, FGFR4, PRDM16, PGC-1α, Tmem26, Cpt1, Cpt2 and PPAR-α). Conclusion: We for the first time demonstrated that TNVs could significantly improve glucose and lipid metabolism via activating the expression of genes related to fatty acid β-oxidation and glycolysis.

Medicinal plant-derived exosome-like nanovesicles is a kind of vesicles with a diameter of 30– 300 nm extracted from medicinal plants, which can regulate the microenvironment of various systems, diseases and cells through multiple drug delivery routes, so as to achieve the purpose of alleviating and treating diseases. In this paper, the extraction and identification methods of nanovesicles derived from medicinal plants were summarized. Then, according to the systematic classification of diseases, the effects and mechanisms of the treatment of diseases and the regulation of the microenvironment by the nanovesicles derived from medicinal plants were summarized and analyzed. This paper finds Medicinal plant-derived exosome-like nanovesicles, as plant-derived nanoscale vesicles, can act more efficiently on various microenvironments of the body such as inflammation, tumors, immunity and the intestine through various administration methods such as oral administration and intravenous injection according to the characteristics of the disease, achieving the effect of treating diseases and alleviating symptoms. Medicinal plant-derived exosome-like nanovesicles have initiated a new model of transboundary communication regulation involving plants in the human microenvironment, using their own advantages to regulate the human microenvironment. Meanwhile, it can also be used as a drug carrier to achieve a dual communication regulation effect. It provides ideas for the follow-up research and clinical use of nanovesicles derived from medicinal plants.

Background: Type 2 diabetes (T2D) is a prevalent chronic disease with elusive. Combining transcriptome and single-cell sequencing data to explore biomarkers of T2D could provide new insights into the in-depth understanding of the molecular mechanisms and diagnosis of T2D. Methods: The GSE41762 dataset including RNA-seq data for healthy and T2D patients, was obtained from the Gene Expression Omnibus (GEO) database. The potential functions of the differentially expressed genes (DEGs) were revealed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Moreover, biomarkers were screened out by the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm and receiver operating characteristic (ROC) analysis. Furthermore, single-cell RNA (sc-RNA)-seq data in the “E-MTAB-5061” dataset was downloaded from the ArrayExpress (European Bioinformatics Institute, EBI) database. Principal components analysis (PCA) and t-distributed stochastic neighbor embedding (tSNE) were used for dimensionality reduction analysis and cell clustering. The FindAllMarkers function was used annotate different cell clusters, and key cell clusters were screened by the expression levels of the biomarkers. Finally, the transcription factors (TFs) of the biomarkers were recognized. Results: A total of 111 DEGs were screened in the GSE41762 dataset, which were mainly related to hormone secretion, specialized postsynaptic membrane, pancreatic secretion, JAK-STAT signaling pathway, and Ras signaling pathway. In addition, SLC2A2, SERPINF1, RASGRP1, and CHL1 were screened out as biomarkers of T2D, which possessed potential diagnostic value as AUC value greater than 0.8. A total of 1,515 T2D group cells and 1,817 healthy cohort cells were screened as core cells in the “E-MTAB-5061” dataset. Following tSNE dimensionality reduction cluster analysis, the core cells were divided into 13 cell clusters. According to the marker genes, the 13 cell clusters were annotated into six types of cells. Notably, SERPINF1 was highly expressed in fibroblasts and might be regulated by NR2F2 (nuclear receptor subfamily2, group F, and member 2). Conclusions: This study identified four biomarkers (SLC2A2, SERPINF1, RASGRP1, and CHL1) for T2D, which provided new markers for the clinical diagnosis of T2D. Among them, SERPINF1 might be regulated by NR2F2, which provides valuable insight into the pathogensis of T2D.

Objective: This is the first study to explore the mechanism of colchicine in treating coronary artery disease using network pharmacology and molecular docking technology, aiming to predict the key targets and main approaches of colchicine in treating coronary artery disease. It is expected to provide new ideas for research on disease mechanism and drug development.Methods: Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Swiss Target Prediction and PharmMapper databases were used to obtain drug targets. GeneCards, Online Mendelian Inheritance in Man (OMIM), Therapeutic Target Database (TTD), DrugBank and DisGeNET databases were utilized to gain disease targets. The intersection of the two was taken to access the intersection targets of colchicine for the treatment of coronary artery disease. The Sting database was employed to analyze the protein-protein interaction network. Gene Ontology (GO) functional enrichment analysis was performed using Webgestalt database. Reactom database was applied for Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Molecular docking was simulated using AutoDock 4.2.6 and PyMOL2.4 software.Results: A total of 70 intersecting targets of colchicine for the treatment of coronary artery disease were obtained, and there were interactions among 50 targets. GO functional enrichment analysis yielded 13 biological processes, 18 cellular components and 16 molecular functions. 549 signaling pathways were obtained by KEGG enrichment analysis. The molecular docking results of key targets were generally good.Conclusion: Colchicine may treat coronary artery disease through targets such as Cytochrome c (CYCS), Myeloperoxidase (MPO) and Histone deacetylase 1 (HDAC1). The mechanism of action may be related to the cellular response to chemical stimulus and p75NTR-mediated negative regulation of cell cycle by SC1, which is valuable for further research exploration. However, this research still needs to be verified by experiments. Future research will explore new drugs for treating coronary artery disease from these targets.