Microorganisms evolve resistance to antibiotics as a function of evolution. Antibiotics have accelerated bacterial resistance through mutations and acquired resistance through a combination of factors.

Intestinal barrier dysfunction is not only the consequence of liver cirrhosis, but also an active participant in the development of liver cirrhosis. Previous studies showed that external administration of insulin-like growth factor 1 (IGF-1) improved intestinal barrier function in liver cirrhosis. However, the mechanism of IGF-1 on intestinal barrier in liver cirrhosis is not fully elucidated. The present study aims to investigate the mechanisms of IGF-1 improving intestinal barrier function via regulating tight junctions in intestines. We used carbon tetrachloride induced liver cirrhotic rats to investigate the effect of IGF-1 on intestinal claudin-1 and occludin expressions, serum alanine transaminase (ALT) and aspartate transaminase (AST) levels, severity of liver fibrosis, portal pressures, enterocytic apoptosis and lipopolysaccharides (LPS) levels in portal vein. The changes of IGF-1 in serum during the development of rat liver cirrhosis were also evaluated. Additionally, we assessed the effect of IGF-1 on claudin-1 and occludin expressions, changes of transepithelial electrical resistance (TEER) and apoptosis in Caco-2 cells to confirm in vivo findings. Serum IGF-1 levels were decreased in the development of rat liver cirrhosis, and external administration of IGF-1 restored serum IGF-1 levels. External administration of IGF-1 reduced serum ALT and AST levels, severity of liver fibrosis, LPS levels in portal vein, enterocytic apoptosis and portal pressure in cirrhotic rats. External administration of IGF-1 increased the expressions of claudin-1 and occludin in enterocytes, and attenuated tight junction dysfunction in intestines of cirrhotic rats. LPS decreased TEER in Caco-2 cell monolayer. LPS also decreased claudin-1 and occludin expressions and increased apoptosis in Caco-2 cells. Furthermore, IGF-1 attenuated the effect of LPS on TEER, claudin-1 expression, occludin expression and apoptosis in Caco-2 cells. Tight junction dysfunction develops during the development of liver cirrhosis, and endotoxemia will develop subsequently. Correspondingly, increased endotoxin in portal system worsens tight junction dysfunction via decreasing intestinal occludin and claudin-1 expressions and increasing enterocytic apoptosis. Endotoxemia and intestinal barrier dysfunction form a vicious circle. External administration of IGF-1 breaks this vicious circle. Improvement of tight junctions might be one possible mechanism of the restoration of intestinal barrier function mediated by IGF-1.

Currently, both acute kidney injury (AKI) and chronic kidney disease (CKD) are considered to be the leading public health problems with gradually increasing incidence rates around the world. Rhein is a monomeric component of anthraquinone isolated from rhubarb, a traditional Chinese medicine. It has anti-inflammation, anti-oxidation, anti-apoptosis, anti-bacterial and other pharmacological activities, as well as a renal protective effects. Rhein exerts its nephroprotective effects mainly through decreasing hypoglycemic and hypolipidemic, playing anti-inflammatory, antioxidant and anti-fibrotic effects and regulating drug-transporters. However, the latest studies show that rhein also has potential kidney toxicity in case of large dosages and long use times. The present review highlights rhein’s molecular targets and its different effects on the kidney based on the available literature and clarifies that rhein regulates the function of the kidney in a positive and negative way. It will be helpful to conduct further studies on how to make full use of rhein in the kidney and to avoid kidney damage so as to make it an effective kidney protection drug.

With the advancement of computer technology, machine learning-based artificial intelligence technology has been increasingly integrated and applied in the fields of medicine, biology, and pharmacy, thereby facilitating their development. Transporters have important roles in influencing drug resistance, drug–drug interactions, and tissue-specific drug targeting. The investigation of drug transporter substrates and inhibitors is a crucial aspect of pharmaceutical development. However, long duration and high expenses pose significant challenges in the investigation of drug transporters. In this review, we discuss the present situation and challenges encountered in applying machine learning techniques to investigate drug transporters. The transporters involved include ABC transporters (P-gp, BCRP, MRPs, and BSEP) and SLC transporters (OAT, OATP, OCT, MATE1,2-K, and NET). The aim is to offer a point of reference for and assistance with the progression of drug transporter research, as well as the advancement of more efficient computer technology. Machine learning methods are valuable and attractive for helping with the study of drug transporter substrates and inhibitors, but continuous efforts are still needed to develop more accurate and reliable predictive models and to apply them in the screening process of drug development to improve efficiency and success rates.

The kidney is critical in the human body’s excretion of drugs and their metabolites. Renal transporters participate in actively secreting substances from the proximal tubular cells and reabsorbing them in the distal renal tubules. They can affect the clearance rates (CLr) of drugs and their metabolites, eventually influence the clinical efficiency and side effects of drugs, and may produce drug–drug interactions (DDIs) of clinical significance. Renal transporters and renal transporter-mediated DDIs have also been studied by many researchers. In this article, the main types of in vitro research models used for the study of renal transporter-mediated DDIs are membrane-based assays, cell-based assays, and the renal slice uptake model. In vivo research models include animal experiments, gene knockout animal models, positron emission tomography (PET) technology, and studies on human beings. In addition, in vitro–in vivo extrapolation (IVIVE), ex vivo kidney perfusion (EVKP) models, and, more recently, biomarker methods and in silico models are included. This article reviews the traditional research methods of renal transporter-mediated DDIs, updates the recent progress in the development of the methods, and then classifies and summarizes the advantages and disadvantages of each method. Through the sorting work conducted in this paper, it will be convenient for researchers at different learning stages to choose the best method for their own research based on their own subject’s situation when they are going to study DDIs mediated by renal transporters.