Rat

Interleukin-12 Inhibits Tumor Growth and Metastasis Promoted by Tumor-Associated Mesenchymal Stem Cells in Triple-Negative Breast Cancer
Interleukin-12 Inhibits Tumor Growth and Metastasis Promoted by Tumor-Associated Mesenchymal Stem Cells in Triple-Negative Breast Cancer

The aim of this study was to understand the interactions between tumor-associated mesenchymal stem cells (TA-MSCs) and triple-negative breast cancer (TNBC) cells, which appear to be necessary for developing effective therapies. The findings of the present study revealed a complex interplay between TA-MSCs and TNBC cells that affects tumor growth and metastasis. Preclinical results indicate that intratumoral IL-12 immunotherapy shows promise in overcoming TA-MSC-promoted tumor growth and metastasis.

Jan 11, 2025

Interaction between high-intensity interval training and high-protein diet on gut microbiota composition and body weight in obese male rats
Interaction between high-intensity interval training and high-protein diet on gut microbiota composition and body weight in obese male rats

Diet and exercise are two critical factors that regulate gut microbiota, affecting weight management. The present study investigated the effect of 10 weeks of high-intensity interval training (HIIT) and a high-protein diet (HPD) on gut microbiota composition and body weight changes in obese male Wistar rats. Forty obese rats were randomly divided into five groups, including HPD, HIIT + HPD, HIIT + high-fat diet (HFD) (continuing HFD during intervention), obese control 1 (continuing HFD during intervention), obese control 2 (cutting off HFD at the beginning of the intervention and continuing standard diet), and eight non-obese Wistar rats as a non-obese control (NOC) group (standard diet). Microbial community composition and diversity analysis by sequencing 16S rRNA genes derived from the fecal samples, body weight, and Lee index were assessed. The body weight and Lee index in the NOC, HIIT + HFD, HPD, and HIIT + HPD groups were significantly lower than that in the OC1 and OC2 groups along with the lower body weight and Lee index in the HPD and HIIT + HPD groups compared with the HIIT + HFD group. Also, HFD consumption and switching from HFD to a standard diet or HPD increased gut microbiota dysbiosis. Furthermore, HIIT along with HFD increased the adverse effects of HFD on gut microbiota, while the HIIT + HPD increased microbial richness, improved gut microbiota dysbiosis, and changed rats’ phenotype to lean. It appears that HFD discontinuation without doing HIIT does not improve gut microbiota dysbiosis. Also, the HIIT + HFD, HPD, and HIIT + HPD slow down HFD-induced weight gain, but HIIT + HPD is a more reliable strategy for weight management due to its beneficial effects on gut microbiota composition.

Aug 29, 2023

PrESOgenesis: a two-layer multi-label predictor for identifying fertility-related proteins using support vector machine and pseudo amino acid composition approach
PrESOgenesis: a two-layer multi-label predictor for identifying fertility-related proteins using support vector machine and pseudo amino acid composition approach

Successful spermatogenesis and oogenesis are the two genetically independent processes preceding embryo development. To date, several fertility-related proteins have been described in mammalian species. Nevertheless, further studies are required to discover more proteins associated with the development of germ cells and embryogenesis in order to shed more light on the processes. This work builds on our previous software (OOgenesis_Pred), mainly focusing on algorithms beyond what was previously done, in particular new fertility-related proteins and their classes (embryogenesis, spermatogenesis and oogenesis) based on the support vector machine according to the concept of Chou’s pseudo-amino acid composition features. The results of five-fold cross validation, as well as the independent test demonstrated that this method is capable of predicting the fertility-related proteins and their classes with accuracy of more than 80%. Moreover, by using feature selection methods, important properties of fertility-related proteins were identified that allowed for their accurate classification. Based on the proposed method, a two-layer classifier software, named as “PrESOgenesis” (https://github.com/mrb20045/PrESOgenesis) was developed. The tool identified a query sequence (protein or transcript) as fertility or non-fertility-related protein at the first layer and then classified the predicted fertility-related protein into different classes of embryogenesis, spermatogenesis or oogenesis at the second layer.

Jun 13, 2018