Deep reinforcement learning task scheduling method based on server real-time performance.

Server load levels affect the performance of cloud task execution, which is rooted in the impact of server performance on cloud task execution. Traditional cloud task scheduling methods usually only consider server load without fully considering the server's real-time load-performance mapping relationship, resulting in the inability to evaluate the server's real-time processing capability accurately. This deficiency directly affects the efficiency, performance, and user experience of cloud task scheduling. Firstly, we construct a performance platform model to monitor server real-time load and performance status information in response to the above problems. In addition, we propose a new deep reinforcement learning task scheduling method based on server real-time performance (SRP-DRL). This method introduces a real-time performance-aware strategy and adds status information about the real-time impact of task load on server performance on top of considering server load. It enhances the perception capability of the deep reinforcement learning (DRL) model in cloud scheduling environments and improves the server's load-balancing ability under latency constraints. Experimental results indicate that the SRP-DRL method has better overall performance regarding task average response time, success rate, and server average load variance compared to Random, Round-Robin, Earliest Idle Time First (EITF), and Best Fit (BEST-FIT) task scheduling methods. In particular, the SRP-DRL is highly effective in reducing server average load variance when numerous tasks arrive within a unit of time, ultimately optimizing the performance of the cloud system.

The Recombinant Lactobacillus Strains with the Surface-Displayed Expression of Amuc_1100 Ameliorate Obesity in High-Fat Diet-Fed Adult Mice.

Excessive dietary fat intake is closely associated with an increased risk of obesity, type 2 diabetes, cardiovascular disease, gastrointestinal diseases, and certain types of cancer. The administration of multi-strain probiotics has shown a significantly beneficial effect on the mitigation of obesity induced by high-fat diets (HFDs). In this study, Amuc_1100, an outer membrane protein of Akkermansia muciniphila, was fused with green fluorescent protein and LPXTG motif anchor protein and displayed on the surface of Lactobacillus rhamnosus (pLR-GAA) and Lactobacillus plantarum (pLP-GAA), respectively. The localization of the fusion protein on the bacterial cell surface was confirmed via fluorescence microscopy and Western blotting. Both recombinant strains demonstrated the capacity to ameliorate hyperglycemia and decrease body weight gain in a dose-dependent manner. Moreover, daily oral supplementation of pLR-GAA or pLP-GAA suppressed the HFD-induced intestinal permeability by regulating the mRNA expressions of tight junction proteins and inflammatory cytokines, thereby reducing gut microbiota-derived lipopolysaccharide concentration in serum and mitigating damage to the gut, liver, and adipose tissue. Compared with Lactobacillus rhamnosus treatment, high-dose pLR-GAA restored the expression level of anti-inflammatory factor interleukin-10 in the intestine. In conclusion, our approach enables the maintenance of intestinal health through the use of recombinant probiotics with surface-displayed functional protein, providing a potential therapeutic strategy for HFD-induced obesity and associated metabolic comorbidities.

Comprehensive bioinformatics analysis of KIF20A as a prognosis biomarker for clear cell renal cell carcinoma.

It has been shown that kinesin family member 20A (KIF20A) is involved in the development of several cancers. However, research on clear cell renal cell carcinoma (ccRCC) and KIF20A is still exploratory. The current research was carried out to determine whether KIF20A expression has any prognosis value in ccRCC. Data were downloaded from The Cancer Genome Atlas (TCGA) database to validate the KIF20A mRNA expression and to perform clinicopathological analysis. Receiver operating characteristic (ROC) curves were used in evaluating KIF20A's diagnostic performance for ccRCC. The prognostic value of KIF20A in ccRCC was estimated by the Kaplan-Meier survival curve and Cox regression analysis. Gene set enrichment analysis (GSEA), functional annotations, and immune infiltration analysis were used to determine the potential mechanism of KIF20A's role in ccRCC. The increase in KIF20A mRNA expression was associated with sex, clinical stage, histologic grade, and TNM stage. ROC curve indicated that KIF20A could distinguish ccRCC from normal kidney samples. Survival study showed that high KIF20A expression predicted poor ccRCC prognosis. Thus, KIF20A expression could be used as an independent overall survival (OS) risk factor for ccRCC patients. Co-expression analysis identified TPX2 as a strong, positively correlated factor with KIF20A in ccRCC. Functional enrichment analyses and GSEA showed that KIF20A and TPX2 participated in various tumor-related pathways. Moreover, KIF20A and TPX2 expression were significantly associated with the level of immune infiltration into ccRCC. KIF20A may be a therapeutic target and a prognostic biomarker for ccRCC.

High-fidelity reprogramming into Leydig-like cells by CRISPR activation and paracrine factors.

Androgen deficiency is a common medical conditions that affects males of all ages. Transplantation of testosterone-producing cells is a promising treatment for male hypogonadism. However, getting a cell source with the characteristics of Leydig cells (LCs) is still a challenge. Here, a high-efficiency reprogramming of skin-derived fibroblasts into functional Leydig-like cells (LLCs) based on epigenetic mechanism was described. By performing an integrated analysis of genome-wide DNA methylation and transcriptome profiling in LCs and fibroblasts, the potentially epigenetic-regulating steroidogenic genes and signaling pathways were identified. Then by using CRISPR/dCas9 activation system and signaling pathway regulators, the male- or female-derived fibroblasts were reprogrammed into LLCs with main LC-specific traits. Transcriptomic analysis further indicated that the correlation coefficients of global genes and transcription factors between LLCs and LCs were higher than 0.81 and 0.96, respectively. After transplantation in the testes of hypogonadal rodent models, LLCs increased serum testosterone concentration significantly. In type 2 diabetic rats model, LLCs which were transplanted in armpit, have the capability to restore the serum testosterone level and improve the hyperglycemia status. In conclusion, our approach enables skin-derived fibroblasts reprogramming into LLCs with high fidelity, providing a potential cell source for the therapeutics of male hypogonadism and metabolic-related comorbidities.