The continuous increase in poultry production over the last decades to meet the high growing demand and provide food security has attracted much concern due to the recent negative impacts of the most challenging environmental stressor, heat stress (HS), on birds. The poultry industry has responded by adopting different environmental strategies such as the use of environmentally controlled sheds and modern ventilation systems. However, such strategies are not long-term solutions and it cost so much for farmers to practice. The detrimental effects of HS include the reduction in growth, deterioration of meat quality as it reduces water-holding capacity, pH and increases drip loss in meat consequently changing the normal color, taste and texture of chicken meat. HS causes poor meat quality by impairing protein synthesis and augmenting undesirable fat in meat. Studies previously conducted show that HS negatively affects the skeletal muscle growth and development by changing its effects on myogenic regulatory factors, insulin growth factor-1, and heat-shock proteins. The focus of this article is in 3-fold: (1) to identify the mechanism of heat stress that causes meat production and quality loss in chicken; (2) to discuss the physiological, metabolic and genetic changes triggered by HS causing setback to the world poultry industry; (3) to identify the research gaps to be addressed in future studies.

No abstract

Background. High-grade serous ovarian cancer (HGSOC) carries the highest mortality in the gynecological cancers; however, therapeutic outcomes have not significantly improved in recent decades. Macrophages play an essential role in the occurrence and development of ovarian cancer, so the mechanisms of macrophage infiltration should be elucidated. Method. We downloaded transcriptome data of ovarian cancers from the Gene Expression Omnibus and The Cancer Genome Atlas. After rigorous screening, 1566 HGSOC were used for data analysis. CIBERSORT was used to estimate the level of macrophage infiltration and WGCNA was used to identify macrophage-related modules. We constructed a macrophage-related prognostic model using machine learning LASSO algorithm and verified it using multiple HGSOC cohorts. Results. In the GPL570-OV cohort, high infiltration level of M1 macrophages was associated with a good outcome, while high infiltration level of M2 macrophages was associated with poor outcomes. We used WGCNA to select genes correlated with macrophage infiltration. These genes were used to construct protein-protein interaction maps of macrophage infiltration. IFL44L, RSAD2, IFIT3, MX1, IFIH1, IFI44, and ISG15 were the hub genes in the network. We then constructed a macrophage-related prognostic model composed of CD38, ACE2, BATF2, HLA-DOB, and WARS. The model had the ability to predict the overall survival rate of HGSOC patients in GPL570-OV, GPL6480-OV, TCGA-OV, GSE50088, and GSE26712. In exploring the immune microenvironment, we found that CD4 memory T cells and activated mast cells showed that the degree of infiltration was higher in the high-risk group, while M1 macrophages were the opposite, and HLA molecules were overexpressed in the high-risk group. Conclusion. We constructed a macrophage infiltration-related protein interaction network that provides a basis for studying macrophages in HGSOC. Our macrophage-related prognostic model is robust and widely applicable. It predicts overall survival in HGSOC patients and may improve HGSOC treatment.

Animal growth and development are regulated by neural and endocrine growth axes, in which cell proliferation plays key roles. Recently, many research showed that circular RNAs were involved in hepatocyte and myoblast proliferation. Previously, we identified a circular RNA derived from the chicken GHR gene, named circGHR. However, the function of circGHR is unclear. The objective of this study was to investigate circGHR expression pattern and its roles in cell proliferation. Results indicated that circGHR was a closed-loop structure molecule, and it was richer in the nucleus of hepatocytes and myoblast. Real-time PCR showed that circGHR was increased from E13 to the 7th week in the liver but decreased in the thigh and breast muscle. The CCK-8 assay displayed that circGHR promoted cell proliferation. Simultaneously, the biomarker genes PCNA, CCND1, and CDK2 and the linear transcripts GHR and GHBP were upregulated when circGHR was overexpressed. Altogether, these data exhibited that circGHR could promote cell proliferation possibly by regulating GHR mRNA and GHBP expression.

No abstract