Heat stress is a non-specific physiological response of the body when exposed to high ambient temperatures, which can break the balance of body redox and result in oxidative stress that affects growth performance as well as the health of poultry species. Polyphenols have attracted much attention in recent years due to their antioxidant ability and thus, can be an effective attenuator of heat stress. In this paper, the potential mechanisms underlying the inhibitory effect of polyphenols on heat stress in poultry has been reviewed to provide a reference and ideas for future studies related to polyphenols and poultry production.

Polyphenols from the Lonicera caerulea L. berry have shown protective effects on experimental non-alcoholic fatty liver disease (NAFLD) in our previous studies. As endotoxins from gut bacteria are considered to be the major trigger of inflammation in NAFLD, this study aims to clarify the regulatory effects of L. caerulea L. berry polyphenols (LCBP) on gut microbiota in a high fat diet (HFD)-induced mouse model. C57BL/6N mice were fed with a normal diet, HFD, or HFD containing 0.5–1% of LCBP for 45 days. The results revealed that supplementation with LCBP decreased significantly the levels of IL-2, IL-6, MCP-1, and TNF-α in serum, as well as endotoxin levels in both serum and liver in HFD-fed mice. Fecal microbiota characterization by high throughput 16S rRNA gene sequencing revealed that a HFD increased the Firmicutes/Bacteroidetes ratio, and LCBP reduced this ratio by increasing the relative abundance of Bacteroides, Parabacteroides, and another two undefined bacterial genera belonging to the order of Bacteroidales and family of Rikenellaceae, and also by decreasing the relative abundance of six bacterial genera belonging to the phylum Firmicutes, including Staphylococcus, Lactobacillus, Ruminococcus, and Oscillospira. These data demonstrated that LCBP potentially attenuated inflammation in NAFLD through modulation of gut microbiota, especially the ratio of Firmicutes to Bacteroidetes.

The energy and metabolic state of sows will alter considerably over different phases of gestation. Maternal metabolism increases dramatically, particularly in late pregnancy. This is accompanied by the development of an increase in oxidative stress, which has a considerable negative effect on the maternal and the placenta. As the only link between the maternal and the fetus, the placenta is critical for the maternal to deliver nutrients to the fetus and for the fetus’ survival and development. This review aimed to clarify the changes in energy and metabolism in sows during different pregnancy periods, as well as the impact of maternal oxidative stress on the placenta, which affects the fetus’ survival and development.

This review systematically examines the influence of oxidative stress on the reproductive function of male livestock, with a particular focus on the modulation of autophagy. Spermatogenesis, a highly precise biological process, is vulnerable to a range of internal and external factors, among which oxidative stress notably disrupts autophagic processes within the testes. This disruption results in diminished sperm quality, impaired testosterone synthesis, and compromised integrity of the blood–testis barrier. Furthermore, this review elucidates the molecular mechanisms by which oxidative stress-induced autophagy dysfunction impairs spermatogenesis and mitochondrial function, consequently reducing sperm motility. These findings aim to provide a theoretical foundation and serve as a reference for improving reproductive performance and sperm quality in livestock.

In this paper, we present a novel approach to reconstruct a unique image of an observed scene with widely distributed radar sensors. The problem is posed as a constrained optimization problem in which the global image which represents the aggregate view of the sensors is a decision variable. While the problem is designed to promote a sparse solution for the global image, it is constrained such that a relationship with local images that can be reconstructed using the measurements at each sensor is respected. Two problem formulations are introduced by stipulating two different establishments of that relationship. The proposed formulations are designed according to consensus ADMM (CADMM) and sharing ADMM (SADMM), and their solutions are provided accordingly as iterative algorithms. We drive the explicit variable updates for each algorithm in addition to the recommended scheme for hybrid parallel implementation on the distributed sensors and a central processing unit. Our algorithms are validated and their performance is evaluated exploiting Civilian Vehicles Dome data-set to realize different scenarios of practical relevance. Experimental results show the effectiveness of the proposed algorithms, especially in cases with limited measurements.