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Oxidative stress suppresses animal health, performance, and production, subsequently impacting economic feasibility; hence, maintaining and improving oxidative status especially through natural nutrition strategy are essential for normal physiological process in animals. Phytochemicals are naturally occurring antioxidants that could be considered as one of the most promising materials used in animal diets in various forms. In this review, their antioxidant effects on animals are discussed as reflected by improved apparent performance, productivity, and the internal physiological changes. Moreover, the antioxidant actions toward animals further describe a molecular basis to elucidate their underlying mechanisms targeting signal transduction pathways, especially through the antioxidant response element/nuclear factor (erythroid-derived 2)-like 2 transcription system.

Networks, such as social networks, biochemical networks, and protein-protein interaction networks are ubiquitous in the real world. Network representation learning aims to embed nodes in a network as low-dimensional, dense, real-valued vectors, and facilitate downstream network analysis. The existing embedding methods commonly endeavor to capture structure information in a network, but lack of consideration of subsequent tasks and synergies between these tasks, which are of equal importance for learning desirable network representations. To address this issue, we propose a novel multi-task network representation learning (MTNRL) framework, which is end-to-end and more effective for underlying tasks. The original network and the incomplete network share a unified embedding layer followed by node classification and link prediction tasks that simultaneously perform on the embedding vectors. By optimizing the multi-task loss function, our framework jointly learns task-oriented embedding representations for each node. Besides, our framework is suitable for all network embedding methods, and the experiment results on several benchmark datasets demonstrate the effectiveness of the proposed framework compared with state-of-the-art methods.

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One-day-old chicks are susceptible to infection by strains of Salmonella enterica subspecies. Because multistrain probiotics are suggested to be more effective than monostrain probiotics due to the additive and synergistic effects, in this study, we prepared a multistrain formula A (MFA) consisting of 4 lactic acid bacteria (LAB) strains selected by enhancing the TNF-α production for mouse macrophage 264.7 cells. The antagonistic effect of this MFA against the cecal colonization, viscera invasiveness, as well as the inflammation of 1-d-old chicks challenged with Salmonella Typhimurium were then assayed. One-day-old chicks were fed with MFA from d 1 to d 3, and on d 4, chicks were challenged with Salmonella Typhimurium (200 μL, 10(6) cfu/mL). The livers, spleens, and cecal tonsils of chicks were then removed on d 3 and 6 postinfection. Compared with the multistrain formula B (MFB) which consisted of LAB strains selected at random, the efficacy of MFA to reduce the Salmonella counts recovered from the cecal tonsils, spleens, and livers of chicks were significantly higher. Moreover, when the levels of proinflammatory cytokines, such as IL-1β, IL-6, interferon (IFN)-γ, and anti-inflmmatory cytokine, that is, IL-10, in cecal tonsils were measured by reverse-transcription real-time quantitative PCR; it was found that chicks fed with MFA for 3 d had lower levels of IL-1β, IL-6, IFN-γ and a higher level of IL-10 in the cecal tonsils of chicks as compared with those of the chicks fed with MFB or without LAB. These results suggest that multistrain probiotics consisting of LAB strains selected by immunomodulatory activity and adherence are more effective than those consisting of strains selected at random in antagonistic effect against Salmonella colonization, invasion, and the induced inflammation.