Proanthocyanidins have been suggested as an effective antibiotic alternative, however their mechanisms are still unknown. The present study investigated the effects of grape seed proanthocyanidins on gut microbiota and mucosal barrier using a weaned piglet model in comparison with colistin. Piglets weaned at 28 day were randomly assigned to four groups treated with a control ration, or supplemented with 250 mg/kg proanthocyanidins, kitasamycin/colistin, or 250 mg/kg proanthocyanidins and half-dose antibiotics, respectively. On day 28, the gut chyme and tissue samples were collected to test intestinal microbiota and barrier function, respectively. Proanthocyanidins treated piglets had better growth performance and reduced diarrhea incidence ( P < 0.05), accompanied with decreased intestinal permeability and improved mucosal morphology. Gene sequencing analysis of 16S rRNA revealed that dietary proanthocyanidins improved the microbial diversity in ileal and colonic digesta, and the most abundant OTUs belong to Firmicutes and Bacteroidetes spp . Proanthocyanidins treatment decreased the abundance of Lactobacillaceae , and increased the abundance of Clostridiaceae in both ileal and colonic lumen, which suggests that proanthocyanidins treatment changed the bacterial composition and distribution. Administration of proanthocyanidins increased the concentration of propionic acid and butyric acid in the ileum and colon, which may activate the expression of GPR41. In addition, dietary proanthocyanidins improved the antioxidant indices in serum and intestinal mucosa, accompanied with increasing expression of barrier occludin. Our findings indicated that proanthocyanidins with half-dose colistin was equivalent to the antibiotic treatment and assisted weaned animals in resisting intestinal oxidative stress by increasing diversity and improving balance of gut microbes.

The present study was carried out to determine whether low dose of zinc oxide nanoparticles (Nano-ZnO) could serve as a potential substitute of pharmacological dose of traditional ZnO in weaned piglets. 180 crossbred weaning piglets were randomly assigned to 3 treatments. Experimental animals were fed basal diet supplemented with 0 mg Zn/kg (Control), 600 mg Zn/kg (Nano-ZnO) and 2000 mg Zn/kg (ZnO) for 14 days. On day 14 after weaning, the piglets fed Nano-ZnO did not differ from those fed traditional ZnO in growth performance and jejunal morphology, while Nano-ZnO treatment could significantly alleviate the incidence of diarrhea (P < 0.05). In jejunum, the mRNA expressions of intestinal antioxidant enzymes and tight junction proteins were increased (P < 0.05) in Nano-ZnO treatment. In ileum, the expression levels of IFN-γ, IL-1β, TNF-α and NF-κB were decreased (P < 0.05). Gene sequencing analysis of 16S rRNA revealed that dietary Nano-ZnO increased the bacterial richness and diversity in ileum, while decreased both of them in cecum and colon. Specifically, the relative abundances of Streptococcus in ileum, Lactobacillus in colon were increased, while the relative abundances of Lactobacillus in ileum, Oscillospira and Prevotella in colon were decreased (P < 0.05). In conclusion, our data reveal that low dose of Nano-ZnO (600 mg Zn/kg) can effectively reduce piglet diarrhea incidence, similar to high dose of traditional ZnO (2000 mg Zn/kg), which may be mediated by improving intestinal microbiota and inflammation response in piglets, and help to reduce zinc environmental pollution.

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A plethora of multi-view subspace clustering (MVSC) methods have been proposed over the past few years. Researchers manage to boost clustering accuracy from different points of view. However, many state-of-the-art MVSC algorithms, typically have a quadratic or even cubic complexity, are inefficient and inherently difficult to apply at large scales. In the era of big data, the computational issue becomes critical. To fill this gap, we propose a large-scale MVSC (LMVSC) algorithm with linear order complexity. Inspired by the idea of anchor graph, we first learn a smaller graph for each view. Then, a novel approach is designed to integrate those graphs so that we can implement spectral clustering on a smaller graph. Interestingly, it turns out that our model also applies to single-view scenario. Extensive experiments on various large-scale benchmark data sets validate the effectiveness and efficiency of our approach with respect to state-of-the-art clustering methods.

Type 2 diabetes has become a global public health problem affecting approximately 380 million people throughout the world. It can cause many complications and lead to greater mortality. At present, there is no available medicine for effectively preventing diabetes. L-arginine, a functional amino acid, the precursor of nitric oxide, plays a crucial role in maintenance, reproduction, growth, anti-aging and immunity for animals. Growing clinical evidence indicates that dietary L-arginine supplementation can reduce obesity, decrease arterial blood pressure, resist oxidation and normalize endothelial dysfunction to bring about remission of type 2 diabetes. The potential molecular mechanism may play a role in modulating glucose homeostasis, promoting lipolysis, maintaining hormone levels, ameliorating insulin resistance, and fetal programing in early stages. The possible signaling pathway of the beneficial effects of L-arginine likely involves L-arginine-nitric oxide pathway through which cell signal protein can be activated. Accumulating studies have indicated that L-arginine may have potential to prevent and/or relieve type 2 diabetes via restoring insulin sensitivity in vivo.