β-hydroxybutyrate administration improves liver injury and metabolic abnormality in postnatal growth retardation piglets

Abnormal hepatic energy metabolism limits the growth and development of piglets. We hypothesized that β-hydroxybutyrate (BHB) might improve the growth performance of piglets by maintaining hepatic caloric homeostasis. A total of 30 litters of newborn piglets were tracked, and 30 postnatal growth retardation (PGR) piglets and 40 healthy piglets were selected to treat with normal saline with or without BHB (25 mg/kg/days) at 7-d-old. At the age of 42 days, 8 piglets in each group were sacrificed, and serum and liver were collected. Compared with the healthy-control group piglets, PGR piglets showed lower body weight (BW) and liver weight (p < 0.05), and exhibited liver injury and higher inflammatory response. The contents of serum and hepatic BHB were lower (p < 0.05), and gene expression related to hepatic ketone body production were down-regulated in PGR piglets (p < 0.05). While BHB treatment increased BW and serum BHB levels, but decreased hepatic BHB levels in PGR piglets (p < 0.05). BHB alleviated the liver injury by inhibiting the apoptosis and inflammation in liver of PGR piglets (p < 0.05). Compared with the healthy-control group piglets, liver glycogen content and serum triglyceride level of PGR piglets were increased (p < 0.05), liver gluconeogenesis gene and lipogenesis gene expression were increased (p < 0.05), and liver NAD+ level was decreased (p < 0.05). BHB supplementation increased the ATP levels in serum and liver (p < 0.05), whereas decreased the serum glucose, cholesterol, triglyceride and high-density lipoprotein cholesterol levels and glucose and lipid metabolism in liver of PGR piglets (p < 0.05). Therefore, BHB treatment might alleviate the liver injury and inflammation, and improve hepatic energy metabolism by regulating glucose and lipid metabolism, thereby improving the growth performance of PGR piglets

Adaptive Correlation Model for Visual Tracking Using Keypoints Matching and Deep Convolutional Feature

Although correlation filter (CF)-based visual tracking algorithms have achieved appealing results, there are still some problems to be solved. When the target object goes through long-term occlusions or scale variation, the correlation model used in existing CF-based algorithms will inevitably learn some non-target information or partial-target information. In order to avoid model contamination and enhance the adaptability of model updating, we introduce the keypoints matching strategy and adjust the model learning rate dynamically according to the matching score. Moreover, the proposed approach extracts convolutional features from a deep convolutional neural network (DCNN) to accurately estimate the position and scale of the target. Experimental results demonstrate that the proposed tracker has achieved satisfactory performance in a wide range of challenging tracking scenarios

Ellagic Acid Alleviates Oxidative Stress by Mediating Nrf2 Signaling Pathways and Protects against Paraquat-Induced Intestinal Injury in Piglets

The gastrointestinal tract is a key source of superoxide so as to be one of the most vulnerable to oxidative stress damage. Ellagic acid (EA), a polyphenol displays widely biological activities owing to its strong antioxidant properties. Here, we investigated the protective benefits of EA on oxidative stress and intestinal barrier injury in paraquet (PQ)-challenged piglets. A total of 40 weaned piglets were randomly divided into five groups: Control, PQ, 0.005% EA-PQ, 0.01% EA-PQ, and 0.02% EA-PQ. Piglets were intraperitoneally injected with 4 mg/kg (BW) PQ or saline on d-18, and sacrificed on d-21 of experiment. EA treatments eliminated growth-check induced by PQ and increased serum superoxide dismutase (SOD) activity but decreased serum malondialdehyde (MDA) level as compared to PQ group. EA supplementation promoted Nrf2 nuclear translocation and enhanced heme oxygenase-1 (HO-1) and quinone oxidoreductase 1 (NQO1) protein abundances of small intestinal mucosa. Additionally, EA improved PQ-induced crypt deepening, goblet cells loss, and villi morphological damage. Consistently, EA increased tight junction protein expression as was evident from the decreased serum diamine oxidase (DAO) levels. EA could ameliorate the PQ-induced oxidative stress and intestinal damage through mediating Nrf2 signaling pathway. Intake of EA-rich food might prevent oxidative stress-mediated gut diseases

Clec7a drives gut fungus-mediated host lipid deposition

Abstract Background Compared to that of bacteria, the role of gut fungi in obesity development remains unknown. Results Here, alterations in gut fungal biodiversity and composition were confirmed in obese pig models and high-fat diet (HFD)-fed mice. Antifungal drugs improved diet-induced obesity, while fungal reconstruction by cohousing or fecal microbiota transplantation maintained the obese phenotype in HFD-fed mice. Fungal profiling identified 5 fungal species associated with obesity. Specifically, Ascomycota_sp. and Microascaceae_sp. were reduced in obese mice and negatively correlated with fat content. Oral supplementation with fungi was sufficient to prevent and treat diet-induced obesity. Clec7a, which is involved in fungal recognition, was highly expressed in HFD-fed mice. The Clec7a agonist accelerated diet-induced obesity, while Clec7a deficieny in mice resulted in resistance to diet-induced obesity and blocked the anti-obese effect of antifungal drugs and fungi. Conclusions Taken together, these results indicate that gut fungi/Clec7a signaling is involved in diet-induced obesity and may have therapeutic implications as a biomarker for metabolic dysregulation in humans. Video Abstrac

A Survey of Artificial Intelligence Techniques Applied in Energy Storage Materials R&D

Energy shortage is a severe challenge nowadays. It has affected the development of new energy sources. Artificial intelligence (AI), such as learning and analyzing, has been widely used for various advantages. It has been successfully applied to predict materials, especially energy storage materials. In this paper, we present a survey of the present status of AI in energy storage materials via capacitors and Li-ion batteries. We picture the comprehensive progress of AI in energy storage materials, including the advantages and disadvantages of material data to support AI. Finally, we provide some ideas to solve those challenges