Betulin Targets Lipin1/2-Meidated P2X7 Receptor as a Therapeutic Approach to Attenuate Lipid Accumulation and Metaflammation
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- Biomolecules & Therapeutics
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- v.30 no.3
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- pp.246-256
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- 2022
The present study focused on the potential mechanism of betulin (BT), a pentacyclic triterpenoid isolated from the bark of white birch (Betula pubescens), against chronic alcohol-induced lipid accumulation and metaflammation. AML-12 and RAW 264.7 cells were administered ethanol (EtOH), lipopolysaccharide (LPS) or BT. Male C57BL/6 mice were fed Lieber-DeCarli liquid diets containing 5% EtOH for 4 weeks, followed by single EtOH gavage on the last day and simultaneous treatment with BT (20 or 50 mg/kg) by oral gavage once per day. In vitro, MTT showed that 0-25 mM EtOH and 0-25 µM BT had no toxic effect on AML-12 cells. BT could regulate sterolregulatory-element-binding protein 1 (SREBP1), lipin1/2, P2X7 receptor (P2X7r) and NOD-like receptor family, pyrin domains-containing protein 3 (NLRP3) expressions again EtOH-stimulation. Oil Red O staining also indicated that BT significantly reduced lipid accumulation in EtOH-stimulated AML-12 cells. Lipin1/2 deficiency indicated that BT might mediate lipin1/2 to regulate SREBP1 and P2X7r expression and further alleviate lipid accumulation and inflammation. In vivo, BT significantly alleviated histopathological changes, reduced serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) and triglyceride (TG) levels, and regulated lipin1/2, SREBP1, peroxisome proliferator activated receptor α/γ (PPARα/γ) and PGC-1α expression compared with the EtOH group. BT reduced the secretion of inflammatory factors and blocked the P2X7r-NLRP3 signaling pathway. Collectively, BT attenuated lipid accumulation and metaflammation by regulating the lipin1/2-mediated P2X7r signaling pathway.
Objective: We aimed to investigate the effect of the differing amino acid (AA) release dynamics of two protein sources on the growth performance, nitrogen deposition, plasma biochemical parameters, and muscle synthesis and degradation of piglets when included in their diets at normal and low concentrations. Methods: Forty-eight piglets (Duroc×Landrace×Large White) with initial body weight of 7.45±0.58 kg were assigned to six groups and fed one of 6 diets. The 6 dietary treatments were arranged by 3×2 factorial with 3 protein sources and 2 dietary protein levels. They are NCAS (a normal protein content with casein), NBlend (a normal protein content with blend of casein and corn gluten meal), NCGM (a normal protein content with corn gluten meal), LCAS (a low protein content with casein), LBlend (a low protein content with blend of casein and corn gluten meal), LCGM (a low protein content with corn gluten meal). The release dynamics of AA in these diets were determined by in vitro digestion. The digestibility, utilization and biological value of nitrogen in piglets were determined by micro Kjeldahl method. Plasma insulin was measured by enzyme-linked immunosorbent assay kits. The protein expression of mediators of muscle synthesis and degradation was determined by western blotting. Results: Although the consumption of a low-protein diet supplemented with crystalline AA was associated with greater nitrogen digestion and utilization (p<0.05), the final body weight, growth performance, nitrogen deposition, and phosphorylation of ribosomal protein S6 kinase 1 and eIF4E binding protein 1 in the muscle of pigs in the low-protein diet-fed groups were lower than those of the normal-protein diet-fed groups (p<0.05) because of the absence of non-essential AA. Because of the more balanced release of AA, the casein (CAS) and Blend-fed groups showed superior growth performance, final body weight and nitrogen deposition, and lower expression of muscle ring finger 1 and muscle atrophy F-box than the CGM-fed groups (p<0.05). Conclusion: We conclude that the balanced release of AA from CAS containing diets and mixed diets could reduce muscle degradation, favor nitrogen retention, % intake and improve growth performance in pigs consuming either a normal- or low-protein diet.
Despite recent breakthroughs in deep learning and computer vision fields, the pixel-wise identification of tiny objects in high-resolution images with complex disturbances remains challenging. This study proposes a modified U-net for tiny crack segmentation in real-world steel-box-girder bridges. The modified U-net adopts the common U-net framework and a novel Self-Attention-Self-Adaption (SASA) neuron as the fundamental computing element. The Self-Attention module applies softmax and gate operations to obtain the attention vector. It enables the neuron to focus on the most significant receptive fields when processing large-scale feature maps. The Self-Adaption module consists of a multiplayer perceptron subnet and achieves deeper feature extraction inside a single neuron. For data augmentation, a grid-based crack random elastic deformation (CRED) algorithm is designed to enrich the diversities and irregular shapes of distributed cracks. Grid-based uniform control nodes are first set on both input images and binary labels, random offsets are then employed on these control nodes, and bilinear interpolation is performed for the rest pixels. The proposed SASA neuron and CRED algorithm are simultaneously deployed to train the modified U-net. 200 raw images with a high resolution of 4928 × 3264 are collected, 160 for training and the rest 40 for the test. 512 × 512 patches are generated from the original images by a sliding window with an overlap of 256 as inputs. Results show that the average IoU between the recognized and ground-truth cracks reaches 0.409, which is 29.8% higher than the regular U-net. A five-fold cross-validation study is performed to verify that the proposed method is robust to different training and test images. Ablation experiments further demonstrate the effectiveness of the proposed SASA neuron and CRED algorithm. Promotions of the average IoU individually utilizing the SASA and CRED module add up to the final promotion of the full model, indicating that the SASA and CRED modules contribute to the different stages of model and data in the training process.
1. The 'Kao Zheng Pai(考證派) comes from the 'Zhe Zhong Pai' and is a school that is influenced by the confucianism of the Qing dynasty. In Japan Inoue Kinga(井上金娥), Yoshida Koton(吉田篁墩) became central members, and the rise of the methodology of historical research(考證學) influenced the members of the 'Zhe Zhong Pai', and the trend of historical research changed from confucianism to medicine, making a school of medicine based on the study of texts and proving that the classics were right. 2. Based on the function of 'Nei Qu Li '(內驅力) the 'Kao Zheng Pai', in the spirit of 'use confucianism as the base', researched letters, meanings and historical origins. Because they were influenced by the methodology of historical research(考證學) of the Qing era, they valued the evidential research of classic texts, and there was even one branch that did only historical research, the 'Rue Xue Kao Zheng Pai'(儒學考證派). Also, the 'Yi Xue Kao Zheng Pai'(醫學考證派) appeared by the influence of Yoshida Kouton and Kariya Ekisai(狩谷掖齋). 3. In the 'Kao Zheng Pai(考證派)'s theories and views the 'Yi Xue Kao Zheng Pai' did not look at medical scriptures like the "Huang Di Nei Jing"("黃帝內經") and did not do research on 'medical' related areas like acupuncture, the meridian and medicinal herbs. Since they were doctors that used medicine, they naturally were based on 'formulas'(方劑) and since their thoughts were based on the historical ideologies, they valued the "Shang Han Ja Bing Lun" which was revered as the 'ancestor of all formulas'(衆方之祖). 4. The lives of the important doctors of the 'Kao Zheng Pai' Meguro Dotaku(目黑道琢) Yamada Seichin(山田正珍), Yamada Kyoko(山田業廣), Mori Ritsi(森立之) Kitamura Naohara(喜多村直寬) are as follows. 1) Meguro Dotaku(目黑道琢 1739
1.The 'Kao Zheng Pai'(考證派) comes from the 'Zhe Zhong Pai(折衷派)' and is a school that is influenced by the confucianism of the Qing dynasty. In Japan Inoue Kinga(井上金峨), Yoshida Koton(古田篁墩