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1.
Int J Biol Macromol ; 259(Pt 1): 129144, 2024 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-38181918

RESUMO

TMEM182, a transmembrane protein highly expressed in muscle and adipose tissues, plays a crucial role in muscle cell differentiation, metabolism, and signaling. However, its role in fat deposition and metabolism is still unknown. In this study, we used overexpression and knockout models to examine the impact of TMEM182 on fat synthesis and metabolism. Our results showed that TMEM182 overexpression increased the expression of fat synthesis-related genes and promoted the differentiation of preadipocytes into fat cells. In TMEM182 knockout mice, there was a significant decrease in abdominal fat deposition. RNA sequencing results showed that TMEM182 overexpression in preadipocytes enhanced the activity of pathways related to fat formation, ECM-receptor interaction, and cell adhesion. Furthermore, our analysis using UPLC-MS/MS showed that TMEM182 significantly altered the metabolite and lipid content and composition in chicken breast muscle. Specifically, TMEM182 increased the content of amino acids and their derivatives in chicken breast muscle, promoting amino acid metabolic pathways. Lipidomics also revealed a significant increase in the content of glycerophospholipids, sphingolipids, and phospholipids in the breast muscle after TMEM182 overexpression. These findings suggest that TMEM182 plays a crucial role in regulating fat deposition and metabolism, making it a potential target for treating obesity-related diseases and animal breeding.


Assuntos
Proteínas Aviárias , Lipidômica , Proteínas de Membrana , Espectrometria de Massas em Tandem , Animais , Camundongos , Adipócitos/metabolismo , Tecido Adiposo/metabolismo , Galinhas , Cromatografia Líquida , Metabolismo dos Lipídeos/genética , Proteínas de Membrana/genética , Proteínas de Membrana/metabolismo , Proteínas Aviárias/metabolismo
2.
Food Chem ; 438: 137967, 2024 Apr 16.
Artigo em Inglês | MEDLINE | ID: mdl-37979274

RESUMO

A comprehensive comparison of metabolomic, lipidomic, and proteomic profiles was conducted between the breast and leg muscles of Shitou goose (STE) and Wuzhong goose (WZE), which exhibit significant variations in body size and growth rate, to evaluate their impact on meat quality. WZE had higher intramuscular fat content in their breast muscles, which were also chewier and had higher drip and cooking losses than STE. Metabolomic analysis revealed differential regulation of amino acid and purine metabolism between WZE and STE. Lipidomic analysis indicated a higher abundance of PE and PC lipid molecules in WZE. Integration of proteomic and metabolomic data highlighted purine metabolism and amino acid biosynthesis as the major distinguishing pathways between STE and WZE. The primary differential pathways between breast and leg muscles were associated with energy metabolism and fatty acid metabolism. This comprehensive analysis provides valuable insights into the distinct meat quality of STE and WZE.


Assuntos
Gansos , Lipidômica , Animais , Proteômica , Aminoácidos , Carne/análise , Purinas
3.
Sci Total Environ ; 882: 163305, 2023 Jul 15.
Artigo em Inglês | MEDLINE | ID: mdl-37054798

RESUMO

Microplastic (MP) pollution has become one of the global environmental concerns, but the contamination and effect of MP on chicken skeletal muscle are scarcely researched. Here, we found MP contamination in the chicken skeletal muscles, which were directly collected from a large-scale chicken farm. Using Pyrolysis-Gas Chromatography-Mass Spectrometry and Agilent 8700 laser direct infrared imaging spectrometer, we found that polystyrene (PS) and polyamide are the significant type of MPs detected in chicken skeletal muscle. Constant PS-MP oral feeding for >21 days increases the content of MP deposited in chicken breast muscle, but the MP content in the leg muscle was gradually decreased. Surprisingly, the chicken's body and skeletal muscle weight was increased after constant PS-MP feeding. Physiological results showed that PS-MP exposure inhibited energy and lipid metabolism, induced oxidative stress, and potential for neurotoxicity in the skeletal muscle. Metabolomic analysis of the liquid chromatography-tandem mass spectrometry and gas chromatography coupled with the mass spectrometer results showed that PS-MP exposure changed the metabolomic profile and reduced meat quality. In vitro, experimental results showed that PS-MP exposure induced chicken primary myoblasts proliferation and apoptosis but decreased myoblasts differentiation. Transcriptome analysis of the skeletal muscle indicates that PS-MP exposure affects skeletal muscle function by regulating genes involved in neural function and muscle development. Considering that chicken is one of the most important meat foods in the world, this study will provide an essential reference for protecting meat food safety.


Assuntos
Microplásticos , Plásticos , Animais , Microplásticos/metabolismo , Plásticos/metabolismo , Galinhas/genética , Cromatografia Gasosa-Espectrometria de Massas , Músculo Esquelético/metabolismo , Poliestirenos/toxicidade , Carne/análise
4.
Sensors (Basel) ; 21(10)2021 May 13.
Artigo em Inglês | MEDLINE | ID: mdl-34068351

RESUMO

Lightweight UAVs equipped with deep learning models have become a trend, which can be deployed for automatic navigation in a wide range of civilian and military missions. However, real-time applications usually need to process a large amount of image data, which leads to a very large computational complexity and storage consumption, and restricts its deployment on resource-constrained embedded edge devices. To reduce the computing requirements and storage occupancy of the neural network model, we proposed the ensemble binarized DroNet (EBDN) model, which implemented the reconstructed DroNet with the binarized and ensemble learning method, so that the model size of DroNet was effectively compressed, and ensemble learning method was used to overcome the defect of the poor performance of the low-precision network. Compared to the original DroNet, EBDN saves more than 7 times of memory footprint with similar model accuracy. Meanwhile, we also proposed a novel and high-efficiency hardware architecture to realize the EBDN on the chip (EBDNoC) system, which perfectly realizes the mapping of an algorithm model to hardware architecture. Compared to other solutions, the proposed architecture achieves about 10.21 GOP/s/kLUTs resource efficiency and 208.1 GOP/s/W energy efficiency, while also providing a good trade-off between model performance and resource utilization.

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