Robotics & Machine Learning Daily News2024,Issue(Jun.18) :188-189.

Artificial intelligence as a ploy to delve into the intricate relationship betwe en genetics and mitochondria in MASLD patients

人工智能作为探索MASLD患者遗传与线粒体复杂关系的策略

Robotics & Machine Learning Daily News2024,Issue(Jun.18) :188-189.

Artificial intelligence as a ploy to delve into the intricate relationship betwe en genetics and mitochondria in MASLD patients

人工智能作为探索MASLD患者遗传与线粒体复杂关系的策略

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摘要

根据基于预印摘要的新闻报道,我们的记者获得了来自BI orxiv.org的以下引文:“背景和目的:线粒体(MT-)功能障碍是进步性MASLD的标志。mtDNA拷贝数(mtDNA-CN)和无细胞循环mtDNA(CCF-MTDN A),它们分别反映了MT质量和MT功能障碍。本研究从一个发现(n=28)和一个验证(n=824)的队列中进一步探讨了MT-生物发生、功能和MT-生物标志物,并以风险变异体(NRV=3)的数量为基础,利用人工智能(AI)建立了新的风险评分,以此为基础,对HepG2细胞中PNPLA3/MBO AT7/TM6SF2缺失增加了MT-质量、mtDNACN和CF-mtDNA。方法:采用透射电镜、免疫组化、基因表达等方法评价肝脏MASLD的形态和动力学,检测PBMC和血清标本中MTDNA-CN和CF-mtDNA,GPT-4作为人工智能工具,支持建立MASLD进展形式(MASH、纤维化和HCC)的新风险评分。NR V=3例患者表现出最高的MT质量和显著的MT形态改变(即胎膜破裂),这些患者的MT生物发生、融合和分裂标记物PGC-1、OPA1、DRP1和PINK1升高,支持MT动力学的增强。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-According to news reporting based on a preprint abstract, our journalists obtained the following quote sourced from bi orxiv.org: "Background and Aims: Mitochondrial (mt-) dysfunction is a hallmark of progressi ve MASLD. MtDNA copy number (mtDNA-CN) and cell-free circulating mtDNA (ccf-mtDN A), which reflect mt-mass and mt-dysfunction, respectively, are gaining attentio n as non-invasive disease biomarkers. We previously demonstrated that PNPLA3/MBO AT7/TM6SF2 deficiency in HepG2 cells increased mt-mass, mtDNACN and ccf-mtDNA. This study furtherly explored mt-biogenesis, function and mt-biomarkers in biops ied MASLD patients from a Discovery (n=28) and a Validation (n=824) cohort, stra tified by the number of risk variants (NRV=3). We took advantage of artificial i ntelligence (AI) to develop new risk scores, predicting MASLD evolution by integ rating anthropometric and genetic data (Age, BMI, NRV) with mtbiomarkers. Metho ds: Hepatic mt-morphology and dynamics were assessed by TEM, IHC and gene expres sion. mtDNA-CN and ccf-mtDNA were measured in PBMCs and serum samples. GPT-4 was employed as AI tool to support the construction of novel risk scores for MASLD progressive forms (MASH, fibrosis and HCC). Results: In the Discovery cohort, NR V=3 patients showed the highest mt-mass and significant mtmorphological changes (i.e. membranes rupture). An elevated PGC-1, OPA1, DRP1 and PINK1, markers of m t-biogenesis, fusion and fission were found in these patients, supporting an enh anced mt-dynamics.

Key words

Artificial Intelligence/Cellular Struct ures/Cytoplasm/Cytoplasmic Structures/Emerging Technologies/Genetics/Intrac ellular Space/Machine Learning/Mitochondria/Organelles/Subcellular Fractions

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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