摘要
由新闻记者-机器人与机器学习的工作人员新闻编辑每日新闻-生物医学工程的新研究-组织工程是一篇报道的主题。根据《新闻周刊》编辑在南京的新闻报道,研究表明:“一种微量酸(AA)代谢在肝再生过程中起着重要作用。然而,它在不同条件下对肝切除术后肝再生的测量价值尚不清楚。”我们的新闻记者引用了中国医药大学的研究，将机器学习(ML)模型与AA代谢指标相结合,对健康和非酒精性脂肪性肝炎(N ASH)小鼠肝再生进行评价,计算健康和非酒精性脂肪性肝炎(N ASH)小鼠70%肝切除后肝脏指数(肝重/体重),采用超高效液相色谱-串联质谱分析测定血清39种氨基酸含量,并用正交偏最小二乘判别分析确定差异。采用SHapley相加解释算法识别部分AA信号,采用最小绝对收缩和S选择算子、随机森林、K-近邻(KNN)、支持向量回归和极梯度增强5种ML模型评估肝指数,在健康组和NASH组分别识别出El偶数和22种差异AA信号。在这些代谢产物中，精氨酸和脯氨酸代谢是两组肝再生相关的常见代谢途径，分别鉴定出5个氨基酸信号，分别为健康组羟赖氨酸、L-丝氨酸、3-ME组氨酸、L-酪氨酸和高瓜氨酸，NASH组L-精氨酸、2-aminobutyric酸、肌氨酸、β-丙氨酸和L-半胱氨酸。健康组和NASH组的决定系数分别为0.0037、0.0047、0.79和0.0028、0.0034、0.71.
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Biomedical Engineering-Tissue Engineering is the subject of a report. According to news reporting ou t of Nanjing, People's Republic of China, by NewsRx editors, research stated, "A mino acid (AA) metabolism plays a vital role in liver regeneration. However, its measuring utility for post-hepatectomy liver regeneration under different condi tions remains unclear." Our news journalists obtained a quote from the research from China Pharmaceutica l University, "We aimed to combine machine learning (ML) models with AA metabolo mics to assess liver regeneration in health and non-alcoholic steatohepatitis (N ASH). The liver index (liver weight/body weight) was calculated following 70% hepatectomy in healthy and NASH mice. The serum levels of 39 amino acids were me asured using ultra-high performance liquid chromatography-tandem mass spectromet ry analysis. We used orthogonal partial least squares discriminant analysis to d etermine differential AAs and disturbed metabolic pathways during liver regenera tion. The SHapley Additive exPlanations algorithm was performed to identify pote ntial AA signatures, and five ML models including least absolute shrinkage and s election operator, random forest, K-nearest neighbor (KNN), support vector regre ssion, and extreme gradient boosting were utilized to assess the liver index. El even and twenty-two differential AAs were identified in the healthy and NASH gro ups, respectively. Among these metabolites, arginine and proline metabolism were commonly disturbed metabolic pathways related to liver regeneration in both gro ups. Five AA signatures were identified, including hydroxylysine, L-serine, 3-me thylhistidine, L-tyrosine, and homocitrulline in healthy group, and L-arginine, 2-aminobutyric acid, sarcosine, beta-alanine, and L-cysteine in NASH group. The KNN model demonstrated the best evaluation performance with mean absolute error, root mean square error, and coefficient of determination values of 0.0037, 0.00 47, 0.79 and 0.0028, 0.0034, 0.71 for the healthy and NASH groups, respectively. "
NETL
NSTL