Scholarlink

<p>The liver is capable of regeneration, regaining mass through compensatory hypertrophy even after resecting 70% of its mass. However, the underlying regenerative mechanism remains poorly understood. Thus, in this study, microarray data were procured over time, from 0 to 14 days post-70% partial hepatectomy (PH) in mice. This dataset was correlated with the body weight and liver weight measured at the time of liver harvest, allowing us to determine the progress of compensatory hypertrophy in each sample. Furthermore, the impact of individual differences in regenerative capacity was analyzed by preparing three biological replicates at each time point. The microarray data were confirmed to be of high quality based on the RNA integrity number and QC stats of the dataset. The reliability of the dataset was further supported by the results of hierarchical clustering and the expression variation of cell cycle–related genes. This microarray data will contribute to the elucidation of the regenerative mechanism in the 70% PH model.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Time-course liver microarray data from 0 to 14 days in a 70% partial hepatectomy mouse model

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年5月10日

查看全文
  • Takashi Nishi,
  • Yoshinao Oki,
  • Reiko Hagiwara,
  • Koichiro Kano

摘要

The liver is capable of regeneration, regaining mass through compensatory hypertrophy even after resecting 70% of its mass. However, the underlying regenerative mechanism remains poorly understood. Thus, in this study, microarray data were procured over time, from 0 to 14 days post-70% partial hepatectomy (PH) in mice. This dataset was correlated with the body weight and liver weight measured at the time of liver harvest, allowing us to determine the progress of compensatory hypertrophy in each sample. Furthermore, the impact of individual differences in regenerative capacity was analyzed by preparing three biological replicates at each time point. The microarray data were confirmed to be of high quality based on the RNA integrity number and QC stats of the dataset. The reliability of the dataset was further supported by the results of hierarchical clustering and the expression variation of cell cycle–related genes. This microarray data will contribute to the elucidation of the regenerative mechanism in the 70% PH model.