by Josh Conway – Lifespan.io
As expected, this paper begins with a discussion of stem cell exhaustion and its downstream consequences. It continues with an elaboration on stemness, the particular biochemistry that stem cells exhibit, which underlies efforts to determine what exactly makes a stem cell a stem cell [1]. These researchers note that, even though stem cell exhaustion is a hallmark of aging, most previous efforts, including machine learning efforts, have attempted to define stemness in the context of cancer [2] rather than aging.
Therefore, this team has put machine learning to work in analyzing the transcriptome, the collection of gene transcriptions that RNA has made from DNA. Taking a total of 17,382 samples from 30 different tissues of people between 20 and 79 years old, the researchers followed the same rigorous path as the cancer researchers did [2], assigning a score to samples based on how much they resembled known stem cells.
