Research conducted in collaboration between the Institute of Complex Systems of the National Research Council (Cnr-Isc) and the Sapienza University of Rome has identified an internal regulatory system that organizes the development of skeletal stem cell lines through measurable criteria. The results of the study appeared in the scientific newspaper PRX Life of the American Physical Society, highlight how the marked fluctuations in the behavior of the stem cells are not attributable to random factors, but derive from a specific form of biological memory. The investigation made use of the application of a model derived from statistical physics called “inheritance entropy“, or heredity entropy, used for quantify the level of organization and transmission of characters along the family tree of the colony. When a stem cell starts the division phase, the generated lineage is divided into different trajectories, where certain branches maintain constant multiplication and others undergo an early arrest. Research shows that this interruption responds to a structured program linked to the history of the cell lineage.
Andrea Cavagna, Cnr-Isc researcher and one of the signatories of the work, specified: “LThe key to this discovery lies in the calculation of entropy, a concept which in physics measures the degree of disorder of a system. We discovered that at certain points in the family tree an epigenetic modification is activated, that is, a change that influences cellular behavior without altering the DNA, which acts as a biological countdown for all future descendants“. This alteration operates like a timed mechanism, the effects of which do not appear immediately but influence subsequent replicative cycles in a deferred manner. “This time frame creates a highly organized pattern within the colony“, adds Cavagna“It is precisely this surplus of order that reduces entropy, demonstrating that the growth of stem cells follows much more structured rules than expected, guided by an ancestral memory and not by chance“.
The introduction of this measurement methodology based onhereditary entropy offers new perspectives for investigation in the field of regenerative medicine and in study models linked to the senescence of biological tissues. Understanding these dynamics of information transmission could also find application in the field of oncology research, in particular for the analysis of hereditary processes that regulate drug resistance phenomena within tumor cell populations.
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