https://www.selleckchem.com/products/cilofexor-gs-9674.html We show that, contrary to long-standing assumptions, syntactic traits, modeled here within the generative biolinguistic framework, provide insights into deep-time language history. To support this claim, we have encoded the diversity of nominal structures using 94 universally definable binary parameters, set in 69 languages spanning across up to 13 traditionally irreducible Eurasian families. We found a phylogenetic signal that distinguishes all such families and matches the family-internal tree topologies that are safely established through classical etymological methods and datasets. We have retrieved "near-perfect" phylogenies, which are essentially immune to homoplastic disruption and only moderately influenced by horizontal convergence, two factors that instead severely affect more externalized linguistic features, like sound inventories. This result allows us to draw some preliminary inferences about plausible/implausible cross-family classifications; it also provides a new source of evidence for testing the representation of diversity in syntactic theories. This study aimed to examine the long-term association between social activity, physical function decline and cognitive function, as well as verify the long-term mediating effect of physical function decline on the relationship between social activity and cognitive function. Data from the Korean Longitudinal Study of Aging (KLoSA) that was collected over 10 years was analyzed. The sample included 10,240 adults aged 45-93 years (Mean age = 61.66 [SD = 11.061]). Multivariate latent growth modeling (LGM) was applied to verify the long-term effect of social activity and physical function on cognitive function. The results revealed that social activity had a positive impact on cognitive function and negative impact on physical function decline after controlling for age and education level. Additionally, physical function decline negatively influenced co