Small-world dynamics drove Phanerozoic divergence of burrowing behaviors

Species of burrowing animals have changed substantially over evolutionary time scales, but, surprisingly, burrows display persisting morphological patterns throughout the Phanerozoic. Deep-sea burrows are geometrically patterned, whereas shallow-marine burrows display simpler morphologies. This divergence between burrow associations is one of the central conundrums of paleontology, but it has never been quantitatively demonstrated, and the organizing principles responsible for this structure remain unknown. We show that the divergence of burrow associations has been shaped by small-world dynamics, which is proposed as a major macroevolutionary force in marine environments. Using network analysis, our study reveals that the association patterns between burrow morphotypes in 45 paleontological sites span -500 m.y. Strong statistical support is demonstrated for a surprising association pattern, according to which the data set is optimally partitioned into two subgroups of tightly associated burrow types. These groups correspond to shallow-and deep-marine biomes. Our analysis demonstrates that across the Phanerozoic Eon, burrows did not assemble randomly nor regularly, following instead small-world assembly rules remarkably similar to those that shape human social networks. As such, small-world dynamics deeply influenced gene flow and natural variation in heritable behavior across evolutionary time

Gonial angle, mandibular divergence and nasal to oral conductance ratio relationships in children with malocclusion

Abstract a congress

Genome classification by dictionary-based indexes

A major application of bioinformatics concerns with the analysis of the full genomes of organisms that have been sequenced from the late 1990s. Several techniques of genome analysis are based on sequence alignment, structure prediction, phylogenomics, gene prediction and other biology-driven approaches [2]. In [1] a new approach has been proposed for genome analysis and comparative genomics which takes its roots in text analysis and information theory. The aim is to provide sets of linguistic/informational indexes able to characterize genome properties which are relevant in specific biological contexts. Here we determine a set of indexes having the capability of discriminating genomes, in almost full accordance with the domains to which\ua0their organisms belong.\ua

Neutrophils promote Alzheimer's disease–like pathology and cognitive decline via LFA-1 integrin

Inflammation is a pathological hallmark of Alzheimer's disease, and innate immune cells have been shown to contribute to disease pathogenesis. In two transgenic models of Alzheimer's disease (5xFAD and 3xTg-AD mice), neutrophils extravasated and were present in areas with amyloid-β (Aβ) deposits, where they released neutrophil extracellular traps (NETs) and IL-17. Aβ42 peptide triggered the LFA-1 integrin high-affinity state and rapid neutrophil adhesion to integrin ligands. In vivo, LFA-1 integrin controlled neutrophil extravasation into the CNS and intraparenchymal motility. In transgenic Alzheimer's disease models, neutrophil depletion or inhibition of neutrophil trafficking via LFA-1 blockade reduced Alzheimer's disease-like neuropathology and improved memory in mice already showing cognitive dysfunction. Temporary depletion of neutrophils for 1 month at early stages of disease led to sustained improvements in memory. Transgenic Alzheimer's disease model mice lacking LFA-1 were protected from cognitive decline and had reduced gliosis. In humans with Alzheimer's disease, neutrophils adhered to and spread inside brain venules and were present in the parenchyma, along with NETs. Our results demonstrate that neutrophils contribute to Alzheimer's disease pathogenesis and cognitive impairment and suggest that the inhibition of neutrophil trafficking may be beneficial in Alzheimer's disease