7 research outputs found
MicroMotility: State of the art, recent accomplishments and perspectives on the mathematical modeling of bio-motility at microscopic scales
Mathematical modeling and quantitative study of biological motility (in particular, of motility at microscopic scales) is producing new biophysical insight and is offering opportunities for new discoveries at the level of both fundamental science and technology. These range from the explanation of how complex behavior at the level of a single organism emerges from body architecture, to the understanding of collective phenomena in groups of organisms and tissues, and of how these forms of swarm intelligence can be controlled and harnessed in engineering applications, to the elucidation of processes of fundamental biological relevance at the cellular and sub-cellular level. In this paper, some of the most exciting new developments in the fields of locomotion of unicellular organisms, of soft adhesive locomotion across scales, of the study of pore translocation properties of knotted DNA, of the development of synthetic active solid sheets, of the mechanics of the unjamming transition in dense cell collectives, of the mechanics of cell sheet folding in volvocalean algae, and of the self-propulsion of topological defects in active matter are discussed. For each of these topics, we provide a brief state of the art, an example of recent achievements, and some directions for future research
Relative position of constitutive heterochromatin and of nucleolar structures during mouse spermiogenesis
Quantitative Cytoarchitectonic Findings in Postmortem Brain Tissue from Mood Disorder Patients
A community-based transcriptomics classification and nomenclature of neocortical cell types
To understand the function of cortical circuits it is necessary to classify their underlying cellular diversity. Traditional attempts based on comparing anatomical or physiological features of neurons and glia, while productive, have not resulted in a unified taxonomy of neural cell types. The recent development of single-cell transcriptomics has enabled, for the first time, systematic high-throughput profiling of large numbers of cortical cells and the generation of datasets that hold the promise of being complete, accurate and permanent. Statistical analyses of these data have revealed the existence of clear clusters, many of which correspond to cell types defined by traditional criteria, and which are conserved across cortical areas and species. To capitalize on these innovations and advance the field, we, the Copenhagen Convention Group, propose the community adopts a transcriptome-based taxonomy of the cell types in the adult mammalian neocortex. This core classification should be ontological, hierarchical and use a standardized nomenclature. It should be configured to flexibly incorporate new data from multiple approaches, developmental stages and a growing number of species, enabling improvement and revision of the classification. This community-based strategy could serve as a common foundation for future detailed analysis and reverse engineering of cortical circuits and serve as an example for cell type classification in other parts of the nervous system and other organs