Schwarz, J. M. | bioRxiv Science

bioRxiv2018

Brain folding is initiated by mechanical constraints without a cellular pre-pattern

During human brain development the cerebellum and cerebral cortex fold into robust patterns that increase and compartmentalize neural circuits. Although differential expansion of elastic materials has been proposed to explain brain folding, the cellular and physical processes responsible at the time of folding have not been defined. Here we used the murine cerebellum, with 8-10 folds, as a tractable model to study brain folding. At folding initiation we considered the cerebellum as a bilayer system with a fluidlike outer layer of proliferating precursors and an incompressible core. We discovered that there is no obvious cellular pre-pattern for folding, since when folding initiates, the precursors within the outer layer have uniform sizes, shapes and proliferation, as well as a distribution of glial fibers. Furthermore, although differential expansion is created by the outer layer expanding faster than the core at folding initiation, thickness variations arise in the outer layer that are inconsistent with elastic material models. A multiphase model was applied that includes radial and circumferential tension and mechanical constraints derived from in vivo measurements. Our results demonstrate that cerebellar folding emerges from mechanical forces generated by uniform cell behaviors. We discuss how our findings apply to human cerebral cortex folding.

developmental biology↗

bioRxiv2018

Phenotero: annotate as you write

Controlled vocabularies and ontologies have become a valuable resource for knowledge representation, data integration, and downstream analyses in the biomedical domain. In precision medicine, especially in clinical genetics, the Human Phenotype Ontology (HPO) as well as disease ontologies like the Orphanet Rare Disease Ontology (ORDO) or Medical Subject Headings (MeSH) are often used for deep phenotyping of patients and coding of clinical diagnoses. However, the process of assigning ontology classes (annotating) to patient descriptions is often disconnected from the process of writing patient reports or manuscripts in word processing software such as Microsoft Word or LibreOffice. This additional workload and the requirement to install dedicated software may discourage usage of ontologies for parts of the target audience.\n\nTo improve this situation, we present Phenotero, a freely available and simple solution to annotate patient phenotypes and diseases at the time of writing clinical reports or manuscripts. We adopt Zotero, a well-established, actively developed citation management software to generate a tool which allows to reference classes from ontologies within clinical reports or manuscripts at the time of writing. We expect this approach to decrease the additional workload to a minimum while ensuring high quality associations with ontology classes. Standardised collection of phenotypic information at the time of describing the patient allows for streamlining of clinic workflow, efficient data entry, and will subsequently promote clinical and molecular diagnosis, remove ambiguousness from manuscripts, and allow sharing of anonymised patient phenotype data with ultimate goal of a better understanding of the disease. Thus, we hope that our integrated approach will further promote the usage of ontologies and controlled vocabularies in the clinical setting and in the biomedical domain.

bioinformatics↗