A microfluidic cell capture device was designed, fabricated, evaluated by numerical simulations and validated experimentally. The cell capture device was designed with a minimal footprint compartment comprising internal micropillars with the goal to obtain a compact, integrated bioanalytical system. The design of the device was accomplished by computational fluid dynamics (CFD) simulations. Various microdevice designs were rapidly prototyped in poly-dimethylsiloxane using conventional soft lithograpy technique applying micropatterned SU-8 epoxy based negative photoresist as moulding replica. The numerically modeled flow characteristics of the cell capture device were experimentally validated by tracing and microscopic recording the flow trajectories using yeast cells. Finally, we give some perspectives on how CFD modeling can be used in the early stage of microfluidics-based cell capture device development.
Recently, cerebral folate deficiency (CFD) was suggested to be involved in the pathogenesis of autism spectrum disorders (ASD). However, the exact role of folate metabolism in the pathogenesis of ASD, identification of underlying pathogenic mechanisms and impaired metabolic pathways remain unexplained. The aim of our study was to develop and test a novel, unbiased, bioinformatics approach in order to identify links between ASD and disturbed cerebral metabolism by focusing on abnormal folate metabolism, which could foster patient stratification and novel therapeutic interventions. An unbiased, automatable, computational workflow interaction model was developed using available data from public databases. The interaction network model of ASD-associated genes with known cerebral expression and function (SFARI) and metabolic networks (MetScape), including connections to known metabolic substrates, metabolites and cofactors involving folates, was established. Intersection of bioinformatically created networks resulted in a limited amount of interaction modules pointing to common disturbed metabolic pathways, linking ASD to CFD. Two independent interaction modules (comprising three pathways) covering enzymes encoded by ASD-related genes and folate cofactors utilizing enzymes were generated. Module 1 suggested possible interference of CFD with serine and lysine metabolism, while module 2 identified correlations with purine metabolism and inosine monophosphate production. Since our approach was primarily conceived as a proof of principle, further amendments of the presented initial model are necessary to obtain additional actionable outcomes. Our modelling strategy identified not only previously known interactions supported by evidence-based analyses, but also novel plausible interactions, which could be validated in subsequent functional and/or clinical studies. Autism Res 2017, 10: 1424-1435. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.
- MeSH
- Databases, Factual MeSH
- Humans MeSH
- Brain metabolism MeSH
- Folic Acid Deficiency complications MeSH
- Autism Spectrum Disorder complications metabolism MeSH
- Models, Theoretical * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
