Project description:We propose a detailed CellML model of the human cerebral circulation that runs faster than real time on a desktop computer and is designed for use in clinical settings when the speed of response is important. A lumped parameter mathematical model, which is based on a one-dimensional formulation of the flow of an incompressible fluid in distensible vessels, is constructed using a bond graph formulation to ensure mass conservation and energy conservation. The model includes arterial vessels with geometric and anatomical data based on the ADAN circulation model. The peripheral beds are represented by lumped parameter compartments. We compare the hemodynamics predicted by the bond graph formulation of the cerebral circulation with that given by a classical one-dimensional Navier-Stokes model working on top of the whole-body ADAN model. Outputs from the bond graph model, including the pressure and flow signatures and blood volumes, are compared with physiological data.
Project description:Ceramides contribute to the lipotoxicity that underlies diabetes, hepatic steatosis, and heart disease. By genetically engineering mice, we deleted the enzyme dihydroceramide desaturase-1 (DES1) which inserts a conserved double bond into the backbone of ceramides and other predominant sphingolipids. Ablation of DES1 from whole animals, or tissue-specific deletion in the liver, and/or adipose tissue resolved hepatic steatosis and insulin resistance in mice caused by leptin deficiency or obesogenic diets. Mechanistic studies revealed new ceramide actions that promoted lipid uptake and storage and impaired glucose utilization, none of which could be recapitulated by (dihydro)ceramides that lacked the critical double bond. These studies suggest that inhibition of DES1 may provide a means of treating hepatic steatosis and cardiometabolic disorders.
Project description:Background: The ability to form enduring social bonds is characteristic of human nature and as a result, impairments in social affiliation are central features of severe neuropsychiatric disorders including autism spectrum disorders and schizophrenia. Due to its ability to form long-term pair-bonds, the socially monogamous prairie vole (Microtus ochrogaster) has emerged as an excellent model to study the neurobiology of social attachment. Despite the enduring nature of the bond, however, surprisingly few genes have been implicated in the pair-bonding process in either sex. Results: Using RNA-sequencing, we aimed at identifying the transcriptomic regulations in the nucleus accumbens (NAc) underlying the formation and maintenance of a pair-bond in male and female prairie voles and found sex-specific response patterns despite similar behavioral indicators of pair-bond establishment. Indeed, 24 hrs of cohabitation with an opposite-sex partner induced widespread transcriptomic changes that remained sustained to some extent in females after 3 weeks, but returned to baseline before a second set of regulations in males. This led to a highly sexually-biased NAc transcriptome in the later phase of the bond related to processes such as neurotransmission, protein turnover, and DNA transcription. In particular, we found sex-specific alterations of mitochondrial dynamics following cohabitation, with a shift towards fission in males. Conclusions: In addition to identifying the genes, networks, and pathways involved in the pair-bonding process in the NAc, our work illustrates the vast extent of sex differences in the molecular mechanisms underlying pair-bonding in prairie voles, and paves the way to further our understanding of the complex social bonding process.
Project description:Deciphering the metabolome is essential for a better understanding of the cellular metabolism as a system. Typical metabolomics data show a few but significant correlations among metabolite levels when data sampling is repeated across individuals grown under strictly controlled conditions. Although several studies have assessed topologies in metabolomic correlation networks, it remains unclear whether highly connected metabolites in these networks have specific functions in known tissue- and/or genotype-dependent biochemical pathways. In our study of metabolite profiles we subjected root tissues to gas chromatography-time-of-flight/mass spectrometry (GC-TOF/MS) and used published information on the aerial parts of 3 Arabidopsis genotypes, Col-0 wild-type, methionine over-accumulation 1 (mto1), and transparent testa4 (tt4) to compare systematically the metabolomic correlations in samples of roots and aerial parts. We then applied graph clustering to the constructed correlation networks to extract densely connected metabolites and evaluated the clusters by biochemical-pathway enrichment analysis. We found that the number of significant correlations varied by tissue and genotype and that the obtained clusters were significantly enriched for metabolites included in biochemical pathways. We demonstrate that the graph-clustering approach identifies tissue- and/or genotype-dependent metabolomic clusters related to the biochemical pathway. Metabolomic correlations complement information about changes in mean metabolite levels and may help to elucidate the organization of metabolically functional modules.