Best results when simulating flow diverters as porous media are obtained on models based on geometrical properties using a heterogeneous medium based on equations for flat rhomboidal wire frames. (In this paper, such model is called "R2")
Flow diverters can be simulated with porous media with a good agreement to standard CFD simulations in less than a quarter of the time.
PHOSPHOLIPID:DIACYLGLYCEROL ACYLTRANSFERASE (PDAT) is an enzyme that catalyzes the transfer of a fatty acyl moiety from the sn-2 position of a phospholipid to the sn-3-position of sn-1,2-diacylglyerol, thus forming triacylglycerol and a lysophospholipid. Although the importance of PDAT in triacylglycerol biosynthesis has been illustrated in some previous studies, the evolutionary relationship of plant PDATs has not been studied in detail. In this study, we investigated the evolutionary relationship of the PDAT gene family across the green plants using a comparative phylogenetic framework. We found that the PDAT candidate genes are present in all examined green plants, including algae, lowland plants (a moss and a lycophyte), monocots, and eudicots. Phylogenetic analysis revealed the evolutionary division of the PDAT gene family into seven major clades. The separation is supported by the conservation and variation in the gene structure, protein properties, motif patterns, and/or selection constraints. We further demonstrated that there is a eudicot-wide PDAT gene expansion, which appears to have been mainly caused by the eudicot-shared ancient gene duplication and subsequent species-specific segmental duplications. In addition, selection pressure analyses showed that different selection constraints have acted on three core eudicot clades, which might enable paleoduplicated PDAT paralogs to either become nonfunctionalized or develop divergent expression patterns during evolution. Overall, our study provides important insights into the evolution of the plant PDAT gene family and explores the evolutionary mechanism underlying the functional diversification among the core eudicot PDAT paralogs.
Diacylglycerol acyltransferase (DGAT) catalyzes the acyl-CoA-dependent acylation of sn-1, 2-diacylglycerol to produce triacylglycerol, which is the main component of the seed oil of Brassica oilseed species. Phylogenetic analysis of the amino acid sequences encoded by four transcriptionally active DGAT1 genes from Brassica napus suggests that the gene forms diverged over time into two clades (I and II), with representative members in each genome (A and C). The majority of the amino acid sequence differences in these forms of DGAT1, however, reside outside of motifs suggested to be involved in catalysis. Despite this, the clade II enzymes displayed a significantly enhanced preference for linoleoyl-CoA when assessed using in-vitro enzyme assays with yeast microsomes containing recombinant enzyme forms. These findings contribute to our understanding of triacylglycerol biosynthesis in B. napus, and may advance our ability to engineer DGAT1s with desired substrate selectivity properties.
In computational fluid dynamics, there is a high interest in modeling flow diverter stents as porous media due to its reduced computational loads. One of the main difficulties of such models is proper parameter setup. Most authors assume flow diverter's wire screen as an isotropic and homogeneous medium, while others proposes anisotropic configurations, yet very little is discussed about the effect of these assumptions on model's accuracy. In this paper, we compare the effect of different models on hemodynamics in relation to their parameters. The fidelity and efficiency of the different models to capture wire screen effect on fluid flow are quantitatively analyzed and compared.
The data-driven approach described in this paper provides an unbiased means for systematic prioritization of patient-specific drug combinations that selectively inhibit AML cells and avoid co-inhibition of non-malignant cells
This is the first systematic approach to personalized drug combinations selection that takes into account both the molecular heterogeneity of AML cells and the possible toxic effects of combinations
Non-structural protein 1 (nsp1) is found in all Betacoronavirus genus, an important viral group that causes severe respiratory human diseases. This protein has significant role in pathogenesis and it is considered a probably major virulence factor. As it is absent in humans, it becomes an interesting target of study, especially when it comes to the rational search for drugs, since it increases the specificity of the target and reduces possible adverse effects that may be caused to the patient. Using approaches in silico we seek to study the behavior of nsp1 in solution to obtain its most stable conformation and find possible drugs with affinity to all of them. For this purpose, complete model of nsp1 of SARS-CoV-2 were predicted and its stability analyzed by molecular dynamics simulations in five different replicas. After main pocket validation using two control drugs and the main conformations of nsp1, molecular docking based on virtual screening were performed to identify novel potential inhibitors from DrugBank database. It has been found 16 molecules in common to all five nsp1 replica conformations. Three of them was ranked as the best compounds among them and showed better energy score than control molecules that have in vitro activity against nsp1 from SARS-CoV-2. The results pointed out here suggest new potential drugs for therapy to aid the rational drug search against COVID-19.
Aging clocks dissociate biological from chronological age. The estimation of biological age is important for identifying gerontogenes and assessing environmental, nutritional or therapeutic impacts on the aging process. Recently, methylation markers were shown to allow estimation of biological age based on age-dependent somatic epigenetic alterations. However, DNA methylation is absent in some species such as Caenorhabditis elegans and it remains unclear whether and how the epigenetic clocks affect gene expression. Aging clocks based on transcriptomes have suffered from considerable variation in the data and relatively low accuracy. Here, we devised an approach that uses temporal scaling and binarization of C. elegans transcriptomes to define a gene set that predicts biological age with an accuracy that is close to the theoretical limit. Our model accurately predicts the longevity effects of diverse strains, treatments and conditions. The involved genes support a role of specific transcription factors as well as innate immunity and neuronal signaling in the regulation of the aging process. We show that this transcriptome clock can also be applied to human age prediction with high accuracy. This transcriptome aging clock could therefore find wide application in genetic, environmental and therapeutic interventions in the aging process.
This technical study describes all-atom modeling and simulation of a fully-glycosylated full- length SARS-CoV-2 spike (S) protein in a viral membrane. First, starting from PDB:6VSB and 6VXX, full-length S protein structures were modeled using template-based modeling, de-novo protein structure prediction, and loop modeling techniques in GALAXY modeling suite. Then, using the recently-determined most occupied glycoforms, 22 N-glycans and 1 O-glycan of each monomer were modeled using Glycan Reader & Modeler in CHARMM-GUI. These fully- glycosylated full-length S protein model structures were assessed and further refined against the low-resolution data in their respective experimental maps using ISOLDE. We then used CHARMM-GUI Membrane Builder to place the S proteins in a viral membrane and performed all-atom molecular dynamics simulations. All structures are available in CHARMM-GUI COVID-19 Archive (http://www.charmm-gui.org/docs/archive/covid19), so researchers can use these models to carry out innovative and novel modeling and simulation research for the prevention and treatment of COVID-19.