969 research outputs found
S4HARA: System for HIV/AIDS resource allocation
This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens
Genetic Interactions Affect Lung Function in Patients with Systemic Sclerosis.
Scleroderma, or systemic sclerosis (SSc), is an autoimmune disease characterized by progressive fibrosis of the skin and internal organs. The most common cause of death in people with SSc is lung disease, but the pathogenesis of lung disease in SSc is insufficiently understood to devise specific treatment strategies. Developing targeted treatments requires not only the identification of molecular processes involved in SSc-associated lung disease, but also understanding of how these processes interact to drive pathology. One potentially powerful approach is to identify alleles that interact genetically to influence lung outcomes in patients with SSc. Analysis of interactions, rather than individual allele effects, has the potential to delineate molecular interactions that are important in SSc-related lung pathology. However, detecting genetic interactions, or epistasis, in human cohorts is challenging. Large numbers of variants with low minor allele frequencies, paired with heterogeneous disease presentation, reduce power to detect epistasis. Here we present an analysis that increases power to detect epistasis in human genome-wide association studies (GWAS). We tested for genetic interactions influencing lung function and autoantibody status in a cohort of 416 SSc patients. Using Matrix Epistasis to filter SNPs followed by the Combined Analysis of Pleiotropy and Epistasis (CAPE), we identified a network of interacting alleles influencing lung function in patients with SSc. In particular, we identified a three-gene network comprising WNT5A, RBMS3, and MSI2, which in combination influenced multiple pulmonary pathology measures. The associations of these genes with lung outcomes in SSc are novel and high-confidence. Furthermore, gene coexpression analysis suggested that the interactions we identified are tissue-specific, thus differentiating SSc-related pathogenic processes in lung from those in skin
Geometry of Deformations of Relativistic Membranes
A kinematical description of infinitesimal deformations of the worldsheet
spanned in spacetime by a relativistic membrane is presented. This provides a
framework for obtaining both the classical equations of motion and the
equations describing infinitesimal deformations about solutions of these
equations when the action describing the dynamics of this membrane is
constructed using {\it any} local geometrical worldsheet scalars. As examples,
we consider a Nambu membrane, and an action quadratic in the extrinsic
curvature of the worldsheet.Comment: 20 pages, Plain Tex, sign errors corrected, many new references
added. To appear in Physical Review
The dynamics of curved gravitating walls
We examine the dynamics of a self-gravitating domain wall using the model as a specific example. We find that the Nambu motion of the wall
is quite generic and dominates the wall motion even in the presence of gravity.
We calculate the corrections to this leading order motion, and estimate the
effect of the inclusion of gravity on the dynamics of the wall. We then treat
the case of a spherical gravitating thick wall as a particular example, solving
the field equations and calculating the corrections to the Nambu motion
analytically for this specific case. We find that the presence of gravity
retards collapse in this case.Comment: 19 pages revtex, 3 figures, references added, equations correcte
WHAT TASKS TO AUTOMATE? AN INVESTIGATION OF WHAT TASKS MAKE SENSE TO AUTOMATE FOR FUTURE AVIATION PLATFORMS
The Army is developing a new generation of aircraft called Future Vertical Lift (FVL). These aircraft will integrate new technologies that change Army Aviation’s machinery, methods, and aircrew domains. Key to this effort is the development of automation to reduce pilot cognitive workload and prevent cognitive overload.
The purpose of this research was to develop an understanding of the factors that influence pilot cognitive workload and to provide insight into what tasks make sense to automate for FVL. Researchers used a mixed methods approach, relying on scholarly literature and semi-structured interviews to elicit cognitive workload data from Army rotary-wing pilots. Researchers used the data from a simple and a complex MEDEVAC flight scenario to develop an influence diagram that models pilot cognitive workload based on influencing factors and subfactors.
At a high level, the data indicate that pilot task demand and environmental factors have the most influence on cognitive workload during complex missions in challenging conditions. At a low level, the data indicate that light factors, intra-flight coordination, and task complexity are most influential on cognitive workload. The results suggest that tasks impacting these factors should be considered for automation to prevent pilot cognitive overload in FVL.DEVCOM AvMCCaptain, United States ArmyMajor, United States ArmyCaptain, United States ArmyMajor, United States ArmyApproved for public release. Distribution is unlimited
Differential splicing of neuronal genes in a Trem2*R47H mouse model mimics alterations associated with Alzheimer\u27s disease.
BACKGROUND: Molecular characterization of late-onset Alzheimer\u27s disease (LOAD), the leading cause of age-related dementia, has revealed transcripts, proteins, and pathway alterations associated with disease. Assessing these postmortem signatures of LOAD in experimental model systems can further elucidate their relevance to disease origins and progression. Model organisms engineered with human genetic factors further link these signatures to disease-associated variants, especially when studies are designed to leverage homology across species. Here we assess differential gene splicing patterns in aging mouse models carrying humanized APOE4 and/or the Trem2*R47H variant on a C57BL/6J background. We performed a differential expression of gene (DEG) and differential splicing analyses on whole brain transcriptomes at multiple ages. To better understand the difference between differentially expressed and differentially spliced genes, we evaluated enrichment of KEGG pathways and cell-type specific gene signatures of the adult brain from each alteration type. To determine LOAD relevance, we compared differential splicing results from mouse models with multiple human AD splicing studies.
RESULTS: We found that differentially expressed genes in Trem2*R47H mice were significantly enriched in multiple AD-related pathways, including immune response, osteoclast differentiation, and metabolism, whereas differentially spliced genes were enriched for neuronal related functions, including GABAergic synapse and glutamatergic synapse. These results were reinforced by the enrichment of microglial genes in DEGs and neuronal genes in differentially spliced genes in Trem2*R47H mice. We observed significant overlap between differentially spliced genes in Trem2*R47H mice and brains from human AD subjects. These effects were absent in APOE4 mice and suppressed in APOE4.Trem2*R47H double mutant mice relative to Trem2*R47H mice.
CONCLUSIONS: The cross-species observation that alternative splicing observed in LOAD are present in Trem2*R47H mouse models suggests a novel link between this candidate risk gene and molecular signatures of LOAD in neurons and demonstrates how deep molecular analysis of new genetic models links molecular disease outcomes to a human candidate gene
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