1,143 research outputs found
Fabricación y diseño de estructuras parrilla
Grid structures have been in use for decades. Many were made of reinforced concrete or metals. Grids made of composite materials offer high stiffness and strength at low mass that are competitive with traditional composite laminates.
Commonly available manufacturing processes such as filament winding, pultrusion and tubes made from female molds are used to produce composite grids. Cost effective grids can then be made in large sizes and quantities. Grids derive their global stiffness and strength from their ribs. They are fundamentally different from laminates which derive theirs from plies. The models for stiffness and failure modes can be viewed as simple extensions of laminated plate theory. It is hoped that grids will emerge as one of the common structural forms along with solid, stiffened and sandwich panels. Potential applications of composite grids are also mentioned.Las estructuras parrilla se han usado durante décadas. Muchas de ellas han sido fabricadas con hormigón armado o con metales. Las estructuras parrilla de materiales compuestos presentan rigideces y resistencias superiores, con menor peso en relación a laminados tradicionales de materiales compuestos.
Para la fahricacion.de este tipo de estructuras, se utilizan procesos convencionales como son enrollamiento continuo, pultrusión y perfiles fabricados a partir de moldes hembra. Las estructuras parrilla presentan una gran rigidez y resistencia debido a los refuerzos (largueros y travesaños). Los modelos utilizados para estudiar la rigidez y los modos de rotura, se derivan de la teorÃa de placas laminadas. Las estructuras parrilla de materiales compuestos tienen un prometedor futuro, tanto solas como reforzadas con un núcleo, como constituyentes de una estructura sándwich
Increasing fMRI Sampling Rate Improves Granger Causality Estimates
Estimation of causal interactions between brain areas is necessary for elucidating large-scale functional brain networks underlying behavior and cognition. Granger causality analysis of time series data can quantitatively estimate directional information flow between brain regions. Here, we show that such estimates are significantly improved when the temporal sampling rate of functional magnetic resonance imaging (fMRI) is increased 20-fold. Specifically, healthy volunteers performed a simple visuomotor task during blood oxygenation level dependent (BOLD) contrast based whole-head inverse imaging (InI). Granger causality analysis based on raw InI BOLD data sampled at 100-ms resolution detected the expected causal relations, whereas when the data were downsampled to the temporal resolution of 2 s typically used in echo-planar fMRI, the causality could not be detected. An additional control analysis, in which we SINC interpolated additional data points to the downsampled time series at 0.1-s intervals, confirmed that the improvements achieved with the real InI data were not explainable by the increased time-series length alone. We therefore conclude that the high-temporal resolution of InI improves the Granger causality connectivity analysis of the human brain
Heterozygote advantage at HLA class I and II loci and reduced risk of colorectal cancer
Objective: Reduced diversity at Human Leukocyte Antigen (HLA) loci may adversely affect the host's ability to recognize tumor neoantigens and subsequently increase disease burden. We hypothesized that increased heterozygosity at HLA loci is associated with a reduced risk of developing colorectal cancer (CRC). Methods: We imputed HLA class I and II four-digit alleles using genotype data from a population-based study of 5,406 cases and 4,635 controls from the Molecular Epidemiology of Colorectal Cancer Study (MECC). Heterozygosity at each HLA locus and the number of heterozygous genotypes at HLA class -I (A, B, and C) and HLA class -II loci (DQB1, DRB1, and DPB1) were quantified. Logistic regression analysis was used to estimate the risk of CRC associated with HLA heterozygosity. Individuals with homozygous genotypes for all loci served as the reference category, and the analyses were adjusted for sex, age, genotyping platform, and ancestry. Further, we investigated associations between HLA diversity and tumor-associated T cell repertoire features, as measured by tumor infiltrating lymphocytes (TILs; N=2,839) and immunosequencing (N=2,357). Results: Individuals with all heterozygous genotypes at all three class I genes had a reduced odds of CRC (OR: 0.74; 95% CI: 0.56-0.97, p= 0.031). A similar association was observed for class II loci, with an OR of 0.75 (95% CI: 0.60-0.95, p= 0.016). For class-I and class-II combined, individuals with all heterozygous genotypes had significantly lower odds of developing CRC (OR: 0.66, 95% CI: 0.49-0.87, p= 0.004) than those with 0 or one heterozygous genotype. HLA class I and/or II diversity was associated with higher T cell receptor (TCR) abundance and lower TCR clonality, but results were not statistically significant. Conclusion: Our findings support a heterozygote advantage for the HLA class-I and -II loci, indicating an important role for HLA genetic variability in the etiology of CRC
Effective cerebral connectivity during silent speech reading revealed by functional magnetic resonance imaging
Science Impacts of the SPHEREx All-Sky Optical to Near-Infrared Spectral Survey: Report of a Community Workshop Examining Extragalactic, Galactic, Stellar and Planetary Science
SPHEREx is a proposed SMEX mission selected for Phase A. SPHEREx will carry
out the first all-sky spectral survey and provide for every 6.2" pixel a
spectra between 0.75 and 4.18 m [with R41.4] and 4.18 and 5.00
m [with R135]. The SPHEREx team has proposed three specific science
investigations to be carried out with this unique data set: cosmic inflation,
interstellar and circumstellar ices, and the extra-galactic background light.
It is readily apparent, however, that many other questions in astrophysics and
planetary sciences could be addressed with the SPHEREx data. The SPHEREx team
convened a community workshop in February 2016, with the intent of enlisting
the aid of a larger group of scientists in defining these questions. This paper
summarizes the rich and varied menu of investigations that was laid out. It
includes studies of the composition of main belt and Trojan/Greek asteroids;
mapping the zodiacal light with unprecedented spatial and spectral resolution;
identifying and studying very low-metallicity stars; improving stellar
parameters in order to better characterize transiting exoplanets; studying
aliphatic and aromatic carbon-bearing molecules in the interstellar medium;
mapping star formation rates in nearby galaxies; determining the redshift of
clusters of galaxies; identifying high redshift quasars over the full sky; and
providing a NIR spectrum for most eROSITA X-ray sources. All of these
investigations, and others not listed here, can be carried out with the nominal
all-sky spectra to be produced by SPHEREx. In addition, the workshop defined
enhanced data products and user tools which would facilitate some of these
scientific studies. Finally, the workshop noted the high degrees of synergy
between SPHEREx and a number of other current or forthcoming programs,
including JWST, WFIRST, Euclid, GAIA, K2/Kepler, TESS, eROSITA and LSST.Comment: Report of the First SPHEREx Community Workshop,
http://spherex.caltech.edu/Workshop.html , 84 pages, 28 figure
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Genetically Determined Plasma Lipid Levels and Risk of Diabetic Retinopathy: A Mendelian Randomization Study.
Results from observational studies examining dyslipidemia as a risk factor for diabetic retinopathy (DR) have been inconsistent. We evaluated the causal relationship between plasma lipids and DR using a Mendelian randomization approach. We pooled genome-wide association studies summary statistics from 18 studies for two DR phenotypes: any DR (N = 2,969 case and 4,096 control subjects) and severe DR (N = 1,277 case and 3,980 control subjects). Previously identified lipid-associated single nucleotide polymorphisms served as instrumental variables. Meta-analysis to combine the Mendelian randomization estimates from different cohorts was conducted. There was no statistically significant change in odds ratios of having any DR or severe DR for any of the lipid fractions in the primary analysis that used single nucleotide polymorphisms that did not have a pleiotropic effect on another lipid fraction. Similarly, there was no significant association in the Caucasian and Chinese subgroup analyses. This study did not show evidence of a causal role of the four lipid fractions on DR. However, the study had limited power to detect odds ratios less than 1.23 per SD in genetically induced increase in plasma lipid levels, thus we cannot exclude that causal relationships with more modest effect sizes exist
Predicting residue-wise contact orders in proteins by support vector regression
BACKGROUND: The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. RESULTS: We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. CONCLUSION: The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences
Plcg2M28L Interacts With High Fat/High Sugar Diet to Accelerate Alzheimer\u27s Disease-Relevant Phenotypes in Mice.
Obesity is recognized as a significant risk factor for Alzheimer\u27s disease (AD). Studies have supported the notion that obesity accelerates AD-related pathophysiology in mouse models of AD. The majority of studies, to date, have focused on the use of early-onset AD models. Here, we evaluate the impact of genetic risk factors on late-onset AD (LOAD) in mice fed with a high fat/high sugar diet (HFD). We focused on three mouse models created through the IU/JAX/PITT MODEL-AD Center. These included a combined risk model wit
Clinically Actionable Hypercholesterolemia and Hypertriglyceridemia in Children with Nonalcoholic Fatty Liver Disease
OBJECTIVE:
To determine the percentage of children with nonalcoholic fatty liver disease (NAFLD) in whom intervention for low-density lipoprotein cholesterol or triglycerides was indicated based on National Heart, Lung, and Blood Institute guidelines.
STUDY DESIGN:
This multicenter, longitudinal cohort study included children with NAFLD enrolled in the National Institute of Diabetes and Digestive and Kidney Diseases Nonalcoholic Steatohepatitis Clinical Research Network. Fasting lipid profiles were obtained at diagnosis. Standardized dietary recommendations were provided. After 1 year, lipid profiles were repeated and interpreted according to National Heart, Lung, and Blood Institute Expert Panel on Integrated Guidelines for Cardiovascular Health and Risk Reduction. Main outcomes were meeting criteria for clinically actionable dyslipidemia at baseline, and either achieving lipid goal at follow-up or meeting criteria for ongoing intervention.
RESULTS:
There were 585 participants, with a mean age of 12.8 years. The prevalence of children warranting intervention for low-density lipoprotein cholesterol at baseline was 14%. After 1 year of recommended dietary changes, 51% achieved goal low-density lipoprotein cholesterol, 27% qualified for enhanced dietary and lifestyle modifications, and 22% met criteria for pharmacologic intervention. Elevated triglycerides were more prevalent, with 51% meeting criteria for intervention. At 1 year, 25% achieved goal triglycerides with diet and lifestyle changes, 38% met criteria for advanced dietary modifications, and 37% qualified for antihyperlipidemic medications.
CONCLUSIONS:
More than one-half of children with NAFLD met intervention thresholds for dyslipidemia. Based on the burden of clinically relevant dyslipidemia, lipid screening in children with NAFLD is warranted. Clinicians caring for children with NAFLD should be familiar with lipid management
Description of the data from the Collaborative Study on the Genetics of Alcoholism (COGA) and single-nucleotide polymorphism genotyping for Genetic Analysis Workshop 14
The data provided to the Genetic Analysis Workshop 14 (GAW 14) was the result of a collaboration among several different groups, catalyzed by Elizabeth Pugh from The Center for Inherited Disease Research (CIDR) and the organizers of GAW 14, Jean MacCluer and Laura Almasy. The DNA, phenotypic characterization, and microsatellite genomic survey were provided by the Collaborative Study on the Genetics of Alcoholism (COGA), a nine-site national collaboration funded by the National Institute of Alcohol and Alcoholism (NIAAA) and the National Institute of Drug Abuse (NIDA) with the overarching goal of identifying and characterizing genes that affect the susceptibility to develop alcohol dependence and related phenotypes. CIDR, Affymetrix, and Illumina provided single-nucleotide polymorphism genotyping of a large subset of the COGA subjects. This article briefly describes the dataset that was provided
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