University of Texas at Austin

About: University of Texas at Austin is a education organization based out in Austin, Texas, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 94352 authors who have published 206297 publications receiving 9070052 citations. The organization is also known as: UT-Austin & UT Austin.

The Apache Point Observatory Galactic Evolution Experiment (APOGEE)

Abstract: National Science Foundation [AST-1109178, AST-1616636]; Gemini Observatory; Spanish Ministry of Economy and Competitiveness [AYA-2011-27754]; NASA [NNX12AE17G]; Hungarian Academy of Sciences; Hungarian NKFI of the Hungarian National Research, Development and Innovation Office [K-119517]; Alfred P. Sloan Foundation; National Science Foundation; U.S. Department of Energy Office of Science

Absolute protein expression profiling estimates the relative contributions of transcriptional and translational regulation

Abstract: We report a method for large-scale absolute protein expression measurements (APEX) and apply it to estimate the relative contributions of transcriptional- and translational-level gene regulation in the yeast and Escherichia coli proteomes. APEX relies upon correcting each protein's mass spectrometry sampling depth (observed peptide count) by learned probabilities for identifying the peptides. APEX abundances agree with measurements from controls, western blotting, flow cytometry and two-dimensional gels, as well as known correlations with mRNA abundances and codon bias, providing absolute protein concentrations across approximately three to four orders of magnitude. Using APEX, we demonstrate that 73% of the variance in yeast protein abundance (47% in E. coli) is explained by mRNA abundance, with the number of proteins per mRNA log-normally distributed about approximately 5,600 ( approximately 540 in E. coli) protein molecules/mRNA. Therefore, levels of both eukaryotic and prokaryotic proteins are set per mRNA molecule and independently of overall protein concentration, with >70% of yeast gene expression regulation occurring through mRNA-directed mechanisms.

Galaxy luminosity functions to z∼ 1 from DEEP2 and COMBO-17: Implications for red galaxy formation

Abstract: The DEEP2 and COMBO-17 surveys are compared to study luminosity functions of red and blue galaxies to z ~ 1. The two surveys have different methods and sensitivities, but nevertheless results agree. After z ~ 1, M has dimmed by 1.2-1.3 mag for all colors of galaxies, * for blue galaxies has hardly changed, and * for red galaxies has at least doubled (our formal value is ~0.5 dex). Luminosity density jB has fallen by 0.6 dex for blue galaxies but has remained nearly constant for red galaxies. These results imply that the number and total stellar mass of blue galaxies have been substantially constant since z ~ 1, whereas those of red galaxies (near L*) have been significantly rising. To explain the new red galaxies, a ``mixed'' scenario is proposed in which star formation in blue cloud galaxies is quenched, causing them to migrate to the red sequence, where they merge further in a small number of stellar mergers. This mixed scenario matches the local boxy-disky transition for nearby ellipticals, as well as red sequence stellar population scaling laws such as the color-magnitude and Mg-? relations (which are explained as fossil relics from blue progenitors). Blue galaxies enter the red sequence via different quenching modes, each of which peaks at a different characteristic mass and time. The red sequence therefore likely builds up in different ways at different times and masses, and the concept of a single process that is ``downsizing'' (or upsizing) probably does not apply. Our claim in this paper of a rise in the number of red galaxies applies to galaxies near L*. Accurate counts of brighter galaxies on the steep part of the Schechter function require more accurate photometry than is currently available.

Neural mechanisms of the cognitive model of depression

Abstract: In the 40 years since Aaron Beck first proposed his cognitive model of depression, the elements of this model — biased attention, biased processing, biased thoughts and rumination, biased memory, and dysfunctional attitudes and schemas — have been consistently linked with the onset and maintenance of depression. Although numerous studies have examined the neural mechanisms that underlie the cognitive aspects of depression, their findings have not been integrated with Beck's cognitive model. In this Review, we identify the functional and structural neurobiological architecture of Beck's cognitive model of depression. Although the mechanisms underlying each element of the model differ, in general the negative cognitive biases in depression are facilitated by increased influence from subcortical emotion processing regions combined with attenuated top-down cognitive control.

Site-specific glycan analysis of the SARS-CoV-2 spike.

Abstract: The emergence of the betacoronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), represents a considerable threat to global human health. Vaccine development is focused on the principal target of the humoral immune response, the spike (S) glycoprotein, which mediates cell entry and membrane fusion. The SARS-CoV-2 S gene encodes 22 N-linked glycan sequons per protomer, which likely play a role in protein folding and immune evasion. Here, using a site-specific mass spectrometric approach, we reveal the glycan structures on a recombinant SARS-CoV-2 S immunogen. This analysis enables mapping of the glycan-processing states across the trimeric viral spike. We show how SARS-CoV-2 S glycans differ from typical host glycan processing, which may have implications in viral pathobiology and vaccine design.