The Biology of Climate Change: The effects of changing climate on migrating and over-wintering species at a high-elevation field station

Students engage with long-term environmental and phenology data sets (spanning over 40 years) collected at the Rocky Mountain Biological Laboratory, a high-elevation field station in Colorado, to explore the effects of climate change on the phenology of migrating and hibernating species. After becoming familiar with the geographic context, people involved with the data collection, and organisms studied through background readings and videos, students explore the raw data set in Excel or using an interactive data visualization tool. In small groups, students reproduce figures and regressions from Inouye et al. (2000) based on those data, then expand their analyses with data collected during the subsequent decade. By comparing analyses that encompass different time spans, students evaluate the original interpretations from Inouye et al. (2000), explain possible discrepancies, and generate predictions for future patterns. Finally, students build upon their initial analyses by developing and testing hypotheses about patterns found in other organisms in the data set, and combine these to discuss the ecological consequences of shifting plant and animal phenology in group presentations

Cyberinfrastructure resources enabling creation of the loblolly pine reference transcriptome

This paper was presented at XSEDE 15 conference.Today's genomics technologies generate more sequence data than ever before possible, and at substantially lower costs, serving researchers across biological disciplines in transformative ways. Building transcriptome assemblies from RNA sequencing reads is one application of next-generation sequencing (NGS) that has held a central role in biological discovery in both model and non- model organisms, with and without whole genome sequence references. A major limitation in effective building of transcriptome references is no longer the sequencing data generation itself, but the computing infrastructure and expertise needed to assemble, analyze and manage the data. Here we describe a currently available resource dedicated to achieving such goals, and its use for extensive RNA assembly of up to 1.3 billion reads representing the massive transcriptome of loblolly pine, using four major assembly software installations. The Mason cluster, an XSEDE second tier resource at Indiana University, provides the necessary fast CPU cycles, large memory, and high I/O throughput for conducting large-scale genomics research. The National Center for Genome Analysis Support, or NCGAS, provides technical support in using HPC systems, bioinformatic support for determining the appropriate method to analyze a given dataset, and practical assistance in running computations. We demonstrate that a sufficient supercomputing resource and good workflow design are elements that are essential to large eukaryotic genomics and transcriptomics projects such as the complex transcriptome of loblolly pine, gene expression data that inform annotation and functional interpretation of the largest genome sequence reference to date.This work was supported in part by USDA NIFA grant 2011- 67009-30030, PineRefSeq, led by the University of California, Davis, and NCGAS funded by NSF under award No. 1062432

Assessing Differences between Early and Later Adopters of Accountable Care Organizations Using Taxonomic Analysis

Objective. To compare early and later adopters of the accountable care organization (ACO) model, using the taxonomy of larger, integrated system; smaller, physician-led; and hybrid ACOs. Data sources. The National Survey of ACOs, Waves 1 and 2. Studydesign. Clusteranalysisusingthetwo-stepclusteringapproach,validatedusing discriminant analysis. Wave 2 data analyzed separately to assess differences from Wave 1 and then data pooled across waves. Findings. Compared to early ACOs, later adopter ACOs included a greater breadth of provider group types and a greater proportion self-reported as integrated delivery systems. When data from the two time periods were combined, a three-cluster solution similar to the original cluster solution emerged. Of the 251 ACOs, 31.1 percent were larger, integrated system ACOs; 45.0 percent were smaller physician-led ACOs; and 23.9 percent were hybrid ACOs—compared to 40.1 percent, 34.0 percent, and 25.9 percent from Wave 1 clusters, respectively. Conclusions. While there are some differences between ACOs formed prior to August 2012 and those formed in the following year, the three-cluster taxonomy appears to best describe the types of ACOs in existence as of July 2013. The updated taxonomy can be used by researchers, policy makers, and health care organizations to support evaluation and continued development of ACOs

Variance as a predictor of health outcomes: Subject-level trajectories and variability of sex hormones to predict body fat changes in peri- and post-menopausal women

Longitudinal biomarker data and cross-sectional outcomes are routinely collected in modern epidemiology studies, often with the goal of informing tailored early intervention decisions. For example, hormones such as estradiol and follicle-stimulating hormone may predict changes in womens' health during the midlife. Most existing methods focus on constructing predictors from mean marker trajectories. However, subject-level biomarker variability may also provide critical information about disease risks and health outcomes. In this paper, we develop a joint model that estimates subject-level means and variances of longitudinal biomarkers to predict a cross-sectional health outcome. Simulations demonstrate excellent recovery of true model parameters. The proposed method provides less biased and more efficient estimates, relative to alternative approaches that either ignore subject-level differences in variances or perform two-stage estimation where estimated marker variances are treated as observed. Analyses of women's health data reveal larger variability of E2 or larger variability of FSH were associated with higher levels of fat mass change and higher levels of lean mass change across the menopausal transition

A New Population of High-z, Dusty Lyα Emitters and Blobs Discovered by WISE: Feedback Caught in the Act?

By combining data from the NASA Wide-field Infrared Survey Explorer (WISE) mission with optical spectroscopy from the W. M. Keck telescope, we discover a mid-IR color criterion that yields a 78% success rate in identifying rare, typically radio-quiet, 1.6 ≾ z ≾ 4.6 dusty Lyα emitters (LAEs). Of these, at least 37% have emission extended on scales of 30-100 kpc and are considered Lyα "blobs" (LABs). The objects have a surface density of only ~0.1 deg^(–2), making them rare enough that they have been largely missed in deep, small area surveys. We measured spectroscopic redshifts for 92 of these galaxies, and find that the LAEs (LABs) have a median redshift of 2.3 (2.5). The WISE photometry coupled with data from Herschel (Herschel is an ESA space observatory with science instruments provided by European-led Principal Investigator consortia and with important participation from NASA) reveals that these galaxies are in the Hyper Luminous IR galaxy regime (L IR ≳ 10^(13)-10^(14) L_☉) and have warm colors. They are typically more luminous and warmer than other dusty, z ~ 2 populations such as submillimeter-selected galaxies and dust-obscured galaxies. These traits are commonly associated with the dust being illuminated by intense active galactic nucleus activity. We hypothesize that the combination of spatially extended Lyα, large amounts of warm IR-luminous dust, and rarity (implying a short-lived phase) can be explained if the galaxies are undergoing brief, intense "feedback" transforming them from an extreme dusty starburst/QSO into a mature galaxy

vFitness: a web-based computing tool for improving estimation of in vitro HIV-1 fitness experiments

<p>Abstract</p> <p>Background</p> <p>The replication rate (or fitness) between viral variants has been investigated <it>in vivo </it>and <it>in vitro </it>for human immunodeficiency virus (HIV). HIV fitness plays an important role in the development and persistence of drug resistance. The accurate estimation of viral fitness relies on complicated computations based on statistical methods. This calls for tools that are easy to access and intuitive to use for various experiments of viral fitness.</p> <p>Results</p> <p>Based on a mathematical model and several statistical methods (least-squares approach and measurement error models), a Web-based computing tool has been developed for improving estimation of virus fitness in growth competition assays of human immunodeficiency virus type 1 (HIV-1).</p> <p>Conclusions</p> <p>Unlike the two-point calculation used in previous studies, the estimation here uses linear regression methods with all observed data in the competition experiment to more accurately estimate relative viral fitness parameters. The dilution factor is introduced for making the computational tool more flexible to accommodate various experimental conditions. This Web-based tool is implemented in C# language with Microsoft ASP.NET, and is publicly available on the Web at <url>http://bis.urmc.rochester.edu/vFitness/</url>.</p

Spitzer Photometry of WISE-Selected Brown Dwarf and Hyper-Luminous Infrared Galaxy Candidates

We present Spitzer 3.6 and 4.5 $\mu$m photometry and positions for a sample of 1510 brown dwarf candidates identified by the WISE all-sky survey. Of these, 166 have been spectroscopically classified as objects with spectral types M(1), L(7), T(146), and Y(12); Sixteen other objects are non-(sub)stellar in nature. The remainder are most likely distant L and T dwarfs lacking spectroscopic verification, other Y dwarf candidates still awaiting follow-up, and assorted other objects whose Spitzer photometry reveals them to be background sources. We present a catalog of Spitzer photometry for all astrophysical sources identified in these fields and use this catalog to identify 7 fainter (4.5 $\mu$m $\sim$ 17.0 mag) brown dwarf candidates, which are possibly wide-field companions to the original WISE sources. To test this hypothesis, we use a sample of 919 Spitzer observations around WISE-selected high-redshift hyper-luminous infrared galaxy (HyLIRG) candidates. For this control sample we find another 6 brown dwarf candidates, suggesting that the 7 companion candidates are not physically associated. In fact, only one of these 7 Spitzer brown dwarf candidates has a photometric distance estimate consistent with being a companion to the WISE brown dwarf candidate. Other than this there is no evidence for any widely separated ($>$ 20 AU) ultra-cool binaries. As an adjunct to this paper, we make available a source catalog of $\sim$ 7.33 $\times 10^5$ objects detected in all of these Spitzer follow-up fields for use by the astronomical community. The complete catalog includes the Spitzer 3.6 and 4.5 $\mu$m photometry, along with positionally matched $B$ and $R$ photometry from USNO-B; $J$, $H$, and $K_s$ photometry from 2MASS; and $W1$, $W2$, $W3$, and $W4$ photometry from the WISE all-sky catalog

Building Capacity for Cancer Research in the Era of COVID-19: Implementation and Results From an International Virtual Clinical Research Training Program in Zambia

DOI: 10.1200/GO.21.00372 JCO Global Oncology no. 8 (2022) Published online May 20, 2022. PMID: 35594499https://openworks.mdanderson.org/mozart/1024/thumbnail.jp

A New Population of High Redshift, Dusty Lyman-Alpha Emitters and Blobs Discovered by WISE

We report a new technique to select 1.6<z<4.6 dusty Lyman-alpha emitters (LAEs), over a third of which are `blobs' (LABs) with emission extended on scales of 30-100kpc. Combining data from the NASA Wide-field Infrared Survey Explorer (WISE) mission with optical spectroscopy from the W.M. Keck telescope, we present a color criteria that yields a 78% success rate in identifying rare, dusty LAEs of which at least 37% are LABs. The objects have a surface density of only ~0.1 per square degree, making them rare enough that they have been largely missed in narrow surveys. We measured spectroscopic redshifts for 92 of these WISE-selected, typically radio-quiet galaxies and find that the LAEs (LABs) have a median redshift of 2.3 (2.5). The WISE photometry coupled with data from Herschel reveals that these galaxies have extreme far-infrared luminosities (L_IR>10^{13-14}L_sun) and warm colors, typically larger than submillimeter-selected galaxies (SMGs) and dust-obscured galaxies (DOGs). These traits are commonly associated with the dust being energized by intense AGN activity. We hypothesize that the combination of spatially extended Lyman-alpha, large amounts of warm IR-luminous dust, and rarity (implying a short-lived phase) can be explained if the galaxies are undergoing strong `feedback' transforming them from an extreme dusty starburst to a QSO.Comment: Submitted to ApJ Letters, 6 pages, 4 figures. Comments welcom

Circulating Uromodulin inhibits systemic oxidative stress by inactivating the TRPM2 channel

High serum concentrations of kidney-derived protein uromodulin (Tamm-Horsfall protein or THP) have recently been shown to be independently associated with low mortality in both older adults and cardiac patients, but the underlying mechanism remains unclear. Here, we show that THP inhibits the generation of reactive oxygen species (ROS) both in the kidney and systemically. Consistent with this experimental data, the concentration of circulating THP in patients with surgery-induced acute kidney injury (AKI) correlated with systemic oxidative damage. THP in the serum dropped after AKI, and was associated with an increase in systemic ROS. The increase in oxidant injury correlated with post-surgical mortality and need for dialysis. Mechanistically, THP inhibited the activation of the transient receptor potential cation channel, subfamily M, member 2 (TRPM2) channel. Furthermore, inhibition of TRPM2 in vivo in a mouse model, mitigated the systemic increase in ROS during AKI and THP deficiency. Our results suggest that THP is a key regulator of systemic oxidative stress by suppressing TRPM2 activity and our findings might help to explain how circulating THP deficiency is linked with poor outcomes and increased mortality