Melanism as a potential thermal benefit in eastern fox squirrels (Sciurus niger)

Melanistic fox squirrels (Sciurus niger) have expanded westward and increased in frequency in the Omaha, Nebraska, and Council Bluffs, Iowa, metropolitan areas. The selective advantage of melanism is currently unknown, but thermal advantages have been hypothesized, especially in winter. No difference in metabolic response curves were measured between melanistic (black) and rufus (orange) fox squirrels. When exposed to sunny skies, both melanistic and rufus squirrels had higher surface (skin and fur) temperature as ambient temperatures increased. Melanistic squirrel surface temperatures did not differ when squirrels were exposed to sunny or cloudy skies. However, rufus individuals showed significantly lower increases in surface temperatures when under cloudy skies. During fall months, rufus individuals were about 1.5 times more active throughout the day than melanistic individuals. However, in winter, melanistic fox squirrels were approximately 30% more active in the mornings (before 13:00) compared to rufus squirrels. Pre-winter body condition was higher in melanistic (25.5 ± 1.8 g/cm) compared to rufus (20.30 ± 3.6 g/cm) fox squirrels; however, there were no significant differences between melanistic (22.8 ± 1.4 g/cm) and rufus (23.9 ± 0.8 g/cm) fox squirrel post-winter body condition. The results of this study indicate that melanistic fox squirrels may have a slight winter thermal advantage over rufus fox squirrels by maintaining higher skin temperatures

A flexible distribution class for count data

The Poisson, geometric and Bernoulli distributions are special cases of a flexible count distribution, namely the Conway-Maxwell-Poisson (CMP) distribution – a two-parameter generalization of the Poisson distribution that can accommodate data over- or under-dispersion. This work further generalizes the ideas of the CMP distribution by considering sums of CMP random variables to establish a flexible class of distributions that encompasses the Poisson, negative binomial, and binomial distributions as special cases. This sum-of-Conway-Maxwell-Poissons (sCMP) class captures the CMP and its special cases, as well as the classical negative binomial and binomial distributions. Through simulated and real data examples, we demonstrate this model’s flexibility, encompassing several classical distributions as well as other count data distributions containing significant data dispersion

Erratum to: Melanism as a potential thermal benefit in eastern fox squirrels (Sciurus niger)

Melanistic fox squirrels (Sciurus niger) have expanded westward and increased in frequency in the Omaha, Nebraska, and Council Bluffs, Iowa, metropolitan areas. The selective advantage of melanism is currently unknown, but thermal advantages have been hypothesized, especially in winter. No difference in metabolic response curves were measured between melanistic (black) and rufus (orange) fox squirrels. When exposed to sunny skies, both melanistic and rufus squirrels had higher surface (skin and fur) temperature as ambient temperatures increased. Melanistic squirrel surface temperatures did not differ when squirrels were exposed to sunny or cloudy skies. However, rufus individuals showed significantly lower increases in surface temperatures when under cloudy skies. During fall months, rufus individuals were about 1.5 times more active throughout the day than melanistic individuals. However, in winter, melanistic fox squirrels were approximately 30% more active in the mornings (before 13:00) compared to rufus squirrels. Pre-winter body condition was higher in melanistic (25.5 ± 1.8 g/cm) compared to rufus (20.30 ± 3.6 g/cm) fox squirrels; however, there were no significant differences between melanistic (22.8 ± 1.4 g/cm) and rufus (23.9 ± 0.8 g/cm) fox squirrel post-winter body condition. The results of this study indicate that melanistic fox squirrels may have a slight winter thermal advantage over rufus fox squirrels by maintaining higher skin temperatures

Kepler-445, Kepler-446 And The Occurrence Of Compact Multiples Orbiting Mid-M Dwarf Stars

We confirm and characterize the exoplanetary systems Kepler-445 and Kepler-446: two mid-M dwarf stars, each with multiple, small, short-period transiting planets. Kepler-445 is a metal-rich ([ Fe/H] = + 0.25 0.10) M4 dwarf with three transiting planets, and Kepler-446 is a metal-poor ([ Fe/H] = -0.30 0.10) M4 dwarf also with three transiting planets. Kepler-445c is similar toGJ 1214b: both in planetary radius and the properties of the host star. The Kepler-446 system is similar to the Kepler-42 system: both are metal-poor with large galactic space velocities and three short-period, likely rocky transiting planets that were initially assigned erroneously large planet-to-star radius ratios. We independently determined stellar parameters from spectroscopy and searched for and fitted the transit light curves for the planets, imposing a strict prior on stellar density in order to remove correlations between the fitted impact parameter and planet-to-star radius ratio for short-duration transits. Combining Kepler-445, Kepler-446, and Kepler-42, and isolating all mid-M dwarf stars observed by Kepler with the precision necessary to detect similar systems, we calculate that 21+ 7 -5 % of mid-M dwarf stars host compact multiples ( multiple planets with periods of less than 10 days) for a wide range of metallicities. We suggest that the inferred planet masses for these systems support highly efficient accretion of protoplanetary disk metals by mid-M dwarf protoplanets.NSF DGE1144152, AST-1005313NASA NAS5-26555NASA Office of Space Science NNX13AC07GAstronom

The gold standard: accurate stellar and planetary parameters for eight Kepler M dwarf systems enabled by parallaxes

We report parallaxes and proper motions from the Hawaii Infrared Parallax Program for eight nearby M dwarf stars with transiting exoplanets discovered by Kepler. We combine our directly measured distances with mass-luminosity and radius–luminosity relationships to significantly improve constraints on the host stars’ properties. Our astrometry enables the identification of wide stellar companions to the planet hosts. Within our limited sample, all the multi-transiting planet hosts (three of three) appear to be single stars, while nearly all (four of five) of the systems with a single detected planet have wide stellar companions. By applying strict priors on average stellar density from our updated radius and mass in our transit fitting analysis, we measure the eccentricity probability distributions for each transiting planet. Planets in single-star systems tend to have smaller eccentricities than those in binaries, although this difference is not significant in our small sample. In the case of Kepler-42bcd, where the eccentricities are known to be ≃0, we demonstrate that such systems can serve as powerful tests of M dwarf evolutionary models by working in L⋆ − ρ⋆ space. The transit-fit density for Kepler- 42bcd is inconsistent with model predictions at 2.1σ (22%), but matches more empirical estimates at 0.2σ (2%), consistent with earlier results showing model radii of M dwarfs are underinflated. Gaia will provide high-precision parallaxes for the entire Kepler M dwarf sample, and TESS will identify more planets transiting nearby, late-type stars, enabling significant improvements in our understanding of the eccentricity distribution of small planets and the parameters of late-type dwarfs.Support for Program number HST-HF2-51364.001-A was provided by NASA through a grant from the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Incorporated, under NASA contract NAS5-26555.Some of the data presented in this paper were obtained from the Mikulski Archive for Space Telescopes (MAST). STScI is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS5-26555. Support for MAST for non-HST data is provided by the NASA Office of Space Science via grant NNX09AF08G and by other grants and contracts. This paper includes data collected by the Kepler mission. Funding for the Kepler mission is provided by the NASA Science Mission directorate. The authors acknowledge the Texas Advanced Computing Center (TACC) at The University of Texas at Austin for providing HPC resources that have contributed to the research results reported within this paper. URL: http://www.tacc.utexas.edu. (HST-HF2-51364.001-A - NASA through Space Telescope Science Institute; NAS5-26555 - NASA; NNX09AF08G - NASA Office of Space Science; NASA Science Mission directorate

LUCAS: A highly accurate yet simple risk calculator that predicts survival of COVID-19 patients using rapid routine tests

Background There is an urgent need to develop a simplified risk tool that enables rapid triaging of SARS CoV-2 positive patients during hospital admission, which complements current practice. Many predictive tools developed to date are complex, rely on multiple blood results and past medical history, do not include chest X ray results and rely on Artificial Intelligence rather than simplified algorithms. Our aim was to develop a simplified risk-tool based on five parameters and CXR image data that predicts the 60-day survival of adult SARS CoV-2 positive patients at hospital admission. Methods We analysed the NCCID database of patient blood variables and CXR images from 19 hospitals across the UK contributed clinical data on SARS CoV-2 positive patients using multivariable logistic regression. The initial dataset was non-randomly split between development and internal validation dataset with 1434 and 310 SARS CoV-2 positive patients, respectively. External validation of final model conducted on 741 Accident and Emergency admissions with suspected SARS CoV-2 infection from a separate NHS Trust which was not part of the initial NCCID data set. Findings The LUCAS mortality score included five strongest predictors (lymphocyte count, urea, CRP, age, sex), which are available at any point of care with rapid turnaround of results. Our simple multivariable logistic model showed high discrimination for fatal outcome with the AUC-ROC in development cohort 0.765 (95% confidence interval (CI): 0.738 - 0.790), in internal validation cohort 0.744 (CI: 0.673 - 0.808), and in external validation cohort 0.752 (CI: 0.713 - 0.787). The discriminatory power of LUCAS mortality score was increased slightly when including the CXR image data (for normal versus abnormal): internal validation AUC-ROC 0.770 (CI: 0.695 - 0.836) and external validation AUC-ROC 0.791 (CI: 0.746 - 0.833). The discriminatory power of LUCAS and LUCAS + CXR performed in the upper quartile of pre-existing risk stratification scores with the added advantage of using only 5 predictors. Interpretation This simplified prognostic tool derived from objective parameters can be used to obtain valid predictions of mortality in patients within 60 days SARS CoV-2 RT-PCR results. This free-to-use simplified tool can be used to assist the triage of patients into low, moderate, high or very high risk of fatality and is available at https://mdscore.net/. What is already known on this topic? Clinical prediction models such as NEWS2 is currently used in practice as mortality risk assessment. In a rapid response to support COVID-19 patient assessment and resource management, published risk tools and models have been found to have a high risk of bias and therefore cannot be translated into clinical practice. What this study adds? A newly developed and validated risk tool (LUCAS) based on rapid and routine blood tests predicts the mortality of patients infected with SARS-CoV-2 virus. This prediction model has both high and robust predictive power and has been tested on an external set of patients and therefore can be used to effectively triage patients when resources are limited. In addition, LUCAS can be used with chest imaging information and NEWS2 score

Touchstone Stars: Highlights from the Cool Stars 18 Splinter Session

We present a summary of the splinter session on "touchstone stars" -- stars with directly measured parameters -- that was organized as part of the Cool Stars 18 conference. We discuss several methods to precisely determine cool star properties such as masses and radii from eclipsing binaries, and radii and effective temperatures from interferometry. We highlight recent results in identifying and measuring parameters for touchstone stars, and ongoing efforts to use touchstone stars to determine parameters for other stars. We conclude by comparing the results of touchstone stars with cool star models, noting some unusual patterns in the differences.Comment: Proceedings of the 18th Cambridge Workshop on Cool Stars, Stellar Systems, and the Sun, Eds G. van Belle & H. Harri

Proglacial icings as indicators of glacier thermal regime : ice thickness changes and icing occurrence in Svalbard

Proglacial icings (also known as naled or aufeis) are frequently observed in the forefields of polar glaciers. Their formation has been ascribed to the refreezing of upwelling groundwater that has originated from subglacial melt, and thus the presence of icings has been used as evidence of polythermal glacier regime. We provide an updated analysis of icing occurrence in Svalbard and test the utility of icings as an indicator of thermal regime by comparing icing presence with: (1) mean glacier thickness, as a proxy for present thermal regime; and (2) evidence of past surge activity, which is an indicator of past thermal regime. A total of 279 icings were identified from TopoSvalbard imagery covering the period 2008-2012, of which 143 corresponded to icings identified by Bukowska-Jania and Szafraniec (2005) from aerial photographs from 1990. Only 46% of icings observed in 2008-2012 were found to occur at glaciers with thicknesses consistent with a polythermal regime, meaning a large proportion were associated with glaciers predicted to be of a cold or transitional thermal regime. As a result, icing presence alone may be an unsuitable indicator of glacier regime. We further found that, of the 279 glaciers with icings, 63% of cold-based glaciers and 64% of transitional glaciers were associated with evidence of surge activity. We therefore suggest that proglacial icing formation in Svalbard may reflect historical (rather than present) thermal regime, and that icings possibly originate from groundwater effusion from subglacial taliks that persist for decades following glacier thinning and associated regime change

Linking chondrocyte and synovial transcriptional profile to clinical phenotype in osteoarthritis.

OBJECTIVES: To determine how gene expression profiles in osteoarthritis joint tissues relate to patient phenotypes and whether molecular subtypes can be reproducibly captured by a molecular classification algorithm. METHODS: We analysed RNA sequencing data from cartilage and synovium in 113 osteoarthritis patients, applying unsupervised clustering and Multi-Omics Factor Analysis to characterise transcriptional profiles. We tested the association of the molecularly defined patient subgroups with clinical characteristics from electronic health records. RESULTS: We detected two patient subgroups in low-grade cartilage (showing no/minimal degeneration, cartilage normal/softening only), with differences associated with inflammation, extracellular matrix-related and cell adhesion pathways. The high-inflammation subgroup was associated with female sex (OR 4.12, p=0.0024) and prescription of proton pump inhibitors (OR 4.21, p=0.0040). We identified two independent patient subgroupings in osteoarthritis synovium: one related to inflammation and the other to extracellular matrix and cell adhesion processes. A seven-gene classifier including MMP13, APOD, MMP2, MMP1, CYTL1, IL6 and C15orf48 recapitulated the main axis of molecular heterogeneity in low-grade knee osteoarthritis cartilage (correlation ρ=-0.88, p<10-10) and was reproducible in an independent patient cohort (ρ=-0.85, p<10-10). CONCLUSIONS: These data support the reproducible stratification of osteoarthritis patients by molecular subtype and the exploration of new avenues for tailored treatments