Testing asteroseismology with Gaia DR2: Hierarchical models of the Red Clump

Asteroseismology provides fundamental stellar parameters independent of distance, but subject to systematics under calibration. Gaia DR2 has provided parallaxes for a billion stars, which are offset by a parallax zero-point. Red Clump (RC) stars have a narrow spread in luminosity, thus functioning as standard candles to calibrate these systematics. This work measures how the magnitude and spread of the RC in the Kepler field are affected by changes to temperature and scaling relations for seismology, and changes to the parallax zero-point for Gaia. We use a sample of 5576 RC stars classified through asteroseismology. We apply hierarchical Bayesian latent variable models, finding the population level properties of the RC with seismology, and use those as priors on Gaia parallaxes to find the parallax zero-point offset. We then find the position of the RC using published values for the zero-point. We find a seismic temperature insensitive spread of the RC of ~0.03 mag in the 2MASS K band and a larger and slightly temperature-dependent spread of ~0.13 mag in the Gaia G band. This intrinsic dispersion in the K band provides a distance precision of ~1% for RC stars. Using Gaia data alone, we find a mean zero-point of -41 $\pm$ 10 $\mu$as. This offset yields RC absolute magnitudes of -1.634 $\pm$ 0.018 in K and 0.546 $\pm$ 0.016 in G. Obtaining these same values through seismology would require a global temperature shift of ~-70 K, which is compatible with known systematics in spectroscopy.Comment: Accepted for publication in MNRA

Ranking ligand affinity for the DNA minor groove by experiment and simulation

The structural and thermodynamic basis for the strength and selectivity of the interactions of minor-groove binders (MGBs) with DNA is not fully understood. In 2003 we reported the first example of a thiazole containing MGB that bound in a phase shifted pattern that spanned 6 base-pairs rather than the usual 4 (for tricyclic distamycin-like compounds). Since then, using DNA footprinting, nuclear magnetic resonance spectroscopy, isothermal titration calorimetry and molecular dynamics, we have established that the flanking bases around the central 4 being read by the ligand have subtle effects on recognition. We have investigated the effect of these flanking sequences on binding and the reasons for the differences and established a computational method to rank ligand affinity against varying DNA sequences

Auditory sensitivity in aquatic animals

© 2016 Acoustical Society of America. A critical concern with respect to marine animal acoustics is the issue of hearing "sensitivity," as it is widely used as a criterion for the onset of noise-induced effects. Important aspects of research on sensitivity to sound by marine animals include: uncertainties regarding how well these species detect and respond to different sounds; the masking effects of man-made sounds on the detection of biologically important sounds; the question how internal state, motivation, context, and previous experience affect their behavioral responses; and the long-term and cumulative effects of sound exposure. If we are to better understand the sensitivity of marine animals to sound we must concentrate research on these questions. In order to assess population level and ecological community impacts new approaches can possibly be adopted from other disciplines and applied to marine fauna

APOL1 Kidney-Risk Variants Induce Mitochondrial Fission

IntroductionAPOL1 G1 and G2 nephropathy-risk variants cause mitochondrial dysfunction and contribute to kidney disease. Analyses were performed to determine the genetic regulation of APOL1 and elucidate potential mechanisms in APOL1-nephropathy.MethodsA global gene expression analysis was performed in human primary renal tubule cell lines derived from 50 African American individuals. Follow-up gene knock out, cell-based rescue, and microscopy experiments were performed.ResultsAPOL1 genotypes did not alter APOL1 expression levels in the global gene expression analysis. Expression quantitative trait locus (eQTL) analysis in polyinosinic-polycytidylic acid (poly IC)-stimulated renal tubule cells revealed that single nucleotide polymorphism (SNP) rs513349 adjacent to BAK1 was a trans eQTL for APOL1 and a cis eQTL for BAK1; APOL1 and BAK1 were co-expressed in cells. BAK1 knockout in a human podocyte cell line resulted in diminished APOL1 protein, supporting a pivotal effect for BAK1 on APOL1 expression. Because BAK1 is involved in mitochondrial dynamics, mitochondrial morphology was examined in primary renal tubule cells and HEK293 Tet-on cells of various APOL1 genotypes. Mitochondria in APOL1 wild-type (G0G0) tubule cells maintained elongated morphology when stimulated by low-dose poly IC, whereas those with G1G1, G2G2, and G1G2 genotypes appeared to fragment. HEK293 Tet-on cells overexpressing APOL1 G0, G1, and G2 were created; G0 cells appeared to promote mitochondrial fusion, whereas G1 and G2 induced mitochondrial fission. The mitochondrial dynamic regulator Mdivi-1 significantly preserved cell viability and mitochondrial cristae structure and reversed mitochondrial fission induced by overexpression of G1 and G2.ConclusionResults suggest the mitochondrial fusion/fission pathway may be a therapeutic target in APOL1-nephropathy

Compendium of Single Event Effects Results for Candidate Spacecraft Electronics for NASA

Susceptibility of a variety of candidate spacecraft electronics to proton and heavy ion induced single event effects is studied. Devices tested include digital, linear bipolar, and hybrid devices

Consistent phenological shifts in the making of a biodiversity hotspot: the Cape flora

Background The best documented survival responses of organisms to past climate change on short (glacial-interglacial) timescales are distributional shifts. Despite ample evidence on such timescales for local adaptations of populations at specific sites, the long-term impacts of such changes on evolutionary significant units in response to past climatic change have been little documented. Here we use phylogenies to reconstruct changes in distribution and flowering ecology of the Cape flora - South Africa's biodiversity hotspot - through a period of past (Neogene and Quaternary) changes in the seasonality of rainfall over a timescale of several million years. Results Forty-three distributional and phenological shifts consistent with past climatic change occur across the flora, and a comparable number of clades underwent adaptive changes in their flowering phenology (9 clades; half of the clades investigated) as underwent distributional shifts (12 clades; two thirds of the clades investigated). Of extant Cape angiosperm species, 14-41% have been contributed by lineages that show distributional shifts consistent with past climate change, yet a similar proportion (14-55%) arose from lineages that shifted flowering phenology. Conclusions Adaptive changes in ecology at the scale we uncover in the Cape and consistent with past climatic change have not been documented for other floras. Shifts in climate tolerance appear to have been more important in this flora than is currently appreciated, and lineages that underwent such shifts went on to contribute a high proportion of the flora's extant species diversity. That shifts in phenology, on an evolutionary timescale and on such a scale, have not yet been detected for other floras is likely a result of the method used; shifts in flowering phenology cannot be detected in the fossil record

An empirical approach to selecting community-based alcohol interventions:combining research evidence, rural community views and professional opinion

<p>Abstract</p> <p>Background</p> <p>Given limited research evidence for community-based alcohol interventions, this study examines the intervention preferences of rural communities and alcohol professionals, and factors that influence their choices.</p> <p>Method</p> <p>Community preferences were identified by a survey of randomly selected individuals across 20 regional Australian communities. The preferences of alcohol professionals were identified by a survey of randomly selected members of the Australasian Professional Society on Alcohol and Other Drugs. To identify preferred interventions and the extent of support for them, a budget allocation exercise was embedded in both surveys, asking respondents to allocate a given budget to different interventions. Tobit regression models were estimated to identify the characteristics that explain differences in intervention preferences.</p> <p>Results</p> <p>Community respondents selected school programs most often (88.0%) and allocated it the largest proportion of funds, followed by promotion of safer drinking (71.3%), community programs (61.4%) and police enforcement of alcohol laws (60.4%). Professionals selected GP training most often (61.0%) and allocated it the largest proportion of funds, followed by school programs (36.6%), community programs (33.8%) and promotion of safer drinking (31.7%). Community views were susceptible to response bias. There were no significant predictors of professionals' preferences.</p> <p>Conclusions</p> <p>In the absence of sufficient research evidence for effective community-based alcohol interventions, rural communities and professionals both strongly support school programs, promotion of safer drinking and community programs. Rural communities also supported police enforcement of alcohol laws and professionals supported GP training. The impact of a combination of these strategies needs to be rigorously evaluated.</p

Population-based estimates of the prevalence of FMR1 expansion mutations in women with early menopause and primary ovarian insufficiency

PURPOSE: Primary ovarian insufficiency before the age of 40 years affects 1% of the female population and is characterized by permanent cessation of menstruation. Genetic causes include FMR1 expansion mutations. Previous studies have estimated mutation prevalence in clinical referrals for primary ovarian insufficiency, but these are likely to be biased as compared with cases in the general population. The prevalence of FMR1 expansion mutations in early menopause (between the ages of 40 and 45 years) has not been published. METHODS: We studied FMR1 CGG repeat number in more than 2,000 women from the Breakthrough Generations Study who underwent menopause before the age of 46 years. We determined the prevalence of premutation (55–200 CGG repeats) and intermediate (45–54 CGG repeats) alleles in women with primary ovarian insufficiency (n = 254) and early menopause (n = 1,881). RESULTS: The prevalence of the premutation was 2.0% in primary ovarian insufficiency, 0.7% in early menopause, and 0.4% in controls, corresponding to odds ratios of 5.4 (95% confidence interval = 1.7–17.4; P = 0.004) for primary ovarian insufficiency and 2.0 (95% confidence interval = 0.8–5.1; P = 0.12) for early menopause. Combining primary ovarian insufficiency and early menopause gave an odds ratio of 2.4 (95% confidence interval = 1.02–5.8; P = 0.04). Intermediate alleles were not significant risk factors for either early menopause or primary ovarian insufficiency. CONCLUSION: FMR1 premutations are not as prevalent in women with ovarian insufficiency as previous estimates have suggested, but they still represent a substantial cause of primary ovarian insufficiency and early menopause

Bayesian calibration, validation and uncertainty quantification for predictive modelling of tumour growth: a tutorial

In this work we present a pedagogical tumour growth example, in which we apply calibration and validation techniques to an uncertain, Gompertzian model of tumour spheroid growth. The key contribution of this article is the discussion and application of these methods (that are not commonly employed in the field of cancer modelling) in the context of a simple model, whose deterministic analogue is widely known within the community. In the course of the example we calibrate the model against experimental data that is subject to measurement errors, and then validate the resulting uncertain model predictions. We then analyse the sensitivity of the model predictions to the underlying measurement model. Finally, we propose an elementary learning approach for tuning a threshold parameter in the validation procedure in order to maximize predictive accuracy of our validated model