Testing the white dwarf mass-radius relationship with eclipsing binaries

We present high-precision, model-independent, mass and radius measurements for 16 white dwarfs in detached eclipsing binaries and combine these with previously published data to test the theoretical white dwarf mass–radius relationship. We reach a mean precision of 2.4 per cent in mass and 2.7 per cent in radius, with our best measurements reaching a precision of 0.3 per cent in mass and 0.5 per cent in radius. We find excellent agreement between the measured and predicted radii across a wide range of masses and temperatures. We also find the radii of all white dwarfs with masses less than 0.48 M⊙ to be fully consistent with helium core models, but they are on average 9 per cent larger than those of carbon–oxygen core models. In contrast, white dwarfs with masses larger than 0.52 M⊙ all have radii consistent with carbon–oxygen core models. Moreover, we find that all but one of the white dwarfs in our sample have radii consistent with possessing thick surface hydrogen envelopes (10−5 ≥ MH/MWD ≥ 10−4), implying that the surface hydrogen layers of these white dwarfs are not obviously affected by common envelope evolution

Optimising medication data collection in a large-scale clinical trial

© 2019 Lockery et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Objective: Pharmaceuticals play an important role in clinical care. However, in community-based research, medication data are commonly collected as unstructured free-text, which is prohibitively expensive to code for large-scale studies. The ASPirin in Reducing Events in the Elderly (ASPREE) study developed a two-pronged framework to collect structured medication data for 19,114 individuals. ASPREE provides an opportunity to determine whether medication data can be cost-effectively collected and coded, en masse from the community using this framework. Methods: The ASPREE framework of type-to-search box with automated coding and linked free text entry was compared to traditional method of free-text only collection and post hoc coding. Reported medications were classified according to their method of collection and analysed by Anatomical Therapeutic Chemical (ATC) group. Relative cost of collecting medications was determined by calculating the time required for database set up and medication coding. Results Overall, 122,910 participant structured medication reports were entered using the type-tosearch box and 5,983 were entered as free-text. Free-text data contributed 211 unique medications not present in the type-to-search box. Spelling errors and unnecessary provision of additional information were among the top reasons why medications were reported as freetext. The cost per medication using the ASPREE method was approximately USD $0.03 compared with USD$0.20 per medication for the traditional method. Conclusion Implementation of this two-pronged framework is a cost-effective alternative to free-text only data collection in community-based research. Higher initial set-up costs of this combined method are justified by long term cost effectiveness and the scientific potential for analysis and discovery gained through collection of detailed, structured medication data

Identifying Ligand Binding Conformations of the β2-Adrenergic Receptor by Using Its Agonists as Computational Probes

Recently available G-protein coupled receptor (GPCR) structures and biophysical studies suggest that the difference between the effects of various agonists and antagonists cannot be explained by single structures alone, but rather that the conformational ensembles of the proteins need to be considered. Here we use an elastic network model-guided molecular dynamics simulation protocol to generate an ensemble of conformers of a prototypical GPCR, β2-adrenergic receptor (β2AR). The resulting conformers are clustered into groups based on the conformations of the ligand binding site, and distinct conformers from each group are assessed for their binding to known agonists of β2AR. We show that the select ligands bind preferentially to different predicted conformers of β2AR, and identify a role of β2AR extracellular region as an allosteric binding site for larger drugs such as salmeterol. Thus, drugs and ligands can be used as "computational probes" to systematically identify protein conformers with likely biological significance. © 2012 Isin et al

High-speed photometry of Gaia14aae: an eclipsing AMCVn that challenges formation models

AM CVn-type systems are ultracompact, hydrogen-deficient accreting binaries with degenerate or semidegenerate donors. The evolutionary history of these systems can be explored by constraining the properties of their donor stars. We present high-speed photometry of Gaia14aae, an AM CVn with a binary period of 49. 7 min and the first AM CVn in which the central white dwarf is fully eclipsed by the donor star. Modelling of the light curves of this system allows for the most precise measurement to date of the donor mass of an AM CVn, and relies only on geometric and well-tested physical assumptions. We find a mass ratio q = M2/M1 = 0.0287 ± 0.0020 and masses M1 = 0.87 ± 0.02 M⊙ and M2 = 0.0250 ± 0.0013 M⊙. We compare these properties to the three proposed channels for AM CVn formation. Our measured donor mass and radius do not fit with the contraction that is predicted for AM CVn donors descended from white dwarfs or helium stars at long orbital periods. The donor properties we measure fall in a region of parameter space in which systems evolved from hydrogen-dominated cataclysmic variables are expected, but such systems should show spectroscopic hydrogen, which is not seen in Gaia14aae. The evolutionary history of this system is therefore not clear. We consider a helium-burning star or an evolved cataclysmic variable to be the most likely progenitors, but both models require additional processes and/or fine-tuning to fit the data. Additionally, we calculate an updated ephemeris which corrects for an anomalous time measurement in the previously published ephemeris

Just when you thought it was safe to go into the membrane: the growing complexities of extra-nuclear progesterone signaling

The diversity of membrane-initiated progesterone actions has made characterization and establishment of its biological importance a complicated endeavor. A new study by Zuo and colleagues shows that progesterone via endogenous membrane progesterone receptor-α acts as a negative regulator of proliferation and epithelial to mesenchymal transition in a breast cancer cell line. These progesterone-mediated actions appear to be regulated through epidermal growth factor receptor and phosphatidylinositol 3-kinase signaling localized in caveolae. Moreover, the study shows expression of membrane progesterone receptor-α in benign and malignant breast cancer tissues. These data bring forth novel concepts with regard to progesterone actions in the breast; however, further work is warranted to fully characterize the physiologic actions of extra-nuclear progesterone signaling in the breast

Aurora kinase A drives the evolution of resistance to third-generation EGFR inhibitors in lung cancer.

Although targeted therapies often elicit profound initial patient responses, these effects are transient due to residual disease leading to acquired resistance. How tumors transition between drug responsiveness, tolerance and resistance, especially in the absence of preexisting subclones, remains unclear. In epidermal growth factor receptor (EGFR)-mutant lung adenocarcinoma cells, we demonstrate that residual disease and acquired resistance in response to EGFR inhibitors requires Aurora kinase A (AURKA) activity. Nongenetic resistance through the activation of AURKA by its coactivator TPX2 emerges in response to chronic EGFR inhibition where it mitigates drug-induced apoptosis. Aurora kinase inhibitors suppress this adaptive survival program, increasing the magnitude and duration of EGFR inhibitor response in preclinical models. Treatment-induced activation of AURKA is associated with resistance to EGFR inhibitors in vitro, in vivo and in most individuals with EGFR-mutant lung adenocarcinoma. These findings delineate a molecular path whereby drug resistance emerges from drug-tolerant cells and unveils a synthetic lethal strategy for enhancing responses to EGFR inhibitors by suppressing AURKA-driven residual disease and acquired resistance

A high incidence of vertebral fracture in women with breast cancer

Because treatment for breast cancer may adversely affect skeletal metabolism, we investigated vertebral fracture risk in women with non-metastatic breast cancer. The prevalence of vertebral fracture was similar in women at the time of first diagnosis to that in an age-matched sample of the general population. The incidence of vertebral fracture, however, was nearly five times greater than normal in women from the time of first diagnosis [odds ratio (OR), 4.7; 95% confidence interval (95% CI), 2.3–9.9], and 20-fold higher in women with soft-tissue metastases without evidence of skeletal metastases (OR, 22.7; 95% CI, 9.1–57.1). We conclude that vertebral fracture risk is markedly increased in women with breast cancer. © 1999 Cancer Research Campaig

Aptamer-based multiplexed proteomic technology for biomarker discovery

Interrogation of the human proteome in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 [mu]L of serum or plasma). Our current assay allows us to measure ~800 proteins with very low limits of detection (1 pM average), 7 logs of overall dynamic range, and 5% average coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding DNA aptamer concentration signature, which is then quantified with a DNA microarray. In essence, our assay takes advantage of the dual nature of aptamers as both folded binding entities with defined shapes and unique sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to discover unique protein signatures characteristic of various disease states. More generally, we describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine

Functional divergence in the role of N-linked glycosylation in smoothened signaling

The G protein-coupled receptor (GPCR) Smoothened (Smo) is the requisite signal transducer of the evolutionarily conserved Hedgehog (Hh) pathway. Although aspects of Smo signaling are conserved from Drosophila to vertebrates, significant differences have evolved. These include changes in its active sub-cellular localization, and the ability of vertebrate Smo to induce distinct G protein-dependent and independent signals in response to ligand. Whereas the canonical Smo signal to Gli transcriptional effectors occurs in a G protein-independent manner, its non-canonical signal employs Gαi. Whether vertebrate Smo can selectively bias its signal between these routes is not yet known. N-linked glycosylation is a post-translational modification that can influence GPCR trafficking, ligand responsiveness and signal output. Smo proteins in Drosophila and vertebrate systems harbor N-linked glycans, but their role in Smo signaling has not been established. Herein, we present a comprehensive analysis of Drosophila and murine Smo glycosylation that supports a functional divergence in the contribution of N-linked glycans to signaling. Of the seven predicted glycan acceptor sites in Drosophila Smo, one is essential. Loss of N-glycosylation at this site disrupted Smo trafficking and attenuated its signaling capability. In stark contrast, we found that all four predicted N-glycosylation sites on murine Smo were dispensable for proper trafficking, agonist binding and canonical signal induction. However, the under-glycosylated protein was compromised in its ability to induce a non-canonical signal through Gαi, providing for the first time evidence that Smo can bias its signal and that a post-translational modification can impact this process. As such, we postulate a profound shift in N-glycan function from affecting Smo ER exit in flies to influencing its signal output in mice