RADIAL VELOCITY MONITORING OFKEPLERHEARTBEAT STARS

Heartbeat stars (HB stars) are a class of eccentric binary stars with close periastron passages. The characteristic photometric HB signal evident in their light curves is produced by a combination of tidal distortion, heating, and Doppler boosting near orbital periastron. Many HB stars continue to oscillate after periastron and along the entire orbit, indicative of the tidal excitation of oscillation modes within one or both stars. These systems are among the most eccentric binaries known, and they constitute astrophysical laboratories for the study of tidal effects. We have undertaken a radial velocity (RV) monitoring campaign of Kepler HB stars in order to measure their orbits. We present our first results here, including a sample of 22 Kepler HB systems, where for 19 of them we obtained the Keplerian orbit and for 3 other systems we did not detect a statistically significant RV variability. Results presented here are based on 218 spectra obtained with the Keck/HIRES spectrograph during the 2015 Kepler observing season, and they have allowed us to obtain the largest sample of HB stars with orbits measured using a single instrument, which roughly doubles the number of HB stars with an RV measured orbit. The 19 systems measured here have orbital periods from 7 to 90 days and eccentricities from 0.2 to 0.9. We show that HB stars draw the upper envelope of the eccentricity–period distribution. Therefore, HB stars likely represent a population of stars currently undergoing high eccentricity migration via tidal orbital circularization, and they will allow for new tests of high eccentricity migration theories

Breast epithelial cell proliferation is markedly increased with short-term high levels of endogenous estrogen secondary to controlled ovarian hyperstimulation

Oocyte donors have high serum estradiol (E2) levels similar to the serum levels seen in the first trimester of pregnancy. We report in this article our studies comparing cell proliferation, Ki67 (MIB1), and estrogen and progesterone receptor levels (ERα, PRA, and PRB) in the breast terminal duct lobular units of oocyte donors, women in early pregnancy, and in normally cycling women. Breast tissue and blood samples were obtained from 10 oocyte donors, and 30 pregnant women at 5–18 weeks of gestation. Breast tissue samples were also obtained from 26 normally cycling women. In the oocyte donors: peak E2 (mean ~15,300 pmol/l) was reached on the day before oocyte (and tissue) donation; peak progesterone (P4; mean 36.3 nmol/l) was reached on the day of donation; Ki67 was positively associated with level of E2, and the mean Ki67 was 7.0% significantly greater than the mean 1.8% of cycling women. In the pregnant women: mean E2 rose from ~2,000 pmol/l at 5 weeks of gestation to ~27,000 pmol/l at 18 weeks; mean P4 did not change from ~40 nmol/l until around gestational week 11 when it increased to ~80 nmol/l; mean Ki67 was 15.4% and did not vary with gestational age or E2. Oocyte donors have greatly increased levels of E2 and of breast-cell proliferation, both comparable in the majority of donors to the levels seen in the first trimester of pregnancy. Whether their short durations of greatly increased E2 levels are associated with any long-term beneficial effects on the breast, as occurring in rodent models, is not known

Cancer survivors’ experiences of a community-based cancer-specific exercise programme: results of an exploratory survey

Purpose Exercise levels often decline following cancer diagnosis despite growing evidence of its benefits. Treatment side-effects, older age, lack of confidence and opportunity to exercise with others in similar circumstances influence this. Our study explored the experiences of people attending a cancer-specific community-based exercise programme (CU Fitter™). Methods A survey distributed to those attending the programme gathered demographic/clinical information, self-reported exercise levels, information provision and barriers to/benefits of exercise. Results Sixty surveys were evaluable from 65/100 returned (62% female, 68% >60yrs, 66% breast/prostate cancer). Most (68%) were receiving treatment. 68% attended classes once or twice weekly. 55% received exercise advice after diagnosis, usually from their hospital doctor/nurse. More (73%) had read about exercising, but less used the internet to source information (32%). Self-reported exercise levels were higher currently than before diagnosis (p=0.05). 48% said their primary barrier to exercising was the physical impact of cancer/treatment. Improving fitness/health (40%) and social support (16%) were the most important gains from the programme. Many (67%) had made other lifestyle changes and intented to keep (50%), or increase (30%) exercising. Conclusions This community-based cancer-specific exercise approach engaged people with cancer and showed physical, psychological, and social benefits. Implications for cancer survivors Community grown exercise initiatives bring cancer survivors together creating their own supportive environment. Combining this with instructors familiar with the population and providing an open-ended service may prove particularly motivating and beneficial. Further work is required to provide evidence for this

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]

Evidence synthesis to inform model-based cost-effectiveness evaluations of diagnostic tests: a methodological systematic review of health technology assessments

Background: Evaluations of diagnostic tests are challenging because of the indirect nature of their impact on patient outcomes. Model-based health economic evaluations of tests allow different types of evidence from various sources to be incorporated and enable cost-effectiveness estimates to be made beyond the duration of available study data. To parameterize a health-economic model fully, all the ways a test impacts on patient health must be quantified, including but not limited to diagnostic test accuracy. Methods: We assessed all UK NIHR HTA reports published May 2009-July 2015. Reports were included if they evaluated a diagnostic test, included a model-based health economic evaluation and included a systematic review and meta-analysis of test accuracy. From each eligible report we extracted information on the following topics: 1) what evidence aside from test accuracy was searched for and synthesised, 2) which methods were used to synthesise test accuracy evidence and how did the results inform the economic model, 3) how/whether threshold effects were explored, 4) how the potential dependency between multiple tests in a pathway was accounted for, and 5) for evaluations of tests targeted at the primary care setting, how evidence from differing healthcare settings was incorporated. Results: The bivariate or HSROC model was implemented in 20/22 reports that met all inclusion criteria. Test accuracy data for health economic modelling was obtained from meta-analyses completely in four reports, partially in fourteen reports and not at all in four reports. Only 2/7 reports that used a quantitative test gave clear threshold recommendations. All 22 reports explored the effect of uncertainty in accuracy parameters but most of those that used multiple tests did not allow for dependence between test results. 7/22 tests were potentially suitable for primary care but the majority found limited evidence on test accuracy in primary care settings. Conclusions: The uptake of appropriate meta-analysis methods for synthesising evidence on diagnostic test accuracy in UK NIHR HTAs has improved in recent years. Future research should focus on other evidence requirements for cost-effectiveness assessment, threshold effects for quantitative tests and the impact of multiple diagnostic tests