Urgent care axis for the older adult: where is best to target interventions?

Background We explored the urgent care axis across EDs in Yorkshire and Humber (Y&H) for patients aged ≥75 years to identify where interventions could be targeted to prevent ED attendances and inpatient admissions. Methods Hospital Episode Statistics (HES) data for attendances across 18 EDs in Y&H from April 2011 to March 2014 were retrospectively analysed. HES A&E and Admitted Patient Care patient records data were linked to describe the entire patient pathway. The population studied was adult patients attending type 1 EDs, comparing those ≥75 years with those under 75. Data analysed included arrival mode, presentation time, time in ED, outcome (admitted/discharged), admission length of stay, International Classification of Diseases 10th Revision (ICD-10) and cause codes related to admission. Short-stay admissions and admissions with potentially avoidable conditions (identified by ICD-10 codes and cause codes) were identified. Comparative analysis was undertaken between sites. Results There were 3 736 541 ED attendances, of which 625 772 (16.7%) were ≥75 years. Older patients were significantly more likely to attend via ambulance than the younger cohort (OR 7.7, 95% CI 7.6 to 7.7), and had significantly longer median stays within ED (195 vs 136 min, p<0.001) and increased likelihood of admission (OR 4.5, 95% CI 4.5 to 4.6). Short-stay admissions accounted for 28.3% of older adult admissions. 37.3% of older adult admissions were with conditions that were potentially avoidable, accounting for 42.3% of short-stay admissions. There was regional variation in the proportions of older adults admitted (between 34.3% and 40.9%). Discussion Large numbers of older adults present to EDs mainly by ambulance. Significant proportions are admitted for short periods with conditions that might potentially be managed outside of hospital. Variation across the region warrants further study

Fitting the integrated Spectral Energy Distributions of Galaxies

Fitting the spectral energy distributions (SEDs) of galaxies is an almost universally used technique that has matured significantly in the last decade. Model predictions and fitting procedures have improved significantly over this time, attempting to keep up with the vastly increased volume and quality of available data. We review here the field of SED fitting, describing the modelling of ultraviolet to infrared galaxy SEDs, the creation of multiwavelength data sets, and the methods used to fit model SEDs to observed galaxy data sets. We touch upon the achievements and challenges in the major ingredients of SED fitting, with a special emphasis on describing the interplay between the quality of the available data, the quality of the available models, and the best fitting technique to use in order to obtain a realistic measurement as well as realistic uncertainties. We conclude that SED fitting can be used effectively to derive a range of physical properties of galaxies, such as redshift, stellar masses, star formation rates, dust masses, and metallicities, with care taken not to over-interpret the available data. Yet there still exist many issues such as estimating the age of the oldest stars in a galaxy, finer details ofdust properties and dust-star geometry, and the influences of poorly understood, luminous stellar types and phases. The challenge for the coming years will be to improve both the models and the observational data sets to resolve these uncertainties. The present review will be made available on an interactive, moderated web page (sedfitting.org), where the community can access and change the text. The intention is to expand the text and keep it up to date over the coming years.Comment: 54 pages, 26 figures, Accepted for publication in Astrophysics & Space Scienc

Implementing subtype-specific pre-clinical models of breast cancer to study pre-treatment aspirin effects

YesBackgorund Prior data suggest pre-diagnostic aspirin use impacts breast tumour biology and patient outcome. Here, we employed faithful surgical resection models of HER2+ and triple-negative breast cancer (TNBC), to study outcome and response mechanisms across breast cancer subtypes. Method NOD/SCID mice were implanted with HER2+ MDA-MB-231/LN/2-4/H2N, trastuzumab-resistant HER2+ HCC1954 or a TNBC patient-derived xenograft (PDX). A daily low-dose aspirin regimen commenced until primary tumours reached ~250 mm3 and subsequently resected. MDA-MB-231/LN/2-4/H2N mice were monitored for metastasis utilising imaging. To interrogate the survival benefit of pre-treatment aspirin, 3 weeks post-resection, HCC1954/TNBC animals received standard-of-care (SOC) chemotherapy for 6 weeks. Primary tumour response to aspirin was interrogated using immunohistochemistry. Results Aspirin delayed time to metastasis in MDA-MB-231/LN/2-4/H2N xenografts and decreased growth of HER2+/TNBC primary tumours. Lymphangiogenic factors and lymph vessels number were decreased in HER2+ tumours. However, no survival benefit was seen in aspirin pre-treated animals (HCC1954/TNBC) that further received adjuvant SOC, compared with animals treated with SOC alone. In an effort to study mechanisms responsible for the observed reduction in lymphangiogenesis in HER2+ BC we utilised an in vitro co-culture system of HCC1954 tumour cells and mesenchymal stromal cells (MSC). Aspirin abrogated the secretion of VEGF-C in MSCs and also decreased the lymph/angiogenic potential of the MSCs and HCC1954 by tubule formation assay. Furthermore, aspirin decreased the secretion of uPA in HCC1954 cells potentially diminishing its metastatic capability. Conclusion Our data employing clinically relevant models demonstrate that aspirin alters breast tumour biology. However, aspirin may not represent a robust chemo-preventative agent in the HER2+ or TNBC setting.Funding is acknowledged from the Irish Cancer Society Collaborative Cancer Research Centre under BREAST- PREDICT grant CCRC13GAL (www.breas tpred ict.com). I.S.M, E.M and A.T.B, are members of the EurOPDX Consortium, and receive funding from the European Union's Horizon 2020 research and innovation programme, grant agreement no. #731105 (EurOPDX Research Infrastructure, www.europ dx.eu)

The Physics of Star Cluster Formation and Evolution

© 2020 Springer-Verlag. The final publication is available at Springer via https://doi.org/10.1007/s11214-020-00689-4.Star clusters form in dense, hierarchically collapsing gas clouds. Bulk kinetic energy is transformed to turbulence with stars forming from cores fed by filaments. In the most compact regions, stellar feedback is least effective in removing the gas and stars may form very efficiently. These are also the regions where, in high-mass clusters, ejecta from some kind of high-mass stars are effectively captured during the formation phase of some of the low mass stars and effectively channeled into the latter to form multiple populations. Star formation epochs in star clusters are generally set by gas flows that determine the abundance of gas in the cluster. We argue that there is likely only one star formation epoch after which clusters remain essentially clear of gas by cluster winds. Collisional dynamics is important in this phase leading to core collapse, expansion and eventual dispersion of every cluster. We review recent developments in the field with a focus on theoretical work.Peer reviewe

Physical activity, sedentary time and breast cancer risk: a Mendelian randomisation study

Objectives: Physical inactivity and sedentary behaviour are associated with higher breast cancer risk in observational studies, but ascribing causality is difficult. Mendelian randomisation (MR) assesses causality by simulating randomised trial groups using genotype. We assessed whether lifelong physical activity or sedentary time, assessed using genotype, may be causally associated with breast cancer risk overall, pre/post-menopause, and by case-groups defined by tumour characteristics. Methods: We performed two-sample inverse-variance-weighted MR using individual-level Breast Cancer Association Consortium case-control data from 130 957 European-ancestry women (69 838 invasive cases), and published UK Biobank data (n=91 105–377 234). Genetic instruments were single nucleotide polymorphisms (SNPs) associated in UK Biobank with wrist-worn accelerometer-measured overall physical activity (nsnps=5) or sedentary time (nsnps=6), or accelerometer-measured (nsnps=1) or self-reported (nsnps=5) vigorous physical activity. Results: Greater genetically-predicted overall activity was associated with lower breast cancer overall risk (OR=0.59; 95% confidence interval (CI) 0.42 to 0.83 per-standard deviation (SD;~8 milligravities acceleration)) and for most case-groups. Genetically-predicted vigorous activity was associated with lower risk of pre/perimenopausal breast cancer (OR=0.62; 95% CI 0.45 to 0.87,≥3 vs. 0 self-reported days/week), with consistent estimates for most case-groups. Greater genetically-predicted sedentary time was associated with higher hormone-receptor-negative tumour risk (OR=1.77; 95% CI 1.07 to 2.92 per-SD (~7% time spent sedentary)), with elevated estimates for most case-groups. Results were robust to sensitivity analyses examining pleiotropy (including weighted-median-MR, MR-Egger). Conclusion: Our study provides strong evidence that greater overall physical activity, greater vigorous activity, and lower sedentary time are likely to reduce breast cancer risk. More widespread adoption of active lifestyles may reduce the burden from the most common cancer in women

Breast cancer risk genes: association analysis in more than 113,000 women

BACKGROUNDGenetic testing for breast cancer susceptibility is widely used, but for many genes, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are lacking.METHODSWe used a panel of 34 putative susceptibility genes to perform sequencing on samples from 60,466 women with breast cancer and 53,461 controls. In separate analyses for protein-truncating variants and rare missense variants in these genes, we estimated odds ratios for breast cancer overall and tumor subtypes. We evaluated missense-variant associations according to domain and classification of pathogenicity.RESULTSProtein-truncating variants in 5 genes (ATM, BRCA1, BRCA2, CHEK2, and PALB2) were associated with a risk of breast cancer overall with a P value of less than 0.0001. Protein-truncating variants in 4 other genes (BARD1, RAD51C, RAD51D, and TP53) were associated with a risk of breast cancer overall with a P value of less than 0.05 and a Bayesian false-discovery probability of less than 0.05. For protein-truncating variants in 19 of the remaining 25 genes, the upper limit of the 95% confidence interval of the odds ratio for breast cancer overall was less than 2.0. For protein-truncating variants in ATM and CHEK2, odds ratios were higher for estrogen receptor (ER)-positive disease than for ER-negative disease; for protein-truncating variants in BARD1, BRCA1, BRCA2, PALB2, RAD51C, and RAD51D, odds ratios were higher for ER-negative disease than for ER-positive disease. Rare missense variants (in aggregate) in ATM, CHEK2, and TP53 were associated with a risk of breast cancer overall with a P value of less than 0.001. For BRCA1, BRCA2, and TP53, missense variants (in aggregate) that would be classified as pathogenic according to standard criteria were associated with a risk of breast cancer overall, with the risk being similar to that of protein-truncating variants.CONCLUSIONSThe results of this study define the genes that are most clinically useful for inclusion on panels for the prediction of breast cancer risk, as well as provide estimates of the risks associated with protein-truncating variants, to guide genetic counseling. (Funded by European Union Horizon 2020 programs and others.)Molecular tumour pathology - and tumour geneticsMTG1 - Moleculaire genetica en pathologie van borstkanke

A case-only study to identify genetic modifiers of breast cancer risk for BRCA1/BRCA2 mutation carriers

Breast cancer (BC) risk for BRCA1 and BRCA2 mutation carriers varies by genetic and familial factors. About 50 common variants have been shown to modify BC risk for mutation carriers. All but three, were identified in general population studies. Other mutation carrier-specific susceptibility variants may exist but studies of mutation carriers have so far been underpowered. We conduct a novel case-only genome-wide association study comparing genotype frequencies between 60,212 general population BC cases and 13,007 cases with BRCA1 or BRCA2 mutations. We identify robust novel associations for 2 variants with BC for BRCA1 and 3 for BRCA2 mutation carriers, P < 10−8, at 5 loci, which are not associated with risk in the general population. They include rs60882887 at 11p11.2 where MADD, SP11 and EIF1, genes previously implicated in BC biology, are predicted as potential targets. These findings will contribute towards customising BC polygenic risk scores for BRCA1 and BRCA2 mutation carriers