Macroevolutionary consequences of profound climate change on niche evolution in marine molluscs over the past three million years

In order to predict the fate of biodiversity in a rapidly changing world, we must first understand how species adapt to new environmental conditions. The long-term evolutionary dynamics of species’ physiological tolerances to differing climatic regimes remain obscure. Here, we unite palaeontological and neontological data to analyse whether species’ environmental tolerances remain stable across 3 Myr of profound climatic changes using 10 phylogenetically, ecologically and developmentally diverse mollusc species from the Atlantic and Gulf Coastal Plains, USA. We additionally investigate whether these species’ upper and lower thermal tolerances are constrained across this interval. We find that these species’ environmental preferences are stable across the duration of their lifetimes, even when faced with significant environmental perturbations. The results suggest that species will respond to current and futurewarming either by altering distributions to track suitable habitat or, if the pace of change is too rapid, by going extinct. Our findings also support methods that project species’ present-day environmental requirements to future climatic landscapes to assess conservation risks

A comparison of machine learning methods for predicting recurrence and death after curative-intent radiotherapy for non-small cell lung cancer: Development and validation of multivariable clinical prediction models.

Background Surveillance is universally recommended for non-small cell lung cancer (NSCLC) patients treated with curative-intent radiotherapy. High-quality evidence to inform optimal surveillance strategies is lacking. Machine learning demonstrates promise in accurate outcome prediction for a variety of health conditions. The purpose of this study was to utilise readily available patient, tumour, and treatment data to develop, validate and externally test machine learning models for predicting recurrence, recurrence-free survival (RFS) and overall survival (OS) at 2 years from treatment. Methods A retrospective, multicentre study of patients receiving curative-intent radiotherapy for NSCLC was undertaken. A total of 657 patients from 5 hospitals were eligible for inclusion. Data pre-processing derived 34 features for predictive modelling. Combinations of 8 feature reduction methods and 10 machine learning classification algorithms were compared, producing risk-stratification models for predicting recurrence, RFS and OS. Models were compared with 10-fold cross validation and an external test set and benchmarked against TNM-stage and performance status. Youden Index was derived from validation set ROC curves to distinguish high and low risk groups and Kaplan-Meier analyses performed. Findings Median follow-up time was 852 days. Parameters were well matched across training-validation and external test sets: Mean age was 73 and 71 respectively, and recurrence, RFS and OS rates at 2 years were 43% vs 34%, 54% vs 47% and 54% vs 47% respectively. The respective validation and test set AUCs were as follows: 1) RFS: 0·682 (0·575–0·788) and 0·681 (0·597–0·766), 2) Recurrence: 0·687 (0·582–0·793) and 0·722 (0·635–0·81), and 3) OS: 0·759 (0·663–0·855) and 0·717 (0·634–0·8). Our models were superior to TNM stage and performance status in predicting recurrence and OS. Interpretation This robust and ready to use machine learning method, validated and externally tested, sets the stage for future clinical trials entailing quantitative personalised risk-stratification and surveillance following curative-intent radiotherapy for NSCLC. Funding A full list of funding bodies that contributed to this study can be found in the Acknowledgements section

Listening In on the Past: What Can Otolith δ18O Values Really Tell Us about the Environmental History of Fishes?

Oxygen isotope ratios from fish otoliths are used to discriminate marine stocks and reconstruct past climate, assuming that variations in otolith δ18O values closely reflect differences in temperature history of fish when accounting for salinity induced variability in water δ18O. To investigate this, we exploited the environmental and migratory data gathered from a decade using archival tags to study the behaviour of adult plaice (Pleuronectes platessa L.) in the North Sea. Based on the tag-derived monthly distributions of the fish and corresponding temperature and salinity estimates modelled across three consecutive years, we first predicted annual otolith δ18O values for three geographically discrete offshore sub-stocks, using three alternative plausible scenarios for otolith growth. Comparison of predicted vs. measured annual δ18O values demonstrated >96% correct prediction of sub-stock membership, irrespective of the otolith growth scenario. Pronounced inter-stock differences in δ18O values, notably in summer, provide a robust marker for reconstructing broad-scale plaice distribution in the North Sea. However, although largely congruent, measured and predicted annual δ18O values of did not fully match. Small, but consistent, offsets were also observed between individual high-resolution otolith δ18O values measured during tag recording time and corresponding δ18O predictions using concomitant tag-recorded temperatures and location-specific salinity estimates. The nature of the shifts differed among sub-stocks, suggesting specific vital effects linked to variation in physiological response to temperature. Therefore, although otolith δ18O in free-ranging fish largely reflects environmental temperature and salinity, we counsel prudence when interpreting otolith δ18O data for stock discrimination or temperature reconstruction until the mechanisms underpinning otolith δ18O signature acquisition, and associated variation, are clarified

Star forming dwarf galaxies

Star forming dwarf galaxies (SFDGs) have a high gas content and low metallicities, reminiscent of the basic entities in hierarchical galaxy formation scenarios. In the young universe they probably also played a major role in the cosmic reionization. Their abundant presence in the local volume and their youthful character make them ideal objects for detailed studies of the initial stellar mass function (IMF), fundamental star formation processes and its feedback to the interstellar medium. Occasionally we witness SFDGs involved in extreme starbursts, giving rise to strongly elevated production of super star clusters and global superwinds, mechanisms yet to be explored in more detail. SFDGs is the initial state of all dwarf galaxies and the relation to the environment provides us with a key to how different types of dwarf galaxies are emerging. In this review we will put the emphasis on the exotic starburst phase, as it seems less important for present day galaxy evolution but perhaps fundamental in the initial phase of galaxy formation.Comment: To appear in JENAM Symposium "Dwarf Galaxies: Keys to Galaxy Formation and Evolution", P. Papaderos, G. Hensler, S. Recchi (eds.). Lisbon, September 2010, Springer Verlag, in pres

Resolution of Hypoglycemia and Cardiovascular Dysfunction After Rituximab Treatment of Insulin Autoimmune Syndrome

D.C. is funded by a Diabetes Research & Wellness Foundation Sutherland-Earl Clinical Fellowship (RG68554). R.W.H. is supported by the Wellcome Trust–University of Edinburgh Institutional Strategic Support Fund. N.D. is supported by a British Heart Foundation Intermediate Clinical Research Fellowship (FS/13/30/29994). R.S. is funded by the Wellcome Trust (grant WT098498)

Reporting and evaluating genetic association studies

Genetic association studies have become an important part of our scientific landscape. This commentary discusses some basic scientific issues which should be considered when reporting and evaluating such studies including SNP Discovery, Genotyping and Haplotype Analysis; Population Size, Matching of Cases and Controls, and Population Stratification; Phenotype Definition and Multiple Related Phenotypes; Multiple Testing; Replication; Genome-wide Association Studies (GWAS); and the Role of Functional Studies. All of these elements are important in evaluating such studies and should be carefully considered when these studies are conceived and carried out

Adolescent diet and risk of breast cancer

BACKGROUND: Early life exposures, including diet, have been implicated in the etiology of breast cancer. METHODS: A nested case-control study was conducted among participants in the Nurses' Health Study who completed a 24-item questionnaire about diet during high school. There were 843 eligible cases diagnosed between onset of study (1976) and before the return of the high school diet questionnaire (1986), who were matched 10:1 with controls on the basis of age. RESULTS: Women who had, during adolescence, a higher consumption of eggs, vegetable fat and fiber had a lower risk of breast cancer, whereas risk of breast cancer was increased among women who consumed more butter. CONCLUSIONS: A possible association of elements of adolescent diet with risk of breast cancer is reported, but the findings require confirmation in prospective study