An invasive-native mammalian species replacement process captured by camera trap survey random encounter models

Camera traps are used to estimate densities or abundances using capture-recapture and, more recently, random encounter models (REMs). We deploy REMs to describe an invasive-native species replacement process, and to demonstrate their wider application beyond abundance estimation. The Irish hare Lepus timidus hibernicus is a high priority endemic of conservation concern. It is threatened by an expanding population of non-native, European hares L. europaeus, an invasive species of global importance. Camera traps were deployed in thirteen 1 km squares, wherein the ratio of invader to native densities were corroborated by night-driven line transect distance sampling throughout the study area of 1652 km2. Spatial patterns of invasive and native densities between the invader’s core and peripheral ranges, and native allopatry, were comparable between methods. Native densities in the peripheral range were comparable to those in native allopatry using REM, or marginally depressed using Distance Sampling. Numbers of the invader were substantially higher than the native in the core range, irrespective of method, with a 5:1 invader-to-native ratio indicating species replacement. We also describe a post hoc optimization protocol for REM which will inform subsequent (re-)surveys, allowing survey effort (camera hours) to be reduced by up to 57% without compromising the width of confidence intervals associated with density estimates. This approach will form the basis of a more cost-effective means of surveillance and monitoring for both the endemic and invasive species. The European hare undoubtedly represents a significant threat to the endemic Irish hare.

Comprehensive molecular pathology analysis of small bowel adenocarcinoma reveals novel targets with potential for clinical utility

Small bowel accounts for only 0.5% of cancer cases in the US but incidence rates have been rising at 2.4% per year over the past decade. One-third of these are adenocarcinomas but little is known about their molecular pathology and no molecular markers are available for clinical use. Using a retrospective 28 patient matched normal-tumor cohort, next-generation sequencing, gene expression arrays and CpG methylation arrays were used for molecular profiling. Next-generation sequencing identified novel mutations in IDH1, CDH1, KIT, FGFR2, FLT3, NPM1, PTEN, MET, AKT1, RET, NOTCH1 and ERBB4. Array data revealed 17% of CpGs and 5% of RNA transcripts assayed to be differentially methylated and expressed respectively (p < 0.01). Merging gene expression and DNA methylation data revealed CHN2 as consistently hypermethylated and downregulated in this disease (Spearman -0.71, p < 0.001). Mutations in TP53 which were found in more than half of the cohort (15/28) and Kazald1 hypomethylation were both were indicative of poor survival (p = 0.03, HR = 3.2 and p = 0.01, HR = 4.9 respectively). By integrating high-throughput mutational, gene expression and DNA methylation data, this study reveals for the first time the distinct molecular profile of small bowel adenocarcinoma and highlights potential clinically exploitable markers.

Allocating Participants to Groups In Educational Trials: What Does Random Mean?

What is meant by the term random? Do we understand how to identify which type of randomisation to use in our future research projects? We, as researchers, often explain randomisation to potential research participants as being a 50/50 chance of selection to either an intervention or control group, akin to drawing numbers out of a hat. Is this an accurate explanation? And are all methods of randomisation equal? This paper aims to guide the researcher through the different techniques used to randomise participants with examples of how they can be used in educational research.

Evidence for the reliability and validity, but not the practical utility of the two-factor Consideration of Future Consequences Scale-14

Researchers have proposed 1-factor, 2-factor, and bifactor solutions to the 12-item Consideration of Future Consequences Scale (CFCS-12). In order to overcome some measurement problems and to create a robust and conceptually useful two-factor scale the CFCS-12 was recently modified to include two new items and to become the CFCS-14. Using a University sample, we tested four competing models for the CFCS-14: (a) a 12-item unidimensional model, (b) a model fitted for two uncorrelated factors (CFC-Immediate and CFC-Future), (c) a model fitted for two correlated factors (CFC-I and CFC-F), and (d) a bifactor model. Results suggested that the addition of the two new items has strengthened the viability of a two factor solution of the CFCS-14. Results of linear regression models suggest that the CFC-F factor is redundant. Further studies using alcohol and mental health indicators are required to test this redundancy.

Utility of US Norms for the Bayley Scales of Infant Development (III) in UK and Irish Children

The aim of this paper is to explore the utility of the United States norms for United Kingdom and Republic of Ireland populations. The Bayley Scales of Infant Development (BSID III) is a globally used developmental assessment for typically developing and clinical samples of children aged 1 to 42 months. A UK norming exercise (REF) confirmed the suitability of US norms for UK based research and practice. However, debate has continued concerning the utility of the US norms in other countries. This paper further explores the utility of the US norms for the UK and ROI populations using BSID III developmental outcome data from two samples of over one thousand typically developing children.