New insights into sequence variation in the IGS region of 21 cyathostomin species and the implication for molecular identification

Cyathostomins comprise a group of 50 species of parasitic nematodes that infect equids. Ribosomal DNA sequences, in particular the intergenic spacer (IGS) region, have been utilized via several methodologies to identify pre-parasitic stages of the commonest species that affect horses. These methods rely on the availability of accurate sequence information for each species, as well as detailed knowledge of the levels of intra- and inter-specific variation. Here, the IGS DNA region was amplified and sequenced from 10 cyathostomin species for which sequence was not previously available. Also, additional IGS DNA sequences were generated from individual worms of 8 species already studied. Comparative analysis of these sequences revealed a greater range of intra-specific variation than previously reported (up to 23%); whilst the level of inter-specific variation (3-62%) was similar to that identified in earlier studies. The reverse line blot (RLB) method has been used to exploit the cyathostomin IGS DNA region for species identification. Here, we report validation of novel and existing DNA probes for identification of cyathostomins using this method and highlight their application in differentiating life-cycle stages such as third-stage larvae that cannot be identified to species by morphological means.

Summary of the Snowmastodon Project Special Volume: A high-elevation, multi-proxy biotic and environmental record of MIS 6-4 from the Ziegler Reservoir fossil site, Snowmass Village, Colorado, USA

In North America, terrestrial records of biodiversity and climate change that span Marine Oxygen Isotope Stage (MIS) 5 are rare. Where found, they provide insight into how the coupling of the ocean-atmosphere system is manifested in biotic and environmental records and how the biosphere responds to climate change. In 2010-2011, construction at Ziegler Reservoir near Snowmass Village, Colorado (USA) revealed a nearly continuous, lacustrine/wetland sedimentary sequence that preserved evidence of past plant communities between similar to 140 and 55 lea, including all of MIS 5. At an elevation of 2705 m, the Ziegler Reservoir fossil site also contained thousands of well-preserved bones of late Pleistocene megafauna, including mastodons, mammoths, ground sloths, horses, camels, deer, bison, black bear, coyotes, and bighorn sheep. In addition, the site contained more than 26,000 bones from at least 30 species of small animals including salamanders, otters, muskrats, minks, rabbits, beavers, frogs, lizards, snakes, fish, and birds. The combination of macro- and micro-vertebrates, invertebrates, terrestrial and aquatic plant macrofossils, a detailed pollen record, and a robust, directly dated stratigraphic framework shows that high-elevation ecosystems in the Rocky Mountains of Colorado are climatically sensitive and varied dramatically throughout MIS 5 

Seasonal variation in month of diagnosis in children with type 1 diabetes registered in 23 European centers during 1989-2008: little short-term influence of sunshine hours or average temperature

BACKGROUND: The month of diagnosis in childhood type 1 diabetes shows seasonal variation.

OBJECTIVE: We describe the pattern and investigate if year-to-year irregularities are associated with meteorological factors using data from 50 000 children diagnosed under the age of 15 yr in 23 population-based European registries during 1989-2008.

METHODS: Tests for seasonal variation in monthly counts aggregated over the 20 yr period were performed. Time series regression was used to investigate if sunshine hour and average temperature data were predictive of the 240 monthly diagnosis counts after taking account of seasonality and long term trends.

RESULTS: Significant sinusoidal pattern was evident in all but two small centers with peaks in November to February and relative amplitudes ranging from ±11 to ±38% (median ±17%). However, most centers showed significant departures from a sinusoidal pattern. Pooling results over centers, there was significant seasonal variation in each age-group at diagnosis, with least seasonal variation in those under 5 yr. Boys showed greater seasonal variation than girls, particularly those aged 10-14 yr. There were no differences in seasonal pattern between four 5-yr sub-periods. Departures from the sinusoidal trend in monthly diagnoses in the period were significantly associated with deviations from the norm in average temperature (0.8% reduction in diagnoses per 1 °C excess) but not with sunshine hours.

CONCLUSIONS: Seasonality was consistently apparent throughout the period in all age-groups and both sexes, but girls and the under 5 s showed less marked variation. Neither sunshine hour nor average temperature data contributed in any substantial way to explaining departures from the sinusoidal pattern.

Urban/rural variation in the influence of widowhood on mortality risk: a cohort study of almost 300,000 couples

Death of a spouse is associated with increased mortality risk for the surviving partner (the widowhood effect). We investigated whether the effect magnitude varied between urban, rural and intermediate areas, assembling death records (2001-2009) for a prospective cohort of 296,125 married couples in Northern Ireland. The effect was greatest during the first six months of widowhood in all areas and for both sexes. Subsequently, the effect was attenuated among men in rural and intermediate areas but persisted in urban areas (HRs and 95% CIs: rural 1.09 [0.99, 1.21]; urban 1.35 [1.26, 1.44]). Among women the effect was attenuated in all areas (rural 1.06 [0.96, 1.17]; urban 1.09 [1.01, 1.17]). The impacts of spousal bereavement varied between urban and more rural areas, possibly due to variation in social support provided by the wider community. We identify men in urban areas as being in greatest need of such support and a possible target for health interventions.

A new statistical framework for the quantification of covariate associations with species distributions

Identifying processes that shape species geographical ranges is a prerequisite for understanding environmental change. Currently, species distribution modelling methods do not offer credible statistical tests of the relative influence of climate factors and typically ignore other processes (e.g. biotic interactions and dispersal limitation). We use a hierarchical model fitted with Markov Chain Monte Carlo to combine ecologically plausible niche structures using regression splines to describe unimodal but potentially skewed response terms. We apply spatially explicit error terms that account for (and may help identify) missing variables. Using three example distributions of European bird species, we map model results to show sensitivity to change in each covariate. We show that the overall strength of climatic association differs between species and that each species has considerable spatial variation in both the strength of the climatic association and the sensitivity to climate change. Our methods are widely applicable to many species distribution modelling problems and enable accurate assessment of the statistical importance of biotic and abiotic influences on distributions.