Response of littoral chironomid community and organic matter to late glacial lake level and environmental changes at Lago dell'Accesa (Tuscany, Italy).

International audienceThis study focuses on the response of lacustrine littoral chironomid communities to late glacial changes in limnological, environmental and climate conditions in the Mediterranean context. Late glacial chironomid (Diptera: Chironomidae) assemblages, organic petrography and geochemistry were analysed in a sediment core from the littoral zone of Lago dell'Accesa (Tuscany, Italy), where the lake-level fluctuations and the vegetation history have been previously reconstructed. Comparison of the chironomid stratigraphy to other proxies (pollen assemblages, organic petrography and geochemistry, lake-level) and regional climate reconstruction suggested the predominant influence of lake-level changes on the littoral chironomid fauna. The main lowering events that occurred during the Oldest and the Younger Dryas were followed by higher proportions of taxa typical of littoral habitats. A complementary study of organic matter suggested the indirect impact of lake-level on the chironomids through changes in humic status and habitat characteristics, such as the type of substrate and aquatic macrophyte development. Several chironomid taxa, such as Glyptotendipes, Microtendipes and Cricotopus type patens, were identified as possible indicators of low lake-level in the late glacial records. Nevertheless, this study suggested that parallel analyses of organic matter and chironomid assemblages may be needed to circumvent misinterpretation of littoral chironomid assemblage stratigraphy. There was a weak response of the chironomid assemblages to small lake-level lowerings that corresponded to the Older Dryas and Preboreal oscillations. A higher level of determination, e.g. to the species group level, may be necessary to increase the sensibility of the indicators to lake-level changes

The use of discrete choice experiments to inform health workforce policy: a systematic review.

BACKGROUND: Discrete choice experiments have become a popular study design to study the labour market preferences of health workers. Discrete choice experiments in health, however, have been criticised for lagging behind best practice and there are specific methodological considerations for those focused on job choices. We performed a systematic review of the application of discrete choice experiments to inform health workforce policy. METHODS: We searched for discrete choice experiments that examined the labour market preferences of health workers, including doctors, nurses, allied health professionals, mid-level and community health workers. We searched Medline, Embase, Global Health, other databases and grey literature repositories with no limits on date or language and contacted 44 experts. Features of choice task and experimental design, conduct and analysis of included studies were assessed against best practice. An assessment of validity was undertaken for all studies, with a comparison of results from those with low risk of bias and a similar objective and context. RESULTS: Twenty-seven studies were included, with over half set in low- and middle-income countries. There were more studies published in the last four years than the previous ten years. Doctors or medical students were the most studied cadre. Studies frequently pooled results from heterogeneous subgroups or extrapolated these results to the general population. Only one third of studies included an opt-out option, despite all health workers having the option to exit the labour market. Just five studies combined results with cost data to assess the cost effectiveness of various policy options. Comparison of results from similar studies broadly showed the importance of bonus payments and postgraduate training opportunities and the unpopularity of time commitments for the uptake of rural posts. CONCLUSIONS: This is the first systematic review of discrete choice experiments in human resources for health. We identified specific issues relating to this application of which practitioners should be aware to ensure robust results. In particular, there is a need for more defined target populations and increased synthesis with cost data. Research on a wider range of health workers and the generalisability of results would be welcome to better inform policy

Predicting Bison Migration out of Yellowstone National Park Using Bayesian Models

Long distance migrations by ungulate species often surpass the boundaries of preservation areas where conflicts with various publics lead to management actions that can threaten populations. We chose the partially migratory bison (Bison bison) population in Yellowstone National Park as an example of integrating science into management policies to better conserve migratory ungulates. Approximately 60% of these bison have been exposed to bovine brucellosis and thousands of migrants exiting the park boundary have been culled during the past two decades to reduce the risk of disease transmission to cattle. Data were assimilated using models representing competing hypotheses of bison migration during 1990–2009 in a hierarchal Bayesian framework. Migration differed at the scale of herds, but a single unifying logistic model was useful for predicting migrations by both herds. Migration beyond the northern park boundary was affected by herd size, accumulated snow water equivalent, and aboveground dried biomass. Migration beyond the western park boundary was less influenced by these predictors and process model performance suggested an important control on recent migrations was excluded. Simulations of migrations over the next decade suggest that allowing increased numbers of bison beyond park boundaries during severe climate conditions may be the only means of avoiding episodic, large-scale reductions to the Yellowstone bison population in the foreseeable future. This research is an example of how long distance migration dynamics can be incorporated into improved management policies

Metabolomic analysis of human disease and its application to the eye

Metabolomics, the analysis of the metabolite profile in body fluids or tissues, is being applied to the analysis of a number of different diseases as well as being used in following responses to therapy. While genomics involves the study of gene expression and proteomics the expression of proteins, metabolomics investigates the consequences of the activity of these genes and proteins. There is good reason to think that metabolomics will find particular utility in the investigation of inflammation, given the multi-layered responses to infection and damage that are seen. This may be particularly relevant to eye disease, which may have tissue specific and systemic components. Metabolomic analysis can inform us about ocular or other body fluids and can therefore provide new information on pathways and processes involved in these responses. In this review, we explore the metabolic consequences of disease, in particular ocular conditions, and why the data may be usefully and uniquely assessed using the multiplexed analysis inherent in the metabolomic approach

Recommendations for Bioinformatics in Clinical Practice

Abstract Next Generation Sequencing (NGS) is increasingly used in clinical diagnostics, largely driven by the success and robustness of Whole Genome Sequencing (WGS). Whereas updated guidelines exist for how to interpret and report on variants that are identified from NGS using bioinformatics pipelines, there is a need for standardised bioinformatics practices for diagnostics to ensure clinical consensus, accuracy, reproducibility and comparability of the results. This article presents consensus recommendations developed by 13 clinical bioinformatics units taking part in the Nordic Alliance for Clinical Genomics (NACG), by expert bioinformaticians working in clinical production. The recommendations are based on clinical practice and focus on analysis types, test and validation, standardisation and accreditation, as well as core competencies and technical management required for clinical bioinformatics operations. Key recommendations include adopting the hg38 genome build as the reference and a standard set of recommended analyses, including the use of multiple tools for structural variant (SV) calling and in-house data sets for filtering recurrent calls. Clinical bioinformatics production should operate under the ISO 15189 standard, utilising off-grid clinical-grade high-performance computing systems, standardised file formats, and strict code version control. Containerized software containers or environment management systems are needed to ensure reproducibility. Pipelines should be rigorously documented and tested for accuracy and reproducibility, minimally covering unit, integration, and end-to-end testing. Standard truth sets such as GIAB and SEQC2 for germline and somatic variant calling, respectively, should be supplemented by recall testing of previously validated clinical cases. Data integrity must be verified using file hashing, and sample identity should be checked via sample fingerprinting and genetically inferred identification markers such as sex and relatedness. Finally, clinical bioinformatics teams should encompass diverse skills, including software development, data management, quality assurance, and domain expertise in human genetics. These recommendations provide a consensus framework for standardising bioinformatics practices across clinical WGS applications and can serve as a practical guide to facilities that are new to large-scale sequencing-based diagnostics, or as a reference for those who already run high-volume clinical production using NGS

Influences of mating group composition on the behavioral time-budget of male and female Alpine Ibex (Capra ibex) during the rut.

During the rut, polygynous ungulates gather in mixed groups of individuals of different sex and age. Group social composition, which may vary on a daily basis, is likely to have strong influences on individual's time-budget, with emerging properties at the group-level. To date, few studies have considered the influence of group composition on male and female behavioral time budget in mating groups. Focusing on a wild population of Alpine ibex, we investigated the influence of group composition (adult sex ratio, the proportion of dominant to subordinate males, and group size) on three behavioral axes obtained by Principal Components Analysis, describing male and female group time-budget. For both sexes, the first behavioral axis discerned a trade-off between grazing and standing/vigilance behavior. In females, group vigilance behavior increased with increasingly male-biased sex ratio, whereas in males, the effect of adult sex ratio on standing/vigilance behavior depended on the relative proportion of dominant males in the mating group. The second axis characterized courtship and male-male agonistic behavior in males, and moving and male-directed agonistic behavior in females. Mating group composition did not substantially influence this axis in males. However, moving and male-directed agonistic behavior increased at highly biased sex ratios (quadratic effect) in females. Finally, the third axis highlighted a trade-off between moving and lying behavior in males, and distinguished moving and female-female agonistic behavior from lying behavior in females. For males, those behaviors were influenced by a complex interaction between group size and adult sex ratio, whereas in females, moving and female-female agonistic behaviors increased in a quadratic fashion at highly biased sex ratios, and also increased with increasing group size. Our results reveal complex behavioral trade-offs depending on group composition in the Alpine ibex, and emphasize the importance of social factors in influencing behavioral time-budgets of wild ungulates during the rut