Development of an acute ovine model of polycystic ovaries to assess the effect of ovarian denervation

Introduction: Polycystic ovary syndrome (PCOS) seems to be associated with increased ovarian sympathetic nerve activity and in rodent models of PCOS reducing the sympathetic drive to the ovary, through denervation or neuromodulation, improves ovulation rate. We hypothesised that sympathetic nerves work with gonadotropins to promote development and survival of small antral follicles to develop a polycystic ovary phenotype.Methods: Using a clinically realistic ovine model we showed a rich sympathetic innervation to the normal ovary and reinnervation after ovarian transplantation. Using needlepoint diathermy to the nerve plexus in the ovarian vascular pedicle we were able to denervate the ovary resulting in reduced intraovarian noradrenaline and tyrosine hydroxylase immunostained sympathetic nerves. We developed an acute polycystic ovary (PCO) model using gonadotrophin releasing hormone (GnRH) agonist followed infusion of follicle stimulating hormone (FSH) with increased pulsatile luteinising hormone (LH). This resulted in increased numbers of smaller antral follicles in the ovary when compared to FSH infusion suggesting a polycystic ovary.Results: Denervation had no effect of the survival or numbers of follicles in the acute PCO model and did not impact on ovulation, follicular and luteal hormone profiles in a normal cycle.Discussion: Although the ovary is richly inervated we did not find evidence for a role of sympathetic nerves in ovarian function or small follicle growth and surviva

Ocean ecosystem-based management mandates and implementation in the North Atlantic

Ecosystem-based management (EBM) necessarily requires a degree of coordination across countries that share ocean ecosystems, and among national agencies and departments that have responsibilities relating to ocean health and marine resource utilization. This requires political direction, legal input, stakeholder consultation and engagement, and complex negotiations. Currently there is a common perception that within and across national jurisdictions there is excessive legislative complexity, a relatively low level of policy coherence or alignment with regards to ocean and coastal EBM, and that more aligned legislation is needed to accelerate EBM adoption. Our Atlantic Ocean Research Alliance (AORA) task group was comprised of a small, focused and interdisciplinary mix of lawyers, social scientists, and natural scientists from Canada, the USA, and the EU. We characterized, compared, and synthesized the mandates that govern marine activities and ocean stressors relative to facilitating EBM in national and international waters of the North Atlantic, and identified formal mandates across jurisdictions and, where possible, policy and other non-regulatory mandates. We found that irrespective of the detailed requirements of legislation or policy across AORA jurisdictions, or the efficacy of their actual implementation, most of the major ocean pressures and uses posing threats to ocean sustainability have some form of coverage by national or regional legislation. The coverage is, in fact, rather comprehensive. Still, numerous impediments to effective EBM implementation arise, potentially relating to the lack of integration between agencies and departments, a lack of adequate policy alignment, and a variety of other socio-political factors. We note with concern that if challenges regarding EBM implementation exist in the North Atlantic, we can expect that in less developed regions where financial and governance capacity may be lower, that implementation of EBM could be even more challenging

Vulnerability to climate change of managed stocks in the California Current large marine ecosystem

Introduction: Understanding how abundance, productivity and distribution of individual species may respond to climate change is a critical first step towards anticipating alterations in marine ecosystem structure and function, as well as developing strategies to adapt to the full range of potential changes. Methods: This study applies the NOAA (National Oceanic and Atmospheric Administration) Fisheries Climate Vulnerability Assessment method to 64 federally-managed species in the California Current Large Marine Ecosystem to assess their vulnerability to climate change, where vulnerability is a function of a species’ exposure to environmental change and its biological sensitivity to a set of environmental conditions, which includes components of its resiliency and adaptive capacity to respond to these new conditions. Results: Overall, two-thirds of the species were judged to have Moderate or greater vulnerability to climate change, and only one species was anticipated to have a positive response. Species classified as Highly or Very Highly vulnerable share one or more characteristics including: 1) having complex life histories that utilize a wide range of freshwater and marine habitats; 2) having habitat specialization, particularly for areas that are likely to experience increased hypoxia; 3) having long lifespans and low population growth rates; and/or 4) being of high commercial value combined with impacts from non-climate stressors such as anthropogenic habitat degradation. Species with Low or Moderate vulnerability are either habitat generalists, occupy deep-water habitats or are highly mobile and likely to shift their ranges. Discussion: As climate-related changes intensify, this work provides key information for both scientists and managers as they address the long-term sustainability of fisheries in the region. This information can inform near-term advice for prioritizing species-level data collection and research on climate impacts, help managers to determine when and where a precautionary approach might be warranted, in harvest or other management decisions, and help identify habitats or life history stages that might be especially effective to protect or restore

A high-resolution map of human evolutionary constraint using 29 mammals.

The comparison of related genomes has emerged as a powerful lens for genome interpretation. Here we report the sequencing and comparative analysis of 29 eutherian genomes. We confirm that at least 5.5% of the human genome has undergone purifying selection, and locate constrained elements covering ∼4.2% of the genome. We use evolutionary signatures and comparisons with experimental data sets to suggest candidate functions for ∼60% of constrained bases. These elements reveal a small number of new coding exons, candidate stop codon readthrough events and over 10,000 regions of overlapping synonymous constraint within protein-coding exons. We find 220 candidate RNA structural families, and nearly a million elements overlapping potential promoter, enhancer and insulator regions. We report specific amino acid residues that have undergone positive selection, 280,000 non-coding elements exapted from mobile elements and more than 1,000 primate- and human-accelerated elements. Overlap with disease-associated variants indicates that our findings will be relevant for studies of human biology, health and disease

Localization of type 1 diabetes susceptibility to the MHC class I genes HLA-B and HLA-A

The major histocompatibility complex (MHC) on chromosome 6 is associated with susceptibility to more common diseases than any other region of the human genome, including almost all disorders classified as autoimmune. In type 1 diabetes the major genetic susceptibility determinants have been mapped to the MHC class II genes HLA-DQB1 and HLA-DRB1 (refs 1-3), but these genes cannot completely explain the association between type 1 diabetes and the MHC region. Owing to the region's extreme gene density, the multiplicity of disease-associated alleles, strong associations between alleles, limited genotyping capability, and inadequate statistical approaches and sample sizes, which, and how many, loci within the MHC determine susceptibility remains unclear. Here, in several large type 1 diabetes data sets, we analyse a combined total of 1,729 polymorphisms, and apply statistical methods - recursive partitioning and regression - to pinpoint disease susceptibility to the MHC class I genes HLA-B and HLA-A (risk ratios >1.5; Pcombined = 2.01 × 10-19 and 2.35 × 10-13, respectively) in addition to the established associations of the MHC class II genes. Other loci with smaller and/or rarer effects might also be involved, but to find these, future searches must take into account both the HLA class II and class I genes and use even larger samples. Taken together with previous studies, we conclude that MHC-class-I-mediated events, principally involving HLA-B*39, contribute to the aetiology of type 1 diabetes. ©2007 Nature Publishing Group

Using formative assessment to influence self- and co-regulated learning: the role of evaluative judgement

Recently, the concept of evaluative judgement has gained attention as a pedagogical approach to classroom formative assessment practices. Evaluative judgement is the capacity to be able to judge the work of oneself and that of others, which implies developing knowledge about one’s own assessment capability. A focus on evaluative judgement helps us to better understand what is the influence of assessment practices in the regulation of learning. In this paper, we link evaluative judgement to two self-regulated learning models (Zimmerman and Winne) and present a model on the effects on co-regulation of learning. The models help us to understand how students can be self-regulated through developing their evaluative judgement. The co-regulation model visualises how the learner can become more strategic in this process through teacher and peer assessment in which assessment knowledge and regulation strategies are shared with the learner. The connections we make here are crucial to strengthening our understanding of the influence of assessment practices on students’ learnin

Evidence-based Kernels: Fundamental Units of Behavioral Influence

This paper describes evidence-based kernels, fundamental units of behavioral influence that appear to underlie effective prevention and treatment for children, adults, and families. A kernel is a behavior–influence procedure shown through experimental analysis to affect a specific behavior and that is indivisible in the sense that removing any of its components would render it inert. Existing evidence shows that a variety of kernels can influence behavior in context, and some evidence suggests that frequent use or sufficient use of some kernels may produce longer lasting behavioral shifts. The analysis of kernels could contribute to an empirically based theory of behavioral influence, augment existing prevention or treatment efforts, facilitate the dissemination of effective prevention and treatment practices, clarify the active ingredients in existing interventions, and contribute to efficiently developing interventions that are more effective. Kernels involve one or more of the following mechanisms of behavior influence: reinforcement, altering antecedents, changing verbal relational responding, or changing physiological states directly. The paper describes 52 of these kernels, and details practical, theoretical, and research implications, including calling for a national database of kernels that influence human behavior