66 research outputs found

    The multifactorial role of the 3Rs in shifting the harm-benefit analysis in animal models of disease

    Get PDF
    AbstractEthics on animal use in science in Western society is based on utilitarianism, weighing the harms and benefits to the animals involved against those of the intended human beneficiaries. The 3Rs concept (Replacement, Reduction, Refinement) is both a robust framework for minimizing animal use and suffering (addressing the harms to animals) and a means of supporting high quality science and translation (addressing the benefits). The ambiguity of basic research performed early in the research continuum can sometimes make harm-benefit analysis more difficult since anticipated benefit is often an incremental contribution to a field of knowledge. On the other hand, benefit is much more evident in translational research aimed at developing treatments for direct application in humans or animals suffering from disease. Though benefit may be easier to define, it should certainly not be considered automatic. Issues related to model validity seriously compromise experiments and have been implicated as a major impediment in translation, especially in complex disease models where harms to animals can be intensified. Increased investment and activity in the 3Rs is delivering new research models, tools and approaches with reduced reliance on animal use, improved animal welfare, and improved scientific and predictive value

    Investigating the NPY/AgRP/GABA to GnRH neuron circuit in prenatally androgenized PCOS-like mice

    Get PDF
    Polycystic ovary syndrome (PCOS), the most common form of anovulatory infertility, is associated with altered signaling within the hormone-sensitive neuronal network that regulates gonadotropin-releasing hormone (GnRH) neurons, leading to a pathological increase in GnRH secretion. Circuit remodeling is evident between GABAergic neurons in the arcuate nucleus (ARN) and GnRH neurons in a murine model of PCOS. One-third of ARN GABA neurons co-express neuropeptide Y (NPY), which has a known yet complex role in regulating GnRH neurons and reproductive function. Here, we investigated whether the NPY-expressing subpopulation (NPYARN) of ARN GABA neurons (GABAARN) is also affected in prenatally androgenized (PNA) PCOS-like NPYARN reporter mice [Agouti-related protein (AgRP)-Cre;τGFP]. PCOS-like mice and controls were generated by exposure to di-hydrotestosterone or vehicle (VEH) in late gestation. τGFP-expressing NPYARN neuron fiber appositions with GnRH neurons and gonadal steroid hormone receptor expression in τGFP-expressing NPYARN neurons were assessed using confocal microscopy. Although GnRH neurons received abundant close contacts from τGFP-expressing NPYARN neuron fibers, the number and density of putative inputs was not affected by prenatal androgen excess. NPYARN neurons did not co-express progesterone receptor or estrogen receptor α in either PNA or VEH mice. However, the proportion of NPYARN neurons co-expressing the androgen receptor was significantly elevated in PNA mice. Therefore, NPYARN neurons are not remodeled by prenatal androgen excess like the wider GABAARN population, indicating GABA-to-GnRH neuron circuit remodeling occurs in a presently unidentified non-NPY/AgRP population of GABAARN neurons. NPYARN neurons do, however, show independent changes in the form of elevated androgen sensitivity

    Born in Bradford's Better Start: an experimental birth cohort study to evaluate the impact of early life interventions.

    Get PDF
    BACKGROUND: Early interventions are recognised as key to improving life chances for children and reducing inequalities in health and well-being, however there is a paucity of high quality research into the effectiveness of interventions to address childhood health and development outcomes. Planning and implementing standalone RCTs for multiple, individual interventions would be slow, cumbersome and expensive. This paper describes the protocol for an innovative experimental birth cohort: Born in Bradford's Better Start (BiBBS) that will simultaneously evaluate the impact of multiple early life interventions using efficient study designs. Better Start Bradford (BSB) has been allocated £49 million from the Big Lottery Fund to implement 22 interventions to improve outcomes for children aged 0-3 in three key areas: social and emotional development; communication and language development; and nutrition and obesity. The interventions will be implemented in three deprived and ethnically diverse inner city areas of Bradford. METHOD: The BiBBS study aims to recruit 5000 babies, their mothers and their mothers' partners over 5 years from January 2016-December 2020. Demographic and socioeconomic information, physical and mental health, lifestyle factors and biological samples will be collected during pregnancy. Parents and children will be linked to their routine health and local authority (including education) data throughout the children's lives. Their participation in BSB interventions will also be tracked. BiBBS will test interventions using the Trials within Cohorts (TwiCs) approach and other quasi-experimental designs where TwiCs are neither feasible nor ethical, to evaluate these early life interventions. The effects of single interventions, and the cumulative effects of stacked (multiple) interventions on health and social outcomes during the critical early years will be measured. DISCUSSION: The focus of the BiBBS cohort is on intervention impact rather than observation. As far as we are aware BiBBS is the world's first such experimental birth cohort study. While some risk factors for adverse health and social outcomes are increasingly well described, the solutions to tackling them remain elusive. The novel design of BiBBS can contribute much needed evidence to inform policy makers and practitioners about effective approaches to improve health and well-being for future generations

    Special Low Protein Foods Prescribed in England for PKU Patients: An Analysis of Prescribing Patterns and Cost.

    Get PDF
    Patients with phenylketonuria (PKU) are reliant on special low protein foods (SLPFs) as part of their dietary treatment. In England, several issues regarding the accessibility of SLPFs through the national prescribing system have been highlighted. Therefore, prescribing patterns and expenditure on all SLPFs available on prescription in England (n = 142) were examined. Their costs in comparison to regular protein-containing (n = 182) and 'free-from' products (n = 135) were also analysed. Similar foods were grouped into subgroups (n = 40). The number of units and costs of SLPFs prescribed in total and per subgroup from January to December 2020 were calculated using National Health Service (NHS) Business Service Authority (NHSBSA) ePACT2 (electronic Prescribing Analysis and Cost Tool) for England. Monthly patient SLPF units prescribed were calculated using patient numbers with PKU and non-PKU inherited metabolic disorders (IMD) consuming SLPFs. This was compared to the National Society for PKU (NSPKU) prescribing guidance. Ninety-eight percent of SLPF subgroups (n = 39/40) were more expensive than regular and 'free-from' food subgroups. However, costs to prescribe SLPFs are significantly less than theoretical calculations. From January to December 2020, 208,932 units of SLPFs were prescribed (excluding milk replacers), costing the NHS £2,151,973 (including milk replacers). This equates to £962 per patient annually, and prescribed amounts are well below the upper limits suggested by the NSPKU, indicating under prescribing of SLPFs. It is recommended that a simpler and improved system should be implemented. Ideally, specialist metabolic dietitians should have responsibility for prescribing SLPFs. This would ensure that patients with PKU have the necessary access to their essential dietary treatment, which, in turn, should help promote dietary adherence and improve metabolic control

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

    Get PDF
    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

    Large expert-curated database for benchmarking document similarity detection in biomedical literature search

    Get PDF
    Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe
    corecore