A manifesto for reproducible science

Improving the reliability and efficiency of scientific research will increase the credibility of the published scientific literature and accelerate discovery. Here we argue for the adoption of measures to optimize key elements of the scientific process: methods, reporting and dissemination, reproducibility, evaluation and incentives. There is some evidence from both simulations and empirical studies supporting the likely effectiveness of these measures, but their broad adoption by researchers, institutions, funders and journals will require iterative evaluation and improvement. We discuss the goals of these measures, and how they can be implemented, in the hope that this will facilitate action toward improving the transparency, reproducibility and efficiency of scientific research

Differential hypoglycaemic, anorectic, autonomic and emetic effects of the glucagon-like peptide receptor agonist, exendin-4, in the conscious telemetered ferret.

Background: Rodents are incapable of emesis and consequently the emetic potential of glucagon-like peptide-1 receptor (GLP-1R) agonists in studies designed to assess a potential blood glucose lowering action of the compound was missed. Therefore, we investigated if the ferret, a carnivore with demonstrated translation capability in emesis research, would identify the emetic potential of the GLP-1R agonist, exendin-4, and any associated effects on gastric motor function, appetite and cardiovascular homeostasis. Methods: The biological activity of the GLP-1R ligands was investigated in vivo using a glucose tolerance test in pentobarbitone-anesthetised ferrets and in vitro using organ bath studies. Radiotelemetry was used to investigate the effect of exendin-4 on gastric myoelectric activity (GMA) and cardiovascular function in conscious ferrets; behaviour was also simultaneously assessed. Western blot was used to characterize GLP-1R distribution in the gastrointestinal and brain tissues. Results: In anesthetised ferrets, exendin-4 (30 nmol/kg, s.c.) reduced experimentally elevated blood glucose levels by 36.3%, whereas the GLP-1R antagonist, exendin (9–39) (300 nmol/kg, s.c.) antagonised the effect and increased AUC0–120 by 31.0% when injected alone (P < 0.05). In animals with radiotelemetry devices, exendin-4 (100 nmol/kg, s.c.) induced emesis in 1/9 ferrets, but inhibited food intake and decreased heart rate variability (HRV) in all animals (P < 0.05). In the animals not exhibiting emesis, there was no effect on GMA, mean arterial blood pressure, heart rate, or core body temperature. In the ferret exhibiting emesis, there was a shift in the GMA towards bradygastria with a decrease in power, and a concomitant decrease in HRV. Western blot revealed GLP-1R throughout the gastrointestinal tract but exendin-4 (up to 300 nM) and exendin (9–39), failed to contract or relax isolated ferret gut tissues. GLP-1R were found in all major brain regions and the levels were comparable those in the vagus nerve. Conclusions: Peripherally administered exendin-4 reduced blood glucose and inhibited feeding with a low emetic potential similar to that in humans (11% vs 12.8%). A disrupted GMA only occurred in the animal exhibiting emesis raising the possibility that disruption of the GMA may influence the probability of emesis occurring in response to treatment with GLP-1R agonists

Reporting animal research:Explanation and elaboration for the ARRIVE guidelines 2.0

Improving the reproducibility of biomedical research is a major challenge. Transparent and accurate reporting is vital to this process; it allows readers to assess the reliability of the findings and repeat or build upon the work of other researchers. The ARRIVE guidelines (Animal Research: Reporting In Vivo Experiments) were developed in 2010 to help authors and journals identify the minimum information necessary to report in publications describing in vivo experiments. Despite widespread endorsement by the scientific community, the impact of ARRIVE on the transparency of reporting in animal research publications has been limited. We have revised the ARRIVE guidelines to update them and facilitate their use in practice. The revised guidelines are published alongside this paper. This explanation and elaboration document was developed as part of the revision. It provides further information about each of the 21 items in ARRIVE 2.0, including the rationale and supporting evidence for their inclusion in the guidelines, elaboration of details to report, and examples of good reporting from the published literature. This document also covers advice and best practice in the design and conduct of animal studies to support researchers in improving standards from the start of the experimental design process through to publication

The IMPROVE guidelines (Ischaemia Models: Procedural Refinements Of in Vivo Experiments)

Most in vivo models of ischaemic stroke target the middle cerebral artery and a spectrum of stroke severities, from mild to substantial, can be achieved. This review describes opportunities to improve the in vivo modelling of ischaemic stroke and animal welfare. It provides a number of recommendations to minimise the level of severity in the most common rodent models of middle cerebral artery occlusion, while sustaining or improving the scientific outcomes. The recommendations cover basic requirements pre-surgery, selecting the most appropriate anaesthetic and analgesic regimen, as well as intraoperative and post-operative care. The aim is to provide support for researchers and animal care staff to refine their procedures and practices, and implement small incremental changes to improve the welfare of the animals used and to answer the scientific question under investigation. All recommendations are recapitulated in a summary poster (see supplementary information)

Building a Systematic Online Living Evidence Summary of COVID-19 Research

Throughout the global coronavirus pandemic, we have seen an unprecedented volume of COVID-19 researchpublications. This vast body of evidence continues to grow, making it difficult for research users to keep up with the pace of evolving research findings. To enable the synthesis of this evidence for timely use by researchers, policymakers, and other stakeholders, we developed an automated workflow to collect, categorise, and visualise the evidence from primary COVID-19 research studies. We trained a crowd of volunteer reviewers to annotate studies by relevance to COVID-19, study objectives, and methodological approaches. Using these human decisions, we are training machine learning classifiers and applying text-mining tools to continually categorise the findings and evaluate the quality of COVID-19 evidence