Background and Purpose—Preclinical research using animals often informs clinical trials. However, its value is dependent on its scientific validity and reproducibility, which are, in turn, dependent on rigorous study design and reporting. In 2011, Stroke introduced a Basic Science Checklist to enhance the reporting and methodology of its preclinical studies. Except for Nature and Science journals, few others have implemented similar initiatives. We sought to estimate the impact of these journal interventions on the quality of their published reports.Methods—All articles published in Stroke, Nature Medicine, and Science Translational Medicine over 9 to 18 years and in 2 control journals without analogous interventions over a corresponding 11.5 years were reviewed to identify reports of experiments in nonhuman mammals with proposed clinical relevance. The effect of journal interventions on the reporting and use of key study design elements was estimated via interrupted time-series analyses.Results—Of 33 009 articles screened, 4162 studies met inclusion criteria. In the 3.5 to 12 years preceding each journal’s intervention, the proportions of studies reporting and using key study design elements were stable except for blinding in Stroke and randomization in Science Translational Medicine, which were both increasing. Post-intervention, abrupt and often marked increases were seen in the reporting of randomization status (level change: +17% to +44%, P≤0.005), blinding (level change: +20% to +40%, P≤0.008), and sample size estimation (level change: 0% to +40%, P≤0.002 in 2 journals). Significant but more modest improvements in the use of these study design elements were also observed. These improvements were not seen in control journals.Conclusions—Journal interventions such as Stroke’s author submission checklist can meaningfully improve the quality of published preclinical research and should be considered to enhance study transparency and design. However, such interventions are alone insufficient to fully address widespread shortcomings in preclinical research practices.

The structure of the course is designed to have students acquire a broad understanding of the field of Marine Chemistry; to get a feel for experimental methodologies, the results that they have generated and the theoretical insights they have yielded to date.

This lesson is part of Software Carpentry workshops and teach an introduction to plotting and programming using python. This lesson is an introduction to programming in Python for people with little or no previous programming experience. It uses plotting as its motivating example, and is designed to be used in both Data Carpentry and Software Carpentry workshops. This lesson references JupyterLab, but can be taught using a regular Python interpreter as well. Please note that this lesson uses Python 3 rather than Python 2.

Software Carpentry lesson on how to use the shell to navigate the filesystem and write simple loops and scripts. The Unix shell has been around longer than most of its users have been alive. It has survived so long because it’s a power tool that allows people to do complex things with just a few keystrokes. More importantly, it helps them combine existing programs in new ways and automate repetitive tasks so they aren’t typing the same things over and over again. Use of the shell is fundamental to using a wide range of other powerful tools and computing resources (including “high-performance computing” supercomputers). These lessons will start you on a path towards using these resources effectively.

We present a consensus-based checklist to improve and document the transparency of research reports in social and behavioural research. An accompanying online application allows users to complete the form and generate a report that they can submit with their manuscript or post to a public repository.