Radio Feature (5 Min) von Hellmuth Norwig im SWR zur Ungleichverteilung der Geschlechter bei Tierexperimenten. Sie sind überwiegend männlichen Geschlechts, in den wenigsten Fällen orientiert sich das verwendete Geschlecht an der Geschlechterverteilung der Erkrankung beim Menschen.
Based on research, mainly in rodents, tremendous progress has been made in our basic understanding of the pathophysiology of stroke. After many failures, however, few scientists today deny that bench-to-bedside translation in stroke has a disappointing track record. I here summarize many measures to improve the predictiveness of preclinical stroke research, some of which are currently in various stages of implementation: We must reduce preventable (detrimental) attrition. Key measures for this revolve around improving preclinical study design. Internal validity must be improved by reducing bias; external validity will improve by including aged, comorbid rodents of both sexes in our modeling. False-positives and inflated effect sizes can be reduced by increasing statistical power, which necessitates increasing group sizes. Compliance to reporting guidelines and checklists needs to be enforced by journals and funders. Customizing study designs to exploratory and confirmatory studies will leverage the complementary strengths of both modes of investigation. All studies should publish their full data sets. On the other hand, we should embrace inevitable NULL results. This entails planning experiments in such a way that they produce high-quality evidence when NULL results are obtained and making these available to the community. A collaborative effort is needed to implement some of these recommendations. Just as in clinical medicine, multicenter approaches help to obtain sufficient group sizes and robust results. Translational stroke research is not broken, but its engine needs an overhauling to render more predictive results.
Read the full article at the Publishers site (STROKE/AHA). If your library does not have a subscription, here is the Authors Manuscript (Stroke/AHA did not allow me to even pay for open access, as it is ‘a special article…’).
Recently, NIH Scientists B. Ian Hutchins and colleagues have (pre)published “The Relative Citation Ratio (RCR). A new metric that uses citation rates to measure influence at the article level”. [Note added 9.9.2016: A peer reviewed version of the article has now appeared in PLOS Biol]. Just as Stefano Bertuzzi, the Executive Director of the American Society for Cell Biology, I am enthusiastic about the RCR. The RCR appears to be a viable alternative to the widely (ab)used Journal Impact Factor (JIF).
The RCR has been recently discussed in several blogs and editorials (e.g. NIH metric that assesses article impact stirs debate; NIH’s new citation metric: A step forward in quantifying scientific impact? ). At a recent workshop organized by the National Library of Medicine (NLM) I learned that the NIH is planning to widely use the RCR in its own grant assessments as an antidote to JIF, raw article citations, h-factors, and other highly problematic or outright flawed metrics. Continue reading
Microbiota and its contribution to brain function and diseases has become a hot topic in neuroscience. In this article in the Journal of Cerebral Blood Flow and Metabolism we discuss the emerging role of commensal bacteria in the course of stroke. Further, we review potential pitfalls in microbiota research and their impact on how we interpret the available evidence, emerging results, and on how we design future studies
Every professional doing active research in the life sciences is required to keep a laboratory notebook. However, while science has changed dramatically over the last centuries, laboratory notebooks have remained essentially unchanged since pre-modern science. In an article published in F1000Research, an open access post-publication immediate publication platform, we argue that the implementation of electronic laboratory notebooks (eLN) in academic research is overdue, and we provide researchers and their institutions with the background and practical knowledge to select and initiate the implementation of an eLN in their laboratories. In addition, we present data from surveying biomedical researchers and technicians regarding which hypothetical features and functionalities they hope to see implemented in an eLN, and which ones they regard less important. We also present data on acceptance and satisfaction of those who have recently switched from paper laboratory notebook to an eLN. We thus provide answers to the following questions: What does an electronic laboratory notebook afford a biomedical researcher, what does it require, and how should one go about implementing it? Read the full article