Show and tell: disclosure and data sharing in experimental pathology

Reproducibility of data from experimental investigations using animal models is increasingly under scrutiny because of the potentially negative impact of poor reproducibility on the translation of basic research. Histopathology is a key tool in biomedical research, in particular for the phenotyping of animal models to provide insights into the pathobiology of diseases. Failure to disclose and share crucial histopathological experimental details compromises the validity of the review process and reliability of the conclusions. We discuss factors that affect the interpretation and validation of histopathology data in publications and the importance of making these data accessible to promote replicability in research.

Springer Nature is Introducing a Standardized Set of Research Data Sharing Policies

We want to enable our authors to publish the best research and maximize the benefit of research funding, which includes achieving good practice in the sharing and archiving of research data. We also aim to facilitate authors’ compliance with institution and research funder requirements to share data. Encourage publication of more open and reproducible research.

MRI software bugs could upend years of research

A whole pile of "this is how your brain looks like" MRI-based science has been invalidated because someone finally got around to checking the data. The problem is simple: to get from a high-resolution magnetic resonance imaging scan of the brain to a scientific conclusion, the brain is divided into tiny "voxels." Software, rather than humans, then scans the voxels looking for clusters. In this paper at PNAS, they write: "the most common software packages for fMRI analysis (SPM, FSL, AFNI) can result in false-positive rates of up to 70%. These results question the validity of some 40,000 fMRI studies and may have a large impact on the interpretation of neuroimaging results."

Biomedical researchers lax about validating antibodies for experiments

Nearly one-third of junior scientists spend no time validating antibodies, even though accurate results depend on these reagents working as expected, according to the results of a survey reported today in BioTechniques. "This is quite alarming," says Matthias Uhlén, a protein researcher at the Royal Institute of Technology in Stockholm who heads an international working group on antibody validation, but who was not directly involved in the survey.

Can Robots Help Solve the Reproducibility Crisis?

In recent years, there’s been increasing awareness of a problem across many scientific fields—the problem of reproducibility. Can experiments be repeated (or "reproduced") to arrive at the same result? Evidence is piling up that the answer, all too often, is no. This makes it difficult to know which results we can confidently rely on, and which are spurious.