Search

Effective sharing of experimental methods is crucial to ensuring that others can repeat results. An abundance of tools is available to help. Effective sharing of experimental methods is crucial to ensuring that others can repeat results. An abundance of tools is available to help.

Chemical probes and screening libraries can easily get mixed up or messed up, causing misleading results for unwary biologists.

Research antibodies don’t always do what it says on the tin. Test for true signals before you start your experiment. Research antibodies don’t always do what it says on the tin. Test for true signals before you start your experiment.

Additional file 4. Road testing methods and results. Methodology used to road test the revised ARRIVE guidelines and E&E (as published in preprint) and how this information was used in the development of ARRIVE 2.0.

Additional file 1. Noteworthy changes in ARRIVE 2.0. This table recapitulates noteworthy changes in the ARRIVE guidelines 2.0, compared to the original ARRIVE guidelines published in 2010.

Additional file 2. Delphi methods and results. Methodology and results of the Delphi study that was used to prioritise the items of the guidelines into the ARRIVE Essential 10 and Recommended Set.

Reproducible science requires transparent reporting. The ARRIVE guidelines were originally developed in 2010 to improve the reporting of animal research. They consist of a checklist of information to include in publications describing in vivo experiments to enable others to scrutinise the work adequately, evaluate its methodological rigour, and reproduce the methods and results. Despite considerable levels of endorsement by funders and journals over the years, adherence to the guidelines has been inconsistent, and the anticipated improvements in the quality of reporting in animal research publications have not been achieved.Here we introduce ARRIVE 2019. The guidelines have been updated and information reorganised to facilitate their use in practice. We used a Delphi exercise to prioritise the items and split the guidelines into two sets, the ARRIVE Essential 10, which constitute the minimum requirement, and the Recommended Set, which describes the research context. This division facilitates improved reporting of animal research by supporting a stepwise approach to implementation. This helps journal editors and reviewers to verify that the most important items are being reported in manuscripts. We have also developed the accompanying Explanation and Elaboration document that serves 1) to explain the rationale behind each item in the guidelines, 2) to clarify key concepts and 3) to provide illustrative examples. We aim through these changes to help ensure that researchers, reviewers and journal editors are better equipped to improve the rigour and transparency of the scientific process and thus reproducibility.

Improving the reproducibility of biomedical research is a major challenge. Transparent and accurate reporting are 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 NC3Rs developed the ARRIVE guidelines 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 the ARRIVE guidelines 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 2019, 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.

As the imaging technique produces ever-sharper protein structures, researchers are racing to develop tools to assess how accurate they are. As the imaging technique produces ever-sharper protein structures, researchers are racing to develop tools to assess how accurate they are.

Some advocates are betting that documenting experimental plans online will improve animal research, but uptake has been slow. Some advocates are betting that documenting experimental plans online will improve animal research, but uptake has been slow.

Antibodies used in research often give murky results. Broader awareness and advanced technologies promise clarity.

Programming tools can speed up and strengthen analyses, but mastering the skills takes time and can be daunting.

In 2010, the NC3Rs published the Animal Research:Reporting of In Vivo Experiments (ARRIVE) guidelinesto improve the reporting of animal research. Despiteconsiderable levels of support from the scientific community,the impact on the quality of reporting in animal researchpublications has been limited. This position paper highlightsthe strategy of an expert working group established torevise the guidelines and facilitate their uptake. The group’sinitial work will focus on three main areas: prioritisationof the ARRIVE items into a tiered system, development ofan explanation and elaboration document, and revision ofspecific items.

A look at some of the most innovative science-education programmes from kindergarten to university.

Antibodies are the workhorses of biological experiments, but they are littering the field with false findings. A few evangelists are pushing for change.

This study documents reporting errors in a sample of over 250,000 p-values reported in eight major psychology journals from 1985 until 2013, using the new R package “statcheck.” statcheck retrieved null-hypothesis significance testing (NHST) results from over half of the articles from this period. In line with earlier research, we found that half of all published psychology papers that use NHST contained at least one p-value that was inconsistent with its test statistic and degrees of freedom. One in eight papers contained a grossly inconsistent p-value that may have affected the statistical conclusion. In contrast to earlier findings, we found that the average prevalence of inconsistent p-values has been stable over the years or has declined. The prevalence of gross inconsistencies was higher in p-values reported as significant than in p-values reported as nonsignificant. This could indicate a systematic bias in favor of significant results. Possible solutions for the high prevalence of reporting inconsistencies could be to encourage sharing data, to let co-authors check results in a so-called “co-pilot model,” and to use statcheck to flag possible inconsistencies in one’s own manuscript or during the review process.

A torrent of low-quality meta-analyses and systematic reviews in biomedicine might be hiding valuable research and misleading scientists.

'Reproducibility editor' Victoria Stodden explains the growing movement to make code and data available to others.

Despite well-known problems with reproducibility, a common component of biomedical research often remains unchecked.

Giant survey suggests journals should pay more attention to detecting inappropriate duplications.

High-quality, data-rich samples are essential for future research. But obtaining and storing these samples is not as straightforward as many researchers think.

As the less familiar cousin of quantitative PCR moves mainstream, researchers have more options to choose from.

Knocking out a gene may be the most straightforward way to probe a protein’s function, but such experiments are blunt instruments. Removing a protein from a cell altogether can be both too much and too little, explains Kevan Shokat, a chemical biologist at the University of California, San Francisco. “You can either get no phenotype because another protein will replace it, or you’ll destroy a whole complex because it’s so central.” In response to this and other challenges, researchers have developed multiple systems in which proteins are engineered to respond to small molecules or light. Depending on the technology, scientists can inhibit proteins, activate them, bring them together or send them to specific cellular locations. Though less familiar than adding or removing genes, these techniques offer faster and more subtle ways to perturb protein function.

As increasing numbers of protein–protein interactions are identified, researchers are finding ways to interrogate these data and understand the interactions in a relevant context.

As more genomes are assembled from scratch, scientists are struggling to assess and improve their quality.

Such tools have been commercialized. Several vendors sell reprogramming systems using retroviruses and lentiviruses. A lentivirus produced by Stemgent and sold by Sigma-Aldrich encodes all four of the classic reprogramming factors (Oct4, Sox2, c-Myc and Klf4) in a single construct, with expression activated by doxycycline2. Millipore also offers polycistronic lentiviral reprogramming kits. Life Technologies sells a reprogramming kit that includes Sendai virus. And constructs for these and other tools are generally available from the nonprofit plasmid repository Addgene. Researchers working with mouse cells can use reprogramming systems that allow remarkable control over the transgenes. Separate teams led by Hochedlinger3 and by Rudolf Jaenisch4 at the Whitehead Institute in Cambridge, Massachusetts have crafted mice in which genes for pluripotency factors are placed under the control of doxycycline and inserted into a genomic locus that is never silenced by methylation and therefore is potentially active in any cell in the mice. These so-called reprogrammable mice allow iPS cells to be generated from any tissue: instead of adding viruses to introduce Scientists recognize the cells when they see them: compact colonies with clear edges, and large nuclei that spread almost to the cell membrane. Successful reprogramming experiments make i n d u c e d p l u r i p o t e n t s t e m (iPS) cel ls that resemble embryonic stem cells in both morphology and behavior. Yet appearance can deceive. “I’ve seen a lot of colonies that look beaut i fu l , but when you test them molecularly and functionally, the colonies are not real, not fully reprogrammed,” says Konrad Hochedlinger, a stem cell biologist at Massachusetts General Hospital. Ultimately, iPS cell lines are assessed with functional tests that require several weeks. For mouse iPS cells, that means generating mouse pups; for human iPS cells, testing for differentiation into all major lineages. These tests are time consuming and expensive, and so researchers need reliable ways to pick the best candidate colonies from a reprogramming experiment, much as an employer will sift through resumes before taking the time to interview job candidates. Surrogate markers of quality are important at several steps: picking which colonies to expand, picking which colony expansions to passage into cell lines, and figuring out which cell lines to submit to the most stringent tests. Picking colonies To make iPS cells, researchers introduce a suite of reprogramming factors into cells, usually by adding genes that encode transcription factors active in pluripotent cells. (A similar approach can be used to make differentiated cells directly; Box 1.) Cells respond to the reprogramming factors by dividing to form colonies, some of which can generate iPS cell lines. For reprogramming to go to completion, a cell must restart its own pluripotency genes and silence any introduced genes. Often ‘partially reprogrammed’ cells far outnumber fully reprogrammed ones. These partially reprogrammed cells can closely resemble embryonic stem cell colonies, but they cannot differentiate into the full range of cell types, and their gene expression may be quite different from that of embryonic stem cells. One way to reduce contamination by partially reprogrammed cells is to halt their growth early. For this, researchers sometimes use reprogramming factors that can be turned on and off at will. The introduced pluripotency genes can be constructed so that they are only expressed in the presence of a small molecule like doxycycline; removing doxycycline from the culture medium will silence them. Fully reprogrammed cells have already activated their own pluripotency genes and so continue to grow, but partially reprogrammed cells do not. Non-integrating systems, such as Sendai viruses and episomes, offer a similar advantage. Because they are not copied when cells divide, they are diluted out when cells expand, depriving partially reprogrammed cells of pluripotency factors. Growing cells under feeder-free conditions and with fully defined media can also cut down on the growth of partially reprogrammed cells1. Chimeric mice with all four reprogramming factors in the same genomic locus make producing iPS cells more straightforward. Re f. 3 Konrad Hochedlinger at Massachusetts General Hospital says that many beautiful colonies in reprogramming experiments fail to produce high-quality pluripotent stem cells.