Community-developed checklists for publishing images and image analyses.

Images document scientific discoveries and are prevalent in modern biomedical research. Microscopy imaging in particular is currently undergoing rapid technological advancements. However, for scientists wishing to publish obtained images and image-analysis results, there are currently no unified guidelines for best practices. Consequently, microscopy images and image data in publications may be unclear or difficult to interpret. Here, we present community-developed checklists for preparing light microscopy images and describing image analyses for publications. These checklists offer authors, readers and publishers key recommendations for image formatting and annotation, color selection, data availability and reporting image-analysis workflows. The goal of our guidelines is to increase the clarity and reproducibility of image figures and thereby to heighten the quality and explanatory power of microscopy data.

Community-developed checklists for publishing images and image analyses.

Images document scientific discoveries and are prevalent in modern biomedical research. Microscopy imaging in particular is currently undergoing rapid technological advancements. However for scientists wishing to publish the obtained images and image analyses results, there are to date no unified guidelines. Consequently, microscopy images and image data in publications may be unclear or difficult to interpret. Here we present community-developed checklists for preparing light microscopy images and image analysis for publications. These checklists offer authors, readers, and publishers key recommendations for image formatting and annotation, color selection, data availability, and for reporting image analysis workflows. The goal of our guidelines is to increase the clarity and reproducibility of image figures and thereby heighten the quality and explanatory power of microscopy data is in publications.

The raw truth about paper mills.

In 2018, the community first observed scientific papers in the biomedical literature that seemed to display systematically fabricated data, pointing to the existence of paper mills: unofficial, potentially illegal organizations selling fake scientific manuscripts. In the present article, we share relevant information specifically about the 'raw data' associated with paper mill manuscripts. If a submitted manuscript displays clear indicators of potential paper mill involvement, we found that the raw data at close inspection often raise doubts about their authenticity. In the absence of real data, paper mills may need to fabricate raw data images when responding to requests from journals. Given the necessity to streamline production of fake manuscripts, the alleged raw data might be created using templates. Some potential methods for generating fake Western blot images are discussed. Paying close attention to image data, including graphs, diagrams, plots and tables, ideally at pre-publication stage, can clearly help prevent publication of incorrect and fabricated information.

Digital magic, or the dark arts of the 21st century-how can journals and peer reviewers detect manuscripts and publications from paper mills?

In recent years, it has been proposed that unrealistic requirements for academics and medical doctors to publish in scientific journals, combined with monetary publication rewards, have led to forms of contract cheating offered by organizations known as paper mills. Paper mills are alleged to offer products ranging from research data through to ghostwritten fraudulent or fabricated manuscripts and submission services. While paper mill operations remain poorly understood, it seems likely that paper mills need to balance product quantity and quality, such that they produce or contribute to large numbers of manuscripts that will be accepted for publication. Producing manuscripts at scale may be facilitated by the use of manuscript templates, which could give rise to shared features such as textual and organizational similarities, the description of highly generic study hypotheses and experimental approaches, digital images that show evidence of manipulation and/or reuse, and/or errors affecting verifiable experimental reagents. Based on these features, we propose practical steps that editors, journal staff, and peer reviewers can take to recognize and respond to research manuscripts and publications that may have been produced with undeclared assistance from paper mills.