Bioimaging data have significant potential for reuse, but unlocking this potential requires systematic archiving of data and metadata in public databases. We propose draft metadata guidelines to begin addressing the needs of diverse communities within light and electron microscopy. We hope this publication and the proposed Recommended Metadata for Biological Images (REMBI) will stimulate discussions about their implementation and future extension.

Previous studies have shown that nursing interventions are effective in helping people to stop smoking, but that the participation of nurses in tobacco control activities has been far from satisfactory. The primary objective of this study is to identify factors that encourage or discourage nurses from participating in providing smoking-cessation interventions to their clients, based on the 5 A’s (ask, advise, assess, assist, arrange) framework. A cross-sectional survey was conducted among 4413 nurses in Hong Kong from different clinical specialties. A logistics regression analysis found that predictors for the practicing of all of the 5 A’s are nurses who want to receive training in smoking-cessation interventions, those who have received such training, and those who are primarily working in a medical unit or in ambulatory/outpatient settings. The regression model also showed that attitude towards smoking cessation was positively associated with all of the 5 A’s. The results indicate a need to encourage and provide nurses with opportunities to receive training on smoking-cessation interventions. Strategies to persuade nurses to provide smoking-cessation interventions are also important, since nurses are motivated to perform smoking-cessation interventions when they feel a stronger sense of mission to control tobacco use.

Faced with the need to support a growing number of whole slide imaging (WSI) file formats, our team has extended a long-standing community file format (OME-TIFF) for use in digital pathology. The format makes use of the core TIFF specification to store multi-resolution (or "pyramidal") representations of a single slide in a flexible, performant manner. Here we describe the structure of this format, its performance characteristics, as well as an open-source library support for reading and writing pyramidal OME-TIFFs.

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A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals and institutes across diverse modalities facing these problems have designed a format specification process (OME-NGFF) to address these needs. This paper brings together a wide range of those community members to describe the format itself -- OME-Zarr -- along with tools and data resources available today to increase FAIR access and remove barriers in the scientific process. The current momentum offers an opportunity to unify a key component of the bioimaging domain -- the file format that underlies so many personal, institutional, and global data management and analysis tasks.