Assessment of Color Reproducibility and Mitigation of Color Variation in Whole Slide Image Scanners for Toxicologic Pathology.

Digital pathology workflows in toxicologic pathology rely on whole slide images (WSIs) from histopathology slides. Inconsistent color reproduction by WSI scanners of different models and from different manufacturers can result in different color representations and inter-scanner color variation in the WSIs. Although pathologists can accommodate a range of color variation during their evaluation of WSIs, color variability can degrade the performance of computational applications in digital pathology. In particular, color variability can compromise the generalization of artificial intelligence applications to large volumes of data from diverse sources. To address these challenges, we developed a process that includes two modules: (1) assessing the color reproducibility of our scanners and the color variation among them and (2) applying color correction to WSIs to minimize the color deviation and variation. Our process ensures consistent color reproduction across WSI scanners and enhances color homogeneity in WSIs, and its flexibility enables easy integration as a post-processing step following scanning by WSI scanners of different models and from different manufacturers.

Toxicologic Pathology Forum: A Roadmap for Building State-of-the-Art Digital Image Data Resources for Toxicologic Pathology in the Pharmaceutical Industry.

Digitization of histologic slides brings with it the promise of enhanced toxicologic pathology practice through the increased application of computational methods. However, the development of these advanced methods requires access to substrate image data, that is, whole slide images (WSIs). Deep learning methods, in particular, rely on extensive training data to develop robust algorithms. As a result, pharmaceutical companies interested in leveraging computational methods in their digital pathology workflows must first invest in data infrastructure to enable data access for both data scientists and pathologists. The process of building robust image data resources is challenging and includes considerations of generation, curation, and storage of WSI files, and WSI access including via linked metadata. This opinion piece describes the collective experience of building resources for WSI data in the Roche group. We elaborate on the challenges encountered and solutions developed with the goal of providing examples of how to build a data resource for digital pathology analytics in the pharmaceutical industry.

Functional trait trade-off and species abundance: insights from a multi-decadal study.

Phylogenetically informed trait comparisons across entire communities show promise in advancing community ecology. We use this approach to better understand the composition of a community of winter annual plants with multiple decades of monitoring and detailed morphological, phenological and physiological measurements. Previous research on this system revealed a physiological trade-off among dominant species that accurately predicts population and community dynamics. Here we expanded our investigation to 51 species, representing 96% of individual plants recorded over 30 years, and analysed trait relationships in the context of species abundance and phylogenetic relationships. We found that the functional-trait trade-off scales to the entire community, albeit with diminished strength. It is strongest for dominant species and weakens as progressively rarer species are included. The trade-off has been consistently expressed over three decades of environmental change despite some turnover in the identity of dominant species.

Characterization of 19 microsatellite loci in the clonal monkshood Aconitum kusnezoffii (Ranunculaceae).

PREMISE OF THE STUDY: Microsatellite loci were isolated and characterized from Aconitum kusnezoffii (Ranunculaceae) to estimate male and female reproductive success and evaluate the effects of clonal growth on sexual reproduction. METHODS AND RESULTS: A genomic enrichment approach was used to develop microsatellite markers. In three investigated A. kusnezoffii populations, a total of 19 microsatellite loci were successfully amplified, and 13 of these loci were polymorphic. Most of the primer pairs designed for the identified loci also amplified corresponding microsatellite loci in A. barbatum var. puberulum and A. alboviolaceum. CONCLUSIONS: The identified microsatellite loci will be useful for quantifying male and female fitness in A. kusnezoffii and evaluating the effects of clonal growth on sexual reproduction.