English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Histological examination is a crucial step in an autopsy; however, thetraditional histochemical staining of post-mortem samples faces multiplechallenges, including the inferior staining quality due to autolysis caused bydelayed fixation of cadaver tissue, as well as the resource-intensive nature ofchemical staining procedures covering large tissue areas, which demandsubstantial labor, cost, and time. These challenges can become more pronouncedduring global health crises when the availability of histopathology services islimited, resulting in further delays in tissue fixation and more severestaining artifacts. Here, we report the first demonstration of virtual stainingof autopsy tissue and show that a trained neural network can rapidly transformautofluorescence images of label-free autopsy tissue sections into brightfieldequivalent images that match hematoxylin and eosin (H&E) stained versions ofthe same samples, eliminating autolysis-induced severe staining artifactsinherent in traditional histochemical staining of autopsied tissue. Our virtualH&E model was trained using >0.7 TB of image data and a data-efficientcollaboration scheme that integrates the virtual staining network with an imageregistration network. The trained model effectively accentuated nuclear,cytoplasmic and extracellular features in new autopsy tissue samples thatexperienced severe autolysis, such as COVID-19 samples never seen before, wherethe traditional histochemical staining failed to provide consistent stainingquality. This virtual autopsy staining technique can also be extended tonecrotic tissue, and can rapidly and cost-effectively generate artifact-freeH&E stains despite severe autolysis and cell death, also reducing labor, costand infrastructure requirements associated with the standard histochemicalstaining.

Virtual histological staining of unlabeled autopsy tissue