ArticleJournal of pathology informatics2016
Quantitative analysis of myocardial tissue with digital autofluorescence microscopy.
Article in Journal of pathology informatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 12 citations in OpenAlex.
- Quantitative proteomics of formalin-fixed, paraffin-embedded cardiac specimens uncovers protein signatures of specialized regions and patient groups.Nature cardiovascular research · 2025Article
- Senescence Rejuvenation through Reduction in Mitochondrial Reactive Oxygen Species Generation byAntioxidants (Basel, Switzerland) · 2024Article
- Identification of Cellular Isoschaftoside-Mediated Anti-Senescence Mechanism inMolecules (Basel, Switzerland) · 2024Article
- Management of autofluorescence in formaldehyde-fixed myocardium: choosing the right treatment.European journal of histochemistry : EJH · 2023Article
- An Overview of the Role of Lipofuscin in Age-Related Neurodegeneration.Frontiers in neuroscience · 2018Review
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe opportunity offered by whole slide scanners of automated histological analysis implies an ever increasing importance of digital pathology. To go beyond the importance of conventional pathology, however, digital pathology may need a basic histological starting point similar to that of hematoxylin and eosin staining in conventional pathology. This study presents an automated fluorescence-based microscopy approach providing highly detailed morphological data from unstained microsections. This data may provide a basic histological starting point from which further digital analysis including staining may benefit.
methodsThis study explores the inherent tissue fluorescence, also known as autofluorescence, as a mean to quantitate cardiac tissue components in histological microsections. Data acquisition using a commercially available whole slide scanner and an image-based quantitation algorithm are presented.
resultsIt is shown that the autofluorescence intensity of unstained microsections at two different wavelengths is a suitable starting point for automated digital analysis of myocytes, fibrous tissue, lipofuscin, and the extracellular compartment. The output of the method is absolute quantitation along with accurate outlines of above-mentioned components. The digital quantitations are verified by comparison to point grid quantitations performed on the microsections after Van Gieson staining.
conclusionThe presented method is amply described as a prestain multicomponent quantitation and outlining tool for histological sections of cardiac tissue. The main perspective is the opportunity for combination with digital analysis of stained microsections, for which the method may provide an accurate digital framework.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.