ArticlePloS one2017
Automated fluorescent miscroscopic image analysis of PTBP1 expression in glioma.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed, 39 citations in OpenAlex.
- Glioma Grade Classification Using Machine Learning and MRI Radiomics: A Single-Center Prospective Study Comparing Original and Wavelet-Transformed Features From Anatomical, Diffusion-Weighted, and Post-Contrast Imaging.Health science reports · 2026Article
- StrokeENDPredictor-19: Setting New Prediction Model in Neurological Prognosis in Acute Ischemic Stroke.Annals of biomedical engineering · 2025Article
- Integrating SAM priors with U-Net for enhanced multiclass cell detection in digital pathology.Scientific reports · 2025Article
- Semi-supervised tissue segmentation from histopathological images with consistency regularization and uncertainty estimation.Scientific reports · 2025Article
- PTBP1 as a potential regulator of disease.Molecular and cellular biochemistry · 2024Review
- Glioblastoma pseudoprogression and true progression reveal spatially variable transcriptional differences.Acta neuropathologica communications · 2023Article
- Raidionics: an open software for pre- and postoperative central nervous system tumor segmentation and standardized reporting.Scientific reports · 2023Article
- Identification of disease-related aberrantly spliced transcripts in myeloma and strategies to target these alterations by RNA-based therapeutics.Blood cancer journal · 2023Article
- Modality specific U-Net variants for biomedical image segmentation: a survey.Artificial intelligence review · 2022Article
- Differentiating Staphylococcus infection-associated glomerulonephritis and primary IgA nephropathy: a mass spectrometry-based exploratory study.Scientific reports · 2020Article
- WGAN domain adaptation for the joint optic disc-and-cup segmentation in fundus images.International journal of computer assisted radiology and surgery · 2020Article
- Segmentation and Modelling of the Nuclear Envelope of HeLa Cells Imaged with Serial Block Face Scanning Electron Microscopy.Journal of imaging · 2019Article
- Development of a Novel FIJI-Based Method to Investigate Neuronal Circuitry in Neonatal Mice.Developmental neurobiology · 2018Article
- Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 2 countries.
Funding
Abstract
Multiplexed immunofluorescent testing has not entered into diagnostic neuropathology due to the presence of several technical barriers, amongst which includes autofluorescence. This study presents the implementation of a methodology capable of overcoming the visual challenges of fluorescent microscopy for diagnostic neuropathology by using automated digital image analysis, with long term goal of providing unbiased quantitative analyses of multiplexed biomarkers for solid tissue neuropathology. In this study, we validated PTBP1, a putative biomarker for glioma, and tested the extent to which immunofluorescent microscopy combined with automated and unbiased image analysis would permit the utility of PTBP1 as a biomarker to distinguish diagnostically challenging surgical biopsies. As a paradigm, we utilized second resections from patients diagnosed either with reactive brain changes (pseudoprogression) and recurrent glioblastoma (true progression). Our image analysis workflow was capable of removing background autofluorescence and permitted quantification of DAPI-PTBP1 positive cells. PTBP1-positive nuclei, and the mean intensity value of PTBP1 signal in cells. Traditional pathological interpretation was unable to distinguish between groups due to unacceptably high discordance rates amongst expert neuropathologists. Our data demonstrated that recurrent glioblastoma showed more DAPI-PTBP1 positive cells and a higher mean intensity value of PTBP1 signal compared to resections from second surgeries that showed only reactive gliosis. Our work demonstrates the potential of utilizing automated image analysis to overcome the challenges of implementing fluorescent microscopy in diagnostic neuropathology.
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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.