AIMC Topic: Keratins
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AI, docking, and molecular dynamics to track the binding of structural peptides to different keratin models.
International journal of biological macromolecules
May 30, 2025
The present work shows a computational approach to assess the interactions of different nature-inspired peptides with hair keratin models. An updated keratin model was validated, and comparisons with previous models were traced, thereby highlighting ...
Evaluation of tumor budding with virtual panCK stains generated by novel multi-model CNN framework.
Computer methods and programs in biomedicine
Aug 22, 2024
As the global incidence of cancer continues to rise rapidly, the need for swift and precise diagnoses has become increasingly pressing. Pathologists commonly rely on H&E-panCK stain pairs for various aspects of cancer diagnosis, including the detecti...
Deep learning approach for accurate prostate cancer identification and stratification using combined immunostaining of cytokeratin, p63, and racemase.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Aug 19, 2023
BACKGROUND: Prostate cancer (PCa) is the most frequently diagnosed cancer in men worldwide, affecting around 1.4 million individuals. Current PCa diagnosis relies on histological analysis of prostate biopsy samples, an activity that is both time-cons...
Integrative measurement analysis via machine learning descriptor selection for investigating physical properties of biopolymers in hairs.
Scientific reports
Dec 21, 2021
Integrative measurement analysis of complex subjects, such as polymers is a major challenge to obtain comprehensive understanding of the properties. In this study, we describe analytical strategies to extract and selectively associate compositional i...
Automated annotations of epithelial cells and stroma in hematoxylin-eosin-stained whole-slide images using cytokeratin re-staining.
The journal of pathology. Clinical research
Oct 30, 2021
The diagnosis of solid tumors of epithelial origin (carcinomas) represents a major part of the workload in clinical histopathology. Carcinomas consist of malignant epithelial cells arranged in more or less cohesive clusters of variable size and shape...
Deep learning-based virtual cytokeratin staining of gastric carcinomas to measure tumor-stroma ratio.
Scientific reports
Sep 28, 2021
The tumor-stroma ratio (TSR) determined by pathologists is subject to intra- and inter-observer variability. We aimed to develop a computational quantification method of TSR using deep learning-based virtual cytokeratin staining algorithms. Patients ...
SHIFT: speedy histological-to-immunofluorescent translation of a tumor signature enabled by deep learning.
Scientific reports
Oct 15, 2020
Spatially-resolved molecular profiling by immunostaining tissue sections is a key feature in cancer diagnosis, subtyping, and treatment, where it complements routine histopathological evaluation by clarifying tumor phenotypes. In this work, we presen...
Assessment of individual tumor buds using keratin immunohistochemistry: moderate interobserver agreement suggests a role for machine learning.
Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Dec 16, 2019
Tumor budding is a promising and cost-effective biomarker with strong prognostic value in colorectal cancer. However, challenges related to interobserver variability persist. Such variability may be reduced by immunohistochemistry and computer-aided ...
Cytokeratin-Supervised Deep Learning for Automatic Recognition of Epithelial Cells in Breast Cancers Stained for ER, PR, and Ki-67.
IEEE transactions on medical imaging
Aug 7, 2019
Immunohistochemistry (IHC) of ER, PR, and Ki-67 are routinely used assays in breast cancer diagnostics. Determination of the proportion of stained cells (labeling index) should be restricted on malignant epithelial cells, carefully avoiding tumor inf...
Prediction of early colorectal cancer metastasis by machine learning using digital slide images.
Computer methods and programs in biomedicine
Jun 22, 2019
BACKGROUND AND OBJECTIVES: Prediction of lymph node metastasis (LNM) for early colorectal cancer (CRC) is critical for determining treatment strategies after endoscopic resection. Some histologic parameters for predicting LNM have been established, b...
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