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Fibroblasts

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Whey Protein Complexes with Green Tea Polyphenols: Antimicrobial, Osteoblast-Stimulatory, and Antioxidant Activities.

Cells, tissues, organs
Polyphenols are known for their antimicrobial activity, whilst both polyphenols and the globular protein β-lactoglobulin (bLG) are suggested to have antioxidant properties and promote cell proliferation. These are potentially useful properties for a ...

The antifibrotic effect of isolate tagitinin C from tithonia diversifolia (Hemsley) A. Gray on keloid fibroblast cell.

The Pan African medical journal
INTRODUCTION: Keloids characterized by fibroblast hyperproliferation and depositions of collagen which similar to cancer cells. Tagitinin C is a class of sesquiterpene lactones (SLS) was isolated from the leaves of the moon flower (Hemsley) A. Gray....

DeepNEU: cellular reprogramming comes of age - a machine learning platform with application to rare diseases research.

Orphanet journal of rare diseases
BACKGROUND: Conversion of human somatic cells into induced pluripotent stem cells (iPSCs) is often an inefficient, time consuming and expensive process. Also, the tendency of iPSCs to revert to their original somatic cell type over time continues to ...

Machine-Learning-Driven Surface-Enhanced Raman Scattering Optophysiology Reveals Multiplexed Metabolite Gradients Near Cells.

ACS nano
The extracellular environment is a complex medium in which cells secrete and consume metabolites. Molecular gradients are thereby created near cells, triggering various biological and physiological responses. However, investigating these molecular gr...

A novel machine learning based approach for iPS progenitor cell identification.

PLoS computational biology
Identification of induced pluripotent stem (iPS) progenitor cells, the iPS forming cells in early stage of reprogramming, could provide valuable information for studying the origin and underlying mechanism of iPS cells. However, it is very difficult ...

Machine learning utilising spectral derivative data improves cellular health classification through hyperspectral infra-red spectroscopy.

PloS one
The objective differentiation of facets of cellular metabolism is important for several clinical applications, including accurate definition of tumour boundaries and targeted wound debridement. To this end, spectral biomarkers to differentiate live a...

Quantitative scoring of epithelial and mesenchymal qualities of cancer cells using machine learning and quantitative phase imaging.

Journal of biomedical optics
SIGNIFICANCE: We introduce an application of machine learning trained on optical phase features of epithelial and mesenchymal cells to grade cancer cells' morphologies, relevant to evaluation of cancer phenotype in screening assays and clinical biops...

Spage2vec: Unsupervised representation of localized spatial gene expression signatures.

The FEBS journal
Investigations of spatial cellular composition of tissue architectures revealed by multiplexed in situ RNA detection often rely on inaccurate cell segmentation or prior biological knowledge from complementary single-cell sequencing experiments. Here,...

Artificial intelligence identifies inflammation and confirms fibroblast foci as prognostic tissue biomarkers in idiopathic pulmonary fibrosis.

Human pathology
A large number of fibroblast foci (FF) predict mortality in idiopathic pulmonary fibrosis (IPF). Other prognostic histological markers have not been identified. Artificial intelligence (AI) offers a possibility to quantitate possible prognostic histo...