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Penney M. Gilbert

Researcher at University of Toronto

Publications -  59
Citations -  5128

Penney M. Gilbert is an academic researcher from University of Toronto. The author has contributed to research in topics: Skeletal muscle & Stem cell. The author has an hindex of 18, co-authored 50 publications receiving 4345 citations. Previous affiliations of Penney M. Gilbert include University of Pennsylvania & Stanford University.

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Substrate Elasticity Regulates Skeletal Muscle Stem Cell Self-Renewal in Culture

TL;DR: Using a bioengineered substrate to recapitulate key biophysical and biochemical niche features in conjunction with a highly automated single-cell tracking algorithm, it is shown that substrate elasticity is a potent regulator of MuSC fate in culture.
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Designing materials to direct stem-cell fate

TL;DR: Further synergism of cell biological and biomaterials technologies promises to have a profound impact on stem-cell biology and provide insights that will advance stem- cell-based clinical approaches to tissue regeneration.
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Rejuvenation of the muscle stem cell population restores strength to injured aged muscles

TL;DR: Subjecting theMuSC population from aged mice to transient inhibition of p38α and p38β in conjunction with culture on soft hydrogel substrates rapidly expands the residual functional MuSC population, rejuvenating its potential for regeneration and serial transplantation as well as strengthening of damaged muscles of aged mice.
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Tissue mechanics modulate microRNA-dependent PTEN expression to regulate malignant progression

TL;DR: This work demonstrates that increased matrix stiffness modulates microRNA expression to drive tumor progression through integrin activation of β-catenin and MYC and identifies a mechanically regulated microRNA circuit that can promote malignancy and suggest potential prognostic roles for HOXA9 and miR-18a levels in stratifying patients with luminal breast cancers.
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Global Linking of Cell Tracks Using the Viterbi Algorithm

TL;DR: A global track linking algorithm, which links cell outlines generated by a segmentation algorithm into tracks, which can handle mitosis, apoptosis, and migration in and out of the imaged area, and can also deal with false positives, missed detections, and clusters of jointly segmented cells.