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Record W2059844340 · doi:10.1091/mbc.e11-01-0035

Targeted inactivation of integrin-linked kinase in hair follicle stem cells reveals an important modulatory role in skin repair after injury

2011· article· en· W2059844340 on OpenAlexafffund
Kerry‐Ann Nakrieko, Alena Rudkouskaya, Timothy S. Irvine, Sudhir J.A. D’Souza, Lina Dagnino

Bibliographic record

VenueMolecular Biology of the Cell · 2011
Typearticle
Languageen
FieldMedicine
TopicHair Growth and Disorders
Canadian institutionsMcMaster UniversityLawson Health Research InstituteWestern University
FundersCanadian Institutes of Health ResearchCancer Research Society
KeywordsBiologyHair follicleStem cellCell biologyIntegrin-linked kinaseKeratinEpidermis (zoology)Wound healingSkin repairRegeneration (biology)PopulationMorphogenesisProtein kinase AImmunologyAnatomyKinaseGeneticsCyclin-dependent kinase 2Medicine

Abstract

fetched live from OpenAlex

Integrin-linked kinase (ILK) is key for normal epidermal morphogenesis, but little is known about its role in hair follicle stem cells and epidermal regeneration. Hair follicle stem cells are important contributors to newly formed epidermis following injury. We inactivated the Ilk gene in the keratin 15--expressing stem cell population of the mouse hair follicle bulge. Loss of ILK expression in these cells resulted in impaired cutaneous wound healing, with substantially decreased wound closure rates. ILK-deficient stem cells produced very few descendants that moved toward the epidermal surface and into the advancing epithelium that covers the wound. Furthermore, those few mutant cells that homed in the regenerated epidermis exhibited a reduced residence time. Paradoxically, ILK-deficient bulge stem cells responded to anagen growth signals and contributed to newly regenerated hair follicles during this phase of hair follicle growth. Thus ILK plays an important modulatory role in the normal contribution of hair follicle stem cell progeny to the regenerating epidermis following injury.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score0.464

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.229
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations23
Published2011
Admission routes2
Has abstractyes

Explore more

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