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Keratin 19 as a Stem Cell Marker In Vivo and In Vitro

2004· article· en· W6632255 on OpenAlexaff
Danielle Larouche, Cindy J. Hayward, Kristine Cuffley, Lucie Germain

Bibliographic record

VenueHumana Press eBooks · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSkin and Cellular Biology Research
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsIn vitroIn vivoKeratinStem cellCell biologyStem cell markerBiologyChemistryBiochemistryGenetics

Abstract

fetched live from OpenAlex

The skin is a dynamic tissue in which terminally differentiated keratinocytes are replaced by the proliferation of new epithelial cells that will undergo differentiation. The rapid and continual turnover of skin throughout life depends on a cell population with unique characteristics: the stem cells. These cells are relatively undifferentiated, retain a high capacity for self-renewal throughout their lifetime, have a large proliferative potential, and are normally slow cycling. The long-term regeneration of grafted cultured epidermis indicates that epidermal stem cells are maintained in cultures. In animals they can be identified with 3H-thymidine or bromodeoxyuridine based on their property of slow cycling. The development of markers such as keratin 19 also permits their study in human tissues. In this chapter, protocols to study skin stem cells using their property of slow cycling and their expression of keratin 19 will be described in detail. The methods include the double labeling of tissues for keratin 19 and label-retaining cells (auto radiography of 3H-thymidine) in situ. The labeling of keratin 19 by immunofluorescence of by flow cytometry is described for cells in vitro.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.023
GPT teacher head0.268
Teacher spread0.246 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations45
Published2004
Admission routes1
Has abstractyes

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