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Record W2067752807 · doi:10.1182/blood-2011-01-331819

Genetic interaction between Kit and Scl

2013· article· en· W2067752807 on OpenAlexafffund
Julie Lacombe, Gorazd Krosl, Mathieu Tremblay, Bastien Gerby, Richard Martin, Peter D. Aplan, Sébastien Lemieux, Trang Hoang

Bibliographic record

VenueBlood · 2013
Typearticle
Languageen
FieldMedicine
TopicAcute Lymphoblastic Leukemia research
Canadian institutionsUniversité de MontréalHôpital Maisonneuve-RosemontInstitute for Research in Immunology and Cancer
FundersCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsProgenitor cellHaematopoiesisBiologyStem cellImmunologyCell biology

Abstract

fetched live from OpenAlex

SCL/TAL1, a tissue-specific transcription factor of the basic helix-loop-helix family, and c-Kit, a tyrosine kinase receptor, control hematopoietic stem cell survival and quiescence. Here we report that SCL levels are limiting for the clonal expansion of Kit⁺ multipotent and erythroid progenitors. In addition, increased SCL expression specifically enhances the sensitivity of these progenitors to steel factor (KIT ligand) without affecting interleukin-3 response, whereas a DNA-binding mutant antagonizes KIT function and induces apoptosis in progenitors. Furthermore, a twofold increase in SCL levels in mice bearing a hypomorphic Kit allele (W41/41) corrects their hematocrits and deficiencies in erythroid progenitor numbers. At the molecular level, we found that SCL and c-Kit signaling control a common gene expression signature, of which 19 genes are associated with apoptosis. Half of those were decreased in purified megakaryocyte/erythroid progenitors (MEPs) from W41/41 mice and rescued by the SCL transgene. We conclude that Scl operates downstream of Kit to support the survival of MEPs. Finally, higher SCL expression upregulates Kit in normal bone marrow cells and increases chimerism after bone marrow transplantation, indicating that Scl is also upstream of Kit. We conclude that Scl and Kit establish a positive feedback loop in multipotent and MEPs.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score0.706

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)0.0000.001

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 head0.017
GPT teacher head0.279
Teacher spread0.262 · 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 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

Citations24
Published2013
Admission routes2
Has abstractyes

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