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Antagonistic Roles of ERK1/2 and p38 MAP Kinases in Hemoglobin Synthesis.

2005· article· en· W2552129324 on OpenAlexaff
Volker Blank, Damien Lehalle, Louay Mardini, Mansouria Merad Boudia, Anna Derjuga, Amy P. Moore

Bibliographic record

VenueBlood · 2005
Typearticle
Languageen
FieldMedicine
TopicErythrocyte Function and Pathophysiology
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
Keywordsp38 mitogen-activated protein kinasesMAPK/ERK pathwayHemeKinaseCell biologyBiologyTransferrin receptorHemoglobinProtein kinase AGlobinSignal transductionMitogen-activated protein kinaseMolecular biologyBiochemistryChemistryTransferrinEnzyme

Abstract

fetched live from OpenAlex

Abstract Murine erythroleukemia (MEL) cells provide a valuable model to study the molecular events leading to erythroid differentiation. Maturing erythroid cells synthesize large quantities of hemoglobin, a process requiring the coordinated synthesis of heme and globin. Here, we investigated the role of the ERK and p38 mitogen-activated protein kinase (MAPK) signaling pathways in the differentiation of MEL cells. We determined the effect of the MEK1/2 inhibitor U0126 that blocks the ERK1/2 pathway, and the p38 inhibitor SB202190 on the differentiation potential of MEL cells induced by hexamethylene bisacetamide (HMBA). We found that treatment of HMBA induced MEL cells with the ERK1/2 pathway inhibitor U0126 results in higher hemoglobin levels. Using a fluorometric assay, we determined that intracellular heme levels also increased. Immunoblot studies showed an increase in globin protein levels. In contrast, treatment of MEL cells with the p38 inhibitor SB202190 has the opposite effect, leading to decreased amounts of heme and hemoglobin. In addition, inhibition of the p38 pathways results in lower transferrin receptor levels. Our results suggest that the ERK1/2 and p38 pathways play antagonistic roles in HMBA induced erythroid differentiation in MEL cells. This data also provides a novel link between MAPK signaling and the regulation of heme biosynthesis and iron uptake in erythroid cells.

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 score0.173
Threshold uncertainty score0.256

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 head0.011
GPT teacher head0.241
Teacher spread0.229 · 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

Citations0
Published2005
Admission routes1
Has abstractyes

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