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Record W4213190714 · doi:10.1016/j.crimmu.2022.02.001

Role of NR4A family members in myeloid cells and leukemia

2022· article· en· W4213190714 on OpenAlexafffund
Salix Boulet, Laure Le Corre, Livia Odagiu, Nathalie Labrecque

Bibliographic record

VenueCurrent Research in Immunology · 2022
Typearticle
Languageen
FieldNeuroscience
TopicNuclear Receptors and Signaling
Canadian institutionsUniversité de MontréalHôpital Maisonneuve-Rosemont
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health Research
KeywordsMyeloid leukemiaMyeloidBiologyInnate immune systemMyeloid cellsTranscription factorCell biologyImmune systemCompartment (ship)LeukemiaImmunologyCancer researchGeneGenetics

Abstract

fetched live from OpenAlex

The myeloid cellular compartment comprises monocytes, dendritic cells (DCs), macrophages and granulocytes. As diverse as this group of cells may be, they are all an important part of the innate immune system and are therefore linked by the necessity to be acutely sensitive to their environment and to rapidly and appropriately respond to any changes that may occur. The nuclear orphan receptors NR4A1, NR4A2 and NR4A3 are encoded by immediate early genes as their expression is rapidly induced in response to various signals. It is perhaps because of this characteristic that this family of transcription factors has many known roles in myeloid cells. In this review, we will regroup and discuss the diverse roles NR4As have in different myeloid cell subsets, including in differentiation, migration, activation, and metabolism. We will also highlight the importance these molecules have in the development of myeloid leukemia.

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)0.000
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: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.085
GPT teacher head0.354
Teacher spread0.268 · 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

Citations17
Published2022
Admission routes2
Has abstractyes

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