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Record W2057048950 · doi:10.1002/dvdy.20110

TRAF6‐dependent NF‐kB transcriptional activity during mouse development

2004· article· en· W2057048950 on OpenAlexafffund
Kathleen M. Dickson, Asha Bhakar, Philip A. Barker

Bibliographic record

VenueDevelopmental Dynamics · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNF-κB Signaling Pathways
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersCanadian Institutes of Health ResearchAmgen
KeywordsBiologyCell biologyTranscriptional activityNF-κBNFKB1Transcription factorMolecular biologyGeneticsSignal transductionGene

Abstract

fetched live from OpenAlex

Nuclear factor-kappa B (NF-kB) transcriptional activity is induced by numerous stimuli. To identify tissues exhibiting NF-kB transcriptional activity during development, we analyzed transgenic reporter mice that express beta-galactosidase from an NF-kB-responsive element. We report that NF-kB activation is widespread and present in numerous epithelial structures and within vasculature. Several regions of the developing central nervous system, including the roof plate and floor plate of the midbrain, show prominent NF-kB activation. To assess the role of the TRAF6 adaptor protein in developmental NF-kB activity, we analyzed NF-kB activation in reporter mice rendered null for TRAF6. Deletion of TRAF6 resulted in the loss of NF-kB activity in epithelia, in vasculature, and in roof and floor plate but had no effect on NF-kB activity developing telencephalon, choroid plexus, cochlear canal, and thymus. These data indicate that NF-kB transcriptional activity is present in a broad range of structures during development and that TRAF6 plays a critical role mediating developmental NF-kB activation in many but not all tissues.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.009
GPT teacher head0.206
Teacher spread0.197 · 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 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

Citations51
Published2004
Admission routes2
Has abstractyes

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