MétaCan
Menu
Back to cohort

Constitutive Nuclear Factor-κB Activity Is Required for Central Neuron Survival

2002· article· en· W1767114057 on OpenAlexafffund
Asha Bhakar, Laura-Lee Tannis, Christine Zeindler, Maria Pia Russo, Christian Jobin, David S. Park, Sandra Macpherson, Philip A. Barker

Bibliographic record

VenueJournal of Neuroscience · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNF-κB Signaling Pathways
Canadian institutionsMcGill UniversityUniversity of OttawaMontreal Neurological Institute and Hospital
FundersCanadian Institutes of Health ResearchKillam Trusts
KeywordsNeuroprotectionBiologyNF-κBNeocortexTransgeneGenetically modified mouseNeuroscienceNeuronIκBαTumor necrosis factor alphaCell biologyNFKB1Transcription factorImmunologySignal transductionGeneGenetics

Abstract

fetched live from OpenAlex

The function of nuclear factor (NF)-kappaB within the developing and mature CNS is controversial. We have generated transgenic mice to reveal NF-kappaB transcriptional activity in vivo. As expected, constitutive NF-kappaB activity was observed within immune organs, and tumor necrosis factor-inducible NF-kappaB activity was present in mesenchymal cells. Intriguingly, NF-kappaB activity was also prominent in the CNS throughout development, especially within neocortex, olfactory bulbs, amygdala, and hippocampus. NF-kappaB in the CNS was restricted to neurons and blocked by overexpression of dominant-negative NF-kappaB-inducible kinase or the IkappaBalphaM super repressor. Blocking endogenous neuronal NF-kappaB activity in cortical neurons using recombinant adenovirus induced neuronal death, whereas induction of NF-kappaB activity increased levels of anti-apoptotic proteins and was strongly neuroprotective. Together, these data demonstrate a physiological role for NF-kappaB in maintaining survival of central neurons.

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 score0.001
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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.063
GPT teacher head0.279
Teacher spread0.217 · 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

Citations317
Published2002
Admission routes2
Has abstractyes

Explore more

Same venueJournal of NeuroscienceSame topicNF-κB Signaling PathwaysFrench-language works237,207