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p63 Antagonizes p53 to Promote the Survival of Embryonic Neural Precursor Cells

2009· article· en· W2024145119 on OpenAlexafffund
Sagar B. Dugani, Annie Paquin, Masashi Fujitani, David R. Kaplan, Freda D. Miller

Bibliographic record

VenueJournal of Neuroscience · 2009
Typearticle
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsUniversity of TorontoHospital for Sick Children
FundersCanadian Institutes of Health ResearchHospital for Sick ChildrenJapan Society for the Promotion of ScienceGovernment of OntarioPhilipps-Universität MarburgHoward Hughes Medical Institute
KeywordsEmbryonic stem cellBiologyGene silencingNeuroscienceGene knockdownApoptosisNeurogenesisCell biologyCerebral cortexPrecursor cellGeneticsGeneCell

Abstract

fetched live from OpenAlex

The molecular mechanisms that regulate survival of embryonic neural precursors are still relatively ill-defined. Here, we have asked whether the p53 family member p63 plays any role during this developmental window, focusing on the embryonic cerebral cortex. We show that genetic knockdown of p63 either in culture or in the embryonic telencephalon causes apoptosis of cortical precursors and newly born cortical neurons, and that this can be rescued by expression of DeltaNp63, but not TAp63 isoforms. This cortical precursor apoptosis is the consequence of deregulated p53 activity, since both basal precursor apoptosis and that induced by loss of p63 are rescued by coincident genetic silencing of p53. Finally, we demonstrate that the third p53 family member, DeltaNp73, does not regulate survival of cortical precursor cells, but that it collaborates with DeltaNp63 to ensure the survival of newly born cortical neurons. Thus, the balance of DeltaNp63 versus p53 determines the life versus death of embryonic cortical precursors, a role that these p53 family members may well play in other populations of developing and/or adult neural precursors.

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 score0.003

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.287
Teacher spread0.263 · 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

Citations42
Published2009
Admission routes2
Has abstractyes

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