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Record W1983989514 · doi:10.4161/nucl.1.4.12107

The mechanisms regulating the subcellular localization of AID

2010· article· en· W1983989514 on OpenAlexafffund
Anne‐Marie Patenaude, Javier M. Di Noia

Bibliographic record

VenueNucleus · 2010
Typearticle
Languageen
FieldImmunology and Microbiology
TopicT-cell and B-cell Immunology
Canadian institutionsMcGill UniversityUniversité de MontréalMontreal Clinical Research Institute
FundersCanadian Institutes of Health ResearchCanada Research Chairs
KeywordsImportinSubcellular localizationNuclear transportCytoplasmNuclear export signalNuclear localization sequenceNucleusCell nucleusCell biologyBiology

Abstract

fetched live from OpenAlex

Activation induced deaminase (AID) is a unique enzyme that directly introduces mutations in the immunoglobulin genes to generate antibody diversity during the humoral immune response. Since this mutator enzyme poses a measurable risk of off-target mutation, which can be deleterious or transforming for a cell, several regulatory mechanisms exist to control its activity. At least three of these mechanisms affect AID subcellular localization. It was recently found that AID is actively imported into the nucleus, most likely through importin-α/β recognizing a structural nuclear localization signal. However, AID is largely excluded from the nucleus in steady state thanks to two mechanisms. In addition to nuclear export through the exportin CRM1, a mechanism retaining AID in the cytoplasm exists. Cytoplasmic retention hinders the passive diffusion of AID into the nucleus playing an important role in the nuclear exclusion of AID. Subcellular localization of AID also determines its stability. The regulation of the nuclear fraction of AID by these many mechanisms has functional implications for antibody diversification.

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 score0.006

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.008
GPT teacher head0.202
Teacher spread0.194 · 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

Citations31
Published2010
Admission routes2
Has abstractyes

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