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ATM‐dependent DNA damage surveillance in T‐cell development and leukemogenesis: the DSB connection

2006· review· en· W2006531104 on OpenAlex
Irina Matei, Cynthia J. Guidos, Jayne S. Danska

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueImmunological Reviews · 2006
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsBiologyAtaxia-telangiectasiaDNA damageAntigenDNA repairT-cell receptorImmune systemCell biologyGeneticsCancer researchImmunologyDNAT cell

Abstract

fetched live from OpenAlex

The immune system is capable of recognizing and eliminating an enormous array of pathogens due to the extremely diverse antigen receptor repertoire of T and B lymphocytes. However, the development of lymphocytes bearing receptors with unique specificities requires the generation of programmed double strand breaks (DSBs) coupled with bursts of proliferation, rendering lymphocytes susceptible to mutations contributing to oncogenic transformation. Consequently, mechanisms responsible for monitoring global genomic integrity must be activated during lymphocyte development to limit the oncogenic potential of antigen receptor locus recombination. Mutations in ATM (ataxia-telangiectasia mutated), a kinase that coordinates DSB monitoring and the response to DNA damage, result in impaired T-cell development and predispose to T-cell leukemia. Here, we review recent evidence providing insight into the mechanisms by which ATM promotes normal lymphocyte development and protects from neoplastic transformation.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.997
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.042
GPT teacher head0.295
Teacher spread0.253 · 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