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Record W2109512616 · doi:10.1139/o05-038

The role of poly(ADP-ribose) in the DNA damage signaling network

2005· review· en· W2109512616 on OpenAlexvenueno aff
Maria Malanga, Felix R. Althaus

Bibliographic record

VenueBiochemistry and Cell Biology · 2005
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer therapeutics and mechanisms
Canadian institutionsnot available
FundersSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsDNA repairPoly ADP ribose polymeraseDNA damageBiologyDNAChromatinHistoneNAD+ kinaseCell biologyBiochemistryDNA repair protein XRCC4PolymeraseNucleotide excision repairEnzyme

Abstract

fetched live from OpenAlex

DNA damage signaling is crucial for the maintenance of genome integrity. In higher eukaryotes a NAD+-dependent signal transduction mechanism has evolved to protect cells against the genome destabilizing effects of DNA strand breaks. The mechanism involves 2 nuclear enzymes that sense DNA strand breaks, poly(ADP-ribose) polymerase-1 and -2 (PARP-1 and PARP-2). When activated by DNA breaks, these PARPs use NAD+ to catalyze their automodification with negatively charged, long and branched ADP-ribose polymers. Through recruitment of specific proteins at the site of damage and regulation of their activities, these polymers may either directly participate in the repair process or coordinate repair through chromatin unfolding, cell cycle progression, and cell survival-cell death pathways. A number of proteins, including histones, DNA topoisomerases, DNA methyltransferase-1 as well as DNA damage repair and checkpoint proteins (p23, p21, DNA-PK, NF-kB, XRCC1, and others) can be targeted in this manner; the interaction involves a specific poly(ADP-ribose)-binding sequence motif of 20-26 amino acids in the target domains.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.004

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 head0.014
GPT teacher head0.273
Teacher spread0.259 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations273
Published2005
Admission routes1
Has abstractyes

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