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Record W2164522226 · doi:10.1242/jcs.02816

The number of PML nuclear bodies increases in early S phase by a fission mechanism

2006· article· en· W2164522226 on OpenAlexaff
Graham Dellaire, Reagan W. Ching, Hesam Dehghani, Ying Ren, David P. Bazett‐Jones

Bibliographic record

VenueJournal of Cell Science · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinoids in leukemia and cellular processes
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsBiologyChromatinInterphaseMitosisCell biologyNuclear proteinPromyelocytic leukemia proteinCell nucleusDNADNA damageFissionCell cycleGeneticsTranscription factorCytoplasmApoptosisGenePhysicsNuclear physics

Abstract

fetched live from OpenAlex

Promyelocytic leukemia (PML) nuclear bodies have been implicated in a variety of cellular processes including apoptosis, tumour suppression, anti-viral response, DNA repair and transcriptional regulation. PML nuclear bodies are both positionally and structurally stable over extended periods of interphase. As demonstrated in this study, the structural stability is lost as cells enter S phase, evidenced both by distortions in shape and by fission and fusion events. At the end of this period of structural instability, the number of PML nuclear bodies has increased by a factor of twofold. Association of the fission products with chromatin implies that the PML nuclear bodies respond to changes in chromatin organisation or topology, and thus could play a role in monitoring genome integrity during DNA synthesis or in the continued maintenance of functional chromosomal domains prior to mitosis.

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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.003
GPT teacher head0.245
Teacher spread0.242 · 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

Citations99
Published2006
Admission routes1
Has abstractyes

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