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Record W2133439861 · doi:10.1002/gcc.22046

Nuclear remodeling of telomeres in chronic myeloid leukemia

2013· article· en· W2133439861 on OpenAlexafffund
Oumar Samassékou, Josée Hébert, Sabine Mai, Ju Yan

Bibliographic record

VenueGenes Chromosomes and Cancer · 2013
Typearticle
Languageen
FieldMedicine
TopicTelomeres, Telomerase, and Senescence
Canadian institutionsUniversity of ManitobaResearch ManitobaCancerCare ManitobaHôpital Maisonneuve-RosemontUniversité de Sherbrooke
FundersResearch ManitobaCancer Research Institute
KeywordsTelomereMyeloid leukemiaBiologyGenome instabilityCancer researchCancerChromosomal translocationLeukemiaChromosome instabilityCancer cellGeneticsDNAGeneDNA damageChromosome

Abstract

fetched live from OpenAlex

Chronic myeloid leukemia (CML) is a hematologic cancer characterized by the proliferation of myeloid cells and the translocation between chromosomes 9 and 22, [t(9;22)(q34.1;q11.2)]. At the chronic phase (CP), CML cells present longer telomeres than at the other clinical phases, display arm-specific maintenance of individual telomere lengths, and are chromosomally stable. We asked whether an alteration of nuclear organization of telomeres, which is associated with genomic instability, occurs in CML cells at the CP. We used fluorescent in situ hybridization of telomeres combined with three-dimensional (3D) quantification to study the nuclear telomeric architecture of CML cells at the CP. We found that cells can exhibit high telomere numbers, different telomere distributions, and alterations in peripheral or central nuclear location of telomeres. Also, we show that CML cells can be categorized in two groups according to the number of their telomere aggregates (TAs). We propose that the presence of high TAs in some samples is associated with the increased genomic instability and could be an indication of the clinical transitional phase. Also, alterations of nuclear organization of telomeres at the CP confirm that nuclear remodeling of telomeres can occur at an early clinical stage of a cancer.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.650
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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 head0.015
GPT teacher head0.258
Teacher spread0.243 · 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 teacher head, not a consensus.

Study designObservational
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

Citations9
Published2013
Admission routes2
Has abstractyes

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