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Record W2064192911 · doi:10.3390/cancers5031086

Dynamic Length Changes of Telomeres and Their Nuclear Organization in Chronic Myeloid Leukemia

2013· article· en· W2064192911 on OpenAlexaff
Oumar Samassékou

Bibliographic record

VenueCancers · 2013
Typearticle
Languageen
FieldMedicine
TopicTelomeres, Telomerase, and Senescence
Canadian institutionsUniversity of ManitobaCancerCare Manitoba
Fundersnot available
KeywordsTelomereTelomeraseMyeloid leukemiaBiologyCancer researchMechanism (biology)CancerLeukemiaGenome instabilityGeneticsCell biologyDNAGeneDNA damage

Abstract

fetched live from OpenAlex

Chronic myeloid leukemia (CML) is a myeloproliferative neoplasm characterized by the t(9;22) translocation. As in most cancers, short telomeres are one of the features of CML cells, and telomere shortening accentuates as the disease progresses from the chronic phase to the blastic phase. Although most individual telomeres are short, some of them are lengthened, and long individual telomeres occur non-randomly and might be associated with clonal selection. Telomerase is the main mechanism used to maintain telomere lengths, and its activity increases when CML evolves toward advanced stages. ALT might be another mechanism employed by CML cells to sustain the homeostasis of their telomere lengths and this mechanism seems predominant at the early stage of leukemogenesis. Also, telomerase and ALT might jointly act to maintain telomere lengths at the chronic phase, and as CML progresses, telomerase becomes the major mechanism. Finally, CML cells display an altered nuclear organization of their telomeres which is characterized by the presence of high number of telomeric aggregates, a feature of genomic instability, and differential positioning of telomeres. CML represents a good model to study mechanisms responsible for dynamic changes of individual telomere lengths and the remodeling of telomeric nuclear organization throughout cancer progression.

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 score0.002

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)0.0010.000

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 head0.008
GPT teacher head0.221
Teacher spread0.214 · 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

Citations9
Published2013
Admission routes1
Has abstractyes

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