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Record W3163066072 · doi:10.3390/curroncol28030166

Leukemia Cell Lines: In Vitro Models for the Study of Chronic Neutrophilic Leukemia

2021· article· en· W3163066072 on OpenAlexvenueno aff
Hans G. Drexler, Stefan Nagel, Hilmar Quentmeier

Bibliographic record

VenueCurrent Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsnot available
Fundersnot available
KeywordsNeuroblastoma RAS viral oncogene homologLeukemiaFusion geneGeneBiologyCancer researchMutationComputational biologyGenetics

Abstract

fetched live from OpenAlex

Chronic neutrophilic leukemia (CNL) is a rare myeloproliferative neoplasm that is genetically characterized by the absence of both the Philadelphia chromosome and BCR-ABL1 fusion gene and the high prevalence of mutations in the colony-stimulating factor 3 receptor (CSF3R). Additional disease-modifying mutations have been recognized in CNL samples, portraying a distinct mutational landscape. Despite the growing knowledge base on genomic aberrations, further progress could be gained from the availability of representative models of CNL. To address this gap, we screened a large panel of available leukemia cell lines, followed by a detailed mutational investigation with focus on the CNL-associated candidate driver genes. The sister cell lines CNLBC-1 and MOLM-20 were derived from a patient with CNL and carry CNL-typical molecular hallmarks, namely mutations in several genes, such as CSF3R, ASXL1, EZH2, NRAS, and SETBP1. The use of these validated and comprehensively characterized models will benefit the understanding of the pathobiology of CNL and help inform therapeutic strategies.

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)0.001
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.111
GPT teacher head0.405
Teacher spread0.293 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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