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Record W2783138054 · doi:10.14740/jh365w

Role of Nucleophosmin Gene Mutation in Leukemogenesis of Acute Myeloid Leukemia

2018· article· en· W2783138054 on OpenAlexvenueno aff
Safaa A. A. Khaled, John Burthem, El-Badry E. Abo Elnoor, Lobna F. ElToni, Hanan Ahmed, Sohier M. Ahmed

Bibliographic record

VenueJournal of Hematology · 2018
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsnot available
FundersShaqra University
KeywordsNucleophosminMyeloid leukemiaMitosisCancer researchCell cycleBiologyCell cultureMutationLeukemiaHaematopoiesisCell growthMyeloidGene mutationStem cellCellGeneCell biologyImmunologyGenetics

Abstract

fetched live from OpenAlex

BACKGROUND: AML through studying its contribution in proliferation of AML cell line cells. METHODS: Two types of human leukemia cell lines were used. One of them was a model for AMLs with mNPM and the other for AMLs with wild type (wt) NPM. Assessment of the proliferative role of mNPM in AML was carried out using cell culture and viability studies. The obtained results were reaffirmed by immunocytochemical and immunoblotting techniques. RESULTS: Analysis of results was done with the appropriate computer software. It showed higher proliferative potential of cells with mNPM compared to those bearing wtNPM only. Furthermore, the immunocytochemical studies demonstrated subcellular localization of NPM isoforms during various phases of mitosis. Mitosis was associated with cytoplasmic translocation of wtNPM in certain phases, while localization of mNPM remained unchanged throughout the cell cycle. Results of immunoblotting showed little or no change in protein expression of either NPM moieties during mitosis. CONCLUSIONS: The current study demonstrated important contribution of NPM gene mutation in enhancing proliferation of AML cell lines. These results confirmed the role of mNPM in AML leukemogenesis, and highlighted the importance of targeting mNPM in new evolving AML therapies.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.022
Threshold uncertainty score0.487

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.013
GPT teacher head0.297
Teacher spread0.284 · 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.

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

Citations6
Published2018
Admission routes1
Has abstractyes

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