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Record W2955297231 · doi:10.14740/wjon1211

Acute Myeloid Leukemia Acquiring Promyelocytic Leukemia-Retinoic Acid Receptor Alpha at Relapse

2019· article· en· W2955297231 on OpenAlexvenueno aff
Varsha Gupta, Mohammed Shariff, Ravneet Bajwa, Ishan Patel, Hashem Ayyad, Michael J. Levitt, Peter Mencel, Mohammad Hossain

Bibliographic record

VenueWorld Journal of Oncology · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinoids in leukemia and cellular processes
Canadian institutionsnot available
Fundersnot available
KeywordsAcute promyelocytic leukemiaArsenic trioxideMedicineMyeloid leukemiaRetinoic acidLeukemiaOncologyCancer researchTretinoinInternal medicineMyeloidRetinoic acid receptor alphaRetinoic acid receptorBiologyApoptosisCell culture

Abstract

fetched live from OpenAlex

Acute promyelocytic leukemia (APL) is identified as the M3 subtype of acute myeloid leukemia (AML). APL is presently one of the most curable leukemias. We describe here a rare case of APL who presented as a relapsed disease after 1 year of chemotherapy for AML. The patient lacked t(15;17) at the initial presentation but was present later at the time of relapse. The patient attained a complete remission following treatment with all-trans retinoic acid (ATRA) and arsenic trioxide-based therapy. We discuss the possible mechanism behind secondary acquisition of promyelocytic leukemia/retinoic acid receptor alpha (PML-RARA) at relapse of AML. We also briefly discuss the clinical features, diagnosis and treatment of APL.

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 categoriesMeta-epidemiology (narrow)
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 score0.404
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.256
Teacher spread0.248 · 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 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

Citations3
Published2019
Admission routes1
Has abstractyes

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