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Record W2598764473 · doi:10.1002/cbin.10770

MicroRNA: an important regulator in acute myeloid leukemia

2017· review· en· W2598764473 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCell Biology International · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsNational Research Council Institute for Biodiagnostics
Fundersnot available
KeywordsmicroRNAMyeloid leukemiaBiologyHaematopoiesisCarcinogenesisRegulatorCancer researchLeukemiaEpigeneticsMyeloidBioinformaticsComputational biologyImmunologyGeneStem cellGenetics

Abstract

fetched live from OpenAlex

MicroRNAs (miRNAs) are a general class of endogenous non-coding RNAs with a length of 22 nucleotides, widely existing in diverse species and playing important roles in malignancies initiation and progression. MiRNAs are essential to many in vivo biological processes such as cell proliferation, apoptosis, immune response, and tumorigenesis. Significant progress till date has been made in understanding the roles of microRNAs in normal hematopoiesis and hematopoietic malignant diseases. In this review, we summarize the particular signatures of microRNAs in acute myeloid leukemia (AML) patients with specific karyotype and the clinical significance of microRNAs in early diagnosis and treatment. MicroRNAs hypermethylation was also proved to correlate with the pathogenesis of AML. However, the target genes and exact pathways of microRNAs participating in these processes are still unknown and more efforts need to be made in the near future.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.989
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.028
GPT teacher head0.336
Teacher spread0.309 · 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