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Record W3092945883 · doi:10.3390/ijms21207539

Role of microRNAs in Diagnosis, Prognosis and Management of Multiple Myeloma

2020· review· en· W3092945883 on OpenAlexaff
Amro M. Soliman, Seong Lin Teoh, Pasuk Mahakkanukrauh, Srijit Das

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2020
Typereview
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsmicroRNAMultiple myelomaMalignancyMedicineBone marrowDiseaseCancer researchHematological malignancyBioinformaticsPathologyOncologyInternal medicineBiologyGene

Abstract

fetched live from OpenAlex

Multiple myeloma (MM) is a cancerous bone disease characterized by malignant transformation of plasma cells in the bone marrow. MM is considered to be the second most common blood malignancy, with 20,000 new cases reported every year in the USA. Extensive research is currently enduring to validate diagnostic and therapeutic means to manage MM. microRNAs (miRNAs) were shown to be dysregulated in MM cases and to have a potential role in either progression or suppression of MM. Therefore, researchers investigated miRNAs levels in MM plasma cells and created tools to test their impact on tumor growth. In the present review, we discuss the most recently discovered miRNAs and their regulation in MM. Furthermore, we emphasized utilizing miRNAs as potential targets in the diagnosis, prognosis and treatment of MM, which can be useful for future clinical management.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.043
GPT teacher head0.372
Teacher spread0.329 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations22
Published2020
Admission routes1
Has abstractyes

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