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miR-638: A Promising Cancer Biomarker with Therapeutic Potential

2022· review· en· W4225527496 on OpenAlexaff
Elham Hasheminasabgorji, Mohammad Amir Mishan, Mohammad Amin Khazeei Tabari, Abouzar Bagheri

Bibliographic record

VenueCurrent Molecular Medicine · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsUniversity of Calgary
FundersMazandaran University of Medical Sciences
KeywordsmicroRNACancerBiomarkerMedicineCancer researchDiagnostic biomarkerCancer biomarkersBioinformaticsBiologyComputational biologyInternal medicineGeneGenetics

Abstract

fetched live from OpenAlex

BACKGROUND: There is an unmet need to improve the diagnosis of cancer with precise treatment strategies. Therefore, more powerful diagnostic, prognostic, and therapeutic biomarkers are needed to overcome tumor cells. microRNAs (miRNAs, miRs), as a class of small non-coding RNAs, play essential roles in cancer through the tumor-suppressive or oncogenic effects by post-transcriptional regulation of their targets. Many studies have provided shreds of evidence on aberrantly expressed miRNAs in numerous cancers and have shown that miRNAs could play potential roles as diagnostic, prognostic, and even therapeutic biomarkers in patients with cancers. Findings have revealed that miR-638 over or underexpression might play a critical role in cancer initiation, development, and progression. However, the mechanistic effects of miR-638 on cancer cells are still controversial. CONCLUSION: In the present review, we have focused on the diagnostic, prognostic, and therapeutic potentials of miR-638 and discussed its mechanistic roles in various types of cancers.

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)0.000
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 score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.052
GPT teacher head0.363
Teacher spread0.311 · 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 designNot applicable
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

Citations10
Published2022
Admission routes1
Has abstractyes

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