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Record W2795607856 · doi:10.1530/rep-17-0603

MicroRNAs: crucial regulators of placental development

2018· review· en· W2795607856 on OpenAlexafffund
Heyam Hayder, Jacob A. O’Brien, Uzma Nadeem, Chun Peng

Bibliographic record

VenueReproduction · 2018
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsToronto Metropolitan UniversityYork University
FundersCanadian Institutes of Health Research
KeywordsmicroRNATrophoblastBiologyPlacentaAngiogenesisVasculogenesisCell biologyBiogenesisRegulation of gene expressionBioinformaticsComputational biologyGeneFetusGeneticsPregnancyStem cell

Abstract

fetched live from OpenAlex

MicroRNAs (miRNAs) are small non-coding single-stranded RNAs that are integral to a wide range of cellular processes mainly through the regulation of translation and mRNA stability of their target genes. The placenta is a transient organ that exists throughout gestation in mammals, facilitating nutrient and gas exchange and waste removal between the mother and the fetus. miRNAs are expressed in the placenta, and many studies have shown that miRNAs play an important role in regulating trophoblast differentiation, migration, invasion, proliferation, apoptosis, vasculogenesis/angiogenesis and cellular metabolism. In this review, we provide a brief overview of canonical and non-canonical pathways of miRNA biogenesis and mechanisms of miRNA actions. We highlight the current knowledge of the role of miRNAs in placental development. Finally, we point out several limitations of the current research and suggest future directions.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.025
GPT teacher head0.299
Teacher spread0.274 · 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 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

Citations153
Published2018
Admission routes2
Has abstractyes

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