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

MicroRNAs: crucial regulators of placental development

2018· review· en· W2795607856 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.
fundA Canadian funder is recorded on the work.

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.960
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 science0.0000.000
Research integrity0.0000.000
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 head0.025
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