MétaCan
Menu
Back to cohort
Record W4313396422 · doi:10.3389/fendo.2022.1118426

Editorial: MicroRNAs in endocrinology and cell signaling

2022· editorial· en· W4313396422 on OpenAlexaff
Chun Peng, Julang Li

Bibliographic record

VenueFrontiers in Endocrinology · 2022
Typeeditorial
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsUniversity of GuelphYork University
Fundersnot available
KeywordsmicroRNABiologyBioinformaticsSignal transductionInternal medicineComputational biologyEndocrinologyMedicineCell biologyGeneticsGene

Abstract

fetched live from OpenAlex

MicroRNAs in endocrinology and cell signalingSince the discovery of the first microRNA (miRNA) in C. elegans (1), our understanding of miRNA biology has been constantly expanding.It is now wellestablished that miRNAs play key roles in regulating gene expression and thereby being critically involved in the proper functioning of cells, tissues, and organisms.The role of miRNAs in the endocrine system and cellular signaling events has also been clearly revealed.They regulate the development of endocrine glands, control hormone production and secretion, and modulate the activity of hormones by affecting their receptors and intracellular signaling networks.Conversely, hormones and various cellular signaling pathways also regulate miRNA biogenesis.Finally, miRNAs are detected in body fluids and are proposed to have hormone-like activities (2-7).The proper production and activity of miRNAs ensure the normal functioning of organisms while their dysregulation is associated with the development of diseases.Many studies have reported that miRNAs regulate the differentiation, proliferation, and apoptosis of hormone-producing cells.For example, miRNAs play important roles in modulating pancreatic b cell differentiation, growth and survival, and dysregulation of miRNAs has been observed in diabetic patients (8).Similarly, miRNAs regulate thyroid follicular cell proliferation and differentiation, while aberrant expression of miRNAs contributes to the development of diseases, such as goiter and thyroid cancer (9).MicroRNAs alter the production and secretion of hormones, growth factors, and other intercellular signaling molecules.For peptide hormones, miRNAs can directly target the genes encoding signaling molecules (10, 11) or indirectly by targeting genes that control their production (12).They can also target genes involved in exocytosis and therefore affecting the secretion of hormones, such as insulin (13).For non-peptide hormones, miRNAs regulate the expression of enzymes involved in hormone production or degradation.For example, several miRNAs have been reported to regulate aromatase expression and thereby affecting estradiol production (14, 15).MicroRNAs are major regulators of intracellular signaling events.They regulate the levels and/or activation of receptors and downstream mediators of hormones, growth factors, and other signaling molecules.For example, many miRNAs are known to target Frontiers in Endocrinology frontiersin.org01

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)0.004
metaresearch head score (Gemma)0.011
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.022
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0040.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0030.001
Science and technology studies0.0020.002
Scholarly communication0.0050.004
Open science0.0030.002
Research integrity0.0100.014
Insufficient payload (model declined to judge)0.0220.016

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 head0.004
GPT teacher head0.227
Teacher spread0.222 · 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
GenreEditorial

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

Citations4
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in EndocrinologySame topicMicroRNA in disease regulationFrench-language works237,207