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Record W3046869044 · doi:10.1139/cjpp-2019-0559

miR-138-5p targets sirtuin1 to regulate acute lung injury by regulation of the NF-κB signaling pathway

2020· article· en· W3046869044 on OpenAlexvenueno aff
Yinshan Wu, Weiliang Jiang, Zhuhua Lu, Wei Su, Nan Liu, Feng Guo

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2020
Typearticle
Languageen
FieldMedicine
TopicSirtuins and Resveratrol in Medicine
Canadian institutionsnot available
Fundersnot available
KeywordsApoptosisOxidative stressSignal transductionNF-κBLipopolysaccharideCell biologyA549 cellInflammationViability assayMedicineCancer researchImmunologyPharmacologyBiologyInternal medicineBiochemistry

Abstract

fetched live from OpenAlex

Acute lung injury (ALI), a disease with a high mortality rate, is a noncardiogenic pulmonary inflammatory response and characterized by damage to the pulmonary system. In this study, we explored the mechanism of the occurrence and development of ALI. It was firstly found that miR-138-5p could inhibit the expression of sirtuin1 (SIRT1), and we further demonstrated that miR-138-5p targets directly SIRT1 through the luciferase assay, while the latter negatively regulated the expression of NF-κB. A549 cells were treated with lipopolysaccharide in vitro to simulate ALI cells and induce ALI in the model mice. The results showed that inhibiting the expression of miR-138-5p could effectively increase the viability of damaged cells, promote cell proliferation, reduce apoptosis, inhibit the inflammatory response, reduce oxidative stress, and then relieve ALI symptoms. Collectively, our results suggested that miR-138-5p can inhibit SIRT1 expression and indirectly activate the NF-κB signaling pathway, thus regulating the development of ALI.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.269
Teacher spread0.259 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations7
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Physiology and PharmacologySame topicSirtuins and Resveratrol in MedicineFrench-language works237,207