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Record W2999430242 · doi:10.1139/bcb-2019-0364

MiR-1180 promotes cardiomyocyte cell cycle re-entry after injury through the NKIRAS2–NFκB pathway

2020· article· en· W2999430242 on OpenAlexvenueno aff
Yuhui Ding, Liyuan Bi, Jun Wang

Post-publication record

OpenAlex flags this work as retracted, but it carries no matching Retraction Watch record in this frame.

Bibliographic record

VenueBiochemistry and Cell Biology · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiac Ischemia and Reperfusion
Canadian institutionsnot available
Fundersnot available
KeywordsCell biologyCell cycleCell injuryChemistryCellBiologyApoptosisBiochemistry

Abstract

fetched live from OpenAlex

Heart failure (HF) is associated with a considerable number of symptoms and significantly impaired health for humans, including reduced quality of life and physical functioning. Previous studies have indicated that miRNAs have important roles in regulating the development of HF. MiR-1180 is involved in the proliferation, migration, invasiveness, and chemoresistance of cancer cells; however, the underlying mechanisms and role of miR-1180 in the functioning of cardiomyocytes remains unclear. In this study, we found that miR-1180 promotes cell activity and cell cycle processes by driving energy generation through NKIRAS2, which declines over time during development. The expression of miR-1180 is down-regulated in cells subjected to hypoxia-reoxygenation, and use of an miR-1180 mimic significantly reduced myocardial injury and cell apoptosis. In addition, miR-1180 regulates the NFκB pathway through NKIRAS2 in cardiomyocytes. These findings suggest that miR-1180 maybe a novel therapeutic target for use in getting cardiomyocytes to re-enter the cell cycle as well as for cardiac repair following myocardial injury.

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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.007
GPT teacher head0.225
Teacher spread0.218 · 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

Citations8
Published2020
Admission routes1
Has abstractyes

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