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Record W4394269177 · doi:10.6084/m9.figshare.19448246

Circ<i>RIMKLB</i> promotes myoblast proliferation and inhibits differentiation by sponging <i>miR-29c</i> to release <i>KCNJ12</i>

2022· dataset· en· W4394269177 on OpenAlexaff
Jian Wang, Yifan Wen, Jiawei Xu, Binglin Yue, Jialin Zhong, Li Zheng, Chuzhao Lei, Hong Chen, Yongzhen Huang

Bibliographic record

VenueFigshare · 2022
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCircular RNAs in diseases
Canadian institutionsInstitute for Clinical Evaluative SciencesPublic Health OntarioUniversity of TorontoHealth Canada
Fundersnot available
KeywordsChemistryCell biologyBiology

Abstract

fetched live from OpenAlex

Muscle development is a complex process that was regulated by many factors, among which non-coding RNAs (ncRNAs) play a vital role in regulating multiple life activities of muscle cells. Circular RNA (circRNA), a type of non-coding RNA with closed-loop structure, has been reported to affect multiple life processes. However, the roles of circRNAs on muscle development have not been fully elucidated. The present study aimed to determine whether and how circ<i>RIMKLB</i> affects muscle development. Our study revealed that circ<i>RIMKLB</i> promoted myoblast proliferation and inhibited differentiation. Besides, <i>miR-29</i>c was proved as a downstream target of circ<i>RIMKLB</i> using dual-luciferase reporter assay and RNA-binding protein immunoprecipitation (RIP) assay. Also, potassium inwardly rectifying channel subfamily J member 12 (<i>KCNJ12</i>) was identified as a novel target of <i>miR-29c</i> via dual-luciferase reporter assay, quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR), and western blot. Circ<i>RIMKLB</i> and <i>KCNJ12</i> were both proved to regulate cell cycle on muscle regeneration after injury <i>in vivo</i>. In conclusion, we demonstrated that circ<i>RIMKLB</i> sponged <i>miR-29c</i>, releasing <i>KCNJ12</i> to regulate myoblast proliferation and differentiation and regulating cell cycle during muscle regeneration after injury <i>in vivo</i>.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.032
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0320.000

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 head0.009
GPT teacher head0.230
Teacher spread0.221 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2022
Admission routes1
Has abstractyes

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