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Record W4379538052 · doi:10.1167/iovs.64.7.13

MicroRNA 9 Is a Regulator of Endothelial to Mesenchymal Transition in Diabetic Retinopathy

2023· article· en· W4379538052 on OpenAlexafffund
Eric Wang, Biao Feng, Subrata Chakrabarti

Bibliographic record

VenueInvestigative Ophthalmology & Visual Science · 2023
Typearticle
Languageen
FieldMedicine
TopicRetinal Diseases and Treatments
Canadian institutionsWestern University
FundersCanadian Institutes of Health ResearchLawson Health Research Institute
KeywordsRegulatormicroRNAMesenchymal stem cellDiabetic retinopathyEpigeneticsPsychological repressionCell biologyCancer researchMedicineBiologyEndocrinologyDiabetes mellitusGeneticsGeneGene expression

Abstract

fetched live from OpenAlex

Purpose: Diabetic retinopathy (DR) is a significant cause of blindness. Most research around DR focus on late-stage developments rather than early changes such as early endothelial dysfunction. Endothelial-to-mesenchymal transition (EndMT), an epigenetically regulated process whereby endothelial cells lose endothelial characteristics and adopt mesenchymal-like phenotypes, contributes to early endothelial changes in DR. The epigenetic regulator microRNA 9 (miR-9) is suppressed in the eyes during DR. MiR-9 plays a role in various diseases and regulates EndMT-related processes in other organs. We investigated the role miR-9 plays in glucose-induced EndMT in DR. Methods: We examined the effects of glucose on miR-9 and EndMT using human retinal endothelial cells (HRECs). We then used HRECs and an endothelial-specific miR-9 transgenic mouse line to investigate the effect of miR-9 on glucose-induced EndMT. Finally, we used HRECs to probe the mechanisms through which miR-9 may regulate EndMT. Results: We found that miR-9 inhibition was both necessary and sufficient for glucose-induced EndMT. Overexpression of miR-9 prevented glucose-induced EndMT, whereas suppressing miR-9 caused glucose-like EndMT changes. We also found that preventing EndMT with miR-9 overexpression improved retinal vascular leakage in DR. Finally, we showed that miR-9 regulates EndMT at an early stage by regulating EndMT-inducing signals such as proinflammatory and TGF-β pathways. Conclusions: We have shown that miR-9 is an important regulator of EndMT in DR, potentially making it a good target for RNA-based therapy in early DR.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.454
Threshold uncertainty score0.588

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.002
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 head0.033
GPT teacher head0.347
Teacher spread0.314 · 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.

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

Citations20
Published2023
Admission routes2
Has abstractyes

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