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Record W4289932153 · doi:10.3389/fncel.2022.916696

The role of hypoxia-associated miRNAs in acquired sensorineural hearing loss

2022· review· en· W4289932153 on OpenAlexaff
Sina Safabakhsh, Printha Wijesinghe, Morgan Nunez, Desmond A. Nunez

Bibliographic record

VenueFrontiers in Cellular Neuroscience · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related molecular mechanisms research
Canadian institutionsStornoway Diamond (Canada)Vancouver General HospitalUniversity of British Columbia
FundersFondation Pour l'Audition
KeywordsSensorineural hearing lossHearing lossHypoxia (environmental)MedicinemicroRNABioinformaticsOxidative stressAudiologyBiologyInternal medicineGeneticsGene

Abstract

fetched live from OpenAlex

Introduction: Sensorineural hearing loss (SNHL) is a prevalent sensory deficit presenting commonly as age-related hearing loss. Other forms of SNHL include noise-induced and sudden SNHL. Recent evidence has pointed to oxidative stress as a common pathogenic pathway in most subtypes of acquired SNHL. MicroRNAs (miRNAs) are small non-coding RNA sequences that suppress target mRNA expression and affect downstream processes. Many studies have shown that miRNAs are integral biomolecules in hypoxia-adaptive responses. They also promote apoptosis in response to oxidative stress resulting in SNHL. Our hypothesis is that miRNAs are involved in the pathophysiological responses to hypoxia and oxidative stress that result in SNHL. This study reviews the evidence for hypoxia-adaptive miRNAs (hypoxamiRs) in different types of acquired SNHL and focuses on miRNAs involved in hypoxia driven SNHL. Methods: Electronic bibliographic databases PubMed, Ovid MEDLINE, Ovid EMBASE, and Web of Science Core Collection were searched independently by two investigators for articles published in English from the inception of individual databases to the end of July 2020. The text word or medical subject heading searches of all fields, titles, abstracts, or subject headings depending on the database were undertaken with combinations of the words “microRNAs”, “hypoxia”, “hypoxamiRs”, “oxidative stress”, “ischemia” and “hearing loss”. The reference lists of studies meeting the inclusion criteria were searched to identify additional relevant studies. The inclusion criteria included relevant clinical studies with human subjects, animals, and in vitro experiments. The risk of bias was assessed using the Cochrane risk of bias assessment tool for human studies and the Systematic Review Center for Laboratory animal Experimentation (SYRCLE) a risk of bias assessment tool for animal model and in vitro studies. Results: A total of 15 primary articles were selected for full text screening after excluding duplicates, reviews, retracted articles, and articles not published in English. All nine articles meeting the study inclusion criteria were from animal or in vitro model studies and were assessed to be at low risk of bias. miRNAs miR-34a and miR-29b were reported to be involved in SNHL in inner ear cell models exposed to oxidative stress. Signaling pathways Sirtuin 1/peroxisome proliferator-activated receptor gamma coactivator-1-alpha (SIRT1/PGC-1α), SIRT1/p53, and SIRT1/hypoxia-inducible factor 1-alpha (HIF-1α) were identified as underlying pathways involved in acquired SNHL. Conclusion: There is evidence that miR-34a and -29b are involved in hypoxia-driven and other causes of oxidative stress-related acquired SNHL. Further studies are required to determine if these findings are clinically applicable.

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)0.002
metaresearch head score (Gemma)0.006
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.030
GPT teacher head0.292
Teacher spread0.262 · 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
GenreReview

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

Citations18
Published2022
Admission routes1
Has abstractyes

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