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Record W4407039795 · doi:10.3390/ijms26031245

Serum and Plasma miRNA Expression Levels in Sudden Sensorineural Hearing Loss

2025· article· en· W4407039795 on OpenAlexafffund
Desmond A. Nunez, Reyhaneh Abgoon, Printha Wijesinghe, Cathie Garnis

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related molecular mechanisms research
Canadian institutionsOccupational Cancer Research CentreVancouver General HospitalVancouver Coastal Health Research InstituteUniversity of British ColumbiaVancouver Coastal Health
FundersVancouver Coastal Health Research InstituteFondation Pour l'Audition
KeywordsmicroRNAMedicineInternal medicineDiseaseReal-time polymerase chain reactionHearing lossGastroenterologyOncologyAudiologyBiologyGeneGenetics

Abstract

fetched live from OpenAlex

Sudden sensorineural hearing loss (SSNHL) is a rapidly developing acquired idiopathic disorder. Differential expressions of microRNAs (miRNAs) have been identified in the acute serum of SSNHL patients. miRNAs are transmitted in both serum and plasma, but it is unknown which better reflects changes associated with inner ear disease. Therefore, we sought to compare the serum and plasma miRNA expression levels in adult SSNHL patients. We extracted and reverse transcribed total RNA from serum and plasma, and analyzed the product with quantitative real-time PCR. hsa-miR-191-5p was used for normalization, and miRNA expression levels were calculated using the delta Ct method. Serum and plasma samples from 17 SSNHL patients (mean age 51.9 years, standard deviation 13.9 years) showed no significant differences in miR-128-3p, miR-132-3p, miR-375-3p, miR-590-5p, miR-30a-3p, miR-140-3p, miR-186-5p, and miR-195-5p expression levels on Wilcoxon signed-rank test analyses. We conclude that plasma and serum are equally suitable for investigating potential miRNA SSNHL disease markers.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.020
GPT teacher head0.337
Teacher spread0.317 · 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

Citations4
Published2025
Admission routes2
Has abstractyes

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