A review of the auditory-gut-brain axis
Bibliographic record
Abstract
Hearing loss places a substantial burden on medical resources across the world and impacts quality of life for those affected. Further, it can occur peripherally and/or centrally. With many possible causes of hearing loss, there is scope for investigating the underlying mechanisms involved. Various signaling pathways connecting gut microbes and the brain (the gut-brain axis) have been identified and well established in a variety of diseases and disorders. However, the role of these pathways in providing links to other parts of the body has not been explored in much depth. Therefore, the aim of this review is to explore potential underlying mechanisms that connect the auditory system to the gut-brain axis. Using select keywords in PubMed, and additional hand-searching in google scholar, relevant studies were identified. In this review we summarize the key players in the auditory-gut-brain axis under four subheadings: anatomical, extracellular, immune and dietary. Firstly, we identify important anatomical structures in the auditory-gut-brain axis, particularly highlighting a direct connection provided by the vagus nerve. Leading on from this we discuss several extracellular signaling pathways which might connect the ear, gut and brain. A link is established between inflammatory responses in the ear and gut microbiome-altering interventions, highlighting a contribution of the immune system. Finally, we discuss the contribution of diet to the auditory-gut-brain axis. Based on the reviewed literature, we propose numerous possible key players connecting the auditory system to the gut-brain axis. In the future, a more thorough investigation of these key players in animal models and human research may provide insight and assist in developing effective interventions for treating hearing loss.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".