Exploring the Therapeutic Potential of Transcutaneous Vagus Nerve Stimulation in ALS-Related Inflammation and Depression
Bibliographic record
Abstract
Introduction: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder characterized by progressive motor neuron loss and muscle control impairment.1,2 Chronic inflammation, driven by elevated cytokines, exacerbates ALS symptoms. Since ALS patients typically maintain cognitive function, they are aware of their symptoms, which can lead to depression. Depression amplifies the inflammatory response in ALS patients creating a self-perpetuating cycle.3,4,5,6,7 Transcutaneous vagus nerve stimulation (tVNS) is a non-invasive method shown to reduce inflammation in other conditions, but remains unexplored in ALS and comorbid depression.5,8,9,10 This study investigates the therapeutic potential of tVNS in mitigating the positive feedback loop between ALS, depression, and inflammation. Methods: Fifty adults (18+), diagnosed with ALS and comorbid depression, will be randomly allocated to the treatment or control group in a double-blind study.11,12,13,14 tVNS will be delivered via Ag/AgCl electrodes on the left ear twice daily for thirty minutes, five days per week, for twelve weeks, starting at 1 mA, with current adjusted based on participant tolerability.12 Treatment groups will receive stimulation at the left inner tragus, targeting vagal afferents, while control groups will receive stimulation at the left posterior earlobe, a site with minimal vagal innervation.11 Cytokine levels (IL-1β, TNF-α, IL-6) will be quantified through RT-qPCR. Depression and ALS symptoms will be measured at baseline, post-treatment, and six months post-intervention, using the ALS Functional Rating Scale-Revised and American Psychological Association’s Severity Measure for Depression.15,16 Data will be analyzed using a two-way mixed ANOVA. Findings: We anticipate reduced cytokine levels and improved ALS & depression symptoms in the treatment group compared to controls. These findings have potential to holistically enhance quality of life for ALS patients, alleviating physical and psychological burdens.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".