Brain-Gut Axis: Invasive and Noninvasive Vagus Nerve Stimulation, Limitations, and Potential Therapeutic Approaches
Bibliographic record
Abstract
Inflammatory bowel disease (IBD) is a chronic relapsing condition with no known etiology and is characterized by disrupted gut homeostasis, chronic inflammation, and ulcerative lesions. Although current treatments can reduce disease activity, IBD frequently recurs once treatments are discontinued, indicating that treatments are ineffective in providing long-term remission. The lack of responsiveness and reluctance of some affected persons to take medications because of potential adverse effects has enhanced the need for novel therapeutic approaches. The vagus nerve (VN) is likely important in the pathogenesis of IBD, considering the decreased activity of the parasympathetic nervous system, especially the VN, and the impaired interaction between the enteric nervous system and central nervous system in patients with IBD. Vagus nerve stimulation (VNS) has demonstrated anti-inflammatory effects in various inflammatory disorders, including IBD, by inhibiting the production of inflammatory cytokines by immune cells. It has been suggested that stimulating the vagus nerve to induce its anti-inflammatory effects may be a potential therapeutic approach for IBD. Noninvasive techniques for VNS have been developed. Considering the importance of VN function in the brain-gut axis, VNS is a promising treatment option for IBD. This review discusses the potential therapeutic advantages and drawbacks of VNS, particularly the use of noninvasive transcutaneous auricular vagus nerve stimulation.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".