Selective activation of TRPV1+ sensory neurons in the pancreas halts islet autoimmunity and restore normoglycemia in Diabetic Non‐Obese Diabetic (NOD) mice
Bibliographic record
Abstract
Hyperglycemia, as a result of autoimmune destruction of insulin‐producing beta cells, is the clinical outcome in human type‐1 diabetics and in the NOD mouse model. Our lab recently reported that NOD mice possess a hypo‐functional mutation in the Transient Receptor Potential Vanilloid 1 (TRPV1), which is expressed on a major subset of sensory neurons and is associated with increased beta cell stress and T‐cell autoimmunity. Here, we demonstrate that TRPV1+ sensory innervations in the pancreas receive input from cutaneous thoracic 8–11 nerves on the chest wall. Stimulation of intercostal nerves by surgical transection or the application of a TRPV1 agonist directly on the axons triggers the release of vasodilatory neuropeptides (ex. Substance P) in the pancreas, as indicated by an increase in Evans Blue plasma extravasation. Surprisingly, nerve stimulation induces an acute (6–12 hr post) wave of T‐cell apoptosis in islet infiltrates and pancreas‐draining lymph node (pLN) in NOD.BDC2.5 T‐cell receptor transgenics and NOD wild‐type mice. Further analysis reveals a skewing of the ratio between pathogenic and regulatory T‐cells in the pLN to a more protective phenotype. Lastly, nerve stimulation restores long‐term normoglycemia in diabetic NOD mice, especially during the early phase of overt disease. Stimulation of TRPV+ neurons may be a novel therapy in Type‐1 Diabetes. Y.C. is supported by a CIHR studentship.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".