Resiniferatoxin Mediated Ablation of TRPV1+ Neurons Removes TRPA1 as Well
Bibliographic record
Abstract
OBJECTIVES: Resiniferatoxin, the most potent agonist of inflammatory pain/vanilloid receptor/cation channel (TRPV1) can be used for neuron subtype specific ablation of pain generating cells at the level of the peripheral nervous system by Ca(2+)-excytotoxicity. Molecular neurosurgery is an emerging technology either to alleviate severe pain in cancer or treat/prevent different local neuropathies. Our aim was determining sensory modalities that may be lost after resiniferatoxin treatment. METHODS: Newborn or adult mice were treated with resiniferatoxin, then changes in chemical and heat sensitivity were correlated with alterations of the cell composition of sensory ganglions. RESULTS: Only mice treated at adult age became less sensitive to heat stimuli, while both treatment groups lost sensitivity to specific vanilloid agonists of TRPV1 and, interestingly, to allyl-isothiocyanate, a selective agonist of TRPA1. Our in vivo and post mortem analytical results confirmed that TRPV1 and TRPA1 function together and resiniferatoxin-mediated neurosurgery removes both sensor molecules. DISCUSSION: In adult mice resiniferatoxin causes: i) desensitization to heat and ii) sensitization to cold. Cold hyperalgesia, an imbalance in thermosensation, might be conferred by a prominent cold receptor that is expressed in surviving resiniferatoxin-resistant sensory neurons and compensates for pain signals lost with TRPA1 and TRPV1 double positive cells in the peripheral nervous system.
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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) | 0.000 | 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 | 0.001 |
| 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".