Bortezomib-induced neuropathy is in part mediated by the sensitization of TRPV1 channels
Bibliographic record
Abstract
TRPV1 is an ion channel that transduces noxious heat and chemical stimuli and is expressed in small fiber primary sensory neurons that represent almost half of skin nerve terminals. Tissue injury and inflammation result in the sensitization of TRPV1 and sustained activation of TRPV1 can lead to cellular toxicity though calcium influx. To identify signals that trigger TRPV1 sensitization after a 24-h exposure, we developed a phenotypic assay in mouse primary sensory neurons and performed an unbiased screen with a compound library of 480 diverse bioactive compounds. Chemotherapeutic agents, calcium ion deregulators and protein synthesis inhibitors were long-acting TRPV1 sensitizers. Amongst the strongest TRPV1 sensitizers were proteasome inhibitors, a class that includes bortezomib, a chemotherapeutic agent that causes small fiber neuropathy in 30-50% of patients. Prolonged exposure of bortezomib produced a TRPV1 sensitization that lasted several days and neurite retraction in vitro and histological and behavioral changes in male mice in vivo. TRPV1 knockout mice were protected from epidermal nerve fiber loss and a loss of sensory discrimination after bortezomib treatment. We conclude that long-term TRPV1 sensitization contributes to the development of bortezomib-induced neuropathy and the consequent loss of sensation, major deficits experienced by patients under this chemotherapeutic agent.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".