Bioenergetic deficits in peripheral nerve sensory axons during chemotherapy-induced neuropathic pain resulting from peroxynitrite-mediated post-translational nitration of mitochondrial superoxide dismutase
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Bibliographic record
Abstract
Many of the widely used anticancer drugs induce dose-limiting peripheral neuropathies that undermine their therapeutic efficacy. Animal models of chemotherapy-induced painful peripheral neuropathy (CIPN) evoked by a variety of drug classes, including taxanes, vinca alkaloids, platinum-complexes, and proteasome-inhibitors, suggest that the common underlying mechanism in the development of these neuropathies is mitotoxicity in primary nerve sensory axons (PNSAs) arising from reduced mitochondrial bioenergetics [eg adenosine triphosphate (ATP) production deficits due to compromised respiratory complex I and II activity]. The causative mechanisms of this mitotoxicity remain poorly defined. However, peroxynitrite, an important pro-nociceptive agent, has been linked to mitotoxicity in several disease states and may also drive the mitotoxicity associated with CIPN. Our findings reveal that the development of mechano-hypersensitivity induced by paclitaxel, oxaliplatin, and bortezomib was prevented by administration of the peroxynitrite decomposition catalyst Mn(III) 5,10,15,20-tetrakis(N-n-hexylpyridinium-2-yl)porphyrin (MnTE-2-PyP(5+)) without interfering with their anti-tumor effects. Peak CIPN was associated with the nitration and inactivation of superoxide dismutase in the mitochondria, but not in the cytosol, as well as a significant decrease in ATP production within the PNSAs; all of these events were attenuated by MnTE-2-PyP(5+). Our results provide continued support for the role of mitotoxicity in the development of CIPN across chemotherapeutic drug classes, and identify peroxynitrite as a key mediator in these processes, thereby providing the rationale towards development of "peroxynitrite-targeted" therapeutics for CIPN.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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) | 0.001 | 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 it