Mitochondrial and Bioenergetic Dysfunction in Trauma-Induced Painful Peripheral Neuropathy
Bibliographic record
Abstract
BACKGROUND: Mitochondrial dysfunction is observed in various neuropathic pain phenotypes, such as chemotherapy induced neuropathy, diabetic neuropathy, HIV-associated neuropathy, and in Charcot-Marie-Tooth neuropathy. To investigate whether mitochondrial dysfunction is present in trauma-induced painful mononeuropathy, a time-course of mitochondrial function and bioenergetics was characterized in the mouse partial sciatic nerve ligation model. RESULTS: Traumatic nerve injury induces increased metabolic indices of the nerve, resulting in increased oxygen consumption and increased glycolysis. Increased metabolic needs of the nerve are concomitant with bioenergetic and mitochondrial dysfunction. Mitochondrial dysfunction is characterized by reduced ATP synthase activity, reduced electron transport chain activity, and increased futile proton cycling. Bioenergetic dysfunction is characterized by reduced glycolytic reserve, reduced glycolytic capacity, and increased non-glycolytic acidification. CONCLUSION: Traumatic peripheral nerve injury induces persistent mitochondrial and bioenergetic dysfunction which implies that pharmacological agents which seek to normalize mitochondrial and bioenergetic dysfunction could be expected to be beneficial for pain treatment. Increases in both glycolytic acidification and non-glycolytic acidification suggest that pH sensitive drugs which preferentially act on acidic tissue will have the ability to preferential act on injured nerves without affecting healthy tissues.
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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".