FeTMPyP a peroxynitrite decomposition catalyst ameliorated functional and behavioral deficits in chronic constriction injury induced neuropathic pain in rats
Bibliographic record
Abstract
Neuropathic pain is a maladaptive pain phenotype that results from injury or damage to the somatosensory nervous system and is proposed to be linked to a cascade of events including excitotoxicity, oxidative stress, mitochondrial dysfunction, neuroinflammation and apoptosis. Oxidative/nitrosative stress is a critical link between neuroinflammation and neurodegeneration through poly (ADP) ribose polymerase (PARP) overactivation. Hence, the present study investigated the antioxidant and anti-inflammatory effects of peroxynitrite decomposition catalyst; FeTMPyP in chronic constriction injury (CCI) of sciatic nerve-induced neuropathy in rats. CCI of the sciatic nerve manifested significant deficits in behavioral, biochemical, functional parameters and was markedly reversed by administration of FeTMPyP. After 14 days of CCI induction, oxidative/nitrosative stress and inflammatory markers such as iNOS, NF-kB, TNF-α and IL-6 were elevated in sciatic nerves of CCI rats along with depleted levels of ATP and elevated levels of poly (ADP) ribose (PAR) in both sciatic nerves in ipsilateral (L4-L5) dorsal root ganglions (DRG's), suggesting over activation of PARP. Additionally, CCI resulted in aberrations in mitochondrial function as evident by decreased Mn-SOD levels and respiratory complex activities with increased mitochondrial fission protein DRP-1. These changes were reversed by treatment with FeTMPyP (1 & 3 mg/kg, p.o.). Findings of this study suggest that FeTMPyP, by virtue of its antioxidant properties, reduced both PARP over-activation and subsequent neuroinflammation resulted in protection against CCI-induced functional, behavioral and biochemical deficits.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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 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".