Neuroprotective potential of saroglitazar in <scp>6‐OHDA</scp> induced Parkinson's disease in rats
Bibliographic record
Abstract
Parkinson's disease (PD) is a neurodegenerative disorder that affects 2%-3% of the population worldwide. Clinical presentation of PD includes motor and non-motor symptoms. The interplay between pathogenic factors such as increased oxidative stress, neuroinflammation, mitochondrial dysfunction and apoptosis are responsible for neurodegeneration in PD. Intrastriatal administration of 6-hydroxy dopamine (6-OHDA) in rat brain provoked oxidative and nitrosative stress by decreasing endogenous antioxidants such as superoxide dismutase, catalase, glutathione, glutathione peroxidase and glutathione reductase. Consequently, interleukin-6, tumour necrosis-α, interferon-γ and cyclooxygenase-2 mediated neuroinflammation leads to mitochondrial dysfunction, involving inhibition of complex-II and IV activities, followed by apoptosis and degeneration of striatal dopaminergic neurons. Degeneration of dopaminergic neurons resulted in reduced dopamine turnover, consequently induced behavioural abnormalities in rats. Activation of peroxisome proliferator-activated receptors (PPARs) have protective role in PD by modulating response of antioxidant enzymes, neuroinflammation and apoptosis in various animal models of PD. Saroglitazar (SG) being dual PPAR-α/γ agonist activates both PPAR-α and PPAR-γ receptors and provide neuroprotection by reducing oxidative stress, neuroinflammation, mitochondrial dysfunction and apoptosis of dopaminergic cells in 6-OHDA induced PD in rats. Thereby, SG restored striatal histopathological damage and dopamine concentration in rat striatum, and behavioural alterations in rats. Thus, SG proved neuroprotective effects in rat model of PD. Potential benefits of SG in rat model of PD advocates to consider it for further preclinical and clinical evaluation.
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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) | 0.001 | 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) | 0.002 | 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".