Sensitivity of functional targeted neuropeptide evaluation in testing pregabalin analgesic efficacy in a rat model of osteoarthritis pain
Bibliographic record
Abstract
The monosodium iodoacetate (MIA)-induced joint degeneration in rats is the most used animal model to screen analgesic drugs to alleviate osteoarthritis (OA) pain. This study aimed to evaluate the analgesic efficacy of pregabalin (PGB) in an MIA-induced OA model in rodents by using functional and neuroproteomic pain assessment methods. Treatment group included PGB in curative intent over 9 days compared to gold standard therapy (positive controls) and placebo (negative control). Functional assessments of pain (quantitative sensory testing and operant test) were performed concomitantly with spinal neuropeptides quantification. At day 21 post-OA induction, PGB in MIA rats reduced tactile allodynia (P = 0.028) and improved the place escape/avoidance behaviour (P = 0.04) compared to values recorded at last time-point before initiating analgesic therapy. All spinal neuropeptide concentrations, such as substance P, calcitonin gene-related peptide, bradykinin and somatostatin, came back to normal (non-affected) rat values, compared to their increase observed in MIA rats receiving the placebo (P < 0.0001). Initiated 13 days after chemical OA induction, repeated medication with PGB provided analgesia according to quantitative sensory testing, operant test and targeted neuropeptides pain assessment methods. This report highlights the interest of using reliable and sensitive methods like targeted neuropeptide quantification to detect the analgesic effects of a test article with concomitant functional assessments of pain when studying OA pain components.
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How this classification was reachedexpand
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 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".