Predictive and concurrent validity of pain sensitivity phenotype, neuropeptidomics and neuroepigenetics in the MI-RAT osteoarthritic surgical model in rats
Bibliographic record
Abstract
Background Micro-RNAs could provide great insights about the neuropathological mechanisms associated with osteoarthritis (OA) pain processing. Using the validated Montreal Induction of Rat Arthritis Testing (MI-RAT) model, this study aimed to characterize neuroepigenetic markers susceptible to correlate with innovative pain functional phenotype and targeted neuropeptide alterations. Methods Functional biomechanical, somatosensory sensitization (peripheral–via tactile paw withdrawal threshold; central–via response to mechanical temporal summation), and diffuse noxious inhibitory control (via conditioned pain modulation) alterations were assessed sequentially in OA (n = 12) and Naïve (n = 12) rats. Joint structural, targeted spinal neuropeptides and differential expression of spinal cord micro-RNAs analyses were conducted at the sacrifice (day (D) 56). Results The MI-RAT model caused important structural damages (reaching 35.77% of cartilage surface) compared to the Naïve group (P < 0.001). This was concomitantly associated with nociceptive sensitization: ipsilateral weight shift to the contralateral hind limb (asymmetry index) from −55.61% ± 8.50% (D7) to −26.29% ± 8.50% (D35) (P < 0.0001); mechanical pain hypersensitivity was present as soon as D7 and persisting until D56 (P < 0.008); central sensitization was evident at D21 (P = 0.038); pain endogenous inhibitory control was distinguished with higher conditioned pain modulation rate (P < 0.05) at D7, D21, and D35 as a reflect of filtrated pain perception. Somatosensory profile alterations of OA rats were translated in a persistent elevation of pro-nociceptive neuropeptides substance P and bradykinin, along with an increased expression of spinal miR-181b (P = 0.029) at D56. Conclusion The MI-RAT OA model is associated, not only with structural lesions and static weight-bearing alterations, but also with a somatosensory profile that encompasses pain centralized sensitization, associated to active endogenous inhibitory/facilitatory controls, and corresponding neuropeptidomic and neuroepigenetic alterations. This preliminary neuroepigenetic research confirms the crucial role of pain endogenous inhibitory control in the development of OA chronic pain (not only hypersensitivity) and validates the MI-RAT model for its study.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".