Anti-allodynic Effect of Mangiferin in Rats With Chronic Post-ischemia Pain: A Model of Complex Regional Pain Syndrome Type I
Bibliographic record
Abstract
The present study reproduces chronic post-ischemia pain (CPIP), a model of complex regional pain syndrome type I (CRPS-I), in rats to examine the possible transient and long-term anti-allodynic effect of MG; as well as its potential beneficial interactions with some standard analgesic drugs and sympathetic-mediated vasoconstriction and vasodilator agents during the earlier stage of the pathology. A single dose of MG (50 and 100 mg/kg, p.o.) decreased mechanical allodynia 72 h post-ischemia-reperfusion (I/R). MG 100 mg/kg, i.p. (pre- vs. post-drug) increased von Frey thresholds in a yohimbine and naloxone-sensitive manner. Sub-effective doses of morphine, amitriptyline, prazosin, clonidine and a NO donor, SIN-1, in the presence of MG were found to be significantly anti-allodynic. A long-term anti-allodynic effect at 7 and 13 days post-I/R after repeated oral doses of MG (50 and 100 mg/kg) was also observed. Further, MG decreased spinal and muscle interleukin-1β concentration and restored muscle redox status. These results indicate that MG has a transient and long-term anti-allodynic effect in CPIP rats, that appears to be at least partially attributable to the opioid and α2 adrenergic receptors. Additionally, its anti-inflammatory and antioxidant mechanisms could also be implicated in this effect. The association of MG with sub-effective doses of these drugs enhances the anti-allodynic effect, however an isobolographic analysis should be performed to define a functional interaction between them. These findings suggest the possible clinical use of MG in the treatment of CRPS-I in both early sympathetically maintained pain and long-term sympathetically-independent pain.
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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 | 0.000 | 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 | 0.001 |
| 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".