Progesterone prevents development of neuropathic pain in a rat model: Timing and duration of treatment are critical
Bibliographic record
Abstract
BACKGROUND: Progesterone is emerging as an important protective agent against various injuries to the nervous system. Neuroprotective and remyelinating effects have been documented for this neurosteroid, which is synthesized by, and acts on, the central and peripheral nervous systems. Neuropathic pain is a severe, persistent condition that is generally resistant to treatment, and poses major personal, social, and economic burdens. The purpose of this study was to determine if single-dose or repeated progesterone administration would alleviate tactile hypersensitivity in a rat model of neuropathic pain, and to determine if early versus late initiation of treatment has an effect on the outcome. METHODS: Rats were unilaterally implanted with a polyethylene cuff around the sciatic nerve, and sensitivity to von Frey filament stimulation was measured over approximately 12 weeks. RESULTS: Rats given progesterone starting one hour after cuff implantation, and daily until day 4, exhibited tactile hypersensitivity similar to that of vehicle-treated rats for the duration of the study. When progesterone was started one hour after cuff implantation and given daily until day 10, rats exhibited no tactile hypersensitivity in the later part of the study, after treatment had stopped. When progesterone treatment was initiated at 20 days, once the model had been fully established, and given daily for 4 or even 11 days, no differences in withdrawal thresholds were observed compared with controls. Progesterone did not have any effect on withdrawal thresholds when given as a single dose, as measured at 30, 60 and 90 minutes after administration. CONCLUSION: These results indicate that progesterone, when administered immediately after nerve injury, and for a sufficient period of time, can prevent the development of neuropathic pain, and may offer new strategies for the treatment of this highly debilitating condition.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".