Tetrodotoxin suppresses thermal hyperalgesia and mechanical allodynia in a rat full thickness thermal injury pain model
Bibliographic record
Abstract
Burn injuries have been identified as the primary cause of injury in 5% of U.S. military personnel evacuated from Operations Iraqi Freedom and Enduring Freedom. Severe burn-associated pain is typically treated with opioids such as fentanyl, morphine, and methadone. Side effects of opioids include respiratory depression, cardiac depression, decrease in motor and cognitive function, as well as the development of hyperalgesia, tolerance and dependence. These effects have led us to search for novel analgesics for the treatment of burn-associated pain in wounded combat service members. Tetrodotoxin (TTX) is a selective voltage-gated sodium channel blocker currently in clinical trials as an analgesic. A phase 3 clinical trial for cancer-related pain has been completed and phase 3 clinical trials on chemotherapy-induced neuropathic pain are planned. It has also been shown in mice to inhibit the development of chemotherapy-induced neuropathic pain. TTX was originally identified as a neurotoxin in marine animals but has now been shown to be safe in humans at therapeutic doses. The antinociceptive effects of TTX are thought to be due to inhibition of Na(+) ion influx required for initiation and conduction of nociceptive impulses. One TTX sensitive sodium channel, Nav1.7, has been shown to be essential in lowering the heat pain threshold after burn injuries. To date, the analgesic effect of TTX has not been tested in burn-associated pain. Male Sprague-Dawley rats were subjected to a full thickness thermal injury on the right hind paw. TTX (8 μg/kg) was administered once a day systemically by subcutaneous injection beginning 3 days post thermal injury and continued through 7 days post thermal injury. Thermal hyperalgesia and mechanical allodynia were assessed 60 and 120 min post injection on each day of TTX treatment. TTX significantly reduced thermal hyperalgesia at all days tested and had a less robust, but statistically significant suppressive effect on mechanical allodynia. These results suggest that systemic TTX may be an effective, rapidly acting analgesic for battlefield burn injuries and has the potential for replacing or reducing the need for opioid analgesics.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".