Detection of free radicals in ischemic and reperfused canine gracilis muscle flaps by use of spin-trapping electron paramagnetic resonance spectroscopy
Bibliographic record
Abstract
OBJECTIVE: To determine whether free radicals are produced in ischemic and reperfused canine skeletal muscle, whether free radicals can be detected from effluent blood by use of spin-trapping electron paramagnetic resonance (EPR) spectroscopy, and whether free radical-induced skeletal muscle damage is detectable by use of light microscopy. ANIMALS: 6 healthy mixed-breed dogs. PROCEDURES: Dogs were anesthetized and both gracilis muscles were isolated, leaving only the major vascular pedicle intact. Ischemia was induced in 1 flap for 4 hours; the contralateral flap served as the control. Ischemic flaps were then reperfused for 15 minutes. alpha-Phenyl-N-tert-butylnitrone, a spin-trapping agent, was administered intravenously to each dog 1 hour prior to reperfusion. Following reperfusion, effluent blood samples from muscle flaps were obtained and processed for EPR spectroscopy. Muscle biopsy specimens were obtained for histologic evaluation, and dogs were euthanatized. RESULTS: Spin adducts were not detected in blood from control flaps. However, spin adducts were detected in all ischemic-reperfused muscle flaps. Principal signals identified were characteristic of oxygen- and carbon-centered radicals. Significantly more muscle damage was detected in ischemic-reperfused flaps, compared with control flaps. CONCLUSIONS AND CLINICAL RELEVANCE: Free radicals may be an important component of injury induced by ischemia and reperfusion of canine skeletal muscle. Spin-trap adducts of free radicals can be detected in effluent blood of canine muscle flaps by use of spin-trapping EPR spectroscopy. Spin-trapping EPR spectroscopy may be useful for the study of antioxidants and free radical scavengers in attenuating ischemia and reperfusion-mediated skeletal muscle damage.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".