Adenosine Treatment Augments Random Flap Survival in Rats
Bibliographic record
Abstract
Adenosine and purine nucleosides are intermediates in the pathway of purine nucleotide degradation. Adenosine causes vasodilation in all arterioles, except those in the kidney, and is the major regulator of coronary blood flow. The objective of the present study was to investigate the efficacy and role of 9-beta-D-ribofuranosyl adenosine (RFA), a derivative of adenosine, for the augmentation of random flap survival in rats. Varying doses of adenosine and a nonselective adenosine antagonist, 8-phenyltheophylline, were administered before elevation of 3x10 cm dorsal random flaps in 60 rats. The rats were randomly assigned to five groups and received the following treatment: group I (controls) was treated with placebo (saline, 1 mL/day); group II was treated with RFA 25 μg/kg/day; group III was treated with RFA 50 μg/kg/day; group IV was treated with RFA 100 μg/kg/day; and group V was treated with 8-phenyltheophylline (10 mg/kg/day). All daily injections were given intravenously for seven days. Flap survival was assessed on day 8. Therapeutic and higher doses of adenosine-treated flaps showed a significant increase in viability compared with saline-treated flaps in the control group, while there was no improvement in flap survival with low dose adenosine. Phenyltheophylline reversed the beneficial effect of adenosine and increased flap necrosis, which was comparable with that of the controls. The findings show that adenosine can enhance flap survival, and this beneficial effect is possibly due to vasodilation, inhibition of noradrenalin release, reduction of energy consumption, inhibition of reactive oxygen species and a preconditioning effect; however, this effect seems to be dose-related. Adenosine is an easily available drug for clinical use in ischemic heart diseases and should be considered in potentially ischemic flaps.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".