Abstract TP109: Impact of ATP-Induced Mild Hypothermia on Focal Cerebral Ischemia in Rats
Bibliographic record
Abstract
Brain ischemia is a devastating disorder without effective therapies. One of the most promising approaches to attenuate ischemic brain injury is mild hypothermia. Recent studies show that adenosine nucleotides can induce hypothermia in mice. The purpose of the present study was to test the hypothesis that ATP, a common form of energy currency, induces mild hypothermia in rats and reduces brain injury following focal cerebral ischemia. ATP solution was dissolved in water and intraperitoneally injected; and focal stroke was induced by a suture model of middle cerebral artery occlusion and ischemic outcomes were evaluated within 24 hr. We found that injections of ATP lowered core body temperature in a dose-dependent manner; the dose appropriate for subsequent experiments was 2 g/kg as it reduced temperature to the range of mild hypothermia for approximately 7 hours. While intravenous injection of ATP was less effective in lowering body temperature. However, when ATP-induced hypothermia was applied to stroke, a neuroprotective effect was not observed. In contrast, the infarct volume grew even larger in ATP-treated rats. Not surprisingly, this was accompanied by an increased rate of seizure events, hemorrhagic transformation, and higher mortality. Continuous monitoring of physiological parameters revealed that ATP severely reduced heartbeat rate and blood pressure. ATP also raised blood glucose to dangerous levels and this was accompanied by severe acidosis and hypocalcemia. Western blotting showed that ATP treatment decreased levels of both phospho-Akt and total-Akt in the ischemic cortex. Our results reveal that, despite inducing hypothermia, ATP is not appropriate for protecting the brain against stroke, as it is associated with exaggerated ischemic outcomes and dangerous systemic side effects.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".