A novel selective cooling system for the brain: feasibility study in rabbits vs piglets
Bibliographic record
Abstract
BACKGROUND: Selective brain cooling (SBC) methods could alleviate the complications associated with systemic hypothermia. The authors (MFB, LK, and T-YL) have developed a simple and an effective nasopharyngeal SBC method using a vortex tube. The primary focus of the study is to evaluate the effectiveness of this approach on rabbits and compare it with our previous published finding on piglets, which are mammals without and with a carotid rete, respectively. METHODS: Experiments were conducted on six rabbits. Body temperature was measured continuously using an esophageal temperature probe while brain temperature was measured with an implanted thermometer. Two successive experiments were performed on each animal. In the first experiment, brain cooling was initiated by blowing room temperature air from the hospital medical air outlet, at a flow rate of 14-15 L/min into both nostrils for 60 min. The second series of measurements and brain cooling was performed in the same manner as the first one but blowing cold air (- 7 °C) at the same flow rate. RESULTS: One hour post cooling with room temperature air at a flow rate of 14-15 L/min, the brain temperature was 34.2 ± 1.2 °C which resulted in mean brain cooling rates of 3.7 ± 0.9 °C/h. Brain temperature could be reduced more rapidly at mean rates of 5.2 ± 1.9 °C/h, while the body temperature as measured by the esophageal temperature probe was maintained above 36 °C during cooling and maintaining period. CONCLUSIONS: We have demonstrated that using the vortex tube allows initial rapid and SBC in rabbits. Moreover, comparing results between piglets and rabbits demonstrates clearly that the lack of a carotid rete does not prevent specific cooling of the brain by means of the nasopharyngeal method.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".