Selection of preclinical models to evaluate intranasal brain cooling for acute ischemic stroke
Bibliographic record
Abstract
Stroke accounts for a large proportion of global mortality and morbidity. Selective hypothermia, via intranasal cooling devices, is a promising intervention in acute ischemic stroke. However, prior to large clinical trials, preclinical studies in large animal models of ischemic stroke are needed to assess the efficacy, safety, and feasibility of intranasal cooling for selective hypothermia as a neuroprotective strategy. Here, we review the available scientific literature for evidence supporting selective hypothermia and make recommendations of a preclinical, large, animal-based, ischemic stroke model that has the greatest potential for evaluating intranasal cooling for selective hypothermia and neuroprotection. We conclude that among large animal models of focal ischemic stroke including pigs, sheep, dogs, and nonhuman primates (NHPs), cynomolgus macaques have nasal anatomy, nasal vasculature, neuroanatomy, and cerebrovasculature that are most similar to those of humans. Moreover, middle cerebral artery stroke in cynomolgus macaques produces functional and behavioral deficits that are quantifiable to a greater degree of precision and detail than those that can be revealed through available assessments for other large animals. These NHPs are also amenable to extensive neuroimaging studies as a means of monitoring stroke evolution and evaluating infarct size. Hence, we suggest that cynomolgus macaques are best suited to assess the safety and efficacy of intranasal selective hypothermia through an evaluation of hyperacute diffusion-weighted imaging and subsequent investigation of chronic functional recovery, prior to randomized clinical trials in humans.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".