Training the Brain to Survive Stroke
Bibliographic record
Abstract
Background: Presently, little can be done to repair brain tissue after stroke damage. We hypothesized that the mammalian brain has an intrinsic capacity to adapt to low oxygen which would improve outcome from a reversible hypoxic/ischemic episode. Acclimation to chronic hypoxia causes increased capillarity and tissue oxygen levels which may improve the capacity to survive ischemia. Identification of these adaptations will lead to protocols which high risk groups could use to improve recovery and reduce costs. Methods and Findings: Rats were exposed to hypoxia (3 weeks living at K an atmosphere). After acclimation, capillary density was measured morphometrically and was increased by 30% in the cortex. Novel implantable oxygen sensors showed that partial pressure of oxygen in the brain was increased by 40% in the normal cortex. Infarcts were induced in brain with 1 h reversible middle cerebral artery occlusions. After ischemia (48 h) behavioural scores were improved and T2 weighted MRI lesion volumes were reduced by 52% in acclimated groups. There was a reduction in inflammation indicated by reduced lymphocytes (by 27–33%), and ED1 positive cells (by 35–45%). Conclusions: It is possible to stimulate a natural adaptive mechanism in the brain which will reduce damage and improve outcome for a given ischemic event. Since these adaptations occur after factors such as HIF-1a have returned to baseline, protection is likely related more to morphological changes such as angiogenesis. Such pre-conditioning, perhaps with exercise or pharmaceuticals, would not necessarily reduce the incidence of stroke, but the severity of damage could be reduced by 50%.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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; both teacher heads agree on what is shown here.
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".