Monitoring Stroke Progression: <i>In Vivo</i> Imaging of Cortical Perfusion, Blood—Brain Barrier Permeability and Cellular Damage in the Rat Photothrombosis Model
Bibliographic record
Abstract
Focal cerebral ischemia is among the main causes of death and disability worldwide. The ischemic core often progresses, invading the peri-ischemic brain; however, assessing the propensity of the peri-ischemic brain to undergo secondary damage, understanding the underlying mechanisms, and adjusting treatment accordingly remain clinically unmet challenges. A significant hallmark of the peri-ischemic brain is dysfunction of the blood-brain barrier (BBB), yet the role of disturbed vascular permeability in stroke progression is unclear. Here we describe a longitudinal in vivo fluorescence imaging approach for the evaluation of cortical perfusion, BBB dysfunction, free radical formation and cellular injury using the photothrombosis vascular occlusion model in male Sprague Dawley rats. Blood-brain barrier dysfunction propagated within the peri-ischemic brain in the first hours after photothrombosis and was associated with free radical formation and cellular injury. Inhibiting free radical signaling significantly reduced progressive cellular damage after photothrombosis, with no significant effect on blood flow and BBB permeability. Our approach allows a dynamic follow-up of cellular events and their response to therapeutics in the acutely injured cerebral cortex.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".