Longitudinal optical coherence tomography imaging of tissue repair and microvasculature regeneration and function after targeted cerebral ischemia
Bibliographic record
Abstract
SIGNIFICANCE: Understanding how the brain recovers from cerebral tissue and vascular damage after an ischemic event can help develop new therapeutic strategies for the treatment of stroke. AIM: We investigated cerebral tissue repair and microvasculature regeneration and function after a targeted ischemic stroke. APPROACH: Following photothrombosis occlusion of microvasculature, chronic optical coherence tomography (OCT)-based angiography was used to track ischemic tissue repair and microvasculature regeneration at three different cortical depths and up to 28 days in awake animals. Capillary network orientation analysis was performed to study the structural pattern of newly formed microvasculature. Based on the time-resolved OCT-angiography, we also investigated capillary stalling, which is likely related to ischemic stroke-induced inflammation. RESULTS: Deeper cerebral tissue was found to have a larger ischemic area than shallower regions at any time point during the course of poststroke recovery, which suggests that cerebral tissue located deep in the cortex is more vulnerable. Regenerated microvasculature had a highly organized pattern at all cortical depths with a higher degree of structural reorganization in deeper regions. Additionally, capillary stalling event analysis revealed that cerebral ischemia augmented stalling events considerably. CONCLUSION: Longitudinal OCT angiography reveals that regenerated capillary network has a highly directional pattern and an increased density and incidence of capillary stalling event.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".