Tissue processing and optimal visualization of cerebral infarcts following sub-acute focal ischemia in rats
Bibliographic record
Abstract
Transient cerebral ischemia followed by reperfusion in an infarcted brain comes with predictable acute and chronic morphological alterations in neuronal and non-neuronal cells. An accurate delineation of the cerebral infarct is not a simple task due to the complex shapes and indistinct borders of the infarction. Thus, an exact macroscopic histological approach for infarct volume estimation can lead to faster and more reliable preclinical research results. This study investigated the effect(s) of confounding factors such as fixation and tissue embedding on the quality of macroscopic visualization of focal cerebral ischemia by anti-microtubule-associated-protein-2 antibody (MAP2) with conventional Hematoxylin and Eosin (HE) staining serving as the control. The aim was to specify the most reliable macroscopic infarct size estimation method after sub-acute focal cerebral ischemia based on the qualitative investigation. Our results showed that the ischemic area on the MAP2-stained sections could be identified macroscopically on both cryo-preserved and paraffin-embedded sections from both immersion- and perfusion-fixed brains. The HE staining did not clearly depict an infarct area for macroscopic visualization. Therefore both immersion-fixed and perfused-fixed-MAP2 stained sections can be used reliably to quantify cerebral infarcts.
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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) | 0.001 | 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".