Microtubule‐associated protein 2, an early blood marker of ischemic brain injury
Bibliographic record
Abstract
The aim of this study was to develop a sensitive and rapid blood marker to detect ischemic brain injury, because imaging techniques have a limited capacity to identify lesions during the first crucial hours without massive tissue destruction. Rats were subjected to middle cerebral artery occlusion for various durations (0.5-3 hr), followed by reperfusion. At different time points after ischemia and/or ischemia-reperfusion, the amounts of glial fibrillary acidic protein (GFAP) and microtubule-associated protein 2 (MAP2) in the cerebrospinal fluid (CSF) and serum were analyzed by Western blotting. Brain infarction was observed in an ischemia-duration-dependent manner. GFAP was drastically increased in the CSF 24 and 48 hr after reperfusion, without change in the serum level. Serum levels of MAP2 remarkably increased as early as 0.5 hr of ischemia, much earlier than the observation of minimal tissue injury 3 hr following occlusion. The serum MAP2 level was further increased by a short period (2 hr) of reperfusion, even in 0.5- and 1-hr ischemic rats, despite not observing any typical tissue injuries 24 hr after reperfusion. These results indicate that the MAP2 protein may be able to detect early neuronal injuries, because the level of this protein in the blood spikes before the appearance of visible macrolesions. Therefore, MAP2 could potentially be used as a novel early marker for the detection of a neurotoxic insult.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".