Clot Fragments Formed from Original Thrombus Obstruct Downstream Arteries in the Ischemic Injured Brain
Bibliographic record
Abstract
OBJECTIVE: Embolic occlusion of the middle cerebral artery (MCA) leads to distal perfusion deficits as the vessel is recanalized. However, the mechanism for the perfusion deficits is not fully understood. The authors examined whether distal movement of fragments formed from the original thrombus contributes to the perfusion deficits. METHODS: In the first series, they studied whether the reduction in perfusion deficits is due to the dissolution of the original clots embolized or due to collateral perfusion. In the second series, they studied whether fragments formed from the original clots move to distal arterial system. In the third series, they studied whether plasminogen activator plays a role in the thrombolysis following ischemia. RESULTS: Occlusion of MCA permanently resulted in large perfusion deficits in the ipsilateral hemisphere, and these perfusion deficits did not change significantly after the occlusion. In contrast, perfusion deficits reduced significantly in a model of transient MCA occlusion. The numbers of fragments formed from the original clots increased gradually after the MCA occlusion in the ischemic injured brain. In addition, expression of urokinase plasminogen activator was also upregulated. CONCLUSION: The present study thus reveals the mechanisms of the downstream arterial occlusion following the dissolution of original thrombus.
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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) | 0.000 | 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) | 0.002 | 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".