The extracellular matrix as modifier of neuroinflammation and recovery in ischemic stroke and intracerebral hemorrhage
Bibliographic record
Abstract
Stroke is the second leading cause of death worldwide and has two major subtypes: ischemic stroke and hemorrhagic stroke. Neuroinflammation is a pathological hallmark of ischemic stroke and intracerebral hemorrhage (ICH), contributing to the extent of brain injury but also in its repair. Neuroinflammation is intricately linked to the extracellular matrix (ECM), which is profoundly altered after brain injury and in aging. In the early stages after ischemic stroke and ICH, immune cells are involved in the deposition and remodeling of the ECM thereby affecting processes such as blood-brain barrier and cellular integrity. ECM components regulate leukocyte infiltration into the central nervous system, activate a variety of immune cells, and induce the elevation of matrix metalloproteinases (MMPs) after stroke. In turn, excessive MMPs may degrade ECM into components that are pro-inflammatory and injurious. Conversely, in the later stages after stroke, several ECM molecules may contribute to tissue recovery. For example, thrombospondin-1 and biglycan may promote activity of regulatory T cells, inhibit the synthesis of proinflammatory cytokines, and aid regenerative processes. We highlight these roles of the ECM in ischemic stroke and ICH and discuss their potential cellular and molecular mechanisms. Finally, we discuss therapeutics that could be considered to normalize the ECM in stroke. Our goal is to spur research on the ECM in order to improve the prognosis of ischemic stroke and ICH.
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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 | 0.001 |
| 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 | 0.001 |
| 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".