Intracerebral hemorrhage induces macrophage activation and matrix metalloproteinases
Bibliographic record
Abstract
Intracerebral hemorrhage (ICH) is characterized by parenchymal hematoma formation with surrounding inflammation. Matrix metalloproteinases (MMPs) have been implicated in the pathogenesis of neurological diseases defined by inflammation and cell death. To investigate the expression profile and pathogenic aspects of MMPs in ICH, we examined MMP expression in vivo using a collagenase-induced rat model of ICH. ICH increased brain MMP-2, -3, -7, and -9 mRNA levels relative to sham-injected (control) animals in the vicinity of the hematoma, but MMP-12 (macrophage metalloelastase) was the most highly induced MMP (>80-fold). Immunohistochemistry showed MMP-12 to be localized in activated monocytoid cells surrounding the hematoma. In vitro studies showed that thrombin, released during ICH, induced MMP-12 expression in monocytoid cells, which was reduced by minocycline application. Similarly, in vivo minocycline treatment significantly reduced MMP-12 levels in brain. Neuropathological studies disclosed marked glial activation and apoptosis after ICH that was reduced by minocycline treatment. Neurobehavioral outcomes also were improved with minocycline treatment compared with untreated ICH controls. Thus, select MMPs exhibit increased expression after ICH, whereas minocycline is neuroprotective after ICH by suppressing monocytoid cell activation and downregulating MMP-12 expression.
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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 | 0.000 | 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) | 0.001 | 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".