Targeted deletion of EMMPRIN in microglia/macrophages mitigates neuronal death in intracerebral hemorrhage
Bibliographic record
Abstract
BACKGROUND: Intracerebral hemorrhage (ICH) is a devastating subtype of stroke with high mortality and limited therapeutic options. Microglia and macrophages are rapidly recruited to the lesion site and contribute substantially to secondary brain injury. However, the key molecular mediators that drive their neurotoxic effects remain incompletely understood. METHODS: We investigated the role of extracellular matrix metalloproteinase inducer (EMMPRIN, also known as CD147) in promoting microglia/macrophage-mediated neurotoxicity after ICH. EMMPRIN was selectively deleted in myeloid cells using both AAV-mediated knockdown and CX3CR1Cre:EMMPRINfl/fl mice. Neuronal survival and functional outcomes were assessed using histological, molecular, and behavioral analyses. RESULTS: Targeted deletion of EMMPRIN in microglia/macrophages significantly reduced neuronal death and improved neurological recovery following ICH. Mechanistically, EMMPRIN-mediated neurotoxicity was associated with elevated expression of matrix metalloproteinases and enhanced activation of the p38 mitogen-activated protein kinase (MAPK) pathway, and with downstream engagement of myocyte enhancer factor 2 C (MEF2C) and B-cell lymphoma 2 (Bcl2). Notably, EMMPRIN deletion also enhanced neurogenesis and oligodendrogenesis in the perihematomal region, suggesting a potential role in promoting endogenous brain repair. CONCLUSIONS: These findings establish EMMPRIN elevation in myeloid cells as a prominent regulator of ICH pathophysiology and a promising therapeutic target to limit secondary injury and promote brain repair.
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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 | 0.001 |
| 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".