Neutrophil Depletion Reduces Blood-Brain Barrier Breakdown, Axon Injury, and Inflammation After Intracerebral Hemorrhage
Bibliographic record
Abstract
Neutrophils are thought to contribute to damage after intracerebral hemorrhage (ICH), but there is little direct evidence for this. We depleted circulating blood neutrophils with an anti-polymorphonuclear leukocyte antibody (anti-PMN) before inducing ICH in the rat striatum. Neutrophil infiltration, which was mainly at the edge of the hematoma, was decreased by more than 60% by anti-PMN mediated depletion. We then analyzed neutrophil contributions to BBB breakdown, white matter damage (axons and myelin), and glial and inflammatory responses, both spatially and temporally. Neutrophil depletion reduced BBB leakiness in the peri-hematoma region. Matrix metalloprotease 9, which is thought to contribute to BBB breakdown, was restricted to neutrophils after ICH and was thus reduced by neutrophil depletion. Early perihematomal axonal injury seen at 1 and 3 days after ICH was decreased by depleting neutrophils, and at later times (7 and 14 days), the astrocytic and microglia/macrophage responses were reduced in the perihematoma region and the surrounding striatum. Detailed spatial analysis showed that neutrophil depletion reduced infiltration of activated microglia/macrophages in the peri-hematoma white matter tracts and decreased myelin fragmentation and axon damage. These results show that, in experimental ICH, neutrophils produce matrix metalloprotease9and contribute to blood vessel disruption, BBB breakdown, axon damage, and astrocytic and microglial/macrophage responses that evolve after ICH.
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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) | 0.001 | 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) | 0.001 | 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".