Neutrophil infiltration to the brain is platelet‐dependent, and is reversed by blockade of platelet GPIb<i>α</i>
Why this work is in the frame
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Bibliographic record
Abstract
Neutrophils are key components of the innate immune response, providing host defence against infection and being recruited to non-microbial injury sites. Platelets act as a trigger for neutrophil extravasation to inflammatory sites but mechanisms and tissue-specific aspects of these interactions are currently unclear. Here, we use bacterial endotoxin in mice to trigger an innate inflammatory response in different tissues and measure neutrophil invasion with or without platelet reduction. We show that platelets are essential for neutrophil infiltration to the brain, peritoneum and skin. Neutrophil numbers do not rise above basal levels in the peritoneum and skin and are decreased (~60%) in the brain when platelet numbers are reduced. In contrast neutrophil infiltration in the lung is unaffected by platelet reduction, up-regulation of CXCL-1 (2·4-fold) and CCL5 (1·4-fold) acting as a compensatory mechanism in platelet-reduced mice during lung inflammation. In brain inflammation targeting platelet receptor GPIbα results in a significant decrease (44%) in platelet-mediated neutrophil invasion, while maintaining platelet numbers in the circulation. These results suggest that therapeutic blockade of platelet GPIbα could limit the harmful effects of excessive inflammation while minimizing haemorrhagic complications of platelet reduction in the brain. The data also demonstrate the ability to target damaging brain inflammation in stroke and related disorders without compromising lung immunity and hence risk of pneumonia, a major complication post stroke. In summary, our data reveal an important role for platelets in neutrophil infiltration to various tissues, including the brain, and so implicate platelets as a key, targetable component of cerebrovascular inflammatory disease or injury.
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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 | 0.000 |
| 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 | 0.001 |
| 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 | 0.001 |
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 it