Imaging the dynamic platelet‐neutrophil response in sterile liver injury and repair in mice
Bibliographic record
Abstract
UNLABELLED: Although platelets have been extensively studied in hemostasis and inflammation, their role is not well understood in sterile liver injury and repair. Using a thermally induced focal liver injury and repair model and multichannel spinning disk confocal microscopy allowed visualization of the dynamic behavior of platelets and neutrophils in this insult. Platelets instantaneously adhered to molecularly altered sinusoidal endothelium adjacent to the afflicted area, paving approximately 200 µm abutting the injury. Platelets remained adherent for at least 4 hours, but dissipated by 8 hours. The early recruitment occurred by GPIIbIIIa (CD41) and the later recruitment was dependent upon both GPIIbIIIa and GPIb (CD42B). Platelets did not occlude the vessels, but rather paved the altered endothelium. Endothelin-induced vasoconstriction by hepatic stellate cells, and not platelet accumulation or coagulation, was responsible for temporarily restricted perfusion around the injury. Neutrophils crawled into the injury from significant distances through the sinusoids. The crawling neutrophils required the platelet-paved endothelium given that very little neutrophil recruitment was noted in thrombocytopenic or CD41-deficient mice. As platelets slowly dissipated, neutrophil recruitment was also halted. Previous work suggested that platelets binding to immobilized neutrophils induced neutrophil extracellular trap (NET) formation in response to infection as well as during thrombosis and other forms of sterile injury. In this model of neutrophils crawling on immobilized platelets, very few NETs were observed and no additional injury was noted. In fact, GPIIbIIIa-deficient mice had delayed repair. CONCLUSION: In a liver model of sterile injury and repair, platelets play a critical role in forming a substratum and pave the way for neutrophils to enter the injured site for subsequent repair.
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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 | 0.001 | 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) | 0.000 | 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".