Neutrophils Promote Liver Metastasis via Mac-1–Mediated Interactions with Circulating Tumor Cells
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although circulating neutrophils are associated with distant metastasis and poor outcome in a number of epithelial malignancies, it remains unclear whether neutrophils play an active causal role in the metastatic cascade. Using in vivo models of metastasis, we found that neutrophils promote cancer cell adhesion within liver sinusoids and, thereby, influence metastasis. Neutrophil depletion before cancer cell inoculation resulted in a decreased number of gross metastases in an intrasplenic model of liver metastasis. This effect was reversed when inflamed neutrophils were co-inoculated with cancer cells. In addition, early adhesion within liver sinusoids was inhibited in the absence of neutrophils and partially restored with a short perfusion of isolated activated neutrophils. Intravital microscopy showed that cancer cells adhered directly on top of arrested neutrophils, indicating that neutrophils may act as a bridge to facilitate interactions between cancer cells and the liver parenchyma. The adhesion of lipopolysaccharide-activated neutrophils to cancer cells was mediated by neutrophil Mac-1/ICAM-1. Our findings, therefore, show a novel role for neutrophils in the early adhesive steps of liver metastasis.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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