Angiostatin inhibits monocyte/macrophage migration <i>via</i> disruption of actin cytoskeleton
Bibliographic record
Abstract
In light of the involvement of tumor-associated macrophages (TAM) in the promotion of tumor growth and metastasis, strategies to prevent TAM recruitment within the tumor microenvironment are currently under investigation. The recent observation that angiostatin reduces macrophage infiltration in an atherosclerosis model prompted our laboratory to further explore the use of human plasminogen angiostatin (hK1-3) protein as a macrophage modulatory agent. We demonstrate that hK1-3 blocks migration of murine peritoneal macrophages (91% decrease, P<0.00005) and human monocytes (85% decrease, P<0.05) in vitro. Cell viability of hK1-3-treated cells is not affected, as determined by fluorochrome-labeled inhibitors of caspase-propidium iodide (FLICA/PI) flow cytometry analysis. Furthermore, confocal microscopy of phalloidin-stained cells reveals that hK1-3 leads to disruption of actin filopodia/lamellipodia in human monocytes and induces distinct podosome accumulation in mature differentiated macrophages. Paradoxically, we observed a 3.5-fold increase in secretion and a 3- to 5.5-fold increase in gelatinolytic activity of macrophage-produced matrix metalloproteinase-9, which we suggest is a cellular response to compensate for the dominant static effect of hK1-3 on actin. We also demonstrate that hK1-3 induces the phosphorylation of extracellular signal-regulated kinase (ERK1/2) in human monocytes. hK1-3-mediated macrophage immobilization has the potential to be exploited therapeutically in pathological conditions associated with cellular hypoxia, such as cancer and atherosclerosis.
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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".