Secretion of hepatocyte growth factor and vascular endothelial growth factor during uveal melanoma???monocyte in vitro interactions
Bibliographic record
Abstract
Host-tumour interactions in uveal melanoma, and their involvement in the biological events leading to metastasis and eventually mortality, are not well understood. It is known that uveal melanoma disseminates predominantly via a haematogenous route with metastasis developing primarily in the liver. Therefore, cytokines involved in angiogenesis, such as vascular endothelial growth factor (VEGF), and those expressed in large quantities within the liver, such as hepatocyte growth factor (HGF), are of particular interest in uveal melanoma research. This study investigated the levels of HGF and VEGF in monocyte and uveal melanoma-conditioned medium. Five human uveal melanoma cell lines and one monocyte cell line were seeded in six-well plates. After 18 h, melanoma-conditioned medium (MCM) was placed on the monocyte cell line and monocyte-conditioned medium (MoCM) was placed on each uveal melanoma cell line. Tumour cells and monocytes incubated in fresh, as opposed to conditioned, medium after 18 h were used as controls. VEGF and HGF levels were determined by immunoassay prior to media transfer and 6, 12, 24 and 36 h thereafter. Both cytokines showed an upregulation of expression from all cells after incubation in conditioned medium. 28SC incubated in MCM expressed higher levels of the given cytokines than did uveal melanoma cells incubated in MoCM. In addition, each cell line exhibited a distinct pattern of expression, with individual cell lines exhibiting different peak levels of cytokine production at different time points. These results offer insight into the upregulation of VEGF and HGF, which may play a role in tumour-host cell interactions.
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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) | 0.000 | 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) | 0.001 | 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".