Bibliographic record
Abstract
The matricellular protein connective tissue growth factor (CTGF, CCN2) is overexpressed in several forms of cancer and may represent a novel target in anti-cancer therapy. However, whether CCN2 is expressed in melanoma cells is unknown. The highly metastatic murine melanoma cell line B16(F10) was used for our studies. Real time polymerase chain reaction analysis was used to detect mRNA expression of CCN1, CCN2, CCN3 and CCN4 in Western blot and immunofluorescence analyses were used to detect CCN2 protein. Inhibitors of signal transduction cascades were used to probe the mechanism underlying CCN2 expression in B16(F10) cells. CCN2 was expressed in B16(F10) cells, and was reduced by the FAK/src inhibitor PP2 and the MEK/ERK inhibitor U0126 indicating that CCN2 acts downstream of these pathways in B16(F10) murine melanoma cells. Expression of CCN1, CCN3 and CCN4 was not reduced by PP2 or U0126; in fact, expression of CCN4 mRNA was elevated by PP2 or U0126 treatment. To our surprise, CCN2 protein was detected in the nuclei of B16(F10) cells, and was undetectable in the cytoplasm. CCN2 was expressed in B16(F10) melanoma cells, adding to the list of cancer cells in which CCN2 is expressed. Of the CCN family members tested, only CCN2 is downstream of the highly oncogenic MEK/ERK pathway. CCN2 should be further evaluated for a possible role in melanoma growth and progression.
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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) | 0.002 | 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 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".