Sulindac treatment alters collagen and matrilysin expression in adenomas of ApcMin/+ mice
Bibliographic record
Abstract
Non-steroidal anti-inflammatory drugs (NSAIDs) have shown potential as chemopreventive agents against cancer formation, especially colorectal cancers. However, the mechanisms by which these drugs act are not fully understood. In this study, Apc(Min/+) mice, a genetic model of human familial adenomatous polyposis, were treated with sulindac, and these mice demonstrated tumor reduction of >80%, consistent with previous reports. Gene microarray analyses of RNA from adenoma-derived dysplastic epithelial cells revealed that collagen genes, viz. Col1a2, Col5a2, Col6a2 and Col6a3, were upregulated, and matrilysin matrix metalloproteases-7 (Mmp7) was downregulated, in sulindac-treated mice. Reverse transcription-polymerase chain reaction validated gene expression of the Col6a2 subunit of collagen VI and of Mmp7. Confocal microscopy and immunofluorescence showed that within the tumors of non-treated mice, collagen VI was present in low amounts, but was enhanced within the tumors of sulindac-treated mice. Collagens I and V demonstrated similar patterns, but were not as prominent as collagen VI. Mmp7 was found in 'hot spot' areas within the tumors of Apc(Min/+) mice treated with the vehicle, but was greatly diminished in those mice treated with sulindac. Studies with Apc(Min/+)/Mmp7(-/-) double-deficient mice demonstrated the reciprocal relationships of Mmp7 expression and the levels of these three collagens in vivo. The results of this study demonstrated that sulindac was effective in increasing the expression of different collagens and decreasing the expression of Mmp7, effects that may contribute to altered tumor burden in cancer patients undergoing NSAIDs treatments.
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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 | 0.000 | 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) | 0.000 | 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".