Evaluation of the Migrastatic Properties of Selective MMP-2 Inhibitors in Colorectal Cancer: An In Ovo Approach
Bibliographic record
Abstract
Colorectal cancer accounts for about 10% of all cancer diagnoses and is the second leading cause of cancer-related death. Until the cancer has progressed to an advanced stage, colorectal cancer typically shows no symptoms. The medications currently utilized to treat colorectal cancer have serious drawbacks. The aim of the study was to evaluate the ability of newly developed synthetic matrix metalloprotease-2 inhibitors to prevent metastases. This study used computational models to evaluate pharmacokinetic characteristics and ligand-binding affinities for preliminary screening. Later, we used the human colorectal cancer cell line SW620 in an in ovo approach to assess its anti-migratory properties. The chorioallantoic membrane was used to transplant tumor cells. In order to assess migrastatic activity in a preclinical model using an in ovo technique, we measured changes in the chick embryo's total body weight, colon length and body weight, complete blood count and histopathology of the colon, liver and stomach. In addition, the histology of the stomach, liver, colon, and chorioallantoic membrane was taken into account while assessing the activity. We discovered that compound N5 ({4-[(3'-amino[1,1'-biphenyl]-4-carbonyl) amino] phenyl~acetic acid) had the best migrastatic action by blocking matrix metalloprotease-2. The new compound showed potential as a matrix metalloprotease-2 inhibitor compared to doxycycline. A more robust platform was needed for further investigation and progress of novel compound towards clinical setting.
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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 | 0.003 | 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 | 0.000 |
| 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".