Influence of Active and Non-active Protein C on Human Ovarian Cancer Stem Cells
Bibliographic record
Abstract
Abstract Introduction: The coagulation/fibrinolysticsystem control the intravascular fibrin hemostasis;in addition to participating in a wide variety of physio-pathological processes. The components of the system have an influence on tumor growth, invasion and metastasis. This is a result of their involvement in tumor matrix construction, angiogenesis and cell migration. Several homeostatic markers are currently used to predict the advent of thrombosis. However, none of these markers directly indicate the course and progression of the disease. Destabilization of peri-tumoral matrix enhances the malignant phenotype of cancer cells. The characterization of cytokines and proteolytic enzymes, secreted in tumor microenvironment, plays an important role in the mechanism of the escape phenomenon. However, the consequence of interaction of protein C on cancer stem cells is poorly investigated. Objective: The aim of our study was to analyze the physio-pathological response of human ovarian cancer stem cells (OVCAR-3) to active and non-active protein C. OVCAR-3 cells were cultured in DMEM medium containing 10% fetal calf serum, penicillin (50 U/ml), and streptomycin (50 μg/ml) and incubated in a humidified atmosphere containing 5% CO2 at 37°C, as recommended by the supplier (PAA Laboratories Inc, Etobicoke, ON, USA). Cells were characterized by flow cytometry for their propriety of stem cell like with specific anti CD133 and CD117 antibodies. The influence of active and non-active protein C (10 µg/ml, Eli Lilly) on this cell was performed by cytokine array (Ray Biotech, CliniScience) and in parallel by a wound healing test. We demonstrated by a wound healing test that the migration of ovarian cancer cells enhanced when incubated with Active protein C compared to the cells that were incubated with Non-active protein C. Also the cytokine array showed different cytokines secreted by cells incubated with Active protein C and Non-active protein C. It was found that Active protein C not only provides cancer cells cytoprotective effects, it may also participate in extracellular matrix local destabilization, thereby promoting metastatic dissemination.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".