Thrombin modifies growth, proliferation and apoptosis of human colon organoids: a protease‐activated receptor 1‐ and protease‐activated receptor 4‐dependent mechanism
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Thrombin is massively released upon tissue damage associated with bleeding or chronic inflammation. The effects of this thrombin on tissue regrowth and repair has been scarcely addressed and only in cancer cell lines. Hence, the purpose of the present study was to determine thrombin's pharmacological effects on human intestinal epithelium growth, proliferation and apoptosis, using three-dimensional cultures of human colon organoids. EXPERIMENTAL APPROACH: of thrombin, in the presence or not of protease-activated receptor (PAR) antagonists. Organoid morphology, metabolism, proliferation and apoptosis were followed. KEY RESULTS: Thrombin favoured organoid maturation leading to a decreased number of immature cystic structures and a concomitant increased number of larger structures releasing cell debris and apoptotic cells. The size of budding structures, metabolic activity and proliferation were significantly reduced in organoid cultures exposed to thrombin, while apoptosis was dramatically increased. Both PAR1 and PAR4 antagonists inhibited apoptosis regardless of thrombin doses. Thrombin-induced inhibition of proliferation and metabolic activity were reversed by PAR4 antagonist for thrombin's lowest dose and by PAR1 antagonist for thrombin's highest dose. CONCLUSIONS AND IMPLICATIONS: Overall, our data suggest that the presence of thrombin in the vicinity of human colon epithelial cells favours their maturation at the expense of their regenerative capacities. Our data point to thrombin and its two receptors PAR1 and PAR4 as potential molecular targets for epithelial repair therapies.
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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 | 0.000 |
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".