Human Odontoblast Culture Method: The Expression of Collagen and Matrix Metalloproteinases (MMPs)
Bibliographic record
Abstract
Studies on mature human odontoblasts have suffered for the lack of in vitro models. We recently introduced a human odontoblast and pulp tissue organ culture method, in which the odontoblasts are cultured in the pulp chamber after removal of the pulp tissue, and the pulp tissue can be cultured separately (Tjäderhane et al., 1998a). With this method, we have studied the effects of growth factors on the expression of collagen and extracellular matrix (ECM)-degrading enzymes, matrix metalloproteinases (MMPs), in mature human odontoblasts. TGF-beta 1 was selected because of its ability to regulate the response of the dentin-pulp complex to external irritation. The effect of TGF-beta 1 (10 ng/mL) on pro alpha 1(I) collagen mRNA was analyzed by quantitative PCR, and type I procollagen propeptide (PINP) was analyzed from conditioned culture media with RIA. Odontoblast media were also assayed for respective type III procollagen propeptide (PIIINP). TGF-beta had a negligible effect on collagen mRNA expression or protein synthesis, indicating that TGF-beta alone does not markedly induce dentin matrix formation per se in the human dentin-pulp complex (Palosaari et al., 2001). However, TGF-beta 1 seems to regulate MMP expression in mature human odontoblasts differentially. A strong down-regulation of MMP-8 (Palosaari et al., 2000), a modest down-regulation of MMP-20 (Tjäderhane et al., 2000), and considerable up-regulation of MMP-9, with no apparent effect on MMP-2 expression (Tjäderhane et al., 1998b), indicate that growth factors may affect the matrix synthesis by controlling the expression and activity of MMPs instead of collagen synthesis. The altered expression of MMPs may result in altered ECM formation, which in turn may contribute to the formation of atubular reparative dentin.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".