The enamel protein ODAM promotes mineralization in a collagen matrix
Bibliographic record
Abstract
Purpose/aim of the study: Odontogenic ameloblast-associated protein (ODAM) is predominantly expressed during the maturation stage of enamel formation and interacts strongly with amelotin (AMTN). AMTN is involved in enamel mineralization, but the effect of ODAM on mineralization has not been investigated. This study determined whether ODAM was able to induce hydroxyapatite (HA) mineralization in modified simulated body fluid (SBF) and in a collagen matrix in vitro. MATERIALS AND METHODS: To monitor the kinetics of calcium phosphate mineralization, recombinant human (rh) ODAM protein in SBF buffer was incubated at 37°C and a light-scattering assay was conducted at intervals. To investigate the nucleation of ODAM in collagen matrix, the ODAM-impregnated collagen hydrogel was incubated in SBF buffer for 24 hours. Bovine serum albumin (BSA) was used as negative control. Mineral deposits were visualized using electron microscopy. RESULTS: The presence of rh-ODAM protein in SBF resulted in higher light-scattering values after 18-24 hours. Calcium phosphate precipitates were observed on the surface of the ODAM-treated, but not BSA-treated collagen hydrogel after 24 hours in SBF. TEM and SAED analyses showed that these crystals consisted of needle-like HA. CONCLUSION: Similar to AMTN, ODAM is able to promote HA nucleation in a dose-dependent manner in SBF, and even outside of its biological context in vitro.
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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) | 0.001 | 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".