Dental phenotype of a mouse model expressing a truncated form of ameloblastin
Bibliographic record
Abstract
Ameloblastin (AMBN) is the second most abundant protein produced by ameloblasts and is found mainly in forming enamel. Our aim was to characterize the tooth phenotype in a mouse model lacking expression of full‐length AMBN (AMBN −FL ). Since after building enamel ameloblasts and associated cells participate in the formation of the gingival attachment to the tooth (junctional epithelium, JE), we have also examined its integrity. Materials and Methods Mandibles from normal and AMBN −FL mice were processed for morphological analyses and immunohistochemical detection of AMBN. Freeze‐dried enamel organs and enamel were prepared for molecular and biochemical analyses. Results Our data show that absence of full‐length AMBN causes structural changes at the level of the enamel organ, shows displatic enamel layer, and loss of integrity of the JE. Immunohistochemical staining indicated that the enamel organ in these mice continued to produce an AMBN‐related peptide that is translated from a truncated RNA missing exons 5 and 6. The protein was deduced to have 295 amino acids and an apparent molecular weight of 32‐35 kDa. Conclusion Our study shows that AMBN influences both cells and matrix events. Identification of the portion of AMBN protein still produced in this AMBN −FL mouse model provides new insights on the functional domains that may be implicated in these activities. Supported by the CIHR.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".