Amelogenins: A Review of Formative and Degradative Aspects, and Transgene Expression in Bone Cells
Bibliographic record
Abstract
The cells that form calcified tissues produce various matrix proteins that foster a favourable environment for the regulated and structured deposition of calcium and phosphate ions into a carbonated form of apatite mineral. Differing from collagen-based calcified tissues, the organic matrix of enamel is produced by epithelially-derived cells – the ameloblasts, and consists of two major classes of proteins, amelogenins (AMEL) and nonamelogenins [1]. The AMEL class comprises full-length proteins, truncated isoforms resulting from alternative mRNA splicing, and fragments generated by extracellular proteolytic processing [1]. Enamel is distinctive from other calcified tissues because its organic matrix must ultimately be almost totally removed for it to achieve its full mineralization status. Thus, amelogenesis involves both formative and degradative processes. Studies over the past few years have revealed unexpected potentials for AMEL beyond structuring and organizing mineral at the surface of teeth, in particular their apparent capacity to influence osteogenic events. The objective of this mini-review is to highlight some key features of AMEL as related to both processes, and briefly go over our efforts to introduce enamel protein transgenes in bone forming cells.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".