Immunocytochemical characterization of ectopic enamel deposits and cementicles in human teeth
Bibliographic record
Abstract
Despite the relative frequency and clinical relevance of radicular enamel deposits and cementicles, their etiology and nature are unknown. The purpose of the present study was therefore to evaluate the presence and distribution of mineralization-associated non-collagenous matrix proteins (NCPs) in various types of root-associated ectopic mineralizations. Human teeth were processed for embedding in epoxy or acrylic resins. Tissue sections were incubated with antibodies to amelogenins (AMEL), bone sialoprotein (BSP), and osteopontin (OPN). Radicular enamel deposits contained residual organic matrix that labeled for AMEL. In contrast, BSP and OPN were not detected in the residual enamel matrix, they were found in the cementum deposited on its surface as well as in collagen-free cementicle-like structures in the adjacent periodontal ligament. True cementicles consisted of a collagenous matrix intermixed with a non-collagenous ground substance. Labeling for BSP and OPN was mainly associated with the interfibrillar ground substance. No immunoreactivity for AMEL was detected in cementicles. These data indicate that ectopic enamel deposits on the root retain a high amount of AMEL, whereas cementicles contain BSP and OPN, two NCPs typically found in bone and cementum. These NCPs may, like in their normal tissue counterparts, play a role in the mineralization process.
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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".