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Amelogenins: A Review of Formative and Degradative Aspects, and Transgene Expression in Bone Cells

2010· review· en· W2228360098 on OpenAlexaff
Rima Wazen, S. Zalzal, Antonio Nanci

Bibliographic record

VenueBENTHAM SCIENCE PUBLISHERS eBooks · 2010
Typereview
Languageen
FieldMedicine
TopicPeriodontal Regeneration and Treatments
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsAmelogeninAmeloblastAmelogenesisEnamel paintExtracellular matrixCell biologyChemistryMineralization (soil science)Matrix (chemical analysis)ApatiteBiochemistryBiologyMaterials scienceGeneMineralogy

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.981
Threshold uncertainty score0.905

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.034
GPT teacher head0.329
Teacher spread0.295 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations1
Published2010
Admission routes1
Has abstractyes

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