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Record W3204064914 · doi:10.1177/00220345211043463

A Brief History of the Discovery of Amelogenin Nanoribbons In Vitro and In Vivo

2021· article· en· W3204064914 on OpenAlexaff
Yushi Bai, Johan Bonde, Karina M. M. Carneiro, Yu Zhang, W. Li, Stefan Habelitz

Bibliographic record

VenueJournal of Dental Research · 2021
Typearticle
Languageen
FieldMedicine
TopicBone and Dental Protein Studies
Canadian institutionsUniversity of Toronto
FundersNational Institute of Dental and Craniofacial Research
KeywordsAmelogeninEnamel paintExtracellular matrixAmelogenesisChemistryCell biologyBiophysicsIn vitroApatiteNanotechnologyMaterials scienceBiologyBiochemistryAmeloblastMineralogyComposite material

Abstract

fetched live from OpenAlex

Without evidence for an organic framework, biological and biochemical processes observed during amelogenesis provided limited information on how extracellular matrix proteins control the development of the complex fibrous architecture of human enamel. Over a decade ago, amelogenin nanoribbons were first observed from recombinant proteins during in vitro mineralization experiments in our laboratory. In enamel from mice lacking the enzyme kallikrein 4 (KLK4), we later uncovered ribbon-like protein structures that matched the morphology, width, and thickness of the nanoribbons assembled by recombinant proteins. Interestingly, similar structures had already been described since the 1960s, when enamel sections from various mammals were demineralized and stained for transmission electron microscopy analysis. However, at that time, researchers were not aware of the ability of amelogenin to form nanoribbons and instead associated the filamentous nanostructures with possible imprints of mineral ribbons in the gel-like matrix of developing enamel. Further evidence for the significance of amelogenin nanoribbons for enamel development was stipulated when recent mineralization experiments succeeded in templating and orienting the growth of apatite ribbons along the protein nanoribbon framework. This article provides a brief historical review of the discovery of amelogenin nanoribbons in our laboratory in the context of reports by others on similar structures in the developing enamel matrix.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.143
Threshold uncertainty score0.196

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.057
GPT teacher head0.351
Teacher spread0.294 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations16
Published2021
Admission routes1
Has abstractyes

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