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Record W2131890281 · doi:10.3390/ijms14010920

Proteome and Peptidome of Human Acquired Enamel Pellicle on Deciduous Teeth

2013· article· en· W2131890281 on OpenAlexafffund
Jason N. Zimmerman, William Custódio, Šahza Hatibović‐Kofman, Young Ho Lee, Yizhi Xiao, Walter L. Siqueira

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2013
Typearticle
Languageen
FieldMedicine
TopicBone and Dental Protein Studies
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsEnamel paintProteomeDeciduous teethDeciduousDentistryChemistryBiologyBiochemistryBotanyMedicine

Abstract

fetched live from OpenAlex

Understanding the composition and structure of the acquired enamel pellicle (AEP) has been a major goal in oral biology. Our lab has conducted studies on the composition of AEP formed on permanent enamel. The exhaustive exploration has provided a comprehensive identification of more than 100 proteins from AEP formed on permanent enamel. The AEP formed on deciduous enamel has not been subjected to the same biochemical characterization scrutiny as that of permanent enamel, despite the fact that deciduous enamel is structurally different from permanent enamel. We hypothesized that the AEP proteome and peptidome formed on deciduous enamel may also be composed of unique proteins, some of which may not be common with AEP of permanent enamel explored previously. Pellicle material was collected from 10 children (aged 18-54 months) and subjected to mass spectrometry analysis. A total of 76 pellicle proteins were identified from the deciduous pellicle proteome. In addition, 38 natural occurring AEP peptides were identified from 10 proteins, suggesting that primary AEP proteome/peptidome presents a unique proteome composition. This is the first study to provide a comprehensive investigation of in vivo AEP formed on deciduous enamel.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.211
Threshold uncertainty score0.185

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.021
GPT teacher head0.316
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 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

Citations80
Published2013
Admission routes2
Has abstractyes

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