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Record W2991308802 · doi:10.2147/ijn.s217420

<p>Phenotypic Properties of Collagen in Dentinogenesis Imperfecta Associated with Osteogenesis Imperfecta</p>

2019· article· en· W2991308802 on OpenAlexaff
S Ibrahim, Adam Strange, Sebastián Aguayo, Albatool Shinawi, Nabilah Harith, Nurjehan Mohamed-Ibrahim, Samera Siddiqui, Susan Parekh, Laurent Bozec

Bibliographic record

VenueInternational Journal of Nanomedicine · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnective tissue disorders research
Canadian institutionsUniversity of Toronto
FundersUniversiti Sains Islam MalaysiaUniversiti Sains MalaysiaInternational Association for Dental Research
KeywordsDentinogenesis imperfectaDentinOsteogenesis imperfectaMolarDemineralizationChemistryUltrastructureDentinogenesisType I collagenDentinal TubuleMaterials scienceBiophysicsDentistryAnatomyPathologyOdontoblastMedicineBiologyComposite materialEnamel paint

Abstract

fetched live from OpenAlex

INTRODUCTION: Dentinogenesis imperfecta type 1 (OIDI) is considered a relatively rare genetic disorder (1:5000 to 1:45,000) associated with osteogenesis imperfecta. OIDI impacts the formation of collagen fibrils in dentin, leading to morphological and structural changes that affect the strength and appearance of teeth. However, there is still a lack of understanding regarding the nanoscale characterization of the disease, in terms of collagen ultrastructure and mechanical properties. Therefore, this research presents a qualitative and quantitative report into the phenotype and characterization of OIDI in dentin, by using a combination of imaging, nanomechanical approaches. METHODS: For this study, 8 primary molars from OIDI patients and 8 primary control molars were collected, embedded in acrylic resin and cut into longitudinal sections. Sections were then demineralized in 37% phosphoric acid using a protocol developed in-house. Initial experiments demonstrated the effectiveness of the demineralization protocol, as the ATR-FTIR spectral fingerprints showed an increase in the amide bands together with a decrease in phosphate content. Structural and mechanical analyses were performed directly on both the mineralized and demineralized samples using a combination of scanning electron microscopy, atomic force microscopy, and Wallace indentation. RESULTS: Mesoscale imaging showed alterations in dentinal tubule morphology in OIDI patients, with a reduced number of tubules and a decreased tubule diameter compared to healthy controls. Nanoscale collagen ultrastructure presented a similar D-banding periodicity between OIDI and controls. Reduced collagen fibrils diameter was also recorded for the OIDI group. The hardness of the (mineralized) control dentin was found to be significantly higher (p<0.05) than that of the OIDI (mineralized) dentine. Both the exposed peri- and intratubular dentinal collagen presented bimodal elastic behaviors (Young's moduli). The control samples presented a stiffening of the intratubular collagen when compared to the peritubular collagen. In case of the OIDI, this stiffening in the collagen between peri- and intratubular dentinal collagen was not observed and the exposed collagen presented overall a lower elasticity than the control samples. CONCLUSION: This study presents a systematic approach to the characterization of collagen structure and properties in OIDI as diagnosed in dentin. Structural markers for OIDI at the mesoscale and nanoscale were found and correlated with an observed lack of increased elastic moduli of the collagen fibrils in the intratubular OIDI dentin. These findings offer an explanation of how structural changes in the dentin could be responsible for the failure of some adhesive restorative materials as observed in patients affected by OIDI.

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 score0.148
Threshold uncertainty score0.527

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 science0.0010.000
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 head0.010
GPT teacher head0.252
Teacher spread0.242 · 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".

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Citations38
Published2019
Admission routes1
Has abstractyes

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