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Record W2792947577 · doi:10.1111/iej.12889

Cytocompatibility of Biodentine and <scp>iR</scp>oot <scp>FS</scp> with human periodontal ligament cells: an <i>in vitro</i> study

2018· article· en· W2792947577 on OpenAlexaff
Tao Luo, Jun Liu, Yan Sun, Ya Shen, Ling Zou

Bibliographic record

VenueInternational Endodontic Journal · 2018
Typearticle
Languageen
FieldDentistry
TopicEndodontics and Root Canal Treatments
Canadian institutionsUniversity of British Columbia
FundersSichuan UniversityFoundation for the Author of National Excellent Doctoral Dissertation of the People's Republic of ChinaNational Natural Science Foundation of China
KeywordsPeriodontal fiberAlkaline phosphataseFlow cytometryStainingAndrologyIn vitroAdhesionMolecular biologyChemistryBiologyDentistryMedicineBiochemistry

Abstract

fetched live from OpenAlex

AIM: To evaluate the cytocompatibility of Biodentine and iRoot FS with human periodontal ligament cells (hPDLCs). METHODOLOGY: Human periodontal ligament cells were characterized by flow cytometry and immunocytochemical analysis. Human periodontal ligament cell adhesion was assessed by scanning electron microscopy at day 3; proliferation by live/dead assay at days 1, 3 and 7; and osteogenic differentiation by alkaline phosphatase (ALP) activity staining, ALP quantification analysis and qRT-PCR at days 7 and 14. Data were analysed with anova and independent sample t-tests with SPSS 21.0. RESULTS: Both iRoot FS and Biodentine increased the adhesion of hPDLCs at day 3. Compared to Biodentine, iRoot FS positively increased hPDLC proliferation on days 3 (P = 0.03) and 7 (P = 0.00). Osteogenic marker ALP was observed consistently in all samples, with iRoot FS having significantly higher ALP activity at day 14 (P = 0.00). Compared with Biodentine, iRoot FS significantly increased the mRNA level of ALP, COL1 and Runx2, and OCN increased only on day 14 (P < 0.05). CONCLUSIONS: iRoot FS had a positive effect on the adhesion, proliferation and biomineralization of hPDLCs compared with Biodentine.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.020
GPT teacher head0.297
Teacher spread0.277 · 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.

Study designObservational
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

Citations18
Published2018
Admission routes1
Has abstractyes

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