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Record W3033336346 · doi:10.1080/17425247.2020.1777981

Bioactive molecule carrier systems in endodontics

2020· review· en· W3033336346 on OpenAlexafffund
Anil Kishen, Hebatullah Hussein

Bibliographic record

VenueExpert Opinion on Drug Delivery · 2020
Typereview
Languageen
FieldDentistry
TopicEndodontics and Root Canal Treatments
Canadian institutionsUniversity of TorontoMount Sinai HospitalSinai Health System
FundersUniversity of TorontoAmerican Association of Endodontists Foundation
KeywordsRegenerative medicineTissue engineeringRegeneration (biology)NanotechnologyStem cellBiomedical engineeringComputer scienceMaterials scienceBiologyCell biologyMedicine

Abstract

fetched live from OpenAlex

Introduction Bioactive molecule carrier systems (BACS) are biomaterial-based substrates that facilitate the delivery of active signaling molecules for different biologically based therapeutic applications, which include regenerative endodontic procedures. Tissue regeneration or organized repair in regenerative endodontic procedures is governed by the dynamic orchestration of interactions between stem/progenitor cells, bioactive molecules, and extracellular matrix. BACS aid in mimicking some of the complex physiological processes, overcoming some of the challenges faced in the clinical translation of regenerative endodontic procedures.Areas covered This narrative review addresses the role of BACS in stem/progenitor cell proliferation, migration, and differentiation with the application for dentin-pulp tissue engineering both in vitro and in vivo. BACS shield the bioactivity of the immobilized molecules against environmental factors, while its design allows the pre-programmed release of bioactive molecules in a spatial and temporal-controlled manner. The polymeric and non-polymeric materials used to synthesize micro and nanoscale-based BACS are reviewed.Expert opinion Comprehensive characterization of well-designed and customized BACS is necessary to be able to deliver multiple bioactive molecules in spatiotemporally controlled manner and to address the release kinetics required for potential in vivo application. This warrants further laboratory-based experiments and rigorous clinical investigations to enable their clinical translation for regenerative endodontic procedures.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.880
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
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)0.0000.001

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 head0.056
GPT teacher head0.346
Teacher spread0.291 · 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 designNot applicable
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

Citations15
Published2020
Admission routes2
Has abstractyes

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