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Record W2111849332 · doi:10.1177/0022034512467034

Effects of Etch-and-Rinse and Self-etch Adhesives on Dentin MMP-2 and MMP-9

2012· article· en· W2111849332 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Dental Research · 2012
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsWestern University
FundersNational Institute of Dental and Craniofacial ResearchUniversità degli Studi di TriesteMinistero dell’Istruzione, dell’Università e della Ricerca
KeywordsAdhesiveDentinMaterials scienceMatrix metalloproteinaseComposite materialDentistryChemistryMedicine

Abstract

fetched live from OpenAlex

Auto-degradation of collagen matrices occurs within hybrid layers created by contemporary dentin bonding systems, by the slow action of host-derived matrix metalloproteinases (MMPs). This study tested the null hypothesis that there are no differences in the activities of MMP-2 and -9 after treatment with different etch-and-rinse or self-etch adhesives. Tested adhesives were: Adper Scotchbond 1XT (3M ESPE), PQ1 (Ultradent), Peak LC (Ultradent), Optibond Solo Plus (Kerr), Prime&Bond NT (Dentsply) (all 2-step etch-and-rinse adhesives), and Adper Easy Bond (3M ESPE), Tri-S (Kuraray), and Xeno-V (Dentsply) (1-step self-etch adhesives). MMP-2 and -9 activities were quantified in adhesive-treated dentin powder by means of an activity assay and gelatin zymography. MMP-2 and MMP-9 activities were found after treatment with all of the simplified etch-and-rinse and self-etch adhesives; however, the activation was adhesive-dependent. It is concluded that all two-step etch-and-rinse and the one-step self-etch adhesives tested can activate endogenous MMP-2 and MMP-9 in human dentin. These results support the role of endogenous MMPs in the degradation of hybrid layers created by these adhesives.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.550
Threshold uncertainty score0.345

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.033
GPT teacher head0.372
Teacher spread0.339 · 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