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Antimicrobial Treatment of Dental Osseous Defects with Silver Doped Bioglass: Osteoblast Cell Response

2005· article· en· W2027503800 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

VenueKey engineering materials · 2005
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsKensington Health
FundersEngineering and Physical Sciences Research Council
KeywordsBioactive glassOsteoblastAntimicrobialResorptionViability assayDentistryMaterials scienceNuclear chemistryCytotoxicityDissolutionChemistryCellMedicineBiochemistryIn vitroInternal medicineOrganic chemistry

Abstract

fetched live from OpenAlex

In dentistry, chronic periodontitis often leads to bone resorption together with an increasing risk of bacteremia. Bioactive glass has found extensive application as dental graft material. A successful antimicrobial bactericidal effect has been shown from the introduction of Ag2O into the glass composition. In this study, the cytotoxicity of soluble silver, calcium and silica ions on primary human osteoblasts was investigated by measurements of mitochondrial activity and neutral red dye uptake. Silver concentrations of 4 - 6 ppm (1 mg/ml conc.) and 6 - 9 ppm (2 mg/ml conc.) have been measured in complete culture medium. It was found that the bioactive gel-glass extract with an initial concentration of 1 mg/ml (1mg glass per ml of culture medium) has no negative effect, whereas increased gel-glass concentration of 2 mg/ml seemed to have a toxic effect on the cell viability of human osteoblasts. It might be concluded that a reduction of the rate of silver dissolution from the bioactive gel-glass might preserve a maximum cell viability.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.218
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
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 head0.004
GPT teacher head0.175
Teacher spread0.171 · 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