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Record W1923345711 · doi:10.1177/0954411915584962

In vitro degradation and cell viability assessment of Zn–3Mg alloy for biodegradable bone implants

2015· article· en· W1923345711 on OpenAlexaff
MS Dambatta, N. S. Murni, S. Izman, Denni Kurniawan, Hendra Hermawan

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part H Journal of Engineering in Medicine · 2015
Typearticle
Languageen
FieldMaterials Science
TopicMagnesium Alloys: Properties and Applications
Canadian institutionsUniversité Laval
FundersUniversiti Teknologi MalaysiaKementerian Pendidikan MalaysiaUniversiti Teknologi MARA
KeywordsDegradation (telecommunications)AlloyIn vitroViability assayBiomedical engineeringChemistryMaterials scienceDentistryNuclear chemistryMetallurgyMedicineBiochemistryEngineering

Abstract

fetched live from OpenAlex

This article reports the in vitro degradation and cytotoxicity assessment of Zn-3Mg alloy developed for biodegradable bone implants. The alloy was prepared using casting, and its microstructure was composed of Mg2Zn11 intermetallic phase distributed within a Zn-rich matrix. The degradation assessment was done using potentiodynamic polarization and electrochemical impedance spectrometry. The cell viability and the function of normal human osteoblast cells were assessed using 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium and alkaline phosphatase extracellular enzyme activity assays. The results showed that the degradation rate of the alloy was slower than those of pure Zn and pure Mg due to the formation of a high polarization resistance oxide film. The alloy was cytocompatible with the normal human osteoblast cells at low concentrations (<0.5 mg/mL), and its alkaline phosphatase activity was superior to pure Mg. This assessment suggests that Zn-3Mg alloy has the potential to be developed as a material for biodegradable bone implants, but the toxicity limit must be carefully observed.

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)0.002
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 score0.044
Threshold uncertainty score0.315

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 science0.0000.000
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 head0.025
GPT teacher head0.262
Teacher spread0.236 · 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".

Quick stats

Citations27
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Institution of Mechanical Engineers Part H Journal of Engineering in MedicineSame topicMagnesium Alloys: Properties and ApplicationsFrench-language works237,207