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Record W2008241339 · doi:10.1002/jbm.a.32688

Effect of chromium and cobalt ions on the expression of antioxidant enzymes in human U937 macrophage‐like cells

2010· article· en· W2008241339 on OpenAlexaff
C. Tkaczyk, Olga L. Huk, Fackson Mwale, John Antoniou, David J. Zukor, Alain Petit, Maryam Tabrizian

Bibliographic record

VenueJournal of Biomedical Materials Research Part A · 2010
Typearticle
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsSuperoxide dismutaseCatalaseAntioxidantReactive oxygen speciesGlutathione peroxidaseEnzymeMolecular biologyCobaltChromiumBiochemistrySuperoxideMetal ions in aqueous solutionDismutaseBiologyChemistryMaterials scienceMetalInorganic chemistryMetallurgy

Abstract

fetched live from OpenAlex

The main concern associated with metal-on-metal (MM) hip prosthesis is the presence of metal ions, mainly chromium (Cr) and cobalt (Co), which are found both systemically and locally in the organism of patients. Previous studies revealed that Cr(III) and Co(II) ions could induce damages to proteins in macrophage-like cells in vitro, probably through the formation of reactive oxygen species (ROS). We then hypothesized that these ions can modify the expression of antioxidant enzymes in these cells. Results showed that Cr(VI) induced the protein expression of Mn-superoxide dismutase, Cu/Zn-superoxide dismutase, catalase, glutathione peroxidase, and heme oxygenase-1 (HO-1) but had no effect of the expression of their mRNA. Cr(III) have no effect on the expression of all these antioxidant enzymes. Co(II) induced the expression of both protein and mRNA of HO-1 only. In conclusion, results showed that Cr(VI), Cr(III), and Co(II) had differential effects on the expression of antioxidant enzymes in macrophage-like cells in vitro.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.010
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.361
Teacher spread0.337 · 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 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

Citations24
Published2010
Admission routes1
Has abstractyes

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Same venueJournal of Biomedical Materials Research Part ASame topicOrthopaedic implants and arthroplastyFrench-language works237,207