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Record W4390912622 · doi:10.3390/nano14020198

Characterization and Cellular Toxicity Studies of Commercial Manganese Oxide Nanoparticles

2024· article· en· W4390912622 on OpenAlexafffund
Linda J. Johnston, Xiaomei Du, Andre Zborowski, David C. Kennedy

Bibliographic record

VenueNanomaterials · 2024
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticles: synthesis and applications
Canadian institutionsNational Research Council Canada
FundersHealth CanadaUniversity of Ottawa
KeywordsNanoparticleManganeseCatalysisManganese oxideCharacterization (materials science)ToxicityReactive oxygen speciesNanotechnologyNanomaterialsMaterials scienceOxideNanotoxicologyChemistryEnvironmental chemistryBiochemistryMetallurgyOrganic chemistry

Abstract

fetched live from OpenAlex

Manganese oxide nanoparticles (MnOx NPs) are finding applications in several environmentally important areas such as farming and energy storage. MnOx NPs span a range of metal oxidation states that open up a wide range of applications in catalysis as well. As a result, it is important to understand how such materials can impact human health through incidental exposure. In this study, we examined a range of commercially available Mn2O3 NPs and compared our characterization data to those supplied by manufacturers. Discrepancies were noted and then measured values were used to assess the biological impact of these materials on three mammalian cell lines—A549, HepG2 and J774A.1 cells. Cell toxicity assays showed that all Mn2O3 particles exhibited cytotoxic effects that may be correlated, at least in part, to the production of reactive oxygen species. All eight nanoforms also activated caspase 3 but not caspase 1, although the magnitude of these changes varied greatly between materials.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.423

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 head0.035
GPT teacher head0.288
Teacher spread0.254 · 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

Citations14
Published2024
Admission routes2
Has abstractyes

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