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Record W4411601063 · doi:10.1371/journal.pone.0313055

Identification and mitigation of blood’s interference with the antimicrobial activity of AgNbO3 particles

2025· article· en· W4411601063 on OpenAlexafffund
Cyrus Talebpour, Fereshteh Fani, Marc Ouellette, Marilynn R. Fairfax, Houshang Alamdari, Hossein Salimnia

Bibliographic record

VenuePLoS ONE · 2025
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticles: synthesis and applications
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsHemoglobinAntimicrobialChelationFerricChemistryHemeLysisHemolysisBiochemistryMicrobiologyMedicineBiologyInorganic chemistryInternal medicineOrganic chemistry

Abstract

fetched live from OpenAlex

The detrimental impact of blood on the antimicrobial activity of AgNbO3 particles was identified and investigated. It was observed that the impact is more severe in the case of lysed blood. The same phenomenon also operates in the case of commonly used silver salt, AgNO3. The inhibition was shown to be due to hemoglobin, but may be unrelated to the heme moiety. In an attempt to find additives to mitigate the inhibitory effect of hemoglobin, iron ions and the chelating agent, K2EDTA, were initially considered as potential candidates. Including ferric iron on the particles was shown to have a marginal effect, but supplying the medium with K2EDTA chelating agent, provided a better outcome for countering the deleterious impact of hemoglobin on AgNbO3 activity. These findings may be relevant for adapting the silver compounds to applications such as wound dressings, where silver's antimicrobial action would have to take place in a blood containing environment.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.022
GPT teacher head0.226
Teacher spread0.204 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2025
Admission routes2
Has abstractyes

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