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Record W2788022358 · doi:10.22203/ecm.v035a02

TiO2 nanoparticles can selectively bind CXCL8 impacting on neutrophil chemotaxis

2018· article· en· W2788022358 on OpenAlex
Joanna Batt, Mike Milward, Iain Chapple, Melissa M. Grant, Scott J. Roberts, Owen Addison

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

VenueEuropean Cells and Materials · 2018
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Nanomaterials in Catalysis
Canadian institutionsUniversity of Alberta
FundersNational Institute for Health and Care Research
KeywordsInterleukin 8ChemotaxisChemokineChemistryTitaniumInflammationBiophysicsMaterials scienceImmunologyReceptorMedicineBiochemistryBiology

Abstract

fetched live from OpenAlex

The interaction between TiO 2 nanoparticles (NPs) and inflammatory cytokines, including CXCL8, a clinically relevant pro-inflammatory chemokine, was investigated. TiO 2 is present in tissues adjacent to failing implanted Ti (titanium) devices. TiO 2 NPs were shown to bind to CXCL8 in vitro, causing perturbation of quantification of CXCL8 by ELISA, in both simple and complex protein panels, in a dose-dependent manner. Binding between TiO 2 NPs and CXCL8 was demonstrated by protein gel electrophoresis. TiO 2 NPs were also shown to inactivate the chemoattractant property of CXCL8 in a dose-dependent manner, suggesting that the binding between TiO 2 NPs and CXCL8 is likely to be clinically relevant. The results of this study disputed the applicability of detection of CXCL8 by ELISA in systems where TiO 2 NPs were present. Clinically, the disruption of neutrophil chemotaxis due to CXCL8 binding to TiO 2 NPs might result in a hampered inflammatory response.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.004
Threshold uncertainty score1.000

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)0.0010.001

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 head0.013
GPT teacher head0.233
Teacher spread0.220 · 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