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Record W2900552673 · doi:10.1128/iai.00790-18

Novel Assay To Characterize Neutrophil Responses to Oral Biofilms

2018· article· en· W2900552673 on OpenAlexaff
Morvarid Oveisi, Harold Shifman, Noah Fine, Chunxiang Sun, Naomi Glogauer, Dilani B. Senadheera, Michael Glogauer

Bibliographic record

VenueInfection and Immunity · 2018
Typearticle
Languageen
FieldDentistry
TopicOral microbiology and periodontitis research
Canadian institutionsPrincess Margaret Cancer CentreMount Sinai HospitalUniversity of Toronto
Fundersnot available
KeywordsBiologyBiofilmNeutrophil extracellular trapsMicrobiologyInflammationPeriodontal diseaseImmunologyNeutrophileBacteriaMedicine

Abstract

fetched live from OpenAlex

assay was developed to characterize neutrophil activation states based on CD marker expressions in response to oral monospecies bacterial biofilms. Using this approach, changes in CD marker expressions in response to specific prominent oral commensal and pathogenic bacteria were assayed. Several functional assays, including assays for phagocytosis, production of reactive oxygen species, activation of the transcription factor Nrf2, neutrophil extracellular trap formation, and myeloperoxidase release, were also performed to correlate neutrophil function with CD marker expression. Our results demonstrate that neutrophils display bacterial species-specific responses. This assay can be used to characterize how specific biofilms alter specific neutrophil pathways associated with their activation.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.059
GPT teacher head0.343
Teacher spread0.285 · 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

Citations30
Published2018
Admission routes1
Has abstractyes

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