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Kinetics of KB and HEp‐2 cell responses to an invasive, cytolethal distending toxin‐producing strain of <i>Actinobacillus actinomycetemcomitans</i>

2002· article· en· W2003087273 on OpenAlexafffund
Joseph M. DiRienzo, M Song, Luke Wan, Richard P. Ellen

Bibliographic record

VenueOral Microbiology and Immunology · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacillus and Francisella bacterial research
Canadian institutionsUniversity of Toronto
FundersNational Institute of Dental and Craniofacial ResearchMedical Research CouncilU.S. Public Health ServiceSick Kids Foundation
KeywordsCytolethal distending toxinActinobacillusMicrobiologyBiologyToxinPathogenStrain (injury)Cell cultureCytotoxicityGentamicin protection assayBacteriaPasteurellaceaeCellMolecular biologyIn vitroMicrobial toxinsBiochemistryWestern blotAntibioticsGeneticsGene

Abstract

fetched live from OpenAlex

The periodontal pathogen Actinobacillus actinomycetemcomitans produces cytolethal distending toxin (CDT), a complex multicomponent toxin that arrests the growth of many types of eukaryotic cell. The kinetics of the effects of CDT-containing extracts, from an invasive strain of this bacterium, were examined on epithelial-like cells routinely used in invasion studies. Both KB and HEp-2 cells were exquisitely sensitive to the effects of the CDT with TD50 of 30 and 300 pg of total bacterial protein, respectively. Initial cell morphology changes were relatively rapid, occurring within the first 13 h of exposure. CDT-treated KB cells increased in size to 4-5 times the size of untreated controls. Cytotoxicity was irreversible when attached cells were incubated, for a minimum of 120 min, with nanogram quantities of CDT-containing extract. As cultures aged, the cells became more resistant to the effects of the CDT-containing extracts. These findings have important implications for understanding the ability of A. actinomycetemcomitans to invade and multiply in epithelial cells.

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)0.000
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 score0.007
Threshold uncertainty score0.741

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.020
GPT teacher head0.245
Teacher spread0.224 · 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

Citations25
Published2002
Admission routes2
Has abstractyes

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