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Cytotoxic Necrotizing Factor Type 1-Positive<i>Escherichia coli</i>Causes Increased Inflammation and Tissue Damage to the Prostate in a Rat Prostatitis Model

2001· article· en· W2099197531 on OpenAlexafffund
Karen E. Rippere-Lampe, Michael D. Lang, Howard Ceri, Merle S. Olson, Hank Lockman, Alison D. O’Brien

Bibliographic record

VenueInfection and Immunity · 2001
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEscherichia coli research studies
Canadian institutionsUniversity of Calgary
FundersNational Institute of Allergy and Infectious DiseasesNatural Sciences and Engineering Research Council of CanadaNational Institutes of HealthFondation pour la Recherche Médicale
KeywordsProstatitisVirulenceBiologyEscherichia coliVirulence factorMicrobiologyCytotoxic T cellInflammationProstateImmunologyIn vitroGeneGeneticsCancer

Abstract

fetched live from OpenAlex

Infection of rat prostates with cytotoxic necrotizing factor type 1 (CNF1)-positive uropathogenic Escherichia coli caused more inflammation-mediated morphological and histological tissue damage than did infection with isogenic CNF1-negative mutants. These striking differences occurred despite the finding that bacterial counts for the strain pairs were indistinguishable. We conclude that CNF1 contributes to E. coli virulence in a model of acute prostatitis. To our knowledge, the results of this study provide the first demonstration of a role for any uropathogenic E. coli virulence factor in acute prostatitis.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.669
Threshold uncertainty score0.402

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 studies0.0000.000
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 head0.016
GPT teacher head0.286
Teacher spread0.269 · 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

Citations97
Published2001
Admission routes2
Has abstractyes

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