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Record W235469835 · doi:10.1007/0-306-48741-1_11

Animal Models of Chlamydia pneumoniae Infection and Atherosclerosis

2006· book-chapter· en· W235469835 on OpenAlexaff
I. W. Fong

Bibliographic record

VenueKluwer Academic Publishers eBooks · 2006
Typebook-chapter
Languageen
FieldImmunology and Microbiology
TopicReproductive tract infections research
Canadian institutionsSt. Michael's HospitalUniversity of Toronto
Fundersnot available
KeywordsChlamydiaMedicineAnimal modelMicrobiologyVirologyBiologyImmunologyInternal medicine

Abstract

fetched live from OpenAlex

Chlamydia pneumoniae has been associated with cardiovascular disease and stroke in humans by numerous cross-sectional and case–control studies, but prospective, longitudinal studies have produced mixed results and most have not confirmed this association. However, pathological studies have established the association of C. pneumoniae antigen or DNA with atherosclerosis from surgical and autopsy vascular specimens, with odds ratio of around 20. Although in vitro and cell culture studies have supported biological plausible mechanisms for C. pneumoniae to induce or accelerate atherosclerosis, they lack the complexity of a real disease, thus limiting the scope of testing the hypothesis of causality. Animal models are more likely to mimic real disease in humans, and are critical in many conditions in the understanding of the pathogenesis, cause-andeffect relationships and subsequent approaches to treatment and prevention of diseases. Thus, animal experimentation in medical research has played a major role in our understanding of diseases. The earliest recorded use of animal models extends as far back as 500 BC, when Alcmaeon of Croton defined the function of the optic nerve by transection in a living animal. The Hippocratic treatise on the heart (circa 350 BC) discussed cutting the throat of a pig that drank colored water to study the act of swallowing.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.637
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0030.003
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 head0.036
GPT teacher head0.258
Teacher spread0.222 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2006
Admission routes1
Has abstractyes

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