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Coxsackievirus-induced murine myocarditis and immunomodulatory interventions

2010· book-chapter· en· W79589386 on OpenAlexaff
Michel Noutsias, Peter Liu

Bibliographic record

VenueBirkhäuser Basel eBooks · 2010
Typebook-chapter
Languageen
FieldMedicine
TopicViral Infections and Immunology Research
Canadian institutionsToronto General HospitalHeart and Stroke FoundationCanadian Institutes of Health Research
Fundersnot available
KeywordsMyocarditisCoxsackievirusMedicineImmunologyPathogenesisViral MyocarditisImmune systemDiseaseCardiomyopathyVirusInflammationVirologyEnterovirusHeart failurePathologyCardiology

Abstract

fetched live from OpenAlex

Human acute myocarditis (AMC) and its sequelae, inflammatory cardiomyopathy (DCMi), are mostly caused by cardiotropic viral infections in the Western world. Insights from coxsackievirus B (CVB)-induced experimental myocarditis have substantially contributed to a better understanding of the complex pathogenesis of myocarditis, and have also helped to explain the highly differential courses of human disease. Several inbred murine strains are available for modeling acute myocarditis and chronic ongoing myocarditis after intraperitoneal CVB inoculation. Acute, subacute and chronic phases can be differentiated. The onset and the differential courses of CVB-induced myocarditis are orchestrated by complex virus-host interactions. Several immunomodulatory regimens targeting key players of the innate and the adaptive immune system have unraveled the underlying mechanisms, and identified promising intervention strategies. The latter may, once they have been clinically evaluated, translate to novel treatment strategies for patients. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.006

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 head0.065
GPT teacher head0.319
Teacher spread0.254 · 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

Citations2
Published2010
Admission routes1
Has abstractyes

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