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Record W2089389204 · doi:10.1159/000320549

Genes Determining the Course of Virus Persistence in the Liver: Lessons from Murine Infection with Lymphocytic Choriomeningitis Virus

2010· review· en· W2089389204 on OpenAlexaff
Philipp A. Lang, Mike Recher, Dieter Häussinger, Karl S. Lang

Bibliographic record

VenueCellular Physiology and Biochemistry · 2010
Typereview
Languageen
FieldMedicine
TopicHepatitis B Virus Studies
Canadian institutionsOntario Institute for Cancer Research
Fundersnot available
KeywordsLymphocytic choriomeningitisVirusVirologyBiologyHepatitis B virusHepatitis C virusHepatocellular carcinomaImmunologyCD8Liver diseaseImmune systemCancer research

Abstract

fetched live from OpenAlex

More than 500 million people worldwide are persistently infected with either hepatitis B virus (HBV) or hepatitis C virus (HCV). Although both viruses are poorly cytopathic, persistent infection causes severe immunopathologic damage to liver tissue; histologically, such damage is characterized by fatty liver disease, liver fibrosis, and a higher likelihood of hepatocellular carcinoma. Virus-specific CD8+ T cells play a crucial role during infection with hepatitis viruses. On the one hand, rapid activation of CD8+ T cells can control the virus and therefore inhibit its persistence. On the other hand, once the virus persists in the liver, the chronic activation of virus-specific T cells leads to continued liver cell damage. This double-edged role of CD8+ T cells determines the final outcome of infection. In half of cases of human HCV infection, the virus persists; in the other half, the virus is controlled. Additional insights into the molecular mechanisms that determine the course of the disease may be gained from the study of appropriate murine models. This review discusses the similarities and differences between infection with lymphocytic choriomeningitis virus (LCMV) in mice and chronic infection with hepatitis virus in humans.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.749
Threshold uncertainty score0.709

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.042
GPT teacher head0.296
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

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

Citations13
Published2010
Admission routes1
Has abstractyes

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