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Record W2161532632 · doi:10.1002/hep.26523

Autoimmune hepatitis experimental model based on adenoviral infections

2013· letter· en· W2161532632 on OpenAlexaffabout
Pascal Lapierre, Kathie Béland, Fernando Álvarez

Bibliographic record

VenueHepatology · 2013
Typeletter
Languageen
FieldMedicine
TopicLiver Diseases and Immunity
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineArmand Frappier MuseumInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsAutoimmune hepatitisFibrosisImmunologyMedicineAdoptive cell transferHepatitisPathologyBiologyImmune systemT cell

Abstract

fetched live from OpenAlex

We read with great interest the article by Hardtke-Wolenski et al.1 describing the development of an animal model of autoimmune hepatitis based on a self-limited adenoviral infection. The adenovirus administered encoded for formiminotransferase cyclodeaminase (FTCD), a targeted liver antigen in type 2 autoimmune hepatitis (AIH), identified in 1999. This report confirms our previously published findings that a self-limited adenoviral infection, with a virus encoding for FTCD, can lead to the development of an AIH in mice.2 The researchers state that “danger signals” are necessary for the initiation of an autoimmune response against the liver based on adenoviral infections and hydrodynamic transfection experiments with an observation period of 12 weeks. These results are in contrast with previous findings in models of AIH generated by DNA vaccination3 or adoptive transfer,4 where a peripheral activation of T-cell specific to a liver autoantigen, in the absence of inflammation (danger signals), led to an active autoimmune response. The researchers describe the development of fibrosis in their model, but it is solely based on silver staining of liver sections. It should be remembered that silver staining of reticulin proteins mainly reflects changes in the liver structure (as in Fig. 2C), where mild alterations are observed. These can be interpreted as the result of hepatocyte lysis secondary to the lymphocyte infiltration. Trichrome staining would have allowed one to visualize collagen deposition, the hallmark of liver fibrosis. The researchers bring up an interesting point when they discuss the need for a predisposing genetic background (nonobese diabetes, in this case) for the development of an AIH in mice, an observation we previously reported on in our model of type 2 AIH. However, the complete absence of an AIH in C57BL/6 and FVB/N mice in their model is rather puzzling. We2 and others5 found that AIH can be triggered in both these mouse strains. This could be attributed to the duration of the observation period, which is critical in view of the fact that we observed the development of AIH as late as 8 months after adenoviral infection.2 In the article, it is not clear whether the C57BL/6 and FVB/N mice were followed for more than 12 weeks. It could also be the result of the plaque-forming units of adenovirus used, an important factor in the outcome of an adenoviral infection or their adenovirus construction, because our vector encoded for CYP2D6 in addition to FTCD,2 whereas Holdener et al. used an adenoviral vector encoding for CYP2D6.5 Pascal Lapierre, Ph.D.1 Kathie Béland, M.Sc.2 Fernando Alvarez, M.D.2 1Department of Immunovirology, INRS-Institut Armand-Frappier, Laval, Quebec, Canada 2Department of Gastroenterology, Hepatology, and Nutrition, CHU Sainte-Justine, Montréal, Quebec, Canada

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.449
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.022
GPT teacher head0.272
Teacher spread0.250 · 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
GenreCommentary

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

Citations4
Published2013
Admission routes2
Has abstractyes

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