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Record W4223494892 · doi:10.1177/20587384211068667

Patients with treated autoimmune hepatitis and persistent suppression of plasmacytoid dendritic cells: A different point of view

2022· article· en· W4223494892 on OpenAlexaff
Irene Santos, Mayra T de Assunção, Renan Marrichi Mauch, Natascha Silva Sandy, Marcos Tadeu Nolasco da Silva, Maria Angela Bellomo‐Brandão, Adriana Gut Lopes Riccetto

Bibliographic record

VenueInternational Journal of Immunopathology and Pharmacology · 2022
Typearticle
Languageen
FieldMedicine
TopicLiver Diseases and Immunity
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsFOXP3Autoimmune hepatitisMedicineImmunophenotypingImmunologyCD19CD8IL-2 receptorCD38Plasmacytoid dendritic cellPathogenesisFlow cytometryT cellDendritic cellHepatitisImmune systemBiology

Abstract

fetched live from OpenAlex

Objectives: Plasmacytoid dendritic cells (pDCs) have been shown to have a role in autoimmune diseases, but their role in Autoimmune Hepatitis (AIH) is not completely clear. In the present study, we assessed the frequency of pDCs in peripheral blood of AIH patients under long-term standard immunosuppressive therapy. Methods: This cross-sectional analysis enrolled 27 AIH patients and 27 healthy controls. We analyzed and compared their proportion of pDCs, CD4 + , CD8 + , γδ T cells, CD25 + regulatory T (Treg) cells, FoxP3 + , Foxp3 + CD39 + Treg cells, total B (CD19 + ) cells, and plasma cells (CD38 + ) in peripheral blood using flow cytometry immunophenotyping. Results: AIH patients had a lower percentage of pDCs (median frequencies of 0.2% vs. 0.4%; p = .002) and higher expression of CD8 T cells (32.5% vs 28.6%; p = 0.008) in peripheral blood, when compared to healthy controls. We did not find statistically significant differences between the groups regarding the other cell subtypes.Conclusion: Our data suggest a persistent suppression of pDCs in AIH patients, along with increased CD8 T cell activity, years after AIH diagnosis and despite of good clinical response to treatment, thus pointing to a role of pDCs in the AIH pathogenesis.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.269
Threshold uncertainty score0.637

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)0.0010.000

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 head0.008
GPT teacher head0.255
Teacher spread0.247 · 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 designObservational
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
Published2022
Admission routes1
Has abstractyes

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