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Record W3111125499 · doi:10.4049/jimmunol.2000433

CD4+CTLs in Fibrosing Mediastinitis Linked to <i>Histoplasma capsulatum</i>

2020· article· en· W3111125499 on OpenAlexaff
Hugues Allard‐Chamard, Faisal Alsufyani, Naoki Kaneko, Kelly Xing, Cory A. Perugino, Vinay S. Mahajan, Joseph Wheat, George S. Deepe, James Loyd, Shiv Pillai

Bibliographic record

VenueThe Journal of Immunology · 2020
Typearticle
Languageen
FieldMedicine
TopicIgG4-Related and Inflammatory Diseases
Canadian institutionsUniversité de Sherbrooke
FundersNational Institute of Allergy and Infectious DiseasesNational Institutes of Health
KeywordsFibrosisHistoplasmosisImmunologyPathogenesisDiseaseHistoplasmaPathologyMedicineHistoplasma capsulatumBiology

Abstract

fetched live from OpenAlex

Abstract Although fibrotic disorders are frequently assumed to be linked to TH2 cells, quantitative tissue interrogation studies have rarely been performed to establish this link and certainly many fibrotic diseases do not fall within the type 2/allergic disease spectrum. We have previously linked two human autoimmune fibrotic diseases, IgG4-related disease and systemic sclerosis, to the clonal expansion and lesional accumulation of CD4+CTLs. In both these diseases TH2 cell accumulation was found to be sparse. Fibrosing mediastinitis linked to Histoplasma capsulatum infection histologically resembles IgG4-related disease in terms of the inflammatory infiltrate and fibrosis, and it provides an example of a fibrotic disease of infectious origin in which the potentially profibrotic T cells may be induced and reactivated by fungal Ags. We show in this study that, in this human disease, CD4+CTLs accumulate in the blood, are clonally expanded, infiltrate into disease lesions, and can be reactivated in vitro by H. capsulatum Ags. TH2 cells are relatively sparse at lesional sites. These studies support a general role for CD4+CTLs in inflammatory fibrosis and suggest that fibrosing mediastinitis is an Ag-driven disease that may provide important mechanistic insights into the pathogenesis of idiopathic fibrotic diseases.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.855
Threshold uncertainty score0.317

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.001
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 head0.018
GPT teacher head0.243
Teacher spread0.225 · 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 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

Citations21
Published2020
Admission routes1
Has abstractyes

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