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Record W2915198159 · doi:10.1080/1744666x.2019.1584038

The molecular immunology of human susceptibility to fungal diseases: lessons from single gene defects of immunity

2019· review· en· W2915198159 on OpenAlexaff
Donald C. Vinh

Bibliographic record

VenueExpert Review of Clinical Immunology · 2019
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmunodeficiency and Autoimmune Disorders
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsImmunityImmunologyImmune systemAntifungalExpert opinionBiologyMedicineComputational biologyIntensive care medicineMicrobiology

Abstract

fetched live from OpenAlex

INTRODUCTION: Fungal diseases are a threat to human health. Therapies targeting the fungus continue to lead to disappointing results. Strategies targeting the host response represent unexplored opportunities for innovative treatments. To do so rationally requires the identification and neat delineation of critical mechanistic pathways that underpin human antifungal immunity. The study of humans with single-gene defects of the immune system, i.e. inborn errors of immunity (IEIs), provides a foundation for these paradigms. Areas covered: A systematic literature search in PubMed, Scopus, and abstracts of international congresses was performed to review the history of genetic resistance/susceptibility to fungi and identify IEIs associated with fungal diseases. Immunologic mechanisms from relevant IEIs were integrated with current definitions and understandings of mycoses to establish a framework to map out critical immunobiological pathways of human antifungal immunity. Expert opinion: Specific immune responses non-redundantly govern susceptibility to their corresponding mycoses. Defining these molecular pathways will guide the development of host-directed immunotherapies that precisely target distinct fungal diseases. These findings will pave the way for novel strategies in the treatment of these devastating infections.

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)0.003
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.941
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0100.005
Bibliometrics0.0000.001
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0040.002
Research integrity0.0020.002
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 head0.083
GPT teacher head0.438
Teacher spread0.355 · 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.

Study designNot applicable
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

Citations10
Published2019
Admission routes1
Has abstractyes

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