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Record W4390976773 · doi:10.1080/1744666x.2024.2306885

Comparison of high- and low-molecular-weight sensitizing agents causing occupational asthma: an evidence-based insight

2024· review· en· W4390976773 on OpenAlexaff
Virginie Doyen, Denyse Gautrin, Olivier Vandenplas, Jean‐Luc Malo

Bibliographic record

VenueExpert Review of Clinical Immunology · 2024
Typereview
Languageen
FieldMedicine
TopicOccupational exposure and asthma
Canadian institutionsUniversité de MontréalHôpital du Sacré-Cœur de Montréal
Fundersnot available
KeywordsMedicineOccupational asthmaAsthmaEnvironmental healthImmunology

Abstract

fetched live from OpenAlex

INTRODUCTION: The many substances used at the workplace that can cause sensitizer-induced occupational asthma are conventionally categorized into high-molecular-weight (HMW) agents and low-molecular-weight (LMW) agents, implying implicitly that these two categories of agents are associated with distinct phenotypic profiles and pathophysiological mechanisms. AREAS COVERED: The authors conducted an evidence-based review of available data in order to identify the similarities and differences between HMW and LMW sensitizing agents. EXPERT OPINION: Compared with LMW agents, HMW agents are associated with a few distinct clinical features (i.e. concomitant work-related rhinitis, incidence of immediate asthmatic reactions and increase in fractional exhaled nitric oxide upon exposure) and risk factors (i.e. atopy and smoking). However, some LMW agents may exhibit 'HMW-like' phenotypic characteristics, indicating that LMW agents are a heterogeneous group of agents and that pooling them into a single group may be misleading. Regardless of the presence of detectable specific IgE antibodies, both HMW and LMW agents are associated with a mixed Th1/Th2 immune response and a predominantly eosinophilic pattern of airway inflammation. Large-scale multicenter studies are needed that use objective diagnostic criteria and assessment of airway inflammatory biomarkers to identify the pathobiological pathways involved in OA caused by the various non-protein agents.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.888
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.197
GPT teacher head0.532
Teacher spread0.336 · 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 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

Citations10
Published2024
Admission routes1
Has abstractyes

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