MétaCan
Menu
Back to cohort
Record W2133563830 · doi:10.1186/1710-1492-10-20

Relationship between platelet activating factor acetylhydrolase activity and apolipoprotein B levels in patients with peanut allergy

2014· article· en· W2133563830 on OpenAlexaffvenue
Boris Perelman, Areej Adil, Peter Vadas

Bibliographic record

VenueAllergy Asthma and Clinical Immunology · 2014
Typearticle
Languageen
FieldMedicine
TopicFood Allergy and Anaphylaxis Research
Canadian institutionsSt. Michael's Hospital
FundersNational Peanut Board
KeywordsApolipoprotein BAnaphylaxisPlatelet-activating factorLipoproteinEndocrinologyInternal medicineChemistryAllergyPhospholipidPeanut allergyImmunologyMedicineBiochemistryFood allergyCholesterol

Abstract

fetched live from OpenAlex

BACKGROUND: Platelet-activating factor (PAF) is a highly potent phospholipid mediator responsible for the life-threatening manifestations of anaphylaxis. PAF acetylhydrolase (PAF-AH) inactivates PAF and protects against severe anaphylaxis whereas deficiency of PAF-AH predisposes to severe or fatal anaphylaxis. Determinants of PAF-AH activity have not been studied in patients with peanut allergy. OBJECTIVES: To determine whether plasma PAF-AH activity in patients with peanut allergy is related to formation of circulating complexes with apolipoprotein B (apoB) the main surface protein on low density lipoprotein particles. METHODS: Plasma PAF-AH activity and apoB concentrations were measured in 63 peanut allergic patients (35 boys, 28 girls, ages 2 - 19 years). ApoB concentration was measured immunoturbidimetrically using goat anti-human apoB. The correlation between PAF-AH activity and apoB concentration was determined. RESULTS: A positive correlation was found between PAF-AH activity and apoB concentration (r(2) = 0.59, P < 0.0001). CONCLUSION: In peanut allergic patients, PAF-AH activity strongly correlates with apoB concentration, suggesting the presence of circulating PAF-AH- lipoprotein complexes.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.211
Threshold uncertainty score0.883

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.001
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 head0.043
GPT teacher head0.326
Teacher spread0.283 · 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

Citations22
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueAllergy Asthma and Clinical ImmunologySame topicFood Allergy and Anaphylaxis ResearchFrench-language works237,207