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Record W2003767334 · doi:10.1159/000231747

Modulation of the IgE Antibody Response in Rats to Kentucky Blue Grass Pollen Allergens

2009· article· en· W2003767334 on OpenAlexaff
A.K.M. Ekramoddoullah, F.T. Kisil, A.H. Sehon

Bibliographic record

VenueInternational Archives of Allergy and Applied Immunology · 2009
Typearticle
Languageen
FieldMedicine
TopicAllergic Rhinitis and Sensitization
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsImmunoglobulin ESephadexAntibodyChemistryImmunologySalineAntiserumTiterMicrogramIn vitroBiochemistryEndocrinologyBiologyEnzyme

Abstract

fetched live from OpenAlex

The low molecular weight dialyzable fraction (D) prepared from the aqueous extract of Kentucky Blue Grass pollen was shown to suppress the formation of IgE antibodies in rats immunized with the nondialyzable fraction (R). In an attempt to establish the nature of the constituents responsible for this suppression, D was fractionated by gel filtration through Sephadex G-25. The first fraction eluted (DI) elicited skin reactions in rats sensitized with a rat reaginic serum to R and also gave a precipitate with a rabbit antiserum to R. A later fraction (DIII) was devoid of these two properties. To investigate the effects of these fractions on the antibody response, rats received either DI or DIII, administered in saline, prior to their immunization with R in presence of aluminum hydroxide. Pretreatment with DI resulted in a reduction of IgE antibody levels as compared with the IgE antibody response in control animals which had received pretreatment only with saline; however, pretreatment with DI did not affect the anti-R-hemagglutinating titers. In contrast, pretreatment with DIII enhanced both the IgE and the hemagglutinating antibodies. Hence, it is concluded that the composite fraction D contains one group of constituents capable of suppressing and another of enhancing the IgE antibody response.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.968
Threshold uncertainty score0.307

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)0.0000.000

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 head0.008
GPT teacher head0.256
Teacher spread0.248 · 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

Citations3
Published2009
Admission routes1
Has abstractyes

Explore more

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