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Record W2024693005 · doi:10.1081/ias-120013034

IDENTIFICATION OF ANTIGENIC AND ALLERGENIC NATURAL RUBBER LATEX PROTEINS BY IMMUNOBLOTTING1*

2002· article· en· W2024693005 on OpenAlex
Vesna J. Tomazic‐Jezic, Wava Truscott

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Immunoassay and Immunochemistry · 2002
Typearticle
Languageen
FieldEngineering
TopicLubricants and Their Additives
Canadian institutionsKimberly-Clark (Canada)
Fundersnot available
KeywordsAntiserumWestern blotAntigenLowry protein assayChemistryChromatographyNatural rubberAntibodyImmunoassayMolecular biologyBiochemistryBiologyImmunology

Abstract

fetched live from OpenAlex

Quantitation of proteins in finished natural rubber latex (NRL) products is essential in predicting their allergenic potential. The ASTM standard Modified Lowry method for measuring total protein content has been used for several years. Most recently, ASTM published a standard for more sensitive and more specific enzyme immunoassay for quantitation of antigenic NRL proteins. It is an ELISA inhibition assay, using rabbit anti NRL sera. Since the measurement of proteins in this method depends on recognition capacity of rabbit antibodies, the selection of an appropriate protein source for rabbit immunization is crucial for the accuracy of such test. In this study, we evaluated the composition of NRL proteins from ammoniated (AL) and nonammoniated (NAL) raw latex and from finished NRL products, and compared the effectiveness of sera from rabbits immunized with NRL proteins, to react with those extracts. Immune rabbit sera were analyzed by immunoblotting against extracts of several samples of AL, NAL, and glove proteins. In the NAL extracts, we identified 26-28 protein bands by SDS-PAGE. AL samples had between 6 and 9 bands with a great variation in the band positions among the samples. The Western blot analysis showed that anti-AL rabbit serum reacted with 4-9 protein bands in various AL extracts. The highest intensity of reaction was observed with the extract used to immunize the rabbits. Similar reaction was observed with anti-NAL serum. However, when the antisera were blotted against NAL extracts, anti-NAL serum reacted more strongly and with a larger number of proteins than anti-AL serum. In summary, anti-NAL serum recognized an equal number of proteins in AL extract as anti-AL serum. However, anti-AL serum recognized fewer protein molecules in NAL extract than anti-NAL serum. Our findings suggest that NAL extract contains more individual proteins than other extracts, and sera from rabbits immunized with this antigen have a greater capacity to react with a wide spectrum of NRL proteins. This finding may be helpful in selecting the representative reference antigen and antiserum for further efforts in NRL protein quantitation.

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.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.604

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 head0.003
GPT teacher head0.166
Teacher spread0.163 · 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