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Record W2565379546 · doi:10.1128/9781555818722.ch88

Detection of Autoantibodies by Enzyme-Linked Immunosorbent Assay and Bead Assays

2016· book-chapter· en· W2565379546 on OpenAlex
Edward K. L. Chan, Rufus W. Burlingame, Marvin J. Fritzler

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

VenueASM Press eBooks · 2016
Typebook-chapter
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAutoantibodyAntigenComplement fixation testImmunologyPrecipitinAntibodyCounterimmunoelectrophoresisBlotImmunodiffusionBiologyMolecular biologySerologyBiochemistryGene

Abstract

fetched live from OpenAlex

Autoantibodies directed against intracellular antigens are characteristic features of a number of human autoimmune diseases and certain malignancies (1–3). Studies of systemic autoimmune rheumatic diseases have provided strong evidence that autoantibodies are maintained by antigen-driven responses (4, 5) and that autoantibodies can be reporters from the immune system, revealing the identities of antigens involved in disease pathogenesis. Historically, autoantibody detection and analysis have relied on a number of different technologies, such as hemagglutination and particle aggregation, immunodiffusion, indirect immunofluorescence (IIF), complement fixation, counterimmunoelectrophoresis (CIE), Western and dot blotting, immunoprecipitation (IP), and enzyme-linked immunosorbent assay (ELISA), and on functional assays that demonstrate inhibition of the catalytic or other functional activity of the antigen of interest. These technologies have limitations because they tend to be labor-intensive and time-consuming, are limited in throughput, are semiquantitative, and are not adaptable to leading-edge research. Immunodiffusion has been used for over 50 years, and it is still used in some clinical laboratories because it is inexpensive and has high specificity, but it lacks sensitivity and can take up to 48 h before precipitin lines are interpretable. Western blotting is more costly and time-consuming, and not all autoantibodies are detected by this technique. For example, in the SS-A/Ro system, it has been observed that IP techniques are required to identify some sera that contain antibodies reacting only with the “native” SS-A/Ro particle (6). IP protocols that use extracts from [35S]methionine-labeled cells are not suitable for the detection of all autoantibodies, such as antibodies to Ro52/TRIM21 protein (7). ELISA techniques have rapidly advanced, but highly specific, sensitive, and reliable assays that use highly purified or recombinant proteins are limited by intermanufacturer and interlaboratory variation of results (8). Immunodiffusion and CIE generally favor high-titer sera and often cannot discriminate multiple autoantibody responses that are characteristic of systemic autoimmune rheumatic disease sera.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.834
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.031
GPT teacher head0.281
Teacher spread0.250 · 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