Sensitive Detection of Human IgG in ELISA Using a Monoclonal Anti-IgG-Peroxidase Conjugate
Bibliographic record
Abstract
Enzyme-antibody (Ab) conjugates specific for IgG are widely used in indirect immunological assays and have been until recently routinely prepared with polyclonal IgG-specific animal Abs. The use of monoclonal Abs (MAbs) could permit a better standardization of the IgG-specific conjugate reagents but is expected to result in lower reactivity due to the recognition of a single epitope by the MAbs. In this work, we have characterized a monoclonal anti-human IgG-peroxidase (HRP) reagent and compared its reactivity with commercial reagents. The murine C5-1 anti-human IgG MAb was selected for conjugation because of its high affinity (K(a) = 1.9 x 10(10)M), pan-IgG reactivity and absence of cross-reactivity with various structures including animal IgGs. The specific activity and binding kinetics of the C5-1:HRP conjugate were similar to the ones of two polyclonal anti-IgG:HRP conjugates when tested with immobilized human IgG. The C5-1:HRP conjugate could detect low amounts of human IgG much more effectively than two commercial monoclonal conjugates although it was slightly less effective than a polyclonal conjugate. However, the C5-1 conjugate yielded reduced background reactivity compared to the polyclonal conjugate, resulting in similar signal-to-noise ratios. These results indicate that the C5-1:HRP conjugate could be a suitable substitute for anti-human IgG conjugates prepared from animal antisera.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".