Comparison of fluorogenic and chromogenic assay systems in the detection of Escherichia coli O157 by a novel polymyxin-based ELISA
Bibliographic record
Abstract
AIMS: Different indicator enzymes and fluorogenic or chromogenic substrates were compared as detector systems in a novel polymyxin-based enzyme-linked immunosorbent assay (ELISA) for Escherichia coli O157 lipopolysaccharide (LPS) antigens. METHODS AND RESULTS: An ELISA system was developed using polymyxin immobilized in the wells of a microtitre plate as a high-affinity adsorbent for E. coli O157 LPS antigens, which were immunoenzymatically detected using anti-E. coli O157 antibody-enzyme conjugates. With peroxidase as the indicator enzyme the fluorogenic substrates Amplex Red and QuantaBlu produced only slight improvement in the performance characteristics of the polymyxin-ELISA compared with the use of the chromogenic substrate tetramethylbenzidine (TMB). On the other hand, with alkaline phosphatase as the indicator enzyme a pronounced improvement in assay performance was noted using the fluorogenic substrate Attophos compared with the chromogenic substrate p-nitrophenylphosphate. CONCLUSIONS: The detection system exhibiting the best characteristics with respect to cost, ease of use and overall performance in the detection of E. coli O157 in enrichment cultures from a variety of solid foods was based on the use of peroxidase as the indicator enzyme with the chromogenic substrate TMB. SIGNIFICANCE AND IMPACT OF THE STUDY: The polymyxin-ELISA provides a rapid, simple and inexpensive assay system for the detection of E. coli O157 in foods.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".