Immunoaffinity Purification of Chlorimuron-ethyl from Soil Extracts Prior to Quantitation by Enzyme-Linked Immunosorbent Assay
Bibliographic record
Abstract
A competitive-indirect enzyme-linked immunosorbent assay (CI-ELISA) was developed to quantify chlorimuron-ethyl in soil. The linear working range of the assay was from 1 to 1000 ng mL(-)(1). The assay had an I(50) value of 54 ng mL(-)(1), with a limit of detection of 2 ng mL(-)(1) and a limit of quantification of 27 ng mL(-)(1). Three soils were extracted using a carbonate buffer (pH 9.0) and the extracts spiked with chlorimuron-ethyl. Because of the effects of coextractants (matrix effects) from soil on the accuracy and precision of the ELISA, immunoaffinity chromatography (IAC) was used to purify chlorimuron-ethyl from soil extracts prior to analysis. The immunoaffinity columns, which had a total binding capacity of 1350 ng of chlorimuron-ethyl mL(-)(1) of immunosorbent, were prepared by binding anti-chlorimuron-ethyl antibodies to protein G Sepharose 4B. Although the matrix effects were largely removed using the affinity column, they could be completely removed by first passing the extract through a column containing epoxy-coupled 1,6-diaminohexane (EAH) Sepharose 4B to remove organic acids prior to IAC. Assay sensitivity was increased 100-fold using IAC to purify and simultaneously concentrate chlorimuron-ethyl from soil extracts. The purification strategy (EAH followed by IAC chromatography) removed matrix effects from all three soils and allowed for the accurate quantitation of chlorimuron-ethyl in soil extracts.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".