Antibody Functionalised Gold Nanoprobes Based Colorimetric Assay for the Direct Detection of Phenylurea Herbicide
Bibliographic record
Abstract
One-step homogeneous colorimetric immunoassay format for direct detection of herbicide diuron is reported. Gold nanoparticles (30 nm) functionalised with specific anti-diuron antibody was used as bioprobes for the development of non-crosslinking hybridization method, where aggregation of the gold-nanoprobes is induced by an increasing salt concentration, and is prevented by the amount of antigen (diuron) present in sample solution. The aggregation profile of the antibody functionalised gold nanoparticles directed by the immunoreaction was investigated using transmission electron microscopy (TEM), dynamic light scattering (DLS) and was further confirmed colorimetrically by measuring the change in the absorption ratio (620/520 nm) with increasing amounts of diuron. The assay exhibited an excellent sensitivity and specificity based on absorbance profile showing the dynamic response range from 0.1-50 ng/mL for diuron with a detection limit of ~5 ng/mL. The new technique could be used for fast, high-throughput screening of pesticides in environmental diagnostics at a very low cost.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".