Sensitive double antibody sandwich ELISA for the quantification of phosvitin
Bibliographic record
Abstract
An effective double antibody sandwich ELISA (DAS-ELISA) method based on monoclonal (mAb) and chicken egg yolk IgY antibodies was developed to determine phosvitin (PV) content in therapeutic and functional products. Leghorn laying hens were immunized with purified PV to produce anti-PV IgY antibody in the egg yolk. High anti-PV IgY titer obtained from the egg yolks collected during 4–10 weeks of the immunization period contained approximately 6.2% of specific anti-PV IgY in total IgY. The PV detection range of the DAS-ELISA and biotinylated DAS-ELISA was 16.8–90 and 7.5–40 ng/mL, respectively. However, biotinylated DAS-ELISA was the better method for PV quantification in terms of accuracy and sensitivity. This highly efficient PV detection method may recuperate the performance of the existing protein assay methods as well as facilitate future research on PV bioactivities and applications.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".