Extraction and quantification by ELISA of eggshell organic matrix proteins (ovocleidin-17, ovalbumin, ovotransferrin) in shell from young and old hens
Bibliographic record
Abstract
The eggshell matrix is mainly composed of proteins that are thought to influence shell formation and calcification and, thus, modify the resulting properties of the shell. We investigated the potential of some of these proteins as biomarkers of eggshell quality by developing a competitive indirect ELISA for quantifying ovotransferrin, ovalbumin, and ovocleidin-17 in eggshell extract. Eggshell fragments were demineralized in acetic acid (20%) and freeze-dried. The micro-extraction yield was markedly increased (>50%) when Tween 20 was added to the subsequent extraction and dialysis milieus. Microplates were coated with ovotransferrin and ovalbumin in a 0.1M carbonate-bicarbonate buffer, but ovocleidin-17 was fixed with acetone (-20 C, 20 min). Optimal dilutions of the monoclonal (ovotransferrin) and polyclonal (ovalbumin and ovocleidin-17) antibodies were 1/3,000, 1/25,000 and 1/4,000, respectively. The inhibition curves were optimized by preincubating the antibodies and proteins overnight. The intraassay coefficient (<5%), parallelism of the standards and samples curves, and recovery (101%) were satisfactory for ovotransferrin. Measurements of ovalbumin were less precise because of higher interassay variation and differences between the slopes of standard and sample inhibition curves. Ovocleidin-17 assays showed similar slopes for standard and eggshell extracts. Although the total protein in soluble matrix extracts was not affected by age, the concentrations of these proteins were higher in eggshell extracts from older hens compared with those from young hens: 1.98x for ovotransferrin, 1.86x for ovalbumin, and 1.58x for ovocleidin-17. The quantification of specific eggshell matrix proteins in shell of differing quality is, therefore, a promising tool for analyzing the origin of eggshell faults and may provide useful information for breeding programs.
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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) | 0.000 | 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) | 0.001 | 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 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".