iTRAQ‐Based Quantitative Proteomic Analysis of Duck Eggshell During Biomineralization
Bibliographic record
Abstract
The avian egg is a valuable model for the calcitic biomineralization process as it is the fastest calcification process occurring in nature and is a clear example of biomineralization. In this study, iTRAQ MS/MS is used to detect and study for the first time: 1) the overall duck eggshell proteome; 2) regional differences in the proteome between the inner and outer portions of the duck eggshell. The new reference protein datasets allow us to identify 179 more eggshell proteins than solely using the current release of Ensembl duck annotations. In total, 484 proteins are identified in the entire duck eggshell proteome. Twenty-eight novel proteins of unknown function that are involved in eggshell formation are also identified. Among the identified eggshell proteins, 54 proteins show differential abundances between the inner, partially mineralized eggshell (obtained 16 h after ovulation) compared to the overall complete eggshell (normally expulsed eggshell). At least 64 of the abundant matrix proteins are common to eggshell of 4 different domesticated bird species (chicken, duck, quail, turkey) and zebra finch. This study provides a new resource for avian eggshell proteomics, and augments the inventory of eggshell matrix proteins that will lead to a deeper understanding of calcitic biomineralization.
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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 | 0.000 | 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 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".