From Nutrition to Innovation: Biomedical Applications of Egg Components
Bibliographic record
Abstract
Valued for their nutritional content, eggs have recently gained attention as a versatile biomaterial owing to their biocompatibility, biodegradability, and unique structural and biochemical composition. This review highlights the biomedical potential of various egg components-eggshell, eggshell membrane, egg white, and egg yolk-and their applications in bone grafting, tissue engineering, wound healing, drug delivery, and biosensors. Eggshells serve as a natural, calcium-rich source for bone tissue engineering and regenerative medicine. The eggshell membrane, with its antimicrobial and structural properties, offers promise as a wound healing scaffold. Egg white, known for its gelation and film-forming capabilities, is utilized in hydrogel-based systems for drug delivery and biosensing. Egg yolk, rich in lipids and immunoglobulin Y (IgY) antibodies, is being explored for diagnostic and therapeutic applications. This review critically examines the advantages and limitations of each egg-derived component and outlines current research gaps, offering insights into future directions for the development of egg-based biomaterials in biomedical engineering.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".