Eggshell Membrane as a Biomaterial for Bone Regeneration
Bibliographic record
Abstract
The physicochemical features of the avian eggshell membrane play an essential role in the process of calcium carbonate deposition during shell mineralization, giving rise to a porous mineralized tissue with remarkable mechanical properties and biological functions. The membrane could be useful by itself or as a bi-dimensional scaffold to build future bone-regenerative materials. This review focuses on the biological, physical, and mechanical properties of the eggshell membrane that could be useful for that purpose. Due to its low cost and wide availability as a waste byproduct of the egg processing industry, repurposing the eggshell membrane for bone bio-material manufacturing fulfills the principles of a circular economy. In addition, eggshell membrane particles have has the potential to be used as bio-ink for 3D printing of tailored implantable scaffolds. Herein, a literature review was conducted to ascertain the degree to which the properties of the eggshell membrane satisfy the requirements for the development of bone scaffolds. In principle, it is biocompatible and non-cytotoxic, and induces proliferation and differentiation of different cell types. Moreover, when implanted in animal models, it elicits a mild inflammatory response and displays characteristics of stability and biodegradability. Furthermore, the eggshell membrane possesses a mechanical viscoelastic behavior comparable to other collagen-based systems. Overall, the biological, physical, and mechanical features of the eggshell membrane, which can be further tuned and improved, make this natural polymer suitable as a basic component for developing new bone graft materials.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".