Films, Gels and Electrospun Fibers from Serum Albumin Globular Protein for Medical Device Coating, Biomolecule Delivery and Regenerative Engineering
Bibliographic record
Abstract
Albumin is a natural biomaterial that is abundantly available in blood and body fluids. It is clinically used as a plasma expander, thereby increasing the plasma thiol concentration due to its cysteine residues. Albumin is a regulator of intervascular oncotic pressure, serves as an anti-inflammatory modulator, and it has a buffering role due to its histidine imidazole residues. Because of its unique biological and physical properties, albumin has also emerged as a suitable biomaterial for coating implantable devices, for cell and drug delivery, and as a scaffold for tissue engineering and regenerative medicine. As a biomaterial, albumin can be used as surface-modifying film or processed either as cross-linked protein gels or as electrospun fibers. Herein we have discussed how albumin protein can be utilized in regenerative medicine as a hydrogel and as a fibrous mat for a diverse role in successfully delivering drugs, genes, and cells to targeted tissues and organs. The review of prior studies indicated that albumin is a tunable biomaterial from which different types of scaffolds with mechanical properties adjustable for various biomedical applications can be fabricated. Based on the progress made to date, we concluded that albumin-based device coatings, delivery of drugs, genes, and cells are promising strategies in regenerative and personalized medicine.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".