Drug Delivery Platforms for Cardiovascular Applications Based on Alginate-Based Hollow Structures
Bibliographic record
Abstract
Over the past decade, electrospinning, a broadly used technology for electrostatic fibre formation which utilizes electrical forces to produce polymer fibres with diameters ranging from several nanometres to several micrometres using natural/synthetic polymer solutions has seen a tremendous increase in both research and commercial applications.This process offers unique capabilities for producing novel natural nanofibers and fabrics with controllable pore structure using different polymers [1][2][3][4][5].Co-axial processing of alginate gels offers an alternative procedure to synthesized hollow fibres and nanobeads.The challenge of the procedure is to adequately choose the needles diameter, the flows of through the two needles, the concentrations of the solutions, etc.Alginate/natural agent hollow fibres were successfully synthesized by coaxial electrospinning method using 3% alginate solution, 1-5 % natural agent and CaCl2 solutions (1 -100g/L) as reticulation agent.The rapid consolidation of the alginate hollow tubes is assured by passing a CaCl2 solution through the inner needle while these alginate structures are directly poured into the CaCl2 solution when hollow fibres with controlled characteristics were obtained.Natural agents such as pure polyphenols, antibiotics, analgesic, were loaded inside the wall of the alginate hallow fibres.The obtained hollow fibres were characterized by FTIR, scanning electron microscopy (SEM), tubes shrinking and water uptake.These structures will be evaluated from the point of view of loading and delivery of biological active agents such as natural or synthetic agents: antioxidants, anti-inflammatory or antimicrobial agents.The as obtained hollow fibres were also evaluated from the point of view of biocompatibility against endothelial cells but also according to their potential antimicrobial, anti-inflammatory activity.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".