Process and formulation variables in the preparation of injectable and biodegradable magnetic microspheres
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The aim of this study was to prepare biodegradable sustained release magnetite microspheres sized between 1 to 2 microm. The microspheres with or without magnetic materials were prepared by a W/O/W double emulsion solvent evaporation technique using poly(lactide-co-glycolide) (PLGA) as the biodegradable matrix forming polymer. Effects of manufacturing and formulation variables on particle size were investigated with non-magnetic microspheres. Microsphere size could be controlled by modification of homogenization speed, PLGA concentration in the oil phase, oil phase volume, solvent composition, and polyvinyl alcohol (PVA) concentration in the outer water phase. Most influential were the agitation velocity and all parameters that influence the kinematic viscosity of oil and outer water phase, specifically the type and concentration of the oil phase. The magnetic component yielding homogeneous magnetic microspheres consisted of magnetite nanoparticles of 8 nm diameter stabilized with a polyethylene glycole/polyacrylic acid (PEG/PAA) coating and a saturation magnetization of 47.8 emu/g. Non-magnetic and magnetic microspheres had very similar size, morphology, and size distribution, as shown by scanning electron microscopy. The optimized conditions yielded microspheres with 13.7 weight% of magnetite and an average diameter of 1.37 microm. Such biodegradable magnetic microspheres seem appropriate for vascular administration followed by magnetic drug targeting.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it