Poly(ethylene-co-vinylalcohol)/Poly(δ-valerolactone)/Aspirin Composite: Model for a New Drug-Carrier System
Bibliographic record
Abstract
The release dynamics of aspirin(ASP), used as a drug model, from the poly(ethylene-co-vinyl alcohol)/poly(δ-valerolactone) (PE-co-VAL/Pδ-VL) hydrogel blend was controlled by varying the blend’s degree of swelling through a gradual loading of Pδ-VL (hydrophobic polymer) in this copolymer matrix. To achieve this goal, a series of PE-co-VAL/Pδ-VL blends with different ratios was prepared through the solvent casting method, and the miscibility of this polymer blend was evaluated by using Fourier transform infrared spectroscopy, differential scanning calorimetry, X-ray diffraction, and scanning electronic microscopy methods. The tests of cell adhesion and growth on the PE-co-VAL/Pδ-VL specimens were performed using the 3-(4,5-demethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) method and the results obtained were the best performance in terms of cell viability, cell adhesion, and growth of the PE-co-VAL/Pδ-VL50 material. The dynamic mechanical properties of the prepared material were also examined by dynamic mechanical analysis; the results obtained showed a material having intermediary mechanical properties between those of the two components. On the basis of these characterizations, the blend showing the best performance, such as the PE-co-VAL/Pδ-VL50 system, was chosen as a carrier to study the in vitro control of the release dynamics of ASP from the ASP/PE-co-VAL/Pδ-VL drug-carrier system when administered orally, in which the influences of the ASP content and the degree of swelling of the PE-co-VAL/Pδ-VL blend were investigated. Based on the data obtained and the gastrointestinal transit time reported by Beltzer et al., it was possible to estimate the distribution of the in vitro cumulative ASP released in different digestive system organs regardless of the actions of any enzymes and microorganisms and select the best-performing drug-carrier system.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".