Entirely Biomass-Derived Hydrogel Composites for Possible Applications in Drug Delivery
Bibliographic record
Abstract
Abstract Entirely biomass-based chitosan-alginate hydrogel composites were prepared using mussel-derived calcite. Composite hydrogel beads were prepared with 0.0, 1.0, and 2.5 wt % calcite and were characterized using IR spectroscopy, scanning electron microscopy (SEM), and thermogravimetric analysis (TGA). Diameters of beads were measured to ensure uniform preparation. The swelling behavior of beads was tested in 0.1 M HCl, 0.1 M potassium phosphate buffer, and deionized water at 37 °C. Beads containing calcite were found to have significantly less swelling ability in 0.1 M HCl and deionized water, but in 0.1 M potassium phosphate buffer, no change in swelling ability was observed for beads containing zero calcite compared with those containing calcite. Encapsulation efficiency (EE) measurements of methylene blue, as a model drug, showed that 0.0 wt % calcite beads had an EE of 80.8% and those containing calcite had lower EE: 60.7% (1.0 wt % calcite) and 71.6% (2.5 wt % calcite). Methylene blue release in a surrogate gastric environment (0.1 M HCl followed by 0.1 K buffer) showed that 0.0 wt % calcite beads had the least controlled release, whereas those containing calcite showed controlled release. Drug release results were found to be significant through a one-way ANOVA test (p < 0.05). TGA data show that SC levels in beads after placement in a surrogate gastric fluid (0.1 M HCl) are significantly reduced due to the reaction between calcite and HCl.
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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".