Preparation of glutinous rice starch/polyvinyl alcohol copolymer electrospun fibers for using as a drug delivery carrier
Bibliographic record
Abstract
Glutinous rice starch (GRS) is commonly produced in the Northeast of Thailand. GRS is a biopolymer which is widely used in the food industry but not yet commonly applied within the pharmaceutical industry as an alternative resource. GRS exhibits a branch chain structure which is not feasible to fabricate as nanofiber. Therefore, combining GRS with polyvinyl alcohol (PVA) in hybrid form can be a potential platform to produce GRS-PVA nanofibers. Smooth nanofibers of 2% (w/v) GRS combined with 8% (w/v) PVA were fabricated by an electrospinning process. A scanning electron microscope (SEM) revealed an average diameter size of the GRS-PVA nanofibers equal to 191 ± 25 nm. A highly water soluble model drug, Chlorpheniramine maleate (CPM), was incorporated into the GRS-PVA electrospun fibers to prove a drug delivery carrier concept and drug release control of the nanofibers. The GRS-PVA nanofibers exhibited a biphasic CPM release in which approximately 60% of the drug immediately released in 10 min, and it reached 90% drug release in 120 min. This study demonstrated a potential application of GRS combining with PVA as an oral drug delivery carrier. Therefore, it can be a promised step that expands the application GRS in pharmaceuticals and related areas.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".