Electrospun Starch Nanofibers as a Delivery Carrier for Carvacrol as Anti‐Glioma Agent
Bibliographic record
Abstract
Abstract Phenolic compounds are prone to degradation from external deleterious conditions. Thus, a carrier for its delivery can be useful in protecting them and ensuring their optimal release profile. The objective of this study is to produce starch nanofibers as delivery carriers for carvacrol and to evaluate its in‐vitro digestion simulation and anti‐glioma activity. Nanofibers are produced by electrospinning of a starch solution where carvacrol is incorporated in various concentrations (20, 30, and 40% v/w; dry basis). The nanofibers are evaluated by in‐vitro digestion simulation and anti‐tumoral activity in C6 rat glioma cells and cytotoxicity in astrocytes. By measuring the residual amount of carvacrol after digestion, the starch nanofibers are shown to be a promising vehicle for the delivery of carvacrol by resisting in‐vitro digestion. The carvacrol‐loaded starch nanofibers result in up to 50% reduction in tumoral cells (C6 rat glioma cells). Free carvacrol elicits cytotoxicity in astrocytes after 72 h of treatment; interestingly the carvacrol‐loaded starch nanofibers are not toxic to this cell. In view of the demand for natural drugs in pharmaceutical applications, the nanofibers may be promising for cancer complementary treatment.
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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) | 0.000 | 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 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".