A novel method to chemically bind thiazolidine-2,4-dione through cross-linked chitosan nanoparticles using malanodialdehyde as a cross-linker
Bibliographic record
Abstract
Chitosan is a biodegradable natural polymer with great potential for pharmaceutical applications because of its biocompatibility, high charge density, nontoxicity and mucoadhesion. It has been shown that it not only improves the dissolution of poorly soluble drugs but also exerts a significant effect on fat metabolism in the body. Gel formation can be obtained by interactions of chitosans with low molecular counterions such as polyphosphates, sulfates, and cross-linkers. This gelling property of chitosan allows a wide range of applications such as the coating of pharmaceuticals and food products, gel entrapment of biochemicals, plant embryos, whole cells, microorganisms, and algae. This manuscript is an insight into the exploitation of its properties for microencapsulating drugs. Herein, we report a novel method to chemically bind thiazolidine-2,4-dione through cross-linked chitosan nanoparticles using malanodialdehyde as a new cross-linker and well characterized by FT-IR, NMR, TGA, DSC, powder X-ray diffraction, TEM, and cyclic voltametry.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".