pH-responsive polymer-based biomacromolecule nanosponges as biodegradable carriers for DOX delivery
Bibliographic record
Abstract
Cellulose is the most abundant renewable biomaterial on earth and beta-cyclodextrin (BCD) is among the most commonly used biocompatible drug encapsulation agents. Combining these bio-organic materials is a very powerful approach to greatly enhance the bioavailability of many drugs. These systems also allow for optimal selective drug release profiles, high biocompatibility, as well as “green nanomedicine” approaches that are eco-friendly in their synthesis and have minimal ecological toxicity. herein, we designed a new type of green and biopolymer-based nanosponge drug carriers which is polymerized by crosslinking beta-cyclodextrin ethylene diamine (βCD-EDA) with bifunctional hairy nanocellulose (BHNC). BHNC contains, besides aldehyde groups, carboxyl groups which can react with amino groups in βCD-EDA. Firstly, the crosslinker βCD-EDA was obtained through a simple nucleophilic substitution reaction between beta-cyclodextrin carbonyl imidazole (βCD-CI) and ethylene diamine (EDA). Secondly, BHNC was functionalized with the crosslinker βCD-EDA through a facile nucleophilic substitution crosslinking reaction of the BHNC activated carboxyl groups by the amines of βCD-EDA. We refer to the polymerized highly crosslinked BHNC-βCD-EDA network as BBE. Various ratios of βCD-EDA and BHNC were polymerized with the help of DMTMM as an activator, which resulted in different morphological shapes of BBE, and thus in different release profiles and pH-responsiveness. Unlike other polymer-based βCDs and nanosponges, these new types of crosslinked polymer were prepared in a green and safe solvent (water) and with very short reaction times and at low temperatures. Finally, the BBE polymers were tested as biocompatible nanocarriers for controllable doxorubicin (DOX) delivery. These hyper crosslinked polymers show a high capacity for loading DOX with extended drug release. Furthermore, breast cancer cell cultures show lower cell viability when DOX was loaded in various BBEs than control samples or DOX alone, indicating that our DOX-BBE drug delivery systems are better anticancer agents than DOX alone.
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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".