Copolymer Involving 2-Hydroxyethyl Methacrylate and 2-Chloroquinyl Methacrylate: Synthesis, Characterization and In Vitro 2-Hydroxychloroquine Delivery Application
Bibliographic record
Abstract
The Poly(2-chloroquinyl methacrylate-co-2-hydroxyethyl methacrylate) (CQMA-co-HEMA) drug carrier system was prepared with different compositions through a free-radical copolymerization route involving 2-chloroquinyl methacrylate (CQMA) and 2-hydroxyethyl methacrylate) (HEMA) using azobisisobutyronitrile as the initiator. 2-Chloroquinyl methacrylate monomer (CQMA) was synthesized from 2-hydroxychloroquine (HCQ) and methacryloyl chloride by an esterification reaction using triethylenetetramine as the catalyst. The structure of the CQMA and CQMA-co-HEMA copolymers was confirmed by a CHN elementary analysis, Fourier transform infra-red (FTIR) and nuclear magnetic resonance (NMR) analysis. The absence of residual aggregates of HCQ or HCQMA particles in the copolymers prepared was confirmed by a differential scanning calorimeter (DSC) and XR-diffraction (XRD) analyses. The gingival epithelial cancer cell line (Ca9-22) toxicity examined by a lactate dehydrogenase (LDH) assay revealed that the grafting of HCQ onto PHEMA slightly affected (4.2–9.5%) the viability of the polymer carrier. The cell adhesion and growth on the CQMA-co-HEMA drug carrier specimens carried out by the (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) (MTT) assay revealed the best performance with the specimen containing 3.96 wt% HCQ. The diffusion of HCQ through the polymer matrix obeyed the Fickian model. The solubility of HCQ in different media was improved, in which more than 5.22 times of the solubility of HCQ powder in water was obtained. According to Belzer, the in vitro HCQ dynamic release revealed the best performance with the drug carrier system containing 4.70 wt% CQMA.
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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".