Cationic Galactose-Conjugated Copolymers for Epidermal Growth Factor (EGFR) Knockdown in Cervical Adenocarcinoma
Bibliographic record
Abstract
Glycopolymers of statistical and block configurations were synthesized from 2-lactobionamidoethyl methacrylamide (LAEMA) and 2-aminoethyl methacrylamide hydrochloride (AEMA) by the reversible addition-fragmentation chain transfer (RAFT) polymerization. These cationic glycopolymers were found to form very stable polyplexes with EGFR siRNA as determined by dynamic light scattering and agarose gel electrophoresis. The polyplexes revealed to be very stable even in the presence of serum proteins. Transfection studies of the glycopolymer-EGFR siRNA polyplexes were achieved in HeLa cells to determine the EGFR knockdown efficiency, cellular uptake and cytotoxicity. In this study, the block copolymer with the shortest AEMA segment was the most effective in EGFR gene silencing, however this block copolymer revealed to be slightly more toxic as compared to the statistical copolymers studied at higher w/w ratios. In addition, gene silencing of up to 80-85% was achieved with this low-molecular-weight block copolymer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".