Biotinylated Glyco-Functionalized Quantum Dots: Synthesis, Characterization, and Cytotoxicity Studies
Bibliographic record
Abstract
Quantum dots (QDs) containing surface carboxylic groups have been successfully modified using biotinylated glycopolymer and carbohydrate/biotin reagents via EDC coupling. The biotinylated glycopolymer was synthesized in controlled dimension via the reversible addition-fragmentation chain transfer (RAFT) polymerization of the three monomers containing biotin, sugar, and amine groups as pendent groups, respectively. The modified QDs were analyzed by dynamic light scattering and fluorescence spectrophotometry, and the data revealed no change in the physical properties of QDs after surface modification. Furthermore, the surface modified QDs showed excellent water solubility and colloidal stability. Subsequently, the availability of the biotin ligand on the surface of functionalized QDs was quantified using 4-hydroxyazobenzene 2-carboxylic acid (HABA)/avidin binding assay. Cell viability studies revealed that the cytotoxicity of QDs after surface functionalization is improved and that the biotinylated glycopolymer modified QDs showed an enhancement in biocompatibility as compared to that of the original QDs. The biotinylated glyco-functionalized quantum dots may act as new suitable fluorescent probes in biomedical applications.
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) | 0.000 | 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".