A novel type of quantum dot–transferrin conjugate using DNA hybridization mimics intracellular recycling of endogenous transferrin
Bibliographic record
Abstract
Colloidal nanoparticles such as Quantum Dots (QDs) are promising alternatives to organic fluorophores, especially for long duration bioimaging. For specific targeting applications, QDs frequently require functionalization with selected proteins. In this regard, conjugation of proteins to QDs such that the nanobioconjugates retain the endogenous behavior of the coupled protein remains challenging. We have developed a novel method to conjugate a protein, transferrin (Tf), to QDs using DNA hybridization. These conjugates are characterized biochemically, and the trafficking properties in live cells are investigated. Although the internalization kinetics into the cells is much reduced compared to Tf labelled with organic dye, we could show that DNA hybridization-based QD-Tf conjugates are the first for which recycling from endosomes to the plasma membrane can be observed. This recycling occurs with kinetics that is similar to dye labelled Tf. We could image and follow the trajectories of recycling of individual vesicles for several tens of minutes. The conjugation of QDs to proteins mediated by DNA hybridization yields a new generation of ultra-bright and photostable probes that preserves the intracellular properties of the dye labelled protein better than previously reported QD conjugates using other surface chemistries for direct coupling.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".