Polyacrylamide gel electrophoresis of semiconductor quantum dots and their bioconjugates: materials characterization and physical insights from spectrofluorimetric detection
Bibliographic record
Abstract
Colloidal semiconductor quantum dot (QD) nanocrystals have ideal fluorescence properties for bioanalysis and bioimaging, but these materials must be functionalized with an inorganic shell, organic ligand or polymer coating, and conjugated with biomolecules to be useful in such applications. Several different analytical techniques are used to characterize QDs and their multiple layers of functionalization. Here, we revisit poly(acrylamide) gel electrophoresis (PAGE), which has been scarcely used for the characterization of QDs and their bioconjugates in deference to the routine use of agarose gel electrophoresis. We implemented PAGE in a novel "stubby" capillary format with spectrofluorimetric detection, the combination of which enabled more rapid and more detailed characterization of QDs than was possible with both poly(acrylamide) and agarose slab gels. Correlations between the peak photoluminescence (PL) emission wavelength and electropherogram peaks, especially when combined with Ferguson analysis, provided new and significant insight into the key factors that determine the electrophoretic mobility of QDs, and helped to resolve heterogeneity and sub-populations in ensembles of QDs. The method was useful for characterization of the inorganic core/shell nanocrystals, their organic ligand and polymer coatings, and their final bioconjugates, the latter of which were in the form of peptide and protein conjugates. With further development and optimization, we anticipate that capillary PAGE with spectrofluorimetric detection will become a valuable addition to the toolbox of characterization techniques suitable for QDs, their bioconjugates, and other nanoparticle materials as well.
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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".