Semiconductor Quantum Dots Surface Modification for Potential Cancer Diagnostic and Therapeutic Applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Semiconductor Quantum dots (QDs) have generated extensive interest for biological and clinical applications. These applications arise from their unique properties, such as high brightness, long‐term stability, simultaneous detection of multiple signals, tunable emission spectra. However, high‐quality QDs, whether single or core‐shell QDs, are most commonly synthesized in organic solution and surface‐stabilized with hydrophobic organic ligands and thus lack intrinsic aqueous solubility. For biological applications, very often it is necessary to make the QDs dispersible in water and therefore to modify the QD surfaces with various bifunctional surface ligands or caps to promote solubility in aqueous media. Well‐defined methods have been developed for QD surface modification to impart biocompatibility to these systems. In this review, we summarize the recent progress and strategies of QDs surface modification for potential cancer diagnostic and therapeutic applications. In addition, the question that arose from QD surface modification, such as impact of size increase of QD bioconjugates after surface‐functionalization or surface modification on photophysical properties of QDs, are also discussed.
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.
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 | 0.001 | 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 it