Adsorption and Hybridization of Oligonucleotides on Mercaptoacetic Acid-Capped CdSe/ZnS Quantum Dots and Quantum Dot−Oligonucleotide Conjugates
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
Interest in the unique optical properties of quantum dots (QDs) has resulted in the development QD-bioconjugates for imaging and diagnostics. Although these applications are numerous, considerably less is known about the interactions between QDs and biomolecules. In this work, we describe hydrogen-bonding interactions between oligonucleotides and CdSe/ZnS quantum dots capped with mercaptoacetic acid ligands. The strength of the interactions can be modulated by changes in the pH and ionic strength, the addition of formamide, and differences between ssDNA and dsDNA. Fluorescence resonance energy transfer experiments have shown that conjugated oligonucleotides adopt a conformation that lies across the surface of the QD. The hydrogen-bonding interactions also affect the kinetics of hybridization with QD-DNA conjugates and the thermal stability of QD-conjugated dsDNA. The former is analogous to conventional solid-phase hybridization, where stronger oligonucleotide adsorption leads to faster kinetics. With respect to the latter, interactions with the QD surface can sharpen the melt transition and alter the melt temperature of dsDNA. These effects are largely absent when adsorptive interactions are minimized.
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 | 0.000 | 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 it