Bibliographic record
Abstract
Two-photon excitation fluorescence cross-correlation spectroscopy (TPE-XCS) is a very suitable method for studying interactions of two distinctly labeled fluorescent molecules. As such, it lends itself nicely to the study of ligand-receptor interactions. By labeling the ligand with one color of fluorescent dye and the receptor with another, it is possible to directly monitor ligand binding rather than inferring binding by monitoring downstream effects. One challenge of the TPE-XCS approach is that of separating the signal due to the receptor from that of the ligand. Using standard organic fluorescent labels there is almost inevitably spectral cross talk between the detection channels, which must be accounted for in TPE-XCS data analysis. However, using quantum dots as labels for both ligand and receptor this limitation can be alleviated, because of the dot's narrower emission spectra. Using solely quantum dots as fluorescent labels is a novel approach to TPE-XCS, which may be generalizable to many pairs of interacting biomolecules after the proof of principle and the assessment of limitations presented here. Moreover, it is essential that relevant pharmacological parameters such as the equilibrium dissociation constant, K(d), can be easily extracted from the XCS data with minimal processing. Herein, we present a modified expression for fractional occupancy based on the auto- and cross-correlation decays obtained from a well-defined ligand-receptor system. Nanocrystalline semiconductor quantum dots functionalized with biotin (lambda(em) = 605 nm) and streptavidin (lambda(em) = 525 nm) were used for which an average K(d) value of 0.30 +/- 0.04 x 10(-9) M was obtained (cf. native system approximately 10(-15)). Additionally, the off-rate coefficient (k(off)) for dissociation of the two quantum dots was determined as 5 x 10(-5) s(-1). This off-rate is slightly larger than for native biotin-streptavidin (5 x 10(-6) s(-1)); the bulky nature of the quantum dots and restricted motion/orientation of functionalized dots in solution can account for differences in the streptavidin-biotin mediated dot-dot binding compared with those for native streptavidin-biotin.
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 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 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".