CdSe Quantum Dots for Two-Photon Fluorescence Thermal Imaging
Bibliographic record
Abstract
The technological development of quantum dots has ushered in a new era in fluorescence bioimaging, which was propelled with the advent of novel multiphoton fluorescence microscopes. Here, the potential use of CdSe quantum dots has been evaluated as fluorescent nanothermometers for two-photon fluorescence microscopy. In addition to the enhancement in spatial resolution inherent to any multiphoton excitation processes, two-photon (near-infrared) excitation leads to a temperature sensitivity of the emission intensity much higher than that achieved under one-photon (visible) excitation. The peak emission wavelength is also temperature sensitive, providing an additional approach for thermal imaging, which is particularly interesting for systems where nanoparticles are not homogeneously dispersed. On the basis of these superior thermal sensitivity properties of the two-photon excited fluorescence, we have demonstrated the ability of CdSe quantum dots to image a temperature gradient artificially created in a biocompatible fluid (phosphate-buffered saline) and also their ability to measure an intracellular temperature increase externally induced in a single living cell.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".