Measurement of cell surface protein dynamics by two-photon image correlation spectroscopy and image cross-correlation spectroscopy
Bibliographic record
Abstract
Advances in laser-scanning microscopy and the advent of confocal microscopy permitted the development of image correlation spectroscopy (ICS). ICS is an imaging analog of fluorescence correlation spectroscopy (FCS) optimized for measuring the aggregation state of fluorescently labeled macromolecules on the surface of biological cells. The ICS method entails spatial autocorrelation analysis of fluorescence fluctuations within an image sampled from an area of the sample as well as temporal autocorrelation analysis of fluorescence fluctuations through a time series of images. Together, the spatial/temporal autocorrelation analysis enables measurement of fluorophore concentration, aggregation state and transport properties. ICS was first implemented on a confocal laser-scanning microscope (CLSM) using single photon excitation. More recently we have extended the method for two-photon ICS as well as image cross-correlation spectroscopy (ICCS). ICCS allows measurement of co-localization of non-identical molecules labeled with fluorophores of different emission wavelengths. We present a variety of applications of the ICS and ICCS methods in cellular systems. We will discuss the measurement of the transport and clustering properties of membrane receptors by single photon ICS and two-photon ICCS. As well, we will describe how spatial ICS may be used to quantify the distribution of fluorescently labeled dendritic spines in neurons.
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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".