Using confocal imaging to measure changes in intracellular ions
Bibliographic record
Abstract
Abstract Until the development of three-dimensional (3D) imaging, many questions were raised concerning ion traffic and localization, but these were never fully answered because of the absence of a technique enabling the visualization of dye distribution at the 3D level. The recent development and use of confocal microscopy, coupled to high performance hardware and software systems, has provided scientists with the capability of overcoming some of the limitations of standard microscopic imaging measurements. Until recently, access to confocal microscopy was fairly limited. Today, the majority of laboratories dealing with molecular and cell biology, pharmacology, biophysics, biochemistry, etc., are equipped with this powerful scientific tool. This increase in the need for confocal microscopy has been highly supported by a growing industry for developing new fluorescent probes. However, in order to optimize this technique, scientists need to be familiar with the basic approaches and limitations of confocal microscopy. In this chapter, we will discuss sample preparation, labelling of structures and functional probes, the settings of parameters, development of specific ligand probes, as well as protocols for measurements and limitations of the technique. For further information, the reader should refer to recent key references (1-4).
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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) | 0.008 | 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".