A simple, inexpensive and multi-scale 3-D fluorescent test sample for optical sectioning microscopies
Bibliographic record
Abstract
ABSTRACT Fluorescence standards allow for quality control and for the comparison of data sets across instruments and laboratories in applications of quantitative fluorescence. For example, users of microscopy core facilities expect a homogenous and time-invariant illumination and a uniform detection sensitivity, which are prerequisites for quantitative imaging analysis, particle tracking or fluorometric pH or Ca 2+ -concentration measurements. Similarly, confirming the three-dimensional (3-D) resolution of optical sectioning micro-scopes prior to volumetric reconstructions calls for a regular calibration with a standardised point source. Typically, the test samples required for such calibration measurements are different ones, and they depend much on the very microscope technique used. Also, the ever-increasing choice among these techniques increases the demand for comparison and metrology across instruments. Here, we advocate and demonstrate the multiple uses of a surprisingly versatile and simple 3-D test sample that can complement existing and much more expensive calibration samples: simple commercial tissue paper labelled with a fluorescent highlighter pen. We provide relevant sample characteristics and show examples ranging from the sub-µm to cm scale, acquired on epifluorescence, confocal, image scanning, two-photon (2P) and light-sheet microscopes. Graphical abstract Pyranine-labeled tissue paper, imaged upon 405-nm epifluorescence excitation through a 455LP LP dichroic and 465LP emission filter. Objective ×20/NA0.25. Overlaid are the normalised absorbance (dashed) and emission spectra (through line), respectively. In the present work we show that this “primitive” and inexpensive three-dimensional (3-D) test sample is a surprisingly versatile and powerful tool for quality assessment, comparison across microscopes as well as routine metrology for optical sectioning techniques, both for research labs and imaging core facilities. Research highlights - highlighter-pen marked tissue paper is a surprisingly powerful and versatile test sample for 3-D fluorescence microscopies - standard tissue paper presents features ranging from 400 nm to centimetres - our sample can simultaneously be used for testing intensity, field homogeneity, resolution, optical sectioning and image contrast - it is easy to prepare, versatile, photostable and inexpensive
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 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".