Aqueous mounting media increasing tissue translucence improve image quality in Structured Illumination Microscopy of thick biological specimen
Bibliographic record
Abstract
Structured Illumination Microscopy (SIM) is a super-resolution microscopy method that has significantly advanced studies of cellular structures. It relies on projection of illumination patterns onto a fluorescently labelled biological sample. The information derived from the sample is then shifted to a detectable band, and in the process of image calculation in Fourier space the resolution is doubled. Refractive index homogeneity along the optical path is crucial to maintain a highly modulated illumination pattern necessary for high-quality SIM. This applies in particular to thick samples consisting of large cells and tissues. Surprisingly, sample mounting media for SIM have not undergone a significant evolution for almost a decade. Through identification and systematic evaluation of a number of non-hazardous, water-soluble chemical components of mounting media, we demonstrate an unprecedented improvement in SIM-image quality. Mounting solutions presented in this research are capable of reducing abundant light scattering which constitutes the limiting factor in 3D-SIM imaging of large Hodgkin's lymphoma and embryonic stem cells as well as 10 µm tissue sections. Moreover, we demonstrate usefulness of some of the media in single molecule localisation microscopy. The results presented here are of importance for standardisation of 3D-SIM data acquisition pipelines for an expanding community of users.
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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 | 0.002 | 0.001 |
| 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 | 0.001 |
| 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".