Review of expansion microscopy combined with advanced imaging modalities
Bibliographic record
Abstract
Expansion microscopy (ExM) is a powerful high-resolution imaging technique that enhances the spatial resolution of conventional light microscopy by physically enlarging biological specimens by embedding and cross-linking them in a swellable polymer network. This review explores the combination of ExM with commonly used advanced fluorescence imaging modalities, including light sheet fluorescence microscopy (LSFM), stimulated emission depletion (STED), structured illumination microscopy (SIM), single-molecule localisation microscopy (SMLM), and computational super-resolution radial fluctuations (SRRF) to push the boundaries of achievable resolution in biological imaging. By integrating ExM with these optical and analytical approaches, researchers can visualise subcellular structures and molecular complexes with unprecedented clarity, enabling the study of intricate biological processes that are otherwise inaccessible with conventional light microscopy methods. The review covers the theoretical resolutions attainable with each combined technique, example biological questions they can address, and key considerations for optimising their use. Together, these advancements offer novel insights into nanoscale cellular and subcellular structures, opening new avenues for exploration in fields such as neuroscience, cancer research, and developmental biology.
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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".