Evidence map›Paper›PMID 41501068›Full record

ArticleNature communications2026

Smart hybrid microscopy for cell-friendly detection of rare events.

Willi L Stepp, Giorgio Tortarolo, Juan C Landoni, Emine Berna Durmus, Santiago N Rodriguez Alvarez, Kyle M Douglass, Martin Weigert, Suliana Manley

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Willi L SteppInstitute of Physics, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland. willi@stepp.one.ORCID http://orcid.org/0000-0001-9818-0377
Giorgio TortaroloInstitute of Physics, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland.ORCID http://orcid.org/0000-0002-1182-2478
Juan C LandoniInstitute of Physics, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland.ORCID http://orcid.org/0000-0002-0318-6707
Emine Berna DurmusInstitute of Physics, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland.ORCID http://orcid.org/0009-0005-3034-4044
Santiago N Rodriguez AlvarezInstitute of Physics, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland.
Kyle M DouglassInstitute of Physics, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland.ORCID http://orcid.org/0000-0003-4694-0922
Martin WeigertCenter for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI), Dresden, Germany.ORCID http://orcid.org/0000-0002-7780-9057
Suliana ManleyInstitute of Physics, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland. suliana.manley@epfl.ch.ORCID http://orcid.org/0000-0002-4755-4778

Funding

Carl-Zeiss-Stiftung (Carl Zeiss Foundation) Zeiss-EPFL IDEASEC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council) 819823 PikoHuman Frontier Science Program (HFSP) RGP0038/2021Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation) 10268
6 · The paper itself

Abstract

Fluorescence microscopy offers unparalleled access to the spatial organization and dynamics of biological events in living samples, yet capturing rare processes over extended durations remains challenging due to trade-offs between exposure to excitation light and sample health. Here, we introduce hybrid-EDA, an event-driven acquisition (EDA) framework that combines the gentleness and contextual richness of phase-contrast with the functional specificity of fluorescence. We develop surveillance for events of interest in label-free microscopy using dynamics-informed neural networks that trigger smart fluorescence acquisitions upon detection. This allows us to dramatically reduce phototoxic damage while obtaining specific and functional information from fluorescence when beneficial. We demonstrate how hybrid-EDA enables improved imaging acquisitions of organelle contacts and mitochondrial divisions. We envision that hybrid-EDA will enable insights into a range of dynamic and rare biological processes, providing a powerful and general strategy for cell-friendly imaging.

Indexed as

Microscopy, FluorescenceMicroscopy, Phase-ContrastAnimalsHumansMitochondriaNeural Networks, Computer

Identifiers

PMID41501068
PMCPMC12881448

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.