Nico Schramma

@nicoschramma.bsky.social

PostDoc medicalbiochemistry.nl (Amsterdam Medical Center van Buul Lab) Coordinator vascularimmunology.nl PhD Fluidlab.nl Biophysics of Endothelium & Immune cells, Chloroplasts, Bioluminescence, Active Glass tinyurl.com/gscholar-schra nicoschra.github.io

A week ago I thought about how to bridge different microscope experiments by using nuclei positions for registration. Then this came out the day later! The BioImageAnalysis community is truly the best :) Thanks for putting out so many great tools to advance research 😊😊😊

Guillaume Jacquemet@guijacquemet.bsky.social · 3mo ago

Delighted to share our latest preprint "NucleiSky enables cross-scale multimodal registration of microscopy data using nuclei constellations" www.biorxiv.org/content/10.6... Code and App: github.com/CellMigratio...

Global topsoil contains ~110 quadrillion km of fungal threads, roughly one billion times the distance from the Earth to the Sun. A new study in @science.org maps this hidden arbuscular mycorrhizal infrastructure for the first time. Explore the Mycorrhizal Infrastructure Map: buff.ly/PISOj8k

A hidden infrastructure

Mapping Earth’s underground mycorrhizal fungal networks — the hidden infrastructure beneath our feet.

a-hidden-infrastructure.spun.earth

And now it's out! Happy that PNAS selected for the cover this SEM image snapped by @samjlord.bsky.social, one of the most evocative visualizations of Euplotes that I have ever encountered. www.pnas.org/doi/10.1073/... Stay tuned for what is shaping up to be some fascinating follow-up in the lab...

Scanning electron microscopy image of the ciliate Euplotes gigatrox on the cover of the journal PNAS. Distinct punk rock vibes
Ben Larson@blarson.bsky.social · last yr.

What could be more exciting than watching Euplotes scurry around under the microscope? How about adding some raptorial predation by supergiant cannibal cells? www.biorxiv.org/content/10.1... Video by Vittorio Boscaro. 1/n

All you ever wanted to know about how to analyse the nematic nature of cellular tissues is right here 👀👇🏼! Bonus #1: we did it for many cell types and uncovered unexpected defect behavior 🐌 Bonus #2: for theoreticians looking for parameter values for your simulation🧑🏼‍💻 tinyurl.com/2s399yen

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Briefly, after organ injury, 100 milliseconds, we detected collective changes in membrane potential at the tissue level. This is so far the earliest detected wound-response!! This electric signal sparks the formation of a tissue-wide calcium wave👇

PAPER OUT ✨ How can we make smart microscopy more interoperable? What are the technical and cultural challenges? 30+ people from academia and industry propose a roadmap: doi.org/10.1515/mim-... Also a review of applications and repo of implementations. Join the discussion! smartmicroscopy.github.io

Screenshot of the abstract:
Smart microscopy is transforming life sciences by automating experimental imaging workflows and enabling real-time adaptation based on feedback from images and other data streams. This shift increases throughput, improves reproducibility, and expands the functional capabilities of microscopes. However, the current landscape is highly fragmented. Academic researchers often develop custom solutions for specific scientific needs, while industry offerings are typically proprietary and tied to specific hardware. This diversity, while fostering innovation, also creates major challenges in interoperability, reproducibility, and standardization, which slows progress and adaption. This article presents a collaborative effort between academic and industry leaders to survey the current state of smart microscopy, highlight representative implementations, and identify common technical and organizational barriers. We propose a framework for greater interoperability based on shared standards, modular software design, and community-driven development. Our goal is to support collaboration across the field and lay the groundwork for a more connected, reusable, and accessible smart microscopy ecosystem. We conclude with a call to action for researchers, hardware developers, and institutions to join in building an open, interoperable foundation that will unlock the full potential of smart microscopy in life science research.Screenshot of Figure 5: Interoperable smart microscopy ecosystem. Concept of a modular architecture for smart microscopy, where standardized experiment descriptions (e.g. useq-schema) and open data formats (e.g. OME-Zarr) allow integration of diverse microscopes, analysis tools, and user interfaces. Core components such as segmentation [76], [77], tracking [79], [80], and experiment logic are decoupled from specific hardware, enabling reuse across platforms. The system supports multiple input modalities (code, GUI, or natural language) and can be extended with additional devices like fluidics or environmental control modules. This structure enables flexible, feedback-driven acquisition strategies and cross-platform reproducibility.Screenshot of figure 4: Strategies for hardware abstraction that allow smart microscopy workflows to run across different microscope systems, illustrated with example implementations collected on the SMWG website. (A) Software communication layers: Image analysis and experiment logic are implemented in a platform-independent manner, while platform-specific adaptors control acquisition through proprietary microscope software via macros, APIs, or other interfaces. Custom GUIs allow users to configure analysis, while the vendor-provided software manages hardware and acquisition settings. By developing additional adaptors, these workflows can be extended to support microscope systems from other vendors. Example implementation: AutoMicTools , Supplementary Information S3. (B) Device-level standardization (e.g. μManager-based workflows) bypasses proprietary GUIs and provides a unified API for direct device control across manufacturers. This API abstracts vendor-specific differences, enabling consistent control of a growing collection of supported hardware. Example implementation: UU_smart_microscopy , Supplementary Information S2. (C) Event-based standardization decouples experimental design from hardware by describing acquisition events (e.g. acquire frame at x, y, t with channel c) in a structured format (e.g. useq-schema). Control software interprets these definitions and translates them into device-specific commands, enabling the use of vendor-specific features and optimizations during execution. Example implementation: rtm-pymmcore, Supplementary Information S1.
eurobioimaging.bsky.social@eurobioimaging.bsky.social · 7mo ago

🚨Publication! New review on #SmartMicroscopy: current implementations and a roadmap for interoperability by @lhinderling.bsky.social & colleagues from #EuroBioImaging's #SmartMicroscopy Working Group! 🔗 www.eurobioimaging.eu/news/new-pub... 📸 Hinderling et al, 2026, (DOI: 10.1515/mim-2025-0029)

Hot out of press!!! Studying chloroplast organisation from the perspective of packing problems in confinement. chloroplasts show multiple configurations for different purposes (optimal light uptake in dim light vs. light avoidance in strong light for photo protection)🌿 www.pnas.org/doi/10.1073/...

Optimal disk packing of chloroplasts in plant cells | PNAS

Photosynthesis is essential for ecosystem survival, but while plants require light, excessive exposure can damage cells. Chloroplasts, photosynthet...

pnas.org