⚙️ What makes the RT‑SuperES system unique?
We combine live-cell super-resolution microscopy with real-time AI-based reconstruction, reducing processing time from hours to milliseconds.
Enabling insights as they happen!
#RTSuperES#AIinScience#Microscopy@EUeic#PathfinderOpen
Smart microscopy can start before any AI enters the loop.
TIDT-NAS asks a simpler question: where do additional measurements actually add information?
It samples densely near the specimen, where high-frequency structure is concentrated, and sparsely through extended defocus. In live HeLa cells, that reduced one scan from 71 axial images to 26 while enabling ~1 Hz 4D refractive-index imaging.
Smart acquisition can also mean knowing where not to measure redundantly.
doi.org/10.1186/s43074-026-0…#RTSuperES#SmartMicroscopy
🚨I have open PhD positions to join my new lab at #NIMSB🚀!! nimsb.unl.pt/join-us/
🌟I'm looking for motivated candidates, eager to join a multidisciplinary team + study the intracellular dynamics driving cancer cell migration with advanced computational methods & microscopy👾
Microscopy reproducibility cannot stop at acquisition metadata.
A new paper involving @EuroBioImaging and @galaxyproject makes the case for FAIR bioimage analysis built around executable workflows, provenance and reusable training.
My take: as microscopy becomes adaptive, the analysis path becomes part of the experiment. If an algorithm changes what we image next, we should be able to reconstruct why.
doi.org/10.1111/jmi.70165#RTSuperES#Bioimaging#OpenScience
Lysosome repair is not just a list of proteins. It is a spatially organized event.
A new @NatureCellBio study used live imaging and lattice-SIM to watch DFCP1-positive ER domains assemble around damaged lysosomes. DFCP1 helps concentrate VPS13C and supports membrane repair.
What imaging adds here is time and topology: not only who participates, but where the repair machinery assembles and in what sequence.
doi.org/10.1038/s41556-026-0…#RTSuperES#CellBiology#Microscopy
“Most informative” is not intrinsic to an image.
SimuScan uses AI to identify nanoscale features and guide follow-up AFM scans, but users define what gets prioritised.
AI can decide where to look next. Science still defines what matters.
doi.org/10.1038/s41467-026-7…#RTSuperES
“Most informative” is not an intrinsic property of an image.
@ORNL’s SimuScan can identify nanoscale features and steer follow-up AFM scans, but the targets are ranked according to user-defined criteria.
That distinction matters. AI can optimize where to look next, but science still has to define what is worth looking for.
For adaptive microscopy, the hard problem may not be autonomy itself, but choosing the right objective.
doi.org/10.1038/s41467-026-7…#RTSuperES#SmartMicroscopy#AI
Imaging one organ at a time can hide physiology that exists between organs.
WHOLISTIC records cellular Ca²⁺ activity across larval zebrafish and revealed brainstem control of blood-flow redistribution during hypoxia.
doi.org/10.1038/s41586-026-1…#RTSuperES
What if, instead of filtering background away, we moved the signal somewhere the background isn't?
PP-LID makes upconversion nanoparticles generate a new beat-frequency signal absent from the excitation light, enabling camera-based isolation.
doi.org/10.1038/s41377-026-0…#RTSuperES
Does microscopy analysis always need the full image volume?
DeepWonder3D works from multiview projections rather than every voxel, improving 3D neuronal localization with ~10× lower computational cost.
Sometimes the representation is part of the solution.
doi.org/10.1038/s41592-026-0…#RTSuperES
What if multiple imaging modes could be encoded into the coverslip?
A new preprint demonstrates a meta-coverslip for bright-field, differential, fluorescence and holographic imaging, switching functions by changing wavelength.
arxiv.org/abs/2609.02335#RTSuperES#Microscopy
Sometimes nanometres are not just resolution. They are biology.
A new study shows that membrane-to-cortex distance can regulate mDia1 activity and cell mechanics, turning nanoscale geometry into a functional cellular parameter.
doi.org/10.1038/s41467-026-7…#RTSuperES
Hot from the oven!🔥🔥 Excited to share Tamar Segal's PhD work in @GenomeBiology, where we developed a pipeline to identify regulators of transcriptional noise in embryonic stem cells, revealing NAP1L1 as a stabilizer! Congrats Tamar and authors!
link.springer.com/article/10…
Broad first, detailed where it matters.
A new Euro-BioImaging case study combines multiplex spatial phenotyping with confocal microscopy to study tumour therapy resistance.
A good example of matching imaging depth to the biological question.
eurobioimaging.eu/news/under…#RTSuperES#Bioimaging
How much biological time is hidden inside one super-resolution image?
SPIFFI gets ~1.7× instantaneous resolution enhancement from a single exposure and captured live-cell dynamics blurred by methods integrating many frames.
doi.org/10.1038/s41592-026-0…#RTSuperES
How far has microscopy advanced if only a few specialist labs can use it?
As IMC21 begins, its programme includes widening access through open-source instruments, low-cost optics, shared facilities, training and standards.
imc21.org.uk/congress/confer…#RTSuperES#IMC21
What if a smart microscope could decide from photon statistics, not only images?
A new SPAD-array study uses Bayesian inference to estimate active fluorophore number from photon-count statistics.
Could detector-level information drive acquisition?
doi.org/10.1038/s41598-026-6…#RTSuperES
Where does an imaging system begin?
Not necessarily at the microscope.
New fluorogenic peptide probes enable multicolour, wash-free real-time live-cell microscopy—a reminder that acquisition quality can be engineered into the reporter itself.
doi.org/10.1038/s41557-026-0…#RTSuperES
What should “high-content” microscopy mean?
Not necessarily more images. Chem-SIM combines SIM with mid-IR photothermal modulation, adding chemical fingerprints to spatial information.
Could type of information become an adaptive choice?
doi.org/10.1038/s41467-026-7…#RTSuperES