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New microscopy technology enables nanoscale imaging of centimetre-scale tissues, making it possible to image the entire expanded mouse brain at cellular and subcellular resolution. #ReviewedPreprint

eLife - the journal

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35,249 views • 2 years ago •via X (Twitter)

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New microscopy technology enables nanoscale imaging of centimetre-scale tissues, making it possible to image the entire expanded mouse brain at cellular and subcellular resolution. #ReviewedPreprint

New microscopy technology enables nanoscale imaging of centimetre-scale tissues, making it possible to image the entire expanded mouse brain at cellular and subcellular resolution. #ReviewedPreprint

eLife - the journal

27,496 views • 2 years ago

Researchers can freely access the Allen Mouse Brain Common Coordinate Framework (v3), a complete and high-resolution 3D atlas of the mouse brain. Learn more about it at #SfN23

Researchers can freely access the Allen Mouse Brain Common Coordinate Framework (v3), a complete and high-resolution 3D atlas of the mouse brain. Learn more about it at #SfN23

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🚨🔬💻Happy to introduce the new #eSRRF approach, an analytical #3D #SuperResolution #Microscopy method with improved image fidelity and resolution for live-cell nanoscopy. #eSRRF enables optimization based on the data itself for high-quality nanoscopy

🚨🔬💻Happy to introduce the new #eSRRF approach, an analytical #3D #SuperResolution #Microscopy method with improved image fidelity and resolution for live-cell nanoscopy. #eSRRF enables optimization based on the data itself for high-quality nanoscopy

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The bacterial flagellar motor can spin at 100,000 RPM in one direction, then switch gears and flip to spinning in the other direction. How does this work? Cryo-electron microscopy reveals some of the nanoscale mechanics involved:

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ToughSF

1,110,343 views • 2 years ago

The era of ultra-high-resolution imaging has arrived. Modern image sensors exceeding 200 MP resolution are common in smartphones, with over 400 MP sensors under development. However, the large number of pixels poses significant challenges for acquisition and processing, especially on edge devices. Which pixels should be acquired, and when, for bandwidth-efficient imaging and perception? We introduce Policy-based Foveated Imaging and Perception, an on-device, real-time, predictive, and task-aware framework that dynamically allocates sensor resolution to prioritize important regions under specific perception objectives. This paper will be presented at #SIGGRAPH2026! [1/6]

The era of ultra-high-resolution imaging has arrived. Modern image sensors exceeding 200 MP resolution are common in smartphones, with over 400 MP sensors under development. However, the large number of pixels poses significant challenges for acquisition and processing, especially on edge devices. Which pixels should be acquired, and when, for bandwidth-efficient imaging and perception? We introduce Policy-based Foveated Imaging and Perception, an on-device, real-time, predictive, and task-aware framework that dynamically allocates sensor resolution to prioritize important regions under specific perception objectives. This paper will be presented at #SIGGRAPH2026! [1/6]

Gordon Wetzstein

18,310 views • 1 month ago

400G/lane technology has arrived! Scale AI workloads with the first 400G/lane optical DSP: Taurus BCM83640. Debuting at #OFC2026, it enables low-power 1.6T transceivers and paves the path for 204.8T networks. Learn more:

400G/lane technology has arrived! Scale AI workloads with the first 400G/lane optical DSP: Taurus BCM83640. Debuting at #OFC2026, it enables low-power 1.6T transceivers and paves the path for 204.8T networks. Learn more:

Broadcom

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🚨 MIT SCIENTISTS JUST SHRANK A MATERIAL TO 1/2000TH ITS ORIGINAL SIZE …and turned it into a machine that can manipulate light itself. Using a new process called “implosion carving,” researchers create microscopic voids inside a material… then collapse the entire structure down to nanoscale precision. The result? 3D photonic structures smaller than the wavelength of visible light. That means they can bend, guide, and compute using light itself instead of electricity. Why this matters: • Could accelerate optical computing • May drastically reduce energy use in future AI systems • Enables programmable nanostructures in 3D • Pushes manufacturing toward atom-scale engineering • Opens the door to entirely new classes of quantum and photonic devices The wild part is HOW they do it. Instead of building tiny structures directly… they build larger ones first… then “implode” them into nanoscale machines. It’s almost like compressing an entire factory into a speck of dust. We are entering the era where matter itself becomes programmable. Follow for more future physics and breakthrough technology.

🚨 MIT SCIENTISTS JUST SHRANK A MATERIAL TO 1/2000TH ITS ORIGINAL SIZE …and turned it into a machine that can manipulate light itself. Using a new process called “implosion carving,” researchers create microscopic voids inside a material… then collapse the entire structure down to nanoscale precision. The result? 3D photonic structures smaller than the wavelength of visible light. That means they can bend, guide, and compute using light itself instead of electricity. Why this matters: • Could accelerate optical computing • May drastically reduce energy use in future AI systems • Enables programmable nanostructures in 3D • Pushes manufacturing toward atom-scale engineering • Opens the door to entirely new classes of quantum and photonic devices The wild part is HOW they do it. Instead of building tiny structures directly… they build larger ones first… then “implode” them into nanoscale machines. It’s almost like compressing an entire factory into a speck of dust. We are entering the era where matter itself becomes programmable. Follow for more future physics and breakthrough technology.

TheNewPhysics

31,159 views • 2 months ago

SOA PCCT - FUNCTIONAL IMAGING/IAD Maximum level of spatial resolution achievable in CT with Dual Source Photon Counting CT Technology (Quantum HD Cardiac: 100 micron) the semeiology is completely different. Large IAD with dynamic behavior of the issue and flow from LA to RA.

SOA PCCT - FUNCTIONAL IMAGING/IAD Maximum level of spatial resolution achievable in CT with Dual Source Photon Counting CT Technology (Quantum HD Cardiac: 100 micron) the semeiology is completely different. Large IAD with dynamic behavior of the issue and flow from LA to RA.

Dr. Filippo Cademartiri

28,920 views • 2 years ago

E11 Bio is excited to unveil PRISM technology for mapping brain wiring with simple light microscopes. Today, brain mapping in humans and other mammals is bottlenecked by accurate neuron tracing. PRISM uses molecular ID codes and AI to help neurons trace themselves. We discovered a new cell barcoding approach exceeding comparable methods by more than 750x. This is the heart of PRISM. We integrated this capability with microscopy and AI image analysis to automatically trace neurons at high resolution and annotate them with molecular features. This is a key advance towards economically viable brain mapping - 95% of costs stem from neuron tracing. It is also an important step towards democratizing neuron tracing for everyday neuroscience. Solving these problems is critical for curing brain disorders, building safer and human-like AI, and even simulating brain function. In our first pilot study, we acquired a unique dataset in mouse hippocampus. Barcodes improved the accuracy of tracing genetically labelled neurons by 8x – with a clear path to 100x or more. They also permit tracing across spatial gaps – essential for mitigating tissue section loss in whole-brain scaling. Using molecular annotation, we uncover an intriguing feature of synaptic organization, demonstrating how PRISM can be used for systematic discovery 🧵

E11 Bio is excited to unveil PRISM technology for mapping brain wiring with simple light microscopes. Today, brain mapping in humans and other mammals is bottlenecked by accurate neuron tracing. PRISM uses molecular ID codes and AI to help neurons trace themselves. We discovered a new cell barcoding approach exceeding comparable methods by more than 750x. This is the heart of PRISM. We integrated this capability with microscopy and AI image analysis to automatically trace neurons at high resolution and annotate them with molecular features. This is a key advance towards economically viable brain mapping - 95% of costs stem from neuron tracing. It is also an important step towards democratizing neuron tracing for everyday neuroscience. Solving these problems is critical for curing brain disorders, building safer and human-like AI, and even simulating brain function. In our first pilot study, we acquired a unique dataset in mouse hippocampus. Barcodes improved the accuracy of tracing genetically labelled neurons by 8x – with a clear path to 100x or more. They also permit tracing across spatial gaps – essential for mitigating tissue section loss in whole-brain scaling. Using molecular annotation, we uncover an intriguing feature of synaptic organization, demonstrating how PRISM can be used for systematic discovery 🧵

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🚨🇷🇺Russian scientists among first to master compressed light technology The compact on-chip source of quantum compressed light unlocks new advances in ultra-sensitive quantum sensing and computing 🔸 The advance enables compact, ultra-sensitive sensors based on ‘squeezed’ light 🔸 Squeezed light surpasses the standard quantum limit of classical light, enabling measurements far more precise than previously possible 🔸 The technology could revolutionize medical diagnostics by overcoming a key limitation of existing sensors — the risk of tissue damage when increasing beam power for imaging 🔸 It also paves the way for photonic quantum computers capable of solving complex optimization problems, from improving logistics to streamlining production chains The breakthrough marks a major step forward in photonic technology development

🚨🇷🇺Russian scientists among first to master compressed light technology The compact on-chip source of quantum compressed light unlocks new advances in ultra-sensitive quantum sensing and computing 🔸 The advance enables compact, ultra-sensitive sensors based on ‘squeezed’ light 🔸 Squeezed light surpasses the standard quantum limit of classical light, enabling measurements far more precise than previously possible 🔸 The technology could revolutionize medical diagnostics by overcoming a key limitation of existing sensors — the risk of tissue damage when increasing beam power for imaging 🔸 It also paves the way for photonic quantum computers capable of solving complex optimization problems, from improving logistics to streamlining production chains The breakthrough marks a major step forward in photonic technology development

Sputnik

13,756 views • 14 days ago

I've been editing this article about "brain mapping" and connectomics, and I'm just stunned by how quickly the cost estimates to map, say, a mouse brain have plummeted in just the last couple years. It actually seems feasible that we could map the entire human brain -- all 86 billion neurons, and their connections -- in this lifetime. In the 1970s, Sydney Brenner started mapping all the connections between neurons in C. elegans. His team sliced the worm into thin pieces, took photos using an electron microscope, and manually traced and reconstructed each synapse for 302 neurons total. This project took more than a decade of work, and it cost about $16,500 to reconstruct each neuron. Scaling this up to a human brain boggles the mind. Electron microscopy remained the norm in connectomics for decades, because it was the only option available to see synapses at a resolution high enough to be able to trace their paths. Each electron microscope costs several hundreds of thousands of dollars, though, and you need lots of them to map even a mouse brain in a reasonable timeframe. In 2023, the Wellcome Trust released a report estimating how long, and how expensive, it would be to map the mouse connectome (~70M neurons). They estimated that imaging alone would cost $200-300M, and that proofreading (or ensuring that traces between neurons are correct) would cost $7-21 BILLION. (A human can only manually trace about 1 mm of neuron per hour.) Also, the images would occupy about 500 petabytes of data, and getting those data would require 20 electron microscopes running in parallel for about 5 years, continuously. They estimated the whole project would take about 17 years of work. This is, understandably, insane. But now it seems like there's an actual path toward mapping the full mouse brain in about five years for ~$100M dollars. There have been three major breakthroughs in the last year or so: 1/ Expansion microscopy, first developed in 2015, showed that it's possible to "enlarge" the brain by about 5x using a swellable polymer. But an improved method increases this number to >20x expansion, meaning we can now expand brains and image neurons much more easily using cheap light microscopes, rather than expensive electron ones. 2/ E11 Bio (a nonprofit research org) developed protein barcodes that get delivered into brain tissue; each neuron gets a unique combination of barcodes. These cells are then stained with colorful antibodies, which stick to a matching protein barcode, causing each neuron to light up in a distinct color. This makes tracing neurons so much easier. 3/ Google Research released PATHFINDER this May, an AI-based neuron tracing tool that can proofread about 67,200 cubic microns of brain tissue per hour, with very high accuracy. It works on electron micrographs, but something similar could be presumably be developed for the E11 / colorful tag approach. This is an extremely exciting time for neuroscience. (C. elegans connectome below.)

I've been editing this article about "brain mapping" and connectomics, and I'm just stunned by how quickly the cost estimates to map, say, a mouse brain have plummeted in just the last couple years. It actually seems feasible that we could map the entire human brain -- all 86 billion neurons, and their connections -- in this lifetime. In the 1970s, Sydney Brenner started mapping all the connections between neurons in C. elegans. His team sliced the worm into thin pieces, took photos using an electron microscope, and manually traced and reconstructed each synapse for 302 neurons total. This project took more than a decade of work, and it cost about $16,500 to reconstruct each neuron. Scaling this up to a human brain boggles the mind. Electron microscopy remained the norm in connectomics for decades, because it was the only option available to see synapses at a resolution high enough to be able to trace their paths. Each electron microscope costs several hundreds of thousands of dollars, though, and you need lots of them to map even a mouse brain in a reasonable timeframe. In 2023, the Wellcome Trust released a report estimating how long, and how expensive, it would be to map the mouse connectome (~70M neurons). They estimated that imaging alone would cost $200-300M, and that proofreading (or ensuring that traces between neurons are correct) would cost $7-21 BILLION. (A human can only manually trace about 1 mm of neuron per hour.) Also, the images would occupy about 500 petabytes of data, and getting those data would require 20 electron microscopes running in parallel for about 5 years, continuously. They estimated the whole project would take about 17 years of work. This is, understandably, insane. But now it seems like there's an actual path toward mapping the full mouse brain in about five years for ~$100M dollars. There have been three major breakthroughs in the last year or so: 1/ Expansion microscopy, first developed in 2015, showed that it's possible to "enlarge" the brain by about 5x using a swellable polymer. But an improved method increases this number to >20x expansion, meaning we can now expand brains and image neurons much more easily using cheap light microscopes, rather than expensive electron ones. 2/ E11 Bio (a nonprofit research org) developed protein barcodes that get delivered into brain tissue; each neuron gets a unique combination of barcodes. These cells are then stained with colorful antibodies, which stick to a matching protein barcode, causing each neuron to light up in a distinct color. This makes tracing neurons so much easier. 3/ Google Research released PATHFINDER this May, an AI-based neuron tracing tool that can proofread about 67,200 cubic microns of brain tissue per hour, with very high accuracy. It works on electron micrographs, but something similar could be presumably be developed for the E11 / colorful tag approach. This is an extremely exciting time for neuroscience. (C. elegans connectome below.)

Niko McCarty.

66,819 views • 7 months ago

1/ We're thrilled to share our preprint on Deep3P - a new approach that takes us on a deep dive into the world of brain tumors, using three-photon microscopy and #AI. This exciting endeavor is brought to life together with the amazing Prevedel Lab !

1/ We're thrilled to share our preprint on Deep3P - a new approach that takes us on a deep dive into the world of brain tumors, using three-photon microscopy and #AI. This exciting endeavor is brought to life together with the amazing Prevedel Lab !

Varun Venkataramani

67,453 views • 3 years ago

A dream of our lab has been to image the full central dogma from a single endogenous gene, all live and with single molecule resolution. After many years we are happy to unveil a beautiful cell line that makes it possible. Check out our preprint ( (1/n)

A dream of our lab has been to image the full central dogma from a single endogenous gene, all live and with single molecule resolution. After many years we are happy to unveil a beautiful cell line that makes it possible. Check out our preprint ( (1/n)

Timothy

206,280 views • 2 years ago

🚨 SCIENTISTS ARE USING AI TO MAP A HIDDEN “CLEANING SYSTEM” INSIDE THE HUMAN BRAIN AND IT COULD CHANGE HOW WE UNDERSTAND SLEEP, AGING, AND NEURODEGENERATIVE DISEASE. It’s called the glymphatic system a vast network of fluid channels that flushes toxic waste from the brain while you sleep. For years it was almost impossible to observe in detail. Now AI-powered imaging is revealing it like a living galaxy of microscopic rivers and pathways inside neural tissue. Why this matters: Your brain produces toxic proteins constantly. The glymphatic system is one of its primary waste-clearance mechanisms clearing the very proteins linked to Alzheimer’s, Parkinson’s, and other neurodegenerative diseases. But here’s the unsettling part: This cleaning system becomes dramatically less efficient with age, poor sleep, stress, and brain injury. Sleep may not just “rest” your mind it may literally wash your brain. The deeper implication is staggering: The brain isn’t just a computer. It’s a dynamic, living network that constantly rebuilds and cleanses itself in real time. The more we map it, the more it looks like an entire universe of connected energy flows inside our skulls. What if some neurological diseases begin when the brain can no longer properly “wash” itself at night? Follow for more frontier neuroscience and future technology.

🚨 SCIENTISTS ARE USING AI TO MAP A HIDDEN “CLEANING SYSTEM” INSIDE THE HUMAN BRAIN AND IT COULD CHANGE HOW WE UNDERSTAND SLEEP, AGING, AND NEURODEGENERATIVE DISEASE. It’s called the glymphatic system a vast network of fluid channels that flushes toxic waste from the brain while you sleep. For years it was almost impossible to observe in detail. Now AI-powered imaging is revealing it like a living galaxy of microscopic rivers and pathways inside neural tissue. Why this matters: Your brain produces toxic proteins constantly. The glymphatic system is one of its primary waste-clearance mechanisms clearing the very proteins linked to Alzheimer’s, Parkinson’s, and other neurodegenerative diseases. But here’s the unsettling part: This cleaning system becomes dramatically less efficient with age, poor sleep, stress, and brain injury. Sleep may not just “rest” your mind it may literally wash your brain. The deeper implication is staggering: The brain isn’t just a computer. It’s a dynamic, living network that constantly rebuilds and cleanses itself in real time. The more we map it, the more it looks like an entire universe of connected energy flows inside our skulls. What if some neurological diseases begin when the brain can no longer properly “wash” itself at night? Follow for more frontier neuroscience and future technology.

TheNewPhysics

15,641 views • 1 month ago

🔬 Why Perfect Visualization of Stents and Calcified Plaques Requires the Highest Spatial, Temporal and Contrast Resolution: The Case for Ultra-High-Resolution with Photon Counting CT Image: a close look at a RCA stent with very mild intimal hyperplasia. Seeing is everything in coronary imaging. Yet when it comes to stents and heavily calcified plaques, even the best conventional CT systems hit their physical limits — blooming, partial volume effects, and metal artifacts blur what truly matters. That’s where Ultra-High-Resolution Photon Counting CT (PCCT) changes the game. 🧠 Why it matters: Conventional CT often overestimates stenosis in calcified vessels and hides in-stent lumen due to blooming and noise. This leads to diagnostic uncertainty, unnecessary invasive testing, and poor evaluation of stent patency or neo-atherosclerosis. ⚡ What PCCT adds: Ultra-high spatial resolution (0.1 mm voxels) sharply delineates stent struts, plaque borders, and residual lumen. True spectral resolution minimizes blooming and metal artifacts, enhancing visualization even in highly calcified segments. Improved contrast-to-noise enables clear lumen assessment at lower doses. Quantitative, energy-resolved data provide material differentiation between calcium, metal, and contrast — something previously unthinkable in CT. In short, accurate visualization of stents and calcified plaques demands Photon Counting CT — not just for sharper images, but for better diagnostic confidence and patient management. The era of artifact-free coronary imaging has begun — and it’s photon-counting powered. ⚡❤️ #PCCT #CardiacImaging #CoronaryCT #StentImaging #CalciumScore #PhotonCountingCT #PrecisionImaging #CardiovascularImaging #RadiologyInnovation #yesCCT

🔬 Why Perfect Visualization of Stents and Calcified Plaques Requires the Highest Spatial, Temporal and Contrast Resolution: The Case for Ultra-High-Resolution with Photon Counting CT Image: a close look at a RCA stent with very mild intimal hyperplasia. Seeing is everything in coronary imaging. Yet when it comes to stents and heavily calcified plaques, even the best conventional CT systems hit their physical limits — blooming, partial volume effects, and metal artifacts blur what truly matters. That’s where Ultra-High-Resolution Photon Counting CT (PCCT) changes the game. 🧠 Why it matters: Conventional CT often overestimates stenosis in calcified vessels and hides in-stent lumen due to blooming and noise. This leads to diagnostic uncertainty, unnecessary invasive testing, and poor evaluation of stent patency or neo-atherosclerosis. ⚡ What PCCT adds: Ultra-high spatial resolution (0.1 mm voxels) sharply delineates stent struts, plaque borders, and residual lumen. True spectral resolution minimizes blooming and metal artifacts, enhancing visualization even in highly calcified segments. Improved contrast-to-noise enables clear lumen assessment at lower doses. Quantitative, energy-resolved data provide material differentiation between calcium, metal, and contrast — something previously unthinkable in CT. In short, accurate visualization of stents and calcified plaques demands Photon Counting CT — not just for sharper images, but for better diagnostic confidence and patient management. The era of artifact-free coronary imaging has begun — and it’s photon-counting powered. ⚡❤️ #PCCT #CardiacImaging #CoronaryCT #StentImaging #CalciumScore #PhotonCountingCT #PrecisionImaging #CardiovascularImaging #RadiologyInnovation #yesCCT

Dr. Filippo Cademartiri

11,093 views • 6 months ago

BREAKING: Ontario & New York sign a nuclear clean energy partnership. Proud to stand with Doug Ford and Kathy Hochul as they sign a new Memorandum of Understanding for Ontario Power Gen and NY Power Authority to advance the deployment of large-scale nuclear and small modular reactor technology into New York. Ontario's nuclear advantage at work:

BREAKING: Ontario & New York sign a nuclear clean energy partnership. Proud to stand with Doug Ford and Kathy Hochul as they sign a new Memorandum of Understanding for Ontario Power Gen and NY Power Authority to advance the deployment of large-scale nuclear and small modular reactor technology into New York. Ontario's nuclear advantage at work:

Stephen Lecce

27,046 views • 6 months ago

Enter a New Era: V3 LIVE! 🚨 V3 is just the beginning. A powerful suite of new products are in development, each designed to push the boundaries of what’s possible with Alchemist AI. These features will be deployed in phases over the coming weeks, bringing continuous improvements, new capabilities, and expanded creative potential. Just $ALCH it!🪄✨

Enter a New Era: V3 LIVE! 🚨 V3 is just the beginning. A powerful suite of new products are in development, each designed to push the boundaries of what’s possible with Alchemist AI. These features will be deployed in phases over the coming weeks, bringing continuous improvements, new capabilities, and expanded creative potential. Just $ALCH it!🪄✨

ALCHEMIST AI 🔮

32,164 views • 1 year ago

🇨🇳 Zhengzhou recently expanded the 7th and 8th lines of its subway system and this is what the new stations look like. Zhengzhou now has 450km (280 mi) of metro, making it the 10th largest metro in China and 11th largest in the world.

🇨🇳 Zhengzhou recently expanded the 7th and 8th lines of its subway system and this is what the new stations look like. Zhengzhou now has 450km (280 mi) of metro, making it the 10th largest metro in China and 11th largest in the world.

Orikron 🇵🇹 骆培思

182,910 views • 11 months ago

Apple just trained a 3D Gaussian head reconstruction model on 10,000+ subjects. Feed-forward. No test-time optimization. New identity in, reconstructed Gaussian head out. The UV-parameterized Gaussian representation decouples the number of Gaussians from the number and resolution of input images, making it practical to train with many high resolution views. And the heads are not just static either: text-conditioned identity generation, plus blendshape-driven latent animation across identities. We've been building in the 3D Gaussian Splatting space for a while. The gap between "research demo" and "works on real people at scale" is closing fast.

Apple just trained a 3D Gaussian head reconstruction model on 10,000+ subjects. Feed-forward. No test-time optimization. New identity in, reconstructed Gaussian head out. The UV-parameterized Gaussian representation decouples the number of Gaussians from the number and resolution of input images, making it practical to train with many high resolution views. And the heads are not just static either: text-conditioned identity generation, plus blendshape-driven latent animation across identities. We've been building in the 3D Gaussian Splatting space for a while. The gap between "research demo" and "works on real people at scale" is closing fast.

KIRI Engine - 3D Scanner App

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Generating 3D Worlds from a Single Image AI can now turn any photo into a 3D world. World Labs AI creates spaces with an understanding of what it’s building, making it possible to add physics and place new objects inside. Explore here (World Labs demos): marble.worldlabs .ai

Generating 3D Worlds from a Single Image AI can now turn any photo into a 3D world. World Labs AI creates spaces with an understanding of what it’s building, making it possible to add physics and place new objects inside. Explore here (World Labs demos): marble.worldlabs .ai

Leon

89,924 views • 10 months ago