Super-resolution Microscope Builds 3D Images by Mapping Negative Space

Scientists at The University of Texas at Austin have demonstrated a method for making three-dimensional images of structures in biological material under natural conditions at a much higher resolution than other existing methods. The method may help shed light on how cells communicate with one another and provide important insights for engineers working to develop artificial organs such as skin or heart tissue.

The research is described today in the journal Nature Communications.

The scientists, led by physicist Ernst-Ludwig Florin, used their method, called thermal noise imaging, to capture nanometer-scale images of networks of collagen fibrils, which form part of the connective tissue found in the skin of animals. A nanometer is a billionth of a meter or about one-hundred-thousandth of the width of a human hair. Examining collagen fibrils at this scale allowed the scientists to measure for the first time key properties that affect skin’s elasticity, something that could lead to improved designs for artificial skin or tissues.

Taking crisp 3-D images of nanoscale structures in biological samples is extremely difficult, in part because they tend to be soft and bathed in liquid. This means that tiny fluctuations in heat cause structures to move back and forth, an effect known as Brownian motion.

To overcome the blurriness that this creates, other super-resolution imaging techniques often "fix" biological samples by adding chemicals that stiffen various structures, in which case, materials lose their natural mechanical properties. Scientists can sometimes overcome blurriness without fixing the samples if, for example, they focus on rigid structures stuck to a glass surface, but that severely limits the kinds of structures and configurations they can study.

Florin and his team took a different approach. To make an image, they add nanospheres - nanometer-sized beads that reflect laser light - to their biological samples under natural conditions, shine a laser on the sample and compile superfast snapshots of the nanospheres viewed through a light microscope.

The scientists explain that the method, thermal noise imaging, works something like this analogy: Imagine you needed to take a three-dimensional image of a room in total darkness. If you were to throw a glowing rubber ball into the room and use a camera to collect a series of high-speed images of the ball as it bounces around, you would see that as the ball moves around the room, it isn’t able to move through solid objects such as tables and chairs. Combining millions of images taken so fast that they don't blur, you would be able to build a picture of where there are objects (wherever the ball couldn’t go) and where there aren't objects (where it could go).

In thermal noise imaging, the equivalent of the rubber ball is a nanosphere that moves around in a sample by natural Brownian motion - the same unruly force that has bedeviled other microscopy methods.

"This chaotic wiggling is a nuisance for most microscopy techniques because it makes everything blurry," says Florin. "We've turned it to our advantage. We don't need to build a complicated mechanism to move our probe around. We sit back and let nature do it for us."

The original concept for the thermal noise imaging technique was published and patented in 2001, but technical challenges prevented it from being developed into a fully functioning process until now.

The tool allowed the researchers to measure for the first time the mechanical properties of collagen fibrils in a network. Collagen is a biopolymer that forms scaffolds for cells in the skin and contributes to the skin's elasticity. Scientists are still not sure how a collagen network’s architecture results in its elasticity, an important question that must be answered for the rational design of artificial skin.

"If you want to build artificial skin, you have to understand how the natural components work," says Florin. "You could then better design a collagen network that acts as a scaffolding that encourages cells to grow in the right way."

The paper's first author is Tobias Bartsch, a former graduate student at UT Austin and currently a postdoctoral associate at The Rockefeller University. Other co-authors are Martin Kochanczyk, Emanuel Lissek and Janina Lange.

Funding for this research was provided by the National Science Foundation and the Simons Foundation.

Most Popular Now

Accelerating NHS Digital Maturity: Paper…

Digitised clinical noting at South Tees Hospitals NHS Foundation Trust is creating efficiencies for busy doctors and nurses. The trust’s CCIO Dr Andrew Adair, deputy CCIO Dr John Greenaway, and...

AI Tool Helps Predict Who will Benefit f…

A study led by UCLA investigators shows that artificial intelligence (AI) could play a key role in improving treatment outcomes for men with prostate cancer by helping physicians determine who...

New Study Shows Promise for Gamified mHe…

A new study published in Multiple Sclerosis and Related Disorders highlights the potential of More Stamina, a gamified mobile health (mHealth) app designed to help people with Multiple Sclerosis (MS)...

AI in Healthcare: How do We Get from Hyp…

The Highland Marketing advisory board met to consider the government's enthusiasm for AI. To date, healthcare has mostly experimented with decision support tools, and their impact on the NHS and...

Research Shows AI Technology Improves Pa…

Existing research indicates that the accuracy of a Parkinson's disease diagnosis hovers between 55% and 78% in the first five years of assessment. That's partly because Parkinson's sibling movement disorders...

New AI Tool Accelerates Disease Treatmen…

University of Virginia School of Medicine scientists have created a computational tool to accelerate the development of new disease treatments. The tool goes beyond current artificial intelligence (AI) approaches by...

DMEA sparks: The Future of Digital Healt…

8 - 10 April 2025, Berlin, Germany. Digitalization is considered one of the key strategies for addressing the shortage of skilled workers - but the digital health sector also needs qualified...

First Therapy Chatbot Trial Shows AI can…

Dartmouth researchers conducted the first clinical trial of a therapy chatbot powered by generative AI and found that the software resulted in significant improvements in participants' symptoms, according to results...

Who's to Blame When AI Makes a Medi…

Assistive artificial intelligence technologies hold significant promise for transforming health care by aiding physicians in diagnosing, managing, and treating patients. However, the current trend of assistive AI implementation could actually...

DeepSeek: The "Watson" to Doct…

DeepSeek is an artificial intelligence (AI) platform built on deep learning and natural language processing (NLP) technologies. Its core products include the DeepSeek-R1 and DeepSeek-V3 models. Leveraging an efficient Mixture...

Stepping Hill Hospital Announced as SPAR…

Stepping Hill Hospital, part of Stockport NHS Foundation Trust, has replaced its bedside units with state-of-the art devices running a full range of information, engagement, communications and productivity apps, to...

DMEA 2025: Digital Health Worldwide in B…

8 - 10 April 2025, Berlin, Germany. From the AI Act, to the potential of the European Health Data Space, to the power of patient data in Scandinavia - DMEA 2025...