How label-free, super-resolution imaging will push microscopy’s limits – Advanced Science News

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Anton van Leeuwenhoek, who is recognized as the father of microbiology, In 1677, he became the first person to observe bacteria under a microscope, starting a revolution in microscopy that continued into the 18th century. This allowed humans to get into living things by finding organisms that include animals and plants.

Eventually, optical microscopes exhausted the limit defined by half the wavelength of light used – the classical diffraction limit. This means that optical microscopes can resolve bacteria and cells, but not some small subcellular structures, viruses or proteins. Living things smaller than 10 nanometers, such as enzymes and DNA, require an electron microscope to visualize.

But optical microscopes are preferred over electron microscopes because they are non-invasive for looking inside living organisms and looking at cells and tissues to understand the processes that take place there.

Bright fluorescent markers such as dye molecules can be used to push optical microscopes beyond the diffraction limit for the specific labeling of subcellular structures and thus cellular functions, but this has drawbacks. This type of sign is not suitable in all cases, but it can be difficult to achieve. Additionally, labeling can lead to phototoxicity—a toxic reaction that occurs after exposure to chemicals and subsequent exposure to light—which can damage living cells or tissues.

Therefore, scientists are looking for methods that can propel light microscopy without the need for dyes. Label-free super-resolution (LFSR) imaging is based on light scattering processes in nanoscale materials without the need for bright fluorescent signals.

“Label-free imaging is a type of optical microscopy, or more broadly, a type of electromagnetic imaging, that does not rely on the use of bright fluorescent markers added to probe biomedical or other structures to contrast or highlight structures of interest,” said Professor of Physics and Optical Sciences at the University of North Carolina at Charlotte. Vasily Astratov said.

“This is highly desirable imaging in biomedical applications, but due to factors such as the fundamental role of noise and the information capacity of optical systems, the role of prior knowledge will push our understanding of the underlying physical mechanisms beyond the classical distinction. And AI science, near-field and nonlinear optics, as well as advanced Superlens Designs,” he continued.

The needs of LFSR as it continues to evolve as a microscopy technique prompted Astratov and his colleagues in a team of 27 researchers to create a roadmap for the future development of this process. The group’s work and conclusions are documented in A piece of paper Published in the magazine Lasers and photonics reviews.

Astratov explained that this represents a first-of-its-kind vision of past, present and future developments based on the physical methods of LFSR imaging.

A road map to the nanoscale

Initially, the development of LFSR imaging was a slow process based on mutual introduction of new physical methods between different disciplinary concepts. Over the past two decades, the development of LFSR has grown through three major developments.

The first of these is recognizing that imaging is a problem that can be solved by machine learning, using various prior knowledge about objects, training image representation systems such as deep learning networks, and finally using artificial intelligence to recognize images. and improve the quality of optical equipment.

Second was the development of structured illumination microscopy – the use of structured illumination, such as interference patterns between wavelengths of light, to allow high spatial frequencies to be observed with a microscope. A third important aspect of LFSR development is the creation of novel optical concepts such as “perfect” lenses, superlenses and hyperlenses, as well as transformation optics in the context of metamaterials and other materials.

Research co-author and UCLA professor Idoğan Özkan points out that these developments have led to the explosive growth of LFSR imaging.

“To a certain extent, this is similar to the revolution we find in everyday life due to the explosive development of AI ideas in general, which has reached a level of consideration and concern,” said Ozkan. “The explosive growth in LFSR imaging and the combination of a methodological and systematic approach to this field has created an urgent need to develop a vision for the future of this field in general. This roadmap in particular”

In the past, LFSP imaging studies have been conducted in the physics and biomedical optics communities, which have different conferences and different research priorities. The goal of Astrotov and his colleagues was to bring the communities under one roof and create a synergistic interaction between LFSR approaches.

“This area is at the forefront of modern optics and photonics because it affects our entire understanding of the fundamental principles behind the concept of optical resolution,” explains Asratrov.

With the history of the LFSR in the rearview mirror, the team noted that the interplay of these different strategies and aspects creates new opportunities to improve the image of the LFSR.

On-road and off-road bumps for LFSR

Astratov, Ozkan and colleagues point out that there are many bumps in the road for LFSR.

“The realization of the super-resolution of label-free imaging shows the need to examine some business conditions,” said Nikolai Zheludev, a researcher at the University of Southampton and study co-author.

This can include, but is not limited to, trade-offs between nanoscale aperture probe size and acquired signal-to-noise ratio, or learning depth for machine learning approaches, he said. The complexity of the task and the amount of prior knowledge included in the system.

Fortunately, bringing together 27 different international groups means that the “bumps in the road” identified for the LFSR are approaching what Astratov calls “all possible directions.” These angles include pure theory, experimental demonstration of high-resolution potential, and application of LFSR methods in biomedical research and material properties.

However, this approach has its limitations, and the team was willing to do a little “out of the way” based on the microscopy and imaging around light waves. The team noted that LFSR concepts are applicable at longer wavelengths, which could be used for this technique.

“Microwaves can be used to capture images of strongly scattering media – clouds, tissue, sandstorms, water and snow,” Zeludev said. “Combining ultra-low and ultra-low-frequency background electromagnetic waves with computational methods can lead to imaging anywhere and everywhere.”

References: VN Astratov., et al., A road map to label-free high-resolution imagingLasers and Photonics Reviews, (2023), DOI: 10.1002/lpor.202200029



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