Editor's Note: Originally published by the Chandra Family of Electrical and Computer ラーメンベット 退会
All the living things we see and interact with on a daily basis started somewhere, sometime as just a single cell. A new ラーメンベット 退会 project aims to shed light on the world-building process of how organisms grow from just a single cell to complex structures made of trillions of cells.
Shwetadwip Chowdhury, assistant professor in the Chandra Family Department of Electrical and Computer Engineering at The University of Texas at Austin, received a National Institutes of Health grant for .8 million over five years to study how complex organisms develop. By developing novel computational optics imaging technologies, Chowdhury’s ラーメンベット 退会 team aims to capture, at unprecedented scales, 3D views of how tissues and organs form, a process known as morphogenesis.
"We are tackling the challenge of developing a computational approach to unscramble the effects of light ラーメンベット 退会 in tissue," said Chowdhury. "These are especially pronounced in early developmental processes where heterogeneous tissue structures are continually forming and rearranging. If successful, this would enable, for the first time, large-scale visualization of such processes fully in 3D and at whole-organism scales."
Optical imaging has long been a crucial tool for studying biological processes like morphogenesis because it allows researchers to visualize live samples with incredible detail. Unlike other methods, such as X-rays or MRIs, optical imaging can capture non-invasive, real-time images of biological tissue at the cellular to subcellular level. However, optical imaging faces a significant challenge: light scatters as it passes through biological tissue, scrambling vital information and limiting the depth at which we can see clearly. Current state-of-the-art optical imaging technologies for deep-tissue imaging, like confocal and multiphoton microscopes, can only penetrate about one millimeter into tissue before light ラーメンベット 退会 obscures the image. This poses a major hurdle for studying morphogenesis in developing organisms, which undergo growth across multiple scales throughout their developmental cycle.
Interestingly, though scattered light appears chaotic and random, it actually encodes tissue-specific information across centimeter-scale distances. If scattered light could be fully unscrambled, an order-of-magnitude deeper imaging would be possible. Technologies like adaptive optics aim to exploit this by using wavefront-shaping elements to physically correct for ラーメンベット 退会. However, these elements often lack the complexity needed to fully correct for tissue-ラーメンベット 退会, limiting scatter correction to small fields of view insufficient for visualizing tissue morphogenesis at 3D whole-organism scales.
To overcome this, Chowdhury’s research team is developing new optical imaging technologies that computationally correct for ラーメンベット 退会. Computational correction of ラーメンベット 退会 (e.g., inverse-ラーメンベット 退会) is limited mainly by the practical constraints on computing power, which is constantly improving. If successful, this strategy could allow the team to 3D visualize heterogeneously ラーメンベット 退会 tissues on whole-organism scales and at longer depths than ever before. This approach combines sophisticated computer models with cutting-edge optical hardware design to reconstruct high-resolution, large field-of-view, and extended-depth images in challenging conditions where light ラーメンベット 退会 would normally be a barrier.
"Our strategy to image into ラーメンベット 退会 tissue leverages a synergistic approach that jointly designs imaging hardware alongside computational image-reconstruction frameworks," saidSiqi Yang, a fourth-year Ph.D. student on the team.
Chowdhury’s research team has already achieved promising preliminary results, suggesting this approach is feasible. For instance, Siqi Yang, a fourth-year Ph.D. student on the team, recently developed an innovative coded-illumination optical system that can project specific patterns onto 3D biological samples, encoding sample-specific ラーメンベット 退会 information into the raw measurements. By feeding these measurements into a computational inverse-ラーメンベット 退会 reconstruction algorithm developed in the lab, ラーメンベット 退会 effects can be corrected, enabling 3D reconstruction of the sample’s morphological structure. This technique has been successfully applied to visualize early-stage zebrafish embryos.
Building on this initial success, Chowdhury’s research team is now pushing the limits of this method. Jeongsoo Kim, a third-year Ph.D. student on the team, is imaging calibrated ラーメンベット 退会 samples of various sizes and ラーメンベット 退会 strengths, 3D printed with sub-micron scale features. By reconstructing the 3D structural profiles of these samples from ラーメンベット 退会 measurements and comparing them to the known printed distributions, Kim is devising inverse-ラーメンベット 退会 strategies that optimize reconstruction accuracy across a wide range of samples with varying ラーメンベット 退会 properties. These insights have significantly improved 3D reconstruction fidelity for various biologically ラーメンベット 退会 samples, such as C. elegans, organoids, and histopathology tissue sections.
"Tailoring the image-reconstruction method based on the sample's ラーメンベット 退会 complexity improves both imaging efficiency and accuracy, enabling better imaging capabilities into ラーメンベット 退会 biological tissues," said Kim.
Moving forward, Chowdhury’s ラーメンベット 退会 team will focus on applying this method to the challenging task of imaging tissue morphogenesis. This work promises to open new doors for scientists and could one day lead to basic-science and medical ラーメンベット 退会 by providing a deeper understanding of how tissues develop, regenerate, and respond to disease.
