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KAIST Unveils New Possibilities for Treating Intractable Brain Tumors
< Photo 1. (From left) Professor Heung Kyu Lee, KAIST Department of Biological Sciences, and Dr. Keun Bon Ku >
Immunotherapy, which enhances the immune system's T cell response to eliminate cancer cells, has emerged as a key approach in cancer treatment. However, in the case of glioblastoma, an aggressive and treatment-resistant brain tumor, numerous clinical trials have failed to confirm their efficacy. Korean researchers have recently analyzed the mechanisms that cause T cell exhaustion, which is characterized by a loss of function or a weakened response following prolonged exposure to antigens in such intractable cancers, identifying key control factors in T cell activation and clarifying the mechanisms that enhance therapeutic effectiveness.
KAIST (represented by President Kwang Hyung Lee) announced on the 6th of November that Professor Heung Kyu Lee’s team from the Department of Biological Sciences, in collaboration with the Korea Research Institute of Chemical Technology (represented by President Young Kuk Lee), has confirmed improved survival rates in a glioblastoma mouse model. By removing the inhibitory Fc gamma receptor (FcγRIIB), the research team was able to restore the responsiveness of cytotoxic T cells to immune checkpoint inhibitors, leading to enhanced anticancer activity.
The research team examined the effect of FcγRIIB, an inhibitory receptor recently found in cytotoxic T cells, on tumor-infiltrating T cells and the therapeutic effectiveness of the anti-PD-1 immune checkpoint inhibitor.
< Figure 1. Study results on improved survival rate due to increased antitumor activity of anti-PD-1 treatment in inhibitory Fc gamma receptor(Fcgr2b) ablation mice with murine glioblastoma. >
Their findings showed that deleting FcγRIIB induced the increase of tumor antigen-specific memory T cells, which helps to suppress exhaustion, enhances stem-like qualities, and reactivates T cell-mediated antitumor immunity, particularly in response to anti-PD-1 treatment. Furthermore, FcγRIIB deletion led to an increase in antigen-specific memory T cells that maintained continuous infiltration into the tumor tissue.
This study presents a new therapeutic target for tumors unresponsive to immune checkpoint inhibitors and demonstrates that combining FcγRIIB inhibition with anti-PD-1 treatment can produce synergistic effects, potentially improving therapeutic outcomes for tumors like glioblastoma, which typically show resistance to anti-PD-1 therapy.
< Figure 2. Overview of the study on the enhanced response to anti-PD-1 therapy for glioblastoma brain tumors upon deletion of the inhibitory Fc gamma receptor (FcγRIIB) in tumor microenvironment. When the inhibitory Fc gamma receptor (FcγRIIB) of cytotoxic T cells is deleted, an increase in tumor-specific memory T cells (Ttsms) was observed. In addition, this T cell subset is identified as originating from the tumor-draining lymph nodes(TdLNs) and leads to persistent infiltration into the tumor tissue. Anti-PD-1 therapy leads to an increased anti-tumor immune response via Ttsms, which is confirmed by increased tumor cell toxicity and increased cell division and decreased cell de-migration indices. Ultimately, the increased cytotoxic T cell immune response leads to an increase in the survival rate of glioblastoma. >
Professor Heung Kyu Lee explained, "This study offers a way to overcome clinical failures in treating brain tumors with immune checkpoint therapy and opens possibilities for broader applications to other intractable cancers. It also highlights the potential of utilizing cytotoxic T cells for tumor cell therapy."
The study, led by Dr. Keun Bon Ku of KAIST (currently a senior researcher at the Korea Research Institute of Chemical Technology's Center for Infectious Disease Diagnosis and Prevention), along with Chae Won Kim, Yumin Kim, Byeong Hoon Kang, Jeongwoo La, In Kang, Won Hyung Park, Stephen Ahn, and Sung Ki Lee, was published online on October 26 in the Journal for ImmunoTherapy of Cancer, an international journal in tumor immunology and therapy from the Society for Immunotherapy of Cancer. (Paper title: “Inhibitory Fcγ receptor deletion enhances CD8 T cell stemness increasing anti-PD-1 therapy responsiveness against glioblastoma,” http://dx.doi.org/10.1136/jitc-2024-009449).
This research received support from the National Research Foundation of Korea, the Bio & Medical Technology Development Program, and the Samsung Science & Technology Foundation.
2024.11.15 View 359 -
KAIST Succeeds in the Real-time Observation of Organoids using Holotomography
Organoids, which are 3D miniature organs that mimic the structure and function of human organs, play an essential role in disease research and drug development. A Korean research team has overcome the limitations of existing imaging technologies, succeeding in the real-time, high-resolution observation of living organoids.
KAIST (represented by President Kwang Hyung Lee) announced on the 14th of October that Professor YongKeun Park’s research team from the Department of Physics, in collaboration with the Genome Editing Research Center (Director Bon-Kyoung Koo) of the Institute for Basic Science (IBS President Do-Young Noh) and Tomocube Inc., has developed an imaging technology using holotomography to observe live, small intestinal organoids in real time at a high resolution.
Existing imaging techniques have struggled to observe living organoids in high resolution over extended periods and often required additional treatments like fluorescent staining.
< Figure 1. Overview of the low-coherence HT workflow. Using holotomography, 3D morphological restoration and quantitative analysis of organoids can be performed. In order to improve the limited field of view, which is a limitation of the microscope, our research team utilized a large-area field of view combination algorithm and made a 3D restoration by acquiring multi-focus holographic images for 3D measurements. After that, the organoids were compartmentalized to divide the parts necessary for analysis and quantitatively evaluated the protein concentration measurable from the refractive index and the survival rate of the organoids. >
The research team introduced holotomography technology to address these issues, which provides high-resolution images without the need for fluorescent staining and allows for the long-term observation of dynamic changes in real time without causing cell damage.
The team validated this technology using small intestinal organoids from experimental mice and were able to observe various cell structures inside the organoids in detail. They also captured dynamic changes such as growth processes, cell division, and cell death in real time using holotomography.
Additionally, the technology allowed for the precise analysis of the organoids' responses to drug treatments, verifying the survival of the cells.
The researchers believe that this breakthrough will open new horizons in organoid research, enabling the greater utilization of organoids in drug development, personalized medicine, and regenerative medicine.
Future research is expected to more accurately replicate the in vivo environment of organoids, contributing significantly to a more detailed understanding of various life phenomena at the cellular level through more precise 3D imaging.
< Figure 2. Real-time organoid morphology analysis. Using holotomography, it is possible to observe the lumen and villus development process of intestinal organoids in real time, which was difficult to observe with a conventional microscope. In addition, various information about intestinal organoids can be obtained by quantifying the size and protein amount of intestinal organoids through image analysis. >
Dr. Mahn Jae Lee, a graduate of KAIST's Graduate School of Medical Science and Engineering, currently at Chungnam National University Hospital and the first author of the paper, commented, "This research represents a new imaging technology that surpasses previous limitations and is expected to make a major contribution to disease modeling, personalized treatments, and drug development research using organoids."
The research results were published online in the international journal Experimental & Molecular Medicine on October 1, 2024, and the technology has been recognized for its applicability in various fields of life sciences. (Paper title: “Long-term three-dimensional high-resolution imaging of live unlabeled small intestinal organoids via low-coherence holotomography”)
This research was supported by the National Research Foundation of Korea, KAIST Institutes, and the Institute for Basic Science.
2024.10.14 View 937 -
KAIST Changes the Paradigm of Drug Discovery with World's First Atomic Editing
In pioneering drug development, the new technology that enables the easy and rapid editing of key atoms responsible for drug efficacy has been regarded as a fundamental and "dream" technology, revolutionizing the process of discovering potential drug candidates. KAIST researchers have become the first in the world to successfully develop single-atom editing technology that maximizes drug efficacy.
On October 8th, KAIST (represented by President Kwang-Hyung Lee) announced that Professor Yoonsu Park’s research team from the Department of Chemistry successfully developed technology that enables the easy editing and correction of oxygen atoms in furan compounds into nitrogen atoms, directly converting them into pyrrole frameworks, which are widely used in pharmaceuticals.
< Image. Conceptual image illustrating the main idea of the research >
This research was published in the prestigious scientific journal Science on October 3rd under the title "Photocatalytic Furan-to-Pyrrole Conversion."
Many drugs have complex chemical structures, but their efficacy is often determined by a single critical atom. Atoms like oxygen and nitrogen play a central role in enhancing the pharmacological effects of these drugs, particularly against viruses.
This phenomenon, where the introduction of specific atoms into a drug molecule dramatically affects its efficacy, is known as the "Single Atom Effect." In leading-edge drug development, discovering atoms that maximize drug efficacy is key.
However, evaluating the Single Atom Effect has traditionally required multi-step, costly synthesis processes, as it has been difficult to selectively edit single atoms within stable ring structures containing oxygen or nitrogen.
Professor Park’s team overcame this challenge by introducing a photocatalyst that uses light energy. They developed a photocatalyst that acts as a “molecular scissor,” freely cutting and attaching five-membered rings, enabling single-atom editing at room temperature and atmospheric pressure—a world first.
The team discovered a new reaction mechanism in which the excited molecular scissor removes oxygen from furan via single-electron oxidation and then sequentially adds a nitrogen atom.
Donghyeon Kim and Jaehyun You, the study's first authors and candidates in KAIST’s integrated master's and doctoral program in the Department of Chemistry, explained that this technique offers high versatility by utilizing light energy to replace harsh conditions. They further noted that the technology enables selective editing, even when applied to complex natural products or pharmaceuticals. Professor Yoonsu Park, who led the research, remarked, "This breakthrough, which allows for the selective editing of five-membered organic ring structures, will open new doors for building libraries of drug candidates, a key challenge in pharmaceuticals. I hope this foundational technology will be used to revolutionize the drug development process."
The significance of this research was highlighted in the Perspective section of Science, a feature where a peer scientist of prominence outside of the project group provides commentary on an impactful research.
This research was supported by the National Research Foundation of Korea’s Creative Research Program, the Cross-Generation Collaborative Lab Project at KAIST, and the POSCO Science Fellowship of the POSCO TJ Park Foundation.
2024.10.11 View 1433 -
KAIST Develops Stretchable Displays Featuring 25% Expansion Without Image Distortion
Stretchable displays, praised for their spatial efficiency, design flexibility, and human-like flexibility, are seen as the next generation of display technology. A team of Korean researchers has developed a stretchable display that can expand by 25% while maintaining clear image quality without distortion. It can also stretch and contract up to 5,000 times at 15% expansion without any performance degradation, making it the first deformation-free stretchable display with a negative Poisson's ratio* developed in Korea.
*Poisson’s ratio of -1: A ratio where both width and length stretch equally, expressed as a negative value. A positive Poisson's ratio represents the ratio where horizontal stretching leads to vertical contraction, which is the case for most materials.
KAIST (represented by President Kwang-Hyung Lee) announced on the 20th of August that a research team led by Professor Byeong-Soo Bae of the Department of Materials Science and Engineering (Director of the Wearable Platform Materials Technology Center) , in collaboration with the Korea Institute of Machinery & Materials (President Seoghyeon Ryu), successfully developed a stretchable display substrate that suppresses image distortion through omnidirectional stretchability.
Currently, most stretchable displays are made with highly elastic elastomer* materials, but these materials possess a positive Poisson's ratio, causing unavoidable image distortion when the display is stretched.
*Elastomer: A polymer with elasticity similar to rubber.
To address this, the introduction of auxetic* meta-structures has been gaining attention. Unlike conventional materials, auxetic structures have a unique 'negative Poisson's ratio,' expanding in all directions when stretched in just one direction. However, traditional auxetic structures contain many empty spaces, limiting their stability and usability in display substrates.
*Auxetic structure: A special geometric structure that exhibits a negative Poisson's ratio.
To tackle the issue of image distortion, Professor Bae's research team developed a method to create a seamless surface for the auxetic meta-structure, achieving the ideal negative Poisson's ratio of -1 and overcoming the biggest challenge in auxetic meta-structures.
To overcome the second issue of elastic modulus*, the team inserted a textile made of glass fiber bundles with a diameter of just 25 micrometers (a quarter of the thickness of human hair) into the elastomer material. They then filled the empty spaces with the same elastomer, creating a flat and stable integrated film without gaps.
*Elastic Modulus: The ratio that indicates the extent of deformation when force is applied to a material. A higher elastic modulus means that the material is less likely to deform under force.
The research team theoretically identified that the difference in elasticity between the auxetic structure and the elastomer material directly influences the negative Poisson's ratio and successfully achieved an elasticity difference of over 230,000 times, producing a film with a Poisson's ratio of -1, the theoretical limit.
< Figure 2. Deformation of S-AUX film. a) Configurations and visualized principal strain distribution of the optimized S-AUX film at various strain rates. b) Biaxial stretching image. While pristine elastomer shrinks in the directions that were not stretched, S-AUX film developed in this study expands in all directions simultaneously while maintaining its original shape. >
Professor Byeong-Soo Bae, who led the study, explained, "Preventing image distortion using auxetic structures in stretchable displays is a core technology, but it has faced challenges due to the many empty spaces in the surface, making it difficult to use as a substrate. This research outcome is expected to significantly accelerate commercialization through high-resolution, distortion-free stretchable display applications that utilize the entire surface."
This study, co-authored by Dr. Yung Lee from KAIST’s Department of Materials Science and Engineering and Dr. Bongkyun Jang from the Korea Institute of Machinery & Materials, was published on August 20th in the international journal Nature Communications under the title "A seamless auxetic substrate with a negative Poisson's ratio of –1".
The research was supported by the Wearable Platform Materials Technology Center at KAIST, the Korea Institute of Machinery & Materials, and LG Display.
< Figure 3. Structural configuration of the distortion-free display components on the S-AUX film and a contour image of a micro-LED chip transferred onto the S-AUX film. >
< Figure 4. Schematic illustrations and photographic images of the S-AUX film-based image: distortion-free display in its stretched state and released state. >
2024.09.20 View 2171 -
Professor Jimin Park and Dr. Inho Kim join the ranks of the 2024 "35 Innovators Under 35" by the MIT Technology Review
< (From left) Professor Jimin Park of the Department of Chemical and Biomolecular Engineering and Dr. Inho Kim, a graduate of the Department of Materials Science and Engineering >
KAIST (represented by President Kwang-Hyung Lee) announced on the 13th of September that Professor Jimin Park from KAIST’s Department of Chemical and Biomolecular Engineering and Dr. Inho Kim, a graduate from the Department of Materials Science and Engineering (currently a postdoctoral researcher at Caltech), were selected by the MIT Technology Review as the 2024 "35 Innovators Under 35”.
The MIT Technology Review, first published in 1899 by the Massachusetts Institute of Technology, is the world’s oldest and most influential magazine on science and technology, offering in-depth analysis across various technology fields, expanding knowledge and providing insights into cutting-edge technology trends.
Since 1999, the magazine has annually named 35 innovators under the age of 35, recognizing young talents making groundbreaking contributions in modern technology fields. The recognition is globally considered a prestigious honor and a dream for young researchers in the science and technology community.
< Image 1. Introduction for Professor Jimin Park at the Meet 35 Innovators Under 35 Summit 2024 >
Professor Jimin Park is developing next-generation bio-interfaces that link artificial materials with living organisms, and is engaged in advanced research in areas such as digital healthcare and carbon-neutral compound manufacturing technologies. In 2014, Professor Park was also recognized as one of the ‘Asia Pacific Innovators Under 35’ by the MIT Technology Review, which highlights young scientists in the Asia-Pacific region.
Professor Park responded, “It’s a great honor to be named as one of the young innovators by the MIT Technology Review, a symbol of innovation with a long history. I will continue to pursue challenging, interdisciplinary research to develop next-generation interfaces that seamlessly connect artificial materials and living organisms, from atomic to system levels.”
< Image 2. Introduction for Dr. Inho Kim as the 2024 Innovator of Materials Science for 35 Innovators Under 35 >
Dr. Inho Kim, who earned his PhD from KAIST in 2020 under the supervision of Professor Sang Ouk Kim from the Department of Materials Science and Engineering, recently succeeded in developing a new artificial muscle using composite fibers. This new material is considered the most human-like muscle ever reported in scientific literature, while also being 17 times stronger than natural human muscle.
Dr. Kim is researching the application of artificial muscle fibers in next-generation wearable assistive devices that move more naturally, like humans or animals, noting that the fibers are lightweight, flexible, and exhibit conductivity during contraction, enabling real-time feedback. Recognized for this potential, Dr. Inho Kim was named one of the '35 Innovators Under 35' this year, making him the first researcher to win the honor with the research conducted at KAIST and a PhD earned from Korea.
Dr. Kim stated, “I aim to develop robots using these new materials that can replace today’s expensive and heavy exoskeleton suits by eliminating motors and rigid frames. This will significantly reduce costs and allow for better customization, making cutting-edge technology more accessible to those who need it most, like children with cerebral palsy.”
2024.09.13 View 1717 -
KAIST presents strategies for Holotomography in advanced bio research
Measuring and analyzing three-dimensional (3D) images of live cells and tissues is considered crucial in advanced fields of biology and medicine. Organoids, which are 3D structures that mimic organs, are particular examples that significantly benefits 3D live imaging. Organoids provide effective alternatives to animal testing in the drug development processes, and can rapidly determine personalized medicine. On the other hand, active researches are ongoing to utilize organoids for organ replacement.
< Figure 1. Schematic illustration of holotomography compared to X-ray CT. Similar to CT, they share the commonality of measuring the optical properties of an unlabeled specimen in three dimensions. Instead of X-rays, holotomography irradiates light in the visible range, and provides refractive index measurements of transparent specimens rather than absorptivity. While CT obtains three-dimensional information only through mechanical rotation of the irradiating light, holotomography can replace this by applying wavefront control technology in the visible range. >
Organelle-level observation of 3D biological specimens such as organoids and stem cell colonies without staining or preprocessing holds significant implications for both innovating basic research and bioindustrial applications related to regenerative medicine and bioindustrial applications.
Holotomography (HT) is a 3D optical microscopy that implements 3D reconstruction analogous to that of X-ray computed tomography (CT). Although HT and CT share a similar theoretical background, HT facilitates high-resolution examination inside cells and tissues, instead of the human body. HT obtains 3D images of cells and tissues at the organelle level without chemical or genetic labeling, thus overcomes various challenges of existing methods in bio research and industry. Its potential is highlighted in research fields where sample physiology must not be disrupted, such as regenerative medicine, personalized medicine, and infertility treatment.
< Figure 2. Label-free 3D imaging of diverse live cells. Time-lapse image of Hep3B cells illustrating subcellular morphology changes upon H2O2 treatment, followed by cellular recovery after returning to the regular cell culture medium. >
This paper introduces the advantages and broad applicability of HT to biomedical researchers, while presenting an overview of principles and future technical challenges to optical researchers. It showcases various cases of applying HT in studies such as 3D biology, regenerative medicine, and cancer research, as well as suggesting future optical development. Also, it categorizes HT based on the light source, to describe the principles, limitations, and improvements of each category in detail. Particularly, the paper addresses strategies for deepening cell and organoid studies by introducing artificial intelligence (AI) to HT.
Due to its potential to drive advanced bioindustry, HT is attracting interest and investment from universities and corporates worldwide. The KAIST research team has been leading this international field by developing core technologies and carrying out key application researches throughout the last decade.
< Figure 3. Various types of cells and organelles that make up the imaging barrier of a living intestinal organoid can be observed using holotomography. >
This paper, co-authored by Dr. Geon Kim from KAIST Research Center for Natural Sciences, Professor Ki-Jun Yoon's team from the Department of Biological Sciences, Director Bon-Kyoung Koo's team from the Institute for Basic Science (IBS) Center for Genome Engineering, and Dr. Seongsoo Lee's team from the Korea Basic Science Institute (KBSI), was published in 'Nature Reviews Methods Primers' on the 25th of July. This research was supported by the Leader Grant and Basic Science Research Program of the National Research Foundation, the Hologram Core Technology Development Grant of the Ministry of Science and ICT, the Nano and Material Technology Development Project, and the Health and Medical R&D Project of the Ministry of Health and Welfare.
2024.07.30 View 1586 -
The 3rd Global Entrepreneurship Summer School (GESS 2024) Successfully Completed in Silicon Valley
The 2024 Global Entrepreneurship Summer School (2024 KAIST GESS), hosted by the Office of Global Initiatives under the KAIST International Office (Director Man-Sung Yim), was held for the third time. This program allows students to visit Silicon Valley, a global startup hub, to directly experience its famous startup ecosystem and develop their capabilities for global expansion. A total of 20 students were selected through applications, interviews, final presentations, mentoring, and peer evaluations. Additionally, 17 students from the KAIST Impact MBA course at the KAIST Business School also participated.
Before starting the Silicon Valley program, participants received mentoring on business model development and pitching advice from a senior entrepreneur at KAIST for about two months, beginning last May. Afterward, they developed business items for each team at KAIST’s main campus in Daejeon. For seven days, starting from June 23rd, workshops were held under the themes of global entrepreneurship, learning through failure, capital and network, and startup culture at KOTRA Silicon Valley Trade Center, JP Morgan, and Plug and Play Tech Center. This program's lecture series provided prospective entrepreneurs with the opportunity to systematically learn the mindset and gain the experience needed to start a global business.
The participants also visited local companies and gained experience in the field of global technology startups. Visits included Bear Robotics (CEO John Ha), Soundable Health (CEO Cathering Song), ImpriMed (CEO Sungwon Lim), Phantom AI (CEO Hyunggi Cho), B Garage (CEO Aiden Kim), and Simple Steps (CEO Doyeon Kim). Lectures contained vivid experiences from Silicon Valley CEOs and company tours boosted the students' passion for entrepreneurship. In particular, Doyeon Kim, CEO of Simple Steps, which helps prevent career breaks for Korean female immigrants in Silicon Valley and allows talented female immigrants to demonstrate their abilities in society, said, “As a KAIST alumna entrepreneur, it was meaningful to share my experience with this generation of students who dream of starting a global business and creating social enterprises in the United States.”
This program also included a tour of Silicon Valley's big tech companies that have made a significant impact on the digital ecosystem through technological advancement and innovation. This included Broadcom, which maintains a strong global presence in the semiconductor and infrastructure software technology fields. At the invitation of Chairman Hock Tan, GESS participants had the opportunity to attend his lecture and ask questions. Chairman Tan, who received an honorary doctorate in engineering from KAIST last February, emphasized that experiencing failure and giving consistent effort over a long period of time are more important than anything else in order to grow as a global entrepreneur, and that technologies influencing the global market evolve over generations.
< Photo. Group photo of GESS 2024 participants at Broadcom with Chairman Hock Tan (center) ⓒBroadcom>
As part of this program, participants conducted a volunteer program called 'Let's play with AI+ Tech' with the Sunnyvale community in Silicon Valley and Foothill College to help grow together with the community. Through this program, GESS participants cultivated the virtues of a global leader. In this volunteer activity, low-income elementary school students and parents from the Sunnyvale community participated in chatbot training led by KAIST students, providing an opportunity to work with underprivileged groups in the local community.
In the final pitching event, the highlight of the program, local venture investors from Silicon Valley were invited as judges and evaluated the pitches for each team's business items. The participating students, who developed their own business models while receiving advice through face-to-face mentoring from a professional accelerator in Silicon Valley, showcased their creative and innovative ideas, presenting themselves as future global entrepreneurs. Merey Makhmutova (BS in Civil and Environmental Engineering) from the K-Bridge team, who won the final pitch, expressed her ambition: “Even before GESS pitch day, our team kept refining the pitch deck as we attended the lectures and benefitted from the mentoring. Our intense teamwork was a significant reason why we ultimately won first prize.” She added that K-Bridge aims to win an award at the upcoming UKC Pitching Competition and expressed her gratitude for being able to participate in this program. Arseniy Kan (BS in Electrical Engineering) from the KAIST Enablers team, who took second place, said, “The 2024 KAIST GESS Program became the most unforgettable and precious opportunity of my lifetime, and I dream of using this opportunity as a stepping stone to becoming a global entrepreneur.“ Additionally, Kangster (CEO Kang Kim), who won the Impact MBA final pitching session, had the opportunity to secure a meeting with a local investment company after their GESS final pitch.
The 2024 KAIST GESS was held in cooperation with the KAIST International Office, the KAIST College of Business, and Startup KAIST. Director Man-Sung Yim from the Office of Global Initiatives, who hosted the event, said, “KAIST students will grow into leaders with global influence and contribute to the international community by creating global value. At the same time, we hope to raise the international status of our university.” Professor Sangchan Park, who led the 17 Impact MBA students in this educational program, added, “Meeting with companies leading the global market and visiting Silicon Valley has been a valuable learning experience for students aiming to start a global startup.”
KAIST plans to continue promoting its global entrepreneurship education program by enriching its curriculum each year and helping students grow into entrepreneurs with the virtues of global leaders.
2024.07.03 View 3225 -
A 20-year-old puzzle solved: KAIST research team reveals the 'three-dimensional vortex' of zero-dimensional ferroelectrics
Materials that can maintain a magnetized state by themselves without an external magnetic field (i.e., permanent magnets) are called ferromagnets. Ferroelectrics can be thought of as the electric counterpart to ferromagnets, as they maintain a polarized state without an external electric field. It is well-known that ferromagnets lose their magnetic properties when reduced to nano sizes below a certain threshold. What happens when ferroelectrics are similarly made extremely small in all directions (i.e., into a zero-dimensional structure such as nanoparticles) has been a topic of controversy for a long time.
< (From left) Professor Yongsoo Yang, the corresponding author, and Chaehwa Jeong, the first author studying in the integrated master’s and doctoral program, of the KAIST Department of Physics >
The research team led by Dr. Yongsoo Yang from the Department of Physics at KAIST has, for the first time, experimentally clarified the three-dimensional, vortex-shaped polarization distribution inside ferroelectric nanoparticles through international collaborative research with POSTECH, SNU, KBSI, LBNL and University of Arkansas.
About 20 years ago, Prof. Laurent Bellaiche (currently at University of Arkansas) and his colleagues theoretically predicted that a unique form of polarization distribution, arranged in a toroidal vortex shape, could occur inside ferroelectric nanodots. They also suggested that if this vortex distribution could be properly controlled, it could be applied to ultra-high-density memory devices with capacities over 10,000 times greater than existing ones. However, experimental clarification had not been achieved due to the difficulty of measuring the three-dimensional polarization distribution within ferroelectric nanostructures.
The research team at KAIST successfully solved this 20-year-old challenge by implementing a technique called atomic electron tomography. This technique works by acquiring atomic-resolution transmission electron microscope images of the nanomaterials from multiple tilt angles, and then reconstructing them back into three-dimensional structures using advanced reconstruction algorithms. Electron tomography can be understood as essentially the same method with the CT scans used in hospitals to view internal organs in three dimensions; the KAIST team adapted it uniquely for nanomaterials, utilizing an electron microscope at the single-atom level.
< Figure 1. Three-dimensional polarization distribution of BaTiO3 nanoparticles revealed by atomic electron tomography. >(Left) Schematic of the electron tomography technique, which involves acquiring transmission electron microscope images at multiple tilt angles and reconstructing them into 3D atomic structures.(Center) Experimentally determined three-dimensional polarization distribution inside a BaTiO3 nanoparticle via atomic electron tomography. A vortex-like structure is clearly visible near the bottom (blue dot).(Right) A two-dimensional cross-section of the polarization distribution, thinly sliced at the center of the vortex, with the color and arrows together indicating the direction of the polarization. A distinct vortex structure can be observed.
Using atomic electron tomography, the team completely measured the positions of cation atoms inside barium titanate (BaTiO3) nanoparticles, a well-known ferroelectric material, in three dimensions. From the precisely determined 3D atomic arrangements, they were able to further calculate the internal three-dimensional polarization distribution at the single-atom level. The analysis of the polarization distribution revealed, for the first time experimentally, that topological polarization orderings including vortices, anti-vortices, skyrmions, and a Bloch point occur inside the 0-dimensional ferroelectrics, as theoretically predicted 20 years ago. Furthermore, it was also found that the number of internal vortices can be controlled depending on their sizes.
Prof. Sergey Prosandeev and Prof. Bellaiche (who proposed with other co-workers the polar vortex ordering theoretically 20 years ago), joined this collaboration and further proved that the vortex distribution results obtained from experiments are consistent with theoretical calculations.
By controlling the number and orientation of these polarization distributions, it is expected that this can be utilized into next-generation high-density memory device that can store more than 10,000 times the amount of information in the same-sized device compared to existing ones.
Dr. Yang, who led the research, explained the significance of the results: “This result suggests that controlling the size and shape of ferroelectrics alone, without needing to tune the substrate or surrounding environmental effects such as epitaxial strain, can manipulate ferroelectric vortices or other topological orderings at the nano-scale. Further research could then be applied to the development of next-generation ultra-high-density memory.”
This research, with Chaehwa Jeong from the Department of Physics at KAIST as the first author, was published online in Nature Communications on May 8th (Title: Revealing the Three-Dimensional Arrangement of Polar Topology in Nanoparticles).
The study was mainly supported by the National Research Foundation of Korea (NRF) Grants funded by the Korean Government (MSIT).
2024.05.31 View 3636 -
Revolutionary 'scLENS' Unveiled to Decode Complex Single-Cell Genomic Data
Unlocking biological information from complex single-cell genomic data has just become easier and more precise, thanks to the innovative 'scLENS' tool developed by the Biomedical Mathematics Group within the IBS Center for Mathematical and Computational Sciences led by Chief Investigator Jae Kyoung Kim, who is also a professor at KAIST. This new finding represents a significant leap forward in the field of single-cell transcriptomics.
Single-cell genomic analysis is an advanced technique that measures gene expression at the individual cell level, revealing cellular changes and interactions that are not observable with traditional genomic analysis methods. When applied to cancer tissues, this analysis can delineate the composition of diverse cell types within a tumor, providing insights into how cancer progresses and identifying key genes involved during each stage of progression.
Despite the immense potential of single-cell genomic analysis, handling the vast amount of data that it generates has always been challenging. The amount of data covers the expression of tens of thousands of genes across hundreds to thousands of individual cells. This not only results in large datasets but also introduces noise-related distortions, which arise in part due to current measurement limitations.
< Figure 1. Overview of scLENS (single-cell Low-dimensional embedding using the effective Noise Subtract) >
(Left) Current dimensionality reduction methods for scRNA-seq data involve conventional data preprocessing steps, such as log normalization, followed by manual selection of signals from the scaled data. However, this study reveals that the high levels of sparsity and variability in scRNA-seq data can lead to signal distortion during the data preprocessing, compromising the accuracy of downstream analyses.
(Right) To address this issue, the researchers integrated L2 normalization into the conventional preprocessing pipeline, effectively mitigating signal distortion. Moreover, they developed a novel signal detection algorithm that eliminates the need for user intervention by leveraging random matrix theory-based noise filtering and signal robustness testing. By incorporating these techniques, scLENS enables accurate and automated analysis of scRNA-seq data, overcoming the limitations of existing dimensionality reduction methods.
Corresponding author Jae Kyoung Kim highlighted, “There has been a remarkable advancement in experimental technologies for analyzing single-cell transcriptomes over the past decade. However, due to limitations in data analysis methods, there has been a struggle to fully utilize valuable data obtained through extensive cost and time."
Researchers have developed numerous analysis methods over the years to discern biological signals from this noise. However, the accuracy of these methods has been less than satisfactory. A critical issue is that determining signal and noise thresholds often depends on subjective decisions from the users.
The newly developed scLENS tool harnesses Random Matrix Theory and Signal robustness test to automatically differentiate signals from noise without relying on subjective user input.
First author Hyun Kim stated, "Previously, users had to arbitrarily decide the threshold for signal and noise, which compromised the reproducibility of analysis results and introduced subjectivity. scLENS eliminates this problem by automatically detecting signals using only the inherent structure of the data."
During the development of scLENS, researchers identified the fundamental reasons for inaccuracies in existing analysis methods. They found that commonly used data preprocessing methods distort both biological signals and noise. The new preprocessing approach that scLENS offers is free from such distortions.
By resolving issues related to noise threshold determined by subjective user choice and signal distortion in conventional data preprocessing, scLENS significantly outperforms existing methods in accuracy. Additionally, scLENS automates the laborious process of signal dimension selection, allowing researchers to extract biological signals conveniently and automatically.
CI Kim added, "scLENS solves major issues in single-cell transcriptome data analysis, substantially improving the accuracy and efficiency throughout the analysis process. This is a prime example of how fundamental mathematical theories can drive innovation in life sciences research, allowing researchers to more quickly and accurately answer biological questions and uncover secrets of life that were previously hidden."
This research was published in the international journal 'Nature Communications' on April 27.
Terminology
* Single-cell RNA sequencing (scRNA-seq): A technique used to measure gene expression levels in individual cells, providing insights into cell heterogeneity and rare cell types.
* Dimensionality reduction: A method to reduce the number of features or variables in a dataset while preserving the most important information, making data analysis more manageable and interpretable.
* Random matrix theory: A mathematical framework used to model and analyze the properties of large, random matrices, which can be applied to filter out noise in high-dimensional data.
* Signal robustness test: Among the signals, this test selects signals that are robust to the slight perturbation in data because real biological signals should be invariant for such slight modification in the data.
2024.05.09 View 2709 -
KAIST debuts “DreamWaQer” - a quadrupedal robot that can walk in the dark
- The team led by Professor Hyun Myung of the School of Electrical Engineering developed “DreamWaQ”, a deep reinforcement learning-based walking robot control technology that can walk in an atypical environment without visual and/or tactile information
- Utilization of “DreamWaQ” technology can enable mass production of various types of “DreamWaQers”
- Expected to be used in exploration of atypical environment involving unique circumstances such as disasters by fire.
A team of Korean engineering researchers has developed a quadrupedal robot technology that can climb up and down the steps and moves without falling over in uneven environments such as tree roots without the help of visual or tactile sensors even in disastrous situations in which visual confirmation is impeded due to darkness or thick smoke from the flames.
KAIST (President Kwang Hyung Lee) announced on the 29th of March that Professor Hyun Myung's research team at the Urban Robotics Lab in the School of Electrical Engineering developed a walking robot control technology that enables robust 'blind locomotion' in various atypical environments.
< (From left) Prof. Hyun Myung, Doctoral Candidates I Made Aswin Nahrendra, Byeongho Yu, and Minho Oh. In the foreground is the DreamWaQer, a quadrupedal robot equipped with DreamWaQ technology. >
The KAIST research team developed "DreamWaQ" technology, which was named so as it enables walking robots to move about even in the dark, just as a person can walk without visual help fresh out of bed and going to the bathroom in the dark. With this technology installed atop any legged robots, it will be possible to create various types of "DreamWaQers".
Existing walking robot controllers are based on kinematics and/or dynamics models. This is expressed as a model-based control method. In particular, on atypical environments like the open, uneven fields, it is necessary to obtain the feature information of the terrain more quickly in order to maintain stability as it walks. However, it has been shown to depend heavily on the cognitive ability to survey the surrounding environment.
In contrast, the controller developed by Professor Hyun Myung's research team based on deep reinforcement learning (RL) methods can quickly calculate appropriate control commands for each motor of the walking robot through data of various environments obtained from the simulator. Whereas the existing controllers that learned from simulations required a separate re-orchestration to make it work with an actual robot, this controller developed by the research team is expected to be easily applied to various walking robots because it does not require an additional tuning process.
DreamWaQ, the controller developed by the research team, is largely composed of a context estimation network that estimates the ground and robot information and a policy network that computes control commands. The context-aided estimator network estimates the ground information implicitly and the robot’s status explicitly through inertial information and joint information. This information is fed into the policy network to be used to generate optimal control commands. Both networks are learned together in the simulation.
While the context-aided estimator network is learned through supervised learning, the policy network is learned through an actor-critic architecture, a deep RL methodology. The actor network can only implicitly infer surrounding terrain information. In the simulation, the surrounding terrain information is known, and the critic, or the value network, that has the exact terrain information evaluates the policy of the actor network.
This whole learning process takes only about an hour in a GPU-enabled PC, and the actual robot is equipped with only the network of learned actors. Without looking at the surrounding terrain, it goes through the process of imagining which environment is similar to one of the various environments learned in the simulation using only the inertial sensor (IMU) inside the robot and the measurement of joint angles. If it suddenly encounters an offset, such as a staircase, it will not know until its foot touches the step, but it will quickly draw up terrain information the moment its foot touches the surface. Then the control command suitable for the estimated terrain information is transmitted to each motor, enabling rapidly adapted walking.
The DreamWaQer robot walked not only in the laboratory environment, but also in an outdoor environment around the campus with many curbs and speed bumps, and over a field with many tree roots and gravel, demonstrating its abilities by overcoming a staircase with a difference of a height that is two-thirds of its body. In addition, regardless of the environment, the research team confirmed that it was capable of stable walking ranging from a slow speed of 0.3 m/s to a rather fast speed of 1.0 m/s.
The results of this study were produced by a student in doctorate course, I Made Aswin Nahrendra, as the first author, and his colleague Byeongho Yu as a co-author. It has been accepted to be presented at the upcoming IEEE International Conference on Robotics and Automation (ICRA) scheduled to be held in London at the end of May. (Paper title: DreamWaQ: Learning Robust Quadrupedal Locomotion With Implicit Terrain Imagination via Deep Reinforcement Learning)
The videos of the walking robot DreamWaQer equipped with the developed DreamWaQ can be found at the address below.
Main Introduction: https://youtu.be/JC1_bnTxPiQ Experiment Sketches: https://youtu.be/mhUUZVbeDA0
Meanwhile, this research was carried out with the support from the Robot Industry Core Technology Development Program of the Ministry of Trade, Industry and Energy (MOTIE). (Task title: Development of Mobile Intelligence SW for Autonomous Navigation of Legged Robots in Dynamic and Atypical Environments for Real Application)
< Figure 1. Overview of DreamWaQ, a controller developed by this research team. This network consists of an estimator network that learns implicit and explicit estimates together, a policy network that acts as a controller, and a value network that provides guides to the policies during training. When implemented in a real robot, only the estimator and policy network are used. Both networks run in less than 1 ms on the robot's on-board computer. >
< Figure 2. Since the estimator can implicitly estimate the ground information as the foot touches the surface, it is possible to adapt quickly to rapidly changing ground conditions. >
< Figure 3. Results showing that even a small walking robot was able to overcome steps with height differences of about 20cm. >
2023.05.18 View 6604 -
Using light to throw and catch atoms to open up a new chapter for quantum computing
The technology to move and arrange atoms, the most basic component of a quantum computer, is very important to Rydberg quantum computing research. However, to place the atoms at the desired location, the atoms must be captured and transported one by one using a highly focused laser beam, commonly referred to as an optical tweezer. and, the quantum information of the atoms is likely to change midway.
KAIST (President Kwang Hyung Lee) announced on the 27th that a research team led by Professor Jaewook Ahn of the Department of Physics developed a technology to throw and receive rubidium atoms one by one using a laser beam.
The research team developed a method to throw and receive atoms which would minimize the time the optical tweezers are in contact with the atoms in which the quantum information the atoms carry may change. The research team used the characteristic that the rubidium atoms, which are kept at a very low temperature of 40μK below absolute zero, move very sensitively to the electromagnetic force applied by light along the focal point of the light tweezers.
The research team accelerated the laser of an optical tweezer to give an optical kick to an atom to send it to a target, then caught the flying atom with another optical tweezer to stop it. The atom flew at a speed of 65 cm/s, and traveled up to 4.2 μm. Compared to the existing technique of guiding the atoms with the optical tweezers, the technique of throwing and receiving atoms eliminates the need to calculate the transporting path for the tweezers, and makes it easier to fix the defects in the atomic arrangement. As a result, it is effective in generating and maintaining a large number of atomic arrangements, and when the technology is used to throw and receive flying atom qubits, it will be used in studying new and more powerful quantum computing methods that presupposes the structural changes in quantum arrangements.
"This technology will be used to develop larger and more powerful Rydberg quantum computers," says Professor Jaewook Ahn. “In a Rydberg quantum computer,” he continues, “atoms are arranged to store quantum information and interact with neighboring atoms through electromagnetic forces to perform quantum computing. The method of throwing an atom away for quick reconstruction the quantum array can be an effective way to fix an error in a quantum computer that requires a removal or replacement of an atom.”
The research, which was conducted by doctoral students Hansub Hwang and Andrew Byun of the Department of Physics at KAIST and Sylvain de Léséleuc, a researcher at the National Institute of Natural Sciences in Japan, was published in the international journal, Optica, 0n March 9th. (Paper title: Optical tweezers throw and catch single atoms).
This research was carried out with the support of the Samsung Science & Technology Foundation.
<Figure 1> A schematic diagram of the atom catching and throwing technique. The optical tweezer on the left kicks the atom to throw it into a trajectory to have the tweezer on the right catch it to stop it.
2023.03.28 View 4211 -
KAIST team develops smart immune system that can pin down on malignant tumors
A joint research team led by Professor Jung Kyoon Choi of the KAIST Department of Bio and Brain Engineering and Professor Jong-Eun Park of the KAIST Graduate School of Medical Science and Engineering (GSMSE) announced the development of the key technologies to treat cancers using smart immune cells designed based on AI and big data analysis. This technology is expected to be a next-generation immunotherapy that allows precision targeting of tumor cells by having the chimeric antigen receptors (CARs) operate through a logical circuit. Professor Hee Jung An of CHA Bundang Medical Center and Professor Hae-Ock Lee of the Catholic University of Korea also participated in this research to contribute joint effort.
Professor Jung Kyoon Choi’s team built a gene expression database from millions of cells, and used this to successfully develop and verify a deep-learning algorithm that could detect the differences in gene expression patterns between tumor cells and normal cells through a logical circuit. CAR immune cells that were fitted with the logic circuits discovered through this methodology could distinguish between tumorous and normal cells as a computer would, and therefore showed potentials to strike only on tumor cells accurately without causing unwanted side effects.
This research, conducted by co-first authors Dr. Joonha Kwon of the KAIST Department of Bio and Brain Engineering and Ph.D. candidate Junho Kang of KAIST GSMSE, was published by Nature Biotechnology on February 16, under the title Single-cell mapping of combinatorial target antigens for CAR switches using logic gates.
An area in cancer research where the most attempts and advances have been made in recent years is immunotherapy. This field of treatment, which utilizes the patient’s own immune system in order to overcome cancer, has several methods including immune checkpoint inhibitors, cancer vaccines and cellular treatments. Immune cells like CAR-T or CAR-NK equipped with chimera antigen receptors, in particular, can recognize cancer antigens and directly destroy cancer cells.
Starting with its success in blood cancer treatment, scientists have been trying to expand the application of CAR cell therapy to treat solid cancer. But there have been difficulties to develop CAR cells with effective killing abilities against solid cancer cells with minimized side effects. Accordingly, in recent years, the development of smarter CAR engineering technologies, i.e., computational logic gates such as AND, OR, and NOT, to effectively target cancer cells has been underway.
At this point in time, the research team built a large-scale database for cancer and normal cells to discover the exact genes that are expressed only from cancer cells at a single-cell level. The team followed this up by developing an AI algorithm that could search for a combination of genes that best distinguishes cancer cells from normal cells. This algorithm, in particular, has been used to find a logic circuit that can specifically target cancer cells through cell-level simulations of all gene combinations. CAR-T cells equipped with logic circuits discovered through this methodology are expected to distinguish cancerous cells from normal cells like computers, thereby minimizing side effects and maximizing the effects of chemotherapy.
Dr. Joonha Kwon, who is the first author of this paper, said, “this research suggests a new method that hasn’t been tried before. What’s particularly noteworthy is the process in which we found the optimal CAR cell circuit through simulations of millions of individual tumors and normal cells.” He added, “This is an innovative technology that can apply AI and computer logic circuits to immune cell engineering. It would contribute greatly to expanding CAR therapy, which is being successfully used for blood cancer, to solid cancers as well.”
This research was funded by the Original Technology Development Project and Research Program for Next Generation Applied Omic of the Korea Research Foundation.
Figure 1. A schematic diagram of manufacturing and administration process of CAR therapy and of cancer cell-specific dual targeting using CAR.
Figure 2. Deep learning (convolutional neural networks, CNNs) algorithm for selection of dual targets based on gene combination (left) and algorithm for calculating expressing cell fractions by gene combination according to logical circuit (right).
2023.03.09 View 6110