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A Mechanism Underlying Most Common Cause of Epileptic Seizures Revealed
An interdisciplinary study shows that neurons carrying somatic mutations in MTOR can lead to focal epileptogenesis via non-cell-autonomous hyperexcitability of nearby nonmutated neurons During fetal development, cells should migrate to the outer edge of the brain to form critical connections for information transfer and regulation in the body. When even a few cells fail to move to the correct location, the neurons become disorganized and this results in focal cortical dysplasia. This condition is the most common cause of seizures that cannot be controlled with medication in children and the second most common cause in adults. Now, an interdisciplinary team studying neurogenetics, neural networks, and neurophysiology at KAIST has revealed how dysfunctions in even a small percentage of cells can cause disorder across the entire brain. They published their results on June 28 in Annals of Neurology. The work builds on a previous finding, also by a KAIST scientists, who found that focal cortical dysplasia was caused by mutations in the cells involved in mTOR, a pathway that regulates signaling between neurons in the brain. “Only 1 to 2% of neurons carrying mutations in the mTOR signaling pathway that regulates cell signaling in the brain have been found to include seizures in animal models of focal cortical dysplasia,” said Professor Jong-Woo Sohn from the Department of Biological Sciences. “The main challenge of this study was to explain how nearby non-mutated neurons are hyperexcitable.” Initially, the researchers hypothesized that the mutated cells affected the number of excitatory and inhibitory synapses in all neurons, mutated or not. These neural gates can trigger or halt activity, respectively, in other neurons. Seizures are a result of extreme activity, called hyperexcitability. If the mutated cells upend the balance and result in more excitatory cells, the researchers thought, it made sense that the cells would be more susceptible to hyperexcitability and, as a result, seizures. “Contrary to our expectations, the synaptic input balance was not changed in either the mutated or non-mutated neurons,” said Professor Jeong Ho Lee from the Graduate School of Medical Science and Engineering. “We turned our attention to a protein overproduced by mutated neurons.” The protein is adenosine kinase, which lowers the concentration of adenosine. This naturally occurring compound is an anticonvulsant and works to relax vessels. In mice engineered to have focal cortical dysplasia, the researchers injected adenosine to replace the levels lowered by the protein. It worked and the neurons became less excitable. “We demonstrated that augmentation of adenosine signaling could attenuate the excitability of non-mutated neurons,” said Professor Se-Bum Paik from the Department of Bio and Brain Engineering. The effect on the non-mutated neurons was the surprising part, according to Paik. “The seizure-triggering hyperexcitability originated not in the mutation-carrying neurons, but instead in the nearby non-mutated neurons,” he said. The mutated neurons excreted more adenosine kinase, reducing the adenosine levels in the local environment of all the cells. With less adenosine, the non-mutated neurons became hyperexcitable, leading to seizures. “While we need further investigate into the relationship between the concentration of adenosine and the increased excitation of nearby neurons, our results support the medical use of drugs to activate adenosine signaling as a possible treatment pathway for focal cortical dysplasia,” Professor Lee said. The Suh Kyungbae Foundation, the Korea Health Technology Research and Development Project, the Ministry of Health & Welfare, and the National Research Foundation in Korea funded this work. -Publication:Koh, H.Y., Jang, J., Ju, S.H., Kim, R., Cho, G.-B., Kim, D.S., Sohn, J.-W., Paik, S.-B. and Lee, J.H. (2021), ‘Non–Cell Autonomous Epileptogenesis in Focal Cortical Dysplasia’ Annals of Neurology, 90: 285 299. (https://doi.org/10.1002/ana.26149) -ProfileProfessor Jeong Ho Lee Translational Neurogenetics Labhttps://tnl.kaist.ac.kr/ Graduate School of Medical Science and Engineering KAIST Professor Se-Bum Paik Visual System and Neural Network Laboratory http://vs.kaist.ac.kr/ Department of Bio and Brain EngineeringKAIST Professor Jong-Woo Sohn Laboratory for Neurophysiology, https://sites.google.com/site/sohnlab2014/home Department of Biological SciencesKAIST Dr. Hyun Yong Koh Translational Neurogenetics LabGraduate School of Medical Science and EngineeringKAIST Dr. Jaeson Jang Ph.D.Visual System and Neural Network LaboratoryDepartment of Bio and Brain Engineering KAIST Sang Hyeon Ju M.D.Laboratory for NeurophysiologyDepartment of Biological SciencesKAIST
2021.08.26
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KAIST KPC4IR Presents the AI Global Guide for Healthcare
The benchmark for the responsible usage of AI technology in the healthcare sector will promote clarity and high standards for technological applications The KAIST Korea Policy Center for the Fourth Industrial Revolution (KPC4IR) published 'Using AI to Support Healthcare Decisions: A Guide for Society.' This global guide is designed to serve as a benchmark for the responsible usage of AI technologies, and will promote clarity and high standards for technological applications in the healthcare sector. The guide details what should be considered when making clinical decisions to help reduce the chances of the AI giving false or misleading results. The KPC4IR presented the guide in collaboration with the Lloyd’s Register Foundation Institute for the Public Understanding of Risk at the National University of Singapore (NUS IPUR) and Sense about Science, a non-profit organization in the UK specialized in science communication, during the 2021 SIG-KDD (Special Interest Group on Knowledge Discovery and Data Mining) Conference on August 15. AI technology is being widely used in the healthcare sector and has already proved its accuracy and efficiency in diagnosing and predicting diseases. Despite its huge impact on our daily lives in every sector of society, AI technology has some drawbacks and comes with risks, especially due to biased algorithms. “We focused on the ‘reliability’ of AI applications in the healthcare sector to make all data well represented, in good quality. The technology will eventually innovate to better serve the people’s new demand, especially critical demands for safety and precision in healthcare services. This global guide will help both developers and people’s understanding of the appropriate technology applications,” says Director So Young Kim at the KPC4IR. The guide, for instance, says that to scrutinize quality and reliability, the source of the data must be clearly known; the data must have been collected or selected for the purpose it’s being used for; the limitations and assumptions for that purpose have been clearly stated; the biases have been addressed; and it has been properly tested in the real world. It also reflects the importance of the representativeness of data that will affect the accuracy of the AI applications. “By being transparent and demonstrating the steps taken to check that the AI is reliable, researchers and developers can help give people confidence about providing their data,” the guide states. For this guide, the KPC4IR and its collaborators collected data after working with numerous experts from the Graduate School of AI at KAIST, the Science and Technology Policy Institute in Korea, Asan Medical Center in Seoul, Seoul National University Bundang Hospital, and AI solution companies.
2021.08.17
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Brain-Inspired Highly Scalable Neuromorphic Hardware Presented
Neurons and synapses based on single transistor can dramatically reduce the hardware cost and accelerate the commercialization of neuromorphic hardware KAIST researchers fabricated a brain-inspired highly scalable neuromorphic hardware by co-integrating single transistor neurons and synapses. Using standard silicon complementary metal-oxide-semiconductor (CMOS) technology, the neuromorphic hardware is expected to reduce chip cost and simplify fabrication procedures. The research team led by Yang-Kyu Choi and Sung-Yool Choi produced a neurons and synapses based on single transistor for highly scalable neuromorphic hardware and showed the ability to recognize text and face images. This research was featured in Science Advances on August 4. Neuromorphic hardware has attracted a great deal of attention because of its artificial intelligence functions, but consuming ultra-low power of less than 20 watts by mimicking the human brain. To make neuromorphic hardware work, a neuron that generates a spike when integrating a certain signal, and a synapse remembering the connection between two neurons are necessary, just like the biological brain. However, since neurons and synapses constructed on digital or analog circuits occupy a large space, there is a limit in terms of hardware efficiency and costs. Since the human brain consists of about 1011 neurons and 1014 synapses, it is necessary to improve the hardware cost in order to apply it to mobile and IoT devices. To solve the problem, the research team mimicked the behavior of biological neurons and synapses with a single transistor, and co-integrated them onto an 8-inch wafer. The manufactured neuromorphic transistors have the same structure as the transistors for memory and logic that are currently mass-produced. In addition, the neuromorphic transistors proved for the first time that they can be implemented with a ‘Janus structure’ that functions as both neuron and synapse, just like coins have heads and tails. Professor Yang-Kyu Choi said that this work can dramatically reduce the hardware cost by replacing the neurons and synapses that were based on complex digital and analog circuits with a single transistor. "We have demonstrated that neurons and synapses can be implemented using a single transistor," said Joon-Kyu Han, the first author. "By co-integrating single transistor neurons and synapses on the same wafer using a standard CMOS process, the hardware cost of the neuromorphic hardware has been improved, which will accelerate the commercialization of neuromorphic hardware,” Han added.This research was supported by the National Research Foundation (NRF) and IC Design Education Center (IDEC). -PublicationJoon-Kyu Han, Sung-Yool Choi, Yang-Kyu Choi, et al.“Cointegration of single-transistor neurons and synapses by nanoscale CMOS fabrication for highly scalable neuromorphic hardware,” Science Advances (DOI: 10.1126/sciadv.abg8836) -ProfileProfessor Yang-Kyu ChoiNano-Oriented Bio-Electronics Labhttps://sites.google.com/view/nobelab/ School of Electrical EngineeringKAIST Professor Sung-Yool ChoiMolecular and Nano Device Laboratoryhttps://www.mndl.kaist.ac.kr/ School of Electrical EngineeringKAIST
2021.08.05
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A Study Reveals What Triggers Lung Damage during COVID-19
A longitudinal study of macrophages from SARS-CoV-2 infected lungs offers new insights into dynamic immunological changes A KAIST immunology research team found that a specific subtype of macrophages that originated from blood monocytes plays a key role in the hyper-inflammatory response in SARS-CoV-2 infected lungs, by performing single-cell RNA sequencing of bronchoalveolar lavage fluid cells. This study provides new insights for understanding dynamic changes in immune responses to COVID-19. In the early phase of COVID-19, SARS-CoV-2 infected lung tissue and the immediate defense system is activated. This early and fast response is called ‘innate immunity,’ provided by immune cells residing in lungs. Macrophages are major cell types of the innate immune system of the lungs, and newly differentiated macrophages originating from the bloodstream also contribute to early defenses against viruses. Professor Su-Hyung Park and his collaborators investigated the quantitative and qualitative evaluation of immune responses in the lungs of SARS-CoV-2 infected ferrets. To overcome the limitations of research using patient-originated specimens, the researchers used a ferret infection model to obtain SARS-CoV-2 infected lungs sequentially with a defined time interval. The researchers analyzed the 10 subtypes of macrophages during the five-day course of SARS-CoV-2 infection, and found that infiltrating macrophages originating from activated monocytes in the blood were key players for viral clearance as well as damaged lung tissue. Moreover, they found that the differentiation process of these inflammatory macrophages resembled the immune responses in the lung tissue of severe COVID-19 patients. Currently, the research team is conducting a follow-up study to identify the dynamic changes in immune responses during the use of immunosuppressive agents to control hyper-inflammatory response called ‘cytokine storm’ in patients with COVID-19. Dr. Jeong Seok Lee, the chief medical officer at Genome Insight Inc., explained, “Our analysis will enhance the understanding of the early features of COVID-19 immunity and provide a scientific background for the more precise use of immunosuppressive agents targeting specific macrophage subtypes.” “This study is the first longitudinal study using sequentially obtained immune cells originating from SARS-CoV-2 infected lungs. The research describes the innate immune response to COVID-19 using single cell transcriptome data and enhances our understanding of the two phases of inflammatory responses,” Professor Park said. This work was supported by the Ministry of Health and Welfare and KAIST, and was published in Nature Communications on July 28. -PublicationSu-Hyung Park, Jeong Seok Lee, Su-Hyung Park et al. “Single-cell transcriptome of bronchoalverolar lavage fluid reveals sequential change of macrophages during SARS-CoV-2 infection in ferrets” Nature Communications (https://doi.org/10.1038/s41467-021-24807-0) -ProfileProfessor Su-Hyung ParkLaboratory of Translational Immunology and Vaccinologyhttps://ltiv.kaist.ac.kr/ Graduate School of Medical Science and EngineeringKAIST
2021.08.04
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3D Visualization and Quantification of Bioplastic PHA in a Living Bacterial Cell
3D holographic microscopy leads to in-depth analysis of bacterial cells accumulating the bacterial bioplastic, polyhydroxyalkanoate (PHA) A research team at KAIST has observed how bioplastic granule is being accumulated in living bacteria cells through 3D holographic microscopy. Their 3D imaging and quantitative analysis of the bioplastic ‘polyhydroxyalkanoate’ (PHA) via optical diffraction tomography provides insights into biosynthesizing sustainable substitutes for petroleum-based plastics. The bio-degradable polyester polyhydroxyalkanoate (PHA) is being touted as an eco-friendly bioplastic to replace existing synthetic plastics. While carrying similar properties to general-purpose plastics such as polyethylene and polypropylene, PHA can be used in various industrial applications such as container packaging and disposable products. PHA is synthesized by numerous bacteria as an energy and carbon storage material under unbalanced growth conditions in the presence of excess carbon sources. PHA exists in the form of insoluble granules in the cytoplasm. Previous studies on investigating in vivo PHA granules have been performed by using fluorescence microscopy, transmission electron microscopy (TEM), and electron cryotomography. These techniques have generally relied on the statistical analysis of multiple 2D snapshots of fixed cells or the short-time monitoring of the cells. For the TEM analysis, cells need to be fixed and sectioned, and thus the investigation of living cells was not possible. Fluorescence-based techniques require fluorescence labeling or dye staining. Thus, indirect imaging with the use of reporter proteins cannot show the native state of PHAs or cells, and invasive exogenous dyes can affect the physiology and viability of the cells. Therefore, it was difficult to fully understand the formation of PHA granules in cells due to the technical limitations, and thus several mechanism models based on the observations have been only proposed. The team of metabolic engineering researchers led by Distinguished Professor Sang Yup Lee and Physics Professor YongKeun Park, who established the startup Tomocube with his 3D holographic microscopy, reported the results of 3D quantitative label-free analysis of PHA granules in individual live bacterial cells by measuring the refractive index distributions using optical diffraction tomography. The formation and growth of PHA granules in the cells of Cupriavidus necator, the most-studied native PHA (specifically, poly(3-hydroxybutyrate), also known as PHB) producer, and recombinant Escherichia coli harboring C. necator PHB biosynthesis pathway were comparatively examined. From the reconstructed 3D refractive index distribution of the cells, the team succeeded in the 3D visualization and quantitative analysis of cells and intracellular PHA granules at a single-cell level. In particular, the team newly presented the concept of “in vivo PHA granule density.” Through the statistical analysis of hundreds of single cells accumulating PHA granules, the distinctive differences of density and localization of PHA granules in the two micro-organisms were found. Furthermore, the team identified the key protein that plays a major role in making the difference that enabled the characteristics of PHA granules in the recombinant E. coli to become similar to those of C. necator. The research team also presented 3D time-lapse movies showing the actual processes of PHA granule formation combined with cell growth and division. Movies showing the living cells synthesizing and accumulating PHA granules in their native state had never been reported before. Professor Lee said, “This study provides insights into the morphological and physical characteristics of in vivo PHA as well as the unique mechanisms of PHA granule formation that undergo the phase transition from soluble monomers into the insoluble polymer, followed by granule formation. Through this study, a deeper understanding of PHA granule formation within the bacterial cells is now possible, which has great significance in that a convergence study of biology and physics was achieved. This study will help develop various bioplastics production processes in the future.” This work was supported by the Technology Development Program to Solve Climate Changes on Systems Metabolic Engineering for Biorefineries (Grants NRF-2012M1A2A2026556 and NRF-2012M1A2A2026557) and the Bio & Medical Technology Development Program (Grant No. 2021M3A9I4022740) from the Ministry of Science and ICT (MSIT) through the National Research Foundation (NRF) of Korea to S.Y.L. This work was also supported by the KAIST Cross-Generation Collaborative Laboratory project. -PublicationSo Young Choi, Jeonghun Oh, JaeHwang Jung, YongKeun Park, and Sang Yup Lee. Three-dimensional label-free visualization and quantification of polyhydroxyalkanoates in individualbacterial cell in its native state. PNAS(https://doi.org./10.1073/pnas.2103956118) -ProfileDistinguished Professor Sang Yup LeeMetabolic Engineering and Synthetic Biologyhttp://mbel.kaist.ac.kr/ Department of Chemical and Biomolecular Engineering KAIST Endowed Chair Professor YongKeun ParkBiomedical Optics Laboratoryhttps://bmokaist.wordpress.com/ Department of PhysicsKAIST
2021.07.28
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Prof. Changho Suh Named the 2021 James L. Massey Awardee
Professor Changho Suh from the School of Electrical Engineering was named the recipient of the 2021 James L.Massey Award. The award recognizes outstanding achievement in research and teaching by young scholars in the information theory community. The award is named in honor of James L. Massey, who was an internationally acclaimed pioneer in digital communications and revered teacher and mentor to communications engineers. Professor Suh is a recipient of numerous awards, including the 2021 James L. Massey Research & Teaching Award for Young Scholars from the IEEE Information Theory Society, the 2019 AFOSR Grant, the 2019 Google Education Grant, the 2018 IEIE/IEEE Joint Award, the 2015 IEIE Haedong Young Engineer Award, the 2013 IEEE Communications Society Stephen O. Rice Prize, the 2011 David J. Sakrison Memorial Prize (the best dissertation award in UC Berkeley EECS), the 2009 IEEE ISIT Best Student Paper Award, the 2020 LINKGENESIS Best Teacher Award (the campus-wide Grand Prize in Teaching), and the four Departmental Teaching Awards (2013, 2019, 2020, 2021). Dr. Suh is an IEEE Information Theory Society Distinguished Lecturer, the General Chair of the Inaugural IEEE East Asian School of Information Theory, and a Member of the Young Korean Academy of Science and Technology. He is also an Associate Editor of Machine Learning for the IEEE Transactions on Information Theory, the Editor for the IEEE Information Theory Newsletter, a Column Editor for IEEE BITS the Information Theory Magazine, an Area Chair of NeurIPS 2021, and on the Senior Program Committee of IJCAI 2019–2021.
2021.07.27
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Prof. Junil Choi Receives the Neal Shepherd Memorial Award
Professor Junil Choi of the School of Electrical Engineering received the 2021 Neal Shepherd Memorial Award from the IEEE Vehicular Technology Society. The award recognizes the most outstanding paper relating to radio propagation published in major journals over the previous five years. Professor Cho, the recipient of the 2015 IEEE Signal Processing Society’s and the 2019 IEEE Communications Society’s Best Paper Award, was selected as the awardee for his paper titled “The Impact of Beamwidth on Temporal Channel Variation in Vehicular Channels and Its Implications” in IEEE Transaction on Vehicular Technology in 2017. In this paper, Professor Choi and his team derived the channel coherence time for a wireless channel as a function of the beamwidth, taking both Doppler effect and pointing error into consideration. The results showed that a nonzero optimal beamwidth exists that maximizes the channel coherence time. To reduce the impact of the overhead of doing realignment in every channel coherence time, the paper showed that the beams should be realigned every beam coherence time for the best performance. Professor Choi said, “It is quite an honor to receive this prestigious award following Professor Joonhyun Kang who won the IEEE VTS’s Jack Neubauer Memorial Award this year. It shows that our university’s pursuit of excellence in advanced research is being well recognized.”
2021.07.26
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VP Sang Yup Lee Honored with the Pony Chung Innovation Award
Vice President for Research Sang Yup Lee became the recipient of the Innovation Award by the Pony Chung Foundation that was established to honor the late Se-yung Chung, the former chairman of Hyundai Development Company. He will receive 200 million KRW in prize money. Chairman Chung developed Korea’s first domestically manufactured automobile, ‘Pony,’ in the mid-1970s that became the cornerstone of Korea’s auto industry today. Distinguished Professor Lee, from the Department of Chemical and Biomolecular Engineering, is a pioneering scholar in the field of systems metabolic engineering who developed various micro-organisms for producing a wide range of fuels, chemicals, materials, and natural compounds. He recently was elected as a foreign member of the Royal Society in the UK and is the first Korean ever elected into the National Academy of Inventors (NAI) in the US as well as one of 13 scholars elected as an International Member of both the National Academy of Sciences (NAS) and the National Academy of Engineering (NAE) in the US.
2021.07.13
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Professor Jung Receives the Hansong Science Award
Professor Yousung Jung of the Department of Chemical and Biomolecular Engineering has been selected as the recipient of the 5th Hansong Science Award in Chemistry. The award recognizes young and mid-career scholars who made outstanding achievement in physics, chemistry, and life sciences. Recipients receive 50 million KRW in prize money. Professor Jung was recognized for finding a new way to predict synthesis potentials when designing data-based materials and molecules through AI-powered inverse technology. Conventionally, new material discovery mainly relied on a method where the new materials were proposed by an expert’s intuition or experimental trial, then synthesized to measure the properties of the material before it was used. However, this method took a lot of time, which resulted in an inefficient discovery process. Professor Jung’s AI reverse design technology is reported to be more efficient for discovering new materials by finding crystal structures with desired properties using data and AI algorithms. "AI reverse design technology can accelerate the development of new materials and new drugs," Professor Jung said. "It can be used as an algorithm for future autonomous laboratories implemented by robots, algorithms, and data without human intervention," he added.
2021.07.13
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Professor Kang’s Team Receives the IEEE Jack Newbauer Memorial Award
Professor Joonhyuk Kang of the School of Electrical Engineering received the IEEE Vehicular Technology Society’s 2021 Jack Neubauer Memorial Award for his team’s paper published in IEEE Transactions on Vehicular Technology. The Jack Neubauer Memorial Award recognizes the best paper published in the IEEE Transactions on Vehicular Technology journal in the last five years. The team of authors, Professor Kang, Professor Sung-Ah Chung at Kyungpook National University, and Professor Osvaldo Simeone of King's College London reported their research titled Mobile Edge Computing via a UAV-Mounted Cloudlet: Optimization of Bit Allocation and Path Planning in IEEE Transactions on Vehicular Technology, Vol. 67, No. 3, pp. 2049-2063, in March 2018. Their paper shows how the trajectory of aircraft is optimized and resources are allocated when unmanned aerial vehicles perform edge computing to help mobile device calculations. This paper has currently recorded nearly 400 citations (based on Google Scholar). "We are very happy to see the results of proposing edge computing using unmanned aerial vehicles by applying optimization theory, and conducting research on trajectory and resource utilization of unmanned aerial vehicles that minimize power consumption," said Professor Kang.
2021.07.12
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Repurposed Drugs Present New Strategy for Treating COVID-19
Virtual screening of 6,218 drugs and cell-based assays identifies best therapeutic medication candidates A joint research group from KAIST and Institut Pasteur Korea has identified repurposed drugs for COVID-19 treatment through virtual screening and cell-based assays. The research team suggested the strategy for virtual screening with greatly reduced false positives by incorporating pre-docking filtering based on shape similarity and post-docking filtering based on interaction similarity. This strategy will help develop therapeutic medications for COVID-19 and other antiviral diseases more rapidly. This study was reported at the Proceedings of the National Academy of Sciences of the United States of America (PNAS). Researchers screened 6,218 drugs from a collection of FDA-approved drugs or those under clinical trial and identified 38 potential repurposed drugs for COVID-19 with this strategy. Among them, seven compounds inhibited SARS-CoV-2 replication in Vero cells. Three of these drugs, emodin, omipalisib, and tipifarnib, showed anti-SARS-CoV-2 activity in human lung cells, Calu-3. Drug repurposing is a practical strategy for developing antiviral drugs in a short period of time, especially during a global pandemic. In many instances, drug repurposing starts with the virtual screening of approved drugs. However, the actual hit rate of virtual screening is low and most of the predicted drug candidates are false positives. The research group developed effective filtering algorithms before and after the docking simulations to improve the hit rates. In the pre-docking filtering process, compounds with similar shapes to the known active compounds for each target protein were selected and used for docking simulations. In the post-docking filtering process, the chemicals identified through their docking simulations were evaluated considering the docking energy and the similarity of the protein-ligand interactions with the known active compounds. The experimental results showed that the virtual screening strategy reached a high hit rate of 18.4%, leading to the identification of seven potential drugs out of the 38 drugs initially selected. “We plan to conduct further preclinical trials for optimizing drug concentrations as one of the three candidates didn’t resolve the toxicity issues in preclinical trials,” said Woo Dae Jang, one of the researchers from KAIST. “The most important part of this research is that we developed a platform technology that can rapidly identify novel compounds for COVID-19 treatment. If we use this technology, we will be able to quickly respond to new infectious diseases as well as variants of the coronavirus,” said Distinguished Professor Sang Yup Lee. This work was supported by the KAIST Mobile Clinic Module Project funded by the Ministry of Science and ICT (MSIT) and the National Research Foundation of Korea (NRF). The National Culture Collection for Pathogens in Korea provided the SARS-CoV-2 (NCCP43326). -PublicationWoo Dae Jang, Sangeun Jeon, Seungtaek Kim, and Sang Yup Lee. Drugs repurposed for COVID-19 by virtual screening of 6,218 drugs and cell-based assay. Proc. Natl. Acad. Sci. U.S.A. (https://doi/org/10.1073/pnas.2024302118) -ProfileDistinguished Professor Sang Yup LeeMetabolic &Biomolecular Engineering National Research Laboratoryhttp://mbel.kaist.ac.kr Department of Chemical and Biomolecular EngineeringKAIST
2021.07.08
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Quantum Laser Turns Energy Loss into Gain
A new laser that generates quantum particles can recycle lost energy for highly efficient, low threshold laser applications Scientists at KAIST have fabricated a laser system that generates highly interactive quantum particles at room temperature. Their findings, published in the journal Nature Photonics, could lead to a single microcavity laser system that requires lower threshold energy as its energy loss increases. The system, developed by KAIST physicist Yong-Hoon Cho and colleagues, involves shining light through a single hexagonal-shaped microcavity treated with a loss-modulated silicon nitride substrate. The system design leads to the generation of a polariton laser at room temperature, which is exciting because this usually requires cryogenic temperatures. The researchers found another unique and counter-intuitive feature of this design. Normally, energy is lost during laser operation. But in this system, as energy loss increased, the amount of energy needed to induce lasing decreased. Exploiting this phenomenon could lead to the development of high efficiency, low threshold lasers for future quantum optical devices. “This system applies a concept of quantum physics known as parity-time reversal symmetry,” explains Professor Cho. “This is an important platform that allows energy loss to be used as gain. It can be used to reduce laser threshold energy for classical optical devices and sensors, as well as quantum devices and controlling the direction of light.” The key is the design and materials. The hexagonal microcavity divides light particles into two different modes: one that passes through the upward-facing triangle of the hexagon and another that passes through its downward-facing triangle. Both modes of light particles have the same energy and path but don’t interact with each other. However, the light particles do interact with other particles called excitons, provided by the hexagonal microcavity, which is made of semiconductors. This interaction leads to the generation of new quantum particles called polaritons that then interact with each other to generate the polariton laser. By controlling the degree of loss between the microcavity and the semiconductor substrate, an intriguing phenomenon arises, with the threshold energy becoming smaller as energy loss increases. This research was supported by the Samsung Science and Technology Foundation and Korea’s National Research Foundation. -PublicationSong,H.G, Choi, M, Woo, K.Y. Yong-Hoon Cho Room-temperature polaritonic non-Hermitian system with single microcavityNature Photonics (https://doi.org/10.1038/s41566-021-00820-z) -ProfileProfessor Yong-Hoon ChoQuantum & Nanobio Photonics Laboratoryhttp://qnp.kaist.ac.kr/ Department of PhysicsKAIST
2021.07.07
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