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Flexible Sensor-Integrated RFA Needle Leads to Smarter Medical Treatment
Clinical trial of flexible sensor-integrated radiofrequency ablation (RFA) needle tip monitors physical changes and steam pop Researchers have designed a thin polymeric sensor platform on a radiofrequency ablation needle to monitor temperature and pressure in real time. The sensors integrated onto 1.5 mm diameter needle tip have proven their efficacy during clinical tests and expect to provide a new opportunity for safer and more effective medical practices. The research was reported in Advanced Science as the frontispiece on August 5. Radiofrequency ablation (RFA) is a minimally invasive surgery technique for removing tumors and treating cardiovascular disease. During a procedure, an unintended audible explosion called ‘steam pop’ can occur due to the increased internal steam pressure in the ablation region. This phenomenon has been cited as a cause of various negative thermal and mechanical effects on neighboring tissue. Even more, the relationship between steam pop and cancer recurrence is still being investigated. Professor Inkyu Park said that his team’s integrated sensors reliably detected the occurrence of steam pop. The sensors also monitor rapidly spreading hot steam in tissue. It is expected that the diverse properties of tissue undergoing RFA could be checked by utilizing the physical sensors integrated on the needle. “We believe that the integrated sensors can provide useful information about a variety of medical procedures and accompanying environmental changes in the human body, and help develop more effective and safer surgical procedures,” said Professor Park. Professor Park’s team built a thin film type pressure and temperature sensor stack with a thickness of less than 10 μm using a microfabrication process. For the pressure sensor, the team used contact resistance changes between metal electrodes and a carbon nanotube coated polymeric membrane. The entire sensor array was thoroughly insulated with medical tubes to minimize any exposure of the sensor materials to external tissue and maximize its biocompatibility. During the clinical trial, the research team found that the accumulated hot steam is suddenly released during steam pops and this hot air spreads to neighboring tissue, which accelerates the ablation process. Furthermore, using in-situ ultrasound imaging and computational simulations, the research team could confirm the non-uniform temperature distribution around the RFA needle can be one of the primary reasons for the steam popping. Professor Park explained that various physical and chemical sensors for different targets can be added to create other medical devices and industrial tools. “This result will expand the usability and applicability of current flexible sensor technologies. We are also trying to integrate this sensor onto a 0.3mm diameter needle for in-vivo diagnosis applications and expect that this approach can be applied to other medical treatments as well as the industrial field,” added Professor Park. This study was supported by the National Research Foundation of Korea. -PublicationJaeho Park, Jinwoo Lee, Hyo Keun Lim, Inkyu Park et al. “Real-Time Internal Steam Pop Detection during Radiofrequency Ablation with a Radiofrequency Ablation Needle Integrated with a Temperature and Pressure Sensor: Preclinical and clinical pilot tests," Advanced Science (https://doi/org/10.1002/advs.202100725) on August 5, 2021 -ProfileProfessor Inkyu ParkMicro & Nano Tranducers Laboratory http://mintlab1.kaist.ac.kr/ Department of Mechanical EngineeringCollege of EngineeringKAIST
KAIST Entrepreneurial Partnership to Accelerate Startups and Venture Ecosystem
KAIST will launch the KAIST Entrepreneurial Partnership (KEP) program, which connects faculty members who own technology with those who want to launch startup. The program encourages open innovation startups using strategies tailored to market-client demand requirements. This is also one of efforts to help realize ‘one startup per lab,’ initiated by President Kwang Hyung Lee’s new innovation strategy. KEP also aims to introduce the best technologies developing at KAIST to startups and to raise the success rate of technology commercialization. The program will match KAIST faculty and student entrepreneur candidates with parties enrolled in the new Entrepreneur in Residence and Entrepreneurial Partner programs. Each team will be given a six-month test period with funding support. KAIST will invite entrepreneurial experts from both technology and management fields to support the program participants. Around 30 experts with experience in developing new businesses, startups, and investments in large corporations or venture companies will be recruited as entrepreneurial partners. They will offer support for research and business development (R&BD), technology marketing, attracting venture investment from corporations, mergers and acquisitions, and business openings. A survey showed that KAIST members who are interested in starting a business are experiencing difficulties finding an entrepreneurial expert (72.2%), with the complicated startup approval procedures (33.3%), and their lack of knowledge on entrepreneurship and funding (27.8%). The KEP program hopes to encourage KAIST faculty members and students who have well-developed business ideas and the appropriate technology but lack the capabilities to realize and develop them into a business. Associate Vice President of Startups Young-Tae Kim said, “We will develop KEP into KAIST’s distinct entrepreneurial support system and produce exemplary outcomes of faculty and student startups. We will spread the startup DNA and lead the building of a virtuous cycle between entrepreneurship and the venture ecosystem.”
Deep Learning Framework to Enable Material Design in Unseen Domain
Researchers propose a deep neural network-based forward design space exploration using active transfer learning and data augmentation A new study proposed a deep neural network-based forward design approach that enables an efficient search for superior materials far beyond the domain of the initial training set. This approach compensates for the weak predictive power of neural networks on an unseen domain through gradual updates of the neural network with active transfer learning and data augmentation methods. Professor Seungwha Ryu believes that this study will help address a variety of optimization problems that have an astronomical number of possible design configurations. For the grid composite optimization problem, the proposed framework was able to provide excellent designs close to the global optima, even with the addition of a very small dataset corresponding to less than 0.5% of the initial training data-set size. This study was reported in npj Computational Materials last month. “We wanted to mitigate the limitation of the neural network, weak predictive power beyond the training set domain for the material or structure design,” said Professor Ryu from the Department of Mechanical Engineering. Neural network-based generative models have been actively investigated as an inverse design method for finding novel materials in a vast design space. However, the applicability of conventional generative models is limited because they cannot access data outside the range of training sets. Advanced generative models that were devised to overcome this limitation also suffer from weak predictive power for the unseen domain. Professor Ryu’s team, in collaboration with researchers from Professor Grace Gu’s group at UC Berkeley, devised a design method that simultaneously expands the domain using the strong predictive power of a deep neural network and searches for the optimal design by repetitively performing three key steps. First, it searches for few candidates with improved properties located close to the training set via genetic algorithms, by mixing superior designs within the training set. Then, it checks to see if the candidates really have improved properties, and expands the training set by duplicating the validated designs via a data augmentation method. Finally, they can expand the reliable prediction domain by updating the neural network with the new superior designs via transfer learning. Because the expansion proceeds along relatively narrow but correct routes toward the optimal design (depicted in the schematic of Fig. 1), the framework enables an efficient search. As a data-hungry method, a deep neural network model tends to have reliable predictive power only within and near the domain of the training set. When the optimal configuration of materials and structures lies far beyond the initial training set, which frequently is the case, neural network-based design methods suffer from weak predictive power and become inefficient. Researchers expect that the framework will be applicable for a wide range of optimization problems in other science and engineering disciplines with astronomically large design space, because it provides an efficient way of gradually expanding the reliable prediction domain toward the target design while avoiding the risk of being stuck in local minima. Especially, being a less-data-hungry method, design problems in which data generation is time-consuming and expensive will benefit most from this new framework. The research team is currently applying the optimization framework for the design task of metamaterial structures, segmented thermoelectric generators, and optimal sensor distributions. “From these sets of on-going studies, we expect to better recognize the pros and cons, and the potential of the suggested algorithm. Ultimately, we want to devise more efficient machine learning-based design approaches,” explained Professor Ryu.This study was funded by the National Research Foundation of Korea and the KAIST Global Singularity Research Project. -Publication Yongtae Kim, Youngsoo, Charles Yang, Kundo Park, Grace X. Gu, and Seunghwa Ryu, “Deep learning framework for material design space exploration using active transfer learning and data augmentation,” npj Computational Materials (https://doi.org/10.1038/s41524-021-00609-2) -Profile Professor Seunghwa Ryu Mechanics & Materials Modeling Lab Department of Mechanical Engineering KAIST
MCM Utilized at Residential Treatment Center in Gyeonggi
The Mobile Clinic Module (MCM) developed by the KAIST Action for Respiratory Epidemics was installed at special residential treatment center in Gyeonggi Province on September 13. The MCM is an isolate negative pressure unit fitted with high-quality medical equipment, developed by Professor Taek-Jin Nam of the Department of Industrial Design under the KAIST New Deal R&D Initiative. This is also a part of the Korean Disease Control Package Development Project from last July. In January, a ward with four beds for critical care was installed at the Korea Institute for Radiological & Medical Sciences in Seoul for a trial operation, and two mild cases were treated there. It was also implemented as an isolated negative pressure unit in the Daejeon Konyang University Hospital emergency room in June, and has treated 138 cases since. The special residential treatment center installed in the Gyeonggi Provincial Academy gymnasium, which consists of 28 beds in 14 rooms (double occupancy) and a multipurpose room (for X-rays and treatment), is to remain open through October 10. Unlike existing treatment centers that have quarantined COVID-19 patients for two weeks, the Gyeonggi MCM will act as a self-treatment-associated short-term treatment center. While in self-treatment, patients showing symptoms requiring special attention will be moved to the MCM, followed by short-term hospitalization of 1-3 days for observation before further measures are taken. Patients can be treated using the MCM’s own treatment capacities, including in-person and oxygen treatment, X-rays, and IVs. There are individual bathrooms in each room, and the pressure, ventilation, and the automatic opening and closing of the entrance can be centrally monitored and controlled. Patients showing symptoms during treatment will be moved to a specially designated hospital for critical care, and will return to the self-treatment center if no further abnormalities are reported. The Gyeonggi Provincial Medical Center’s Ansung Hospital will take charge of operating the special treatment center. Each day, one or two doctors, three nurses, two nursing assistants, one administrative staff member, two or three disinfection specialists, and a medical imaging engineer will work in three shifts. There will also be about 20 additional specially designated staff members including KAIST researchers, firefighters, and police officers. The MCM was internationally recognized as an excellent medical facility not only for its functionality, economic feasibility, and utility, but also for its unique design and aesthetics. It received two Best of Best awards at the Red Dot Award in product design and Communication Design in user interface. By running this special treatment center, KAIST will conduct research on how to build an optimized model for efficient negative pressure medical units. This research is expected to lead to advances in waste water treatment systems, mobile bathrooms optimized for infectious cases, and MCM user interfaces for electronic devices, etc. Professor Taek-Jin Nam, the general director of the project and design, said “if there is a gymnasium available, we can convert it into a special treatment center fitted with a waste water treatment system, and pressure equipment in two weeks even without additional infrastructure.” The head of the KAIST New Deal R&D Initiative Choongsik Bae said, “our MCM research started in July of last year, and in just over a year, it has become a successful and innovative case that has undergone trials and become commercialized in a short period of time.” He added, “In response to COVID-19, KAIST is conducting research and empirical studies, not just in relation to the MCM, but in other areas of disease control as well.” Based on the excellent disease control technologies developed by KAIST research teams, the KAIST Action for Respiratory Epidemics is conducting technology transfers and industrialization, and is developing a Korean disease control package model
Digital Big Bang, Metaverse Technologies
The GSI Forum 2021 will explore the potential of new metaverse technologies that will change our daily lives KAIST will be hosting a live online international forum on Sept.8 at 9 am (KST) through its KAIST YouTube channel. The forum will explore global trends regarding metaverse technology innovations and applications and discuss how we can build a new technology ecosystem. Titled `Digital Big Bang, Metaverse Technology,' the Global Strategy Institute-International Forum 2021 will be the fourth event of its kind, following the three international forums held in 2020. The forum will delve into the development trends of metaverse platforms and AR/VR technologies and gather experts to discuss how such technologies could transform multiple aspects of our future, including education. President Kwang Hyung Lee explains in his opening remarks that new technologies are truly opening a new horizon for our lives, saying, “In the education sector, digital technology will also create new opportunities to resolve the longstanding pedagogical shortfalls of one-way knowledge delivery systems. New digital technologies will help to unlock the creativity of our students. Education tailored to the students’ individual levels will not only help them accumulate knowledge but improve their ability to use it. Universities around the world are now at the same starting line. We should carve out our own distinct metaverse that is viable for human interactions and diverse technological experiences that promote students’ creativity and collaborative minds.” Minster of Science and ICT Hyesook Lim will introduce how the Korean government is working to develop metaverse industries as a new potential engine of growth for the future in her welcoming remarks. The government’s efforts include collaborations with the private sector, investments in R&D, the development of talent, and regulatory reforms. Minister Lim will also emphasize the importance of national-level discussions regarding the establishment of a metaverse ecosystem and long-term value creation. The organizers have invited global experts to share their knowledge and insights. Kidong Bae, who is in charge of the KT Enterprise Project and ‘Metaverse One Team’ will talk about the current trends in the metaverse market and their implications, as well as KT’s XR technology references. He will also introduce strategies to establish and utilize a metaverse ecosystem, and highlight their new technologies as a global leader in 5G networks. Jinha Lee, co-founder and CPO of the American AR solution company Spatial, will showcase a remote collaboration office that utilizes AR technology as a potential solution for collaborative activities in the post-COVID-19 era, where remote working is the ‘new normal.’ Furthermore, Lee will discuss how future workplaces that are not limited by space or distance will affect our values and creativity. Professor Frank Steinicke from the University of Hamburg will present the ideal form of next-generation immersive technology that combines intelligent virtual agents, mixed reality, and IoT, and discuss his predictions for how the future of metaverse technology will be affected. Marco Tempest, a creative technologist at NASA and a Director’s Fellow at the MIT Media Lab, will also be joining the forum as a plenary speaker. Tempest will discuss the potential of immersive technology in media, marketing, and entertainment, and will propose a future direction for immersive technology to enable the sharing of experiences, emotions, and knowledge. Other speakers include Beomjoo Kim from Unity Technologies Korea, Professor Woontaek Woo from the Graduate School of Culture Technology at KAIST, Vice President of Global Sales at Labster Joseph Ferraro, and CEO of 3DBear Jussi Kajala. They will make presentations on metaverse technology applications for future education. The keynote session will also have an online panel consisting of 50 domestic and overseas metaverse specialists, scientists, and teachers. The forum will hold a Q&A and discussion session where the panel members can ask questions to the keynote speakers regarding the prospects of metaverse and immersive technologies for education. GSI Director Hoon Sohn stated, "KAIST will seize new opportunities that will arise in a future centered around metaverse technology and will be at the forefront to take advantage of the growing demand for innovative science and technology in non-contact societies. KAIST will also play a pivotal role in facilitating global cooperation, which will be vital to establish a metaverse ecosystem.”
Quantum Emitters: Beyond Crystal Clear to Single-Photon Pure
‘Nanoscale Focus Pinspot’ can quench only the background noise without changing the optical properties of the quantum emitter and the built-in photonic structure Photons, fundamental particles of light, are carrying these words to your eyes via the light from your computer screen or phone. Photons play a key role in the next-generation quantum information technology, such as quantum computing and communications. A quantum emitter, capable of producing a single, pure photon, is the crux of such technology but has many issues that have yet to be solved, according to KAIST researchers. A research team under Professor Yong-Hoon Cho has developed a technique that can isolate the desired quality emitter by reducing the noise surrounding the target with what they have dubbed a ‘nanoscale focus pinspot.’ They published their results on June 24 in ACS Nano. “The nanoscale focus pinspot is a structurally nondestructive technique under an extremely low dose ion beam and is generally applicable for various platforms to improve their single-photon purity while retaining the integrated photonic structures,” said lead author Yong-Hoon Cho from the Department of Physics at KAIST. To produce single photons from solid state materials, the researchers used wide-bandgap semiconductor quantum dots — fabricated nanoparticles with specialized potential properties, such as the ability to directly inject current into a small chip and to operate at room temperature for practical applications. By making a quantum dot in a photonic structure that propagates light, and then irradiating it with helium ions, researchers theorized that they could develop a quantum emitter that could reduce the unwanted noisy background and produce a single, pure photon on demand. Professor Cho explained, “Despite its high resolution and versatility, a focused ion beam typically suppresses the optical properties around the bombarded area due to the accelerated ion beam’s high momentum. We focused on the fact that, if the focused ion beam is well controlled, only the background noise can be selectively quenched with high spatial resolution without destroying the structure.” In other words, the researchers focused the ion beam on a mere pin prick, effectively cutting off the interactions around the quantum dot and removing the physical properties that could negatively interact with and degrade the photon purity emitted from the quantum dot. “It is the first developed technique that can quench the background noise without changing the optical properties of the quantum emitter and the built-in photonic structure,” Professor Cho asserted. Professor Cho compared it to stimulated emission depletion microscopy, a technique used to decrease the light around the area of focus, but leaving the focal point illuminated. The result is increased resolution of the desired visual target. “By adjusting the focused ion beam-irradiated region, we can select the target emitter with nanoscale resolution by quenching the surrounding emitter,” Professor Cho said. “This nanoscale selective-quenching technique can be applied to various material and structural platforms and further extended for applications such as optical memory and high-resolution micro displays.” Korea’s National Research Foundation and the Samsung Science and Technology Foundation supported this work. -PublicationMinho Choi, Seongmoon Jun, and Yong-Hoon Cho et al. ACS Nano‘Nanoscale Focus Pinspot for High-Purity Quantum Emitters via Focused-Ion-Beam-Induced Luminescence Quenching,’(https://pubs.acs.org/doi/10.1021/acsnano.1c00587) -ProfileProfessor Yong-Hoon ChoQuantum & Nanobio Photonics Laboratoryhttp://qnp.kaist.ac.kr/ Department of PhysicsKAIST
Genomic Data Reveals New Insights into Human Embryonic Development
KAIST researchers have used whole-genome sequencing to track the development from a single fertilized-egg to a human body Genomic scientists at KAIST have revealed new insights into the process of human embryonic development using large-scale, whole-genome sequencing of cells and tissues from adult humans. The study, published in Nature on Aug.25, is the first to analyse somatic mutations in normal tissue across multiple organs within and between humans. An adult human body comprises trillions of cells of more than 200 types. How a human develops from a single fertilized egg to a fully grown adult is a fundamental question in biomedical science. Due to the ethical challenges of performing studies on human embryos, however, the details of this process remain largely unknown. To overcome these issues, the research team took a different approach. They analysed genetic mutations in cells taken from adult human post-mortem tissue. Specifically, they identified mutations that occur spontaneously in early developmental cell divisions. These mutations, also called genomic scars, act like unique genetic fingerprints that can be used to trace the embryonic development process. The study, which looked at 334 single-cell colonies and 379 tissue samples from seven recently deceased human body donors, is the largest single-cell, whole-genome analysis carried out to date. The researchers examined the genomic scars of each individual in order to reconstruct their early embryonic cellular dynamics. The result revealed several key characteristics of the human embryonic development process. Firstly, mutation rates are higher in the first cell division, but then decrease to approximately one mutation per cell during later cell division. Secondly, early cells contributed unequally to the development of the embryo in all informative donors, for example, at the two-cell stage, one of the cells always left more progeny cells than the other. The ratio of this was different from person to person, implying that the process varies between individuals and is not fully deterministic. The researchers were also able to deduce the timing of when cells begin to differentiate into individual organ-specific cells. They found that within three days of fertilization, embryonic cells began to be distributed asymmetrically into tissues for the left and right sides of the body, followed by differentiation into three germ layers, and then differentiation into specific tissues and organs. “It is an impressive scientific achievement that, within 20 years of the completion of human genome project, genomic technology has advanced to the extent that we are now able to accurately identify mutations in a single-cell genome,” said Professor Young Seok Ju from the Graduate School of Medical Science and Engineering at KAIST. “This technology will enable us to track human embryogenesis at even higher resolutions in the future.” The techniques used in this study could be used to improve our understanding of rare diseases caused by abnormalities in embryonic development, and to design new precision diagnostics and treatments for patients. The research was completed in collaboration with Kyungpook National University Hospital, the Korea Institute of Science and Technology Information, Catholic University of Korea School of Medicine, Genome Insights Inc, and Immune Square Inc. This work was supported by the Suh Kyungbae Foundation, the Ministry of Health and Welfare of Korea, the National Research Foundastion of Korea. -PublicationSeongyeol Park, Nanda Mali, Ryul Kim et al. ‘Clonal dynamics in early human embryogenesis inferred from somatic mutation’ Nature Online ahead of print, Aug. 25, 2021 (https://doi.org/10.1038/s41586-021-03786-8) -ProfileProfessor Young Seok JuLab of Cancer Genomics (https://www.julab.kaist.ac.kr/)Graduate School of Medical Science and EngineeringKAIST
Aline and Blow-yancy Win the Red Dot Design Awards: Brand & Communications Design 2021
‘Aline’ and ‘Blow-yancy’ developed by Professor Sang Su Lee’s team at the Department of Industrial Design won the Red Dot Design Awards in Brand & Communications Design. Aline is a mobile investment portfolio application used in the NH Investment & Securities Co. Blow-yancy is a suva diving VR device for neutral buoyancy training.Professor Lee sought ‘sustainability’ while developing Aline to meet the growing awareness of ESG (environmental, social, and governance) investing. ESG investing relies on independent ratings that help consumers assess a company’s behavior and policies when it comes to its social impact. Aline’s personal value index with six main criteria translates values into sustainable finance. By gathering data from the initial survey and regular value updates, the index is weighted according to the user’s values. Based on the index, the investment portfolio will be adjusted, and consumption against the values will be tracked. Blow-yancy is a diving VR device for neutral buoyancy training. Blow-yancy’s VR mask helps divers feel like they are wearing an actual diving mask. Users can breathe through a regulator with a built-in breathing sensor. It allows training like actual diving without going into the water, therefore enabling safer diving. “We got an idea that about 74% of scuba divers come into contact with corals underwater at least once and that can cause an emergency situation. Divers who cannot maintain neutral buoyance will experience a tough time avoiding them,” said Professor Lee. The hardware consists of a nose covering VR mask, a regulator with a built-in breath sensor, and a controller for virtual BCD control. Blow-yancy’s five virtual missions were organized according to the diving process required by PADI, a professional diving education institute. Professor Lee’s team already received eight recognitions at the iF Design Award in April. Professor Lee said, “We will continue to develop the best UX design items that will improve our global recognition.”
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
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.
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
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
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