본문 바로가기
대메뉴 바로가기
KAIST
Newsletter Vol.23
Receive KAIST news by email!
View
Subscribe
Close
Type your e-mail address here.
Subscribe
Close
KAIST
NEWS
유틸열기
홈페이지 통합검색
-
검색
KOREAN
메뉴 열기
IT
by recently order
by view order
'Jumping Genes' Found to Alter Human Colon Genomes, Offering Insights into Aging and Tumorigenesis
The Korea Advanced Institute of Science and Technology (KAIST) and their collaborators have conducted a groundbreaking study targeting 'jumping genes' in the entire genomes of the human large intestine. Published in Nature on May 18 2023, the research unveils the surprising activity of 'Long interspersed nuclear element-1 (L1),' a type of jumping gene previously thought to be mostly dormant in human genomes. The study shows that L1 genes can become activated and disrupt genomic functions throughout an individual's lifetime, particularly in the colorectal epithelium. (Paper Title: Widespread somatic L1 retrotransposition in normal colorectal epithelium, https://www.nature.com/articles/s41586-023-06046-z) With approximately 500,000 L1 jumping genes, accounting for 17% of the human genome, they have long been recognized for their contribution to the evolution of the human species by introducing 'disruptive innovation' to genome sequences. Until now, it was believed that most L1 elements had lost their ability to jump in normal tissues of modern humans. However, this study reveals that some L1 jumping genes can be widely activated in normal cells, leading to the accumulation of genomic mutations over an individual's lifetime. The rate of L1 jumping and resulting genomic changes vary among different cell types, with a notable concentration observed in aged colon epithelial cells. The study illustrates that every colonic epithelial cell experiences an L1 jumping event by the age of 40 on average. The research, led by co-first authors Chang Hyun Nam (a graduate student at KAIST) and Dr. Jeonghwan Youk (former graduate student at KAIST and assistant clinical professor at Seoul National University Hospital), involved the analysis of whole-genome sequences from 899 single cells obtained from skin (fibroblasts), blood, and colon epithelial tissues collected from 28 individuals. The study uncovers the activation of L1 jumping genes in normal cells, resulting in the gradual accumulation of genomic mutations over time. Additionally, the team explored epigenomic (DNA methylation) sequences to understand the mechanism behind L1 jumping gene activation. They found that cells with activated L1 jumping genes exhibit epigenetic instability, suggesting the critical role of epigenetic changes in regulating L1 jumping gene activity. Most of these epigenomic instabilities were found to arise during the early stages of embryogenesis. The study provides valuable insights into the aging process and the development of diseases in human colorectal tissues. "This study illustrates that genomic damage in normal cells is acquired not only through exposure to carcinogens but also through the activity of endogenous components whose impact was previously unclear. Genomes of apparently healthy aged cells, particularly in the colorectal epithelium, become mosaic due to the activity of L1 jumping genes," said Prof. Young Seok Ju at KAIST. "We emphasize the essential and ongoing collaboration among researchers in clinical medicine and basic medical sciences," said Prof. Min Jung Kim of the Department of Surgery at Seoul National University Hospital. "This case highlights the critical role of systematically collected human tissues from clinical settings in unraveling the complex process of disease development in humans." "I am delighted that the research team's advancements in single-cell genome technology have come to fruition. We will persistently strive to lead in single-cell genome technology," said Prof. Hyun Woo Kwon of the Department of Nuclear Medicine at Korea University School of Medicine. The research team received support from the Research Leader Program and the Young Researcher Program of the National Research Foundation of Korea, a grant from the MD-PhD/Medical Scientist Training Program through the Korea Health Industry Development Institute, and the Suh Kyungbae Foundation. < Figure 1. Experimental design of the study > < Figure 2. Schematic diagram illustrating factors influencing the soL1R landscape. > Genetic composition of rc-L1s is inherited from the parents. The methylation landscape of rc-L1 promoters is predominantly determined by global DNA demethylation, followed by remethylation processes in the developmental stages. Then, when an rc-L1 is promoter demethylated in a specific cell lineage, the source expresses L1 transcripts thus making possible the induction of soL1Rs.
2023.05.22
View 2479
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 3769
KAIST gearing up to train physician-scientists and BT Professionals joining hands with Boston-based organizations
KAIST (President Kwang Hyung Lee) announced on the 29th that it has signed MOUs with Massachusetts General Hospital, a founding member of the Mass General Brigham health care system and a world-class research-oriented hospital, and Moderna, a biotechnology company that developed a COVID-19 vaccine at the Langham Hotel in Boston, MA, USA on the morning of April 28th (local time). The signing ceremony was attended by officials from each institution joined by others headed by Minister LEE Young of the Korean Ministry of SMEs and Startups (MSS), and Commissioner LEE Insil of the Korean Intellectual Property Office. < Photo 1. Photo from the Signing of MOU between KAIST-Harvard University Massachusetts General Hospital and KAIST-Moderna > Mass General is the first and largest teaching hospital of Harvard Medical School in Boston, USA, and it is one of the most innovative hospitals in the world being the alma mater of more than 13 Nobel Prize winners and the home of the Mass General Research Institute, the world’s largest hospital-based research program that utilizes an annual research budget of more than $1.3 billion. KAIST signed a general agreement to explore research and academic exchange with Mass General in September of last year and this MOU is a part of its follow-ups. Mass General works with Harvard and the Massachusetts Institute of Technology (MIT), as well as local hospitals, to support students learn the theories of medicine and engineering, and gain rich clinical research experience. Through this MOU, KAIST will explore cooperation with an innovative ecosystem created through the convergence of medicine and engineering. In particular, KAIST’s goal is to develop a Korean-style training program and implement a differentiated educational program when establishing the science and technology-oriented medical school in the future by further strengthening the science and engineering part of the training including a curriculum on artificial intelligence (AI) and the likes there of. Also, in order to foster innovative physician-scientists, KAIST plans to pursue cooperation to develop programs for exchange of academic and human resources including programs for student and research exchanges and a program for students of the science and technology-oriented medical school at KAIST to have a chance to take part in practical training at Mass General. David F.M. Brown, MD, Mass General President, said, “The collaboration with KAIST has a wide range of potentials, including advice on training of physician-scientists, academic and human resource exchanges, and vitalization of joint research by faculty from both institutions. Through this agreement, we will be able to actively contribute to global cooperation and achieve mutual goals.” Meanwhile, an MOU between KAIST and Moderna was also held on the same day. Its main focus is to foster medical experts in cooperation with KAIST Graduate School of Medical Science and Engineering (GSMSE), and plans to cooperate in various ways in the future, including collaborating for development of vaccine and new drugs, virus research, joint mRNA research, and facilitation of technology commercialization. In over 10 years since its inception, Moderna has transformed from a research-stage company advancing programs in the field of messenger RNA (mRNA) to an enterprise with a diverse clinical portfolio of vaccines and therapeutics across seven modalities. The Company has 48 programs in development across 45 development candidates, of which 38 are currently in active clinical trials. “We are grateful to have laid a foundation for collaboration to foster industry experts with the Korea Advanced Institute of Science and Technology, a leader of science and technology innovation in Korea,” said Arpa Garay, Chief Commercial Officer, Moderna. “Based on our leadership and expertise in developing innovative mRNA vaccines and therapeutics, we hope to contribute to educating and collaborating with professionals in the bio-health field of Korea.“ President Kwang Hyung Lee of KAIST, said, “We deem this occasion to be of grave significance to be able to work closely with Massachusetts General Hospital, one of the world's best research-oriented hospitals, and Moderna, one of the most influential biomedical companies.” President Lee continued, "On the basis of the collaboration with the two institutions, we will be able to bring up qualified physician-scientists and global leaders of the biomedical business who will solve problems of human health and their progress will in turn, accelerate the national R&D efforts in general and diversify the industry."
2023.04.29
View 7561
KAIST Team Develops Highly-Sensitive Wearable Piezoelectric Blood Pressure Sensor for Continuous Health Monitoring
- A collaborative research team led by KAIST Professor Keon Jae Lee verifies the accuracy of the highly-sensitive sensor through clinical trials - Commercialization of the watch and patch-type sensor is in progress A KAIST research team led by Professor Keon Jae Lee from the Department of Materials Science and Engineering and the College of Medicine of the Catholic University of Korea has developed a highly sensitive, wearable piezoelectric blood pressure sensor. Blood pressure is a critical indicator for assessing general health and predicting stroke or heart failure. In particular, cardiovascular disease is the leading cause of global death, therefore, periodic measurement of blood pressure is crucial for personal healthcare. Recently, there has been a growing interest in healthcare devices for continuous blood pressure monitoring. Although smart watches using LED-based photoplethysmography (PPG) technology have been on market, these devices have been limited by the accuracy constraints of optical sensors, making it hard to meet the international standards of automatic sphygmomanometers. Professor Lee’s team has developed the wearable piezoelectric blood pressure sensor by transferring a highly sensitive, inorganic piezoelectric membrane from bulk sapphire substrates to flexible substrates. Ultrathin piezoelectric sensors with a thickness of several micrometers (one hundredth of the human hair) exhibit conformal contact with the skin to successfully collect accurate blood pressure from the subtle pulsation of the blood vessels. Clinical trial at the St. Mary’s Hospital of the Catholic University validated the accuracy of blood pressure sensor at par with international standard with errors within ±5 mmHg and a standard deviation under 8 mmHg for both systolic and diastolic blood pressure. In addition, the research team successfully embedded the sensor on a watch-type product to enable continuous monitoring of blood pressure. Prof. Keon Jae Lee said, “Major target of our healthcare devices is hypertensive patients for their daily medical check-up. We plan to develop a comfortable patch-type sensor to monitor blood pressure during sleep and have a start-up company commercialize these watch and patch-type products soon.” This result titled “Clinical validation of wearable piezoelectric blood pressure sensor for health monitoring” was published in the online issue of Advanced Materials on March 24th, 2023. (DOI: 10.1002/adma.202301627) Figure 1. Schematic illustration of the overall concept for a wearable piezoelectric blood pressure sensor (WPBPS). Figure 2. Wearable piezoelectric blood pressure sensor (WPBPS) mounted on a watch (a) Schematic design of the WPBPS-embedded wristwatch. (b) Block diagram of the wireless communication circuit, which filters, amplifies, and transmits wireless data to portable devices. (c) Pulse waveforms transmitted from the wristwatch to the portable device by the wireless communication circuit. The inset shows a photograph of monitoring a user’s beat-to-beat pulses and their corresponding BP values in real time using the developed WPBPS-mounted wristwatch.
2023.04.17
View 2933
KAIST researchers devises a technology to utilize ultrahigh-resolution micro-LED with 40% reduced self-generated heat
In the digitized modern life, various forms of future displays, such as wearable and rollable displays are required. More and more people are wanting to connect to the virtual world whenever and wherever with the use of their smartglasses or smartwatches. Even further, we’ve been hearing about medical diagnosis kit on a shirt and a theatre-hat. However, it is not quite here in our hands yet due to technical limitations of being unable to fit as many pixels as a limited surface area of a glasses while keeping the power consumption at the a level that a hand held battery can supply, all the while the resolution of 4K+ is needed in order to perfectly immerse the users into the augmented or virtual reality through a wireless smartglasses or whatever the device. KAIST (President Kwang Hyung Lee) announced on the 22nd that Professor Sang Hyeon Kim's research team of the Department of Electrical and Electronic Engineering re-examined the phenomenon of efficiency degradation of micro-LEDs with pixels in a size of micrometers (μm, one millionth of a meter) and found that it was possible to fundamentally resolve the problem by the use of epitaxial structure engineering. Epitaxy refers to the process of stacking gallium nitride crystals that are used as a light emitting body on top of an ultrapure silicon or sapphire substrate used for μLEDs as a medium. μLED is being actively studied because it has the advantages of superior brightness, contrast ratio, and lifespan compared to OLED. In 2018, Samsung Electronics commercialized a product equipped with μLED called 'The Wall'. And there is a prospect that Apple may be launching a μLED-mounted product in 2025. In order to manufacture μLEDs, pixels are formed by cutting the epitaxial structure grown on a wafer into a cylinder or cuboid shape through an etching process, and this etching process is accompanied by a plasma-based process. However, these plasmas generate defects on the side of the pixel during the pixel formation process. Therefore, as the pixel size becomes smaller and the resolution increases, the ratio of the surface area to the volume of the pixel increases, and defects on the side of the device that occur during processing further reduce the device efficiency of the μLED. Accordingly, a considerable amount of research has been conducted on mitigating or removing sidewall defects, but this method has a limit to the degree of improvement as it must be done at the post-processing stage after the grown of the epitaxial structure is finished. The research team identified that there is a difference in the current moving to the sidewall of the μLED depending on the epitaxial structure during μLED device operation, and based on the findings, the team built a structure that is not sensitive to sidewall defects to solve the problem of reduced efficiency due to miniaturization of μLED devices. In addition, the proposed structure reduced the self-generated heat while the device was running by about 40% compared to the existing structure, which is also of great significance in commercialization of ultrahigh-resolution μLED displays. This study, which was led by Woo Jin Baek of Professor Sang Hyeon Kim's research team at the KAIST School of Electrical and Electronic Engineering as the first author with guidance by Professor Sang Hyeon Kim and Professor Dae-Myeong Geum of the Chungbuk National University (who was with the team as a postdoctoral researcher at the time) as corresponding authors, was published in the international journal, 'Nature Communications' on March 17th. (Title of the paper: Ultra-low-current driven InGaN blue micro light-emitting diodes for electrically efficient and self-heating relaxed microdisplay). Professor Sang Hyeon Kim said, "This technological development has great meaning in identifying the cause of the drop in efficiency, which was an obstacle to miniaturization of μLED, and solving it with the design of the epitaxial structure.“ He added, ”We are looking forward to it being used in manufacturing of ultrahigh-resolution displays in the future." This research was carried out with the support of the Samsung Future Technology Incubation Center. Figure 1. Image of electroluminescence distribution of μLEDs fabricated from epitaxial structures with quantum barriers of different thicknesses while the current is running Figure 2. Thermal distribution images of devices fabricated with different epitaxial structures under the same amount of light. Figure 3. Normalized external quantum efficiency of the device fabricated with the optimized epitaxial structure by sizes.
2023.03.23
View 2355
KAIST research team develops clathrin assembly for targeted protein delivery to cancer cells
In order to effectively treat cancer without additional side effects, we need a way to deliver drugs specifically to tumor cells. Protein assemblies have been widely used for drug delivery in the field of cancer treatment, but to use them for drug delivery they must first be functionalized, meaning they must be bound to the protein that recognizes the target tumor cell and deliver a drug that kills it. However, the functionalization process of protein assemblies is very complex, inefficient, and limited to small-sized chemical drugs, which limits their real-life applicability. On March 14, a KAIST research team led by Professor Hak-Sung Kim from the KAIST Department of Biological Sciences reported the development of a clathrin assembly that can specifically deliver drugs to cancer cells. Clathrin assemblies transport materials efficiently through endocytosis in living organisms. They are formed by the self-assembly of triskelion units, which are composed of three heavy chains bonded with three light chains. Inspired by this mechanism, the research team designed a clathrin chain to facilitate the functionalization of tumor cell recognition proteins and toxin proteins in order to deliver drugs specifically to tumor cells. From this, the team created a new type of clathrin assembly. Figure 1. (Upper) Schematic diagram of the development of a new clathrin assembly that simultaneously functionalizes two types of proteins (cancer cell recognition protein and toxin protein) on heavy and light chains of clathrin in a one-pot reaction (bottom, left) Electron microscopy image of clathrin assembly: formation of an assembly with a diameter of about 28 nanometers (bottom, right) Cancer cell killing effect of CLA: CLA functionalized with epidermal growth factor receptor (EGFR) recognition protein and toxin protein kills only the cancer cells that overexpress EGFR. The newly developed clathrin assembly requires a one-pot reaction, meaning both the toxin and tumor-recognition proteins can be functionalized simultaneously and show high efficiency. As a result, this technique is expected to be used in a wide variety of applications in the fields of biology and medicine including drug delivery, vaccine development, and diagnosing illnesses. In this research, an epidermal growth factor receptor (EGFR), a common tumor marker, was used as the recognition protein, allowing drug delivery only to tumor cells. The clathrin assemblies that were functionalized to recognize EGFR showed a bonding strength 900-times stronger than it normally would due to the avidity effect. Based on this finding, the research team confirmed that treatment with toxin-functionalized clathrin assembly led to effective cell death for tumor cells, while it showed no such effect on healthy cells. This research by Dr. Hong-Sik Kim and his colleagues was published in Small volume 19, issue 8 on February 22 under the title, "Construction and Functionalization of a Clathrin Assembly for a Targeted Protein Delivery", and it was selected as the cover paper. Figure 2. Cover Paper: This study was published in the international journal 'Small' on February 22nd, Volume 19, No. 8, and was selected as the cover paper. First author Dr. Hong-Sik Kim said, “Clathrin is difficult to functionalize, and since it is extracted from mammals, realistic applications have been limited.” He added, “But the new clathrin assembly we designed for this research can be functionalized with two different types of proteins through a single-step reaction, and can be produced from E. coli, meaning it can become an applicable protein assembly technology for a wide range of biomedical fields.” This research was funded by the Global Ph.D. Fellowship and the Mid-career Researcher Grant of the National Research Foundation.
2023.03.22
View 2239
KAIST leads AI-based analysis on drug-drug interactions involving Paxlovid
KAIST (President Kwang Hyung Lee) announced on the 16th that an advanced AI-based drug interaction prediction technology developed by the Distinguished Professor Sang Yup Lee's research team in the Department of Biochemical Engineering that analyzed the interaction between the PaxlovidTM ingredients that are used as COVID-19 treatment and other prescription drugs was published as a thesis. This paper was published in the online edition of 「Proceedings of the National Academy of Sciences of America」 (PNAS), an internationally renowned academic journal, on the 13th of March. * Thesis Title: Computational prediction of interactions between Paxlovid and prescription drugs (Authored by Yeji Kim (KAIST, co-first author), Jae Yong Ryu (Duksung Women's University, co-first author), Hyun Uk Kim (KAIST, co-first author), and Sang Yup Lee (KAIST, corresponding author)) In this study, the research team developed DeepDDI2, an advanced version of DeepDDI, an AI-based drug interaction prediction model they developed in 2018. DeepDDI2 is able to compute for and process a total of 113 drug-drug interaction (DDI) types, more than the 86 DDI types covered by the existing DeepDDI. The research team used DeepDDI2 to predict possible interactions between the ingredients (ritonavir, nirmatrelvir) of Paxlovid*, a COVID-19 treatment, and other prescription drugs. The research team said that while among COVID-19 patients, high-risk patients with chronic diseases such as high blood pressure and diabetes are likely to be taking other drugs, drug-drug interactions and adverse drug reactions for Paxlovid have not been sufficiently analyzed, yet. This study was pursued in light of seeing how continued usage of the drug may lead to serious and unwanted complications. * Paxlovid: Paxlovid is a COVID-19 treatment developed by Pfizer, an American pharmaceutical company, and received emergency use approval (EUA) from the US Food and Drug Administration (FDA) in December 2021. The research team used DeepDDI2 to predict how Paxrovid's components, ritonavir and nirmatrelvir, would interact with 2,248 prescription drugs. As a result of the prediction, ritonavir was predicted to interact with 1,403 prescription drugs and nirmatrelvir with 673 drugs. Using the prediction results, the research team proposed alternative drugs with the same mechanism but low drug interaction potential for prescription drugs with high adverse drug events (ADEs). Accordingly, 124 alternative drugs that could reduce the possible adverse DDI with ritonavir and 239 alternative drugs for nirmatrelvir were identified. Through this research achievement, it became possible to use an deep learning technology to accurately predict drug-drug interactions (DDIs), and this is expected to play an important role in the digital healthcare, precision medicine and pharmaceutical industries by providing useful information in the process of developing new drugs and making prescriptions. Distinguished Professor Sang Yup Lee said, "The results of this study are meaningful at times like when we would have to resort to using drugs that are developed in a hurry in the face of an urgent situations like the COVID-19 pandemic, that it is now possible to identify and take necessary actions against adverse drug reactions caused by drug-drug interactions very quickly.” This research was carried out with the support of the KAIST New-Deal Project for COVID-19 Science and Technology and the Bio·Medical Technology Development Project supported by the Ministry of Science and ICT. Figure 1. Results of drug interaction prediction between Paxlovid ingredients and representative approved drugs using DeepDDI2
2023.03.16
View 2917
KAIST researchers develops a tech to enable production of ultrahigh-resolution LED with sub-micrometer scale pixels
Ultrahigh-resolution displays are an essential element for developing next-generation electronic products such as virtual reality (VR), augmented reality (AR), and smart watches, and can be applied not only to head-mounted displays, but also to smart glasses and smart lenses. The technology developed through this research is expected to be used to make such next-generation ultrahigh-resolution displays and other various sub-micro optoelectronic devices. KAIST (President Kwang Hyung Lee) announced on the 22nd that Professor Yong-Hoon Cho's research team of KAIST Department of Physics developed the core technology for an ultrahigh resolution light-emitting diode (LED) display that can realize 0.5 micron-scale pixels smaller than 1/100 of the average hair thickness (about 100 microns) using focused ion beams. Commonly, pixelation of ultrahigh-resolution LED displays usually relies on the etching method that physically cuts the area around the pixel, but as the pixel becomes smaller due to the occurrence of various defects around it, leading to side-effects of having leakage of current increased and light-emission efficiency decreased. In addition, various complex processes such as patterning for pixelation and post-processing for prevention of leakage current are required. Professor Yong-Hoon Cho's research team developed a technology that can create pixels down to the size of a microscale without the complicated pre- and post-processing using a focused ion beam. This method has the advantage of being able to freely set the shape of the emitting pixel without causing any structural deformation on the material surface by controlling the intensity of the focused ion beam. The focused ion beam technology has been widely used for ultrahigh-magnification imaging and nanostructure fabrication in fields such as materials engineering and biology. However, when a focused ion beam is used on a light emitting body such as an LED, light emission of a portion hit by the beam and a surrounding area rapidly decreases, which has been a barrier to fabricating a nano-scale light emitting structure. Upon facing this issue, Professor Cho's research team began the research on the idea that if they turned things around to use these problematic phenomena, they can be used in ultra-fine pixelation method on a sub-micron scale. The research team used a focused ion beam whose intensity was softened to the extent that the surface was not shaved, and found that not only the light-emission rapidly decreased in the area hit by the focused ion beam, but also the local resistance greatly increased. As a result, while the surface of the LED is kept flat, the portion hit by the focused ion beam is optically and electrically isolated, enabling pixelation for independent operation. Professor Yong-Hoon Cho, who led the research, said, “We have newly developed a technology that can create sub-micron-scale pixels without complicated processes using a focused ion beam, which will be a base technology that can be applied to next-generation ultrahigh-resolution displays and nano-photoelectronic devices.” This research in which the Master's student Ji-Hwan Moon and the Ph.D. student Baul Kim of KAIST Department of Physics participated as co-first authors, was carried out with the support of the National Research Foundation of Korea's Support Program for Mid-Career Researchers and the Institute of Information and Communications Technology Planning and Evaluation. It was published online in 'Advanced Materials' on February 13, and was also selected as the internal cover of the next offline edition. (Title: Electrically Driven Sub-Micron Light-Emitting Diode Arrays Using Maskless and Etching-Free Pixelation) Figure 1. Schematic diagram of the technology for ultrahigh density sub-micron-sized pixels through He focused ion beam (FIB) irradiation on an LED device Figure 2. Ultra-high-density pixelation technology of micro light-emitting diodes (μLED) through He focused ion beam (FIB) irradiation Figure 3. Rectangular pixels of different sizes (surface structure picture and luminescence picture) realized by a focused ion beam. Luminescence pictures of pixel arrays ranging in size from 20 µm x 20 µm to 0.5 µm x 0.5 µm, with surface flatness maintained.
2023.03.08
View 2592
KAIST researchers discovers the neural circuit that reacts to alarm clock
KAIST (President Kwang Hyung Lee) announced on the 20th that a research team led by Professor Daesoo Kim of the Department of Brain and Cognitive Sciences and Dr. Jeongjin Kim 's team from the Korea Institute of Science and Technology (KIST) have identified the principle of awakening animals by responding to sounds even while sleeping. Sleep is a very important physiological process that organizes brain activity and maintains health. During sleep, the function of sensory nerves is blocked, so the ability to detect danger in the proximity is reduced. However, many animals detect approaching predators and respond even while sleeping. Scientists thought that animals ready for danger by alternating between deep sleep and light sleep. A research team led by Professor Daesoo Kim at KAIST discovered that animals have neural circuits that respond to sounds even during deep sleep. While awake, the medial geniculate thalamus responds to sounds, but during deep sleep, or Non-REM sleep, the Mediodorsal thalamus responds to sounds to wake up the brain. As a result of the study, when the rats fell into deep sleep, the nerves of the medial geniculate thalamus were also sleeping, but the nerves of mediodorsal thalamus were awake and responded immediately to sounds. In addition, it was observed that when mediodorsal thalamus was inhibited, the rats could not wake up even when a sound was heard, and when the mediodorsal thalamus was stimulated, the rats woke up within a few seconds without sound. This is the first study to show that sleep and wakefulness can transmit auditory signals through different neural circuits, and was reported in the international journal, Current Biology on February 7, and was highlighted by Nature. (https://www.nature.com/articles/d41586-023-00354-0) Professor Daesoo Kim explained, “The findings of this study can used in developing digital healthcare technologies to be used to improve understanding of disorders of senses and wakefulness seen in various brain diseases and to control the senses in the future.” This research was carried out with the support from the National Research Foundation of Korea's Mid-Career Research Foundation Program. Figure 1. Traditionally, sound signals were thought to be propagated from the auditory nerve to the auditory thalamus. However, while in slow-wave sleep, the auditory nerve sends sound signals to the mediodorsal thalamic neurons via the brainstem nerve to induce arousal in the brain. Figure 2. GRIK4 dorsomedial nerve in response to sound stimulation. The awakening effect is induced as the activity of the GRIK4 dorsal medial nerve increases based on the time when sound stimulation is given.
2023.03.03
View 2172
KAIST confers Honorary Doctorate of Science on NYU President Emeritus John Edward Sexton
< Photo 1. NYU President Emeritus John Edward Sexton posing with KAIST President Kwang Hyung Lee holding the Honorary Doctorate at the KAIST Commencement Ceremony > KAIST (President Kwang Hyung Lee) announced that it conferred an honorary doctorate of science degree on NYU President Emeritus John Edward Sexton at the Commencement Ceremony held on the 17th. An official from KAIST explained, "KAIST is conferring an honorary doctorate for President Sexton's longstanding leadership in higher education, and for his contributions to the process of establishing the groundwork for collaboration with NYU through which KAIST is to become a leading global value-creating university." President Emeritus Sexton served as the president of NYU from 2002 to 2015, establishing two degree-granting campuses and several global academic sites of NYU around the world. Because of its steady rise in university rankings, such as its medical school earning the number two position in the United States, not only has NYU joined the ranks of first-class universities, but it has also achieved remarkable growth, with the number of students increasing dramatically from 29,000 to 60,000. In addition, during his tenure as president at NYU, President Emeritus Sexton successfully expanded fundraising to support the University’s academic goals. During his 14-year tenure as president, he organized initiatives such as 'Raise $1 Million Every Day' and 'Call to Action' to raise $4.9 billion in donations, the largest in NYU history to date. President Emeritus Sexton is famous for teaching full time even during his presidential tenure and for the anecdotes about his special care for students, addressing the school members as “family”. In particular, he is famous for giving hugs to all graduates at the commencement ceremony. Minister Park Jin of the Ministry of Foreign Affairs of Korea, who graduated from NYU School of Law in 1999 with a Master of Studies in Law, is one of the graduates who received President Sexton's hug. President Emeritus Sexton, born in 1942, visited KAIST on the 17th to receive the honorary doctorate and to encourage the expedited development of the KAIST-NYU Joint Campus, for which he helped lay the foundation. President Emeritus Sexton said, "I like the slogan, 'Onward and upward together,'" and added, "I look forward to having the two universities achieve their shared vision of becoming the world-class universities together through cooperation to establish the KAIST-NYU Joint Campus." < Photo 2. NYU President Emeritus John Edward Sexton giving the acceptance speech at the KAIST Commencement Ceremony > The US Ambassador to Korea, the Honorable Philip Goldberg, also attended the commencement ceremony at KAIST to congratulate President Emeritus Sexton on the conferment of the honorary doctorate. Ambassador Goldberg has been serving as the US Ambassador to Korea since July of last year. President Kwang Hyung Lee said, “President Emeritus Sexton was a president best described as an innovator who promoted diversity in education and pursued academic excellence throughout his life.” He went on to say, “The KAIST-NYU Joint Campus, which will be completed on the foundation laid by President Emeritus Sexton, will serve as the focal point that will attract global talents flooding into New York by the driving force created from the synergy of the two universities as well as serving as a starting point for KAIST's outstanding talents to pursue their dreams toward the world.” KAIST signed a cooperation agreement with NYU in June of 2022 to build a joint campus, and held a presentation of signage for the KAIST-NYU Joint Campus in September. Currently, about 60 faculty members are planning to begin joint research initiatives in seven fields, including robotics, AI, brain sciences, and climate change. In addition, cooperation in the field of education, including student exchange, minors, double majors, and joint degrees, is under discussion.
2023.02.17
View 4131
KAIST presents a fundamental technology to remove metastatic traits from lung cancer cells
KAIST (President Kwang Hyung Lee) announced on January 30th that a research team led by Professor Kwang-Hyun Cho from the Department of Bio and Brain Engineering succeeded in using systems biology research to change the properties of carcinogenic cells in the lungs and eliminate both drug resistance and their ability to proliferate out to other areas of the body. As the incidences of cancer increase within aging populations, cancer has become the most lethal disease threatening healthy life. Fatality rates are especially high when early detection does not happen in time and metastasis has occurred in various organs. In order to resolve this problem, a series of attempts were made to remove or lower the ability of cancer cells to spread, but they resulted in cancer cells in the intermediate state becoming more unstable and even more malignant, which created serious treatment challenges. Professor Kwang-Hyun Cho's research team simulated various cancer cell states in the Epithelial-to-Mesenchymal Transition (EMT) of lung cancer cells, between epithelial cells without metastatic ability and mesenchymal cells with metastatic ability. A mathematical model of molecular network was established, and key regulators that could reverse the state of invasive and drug resistant mesenchymal cells back to the epithelial state were discovered through computer simulation analysis and molecular cell experiments. In particular, this process succeeded in properly reverting the mesenchymal lung cancer cells to a state where they were sensitive to chemotherapy treatment while avoiding the unstable EMT hybrid cell state in the middle process, which had remained a difficult problem. The results of this research, in which KAIST Ph.D. student Namhee Kim, Dr. Chae Young Hwang, Researcher Taeyoung Kim, and Ph.D. student Hyunjin Kim participated, were published as an online paper in the international journal “Cancer Research” published by the American Association for Cancer Research (AACR) on January 30th. (Paper title: A cell fate reprogramming strategy reverses epithelial-to-mesenchymal transition of lung cancer cells while avoiding hybrid states) Cells in an EMT hybrid state, which are caused by incomplete transitions during the EMT process in cancer cells, have the characteristics of both epithelial cells and mesenchymal cells, and are known to have high drug resistance and metastatic potential by acquiring high stem cell capacity. In particular, EMT is further enhanced through factors such as transforming growth factor-beta (TGF-β) secreted from the tumor microenvironment (TME) and, as a result, various cell states with high plasticity appear. Due to the complexity of EMT, it has been very difficult to completely reverse the transitional process of the mesenchymal cancer cells to an epithelial cell state in which metastatic ability and drug resistance are eliminated while avoiding the EMT hybrid cell state with high metastatic ability and drug resistance. Professor Kwang-Hyun Cho's research team established a mathematical model of the gene regulation network that governs the complex process of EMT, and then applied large-scale computer simulation analysis and complex system network control technology to identify and verify 'p53', 'SMAD4', and 'ERK1' and 'ERK 2' (collectively ERKs) through molecular cell experiments as the three key molecular targets that can transform lung cancer cells in the mesenchymal cell state, reversed back to an epithelial cell state that no longer demonstrates the ability to metastasize, while avoiding the EMT hybrid cell state. In particular, by analyzing the molecular regulatory mechanism of the complex EMT process at the system level, the key pathways were identified that were linked to the positive feedback that plays an important role in completely returning cancer cells to an epithelial cell state in which metastatic ability and drug resistance are removed. This discovery is significant in that it proved that mesenchymal cells can be reverted to the state of epithelial cells under conditions where TGF-β stimulation are present, like they are in the actual environment where cancer tissue forms in the human body. Abnormal EMT in cancer cells leads to various malignant traits such as the migration and invasion of cancer cells, changes in responsiveness to chemotherapy treatment, enhanced stem cell function, and the dissemination of cancer. In particular, the acquisition of the metastatic ability of cancer cells is a key determinant factor for the prognosis of cancer patients. The EMT reversal technology in lung cancer cells developed in this research is a new anti-cancer treatment strategy that reprograms cancer cells to eliminate their high plasticity and metastatic potential and increase their responsiveness to chemotherapy. Professor Kwang-Hyun Cho said, "By succeeding in reversing the state of lung cancer cells that acquired high metastatic traits and resistance to drugs and reverting them to a treatable epithelial cell state with renewed sensitivity to chemotherapy, the research findings propose a new strategy for treatments that can improve the prognosis of cancer patients.” Professor Kwang-Hyun Cho's research team was the first to present the principle of reversal treatment to revert cancer cells to normal cells, following through with the announcement of the results of their study that reverted colon cancer cells to normal colon cells in January of 2020, and also presenting successful re-programming research where the most malignant basal type breast cancer cells turned into less-malignant luminal type breast cancer cells that were treatable with hormonal therapies in January of 2022. This latest research result is the third in the development of reversal technology where lung cancer cells that had acquired metastatic traits returned to a state in which their metastatic ability was removed and drug sensitivity was enhanced. This research was carried out with support from the Ministry of Science and ICT and the National Research Foundation of Korea's Basic Research in Science & Engineering Program for Mid-Career Researchers. < Figure 1. Construction of the mathematical model of the regulatory network to represent the EMT phenotype based on the interaction between various molecules related to EMT. (A) Professor Kwang-Hyun Cho's research team investigated numerous literatures and databases related to complex EMT, and based on comparative analysis of cell line data showing epithelial and mesenchymal cell conditions, they extracted key signaling pathways related to EMT and built a mathematical model of regulatory network (B) By comparing the results of computer simulation analysis and the molecular cell experiments, it was verified how well the constructed mathematical model simulated the actual cellular phenomena. > < Figure 2. Understanding of various EMT phenotypes through large-scale computer simulation analysis and complex system network control technology. (A) Through computer simulation analysis and experiments, Professor Kwang-Hyun Cho's research team found that complete control of EMT is impossible with single-molecule control alone. In particular, through comparison of the relative stability of attractors, it was revealed that the cell state exhibiting EMT hybrid characteristics has unstable properties. (B), (C) Based on these results, Prof. Cho’s team identified two feedbacks (positive feedback consisting of Snail-miR-34 and ZEB1-miR-200) that play an important role in avoiding the EMT hybrid state that appeared in the TGF-β-ON state. It was found through computer simulation analysis that the two feedbacks restore relatively high stability when the excavated p53 and SMAD4 are regulated. In addition, molecular cell experiments demonstrated that the expression levels of E-cad and ZEB1, which are representative phenotypic markers of EMT, changed similarly to the expression profile in the epithelial cell state, despite the TGF-β-ON state. > < Figure 3. Complex molecular network analysis and discovery of reprogramming molecular targets for intact elimination of EMT hybrid features. (A) Controlling the expression of p53 and SMAD4 in lung cancer cell lines was expected to overcome drug resistance, but contrary to expectations, chemotherapy responsiveness was not restored. (B) Professor Kwang-Hyun Cho's research team additionally analyzed computer simulations, genome data, and experimental results and found that high expression levels of TWIST1 and EPCAM were related to drug resistance. (C) Prof. Cho’s team identified three key molecular targets: p53, SMAD4 and ERK1 & ERK2. (D), (E) Furthermore, they identified a key pathway that plays an important role in completely reversing into epithelial cells while avoiding EMT hybrid characteristics, and confirmed through network analysis and attractor analysis that high stability of the key pathway was restored when the proposed molecular target was controlled. > < Figure 4. Verification through experiments with lung cancer cell lines. When p53 was activated and SMAD4 and ERK1/2 were inhibited in lung cancer cell lines, (A), (B) E-cad protein expression increased and ZEB1 protein expression decreased, and (C) mesenchymal cell status including TWIST1 and EPCAM and gene expression of markers related to stem cell potential characteristics were completely inhibited. In addition, (D) it was confirmed that resistance to chemotherapy treatment was also overcome as the cell state was reversed by the regulated target. > < Figure 5. A schematic representation of the research results. Prof. Cho’s research team identified key molecular regulatory pathways to avoid high plasticity formed by abnormal EMT of cancer cells and reverse it to an epithelial cell state through systems biology research. From this analysis, a reprogramming molecular target that can reverse the state of mesenchymal cells with acquired invasiveness and drug resistance to the state of epithelial cells with restored drug responsiveness was discovered. For lung cancer cells, when a drug that enhances the expression of p53, one of the molecular targets discovered, and inhibits the expression of SMAD4 and ERK1 & ERK2 is administered, the molecular network of genes in the state of mesenchymal cells is modified, eventually eliminating metastatic ability and it is reprogrammed to turn into epithelial cells without the resistance to chemotherapy treatments. >
2023.01.30
View 8051
KAIST’s Robo-Dog “RaiBo” runs through the sandy beach
KAIST (President Kwang Hyung Lee) announced on the 25th that a research team led by Professor Jemin Hwangbo of the Department of Mechanical Engineering developed a quadrupedal robot control technology that can walk robustly with agility even in deformable terrain such as sandy beach. < Photo. RAI Lab Team with Professor Hwangbo in the middle of the back row. > Professor Hwangbo's research team developed a technology to model the force received by a walking robot on the ground made of granular materials such as sand and simulate it via a quadrupedal robot. Also, the team worked on an artificial neural network structure which is suitable in making real-time decisions needed in adapting to various types of ground without prior information while walking at the same time and applied it on to reinforcement learning. The trained neural network controller is expected to expand the scope of application of quadrupedal walking robots by proving its robustness in changing terrain, such as the ability to move in high-speed even on a sandy beach and walk and turn on soft grounds like an air mattress without losing balance. This research, with Ph.D. Student Soo-Young Choi of KAIST Department of Mechanical Engineering as the first author, was published in January in the “Science Robotics”. (Paper title: Learning quadrupedal locomotion on deformable terrain). Reinforcement learning is an AI learning method used to create a machine that collects data on the results of various actions in an arbitrary situation and utilizes that set of data to perform a task. Because the amount of data required for reinforcement learning is so vast, a method of collecting data through simulations that approximates physical phenomena in the real environment is widely used. In particular, learning-based controllers in the field of walking robots have been applied to real environments after learning through data collected in simulations to successfully perform walking controls in various terrains. However, since the performance of the learning-based controller rapidly decreases when the actual environment has any discrepancy from the learned simulation environment, it is important to implement an environment similar to the real one in the data collection stage. Therefore, in order to create a learning-based controller that can maintain balance in a deforming terrain, the simulator must provide a similar contact experience. The research team defined a contact model that predicted the force generated upon contact from the motion dynamics of a walking body based on a ground reaction force model that considered the additional mass effect of granular media defined in previous studies. Furthermore, by calculating the force generated from one or several contacts at each time step, the deforming terrain was efficiently simulated. The research team also introduced an artificial neural network structure that implicitly predicts ground characteristics by using a recurrent neural network that analyzes time-series data from the robot's sensors. The learned controller was mounted on the robot 'RaiBo', which was built hands-on by the research team to show high-speed walking of up to 3.03 m/s on a sandy beach where the robot's feet were completely submerged in the sand. Even when applied to harder grounds, such as grassy fields, and a running track, it was able to run stably by adapting to the characteristics of the ground without any additional programming or revision to the controlling algorithm. In addition, it rotated with stability at 1.54 rad/s (approximately 90° per second) on an air mattress and demonstrated its quick adaptability even in the situation in which the terrain suddenly turned soft. The research team demonstrated the importance of providing a suitable contact experience during the learning process by comparison with a controller that assumed the ground to be rigid, and proved that the proposed recurrent neural network modifies the controller's walking method according to the ground properties. The simulation and learning methodology developed by the research team is expected to contribute to robots performing practical tasks as it expands the range of terrains that various walking robots can operate on. The first author, Suyoung Choi, said, “It has been shown that providing a learning-based controller with a close contact experience with real deforming ground is essential for application to deforming terrain.” He went on to add that “The proposed controller can be used without prior information on the terrain, so it can be applied to various robot walking studies.” This research was carried out with the support of the Samsung Research Funding & Incubation Center of Samsung Electronics. < Figure 1. Adaptability of the proposed controller to various ground environments. The controller learned from a wide range of randomized granular media simulations showed adaptability to various natural and artificial terrains, and demonstrated high-speed walking ability and energy efficiency. > < Figure 2. Contact model definition for simulation of granular substrates. The research team used a model that considered the additional mass effect for the vertical force and a Coulomb friction model for the horizontal direction while approximating the contact with the granular medium as occurring at a point. Furthermore, a model that simulates the ground resistance that can occur on the side of the foot was introduced and used for simulation. >
2023.01.26
View 8130
<<
첫번째페이지
<
이전 페이지
1
2
3
4
5
6
7
8
9
10
>
다음 페이지
>>
마지막 페이지 74