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Seanie Lee of KAIST Kim Jaechul Graduate School of AI, named the 2023 Apple Scholars in AI Machine Learning
Seanie Lee, a Ph.D. candidate at the Kim Jaechul Graduate School of AI, has been selected as one of the Apple Scholars in AI/ML PhD fellowship program recipients for 2023. Lee, advised by Sung Ju Hwang and Juho Lee, is a rising star in AI.
< Seanie Lee of KAIST Kim Jaechul Graduate School of AI >
The Apple Scholars in AI/ML PhD fellowship program, launched in 2020, aims to discover and support young researchers with a promising future in computer science. Each year, a handful of graduate students in related fields worldwide are selected for the program. For the following two years, the selected students are provided with financial support for research, international conference attendance, internship opportunities, and mentorship by an Apple engineer.
This year, 22 PhD students were selected from leading universities worldwide, including Johns Hopkins University, MIT, Stanford University, Imperial College London, Edinburgh University, Tsinghua University, HKUST, and Technion. Seanie Lee is the first Korean student to be selected for the program.
Lee’s research focuses on transfer learning, a subfield of AI that reuses pre-trained AI models on large datasets such as images or text corpora to train them for new purposes.
(*text corpus: a collection of text resources in computer-readable forms)
His work aims to improve the performance of transfer learning by developing new data augmentation methods that allow for more effective training using few training data samples and new regularization techniques that prevent the overfitting of large AI models to training data. He has published 11 papers, all of which were accepted to top-tier conferences such as the Annual Meeting of the Association for Computational Linguistics (ACL), International Conference on Learning Representations (ICLR), and Annual Conference on Neural Information Processing Systems (NeurIPS).
“Being selected as one of the Apple Scholars in AI/ML PhD fellowship program is a great motivation for me,” said Lee. “So far, AI research has been largely focused on computer vision and natural language processing, but I want to push the boundaries now and use modern tools of AI to solve problems in natural science, like physics.”
2023.04.20 View 4617 -
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 5172 -
KAIST researchers find the key to overcome the limits in X-ray microscopy
X-ray microscopes have the advantage of penetrating most substances, so internal organs and skeletons can be observed non-invasively through chest X-rays or CT scans. Recently, studies to increase the resolution of X-ray imaging technology are being actively conducted in order to precisely observe the internal structure of semiconductors and batteries at the nanoscale.
KAIST (President Kwang Hyung Lee) announced on April 12th that a joint research team led by Professor YongKeun Park of the Department of Physics and Dr. Jun Lim of the Pohang Accelerator Laboratory has succeeded in developing a core technology that can overcome the resolution limitations of existing X-ray microscopes.
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This study, in which Dr. KyeoReh Lee participated as the first author, was published on 6th of April in “Light: Science and Application”, a world-renowned academic journal in optics and photonics. (Paper title: Direct high-resolution X-ray imaging exploiting pseudorandomness).
X-ray nanomicroscopes do not have refractive lenses. In an X-ray microscope, a circular grating called a concentric zone plate is used instead of a lens. The resolution of an image obtained using the zone plate is determined by the quality of the nanostructure that comprises the plate. There are several difficulties in fabricating and maintaining these nanostructures, which set the limit to the level of resolution for X-ray microscopy.
The research team developed a new X-ray nanomicroscopy technology to overcome this problem. The X-ray lens proposed by the research team is in the form of numerous holes punched in a thin tungsten film, and generates random diffraction patterns by diffracting incident X-rays. The research team mathematically identified that, paradoxically, the high-resolution information of the sample was fully contained in these random diffraction patterns, and actually succeeded in extracting the information and imaging the internal states of the samples.
The imaging method using the mathematical properties of random diffraction was proposed and implemented in the visible light band for the first time by Dr. KyeoReh Lee and Professor YongKeun Park in 2016*. This study uses the results of previous studies to solve the difficult, lingering problem in the field of the X-ray imaging. ※ "Exploiting the speckle-correlation scattering matrix for a compact reference-free holographic image sensor." Nature communications 7.1 (2016): 13359.
The resolution of the image of the constructed sample has no direct correlation with the size of the pattern etched on the random lens used. Based on this idea, the research team succeeded in acquiring images with 14 nm resolution (approximately 1/7 the size of the coronavirus) by using random lenses made in a circular pattern with a diameter of 300 nm.
The imaging technology developed by this research team is a key fundamental technology that can enhance the resolution of X-ray nanomicroscopy, which has been blocked by limitations of the production of existing zone plates.
The first author and one of the co-corresponding author, Dr. KyeoReh Lee of KAIST Department of Physics, said, “In this study, the resolution was limited to 14 nm, but if the next-generation X-ray light source and high-performance X-ray detector are used, the resolution would exceed that of the conventional X-ray nano-imaging and approach the resolution of an electron microscope.” and added, “Unlike an electron microscope, X-rays can observe the internal structure without damaging the sample, so it will be able to present a new standard for non-invasive nanostructure observation processes such as quality inspections for semiconductors.”.
The co-corresponding author, Dr. Jun Lim of the Pohang Accelerator Laboratory, said, “In the same context, the developed image technology is expected to greatly increase the performance in the 4th generation multipurpose radiation accelerator which is set to be established in Ochang of the Northern Chungcheong Province.”
This research was conducted with the support through the Research Leader Program and the Sejong Science Fellowship of the National Research Foundation of Korea.
Fig. 1. Designed diffuser as X-ray imaging lens. a, Schematic of full-field transmission X-ray microscopy. The attenuation (amplitude) map of a sample is measured. The image resolution (dx) is limited by the outermost zone width of the zone plate (D). b, Schematic of the proposed method. A designed diffuser is used instead of a zone plate. The image resolution is finer than the hole size of the diffuser (dx << D).
Fig. 2. The left panel is a surface electron microscopy (SEM) image of the X-ray diffuser used in the experiment. The middle panel shows the design of the X-ray diffuser, and there is an inset in the middle of the panel that shows a corresponding part of the SEM image. The right panel shows an experimental random X-ray diffraction pattern, also known as a speckle pattern, obtained from the X-ray diffuser.
Fig. 3. Images taken from the proposed randomness-based X-ray imaging (bottom) and the corresponding surface electron microscope (SEM) images (top).
2023.04.12 View 4785 -
KAIST research team develops a cheap and safe redox flow battery
Redox flow batteries, one of the potential replacements for the widely used lithium-ion secondary batteries, can be utilized as new and renewable energy as well as for energy storage systems (ESS) thanks to their low cost, low flammability, and long lifetime of over 20 years. Since the price of vanadium, the most widely used active material for redox flow batteries, has been rising in recent years, scientists have been actively searching for redox materials to replace it.
On March 23, a joint research team led by Professors Hye Ryung Byon and Mu-Hyun Baik from the KAIST Department of Chemistry, and Professor Jongcheol Seo from the POSTECH Department of Chemistry announced that they had developed a highly soluble and stable organic redox-active molecule for use in aqueous redox flow batteries.
The research team focused on developing aqueous redox flow batteries by redesigning an organic molecule. It is possible to control the solubility and electrochemical redox potential of organic molecules by engineering their design, which makes them a promising active material candidate with possibly higher energy storage capabilities than vanadium. Most organic redox-active molecules have low solubilities or have slow chemical stability during redox reactions. Low solubility means low energy storage capacity and low chemical stability leads to reduced cycle performance. For this research, the team chose naphthalene diimide (NDI) as their active molecule. Until now, there was little research done on NDI despite its high chemical stability, as it shows low solubility in aqueous electrolyte solutions.
Although NDI molecules are almost insoluble in water, the research team tethered four ammonium functionalities and achieved a solubility as high as 1.5M* in water. In addition, they confirmed that when a 1M solution of NDI was used in neutral redox flow batteries for 500 cycles, 98% of its capacity was maintained. This means 0.004% capacity decay per cycle, and only 2% of its capacity would be lost if the battery were to be operated for 45 days.
Furthermore, the developed NDI molecule can save two electrons per molecule, and the team proved that 2M of electrons could be stored in every 1M of NDI solution used. For reference, vanadium used in vanadium redox flow batteries, which require a highly concentrated sulfuric acid solution, has a solubility of about 1.6M and can only hold one electron per molecule, meaning it can store a total of 1.6M of electrons. Therefore, the newly developed NDI active molecule shows a higher storage capacity compared to existing vanadium devices.
*1M (mol/L): 6.022 x 1023 active molecules are present in 1L of solution
This paper, written by co-first authors Research Professor Vikram Singh, and Ph.D. candidates Seongyeon Kwon and Yunseop Choi, was published in the online version of Advanced Materials on February 7 under the title, Controlling π-π interactions of highly soluble naphthalene diimide derivatives for neutral pH aqueous redox flow batteries. Ph.D. Candidate Yelim Yi and Professor Mi Hee Lee’s team from the KAIST Department of Chemistry also contributed to the study by conducting electron paramagnetic resonance analyses.
Professor Hye Ryung Byon said, “We have demonstrated the principles of molecular design by modifying an existing organic active molecule with low solubility and utilizing it as an active molecule for redox flow batteries. We have also shown that during a redox reaction, we can use molecular interactions to suppress the chemical reactivity of radically formed molecules.”
She added, “Should this be used later for aqueous redox flow batteries, along with its high energy density and high solubility, it would also have the advantage of being available for use in neutral pH electrolytes. Vanadium redox flow batteries currently use acidic solutions, which cause corrosion, and we expect our molecule to solve this issue. Since existing lithium ion-based ESS are flammable, we must develop safer and cheaper next-generation ESS, and our research has shown great promise in addressing this.”
This research was funded by Samsung Research Funding & Incubation Center, the Institute for Basic Science, and the National Research Foundation.
Figure 1. (a) Structures of various NDI molecules. (b) Solubility of NDI molecules in water (black bars) and aqueous electrolytes including KCl electrolyte (blue bars). (c–d) Structural changes of the molecules as the developed NDI molecule stores two electrons. (c) Illustration of cluster combination and separation of NDI molecules developed during redox reaction and (d) Snapshot of the MD simulation. NDI molecules prepared from the left, formation of bimolecular sieve and tetramolecular sieve clusters after the first reductive reaction, and a single molecule with a three-dimensional structure after the second reduction.
Figure 2. Performance results of an aqueous redox flow battery using 1M of the developed NDI molecule as the cathode electrolyte and 3.1M of ammonium iodine as the anode electrolyte. Using 1.5 M KCl solution. (a) A schematic diagram of a redox flow battery. (b) Voltage-capacity graph according to cycle in a redox flow battery. (c) Graphs of capacity and coulombs, voltage, and energy efficiency maintained at 500 cycles.
2023.04.03 View 4431 -
A biohybrid system to extract 20 times more bioplastic from CO2 developed by KAIST researchers
As the issues surrounding global climate change intensify, more attention and determined efforts are required to re-grasp the issue as a state of “crisis” and respond to it properly. Among the various methods of recycling CO2, the electrochemical CO2 conversion technology is a technology that can convert CO2 into useful chemical substances using electrical energy. Since it is easy to operate facilities and can use the electricity from renewable sources like the solar cells or the wind power, it has received a lot of attention as an eco-friendly technology can contribute to reducing greenhouse gases and achieve carbon neutrality.
KAIST (President Kwang Hyung Lee) announced on the 30th that the joint research team led by Professor Hyunjoo Lee and Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering succeeded in developing a technology that produces bioplastics from CO2 with high efficiency by developing a hybrid system that interlinked the electrochemical CO2 conversion and microbial bio conversion methods together. The results of the research, which showed the world's highest productivity by more than 20 times compared to similar systems, were published online on March 27th in the "Proceedings of the National Academy of Sciences (PNAS)".
※ Paper title: Biohybrid CO2 electrolysis for the direct synthesis of polyesters from CO2
※ Author information: Jinkyu Lim (currently at Stanford Linear Accelerator Center, co-first author), So Young Choi (KAIST, co-first author), Jae Won Lee (KAIST, co-first author), Hyunjoo Lee (KAIST, corresponding author), Sang Yup Lee (KAIST, corresponding author)
For the efficient conversion of CO2, high-efficiency electrode catalysts and systems are actively being developed. As conversion products, only compounds containing one or up to three carbon atoms are produced on a limited basis. Compounds of one carbon, such as CO, formic acid, and ethylene, are produced with relatively high efficiency. Liquid compounds of several carbons, such as ethanol, acetic acid, and propanol, can also be produced by these systems, but due to the nature of the chemical reaction that requires more electrons, there are limitations involving the conversion efficiency and the product selection.
Accordingly, a joint research team led by Professor Hyunjoo Lee and Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering at KAIST developed a technology to produce bioplastics from CO2 by linking electrochemical conversion technology with bioconversion method that uses microorganisms.
This electrochemical-bio hybrid system is in the form of having an electrolyzer, in which electrochemical conversion reactions occur, connected to a fermenter, in which microorganisms are cultured. When CO2 is converted to formic acid in the electrolyzer, and it is fed into the fermenter in which the microbes like the Cupriavidus necator, in this case, consumes the carbon source to produce polyhydroxyalkanoate (PHA), a microbial-derived bioplastic.
According to the research results of the existing hybrid concepts, there was a disadvantage of having low productivity or stopping at a non-continuous process due to problems of low efficiency of the electrolysis and irregular results arising from the culturing conditions of the microbes.
In order to overcome these problems, the joint research team made formic acid with a gas diffusion electrode using gaseous CO2. In addition, the team developed a 'physiologically compatible catholyte' that can be used as a culture medium for microorganisms as well as an electrolyte that allows the electrolysis to occur sufficiently without inhibiting the growth of microorganisms, without having to have a additional separation and purification process, which allowed the acide to be supplied directly to microorganisms.
Through this, the electrolyte solution containing formic acid made from CO2 enters the fermentation tank, is used for microbial culture, and enters the electrolyzer to be circulated, maximizing the utilization of the electrolyte solution and remaining formic acid. In addition, a filter was installed to ensure that only the electrolyte solution with any and all microorganisms that can affect the electrosis filtered out is supplied back to the electrolyzer, and that the microorganisms exist only in the fermenter, designing the two system to work well together with utmost efficiency.
Through the developed hybrid system, the produced bioplastic, poly-3-hydroxybutyrate (PHB), of up to 83% of the cell dry weight was produced from CO2, which produced 1.38g of PHB from a 4 cm2 electrode, which is the world's first gram(g) level production and is more than 20 times more productive than previous research. In addition, the hybrid system is expected to be applied to various industrial processes in the future as it shows promises of the continuous culture system.
The corresponding authors, Professor Hyunjoo Lee and Distinguished Professor Sang Yup Lee noted that “The results of this research are technologies that can be applied to the production of various chemical substances as well as bioplastics, and are expected to be used as key parts needed in achieving carbon neutrality in the future.”
This research was received and performed with the supports from the CO2 Reduction Catalyst and Energy Device Technology Development Project, the Heterogeneous Atomic Catalyst Control Project, and the Next-generation Biorefinery Source Technology Development Project to lead the Biochemical Industry of the Oil-replacement Eco-friendly Chemical Technology Development Program by the Ministry of Science and ICT.
Figure 1. Schematic diagram and photo of the biohybrid CO2 electrolysis system.
(A) A conceptual scheme and (B) a photograph of the biohybrid CO2 electrolysis system. (C) A detailed scheme of reaction inside the system. Gaseous CO2 was converted to formate in the electrolyzer, and the formate was converted to PHB by the cells in the fermenter. The catholyte was developed so that it is compatible with both CO2 electrolysis and fermentation and was continuously circulated.
2023.03.30 View 6606 -
Using light to throw and catch atoms to open up a new chapter for quantum computing
The technology to move and arrange atoms, the most basic component of a quantum computer, is very important to Rydberg quantum computing research. However, to place the atoms at the desired location, the atoms must be captured and transported one by one using a highly focused laser beam, commonly referred to as an optical tweezer. and, the quantum information of the atoms is likely to change midway.
KAIST (President Kwang Hyung Lee) announced on the 27th that a research team led by Professor Jaewook Ahn of the Department of Physics developed a technology to throw and receive rubidium atoms one by one using a laser beam.
The research team developed a method to throw and receive atoms which would minimize the time the optical tweezers are in contact with the atoms in which the quantum information the atoms carry may change. The research team used the characteristic that the rubidium atoms, which are kept at a very low temperature of 40μK below absolute zero, move very sensitively to the electromagnetic force applied by light along the focal point of the light tweezers.
The research team accelerated the laser of an optical tweezer to give an optical kick to an atom to send it to a target, then caught the flying atom with another optical tweezer to stop it. The atom flew at a speed of 65 cm/s, and traveled up to 4.2 μm. Compared to the existing technique of guiding the atoms with the optical tweezers, the technique of throwing and receiving atoms eliminates the need to calculate the transporting path for the tweezers, and makes it easier to fix the defects in the atomic arrangement. As a result, it is effective in generating and maintaining a large number of atomic arrangements, and when the technology is used to throw and receive flying atom qubits, it will be used in studying new and more powerful quantum computing methods that presupposes the structural changes in quantum arrangements.
"This technology will be used to develop larger and more powerful Rydberg quantum computers," says Professor Jaewook Ahn. “In a Rydberg quantum computer,” he continues, “atoms are arranged to store quantum information and interact with neighboring atoms through electromagnetic forces to perform quantum computing. The method of throwing an atom away for quick reconstruction the quantum array can be an effective way to fix an error in a quantum computer that requires a removal or replacement of an atom.”
The research, which was conducted by doctoral students Hansub Hwang and Andrew Byun of the Department of Physics at KAIST and Sylvain de Léséleuc, a researcher at the National Institute of Natural Sciences in Japan, was published in the international journal, Optica, 0n March 9th. (Paper title: Optical tweezers throw and catch single atoms).
This research was carried out with the support of the Samsung Science & Technology Foundation.
<Figure 1> A schematic diagram of the atom catching and throwing technique. The optical tweezer on the left kicks the atom to throw it into a trajectory to have the tweezer on the right catch it to stop it.
2023.03.28 View 4190 -
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 4384 -
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 4044 -
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 5159 -
The cause of disability in aged brain meningeal membranes identified
Due to the increase in average age, studies on changes in the brain following general aging process without serious brain diseases have also become an issue that requires in-depth studies. Regarding aging research, as aging progresses, ‘sugar’ accumulates in the body, and the accumulated sugar becomes a causative agent for various diseases such as aging-related inflammation and vascular disease. In the end, “surplus” sugar molecules attach to various proteins in the body and interfere with their functions.
KAIST (President Kwang Hyung Lee), a joint research team of Professor Pilnam Kim and Professor Yong Jeong of the Department of Bio and Brain Engineering, revealed on the 15th that it was confirmed that the function of being the “front line of defense” for the cerebrocortex of the brain meninges, the layers of membranes that surrounds the brain, is hindered when 'sugar' begins to build up on them as aging progresses.
Professor Kim's research team confirmed excessive accumulation of sugar molecules in the meninges of the elderly and also confirmed that sugar accumulation occurs mouse models in accordance with certain age levels. The meninges are thin membranes that surround the brain and exist at the boundary between the cerebrospinal fluid and the cortex and play an important role in protecting the brain. In this study, it was revealed that the dysfunction of these brain membranes caused by aging is induced by 'excess' sugar in the brain. In particular, as the meningeal membrane becomes thinner and stickier due to aging, a new paradigm has been provided for the discovery of the principle of the decrease in material exchange between the cerebrospinal fluid and the cerebral cortex.
This research was conducted by the Ph.D. candidate Hyo Min Kim and Dr. Shinheun Kim as the co-first authors to be published online on February 28th in the international journal, Aging Cell. (Paper Title: Glycation-mediated tissue-level remodeling of brain meningeal membrane by aging)
The meninges, which are in direct contact with the cerebrospinal fluid, are mainly composed of collagen, an extracellular matrix (ECM) protein, and are composed of fibroblasts, which are cells that produce this protein. The cells that come in contact with collagen proteins that are attached with sugar have a low collagen production function, while the meningeal membrane continuously thins and collapses as the expression of collagen degrading enzymes increases.
Studies on the relationship between excess sugar molecules accumulation in the brain due to continued sugar intake and the degeneration of neurons and brain diseases have been continuously conducted. However, this study was the first to identify meningeal degeneration and dysfunction caused by glucose accumulation with the focus on the meninges itself, and the results are expected to present new ideas for research into approach towards discoveries of new treatments for brain disease.
Researcher Hyomin Kim, the first author, introduced the research results as “an interesting study that identified changes in the barriers of the brain due to aging through a convergent approach, starting from the human brain and utilizing an animal model with a biomimetic meningeal model”.
Professor Pilnam Kim's research team is conducting research and development to remove sugar that accumulated throughout the human body, including the meninges. Advanced glycation end products, which are waste products formed when proteins and sugars meet in the human body, are partially removed by macrophages. However, glycated products bound to extracellular matrix proteins such as collagen are difficult to remove naturally. Through the KAIST-Ceragem Research Center, this research team is developing a healthcare medical device to remove 'sugar residue' in the body.
This study was carried out with the National Research Foundation of Korea's collective research support.
Figure 1. Schematic diagram of proposed mechanism showing aging‐related ECM remodeling through meningeal fibroblasts on the brain leptomeninges. Meningeal fibroblasts in the young brain showed dynamic COL1A1 synthetic and COL1‐interactive function on the collagen membrane. They showed ITGB1‐mediated adhesion on the COL1‐composed leptomeningeal membrane and induction of COL1A1 synthesis for maintaining the collagen membrane. With aging, meningeal fibroblasts showed depletion of COL1A1 synthetic function and altered cell–matrix interaction.
Figure 2. Representative rat meningeal images observed in the study. Compared to young rats, it was confirmed that type 1 collagen (COL1) decreased along with the accumulation of glycated end products (AGE) in the brain membrane of aged rats, and the activity of integrin beta 1 (ITGB1), a representative receptor corresponding to cell-collagen interaction. Instead, it was observed that the activity of discoidin domain receptor 2 (DDR2), one of the tyrosine kinases, increased.
Figure 3. Substance flux through the brain membrane decreases with aging. It was confirmed that the degree of adsorption of fluorescent substances contained in cerebrospinal fluid (CSF) to the brain membrane increased and the degree of entry into the periphery of the cerebral blood vessels decreased in the aged rats. In this study, only the influx into the brain was confirmed during the entry and exit of substances, but the degree of outflow will also be confirmed through future studies.
2023.03.15 View 4598 -
KAIST develops 'MetaVRain' that realizes vivid 3D real-life images
KAIST (President Kwang Hyung Lee) is a high-speed, low-power artificial intelligence (AI: Artificial Intelligent) semiconductor* MetaVRain, which implements artificial intelligence-based 3D rendering that can render images close to real life on mobile devices.
* AI semiconductor: Semiconductor equipped with artificial intelligence processing functions such as recognition, reasoning, learning, and judgment, and implemented with optimized technology based on super intelligence, ultra-low power, and ultra-reliability
The artificial intelligence semiconductor developed by the research team makes the existing ray-tracing*-based 3D rendering driven by GPU into artificial intelligence-based 3D rendering on a newly manufactured AI semiconductor, making it a 3D video capture studio that requires enormous costs. is not needed, so the cost of 3D model production can be greatly reduced and the memory used can be reduced by more than 180 times. In particular, the existing 3D graphic editing and design, which used complex software such as Blender, is replaced with simple artificial intelligence learning, so the general public can easily apply and edit the desired style.
* Ray-tracing: Technology that obtains images close to real life by tracing the trajectory of all light rays that change according to the light source, shape and texture of the object
This research, in which doctoral student Donghyun Han participated as the first author, was presented at the International Solid-State Circuit Design Conference (ISSCC) held in San Francisco, USA from February 18th to 22nd by semiconductor researchers from all over the world.
(Paper Number 2.7, Paper Title: MetaVRain: A 133mW Real-time Hyper-realistic 3D NeRF Processor with 1D-2D Hybrid Neural Engines for Metaverse on Mobile Devices (Authors: Donghyeon Han, Junha Ryu, Sangyeob Kim, Sangjin Kim, and Hoi-Jun Yoo))
Professor Yoo's team discovered inefficient operations that occur when implementing 3D rendering through artificial intelligence, and developed a new concept semiconductor that combines human visual recognition methods to reduce them. When a person remembers an object, he has the cognitive ability to immediately guess what the current object looks like based on the process of starting with a rough outline and gradually specifying its shape, and if it is an object he saw right before. In imitation of such a human cognitive process, the newly developed semiconductor adopts an operation method that grasps the rough shape of an object in advance through low-resolution voxels and minimizes the amount of computation required for current rendering based on the result of rendering in the past.
MetaVRain, developed by Professor Yu's team, achieved the world's best performance by developing a state-of-the-art CMOS chip as well as a hardware architecture that mimics the human visual recognition process. MetaVRain is optimized for artificial intelligence-based 3D rendering technology and achieves a rendering speed of up to 100 FPS or more, which is 911 times faster than conventional GPUs. In addition, as a result of the study, the energy efficiency, which represents the energy consumed per video screen processing, is 26,400 times higher than that of GPU, opening the possibility of artificial intelligence-based real-time rendering in VR/AR headsets and mobile devices.
To show an example of using MetaVRain, the research team developed a smart 3D rendering application system together, and showed an example of changing the style of a 3D model according to the user's preferred style. Since you only need to give artificial intelligence an image of the desired style and perform re-learning, you can easily change the style of the 3D model without the help of complicated software. In addition to the example of the application system implemented by Professor Yu's team, it is expected that various application examples will be possible, such as creating a realistic 3D avatar modeled after a user's face, creating 3D models of various structures, and changing the weather according to the film production environment. do.
Starting with MetaVRain, the research team expects that the field of 3D graphics will also begin to be replaced by artificial intelligence, and revealed that the combination of artificial intelligence and 3D graphics is a great technological innovation for the realization of the metaverse.
Professor Hoi-Jun Yoo of the Department of Electrical and Electronic Engineering at KAIST, who led the research, said, “Currently, 3D graphics are focused on depicting what an object looks like, not how people see it.” The significance of this study was revealed as a study that enabled efficient 3D graphics by borrowing the way people recognize and express objects by imitating them.” He also foresaw the future, saying, “The realization of the metaverse will be achieved through innovation in artificial intelligence technology and innovation in artificial intelligence semiconductors, as shown in this study.”
Figure 1. Description of the MetaVRain demo screen
Photo of Presentation at the International Solid-State Circuits Conference (ISSCC)
2023.03.13 View 4546 -
KAIST team develops smart immune system that can pin down on malignant tumors
A joint research team led by Professor Jung Kyoon Choi of the KAIST Department of Bio and Brain Engineering and Professor Jong-Eun Park of the KAIST Graduate School of Medical Science and Engineering (GSMSE) announced the development of the key technologies to treat cancers using smart immune cells designed based on AI and big data analysis. This technology is expected to be a next-generation immunotherapy that allows precision targeting of tumor cells by having the chimeric antigen receptors (CARs) operate through a logical circuit. Professor Hee Jung An of CHA Bundang Medical Center and Professor Hae-Ock Lee of the Catholic University of Korea also participated in this research to contribute joint effort.
Professor Jung Kyoon Choi’s team built a gene expression database from millions of cells, and used this to successfully develop and verify a deep-learning algorithm that could detect the differences in gene expression patterns between tumor cells and normal cells through a logical circuit. CAR immune cells that were fitted with the logic circuits discovered through this methodology could distinguish between tumorous and normal cells as a computer would, and therefore showed potentials to strike only on tumor cells accurately without causing unwanted side effects.
This research, conducted by co-first authors Dr. Joonha Kwon of the KAIST Department of Bio and Brain Engineering and Ph.D. candidate Junho Kang of KAIST GSMSE, was published by Nature Biotechnology on February 16, under the title Single-cell mapping of combinatorial target antigens for CAR switches using logic gates.
An area in cancer research where the most attempts and advances have been made in recent years is immunotherapy. This field of treatment, which utilizes the patient’s own immune system in order to overcome cancer, has several methods including immune checkpoint inhibitors, cancer vaccines and cellular treatments. Immune cells like CAR-T or CAR-NK equipped with chimera antigen receptors, in particular, can recognize cancer antigens and directly destroy cancer cells.
Starting with its success in blood cancer treatment, scientists have been trying to expand the application of CAR cell therapy to treat solid cancer. But there have been difficulties to develop CAR cells with effective killing abilities against solid cancer cells with minimized side effects. Accordingly, in recent years, the development of smarter CAR engineering technologies, i.e., computational logic gates such as AND, OR, and NOT, to effectively target cancer cells has been underway.
At this point in time, the research team built a large-scale database for cancer and normal cells to discover the exact genes that are expressed only from cancer cells at a single-cell level. The team followed this up by developing an AI algorithm that could search for a combination of genes that best distinguishes cancer cells from normal cells. This algorithm, in particular, has been used to find a logic circuit that can specifically target cancer cells through cell-level simulations of all gene combinations. CAR-T cells equipped with logic circuits discovered through this methodology are expected to distinguish cancerous cells from normal cells like computers, thereby minimizing side effects and maximizing the effects of chemotherapy.
Dr. Joonha Kwon, who is the first author of this paper, said, “this research suggests a new method that hasn’t been tried before. What’s particularly noteworthy is the process in which we found the optimal CAR cell circuit through simulations of millions of individual tumors and normal cells.” He added, “This is an innovative technology that can apply AI and computer logic circuits to immune cell engineering. It would contribute greatly to expanding CAR therapy, which is being successfully used for blood cancer, to solid cancers as well.”
This research was funded by the Original Technology Development Project and Research Program for Next Generation Applied Omic of the Korea Research Foundation.
Figure 1. A schematic diagram of manufacturing and administration process of CAR therapy and of cancer cell-specific dual targeting using CAR.
Figure 2. Deep learning (convolutional neural networks, CNNs) algorithm for selection of dual targets based on gene combination (left) and algorithm for calculating expressing cell fractions by gene combination according to logical circuit (right).
2023.03.09 View 6070