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A Mechanism Underlying Most Common Cause of Epileptic Seizures Revealed
An interdisciplinary study shows that neurons carrying somatic mutations in MTOR can lead to focal epileptogenesis via non-cell-autonomous hyperexcitability of nearby nonmutated neurons
During fetal development, cells should migrate to the outer edge of the brain to form critical connections for information transfer and regulation in the body. When even a few cells fail to move to the correct location, the neurons become disorganized and this results in focal cortical dysplasia. This condition is the most common cause of seizures that cannot be controlled with medication in children and the second most common cause in adults.
Now, an interdisciplinary team studying neurogenetics, neural networks, and neurophysiology at KAIST has revealed how dysfunctions in even a small percentage of cells can cause disorder across the entire brain. They published their results on June 28 in Annals of Neurology.
The work builds on a previous finding, also by a KAIST scientists, who found that focal cortical dysplasia was caused by mutations in the cells involved in mTOR, a pathway that regulates signaling between neurons in the brain.
“Only 1 to 2% of neurons carrying mutations in the mTOR signaling pathway that regulates cell signaling in the brain have been found to include seizures in animal models of focal cortical dysplasia,” said Professor Jong-Woo Sohn from the Department of Biological Sciences. “The main challenge of this study was to explain how nearby non-mutated neurons are hyperexcitable.”
Initially, the researchers hypothesized that the mutated cells affected the number of excitatory and inhibitory synapses in all neurons, mutated or not. These neural gates can trigger or halt activity, respectively, in other neurons. Seizures are a result of extreme activity, called hyperexcitability. If the mutated cells upend the balance and result in more excitatory cells, the researchers thought, it made sense that the cells would be more susceptible to hyperexcitability and, as a result, seizures.
“Contrary to our expectations, the synaptic input balance was not changed in either the mutated or non-mutated neurons,” said Professor Jeong Ho Lee from the Graduate School of Medical Science and Engineering. “We turned our attention to a protein overproduced by mutated neurons.”
The protein is adenosine kinase, which lowers the concentration of adenosine. This naturally occurring compound is an anticonvulsant and works to relax vessels. In mice engineered to have focal cortical dysplasia, the researchers injected adenosine to replace the levels lowered by the protein. It worked and the neurons became less excitable.
“We demonstrated that augmentation of adenosine signaling could attenuate the excitability of non-mutated neurons,” said Professor Se-Bum Paik from the Department of Bio and Brain Engineering.
The effect on the non-mutated neurons was the surprising part, according to Paik. “The seizure-triggering hyperexcitability originated not in the mutation-carrying neurons, but instead in the nearby non-mutated neurons,” he said.
The mutated neurons excreted more adenosine kinase, reducing the adenosine levels in the local environment of all the cells. With less adenosine, the non-mutated neurons became hyperexcitable, leading to seizures.
“While we need further investigate into the relationship between the concentration of adenosine and the increased excitation of nearby neurons, our results support the medical use of drugs to activate adenosine signaling as a possible treatment pathway for focal cortical dysplasia,” Professor Lee said.
The Suh Kyungbae Foundation, the Korea Health Technology Research and Development Project, the Ministry of Health & Welfare, and the National Research Foundation in Korea funded this work.
-Publication:Koh, H.Y., Jang, J., Ju, S.H., Kim, R., Cho, G.-B., Kim, D.S., Sohn, J.-W., Paik, S.-B. and Lee, J.H. (2021), ‘Non–Cell Autonomous Epileptogenesis in Focal Cortical Dysplasia’ Annals of Neurology, 90: 285 299. (https://doi.org/10.1002/ana.26149)
-ProfileProfessor Jeong Ho Lee Translational Neurogenetics Labhttps://tnl.kaist.ac.kr/ Graduate School of Medical Science and Engineering KAIST
Professor Se-Bum Paik Visual System and Neural Network Laboratory http://vs.kaist.ac.kr/ Department of Bio and Brain EngineeringKAIST
Professor Jong-Woo Sohn Laboratory for Neurophysiology, https://sites.google.com/site/sohnlab2014/home Department of Biological SciencesKAIST
Dr. Hyun Yong Koh Translational Neurogenetics LabGraduate School of Medical Science and EngineeringKAIST
Dr. Jaeson Jang Ph.D.Visual System and Neural Network LaboratoryDepartment of Bio and Brain Engineering KAIST
Sang Hyeon Ju M.D.Laboratory for NeurophysiologyDepartment of Biological SciencesKAIST
2021.08.26 View 10374 -
3D Visualization and Quantification of Bioplastic PHA in a Living Bacterial Cell
3D holographic microscopy leads to in-depth analysis of bacterial cells accumulating the bacterial bioplastic, polyhydroxyalkanoate (PHA)
A research team at KAIST has observed how bioplastic granule is being accumulated in living bacteria cells through 3D holographic microscopy. Their 3D imaging and quantitative analysis of the bioplastic ‘polyhydroxyalkanoate’ (PHA) via optical diffraction tomography provides insights into biosynthesizing sustainable substitutes for petroleum-based plastics.
The bio-degradable polyester polyhydroxyalkanoate (PHA) is being touted as an eco-friendly bioplastic to replace existing synthetic plastics. While carrying similar properties to general-purpose plastics such as polyethylene and polypropylene, PHA can be used in various industrial applications such as container packaging and disposable products.
PHA is synthesized by numerous bacteria as an energy and carbon storage material under unbalanced growth conditions in the presence of excess carbon sources. PHA exists in the form of insoluble granules in the cytoplasm. Previous studies on investigating in vivo PHA granules have been performed by using fluorescence microscopy, transmission electron microscopy (TEM), and electron cryotomography.
These techniques have generally relied on the statistical analysis of multiple 2D snapshots of fixed cells or the short-time monitoring of the cells. For the TEM analysis, cells need to be fixed and sectioned, and thus the investigation of living cells was not possible. Fluorescence-based techniques require fluorescence labeling or dye staining. Thus, indirect imaging with the use of reporter proteins cannot show the native state of PHAs or cells, and invasive exogenous dyes can affect the physiology and viability of the cells. Therefore, it was difficult to fully understand the formation of PHA granules in cells due to the technical limitations, and thus several mechanism models based on the observations have been only proposed.
The team of metabolic engineering researchers led by Distinguished Professor Sang Yup Lee and Physics Professor YongKeun Park, who established the startup Tomocube with his 3D holographic microscopy, reported the results of 3D quantitative label-free analysis of PHA granules in individual live bacterial cells by measuring the refractive index distributions using optical diffraction tomography. The formation and growth of PHA granules in the cells of Cupriavidus necator, the most-studied native PHA (specifically, poly(3-hydroxybutyrate), also known as PHB) producer, and recombinant Escherichia coli harboring C. necator PHB biosynthesis pathway were comparatively examined.
From the reconstructed 3D refractive index distribution of the cells, the team succeeded in the 3D visualization and quantitative analysis of cells and intracellular PHA granules at a single-cell level. In particular, the team newly presented the concept of “in vivo PHA granule density.” Through the statistical analysis of hundreds of single cells accumulating PHA granules, the distinctive differences of density and localization of PHA granules in the two micro-organisms were found. Furthermore, the team identified the key protein that plays a major role in making the difference that enabled the characteristics of PHA granules in the recombinant E. coli to become similar to those of C. necator.
The research team also presented 3D time-lapse movies showing the actual processes of PHA granule formation combined with cell growth and division. Movies showing the living cells synthesizing and accumulating PHA granules in their native state had never been reported before.
Professor Lee said, “This study provides insights into the morphological and physical characteristics of in vivo PHA as well as the unique mechanisms of PHA granule formation that undergo the phase transition from soluble monomers into the insoluble polymer, followed by granule formation. Through this study, a deeper understanding of PHA granule formation within the bacterial cells is now possible, which has great significance in that a convergence study of biology and physics was achieved. This study will help develop various bioplastics production processes in the future.”
This work was supported by the Technology Development Program to Solve Climate Changes on Systems Metabolic Engineering for Biorefineries (Grants NRF-2012M1A2A2026556 and NRF-2012M1A2A2026557) and the Bio & Medical Technology Development Program (Grant No. 2021M3A9I4022740) from the Ministry of Science and ICT (MSIT) through the National Research Foundation (NRF) of Korea to S.Y.L. This work was also supported by the KAIST Cross-Generation Collaborative Laboratory project.
-PublicationSo Young Choi, Jeonghun Oh, JaeHwang Jung, YongKeun Park, and Sang Yup Lee. Three-dimensional label-free visualization and quantification of polyhydroxyalkanoates in individualbacterial cell in its native state. PNAS(https://doi.org./10.1073/pnas.2103956118)
-ProfileDistinguished Professor Sang Yup LeeMetabolic Engineering and Synthetic Biologyhttp://mbel.kaist.ac.kr/
Department of Chemical and Biomolecular Engineering KAIST
Endowed Chair Professor YongKeun ParkBiomedical Optics Laboratoryhttps://bmokaist.wordpress.com/
Department of PhysicsKAIST
2021.07.28 View 10343 -
Hydrogel-Based Flexible Brain-Machine Interface
The interface is easy to insert into the body when dry, but behaves ‘stealthily’ inside the brain when wet
Professor Seongjun Park’s research team and collaborators revealed a newly developed hydrogel-based flexible brain-machine interface. To study the structure of the brain or to identify and treat neurological diseases, it is crucial to develop an interface that can stimulate the brain and detect its signals in real time. However, existing neural interfaces are mechanically and chemically different from real brain tissue. This causes foreign body response and forms an insulating layer (glial scar) around the interface, which shortens its lifespan.
To solve this problem, the research team developed a ‘brain-mimicking interface’ by inserting a custom-made multifunctional fiber bundle into the hydrogel body. The device is composed not only of an optical fiber that controls specific nerve cells with light in order to perform optogenetic procedures, but it also has an electrode bundle to read brain signals and a microfluidic channel to deliver drugs to the brain.
The interface is easy to insert into the body when dry, as hydrogels become solid. But once in the body, the hydrogel will quickly absorb body fluids and resemble the properties of its surrounding tissues, thereby minimizing foreign body response.
The research team applied the device on animal models, and showed that it was possible to detect neural signals for up to six months, which is far beyond what had been previously recorded. It was also possible to conduct long-term optogenetic and behavioral experiments on freely moving mice with a significant reduction in foreign body responses such as glial and immunological activation compared to existing devices.
“This research is significant in that it was the first to utilize a hydrogel as part of a multifunctional neural interface probe, which increased its lifespan dramatically,” said Professor Park. “With our discovery, we look forward to advancements in research on neurological disorders like Alzheimer’s or Parkinson’s disease that require long-term observation.”
The research was published in Nature Communications on June 8, 2021. (Title: Adaptive and multifunctional hydrogel hybrid probes for long-term sensing and modulation of neural activity) The study was conducted jointly with an MIT research team composed of Professor Polina Anikeeva, Professor Xuanhe Zhao, and Dr. Hyunwoo Yook.
This research was supported by the National Research Foundation (NRF) grant for emerging research, Korea Medical Device Development Fund, KK-JRC Smart Project, KAIST Global Initiative Program, and Post-AI Project.
-PublicationPark, S., Yuk, H., Zhao, R. et al. Adaptive and multifunctional hydrogel hybrid probes for long-term sensing and modulation of neural activity. Nat Commun 12, 3435 (2021). https://doi.org/10.1038/s41467-021-23802-9
-ProfileProfessor Seongjun ParkBio and Neural Interfaces LaboratoryDepartment of Bio and Brain EngineeringKAIST
2021.07.13 View 9336 -
Repurposed Drugs Present New Strategy for Treating COVID-19
Virtual screening of 6,218 drugs and cell-based assays identifies best therapeutic medication candidates
A joint research group from KAIST and Institut Pasteur Korea has identified repurposed drugs for COVID-19 treatment through virtual screening and cell-based assays. The research team suggested the strategy for virtual screening with greatly reduced false positives by incorporating pre-docking filtering based on shape similarity and post-docking filtering based on interaction similarity. This strategy will help develop therapeutic medications for COVID-19 and other antiviral diseases more rapidly. This study was reported at the Proceedings of the National Academy of Sciences of the United States of America (PNAS).
Researchers screened 6,218 drugs from a collection of FDA-approved drugs or those under clinical trial and identified 38 potential repurposed drugs for COVID-19 with this strategy. Among them, seven compounds inhibited SARS-CoV-2 replication in Vero cells. Three of these drugs, emodin, omipalisib, and tipifarnib, showed anti-SARS-CoV-2 activity in human lung cells, Calu-3.
Drug repurposing is a practical strategy for developing antiviral drugs in a short period of time, especially during a global pandemic. In many instances, drug repurposing starts with the virtual screening of approved drugs. However, the actual hit rate of virtual screening is low and most of the predicted drug candidates are false positives.
The research group developed effective filtering algorithms before and after the docking simulations to improve the hit rates. In the pre-docking filtering process, compounds with similar shapes to the known active compounds for each target protein were selected and used for docking simulations. In the post-docking filtering process, the chemicals identified through their docking simulations were evaluated considering the docking energy and the similarity of the protein-ligand interactions with the known active compounds.
The experimental results showed that the virtual screening strategy reached a high hit rate of 18.4%, leading to the identification of seven potential drugs out of the 38 drugs initially selected.
“We plan to conduct further preclinical trials for optimizing drug concentrations as one of the three candidates didn’t resolve the toxicity issues in preclinical trials,” said Woo Dae Jang, one of the researchers from KAIST.
“The most important part of this research is that we developed a platform technology that can rapidly identify novel compounds for COVID-19 treatment. If we use this technology, we will be able to quickly respond to new infectious diseases as well as variants of the coronavirus,” said Distinguished Professor Sang Yup Lee.
This work was supported by the KAIST Mobile Clinic Module Project funded by the Ministry of Science and ICT (MSIT) and the National Research Foundation of Korea (NRF). The National Culture Collection for Pathogens in Korea provided the SARS-CoV-2 (NCCP43326).
-PublicationWoo Dae Jang, Sangeun Jeon, Seungtaek Kim, and Sang Yup Lee. Drugs repurposed for COVID-19 by virtual screening of 6,218 drugs and cell-based assay. Proc. Natl. Acad. Sci. U.S.A. (https://doi/org/10.1073/pnas.2024302118)
-ProfileDistinguished Professor Sang Yup LeeMetabolic &Biomolecular Engineering National Research Laboratoryhttp://mbel.kaist.ac.kr
Department of Chemical and Biomolecular EngineeringKAIST
2021.07.08 View 10746 -
Quantum Laser Turns Energy Loss into Gain
A new laser that generates quantum particles can recycle lost energy for highly efficient, low threshold laser applications
Scientists at KAIST have fabricated a laser system that generates highly interactive quantum particles at room temperature. Their findings, published in the journal Nature Photonics, could lead to a single microcavity laser system that requires lower threshold energy as its energy loss increases.
The system, developed by KAIST physicist Yong-Hoon Cho and colleagues, involves shining light through a single hexagonal-shaped microcavity treated with a loss-modulated silicon nitride substrate. The system design leads to the generation of a polariton laser at room temperature, which is exciting because this usually requires cryogenic temperatures.
The researchers found another unique and counter-intuitive feature of this design. Normally, energy is lost during laser operation. But in this system, as energy loss increased, the amount of energy needed to induce lasing decreased. Exploiting this phenomenon could lead to the development of high efficiency, low threshold lasers for future quantum optical devices.
“This system applies a concept of quantum physics known as parity-time reversal symmetry,” explains Professor Cho. “This is an important platform that allows energy loss to be used as gain. It can be used to reduce laser threshold energy for classical optical devices and sensors, as well as quantum devices and controlling the direction of light.”
The key is the design and materials. The hexagonal microcavity divides light particles into two different modes: one that passes through the upward-facing triangle of the hexagon and another that passes through its downward-facing triangle. Both modes of light particles have the same energy and path but don’t interact with each other.
However, the light particles do interact with other particles called excitons, provided by the hexagonal microcavity, which is made of semiconductors. This interaction leads to the generation of new quantum particles called polaritons that then interact with each other to generate the polariton laser. By controlling the degree of loss between the microcavity and the semiconductor substrate, an intriguing phenomenon arises, with the threshold energy becoming smaller as energy loss increases. This research was supported by the Samsung Science and Technology Foundation and Korea’s National Research Foundation.
-PublicationSong,H.G, Choi, M, Woo, K.Y. Yong-Hoon Cho Room-temperature polaritonic non-Hermitian system with single microcavityNature Photonics (https://doi.org/10.1038/s41566-021-00820-z)
-ProfileProfessor Yong-Hoon ChoQuantum & Nanobio Photonics Laboratoryhttp://qnp.kaist.ac.kr/
Department of PhysicsKAIST
2021.07.07 View 8398 -
Wearable Device to Monitor Sweat in Real Time
An on-skin platform for the wireless monitoring of flow rate, cumulative loss, and temperature of sweat in real time
An electronic patch can monitor your sweating and check your health status. Even more, the soft microfluidic device that adheres to the surface of the skin, captures, stores, and performs biomarker analysis of sweat as it is released through the eccrine glands.
This wearable and wireless electronic device developed by Professor Kyeongha Kwon and her collaborators is a digital and wireless platform that could help track the so-called ‘filling process’ of sweat without having to visually examine the device. The platform was integrated with microfluidic systems to analyze the sweat’s components.
To monitor the sweat release rate in real time, the researchers created a ‘thermal flow sensing module.’ They designed a sophisticated microfluidic channel to allow the collected sweat to flow through a narrow passage and a heat source was placed on the outer surface of the channel to induce a heat exchange between the sweat and the heated channel.
As a result, the researchers could develop a wireless electronic patch that can measure the temperature difference in a specific location upstream and downstream of the heat source with an electronic circuit and convert it into a digital signal to measure the sweat release rate in real time. The patch accurately measured the perspiration rate in the range of 0-5 microliters/minute (μl/min), which was considered physiologically significant. The sensor can measure the flow of sweat directly and then use the information it collected to quantify total sweat loss. Moreover, the device features advanced microfluidic systems and colorimetric chemical reagents to gather pH measurements and determine the concentration of chloride, creatinine, and glucose in a user's sweat.
Professor Kwon said that these indicators could be used to diagnose various diseases related with sweating such as cystic fibrosis, diabetes, kidney dysfunction, and metabolic alkalosis. “As the sweat flowing in the microfluidic channel is completely separated from the electronic circuit, the new patch overcame the shortcomings of existing flow rate measuring devices, which were vulnerable to corrosion and aging,” she explained.
The patch can be easily attached to the skin with flexible circuit board printing technology and silicone sealing technology. It has an additional sensor that detects changes in skin temperature. Using a smartphone app, a user can check the data measured by the wearable patch in real time.
Professor Kwon added, “This patch can be widely used for personal hydration strategies, the detection of dehydration symptoms, and other health management purposes. It can also be used in a systematic drug delivery system, such as for measuring the blood flow rate in blood vessels near the skin’s surface or measuring a drug’s release rate in real time to calculate the exact dosage.”
-PublicationKyeongha Kwon, Jong Uk Kim, John A. Rogers, et al. “An on-skin platform for wireless monitoring of flow rate, cumulative loss and temperature of sweat in real time.” Nature Electronics (doi.org/10.1038/s41928-021-00556-2)
-ProfileProfessor Kyeongha KwonSchool of Electrical EngineeringKAIST
2021.06.25 View 8110 -
Mobile Clinic Module Wins Red Dot and iF Design Awards
The Mobile Clinic Module (MCM), an inflatable negative pressure ward building system developed by the Korea Aid for Respiratory Epidemic (KARE) initiative at KAIST, gained international acclaim by winning the prestigious Red Dot Design Award and iF Design Award.
The MCM was recognized as one of the Red Dot Product Designs of the Year. It also won four iF Design Awards in communication design, interior architecture, user interface, and user experience. Winning the two most influential design awards demonstrates how product design can make a valuable contribution to help contain pandemics and reflects new consumer trends for dealing with pandemics.
Designed to be patient friendly, even in the extreme medical situations such as pandemics or triage, the MCM is the result of collaborations among researchers in a variety of fields including mechanical engineering, computing, industrial and systems engineering, medical hospitals, and engineering companies. The research team was led by Professor Tek-Jin Nam from the Department of Industrial Design.
The MCM is expandable, moveable, and easy to store through a combination of negative pressure frames, air tents, and multi-functional panels. Positive air pressure devices supply fresh air from outside the tent. An air pump and controller maintain air beam pressure, while filtering exhausted air from inside. An internal air information monitoring system efficiently controls inside air pressure and purifies the air. It requires only one-fourth of the volume of existing wards and takes up approximately 40% of their weight. The unit can be transported in a 40-foot container truck.
MCMs are now located at the Korea Institute of Radiological & Medical Sciences and Jeju Vaccine Center and expect to be used at many other facilities. KARE is developing antiviral solutions and devices such as protective gear, sterilizers, and test kits to promptly respond to the pandemic. More than 100 researchers at KAIST are collaborating with industry and clinical hospitals to develop antiviral technologies that will improve preventive measures, diagnoses, and treatments.
Professor Nam said, “Our designers will continue to identify the most challenging issues, and try to resolve them by realizing user-friendly functions. We believe this will significantly contribute to relieving the drastic need for negative pressure beds and provide a place for monitoring patients with moderate symptoms. We look forward to the MCM upgrading epidemic management resources around the globe.”
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2021.04.21 View 7566 -
Professor Jihee Kim Wins the Lucas Prize for Her Income Inequality Theory
Professor Jihee Kim from the School of Business and Technology Management at KAIST was announced as one of two winners of the 2021 Robert E. Lucas Jr. Prize. Professor Kim was recognized for having provided an empirical analysis on engines of income growth, sources of income inequality, and their rich interplay in her paper published in the Journal of Political Economy (JPE) in October 2018. The co-author of this study, Professor Charles I. Jones at Stanford University, was honored to be another awardee of this year’s Lucas Prize.
The Robert E. Lucas Jr. Prize, simply known as the Lucas Prize, is awarded biannually for the most interesting paper in the area of Dynamic Economics published in the leading economics journal JPE in the preceding two years. The prize was established in 2016 in celebration of the 1995 Nobel Prize in Economics Laureate Dr. Lucas’s seminal contributions to economics. The two former prizes were presented in 2019 and 2017 respectively.
Professor Kim and Professor Jones, in their award-winning paper titled 'A Schumpeterian Model of Top Income Inequality', observed that top income inequality was relatively low and stable between 1960 and 1980, but then rose sharply in some countries, including the United States and the United Kingdom.
The authors focused on entrepreneurial activities and the resulting income as the driving force of income inequality. They assumed that the forces that increased the efforts of fast-growing entrepreneurs to improve their products or increased productivity of their efforts could increase income inequality. On the other hand, the forces that enhanced creative destruction or that raised the rate at which high-growth entrepreneurs lost that status could decrease income inequality, according to the authors’ theory.
Professor Kim explained, “Various economic forces due to globalization, the advancement in AI and IT technologies, taxes, and policies related to innovation blocking may explain the varied patterns in income inequality.”
“Through follow-up research, I will continue developing economic theory models that can analyze the impact of changes such as income tax rates and salary negotiations on income inequality,” she added.
Professor Kim received her bachelor’s degree from the KAIST School of Computing in 2005 and pursued her graduates studies at Stanford University, acquiring a master’s degree in economics in 2011 and a doctoral degree in management science and engineering in 2013.
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2021.03.26 View 7014 -
Professor Jae Kyoung Kim to Lead a New Mathematical Biology Research Group at IBS
Professor Jae Kyoung Kim from the KAIST Department of Mathematical Sciences was appointed as the third Chief Investigator (CI) of the Pioneer Research Center (PRC) for Mathematical and Computational Sciences at the Institute for Basic Science (IBS). Professor Kim will launch and lead a new research group that will be devoted to resolving various biological conundrums from a mathematical perspective. His appointment began on March 1, 2021.
Professor Kim, a rising researcher in the field of mathematical biology, has received attention from both the mathematical and biological communities at the international level. Professor Kim puts novel and unremitting efforts into understanding biological systems such as cell-to-cell interactions mathematically and designing mathematical models for identifying causes of diseases and developing therapeutic medicines.
Through active joint research with biologists, mathematician Kim has addressed many challenges that have remained unsolved in biology and published papers in a number of leading international journals in related fields. His notable works based on mathematical modelling include having designed a biological circuit that can maintain a stable circadian rhythm (Science, 2015) and unveiling the principles of how the biological clock in the body maintains a steady speed for the first time in over 60 years (Molecular Cell, 2015). Recently, through a joint research project with Pfizer, Professor Kim identified what causes the differences between animal and clinical test results during drug development explaining why drugs have different efficacies in different people (Molecular Systems Biology, 2019).
The new IBS biomedical mathematics research group led by Professor Kim will further investigate the causes of unstable circadian rhythms and sleeping patterns. The team will aim to present a new paradigm in treatments for sleep disorders.
Professor Kim said, “We are all so familiar with sleep behaviors, but the exact mechanisms behind how such behaviors occur are still unknown. Through cooperation with biomedical scientists, our group will do its best to discover the complicated, fundamental mechanisms of sleep, and investigate the causes and cures of sleep disorders.”
Every year, the IBS selects young and promising researchers and appoints them as CIs. A maximum of five selected CIs can form each independent research group within the IBS PRC, and receive research funds of 1 billion to 1.5 billion KRW over five years.
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2021.03.18 View 8171 -
Acoustic Graphene Plasmons Study Paves Way for Optoelectronic Applications
- The first images of mid-infrared optical waves compressed 1,000 times captured using a highly sensitive scattering-type scanning near-field optical microscope. -
KAIST researchers and their collaborators at home and abroad have successfully demonstrated a new methodology for direct near-field optical imaging of acoustic graphene plasmon fields. This strategy will provide a breakthrough for the practical applications of acoustic graphene plasmon platforms in next-generation, high-performance, graphene-based optoelectronic devices with enhanced light-matter interactions and lower propagation loss.
It was recently demonstrated that ‘graphene plasmons’ – collective oscillations of free electrons in graphene coupled to electromagnetic waves of light – can be used to trap and compress optical waves inside a very thin dielectric layer separating graphene from a metallic sheet. In such a configuration, graphene’s conduction electrons are “reflected” in the metal, so when the light waves “push” the electrons in graphene, their image charges in metal also start to oscillate. This new type of collective electronic oscillation mode is called ‘acoustic graphene plasmon (AGP)’.
The existence of AGP could previously be observed only via indirect methods such as far-field infrared spectroscopy and photocurrent mapping. This indirect observation was the price that researchers had to pay for the strong compression of optical waves inside nanometer-thin structures. It was believed that the intensity of electromagnetic fields outside the device was insufficient for direct near-field optical imaging of AGP.
Challenged by these limitations, three research groups combined their efforts to bring together a unique experimental technique using advanced nanofabrication methods. Their findings were published in Nature Communications on February 19.
A KAIST research team led by Professor Min Seok Jang from the School of Electrical Engineering used a highly sensitive scattering-type scanning near-field optical microscope (s-SNOM) to directly measure the optical fields of the AGP waves propagating in a nanometer-thin waveguide, visualizing thousand-fold compression of mid-infrared light for the first time.
Professor Jang and a post-doc researcher in his group, Sergey G. Menabde, successfully obtained direct images of AGP waves by taking advantage of their rapidly decaying yet always present electric field above graphene. They showed that AGPs are detectable even when most of their energy is flowing inside the dielectric below the graphene.
This became possible due to the ultra-smooth surfaces inside the nano-waveguides where plasmonic waves can propagate at longer distances. The AGP mode probed by the researchers was up to 2.3 times more confined and exhibited a 1.4 times higher figure of merit in terms of the normalized propagation length compared to the graphene surface plasmon under similar conditions.
These ultra-smooth nanostructures of the waveguides used in the experiment were created using a template-stripping method by Professor Sang-Hyun Oh and a post-doc researcher, In-Ho Lee, from the Department of Electrical and Computer Engineering at the University of Minnesota.
Professor Young Hee Lee and his researchers at the Center for Integrated Nanostructure Physics (CINAP) of the Institute of Basic Science (IBS) at Sungkyunkwan University synthesized the graphene with a monocrystalline structure, and this high-quality, large-area graphene enabled low-loss plasmonic propagation.
The chemical and physical properties of many important organic molecules can be detected and evaluated by their absorption signatures in the mid-infrared spectrum. However, conventional detection methods require a large number of molecules for successful detection, whereas the ultra-compressed AGP fields can provide strong light-matter interactions at the microscopic level, thus significantly improving the detection sensitivity down to a single molecule.
Furthermore, the study conducted by Professor Jang and the team demonstrated that the mid-infrared AGPs are inherently less sensitive to losses in graphene due to their fields being mostly confined within the dielectric. The research team’s reported results suggest that AGPs could become a promising platform for electrically tunable graphene-based optoelectronic devices that typically suffer from higher absorption rates in graphene such as metasurfaces, optical switches, photovoltaics, and other optoelectronic applications operating at infrared frequencies.
Professor Jang said, “Our research revealed that the ultra-compressed electromagnetic fields of acoustic graphene plasmons can be directly accessed through near-field optical microscopy methods. I hope this realization will motivate other researchers to apply AGPs to various problems where strong light-matter interactions and lower propagation loss are needed.”
This research was primarily funded by the Samsung Research Funding & Incubation Center of Samsung Electronics. The National Research Foundation of Korea (NRF), the U.S. National Science Foundation (NSF), Samsung Global Research Outreach (GRO) Program, and Institute for Basic Science of Korea (IBS) also supported the work.
Publication:
Menabde, S. G., et al. (2021) Real-space imaging of acoustic plasmons in large-area graphene grown by chemical vapor deposition. Nature Communications 12, Article No. 938. Available online at https://doi.org/10.1038/s41467-021-21193-5
Profile:
Min Seok Jang, MS, PhD
Associate Professorjang.minseok@kaist.ac.krhttp://jlab.kaist.ac.kr/
Min Seok Jang Research GroupSchool of Electrical Engineering
http://kaist.ac.kr/en/Korea Advanced Institute of Science and Technology (KAIST)Daejeon, Republic of Korea
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2021.03.16 View 12314 -
Professor Mu-Hyun Baik Honored with the POSCO TJ Park Prize
Professor Mu-Hyun Baik at the Department of Chemistry was honored to be the recipient of the 2021 POSCO TJ Park Prize in Science. The POSCO TJ Park Foundation awards every year the individual or organization which made significant contribution in science, education, community development, philanthropy, and technology.
Professor Baik, a renowned computational chemist in analyzing complicated chemical reactions to understand how molecules behave and how they change. Professor Baik was awarded in recognition of his pioneering research in designing numerous organometallic catalysts with using computational molecular modelling. In 2016, he published in Science on the catalytic borylation of methane that showed how chemical reactions can be carried out using the natural gas methane as a substrate.
In 2020, he reported in Science that electrodes can be used as functional groups with adjustable inductive effects to change the chemical reactivity of molecules that are attached to them, closely mimicking the inductive effect of conventional functional groups. This constitutes a potentially powerful new way of controlling chemical reactions, offering an alternative to preparing derivatives to install electron-withdrawing functional groups.
Joined at KAIST in 2015, Professor Baik also serves as associate director at the Center for Catalytic Hydrocarbon Functionalization at the Institute for Basic Science (IBS) since 2015. Among the many recognitions and awards that he received include the Kavli Fellowship by the Kavli Foundation and the National Academy of Science in the US in 2019 and the 2018 Friedrich Wilhelm Bessel Award by the Alexander von Humboldt Foundation in Germany.
2021.03.11 View 7470 -
Deep-Learning and 3D Holographic Microscopy Beats Scientists at Analyzing Cancer Immunotherapy
Live tracking and analyzing of the dynamics of chimeric antigen receptor (CAR) T-cells targeting cancer cells can open new avenues for the development of cancer immunotherapy. However, imaging via conventional microscopy approaches can result in cellular damage, and assessments of cell-to-cell interactions are extremely difficult and labor-intensive. When researchers applied deep learning and 3D holographic microscopy to the task, however, they not only avoided these difficultues but found that AI was better at it than humans were.
Artificial intelligence (AI) is helping researchers decipher images from a new holographic microscopy technique needed to investigate a key process in cancer immunotherapy “live” as it takes place. The AI transformed work that, if performed manually by scientists, would otherwise be incredibly labor-intensive and time-consuming into one that is not only effortless but done better than they could have done it themselves. The research, conducted by the team of Professor YongKeun Park from the Department of Physics, appeared in the journal eLife last December.
A critical stage in the development of the human immune system’s ability to respond not just generally to any invader (such as pathogens or cancer cells) but specifically to that particular type of invader and remember it should it attempt to invade again is the formation of a junction between an immune cell called a T-cell and a cell that presents the antigen, or part of the invader that is causing the problem, to it. This process is like when a picture of a suspect is sent to a police car so that the officers can recognize the criminal they are trying to track down. The junction between the two cells, called the immunological synapse, or IS, is the key process in teaching the immune system how to recognize a specific type of invader.
Since the formation of the IS junction is such a critical step for the initiation of an antigen-specific immune response, various techniques allowing researchers to observe the process as it happens have been used to study its dynamics. Most of these live imaging techniques rely on fluorescence microscopy, where genetic tweaking causes part of a protein from a cell to fluoresce, in turn allowing the subject to be tracked via fluorescence rather than via the reflected light used in many conventional microscopy techniques.
However, fluorescence-based imaging can suffer from effects such as photo-bleaching and photo-toxicity, preventing the assessment of dynamic changes in the IS junction process over the long term. Fluorescence-based imaging still involves illumination, whereupon the fluorophores (chemical compounds that cause the fluorescence) emit light of a different color. Photo-bleaching or photo-toxicity occur when the subject is exposed to too much illumination, resulting in chemical alteration or cellular damage.
One recent option that does away with fluorescent labelling and thereby avoids such problems is 3D holographic microscopy or holotomography (HT). In this technique, the refractive index (the way that light changes direction when encountering a substance with a different density—why a straw looks like it bends in a glass of water) is recorded in 3D as a hologram.
Until now, HT has been used to study single cells, but never cell-cell interactions involved in immune responses. One of the main reasons is the difficulty of “segmentation,” or distinguishing the different parts of a cell and thus distinguishing between the interacting cells; in other words, deciphering which part belongs to which cell.
Manual segmentation, or marking out the different parts manually, is one option, but it is difficult and time-consuming, especially in three dimensions. To overcome this problem, automatic segmentation has been developed in which simple computer algorithms perform the identification.
“But these basic algorithms often make mistakes,” explained Professor YongKeun Park, “particularly with respect to adjoining segmentation, which of course is exactly what is occurring here in the immune response we’re most interested in.”
So, the researchers applied a deep learning framework to the HT segmentation problem. Deep learning is a type of machine learning in which artificial neural networks based on the human brain recognize patterns in a way that is similar to how humans do this. Regular machine learning requires data as an input that has already been labelled. The AI “learns” by understanding the labeled data and then recognizes the concept that has been labelled when it is fed novel data. For example, AI trained on a thousand images of cats labelled “cat” should be able to recognize a cat the next time it encounters an image with a cat in it. Deep learning involves multiple layers of artificial neural networks attacking much larger, but unlabeled datasets, in which the AI develops its own ‘labels’ for concepts it encounters.
In essence, the deep learning framework that KAIST researchers developed, called DeepIS, came up with its own concepts by which it distinguishes the different parts of the IS junction process. To validate this method, the research team applied it to the dynamics of a particular IS junction formed between chimeric antigen receptor (CAR) T-cells and target cancer cells. They then compared the results to what they would normally have done: the laborious process of performing the segmentation manually. They found not only that DeepIS was able to define areas within the IS with high accuracy, but that the technique was even able to capture information about the total distribution of proteins within the IS that may not have been easily measured using conventional techniques.
“In addition to allowing us to avoid the drudgery of manual segmentation and the problems of photo-bleaching and photo-toxicity, we found that the AI actually did a better job,” Professor Park added.
The next step will be to combine the technique with methods of measuring how much physical force is applied by different parts of the IS junction, such as holographic optical tweezers or traction force microscopy.
-Profile
Professor YongKeun Park
Department of Physics
Biomedical Optics Laboratory
http://bmol.kaist.ac.kr
KAIST
2021.02.24 View 10361