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What Fuels a “Domino Effect” in Cancer Drug Resistance?
KAIST researchers have identified mechanisms that relay prior acquired resistance to the first-line chemotherapy to the second-line targeted therapy, fueling a “domino effect” in cancer drug resistance. Their study featured in the February 7 edition of Science Advances suggests a new strategy for improving the second-line setting of cancer treatment for patients who showed resistance to anti-cancer drugs. Resistance to cancer drugs is often managed in the clinic by chemotherapy and targeted therapy. Unlike chemotherapy that works by repressing fast-proliferating cells, targeted therapy blocks a single oncogenic pathway to halt tumor growth. In many cases, targeted therapy is engaged as a maintenance therapy or employed in the second-line after front-line chemotherapy. A team of researchers led by Professor Yoosik Kim from the Department of Chemical and Biomolecular Engineering and the KAIST Institute for Health Science and Technology (KIHST) has discovered an unexpected resistance signature that occurs between chemotherapy and targeted therapy. The team further identified a set of integrated mechanisms that promotes this kind of sequential therapy resistance. “There have been multiple clinical accounts reflecting that targeted therapies tend to be least successful in patients who have exhausted all standard treatments,” said the first author of the paper Mark Borris D. Aldonza. He continued, “These accounts ignited our hypothesis that failed responses to some chemotherapies might speed up the evolution of resistance to other drugs, particularly those with specific targets.” Aldonza and his colleagues extracted large amounts of drug-resistance information from the open-source database the Genomics of Drug Sensitivity in Cancer (GDSC), which contains thousands of drug response data entries from various human cancer cell lines. Their big data analysis revealed that cancer cell lines resistant to chemotherapies classified as anti-mitotic drugs (AMDs), toxins that inhibit overacting cell division, are also resistant to a class of targeted therapies called epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs). In all of the cancer types analyzed, more than 84 percent of those resistant to AMDs, representatively ‘paclitaxel’, were also resistant to at least nine EGFR-TKIs. In lung, pancreatic, and breast cancers where paclitaxel is often used as a first-line, standard-of-care regimen, greater than 92 percent showed resistance to EGFR-TKIs. Professor Kim said, “It is surprising to see that such collateral resistance can occur specifically between two chemically different classes of drugs.” To figure out how failed responses to paclitaxel leads to resistance to EGFR-TKIs, the team validated co-resistance signatures that they found in the database by generating and analyzing a subset of slow-doubling, paclitaxel-resistant cancer models called ‘persisters’. The results demonstrated that paclitaxel-resistant cancers remodel their stress response by first becoming more stem cell-like, evolving the ability to self-renew to adapt to more stressful conditions like drug exposures. More surprisingly, when the researchers characterized the metabolic state of the cells, EGFR-TKI persisters derived from paclitaxel-resistant cancer cells showed high dependencies to energy-producing processes such as glycolysis and glutaminolysis. “We found that, without an energy stimulus like glucose, these cells transform to becoming more senescent, a characteristic of cells that have arrested cell division. However, this senescence is controlled by stem cell factors, which the paclitaxel-resistant cancers use to escape from this arrested state given a favorable condition to re-grow,” said Aldonza. Professor Kim explained, “Before this research, there was no reason to expect that acquiring the cancer stem cell phenotype that dramatically leads to a cascade of changes in cellular states affecting metabolism and cell death is linked with drug-specific sequential resistance between two classes of therapies.” He added, “The expansion of our work to other working models of drug resistance in a much more clinically-relevant setting, perhaps in clinical trials, will take on increasing importance, as sequential treatment strategies will continue to be adapted to various forms of anti-cancer therapy regimens.” This study was supported by the Basic Science Research Program of the National Research Foundation of Korea (NRF-2016R1C1B2009886), and the KAIST Future Systems Healthcare Project (KAISTHEALTHCARE42) funded by the Korean Ministry of Science and ICT (MSIT). Undergraduate student Aldonza participated in this research project and presented the findings as the lead author as part of the Undergraduate Research Participation (URP) Program at KAIST. < Figure 1. Schematic overview of the study. > < Figure 2. Big data analysis revealing co-resistance signatures between classes of anti-cancer drugs. > Publication: Aldonza et al. (2020) Prior acquired resistance to paclitaxel relays diverse EGFR-targeted therapy persistence mechanisms. Science Advances, Vol. 6, No. 6, eaav7416. Available online at http://dx.doi.org/10.1126/sciadv.aav7416 Profile: Prof. Yoosik Kim, MA, PhD ysyoosik@kaist.ac.kr https://qcbio.kaist.ac.kr/ Assistant Professor Bio Network Analysis Laboratory Department of Chemical and Biomolecular Engineering Korea Advanced Institute of Science and Technology (KAIST) http://kaist.ac.kr Daejeon, Republic of Korea Profile: Mark Borris D. Aldonza borris@kaist.ac.kr Undergraduate Student Department of Biological Sciences Korea Advanced Institute of Science and Technology (KAIST) http://kaist.ac.kr Daejeon, Republic of Korea (END)
2020.02.10
View 14559
Blood-Based Multiplexed Diagnostic Sensor Helps to Accurately Detect Alzheimer’s Disease
A research team at KAIST reported clinically accurate multiplexed electrical biosensor for detecting Alzheimer’s disease by measuring its core biomarkers using densely aligned carbon nanotubes. Alzheimer’s disease is the most prevalent neurodegenerative disorder, affecting one in ten aged over 65 years. Early diagnosis can reduce the risk of suffering the disease by one-third, according to recent reports. However, its early diagnosis remains challenging due to the low accuracy but high cost of diagnosis. Research team led by Professors Chan Beum Park and Steve Park described an ultrasensitive detection of multiple Alzheimer's disease core biomarker in human plasma. The team have designed the sensor array by employing a densely aligned single-walled carbon nanotube thin films as a transducer. The representative biomarkers of Alzheimer's disease are beta-amyloid42, beta-amyloid40, total tau protein, phosphorylated tau protein and the concentrations of these biomarkers in human plasma are directly correlated with the pathology of Alzheimer’s disease. The research team developed a highly sensitive resistive biosensor based on densely aligned carbon nanotubes fabricated by Langmuir-Blodgett method with a low manufacturing cost. Aligned carbon nanotubes with high density minimizes the tube-to-tube junction resistance compared with randomly distributed carbon nanotubes, which leads to the improvement of sensor sensitivity. To be more specific, this resistive sensor with densely aligned carbon nanotubes exhibits a sensitivity over 100 times higher than that of conventional carbon nanotube-based biosensors. By measuring the concentrations of four Alzheimer’s disease biomarkers simultaneously Alzheimer patients can be discriminated from health controls with an average sensitivity of 90.0%, a selectivity of 90.0% and an average accuracy of 88.6%. This work, titled “Clinically accurate diagnosis of Alzheimer’s disease via multiplexed sensing of core biomarkers in human plasma”, were published in Nature Communications on January 8th 2020. The authors include PhD candidate Kayoung Kim and MS candidate Min-Ji Kim. Professor Steve Park said, “This study was conducted on patients who are already confirmed with Alzheimer’s Disease. For further use in practical setting, it is necessary to test the patients with mild cognitive impairment.” He also emphasized that, “It is essential to establish a nationwide infrastructure, such as mild cognitive impairment cohort study and a dementia cohort study. This would enable the establishment of world-wide research network, and will help various private and public institutions.” This research was supported by the Ministry of Science and ICT, Human Resource Bank of Chungnam National University Hospital and Chungbuk National University Hospital. < A schematic diagram of a high-density aligned carbon nanotube-based resistive sensor that distinguishes patients with Alzheimer’s Disease by measuring the concentration of four biomarkers in the blood. > Profile: Professor Steve Park stevepark@kaist.ac.kr Department of Materials Science and Engineering http://steveparklab.kaist.ac.kr/ KAIST Profile: Professor Chan Beum Park parkcb at kaist.ac.kr Department of Materials Science and Engineering http://biomaterials.kaist.ac.kr/ KAIST
2020.02.07
View 10944
Rachmaninoff the most innovative of 18th and 19th century composers according to network science
Rachmaninoff, followed by Bach, Brahms and Mendelssohn, was the most innovative of the composers who worked during the Baroque, Classical and Romantic eras of music (1700 to 1900) according to a study published in the open access journal EPJ Data Science. A team of researchers from KAIST (Korea Advanced Institute of Science and Technology), calculated novelty scores for 900 classical piano compositions written by 19 composers between approximately 1700 and 1900. The scores were based on how musical compositions differed from all prior pieces of piano music and how they differed from previous piano works by the same composer. The authors found that composers from the Romantic era (1820 to 1910) tended to have high novelty scores. The authors from the Graduate School of Culture Technology at KAIST created a computer model which divided each composition into segments called ‘codewords’. Each ‘codeword’ consisted of all of the notes played together at a given time. Sequences of ‘codewords’ were then compared between compositions. The similarities between the sequences were used to create novelty scores for each composer and to determine the extent to which composers influenced each other. Juyong Park, the corresponding author, said: “Our model allows us to calculate the degree of shared melodies and harmonies between past and future works and to observe the evolution of western musical styles by demonstrating how prominent composers may have influenced each other. The period of music we studied is widely credited for having produced many musical styles that are still influential today.” The model distinguished each new musical period from the one before it by the rise of newly dominant and highly influential composers that indicated dramatic shifts in musical styles. The authors found that compositions from the Classical period (1750 to 1820) tended to have the lowest novelty scores. During this period Haydn and Mozart were highly influential but were later overtaken by Beethoven during the Classical-to-Romantic transitional period. The most innovative composer, indicated by the highest combined novelty score, was Rachmaninoff. His work during the Romantic era was novel when compared to the compositions of the other 18 composers included in the study, and his later works were novel compared to his earlier works. Lower novelty did not necessarily correlate with low influence. Beethoven was ranked in the lower half of novelty scores yet was the most influential composer during the Romantic period (1820 to 1910) and is widely considered one of the greatest composers of all time. Dr. Park said: “While novelty is necessary in a creative work it cannot account for all the creative and artistic qualities that go into creating melodies and harmonies that spread to later generations of composers. That may be why being more novel did not necessarily result in composers being more influential.” The authors suggest that their method could be applied to narrative or visual artworks by creating codewords from groups of words or colours and shapes. However, they caution that as only piano compositions were included in their analysis, it is unknown whether including all works by the 19 composers would have resulted in another composer being identified as the most original. Profile: Prof. Juyong Park, PhD juyongp@kaist.ac.kr Graduate School of Culture Technology (CT) Korea Advanced Institute of Science and Technology (KAIST) https://www.kaist.ac.kr Daejeon 34141, Korea (END)
2020.01.31
View 5213
Cancer cell reversion may offer a new approach to colorectal cancer treatment
A novel approach to reverse the progression of healthy cells to malignant ones may offer a more effective way to eradicate colorectal cancer cells with far fewer side effects, according to a team of researchers based in South Korea. Colorectal cancer, or cancer of the colon, is the third most common cancer in men and the second most common in women worldwide. South Korea has the second highest incident rate of colorectal cancer in the world, topped only by Hungary, according to the World Cancer Research Fund. Their results were published as a featured cover article on January 2 in Molecular Cancer Research, a journal of the American Association for Cancer Research. Led by Kwang-Hyun Cho, a professor and associate vice president of research at KAIST , the researchers used a computational framework to analyze healthy colon cells and colorectal cancer cells. They found that some master regulator proteins involved in cellular replication helped healthy colon cells mature, or differentiate into their specific cell type, and remain healthy. One particular protein, called SETDB1, suppressed the helpful proteins, forcing new cells to remain in a state of immaturity with the potential to become cancerous. “This suggests that differentiated cells have an inherent resistance mechanism against malignant transformation and indicates that cellular reprogramming is indispensable for malignancy,” said Cho. “We speculated that malignant properties might be eradicated if the tissue-specific gene expression is reinstated — if we repress SETDB1 and allow the colon cells to mature and differentiate as they would normally.” Image credit: Kwang-Hyun Cho, KAIST Image restriction: News organizations may use or redistribute this image, with proper attribution, as part of news coverage of this paper only. Using human-derived cells, Cho and his team targeted the tissue-specific gene expression programs identified in their computational analysis. These are the blueprints for the proteins that eventually help immature cells differentiate into tissue-specific cell types, such as colon cells. When a person has a genetic mutation, or has exposure to certain environmental factors, this process can go awry, leading to an overexpression of unhelpful proteins, such as SEDTB1. The researchers specifically reduced the amount of SEDTB1 in these tissue-specific gene expression programs, which allowed the cells to mature and fully differentiate into colon cells. “Our experiment also shows that SETDB1 depletion combined with cytotoxic drugs might be potentially beneficial to anticancer treatment,” Cho said. Cytotoxic drugs are often used for cancer treatment because the type of medicine contains chemicals that are toxic to cancer cells which can prevent them from replicating or growing. He noted that this combination could be more effective in treating cancer by transforming the cancer cell state into a less malignant or resistant state. He eventually pursues a cancer reversion therapy alone instead of conventional cytotoxic drug therapy since the cancer reversion therapy can provide a much less painful experience for patients with cancer who often have severe side effects from treatments intended to kill off cancerous cells, such as chemotherapy. The researchers plan to continue studying how to return cancer cells to healthier states, with the ultimate goal of translating their work to therapeutic treatment for patients with colorectal cancer. “I think our study of cancer reversion would eventually change the current medical practice of treating cancer toward the direction of keeping the patient’s quality of life while minimizing the side effects of current anti-cancer therapies,” Cho said. ### This work was funded by KAIST and the National Research Foundation of Korea grants funded by the Korean government, the Ministry of Science and Information and Communication Technology. Other authors include Soobeom Lee, Chae Young Hwang and Dongsan Kim, all of whom are affiliated with the Laboratory for Systems Biology and Bio-Inspired Engineering in the Department of Bio and Brain Engineering at KAIST; Chansu Lee and Sung Noh Hong, both with the Department of Medicine, and Seok-Hyung Kim of the Department of Pathology in the Samsung Medical Center at the Sungkyunkwan University School of Medicine. -Profile Professor Kwang-Hyun Cho ckh@kaist.ac.kr http://sbie.kaist.ac.kr/ Department of Bio and Brain Engineering KAIST https://www.kaist.ac.kr
2020.01.31
View 7533
New Insights into How the Human Brain Solves Complex Decision-Making Problems
A new study on meta reinforcement learning algorithms helps us understand how the human brain learns to adapt to complexity and uncertainty when learning and making decisions. A research team, led by Professor Sang Wan Lee at KAIST jointly with John O’Doherty at Caltech, succeeded in discovering both a computational and neural mechanism for human meta reinforcement learning, opening up the possibility of porting key elements of human intelligence into artificial intelligence algorithms. This study provides a glimpse into how it might ultimately use computational models to reverse engineer human reinforcement learning. This work was published on Dec 16, 2019 in the journal Nature Communications. The title of the paper is “Task complexity interacts with state-space uncertainty in the arbitration between model-based and model-free learning.” Human reinforcement learning is an inherently complex and dynamic process, involving goal setting, strategy choice, action selection, strategy modification, cognitive resource allocation etc. This a very challenging problem for humans to solve owing to the rapidly changing and multifaced environment in which humans have to operate. To make matters worse, humans often need to often rapidly make important decisions even before getting the opportunity to collect a lot of information, unlike the case when using deep learning methods to model learning and decision-making in artificial intelligence applications. In order to solve this problem, the research team used a technique called 'reinforcement learning theory-based experiment design' to optimize the three variables of the two-stage Markov decision task - goal, task complexity, and task uncertainty. This experimental design technique allowed the team not only to control confounding factors, but also to create a situation similar to that which occurs in actual human problem solving. Secondly, the team used a technique called ‘model-based neuroimaging analysis.’ Based on the acquired behavior and fMRI data, more than 100 different types of meta reinforcement learning algorithms were pitted against each other to find a computational model that can explain both behavioral and neural data. Thirdly, for the sake of a more rigorous verification, the team applied an analytical method called ‘parameter recovery analysis,’ which involves high-precision behavioral profiling of both human subjects and computational models. In this way, the team was able to accurately identify a computational model of meta reinforcement learning, ensuring not only that the model’s apparent behavior is similar to that of humans, but also that the model solves the problem in the same way as humans do. The team found that people tended to increase planning-based reinforcement learning (called model-based control), in response to increasing task complexity. However, they resorted to a simpler, more resource efficient strategy called model-free control, when both uncertainty and task complexity were high. This suggests that both the task uncertainty and the task complexity interact during the meta control of reinforcement learning. Computational fMRI analyses revealed that task complexity interacts with neural representations of the reliability of the learning strategies in the inferior prefrontal cortex. These findings significantly advance understanding of the nature of the computations being implemented in the inferior prefrontal cortex during meta reinforcement learning as well as providing insight into the more general question of how the brain resolves uncertainty and complexity in a dynamically changing environment. Identifying the key computational variables that drive prefrontal meta reinforcement learning, can also inform understanding of how this process might be vulnerable to break down in certain psychiatric disorders such as depression and OCD. Furthermore, gaining a computational understanding of how this process can sometimes lead to increased model-free control, can provide insights into how under some situations task performance might break down under conditions of high cognitive load. Professor Lee said, “This study will be of enormous interest to researchers in both the artificial intelligence and human/computer interaction fields since this holds significant potential for applying core insights gleaned into how human intelligence works with AI algorithms.” This work was funded by the National Institute on Drug Abuse, the National Research Foundation of Korea, the Ministry of Science and ICT, Samsung Research Funding Center of Samsung Electronics. Figure 1 (modified from the figures of the original paper doi:10.1038/s41467-019-13632-1). Computations implemented in the inferior prefrontal cortex during meta reinforcement learning. (A) Computational model of human prefrontal meta reinforcement learning (left) and the brain areas whose neural activity patterns are explained by the latent variables of the model. (B) Examples of behavioral profiles. Shown on the left is choice bias for different goal types and on the right is choice optimality for task complexity and uncertainty. (C) Parameter recoverability analysis. Compared are the effect of task uncertainty (left) and task complexity (right) on choice optimality. -Profile Professor Sang Wan Lee sangwan@kaist.ac.kr Department of Bio and Brain Engineering Director, KAIST Center for Neuroscience-inspired AI KAIST Institute for Artificial Intelligence (http://aibrain.kaist.ac.kr) KAIST Institute for Health, Science, and Technology KAIST (https://www.kaist.ac.kr)
2020.01.31
View 6094
KAIST Vaccine for Tick-Borne Disease ‘SFTS’ Protects Against Lethal Infection
A KAIST research team reported the development of a DNA vaccine for Severe Fever with Thrombocytopenia Syndrome Virus (SFTSV) which completely protects against lethal infection in ferrets. The team confirmed that ferrets immunized with DNA vaccines encoding all SFTSV proteins showed 100% survival rate without detectable viremia and did not develop any clinical symptoms. This study was published in Nature Communications on August 23. Severe Fever with Thrombocytopenia Syndrome (SFTS) is a newly emerging tick-borne infectious disease. The disease causes fever, severe thrombocytopenia, leukocytopenia as well as vomiting and diarrhea. Severe cases end up with organ system failure often accompanied by hemorrhages, and its mortality rate stands at 10–20%. The viral disease has been endemic to East Asia but the spread of the tick vector to North America increases the likelihood of potential outbreak beyond the Far East Asia. The World Health Organization (WHO) has also put SFTSV into the priority pathogen requiring urgent attention category. Currently, no vaccine has been available to prevent SFTS. The research team led by Professor Su-Hyung Park noted that DNA vaccines induce broader immunity to multiple antigens than traditional ones. Moreover, DNA vaccines stimulate both T cell and antibody immunity, which make them suitable for vaccine development. They constructed DNA vaccines that encode full-length Gn, Gc, N, NS, and RNA polymerase genes based on common sequences of 31 SFTSV strains isolated from patients. Their vaccine candidates induced both neutralizing antibody response and multifunctional SFTSV-specific T cell response in mice and ferrets. To investigate the vaccine’s efficacy in vivo, the research team applied a recently developed ferret model that recapitulates fatal clinical symptoms in SFTSV infection in humans. Vaccinated ferrets were completely protected from lethal SFTSV challenge without SFTSV detection in their blood, whereas all control ferrets died within 10 days’ post-infection. The KAIST team found that anti-envelope antibodies play an important role in protective immunity, suggesting that envelope glycoproteins of SFTSV may be the most effective antigens for inducing protective immunity. Moreover, the study revealed that T cell responses specific to non-envelope proteins of SFTSV also can contribute to protection against SFTSV infection. Professor Park said, “This is the first study demonstrating complete protection against lethal SFTSV challenge using an immunocompetent, middle-sized animal model with clinical manifestations of SFTSV infection. We believe this study provides valuable insights into designing preventive vaccines for SFTSV.”
2020.01.31
View 5412
Transformative Electronics Systems to Broaden Wearable Applications
Imagine a handheld electronic gadget that can soften and deform when attached to our skin. This will be the future of electronics we all dreamed of. A research team at KAIST says their new platform called 'Transformative Electronics Systems' will open a new class of electronics, allowing reconfigurable electronic interfaces to be optimized for a variety of applications. A team working under Professor Jae-Woong Jeong from the School of Electrical Engineering at KAIST has invented a multifunctional electronic platform that can mechanically transform its shape, flexibility, and stretchability. This platform, which was reported in Science Advances, allows users to seamlessly and precisely tune its stiffness and shape. "This new class of electronics will not only offer robust, convenient interfaces for use in both tabletop or handheld setups, but also allow seamless integration with the skin when applied onto our bodies," said Professor Jeong. The transformative electronics consist of a special gallium metal structure, hermetically encapsulated and sealed within a soft silicone material, combined with electronics that are designed to be flexible and stretchable. The mechanical transformation of the electronic systems is specifically triggered by temperature change events controlled by the user. "Gallium is an interesting key material. It is biocompatible, has high rigidity in solid form, and melts at a temperature comparable to the skin's temperature," said lead author Sang-Hyuk Byun, a researcher at KAIST. Once the transformative electronic platform comes in contact with a human body, the gallium metal encapsulated inside the silicone changes to a liquid state and softens the whole electronic structure, making it stretchable, flexible, and wearable. The gallium metal then solidifies again once the structure is peeled off the skin, making the electronic circuits stiff and stable. When flexible electronic circuits were integrated onto these transformative platforms, it empowered them with the ability to become either flexible and stretchable or rigid. "This technology could not have been achieved without interdisciplinary efforts," said co-lead author Joo Yong Sim, who is a researcher with ETRI. "We worked together with electrical, mechanical, and biomedical engineers, as well as material scientists and neuroscientists to make this breakthrough." This universal electronics platform allowed researchers to demonstrate applications that were highly adaptable and customizable, such as a multi-purpose personal electronics with variable stiffness and stretchability, a pressure sensor with tuneable bandwidth and sensitivity, and a neural probe that softens upon implantation into brain tissue. Applicable for both traditional and emerging electronics technologies, this breakthrough can potentially reshape the consumer electronics industry, especially in the biomedical and robotic domains. The researchers believe that with further development, this novel electronics technology can significantly impact the way we use electronics in our daily life. < Transformative electronics in soft mode,which becomes wearable for outdoor applications.> Video Material: https://youtu.be/im0J18TfShk Publication: Sang-Hyuk Byun, Joo Yong Sim, Zhanan Zhou, Juhyun Lee, Raza Qazi, Marie C. Walicki, Kyle E. Parker, Matthew P. Haney, Su Hwan Choi, Ahnsei Shon, Graydon B. Gereau, John Bilbily, Shuo Li, Yuhao Liu, Woon-Hong Yeo, Jordan G. McCall, Jianliang Xiao, and Jae-Woong Jeong. 2019. Mechanically transformative electronics, sensors, and implantable devices. Science Advances. Volume 5. No. 11. 12 pages. https://doi.org/10.1126/sciadv.aay0418 Link to download the full-text paper: https://advances.sciencemag.org/content/advances/5/11/eaay0418.full.pdf Profile: Prof. Jae-Woong Jeong, PhD jjeong1@kaist.ac.kr https://www.jeongresearch.org/ Professor Bio-Integrated Electronics and Systems Laboratory School of Electrical Engineering Korea Advanced Institute of Science and Technology (KAIST) https://www.kaist.ac.kr Daejeon 34141, Korea Profile: Sang-Hyuk Byun, PhD Candidate shbun95@kaist.ac.kr (END)
2020.01.31
View 7448
Scientists Discover the Mechanism of DNA High-Order Structure Formation
(Molecular structures of Abo1 in different energy states (left), Demonstration of an Abo1-assisted histone loading onto DNA by the DNA curtain assay. ) The genetic material of our cells—DNA—exists in a high-order structure called “chromatin”. Chromatin consists of DNA wrapped around histone proteins and efficiently packs DNA into a small volume. Moreover, using a spool and thread analogy, chromatin allows DNA to be locally wound or unwound, thus enabling genes to be enclosed or exposed. The misregulation of chromatin structures results in aberrant gene expression and can ultimately lead to developmental disorders or cancers. Despite the importance of DNA high-order structures, the complexity of the underlying machinery has circumvented molecular dissection. For the first time, molecular biologists have uncovered how one particular mechanism uses energy to ensure proper histone placement onto DNA to form chromatin. They published their results on Dec. 17 in Nature Communications. The study focused on proteins called histone chaperones. Histone chaperones are responsible for adding and removing specific histones at specific times during the DNA packaging process. The wrong histone at the wrong time and place could result in the misregulation of gene expression or aberrant DNA replication. Thus, histone chaperones are key players in the assembly and disassembly of chromatin. “In order to carefully control the assembly and disassembly of chromatin units, histone chaperones act as molecular escorts that prevent histone aggregation and undesired interactions,” said Professor Ji-Joon Song in the Department of Biological Sciences at KAIST. “We set out to understand how a unique histone chaperone uses chemical energy to assemble or disassemble chromatin.” Song and his team looked to Abo1, the only known histone chaperone that utilizes cellular energy (ATP). While Abo1 is found in yeast, it has an analogous partner in other organisms, including humans, called ATAD2. Both use ATP, which is produced through a cellular process where enzymes break down a molecule’s phosphate bond. ATP energy is typically used to power other cellular processes, but it is a rare partner for histone chaperones. “This was an interesting problem in the field because all other histone chaperones studied to date do not use ATP,” Song said. By imaging Abo1 with a single-molecule fluorescence imaging technique known as the DNA curtain assay, the researchers could examine the protein interactions at the single-molecule level. The technique allows scientists to arrange the DNA molecules and proteins on a single layer of a microfluidic chamber and examine the layer with fluorescence microscopy. The researchers found through real-time observation that Abo1 is ring-shaped and changes its structure to accommodate a specific histone and deposit it on DNA. Moreover, they found that the accommodating structural changes are powered by ADP. “We discovered a mechanism by which Abo1 accommodates histone substrates, ultimately allowing it to function as a unique energy-dependent histone chaperone,” Song said. “We also found that despite looking like a protein disassembly machine, Abo1 actually loads histone substrates onto DNA to facilitate chromatin assembly.” The researchers plan to continue exploring how energy-dependent histone chaperones bind and release histones, with the ultimate goal of developing therapeutics that can target cancer-causing misbehavior by Abo1’s analogous human counterpart, ATAD2. -Profile Professor Ji-Joon Song Department of Biological Sciences KI for the BioCentury (https://kis.kaist.ac.kr/index.php?mid=KIB_O) KAIST
2020.01.07
View 10542
A System Controlling Road Active Noise to Hit the Road
The research team led by Professor Youngjin Park of the Department of Mechanical Engineering has developed a road noise active noise control (RANC) system to be commercialized in partnership with Hyundai Motor Group. On December 11, Hyundai Motor Group announced the successful development of the RANC system, which significantly reduces the road noise flowing into cars. The carmaker has completed the domestic and American patent applications for the location of sensors and the signal selection method, the core technology of RANC. RANC is a technology for reducing road noise during driving. This system consists of an acceleration sensor, digital signal processor (the control computer to analyze sound signals), microphone, amplifier, and audio system. To make the system as simple as possible, the audio system utilizes the original audio system embedded in the car instead of a separate system. The acceleration sensor first calculates the vibration from the road into the car. The location of the sensor is important for accurately identifying the vibration path. The research team was able to find the optimal sensor location through a number of tests. The System Dynamics and Applied Control Laboratory of Professor Park researched ways to significantly reduce road noise with Hyundai Motor Group for four years from 1993 as a G7 national project and published the results in international journals. In 2002, the researchers published an article titled “Noise Quietens Driving” in Nature, where they announced the first success in reducing road noise in actual cars. The achievement did not lead to commercialization, however, due to the lack of auxiliary technologies at the time, digital amplifiers and DSP for cars for example, and pricing issues. Since 2013, Professor Park’s research team has participated in one technology transfer and eight university-industry projects. Based on these efforts, the team was able to successfully develop the RANC system with domestic technology in partnership with Hyundai’s NVH Research Lab (Research Fellow, Dr. Gangdeok Lee; Ph.D. in aviation engineering, 1996), Optomech (Founder, Professor Gyeongsu Kim; Ph.D. in mechanical engineering, 1999), ARE (CEO Hyeonseok Kim; Ph.D. in mechanical engineering, 1998), WeAcom, and BurnYoung. Professor Park’s team led the project by performing theory-based research during the commercialization stage in collaboration with Hyundai Motor Group. For the commercialization of the RANC system, Hyundai Motor Group is planning to collaborate with the global car audio company Harman to increase the degree of completion and apply the RANC system to the GV 80, the first SUV model of the Genesis brand. “I am very delighted as an engineer to see the research I worked on from my early days at KAIST be commercialized after 20 years,” noted Professor Park. “I am thrilled to make a contribution to such commercialization with my students in my lab.”
2019.12.27
View 11778
New Liquid Metal Wearable Pressure Sensor Created for Health Monitoring Applications
Soft pressure sensors have received significant research attention in a variety of fields, including soft robotics, electronic skin, and wearable electronics. Wearable soft pressure sensors have great potential for the real-time health monitoring and for the early diagnosis of diseases. A KAIST research team led by Professor Inkyu Park from the Department of Mechanical Engineering developed a highly sensitive wearable pressure sensor for health monitoring applications. This work was reported in Advanced Healthcare Materials on November 21 as a front cover article. This technology is capable of sensitive, precise, and continuous measurement of physiological and physical signals and shows great potential for health monitoring applications and the early diagnosis of diseases. A soft pressure sensor is required to have high compliance, high sensitivity, low cost, long-term performance stability, and environmental stability in order to be employed for continuous health monitoring. Conventional solid-state soft pressure sensors using functional materials including carbon nanotubes and graphene have showed great sensing performance. However, these sensors suffer from limited stretchability, signal drifting, and long-term instability due to the distance between the stretchable substrate and the functional materials. To overcome these issues, liquid-state electronics using liquid metal have been introduced for various wearable applications. Of these materials, Galinstan, a eutectic metal alloy of gallium, indium, and tin, has great mechanical and electrical properties that can be employed in wearable applications. But today’s liquid metal-based pressure sensors have low-pressure sensitivity, limiting their applicability for health monitoring devices. The research team developed a 3D-printed rigid microbump array-integrated, liquid metal-based soft pressure sensor. With the help of 3D printing, the integration of a rigid microbump array and the master mold for a liquid metal microchannel could be achieved simultaneously, reducing the complexity of the manufacturing process. Through the integration of the rigid microbump and the microchannel, the new pressure sensor has an extremely low detection limit and enhanced pressure sensitivity compared to previously reported liquid metal-based pressure sensors. The proposed sensor also has a negligible signal drift over 10,000 cycles of pressure, bending, and stretching and exhibited excellent stability when subjected to various environmental conditions. These performance outcomes make it an excellent sensor for various health monitoring devices. First, the research team demonstrated a wearable wristband device that can continuously monitor one’s pulse during exercise and be employed in a noninvasive cuffless BP monitoring system based on PTT calculations. Then, they introduced a wireless wearable heel pressure monitoring system that integrates three 3D-BLiPS with a wireless communication module. Professor Park said, “It was possible to measure health indicators including pulse and blood pressure continuously as well as pressure of body parts using our proposed soft pressure sensor. We expect it to be used in health care applications, such as the prevention and the monitoring of the pressure-driven diseases such as pressure ulcers in the near future. There will be more opportunities for future research including a whole-body pressure monitoring system related to other physical parameters.” This work was supported by a National Research Foundation of Korea (NRF) grant funded by the Ministry of Science and ICT. < Figure 1. The front cover image of Advanced Healthcare Materials, Volume 8, Issue 22. > < Figure 2. Highly sensitive liquid metal-based soft pressure sensor integrated with 3D-printed microbump array. > < Figure 3. High pressure sensitivity and reliable sensing performances of the proposed sensor and wireless heel pressure monitoring application. > -ProfileProfessor Inkyu ParkMicro/Nano Transducers Laboratoryhttp://mintlab1.kaist.ac.kr/ Department of Mechanical EngineeringKAIST
2019.12.20
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‘Carrier-Resolved Photo-Hall’ to Push Semiconductor Advances
(Professor Shin and Dr. Gunawan (left)) An IBM-KAIST research team described a breakthrough in a 140-year-old mystery in physics. The research reported in Nature last month unlocks the physical characteristics of semiconductors in much greater detail and aids in the development of new and improved semiconductor materials. Research team under Professor Byungha Shin at the Department of Material Sciences and Engineering and Dr. Oki Gunawan at IBM discovered a new formula and technique that enables the simultaneous extraction of both majority and minority carrier information such as their density and mobility, as well as gain additional insights about carrier lifetimes, diffusion lengths, and the recombination process. This new discovery and technology will help push semiconductor advances in both existing and emerging technologies. Semiconductors are the basic building blocks of today’s digital electronics age, providing us with a multitude of devices that benefit our modern life. To truly appreciate the physics of semiconductors, it is very important to understand the fundamental properties of the charge carriers inside the materials, whether those particles are positive or negative, their speed under an applied electric field, and how densely they are packed into the material. Physicist Edwin Hall found a way to determine those properties in 1879, when he discovered that a magnetic field will deflect the movement of electronic charges inside a conductor and that the amount of deflection can be measured as a voltage perpendicular to the flow of the charge. Decades after Hall’s discovery, researchers also recognized that they can measure the Hall effect with light via “photo-Hall experiments”. During such experiments, the light generates multiple carriers or electron–hole pairs in the semiconductors. Unfortunately, the basic Hall effect only provided insights into the dominant charge carrier (or majority carrier). Researchers were unable to extract the properties of both carriers (the majority and minority carriers) simultaneously. The property information of both carriers is crucial for many applications that involve light such as solar cells and other optoelectronic devices. In the photo-Hall experiment by the KAIST-IBM team, both carriers contribute to changes in conductivity and the Hall coefficient. The key insight comes from measuring the conductivity and Hall coefficient as a function of light intensity. Hidden in the trajectory of the conductivity, the Hall coefficient curve reveals crucial new information: the difference in the mobility of both carriers. As discussed in the paper, this relationship can be expressed elegantly as: Δµ = d (σ²H)/dσ The research team solved for both majority and minority carrier mobility and density as a function of light intensity, naming the new technique Carrier-Resolved Photo Hall (CRPH) measurement. With known light illumination intensity, the carrier lifetime can be established in a similar way. Beyond advances in theoretical understanding, advances in experimental techniques were also critical for enabling this breakthrough. The technique requires a clean Hall signal measurement, which can be challenging for materials where the Hall signal is weak due to low mobility or when extra unwanted signals are present, such as under strong light illumination. The newly developed photo-Hall technique allows the extraction of an astonishing amount of information from semiconductors. In contrast to only three parameters obtained in the classic Hall measurements, this new technique yields up to seven parameters at every tested level of light intensity. These include the mobility of both the electron and hole; their carrier density under light; the recombination lifetime; and the diffusion lengths for electrons, holes, and ambipolar types. All of these can be repeated N times (i.e. the number of light intensity settings used in the experiment). Professor Shin said, “This novel technology sheds new light on understanding the physical characteristics of semiconductor materials in great detail.” Dr. Gunawan added, “This will will help accelerate the development of next-generation semiconductor technology such as better solar cells, better optoelectronics devices, and new materials and devices for artificial intelligence technology.” Profile: Professor Byungha Shin Department of Materials Science and Engineering KAIST byungha@kaist.ac.kr http://energymatlab.kaist.ac.kr/
2019.11.18
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Gallium-Based Solvating Agent Efficiently Analyzes Optically Active Alcohols
A KAIST research team has developed a gallium-based metal complex enabling the rapid chiral analysis of alcohols. A team working under Professor Hyunwoo Kim reported the efficient new alcohol analysis method using nuclear magnetic resonance (NMR) spectroscopy in iScience. Enantiopure chiral alcohols are ubiquitous in nature and widely utilized as pharmaceuticals. This importance of chirality in synthetic and medicinal chemistry has advanced the search for rapid and facile methods to determine the enantiomeric purities of compounds. To date, chiral analysis has been performed using high-performance liquid chromatography (HPLC) with chiral columns. Along with the HPLC technique, chiral analysis using NMR spectroscopy has gained tremendous attention as an alternative to traditionally employed chromatographic methods due to its simplicity and rapid detection for real-time measurement. However, this method carries drawbacks such as line-broadening, narrow substrate scope, and poor resolution. Thus, compared with popular methods of chromatographic analysis, NMR spectroscopy is infrequently used for chiral analysis. In principle, a chiral solvating agent is additionally required for the NMR measurement of chiral alcohols to obtain two distinct signals. However, NMR analysis of chiral alcohols has been challenging due to weak binding interactions with chiral solvating agents. To overcome the intrinsic difficulty of relatively weak molecular interactions that are common for alcohols, many researchers have used multifunctional alcohols to enhance interactions with solvating agents. Instead, the KAIST team successfully varied the physical properties of metal complexes to induce stronger interactions with alcohols rather than the strategy of using multifunctional analytes, in the hopes of developing a universal chiral solvating agent for alcohols. Compared to the current method of chiral analysis used in the pharmaceutical industry, alcohols that do not possess chromophores can also be directly analyzed with the gallium complexes. Professor Kim said that this method could be a complementary chiral analysis technique at the industry level in the near future. He added that since the developed gallium complex can determine enantiomeric excess within minutes, it can be further utilized to monitor asymmetric synthesis. This feature will benefit a large number of researchers in the organic chemistry community, as well as the pharmaceutical industry. (Figure: Schematic view of the in-situ direct 1H NMR chiral analysis.) -Profile: Professor Hyunwoo Kim Department of Chemistry KAIST http://mdos.kaist.ac.kr hwk34@kaist.ac.kr For more on this article, please go to https://doi.org/10.1016/j.isci2019.07051
2019.11.14
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