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Coordination Chemistry and Alzheimer’s Disease It has become evident recently that the interactions between copper and amyloid-b neurotoxically impact the brain of patients with Alzheimer’s disease. KAIST researchers have reported a new strategy to alter the neurotoxicity in Alzheimer’s disease by using a rationally designed chemical reagent. This strategy, developed by Professor Mi Hee Lim from the Department of Chemistry, can modify the coordination sphere of copper bound to amyloid-b, effectively inhibiting copper’s binding to amyloid-b and altering its aggregation and toxicity. Their study was featured in PNAS last month. The researchers developed a small molecule that is able to directly interact with the coordination sphere of copper–amyloid-b complexes followed by modifications via either covalent conjugation, oxidation, or both under aerobic conditions. The research team simply utilized copper–dioxygen chemistry to design a chemical reagent. Answering how peptide modifications by a small molecule occur remains very challenging. The system includes transition metals and amyloidogenic proteins and is quite heterogeneous, since they are continuously being changed. It is critical to carefully check the multiple variables such as the presence of dioxygen and the type of transition metal ions and amyloidogenic proteins in order to identify the underlying mechanisms and target specificity of the chemical reagent. The research team employed various biophysical and biochemical methods to determine the mechanisms for modifications on the coordination sphere of copper–Aꞵ complexes. Among them, peptide modifications were mainly analyzed using electrospray ionization-mass spectrometry. Mass spectrometry (MS) has been applied to verify such peptide modifications by calculating the shift in exact mass. The research team also performed collision-induced dissociation (CID) of the target ion detected by MS to pinpoint which amino acid residue is specifically modified. The CID fragmentizes the amide bond located between the amino acid residues. This fragmental analysis allows us to identify the specific sites of peptide modifications. The copper and amyloid-b complexes represent a pathological connection between metal ions and amyloid-b in Alzheimer’s disease. Recent findings indicate that copper and amyloid-b can directly contribute toward neurodegeneration by producing toxic amyloid-b oligomers and reactive oxygen species. Professor Lim said, “This study illustrates the first experimental evidence that the 14th histidine residue in copper–amyloid-b complexes can be specifically modified through either covalent conjugation, oxidation, or both. Considering the neurotoxic implications of the interactions between copper and amyloid-b, such modifications at the coordination sphere of copper in amyloid-b could effectively alter its properties and toxicity.” “This multidisciplinary study with an emphasis on approaches, reactivities, and mechanisms looks forward to opening a new way to develop candidates of anti-neurodegenerative diseases,” she added. The National Research Foundation of Korea funded this research.
2020.03.03 View 6722
Stress-Relief Substrate Helps OLED Stretch Two-Dimensionally Highly functional and free-form displays are critical components to complete the technological prowess of wearable electronics, robotics, and human-machine interfaces. A KAIST team created stretchable OLEDs (Organic Light-Emitting Diodes) that are compliant and maintain their performance under high-strain deformation. Their stress-relief substrates have a unique structure and utilize pillar arrays to reduce the stress on the active areas of devices when strain is applied. Traditional intrinsically stretchable OLEDs have commercial limitations due to their low efficiency in the electrical conductivity of the electrodes. In addition, previous geometrically stretchable OLEDs laminated to the elastic substrates with thin film devices lead to different pixel emissions of the devices from different peak sizes of the buckles. To solve these problems, a research team led by Professor Kyung Cheol Choi designed a stretchable substrate system with surface relief island structures that relieve the stress at the locations of bridges in the devices. Their stretchable OLED devices contained an elastic substrate structure comprising bonded elastic pillars and bridges. A patterned upper substrate with bridges makes the rigid substrate stretchable, while the pillars decentralize the stress on the device. Although various applications using micropillar arrays have been reported, it has not yet been reported how elastic pillar arrays can affect substrates by relieving the stress applied to those substrates upon stretching. Compared to results using similar layouts with conventional free-standing, flat substrates or island structures, their results with elastic pillar arrays show relatively low stress levels at both the bridges and plates when stretching the devices. They achieved stretchable RGB (red, green, blue) OLEDs and had no difficulties with material selection as practical processes were conducted with stress-relief substrates. Their stretchable OLEDs were mechanically stable and have two-dimensional stretchability, which is superior to only one-direction stretchable electronics, opening the way for practical applications like wearable electronics and health monitoring systems. Professor Choi said, “Our substrate design will impart flexibility into electronics technology development including semiconductor and circuit technologies. We look forward this new stretchable OLED lowering the barrier for entering the stretchable display market.” This research was published in Nano Letters titled Two-Dimensionally Stretchable Organic Light-Emitting Diode with Elastic Pillar Arrays for Stress Relief. (https://dx.doi.org/10.1021/acs.nanolett.9b03657). This work was supported by the Engineering Research Center of Excellence Program supported by the National Research Foundation of Korea. -Profile Professor Kyung Cheol Choi kyungcc@kaist.ac.kr http://adnc.kaist.ac.kr/ School of Electrical Engineering KAIST
2020.02.27 View 7934
Black Phosphorous Tunnel Field-Effect Transistor as an Alternative Ultra-low Power Switch Researchers have reported a black phosphorus transistor that can be used as an alternative ultra-low power switch. A research team led by Professor Sungjae Cho in the KAIST Department of Physics developed a thickness-controlled black phosphorous tunnel field-effect transistor (TFET) that shows 10-times lower switching power consumption as well as 10,000-times lower standby power consumption than conventional complementary metal-oxide-semiconductor (CMOS) transistors. The research team said they developed fast and low-power transistors that can replace conventional CMOS transistors. In particular, they solved problems that have degraded TFET operation speed and performance, paving the way to extend Moore’s Law. In the study featured in Nature Nanotechnology last month, Professor Cho’s team reported a natural heterojunction TFET with spatially varying layer thickness in black phosphorous without interface problems. They achieved record-low average subthreshold swing values over 4-5 dec of current and record-high, on-state current, which allows the TFETs to operate as fast as conventional CMOS transistors with as much lower power consumption. "We successfully developed the first transistor that achieved the essential criteria for fast, low-power switching. Our newly developed TFETs can replace CMOS transistors by solving a major issue regarding the performance degradation of TFETs,"Professor Cho said. The continuous down-scaling of transistors has been the key to the successful development of current information technology. However, with Moore’s Law reaching its limits due to the increased power consumption, the development of new alternative transistor designs has emerged as an urgent need. Reducing both switching and standby power consumption while further scaling transistors requires overcoming the thermionic limit of subthreshold swing, which is defined as the required voltage per ten-fold current increase in the subthreshold region. In order to reduce both the switching and standby power of CMOS circuits, it is critical to reduce the subthreshold swing of the transistors. However, there is fundamental subthreshold swing limit of 60 mV/dec in CMOS transistors, which originates from thermal carrier injection. The International Roadmap for Devices and Systems has already predicted that new device geometries with new materials beyond CMOS will be required to address transistor scaling challenges in the near future. In particular, TFETs have been suggested as a major alternative to CMOS transistors, since the subthreshold swing in TFETs can be substantially reduced below the thermionic limit of 60 mV/dec. TFETs operate via quantum tunneling, which does not limit subthreshold swing as in thermal injection of CMOS transistors. In particular, heterojunction TFETs hold significant promise for delivering both low subthreshold swing and high on-state current. High on-current is essential for the fast operation of transistors since charging a device to on state takes a longer time with lower currents. Unlike theoretical expectations, previously developed heterojunction TFETs show 100-100,000x lower on-state current (100-100,000x slower operation speeds) than CMOS transistors due to interface problems in the heterojunction. This low operation speed impedes the replacement of CMOS transistors with low-power TFETs. Professor Cho said, “We have demonstrated for the first time, to the best of our knowledge, TFET optimization for both fast and ultra-low-power operations, which is essential to replace CMOS transistors for low-power applications.” He said he is very delighted to extend Moore’s Law, which may eventually affect almost every aspect of life and society. This study (https://doi.org/10.1038/s41565-019-0623-7) was supported by the National Research Foundation of Korea. Publication: Kim et al. (2020) Thickness-controlled black phosphorus tunnel field-effect transistor for low-power switches. Nature Nanotechnology. Available online at https://doi.org/10.1038/s41565-019-0623-7 Profile: Professor Sungjae Cho sungjae.cho@kaist.ac.kr Department of Physics http://qtak.kaist.ac.kr/ KAIST Profile: Seungho Kim, PhD Candidate krksh21@kaist.ac.kr Department of Physics http://qtak.kaist.ac.kr/ KAIST (END)
2020.02.21 View 10567
New Graphene-Based Metasurface Capable of Independent Amplitude and Phase Control of Light Researchers described a new strategy of designing metamolecules that incorporates two independently controllable subwavelength meta-atoms. This two-parametric control of the metamolecule secures the complete control of both amplitude and the phase of light. A KAIST research team in collaboration with the University of Wisconsin-Madison theoretically suggested a graphene-based active metasurface capable of independent amplitude and phase control of mid-infrared light. This research gives a new insight into modulating the mid-infrared wavefront with high resolution by solving the problem of the independent control of light amplitude and phase, which has remained a long-standing challenge. Light modulation technology is essential for developing future optical devices such as holography, high-resolution imaging, and optical communication systems. Liquid crystals and a microelectromechanical system (MEMS) have previously been utilized to modulate light. However, both methods suffer from significantly limited driving speeds and unit pixel sizes larger than the diffraction limit, which consequently prevent their integration into photonic systems. The metasurface platform is considered a strong candidate for the next generation of light modulation technology. Metasurfaces have optical properties that natural materials cannot have, and can overcome the limitations of conventional optical systems, such as forming a high-resolution image beyond the diffraction limit. In particular, the active metasurface is regarded as a technology with a wide range of applications due to its tunable optical characteristics with an electrical signal. However, the previous active metasurfaces suffered from the inevitable correlation between light amplitude control and phase control. This problem is caused by the modulation mechanism of conventional metasurfaces. Conventional metasurfaces have been designed such that a metaatom only has one resonance condition, but a single resonant design inherently lacks the degrees of freedom to independently control the amplitude and phase of light. The research team made a metaunit by combining two independently controllable metaatoms, dramatically improving the modulation range of active metasurfaces. The proposed metasurface can control the amplitude and phase of the mid-infrared light independently with a resolution beyond the diffraction limit, thus allowing complete control of the optical wavefront. The research team theoretically confirmed the performance of the proposed active metasurface and the possibility of wavefront shaping using this design method. Furthermore, they developed an analytical method that can approximate the optical properties of metasurfaces without complex electromagnetic simulations. This analytical platform proposes a more intuitive and comprehensively applicable metasurface design guideline. The proposed technology is expected to enable accurate wavefront shaping with a much higher spatial resolution than existing wavefront shaping technologies, which will be applied to active optical systems such as mid-infrared holography, high-speed beam steering devices that can be applied for LiDAR, and variable focus infrared lenses. Professor Min Seok Jang commented, "This study showed the independent control amplitude and phase of light, which has been a long-standing quest in light modulator technology. The development of optical devices using complex wavefront control is expected to become more active in the future." MS candidate Sangjun Han and Dr. Seyoon Kim of the University of Wisconsin-Madison are the co-first authors of the research, which was published and selected as the front cover of the January 28 edition of ACS Nano titled “Complete complex amplitude modulation with electronically tunable graphene plasmonic metamolecules.” This research was funded by the Samsung Research Funding & Incubation Center for Future Technology. Publication: Han et al. (2020) Complete Complex Amplitude Modulation with Electronically Tunable Graphene Plasmonic Metamolecules. ACS Nano, Vol. 14, Issue 1, pp. 1166-1175. Available online at https://doi.org/10.1021/acsnano.9b09277 Profile: Prof. Min Seok Jang, MS, PhD jang.minseok@kaist.ac.kr http://jlab.kaist.ac.kr/ Associate Professor Jang Research Group School of Electrical Engineering Korea Advanced Institute of Science and Technology (KAIST) http://kaist.ac.kr Daejeon, Republic of Korea Profile: Sangjun Han sangjun.han@kaist.ac.kr MS Candidate School of Electrical Engineering Korea Advanced Institute of Science and Technology (KAIST) http://kaist.ac.kr Daejeon, Republic of Korea (END)
2020.02.20 View 8152
New Catalyst Recycles Greenhouse Gases into Fuel and Hydrogen Gas < Professor Cafer T. Yavuz (left), PhD Candidate Youngdong Song (center), and Researcher Sreerangappa Ramesh (right) > Scientists have taken a major step toward a circular carbon economy by developing a long-lasting, economical catalyst that recycles greenhouse gases into ingredients that can be used in fuel, hydrogen gas, and other chemicals. The results could be revolutionary in the effort to reverse global warming, according to the researchers. The study was published on February 14 in Science. “We set out to develop an effective catalyst that can convert large amounts of the greenhouse gases carbon dioxide and methane without failure,” said Cafer T. Yavuz, paper author and associate professor of chemical and biomolecular engineering and of chemistry at KAIST. The catalyst, made from inexpensive and abundant nickel, magnesium, and molybdenum, initiates and speeds up the rate of reaction that converts carbon dioxide and methane into hydrogen gas. It can work efficiently for more than a month. This conversion is called ‘dry reforming’, where harmful gases, such as carbon dioxide, are processed to produce more useful chemicals that could be refined for use in fuel, plastics, or even pharmaceuticals. It is an effective process, but it previously required rare and expensive metals such as platinum and rhodium to induce a brief and inefficient chemical reaction. Other researchers had previously proposed nickel as a more economical solution, but carbon byproducts would build up and the surface nanoparticles would bind together on the cheaper metal, fundamentally changing the composition and geometry of the catalyst and rendering it useless. “The difficulty arises from the lack of control on scores of active sites over the bulky catalysts surfaces because any refinement procedures attempted also change the nature of the catalyst itself,” Yavuz said. The researchers produced nickel-molybdenum nanoparticles under a reductive environment in the presence of a single crystalline magnesium oxide. As the ingredients were heated under reactive gas, the nanoparticles moved on the pristine crystal surface seeking anchoring points. The resulting activated catalyst sealed its own high-energy active sites and permanently fixed the location of the nanoparticles — meaning that the nickel-based catalyst will not have a carbon build up, nor will the surface particles bind to one another. “It took us almost a year to understand the underlying mechanism,” said first author Youngdong Song, a graduate student in the Department of Chemical and Biomolecular Engineering at KAIST. “Once we studied all the chemical events in detail, we were shocked.” The researchers dubbed the catalyst Nanocatalysts on Single Crystal Edges (NOSCE). The magnesium-oxide nanopowder comes from a finely structured form of magnesium oxide, where the molecules bind continuously to the edge. There are no breaks or defects in the surface, allowing for uniform and predictable reactions. “Our study solves a number of challenges the catalyst community faces,” Yavuz said. “We believe the NOSCE mechanism will improve other inefficient catalytic reactions and provide even further savings of greenhouse gas emissions.” This work was supported, in part, by the Saudi-Aramco-KAIST CO2 Management Center and the National Research Foundation of Korea. Other contributors include Ercan Ozdemir, Sreerangappa Ramesh, Aldiar Adishev, and Saravanan Subramanian, all of whom are affiliated with the Graduate School of Energy, Environment, Water and Sustainability at KAIST; Aadesh Harale, Mohammed Albuali, Bandar Abdullah Fadhel, and Aqil Jamal, all of whom are with the Research and Development Center in Saudi Arabia; and Dohyun Moon and Sun Hee Choi, both of whom are with the Pohang Accelerator Laboratory in Korea. Ozdemir is also affiliated with the Institute of Nanotechnology at the Gebze Technical University in Turkey; Fadhel and Jamal are also affiliated with the Saudi-Armco-KAIST CO2 Management Center in Korea. <Newly developed catalyst that recycles greenhouse gases into ingredients that can be used in fuel, hydrogen gas and other chemicals.> Publication: Song et al. (2020) Dry reforming of methane by stable Ni–Mo nanocatalysts on single-crystalline MgO. Science, Vol. 367, Issue 6479, pp. 777-781. Available online at http://dx.doi.org/10.1126/science.aav2412 Profile: Prof. Cafer T. Yavuz, MA, PhD yavuz@kaist.ac.kr http://yavuz.kaist.ac.kr/ Associate Professor Oxide and Organic Nanomaterials for the Environment (ONE) Laboratory Graduate School of Energy, Environment, Water and Sustainability (EEWS) Korea Advanced Institute of Science and Technology (KAIST) http://kaist.ac.kr Daejeon, Republic of Korea Profile: Youngdong Song ydsong88@kaist.ac.kr Ph.D. Candidate Department of Chemical and Biomolecular Engineering Korea Advanced Institute of Science and Technology (KAIST) http://kaist.ac.kr Daejeon, Republic of Korea (END)
2020.02.17 View 15100
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 11723
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 9056
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 4487
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 5905
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)
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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.”
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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)
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