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E. coli Engineered to Grow on CO₂ and Formic Acid as Sole Carbon Sources
- An E. coli strain that can grow to a relatively high cell density solely on CO₂ and formic acid was developed by employing metabolic engineering. - Most biorefinery processes have relied on the use of biomass as a raw material for the production of chemicals and materials. Even though the use of CO₂ as a carbon source in biorefineries is desirable, it has not been possible to make common microbial strains such as E. coli grow on CO₂. Now, a metabolic engineering research group at KAIST has developed a strategy to grow an E. coli strain to higher cell density solely on CO₂ and formic acid. Formic acid is a one carbon carboxylic acid, and can be easily produced from CO₂ using a variety of methods. Since it is easier to store and transport than CO₂, formic acid can be considered a good liquid-form alternative of CO₂. With support from the C1 Gas Refinery R&D Center and the Ministry of Science and ICT, a research team led by Distinguished Professor Sang Yup Lee stepped up their work to develop an engineered E. coli strain capable of growing up to 11-fold higher cell density than those previously reported, using CO₂ and formic acid as sole carbon sources. This work was published in Nature Microbiology on September 28. Despite the recent reports by several research groups on the development of E. coli strains capable of growing on CO₂ and formic acid, the maximum cell growth remained too low (optical density of around 1) and thus the production of chemicals from CO₂ and formic acid has been far from realized. The team previously reported the reconstruction of the tetrahydrofolate cycle and reverse glycine cleavage pathway to construct an engineered E. coli strain that can sustain growth on CO₂ and formic acid. To further enhance the growth, the research team introduced the previously designed synthetic CO₂ and formic acid assimilation pathway, and two formate dehydrogenases. Metabolic fluxes were also fine-tuned, the gluconeogenic flux enhanced, and the levels of cytochrome bo3 and bd-I ubiquinol oxidase for ATP generation were optimized. This engineered E. coli strain was able to grow to a relatively high OD600 of 7~11, showing promise as a platform strain growing solely on CO₂ and formic acid. Professor Lee said, “We engineered E. coli that can grow to a higher cell density only using CO₂ and formic acid. We think that this is an important step forward, but this is not the end. The engineered strain we developed still needs further engineering so that it can grow faster to a much higher density.” Professor Lee’s team is continuing to develop such a strain. “In the future, we would be delighted to see the production of chemicals from an engineered E. coli strain using CO₂ and formic acid as sole carbon sources,” he added. -Profile:Distinguished Professor Sang Yup Leehttp://mbel.kaist.ac.krDepartment of Chemical and Biomolecular EngineeringKAIST
2020.09.29
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Biomarker Predicts Who Will Have Severe COVID-19
- Airway cell analyses showing an activated immune axis could pinpoint the COVID-19 patients who will most benefit from targeted therapies.- KAIST researchers have identified key markers that could help pinpoint patients who are bound to get a severe reaction to COVID-19 infection. This would help doctors provide the right treatments at the right time, potentially saving lives. The findings were published in the journal Frontiers in Immunology on August 28. People’s immune systems react differently to infection with SARS-CoV-2, the virus that causes COVID-19, ranging from mild to severe, life-threatening responses. To understand the differences in responses, Professor Heung Kyu Lee and PhD candidate Jang Hyun Park from the Graduate School of Medical Science and Engineering at KAIST analysed ribonucleic acid (RNA) sequencing data extracted from individual airway cells of healthy controls and of mildly and severely ill patients with COVID-19. The data was available in a public database previously published by a group of Chinese researchers. “Our analyses identified an association between immune cells called neutrophils and special cell receptors that bind to the steroid hormone glucocorticoid,” Professor Lee explained. “This finding could be used as a biomarker for predicting disease severity in patients and thus selecting a targeted therapy that can help treat them at an appropriate time,” he added. Severe illness in COVID-19 is associated with an exaggerated immune response that leads to excessive airway-damaging inflammation. This condition, known as acute respiratory distress syndrome (ARDS), accounts for 70% of deaths in fatal COVID-19 infections. Scientists already know that this excessive inflammation involves heightened neutrophil recruitment to the airways, but the detailed mechanisms of this reaction are still unclear. Lee and Park’s analyses found that a group of immune cells called myeloid cells produced excess amounts of neutrophil-recruiting chemicals in severely ill patients, including a cytokine called tumour necrosis factor (TNF) and a chemokine called CXCL8. Further RNA analyses of neutrophils in severely ill patients showed they were less able to recruit very important T cells needed for attacking the virus. At the same time, the neutrophils produced too many extracellular molecules that normally trap pathogens, but damage airway cells when produced in excess. The researchers additionally found that the airway cells in severely ill patients were not expressing enough glucocorticoid receptors. This was correlated with increased CXCL8 expression and neutrophil recruitment. Glucocorticoids, like the well-known drug dexamethasone, are anti-inflammatory agents that could play a role in treating COVID-19. However, using them in early or mild forms of the infection could suppress the necessary immune reactions to combat the virus. But if airway damage has already happened in more severe cases, glucocorticoid treatment would be ineffective. Knowing who to give this treatment to and when is really important. COVID-19 patients showing reduced glucocorticoid receptor expression, increased CXCL8 expression, and excess neutrophil recruitment to the airways could benefit from treatment with glucocorticoids to prevent airway damage. Further research is needed, however, to confirm the relationship between glucocorticoids and neutrophil inflammation at the protein level. “Our study could serve as a springboard towards more accurate and reliable COVID-19 treatments,” Professor Lee said. This work was supported by the National Research Foundation of Korea, and Mobile Clinic Module Project funded by KAIST. Figure. Low glucocorticoid receptor (GR) expression led to excessive inflammation and lung damage by neutrophils through enhancing the expression of CXCL8 and other cytokines. Image credit: Professor Heung Kyu Lee, KAIST. Created with Biorender.com. Image usage restrictions: News organizations may use or redistribute these figures and image, with proper attribution, as part of news coverage of this paper only. -Publication: Jang Hyun Park, and Heung Kyu Lee. (2020). Re-analysis of Single Cell Transcriptome Reveals That the NR3C1-CXCL8-Neutrophil Axis Determines the Severity of COVID-19. Frontiers in Immunology, Available online at https://doi.org/10.3389/fimmu.2020.02145 -Profile: Heung Kyu Lee Associate Professor heungkyu.lee@kaist.ac.kr https://www.heungkyulee.kaist.ac.kr/ Laboratory of Host Defenses Graduate School of Medical Science and Engineering (GSMSE) The Center for Epidemic Preparedness at KAIST Institute http://kaist.ac.kr Korea Advanced Institute of Science and Technology (KAIST) Daejeon, Republic of Korea Profile: Jang Hyun Park PhD Candidate janghyun.park@kaist.ac.kr GSMSE, KAIST
2020.09.17
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Microscopy Approach Poised to Offer New Insights into Liver Diseases
Researchers have developed a new way to visualize the progression of nonalcoholic fatty liver disease (NAFLD) in mouse models of the disease. The new microscopy method provides a high-resolution 3D view that could lead to important new insights into NAFLD, a condition in which too much fat is stored in the liver. “It is estimated that a quarter of the adult global population has NAFLD, yet an effective treatment strategy has not been found,” said professor Pilhan Kim from the Graduate School of Medical Science and Engineering at KAIST. “NAFLD is associated with obesity and type 2 diabetes and can sometimes progress to liver failure in serious case.” In the Optical Society (OSA) journal Biomedical Optics Express, Professor Kim and colleagues reported their new imaging technique and showed that it can be used to observe how tiny droplets of fat, or lipids, accumulate in the liver cells of living mice over time. “It has been challenging to find a treatment strategy for NAFLD because most studies examine excised liver tissue that represents just one timepoint in disease progression,” said Professor Kim. “Our technique can capture details of lipid accumulation over time, providing a highly useful research tool for identifying the multiple parameters that likely contribute to the disease and could be targeted with treatment.” Capturing the dynamics of NAFLD in living mouse models of the disease requires the ability to observe quickly changing interactions of biological components in intact tissue in real-time. To accomplish this, the researchers developed a custom intravital confocal and two-photon microscopy system that acquires images of multiple fluorescent labels at video-rate with cellular resolution. “With video-rate imaging capability, the continuous movement of liver tissue in live mice due to breathing and heart beating could be tracked in real time and precisely compensated,” said Professor Kim. “This provided motion-artifact free high-resolution images of cellular and sub-cellular sized individual lipid droplets.” The key to fast imaging was a polygonal mirror that rotated at more than 240 miles per hour to provide extremely fast laser scanning. The researchers also incorporated four different lasers and four high-sensitivity optical detectors into the setup so that they could acquire multi-color images to capture different color fluorescent probes used to label the lipid droplets and microvasculature in the livers of live mice. “Our approach can capture real-time changes in cell behavior and morphology, vascular structure and function, and the spatiotemporal localization of biological components while directly visualizing of lipid droplet development in NAFLD progression,” said Professor Kim. “It also allows the analysis of the highly complex behaviors of various immune cells as NAFLD progresses.” The researchers demonstrated their approach by using it to observe the development and spatial distribution of lipid droplets in individual mice with NAFLD induced by a methionine and choline-deficient diet. Next, they plan to use it to study how the liver microenvironment changes during NAFLD progression by imaging the same mouse over time. They also want to use their microscope technique to visualize various immune cells and lipid droplets to better understand the complex liver microenvironment in NAFLD progression.
2020.08.21
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Deep Learning-Based Cough Recognition Model Helps Detect the Location of Coughing Sounds in Real Time
The Center for Noise and Vibration Control at KAIST announced that their coughing detection camera recognizes where coughing happens, visualizing the locations. The resulting cough recognition camera can track and record information about the person who coughed, their location, and the number of coughs on a real-time basis. Professor Yong-Hwa Park from the Department of Mechanical Engineering developed a deep learning-based cough recognition model to classify a coughing sound in real time. The coughing event classification model is combined with a sound camera that visualizes their locations in public places. The research team said they achieved a best test accuracy of 87.4 %. Professor Park said that it will be useful medical equipment during epidemics in public places such as schools, offices, and restaurants, and to constantly monitor patients’ conditions in a hospital room. Fever and coughing are the most relevant respiratory disease symptoms, among which fever can be recognized remotely using thermal cameras. This new technology is expected to be very helpful for detecting epidemic transmissions in a non-contact way. The cough event classification model is combined with a sound camera that visualizes the cough event and indicates the location in the video image. To develop a cough recognition model, a supervised learning was conducted with a convolutional neural network (CNN). The model performs binary classification with an input of a one-second sound profile feature, generating output to be either a cough event or something else. In the training and evaluation, various datasets were collected from Audioset, DEMAND, ETSI, and TIMIT. Coughing and others sounds were extracted from Audioset, and the rest of the datasets were used as background noises for data augmentation so that this model could be generalized for various background noises in public places. The dataset was augmented by mixing coughing sounds and other sounds from Audioset and background noises with the ratio of 0.15 to 0.75, then the overall volume was adjusted to 0.25 to 1.0 times to generalize the model for various distances. The training and evaluation datasets were constructed by dividing the augmented dataset by 9:1, and the test dataset was recorded separately in a real office environment. In the optimization procedure of the network model, training was conducted with various combinations of five acoustic features including spectrogram, Mel-scaled spectrogram and Mel-frequency cepstrum coefficients with seven optimizers. The performance of each combination was compared with the test dataset. The best test accuracy of 87.4% was achieved with Mel-scaled Spectrogram as the acoustic feature and ASGD as the optimizer. The trained cough recognition model was combined with a sound camera. The sound camera is composed of a microphone array and a camera module. A beamforming process is applied to a collected set of acoustic data to find out the direction of incoming sound source. The integrated cough recognition model determines whether the sound is cough or not. If it is, the location of cough is visualized as a contour image with a ‘cough’ label at the location of the coughing sound source in a video image. A pilot test of the cough recognition camera in an office environment shows that it successfully distinguishes cough events and other events even in a noisy environment. In addition, it can track the location of the person who coughed and count the number of coughs in real time. The performance will be improved further with additional training data obtained from other real environments such as hospitals and classrooms. Professor Park said, “In a pandemic situation like we are experiencing with COVID-19, a cough detection camera can contribute to the prevention and early detection of epidemics in public places. Especially when applied to a hospital room, the patient's condition can be tracked 24 hours a day and support more accurate diagnoses while reducing the effort of the medical staff." This study was conducted in collaboration with SM Instruments Inc. Profile: Yong-Hwa Park, Ph.D. Associate Professor yhpark@kaist.ac.kr http://human.kaist.ac.kr/ Human-Machine Interaction Laboratory (HuMaN Lab.) Department of Mechanical Engineering (ME) Korea Advanced Institute of Science and Technology (KAIST) https://www.kaist.ac.kr/en/ Daejeon 34141, Korea Profile: Gyeong Tae Lee PhD Candidate hansaram@kaist.ac.kr HuMaN Lab., ME, KAIST Profile: Seong Hu Kim PhD Candidate tjdgnkim@kaist.ac.kr HuMaN Lab., ME, KAIST Profile: Hyeonuk Nam PhD Candidate frednam@kaist.ac.kr HuMaN Lab., ME, KAIST Profile: Young-Key Kim CEO sales@smins.co.kr http://en.smins.co.kr/ SM Instruments Inc. Daejeon 34109, Korea (END)
2020.08.13
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Atomic Force Microscopy Reveals Nanoscale Dental Erosion from Beverages
KAIST researchers used atomic force microscopy to quantitatively evaluate how acidic and sugary drinks affect human tooth enamel at the nanoscale level. This novel approach is useful for measuring mechanical and morphological changes that occur over time during enamel erosion induced by beverages. Enamel is the hard-white substance that forms the outer part of a tooth. It is the hardest substance in the human body, even stronger than bone. Its resilient surface is 96 percent mineral, the highest percentage of any body tissue, making it durable and damage-resistant. The enamel acts as a barrier to protect the soft inner layers of the tooth, but can become susceptible to degradation by acids and sugars. Enamel erosion occurs when the tooth enamel is overexposed to excessive consumption of acidic and sugary food and drinks. The loss of enamel, if left untreated, can lead to various tooth conditions including stains, fractures, sensitivity, and translucence. Once tooth enamel is damaged, it cannot be brought back. Therefore, thorough studies on how enamel erosion starts and develops, especially at the initial stages, are of high scientific and clinical relevance for dental health maintenance. A research team led by Professor Seungbum Hong from the Department of Materials Science and Engineering at KAIST reported a new method of applying atomic force microscopy (AFM) techniques to study the nanoscale characterization of this early stage of enamel erosion. This study was introduced in the Journal of the Mechanical Behavior of Biomedical Materials (JMBBM) on June 29. AFM is a very-high-resolution type of scanning probe microscopy (SPM), with demonstrated resolution on the order of fractions of a nanometer (nm) that is equal to one billionth of a meter. AFM generates images by scanning a small cantilever over the surface of a sample, and this can precisely measure the structure and mechanical properties of the sample, such as surface roughness and elastic modulus. The co-lead authors of the study, Dr. Panpan Li and Dr. Chungik Oh, chose three commercially available popular beverages, Coca-Cola®, Sprite®, and Minute Maid® orange juice, and immersed tooth enamel in these drinks over time to analyze their impacts on human teeth and monitor the etching process on tooth enamel. Five healthy human molars were obtained from volunteers between age 20 and 35 who visited the KAIST Clinic. After extraction, the teeth were preserved in distilled water before the experiment. The drinks were purchased and opened right before the immersion experiment, and the team utilized AFM to measure the surface topography and elastic modulus map. The researchers observed that the surface roughness of the tooth enamel increased significantly as the immersion time increased, while the elastic modulus of the enamel surface decreased drastically. It was demonstrated that the enamel surface roughened five times more when it was immersed in beverages for 10 minutes, and that the elastic modulus of tooth enamel was five times lower after five minutes in the drinks. Additionally, the research team found preferential etching in scratched tooth enamel. Brushing your teeth too hard and toothpastes with polishing particles that are advertised to remove dental biofilms can cause scratches on the enamel surface, which can be preferential sites for etching, the study revealed. Professor Hong said, “Our study shows that AFM is a suitable technique to characterize variations in the morphology and mechanical properties of dental erosion quantitatively at the nanoscale level.” This work was supported by the National Research Foundation (NRF), the Ministry of Science and ICT (MSIT), and the KUSTAR-KAIST Institute of Korea. A dentist at the KAIST Clinic, Dr. Suebean Cho, Dr. Sangmin Shin from the Smile Well Dental, and Professor Kack-Kyun Kim at the Seoul National University School of Dentistry also collaborated in this project. Publication: Li, P., et al. (2020) ‘Nanoscale effects of beverages on enamel surface of human teeth: An atomic force microscopy study’. Journal of the Mechanical Behavior of Biomedical Materials (JMBBM), Volume 110. Article No. 103930. Available online at https://doi.org/10.1016/j.jmbbm.2020.103930 Profile: Seungbum Hong, Ph.D. Associate Professor seungbum@kaist.ac.kr http://mii.kaist.ac.kr/ Materials Imaging and Integration (MII) Lab. Department of Materials Science and Engineering (MSE) Korea Advanced Institute of Science and Technology (KAIST) https://www.kaist.ac.kr Daejeon 34141, Korea (END)
2020.07.21
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X-ray Scattering Shines Light on Protein Folding
- Multiple forms of a non-functional, unfolded protein follow different pathways and timelines to reach its folded, functional state, a study reveals. - KAIST researchers have used an X-ray method to track how proteins fold, which could improve computer simulations of this process, with implications for understanding diseases and improving drug discovery. Their findings were reported in the Proceedings of the National Academy of Sciences of the United States of America (PNAS) on June 30. When proteins are translated from their DNA codes, they quickly transform from a non-functional, unfolded state into their folded, functional state. Problems in folding can lead to diseases like Alzheimer’s and Parkinson’s. “Protein folding is one of the most important biological processes, as it forms the functioning 3D protein structure,” explained the physical chemist Hyotcherl Ihee of the Department of Chemistry at KAIST. Dr. Tae Wu Kim, the lead author of this research from Ihee’s group, added, “Understanding the mechanisms of protein folding is important, and could pave the way for disease study and drug development.” Ihee’s team developed an approach using an X-ray scattering technique to uncover how the protein cytochrome c folds from its initial unfolded state. This protein is composed of a chain of 104 amino acids with an iron-containing heme molecule. It is often used for protein folding studies. The researchers placed the protein in a solution and shined ultraviolet light on it. This process provides electrons to cytochrome c, reducing the iron within it from the ferric to the ferrous form, which initiates folding. As this was happening, the researchers beamed X-rays at very short intervals onto the sample. The X-rays scattered off all the atomic pairs in the sample and a detector continuously recorded the X-ray scattering patterns. The X-ray scattering patterns provided direct information regarding the 3D protein structure and the changes made in these patterns over time showed real-time motion of the protein during the folding process. The team found cytochrome c proteins initially exist in a wide variety of unfolded states. Once the folding process is triggered, they stop by a group of intermediates within 31.6 microseconds, and then those intermediates follow different pathways with different folding times to reach an energetically stable folded state. “We don’t know if this diversity in folding paths can be generalized to other proteins,” Ihee confessed. He continued, “However, we believe that our approach can be used to study other protein folding systems.” Ihee hopes this approach can improve the accuracy of models that simulate protein interactions by including information on their unstructured states. These simulations are important as they can help identify barriers to proper folding and predict a protein’s folded state given its amino acid sequence. Ultimately, the models could help clarify how some diseases develop and how drugs interact with various protein structures. Ihee’s group collaborated with Professor Young Min Rhee at the KAIST Department of Chemistry, and this work was supported by the National Research Foundation of Korea (NRF) and the Institute for Basic Science (IBS). Figure. The scientists found that non-functional unfolded forms of the protein cytochrome c follow different pathways and timelines to reach a stable functional folded state. Publications: Kim, T. W., et al. (2020) ‘Protein folding from heterogeneous unfolded state revealed by time-resolved X-ray solution scattering’. PNAS. Volume 117. Issue 26. Page 14996-15005. Available online at https://doi.org/10.1073/pnas.1913442117 Profile: Hyotcherl Ihee, Ph.D. Professor hyotcherl.ihee@kaist.ac.kr http://time.kaist.ac.kr/ Ihee Laboratory Department of Chemistry KAIST https://www.kaist.ac.kr Daejeon 34141, Korea Profile: Young Min Rhee, Ph.D. Professor ymrhee@kaist.ac.kr http://singlet.kaist.ac.kr Rhee Research Group Department of Chemistry KAIST https://www.kaist.ac.kr Daejeon 34141, Korea (END)
2020.07.09
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New Nanoparticle Drug Combination For Atherosclerosis
Physicochemical cargo-switching nanoparticles (CSNP) designed by KAIST can help significantly reduce cholesterol and macrophage foam cells in arteries, which are the two main triggers for atherosclerotic plaque and inflammation. The CSNP-based combination drug delivery therapy was proved to exert cholesterol-lowering, anti-inflammatory, and anti-proliferative functions of two common medications for treating and preventing atherosclerosis that are cyclodextrin and statin. Professor Ji-Ho Park and Dr. Heegon Kim from KAIST’s Department of Bio and Brain Engineering said their study has shown great potential for future applications with reduced side effects. Atherosclerosis is a chronic inflammatory vascular disease that is characterized by the accumulation of cholesterol and cholesterol-loaded macrophage foam cells in the intima. When this atherosclerotic plaque clogs and narrows the artery walls, they restrict blood flow and cause various cardiovascular conditions such as heart attacks and strokes. Heart attacks and strokes are the world’s first and fifth causes of death respectively. Oral statin administration has been used in clinics as a standard care for atherosclerosis, which is prescribed to lower blood cholesterol and inhibit its accumulation within the plaque. Although statins can effectively prevent the progression of plaque growth, they have only shown modest efficacy in eliminating the already-established plaque. Therefore, patients are required to take statin drugs for the rest of their lives and will always carry the risk of plaque ruptures that can trigger a blood clot. To address these issues, Professor Park and Dr. Kim exploited another antiatherogenic agent called cyclodextrin. In their paper published in the Journal of Controlled Release on March 10, Professor Park and Dr. Kim reported that the polymeric formulation of cyclodextrin with a diameter of approximately 10 nanometers(nm) can accumulate within the atherosclerotic plaque 14 times more and effectively reduce the plaque even at lower doses, compared to cyclodextrin in a non-polymer structure. Moreover, although cyclodextrin is known to have a cytotoxic effect on hair cells in the cochlea, which can lead to hearing loss, cyclodextrin polymers developed by Professor Park’s research group exhibited a varying biodistribution profile and did not have this side effect. In the follow-up study reported in ACS Nano on April 28, the researchers exploited both cyclodextrin and statin and form the cyclodextrin-statin self-assembly drug complex, based on previous findings that each drug can exert local anti-atherosclerosis effect within the plaque. The complex formation processes were optimized to obtain homogeneous and stable nanoparticles with a diameter of about 100 nm for systematic injection. The therapeutic synergy of cyclodextrin and statin could reportedly enhance plaque-targeted drug delivery and anti-inflammation. Cyclodextrin led to the regression of cholesterol in the established plaque, and the statins were shown to inhibit the proliferation of macrophage foam cells. The study suggested that combination therapy is required to resolve the complex inflammatory cholesterol-rich microenvironment within the plaque. Professor Park said, “While nanomedicine has been mainly developed for the treatment of cancers, our studies show that nanomedicine can also play a significant role in treating and preventing atherosclerosis, which causes various cardiovascular diseases that are the leading causes of death worldwide.” This work was supported by KAIST and the National Research Foundation (NRF) of Korea. Publications: 1. Heegon Kim, Junhee Han, and Ji-Ho Park. (2020) ‘Cyclodextrin polymer improves atherosclerosis therapy and reduces ototoxicity’ Journal of Controlled Release. Volume 319. Page 77-86. Available online at https://doi.org/10.1016/j.jconrel.2019.12.021 2. Kim, H., et al. (2020) ‘Affinity-Driven Design of Cargo-Switching Nanoparticles to Leverage a Cholesterol-Rich Microenvironment for Atherosclerosis Therapy’ ACS Nano. Available online at https://doi.org/10.1021/acsnano.9b08216 Profile: Ji-Ho Park, Ph.D. Associate Professor jihopark@kaist.ac.kr http://openwetware.org/wiki/Park_Lab Biomaterials Engineering Laboratory (BEL) Department of Bio and Brain Engineering (BIOENG) Korea Advanced Institute of Science and Technology (KAIST) https://www.kaist.ac.kr Daejeon 34141, Korea Profile: Heegon Kim, Ph.D. Postdoctoral Researcher heegon@kaist.ac.kr BEL, BIOENG, KAIST (END)
2020.06.16
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Simple Molecular Reagents to Treat Alzheimer’s Disease
- Researchers report minimalistic principles for designing small molecules with multiple reactivities against dementia. - Sometimes the most complex problems actually have very simple solutions. A group of South Korean researchers reported an efficient and effective redox-based strategy for incorporating multiple functions into simple molecular reagents against neurodegenerative disorders. The team developed redox-active aromatic molecular reagents with a simple structural composition that can simultaneously target and modulate various pathogenic factors in complex neurodegenerative disorders such as Alzheimer’s disease. Alzheimer’s disease is one of the most prevalent neurodegenerative disorders, affecting one in ten people over the age of 65. Early-onset dementia also increasingly affects younger people. A number of pathogenic elements such as reactive oxygen species, amyloid-beta, and metal ions have been suggested as potential causes of Alzheimer’s disease. Each element itself can lead to Alzheimer’s disease, but interactions between them may also aggravate the patient’s condition or interfere with the appropriate clinical care. For example, when interacting with amyloid-beta, metal ions foster the aggregation and accumulation of amyloid-beta peptides that can induce oxidative stress and toxicity in the brain and lead to neurodegeneration. Because these pathogenic factors of Alzheimer’s disease are intertwined, developing therapeutic agents that are capable of simultaneously regulating metal ion dyshomeostasis, amyloid-beta agglutination, and oxidative stress responses remains a key to halting the progression of the disease. A research team led by Professor Mi Hee Lim from the Department of Chemistry at KAIST demonstrated the feasibility of structure-mechanism-based molecular design for controlling a molecule’s chemical reactivity toward the various pathological factors of Alzheimer’s disease by tuning the redox properties of the molecule. This study, featured as the ‘ACS Editors’ Choice’ in the May 6th issue of the Journal of the American Chemical Society (JACS), was conducted in conjunction with KAIST Professor Mu-Hyun Baik’s group and Professor Joo-Young Lee’s group at the Asan Medical Center. Professor Lim and her collaborators rationally designed and generated 10 compact aromatic molecules presenting a range of redox potentials by adjusting the electronic distribution of the phenyl, phenylene, or pyridyl moiety to impart redox-dependent reactivities against the multiple pathogenic factors in Alzheimer’s disease. During the team’s biochemical and biophysical studies, these designed molecular reagents displayed redox-dependent reactivities against numerous desirable targets that are associated with Alzheimer’s disease such as free radicals, metal-free amyloid-beta, and metal-bound amyloid-beta. Further mechanistic results revealed that the redox properties of these designed molecular reagents were essential for their function. The team demonstrated that these reagents engaged in oxidative reactions with metal-free and metal-bound amyloid-beta and led to chemical modifications. The products of such oxidative transformations were observed to form covalent adducts with amyloid-beta and alter its aggregation. Moreover, the administration of the most promising candidate molecule significantly attenuated the amyloid pathology in the brains of Alzheimer’s disease transgenic mice and improved their cognitive defects. Professor Lim said, “This strategy is straightforward, time-saving, and cost-effective, and its effect is significant. We are excited to help enable the advancement of new therapeutic agents for neurodegenerative disorders, which can improve the lives of so many patients.” This work was supported by the National Research Foundation (NRF) of Korea, the Institute for Basic Science (IBS), and the Asan Institute for Life Sciences. Image credit: Professor Mi Hee Lim, KAIST Image usage restrictions: News organizations may use or redistribute this image, with proper attribution, as part of the news coverage of this paper only. Publication: Kim, M. et al. (2020) ‘Minimalistic Principles for Designing Small Molecules with Multiple Reactivities against Pathological Factors in Dementia.’ Journal of the American Chemical Society (JACS), Volume 142, Issue 18, pp.8183-8193. Available online at https://doi.org/10.1021/jacs.9b13100 Profile: Mi Hee Lim Professor miheelim@kaist.ac.kr http://sites.google.com/site/miheelimlab Lim Laboratory Department of Chemistry KAIST Profile: Mu-Hyun Baik Professor mbaik2805@kaist.ac.kr https://baik-laboratory.com/ Baik Laboratory Department of Chemistry KAIST Profile: Joo-Yong Lee Professor jlee@amc.seoul.kr Asan Institute for Life Sciences Asan Medical Center (END)
2020.05.11
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Professor Sukyung Park Named Presidential Science and Technology Adviser
Professor Sukyung Park from the Department of Mechanical Engineering was appointed as the science and technology adviser to the President Jae-in Moon on May 4. Professor Park, at the age of 47, became the youngest member of the president’s senior aide team at Chong Wa Dae. A Chong Wa Dae spokesman said on May 4 while announcing the appointment, “Professor Park, a talent with a great deal of policymaking participation in science and technology, will contribute to accelerating the government’s push for science and technology innovation, especially in the information and communications technology (ICT) sector.” Professor Park joined KAIST in 2004 as the first female professor of mechanical engineering. She is a biomechanics expert who has conducted extensive research on biometric mechanical behaviors. Professor Park is also a member of the KAIST Board of Trustees. Before that, she served as a senior researcher at the Korea Institute of Machinery and Materials (KIMM) as well as a member of the Presidential Advisory Council on Science and Technology. After graduating from Seoul Science High School as the first ever two-year graduate, Professor Park earned a bachelor and master’s degrees in mechanical engineering at KAIST. She then finished her Ph.D. from the University of Michigan. (END)
2020.05.06
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3D Hierarchically Porous Nanostructured Catalyst Helps Efficiently Reduce CO2
- This new catalyst will bring CO2 one step closer to serving as a sustainable energy source. - KAIST researchers developed a three-dimensional (3D) hierarchically porous nanostructured catalyst with carbon dioxide (CO2) to carbon monoxide (CO) conversion rate up to 3.96 times higher than that of conventional nanoporous gold catalysts. This new catalyst helps overcome the existing limitations of the mass transport that has been a major cause of decreases in the CO2 conversion rate, holding a strong promise for the large-scale and cost-effective electrochemical conversion of CO2 into useful chemicals. As CO2 emissions increase and fossil fuels deplete globally, reducing and converting CO2 to clean energy electrochemically has attracted a great deal of attention as a promising technology. Especially due to the fact that the CO2 reduction reaction occurs competitively with hydrogen evolution reactions (HER) at similar redox potentials, the development of an efficient electrocatalyst for selective and robust CO2 reduction reactions has remained a key technological issue. Gold (Au) is one of the most commonly used catalysts in CO2 reduction reactions, but the high cost and scarcity of Au pose obstacles for mass commercial applications. The development of nanostructures has been extensively studied as a potential approach to improving the selectivity for target products and maximizing the number of active stable sites, thus enhancing the energy efficiency. However, the nanopores of the previously reported complex nanostructures were easily blocked by gaseous CO bubbles during aqueous reactions. The CO bubbles hindered mass transport of the reactants through the electrolyte, resulting in low CO2 conversion rates. In the study published in the Proceedings of the National Academy of Sciences of the USA (PNAS) on March 4, a research group at KAIST led by Professor Seokwoo Jeon and Professor Jihun Oh from the Department of Materials Science and Engineering designed a 3D hierarchically porous Au nanostructure with two different sizes of macropores and nanopores. The team used proximity-field nanopatterning (PnP) and electroplating techniques that are effective for fabricating the 3D well-ordered nanostructures. The proposed nanostructure, comprised of interconnected macroporous channels 200 to 300 nanometers (nm) wide and 10 nm nanopores, induces efficient mass transport through the interconnected macroporous channels as well as high selectivity by producing highly active stable sites from numerous nanopores. As a result, its electrodes show a high CO selectivity of 85.8% at a low overpotential of 0.264 V and efficient mass activity that is up to 3.96 times higher than that of de-alloyed nanoporous Au electrodes. “These results are expected to solve the problem of mass transfer in the field of similar electrochemical reactions and can be applied to a wide range of green energy applications for the efficient utilization of electrocatalysts,” said the researchers. This work was supported by the National Research Foundation (NRF) of Korea. Image credit: Professor Seokwoo Jeon and Professor Jihun Oh, KAIST Image usage restrictions: News organizations may use or redistribute this image, with proper attribution, as part of news coverage of this paper only. Publication: Hyun et al. (2020) Hierarchically porous Au nanostructures with interconnected channels for efficient mass transport in electrocatalytic CO2 reduction. Proceedings of the National Academy of Sciences of the USA (PNAS). Available online at https://doi.org/10.1073/pnas.1918837117 Profile: Seokwoo Jeon, PhD Professor jeon39@kaist.ac.kr http://fdml.kaist.ac.kr Department of Materials Science and Engineering (MSE) https://www.kaist.ac.kr Korea Advanced Institute of Science and Technology (KAIST)Daejeon, Republic of Korea Profile: Jihun Oh, PhD Associate Professor jihun.oh@kaist.ac.kr http://les.kaist.ac.kr Department of Materials Science and Engineering (MSE) Department of Energy, Environment, Water and Sustainability (EEWS) KAIST Profile: Gayea Hyun PhD Candidate cldywkd93@kaist.ac.kr http://fdml.kaist.ac.kr Flexible Devices and Metamaterials Laboratory (FDML) Department of Materials Science and Engineering (MSE) KAIST Profile: Jun Tae Song, PhD Assistant Professor song.juntae@cstf.kyushu-u.ac.jp http://www.cstf.kyushu-u.ac.jp/~ishihara-lab/ Department of Applied Chemistry https://www.kyushu-u.ac.jp Kyushu UniversityFukuoka, Japan (END)
2020.03.13
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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 11923
KAIST Showcases Advanced Technologies at CES 2020
< President Sung-Chul Shin experiencing cooling gaming headset developed by TEGWAY > KAIST Pavilion showcased 12 KAIST startups and alumni companies’ technologies at the International Consumer Electronics Show (CES) 2020 held in Las Vegas last month. Especially four companies, TEGWAY, THE.WAVE.TALK, Sherpa Space, and LiBEST won the CES 2020 Innovation Awards presented by the Consumer Technology Association (CTA). The CTA selects the most innovative items from among all submissions. TEGWAY spinned off by KAIST Professor Byung Jin Cho already made international headlines for their flexible, wearable, and temperature immersive thermoelectric device. The device was selected as one of the top ten most promising digital technologies by the Netexplo Forum in 2015, and has been expanded into VR, AR, and games. THE.WAVE.TALK has developed their first home appliance product in collaboration with ID+IM Design Laboratory of KAIST in which Professor Sang-Min Bae heads as creative director. Their real-time bacteria analysis with smart IoT sensor won the home appliances section. Sherpa Space and LiBEST are the alumni companies. Sherpa Space’s lighting for plants won the sustainability, eco-design, and smart energy section, and LiBEST’s full-range flexible battery won the section for technology for a better world. KAIST’s Alumni Association, Development Foundation, and the Office of University-Industry Cooperation (OUIC) made every effort to present KAIST technologies to the global market. President Sung-Chul Shin led the delegation comprising of 70 faculty, researchers, and young entrepreneurs. The KAIST Alumni Association fully funded the traveling costs of 30 alumni entrepreneurs and students, establishing scholarship for the CES participation. Ten young entrepreneurs were selected through the KAIST Startup Awards, and 20 current students preparing to start their own companies were selected via recommendation from the respective departments. Associate Vice President of the OUIC Kyung Cheol Choi said in excitement, “We received many offers for joint research and investment from leading companies around the world,” adding, “We will continue doing our best to generate global value by developing the innovative technologies obtained from education and research into businesses.” The KAIST pavilion at CES 2020 showcased: 1. flexible thermoelectric device ThermoReal and cooling gaming headset from TEGWAY, 2. wearable flexible battery from LiBEST, 3. applications such as conductive transparent electrode film and transparent heating film from J-Micro, 4. on-device AI solution based on deep learning model compression technology from Nota, 5. portable high resolution brain imaging device from OBELAB, 6. real-time bacteria analysis technology from THE.WAVE.TALK, 7. conversation-based AI-1 radio service platform from Timecode Archive, 8. light source solutions for different stages in a plant’s life cycle from Sherpa Space, 9. skin attached micro-LED patch and flexible piezoelectric acoustic sensor from FRONICS, 10. real-time cardiovascular measurement device from Healthrian, 11. block chain based mobile research documentation system from ReDWit, and 12. student-developed comprehensive healthcare device using a smart mirror. (END)
2020.01.13
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