Research
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'Flying Drones for Rescue'
(Video Credit: ⓒNASA JPL)
< Team USRG and Professor Shim (second from the right) >
Having recently won the AI R&D Grand Challenge Competition in Korea, Team USRG (Unmanned System Research Group) led by Professor Hyunchul Shim from the School of Electrical Engineering is all geared up to take on their next challenges: the ‘Defense Advanced Research Projects Agency Subterranean Challenge (DARPA SubT Challenge)’ and ‘Lockheed Martin’s AlphaPilot Challenge’ next month.
Team USRG won the obstacle course race in the ‘2019 AI R&D Grand Challenge Competition’ on July 12. They managed to successfully dominate the challenging category of ‘control intelligence.’ Having to complete the obstacle course race solely using AI systems without any connection to the internet made it difficult for most of the eight participating teams to pass the third section of the race, and only Team USRG passed the long pipeline course during their attempt in the main event. They also demonstrated, after the main event, that their drone can navigate all of the checkpoints including landing on the “H” mark using deep learning.
Their drone flew through polls and pipes, and escaped from windows and mazes against strong winds, amid cheers and groans from the crowd gathered at the Korea Exhibition Center (KINTEX) in Goyang, Korea. The team was awarded three million KRW in prize money, and received a research grant worth six hundred million KRW from the Ministry of Science and ICT (MSIT).
“Being ranked first in the race for which we were never given a chance for a test flight means a lot to our team. Considering that we had no information on the exact size of the course in advance, this is a startling result,” said Professor Shim. “We will carry out further research with this funding, and compete once again with the improved AI and drone technology in the 2020 competition,” he added.
The AI R&D Grand Challenge Competition, which was first started in 2017, has been designed to promote AI research and development and expand its application to addressing high-risk technical challenges with significant socio-economic impact.
This year’s competition presented participants with a task where they had to develop AI software technology for drones to navigate themselves autonomously during complex disaster relief operations such as aid delivery.
Each team participated in one of the four tracks of the competition, and their drones were evaluated based on the criteria for each track. The divisions were broken up into intelligent context-awareness, intelligent character recognition, auditory intelligence, and control intelligence.
Team USRG’s technological prowess has been already well acclaimed among international peer groups. Teamed up with NASA JPL, Caltech, and MIT, they will compete in the subterranean mission during the ‘DARPA SubT Challenge’.
Team CoSTAR, as its name stands for, is working together to build ‘Collaborative SubTerranean Autonomous Resilient Robots.’ Professor Shim emphasized the role KAIST plays in Team CoSTAR as a leader in drone technology.
“I think when our drone technology will be added to our peers’ AI and robotics, Team CoSTAR will bring out unsurpassable synergy in completing the subterrestrial and planetary applications. I would like to follow the footprint of Hubo, the winning champion of the 2015 DARPA Robotics Challenge and even extend it to subterranean exploration,” he said.
These next generation autonomous subsurface explorers are now all optimizing the physical AI robot systems developed by Team CoSTAR. They will test their systems in more realistic field environments August 15 through 22 in Pittsburgh, USA. They have already received funding from DARPA for participating.
Team CoSTAR will compete in three consecutive yearly events starting this year, and the last event, planned for 2021, will put the team to the final test with courses that incorporate diverse challenges from all three events. Two million USD will be awarded to the winner after the final event, with additional prizes of up to 200,000 USD for self-funded teams.
Team USRG also ranked third in the recent Hyundai Motor Company’s ‘Autonomous Vehicle Competition’ and another challenge is on the horizon: Lockheed Martin’s ‘AlphaPilot Challenge’. In this event, the teams will be flying their drones through a series of racing gates, trying to beat the best human pilot. The challenge is hosted by Lockheed Martin, the world’s largest military contractor and the maker of the famed F-22 and F-35 stealth fighters, with the goal of stimulating the development of autonomous drones. Team USRG was selected from out of more than 400 teams from around the world and is preparing for a series of races this fall, beginning from the end of August.
Professor Shim said, “It is not easy to perform in a series of competitions in just a few months, but my students are smart, hardworking, and highly motivated. These events indeed demand a lot, but they really challenge the researchers to come up with technologies that work in the real world. This is the way robotics really should be.”
(END)
2019.07.26 View 10118 -
KAIST-Google Partnership for AI Education and Research
Google has agreed to support KAIST students and professors in the fields of AI research and education. President Sung-Chul Shin and Google Korea Country Director John Lee signed the collaboration agreement during a ceremony on July 19 at KAIST.
Under the agreement, Google will fund the Google AI-Focused Research Awards Program, the PhD Fellowship Program, and Student Travel Grants for KAIST. In addition, Google will continue to provide more academic and career building opportunities for students, including Google internship programs.
KAIST and Google has been collaborating for years. Professor Steven Whang at the School of Electrical Engineering and Professor Sung Ju Hwang at the School of Computing won the AI-Focused Award in 2018 and conduct their researches on "Improving Generalization and Reliability of Any Deep Neural Networks" and "Automatic and Acitionable Model Analysis for TFX," respectively. Outstanding PhD students have been recognized through the PhD Fellowship Program. However, this new collaboration agreement will focus on research, academic development, and technological innovation in AI.
Google plans to support research in the fields of deep learning, cloud machine learning, and voice technologies. Google will fund the development of two educational programs based on Google open source technology each year for two years that will be used in the new AI Graduate School opening for the fall semester.
John Lee of Google Korea said, “This partnership lays a solid foundation for deeper collaboration.” President Shin added, “This partnership will not only advance Korea’s global competitiveness in AI-powered industries but also contribute to the global community by nurturing talents in this most extensive discipline.”
2019.07.22 View 6882 -
Mathematical Modeling Makes a Breakthrough for a New CRSD Medication
PhD Candidate Dae Wook Kim (Left) and Professor Jae Kyoung Kim (Right)
- Systems approach reveals photosensitivity and PER2 level as determinants of clock-modulator efficacy -
Mathematicians’ new modeling has identified major sources of interspecies and inter-individual variations in the clinical efficacy of a clock-modulating drug: photosensitivity and PER2 level. This enabled precision medicine for circadian disruption.
A KAIST mathematics research team led by Professor Jae Kyoung Kim, in collaboration with Pfizer, applied a combination of mathematical modeling and simulation tools for circadian rhythms sleep disorders (CRSDs) to analyze the animal data generated by Pfizer. This study was reported in Molecular Systems Biology as the cover article on July 8.
Pharmaceutical companies have conducted extensive studies on animals to determine the candidacy of this new medication. However, the results of animal testing do not always translate to the same effects in human trials. Furthermore, even between humans, efficacy differs across individuals depending on an individual’s genetic and environmental factors, which require different treatment strategies.
To overcome these obstacles, KAIST mathematicians and their collaborators developed adaptive chronotherapeutics to identify precise dosing regimens that could restore normal circadian phase under different conditions.
A circadian rhythm is a 24-hour cycle in the physiological processes of living creatures, including humans. A biological clock in the hypothalamic suprachiasmatic nucleus in the human brain sets the time for various human behaviors such as sleep.
A disruption of the endogenous timekeeping system caused by changes in one’s life pattern leads to advanced or delayed sleep-wake cycle phase and a desynchronization between sleep-wake rhythms, resulting in CRSDs. To restore the normal timing of sleep, timing of the circadian clock could be adjusted pharmacologically.
Pfizer identified PF-670462, which can adjust the timing of circadian clock by inhibiting the core clock kinase of the circadian clock (CK1d/e). However, the efficacy of PF-670462 significantly differs between nocturnal mice and diurnal monkeys, whose sleeping times are opposite.
The research team discovered the source of such interspecies variations in drug response by performing thousands of virtual experiments using a mathematical model, which describes biochemical interactions among clock molecules and PF-670462. The result suggests that the effect of PF-670462 is reduced by light exposure in diurnal primates more than in nocturnal mice. This indicates that the strong counteracting effect of light must be considered in order to effectively regulate the circadian clock of diurnal humans using PF-670462.
Furthermore, the team also found the source of inter-patients variations in drug efficacy using virtual patients whose circadian clocks were disrupted due to various mutations. The degree of perturbation in the endogenous level of the core clock molecule PER2 affects the efficacy.
This explains why the clinical outcomes of clock-modulating drugs are highly variable and certain subtypes are unresponsive to treatment. Furthermore, this points out the limitations of current treatment strategies tailored to only the patient’s sleep and wake time but not to the molecular cause of sleep disorders.
PhD candidate Dae Wook Kim, who is the first author, said that this motivates the team to develop an adaptive chronotherapy, which identifies a personalized optimal dosing time of day by tracking the sleep-wake up time of patients via a wearable device and allows for a precision medicine approach for CRSDs.
Professor Jae Kyoung Kim said, "As a mathematician, I am excited to help enable the advancement of a new drug candidate, which can improve the lives of so many patients. I hope this result promotes more collaborations in this translational research.”
This research was supported by a Pfizer grant to KAIST (G01160179), the Human Frontiers Science Program Organization (RGY0063/2017), and a National Research Foundation (NRF) of Korea Grant (NRF-2016 RICIB 3008468 and NRF-2017-Fostering Core Leaders of the Future Basic Science Program/ Global Ph.D. Fellowship Program).
Figure 1. Interspecies and Inter-patients Variations in PF-670462 Efficacy
Figure 2. Journal Cover Page
Publication:
Dae Wook Kim, Cheng Chang, Xian Chen, Angela C Doran, Francois Gaudreault, Travis Wager, George J DeMarco, and Jae Kyoung Kim. 2019. Systems approach reveals photosensitivity and PER2 level as determinants of clock-modulator efficacy. Molecular Systems Biology. EMBO Press, Heidelberg, Germany, Vol. 15, Issue No. 7, Article, 16 pages. https://doi.org/10.15252/msb.20198838
Profile: Prof. Jae Kyoung Kim, PhD
jaekkim@kaist.ac.kr
http://mathsci.kaist.ac.kr/~jaekkim
Associate Professor
Department of Mathematical Sciences
Korea Advanced Institute of Science and Technology (KAIST)
http://kaist.ac.kr Daejeon 34141, Korea
Profile: Dae Wook Kim, PhD Candidate
0308kdo@kaist.ac.kr
http://mathsci.kaist.ac.kr/~jaekkim
PhD Candidate
Department of Mathematical Sciences
Korea Advanced Institute of Science and Technology (KAIST)
http://kaist.ac.kr Daejeon 34141, Korea
Profile: Dr. Cheng Chang, PhD
cheng.chang@pfizer.com
Associate Director of Clinical Pharmacology
Clinical Pharmacology, Global Product Development
Pfizer
https://www.pfizer.com/ Groton 06340, USA
(END)
2019.07.09 View 33592 -
Deep Learning-Powered 'DeepEC' Helps Accurately Understand Enzyme Functions
(Figure: Overall scheme of DeepEC)
A deep learning-powered computational framework, ‘DeepEC,’ will allow the high-quality and high-throughput prediction of enzyme commission numbers, which is essential for the accurate understanding of enzyme functions.
A team of Dr. Jae Yong Ryu, Professor Hyun Uk Kim, and Distinguished Professor Sang Yup Lee at KAIST reported the computational framework powered by deep learning that predicts enzyme commission (EC) numbers with high precision in a high-throughput manner.
DeepEC takes a protein sequence as an input and accurately predicts EC numbers as an output. Enzymes are proteins that catalyze biochemical reactions and EC numbers consisting of four level numbers (i.e., a.b.c.d) indicate biochemical reactions. Thus, the identification of EC numbers is critical for accurately understanding enzyme functions and metabolism.
EC numbers are usually given to a protein sequence encoding an enzyme during a genome annotation procedure. Because of the importance of EC numbers, several EC number prediction tools have been developed, but they have room for further improvement with respect to computation time, precision, coverage, and the total size of the files needed for the EC number prediction.
DeepEC uses three convolutional neural networks (CNNs) as a major engine for the prediction of EC numbers, and also implements homology analysis for EC numbers if the three CNNs do not produce reliable EC numbers for a given protein sequence. DeepEC was developed by using a gold standard dataset covering 1,388,606 protein sequences and 4,669 EC numbers.
In particular, benchmarking studies of DeepEC and five other representative EC number prediction tools showed that DeepEC made the most precise and fastest predictions for EC numbers. DeepEC also required the smallest disk space for implementation, which makes it an ideal third-party software component.
Furthermore, DeepEC was the most sensitive in detecting enzymatic function loss as a result of mutations in domains/binding site residue of protein sequences; in this comparative analysis, all the domains or binding site residue were substituted with L-alanine residue in order to remove the protein function, which is known as the L-alanine scanning method.
This study was published online in the Proceedings of the National Academy of Sciences of the United States of America (PNAS) on June 20, 2019, entitled “Deep learning enables high-quality and high-throughput prediction of enzyme commission numbers.”
“DeepEC can be used as an independent tool and also as a third-party software component in combination with other computational platforms that examine metabolic reactions. DeepEC is freely available online,” said Professor Kim.
Distinguished Professor Lee said, “With DeepEC, it has become possible to process ever-increasing volumes of protein sequence data more efficiently and more accurately.”
This work was supported by the Technology Development Program to Solve Climate Changes on Systems Metabolic Engineering for Biorefineries from the Ministry of Science and ICT through the National Research Foundation of Korea. This work was also funded by the Bio & Medical Technology Development Program of the National Research Foundation of Korea funded by the Korean government, the Ministry of Science and ICT.
Profile:
-Professor Hyun Uk Kim (ehukim@kaist.ac.kr)
https://sites.google.com/view/ehukim
Department of Chemical and Biomolecular Engineering
-Distinguished Professor Sang Yup Lee (leesy@kaist.ac.kr)
Department of Chemical and Biomolecular Engineering
http://mbel.kaist.ac.kr
2019.07.09 View 34541 -
Hydrogen-Natural Gas Hydrates Harvested by Natural Gas
A hydrogen-natural gas blend (HNGB) can be a game changer only if it can be stored safely and used as a sustainable clean energy resource. A recent study has suggested a new strategy for stably storing hydrogen, using natural gas as a stabilizer. The research proposed a practical gas phase modulator based synthesis of HNGB without generating chemical waste after dissociation for the immediate service.
The research team of Professor Jae Woo Lee from the Department of Chemical and Biomolecular Engineering in collaboration with the Gwangju Institute of Science and Technology (GIST) demonstrated that the natural gas modulator based synthesis leads to significantly reduced synthesis pressure simultaneously with the formation of hydrogen clusters in the confined nanoporous cages of clathrate hydrates. This approach minimizes the environmental impact and reduces operation costs since clathrate hydrates do not generate any chemical waste in both the synthesis and decomposition processes.
For the efficient storage and transportation of hydrogen, numerous materials have been investigated. Among others, clathrate hydrates offer distinct benefits. Clathrate hydrates are nanoporous inclusion compounds composed of a 3D network of polyhedral cages made of hydrogen-bonded ‘host’ water molecules and captured ‘guest’ gas or liquid molecules.
In this study, the research team used two gases, methane and ethane, which have lower equilibrium conditions compared to hydrogen as thermodynamic stabilizers. As a result, they succeeded in stably storing the hydrogen-natural gas compound in hydrates. According to the composition ratio of methane and ethane, structure I or II hydrates can be formed, both of which can stably store hydrogen-natural gas in low-pressure conditions.
The research team found that two hydrogen molecules are stored in small cages in tuned structure I hydrates, while up to three hydrogen molecules can be stored in both small and large cages in tuned structure II hydrates. Hydrates can store gas up to about 170-times its volume and the natural gas used as thermodynamic stabilizers in this study can also be used as an energy source.
The research team developed technology to produce hydrates from ice, produced hydrogen-natural gas hydrates by substitution, and successfully observed that the tuning phenomenon only occurs when hydrogen is involved in hydrate formation from the start for both structures of hydrates.
They expect that the findings can be applied to not only an energy-efficient gas storage material, but also a smart platform to utilize hydrogen natural gas blends, which can serve as a new alternative energy source with targeted hydrogen contents by designing synthetic pathways of mixed gas hydrates.
The research was published online in Energy Storage Materials on June 6, with the title ‘One-step formation of hydrogen clusters in clathrate hydrates stabilized via natural gas blending’.
Professor Lee said, “HNGB will utilize the existing natural gas infrastructure for transportation, so it is very likely that we can commercialize this hydrate system. We are investigating the kinetic performance through a follow-up strategy to increase the volume of gas storage.
This study was funded by the National Research Foundation of Korea and BK21 plus program.
(Figure1. Schematics showing the storage method for hydrogen in a natural gas hydrate using a substitution method and storage method directly from ice to a hydrogen-natural gas hydrate.)
(Figure 2. Artificially synthesized and dissociated hydrogen-natural gas hydrates. The Raman spectra of tuned sI and sII hydrate showing the hydrogen clusters in each cage.)
2019.06.21 View 39811 -
Efficiently Producing Fatty Acids and Biofuels from Glucose
Researchers have presented a new strategy for efficiently producing fatty acids and biofuels that can transform glucose and oleaginous microorganisms into microbial diesel fuel, with one-step direct fermentative production.
The newly developed strain, created by Distinguished Professor Sang Yup Lee and his team, showed the highest efficiency in producing fatty acids and biodiesels ever reported. It will be expected to serve as a new platform to sustainably produce a wide array of fatty acid-based products from glucose and other carbon substrates.
Fossil fuels, which have long been energy resources for our daily lives, are now facing serious challenges: depletion of their reserves and their role in global warming. The production of sustainable bio-based renewable energy has emerged as an essential alternative and many studies to replace fossil fuels are underway. One of the representative examples is biodiesel. Currently, it is mainly being produced through the transesterification of vegetable oils or animal fats.
The research team engineered oleaginous microorganisms, Rhodococcus opacus, to produce fatty acids and their derivatives that can be used as biodiesel from glucose, one of the most abundant and cheap sugars derived from non-edible biomass.
Professor Lee’s team has already engineered Escherichia coli to produce short-chain hydrocarbons, which can be used as gasoline (published in Nature as the cover paper in 2013). However, the production efficiency of the short-chain hydrocarbons using E. coli (0.58 g/L) fell short of the levels required for commercialization.
To overcome these issues, the team employed oil-accumulating Rhodococcus opacus as a host strain in this study. First, the team optimized the cultivation conditions of Rhodococcus opacus to maximize the accumulation of oil (triacylglycerol), which serves as a precursor for the biosynthesis of fatty acids and their derivatives. Then, they systematically analyzed the metabolism of the strain and redesigned it to enable higher levels of fatty acids and two kinds of fatty acid-derived biodiesels (fatty acid ethyl esters and long-chain hydrocarbons) to be produced.
They found that the resulting strains produced 50.2, 21.3, and 5.2 g/L of fatty acids, fatty acid ethyl esters, and long-chain hydrocarbons, respectively. These are all the highest concentrations ever reported by microbial fermentations. It is expected that these strains can contribute to the future industrialization of microbial-based biodiesel production.
“This technology creates fatty acids and biodiesel with high efficiency by utilizing lignocellulose, one of the most abundant resources on the Earth, without depending on fossil fuels and vegetable or animal oils. This will provide new opportunities for oil and petroleum industries, which have long relied on fossil fuels, to turn to sustainable and eco-friendly biotechnologies,” said Professor Lee.
This paper titled “Engineering of an oleaginous bacterium for the production of fatty acids and fuels” was published in Nature Chemical Biology on June 17.
This work was supported by the Technology Development Program to Solve Climate Changes on Systems Metabolic Engineering for Biorefineries from the Ministry of Science and ICT through the National Research Foundation (NRF) of Korea (NRF-2012M1A2A2026556 and NRF-2012M1A2A2026557).
(Figure: Metabolic engineering for the production of free fatty acids (FFAs), fatty acid ethyl esters (FAEEs), and long-chain hydrocarbons (LCHCs) in Rhodococcus opacus PD630. Researchers have presented a new strategy for efficiently producing fatty acids and biofuels that can transform glucose and oleaginous microorganisms into microbial diesel fuel, with one-step direct fermentative production.)
# # #
Source:
Hye Mi Kim, Tong Un Chae, So Young Choi, Won Jun Kim and Sang Yup Lee. Engineering of an oleaginous bacterium for the production of fatty acids and fuels. Nature Chemical Biology ( https://www.nature.com/nchembio/ ) DOI: 10.1038/s41589-019-0295-5
Profile
Dr. Sang Yup Lee
leesy@kaist.ac.kr
Distinguished Professor at the Department of Chemical and Biomolecular Engineering
KAIST
2019.06.19 View 46423 -
Play Games With No Latency
One of the most challenging issues for game players looks to be resolved soon with the introduction of a zero-latency gaming environment. A KAIST team developed a technology that helps game players maintain zero-latency performance. The new technology transforms the shapes of game design according to the amount of latency.
Latency in human-computer interactions is often caused by various factors related to the environment and performance of the devices, networks, and data processing. The term ‘lag’ is used to refer to any latency during gaming which impacts the user’s performance.
Professor Byungjoo Lee at the Graduate School of Culture Technology in collaboration with Aalto University in Finland presented a mathematical model for predicting players' behavior by understanding the effects of latency on players. This cognitive model is capable of predicting the success rate of a user when there is latency in a 'moving target selection' task which requires button input in a time constrained situation.
The model predicts the players’ task success rate when latency is added to the gaming environment. Using these predicted success rates, the design elements of the game are geometrically modified to help players maintain similar success rates as they would achieve in a zero-latency environment. In fact, this research succeeded in modifying the pillar heights of the Flappy Bird game, allowing the players to maintain their gaming performance regardless of the added latency.
Professor Lee said, "This technique is unique in the sense that it does not interfere with a player's gaming flow, unlike traditional methods which manipulate the game clock by the amount of latency. This study can be extended to various games such as reducing the size of obstacles in the latent computing environment.”
This research, in collaboration with Dr. Sunjun Kim from Aalto University and led by PhD candidate Injung Lee, was presented during the 2019 CHI Conference on Human Factors in Computing Systems last month in Glasgow in the UK.
This research was supported by the National Research Foundation of Korea (NRF) (2017R1C1B2002101, 2018R1A5A7025409), and the Aalto University Seed Funding Granted to the GamerLab respectively.
Figure 1. Overview of Geometric Compensation
Publication:
Injung Lee, Sunjun Kim, and Byungjoo Lee. 2019. Geometrically Compensating Effect of End-to-End Latency in Moving-Target Selection Games. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI’19) . ACM, New York, NY, USA, Article 560, 12 pages. https://doi.org/10.1145/3290605.3300790
Video Material:
https://youtu.be/TTi7dipAKJs
Profile: Prof. Byungjoo Lee, MD, PhD
byungjoo.lee@kaist.ac.kr
http://kiml.org/
Assistant Professor
Graduate School of Culture Technology (CT)
Korea Advanced Institute of Science and Technology (KAIST)
http://kaist.ac.kr Daejeon 34141, Korea
Profile: Injung Lee, PhD Candidate
edndn@kaist.ac.kr
PhD Candidate
Interactive Media Lab
Graduate School of Culture Technology (CT)
Korea Advanced Institute of Science and Technology (KAIST)
http://kaist.ac.kr
Daejeon 34141, Korea
Profile: Postdoc. Sunjun Kim, MD, PhD
kuaa.net@gmail.com
Postdoctoral Researcher
User Interfaces Group
Aalto University
https://www.aalto.fi Espoo 02150, Finland
(END)
2019.06.11 View 44815 -
Early Genome Catastrophes Can Cause Non-Smoking Lung Cancer
Some teenagers harbor catastrophic changes to their genomes that can lead to lung cancer later on in life, even if they never smoke
(Professor Young Seok Ju at the Graduate School of Medical Science and Engineering)
Catastrophic rearrangements in the genome occurring as early as childhood and adolescence can lead to the development of lung cancer in later years in non-smokers. This finding, published in Cell, helps explain how some non-smoking-related lung cancers develop.
Researchers at KAIST, Seoul National University and their collaborators confirmed that gene fusions in non-smokers mostly occur early on, sometimes as early as childhood or adolescence, and on average about three decades before cancer is diagnosed. The study showed that these mutant lung cells, harboring oncogenic seeds, remain dormant for several decades until a number of further mutations accumulate sufficiently for progression into cancer. This is the first study to reveal the landscape of genome structural variations in lung adenocarcinoma.
Lung cancer is the leading cause of cancer-related deaths worldwide, and lung adenocarcinoma is its most common type. Most lung adenocarcinomas are associated with chronic smoking, but about a fourth develop in non-smokers. Precisely what happens in non-smokers for this cancer to develop is not clearly understood.
Researchers analyzed the genomes of 138 lung adenocarcinoma patients, including smokers and non-smokers, with whole-genome sequencing technologies. They explored DNA damage that induced neoplastic transformation.
Lung adenocarcinomas that originated from chronic smoking, referred to as signature 4-high (S4-high) cancers in the study, showed several distinguishing features compared to smoking-unrelated cancers (S4-low).
People in the S4-high group were largely older, men and had more frequent mutations in a cancer-related gene called KRAS. Cancer genomes in the S4-high group were hypermutated with simple mutational classes, such as the substitution, insertion, or deletion of a single base, the building block of DNA.
But the story was very different in the S4-low group. Generally, mutational profiles in this group were much more silent than the S4-high group. However, all cancer-related gene fusions, which are abnormally activated from the merging of two originally separate genes, were exclusively observed in the S4-low group.
The patterns of genomic structural changes underlying gene fusions suggest that about three in four cases of gene fusions emerged from a single cellular crisis causing massive genomic fragmentation and subsequent imprecise repair in normal lung epithelium.
Most strikingly, these major genomic rearrangements, which led to the development of lung adenocarcinoma, are very likely to be acquired decades before cancer diagnosis. The researchers used genomic archaeology techniques to trace the timing of when the catastrophes took place.
Researchers started this study seven years ago when they discovered the expression of the KIF5B-RET gene fusion in lung adenocarcinoma for the first time. Professor Young-Seok Ju, co-lead author from the Graduate School of Medical Science and Engineering at KAIST says, “It is remarkable that oncogenesis can begin by a massive shattering of chromosomes early in life. Our study immediately raises a new question: What induces the mutational catastrophe in our normal lung epithelium.”
Professor Young Tae Kim, co-lead author from Seoul National University says, “We hope this work will help us get one step closer to precision medicine for lung cancer patients.”
The research team plans to further focus on the molecular mechanisms that stimulate complex rearrangements in the body, through screening the genomic structures of fusion genes in other cancer types.
This study was supported by the National Research Foundation of Korea (NRF), Korea Health Industry Development Institute (KHIDI), Suh Kyungbae Foundation, the College of Medicine Research Foundations at Seoul National University and others.
Figure.
(Smoking-unrelated oncogenesis of lung cancers by gene fusions)
Publication.
Jake June-Koo Lee, Seongyeol Park et al., Tracing Oncogene Rearrangements in the Mutational History of Lung Adenocarcinoma
Cell 177, June 13 2019, online publication ahead of print at May 30, 2019
https://doi.org/10.1016/j.cell.2019.05.013
Profile: Prof Young Seok Ju, MD, PhD
ysju@kaist.ac.kr
http://julab.kaist.ac.kr
Associate Professor
Graduate School of Medical Science and Engineering (GSMSE)
Korea Advanced Institute of Science and Technology (KAIST)
Daejeon 34141, Korea
Profile: Prof Young Tae Kim, MD, PhD
ytkim@snu.ac.kr
Professor
Seoul National University Cancer Research Institute
Department of Thoracic and Cardiovascular Surgery
Seoul National University Hospital Seoul 03080, Korea
2019.05.31 View 54834 -
5 Biomarkers for Overcoming Colorectal Cancer Drug Resistance Identified
< Professor Kwang-Hyun Cho's Team >
KAIST researchers have identified five biomarkers that will help them address resistance to cancer-targeting therapeutics. This new treatment strategy will bring us one step closer to precision medicine for patients who showed resistance.
Colorectal cancer is one of the most common types of cancer worldwide. The number of patients has surpassed 1 million, and its five-year survival rate significantly drops to about 20 percent when metastasized. In Korea, the surge of colorectal cancer has been the highest in the last 10 years due to increasing Westernized dietary patterns and obesity. It is expected that the number and mortality rates of colorectal cancer patients will increase sharply as the nation is rapidly facing an increase in its aging population.
Recently, anticancer agents targeting only specific molecules of colon cancer cells have been developed. Unlike conventional anticancer medications, these selectively treat only specific target factors, so they can significantly reduce some of the side-effects of anticancer therapy while enhancing drug efficacy.
Cetuximab is the most well-known FDA approved anticancer medication. It is a biomarker that predicts drug reactivity and utilizes the presence of the ‘KRAS’ gene mutation. Cetuximab is prescribed to patients who don’t carry the KRAS gene mutation.
However, even in patients without the KRAS gene mutation, the response rate of Cetuximab is only about fifty percent, and there is also resistance to drugs after targeted chemotherapy. Compared with conventional chemotherapy alone, the life expectancy only lasts five months on average.
In research featured in the FEBS Journal as the cover paper for the April 7 edition, the KAIST research team led by Professor Kwang-Hyun Cho at the Department of Bio and Brain Engineering presented five additional biomarkers that could increase Cetuximab responsiveness using systems biology approach that combines genomic data analysis, mathematical modeling, and cell experiments. The experimental inhibition of newly discovered biomarkers DUSP4, ETV5, GNB5, NT5E, and PHLDA1 in colorectal cancer cells has been shown to overcome Cetuximab resistance in KRAS-normal genes. The research team confirmed that when suppressing GNB5, one of the new biomarkers, it was shown to overcome resistance to Cetuximab regardless of having a mutation in the KRAS gene.
Professor Cho said, “There has not been an example of colorectal cancer treatment involving regulation of the GNB5 gene.” He continued, “Identifying the principle of drug resistance in cancer cells through systems biology and discovering new biomarkers that could be a new molecular target to overcome drug resistance suggest real potential to actualize precision medicine.”
This study was supported by the National Research Foundation of Korea (NRF) and funded by the Ministry of Science and ICT (2017R1A2A1A17069642 and 2015M3A9A7067220).
Image 1. The cover of FEBS Journal for April 2019
2019.05.27 View 57458 -
Research Day Highlights Most Outstanding Research Achievements
Professor Byung Jin Cho from the School of Electrical Engineering was selected as the Grand Research Prize Winner in recognition of his innovative research achievement in the fields of nano electric and flexible energy devices during the 2019 KAIST Research Day ceremony held on April 23 at the Chung Kunmo Conference Hall.
The ten most outstanding research achievements from the past year were also awarded in the three areas of Research, Innovation, Convergence Researches.
Professor Cho is an internationally recognized researcher in the field of future nano and energy device technology. Professor Cho’s team has continued to research on advanced CMOS (complementary metal-oxide semiconductors). CMOS has become his key research topic over the past three decades.
In 2014, he developed a glass fabric-based thermoelectric generator, which is extremely light and flexible and produces electricity from the heat of the human body. It is so flexible that the allowable bending radius of the generator is as low as 20 mm. There are no changes in performance even if the generator bends upward and downward for up to 120 cycles. His wearable thermoelectric generator was selected as one of the top ten most promising digital technologies by the Netexplo Forum in 2015.
He now is working on high-performance and ultra-flexible CMOS IC for biomedical applications, expanding his scope to thermal haptic technology in VR using graphene-CMOS hybrid integrated circuits; to self-powered wireless sensor nodes and self-powered ECG system using wearable thermoelectric generators .
In his special lecture at the ceremony, Professor Cho stressed the importance of collaboration in making scientific research and presented how he moved to future devices after focusing on scaling the devices.
“When I started the research on semiconductors, I focused on how to scale the device down as much as possible. For decades, we have conducted a number of procedures to produce tiny but efficient materials. Now we have shifted to develop flexible thermoelements and wearable devices,” said Professor Cho.
“We all thought the scaling down is the only way to create value-added technological breakthroughs. Now, the devices have been scaled down to 7nm and will go down to 5 nm soon. Over the past few years, I think we have gone through all the possible technological breakthroughs for reducing the size to 5nm. The semiconductor devices are made of more 1 billion transistors and go through 1,000 technological processes. So, there won’t be any possible way for a single genius to make a huge breakthrough. Without collaboration with others, it is nearly impossible to make any new technological breakthroughs.”
Professor Cho has published more than 240 papers in renowned academic journals and presented more than 300 papers at academic conferences. He has also registered approximately 50 patents in the field of semiconductor device technology.
The top ten research highlights of 2018 as follows:
- Rydberg-Atom Quantum Simulator Development by Professor Jaewook Ahn and Heung-Sun Sim from the Department of Physics
- From C-H to C-C Bonds at Room Temperature by Professor Mu-Hyun Baik from the Department of Chemistry
- The Role of Rodlike Counterions on the Interactions of DNAs by Professor Yong Woon Kim of the Graduate School of Nanoscience and Technology
- The Medal Preoptic Area Induces Hunting-Like Behaviors to Target Objects and Prey by Professor Daesoo Kim from the Department of Biological Sciences
- Identification of the Origin of Brain Tumors and New Therapeutic Strategy by Professor Jeong Ho Lee from the Graduate School of Medical Science and Engineering
- The Linear Frequency Conversion of Light at a Spatiotemporal Boundary by Professor Bumki Min from the Department of Mechanical Engineering
- An Industrial Grade Flexible Transparent Force Touch Sensor by Professor Jun-Bo Yoon from the School of Electrical Engineering
- The Detection and Clustering of Mixed-Type Defect Patterns in Wafer Bin Maps by Professor Heeyoung Kim from the Department of Industrial and Systems Engineering
- The Development of a Reconfigurable Spin-Based Logic Device by Professor Byong-Guk Park from the Department of Materials Science and Engineering
- The Development of a Miniaturized X-Ray Tube Based on Carbon Nanotube and Electronic Brachytherapy Device by Professor Sung Oh Cho from the Department of Nuclear and Quantum Engineering
Professor YongKeun Park from the Department of Physics and Professor In-Chel Park from the School of Electrical Engineering received the Research Award. For the Innovation Award, Professor Munchurl Kim from the School of Electrical Engineering was the recipient and the Convergence Research Awards was conferred to Professor Sung-Yool Choi from the School of Electrical Engineering, Professor Sung Gap Im from the Department of Chemical and Biomolecular Engineering, and Professor SangHee Park from the Department of Materials Science and Engineering during the ceremony.
For more on KAIST’s Top Research Achievements and Highlight of 2018, please refer to the attached below. click.
2019.04.25 View 13715 -
Professor Ji-Hyun Lee Awarded the Sasada Prize
Professor Ji-Hyun Lee from the Graduate School of Culture Technology was awarded the Sasada Prize during the 24th annual Conference of Computer-Aided Architectural Design Research in Asia (CAADRIA) held in Wellington, New Zealand on April 15.
The Sasada Award honors the late Professor Tsuyoshi Sasada (1941-2005), the former Professor of Osaka University and co-founder and fellow of CAADRIA. It is given to an individual who has contributed to the next generation of researchers and academics, to the wider profession and practice in computer-aided design and research, and has earned recognition in the academic community.
Professor Lee was recognized for her development of CAAD (Computer-Aided Architectural Design) through her research work on the land price precision system using case-based reasoning. Her research team proposed a model for estimating the average apartment price in an administrative district after collecting 40 variables from the six major Korean cities, excluding Seoul and Ulsan. Their follow-up studies showed the possibility of replacing existing experts’ predictions.
Professor Lee has been steadily researching for 20 years on case-based reasoning (CBR), a field of artificial intelligence, and has published more than 40 papers in the field of CBR. Meanwhile, the CAAD Future 2019 event will be held at KAIST in June.
2019.04.23 View 5459 -
Blue-enriched White Light to Wake You Up in the Morning
(from left: Professor Hyun Jung Chung, Professor Hyeon-Jeong Suk, Taesu Kim and Professor Kyungah Choi)
Here is a good news for those of who have difficulty with morning alertness. A KAIST research team proposed that a blue-enriched LED light can effectively help people overcome morning drowsiness. This study will provide the basis for major changes in future lighting strategies and thereby help create better indoor environments.
Considerable research has been devoted to unmasking circadian rhythms. The 2017 Nobel Prize in Physiology or Medicine went to Jeffrey C. Hall, Michael Rosbash, and Michael W. Young for unveiling the molecular mechanisms that control circadian rhythms. In particular, the relationship between light and its physiological effects has been investigated since the discovery of a novel, third type of photoreceptor in the human retina in the early 2000s. Rods and cones regulate visual effects, while the third type, photosensitive retinal ganglion cells, regulate a large variety of biological and behavioral processes including melatonin and cortisol secretion, alertness, and functional magnetic resonance imaging (fMRI).
Initial studies on light sources have shown that blue monochromatic, fully saturated lights are effective for stimulating physiological responses, but the relative effectiveness of commercially available white light sources is less well understood. Moreover, the research was more focused on the negative effects of blue light; for instance, when people are exposed to blue light at night, they have trouble achieving deep sleep because the light restrains melatonin secretion.
However, Professor Hyeon-Jeong Suk and Professor Kyungah Choi from the Department of Industrial Design and their team argue that the effects of blue-enriched morning light on physiological responses are time dependent, and that it has positive effects on melatonin levels and the subjective perception of alertness, mood, and visual comfort compared with warm white light.
The team conducted an experiment with 15 university students. They investigated whether an hour of morning light exposure with different chromaticity would affect their physiological and subjective responses differently. The decline of melatonin levels was significantly greater after the exposure to blue-enriched white light in comparison with warm white light.
Professor Suk said, “Light takes a huge part of our lives since we spend most of our time indoors. Light is one of the most powerful tools to affect changes in how we perceive and experience the environment around us.”
Professor Choi added, “When we investigate all of the psychological and physiological effects of light, we see there is much more to light than just efficient quantities. I believe that human-centric lighting strategies could be applied to a variety of environments, including residential areas, learning environments, and working spaces to improve our everyday lives.”
This research was collaborated with Professor Hyun Jung Chung from the Graduate School of Nanoscience and Technology and was published in Scientific Reports (10.1038/s41598-018-36791-5) on January 23, 2019.
Figure 1. Changes in melatonin secretion during day and night time
2019.03.06 View 10535