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Hubo Professor Jun-Ho Oh Donates Startup Shares Worth 5 Billion KRW
Rainbow Robotics stock used to endow the development fund
Emeritus Professor Jun-Ho Oh, who developed the 2015 DARPA Challenge winning humanoid robot DRC-Hubo, donated 5 billion KRW on October 25 during a ceremony held at the KAIST campus in Daejeon.
Professor Oh donated his 20% share (400 shares) of his startup Rainbow Robotics, which was established in 2011. Rainbow Robotics was listed on the KOSDAQ this February. The 400 shares were converted to 200,000 shares with a value of approximately 5 billion KRW when listed this year.
KAIST sold the stocks and endowed the Jun-Ho Oh Fund, which will be used for the development of the university. He was the 39th faculty member who launched a startup with technology from his lab and became the biggest faculty entrepreneur donor.
“I have received huge support and funding for my research. Fortunately, the research had a good result and led to the startup. Now I am very delighted to pay back the university. I feel that I have played a part in building the school’s startup ecosystem and creating a virtuous circle,” said Professor Oh during the ceremony.
KAIST President Kwang Hyung Lee declared, “Professor Oh has been a very impressive exemplary model for our aspiring faculty and student tech startups. We will spare no effort to support startups at KAIST.”
Professor Oh, who retired from the Department of Mechanical Engineering last year, now serves as the CTO at Rainbow Robotics. The company is developing humanoid bipedal robots and collaborative robots, and advancing robot technology including parts for astronomical observations.
Professor Hae-Won Park and Professor Je Min Hwangbo, who are now responsible for the Hubo Lab, also joined the ceremony along with employees of Rainbow Robotics.
2021.10.26 View 10508 -
New Chiral Nanostructures to Extend the Material Platform
Researchers observed a wide window of chiroptical activity from nanomaterials
A research team transferred chirality from the molecular scale to a microscale to extend material platforms and applications. The optical activity from this novel chiral material encompasses to short-wave infrared region.
This platform could serve as a powerful strategy for hierarchical chirality transfer through self-assembly, generating broad optical activity and providing immense applications including bio, telecommunication, and imaging technique. This is the first observation of such a wide window of chiroptical activity from nanomaterials.
“We synthesized chiral copper sulfides using cysteine, as the stabilizer, and transferring the chirality from molecular to the microscale through self-assembly,” explained Professor Jihyeon Yeom from the Department of Materials Science and Engineering, who led the research. The result was reported in ACS Nano on September 14.
Chiral nanomaterials provide a rich platform for versatile applications. Tuning the wavelength of polarization rotation maxima in the broad range is a promising candidate for infrared neural stimulation, imaging, and nanothermometry. However, the majority of previously developed chiral nanomaterials revealed the optical activity in a relatively shorter wavelength range, not in short-wave infrared.
To achieve chiroptical activity in the short-wave infrared region, materials should be in sub-micrometer dimensions, which are compatible with the wavelength of short-wave infrared region light for strong light-matter interaction. They also should have the optical property of short-wave infrared region absorption while forming a structure with chirality.
Professor Yeom’s team induced self-assembly of the chiral nanoparticles by controlling the attraction and repulsion forces between the building block nanoparticles. During this process, molecular chirality of cysteine was transferred to the nanoscale chirality of nanoparticles, and then transferred to the micrometer scale chirality of nanoflowers with 1.5-2 2 μm dimensions formed by the self-assembly.
“We will work to expand the wavelength range of chiroptical activity to the short-wave infrared region, thus reshaping our daily lives in the form of a bio-barcode that can store vast amount of information under the skin,” said Professor Yeom.
This study was funded by the Ministry of Science and ICT, the Ministry of Health and Welfare, the Ministry of Food and Drug Safety, the National Research Foundation of Korea,the KAIST URP Program, the KAIST Creative Challenging Research Program, Samsung and POSCO Science Fellowship.
-PublicationKi Hyun Park, Junyoung Kwon, Uichang Jeong, Ji-Young Kim, Nicholas A.Kotov, Jihyeon Yeom, “Broad Chrioptical Activity from Ultraviolet to Short-Wave Infrared by Chirality Transfer from Molecular to Micrometer Scale," September 14, 2021 ACS Nano (https://doi.org/10.1021/acsnano.1c05888)
-ProfileProfessor Jihyeon YeomNovel Nanomaterials for New Platforms LaboratoryDepartment of Materials Science and EngineeringKAIST
2021.10.22 View 11230 -
Flexible Sensor-Integrated RFA Needle Leads to Smarter Medical Treatment
Clinical trial of flexible sensor-integrated radiofrequency ablation (RFA) needle tip monitors physical changes and steam pop
Researchers have designed a thin polymeric sensor platform on a radiofrequency ablation needle to monitor temperature and pressure in real time. The sensors integrated onto 1.5 mm diameter needle tip have proven their efficacy during clinical tests and expect to provide a new opportunity for safer and more effective medical practices. The research was reported in Advanced Science as the frontispiece on August 5.
Radiofrequency ablation (RFA) is a minimally invasive surgery technique for removing tumors and treating cardiovascular disease. During a procedure, an unintended audible explosion called ‘steam pop’ can occur due to the increased internal steam pressure in the ablation region. This phenomenon has been cited as a cause of various negative thermal and mechanical effects on neighboring tissue. Even more, the relationship between steam pop and cancer recurrence is still being investigated.
Professor Inkyu Park said that his team’s integrated sensors reliably detected the occurrence of steam pop. The sensors also monitor rapidly spreading hot steam in tissue. It is expected that the diverse properties of tissue undergoing RFA could be checked by utilizing the physical sensors integrated on the needle.
“We believe that the integrated sensors can provide useful information about a variety of medical procedures and accompanying environmental changes in the human body, and help develop more effective and safer surgical procedures,” said Professor Park.
Professor Park’s team built a thin film type pressure and temperature sensor stack with a thickness of less than 10 μm using a microfabrication process. For the pressure sensor, the team used contact resistance changes between metal electrodes and a carbon nanotube coated polymeric membrane. The entire sensor array was thoroughly insulated with medical tubes to minimize any exposure of the sensor materials to external tissue and maximize its biocompatibility.
During the clinical trial, the research team found that the accumulated hot steam is suddenly released during steam pops and this hot air spreads to neighboring tissue, which accelerates the ablation process. Furthermore, using in-situ ultrasound imaging and computational simulations, the research team could confirm the non-uniform temperature distribution around the RFA needle can be one of the primary reasons for the steam popping.
Professor Park explained that various physical and chemical sensors for different targets can be added to create other medical devices and industrial tools.
“This result will expand the usability and applicability of current flexible sensor technologies. We are also trying to integrate this sensor onto a 0.3mm diameter needle for in-vivo diagnosis applications and expect that this approach can be applied to other medical treatments as well as the industrial field,” added Professor Park. This study was supported by the National Research Foundation of Korea.
-PublicationJaeho Park, Jinwoo Lee, Hyo Keun Lim, Inkyu Park et al. “Real-Time Internal Steam Pop Detection during Radiofrequency Ablation with a Radiofrequency Ablation Needle Integrated with a Temperature and Pressure Sensor: Preclinical and clinical pilot tests," Advanced Science (https://doi/org/10.1002/advs.202100725) on August 5, 2021
-ProfileProfessor Inkyu ParkMicro & Nano Tranducers Laboratory http://mintlab1.kaist.ac.kr/
Department of Mechanical EngineeringCollege of EngineeringKAIST
2021.10.20 View 9749 -
Industrial Liaison Program to Provide Comprehensive Consultation Services
The ILP’s one-stop solutions target all industrial sectors including conglomerates, small and medium-sized enterprises, venture companies, venture capital (VC) firms, and government-affiliated organizations.
The Industrial Liaison Center at KAIST launched the Industrial Liaison Program (ILP) on September 28, an industry-academic cooperation project to provide comprehensive solutions to industry partners. The Industrial Liaison Center will recruit member companies for this service every year, targeting all industrial sectors including conglomerates, small and medium-sized enterprises, venture companies, venture capital (VC) firms, and government-affiliated organizations.
The program plans to build a one-stop support system that can systematically share and use excellent resource information from KAIST’s research teams, R&D achievements, and infrastructure to provide member companies with much-needed services.
More than 40 KAIST professors with abundant academic-industrial collaboration experience will participate in the program. Experts from various fields with different points of view and experiences will jointly provide solutions to ILP member companies. To actively participate in academic-industrial liaisons and joint consultations, KAIST assigned 10 professors from related fields as program directors.
The program directors will come from four different fields including AI/robots (Professor Alice Oh, School from the School of Computing, Professor Young Jae Jang from the Department of Industrial & Systems Engineering, and Professor Yong-Hwa Park from Department of Mechanical Engineering), bio/medicine (Professor Daesoo Kim from Department of Biological Sciences and Professor YongKeun Park from Department of Physics), materials/electronics (Professor Sang Ouk Kim from the Department of Materials Science and Engineering and Professors Jun-Bo Yoon and Seonghwan Cho from the School of Electrical Engineering), and environment/energy (Professor Hee-Tak Kim from the Department of Biological Sciences and Professor Hoon Sohn from the Department of Civil and Environmental Engineering).
The transdisciplinary board of consulting professors that will lead technology innovation is composed of 30 professors including Professor Min-Soo Kim (School of Computing, AI), Professor Chan Hyuk Kim (Department of Biological Sciences, medicine), Professor Hae-Won Park (Department of Mechanical Engineering, robots), Professor Changho Suh (School of Electrical Engineering, electronics), Professor Haeshin Lee (Department of Chemistry, bio), Professor Il-Doo Kim (Department of Materials Science and Engineering, materials), Professor HyeJin Kim (School of Business Technology and Management), and Professor Byoung Pil Kim (School of Business Technology and Management, technology law)
The Head of the Industrial Liaison Center who is also in charge of the program, Professor Keon Jae Lee, said, “In a science and technology-oriented generation where technological supremacy determines national power, it is indispensable to build a new platform upon which innovative academic-industrial cooperation can be pushed forward in the fields of joint consultation, the development of academic-industrial projects, and the foundation of new industries.
He added, “KAIST professors carry out world-class research in many different fields and faculty members can come together through the ILP to communicate with representatives from industry to improve their corporations’ global competitiveness and further contribute to our nation’s interests by cultivating strong small enterprises
2021.09.30 View 7699 -
Deep Learning Framework to Enable Material Design in Unseen Domain
Researchers propose a deep neural network-based forward design space exploration using active transfer learning and data augmentation
A new study proposed a deep neural network-based forward design approach that enables an efficient search for superior materials far beyond the domain of the initial training set. This approach compensates for the weak predictive power of neural networks on an unseen domain through gradual updates of the neural network with active transfer learning and data augmentation methods.
Professor Seungwha Ryu believes that this study will help address a variety of optimization problems that have an astronomical number of possible design configurations. For the grid composite optimization problem, the proposed framework was able to provide excellent designs close to the global optima, even with the addition of a very small dataset corresponding to less than 0.5% of the initial training data-set size. This study was reported in npj Computational Materials last month.
“We wanted to mitigate the limitation of the neural network, weak predictive power beyond the training set domain for the material or structure design,” said Professor Ryu from the Department of Mechanical Engineering.
Neural network-based generative models have been actively investigated as an inverse design method for finding novel materials in a vast design space. However, the applicability of conventional generative models is limited because they cannot access data outside the range of training sets. Advanced generative models that were devised to overcome this limitation also suffer from weak predictive power for the unseen domain.
Professor Ryu’s team, in collaboration with researchers from Professor Grace Gu’s group at UC Berkeley, devised a design method that simultaneously expands the domain using the strong predictive power of a deep neural network and searches for the optimal design by repetitively performing three key steps.
First, it searches for few candidates with improved properties located close to the training set via genetic algorithms, by mixing superior designs within the training set. Then, it checks to see if the candidates really have improved properties, and expands the training set by duplicating the validated designs via a data augmentation method. Finally, they can expand the reliable prediction domain by updating the neural network with the new superior designs via transfer learning. Because the expansion proceeds along relatively narrow but correct routes toward the optimal design (depicted in the schematic of Fig. 1), the framework enables an efficient search.
As a data-hungry method, a deep neural network model tends to have reliable predictive power only within and near the domain of the training set. When the optimal configuration of materials and structures lies far beyond the initial training set, which frequently is the case, neural network-based design methods suffer from weak predictive power and become inefficient.
Researchers expect that the framework will be applicable for a wide range of optimization problems in other science and engineering disciplines with astronomically large design space, because it provides an efficient way of gradually expanding the reliable prediction domain toward the target design while avoiding the risk of being stuck in local minima. Especially, being a less-data-hungry method, design problems in which data generation is time-consuming and expensive will benefit most from this new framework.
The research team is currently applying the optimization framework for the design task of metamaterial structures, segmented thermoelectric generators, and optimal sensor distributions. “From these sets of on-going studies, we expect to better recognize the pros and cons, and the potential of the suggested algorithm. Ultimately, we want to devise more efficient machine learning-based design approaches,” explained Professor Ryu.This study was funded by the National Research Foundation of Korea and the KAIST Global Singularity Research Project.
-Publication
Yongtae Kim, Youngsoo, Charles Yang, Kundo Park, Grace X. Gu, and Seunghwa Ryu, “Deep learning framework for material design space exploration using active transfer learning and data augmentation,” npj Computational Materials (https://doi.org/10.1038/s41524-021-00609-2)
-Profile
Professor Seunghwa Ryu
Mechanics & Materials Modeling Lab
Department of Mechanical Engineering
KAIST
2021.09.29 View 13195 -
Two Researchers Designated as SUHF Fellows
Professor Taeyun Ku from the Graduate School of Medical Science and Engineering and Professor Hanseul Yang from the Department of Biological Sciences were nominated as 2021 fellows of the Suh Kyungbae Foundation (SUHF).
SUHF selected three young promising scientists from 53 researchers who are less than five years into their careers. A panel of judges comprised of scholars from home and abroad made the final selection based on the candidates’ innovativeness and power to influence. Professor You-Bong Hyun from Seoul National University also won the fellowship.
Professor Ku’s main topic is opto-connectomics. He will study ways to visualize the complex brain network using innovative technology that transforms neurons into optical elements.
Professor Yang will research the possibility of helping patients recover from skin diseases or injuries without scars by studying spiny mouse genes.
SUHF was established by Amorepacific Group Chairman Suh Kyungbae in 2016 with 300 billion KRW of his private funds. Under the vision of ‘contributing to humanity by supporting innovative discoveries of bioscience researchers,’ the foundation supports promising Korean scientists who pioneer new fields of research in biological sciences.
From 2017 to this year, SUHF has selected 20 promising scientists in the field of biological sciences. Selected scientists are provided with up to KRW 500 million each year for five years. The foundation has provided a total of KRW 48.5 billion in research funds to date.
2021.09.15 View 9616 -
Professor Il-Doo Kim Receives the Science Minister’s Award
Professor Il-Doo Kim from the Department of Materials Science and Engineering received the Science and ICT Minister’s Award in recognition of his commercialization and technology transfer achievements during the Day of IP celebration.
Professor Kim, who has made over 222 patents application and registration home and abroad, has advanced toxic gas detection and breath gas sensor technology by arraying nanosensor fibers. His technological advances in micro-electro-mechanical systems (MEMS) helped to advance the commercialization of the MEMS-related sensor and improve its overall competitiveness.
He founded the Il-Doo Kim Research Center in 2019 and focuses on the commercialization of nanofiber manufacturing through electrospinning and highly efficient nanofiber filters. For instance, he succeeded in manufacturing a nano-filter recyclable mask that maintains excellent filtering efficiency even after hand washing through the development of proprietary technology that aligns nanofibers with a diameter of 100~500 nanometers in orthogonal or unidirectional directions.
Professor Kim also serves as an associate editor at ACS Nano. He said, “The importance of IP goes without saying. I look forward to the registration and application of more KAIST patents leading to commercialization, paving the way for national technological competitiveness.”
2021.09.15 View 7839 -
The Dynamic Tracking of Tissue-Specific Secretory Proteins
Researchers develop a versatile and powerful tool for studying the spatiotemporal dynamics of secretory proteins, a valuable class of biomarkers and therapeutic targets
Researchers have presented a method for profiling tissue-specific secretory proteins in live mice. This method is expected to be applicable to various tissues or disease models for investigating biomarkers or therapeutic targets involved in disease progression. This research was reported in Nature Communications on September 1.
Secretory proteins released into the blood play essential roles in physiological systems. They are core mediators of interorgan communication, while serving as biomarkers and therapeutic targets.
Previous studies have analyzed conditioned media from culture models to identify cell type-specific secretory proteins, but these models often fail to fully recapitulate the intricacies of multi-organ systems and thus do not sufficiently reflect biological realities.
These limitations provided compelling motivation for the research team led by Jae Myoung Suh and his collaborators to develop techniques that could identify and resolve characteristics of tissue-specific secretory proteins along time and space dimensions.
For addressing this gap in the current methodology, the research team utilized proximity-labeling enzymes such as TurboID to label secretory proteins in endoplasmic reticulum lumen using biotin. Thereafter, the biotin-labeled secretory proteins were readily enriched through streptavidin affinity purification and could be identified through mass spectrometry.
To demonstrate its functionality in live mice, research team delivered TurboID to mouse livers via an adenovirus. After administering the biotin, only liver-derived secretory proteins were successfully detected in the plasma of the mice. Interestingly, the pattern of biotin-labeled proteins secreted from the liver was clearly distinctive from those of hepatocyte cell lines.
First author Kwang-eun Kim from the Graduate School of Medical Science and Engineering explained, “The proteins secreted by the liver were significantly different from the results of cell culture models. This data shows the limitations of cell culture models for secretory protein study, and this technique can overcome those limitations. It can be further used to discover biomarkers and therapeutic targets that can more fully reflect the physiological state.”
This work research was supported by the National Research Foundation of Korea, the KAIST Key Research Institutes Project (Interdisciplinary Research Group), and the Institute for Basic Science in Korea.
-PublicationKwang-eun Kim, Isaac Park et al., “Dynamic tracking and identification of tissue-specific secretory proteins in the circulation of live mice,” Nature Communications on Sept.1,
2021(https://doi.org/10.1038/s41467-021-25546-y)
-ProfileProfessor Jae Myoung Suh Integrated Lab of Metabolism, Obesity and Diabetes Researchhttps://imodkaist.wixsite.com/home
Graduate School of Medical Science and Engineering College of Life Science and BioengineeringKAIST
2021.09.14 View 10256 -
Digital Big Bang, Metaverse Technologies
The GSI Forum 2021 will explore the potential of new metaverse technologies that will change our daily lives
KAIST will be hosting a live online international forum on Sept.8 at 9 am (KST) through its KAIST YouTube channel. The forum will explore global trends regarding metaverse technology innovations and applications and discuss how we can build a new technology ecosystem.
Titled `Digital Big Bang, Metaverse Technology,' the Global Strategy Institute-International Forum 2021 will be the fourth event of its kind, following the three international forums held in 2020. The forum will delve into the development trends of metaverse platforms and AR/VR technologies and gather experts to discuss how such technologies could transform multiple aspects of our future, including education.
President Kwang Hyung Lee explains in his opening remarks that new technologies are truly opening a new horizon for our lives, saying, “In the education sector, digital technology will also create new opportunities to resolve the longstanding pedagogical shortfalls of one-way knowledge delivery systems. New digital technologies will help to unlock the creativity of our students. Education tailored to the students’ individual levels will not only help them accumulate knowledge but improve their ability to use it. Universities around the world are now at the same starting line. We should carve out our own distinct metaverse that is viable for human interactions and diverse technological experiences that promote students’ creativity and collaborative minds.”
Minster of Science and ICT Hyesook Lim will introduce how the Korean government is working to develop metaverse industries as a new potential engine of growth for the future in her welcoming remarks. The government’s efforts include collaborations with the private sector, investments in R&D, the development of talent, and regulatory reforms. Minister Lim will also emphasize the importance of national-level discussions regarding the establishment of a metaverse ecosystem and long-term value creation.
The organizers have invited global experts to share their knowledge and insights.
Kidong Bae, who is in charge of the KT Enterprise Project and ‘Metaverse One Team’ will talk about the current trends in the metaverse market and their implications, as well as KT’s XR technology references. He will also introduce strategies to establish and utilize a metaverse ecosystem, and highlight their new technologies as a global leader in 5G networks.
Jinha Lee, co-founder and CPO of the American AR solution company Spatial, will showcase a remote collaboration office that utilizes AR technology as a potential solution for collaborative activities in the post-COVID-19 era, where remote working is the ‘new normal.’ Furthermore, Lee will discuss how future workplaces that are not limited by space or distance will affect our values and creativity.
Professor Frank Steinicke from the University of Hamburg will present the ideal form of next-generation immersive technology that combines intelligent virtual agents, mixed reality, and IoT, and discuss his predictions for how the future of metaverse technology will be affected.
Marco Tempest, a creative technologist at NASA and a Director’s Fellow at the MIT Media Lab, will also be joining the forum as a plenary speaker. Tempest will discuss the potential of immersive technology in media, marketing, and entertainment, and will propose a future direction for immersive technology to enable the sharing of experiences, emotions, and knowledge.
Other speakers include Beomjoo Kim from Unity Technologies Korea, Professor Woontaek Woo from the Graduate School of Culture Technology at KAIST, Vice President of Global Sales at Labster Joseph Ferraro, and CEO of 3DBear Jussi Kajala. They will make presentations on metaverse technology applications for future education.
The keynote session will also have an online panel consisting of 50 domestic and overseas metaverse specialists, scientists, and teachers. The forum will hold a Q&A and discussion session where the panel members can ask questions to the keynote speakers regarding the prospects of metaverse and immersive technologies for education.
GSI Director Hoon Sohn stated, "KAIST will seize new opportunities that will arise in a future centered around metaverse technology and will be at the forefront to take advantage of the growing demand for innovative science and technology in non-contact societies. KAIST will also play a pivotal role in facilitating global cooperation, which will be vital to establish a metaverse ecosystem.”
2021.09.07 View 10014 -
How Stingrays Became the Most Efficient Swimmers in Nature
Study shows the hydrodynamic benefits of protruding eyes and mouth in a self-propelled flexible stingray
With their compressed bodies and flexible pectoral fins, stingrays have evolved to become one of nature’s most efficient swimmers. Scientists have long wondered about the role played by their protruding eyes and mouths, which one might expect to be hydrodynamic disadvantages.
Professor Hyung Jin Sung and his colleagues have discovered how such features on simulated stingrays affect a range of forces involved in propulsion, such as pressure and vorticity. Despite what one might expect, their research team found these protruding features actually help streamline the stingrays.
‘The influence of the 3D protruding eyes and mouth on a self-propelled flexible stingray and its underlying hydrodynamic mechanism are not yet fully understood,” said Professor Sung. “In the present study, the hydrodynamic benefit of protruding eyes and mouth was explored for the first time, revealing their hydrodynamic role.”
To illustrate the complex interplay between hydrodynamic forces, the researchers set to work creating a computer model of a self-propelled flexible plate. They clamped the front end of the model and then forced it to mimic the up-and-down harmonic oscillations stingrays use to propel themselves.
To re-create the effect of the eyes and mouth on the surrounding water, the team simulated multiple rigid plates on the model. They compared this model to one without eyes and a mouth using a technique called the penalty immersed boundary method.
“Managing random fish swimming and isolating the desired purpose of the measurements from numerous factors was difficult,” Sung said. “To overcome these limitations, the penalty immersed boundary method was adopted to find the hydrodynamic benefits of the protruding eyes and mouth.”
The team discovered that the eyes and mouth generated a vortex of flow in the forward-backward , which increased negative pressure at the simulated animal’s front, and a side-to-side vortex that increased the pressure difference above and below the stingray. The result was increased thrust and accelerated cruising.
Further analysis showed that the eyes and mouth increased overall propulsion efficiency by more than 20.5% and 10.6%, respectively.
Researchers hope their work, driven by curiosity, further stokes interest in exploring fluid phenomena in nature. They are hoping to find ways to adapt this for next-generation water vehicle designs based more closely on marine animals.
This study was supported by the National Research Foundation of Korea and the State Scholar Fund from the China Scholarship Council.
-ProfileProfessor Hyung Jin SungDepartment of Mechanical EngineeringKAIST
-PublicationHyung Jin Sung, Qian Mao, Ziazhen Zhao, Yingzheng Liu, “Hydrodynamic benefits of protruding eyes and mouth in a self-propelled flexible stingray,” Aug.31, 2021, Physics of Fluids
(https://doi.org/10.1063/5.0061287)
-News release from the American Institute of Physics, Aug.31, 2021
2021.09.06 View 8383 -
Genomic Data Reveals New Insights into Human Embryonic Development
KAIST researchers have used whole-genome sequencing to track the development from a single fertilized-egg to a human body
Genomic scientists at KAIST have revealed new insights into the process of human embryonic development using large-scale, whole-genome sequencing of cells and tissues from adult humans. The study, published in Nature on Aug.25, is the first to analyse somatic mutations in normal tissue across multiple organs within and between humans.
An adult human body comprises trillions of cells of more than 200 types. How a human develops from a single fertilized egg to a fully grown adult is a fundamental question in biomedical science. Due to the ethical challenges of performing studies on human embryos, however, the details of this process remain largely unknown.
To overcome these issues, the research team took a different approach. They analysed genetic mutations in cells taken from adult human post-mortem tissue. Specifically, they identified mutations that occur spontaneously in early developmental cell divisions. These mutations, also called genomic scars, act like unique genetic fingerprints that can be used to trace the embryonic development process.
The study, which looked at 334 single-cell colonies and 379 tissue samples from seven recently deceased human body donors, is the largest single-cell, whole-genome analysis carried out to date. The researchers examined the genomic scars of each individual in order to reconstruct their early embryonic cellular dynamics.
The result revealed several key characteristics of the human embryonic development process. Firstly, mutation rates are higher in the first cell division, but then decrease to approximately one mutation per cell during later cell division. Secondly, early cells contributed unequally to the development of the embryo in all informative donors, for example, at the two-cell stage, one of the cells always left more progeny cells than the other. The ratio of this was different from person to person, implying that the process varies between individuals and is not fully deterministic.
The researchers were also able to deduce the timing of when cells begin to differentiate into individual organ-specific cells. They found that within three days of fertilization, embryonic cells began to be distributed asymmetrically into tissues for the left and right sides of the body, followed by differentiation into three germ layers, and then differentiation into specific tissues and organs.
“It is an impressive scientific achievement that, within 20 years of the completion of human genome project, genomic technology has advanced to the extent that we are now able to accurately identify mutations in a single-cell genome,” said Professor Young Seok Ju from the Graduate School of Medical Science and Engineering at KAIST. “This technology will enable us to track human embryogenesis at even higher resolutions in the future.”
The techniques used in this study could be used to improve our understanding of rare diseases caused by abnormalities in embryonic development, and to design new precision diagnostics and treatments for patients.
The research was completed in collaboration with Kyungpook National University Hospital, the Korea Institute of Science and Technology Information, Catholic University of Korea School of Medicine, Genome Insights Inc, and Immune Square Inc. This work was supported by the Suh Kyungbae Foundation, the Ministry of Health and Welfare of Korea, the National Research Foundastion of Korea.
-PublicationSeongyeol Park, Nanda Mali, Ryul Kim et al. ‘Clonal dynamics in early human embryogenesis inferred from somatic mutation’ Nature Online ahead of print, Aug. 25, 2021 (https://doi.org/10.1038/s41586-021-03786-8)
-ProfileProfessor Young Seok JuLab of Cancer Genomics (https://www.julab.kaist.ac.kr/)Graduate School of Medical Science and EngineeringKAIST
2021.08.31 View 10003 -
KAIST KPC4IR Presents the AI Global Guide for Healthcare
The benchmark for the responsible usage of AI technology in the healthcare sector will promote clarity and high standards for technological applications
The KAIST Korea Policy Center for the Fourth Industrial Revolution (KPC4IR) published 'Using AI to Support Healthcare Decisions: A Guide for Society.' This global guide is designed to serve as a benchmark for the responsible usage of AI technologies, and will promote clarity and high standards for technological applications in the healthcare sector. The guide details what should be considered when making clinical decisions to help reduce the chances of the AI giving false or misleading results.
The KPC4IR presented the guide in collaboration with the Lloyd’s Register Foundation Institute for the Public Understanding of Risk at the National University of Singapore (NUS IPUR) and Sense about Science, a non-profit organization in the UK specialized in science communication, during the 2021 SIG-KDD (Special Interest Group on Knowledge Discovery and Data Mining) Conference on August 15.
AI technology is being widely used in the healthcare sector and has already proved its accuracy and efficiency in diagnosing and predicting diseases. Despite its huge impact on our daily lives in every sector of society, AI technology has some drawbacks and comes with risks, especially due to biased algorithms.
“We focused on the ‘reliability’ of AI applications in the healthcare sector to make all data well represented, in good quality. The technology will eventually innovate to better serve the people’s new demand, especially critical demands for safety and precision in healthcare services. This global guide will help both developers and people’s understanding of the appropriate technology applications,” says Director So Young Kim at the KPC4IR.
The guide, for instance, says that to scrutinize quality and reliability, the source of the data must be clearly known; the data must have been collected or selected for the purpose it’s being used for; the limitations and assumptions for that purpose have been clearly stated; the biases have been addressed; and it has been properly tested in the real world. It also reflects the importance of the representativeness of data that will affect the accuracy of the AI applications.
“By being transparent and demonstrating the steps taken to check that the AI is reliable, researchers and developers can help give people confidence about providing their data,” the guide states.
For this guide, the KPC4IR and its collaborators collected data after working with numerous experts from the Graduate School of AI at KAIST, the Science and Technology Policy Institute in Korea, Asan Medical Center in Seoul, Seoul National University Bundang Hospital, and AI solution companies.
2021.08.17 View 9217