BIO
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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 View 7962 -
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
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2020.08.13 View 14000 -
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
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2020.07.21 View 10841 -
Every Moment of Ultrafast Chemical Bonding Now Captured on Film
- The emerging moment of bond formation, two separate bonding steps, and subsequent vibrational motions were visualized. -
< Emergence of molecular vibrations and the evolution to covalent bonds observed in the research. Video Credit: KEK IMSS >
A team of South Korean researchers led by Professor Hyotcherl Ihee from the Department of Chemistry at KAIST reported the direct observation of the birthing moment of chemical bonds by tracking real-time atomic positions in the molecule. Professor Ihee, who also serves as Associate Director of the Center for Nanomaterials and Chemical Reactions at the Institute for Basic Science (IBS), conducted this study in collaboration with scientists at the Institute of Materials Structure Science of High Energy Accelerator Research Organization (KEK IMSS, Japan), RIKEN (Japan), and Pohang Accelerator Laboratory (PAL, South Korea). This work was published in Nature on June 24.
Targeted cancer drugs work by striking a tight bond between cancer cell and specific molecular targets that are involved in the growth and spread of cancer. Detailed images of such chemical bonding sites or pathways can provide key information necessary for maximizing the efficacy of oncogene treatments. However, atomic movements in a molecule have never been captured in the middle of the action, not even for an extremely simple molecule such as a triatomic molecule, made of only three atoms.
Professor Ihee's group and their international collaborators finally succeeded in capturing the ongoing reaction process of the chemical bond formation in the gold trimer. "The femtosecond-resolution images revealed that such molecular events took place in two separate stages, not simultaneously as previously assumed," says Professor Ihee, the corresponding author of the study. "The atoms in the gold trimer complex atoms remain in motion even after the chemical bonding is complete. The distance between the atoms increased and decreased periodically, exhibiting the molecular vibration. These visualized molecular vibrations allowed us to name the characteristic motion of each observed vibrational mode." adds Professor Ihee.
Atoms move extremely fast at a scale of femtosecond (fs) ― quadrillionths (or millionths of a billionth) of a second. Its movement is minute in the level of angstrom equal to one ten-billionth of a meter. They are especially elusive during the transition state where reaction intermediates are transitioning from reactants to products in a flash. The KAIST-IBS research team made this experimentally challenging task possible by using femtosecond x-ray liquidography (solution scattering). This experimental technique combines laser photolysis and x-ray scattering techniques. When a laser pulse strikes the sample, X-rays scatter and initiate the chemical bond formation reaction in the gold trimer complex. Femtosecond x-ray pulses obtained from a special light source called an x-ray free-electron laser (XFEL) were used to interrogate the bond-forming process. The experiments were performed at two XFEL facilities (4th generation linear accelerator) that are PAL-XFEL in South Korea and SACLA in Japan, and this study was conducted in collaboration with researchers from KEK IMSS, PAL, RIKEN, and the Japan Synchrotron Radiation Research Institute (JASRI).
Scattered waves from each atom interfere with each other and thus their x-ray scattering images are characterized by specific travel directions. The KAIST-IBS research team traced real-time positions of the three gold atoms over time by analyzing x-ray scattering images, which are determined by a three-dimensional structure of a molecule. Structural changes in the molecule complex resulted in multiple characteristic scattering images over time. When a molecule is excited by a laser pulse, multiple vibrational quantum states are simultaneously excited. The superposition of several excited vibrational quantum states is called a wave packet. The researchers tracked the wave packet in three-dimensional nuclear coordinates and found that the first half round of chemical bonding was formed within 35 fs after photoexcitation. The second half of the reaction followed within 360 fs to complete the entire reaction dynamics.
They also accurately illustrated molecular vibration motions in both temporal- and spatial-wise. This is quite a remarkable feat considering that such an ultrafast speed and a minute length of motion are quite challenging conditions for acquiring precise experimental data.
In this study, the KAIST-IBS research team improved upon their 2015 study published by Nature. In the previous study in 2015, the speed of the x-ray camera (time resolution) was limited to 500 fs, and the molecular structure had already changed to be linear with two chemical bonds within 500 fs. In this study, the progress of the bond formation and bent-to-linear structural transformation could be observed in real time, thanks to the improvement time resolution down to 100 fs. Thereby, the asynchronous bond formation mechanism in which two chemical bonds are formed in 35 fs and 360 fs, respectively, and the bent-to-linear transformation completed in 335 fs were visualized. In short, in addition to observing the beginning and end of chemical reactions, they reported every moment of the intermediate, ongoing rearrangement of nuclear configurations with dramatically improved experimental and analytical methods.
They will push this method of 'real-time tracking of atomic positions in a molecule and molecular vibration using femtosecond x-ray scattering' to reveal the mechanisms of organic and inorganic catalytic reactions and reactions involving proteins in the human body. "By directly tracking the molecular vibrations and real-time positions of all atoms in a molecule in the middle of reaction, we will be able to uncover mechanisms of various unknown organic and inorganic catalytic reactions and biochemical reactions," notes Dr. Jong Goo Kim, the lead author of the study.
Publications:
Kim, J. G., et al. (2020) ‘Mapping the emergence of molecular vibrations mediating bond formation’. Nature. Volume 582. Page 520-524. Available online at https://doi.org/10.1038/s41586-020-2417-3
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
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2020.06.24 View 15136 -
A Deep-Learned E-Skin Decodes Complex Human Motion
A deep-learning powered single-strained electronic skin sensor can capture human motion from a distance. The single strain sensor placed on the wrist decodes complex five-finger motions in real time with a virtual 3D hand that mirrors the original motions. The deep neural network boosted by rapid situation learning (RSL) ensures stable operation regardless of its position on the surface of the skin.
Conventional approaches require many sensor networks that cover the entire curvilinear surfaces of the target area. Unlike conventional wafer-based fabrication, this laser fabrication provides a new sensing paradigm for motion tracking.
The research team, led by Professor Sungho Jo from the School of Computing, collaborated with Professor Seunghwan Ko from Seoul National University to design this new measuring system that extracts signals corresponding to multiple finger motions by generating cracks in metal nanoparticle films using laser technology. The sensor patch was then attached to a user’s wrist to detect the movement of the fingers.
The concept of this research started from the idea that pinpointing a single area would be more efficient for identifying movements than affixing sensors to every joint and muscle. To make this targeting strategy work, it needs to accurately capture the signals from different areas at the point where they all converge, and then decoupling the information entangled in the converged signals. To maximize users’ usability and mobility, the research team used a single-channeled sensor to generate the signals corresponding to complex hand motions.
The rapid situation learning (RSL) system collects data from arbitrary parts on the wrist and automatically trains the model in a real-time demonstration with a virtual 3D hand that mirrors the original motions. To enhance the sensitivity of the sensor, researchers used laser-induced nanoscale cracking.
This sensory system can track the motion of the entire body with a small sensory network and facilitate the indirect remote measurement of human motions, which is applicable for wearable VR/AR systems.
The research team said they focused on two tasks while developing the sensor. First, they analyzed the sensor signal patterns into a latent space encapsulating temporal sensor behavior and then they mapped the latent vectors to finger motion metric spaces.
Professor Jo said, “Our system is expandable to other body parts. We already confirmed that the sensor is also capable of extracting gait motions from a pelvis. This technology is expected to provide a turning point in health-monitoring, motion tracking, and soft robotics.”
This study was featured in Nature Communications.
Publication:
Kim, K. K., et al. (2020) A deep-learned skin sensor decoding the epicentral human motions. Nature Communications. 11. 2149. https://doi.org/10.1038/s41467-020-16040-y29
Link to download the full-text paper:
https://www.nature.com/articles/s41467-020-16040-y.pdf
Profile: Professor Sungho Jo
shjo@kaist.ac.kr
http://nmail.kaist.ac.kr
Neuro-Machine Augmented Intelligence Lab
School of Computing
College of Engineering
KAIST
2020.06.10 View 11021 -
‘Mole-bot’ Optimized for Underground and Space Exploration
Biomimetic drilling robot provides new insights into the development of efficient drilling technologies
Mole-bot, a drilling biomimetic robot designed by KAIST, boasts a stout scapula, a waist inclinable on all sides, and powerful forelimbs. Most of all, the powerful torque from the expandable drilling bit mimicking the chiseling ability of a mole’s front teeth highlights the best feature of the drilling robot.
The Mole-bot is expected to be used for space exploration and mining for underground resources such as coalbed methane and Rare Earth Elements (REE), which require highly advanced drilling technologies in complex environments.
The research team, led by Professor Hyun Myung from the School of Electrical Engineering, found inspiration for their drilling bot from two striking features of the African mole-rat and European mole.
“The crushing power of the African mole-rat’s teeth is so powerful that they can dig a hole with 48 times more power than their body weight. We used this characteristic for building the main excavation tool. And its expandable drill is designed not to collide with its forelimbs,” said Professor Myung.
The 25-cm wide and 84-cm long Mole-bot can excavate three times faster with six times higher directional accuracy than conventional models. The Mole-bot weighs 26 kg.
After digging, the robot removes the excavated soil and debris using its forelimbs. This embedded muscle feature, inspired by the European mole’s scapula, converts linear motion into a powerful rotational force. For directional drilling, the robot’s elongated waist changes its direction 360° like living mammals.
For exploring underground environments, the research team developed and applied new sensor systems and algorithms to identify the robot’s position and orientation using graph-based 3D Simultaneous Localization and Mapping (SLAM) technology that matches the Earth’s magnetic field sequence, which enables 3D autonomous navigation underground.
According to Market & Market’s survey, the directional drilling market in 2016 is estimated to be 83.3 billion USD and is expected to grow to 103 billion USD in 2021. The growth of the drilling market, starting with the Shale Revolution, is likely to expand into the future development of space and polar resources. As initiated by Space X recently, more attention for planetary exploration will be on the rise and its related technology and equipment market will also increase.
The Mole-bot is a huge step forward for efficient underground drilling and exploration technologies. Unlike conventional drilling processes that use environmentally unfriendly mud compounds for cleaning debris, Mole-bot can mitigate environmental destruction. The researchers said their system saves on cost and labor and does not require additional pipelines or other ancillary equipment.
“We look forward to a more efficient resource exploration with this type of drilling robot. We also hope Mole-bot will have a very positive impact on the robotics market in terms of its extensive application spectra and economic feasibility,” said Professor Myung.
This research, made in collaboration with Professor Jung-Wuk Hong and Professor Tae-Hyuk Kwon’s team in the Department of Civil and Environmental Engineering for robot structure analysis and geotechnical experiments, was supported by the Ministry of Trade, Industry and Energy’s Industrial Technology Innovation Project.
Profile
Professor Hyun Myung
Urban Robotics Lab
http://urobot.kaist.ac.kr/
School of Electrical Engineering
KAIST
2020.06.05 View 9356 -
Universal Virus Detection Platform to Expedite Viral Diagnosis
Reactive polymer-based tester pre-screens dsRNAs of a wide range of viruses without their genome sequences
The prompt, precise, and massive detection of a virus is the key to combat infectious diseases such as Covid-19. A new viral diagnostic strategy using reactive polymer-grafted, double-stranded RNAs will serve as a pre-screening tester for a wide range of viruses with enhanced sensitivity.
Currently, the most widely using viral detection methodology is polymerase chain reaction (PCR) diagnosis, which amplifies and detects a piece of the viral genome. Prior knowledge of the relevant primer nucleic acids of the virus is quintessential for this test.
The detection platform developed by KAIST researchers identifies viral activities without amplifying specific nucleic acid targets. The research team, co-led by Professor Sheng Li and Professor Yoosik Kim from the Department of Chemical and Biomolecular Engineering, constructed a universal virus detection platform by utilizing the distinct features of the PPFPA-grafted surface and double-stranded RNAs.
The key principle of this platform is utilizing the distinct feature of reactive polymer-grafted surfaces, which serve as a versatile platform for the immobilization of functional molecules. These activated surfaces can be used in a wide range of applications including separation, delivery, and detection. As long double-stranded RNAs are common byproducts of viral transcription and replication, these PPFPA-grafted surfaces can detect the presence of different kinds of viruses without prior knowledge of their genomic sequences.
“We employed the PPFPA-grafted silicon surface to develop a universal virus detection platform by immobilizing antibodies that recognize double-stranded RNAs,” said Professor Kim.
To increase detection sensitivity, the research team devised two-step detection process analogues to sandwich enzyme-linked immunosorbent assay where the bound double-stranded RNAs are then visualized using fluorophore-tagged antibodies that also recognize the RNAs’ double-stranded secondary structure.
By utilizing the developed platform, long double-stranded RNAs can be detected and visualized from an RNA mixture as well as from total cell lysates, which contain a mixture of various abundant contaminants such as DNAs and proteins.
The research team successfully detected elevated levels of hepatitis C and A viruses with this tool.
“This new technology allows us to take on virus detection from a new perspective. By targeting a common biomarker, viral double-stranded RNAs, we can develop a pre-screening platform that can quickly differentiate infected populations from non-infected ones,” said Professor Li.
“This detection platform provides new perspectives for diagnosing infectious diseases. This will provide fast and accurate diagnoses for an infected population and prevent the influx of massive outbreaks,” said Professor Kim.
This work is featured in Biomacromolecules. This work was supported by the Agency for Defense Development (Grant UD170039ID), the Ministry of Science and ICT (NRF-2017R1D1A1B03034660, NRF-2019R1C1C1006672), and the KAIST Future Systems Healthcare Project from the Ministry of Science and ICT (KAISTHEALTHCARE42).
Profile:-Professor Yoosik KimDepartment of Chemical and Biomolecular Engineeringhttps://qcbio.kaist.ac.kr
KAIST-Professor Sheng LiDepartment of Chemical and Biomolecular Engineeringhttps://bcpolymer.kaist.ac.kr
KAIST
Publication:Ku et al., 2020. Reactive Polymer Targeting dsRNA as Universal Virus Detection Platform with Enhanced Sensitivity. Biomacromolecules (https://doi.org/10.1021/acs.biomac.0c00379).
2020.06.01 View 17320 -
Researchers Present a Microbial Strain Capable of Massive Succinic Acid Production
A research team led by Distinguished Professor Sang Yup Lee reported the production of a microbial strain capable of the massive production of succinic acid with the highest production efficiency to date. This strategy of integrating systems metabolic engineering with enzyme engineering will be useful for the production of industrially competitive bio-based chemicals. Their strategy was described in Nature Communications on April 23.
The bio-based production of industrial chemicals from renewable non-food biomass has become increasingly important as a sustainable substitute for conventional petroleum-based production processes relying on fossil resources. Here, systems metabolic engineering, which is the key component for biorefinery technology, is utilized to effectively engineer the complex metabolic pathways of microorganisms to enable the efficient production of industrial chemicals.
Succinic acid, a four-carbon dicarboxylic acid, is one of the most promising platform chemicals serving as a precursor for industrially important chemicals. Among microorganisms producing succinic acid, Mannheimia succiniciproducens has been proven to be one of the best strains for succinic acid production.
The research team has developed a bio-based succinic acid production technology using the M. succiniciproducens strain isolated from the rumen of Korean cow for over 20 years and succeeded in developing a strain capable of producing succinic acid with the highest production efficiency.
They carried out systems metabolic engineering to optimize the succinic acid production pathway of the M. succiniciproducens strain by determining the crystal structure of key enzymes important for succinic acid production and performing protein engineering to develop enzymes with better catalytic performance.
As a result, 134 g per liter of succinic acid was produced from the fermentation of an engineered strain using glucose, glycerol, and carbon dioxide. They were able to achieve 21 g per liter per hour of succinic acid production, which is one of the key factors determining the economic feasibility of the overall production process. This is the world’s best succinic acid production efficiency reported to date. Previous production methods averaged 1~3 g per liter per hour.
Distinguished professor Sang Yup Lee explained that his team’s work will significantly contribute to transforming the current petrochemical-based industry into an eco-friendly bio-based one.
“Our research on the highly efficient bio-based production of succinic acid from renewable non-food resources and carbon dioxide has provided a basis for reducing our strong dependence on fossil resources, which is the main cause of the environmental crisis,” Professor Lee said.
This work was supported by the Technology Development Program to Solve Climate Changes via Systems Metabolic Engineering for Biorefineries and the C1 Gas Refinery Program from the Ministry of Science and ICT through the National Research Foundation of Korea.
2020.05.06 View 8263 -
A Single Biological Factor Predicts Distinct Cortical Organizations across Mammalian Species
-A KAIST team’s mathematical sampling model shows that retino-cortical mapping is a prime determinant in the topography of cortical organization.-
Researchers have explained how visual cortexes develop uniquely across the brains of different mammalian species. A KAIST research team led by Professor Se-Bum Paik from the Department of Bio and Brain Engineering has identified a single biological factor, the retino-cortical mapping ratio, that predicts distinct cortical organizations across mammalian species.
This new finding has resolved a long-standing puzzle in understanding visual neuroscience regarding the origin of functional architectures in the visual cortex. The study published in Cell Reports on March 10 demonstrates that the evolutionary variation of biological parameters may induce the development of distinct functional circuits in the visual cortex, even without species-specific developmental mechanisms.
In the primary visual cortex (V1) of mammals, neural tuning to visual stimulus orientation is organized into one of two distinct topographic patterns across species. While primates have columnar orientation maps, a salt-and-pepper type organization is observed in rodents.
For decades, this sharp contrast between cortical organizations has spawned fundamental questions about the origin of functional architectures in the V1. However, it remained unknown whether these patterns reflect disparate developmental mechanisms across mammalian taxa, or simply originate from variations in biological parameters under a universal development process.
To identify a determinant predicting distinct cortical organizations, Professor Paik and his researchers Jaeson Jang and Min Song examined the exact condition that generates columnar and salt-and-pepper organizations, respectively. Next, they applied a mathematical model to investigate how the topographic information of the underlying retinal mosaics pattern could be differently mapped onto a cortical space, depending on the mapping condition.
The research team proved that the retino-cortical feedforwarding mapping ratio appeared to be correlated to the cortical organization of each species. In the model simulations, the team found that distinct cortical circuitries can arise from different V1 areas and retinal ganglion cell (RGC) mosaic sizes. The team’s mathematical sampling model shows that retino-cortical mapping is a prime determinant in the topography of cortical organization, and this prediction was confirmed by neural parameter analysis of the data from eight phylogenetically distinct mammalian species.
Furthermore, the researchers proved that the Nyquist sampling theorem explains this parametric division of cortical organization with high accuracy. They showed that a mathematical model predicts that the organization of cortical orientation tuning makes a sharp transition around the Nyquist sampling frequency, explaining why cortical organizations can be observed in either columnar or salt-and-pepper organizations, but not in intermediates between these two stages.
Professor Paik said, “Our findings make a significant impact for understanding the origin of functional architectures in the visual cortex of the brain, and will provide a broad conceptual advancement as well as advanced insights into the mechanism underlying neural development in evolutionarily divergent species.”
He continued, “We believe that our findings will be of great interest to scientists working in a wide range of fields such as neuroscience, vision science, and developmental biology.”
This work was supported by the National Research Foundation of Korea (NRF).
Image credit: Professor Se-Bum Paik, 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:
Jaeson Jang, Min Song, and Se-Bum Paik. (2020). Retino-cortical mapping ratio predicts columnar and salt-and-pepper organization in mammalian visual cortex. Cell Reports. Volume 30. Issue 10. pp. 3270-3279. Available online at https://doi.org/10.1016/j.celrep.2020.02.038
Profile:
Se-Bum Paik
Assistant Professor
sbpaik@kaist.ac.kr
http://vs.kaist.ac.kr/
VSNN Laboratory
Department of Bio and Brain Engineering
Program of Brain and Cognitive Engineering
http://kaist.ac.kr
Korea Advanced Institute of Science and Technology (KAIST)
Daejeon, Republic of Korea
Profile:
Jaeson Jang
Ph.D. Candidate
jaesonjang@kaist.ac.kr
Department of Bio and Brain Engineering, KAIST
Profile:
Min Song
Ph.D. Candidate
night@kaist.ac.kr
Program of Brain and Cognitive Engineering, KAIST
(END)
2020.03.11 View 11931 -
Professor Hojong Chang’s Research Team Wins ISIITA 2020 Best Paper Award
The paper written by Professor Hojong Chang’s research team from KAIST Institute for IT Convergence won the best paper award from the International Symposium on Innovation in Information Technology Application (ISIITA) 2020, held this month at Ton Duc Thang University in Vietnam.
ISIITA is a networking symposium where leading researchers from various fields including information and communications, biotechnology, and computer systems come together and share on the convergence of technology.
Professor Chang’s team won the best paper award at this year’s symposium with its paper, “A Study of Single Photon Counting System for Quantitative Analysis of Luminescence”. The awarded paper discusses the realization of a signal processing system for silicon photomultipliers.
The silicon photomultiplier is the core of a urinalysis technique that tests for sodium and potassium in the body using simple chemical reactions. If our bodily sodium and potassium levels exceed a certain amount, it can lead to high blood pressure, cardiovascular problems, and kidney damage.
Through this research, the team has developed a core technique that quantifies the sodium and potassium discharged in the urine. When the reagent is injected into the urine, a very small amount of light is emitted as a result of the chemical reaction. However, if there is a large amount of sodium and potassium, they interrupt the reaction and reduce the emission. The key to this measurement technique is digitizing the strength of this very fine emission of light. Professor Chang’s team developed a system that uses a photomultiplier to measure the chemiluminescence.
Professor Chang said, “I look forward for this signal processing system greatly helping to prevent diseases caused by the excessive consumption of sodium and potassium through quick and easy detection.”
Researcher Byunghun Han who carried out the central research for the system design added, “We are planning to focus on miniaturizing the developed technique, so that anyone can carry our device around like a cellphone.”
The research was supported by the Ministry of Science and ICT.
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2020.02.27 View 8650 -
Professor Jong Chul Ye Appointed as Distinguished Lecturer of IEEE EMBS
Professor Jong Chul Ye from the Department of Bio and Brain Engineering was appointed as a distinguished lecturer by the International Association of Electrical and Electronic Engineers (IEEE) Engineering in Medicine and Biology Society (EMBS). Professor Ye was invited to deliver a lecture on his leading research on artificial intelligence (AI) technology in medical video restoration. He will serve a term of two years beginning in 2020.
IEEE EMBS's distinguished lecturer program is designed to educate researchers around the world on the latest trends and technology in biomedical engineering. Sponsored by IEEE, its members can attend lectures on the distinguished professor's research subject.
Professor Ye said, "We are at a time where the importance of AI in medical imaging is increasing.” He added, “I am proud to be appointed as a distinguished lecturer of the IEEE EMBS in recognition of my contributions to this field.”
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2020.02.27 View 8480 -
New Catalyst Recycles Greenhouse Gases into Fuel and Hydrogen Gas
< Professor Cafer T. Yavuz (left), PhD Candidate Youngdong Song (center), and Researcher Sreerangappa Ramesh (right) >
Scientists have taken a major step toward a circular carbon economy by developing a long-lasting, economical catalyst that recycles greenhouse gases into ingredients that can be used in fuel, hydrogen gas, and other chemicals. The results could be revolutionary in the effort to reverse global warming, according to the researchers. The study was published on February 14 in Science.
“We set out to develop an effective catalyst that can convert large amounts of the greenhouse gases carbon dioxide and methane without failure,” said Cafer T. Yavuz, paper author and associate professor of chemical and biomolecular engineering and of chemistry at KAIST.
The catalyst, made from inexpensive and abundant nickel, magnesium, and molybdenum, initiates and speeds up the rate of reaction that converts carbon dioxide and methane into hydrogen gas. It can work efficiently for more than a month.
This conversion is called ‘dry reforming’, where harmful gases, such as carbon dioxide, are processed to produce more useful chemicals that could be refined for use in fuel, plastics, or even pharmaceuticals. It is an effective process, but it previously required rare and expensive metals such as platinum and rhodium to induce a brief and inefficient chemical reaction.
Other researchers had previously proposed nickel as a more economical solution, but carbon byproducts would build up and the surface nanoparticles would bind together on the cheaper metal, fundamentally changing the composition and geometry of the catalyst and rendering it useless.
“The difficulty arises from the lack of control on scores of active sites over the bulky catalysts surfaces because any refinement procedures attempted also change the nature of the catalyst itself,” Yavuz said.
The researchers produced nickel-molybdenum nanoparticles under a reductive environment in the presence of a single crystalline magnesium oxide. As the ingredients were heated under reactive gas, the nanoparticles moved on the pristine crystal surface seeking anchoring points. The resulting activated catalyst sealed its own high-energy active sites and permanently fixed the location of the nanoparticles — meaning that the nickel-based catalyst will not have a carbon build up, nor will the surface particles bind to one another.
“It took us almost a year to understand the underlying mechanism,” said first author Youngdong Song, a graduate student in the Department of Chemical and Biomolecular Engineering at KAIST. “Once we studied all the chemical events in detail, we were shocked.”
The researchers dubbed the catalyst Nanocatalysts on Single Crystal Edges (NOSCE). The magnesium-oxide nanopowder comes from a finely structured form of magnesium oxide, where the molecules bind continuously to the edge. There are no breaks or defects in the surface, allowing for uniform and predictable reactions.
“Our study solves a number of challenges the catalyst community faces,” Yavuz said. “We believe the NOSCE mechanism will improve other inefficient catalytic reactions and provide even further savings of greenhouse gas emissions.”
This work was supported, in part, by the Saudi-Aramco-KAIST CO2 Management Center and the National Research Foundation of Korea.
Other contributors include Ercan Ozdemir, Sreerangappa Ramesh, Aldiar Adishev, and Saravanan Subramanian, all of whom are affiliated with the Graduate School of Energy, Environment, Water and Sustainability at KAIST; Aadesh Harale, Mohammed Albuali, Bandar Abdullah Fadhel, and Aqil Jamal, all of whom are with the Research and Development Center in Saudi Arabia; and Dohyun Moon and Sun Hee Choi, both of whom are with the Pohang Accelerator Laboratory in Korea. Ozdemir is also affiliated with the Institute of Nanotechnology at the Gebze Technical University in Turkey; Fadhel and Jamal are also affiliated with the Saudi-Armco-KAIST CO2 Management Center in Korea.
<Newly developed catalyst that recycles greenhouse gases into ingredients that can be used in fuel, hydrogen gas and other chemicals.>
Publication:
Song et al. (2020) Dry reforming of methane by stable Ni–Mo nanocatalysts on single-crystalline MgO. Science, Vol. 367, Issue 6479, pp. 777-781. Available online at http://dx.doi.org/10.1126/science.aav2412
Profile: Prof. Cafer T. Yavuz, MA, PhD
yavuz@kaist.ac.kr
http://yavuz.kaist.ac.kr/
Associate Professor
Oxide and Organic Nanomaterials for the Environment (ONE) Laboratory
Graduate School of Energy, Environment, Water and Sustainability (EEWS)
Korea Advanced Institute of Science and Technology (KAIST)
http://kaist.ac.kr
Daejeon, Republic of Korea
Profile: Youngdong Song ydsong88@kaist.ac.kr
Ph.D. Candidate
Department of Chemical and Biomolecular Engineering
Korea Advanced Institute of Science and Technology (KAIST)
http://kaist.ac.kr
Daejeon, Republic of Korea
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2020.02.17 View 15255