BIO
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Deep-Learning and 3D Holographic Microscopy Beats Scientists at Analyzing Cancer Immunotherapy
Live tracking and analyzing of the dynamics of chimeric antigen receptor (CAR) T-cells targeting cancer cells can open new avenues for the development of cancer immunotherapy. However, imaging via conventional microscopy approaches can result in cellular damage, and assessments of cell-to-cell interactions are extremely difficult and labor-intensive. When researchers applied deep learning and 3D holographic microscopy to the task, however, they not only avoided these difficultues but found that AI was better at it than humans were.
Artificial intelligence (AI) is helping researchers decipher images from a new holographic microscopy technique needed to investigate a key process in cancer immunotherapy “live” as it takes place. The AI transformed work that, if performed manually by scientists, would otherwise be incredibly labor-intensive and time-consuming into one that is not only effortless but done better than they could have done it themselves. The research, conducted by the team of Professor YongKeun Park from the Department of Physics, appeared in the journal eLife last December.
A critical stage in the development of the human immune system’s ability to respond not just generally to any invader (such as pathogens or cancer cells) but specifically to that particular type of invader and remember it should it attempt to invade again is the formation of a junction between an immune cell called a T-cell and a cell that presents the antigen, or part of the invader that is causing the problem, to it. This process is like when a picture of a suspect is sent to a police car so that the officers can recognize the criminal they are trying to track down. The junction between the two cells, called the immunological synapse, or IS, is the key process in teaching the immune system how to recognize a specific type of invader.
Since the formation of the IS junction is such a critical step for the initiation of an antigen-specific immune response, various techniques allowing researchers to observe the process as it happens have been used to study its dynamics. Most of these live imaging techniques rely on fluorescence microscopy, where genetic tweaking causes part of a protein from a cell to fluoresce, in turn allowing the subject to be tracked via fluorescence rather than via the reflected light used in many conventional microscopy techniques.
However, fluorescence-based imaging can suffer from effects such as photo-bleaching and photo-toxicity, preventing the assessment of dynamic changes in the IS junction process over the long term. Fluorescence-based imaging still involves illumination, whereupon the fluorophores (chemical compounds that cause the fluorescence) emit light of a different color. Photo-bleaching or photo-toxicity occur when the subject is exposed to too much illumination, resulting in chemical alteration or cellular damage.
One recent option that does away with fluorescent labelling and thereby avoids such problems is 3D holographic microscopy or holotomography (HT). In this technique, the refractive index (the way that light changes direction when encountering a substance with a different density—why a straw looks like it bends in a glass of water) is recorded in 3D as a hologram.
Until now, HT has been used to study single cells, but never cell-cell interactions involved in immune responses. One of the main reasons is the difficulty of “segmentation,” or distinguishing the different parts of a cell and thus distinguishing between the interacting cells; in other words, deciphering which part belongs to which cell.
Manual segmentation, or marking out the different parts manually, is one option, but it is difficult and time-consuming, especially in three dimensions. To overcome this problem, automatic segmentation has been developed in which simple computer algorithms perform the identification.
“But these basic algorithms often make mistakes,” explained Professor YongKeun Park, “particularly with respect to adjoining segmentation, which of course is exactly what is occurring here in the immune response we’re most interested in.”
So, the researchers applied a deep learning framework to the HT segmentation problem. Deep learning is a type of machine learning in which artificial neural networks based on the human brain recognize patterns in a way that is similar to how humans do this. Regular machine learning requires data as an input that has already been labelled. The AI “learns” by understanding the labeled data and then recognizes the concept that has been labelled when it is fed novel data. For example, AI trained on a thousand images of cats labelled “cat” should be able to recognize a cat the next time it encounters an image with a cat in it. Deep learning involves multiple layers of artificial neural networks attacking much larger, but unlabeled datasets, in which the AI develops its own ‘labels’ for concepts it encounters.
In essence, the deep learning framework that KAIST researchers developed, called DeepIS, came up with its own concepts by which it distinguishes the different parts of the IS junction process. To validate this method, the research team applied it to the dynamics of a particular IS junction formed between chimeric antigen receptor (CAR) T-cells and target cancer cells. They then compared the results to what they would normally have done: the laborious process of performing the segmentation manually. They found not only that DeepIS was able to define areas within the IS with high accuracy, but that the technique was even able to capture information about the total distribution of proteins within the IS that may not have been easily measured using conventional techniques.
“In addition to allowing us to avoid the drudgery of manual segmentation and the problems of photo-bleaching and photo-toxicity, we found that the AI actually did a better job,” Professor Park added.
The next step will be to combine the technique with methods of measuring how much physical force is applied by different parts of the IS junction, such as holographic optical tweezers or traction force microscopy.
-Profile
Professor YongKeun Park
Department of Physics
Biomedical Optics Laboratory
http://bmol.kaist.ac.kr
KAIST
2021.02.24 View 5181 -
Attachable Skin Monitors that Wick the Sweat Away
- A silicone membrane for wearable devices is more comfortable and breathable thanks to better-sized pores made with the help of citric acid crystals. -
A new preparation technique fabricates thin, silicone-based patches that rapidly wick water away from the skin. The technique could reduce the redness and itching caused by wearable biosensors that trap sweat beneath them. The technique was developed by bioengineer and professor Young-Ho Cho and his colleagues at KAIST and reported in the journal Scientific Reports last month.
“Wearable bioelectronics are becoming more attractive for the day-to-day monitoring of biological compounds found in sweat, like hormones or glucose, as well as body temperature, heart rate, and energy expenditure,” Professor Cho explained. “But currently available materials can cause skin irritation, so scientists are looking for ways to improve them,” he added.
Attachable biosensors often use a silicone-based compound called polydimethylsiloxane (PDMS), as it has a relatively high water vapour transmission rate compared to other materials. Still, this rate is only two-thirds that of skin’s water evaporation rate, meaning sweat still gets trapped underneath it.
Current fabrication approaches mix PDMS with beads or solutes, such as sugars or salts, and then remove them to leave pores in their place. Another technique uses gas to form pores in the material. Each technique has its disadvantages, from being expensive and complex to leaving pores of different sizes.
A team of researchers led by Professor Cho from the KAIST Department of Bio and Brain Engineering was able to form small, uniform pores by crystallizing citric acid in PDMS and then removing the crystals using ethanol. The approach is significantly cheaper than using beads, and leads to 93.2% smaller and 425% more uniformly-sized pores compared to using sugar. Importantly, the membrane transmits water vapour 2.2 times faster than human skin.
The team tested their membrane on human skin for seven days and found that it caused only minor redness and no itching, whereas a non-porous PDMS membrane did.
Professor Cho said, “Our method could be used to fabricate porous PDMS membranes for skin-attachable devices used for daily monitoring of physiological signals.”
“We next plan to modify our membrane so it can be more readily attached to and removed from skin,” he added.
This work was supported by the Ministry of Trade, Industry and Energy (MOTIE) of Korea under the Alchemist Project.
Image description:
Smaller, more uniformly-sized pores are made in the PDMS membrane by mixing PDMS, toluene, citric acid, and ethanol. Toluene dilutes PDMS so it can easily mix with the other two constituents. Toluene and ethanol are then evaporated, which causes the citric acid to crystallize within the PDMS material. The mixture is placed in a mould where it solidifies into a thin film. The crystals are then removed using ethanol, leaving pores in their place.
Image credit:
Professor Young-Ho Cho, 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:
Yoon, S, et al. (2021) Wearable porous PDMS layer of high moisture permeability for skin trouble reduction. Scientific Reports 11, Article No. 938. Available online at https://doi.org/10.1038/s41598-020-78580-z
Profile:
Young-Ho Cho, Ph.D
Professor
mems@kaist.ac.kr
https://mems.kaist.ac.kr
NanoSentuating Systems Laboratory
Department of Bio and Brain Engineering
https://kaist.ac.kr
Korea Advanced Institute of Science and Technology (KAIST)
Daejeon, Republic of Korea
(END)
2021.02.22 View 5295 -
Wirelessly Rechargeable Soft Brain Implant Controls Brain Cells
Researchers have invented a smartphone-controlled soft brain implant that can be recharged wirelessly from outside the body. It enables long-term neural circuit manipulation without the need for periodic disruptive surgeries to replace the battery of the implant. Scientists believe this technology can help uncover and treat psychiatric disorders and neurodegenerative diseases such as addiction, depression, and Parkinson’s.
A group of KAIST researchers and collaborators have engineered a tiny brain implant that can be wirelessly recharged from outside the body to control brain circuits for long periods of time without battery replacement. The device is constructed of ultra-soft and bio-compliant polymers to help provide long-term compatibility with tissue. Geared with micrometer-sized LEDs (equivalent to the size of a grain of salt) mounted on ultrathin probes (the thickness of a human hair), it can wirelessly manipulate target neurons in the deep brain using light.
This study, led by Professor Jae-Woong Jeong, is a step forward from the wireless head-mounted implant neural device he developed in 2019. That previous version could indefinitely deliver multiple drugs and light stimulation treatment wirelessly by using a smartphone. For more, Manipulating Brain Cells by Smartphone.
For the new upgraded version, the research team came up with a fully implantable, soft optoelectronic system that can be remotely and selectively controlled by a smartphone. This research was published on January 22, 2021 in Nature Communications.
The new wireless charging technology addresses the limitations of current brain implants. Wireless implantable device technologies have recently become popular as alternatives to conventional tethered implants, because they help minimize stress and inflammation in freely-moving animals during brain studies, which in turn enhance the lifetime of the devices. However, such devices require either intermittent surgeries to replace discharged batteries, or special and bulky wireless power setups, which limit experimental options as well as the scalability of animal experiments.
“This powerful device eliminates the need for additional painful surgeries to replace an exhausted battery in the implant, allowing seamless chronic neuromodulation,” said Professor Jeong. “We believe that the same basic technology can be applied to various types of implants, including deep brain stimulators, and cardiac and gastric pacemakers, to reduce the burden on patients for long-term use within the body.”
To enable wireless battery charging and controls, researchers developed a tiny circuit that integrates a wireless energy harvester with a coil antenna and a Bluetooth low-energy chip. An alternating magnetic field can harmlessly penetrate through tissue, and generate electricity inside the device to charge the battery. Then the battery-powered Bluetooth implant delivers programmable patterns of light to brain cells using an “easy-to-use” smartphone app for real-time brain control.
“This device can be operated anywhere and anytime to manipulate neural circuits, which makes it a highly versatile tool for investigating brain functions,” said lead author Choong Yeon Kim, a researcher at KAIST.
Neuroscientists successfully tested these implants in rats and demonstrated their ability to suppress cocaine-induced behaviour after the rats were injected with cocaine. This was achieved by precise light stimulation of relevant target neurons in their brains using the smartphone-controlled LEDs. Furthermore, the battery in the implants could be repeatedly recharged while the rats were behaving freely, thus minimizing any physical interruption to the experiments.
“Wireless battery re-charging makes experimental procedures much less complicated,” said the co-lead author Min Jeong Ku, a researcher at Yonsei University’s College of Medicine.
“The fact that we can control a specific behaviour of animals, by delivering light stimulation into the brain just with a simple manipulation of smartphone app, watching freely moving animals nearby, is very interesting and stimulates a lot of imagination,” said Jeong-Hoon Kim, a professor of physiology at Yonsei University’s College of Medicine. “This technology will facilitate various avenues of brain research.”
The researchers believe this brain implant technology may lead to new opportunities for brain research and therapeutic intervention to treat diseases in the brain and other organs.
This work was supported by grants from the National Research Foundation of Korea and the KAIST Global Singularity Research Program.
-Profile
Professor Jae-Woong Jeong
https://www.jeongresearch.org/
School of Electrical Engineering
KAIST
2021.01.26 View 16795 -
Expanding the Biosynthetic Pathway via Retrobiosynthesis
- Researchers reports a new strategy for the microbial production of multiple short-chain primary amines via retrobiosynthesis. -
KAIST metabolic engineers presented the bio-based production of multiple short-chain primary amines that have a wide range of applications in chemical industries for the first time. The research team led by Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering designed the novel biosynthetic pathways for short-chain primary amines by combining retrobiosynthesis and a precursor selection step.
The research team verified the newly designed pathways by confirming the in vivo production of 10 short-chain primary amines by supplying the precursors. Furthermore, the platform Escherichia coli strains were metabolically engineered to produce three proof-of-concept short-chain primary amines from glucose, demonstrating the possibility of the bio-based production of diverse short-chain primary amines from renewable resources. The research team said this study expands the strategy of systematically designing biosynthetic pathways for the production of a group of related chemicals as demonstrated by multiple short-chain primary amines as examples.
Currently, most of the industrial chemicals used in our daily lives are produced with petroleum-based products. However, there are several serious issues with the petroleum industry such as the depletion of fossil fuel reserves and environmental problems including global warming. To solve these problems, the sustainable production of industrial chemicals and materials is being explored with microorganisms as cell factories and renewable non-food biomass as raw materials for alternative to petroleum-based products. The engineering of these microorganisms has increasingly become more efficient and effective with the help of systems metabolic engineering – a practice of engineering the metabolism of a living organism toward the production of a desired metabolite. In this regard, the number of chemicals produced using biomass as a raw material has substantially increased.
Although the scope of chemicals that are producible using microorganisms continues to expand through advances in systems metabolic engineering, the biological production of short-chain primary amines has not yet been reported despite their industrial importance. Short-chain primary amines are the chemicals that have an alkyl or aryl group in the place of a hydrogen atom in ammonia with carbon chain lengths ranging from C1 to C7. Short-chain primary amines have a wide range of applications in chemical industries, for example, as a precursor for pharmaceuticals (e.g., antidiabetic and antihypertensive drugs), agrochemicals (e.g., herbicides, fungicides and insecticides), solvents, and vulcanization accelerators for rubber and plasticizers. The market size of short-chain primary amines was estimated to be more than 4 billion US dollars in 2014.
The main reason why the bio-based production of short-chain primary amines was not yet possible was due to their unknown biosynthetic pathways. Therefore, the team designed synthetic biosynthetic pathways for short-chain primary amines by combining retrobiosynthesis and a precursor selection step. The retrobiosynthesis allowed the systematic design of a biosynthetic pathway for short-chain primary amines by using a set of biochemical reaction rules that describe chemical transformation patterns between a substrate and product molecules at an atomic level.
These multiple precursors predicted for the possible biosynthesis of each short-chain primary amine were sequentially narrowed down by using the precursor selection step for efficient metabolic engineering experiments.
“Our research demonstrates the possibility of the renewable production of short-chain primary amines for the first time. We are planning to increase production efficiencies of short-chain primary amines. We believe that our study will play an important role in the development of sustainable and eco-friendly bio-based industries and the reorganization of the chemical industry, which is mandatory for solving the environmental problems threating the survival of mankind,” said Professor Lee.
This paper titled “Microbial production of multiple short-chain primary amines via retrobiosynthesis” was published in Nature Communications. 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.
-Publication
Dong In Kim, Tong Un Chae, Hyun Uk Kim, Woo Dae Jang, and Sang Yup Lee. Microbial production of multiple short-chain primary amines via retrobiosynthesis. Nature Communications ( https://www.nature.com/articles/s41467-020-20423-6)
-Profile
Distinguished Professor Sang Yup Lee
leesy@kaist.ac.kr
Metabolic &Biomolecular Engineering National Research Laboratory
http://mbel.kaist.ac.kr
Department of Chemical and Biomolecular Engineering
KAIST
2021.01.14 View 4535 -
A Comprehensive Review of Biosynthesis of Inorganic Nanomaterials Using Microorganisms and Bacteriophages
There are diverse methods for producing numerous inorganic nanomaterials involving many experimental variables. Among the numerous possible matches, finding the best pair for synthesizing in an environmentally friendly way has been a longstanding challenge for researchers and industries.
A KAIST bioprocess engineering research team led by Distinguished Professor Sang Yup Lee conducted a summary of 146 biosynthesized single and multi-element inorganic nanomaterials covering 55 elements in the periodic table synthesized using wild-type and genetically engineered microorganisms. Their research highlights the diverse applications of biogenic nanomaterials and gives strategies for improving the biosynthesis of nanomaterials in terms of their producibility, crystallinity, size, and shape.
The research team described a 10-step flow chart for developing the biosynthesis of inorganic nanomaterials using microorganisms and bacteriophages. The research was published at Nature Review Chemistry as a cover and hero paper on December 3.
“We suggest general strategies for microbial nanomaterial biosynthesis via a step-by-step flow chart and give our perspectives on the future of nanomaterial biosynthesis and applications. This flow chart will serve as a general guide for those wishing to prepare biosynthetic inorganic nanomaterials using microbial cells,” explained Dr.Yoojin Choi, a co-author of this research.
Most inorganic nanomaterials are produced using physical and chemical methods and biological synthesis has been gaining more and more attention. However, conventional synthesis processes have drawbacks in terms of high energy consumption and non-environmentally friendly processes. Meanwhile, microorganisms such as microalgae, yeasts, fungi, bacteria, and even viruses can be utilized as biofactories to produce single and multi-element inorganic nanomaterials under mild conditions.
After conducting a massive survey, the research team summed up that the development of genetically engineered microorganisms with increased inorganic-ion-binding affinity, inorganic-ion-reduction ability, and nanomaterial biosynthetic efficiency has enabled the synthesis of many inorganic nanomaterials.
Among the strategies, the team introduced their analysis of a Pourbaix diagram for controlling the size and morphology of a product. The research team said this Pourbaix diagram analysis can be widely employed for biosynthesizing new nanomaterials with industrial applications.Professor Sang Yup Lee added, “This research provides extensive information and perspectives on the biosynthesis of diverse inorganic nanomaterials using microorganisms and bacteriophages and their applications. We expect that biosynthetic inorganic nanomaterials will find more diverse and innovative applications across diverse fields of science and technology.”
Dr. Choi started this research in 2018 and her interview about completing this extensive research was featured in an article at Nature Career article on December 4.
-ProfileDistinguished Professor Sang Yup Lee leesy@kaist.ac.krMetabolic &Biomolecular Engineering National Research Laboratoryhttp://mbel.kaist.ac.krDepartment of Chemical and Biomolecular EngineeringKAIST
2020.12.07 View 4388 -
Three Professors Named to Highly Cited Researchers 2020 List
Distinguished Professor Sukbok Chang from the Department of Chemistry, Distinguished Professor Sang-Yup Lee from the Department of Chemical & Biomolecular Engineering, and Professor Jiyong Eom from the College of Business were named to Clarivate’s Highly Cited Researchers 2020 list.
Clarivate announced the researchers who rank in the top 1% of citations by field and publication year in the Web of Science citation index. A total of 6,167 researchers from more than 60 countries were listed this year and 37 Korean scholars made the list.
The methodology that determines the “Who’s Who” of influential researchers draws on data and analyses performed by bibliometric experts and data scientists at the Institute for Scientific Information at Clarivate. It also uses the tallies to identify the countries and research institutions where these scientific elite are based. More than 6,000 researchers from 21 fields in the sciences, social sciences, and cross field categories were selected based on the number of highly cited papers they produced over an 11-year period from January 2009 to December 2019.
Professor Chang made the list six years in a row, while Professor Lee made it for four consecutive years, and Professor Eom for the last two years. Professor Chang’s group (http://sbchang.kaist.ac.kr) investigates catalytic hydrocarbon functionalization. Professor Lee (http://mbel.kaist.ac.kr) is a pioneering scholar in the field of metabolic engineering, systems, and synthetic biology. Professor Eom’s (https://kaistceps.quv.kr) research extends to energy and environmental economics and management, energy big data, and green information systems.
2020.11.30 View 3509 -
E. coli Engineered to Grow on CO₂ and Formic Acid as Sole Carbon Sources
- An E. coli strain that can grow to a relatively high cell density solely on CO₂ and formic acid was developed by employing metabolic engineering. -
Most biorefinery processes have relied on the use of biomass as a raw material for the production of chemicals and materials. Even though the use of CO₂ as a carbon source in biorefineries is desirable, it has not been possible to make common microbial strains such as E. coli grow on CO₂.
Now, a metabolic engineering research group at KAIST has developed a strategy to grow an E. coli strain to higher cell density solely on CO₂ and formic acid. Formic acid is a one carbon carboxylic acid, and can be easily produced from CO₂ using a variety of methods. Since it is easier to store and transport than CO₂, formic acid can be considered a good liquid-form alternative of CO₂.
With support from the C1 Gas Refinery R&D Center and the Ministry of Science and ICT, a research team led by Distinguished Professor Sang Yup Lee stepped up their work to develop an engineered E. coli strain capable of growing up to 11-fold higher cell density than those previously reported, using CO₂ and formic acid as sole carbon sources. This work was published in Nature Microbiology on September 28.
Despite the recent reports by several research groups on the development of E. coli strains capable of growing on CO₂ and formic acid, the maximum cell growth remained too low (optical density of around 1) and thus the production of chemicals from CO₂ and formic acid has been far from realized.
The team previously reported the reconstruction of the tetrahydrofolate cycle and reverse glycine cleavage pathway to construct an engineered E. coli strain that can sustain growth on CO₂ and formic acid. To further enhance the growth, the research team introduced the previously designed synthetic CO₂ and formic acid assimilation pathway, and two formate dehydrogenases.
Metabolic fluxes were also fine-tuned, the gluconeogenic flux enhanced, and the levels of cytochrome bo3 and bd-I ubiquinol oxidase for ATP generation were optimized. This engineered E. coli strain was able to grow to a relatively high OD600 of 7~11, showing promise as a platform strain growing solely on CO₂ and formic acid.
Professor Lee said, “We engineered E. coli that can grow to a higher cell density only using CO₂ and formic acid. We think that this is an important step forward, but this is not the end. The engineered strain we developed still needs further engineering so that it can grow faster to a much higher density.”
Professor Lee’s team is continuing to develop such a strain. “In the future, we would be delighted to see the production of chemicals from an engineered E. coli strain using CO₂ and formic acid as sole carbon sources,” he added.
-Profile:Distinguished Professor Sang Yup Leehttp://mbel.kaist.ac.krDepartment of Chemical and Biomolecular EngineeringKAIST
2020.09.29 View 4987 -
Biomarker Predicts Who Will Have Severe COVID-19
- Airway cell analyses showing an activated immune axis could pinpoint the COVID-19 patients who will most benefit from targeted therapies.-
KAIST researchers have identified key markers that could help pinpoint patients who are bound to get a severe reaction to COVID-19 infection. This would help doctors provide the right treatments at the right time, potentially saving lives. The findings were published in the journal Frontiers in Immunology on August 28.
People’s immune systems react differently to infection with SARS-CoV-2, the virus that causes COVID-19, ranging from mild to severe, life-threatening responses.
To understand the differences in responses, Professor Heung Kyu Lee and PhD candidate Jang Hyun Park from the Graduate School of Medical Science and Engineering at KAIST analysed ribonucleic acid (RNA) sequencing data extracted from individual airway cells of healthy controls and of mildly and severely ill patients with COVID-19. The data was available in a public database previously published by a group of Chinese researchers.
“Our analyses identified an association between immune cells called neutrophils and special cell receptors that bind to the steroid hormone glucocorticoid,” Professor Lee explained. “This finding could be used as a biomarker for predicting disease severity in patients and thus selecting a targeted therapy that can help treat them at an appropriate time,” he added.
Severe illness in COVID-19 is associated with an exaggerated immune response that leads to excessive airway-damaging inflammation. This condition, known as acute respiratory distress syndrome (ARDS), accounts for 70% of deaths in fatal COVID-19 infections.
Scientists already know that this excessive inflammation involves heightened neutrophil recruitment to the airways, but the detailed mechanisms of this reaction are still unclear.
Lee and Park’s analyses found that a group of immune cells called myeloid cells produced excess amounts of neutrophil-recruiting chemicals in severely ill patients, including a cytokine called tumour necrosis factor (TNF) and a chemokine called CXCL8.
Further RNA analyses of neutrophils in severely ill patients showed they were less able to recruit very important T cells needed for attacking the virus. At the same time, the neutrophils produced too many extracellular molecules that normally trap pathogens, but damage airway cells when produced in excess.
The researchers additionally found that the airway cells in severely ill patients were not expressing enough glucocorticoid receptors. This was correlated with increased CXCL8 expression and neutrophil recruitment.
Glucocorticoids, like the well-known drug dexamethasone, are anti-inflammatory agents that could play a role in treating COVID-19. However, using them in early or mild forms of the infection could suppress the necessary immune reactions to combat the virus. But if airway damage has already happened in more severe cases, glucocorticoid treatment would be ineffective.
Knowing who to give this treatment to and when is really important. COVID-19 patients showing reduced glucocorticoid receptor expression, increased CXCL8 expression, and excess neutrophil recruitment to the airways could benefit from treatment with glucocorticoids to prevent airway damage. Further research is needed, however, to confirm the relationship between glucocorticoids and neutrophil inflammation at the protein level.
“Our study could serve as a springboard towards more accurate and reliable COVID-19 treatments,” Professor Lee said.
This work was supported by the National Research Foundation of Korea, and Mobile Clinic Module Project funded by KAIST.
Figure. Low glucocorticoid receptor (GR) expression led to excessive inflammation and lung damage by neutrophils through enhancing the expression of CXCL8 and other cytokines.
Image credit: Professor Heung Kyu Lee, KAIST. Created with Biorender.com.
Image usage restrictions: News organizations may use or redistribute these figures and image, with proper attribution, as part of news coverage of this paper only.
-Publication:
Jang Hyun Park, and Heung Kyu Lee. (2020). Re-analysis of Single Cell Transcriptome Reveals That the NR3C1-CXCL8-Neutrophil Axis Determines the Severity of COVID-19. Frontiers in Immunology, Available online at https://doi.org/10.3389/fimmu.2020.02145
-Profile: Heung Kyu Lee
Associate Professor
heungkyu.lee@kaist.ac.kr
https://www.heungkyulee.kaist.ac.kr/
Laboratory of Host Defenses
Graduate School of Medical Science and Engineering (GSMSE)
The Center for Epidemic Preparedness at KAIST Institute
http://kaist.ac.kr
Korea Advanced Institute of Science and Technology (KAIST)
Daejeon, Republic of Korea
Profile: Jang Hyun Park
PhD Candidate
janghyun.park@kaist.ac.kr
GSMSE, KAIST
2020.09.17 View 7194 -
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 3655 -
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 7952 -
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 5778 -
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
(END)
2020.06.24 View 7711