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Study of T Cells from COVID-19 Convalescents Guides Vaccine Strategies
Researchers confirm that most COVID-19 patients in their convalescent stage carry stem cell-like memory T cells for months
A KAIST immunology research team found that most convalescent patients of COVID-19 develop and maintain T cell memory for over 10 months regardless of the severity of their symptoms. In addition, memory T cells proliferate rapidly after encountering their cognate antigen and accomplish their multifunctional roles. This study provides new insights for effective vaccine strategies against COVID-19, considering the self-renewal capacity and multipotency of memory T cells.
COVID-19 is a disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. When patients recover from COVID-19, SARS-CoV-2-specific adaptive immune memory is developed. The adaptive immune system consists of two principal components: B cells that produce antibodies and T cells that eliminate infected cells. The current results suggest that the protective immune function of memory T cells will be implemented upon re-exposure to SARS-CoV-2.
Recently, the role of memory T cells against SARS-CoV-2 has been gaining attention as neutralizing antibodies wane after recovery. Although memory T cells cannot prevent the infection itself, they play a central role in preventing the severe progression of COVID-19. However, the longevity and functional maintenance of SARS-CoV-2-specific memory T cells remain unknown.
Professor Eui-Cheol Shin and his collaborators investigated the characteristics and functions of stem cell-like memory T cells, which are expected to play a crucial role in long-term immunity. Researchers analyzed the generation of stem cell-like memory T cells and multi-cytokine producing polyfunctional memory T cells, using cutting-edge immunological techniques.
This research is significant in that revealing the long-term immunity of COVID-19 convalescent patients provides an indicator regarding the long-term persistence of T cell immunity, one of the main goals of future vaccine development, as well as evaluating the long-term efficacy of currently available COVID-19 vaccines.
The research team is presently conducting a follow-up study to identify the memory T cell formation and functional characteristics of those who received COVID-19 vaccines, and to understand the immunological effect of COVID-19 vaccines by comparing the characteristics of memory T cells from vaccinated individuals with those of COVID-19 convalescent patients.
PhD candidate Jae Hyung Jung and Dr. Min-Seok Rha, a clinical fellow at Yonsei Severance Hospital, who led the study together explained, “Our analysis will enhance the understanding of COVID-19 immunity and establish an index for COVID-19 vaccine-induced memory T cells.”
“This study is the world’s longest longitudinal study on differentiation and functions of memory T cells among COVID-19 convalescent patients. The research on the temporal dynamics of immune responses has laid the groundwork for building a strategy for next-generation vaccine development,” Professor Shin added. This work was supported by the Samsung Science and Technology Foundation and KAIST, and was published in Nature Communications on June 30.
-Publication:
Jung, J.H., Rha, MS., Sa, M. et al. SARS-CoV-2-specific T cell memory is sustained in COVID-19 convalescent patients for 10 months with successful development of stem cell-like memory T cells. Nat Communications 12, 4043 (2021). https://doi.org/10.1038/s41467-021-24377-1
-Profile:
Professor Eui-Cheol Shin
Laboratory of Immunology & Infectious Diseases (http://liid.kaist.ac.kr/)
Graduate School of Medical Science and Engineering
KAIST
2021.07.05 View 10418 -
What Guides Habitual Seeking Behavior Explained
A new role of the ventral striatum explains habitual seeking behavior
Researchers have been investigating how the brain controls habitual seeking behaviors such as addiction. A recent study by Professor Sue-Hyun Lee from the Department of Bio and Brain Engineering revealed that a long-term value memory maintained in the ventral striatum in the brain is a neural basis of our habitual seeking behavior. This research was conducted in collaboration with the research team lead by Professor Hyoung F. Kim from Seoul National University. Given that addictive behavior is deemed a habitual one, this research provides new insights for developing therapeutic interventions for addiction.
Habitual seeking behavior involves strong stimulus responses, mostly rapid and automatic ones. The ventral striatum in the brain has been thought to be important for value learning and addictive behaviors. However, it was unclear if the ventral striatum processes and retains long-term memories that guide habitual seeking.
Professor Lee’s team reported a new role of the human ventral striatum where long-term memory of high-valued objects are retained as a single representation and may be used to evaluate visual stimuli automatically to guide habitual behavior.
“Our findings propose a role of the ventral striatum as a director that guides habitual behavior with the script of value information written in the past,” said Professor Lee.
The research team investigated whether learned values were retained in the ventral striatum while the subjects passively viewed previously learned objects in the absence of any immediate outcome. Neural responses in the ventral striatum during the incidental perception of learned objects were examined using fMRI and single-unit recording.
The study found significant value discrimination responses in the ventral striatum after learning and a retention period of several days. Moreover, the similarity of neural representations for good objects increased after learning, an outcome positively correlated with the habitual seeking response for good objects.
“These findings suggest that the ventral striatum plays a role in automatic evaluations of objects based on the neural representation of positive values retained since learning, to guide habitual seeking behaviors,” explained Professor Lee.
“We will fully investigate the function of different parts of the entire basal ganglia including the ventral striatum. We also expect that this understanding may lead to the development of better treatment for mental illnesses related to habitual behaviors or addiction problems.”
This study, supported by the National Research Foundation of Korea, was reported at Nature Communications (https://doi.org/10.1038/s41467-021-22335-5.)
-ProfileProfessor Sue-Hyun LeeDepartment of Bio and Brain EngineeringMemory and Cognition Laboratoryhttp://memory.kaist.ac.kr/lecture
KAIST
2021.06.03 View 8130 -
Identification of How Chemotherapy Drug Works Could Deliver Personalized Cancer Treatment
The chemotherapy drug decitabine is commonly used to treat patients with blood cancers, but its response rate is somewhat low. Researchers have now identified why this is the case, opening the door to more personalized cancer therapies for those with these types of cancers, and perhaps further afield.
Researchers have identified the genetic and molecular mechanisms within cells that make the chemotherapy drug decitabine—used to treat patients with myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML) —work for some patients but not others. The findings should assist clinicians in developing more patient-specific treatment strategies.
The findings were published in the Proceedings of the National Academies of Science on March 30.
The chemotherapy drug decitabine, also known by its brand name Dacogen, works by modifying our DNA that in turn switches on genes that stop the cancer cells from growing and replicating. However, decitabine’s response rate is somewhat low (showing improvement in just 30-35% of patients), which leaves something of a mystery as to why it works well for some patients but not for others. To find out why this happens, researchers from the KAIST investigated the molecular mediators that are involved with regulating the effects of the drug.
Decitabine works to activate the production of endogenous retroviruses (ERVs), which in turn induces an immune response. ERVs are viruses that long ago inserted dormant copies of themselves into the human genome. Decitabine in essence, ‘reactivates’ these viral elements and produces double-stranded RNAs (dsRNAs) that the immune system views as a foreign body.
“However, the mechanisms involved in this process, in particular how production and transport of these ERV dsRNAs were regulated within the cell were understudied,” said corresponding author Yoosik Kim, professor in the Department of Chemical and Biomolecular Engineering at KAIST.
“So to explain why decitabine works in some patients but not others, we investigated what these molecular mechanisms were,” added Kim.
To do so, the researchers used image-based RNA interference (RNAi) screening. This is a relatively new technique in which specific sequences within a genome are knocked out of action or “downregulated.” Large-scale screening, which can be performed in cultured cells or within live organisms, works to investigate the function of different genes. The KAIST researchers collaborated with the Institut Pasteur Korea to analyze the effect of downregulating genes that recognize ERV dsRNAs and could be involved in the cellular response to decitabine.
From these initial screening results, they performed an even more detailed downregulation screening analysis. Through the screening, they were able to identify two particular gene sequences involved in the production of an RNA-binding protein called Staufen1 and the production of a strand of RNA that does not in turn produce any proteins called TINCR that play a key regulatory role in response to the drug. Staufen1 binds directly to dsRNAs and stabilizes them in concert with the TINCR.
If a patient is not producing sufficient Staufen1 and TINCR, then the dsRNA viral mimics quickly degrade before the immune system can spot them. And, crucially for cancer therapy, this means that patients with lower expression (activation) of these sequences will show inferior response to decitabine. Indeed, the researchers confirmed that MDS/AML patients with low Staufen1 and TINCR expression did not benefit from decitabine therapy.
“We can now isolate patients who will not benefit from the therapy and direct them to a different type of therapy,” said first author Yongsuk Ku. “This serves as an important step toward developing a patient-specific treatment cancer strategy.”
As the researchers used patient samples taken from bone marrow, the next step will be to try to develop a testing method that can identify the problem from just blood samples, which are much easier to acquire from patients.
The team plans to investigate if the analysis can be extended to patients with solid tumors in addition to those with blood cancers.
-Profile
Professor Yoosik Kim
https://qcbio.kaist.ac.kr/
Department of Chemical and Biomolecular Engineering
KAIST
-Publication
Noncanonical immune response to the inhibition of DNA methylation by Staufen1 via stabilization of endogenous retrovirus RNAs, PNAS
2021.05.24 View 8368 -
KPC4IR Leads the Global Blockchain Standards Via Korea Innovation Studies
The Korea Policy Center for the Fourth Industrial Revolution (KPC4IR) at KAIST will play a leading role in the Global Standards Mapping Initiative (GSMI) 2.0 as the Chair of Working Group on South Korea at the Global Blockchain Business Council (GBBC). The GBBC, a Swiss-based non-profit consortium, established the GSMI to map blockchain technology ecosystem, established the GSMI to map blockchain and digital asset standards and regulation globally. The initial release of the GSMI mapped data and outputs from ons, 185 jurisdictions, nearly 400 industry groups, and over 30 technical standard-setting entities.
The GSMI Working Group on South Korea is the only group that will investigate the country-level innovation of blockchain and digital asset alongside six Korean blockchain associations: The GSMI Working Group on South Korea is the only group that will investigate the country-level innovation of blockchain and digital asset alongside six Korean blockchain associations: the Korea Blockchain Association, the Korea Society of Blockchain, Blockchain & Law, the Open Blockchain and DID Association, the Korea Blockchain Startup Association, and the Korea Blockchain Industry Promotion Association. Individual members also joined from the Inter-American Development Bank, Blockchain Labs, and GOPAX.
The GSMI Working Group on South Korea, chaired by KAIST, will leverage their experience in blockchain adoption to assist in setting global standards for the ecosystem. The Group will also highlight how South Korea can be a testbed for ITC adoption and open the door to a blockchain-ready world.
GSMI 2.0 is spearheaded by nine working groups chaired by institutions, such as the World Economic Forum and the GBBC, Ernst & Young, HM Revenue and Customs, Accenture, and Hyperledger - Linux Foundation. Each of the Working Groups will be supported by sixteen fellows from eight fellow program partners. KAIST student Yujin Bang is the South Korea Working Group fellow. The GBBC and the WEF already published the first volume of the GSMI in October 2020 in collaboration with world-leading institutions, including KAIST, MIT Media Lab, and Accenture.
Director of the KPC4IR Professor So Young Kim said, “The designation of KAIST is the result of continued collaborations with the WEF. The participation of this working group will help Korea’s global leadership with blockchain standards.”
2021.05.18 View 6213 -
Observing Individual Atoms in 3D Nanomaterials and Their Surfaces
Atoms are the basic building blocks for all materials. To tailor functional properties, it is essential to accurately determine their atomic structures. KAIST researchers observed the 3D atomic structure of a nanoparticle at the atom level via neural network-assisted atomic electron tomography.
Using a platinum nanoparticle as a model system, a research team led by Professor Yongsoo Yang demonstrated that an atomicity-based deep learning approach can reliably identify the 3D surface atomic structure with a precision of 15 picometers (only about 1/3 of a hydrogen atom’s radius). The atomic displacement, strain, and facet analysis revealed that the surface atomic structure and strain are related to both the shape of the nanoparticle and the particle-substrate interface.
Combined with quantum mechanical calculations such as density functional theory, the ability to precisely identify surface atomic structure will serve as a powerful key for understanding catalytic performance and oxidation effect.
“We solved the problem of determining the 3D surface atomic structure of nanomaterials in a reliable manner. It has been difficult to accurately measure the surface atomic structures due to the ‘missing wedge problem’ in electron tomography, which arises from geometrical limitations, allowing only part of a full tomographic angular range to be measured. We resolved the problem using a deep learning-based approach,” explained Professor Yang.
The missing wedge problem results in elongation and ringing artifacts, negatively affecting the accuracy of the atomic structure determined from the tomogram, especially for identifying the surface structures. The missing wedge problem has been the main roadblock for the precise determination of the 3D surface atomic structures of nanomaterials.
The team used atomic electron tomography (AET), which is basically a very high-resolution CT scan for nanomaterials using transmission electron microscopes. AET allows individual atom level 3D atomic structural determination.
“The main idea behind this deep learning-based approach is atomicity—the fact that all matter is composed of atoms. This means that true atomic resolution electron tomogram should only contain sharp 3D atomic potentials convolved with the electron beam profile,” said Professor Yang.
“A deep neural network can be trained using simulated tomograms that suffer from missing wedges as inputs, and the ground truth 3D atomic volumes as targets. The trained deep learning network effectively augments the imperfect tomograms and removes the artifacts resulting from the missing wedge problem.”
The precision of 3D atomic structure can be enhanced by nearly 70% by applying the deep learning-based augmentation. The accuracy of surface atom identification was also significantly improved.
Structure-property relationships of functional nanomaterials, especially the ones that strongly depend on the surface structures, such as catalytic properties for fuel-cell applications, can now be revealed at one of the most fundamental scales: the atomic scale.
Professor Yang concluded, “We would like to fully map out the 3D atomic structure with higher precision and better elemental specificity. And not being limited to atomic structures, we aim to measure the physical, chemical, and functional properties of nanomaterials at the 3D atomic scale by further advancing electron tomography techniques.”
This research, reported at Nature Communications, was funded by the National Research Foundation of Korea and the KAIST Global Singularity Research M3I3 Project.
-Publication
Juhyeok Lee, Chaehwa Jeong & Yongsoo Yang
“Single-atom level determination of 3-dimensional surface atomic structure via neural network-assisted atomic electron tomography”
Nature Communications
-Profile
Professor Yongsoo Yang
Department of Physics
Multi-Dimensional Atomic Imaging Lab (MDAIL)
http://mdail.kaist.ac.kr
KAIST
2021.05.12 View 9627 -
Prof. Sang Yup Lee Elected as a Foreign Member of the Royal Society
Vice President for Research Distinguished Professor Sang Yup Lee was elected as a foreign member of the Royal Society in the UK. On May 6, the Society announced the list of distinguished new 52 fellows and 10 foreign members who achieved exceptional contributions to science. Professor Lee and Professor V. Narry Kim from Seoul National University are the first foreign members ever elected from Korea.
The Royal Society, established in 1660, is one of the most prestigious national science academies and a fellowship of 1,600 of the world’s most eminent scientists. From Newton to Darwin, Einstein, Hawking, and beyond, pioneers and paragons in their fields are elected by their peers. To date, there are 280 Nobel prize winners among the fellows.
Distinguished Professor Lee from the Department of Chemical and Biomolecular Engineering at KAIST is one of the Highly Cited Researchers (HCRs) who pioneered systems metabolic engineering and developed various micro-organisms for producing a wide range of fuels, chemicals, materials, and natural compounds.
His seminal scholarship and research career have already been recognized worldwide. He is the first Korean ever elected into the National Academy of Inventors (NAI) in the US and one of 13 scholars elected as an International Member of both the National Academy of Sciences (NAS) and the National Academy of Engineering (NAE) in the US. With this fellowship, he added one more accolade of being the first non-US and British Commonwealth scientist elected into the three most prestigious science academies: the NAS, the NAE, and the Royal Society.
2021.05.07 View 9044 -
T-GPS Processes a Graph with Trillion Edges on a Single Computer
Trillion-scale graph processing simulation on a single computer presents a new concept of graph processing
A KAIST research team has developed a new technology that enables to process a large-scale graph algorithm without storing the graph in the main memory or on disks. Named as T-GPS (Trillion-scale Graph Processing Simulation) by the developer Professor Min-Soo Kim from the School of Computing at KAIST, it can process a graph with one trillion edges using a single computer.
Graphs are widely used to represent and analyze real-world objects in many domains such as social networks, business intelligence, biology, and neuroscience. As the number of graph applications increases rapidly, developing and testing new graph algorithms is becoming more important than ever before. Nowadays, many industrial applications require a graph algorithm to process a large-scale graph (e.g., one trillion edges). So, when developing and testing graph algorithms such for a large-scale graph, a synthetic graph is usually used instead of a real graph. This is because sharing and utilizing large-scale real graphs is very limited due to their being proprietary or being practically impossible to collect.
Conventionally, developing and testing graph algorithms is done via the following two-step approach: generating and storing a graph and executing an algorithm on the graph using a graph processing engine.
The first step generates a synthetic graph and stores it on disks. The synthetic graph is usually generated by either parameter-based generation methods or graph upscaling methods. The former extracts a small number of parameters that can capture some properties of a given real graph and generates the synthetic graph with the parameters. The latter upscales a given real graph to a larger one so as to preserve the properties of the original real graph as much as possible.
The second step loads the stored graph into the main memory of the graph processing engine such as Apache GraphX and executes a given graph algorithm on the engine. Since the size of the graph is too large to fit in the main memory of a single computer, the graph engine typically runs on a cluster of several tens or hundreds of computers. Therefore, the cost of the conventional two-step approach is very high.
The research team solved the problem of the conventional two-step approach. It does not generate and store a large-scale synthetic graph. Instead, it just loads the initial small real graph into main memory. Then, T-GPS processes a graph algorithm on the small real graph as if the large-scale synthetic graph that should be generated from the real graph exists in main memory. After the algorithm is done, T-GPS returns the exactly same result as the conventional two-step approach.
The key idea of T-GPS is generating only the part of the synthetic graph that the algorithm needs to access on the fly and modifying the graph processing engine to recognize the part generated on the fly as the part of the synthetic graph actually generated.
The research team showed that T-GPS can process a graph of 1 trillion edges using a single computer, while the conventional two-step approach can only process of a graph of 1 billion edges using a cluster of eleven computers of the same specification. Thus, T-GPS outperforms the conventional approach by 10,000 times in terms of computing resources. The team also showed that the speed of processing an algorithm in T-GPS is up to 43 times faster than the conventional approach. This is because T-GPS has no network communication overhead, while the conventional approach has a lot of communication overhead among computers.
Professor Kim believes that this work will have a large impact on the IT industry where almost every area utilizes graph data, adding, “T-GPS can significantly increase both the scale and efficiency of developing a new graph algorithm.”
This work was supported by the National Research Foundation (NRF) of Korea and Institute of Information & communications Technology Planning & Evaluation (IITP).
Publication:
Park, H., et al. (2021) “Trillion-scale Graph Processing Simulation based on Top-Down Graph Upscaling,” Presented at the IEEE ICDE 2021 (April 19-22, 2021, Chania, Greece)
Profile:
Min-Soo Kim
Associate Professor
minsoo.k@kaist.ac.kr
http://infolab.kaist.ac.kr
School of Computing
KAIST
2021.05.06 View 6592 -
Distinguished Professor Sang Yup Lee Honored with Charles D. Scott Award
Vice President for Research Sang Yup Lee received the 2021 Charles D. Scott Award from the Society for Industrial Microbiology and Biotechnology. Distinguished Professor Lee from the Department of Chemical and Biomolecular Engineering at KAIST is the first Asian awardee.
The Charles D. Scott Award, initiated in 1995, recognizes individuals who have made significant contributions to enable and further the use of biotechnology to produce fuels and chemicals. The award is named in honor of Dr. Charles D. Scott, who founded the Symposium on Biomaterials, Fuels, and Chemicals and chaired the conference for its first ten years.
Professor Lee has pioneered systems metabolic engineering and developed various micro-organisms capable of producing a wide range of fuels, chemicals, materials, and natural compounds, many of them for the first time. Some of the breakthroughs include the microbial production of gasoline, diacids, diamines, PLA and PLGA polymers, and several natural products.
More recently, his team has developed a microbial strain capable of the mass production of succinic acid, a monomer for manufacturing polyester, with the highest production efficiency to date, as well as a Corynebacterium glutamicum strain capable of producing high-level glutaric acid. They also engineered for the first time a bacterium capable of producing carminic acid, a natural red colorant that is widely used for food and cosmetics.
Professor Lee is one of the Highly Cited Researchers (HCR), ranked in the top 1% by citations in their field by Clarivate Analytics for four consecutive years from 2017. He is the first Korean fellow ever elected into the National Academy of Inventors in the US and one of 13 scholars elected as an International Member of both the National Academy of Sciences and the National Academy of Engineering in the USA.
The awards ceremony will take place during the Symposium on Biomaterials, Fuels, and Chemicals held online from April 26.
2021.04.27 View 7903 -
Professor Mu-Hyun Baik Honored with the POSCO TJ Park Prize
Professor Mu-Hyun Baik at the Department of Chemistry was honored to be the recipient of the 2021 POSCO TJ Park Prize in Science. The POSCO TJ Park Foundation awards every year the individual or organization which made significant contribution in science, education, community development, philanthropy, and technology.
Professor Baik, a renowned computational chemist in analyzing complicated chemical reactions to understand how molecules behave and how they change. Professor Baik was awarded in recognition of his pioneering research in designing numerous organometallic catalysts with using computational molecular modelling. In 2016, he published in Science on the catalytic borylation of methane that showed how chemical reactions can be carried out using the natural gas methane as a substrate.
In 2020, he reported in Science that electrodes can be used as functional groups with adjustable inductive effects to change the chemical reactivity of molecules that are attached to them, closely mimicking the inductive effect of conventional functional groups. This constitutes a potentially powerful new way of controlling chemical reactions, offering an alternative to preparing derivatives to install electron-withdrawing functional groups.
Joined at KAIST in 2015, Professor Baik also serves as associate director at the Center for Catalytic Hydrocarbon Functionalization at the Institute for Basic Science (IBS) since 2015. Among the many recognitions and awards that he received include the Kavli Fellowship by the Kavli Foundation and the National Academy of Science in the US in 2019 and the 2018 Friedrich Wilhelm Bessel Award by the Alexander von Humboldt Foundation in Germany.
2021.03.11 View 7472 -
Rare Mutations May Have Big Impact on Schizophrenia Pathology
- Somatic mutations found only in brain cells disrupt synaptic function. -
Schizophrenia is a neurodevelopmental disorder that disrupts brain activity, producing hallucinations, delusions, and other cognitive disturbances. Researchers have long searched for genetic influences in the disease, but genetic mutations have been identified in only a small fraction—fewer than a quarter—of sequenced patients. Now a study shows that “somatic” gene mutations in brain cells could account for some of the disease’s neuropathology.
The results of the study, led by Professor Jeong Ho Lee at the Graduate School of Medical Science and Engineering in collaboration with the Stanley Medical Research Institute in the US, appeared in Biological Psychiatry.
Traditional genetic mutations, called germline mutations, occur in sperm or egg cells and are passed on to offspring by their parents. Somatic mutations, in contrast, occur in an embryo after fertilization, and they can show up throughout the body or in isolated pockets of tissues, making them much harder to detect from blood or saliva samples, which are typically used for such sequencing studies.
Recently, more-advanced genetic sequencing techniques have allowed researchers to detect somatic mutations and studies have shown that even mutations present at very low levels can have functional consequences. A previous study hinted that brain somatic mutations were associated with schizophrenia, but it was not powerful enough to cement an association between brain somatic mutations and schizophrenia.
In the current study, the researchers used deep whole-exome sequencing to determine the genetic code of all exomes, the parts of genes that encode proteins. The scientists sequenced postmortem samples from brain, liver, spleen, or heart tissue of 27 people with schizophrenia and 31 control participants allowing them to compare the sequences in the two tissues. Using a powerful analytic technique, the team identified an average of 4.9 somatic single-nucleotide variants, or mutations, in brain samples from people with schizophrenia, and 5.6 somatic single-nucleotide variants in brain samples from control subjects.
Although there were no significant quantitative differences in somatic single-nucleotide variants between schizophrenia and control tissue samples, the researchers found that the mutations in schizophrenia patients were found in genes already associated with schizophrenia. Of the germline mutations that had previously been associated with schizophrenia, the genes affected encode proteins associated with synaptic neural communication, particularly in a brain region called the dorsolateral prefrontal cortex.
In the new analysis, the researchers determined which proteins might be affected by the newly identified somatic mutations. Remarkably, a protein called GRIN2B emerged as highly affected and two patients with schizophrenia carried somatic mutations on the GRIN2B gene itself. GRIN2B is a protein component of NMDA-type glutamate receptors, which are critical for neural signaling. Faulty glutamate receptors have long been suspected of contributing to schizophrenia pathology; GRIN2B ranks among the most-studied genes in schizophrenia. The somatic mutations identified in the study had a variant allele frequency of only ~1%, indicating that the mutations were rare among brain cells as a whole. Nevertheless, they have the potential to create widespread cortical dysfunction.
Professor Lee said, “Besides the comprehensive genetic analysis of brain-only mutations in postmortem tissues from schizophrenia patients, this study experimentally showed the biological consequence of identified somatic mutations, which led to neuronal abnormalities associated with schizophrenia. Thus, this study suggests that brain somatic mutations can be a hidden major contributor to schizophrenia and provides new insights into the molecular genetic architecture of schizophrenia.
John Krystal, MD, editor of Biological Psychiatry, said of the work, "The genetics of schizophrenia has received intensive study for several decades. Now a new possibility emerges, that in some cases, mutations in the DNA of brain cells contributes to the biology of schizophrenia. Remarkably this new biology points to an old schizophrenia story: NMDA glutamate receptor dysfunction. Perhaps the path through which somatic mutations contribute to schizophrenia converges with other sources of abnormalities in glutamate signaling in this disorder."
Professor Lee and the team next want to assess the functional consequences of the somatic mutations. Because of the location of the GRIN2B mutations found in schizophrenia patients, the researchers hypothesized that they might interfere with the receptors’ localization on neurons. Experiments on the cortical neurons of mice showed that the mutations indeed disrupted the receptors’ usual localization to dendrites, the “listening” ends of neurons, which in turn prevented the formation of normal synapses in the neurons. This finding suggests that the somatic mutations could disrupt neural communication, contributing to schizophrenia pathology.
- Profile:
Professor Jeong Ho Lee
Translational Neurogenetics Laboratory ( https://tnl.kaist.ac.kr/)
The Graduate School of Medical Science and Engineering
KAIST
(END)
2021.03.11 View 6856 -
Highly Deformable Piezoelectric Nanotruss for Tactile Electronics
With the importance of non-contact environments growing due to COVID-19, tactile electronic devices using haptic technology are gaining traction as new mediums of communication.
Haptic technology is being applied in a wide array of fields such as robotics or interactive displays. haptic gloves are being used for augmented information communication technology. Efficient piezoelectric materials that can convert various mechanical stimuli into electrical signals and vice versa are a prerequisite for advancing high-performing haptic technology.
A research team led by Professor Seungbum Hong confirmed the potential of tactile devices by developing ceramic piezoelectric materials that are three times more deformable. For the fabrication of highly deformable nanomaterials, the research team built a zinc oxide hollow nanostructure using proximity field nanopatterning and atomic layered deposition. The piezoelectric coefficient was measured to be approximately 9.2 pm/V and the nanopillar compression test showed an elastic strain limit of approximately 10%, which is more than three times greater than that of the bulk zinc oxide one.
Piezoelectric ceramics have a high piezoelectric coefficient with a low elastic strain limit, whereas the opposite is true for piezoelectric polymers. Therefore, it has been very challenging to obtain good performance in both high piezoelectric coefficients as well as high elastic strain limits. To break the elastic limit of piezoelectric ceramics, the research team introduced a 3D truss-like hollow nanostructure with nanometer-scale thin walls.
According to the Griffith criterion, the fracture strength of a material is inversely proportional to the square root of the preexisting flaw size. However, a large flaw is less likely to occur in a small structure, which, in turn, enhances the strength of the material. Therefore, implementing the form of a 3D truss-like hollow nanostructure with nanometer-scale thin walls can extend the elastic limit of the material. Furthermore, a monolithic 3D structure can withstand large strains in all directions while simultaneously preventing the loss from the bottleneck. Previously, the fracture property of piezoelectric ceramic materials was difficult to control, owing to the large variance in crack sizes. However, the research team structurally limited the crack sizes to manage the fracture properties.
Professor Hong’s results demonstrate the potential for the development of highly deformable ceramic piezoelectric materials by improving the elastic limit using a 3D hollow nanostructure. Since zinc oxide has a relatively low piezoelectric coefficient compared to other piezoelectric ceramic materials, applying the proposed structure to such components promised better results in terms of the piezoelectric activity.
“With the advent of the non-contact era, the importance of emotional communication is increasing. Through the development of novel tactile interaction technologies, in addition to the current visual and auditory communication, mankind will enter a new era where they can communicate with anyone using all five senses regardless of location as if they are with them in person,” Professor Hong said.
“While additional research must be conducted to realize the application of the proposed designs for haptic enhancement devices, this study holds high value in that it resolves one of the most challenging issues in the use of piezoelectric ceramics, specifically opening new possibilities for their application by overcoming their mechanical constraints.
The research was reported in Nano Energy and supported by the Ministry of Science and ICT, the Korea Research Foundation, and the KAIST Global Singularity Research Project.
-Profile: Professor Seungbum Hong
seungbum@kaist.ac.kr
http://mii.kaist.ac.kr/
Department of Materials Science and Engineering
KAIST
2021.02.02 View 9140 -
KAIST Mobile Clinic Module to Fill Negative Pressure Ward Shortage
Efficient versatile ready-for-rapid building system of MCM will serve as both a triage unit and bridge center in emergency medical situations
A team from KAIST has developed a low-cost and ready-for-rapid-production negative pressure room called a Mobile Clinic Module (MCM). The MCM is expandable, moveable, and easy to store through a combination of negative pressure frames, air tents, and multi-function panels.
The MCM expects to quickly meet the high demand for negative pressure beds in the nation and eventually many other countries where the third wave of COVID-19 is raging. The module is now ready to be rolled out after a three-week test period at the Korea Cancer Center Hospital.
Professor Tek-Jin Nam’s team swung into action, rapidly working together with researchers, engineers with expertise in mechanical design, and a team of clinical doctors to complete the MCM as one of KAIST’s New Deal R&D initiatives launched last July.
Professor Nam cites ‘expandability’ as the key feature of the MCM. Eventually, it will serve as both a triage unit and bridge center in emergency medical situations.
“The module is a very efficient and versatile unit building system. It takes approximately two hours to build the basic MCM unit, which comprises four negative pressure bed rooms, nurse’s station, locker room, and treatment room. We believe this will significantly contribute to relieving the drastic need for negative pressure beds and provide a place for monitoring patients with moderate symptoms,” said Professor Nam.
“It will also be helpful for managing less-severe patients who need to be monitored daily in quarantined rooms or as bridge stations where on-site medical staff can provide treatment and daily monitoring before hospitalization. These wards can be efficiently deployed either inside or outside existing hospitals.”
The research team specially designed the negative pressure frame to ensure safety level A for the negative pressure room, which is made of a multi-function panel wall and roofed with an air tent. The multi-function panels can hold medical appliances such as ventilators, oxygen and bio-signal monitors.
Positive air pressure devices supply fresh air from outside the tent. An air pump and controller maintain air beam pressure, while filtering exhausted air. An internal air information monitoring system efficiently controls room air pressure and purifies the air.
While a conventional negative pressure bed is reported to cost approximately 3.5 billion KRW (50 billion won for a ward), this module is estimated to cost 0.75 billion won each (10 billion won for a ward), cutting the costs by approximately 80%.
The MCM is designed to be easily transported and relocated due to its volume, weight, and maintainability. This module requires only one-fourth of the volume of existing wards and takes up approximately 40% of their weight. The unit can be transported in a 40-foot container truck.
“We believe this will significantly contribute to relieving the drastic need for negative pressure beds and provide a place for monitoring patients with moderate symptoms. We look forward to the MCM upgrading epidemic management resources around the world.”
Professor Nam’s team is also developing antiviral solutions and devices such as protective gear, sterilizers, and test kits under the KAIST New Deal R&D Initiative that was launched to promptly and proactively respond to the epidemic. More than 45 faculty members and researchers at KAIST are collaborating with industry and clinical hospitals to develop the antiviral technology that will improve preventive measures, diagnoses, and treatment.
2021.01.07 View 10221