cell+aging
-
Research Day Highlights the Most Impactful Technologies of the Year
Technology Converting Full HD Image to 4-Times Higher UHD Via Deep Learning Cited as the Research of the Year
The technology converting a full HD image into a four-times higher UHD image in real time via AI deep learning was recognized as the Research of the Year. Professor Munchurl Kim from the School of Electrical Engineering who developed the technology won the Research of the Year Grand Prize during the 2021 KAIST Research Day ceremony on May 25. Professor Kim was lauded for conducting creative research on machine learning and deep learning-based image processing.
KAIST’s Research Day recognizes the most notable research outcomes of the year, while creating opportunities for researchers to immerse themselves into interdisciplinary research projects with their peers. The ceremony was broadcast online due to Covid-19 and announced the Ten R&D Achievement of the Year that are expected to make a significant impact.
To celebrate the award, Professor Kim gave a lecture on “Computational Imaging through Deep Learning for the Acquisition of High-Quality Images.” Focusing on the fact that advancements in artificial intelligence technology can show superior performance when used to convert low-quality videos to higher quality, he introduced some of the AI technologies that are currently being applied in the field of image restoration and quality improvement.
Professors Eui-Cheol Shin from the Graduate School of Medical Science and Engineering and In-Cheol Park from the School of Electrical Engineering each received Research Awards, and Professor Junyong Noh from the Graduate School of Culture Technology was selected for the Innovation Award. Professors Dong Ki Yoon from the Department of Chemistry and Hyungki Kim from the Department of Mechanical Engineering were awarded the Interdisciplinary Award as a team for their joint research.
Meanwhile, out of KAIST’s ten most notable R&D achievements, those from the field of natural and biological sciences included research on rare earth element-platinum nanoparticle catalysts by Professor Ryong Ryoo from the Department of Chemistry, real-time observations of the locational changes in all of the atoms in a molecule by Professor Hyotcherl Ihee from the Department of Chemistry, and an investigation on memory retention mechanisms after synapse removal from an astrocyte by Professor Won-Suk Chung from the Department of Biological Sciences.
Awardees from the engineering field were a wearable robot for paraplegics with the world’s best functionality and walking speed by Professor Kyoungchul Kong from the Department of Mechanical Engineering, fair machine learning by Professor Changho Suh from the School of Electrical Engineering, and a generative adversarial networks processing unit (GANPU), an AI semiconductor that can learn from even mobiles by processing multiple and deep networks by Professor Hoi-Jun Yoo from the School of Electrical Engineering.
Others selected as part of the ten research studies were the development of epigenetic reprogramming technology in tumour by Professor Pilnam Kim from the Department of Bio and Brain Engineering, the development of an original technology for reverse cell aging by Professor Kwang-Hyun Cho from the Department of Bio and Brain Engineering, a heterogeneous metal element catalyst for atmospheric purification by Professor Hyunjoo Lee from the Department of Chemical and Biomolecular Engineering, and the Mobile Clinic Module (MCM): a negative pressure ward for epidemic hospitals by Professor Taek-jin Nam (reported at the Wall Street Journal) from the Department of Industrial Design.
2021.05.31 View 12649 -
Simulations Open a New Way to Reverse Cell Aging
Turning off a newly identified enzyme could reverse a natural aging process in cells.
Research findings by a KAIST team provide insight into the complex mechanism of cellular senescence and present a potential therapeutic strategy for reducing age-related diseases associated with the accumulation of senescent cells.
Simulations that model molecular interactions have identified an enzyme that could be targeted to reverse a natural aging process called cellular senescence. The findings were validated with laboratory experiments on skin cells and skin equivalent tissues, and published in the Proceedings of the National Academy of Sciences (PNAS).
“Our research opens the door for a new generation that perceives aging as a reversible biological phenomenon,” says Professor Kwang-Hyun Cho of the Department of Bio and Brain engineering at the Korea Advanced Institute of Science and Technology (KAIST), who led the research with colleagues from KAIST and Amorepacific Corporation in Korea.
Cells respond to a variety of factors, such as oxidative stress, DNA damage, and shortening of the telomeres capping the ends of chromosomes, by entering a stable and persistent exit from the cell cycle. This process, called cellular senescence, is important, as it prevents damaged cells from proliferating and turning into cancer cells. But it is also a natural process that contributes to aging and age-related diseases. Recent research has shown that cellular senescence can be reversed. But the laboratory approaches used thus far also impair tissue regeneration or have the potential to trigger malignant transformations.
Professor Cho and his colleagues used an innovative strategy to identify molecules that could be targeted for reversing cellular senescence. The team pooled together information from the literature and databases about the molecular processes involved in cellular senescence. To this, they added results from their own research on the molecular processes involved in the proliferation, quiescence (a non-dividing cell that can re-enter the cell cycle) and senescence of skin fibroblasts, a cell type well known for repairing wounds. Using algorithms, they developed a model that simulates the interactions between these molecules. Their analyses allowed them to predict which molecules could be targeted to reverse cell senescence.
They then investigated one of the molecules, an enzyme called PDK1, in incubated senescent skin fibroblasts and three-dimensional skin equivalent tissue models. They found that blocking PDK1 led to the inhibition of two downstream signalling molecules, which in turn restored the cells’ ability to enter back into the cell cycle. Notably, the cells retained their capacity to regenerate wounded skin without proliferating in a way that could lead to malignant transformation.
The scientists recommend investigations are next done in organs and organisms to determine the full effect of PDK1 inhibition. Since the gene that codes for PDK1 is overexpressed in some cancers, the scientists expect that inhibiting it will have both anti-aging and anti-cancer effects.
-Profile
Professor Kwang-Hyun Cho
Laboratory for Systems Biology and Bio-Inspired Engineering
http://sbie.kaist.ac.kr
Department of Bio and Brain Engineering
KAIST
2020.11.26 View 10980