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A Single, Master Switch for Sugar Levels?
When a fly eats sugar, a single brain cell sends simultaneous messages to stimulate one hormone and inhibit another to control glucose levels in the body. Further research into this control system with remarkable precision could shed light on the neural mechanisms of diabetes and obesity in humans . A single neuron appears to monitor and control sugar levels in the fly body, according to research published this week in Nature. This new insight into the mechanisms in the fly brain that maintain a balance of two key hormones controlling glucose levels, insulin and glucagon, can provide a framework for understanding diabetes and obesity in humans. Neurons that sense and respond to glucose were identified more than 50 years ago, but what they do in our body has remained unclear. Researchers at the Korea Advanced Institute of Science and Technology (KAIST) and New York University School of Medicine have now found a single “glucose-sensing neuron” that appears to be the master controller in Drosophila, the vinegar fly, for maintaining an ideal glucose balance, called homeostasis. Professor Greg Seong-Bae Suh, Dr. Yangkyun Oh and colleagues identified a key neuron that is excited by glucose, which they called CN neuron. This CN neuron has a unique shape – it has an axon (which is used to transmit information to downstream cells) that is bifurcated. One branch projects to insulin-producing cells, and sends a signal triggering the secretion of the insulin equivalent in flies. The other branch projects to glucagon-producing cells and sends a signal inhibiting the secretion of the glucagon equivalent. When flies consume food, the levels of glucose in their body increase; this excites the CN neuron, which fires the simultaneous signals to stimulate insulin and inhibit glucagon secretion, thereby maintaining the appropriate balance between the hormones and sugar in the blood. The researchers were able to see this happening in the brain in real time by using a combination of cutting-edge fluorescent calcium imaging technology, as well as measuring hormone and sugar levels and applying highly sophisticated molecular genetic techniques. When flies were not fed, however, the researchers observed a reduction in the activity of CN neuron, a reduction in insulin secretion and an increase in glucagon secretion. These findings indicate that these key hormones are under the direct control of the glucose-sensing neuron. Furthermore, when they silenced the CN neuron rendering dysfunctional CN neuron in flies, these animals experienced an imbalance, resulting in hyperglycemia – high levels of sugars in the blood, similar to what is observed in diabetes in humans. This further suggests that the CN neuron is critical to maintaining glucose homeostasis in animals. While further research is required to investigate this process in humans, Suh notes this is a significant step forward in the fields of both neurobiology and endocrinology. “This work lays the foundation for translational research to better understand how this delicate regulatory process is affected by diabetes, obesity, excessive nutrition and diets high in sugar,” Suh said. Profile: Greg Seong-Bae Suh email@example.com Professor Department of Biological Sciences KAIST (Figure: A single glucose-excited CN neuron extends bifurcated axonal branches, one of which innervates insulin producing cells and stimulates their activity an the other axonal branch projects to glucagon producing cells and inhibits their activity.)
Image Analysis to Automatically Quantify Gender Bias in Movies
Many commercial films worldwide continue to express womanhood in a stereotypical manner, a recent study using image analysis showed. A KAIST research team developed a novel image analysis method for automatically quantifying the degree of gender bias in films. The ‘Bechdel Test’ has been the most representative and general method of evaluating gender bias in films. This test indicates the degree of gender bias in a film by measuring how active the presence of women is in a film. A film passes the Bechdel Test if the film (1) has at least two female characters, (2) who talk to each other, and (3) their conversation is not related to the male characters. However, the Bechdel Test has fundamental limitations regarding the accuracy and practicality of the evaluation. Firstly, the Bechdel Test requires considerable human resources, as it is performed subjectively by a person. More importantly, the Bechdel Test analyzes only a single aspect of the film, the dialogues between characters in the script, and provides only a dichotomous result of passing the test, neglecting the fact that a film is a visual art form reflecting multi-layered and complicated gender bias phenomena. It is also difficult to fully represent today’s various discourse on gender bias, which is much more diverse than in 1985 when the Bechdel Test was first presented. Inspired by these limitations, a KAIST research team led by Professor Byungjoo Lee from the Graduate School of Culture Technology proposed an advanced system that uses computer vision technology to automatically analyzes the visual information of each frame of the film. This allows the system to more accurately and practically evaluate the degree to which female and male characters are discriminatingly depicted in a film in quantitative terms, and further enables the revealing of gender bias that conventional analysis methods could not yet detect. Professor Lee and his researchers Ji Yoon Jang and Sangyoon Lee analyzed 40 films from Hollywood and South Korea released between 2017 and 2018. They downsampled the films from 24 to 3 frames per second, and used Microsoft’s Face API facial recognition technology and object detection technology YOLO9000 to verify the details of the characters and their surrounding objects in the scenes. Using the new system, the team computed eight quantitative indices that describe the representation of a particular gender in the films. They are: emotional diversity, spatial staticity, spatial occupancy, temporal occupancy, mean age, intellectual image, emphasis on appearance, and type and frequency of surrounding objects. Figure 1. System Diagram Figure 2. 40 Hollywood and Korean Films Analyzed in the Study According to the emotional diversity index, the depicted women were found to be more prone to expressing passive emotions, such as sadness, fear, and surprise. In contrast, male characters in the same films were more likely to demonstrate active emotions, such as anger and hatred. Figure 3. Difference in Emotional Diversity between Female and Male Characters The type and frequency of surrounding objects index revealed that female characters and automobiles were tracked together only 55.7 % as much as that of male characters, while they were more likely to appear with furniture and in a household, with 123.9% probability. In cases of temporal occupancy and mean age, female characters appeared less frequently in films than males at the rate of 56%, and were on average younger in 79.1% of the cases. These two indices were especially conspicuous in Korean films. Professor Lee said, “Our research confirmed that many commercial films depict women from a stereotypical perspective. I hope this result promotes public awareness of the importance of taking prudence when filmmakers create characters in films.” This study was supported by KAIST College of Liberal Arts and Convergence Science as part of the Venture Research Program for Master’s and PhD Students, and will be presented at the 22nd ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW) on November 11 to be held in Austin, Texas. Publication: Ji Yoon Jang, Sangyoon Lee, and Byungjoo Lee. 2019. Quantification of Gender Representation Bias in Commercial Films based on Image Analysis. In Proceedings of the 22nd ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW). ACM, New York, NY, USA, Article 198, 29 pages. https://doi.org/10.1145/3359300 Link to download the full-text paper: https://files.cargocollective.com/611692/cscw198-jangA--1-.pdf Profile: Prof. Byungjoo Lee, MD, PhD firstname.lastname@example.org http://kiml.org/ Assistant Professor Graduate School of Culture Technology (CT) Korea Advanced Institute of Science and Technology (KAIST) https://www.kaist.ac.kr Daejeon 34141, Korea Profile: Ji Yoon Jang, M.S. email@example.com Interactive Media Lab Graduate School of Culture Technology (CT) Korea Advanced Institute of Science and Technology (KAIST) https://www.kaist.ac.kr Daejeon 34141, Korea Profile: Sangyoon Lee, M.S. Candidate firstname.lastname@example.org Interactive Media Lab Graduate School of Culture Technology (CT) Korea Advanced Institute of Science and Technology (KAIST) https://www.kaist.ac.kr Daejeon 34141, Korea (END)
A Mathematical Model Reveals Long-Distance Cell Communication Mechanism
How can tens of thousands of people in a large football stadium all clap together with the same beat even though they can only hear the people near them clapping? A combination of a partial differential equation and a synthetic circuit in microbes answers this question. An interdisciplinary collaborative team of Professor Jae Kyoung Kim at KAIST, Professor Krešimir Josić at the University of Houston, and Professor Matt Bennett at Rice University has identified how a large community can communicate with each other almost simultaneously even with very short distance signaling. The research was reported at Nature Chemical Biology. Cells often communicate using signaling molecules, which can travel only a short distance. Nevertheless, the cells can also communicate over large distances to spur collective action. The team revealed a cell communication mechanism that quickly forms a network of local interactions to spur collective action, even in large communities. The research team used an engineered transcriptional circuit of combined positive and negative feedback loops in E. coli, which can periodically release two types of signaling molecules: activator and repressor. As the signaling molecules travel over a short distance, cells can only talk to their nearest neighbors. However, cell communities synchronize oscillatory gene expression in spatially extended systems as long as the transcriptional circuit contains a positive feedback loop for the activator. Professor Kim said that analyzing and understanding such high-dimensional dynamics was extremely difficult. He explained, “That’s why we used high-dimensional partial differential equation to describe the system based on the interactions among various types of molecules.” Surprisingly, the mathematical model accurately simulates the synthesis of the signaling molecules in the cell and their spatial diffusion throughout the chamber and their effect on neighboring cells. The team simplified the high-dimensional system into a one-dimensional orbit, noting that the system repeats periodically. This allowed them to discover that cells can make one voice when they lowered their own voice and listened to the others. “It turns out the positive feedback loop reduces the distance between moving points and finally makes them move all together. That’s why you clap louder when you hear applause from nearby neighbors and everyone eventually claps together at almost the same time,” said Professor Kim. Professor Kim added, “Math is a powerful as it simplifies complex thing so that we can find an essential underlying property. This finding would not have been possible without the simplification of complex systems using mathematics." The National Institutes of Health, the National Science Foundation, the Robert A. Welch Foundation, the Hamill Foundation, the National Research Foundation of Korea, and the T.J. Park Science Fellowship of POSCO supported the research. (Figure: Complex molecular interactions among microbial consortia is simplified as interactions among points on a limit cycle (right).)
Two Professors Recognized for the National R&D Excellence 100
< Professor Haeng-Ki Lee (left) and Professor Jeong-Ho Lee (right) > Two KAIST professors were listed among the 2019 National R&D Excellence 100 announced by the Ministry of Science and ICT and the Korea Institute of S&T Evaluation and Planning. Professor Haeng-Ki Lee from the Department of Civil and Environmental Engineering was recognized in the field of mechanics and materials for his research on developing new construction materials through the convergence of nano- and biotechnologies. In the field of life and marine science, Professor Jeong-Ho Lee from the Graduate School of Medical Science and Engineering was lauded for his research of diagnostic tools and therapies for glioblastoma and pediatric brain tumors. A certificate from the Minister of Ministry of Science and ICT will be conferred to these two professors, and their names will be inscribed on a special 2019 National R&D Excellence 100 plaque to celebrate their achievements. The professors will also be given privileges during the process of new R&D project selection. (END)
Object Identification and Interaction with a Smartphone Knock
(Professor Lee (far right) demonstrate 'Knocker' with his students.) A KAIST team has featured a new technology, “Knocker”, which identifies objects and executes actions just by knocking on it with the smartphone. Software powered by machine learning of sounds, vibrations, and other reactions will perform the users’ directions. What separates Knocker from existing technology is the sensor fusion of sound and motion. Previously, object identification used either computer vision technology with cameras or hardware such as RFID (Radio Frequency Identification) tags. These solutions all have their limitations. For computer vision technology, users need to take pictures of every item. Even worse, the technology will not work well in poor lighting situations. Using hardware leads to additional costs and labor burdens. Knocker, on the other hand, can identify objects even in dark environments only with a smartphone, without requiring any specialized hardware or using a camera. Knocker utilizes the smartphone’s built-in sensors such as a microphone, an accelerometer, and a gyroscope to capture a unique set of responses generated when a smartphone is knocked against an object. Machine learning is used to analyze these responses and classify and identify objects. The research team under Professor Sung-Ju Lee from the School of Computing confirmed the applicability of Knocker technology using 23 everyday objects such as books, laptop computers, water bottles, and bicycles. In noisy environments such as a busy café or on the side of a road, it achieved 83% identification accuracy. In a quiet indoor environment, the accuracy rose to 98%. The team believes Knocker will open a new paradigm of object interaction. For instance, by knocking on an empty water bottle, a smartphone can automatically order new water bottles from a merchant app. When integrated with IoT devices, knocking on a bed’s headboard before going to sleep could turn off the lights and set an alarm. The team suggested and implemented 15 application cases in the paper, presented during the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2019) held in London last month. Professor Sung-Ju Lee said, “This new technology does not require any specialized sensor or hardware. It simply uses the built-in sensors on smartphones and takes advantage of the power of machine learning. It’s a software solution that everyday smartphone users could immediately benefit from.” He continued, “This technology enables users to conveniently interact with their favorite objects.” The research was supported in part by the Next-Generation Information Computing Development Program through the National Research Foundation of Korea funded by the Ministry of Science and ICT and an Institute for Information & Communications Technology Promotion (IITP) grant funded by the Ministry of Science and ICT. Figure: An example knock on a bottle. Knocker identifies the object by analyzing a unique set of responses from the knock, and automatically launches a proper application or service.
KAIST to Transfer Core Tech to Domestic Companies amid Japan's Export Curbs
< Associate Vice President Kyung-Cheol Choi of the Office of University-Industry Cooperation (OUIC) at KAIST > KAIST will transfer four core technologies related to materials, parts, and equipment to domestic companies to help them combat the latest export curbs triggered by Korea’s removal from Japan’s ‘white list’ of preferential trade partners. In addition, KAIST’s five patented technologies in the field of artificial intelligence (AI) and materials and parts will also be transferred to the companies in order to reduce the reliance on Japan and achieve technological independence through the ‘localization’ of key technologies. KAIST announced these university-industry cooperation promotion plans at the ‘2019 KAIST Core Tech Transfer Day Conference’ held in Seoul on September 17. More than 200 entrepreneurs and investors attended the briefing and on-site consulting sessions delivered by nine KAIST professors who led the development of the technologies. The four technologies were presented at the conference as those that can replace Japanese technologies subject to the export curbs. They include: 1. ‘Transparent fluorinated polyimide with low thermal expansion’ developed by Professor Sang-Youl Kim of the Department of Chemistry 2. ‘A non-destructive electromagnetic performance testing system’ developed by Professor Jung-Ryul Lee of the Department of Aerospace Engineering 3. ‘A nanotechnology-based electrode material for use in advanced secondary batteries’ developed by Professor Do-Kyung Kim of the Department of Materials Science and Engineering 4. ‘A high-resolution photoresist’ developed by Professor Emeritus Jin-Baek Kim of the Department of Chemistry. Of particular interest is the non-destructive electromagnetic performance testing system technology developed by Professor Jung-Ryul Lee. This new cost-effective technology enables tests that were impossible to carry out using conventional technologies and yields a cost reduction of more than 50 percent compared to foreign technologies. By introducing Professor Do-Kyung Kim’s new electrode material technology, the efficiency of electric vehicles can be increased. As this technology uses relatively low-cost sodium ion batteries, industries can prepare for the possible jump from the more expensive lithium batteries currently being used. Another five patented AI and materials and parts technologies disclosed at the conference include: 1. ‘Enhanced HTTP adaptive streaming with CNN-based super-resolution’ developed by Professor Dong-soo Han of the School of Electrical Engineering 2. ‘Method and apparatus of brain-computer interface design for estimating choice behavior and decision strategy’ developed by Professor Sang-Wan Lee of the Department of Bio and Brain Engineering 3. ‘Eco-friendly fabrication of metal oxide nanoparticles and fabrication of non-toxic polymer sunscreen ingredients by electron irradiation’ developed by Professor Sung-Oh Cho of the Department of Nuclear and Quantum Engineering 4. ‘High-density nanofiber yarn-based coloricmetric gas sensors’ developed by Professor Il-Doo Kim of the Department of Materials Science and Engineering 5. ‘Silicon-pocket energy storage electrode with high energy density and its manufacturing technology’ developed by Professor Jeung-Ku Kang of the Graduate school of EEWS. The patented nanofiber-based coloricmetric gas sensor technology developed by Professor Il-Doo Kim allows for the diagnosis of diseases by only using the patient’s respiration. Due to its high productivity and processability, it is expected to be applied to various fields in the fast-growing disease diagnosis sensor market, which includes mobile devices and wearable sensors. Moreover, Professor Dong-soo Han’s patented adaptive streaming technology attracted attention along with the ever-growing Over The Top (OTT) and Video On Demand (VOD) service markets, since it has significant potential for improving the streaming quality of videos and reducing costs for video providers. Professor Kyung-Cheol Choi, the Associate Vice President of the Office of University-Industry Cooperation (OUIC) at KAIST, said, “KAIST OUIC and KAIST Advisors on Materials and Parts (KAMP) have been working tirelessly to help Korean companies cope with the recent Japanese export restrictions. KAIST’s efforts will enhance the competitiveness and growth of the Korean industry and economy, turning this national crisis into opportunity.” (END)
Sungjoon Park Named Google PhD Fellow
PhD candidate Sungjoon Park from the School of Computing was named a 2019 Google PhD Fellow in the field of natural language processing. The Google PhD fellowship program has recognized and supported outstanding graduate students in computer science and related fields since 2009. Park is one of three Korean students chosen as the recipients of Google Fellowships this year. A total of 54 students across the world in 12 fields were awarded this fellowship. Park’s research on computational psychotherapy using natural language processing (NLP) powered by machine learning earned him this year’s fellowship. He presented of learning distributed representations in Korean and their interpretations during the 2017 Annual Conference of the Association for Computational Linguistics and the 2018 Conference on Empirical Methods in Natural Language Processing. He also applied machine learning-based natural language processing into computational psychotherapy so that a trained machine learning model could categorize client's verbal responses in a counseling dialogue. This was presented at the Annual Conference of the North American Chapter of the Association for Computational Linguistics. More recently, he has been developing on neural response generation model and the prediction and extraction of complex emotion in text, and computational psychotherapy applications.
Algorithm Identifies Optimal Pairs for Composing Metal-Organic Frameworks
The integration of metal-organic frameworks (MOFs) and other metal nanoparticles has increasingly led to the creation of new multifunctional materials. Many researchers have integrated MOFs with other classes of materials to produce new structures with synergetic properties. Despite there being over 70,000 collections of synthesized MOFs that can be used as building blocks, the precise nature of the interaction and the bonding at the interface between the two materials still remains unknown. The question is how to sort out the right matching pairs out of 70,000 MOFs. An algorithmic study published in Nature Communications by a KAIST research team presents a clue for finding the perfect pairs. The team, led by Professor Ji-Han Kim from the Department of Chemical and Biomolecular Engineering, developed a joint computational and experimental approach to rationally design MOF@MOFs, a composite of MOFs where an MOF is grown on a different MOF. Professor Kim’s team, in collaboration with UNIST, noted that the metal node of one MOF can coordinately bond with the linker of a different MOF and the precisely matched interface configurations at atomic and molecular levels can enhance the likelihood of synthesizing MOF@MOFs. They screened thousands of MOFs and identified optimal MOF pairs that can seamlessly connect to one another by taking advantage of the fact that the metal node of one MOF can form coordination bonds with the linkers of the second MOF. Six pairs predicted from the computational algorithm successfully grew into single crystals. This computational workflow can readily extend into other classes of materials and can lead to the rapid exploration of the composite MOFs arena for accelerated materials development. Even more, the workflow can enhance the likelihood of synthesizing MOF@MOFs in the form of large single crystals, and thereby demonstrated the utility of rationally designing the MOF@MOFs. This study is the first algorithm for predicting the synthesis of composite MOFs, to the best of their knowledge. Professor Kim said, “The number of predicted pairs can increase even more with the more general 2D lattice matching, and it is worth investigating in the future.” This study was supported by Samsung Research Funding & Incubation Center of Samsung Electronics. (Figure: An example of a rationally synthesized MOF@MOFs (cubic HKUST-1@MOF-5 ))
Distinguished Professor Sukbok Chang Donates His Prize Money
The honoree of the 2019 Korea Best Scientist and Technologist Award, Distinguished Professor Sukbok Chang donated his prize money of one hundred million KRW to the Chemistry Department Scholarship Fund and the Lyu Keun-Chul Sports Complex Management Fund during a donation ceremony last week. Professor Chang won the award last month in recognition of his pioneering achievements and lifetime contributions to the development of carbon-hydrogen activation strategies, especially for carbon-carbon, carbon-nitrogen, and carbon-oxygen formations. Professor Chang, a world renowned chemist, has been recognized for his highly selective catalytic systems, allowing the controlled defunctionalization of bio-derived platform substrates under mild conditions and opening a new avenue for the utilization of biomass-derived platform chemicals. “All my achievements are the results of my students’ hard work and dedication. I feel very fortunate to have such talented team members. I want to express my sincere gratitude for such a great research environment that we have worked together in so far,” said Professor Chang at the ceremony. KAIST President Sung-Chul Shin said, “Not only will Professor Chang’s donation make a significant contribution to the Department of Chemistry, but also to the improvement of the Lyu Keun-Chul Sports Complex’s management, which directly links to the health and welfare of the KAIST community.” Professor Chang currently holds the position of distinguished professor at KAIST and director of the Center for Catalytic Hydrocarbon Functionalizations in the Institute for Basic Science (IBS). He previously received the Kyung-Ahm Academic Award in 2013 and the Korea Toray Science Award in 2018. All these prize money also went to the school. (END)
Professor Sang Gyu Kim Receives Yeochon Award for Ecology
Professor Sang-Gyu Kim from the Department of Biological Sciences was selected as the winner of the 12th Yeochon Award for Ecology presented by the Yeochon Association for Ecological Research. The award was conferred on August 13 in Jeju at the annual conference co-hosted by the Ecological Society of Korea and the Yeochon Association for Ecological Research. Professor Kim received 10 million KRW in prize money. Professor Kim was recognized for his achievements and contributions in studying herbivorous insects ‘rice weevils’ and their host plant ‘wild tobacco’, especially for having explored the known facts in traditional ecology at the molecular level. His findings are presented in his paper titled ‘Trichobaris weevils distinguish amongst toxic host plants by sensing volatiles that do not affect larval performance’ published in Molecular Ecology in July 2016. Furthermore, Professor Kim’s research team is continuing their work to identify the ecological functions of plant metabolites as well as interactions between flowers and insect vectors at the molecular level. In doing so, the team edits genes in various plant species using the latest gene editing technology. The Yeochon Award for Ecology was first established in 2005 with funds donated by a senior ecologist, the late Honorary Professor Joon-Ho Kim of Seoul National University. The award is named after the professor’s pen name “Yeochon” and is intended to encourage promising next-generation ecologists to produce outstanding research achievements in the field of basic ecology. Professor Kim said, “I will take this award as encouragement to continue taking challenging risks to observe ecological phenomenon from a new perspective. I will continue my research with my students with joy and enthusiasm.”
Enhanced Natural Gas Storage to Help Reduce Global Warming
< Professor Atilhan (left) and Professor Yavuz (right) > Researchers have designed plastic-based materials that can store natural gas more effectively. These new materials can not only make large-scale, cost-effective, and safe natural gas storage possible, but further hold a strong promise for combating global warming. Natural gas (predominantly methane) is a clean energy alternative. It is stored by compression, liquefaction, or adsorption. Among these, adsorbed natural gas (ANG) storage is a more efficient, cheaper, and safer alternative to conventional compressed natural gas (CNG) and liquefied natural gas (LNG) storage approaches that have drawbacks such as low storage efficiency, high costs, and safety concerns. However, developing adsorptive materials that can more fully exploit the advantages of ANG storage has remained a challenging task. A KAIST research team led by Professor Cafer T. Yavuz from the Graduate School of Energy, Environment, Water, and Sustainability (EEWS), in collaboration with Professor Mert Atilhan’s group from Texas A&M University, synthesized 29 unique porous polymeric structures with inherent flexibility, and tested their methane gas uptake capacity at high pressures. These porous polymers had varying synthetic complexities, porosities, and morphologies, and the researchers subjected each porous polymer to pure methane gas under various conditions to study the ANG performances. Of these 29 distinct chemical structures, COP-150 was particularly noteworthy as it achieved a high deliverable gravimetric methane working capacity when cycled between 5 and 100 bar at 273 K, which is 98% of the total uptake capacity. This result surpassed the target set by the United States Department of Energy (US DOE). COP-150 is the first ever structure to fulfil both the gravimetric and volumetric requirements of the US DOE for successful vehicular use, and the total cost to produce the COP-150 adsorbent was only 1 USD per kilogram. COP-150 can be produced using freely available and easily accessible plastic materials, and moreover, its synthesis takes place at room temperature, open to the air, and no previous purification of the chemicals is required. The pressure-triggered flexible structure of COP-150 is also advantageous in terms of the total working capacity of deliverable methane for real applications. The research team believed that the increased pressure flexes the network structure of COP-150 showing “swelling” behavior, and suggested that the flexibility provides rapid desorption and thermal management, while the hydrophobicity and the nature of the covalently bonded framework allow these promising materials to tolerate harsh conditions. This swelling mechanism of expansion-contraction solves two other major issues, the team noted. Firstly, when using adsorbents based on such a mechanism, unsafe pressure spikes that may occur due to temperature swings can be eliminated. In addition, contamination can also be minimized, since the adsorbent remains contracted when no gas is stored. Professor Yavuz said, “We envision a whole host of new designs and mechanisms to be developed based on our concept. Since natural gas is a much cleaner fuel than coal and petroleum, new developments in this realm will help switching to the use of less polluting fuels.” Professor Atilhan agreed the most important impact of their research is on the environment. “Using natural gas more than coal and petroleum will significantly reduce greenhouse gas emissions. We believe, one day, we might see vehicles equipped with our materials that are run by a cleaner natural gas fuel,” he added. This study, reported in Nature Energy on July 8, was supported by National Research Foundation of Korea (NRF) grants ( NRF-2016R1A2B4011027, NRF-2017M3A7B4042140, and NRF-2017M3A7B4042235). < Suggested chemical structure of COP-150 > < Initial ingredients (left) and final product (right) of COP-150 synthesis > < Comparison of highest reported volumetric working capacities > (END)
Manipulating Brain Cells by Smartphone
Researchers have developed a soft neural implant that can be wirelessly controlled using a smartphone. It is the first wireless neural device capable of indefinitely delivering multiple drugs and multiple colour lights, which neuroscientists believe can speed up efforts to uncover brain diseases such as Parkinson’s, Alzheimer’s, addiction, depression, and pain. A team under Professor Jae-Woong Jeong from the School of Electrical Engineering at KAIST and his collaborators have invented a device that can control neural circuits using a tiny brain implant controlled by a smartphone. The device, using Lego-like replaceable drug cartridges and powerful, low-energy Bluetooth, can target specific neurons of interest using drugs and light for prolonged periods. This study was published in Nature Biomedical Engineering. “This novel device is the fruit of advanced electronics design and powerful micro and nanoscale engineering,” explained Professor Jeong. “We are interested in further developing this technology to make a brain implant for clinical applications.” This technology significantly overshadows the conventional methods used by neuroscientists, which usually involve rigid metal tubes and optical fibers to deliver drugs and light. Apart from limiting the subject’s movement due to bulky equipment, their relatively rigid structure causes lesions in soft brain tissue over time, therefore making them not suitable for long-term implantation. Although some efforts have been made to partly mitigate adverse tissue response by incorporating soft probes and wireless platforms, the previous solutions were limited by their inability to deliver drugs for long periods of time as well as their bulky and complex control setups. To achieve chronic wireless drug delivery, scientists had to solve the critical challenge of the exhaustion and evaporation of drugs. To combat this, the researchers invented a neural device with a replaceable drug cartridge, which could allow neuroscientists to study the same brain circuits for several months without worrying about running out of drugs. These ‘plug-n-play’ drug cartridges were assembled into a brain implant for mice with a soft and ultrathin probe (with the thickness of a human hair), which consisted of microfluidic channels and tiny LEDs (smaller than a grain of salt), for unlimited drug doses and light delivery. Controlled with an elegant and simple user interface on a smartphone, neuroscientists can easily trigger any specific combination or precise sequencing of light and drug delivery in any implanted target animal without the need to be physically inside the laboratory. Using these wireless neural devices, researchers can also easily setup fully automated animal studies where the behaviour of one animal could affect other animals by triggering light and/or drug delivery. “The wireless neural device enables chronic chemical and optical neuromodulation that has never been achieved before,” said lead author Raza Qazi, a researcher with KAIST and the University of Colorado Boulder. This work was supported by grants from the National Research Foundation of Korea, US National Institute of Health, National Institute on Drug Abuse, and Mallinckrodt Professorship. (A neural implant with replaceable drug cartridges and Bluetooth low-energy can target specific neurons .) (Micro LED controlling using smartphone application)
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