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When the Shewanella oneidensis bacterium “breathes” in certain metal and sulfur compounds anaerobically, the way an aerobic organism would process oxygen, it produces materials that could be used to enhance electronics, electrochemical energy storage, and drug-delivery devices.

The ability of this bacterium to produce molybdenum disulfide—a material that is able to transfer electrons easily, like graphene—is the focus of research published in Biointerphases by a team of engineers from Rensselaer Polytechnic Institute.

“This has some serious potential if we can understand this process and control aspects of how the bacteria are making these and other materials,” said Shayla Sawyer, an associate professor of electrical, computer, and systems engineering at Rensselaer.

Quantum computers have enormous potential for calculations using novel algorithms and involving amounts of data far beyond the capacity of today’s supercomputers. While such computers have been built, they are still in their infancy and have limited applicability for solving complex problems in materials science and chemistry. For example, they only permit the simulation of the properties of a few atoms for materials research.

Scientists at the U.S. Department of Energy’s (DOE) Argonne National Laboratory and the University of Chicago (UChicago) have developed a method paving the way to using quantum computers to simulate realistic molecules and complex materials, whose description requires hundreds of atoms.

The research team is led by Giulia Galli, director of the Midwest Integrated Center for Computational Materials (MICCoM), a group leader in Argonne’s Materials Science division and a member of the Center for Molecular Engineering at Argonne. Galli is also the Liew Family Professor of Electronic Structure and Simulations in the Pritzker School of Molecular Engineering and a Professor of Chemistry at UChicago. She worked on this project with assistant scientist Marco Govoni and graduate student He Ma, both part of Argonne’s Materials Science division and UChicago.

Summary: New artificial intelligence technology can accurately predict how any chemical is going to smell to humans.

Source: UCR

A pair of researchers at the University of California, Riverside, has used machine learning to understand what a chemical smells like — a research breakthrough with potential applications in the food flavor and fragrance industries.

Hokkaido University researchers have found a soft and wet material that can memorize, retrieve, and forget information, much like the human brain. They report their findings in the journal Proceedings of the National Academy of Sciences (PNAS).

The human brain learns things, but tends to forget them when the information is no longer important. Recreating this dynamic memory process in manmade materials has been a challenge. Hokkaido University researchers now report a hydrogel that mimics the dynamic memory function of the brain: encoding information that fades with time depending on the memory intensity.

Hydrogels are flexible materials composed of a large percentage of water—in this case about 45%—along with other chemicals that provide a scaffold-like structure to contain the water. Professor Jian Ping Gong, Assistant Professor Kunpeng Cui and their students and colleagues in Hokkaido University’s Institute for Chemical Reaction Design and Discovery (WPI-ICReDD) are seeking to develop hydrogels that can serve biological functions.

Scientists discover that oxytocin could be used to treat cognitive disorder like Alzheimer’s disease.

Alzheimer’s disease is a progressive disorder in which the nerve cells (neurons) in a person’s brain and the connections among them degenerate slowly, causing severe memory loss, intellectual deficiencies, and deterioration in motor skills and communication. One of the main causes of Alzheimer’s is the accumulation of a protein called amyloid β (Aβ) in clusters around neurons in the brain, which hampers their activity and triggers their degeneration.

Studies in animal models have found that increasing the aggregation of Aβ in the hippocampus—the brain’s main learning and memory center—causes a decline in the signal transmission potential of the neurons therein. This degeneration affects a specific trait of the neurons, called ‘synaptic plasticity,’ which is the ability of synapses (the site of signal exchange between neurons) to adapt to an increase or decrease in signaling activity over time. Synaptic plasticity is crucial to the development of learning and cognitive functions in the hippocampus. Thus, Aβ and its role in causing cognitive memory and deficits have been the focus of most research aimed at finding treatments for Alzheimer’s.

Now, advancing this research effort, a team of scientists from Japan, led by Professor Akiyoshi Saitoh from the Tokyo University of Science, has looked at oxytocin, a hormone conventionally known for its role in the female reproductive system and in inducing the feelings of love and well-being. “Oxytocin was recently found to be involved in regulating learning and memory performance, but so far, no previous study deals with the effect of oxytocin on Aβ-induced cognitive impairment,” Prof Saitoh says. Realizing this, Prof Saitoh’s group set out to connect the dots. Their findings are published in Biochemical and Biophysical Research Communication.

Continue reading “‘Love hormone’ oxytocin could be used to treat cognitive disorders like Alzheimer’s” »

Scientists from the University of Missouri, the University of Illinois and Yale University have demonstrated that a combination of pencils and paper could be used to create on-skin bioelectronic devices that might be used to monitor personal health. They’ve fabricated and evaluated a rich variety of pencil-paper-based bioelectronic devices, ranging from biophysical sensors and sweat biochemical sensors to thermal stimulators, ambient humidity energy harvesters, and transdermal drug-delivery systems.

Spectroscopy is the use of light to analyze physical objects and biological samples. Different kinds of light can provide different kinds of information. Vacuum ultraviolet light is useful as it can aid people in a broad range of research fields, but generation of that light has been difficult and expensive. Researchers created a new device to efficiently generate this special kind of light using an ultrathin film with nanoscale perforations.

The wavelengths of light you see with your eyes constitute a mere fraction of the possible wavelengths of light that exist. There’s infrared light which you can feel in the form of heat, or see if you happen to be a snake, that has a longer wavelength than visible light. At the opposite end is ultraviolet (UV) light which you can use to produce vitamin D in your skin, or see if you happen to be a bee. These and other forms of light have many uses in science.

Continue reading “New Photonic Crystal Light Converter: Powerful Tool for Observation in Physics and Life Sciences” »

During collective cell migration, directional information is transmitted from a leading edge to the follower cells as a form of ERK activation waves. Hino et al. demonstrate that a mechanochemical feedback loop coupling cell deformation and ERK activation enables sustained propagation of the directional information over a tissue-scale expanse.

Proteins are essential to the life of cells, carrying out complex tasks and catalyzing chemical reactions. Scientists and engineers have long sought to harness this power by designing artificial proteins that can perform new tasks, like treat disease, capture carbon, or harvest energy, but many of the processes designed to create such proteins are slow and complex, with a high failure rate.

In a breakthrough that could have implications across the healthcare, agriculture, and energy sectors, a team lead by researchers in the Pritzker School of Molecular Engineering (PME) at the University of Chicago has developed an artificial intelligence-led process that uses big data to design new proteins.

By developing machine-learning models that can review protein information culled from genome databases, the researchers found relatively simple design rules for building artificial proteins. When the team constructed these artificial proteins in the lab, they found that they performed chemistries so well that they rivaled those found in nature.