Uncovering the organic (carbon-based) chemistry in interstellar space is central to understanding the chemistry of the universe in addition to the origin of life on Earth and the possibilities for life elsewhere.

The list of organic molecules detected in space and understanding how they could be interacting is steadily expanding due to ever-improving direct observations. But laboratory experiments unraveling the complex processes can also offer significant clues. Researchers at Hokkaido University, with colleagues at The University of Tokyo, Japan, report new lab-based insights into the central role of carbon atoms on interstellar ice grains in the journal Nature Astronomy.

Some of the most complex organic molecules in space are thought to be produced on the surface of interstellar ice gains at very low temperatures. Ice grains that are suitable for this purpose are known to be abundant throughout the universe.

All organic molecules are based on a skeleton of bonded carbon atoms. Most carbon atoms originally formed through nuclear fusion reactions in stars, eventually getting dispersed into interstellar space when the stars died in supernovae explosions. But to form complex organic molecules, the carbon atoms need a mechanism to come together on the surface of the ice grains to encounter partner atoms and form chemical bonds with them. The new research suggests a feasible mechanism.

“In our studies, recreating feasible interstellar conditions in the laboratory, we were able to detect weakly-bound carbon atoms diffusing on the surface of ice grains to react and produce C₂ molecules,” says chemist Masashi Tsuge of Hokkaido University’s Institute of Low Temperature Science. C₂ is also known as diatomic carbon, a molecule in which two carbon atoms bond together; its formation is concrete evidence for the presence of diffusing carbon atoms on interstellar ice grains.

The research revealed that the diffusion could occur at temperatures above 30 Kelvin (minus 243 °C/minus 405.4 °F), while, in space, the diffusion of carbon atoms could be activated at just 22 Kelvin (minus 251 °C/minus 419.8 °F).

Tsuge says that the findings bring a previously overlooked chemical process into the frame for explaining how more complex organic molecules could be built by the steady addition of carbon atoms. He suggests these processes could occur in the protoplanetary disks around stars, from which planets are formed. The conditions required can also form in so-called translucent clouds, which would eventually evolve into a star forming region. This may also explain the origin of the chemicals that might have seeded life on Earth.

Besides the question of the origin of life, the work adds a fundamental new process to the variety of chemical reactions that could have built, and could still be building, carbon-based chemistry throughout the universe.

The authors also summarize the more general current understanding of the formation of complex organic chemicals in space, and consider how reactions driven by diffusing carbon atoms might modify the current picture.

Professor Elizabeth Vargis and her team study a condition called age-related macular degeneration that causes damage to the retina, making it difficult to see. They study in vitro models, or a model developed in a laboratory setting, of Bruch’s membrane, a layer in the retina of the eye, to compare the natural aging process to the effects of AMD. They published their research in ACS Biomaterials Science & Engineering this past July.

“By using these models, scientists can better understand the role of Bruch’s membrane in the development of age-related eye diseases,” Vargis said. “This research provides an affordable and widely available option.”

Studying the connection between an aging Bruch’s membrane and deterioration caused by AMD is challenging in live subjects due to the slow progression of the disease and the complexity of isolating specific layers of the retina. Creating an in vitro model of Bruch’s membrane that mimics both its healthy and aged states help researchers understand the relationship between physical changes via aging and AMD. The ideal model should be smooth, nonporous and capable of supporting cell growth. It should also replicate the changes that occur with age in thickness, stiffness and permeability.

Previous models of Bruch’s membrane have captured some of its properties but not all. The most common model is a plastic membrane called a Transwell, which supports cell culture in the retina but is much thicker and stiffer than the natural membrane and cannot easily replicate changes from aging. Other models partially represent Bruch’s membrane but are difficult to produce and/or lack certain crucial aspects required to study AMD.

In previous work with USU Biology Professor Justin Jones, researchers manipulated spider silk proteins to replicate Bruch’s membrane, but challenges in isolating proteins and limited adjustability led to the exploration of other materials. Collaboration with Jones determined that hagfish slime proteins are the best choice for replicating Bruch’s membrane while still maintaining desirable properties. Vargis and her team were able to properly grow retinal cells on hagfish slime proteins and prove that the protein’s behavior changes as the membrane mimic stages of aging and disease.

This study was supported by grants from the NIH, BrightFocus Foundation, and the Office of Naval Research.

When these “microfliers” are dropped from a drone, they use a Miura-ori origami fold to switch from tumbling and dispersing outward through the air to dropping straight to the ground. To spread out the fliers, the researchers control the timing of each device’s transition using a few methods: an onboard pressure sensor (estimating altitude), an onboard timer or a Bluetooth signal.

Microfliers weigh about 400 milligrams — about half as heavy as a nail — and can travel the distance of a football field when dropped from 40 meters (about 131 feet) in a light breeze. Each device has an onboard battery-free actuator, a solar power-harvesting circuit and controller to trigger these shape changes in mid-air. Microfliers also have the capacity to carry onboard sensors to survey temperature, humidity and other conditions while soaring.

The team published these results Sept. 13 in Science Robotics.

“Using origami opens up a new design space for microfliers,” said co-senior author Vikram Iyer, UW assistant professor in the Paul G. Allen School of Computer Science & Engineering. “We combine the Miura-ori fold, which is inspired by geometric patterns found in leaves, with power harvesting and tiny actuators to allow our fliers to mimic the flight of different leaf types in mid-air. In its unfolded flat state, our origami structure tumbles chaotically in the wind, similar to an elm leaf. But switching to the folded state changes the airflow around it and enables a stable descent, similarly to how a maple leaf falls. This highly energy efficient method allows us to have battery-free control over microflier descent, which was not possible before.”

These robotic systems overcome several design challenges. The devices:

• are stiff enough to avoid accidentally transitioning to the folded state before the signal.
• transition between states rapidly. The devices’ onboard actuators need only about 25 milliseconds to initiate the folding.
• change shape while untethered from a power source. The microfliers’ power-harvesting circuit uses sunlight to provide energy to the actuator.

The current microfliers can only transition in one direction — from the tumbling state to the falling state. This switch allows researchers to control the descent of multiple microfliers at the same time, so they disperse in different directions on their way down.

Future devices will be able to transition in both directions, the researchers said. This added functionality will allow for more precise landings in turbulent wind conditions.

Additional co-authors on this paper are Kyle Johnson and Vicente Arroyos, both UW doctoral students in the Allen School; Amélie Ferran, a UW doctoral student in the mechanical engineering department; Raul Villanueva, Dennis Yin and Tilboon Elberier, who completed this work as UW undergraduate students studying electrical and computer engineering; Alberto Aliseda, UW professor of mechanical engineering; Sawyer Fuller, UW assistant professor of mechanical engineering; and Shyam Gollakota, UW professor in the Allen School.

This research was funded by a Moore Foundation fellowship, the National Science Foundation, the National GEM Consortium, the Google fellowship program, the Cadence fellowship program, the Washington NASA Space Grant fellowship Program and the SPEEA ACE fellowship program.

Matthew Kolisnyk and Karnig Kazazian combined functional magnetic resonance imaging (fMRI) with state-of-the art machine learning techniques to tackle one of the most complex issues in critical care.

Whether it is the result of a stroke, cardiac arrest or traumatic brain injury, lives can forever be changed by a serious brain injury. When patients are admitted to the ICU, families are faced with tremendous uncertainty. Will my loved one recover? Are they aware of what is going on? Will they ever be the same again? Despite these essential questions, health-care professionals are equally uncertain about the potential of a good recovery.

The graduate students are PhD candidates at Schulich School of Medicine & Dentistry in the lab of neuroscientist Adrian Owen.

“For years we’ve lacked the tools and techniques to know who is going to survive a serious brain injury,” said Owen.

An interdisciplinary team of researchers from Western, in collaboration with neurologists at London Health Sciences Centre and Lawson Health Research Institute sought to find a solution to this problem. They were led by Loretta Norton, a psychology professor at King’s University College at Western, who was one of the first researchers in the world to measure brain activity in the ICU.

The team measured brain activity in 25 patients at one of London’s two ICUs in the first few days after a serious brain injury and tested whether it could predict who would survive and who would not.

“We previously found that information about the potential for recovery in these patients was captured in the way different brain regions communicate with each other,” said Norton. “Intact communication between brain regions is an important factor for regaining consciousness.”

The breakthrough occurred when the team realized they could combine this imaging technique with an application of AI known as machine learning. They found they could predict patients who would recover with an accuracy of 80 per cent, which is higher than the current standard of care.

“Modern artificial intelligence has shown incredible predictive capabilities. Combining this with our existing imaging techniques was enough to better predict who will recover from their injuries,” said Kolisnyk.

While encouraging, the researchers say the prediction was not perfect and needs further research and testing.

“Given that these models learn best when they have lots of data, we hope our findings will lead to further collaborations with ICUs across Canada,” said Kazazian.