Tiny biological nanoparticles called “small extracellular vesicles” (sEVs) are released from every type of cell in the body and are believed to play a large role in cell-to-cell communication and disease transmission. The new technology, dubbed Acoustic Nanoscale Separation via Wave-pillar Excitation Resonance, or ANSWER for short, not only pulls these nanoparticles from biofluids in under 10 minutes, it also sorts them into size categories believed to have distinct biological roles.

The results appeared online November 23 in the journal Science Advances.

“These nanoparticles have significant potential in medical diagnosis and treatment, but the current technologies for separating and sorting them take several hours or days, are inconsistent, produce low yield or purity, suffer from contamination and sometimes damage the nanoparticles,” said Tony Jun Huang, the William Bevan Distinguished Professor of Mechanical Engineering and Materials Science at Duke.

“We want to make extracting and sorting high-quality sEVs as simple as pushing a button and getting the desired samples faster than it takes to take a shower,” Huang said.

Recent research indicates that sEVs are composed of several subgroups with distinct sizes (e.g., smaller than 50 nanometers, between 60 and 80 nanometers, and between 90 and 150 nanometers). Each size is believed to have different biological properties.

The recent discovery of sEV subpopulations has excited researchers because of their potential to revolutionize the field of non-invasive diagnostics, such as the early detection of cancer and Alzheimer’s disease. But the particles haven’t found their way into clinical settings yet.

Huang said this is largely due to the difficulties associated with separating and isolating these nano-sized sEV subpopulations. To meet this challenge, Huang, his doctoral student Jinxin Zhang, and collaborators at UCLA, Harvard, and Magee-Womens Research Institute, developed the ANSWER platform.

The device uses a single pair of transducers to generate a standing sound wave that envelops a narrow, enclosed channel filled with fluid. The sound wave “leaks” into the liquid center through the channel walls and interacts with the original standing sound wave. With careful design of the wall thickness, channel size and sound frequency, this interaction creates a resonance that forms “virtual pillars” along the center of the channel.

Each of these virtual pillars is essentially a half-egg-shaped region of high pressure. As particles attempt to cross over the pillars, they get pushed toward the edges of the channel. And the bigger the particles, the bigger the push. By tuning the series of virtual pillars to create nuanced forces on the traveling nanoparticles, the researchers can precisely sort them by size into a variety of groups determined by the needs of the experiments at hand.

“The ANSWER EV fractionation technology is the most advanced capability for precise EV fractionation, and it will significantly impact the horizon of EV diagnostics, prognostics and liquid biopsy,” said David Wong, director for UCLA Center for Oral/Head & Neck Oncology Research.

In the new paper, the researchers demonstrate that their ANSWER platform can successfully sort sEVs into three subgroups with 96% accuracy for nanoparticles on the larger end of the spectrum and 80% accuracy for the smallest. They also show flexibility in their system, adjusting the number of groupings and ranges of sizes with simple updates to the sound wave parameters. Each of the experiments only took 10 minutes to complete, whereas other methods such as ultra-centrifugation can take several hours or days.

“Due to its contact-free nature, ANSWER offers a biocompatible approach for the separation of biological nanoparticles.” Zhang said. “Unlike mechanical filtration methods, which have fixed separation cutoff diameters, ANSWER offers a tunable approach to nanoscale separation, and the cutoff diameter can be precisely modified by varying the input acoustic power.”

Moving forward, the researchers will continue improving the ANSWER technology so that it can be efficient in purifying other biologically relevant nanoparticles such as viruses, antibodies and proteins.

This research was supported by the National Institutes of Health (UH3TR002978, R01HD103727, U18TR003778, R01GM132603, R01GM143439 R01GM135486, R01GM144417, R44AG063643) and the National Science Foundation (CMMI-2104295, CMMI-2104526).

Phase transitions describe various phenomena around us, from water turning into ice to magnetic transitions to the superconducting transition where electrical resistance vanishes. In the cases of superconductivity and magnetism, the phase transition is continuous, characterized by “symmetry breaking” that leads to the formation of an ordered state. The ordered state is perfect (defect-free) when this transition is very slow, a regime called the “adiabatic limit.” However, for transitions not satisfying this limit, there appear topological defects, whose generation is described by the Kibble-Zurek (KZ) mechanism. Experimentally, the KZ mechanism manifests as a power-law dependence of the defect density on the cooling rate.

Interestingly, the KZ mechanism, while widely studied for phase transitions at thermal equilibrium, has not yet been demonstrated experimentally for nonequilibrium phase transitions. However, a recent simulation study has suggested that the KZ mechanism can be applied to dynamical ordering transitions between disordered and ordered flow states, a phenomenon that can be experimentally tested in superconducting vortex systems.

To this end, a research group from the Tokyo Institute of Technology (Tokyo Tech), Japan led by Prof. Satoshi Okuma recently showed that the state of motion of a collection of magnetic fluxes (vortices) penetrating a superconductor is in the process of nonequilibrium phase transition from disordered flow to ordered lattice flow, and the lattice defects spontaneously appear in line with the KZ mechanism. Their breakthrough study was published in Physical Review Letters (selected as an Editors’ suggestion).

In their work, the team prepared a 330-nm thick strip-shaped film of amorphous Mo_xGe_1−x (x ≈ 0.78) on a silicon substrate and then cooled it down to enable a superconducting transition at 6.3 K. By applying a magnetic field perpendicular to the surface, the vortices were generated and experiments were performed at 4.1 K under a field strength of 3.5 T.

The team drove the vortices using a driving current that was linearly ramped up at various quench rates (dI/dt). On reaching the end-point of quench, the vortex configuration was frozen by turning off the current abruptly.

“In our study, we tested the simulation predictions by experimentally examining the configurational order of vortices after undergoing dynamical ordering as a function of the quench rate,” explains Prof. Okuma.

The team found that the vortex configuration became less ordered with increasing quench rates, signifying a phase transition. “We investigated the lattice defects appearing during this transition and their variation with the quench rate,” says Prof. Okuma. “We found that the defect density scaled as a power law with the quench rate, consistent with the KZ scenario,” he highlights. The team additionally estimated the power law exponent (≈ 0.4-0.5), which was close to the value predicted by simulation (0.39).

“We also observed an impulse-adiabatic crossover on the ordered side of the transition, another key prediction of the KZ mechanism,” adds Prof. Okuma.

Overall, this study extends the applicability of the Kibble-Zurek mechanism from equilibrium phase transitions to nonequilibrium phase transitions, opening the door to countless new investigations. Given this landmark result, new developments are expected in the research field of nonequilibrium phase transitions.

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The findings were published in a Royal Society Open Science study by recent RIT alumnus Madhusudan Rajendran ’22 MS (bioinformatics) and Associate Professor Gregory Babbitt from the Thomas H. Gosnell School of Life Sciences. They studied how the viral spike proteins in several SARS-CoV-2 variants interact with the host cell receptors known as ACE2 in both humans and various bats of genus Rhinolophus. Babbitt said the results were surprising.

“We were hoping to see really cool adaptive evolution happening as the virus got more used to humans and less used to bats, but we actually saw that there wasn’t a whole lot of change,” said Babbitt. “Because this binding site has not evolved very much, there’s really not much stopping it from transmitting from humans to bats. If you look at the phylogenetic relationships of bats to humans, we’re pretty far apart on the mammalian tree. So it suggests that there would be pretty widespread cross-species infectivity, and the literature has shown there’s been a lot of evidence of that.”

The scientists used a computer simulation method called molecular dynamics to put proteins in a solvated simulation and then watch them move. The approach uses high performance computing on graphics processors to show what every atom does over time. Babbitt said this approach allows scientists to study questions that cannot be answered in a traditional laboratory.

“It would be dangerous to do experiments where we reinfected bats with human viral strains, so our computer-based simulations offered a much safer alternative,” said Babbitt.

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Materials provided by Rochester Institute of Technology. Original written by Luke Auburn. Note: Content may be edited for style and length.

A new MIT study finds that the health benefits associated with wind power could more than quadruple if operators prioritized turning down output from the most polluting fossil-fuel-based power plants when energy from wind is available.

In the study, published in Science Advances, researchers analyzed the hourly activity of wind turbines, as well as the reported emissions from every fossil-fuel-based power plant in the country, between the years 2011 and 2017. They traced emissions across the country and mapped the pollutants to affected demographic populations. They then calculated the regional air quality and associated health costs to each community.

The researchers found that in 2014, wind power that was associated with state-level policies improved air quality overall, resulting in $2 billion in health benefits across the country. However, only roughly 30 percent of these health benefits reached disadvantaged communities.

The team further found that if the electricity industry were to reduce the output of the most polluting fossil-fuel-based power plants, rather than the most cost-saving plants, in times of wind-generated power, the overall health benefits could quadruple to $8.4 billion nationwide. However, the results would have a similar demographic breakdown.

“We found that prioritizing health is a great way to maximize benefits in a widespread way across the U.S., which is a very positive thing. But it suggests it’s not going to address disparities,” says study co-author Noelle Selin, a professor in the Institute for Data, Systems and Society and the Department of Earth, Atmospheric and Planetary Sciences at MIT. “In order to address air pollution disparities, you can’t just focus on the electricity sector or renewables and count on the overall air pollution benefits addressing these real and persistent racial and ethnic disparities. You’ll need to look at other air pollution sources, as well as the underlying systemic factors that determine where plants are sited and where people live.”

Selin’s co-authors are lead author and former MIT graduate student Minghao Qiu PhD ’21, now at Stanford University, and Corwin Zigler at the University of Texas at Austin.

Turn-down service

In their new study, the team looked for patterns between periods of wind power generation and the activity of fossil-fuel-based power plants, to see how regional electricity markets adjusted the output of power plants in response to influxes of renewable energy.

“One of the technical challenges, and the contribution of this work, is trying to identify which are the power plants that respond to this increasing wind power,” Qiu notes.

To do so, the researchers compared two historical datasets from the period between 2011 and 2017: an hour-by-hour record of energy output of wind turbines across the country, and a detailed record of emissions measurements from every fossil-fuel-based power plant in the U.S. The datasets covered each of seven major regional electricity markets, each market providing energy to one or multiple states.

“California and New York are each their own market, whereas the New England market covers around seven states, and the Midwest covers more,” Qiu explains. “We also cover about 95 percent of all the wind power in the U.S.”

In general, they observed that, in times when wind power was available, markets adjusted by essentially scaling back the power output of natural gas and sub-bituminous coal-fired power plants. They noted that the plants that were turned down were likely chosen for cost-saving reasons, as certain plants were less costly to turn down than others.

The team then used a sophisticated atmospheric chemistry model to simulate the wind patterns and chemical transport of emissions across the country, and determined where and at what concentrations the emissions generated fine particulates and ozone — two pollutants that are known to damage air quality and human health. Finally, the researchers mapped the general demographic populations across the country, based on U.S. census data, and applied a standard epidemiological approach to calculate a population’s health cost as a result of their pollution exposure.

This analysis revealed that, in the year 2014, a general cost-saving approach to displacing fossil-fuel-based energy in times of wind energy resulted in $2 billion in health benefits, or savings, across the country. A smaller share of these benefits went to disadvantaged populations, such as minority and low-income communities, though this disparity varied by state.

“It’s a more complex story than we initially thought,” Qiu says. “Certain population groups are exposed to a higher level of air pollution, and those would be low-income people and racial minority groups. What we see is, developing wind power could reduce this gap in certain states but further increase it in other states, depending on which fossil-fuel plants are displaced.”

Tweaking power

The researchers then examined how the pattern of emissions and the associated health benefits would change if they prioritized turning down different fossil-fuel-based plants in times of wind-generated power. They tweaked the emissions data to reflect several alternative scenarios: one in which the most health-damaging, polluting power plants are turned down first; and two other scenarios in which plants producing the most sulfur dioxide and carbon dioxide respectively, are first to reduce their output.

They found that while each scenario increased health benefits overall, and the first scenario in particular could quadruple health benefits, the original disparity persisted: Minority and low-income populations still experienced smaller health benefits than more well-off communities.

“We got to the end of the road and said, there’s no way we can address this disparity by being smarter in deciding which plants to displace,” Selin says.

“One of the things that makes me optimistic about this area is, there’s a lot more attention to environmental justice and equity issues,” Selin concludes. “Our role is to figure out the strategies that are most impactful in addressing those challenges.”

This work was supported in part by the U.S. Environmental Protection Agency, and by the National Institutes of Health.

Publishing their findings in the academic journal Nature Scientific Reports, the team behind the study shows how beginners who undertook piano lessons for just one hour a week over 11 weeks reported significant improvements in recognising audio-visual changes in the environment and reported less depression, stress and anxiety.

In the randomised control study, 31 adults were assigned into either a music training, music listening, or a control group. Individuals with no prior musical experiences or training were instructed to complete weekly one-hour sessions. Whilst the intervention groups played music, the control groups either listened to music or used the time to complete homework.

The researchers found that within just a few weeks of starting lessons*, people’s ability to process multisensory information — i.e., sight and sound — was enhanced. Improved ‘multisensory process’ has benefits for almost every activity we participate in — from driving a car and crossing a road, to finding someone in a crowd or watching TV.

These multisensory improvements extended beyond musical abilities. With musical training, people’s audio-visual processing became more accurate across other tasks. Those who received piano lessons showed greater accuracy in tests where participants were asked to determine whether sound and vision ‘events’ occurred at the same time.

This was true both for simple displays presenting flashes and beeps, and for more complex displays showing a person talking. Such fine-tuning of individuals’ cognitive abilities was not present for the music listening group (where participants listened to the same music as played by the music group), or for the non-music group (where members studied or read).

In addition, the findings went beyond improvements in cognitive abilities, showing that participants also had reduced depression, anxiety and stress scores after the training compared to before it. The authors suggest that music training could be beneficial for people with mental health difficulties, and further research is currently underway to test this.

Cognitive psychologist and music specialist Dr Karin Petrini from the University of Bath’s Department of Psychology, explained: “We know that playing and listening to music often brings joy to our lives, but with this study we were interested in learning more about the direct effects a short period of music learning can have on our cognitive abilities.

“Learning to play an instrument like the piano is a complex task: it requires a musician to read a score, generate movements and monitor the auditory and tactile feedback to adjust their further actions. In scientific terms, the process couples visual with auditory cues and results in a multisensory training for individuals.

“The findings from our study suggest that this has a significant, positive impact on how the brain processes audio-visual information even in adulthood when brain plasticity is reduced.”

Notes

• Each music training session included two segments. The first 20-minute segment was dedicated to finger exercise. The second segment consisted of learning songs from the ABRSM 2017-2018 piano grade one exam list for 40 minutes. All training sessions were carried out on a one-to-one basis. Participants learned these pieces in the order presented below. They proceeded to the next song once they could play the former one correctly and fluently:

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  William Gillock A Stately Sarabande. Classic Piano Repertoire (Elementary).

• Johann Christian Bach Aria in F, BWV Anh. II 131.

• Giuseppe Verdi La donna è mobile (from Rigoletto).

• Bryan Kelly Gypsy Song: No. 6 from A Baker’s Dozen.

• Traditional American Folk Song: When the saints go marching in.

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Researchers at The University of Texas at Austin and Texas A&M University have applied emerging electronic tattoo (e-tattoo) technology to this type of monitoring, known as electrodermal activity or EDA sensing. In a new paper published recently in Nature Communications, the researchers created a graphene-based e-tattoo that attaches to the palm, is nearly invisible and connects to a smart watch.

“It’s so unobstructive that people sometimes forget they had them on, and it also reduces the social stigma of wearing these devices in such prominent places on the body,” said Nanshu Lu, professor in the Department of Aerospace Engineering and Engineering Mechanics and leader of the project.

Lu and her collaborators have been advancing wearable e-tattoo technology for many years. Graphene has been a favorite material because of how thin it is and how well it measures electrical potential from human body, leading to very accurate readings.

But, such ultra-thin materials can’t handle much, if any strain. So that makes applying them to parts of the body that include a lot of movement, such as the palm/wrist, challenging.

The secret sauce of this discovery is how the e-tattoo on the palm is able to successfully transfer data to a rigid circuit — in this case a commercially available smart watch, in out-of-lab, ambulatory settings. They used a serpentine ribbon that has two layers of graphene and gold partially overlapped. By snaking the ribbon back and forth, it can handle the strain that comes with movements of the hand for everyday activities like holding the steering wheel while driving, opening doors, running etc.

Current palm monitoring tech uses bulky electrodes that fall off and are very visible, or EDA sensors applied to other parts of the body, which gives a less accurate reading.

Other researchers have tried similar methods using nanometer-thick straight-line ribbons to connect the tattoo to a reader, but they couldn’t handle the strain of constant movement.

Lu said the researchers were inspired by virtual reality (VR), gaming and the incoming metaverse for this research. VR is used in some cases to treat mental illness; however, the human-aware capability in VR remains lacking in many ways.

“You want to know whether people are responding to this treatment,” Lu said. “Is it helping them? Right now, that’s hard to tell.”

Other members of the team include Hongwoo Jang and Eunbin Kim from the Texas Materials Institute; Sangjun Kim and Kyoung-Ho Ha from the Walker Department of Mechanical Engineering; Xiangxing Yang from the Chandra Family Department of Electrical and Computer Engineering; and Kaan Sel and Roozbeh Jafari from Texas A&M’s Department of Electrical and Computer Engineering.

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