If you’re looking for an indoor space with a low level of particulate air pollution, a commercial airliner flying at cruising altitude may be your best option. A newly reported study of air quality in indoor spaces such as stores, restaurants, offices, public transportation — and commercial jets — shows aircraft cabins with the lowest levels of tiny aerosol particles.
Conducted in July 2020, the study included monitoring both the number of particles and their total mass across a broad range of indoor locations, including 19 commercial flights in which measurements took place throughout departure and arrival terminals, the boarding process, taxiing, climbing, cruising, descent, and deplaning. The monitoring could not identify the types of the particles and therefore does not provide a direct measure of coronavirus exposure risk.
“We wanted to highlight how important it is to have a high ventilation rate and clean air supply to lower the concentration of particles in indoor spaces,” said Nga Lee (Sally) Ng, associate professor and Tanner Faculty Fellow in the School of Chemical and Biomolecular Engineering and the School of Earth and Atmospheric Sciences at the Georgia Institute of Technology. “The in-flight cabin had the lowest particle mass and particle number concentration.”
The study, believed to be the first to measure both size-resolved particle mass and number in commercial flights from terminal to terminal and a broad range of indoor spaces, has been accepted for publication in the journal Indoor Air and posted online at the journal’s website. Supported by Delta Air Lines, the research may be the first to comprehensively measure particle concentrations likely to be encountered by passengers from terminal to terminal.
As scientists learn more about transmission of the coronavirus, the focus has turned to aerosol particles as an important source of viral spread indoors. Infected people can spread the virus as they breathe, talk, or cough, creating particles ranging in size from less than a micron — one millionth of a meter — to 1,000 microns. The larger particles quickly fall out of the air, but the smaller ones remain suspended.
“Especially in poorly ventilated spaces, these particles can be suspended in the air for a long period of time, and can travel to every corner of a room,” Ng said. “If they are viral particles, they can infect people who may be at a considerable distance from a person emitting the particles.”
To better understand the circulation of airborne particles, Delta approached Ng to conduct a study of multiple indoor environments, with a strong focus on air travel conditions. Using handheld instruments able to measure the total number of particles and their mass, Georgia Tech researchers examined air quality in a series of Atlanta area restaurants, stores, offices, homes, and vehicles — including buses, trains, and private automobiles.

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They trained Delta staff to conduct the same type of measurements in terminals, boarding areas, and a variety of aircraft through all phases of flight. The Delta staff recorded their locations as they moved through the terminals, and the instruments produced measurements consistent with the restaurants and stores they passed on their way to and from boarding and departure gates.
“The measurements started as soon as they stepped into the departure terminal,” Ng said. “We were thinking about the whole trip, what a person would encounter from terminal to terminal.”
In flight, aircraft air is exchanged between 10 and 30 times per hour. Some aircraft bring in exclusively outside air, which at cruising altitude is largely free of pollutant particles found in air near the ground. Other aircraft mix outdoor air with recirculated air that goes through HEPA filters, which remove more than 99% of particles.
In all, the researchers evaluated measurements from 19 commercial flights with passenger loads of approximately 50%. The flights included a mix of short- and medium-length flights, and aircraft ranging from the CRJ-200 and A220 to the 757, A321, and 737.
Among all the spaces measured, restaurants had the highest particle levels because of cooking being done there. Stores were next, followed by vehicles, homes, and offices. The average sub-micron particle number concentration measured in restaurants, for instance, was 29,400 particles per cubic centimeter, and in offices it was 2,473 per cubic centimeter.

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“We have quite a comprehensive data set to look at the size distribution of particles across these different spaces,” Ng said. “We can now compare indoor air quality in a variety of different spaces.”
Because of the portable instruments used, the researchers were unable to determine the source of the particles, which could have included both biological and non-biological sources. “Further studies can include direct measurements of viral loads and tracing particle movements in indoor spaces,” she added.
Jonathan Litzenberger, Delta’s managing director of Global Cleanliness Strategy, said the research helps advance the company’s goals of protecting its customers and employees.
“Keeping the air clean and safe during flight is one of the most foundational layers of protection Delta aims to provide to our customers and employees,” he said. “We are always working to better understand the travel environment and confirm that the measures we are implementing are working.”
Overall, the study highlights the importance of improving indoor air quality as a means of reducing coronavirus transmission.
“Regardless of whether you are in an office or an aircraft, having a higher ventilation rate and good particle filtration are the keys to reducing the total particle concentration,” said Ng. “That should also reduce the concentration of any viral particles that may be present.”

A large proportion of the benefit that a person gets from taking a real drug or receiving a treatment to alleviate pain is due to an individual’s mindset, not to the drug itself. Understanding the neural mechanisms driving this placebo effect has been a longstanding question. A meta-analysis published in Nature Communications finds that placebo treatments to reduce pain, known as placebo analgesia, reduce pain-related activity in multiple areas of the brain.
Previous studies of this kind have relied on small-scale studies, so until now, researchers did not know if the neural mechanisms underlying placebo effects observed to date would hold up across larger samples. This study represents the first large-scale mega-analysis, which looks at individual participants’ whole brain images. It enabled researchers to look at parts of the brain that they did not have sufficient resolution to look at in the past. The analysis was comprised of 20 neuroimaging studies with 600 healthy participants. The results provide new insight on the size, localization, significance and heterogeneity of placebo effects on pain-related brain activity.
The research reflects the work of an international collaborative effort by the Placebo Neuroimaging Consortium, led by Tor Wager , the Diana L. Taylor Distinguished Professor in Neuroscience at Dartmouth and Ulrike Bingel, a professor at the Center for Translational Neuro- and Behavioral Sciences in the department of neurology at University Hospital Essen, for which Matthias Zunhammer and Tamás Spisák at the University Hospital Essen, served as co-authors. The meta-analysis is the second with this sample and builds on the team’s earlier research using an established pain marker developed earlier by Wager’s lab.
“Our findings demonstrate that the participants who showed the most pain reduction with the placebo also showed the largest reductions in brain areas associated with pain construction,” explains co-author Wager, who is also the principal investigator of the Cognitive and Affective Neuroscience Lab at Dartmouth. “We are still learning how the brain constructs pain experiences, but we know it’s a mix of brain areas that process input from the body and those involved in motivation and decision-making. Placebo treatment reduced activity in areas involved in early pain signaling from the body, as well as motivational circuits not tied specifically to pain.”
Across the studies in the meta-analysis, participants had indicated that they felt less pain; however, the team wanted to find out if the brain responded to the placebo in a meaningful way. Is the placebo changing the way a person constructs the experience of pain or is it changing the way a person thinks about it after the fact? Is the person really feeling less pain?
With the large sample, the researchers were able to confidently localize placebo effects to specific zones of the brain, including the thalamus and the basal ganglia. The thalamus serves as a gateway for sights and sounds and all kinds of sensory motor input. It has lots of different nuclei, which act like processing stations for different kinds of sensory input. The results showed that parts of the thalamus that are most important for pain sensation were most strongly affected by the placebo. In addition, parts of the somatosensory cortex that are integral to the early processing of painful experiences were also affected. The placebo effect also impacted the basal ganglia, which are important for motivation and connecting pain and other experiences to action. “The placebo can affect what you do with the pain and how it motivates you, which could be a larger part of what’s happening here,” says Wager. “It’s changing the circuitry that’s important for motivation.”
The findings revealed that placebo treatments reduce activity in the posterior insula, which is one of the areas that are involved in early construction of the pain experience. This is the only site in the cortex that you can stimulate and invoke the sense of pain. The major ascending pain pathway goes from parts of the thalamus to the posterior insula. The results provide evidence that the placebo affects that pathway for how pain is constructed.
Prior research has illustrated that with placebo effects, the prefrontal cortex is activated in anticipation of pain. The prefrontal cortex helps keep track of the context of the pain and maintain the belief that it exists. When the prefrontal cortex is activated, there are pathways that trigger opioid release in the midbrain that can block pain and pathways that can modify pain signaling and construction.
The team found that activation of the prefrontal cortex is heterogeneous across studies, meaning that no particular areas in this region were activated consistently or strongly across the studies. These differences across studies are similar to what is found in other areas of self-regulation, where different types of thoughts and mindsets can have different effects. For example, other work in Wager’s laboratory has found that rethinking pain by using imagery and storytelling typically activates the prefrontal cortex, but mindful acceptance does not. Placebo effects likely involve a mix of these types of processes, depending on the specifics of how it is given and people’s predispositions.
“Our results suggest that placebo effects are not restricted solely to either sensory/nociceptive or cognitive/affective processes, but likely involves a combination of mechanisms that may differ depending on the placebo paradigm and other individual factors,” explains Bingel. “The study’s findings will also contribute to future research in the development of brain biomarkers that predict an individual’s responsiveness to placebo and help distinguish placebo from analgesic drug responses, which is a key goal of the new collaborative research center, Treatment Expectation .”
Understanding the neural systems that utilize and moderate placebo responses has important implications for clinical care and drug-development. The placebo responses could be utilized in a context-, patient-, and disease-specific manner. The placebo effect could also be leveraged alongside a drug, surgery, or other treatment, as it could potentially enhance patient outcomes.

Story Source:
Materials provided by Dartmouth College. Original written by Amy D. Olson. Note: Content may be edited for style and length.

Assessing a drug compound by its activity, not simply its structure, is a new approach that could speed the search for COVID-19 therapies and reveal more potential therapies for other diseases.
This action-based focus — called biological activity-based modeling (BABM) — forms the core of a new approach developed by National Center for Advancing Translational Sciences (NCATS) researchers and others. NCATS is part of the National Institutes of Health (NIH). Researchers used BABM to look for potential anti-SARS-CoV-2 agents whose actions, not their structures, are similar to those of compounds already shown to be effective.
NCATS scientists Ruili Huang, Ph.D., and Wei Zheng, Ph.D., led the research team that created the approach. Their findings were posted online Feb. 23 by the journal Nature Biotechnology.
“With this new method, you can find completely new chemical structures based on activity profiles and then develop completely new drugs,” Huang explained. Thus, using information about a compound’s biological activity may expand the pool of promising treatments for a wide range of diseases and conditions.
When researchers seek new compounds or look for existing drugs to repurpose against new diseases, they are increasingly using screening tools to predict which drugs might be good candidates. Virtual screening, or VS, allows scientists to use advanced computer analyses to find potentially effective candidates from among millions of compounds in collections.
Traditional VS techniques look for compounds with structures similar to those known to be effective against a particular target on a pathogen or cell, for example. Those structural similarities are then assumed to deliver similar biological activities.

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With BABM, however, researchers don’t need to know a compound’s chemical structure, according to Huang. Instead, they use a profile of a compound’s activity patterns — how it behaves at multiple concentrations against a panel of targets or tests — to predict its potential effectiveness against a new target or in a new drug assay.
The now-widespread use of quantitative high-throughput screening (qHTS) allows BABM more accuracy in its predictions. qHTS assesses a compound’s effectiveness at multiple concentrations in thousands of tests over time. That practice provides far more detail about how a compound behaves than does traditional high-throughput screening, which tests only a single concentration of the compound. The information generated by qHTS creates a stronger biological activity profile — also known as a signature — for each one of millions of compounds.
To test the BABM approach, the researchers tapped the vast pool of data generated by hundreds of qHTS analyses run on NCATS’ in-house collection of more than 500,000 compounds and drugs. First, they verified BABM’s ability to use activity profiles to identify compounds already shown to be effective against the Zika and Ebola viruses. BABM also identified new compounds that showed promise against those viruses.
The scientists then turned to SARS-CoV-2, the virus that causes COVID-19. They applied BABM, a structure-based model and a combined approach to analyze the NCATS library’s compounds to find potential anti-SARS-CoV-2 agents. BABM predicted that the activity profiles of 311 compounds might indicate promise against the coronavirus.
The researchers then had an outside laboratory test those 311 compounds against the live SARS-CoV-2 virus. The result: Nearly one-third of the BABM-backed compounds (99) showed antivirus activity in the test. The BABM-driven prediction hit rate topped that of the structure-based model — and combining the activity-based and structure-based models yielded even better predictive results.
A key advantage to BABM is speed. “This method is very fast — you essentially just run a computer algorithm, and you can identify many new drug leads, even with new chemical structures,” Huang noted. In fact, screening the entire NCATS library of half a million compounds for anti-SARS-CoV-2 candidates took only a few minutes.
BABM also is a transferable tool — it’s not limited to use in the NCATS compound libraries. “Anyone can use this method by applying any biological activity profile data, including publicly available NCATS data,” Huang emphasized.
The NCATS researchers predict their activity-based model’s impact could extend far beyond the search for COVID-19 treatments and small-molecule drug discovery. Given any substance with an available activity profile, scientists can predict its activity against a new target, for a new indication, or against a new disease.
“In addition to small molecules, this approach can be applied to biologics, antibodies, and other therapies,” Huang said. “BABM is for all drug discovery projects.”