A study done in rooms where COVID-19 patients were isolated shows that the virus’s RNA — part of the genetic material inside a virus — can persist up to a month in dust.
The study did not evaluate whether dust can transmit the virus to humans. It could, however, offer another option for monitoring COVID-19 outbreaks in specific buildings, including nursing homes, offices or schools.
Karen Dannemiller, senior author of the study, has experience studying dust and its relationship to potential hazards like mold and microbes.
“When the pandemic started, we really wanted to find a way that we could help contribute knowledge that might help mitigate this crisis,” said Dannemiller, assistant professor of civil, environmental and geodetic engineering and environmental health sciences at The Ohio State University.
“And we’ve spent so much time studying dust and flooring that we knew how to test it.”
The study, published today (April 13, 2021) in the journal mSystems, found some of the genetic material at the heart of the virus persists in dust, even though it is likely that the envelope around the virus may break down over time in dust. The envelope — the crown-like spiked sphere that contains the virus’s material — plays an important role in the virus’s transmission to humans.

Researchers have identified molecular signatures of the aging process in mice, publishing their results today in the open-access eLife journal.
Their analyses provide one of the most comprehensive characterisations of the molecular signatures of aging across diverse types of cells from different tissues in a mammal, and will aid future studies on aging and related topics.
Aging leads to the decline of major organs and is the main risk factor for many diseases, including cancer, cardiovascular and neurodegenerative diseases. While previous studies have highlighted different hallmarks of the aging process, the underlying molecular and cellular mechanisms remain unclear.
To gain a better understanding of these mechanisms, the Tabula Muris Consortium created the single-cell transcriptomic dataset, called Tabula Muris Senis (TMS). The TMS contains over 300,000 annotated cells from 23 tissues and organs of male and female mice. “These cells were collected from mice of diverse ages, making the data a tremendous opportunity to study the genetic basis of aging across different tissues and cell types,” says first author Martin Jinye Zhang, Postdoctoral Researcher in the Department of Epidemiology, Harvard University, Boston, US.
The original TMS study mainly explored the cell-centric effects of aging, aiming to characterise changes in the composition of cell types within different tissues. In the current gene-centric study, Zhang and colleagues focused on changes in gene expression that occur during the aging process across different cell types.
Using the TMS data, they identified aging-dependent genes in 76 cell types from 23 tissues. They then characterised the aging behaviours of these genes that were both shared among all cell types (‘globally’) and specific to different tissue cells.
“We found that the cell-centric and gene-centric perspectives of the previous and current studies are complementary, as gene expression can change within the same cell type during aging, even if the composition of cells in the tissue does not vary over time,” explains co-senior author Angela Oliveira Pisco, Associate Director of Bioinformatics at the Chan Zuckerberg Biohub, San Francisco, US. “The identification of many shared aging genes suggests that there is a coordinated global aging behaviour in mice.”
The team then used this coordinated activity to develop a single-cell aging score based on the global aging genes. This new high-resolution aging score revealed that different tissue-cell types in the same animal can have a different aging status, shedding light on the diverse aging process across different types of cells.
“Taken together, our results provide a characterisation of aging genes across a wide range of tissue-cell types in the mouse,” concludes senior author James Zou, Assistant Professor of Biomedical Data Science at Stanford University, Stanford, US, and a Chan Zuckerberg Biohub Investigator. “In addition to providing new biological insights on the aging process, this work serves as a comprehensive reference for researchers working in related fields.”
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A gene therapy protects eye cells in mice with a rare disorder that causes vision loss, especially when used in combination with other gene therapies, shows a study published today in eLife.
The findings suggest that this therapy, whether used alone or in combination with other gene therapies that boost eye health, may offer a new approach to preserving vision in people with retinitis pigmentosa or other conditions that cause vision loss.
Retinitis pigmentosa is a slowly progressive disease, which begins with the loss of night vision due to genetic lesions that affect rod photoreceptors — cells in the eyes that sense light when it is low. These photoreceptors die because of their intrinsic genetic defects. This then impacts cone photoreceptors, the eye cells that detect light during the day, which leads to the eventual loss of daylight vision. One theory about why cones die concerns the loss of nutrient supply, especially glucose.
Scientists have developed a few targeted gene therapies to help individuals with certain mutations that affect the photoreceptors, but no treatments are currently available that would be effective for a broad set of families with the disease. “A gene therapy that would preserve photoreceptors in people with retinitis pigmentosa regardless of their specific genetic mutation would help many more patients,” says lead author Yunlu Xue, Postdoctoral Fellow at senior author Constance Cepko’s lab, Harvard Medical School, Boston, US.
To find a widely effective gene therapy for the disease, Xue and colleagues screened 20 potential therapies in mouse models with the same genetic deficits as humans with retinitis pigmentosa. The team chose the therapies based on the effects they have on sugar metabolism.
Their experiments showed that using a virus carrier to deliver a gene called Txnip was the most effective approach in treating the condition across three different mouse models. A version of Txnip called C247S worked especially well, as it helped the cone photoreceptors switch to using alternative energy sources and improved mitochondria health in the cells.
The team then showed that giving the mice gene therapies that reduced oxidative stress and inflammation, along with Txnip gene therapy, provided additional protection for the cells. Further studies are now needed to confirm whether this approach would help preserve vision in people with retinitis pigmentosa.
“The immediate next step is to test Txnip for safety in animals beyond mice, before moving on to a clinical trial in humans,” explains senior author and Howard Hughes Institute Investigator Constance Cepko, the Bullard Professor of Genetics and Neuroscience at Harvard Medical School. “If it ultimately proves safe in people, then we would hope to see it become an effective approach for treating those with retinitis pigmentosa and other forms of progressive vision loss, such as age-related macular degeneration.”
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A new study published in Elementa by researchers at the University of California, Santa Cruz and NOAA examines traditional aspects of seafood sustainability alongside greenhouse gas emissions to better understand the “carbon footprint” of U.S. tuna fisheries.
Fisheries in the United States are among the best managed in the world, thanks to ongoing efforts to fish selectively, end overfishing, and rebuild fish stocks. But climate change could bring dramatic changes in the marine environment that threaten seafood productivity and sustainability. That’s one reason why researchers set out to broaden the conversation about sustainability in seafood by comparing the carbon emissions of different tuna fishing practices.
The paper also puts those emissions in context relative to other sources of protein, like tofu, chicken, pork, or beef. In particular, the study examined how the carbon footprint of tuna was affected by how far from shore fishing fleets operated, or what type of fishing gear they used.
“This can be an opportunity to look at fisheries from different angles, all of which may be important,” said Brandi McKuin, the study’s lead author and a postdoctoral researcher in environmental studies at UC Santa Cruz.
Comparing Carbon Footprints
Generally speaking, less selective tuna fishing gear — like purse seine nets that scoop up many tuna all at once — are more likely to accidentally catch other species during the fishing process. That’s called bycatch, and it’s a conservation concern that often factors into seafood sustainability assessments.

In a series of experiments that began with amoebas — single-celled organisms that extend podlike appendages to move around — Johns Hopkins Medicine scientists say they have identified a genetic pathway that could be activated to help sweep out mucus from the lungs of people with chronic obstructive pulmonary disease a widespread lung ailment.
“Physician-scientists and fundamental biologists worked together to understand a problem at the root of a major human illness, and the problem, as often happens, relates to the core biology of cells,” says Doug Robinson, Ph.D., professor of cell biology, pharmacology and molecular sciences, medicine (pulmonary division), oncology, and chemical and biomedical engineering at the Johns Hopkins University School of Medicine.
Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the U.S., affecting more the 15 million adults, according to the U.S. Centers for Disease Control and Prevention. The disease causes the lungs to fill up with mucus and phlegm, and people with COPD experience chronic cough, wheezing and difficulty breathing. Cigarette smoking is the main cause in as many as three-quarters of COPD cases, and there is no cure or effective treatment available despite decades of research.
In a report on their new work, published Feb. 25 in the Journal of Cell Science, the researchers say they took a new approach to understanding the biology of the disorder by focusing on an organism with a much simpler biological structure than human cells to identify genes that might protect against the damaging chemicals in cigarette smoke.
Robinson and his collaborator, Ramana Sidhaye, M.D., also a professor of medicine in the Division of Pulmonology at Johns Hopkins, with their former lab member Corrine Kliment, M.D., Ph.D., counted on the knowledge that as species evolved, genetic pathways were frequently retained across the animal kingdom.
Enter the soil-dwelling amoeba Dictyostelium discoideum, which has long been studied to understand cell movement and communication. The scientists pumped lab-grade cigarette smoke through a tube and bubbled it into the liquid nutrients bathing the amoeba. Then, the scientists used engineered amoeba to identify genes that could provide protection against the smoke.

Researchers from North Carolina State University have found a way to fine-tune the molecular assembly line that creates antibiotics via engineered biosynthesis. The work could allow scientists to improve existing antibiotics as well as design new drug candidates quickly and efficiently.
Bacteria — such as E. coli — harness biosynthesis to create molecules that are difficult to make artificially.
“We already use bacteria to make a number of drugs for us,” says Edward Kalkreuter, former graduate student at NC State and lead author of a paper describing the research. “But we also want to make alterations to these compounds; for example, there’s a lot of drug resistance to erythromycin. Being able to make molecules with similar activity but improved efficacy against resistance is the general goal.”
Picture an automobile assembly line: each stop along the line features a robot that chooses a particular piece of the car and adds it to the whole. Now substitute erythromycin for the car, and an acyltransferase (AT) — an enzyme — as the robot at the stations along the assembly line. Each AT “robot” will select a chemical block, or extender unit, to add to the molecule. At each station the AT robot has 430 amino acids, or residues, which help it select which extender unit to add.
“Different types of extender units impact the activity of the molecule,” says Gavin Williams, professor of chemistry, LORD Corporation Distinguished Scholar at NC State and corresponding author of the research. “Identifying the residues that affect extender unit selection is one way to create molecules with the activity we want.”
The team used molecular dynamic simulations to examine AT residues and identified 10 residues that significantly affect extender unit selection. They then performed mass spectrometry and in vitro testing on AT enzymes that had these residues changed in order to confirm their activity had also changed. The results supported the computer simulation’s predictions.
“These simulations predict what parts of the enzyme we can change by showing how the enzyme moves over time,” says Kalkreuter. “Generally, people look at static, nonmoving structures of enzymes. That makes it hard to predict what they do, because enzymes aren’t static in nature. Prior to this work, very few residues were thought or known to affect extender unit selection.”
Williams adds that manipulating residues allows for much greater precision in reprogramming the biosynthetic assembly line.
“Previously, researchers who wanted to change an antibiotic’s structure would simply swap out the entire AT enzyme,” Williams says. “That’s the equivalent of removing an entire robot from the assembly line. By focusing on the residues, we’re merely replacing the fingers on that arm — like reprogramming a workstation rather than removing it. It allows for much greater precision.
“Using these computational simulations to figure out which residues to replace is another tool in the toolbox for researchers who use bacteria to biosynthesize drugs.”
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Artificial intelligence could be one of the keys for limiting the spread of infection in future pandemics. In a new study, researchers at the University of Gothenburg have investigated how machine learning can be used to find effective testing methods during epidemic outbreaks, thereby helping to better control the outbreaks.
In the study, the researchers developed a method to improve testing strategies during epidemic outbreaks and with relatively limited information be able to predict which individuals offer the best potential for testing.
“This can be a first step towards society gaining better control of future major outbreaks and reduce the need to shutdown society,” says Laura Natali, a doctoral student in physics at the University of Gothenburg and the lead author of the published study.
Machine learning is a type of artificial intelligence and can be described as a mathematical model where computers are trained to learn to see connections and solve problems using different data sets. The researchers used machine learning in a simulation of an epidemic outbreak, where information about the first confirmed cases was used to estimate infections in the rest of the population. Data about the infected individual’s network of contacts and other information was used: who they have been in close contact with, where and for how long.
“In the study, the outbreak can quickly be brought under control when the method is used, while random testing leads to uncontrolled spread of the outbreak with many more infected individuals. Under real world conditions, information can be added, such as demographic data, age and health-related conditions, which can improve the method’s effectiveness even more. The same method can also be used to prevent reinfections in the population if immunity after the disease is only temporary.”
She emphasises that the study is a simulation and that testing with real data is needed to improve the method even more. Therefore, it is too early to use it in the ongoing coronavirus pandemic. At the same time, she sees the research as a first step in being able to implement more targeted initiatives to reduce the spread of infections, since the machine learning-based testing strategy automatically adapts to the specific characteristics of diseases. As an example, she mentions the potential to easily predict if a specific age group should be tested or if a limited geographic area is a risk zone, such as a school, a community or a specific neighbourhood.
“When a large outbreak has begun, it is important to quickly and effectively identify infectious individuals. In random testing, there is a significant risk failing to achieve this, but with a more goal-oriented testing strategy we can find more infected individuals and thereby also gain the necessary information to decrease the spread of infection. We show that machine learning can be used to develop this type of testing strategy,” she says.
There are few previous studies that have examined how machine learning can be used in cases of pandemics, particularly with a clear focus on finding the best testing strategies.
“We show that it is possible to use relatively simple and limited information to make predictions of who would be most beneficial to test. This allows better use of available testing resources.”
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Wearable electronic devices and biosensors are great tools for health monitoring, but it has been difficult to find convenient power sources for them. Now, a group of scientists has successfully developed and tested a wearable biofuel cell array that generates electric power from the lactate in the wearer’s sweat, opening doors to electronic health monitoring powered by nothing but bodily fluids.
It cannot be denied that, over the past few decades, the miniaturization of electronic devices has taken huge strides. Today, after pocket-size smartphones that could put old desktop computers to shame and a plethora of options for wireless connectivity, there is a particular type of device whose development has been steadily advancing: wearable biosensors. These tiny devices are generally meant to be worn directly on the skin in order to measure specific biosignals and, by sending measurements wirelessly to smartphones or computers, keep track of the user’s health.
Although materials scientists have developed many types of flexible circuits and electrodes for wearable devices, it has been challenging to find an appropriate power source for wearable biosensors. Traditional button batteries, like those used in wrist watches and pocket calculators, are too thick and bulky, whereas thinner batteries would pose capacity and even safety issues. But what if we were the power sources of wearable devices ourselves?
A team of scientists led by Associate Professor Isao Shitanda from Tokyo University of Science, Japan, are exploring efficient ways of using sweat as the sole source of power for wearable electronics. In their most recent study, published in the Journal of Power Sources, they present a novel design for a biofuel cell array that uses a chemical in sweat, lactate, to generate enough power to drive a biosensor and wireless communication devices for a short time. The study was carried out in collaboration with Dr. Seiya Tsujimura from University of Tsukuba, Dr. Tsutomu Mikawa from RIKEN, and Dr. Hiroyuki Matsui from Yamagata University, all in Japan.
Their new biofuel cell array looks like a paper bandage that can be worn, for example, on the arm or forearm. It essentially consists of a water-repellent paper substrate onto which multiple biofuel cells are laid out in series and in parallel; the number of cells depends on the output voltage and power required. In each cell, electrochemical reactions between lactate and an enzyme present in the electrodes produce an electric current, which flows to a general current collector made from a conducting carbon paste.
This is not the first lactate-based biofuel cell, but some key differences make this novel design stand out from existing lactate-based biofuel cells. One is the fact that the entire device can be fabricated via screen printing, a technique generally suitable for cost-effective mass production. This was possible via the careful selection of materials and an ingenious layout. For example, whereas similar previous cells used silver wires as conducting paths, the present biofuel cells employ porous carbon ink. Another advantage is the way in which lactate is delivered to the cells. Paper layers are used to collect sweat and transport it to all cells simultaneously through the capillary effect — the same effect by which water quickly travels through a napkin when it comes into contact with a water puddle.
These advantages make the biofuel cell arrays exhibit an unprecedented ability to deliver power to electronic circuits, as Dr. Shitanda remarks: “In our experiments, our paper-based biofuel cells could generate a voltage of 3.66 V and an output power of 4.3 mW. To the best of our knowledge, this power is significantly higher than that of previously reported lactate biofuel cells.” To demonstrate their applicability for wearable biosensors and general electronic devices, the team fabricated a self-driven lactate biosensor that could not only power itself using lactate and measure the lactate concentration in sweat, but also communicate the measured values in real-time to a smartphone via a low-power Bluetooth device.
As explained in a previous study also led by Dr. Shitanda, lactate is an important biomarker that reflects the intensity of physical exercise in real-time, which is relevant in the training of athletes and rehabilitation patients. However, the proposed biofuel cell arrays can power not only wearable lactate biosensors, but also other types of wearable electronics. “We managed to drive a commercially available activity meter for 1.5 hours using one drop of artificial sweat and our biofuel cells,” explains Dr. Shitanda, “and we expect they should be capable of powering all sorts of devices, such as smart watches and other commonplace portable gadgets.”
Hopefully, with further developments in wearable biofuel cells, powering portable electronics and biosensors will be no sweat!
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New data published by researchers at The Ohio State University Comprehensive Cancer Center — Arthur G. James Cancer Hospital and Richard J. Solove Research Institute (OSUCCC — James) suggests that an oral drug currently used in the clinical setting to treat neuromuscular diseases could also help prevent a common form of skin cancer caused by damage from ultraviolet-B (UVB) radiation from the sun.
While this data was gathered from preclinical studies, senior author Sujit Basu, MD, PhD, says preliminary results in animal models are very promising and worthy of immediate further investigation through phase I human studies.
Basu and his colleagues reported their initial findings online ahead of print April 12 in Cancer Prevention Research, a journal of the American Association for Cancer Research.
According to the American Cancer Society, more than 5.4 million basal and squamous cell skin cancers are diagnosed annually in the United States. The disease typically recurs throughout a person’s lifetime, and advanced disease can lead to physical disfiguration. These cancers are linked to the sun’s damaging rays, and despite increased public awareness on sun safety precautions, rates of the disease have been increasing for many years.
Previous peer-reviewed, published studies have shown that dopamine receptors play a role in the development of cancerous tumors; however, their role in precancerous lesions is unknown.
In this new study, OSUCCC — James researchers report data showing that the neurotransmitter/neurohormone dopamine, by activating its D2 receptors, can stop the development and progression of certain UVB-induced precancerous squamous skin cancers. Researchers also describe the molecular sequence of events that leads to cancer suppression.
“Cancer control experts have been stressing the importance of reducing exposure to the sun and practicing sun-safe habits for many years, but scientific data shows us that cumulative damage of UV rays ultimately leads to skin cancer for many people. Finding better ways to prevent these cancers from developing is critical to reduce the global burden of this disease,” says Basu, a researcher with the OSUCCC — James Translational Therapeutics Research Program and a professor of pathology at The Ohio State University College of Medicine.
“Our study suggests that a commonly used drug that activates specific dopamine receptors could help reduce squamous cell skin cancer recurrence and possibly even prevent the disease entirely. This is especially exciting because this is a drug that is already readily used in clinical settings and is relatively inexpensive. We are excited to continue momentum in this area of research,” adds Basu.
The OSUCCC — James is working on plans to begin further testing in a phase I experimental clinical trial in the coming months.
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It has been long been known that cannabis users develop psychosis more often than non-users, but what is still not fully clear is whether cannabis actually causes psychosis and, if so, who is most at risk. A new study published in Translational Psychiatry by researchers at the Centre for Addiction and Mental Health (CAMH) and King’s College London helps shed light on both questions. The research shows that while cannabis users had higher rates of psychotic experiences than non-users across the board, the difference was especially pronounced among those with high genetic predisposition to schizophrenia.
“These results are significant because they’re the first evidence we’ve seen that people genetically prone to psychosis might be disproportionately affected by cannabis,” said lead author Dr. Michael Wainberg, Scientist the Krembil Centre for Neuroinformatics at CAMH. “And because genetic risk scoring is still in its early days, the true influence of genetics on the cannabis-psychosis relationship may be even greater than what we found here.”
Using data from the UK Biobank, a large-scale biomedical database containing participants’ in-depth genetic and health information, the authors analyzed the relationship between genetics, cannabis use and psychotic experiences across more than 100,000 people. Each person reported their frequency of past cannabis use, and whether they had ever had various types of psychotic experiences, such as auditory or visual hallucinations. The researchers also scored each person’s genetic risk for schizophrenia, by looking at which of their DNA mutations were more common among schizophrenia patients than among the general population.
Overall, people who had used cannabis were 50 per cent more likely to report psychotic experiences than people who had not. However, this increase was not uniform across the study group: among the fifth of participants with the highest genetic risk scores for schizophrenia, it was 60 per cent, and among the fifth with the lowest scores, it was only 40 per cent. In other words, people genetically predisposed to schizophrenia were at disproportionately higher risk for psychotic experiences if they also had a history of cannabis use.
Notably, because much less is known about the genetics of schizophrenia in non-white populations, the study’s analysis was limited to self-reported white participants. “This study, while limited in scope, is an important step forward in understanding how cannabis use and genetics may interact to influence psychosis risk,” added senior author Dr. Shreejoy Tripathy, Independent Scientist at the Krembil Centre for Neuroinformatics, who supervised the study. “The more we know about the connection between cannabis and psychosis, the more we can inform the public about the potential risks of using this substance. This research offers a window into a future where genetics can help empower individuals to make more informed decisions about drug use.”
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