Culture

Being highly connected to a strong social network has its benefits. Now a new University of Alberta study is showing the same goes for trees, thanks to their underground neighbours.

The study, published in the Journal of Ecology, is the first to show that the growth of adult trees is linked to their participation in fungal networks living in the forest soil.

Though past research has focused on seedlings, these findings give new insight into the value of fungal networks to older trees--which are more environmentally beneficial for functions like capturing carbon and stabilizing soil erosion.

"Large trees make up the bulk of the forest, so they drive what the forest is doing," said researcher Joseph Birch, who led the study for his PhD thesis in the Faculty of Agricultural, Life & Environmental Sciences.

When they colonize the roots of a tree, fungal networks act as a sort of highway, allowing water, nutrients and even the compounds that send defence signals against insect attacks to flow back and forth among the trees.

The network also helps nutrients flow to resource-limited trees "like family units that support one another in times of stress," Birch noted.

Cores taken from 350 Douglas firs in British Columbia showed that annual tree ring growth was related to the extent of fungal connections a tree had with other trees. "They had much higher growth than trees that had only a few connections."

The research also showed that trees with more connections to many unique fungi had much greater growth than those with only one or two connections.

"We found that the more connected an adult tree is, the more it has significant growth advantages, which means the network could really influence large-scale important interactions in the forest, like carbon storage. If you have this network that is helping trees grow faster, that helps sequester more carbon year after year."

It's also possible that if the trees grow faster, they'd have some ability to better survive drought that is expected to intensify with climate change, he added.

"These networks may help them grow more steadily even as conditions become more stressful, and could even help buffer trees against death."

Birch hopes his findings lead to further studies in different kinds of forests in other geographical areas, because it's likely that the connections among trees change from year to year, he said.

"It's a very dynamic system that is probably being broken apart and re-formed quite a bit, like family relationships, so we don't know how they will change under future climates either. Maybe a dry year or a beetle outbreak impacts the network.

"Knowing whether fungal networks are operating the same way in other tree species could factor into how we reforest areas after harvesting them, and it could inform how we want to plant trees to preserve these networks."

DURHAM, N.C. -- A team of Duke University researchers has developed a lab-grown living lung model that mimics the tiny air sacs of the lungs where coronavirus infection and serious lung damage take place. This advance has enabled them to watch the battle between the SARS-CoV-2 coronavirus and lung cells at the finest molecular scale.

The virus damages the delicate, balloon-like air sacs, known as alveoli, leading to pneumonia and acute respiratory distress, the leading cause of death in Covid-19 patients. But scientists have been hampered in Covid-19 studies by the lack of experimental models that mimic human lung tissues.

Now, a team led by Duke cell biologist Purushothama Rao Tata has developed a model using "lung organoids," also dubbed mini-lungs in a dish. The organoids are grown from alveolar epithelial type-2 cells (AT2s) which are the stem cells that repair the deepest portions of the lungs where SARS-CoV-2 attacks.

Earlier research at Duke had shown that just one AT2 cell, isolated into tiny dishes, could multiply to produce millions of cells that assemble themselves into balloon-like organoids that look just like alveoli. However, the "soup" in which the cells were grown contained complex ingredients such as serum from cows that is not completely defined.

Tata's group took on the big challenge of predicting and testing many combinations of chemically pure factors that would do the job just as well, a problem that required close co-operation with Duke's shared computing cluster.

The result is a purely human organoid without any helper cells. Mini-lungs grown in tiny wells will enable high throughput science, in which hundreds of experiments can be run simultaneously to screen for new drug candidates or to identify self-defense chemicals produced by lung cells in response to infection.

"This is a versatile model system that allows us to study not only SARS-CoV-2, but any respiratory virus that targets these cells, including influenza," Tata said. A paper describing the development of the mini-lungs and some early experiments with coronavirus infection appeared early online Oct. 21 in the journal Cell Stem Cell.

In using mini-lungs to study SARS-CoV-2 infection, Tata's team collaborated with virology colleagues at Duke and the University of North Carolina in Chapel Hill. To safely handle these deadly viruses, the researchers utilized state-of-the art biosafety level 3 facilities at Duke and UNC-CH to infect lung organoids. The researchers watched the gene activity and chemical signals that are produced by the lung cells after infection.

"This is a major breakthrough for the field because we were using cells that didn't have purified cultures," said Ralph Baric, a co-author on the paper who is a distinguished professor of epidemiology, microbiology and immunology at UNC and world authority on coronaviruses. The Duke mini-lungs are 100 percent human with no supporting cells that could confuse findings. "This is incredibly elegant work to figure out how to purify and grow AT2 cells in culture in pure form," Baric said.

Baric's lab is capable of changing any nucleotide of the Covid-19 virus's genetic code at will, so it produced a glowing version that would reveal where it went in the mini-lungs, confirming that it did indeed home in on the crucial ACE2 cell surface receptor, leading to infection.

When infected with the virus, the organoids were shown to launch an inflammatory response mediated by interferons. The researchers have also witnessed the cytokine storm of immune molecules the lungs launch in response to the virus.

"It was thought cytokine storm happened due to the large influx of immune cells, but we can see it also happens in the lung stem cells themselves," Tata said.

Tata's lab found the cells produced interferons and experienced self-destructive cell death, just as samples from Covid-19 patients have shown. The signal for cell suicide was sometimes triggered in uninfected neighboring lung cells as well, as the cells struggled to get ahead of the virus. The researchers also compared the gene activity patterns between the mini-lungs and samples from six severe Covid-19 patients and found they agreed with "striking similarity."

"We've only been able to see this from autopsies until now," Tata said. "Now we have a way to figure out how to energize the cells to fight against this deadly virus."

In another series of experiments, mini-lungs treated with low doses of interferons before infection were able to slow viral copying. But suppressing interferon activity before infection led to increased viral replication.

Tata, who is a part of Duke's regenerative medicine initiative, Regeneration Next, said his lab was working on growing the mini lungs in mid-2019 and had achieved a working model just as the coronavirus pandemic emerged. He said his group will be working with both academic and industry partners to use these cells for cell-based therapies and eventually to try to grow a complete lung for transplantation.

Baric said his lab will probably be using the mini-lungs to better understand a new strain of SARS-CoV-2 called D614G that has become the dominant version of the virus. This strain, which emerged in Italy, has a spike protein that is apparently more efficient at recognizing the ACE2 receptor on lung cells, making it even more infectious.

UNIVERSITY PARK, Pa. -- A new tool created by researchers at Penn State and Houston Methodist Hospital could diagnose a stroke based on abnormalities in a patient's speech ability and facial muscular movements, and with the accuracy of an emergency room physician -- all within minutes from an interaction with a smartphone.

"When a patient experiences symptoms of a stroke, every minute counts," said James Wang, professor of information sciences and technology at Penn State. "But when it comes to diagnosing a stroke, emergency room physicians have limited options: send the patient for often expensive and time-consuming radioactivity-based scans or call a neurologist -- a specialist who may not be immediately available -- to perform clinical diagnostic tests."

Wang and his colleagues have developed a machine learning model to aid in, and potentially speed up, the diagnostic process by physicians in a clinical setting.

"Currently, physicians have to use their past training and experience to determine at what stage a patient should be sent for a CT scan," said Wang. "We are trying to simulate or emulate this process by using our machine learning approach."

The team's novel approach is the first to analyze the presence of stroke among actual emergency room patients with suspicion of stroke by using computational facial motion analysis and natural language processing to identify abnormalities in a patient's face or voice, such as a drooping cheek or slurred speech.

The results could help emergency room physicians to more quickly determine critical next steps for the patient. Ultimately, the application could be utilized by caregivers or patients to make self-assessments before reaching the hospital.

"This is one of the first works that is enabling AI to help with stroke diagnosis in emergency settings," added Sharon Huang, associate professor of information sciences and technology at Penn State.

To train the computer model, the researchers built a dataset from more than 80 patients experiencing stroke symptoms at Houston Methodist Hospital in Texas. Each patient was asked to perform a speech test to analyze their speech and cognitive communication while being recorded on an Apple iPhone.

"The acquisition of facial data in natural settings makes our work robust and useful for real-world clinical use, and ultimately empowers our method for remote diagnosis of stroke and self-assessment," said Huang.

Testing the model on the Houston Methodist dataset, the researchers found that its performance achieved 79% accuracy -- comparable to clinical diagnostics by emergency room doctors, who use additional tests such as CT scans. However, the model could help save valuable time in diagnosing a stroke, with the ability to assess a patient in as little as four minutes.

"There are millions of neurons dying every minute during a stroke," said John Volpi, a vascular neurologist and co-director of the Eddy Scurlock Stroke Center at Houston Methodist Hospital. "In severe strokes it is obvious to our providers from the moment the patient enters the emergency department, but studies suggest that in the majority of strokes, which have mild to moderate symptoms, that a diagnosis can be delayed by hours and by then a patient may not be eligible for the best possible treatments."

"The earlier you can identify a stroke, the better options (we have) for the patients," added Stephen T.C. Wong, John S. Dunn, Sr. Presidential Distinguished Chair in Biomedical Engineering at the Ting Tsung and Wei Fong Chao Center for BRAIN and Houston Methodist Cancer Center. "That's what makes an early diagnosis essential."

Volpi said that physicians currently use a binary approach toward diagnosing strokes: They either suspect a stroke, sending the patient for a series of scans that could involve radiation; or they do not suspect a stroke, potentially overlooking patients who may need further assessment.

"What we think in that triage moment is being either biased toward overutilization (of scans, which have risks and benefits) or underdiagnosis," said Volpi, a co-author on the paper. "If we can improve diagnostics at the front end, then we can better expose the right patients to the right risks and not miss patients who would potentially benefit."

He added, "We have great therapeutics, medicines and procedures for strokes, but we have very primitive and, frankly, inaccurate diagnostics."

Other collaborators on the project include Tongan Cai and Mingli Yu, graduate students working with Wang and Huang at Penn State; and Kelvin Wong, associate research professor of electronic engineering in oncology at Houston Methodist Hospital.

WASHINGTON, Oct. 22, 2020 -- Over the last century, the compound ammonium nitrate has been involved in at least 30 disasters and terrorist attacks. Under normal circumstances, it's totally harmless and used in things like fertilizer, so what makes ammonium nitrate turn deadly?: https://youtu.be/-SeT3N3A19c.

Conducted by an international consortium, led by the London School of Hygiene & Tropical Medicine and the University of Maryland School of Medicine, the research is the first meta-analysis of preventive malaria treatments among school-age children.

The team pooled data from 11 different clinical studies that tested malaria preventative medications in 15,000 children aged 5 to 15 living in seven different countries across sub-Saharan Africa. Half were given preventive malaria treatment, whereas the other half were either given a placebo or not treated as a control.

Doses of preventive drugs were given as often as once a month, or as infrequently as once a year, depending on the study. The children were monitored for an average of 43 weeks. Six of the clinical trials evaluated cognitive function between children who received the malaria preventatives and those who did not.

Overall, the team found that preventive antimalarial treatment across all malaria transmission settings cuts the prevalence of malaria among schoolchildren by 46% and subsequent cases of clinical malaria by 50%.

Preventive treatment provided consistent protection for schoolchildren regardless of transmission setting - from areas where the underlying prevalence of malaria was greater than 50% and where it was less than 10%. Preventive treatment also reduced cases of anaemia among schoolchildren by 15% and, among children over 10 years of age, was associated with improved learning.

An estimated 3.4 billion people worldwide are at risk of contracting malaria, and 400,000 die from the disease every year, according to the World Health Organization (WHO). While the WHO recommends providing intermittent preventive treatment to pregnant women, infants and young children in some malaria-endemic areas, they have not issued recommendations for school-age children. This is despite growing evidence that use of these preventive mediations works to prevent infections.

Dr Matthew Chico, Assistant Professor of Public Health at the London School of Hygiene & Tropical Medicine and senior author, said: "School-aged children in malaria-endemic areas of sub-Saharan Africa are at substantial risk of infection, and often need treatment. Furthermore, this age group is a major reservoir for human-human transmission.

"Our study shows that preventive treatment of malaria among school-aged children reduces the burden of malaria in this age group. Combined with a malaria vaccine and insecticide treated bednets, a three-pronged approach might just produce the silver bullet we need for malaria elimination."

Malaria is transmitted by mosquitos infected with a parasite and remains prevalent in Africa, Central and South America, and Southeast Asia.

Malaria can cause fevers, headache and chills, as well as anaemia due to the parasite's destruction of red blood cells. Anaemia can cause severe fatigue, headaches, delayed development and poor performance in school. Malaria can also lead to organ failure and can be fatal if left untreated.

Public health campaigns to provide antimalarial medications to school-aged children may be a way to improve the health and wellness of children, but also to curb the disease spread in communities where malaria is endemic.

Dr Lauren Cohee, faculty member in the Malaria Research Program in the Center for Vaccine Development and Global Health at the University of Maryland School of Medicine and study first author, said: "Utilizing schools as a platform to deliver preventive treatment improves the feasibility of this intervention and builds upon the ever increasing rates of primary school enrolment across the malaria endemic world.

"Preventive treatment of malaria could be added to existing school-based health programs, including nutrition and deworming, to further promote the overall health of the learner."

The authors acknowledge limitations of their study, including the variability between studies. However, because the team combined individual participant data from 11 studies, it was possible to account for differences in study design and setting, treatment type, as well as participant characteristics in ways that would not otherwise be possible.

Doctors and biostatisticians at the University of Michigan Rogel Cancer Center have led the development and validation of a staging system to better predict outcomes and inform treatment decisions for men diagnosed with non-metastatic prostate cancer.

Although it is one of the most common cancers worldwide, prostate cancer remains one of the few major cancers for which the familiar, numerical staging system -- ranging from stage 1 to stage 4 -- has not been adopted into national guidelines for treatment or for the testing of new medicines in clinical trials.

The new proposed system -- dubbed STAR-CAP -- which appears in JAMA Oncology, draws on patient, tumor and outcomes data from nearly 20,000 patients from 55 centers in the U.S., Canada and Europe to create a robust model with strong prognostic power.

"Localized prostate cancer is sometimes less aggressive, sometimes more -- and whether we're patients, physicians or researchers, we all want to know as best we can how aggressive a particular cancer is likely to be," says study co-first author Robert Dess, M.D., an assistant professor of radiation oncology at Michigan Medicine. "That information helps with our conversations with patients, it helps with clinical trial design and it is particularly valuable when you can make those estimates based off of standard information that you would collect when you first see a patient to discuss their treatment options."

The system assigns patients to a particular stage through a point system based on several key variables. These include the patient's age, tumor category, Gleason grade of cell abnormality and prostate-specific antigen levels, also known as PSA levels. And STAR-CAP uses more granularity in these categories than many of the previous models, the authors note.

The model divides patients into nine stages of non-metastatic prostate cancer based on their point score -- from stage 1 to stage 3, with each stage split into substages of A, B and C.

STAR-CAP's predictions outperformed or equaled previous, non-validated models, including the current American Joint Committee on Cancer staging system, the study notes. And for a significant number of patients, the new model would reclassify them as having less advanced disease -- 22% of patients, for example, who would be classified as stage 3A under the AJCC's 8th edition criteria would be classified as stage 1C using the STAR-CAP system, a downgrade of four classification steps.

"This is the kind of information that can give patients and doctors more confidence when discussing treatment options and expected outcomes," Dess says.

Several years ago, the AJCC established criteria to evaluate prediction models for the staging of prostate cancer -- however, since no models met the criteria, the most recent staging designations were based on the consensus of experts in the field, says study co-senior author Daniel Spratt, M.D., the Laurie Snow Endowed Research Professor of Radiation Oncology at Michigan Medicine.

"None of the previous models evaluated met the criteria, so none of them could be used," Spratt says. "So we said, 'Well, let's make one.' We wanted it to be transparent, robust and validated, so that we can start moving closer to communicate using a common staging system, similar to other cancers. Right now we primarily categorize people as low risk, intermediate risk or high risk -- which is a fairly blunt and imprecise system."

Moreover, the new scoring system is designed to be able to be used worldwide with information that is commonly gathered about a patient and their cancer.

"We're leveraging a backbone of more than three decades of research," Dess says. "And we wanted to do it in a formal way and provide the best validated prognostic system we could come up with that was simple, easy to use, and that relied on readily available information."

The team has made the scoring system available to doctors and researcher worldwide via a web-based app at STAR-CAP.org.

"We know that some of the newest tools that we have that are just coming online like genomics or molecular imaging may improve upon this system, but we wanted to create the best, most widely accessible model based on the data we currently have -- understanding that new tools may help us develop even better models in the future," Dess says.

Both Dess and Spratt stressed that the effort would not have been possible without co-first author Krithika Suresh, Ph.D., a former biostatistics graduate student, and co-senior author Matthew Schipper, Ph.D., a research professor of biostatistics at the School of Public Health and research associate professor of radiation oncology at Michigan Medicine, who led the work's complex statistical analyses. Elizabeth Chase, a doctoral candidate in biostatistics was also instrumental, helping to design and develop the online web application, they said.

Nor would the work have been possible without the participation of numerous national and international collaborators.

"This work doesn't get done unless you have the collaborative spirit of investigators across the country and around world," Dess adds.

White Americans support strict immigration policies while at the same time favor the DREAM Act that would grant legal status to some immigrants who were brought to the United States as children, a contradiction linked to racial resentment and the belief that equality already exists, according to a Rutgers-led study.

"White Americans' support for punitive immigration policies hurt the very same group for which they support a pathway to legalization," said author Yalidy Matos, an assistant professor of political science at Rutgers' School of Arts and Sciences. "Racial resentment and the belief that equal opportunity is already available to all, known as anti-egalitarianism, are predispositions that underscore American values such as work ethic, meritocracy and individualism. The same values that lead people to support restrictive immigration policies also lead them to support the DREAM Act."

The study, published in the journal Perspective on Politics, found that in 2012, more than 48 percent of white Americans who supported the DREAM Act also supported police enforcement of immigration. Of these 48 percent, approximately 19 percent were Democrats, 40 percent were Independents and 41 percent were Republicans.

White Democrats' support for the DREAM Act and local immigration enforcement by the police is influenced by racial resentment and the belief that opportunity and equality already exists. White Republicans are only influenced by racial resentment.

Matos says white Americans' political behavior demonstrates that predispositions to these opposing beliefs can override partisanship for Democrats, leaving some to defect from party-aligned immigration policy preferences.

According to the data, Democrats (0.58), Independents (0.69) and Republicans (0.75) who support the DREAM Act and oppose sanctuary cities, a term applied to jurisdictions with policies designed to limit involvement in federal immigration enforcement actions, have higher levels of racial resentment than Democrats (0.24), Independents (0.34) and Republicans (0.59) who support the DREAM Act and support sanctuary cities.

Matos recommends Americans think broadly about supporting restrictive immigration policies, especially local level immigration enforcement programs that can nullify their own support towards the DREAM Act.

"Support for the DREAM Act is a great start but ultimately not enough to diminish the indirect effects of other immigration policies," Matos said. "Immigration reform at-large will continue to struggle in Congress if white Americans continue to be driven by the values of meritocracy and work ethic and define equality as equality of opportunity without regard to structural barriers. This is especially the case for Democrats and Independents."

SPOKANE, Wash. - Increasing the amount of time spent asleep immediately after a traumatic experience may ease any negative consequences, suggests a new study conducted by researchers at Washington State University's Elson S. Floyd College of Medicine.

Published today in Scientific Reports, the study helps build a case for the use of sleep therapeutics following trauma exposure, said William Vanderheyden, an assistant research professor and the lead author on the study. "Basically, our study has found that if you can improve sleep, you can improve function."

The finding holds particular promise for populations that are routinely exposed to trauma, such as military personnel and first responders, and may also benefit victims of accidents, natural disaster, violence, and abuse.

Vanderheyden made the discovery following a series of experiments in rats in which he and coauthor Christopher Davis examined the links between poor sleep and post-traumatic stress disorder (PTSD)--a psychiatric condition that affects an estimated 8 million Americans each year.

"People with PTSD oftentimes experience nightmares and other types of sleep disturbances, such as frequent awakenings and insomnia," said Vanderheyden. "One thought was that those sleep disturbances may cause further cognitive impairment and worsen the effects of PTSD or the initial trauma. So we wanted to see whether repairing the sleep disturbances associated with trauma exposure could help alleviate the symptoms of PTSD."

Their study used methods reviewed and approved by Washington State University's Institutional Animal Care and Use Committee, which oversees all university animal research procedures to ensure animals' humane treatment throughout their lifecycle. This included a commonly used PTSD rodent model in combination with optogenetics, a technique that uses light-sensitive proteins to control the activity of brain cells.

After going through the PTSD protocol, rats were assigned to two groups. In one group, the researchers used optogenetic stimulation to activate melanin-concentrating hormone (MCH)--a sleep-promoting brain cell type--over a period of seven days. Animals in the second group served as controls.

Comparing the two groups, the researchers found that optogenetic stimulation increased the duration of rapid eye movement (REM) sleep--the sleep phase thought to be important for learning and memory--across the rats' rest and active phases.

The researchers then assessed the rats' behavior on a three-day classical conditioning experiment involving a memory task. On day one, rats learned to associate an audible tone with the mildly unpleasant experience of receiving a small foot shock immediately after hearing the tone. After several occurrences, rats would freeze after hearing the tone, anticipating the foot shock. On day two, they heard the tone 30 times without receiving the shock, allowing them to gradually extinguish that memory. On the third day, the researchers played the tone 10 times to test to what extent the previous day's memory extinction had stuck. They found that rats that had received optogenetic stimulation to increase their sleep time had more successfully extinguished the memory, freezing less than control rats.

"This highlights that there is a time-sensitive window when--if you intervene to improve sleep--you could potentially stave off the negative effects of trauma," Vanderheyden said. "Conversely, it seems likely that if you are kept awake after a trauma, this could potentially be harmful to your cognitive function, though we haven't directly tested this as part of our study."

As an example, he mentioned victims of traffic accidents, who may not get much opportunity to sleep as they are poked, prodded, examined, and treated after being hospitalized for injuries. Though prioritizing sleep may not be feasible in victims with potentially life-threatening injuries, increasing sleep in other trauma-exposed populations could practically be done. Military personnel coming back from patrol could be encouraged to sleep and potentially be given sleep-promoting drugs to help them stave off any trauma experienced during their patrol, Vanderheyden said.

Vanderheyden cautioned that although their experiments suggest that manipulating sleep immediately after a trauma may be beneficial, such an intervention may or may not be effective for traumatic experiences that occurred in the more distant past.

As a next step, Vanderheyden and Davis want to delve deeper into molecular mechanisms that improve function in response to increased sleep. Their goal is to pinpoint those molecules that are important for regulating sleep or learning and memory, which will help them identify targets for the development of better drugs to help trauma-exposed populations.

Based on their findings, Vanderheyden also suggested that the use of antidepressants known as selective serotonin reuptake inhibitors (SSRIs) in people with PTSD may need to be reexamined, as SSRIs are known to suppress REM sleep.

"We may be doing our trauma victims a disservice by prescribing a class of drugs that actually eliminates a potential therapeutic avenue for them by removing their REM sleep when our findings suggest that we should be increasing REM sleep," Vanderheyden said.

'Mini-lungs' grown from tissue donated to Cambridge hospitals has provided a team of scientists from South Korea and the UK with important insights into how COVID-19 damages the lungs. Writing in the journal Cell Stem Cell, the researchers detail the mechanisms underlying SARS-CoV-2 infection and the early innate immune response in the lungs.

To date, there have been more than 40 million cases of COVID-19 and almost 1.13 million deaths worldwide. The main target tissues of SARS-CoV-2, the virus that causes COVID-19, especially in patients that develop pneumonia, appear to be alveoli - tiny air sacs in the lungs that take up the oxygen we breathe and exchange it with carbon dioxide to exhale.

To better understand how SARS-CoV-2 infects the lungs and causes disease, a team of scientists from the UK and South Korea turned to organoids - 'mini-organs' grown in three dimensions to mimic the behaviour of tissue and organs.

The team used tissue donated to tissue banks at the Royal Papworth Hospital NHS Foundation Trust and Addenbrooke's Hospital, Cambridge University NHS Foundations Trust, UK, and Seoul National University Hospital to extract a type of lung cell known as human lung alveolar type 2 cells. By reprogramming these cells back to their earlier 'stem cell' stage, they were able to grow self-organising alveolar-like 3D structures that mimic the behaviour of key lung tissue.

Dr Joo-Hyeon Lee, co-senior author, and a Group Leader at the Wellcome-MRC Cambridge Stem Cell Institute, University of Cambridge, said: "We still know surprisingly little about how SARS-CoV-2 infects the lungs and causes disease. Our approach has allowed us to grow 3D models of key lung tissue - in a sense, 'mini-lungs' - in the lab and study what happens when they become infected."

The team infected the organoids with a strain of SARS-CoV-2 taken from a patient in South Korea who was diagnosed with COVID-19 on 26 January 26 2020 after traveling to Wuhan, China. Using a combination of fluorescence imaging and single cell genetic analysis, they were able to study how the cells responded to the virus.

When the 3D models were exposed to SARS-CoV-2, the virus began to replicate rapidly, reaching full cellular infection just six hours after infection. Replication enables the virus to spread throughout the body, infecting other cells and tissue.

Around the same time, the cells began to produce interferons - proteins that act as warning signals to neighbouring cells, telling them to activate their antiviral defences. After 48 hours, the interferons triggered the innate immune response - its first line of defence - and the cells started fighting back against infection.

Sixty hours after infection, a subset of alveolar cells began to disintegrate, leading to cell death and damage to the lung tissue.

Although the researchers observed changes to the lung cells within three days of infection, clinical symptoms of COVID-19 rarely occur so quickly and can sometimes take more than ten days after exposure to appear. The team say there are several possible reasons for this. It may take several days from the virus first infiltrating the upper respiratory tract to it reaching the alveoli. It may also require a substantial proportion of alveolar cells to be infected or for further interactions with immune cells resulting in inflammation before a patient displays symptoms.

"Based on our model we can tackle many unanswered key questions, such as understanding genetic susceptibility to SARS-CoV-2, assessing relative infectivity of viral mutants, and revealing the damage processes of the virus in human alveolar cells," said Dr Young Seok Ju, co-senior author, and an Associate Professor at Korea Advanced Institute of Science and Technology. "Most importantly, it provides the opportunity to develop and screen potential therapeutic agents against SARS-CoV-2 infection."

"We hope to use our technique to grow these 3D models from cells of patients who are particularly vulnerable to infection, such as the elderly or people with diseased lungs, and find out what happens to their tissue," added Dr Lee.

New research from an immunology team at the University of Chicago may shed light on the challenges of developing a universal flu vaccine that would provide long-lasting and broad protection against influenza viruses.

The study, published October 22 in Immunity, explores the behavior of polyreactive antibodies -- antibodies that are capable of binding to more than one distinct antigen -- in an effort to understand their role against influenza viruses. The researchers identified that broadly neutralizing antibodies are commonly polyreactive and are preferentially induced by novel and pandemic-level influenza viruses.

The research is inspired by the limited efficacy of the annual flu vaccine, which must be adjusted each year to provide the best protection against commonly circulating strains of the virus, and why it so rarely induces broadly neutralizing antibodies.

"For whatever reason, when we are exposed to the flu virus, the antibody response mounted targets the parts of the virus that want to change, so you have to get vaccinated every year to keep up," said Jenna Guthmiller, PhD, a postdoctoral fellow at the University of Chicago. "But there are some parts of the virus that don't change. So why doesn't the seasonal flu vaccine produce antibodies that target those?"

This study has implications for the development of a universal flu vaccine that can elicit broadly neutralizing antibodies and that would only need be administered once or twice during a person's lifetime, instead of every year.

These polyreactive antibodies, like all antibodies, are produced by the body's B cells. When a person receives their annual flu vaccine, B cells will bind to the inactivated virus and begin generating antibodies against it, preparing the body to fight off the pathogen if it encounters the live flu virus in the environment.

This vaccine-induced immune response tends to produce very specific antibodies that target those frequently-changing epitopes on the surface of the virus, in contrast to broadly neutralizing antibodies that can identify the conserved regions that are the same every year.

It's not clear why these polyreactive antibodies aren't produced by the annual vaccine.

"Our research is trying to understand the features of broadly neutralizing antibodies, and why they're so rarely induced by the seasonal flu vaccine," said Guthmiller. "In this case, we were interested in understanding what gives polyreactive antibodies the ability to bind to multiple antigens, and the implications of that polyreactivity for the overall immune response."

The new study found that these polyreactive antibodies tend to bind to the portions of the flu virus that are conserved, and that they are preferentially produced when the body encounters a novel flu strain. Importantly, their unique ability to bind to more than one antigen is potentially due to their flexibility; the antibodies themselves can slightly adjust their conformation, allowing them to imperfectly bind to multiple similarly-shaped antigens.

This means that polyreactive antibodies are broadly neutralizing due to their ability to attach to and block the portions of influenza virus that are similar across strains and from year to year. Polyreactive antibodies are therefore ideal candidates for developing a universal flu vaccine -- one that can not only protect against common annual strains, but also novel influenza viruses, like the H1N1 strain seen during the 2009 pandemic.

The flexibility and strength of these polyreactive antibodies may make it seem like the ideal immune solution to protect against the flu, so why doesn't the seasonal flu vaccine tend to trigger their production?

In the study, the investigators also found that these polyreactive antibodies can sometimes bind to the body's own antigens, causing the polyreactive B cells to be destroyed to avoid an autoimmune response.

"What we're seeing is that there's this balance. Polyreactivity provides these beneficial features, like broader and better binding, but that comes at the cost of binding to self, which can cause issues," said Guthmiller. "Our seasonal flu vaccine keeps calling back the same specific antibody response because it's effective against these limited strains. To get these broadly neutralizing antibodies, like we'd want in a universal flu vaccine, we'll need something very different, but now we know this has the potential to be self-defeating because of this self-binding."

These results speak to the challenge of developing such a vaccine. "We already know it is difficult to target influenza in a universal fashion," said Patrick Wilson, PhD, a professor of medicine at UChicago. "For better or worse, this paper provides important insights into properties of antibodies that can more universally target many influenza strains."

The researchers are now working to understand how and why these polyreactive antibodies are self-reactive, and whether or not the immune system actively works to prevent them from being produced. Clarifying their role in the immune response will determine if these polyreactive antibodies can be leveraged safely and effectively and how they might be leveraged to produce a universal influenza vaccine.

Despite having bat-like wings, two small dinosaurs, Yi and Ambopteryx, struggled to fly, only managing to glide clumsily between the trees where they lived, according to a new study led by an international team of researchers, including McGill University Professor Hans Larsson. Unable to compete with other tree-dwelling dinosaurs and early birds, they went extinct after just a few million years. The findings, published in iScience, support that dinosaurs evolved flight in several different ways before modern birds evolved.

"We know some dinosaurs could fly before they evolved into birds," says Professor Larsson, Director of McGill's Redpath Museum. "What this shows us is that at least one lineage of dinosaurs experimented with a completely different mode of aerial locomotion. Gliding evolved countless times in arboreal amphibians, mammals, lizards, and even snakes - and now we have an example of dinosaurs."

Yi and Ambopteryx were small animals from the Late Jurassic of China, living about 160 million years ago. Weighing in at about half a kilogram, they are unusual theropod dinosaurs. Theropods are carnivorous dinosaurs that include all birds alive today. Most theropods were ground-loving carnivores, but Yi and Ambopteryx were at home in the trees and lived on a diet of insects, seeds, and plants.

"Once birds got into the air, these two species were so poorly capable of being in the air that they just got squeezed out," says lead author Thomas Dececchi, an assistant professor of biology at Mount Marty University. "Maybe you can survive a few million years underperforming, but you have predators from the top, competition from the bottom, and even some small mammals adding into that, squeezing them out until they disappeared."

Little creatures could glide, not fly

Curious about how these animals could have flown, the researchers, scanned fossils using Laser-Stimulated Fluorescence (LSF), a technique that uses laser light to pick up soft tissue details of their wing membranes that can't be seen with standard white light. Later, the team used mathematical models to predict how they might have flown, testing different variables like weight, wingspan, wing shape, and muscle placement.

"The results are clear these animals were not able to fly like birds," says Larsson. "They didn't have adaptations to even get close to the physical thresholds for powered flight, but their weird membranous wings do give them enough of an aerofoil to have glided. They are not comparable to living gliding squirrels or lizards but seem to have come up with a really novel way of getting a large enough wing membrane."

Although gliding is not an efficient form of flight since it can only be done if the animal has already climbed to a high point, it probably did help Yi and Ambopteryx stay out of danger while they were still alive.

"Living gliders don't travel long distances through the air," says Dececchi. "It's not efficient, but it can be used as an escape hatch. It's not a great thing to do, but sometimes it's a choice between losing a bit of energy and being eaten. Once they were put under pressure, they just lost their space. They couldn't win on the ground. They couldn't win in the air. They were done."

The researchers are now looking more closely at the musculoskeletal anatomy of these bat-winged and other feathered dinosaurs that evolved around the origin of birds. "The diversity of dinosaurs just before the origin of birds amazes me," Larsson says. "We used to think of birds evolving as a linear trend from their ground-dwelling dinosaur ancestry. We can know revise this textbook scenario to one that had an explosive diversity of experimentation, with dinosaurs evolving powered flight several times independently from birds, many having fully feathered wings but with bodies too heavy or wings too small to have gotten off the ground, and now, a weird bat-winged group of dinosaurs that were not only the first arboreal dinosaurs, but ones that glided! I feel like we are still just scratching the surface."

A team of medics from RUDN University conducted an experiment on rats and confirmed that surgeries in the nasal cavity can cause behavioral changes, namely, make the animals timider. This effect is associated with an ANS reaction triggered by stress. The results of the experiment were published in the Journal of Physics: Conference Series.

A deflected nasal septum can be corrected with a simple surgery that is often performed under local anesthesia. This procedure is recommended for patients with apnoea or chronic maxillitis. However, the side effects of the surgery include inflammations and edema. These processes and breathing difficulties caused by them can affect the autonomic nervous system (ANS) that regulates all involuntary functions of our body, such as digestion, blood supply, and heart rate maintenance. It is yet unknown what parts of the ANS react to septoplasty, and what behavioral changes such a reaction can lead to. A team of medics from RUDN University carried out experimental surgeries on rats and identified behavioral and physiological reactions to them.

For their experiment, the team chose ten healthy male rats. The animals received total anesthesia, and their septums were not actually cut but just scratched. No local painkillers or anti-inflammatory drugs were used after the surgery as they could have had an impact on the animals' ANSs. To assess the changes in their behavior, the team placed the rats in an unfamiliar environment: the so-called "open field", a square-shaped chamber with an open and well-lit center and holes in the center and all four corners. The open field test was performed once before the surgery and three times after it (in 2, 4, and 6 days, respectively). The medics also took electrocardiograms (ECG) of the rats before and after the procedure.

A minute by minute comparison of the animals' behavior in the open field before and after the surgery showed a considerable reduction of activity in the latter case. After the procedure, the animals were more reluctant to examine the chamber or enter the holes, stood motionless for long periods of time, left more droppings, and rarely got on their hind legs. The ECG showed that the rats' parasympathetic nervous systems that regulate relaxation and recovery processes were more active after the surgery.

According to the scientists, such behavioral changes may be due to post-surgical anxiety as well as physiological consequences such as inflammation, edema, and pain. Because of all these factors, the animals entered a depression-like state. The inflammation and shortage of oxygen activated the parasympathetic nervous system (PNS), and recovery processes started to dominate in the animals' bodies. Based on a combination of behavioral and physiological data, the medics concluded that the nasal cavity surgery caused the rats to experience stress.

"Before this experiment, we had worked on a study on heart rate changes in human patients after septoplasty. I believe, these two works have a lot in common. Our earlier work had also shown increased PNS activity in certain cases. Post-surgical stress is likely to cause changes in the hippocampus area which leads to altered behavior. We need further studies to identify optimal parameters of local and total anesthesia and post-surgical pain management to prevent such consequences," said PhD Igor Kastyro, a senior lecturer at the Department of Human Physiology, RUDN University.

Old friends get together to relax, share meals, and trust and support each other. In the latter part of life, these friendships are highly valued. Recent research shows this happens in chimpanzees as well as humans.

Chimpanzee and human friendships show many parallels, according to new research published this week in Science by associate professor Martin Muller at The University of New Mexico Anthropology department, associate professor of Anthropology and co-director of the Comparative Human and Primate Physiology Center Melissa Emery Thompson, and their colleagues.

This work, a collaboration among researchers at UNM, University of Michigan, Tufts University, and Harvard University, uses data from the Kanyawara chimpanzee community living in Kibale National Park in Uganda and was funded by the National Institutes of Health and the National Science Foundation. These chimpanzees have been studied for decades by the Kibale Chimpanzee Project, and researchers leveraged this exceptional dataset to test socioemotional selectivity theory - an influential idea in psychology aimed at explaining why humans show changes in social interactions during aging.

"I study chimpanzee behavior and physiology, partly to help understand the evolution of human behavior and physiology... This study was part of a larger project on aging and health in chimpanzees. We were interested to see whether chimpanzees showed changes in their social relationships with aging that mirrored those commonly seen in humans," said Muller, who has traveled to Kibale once or twice a year for 20 years to supervise the collection of these data, and, more recently, worked with graduate students at UNM to organize, clean, and analyze them.

"Dr. Emery Thompson and I were part of this study, as was our graduate student Drew Enigk. Drew provided the data on male dominance ranks for the paper. He went through large numbers of aggressive interactions among the chimpanzees to see who won and lost fights, and who was submissive to whom. He then assigned dominance ranks using an Elo rating procedure, as is done to rank football teams or chess players," Muller noted.

Wild chimpanzees share social aging patterns with humans, by prioritizing strong social bonds, and interacting with others in increasingly positive ways as they get older.

Chimpanzee friends prefer each other's company. They tend to travel in the same groups and sit in proximity. Chimpanzee friends reciprocate. They groom each other, share meat with each other, and support each other in disagreements with other chimpanzees, Muller observed. And friendships can persist over many years. In laboratory studies, chimpanzees trust their friends more than other individuals in risky situations. Endocrine studies have shown that grooming with friends is particularly effective in reducing stress.

Socioemotional selectivity theory proposes that people shift their social behavior from a focus on forming new friends in young adulthood, to maintaining a smaller network of close, fulfilling relationships in old age.

"The proposal is that this shift happens because of our human ability to monitor our own personal time horizons--how much time we have left in our life--which causes us to prioritize emotionally-fulfilling relationships when time is perceived to be running out," Muller explained.

Using 20 years of behavioral data, researchers found that chimpanzees, like humans, increasingly prioritized mutual and equitable friendships with others that invested in them as they got older. Younger adults, in contrast, were more likely to form lopsided relationships where their partner did not reciprocate. Older chimpanzees also were more likely to be seen alone, but tended to socialize more with important partners when they did join the group. Finally, they showed a positivity bias in their overall behavior: reducing their aggressive behavior while maintaining levels of affiliative grooming.

"A major motivation for this paper was testing socioemotional selectivity theory. A large psychological literature suggests that in humans, old age leads to a focus on existing close relationships, increased attention to and memory for positive social interactions, and reduced engagement in tension and conflict. Psychologists have argued that this emphasis on positive relationships and emotions in old age results from a conscious sense of impending mortality. When the end is near, people accentuate the positive and eliminate the negative," Muller said.

"While that may partly be true, our data suggest that something more fundamental may be happening with the aging process," he continued. "No one thinks that wild chimpanzees are conscious of their impending mortality, but they too seem to show this same shift away from negativity in old age. We think that the importance of coalitions and alliances in chimpanzee society may be a critical factor. We have shown in Kibale that despite failing health and falling social status, older chimpanzee males often continue to successfully compete for mating opportunities and sire offspring. They do this primarily by forming coalitions with other males. If older individuals are reliant on coalitions, then this might explain their focus on positive interactions with close friends. Humans, of course, also use coalitions and alliances to a much greater extent than most primates, so this similarity in aging with chimpanzees may not be coincidental."

Taken together, these results show that chimpanzees share these special social aging patterns with humans, even though they do not have the same rich future time perspective and knowledge of their own mortality that we have. This is the first demonstration that a nonhuman shares these characteristics with us. The shared pattern between chimpanzees and humans could represent an adaptive response where older adults focus on important social relationships that provide benefits, and avoid interactions that have negative consequences as they lose competitive fighting ability. This research highlights how long-term behavioral datasets from wild animals like chimpanzees can help us understand and promote healthy aging in humans.

BIRMINGHAM, Ala. - Type 1 diabetes, or T1D, results from the autoimmune destruction of the insulin-producing cells of the pancreas. People with T1D require exogenous insulin and suffer swings in the levels of glucose in the blood that impact life expectancy and increase risks of cardiovascular disease, neuropathies and kidney failure.

One therapy is promising -- transplanting pancreatic islets from cadavers. But this requires immunosuppression, and reactivated autoimmunity leads to low graft viability and function after five years.

Now, a team of University of Alabama at Birmingham researchers has shown a simple way to protect transplanted islets, by coating them with a thin skin of alternating layers of two biopolymers. As reported in the journal Diabetes, this coating delays allograft and autoimmune-mediated rejection in mouse models of T1D.

"Our approach to inhibit proinflammatory immune responses with poly(N-vinylpyrrolidone)-tannic acid-encapsulated islets without systemic immunosuppression is a significant advancement toward successful islet transplants in humans," said senior authors Hubert Tse, Ph.D., and Eugenia Kharlampieva, Ph.D.

The biocompatible poly(N-vinylpyrrolidone)-tannic acid, or PVPON and tannic acid, or TA, are coated onto the islets in multiple alternating layers that are thin enough to allow oxygen and nutrients to easily reach the cells. This nano-thin encapsulation is about 120 times thinner than a sheet of plastic cling wrap. The key to its autoimmune protection, the UAB researchers say, are the layers of TA. This phenolic compound can scavenge reactive oxygen species and has an anti-inflammatory effect.

Oxidative stress from reactive oxygen species, or ROS, was already known to play a key role in the activation of alloreactive and autoreactive immunity toward engrafted islets, and the insulin-producing beta cells of the islets are more sensitive to ROS than many other cells of the body.

In autoimmune transplant experiments for the UAB study, more than half of the (PVPON/TA)-encapsulated grafts survived at 70 days post-transplant, while less than a quarter of the non-encapsulated grafts survived. In alloimmune transplant experiments, where the islets came from a different strain of mice, about 40 percent of the encapsulated grafts survived at 120 days post-transplant, while all of the unencapsulated grafts were rejected in less than 50 days.

In both types of transplantation, systemic immunosuppression was absent. The (PVPON/TA)-encapsulated islets maintained euglycemia significantly longer than non-encapsulated islets, and the grafts were immunomodulatory.

The mice receiving the encapsulated grafts had significant decreases in immune cell infiltration, ROS synthesis, inflammatory chemokines, cytokines and CD8 T cell infiltration, as compared to mice getting the non-encapsulated islets. ROS is known to promote proinflammatory M1 macrophages differentiation; in contrast, the mice receiving the encapsulated islets showed an increase in anti-inflammatory M2 macrophages.

Tse and Kharlampieva say much more can be done to improve immunosuppression by the encapsulation and extend that protection to other sources of islets that are more readily available than human cadaver islets.

"PVPON/TA coatings can be modified to increase the number of layers of PVPON and TA for
encapsulation, complexed with immune inhibitory receptors, including CTLA-4, PD-L1, and/or anti-inflammatory cytokines like IL-10 and TGF-beta, to further enhance localized immunosuppression," they said. "The use of PVPON/TA coatings is not limited to encapsulation of human islets, as our preliminary studies also demonstrate that PVPON/TA encapsulation does not compromise neonatal porcine islet function and can also be expanded to include human stem cell-derived pancreatic beta-cells."

Measures of Earth's vibrations zigged and zagged across Mostafa Mousavi's screen one morning in Memphis, Tenn. As part of his PhD studies in geophysics, he sat scanning earthquake signals recorded the night before, verifying that decades-old algorithms had detected true earthquakes rather than tremors generated by ordinary things like crashing waves, passing trucks or stomping football fans.

"I did all this tedious work for six months, looking at continuous data," Mousavi, now a research scientist at Stanford's School of Earth, Energy & Environmental Sciences (Stanford Earth), recalled recently. "That was the point I thought, 'There has to be a much better way to do this stuff.'"

This was in 2013. Handheld smartphones were already loaded with algorithms that could break down speech into sound waves and come up with the most likely words in those patterns. Using artificial intelligence, they could even learn from past recordings to become more accurate over time.

Seismic waves and sound waves aren't so different. One moves through rock and fluid, the other through air. Yet while machine learning had transformed the way personal computers process and interact with voice and sound, the algorithms used to detect earthquakes in streams of seismic data have hardly changed since the 1980s.

That has left a lot of earthquakes undetected.

Big quakes are hard to miss, but they're rare. Meanwhile, imperceptibly small quakes happen all the time. Occurring on the same faults as bigger earthquakes - and involving the same physics and the same mechanisms - these "microquakes" represent a cache of untapped information about how earthquakes evolve - but only if scientists can find them.

In a recent paper published in Nature Communications, Mousavi and co-authors describe a new method for using artificial intelligence to bring into focus millions of these subtle shifts of the Earth. "By improving our ability to detect and locate these very small earthquakes, we can get a clearer view of how earthquakes interact or spread out along the fault, how they get started, even how they stop," said Stanford geophysicist Gregory Beroza, one of the paper's authors.

Focusing on what matters

Mousavi began working on technology to automate earthquake detection soon after his stint examining daily seismograms in Memphis, but his models struggled to tune out the noise inherent to seismic data. A few years later, after joining Beroza's lab at Stanford in 2017, he started to think about how to solve this problem using machine learning.

The group has produced a series of increasingly powerful detectors. A 2018 model called PhaseNet, developed by Beroza and graduate student Weiqiang Zhu, adapted algorithms from medical image processing to excel at phase-picking, which involves identifying the precise start of two different types of seismic waves. Another machine learning model, released in 2019 and dubbed CRED, was inspired by voice-trigger algorithms in virtual assistant systems and proved effective at detection. Both models learned the fundamental patterns of earthquake sequences from a relatively small set of seismograms recorded only in northern California.

In the Nature Communications paper, the authors report they've developed a new model to detect very small earthquakes with weak signals that current methods usually overlook, and to pick out the precise timing of the seismic phases using earthquake data from around the world. They call it Earthquake Transformer.

According to Mousavi, the model builds on PhaseNet and CRED, and "embeds those insights I got from the time I was doing all of this manually." Specifically, Earthquake Transformer mimics the way human analysts look at the set of wiggles as a whole and then hone in on a small section of interest.

People do this intuitively in daily life - tuning out less important details to focus more intently on what matters. Computer scientists call it an "attention mechanism" and frequently use it to improve text translations. But it's new to the field of automated earthquake detection, Mousavi said. "I envision that this new generation of detectors and phase-pickers will be the norm for earthquake monitoring within the next year or two," he said.

The technology could allow analysts to focus on extracting insights from a more complete catalog of earthquakes, freeing up their time to think more about what the pattern of earthquakes means, said Beroza, the Wayne Loel Professor of Earth Science at Stanford Earth.

Hidden faults

Understanding patterns in the accumulation of small tremors over decades or centuries could be key to minimizing surprises - and damage - when a larger quake strikes.

The 1989 Loma Prieta quake ranks as one of the most destructive earthquake disasters in U.S. history, and as one of the largest to hit northern California in the past century. It's a distinction that speaks less to extraordinary power in the case of Loma Prieta than to gaps in earthquake preparedness, hazard mapping and building codes - and to the extreme rarity of large earthquakes.

Only about one in five of the approximately 500,000 earthquakes detected globally by seismic sensors every year produce shaking strong enough for people to notice. In a typical year, perhaps 100 quakes will cause damage.

In the late 1980s, computers were already at work analyzing digitally recorded seismic data, and they determined the occurrence and location of earthquakes like Loma Prieta within minutes. Limitations in both the computers and the waveform data, however, left many small earthquakes undetected and many larger earthquakes only partially measured.

After the harsh lesson of Loma Prieta, many California communities have come to rely on maps showing fault zones and the areas where quakes are likely to do the most damage. Fleshing out the record of past earthquakes with Earthquake Transformer and other tools could make those maps more accurate and help to reveal faults that might otherwise come to light only in the wake of destruction from a larger quake, as happened with Loma Prieta in 1989, and with the magnitude-6.7 Northridge earthquake in Los Angeles five years later.

"The more information we can get on the deep, three-dimensional fault structure through improved monitoring of small earthquakes, the better we can anticipate earthquakes that lurk in the future," Beroza said.

Earthquake Transformer

To determine an earthquake's location and magnitude, existing algorithms and human experts alike look for the arrival time of two types of waves. The first set, known as primary or P waves, advance quickly - pushing, pulling and compressing the ground like a Slinky as they move through it. Next come shear or S waves, which travel more slowly but can be more destructive as they move the Earth side to side or up and down.

To test Earthquake Transformer, the team wanted to see how it worked with earthquakes not included in training data that are used to teach the algorithms what a true earthquake and its seismic phases look like. The training data included one million hand-labeled seismograms recorded mostly over the past two decades where earthquakes happen globally, excluding Japan. For the test, they selected five weeks of continuous data recorded in the region of Japan shaken 20 years ago by the magnitude-6.6 Tottori earthquake and its aftershocks.

The model detected and located 21,092 events - more than two and a half times the number of earthquakes picked out by hand, using data from only 18 of the 57 stations that Japanese scientists originally used to study the sequence. Earthquake Transformer proved particularly effective for the tiny earthquakes that are harder for humans to pick out and being recorded in overwhelming numbers as seismic sensors multiply.

"Previously, people had designed algorithms to say, find the P wave. That's a relatively simple problem," explained co-author William Ellsworth, a research professor in geophysics at Stanford. Pinpointing the start of the S wave is more difficult, he said, because it emerges from the erratic last gasps of the fast-moving P waves. Other algorithms have been able to produce extremely detailed earthquake catalogs, including huge numbers of small earthquakes missed by analysts - but their pattern-matching algorithms work only in the region supplying the training data.

With Earthquake Transformer running on a simple computer, analysis that would ordinarily take months of expert labor was completed within 20 minutes. That speed is made possible by algorithms that search for the existence of an earthquake and the timing of the seismic phases in tandem, using information gleaned from each search to narrow down the solution for the others.

"Earthquake Transformer gets many more earthquakes than other methods, whether it's people sitting and trying to analyze things by looking at the waveforms, or older computer methods," Ellsworth said. "We're getting a much deeper look at the earthquake process, and we're doing it more efficiently and accurately."

The researchers trained and tested Earthquake Transformer on historic data, but the technology is ready to flag tiny earthquakes almost as soon as they happen. According to Beroza, "Earthquake monitoring using machine learning in near real-time is coming very soon."