Culture

Ancient Maya in the once-bustling city of Tikal built sophisticated water filters using natural materials they imported from miles away, according to the University of Cincinnati.

UC researchers discovered evidence of a filter system at the Corriental reservoir, an important source of drinking water for the ancient Maya in what is now northern Guatemala.

A multidisciplinary team of UC anthropologists, geographers and biologists identified crystalline quartz and zeolite imported miles from the city. The quartz found in the coarse sand along with zeolite, a crystalline compound consisting of silicon and aluminum, create a natural molecular sieve. Both minerals are used in modern water filtration.

The filters would have removed harmful microbes, nitrogen-rich compounds, heavy metals such as mercury and other toxins from the water, said Kenneth Barnett Tankersley, associate professor of anthropology and lead author of the study.

"What's interesting is this system would still be effective today and the Maya discovered it more than 2,000 years ago," Tankersley said.

UC's discovery was published in the journal Scientific Reports.

The Maya created this water filtration system nearly 2,000 years before similar systems were used in Europe, making it one of the oldest water treatment systems of its kind in the world, Tankersley said.

Researchers from UC's College of Arts and Sciences traced the zeolite and quartz to steep ridges around the Bajo de Azúcar about 18 miles northeast of Tikal. They used X-ray diffraction analysis to identify zeolite and crystalline quartz in the reservoir sediments.

At Tikal, zeolite was found exclusively in the Corriental reservoir. 

For the ancient Maya, finding ways to collect and store clean water was of critical importance. Tikal and other Maya cities were built atop porous limestone that made ready access to drinking water difficult to obtain for much of the year during seasonal droughts.

UC geography professor and co-author Nicholas Dunning, who has studied ancient civilizations most of his career, found a likely source of the quartz and zeolite about 10 years ago while conducting fieldwork in Guatemala.

"It was an exposed, weathered volcanic tuff of quartz grains and zeolite. It was bleeding water at a good rate," he said. "Workers refilled their water bottles with it. It was locally famous for how clean and sweet the water was."

Dunning took samples of the material. UC researchers later determined the quartz and zeolite closely matched the minerals found at Tikal. 

UC assistant research professor Christopher Carr, an expert in geographic information system mapping, also conducted work on the UC projects at Bajo de Azúcar and Corriental.

"It was probably through very clever empirical observation that the ancient Maya saw this particular material was associated with clean water and made some effort to carry it back," Dunning said.

UC anthropology professor emeritus Vernon Scarborough, another co-author, said most research on ancient water management has tried to explain how civilizations conserved, collected or diverted water. 

"The quality of water put to potable ends has remained difficult to address," Scarborough said. "This study by our UC team has opened the research agenda by way of identifying the quality of a water source and how that might have been established and maintained."

Of course, reconstructing the lives, habits and motivations of a civilization 1,000 years ago is tricky.

"We don't have absolute proof, but we have strong circumstantial evidence," Dunning said. "Our explanation makes logical sense."

"This is what you have to do as an archaeologist," UC biologist and co-author David Lentz said. "You have to put together a puzzle with some of the pieces missing."

Lentz said the filtration system would have protected the ancient Maya from harmful cyanobacteria and other toxins that might otherwise have made people who drank from the reservoir sick.

"The ancient Maya figured out that this material produced pools of clear water," he said.

Complex water filtration systems have been observed in other ancient civilizations from Greece to Egypt to South Asia, but this is the first observed in the ancient New World, Tankersley said.

"The ancient Maya lived in a tropical environment and had to be innovators. This is a remarkable innovation," Tankersley said. "A lot of people look at Native Americans in the Western Hemisphere as not having the same engineering or technological muscle of places like Greece, Rome, India or China. But when it comes to water management, the Maya were millennia ahead."

Couples that pray together stay together. It's a common religious saying, but a new study from the University of Georgia is giving the proverb some scientific credence.

Churches, mosques and synagogues provide a kind of built-in social life for their members, with religious services, classes and various other gatherings. Going to those types of events with your partner can help strengthen your marriage, especially as you and your partner age, according to the study published by the American Psychological Association's Journal of Psychology of Religion and Spirituality. The researchers also found that partners who didn't originally identify as very religious but frequently engaged in common hobbies or activities together saw their participation in religion grow as a couple over the duration of the study.

"I see this with many retirees--they're sitting in retirement and sometimes it seems as though they get stuck in a rut. At times it can seem like they don't know what to do with all this time they have now. This can be damaging not only to their own well-being, but it can take a toll on their relationship with their spouse," said lead author Victoria King, a postdoctoral researcher at UGA's Center for Family Research. "Engaging in joint hobbies and finding things that they can do together is important and can help strengthen their relationship. Perhaps that hobby might be getting more involved in church. I know that my grandparents look forward to their church related activities that they do together."

The researchers followed 371 couples, most of whom had been married for about 30 years.

The study measured partners' levels of religiosity by gauging how important religion is to them and how often they attended religious services. They also examined how often couples participated in joint activities, such as going on walks or bike rides, taking weekend trips without their children and spending time on hobbies together, among other things. Additionally, study participants were asked how happy they were with their marital relationship and their overall satisfaction with the state of their marriage.

Previous research has shown that as individuals age, the importance of religion in their lives often increases. Because most religions emphasize the sanctity of marriage and the family unit, it makes sense that religious involvement would encourage couples to place an added value on doing things together and keeping their families strong, King said.

"Families and couples now are always pulled in so many different directions, with jam-packed schedules, and family time is often pushed aside," King said. "It is important to find those little times where families or couples can engage in some sort of joint activity together that they can enjoy."

The findings also showed that the driving factor appeared to be the wives. They were the ones who reported being more religious or spending more time with their husbands, meaning that women may spend more time engaging in relationship maintenance than their spouses. Because of that, they may have been more likely to suggest doing things as a couple or becoming more involved in church.

Ivan Smirnov, Leading Research Fellow of the Laboratory of Computational Social Sciences at the Institute of Education of HSE University, has created a computer model that can distinguish high academic achievers from lower ones based on their social media posts. The prediction model uses a mathematical textual analysis that registers users' vocabulary (its range and the semantic fields from which concepts are taken), characters and symbols, post length, and word length.

Every word has its own rating (a kind of IQ). Scientific and cultural topics, English words, and words and posts that are longer in length rank highly and serve as indicators of good academic performance. An abundance of emojis, words or whole phrases written in capital letters, and vocabulary related to horoscopes, driving, and military service indicate lower grades in school. At the same time, posts can be quite short--even tweets are quite informative. The study was supported by a grant from the Russian Science Foundation (RSF), and an article detailing the study's results was published in EPJ Data Science.

Smirnov's study used a representative sample of data from HSE University's longitudinal cohort panel study, 'Educational and Career Trajectories' (TrEC). The study traces the career paths of 4,400 students in 42 Russian regions from high schools participating in PISA (the Programme for International Students Assessment). The study data also includes data about the students' VK accounts (3,483 of the student participants consented to provide this information).

'Since this kind of data, in combination with digital traces, is difficult to obtain, it is almost never used,' Smirnov says. Meanwhile, this kind of dataset allows you to develop a reliable model that can be applied to other settings. And the results can be extrapolated to all other students--high school students and middle school students.

Posts from publicly viewable VK pages were used as a training sample--this included a total of 130,575 posts from 2,468 subjects who took the PISA test in 2012. The test allowed the researcher to assess a student's academic aptitude as well as their ability to apply their knowledge in practice. The study included only publicly visible VK posts from consenting participants.

When developing and testing the model from the PISA test, only students' reading scores were used an indicator of academic aptitude, although there are three tests in total: reading, mathematics, and science. PISA defines reading literacy as 'understanding, using, reflecting on and engaging with written texts in order to achieve one's goals, to develop one's knowledge and potential, and to participate in society.' The exam has six proficiency levels. Students who score a 2 are considered to meet only the basic, minimum level, while those who score a 5 or 6 are considered to be strong students.

In the study, unsupervised machine learning with word vector representations was performed on VK post corpus (totaling 1.9 billion words, with 2.5 million unique words). It was combined with a simpler supervised machine learning model that was trained in individual positions and taught to predict PISA scores.

'We represented each post as a 300-dimensional vector by averaging over vector representations of all its constituent words,' Smirnov writes. 'These post representations were used to train a linear regression model to predict the PISA scores of the posts' authors.'

By 'predict', the researcher does not refer to future forecasting, but rather the correlation between the calculated results and the real scores students earned on the PISA exam, as well as their USE scores (which are publicly available online in aggregated form--i.e., average scores per school). In the preliminary phase, the model learned how to predict the PISA data. In the final model, the calculations were checked against the USE results of high school graduates and university entrants.

The final model was supposed to be able to reliably recognize whether a strong student or a weak student had written a particular social media post, or in other words, differentiate the subjects according to their academic performance. After the training period, the model was able to distinguish posts written by students who scored highly or poorly on PISA (levels 5-6 and levels 0-1) with an accuracy of 93.7%. As for the comparability of PISA and the USE, although these two tests differ, studies have shown that students' scores for the two tests strongly correlate with each other.

'The model was trained using PISA data, and we looked at the correlation between the predicted and the real PISA scores (which are available in the TrEC study),' Smirnov explains. 'With the USE things gets more complicated: since the model does not know anything about the unified exams, it predicted the PISA scores as before. But if we assume that the USE and PISA measure the same thing -- academic performance -- then the higher the predicted PISA results are, the higher the USE results should be.' And the fact that the model learned to predict one thing and can predict another is quite interesting in itself, Smirnov notes.

However, this also needed to be verified, so the model was then applied to 914 Russian high schools (located in St. Petersburg, Samara and Tomsk; this set included almost 39,000 users who created 1.1 million posts) and one hundred of Russia's largest universities (115,800 people; 6.5 million posts) to measure the academic performance of students at these institutions.

It turned out that 'predicted academic performance is closely related to USE scores,' says Smirnov. 'The correlation coefficient is between 0.49 and 0.6. And in the case of universities, when the predicted academic performance and USE scores of applicants were compared (the information is available in HSE's ongoing University Admissions Quality Monitoring study), then the results also demonstrated a strong connection. The correlation coefficient is 0.83, which is significantly higher than for high schools, because there is more data.'

But can the model be applied to other social media sites? 'I checked what would happen if, instead of posts on VK, we gave the model tweets written by the same users,' Smirnov says. 'It turned out that the quality of the model does not significantly decrease.' But since a sufficient number of twitter accounts were available only for the university dataset (2,836), the analysis was performed only on this set.

It is important that the model worked successfully on datasets of different social media sites, such as VK and Twitter, thereby proving that is can be effective in different contexts. This means that it can be applied widely. In addition, the model can be used to predict very different characteristics, from student academic performance to income or depression.

Smirnov's study used a representative sample of data from HSE University's longitudinal cohort panel study, 'Educational and Career Trajectories' (TrEC). The study traces the career paths of 4,400 students in 42 Russian regions from high schools participating in PISA (the Programme for International Students Assessment). The study data also includes data about the students' VK accounts (3,483 of the student participants consented to provide this information).

'Since this kind of data, in combination with digital traces, is difficult to obtain, it is almost never used,' Smirnov says. Meanwhile, this kind of dataset allows you to develop a reliable model that can be applied to other settings. And the results can be extrapolated to all other students--high school students and middle school students.

Posts from publicly viewable VK pages were used as a training sample--this included a total of 130,575 posts from 2,468 subjects who took the PISA test in 2012. The test allowed the researcher to assess a student's academic aptitude as well as their ability to apply their knowledge in practice. The study included only publicly visible VK posts from consenting participants.

It is important that the scores on the standardized PISA and USE tests were used as an academic aptitude metric. This gives a more objective picture than assessment mechanisms that are school-specific (such as grades).

When developing and testing the model from the PISA test, only students' reading scores were used an indicator of academic aptitude, although there are three tests in total: reading, mathematics, and science. PISA defines reading literacy as 'understanding, using, reflecting on and engaging with written texts in order to achieve one's goals, to develop one's knowledge and potential, and to participate in society.' The exam has six proficiency levels. Students who score a 2 are considered to meet only the basic, minimum level, while those who score a 5 or 6 are considered to be strong students.

In the study, unsupervised machine learning with word vector representations was performed on VK post corpus (totaling 1.9 billion words, with 2.5 million unique words). It was combined with a simpler supervised machine learning model that was trained in individual positions and taught to predict PISA scores.

Word vector representations, or word embedding, is a numeric vector of a fixed size that describes some features of a word or their sequence. Embedding is often used for automated word processing. In Smirnov's research, the fastText system was used since it is particularly conducive to working with Russian-language text.

'We represented each post as a 300-dimensional vector by averaging over vector representations of all its constituent words,' Smirnov writes. 'These post representations were used to train a linear regression model to predict the PISA scores of the posts' authors.'

By 'predict', the researcher does not refer to future forecasting, but rather the correlation between the calculated results and the real scores students earned on the PISA exam, as well as their USE scores (which are publicly available online in aggregated form--i.e., average scores per school). In the preliminary phase, the model learned how to predict the PISA data. In the final model, the calculations were checked against the USE results of high school graduates and university entrants.

Results

First, Smirnov highlighted the general textual features of posts in relation to the academic performance of their authors (Fig. 1). The use of capitalized words (-0.08), emojis (-0.06), and exclamations (-0.04) were found to be negatively correlated with academic performance. The use of the Latin characters, average post and word length, vocabulary size, and entropy of users' texts on the other hand, were found to positively correlate with academic performance (from 0.07 to 0.16, respectively).

It was also confirmed that students with different levels of academic performance have different vocabulary ranges. Smirnov explored the resulting model by selecting 400 words with the highest and lowest scores that appear at least 5 times in the training corpus. Thematic clusters were identified and visualized (Fig. 2).

The clusters with the highest scores (in orange) include:

English words (above, saying, yours, must);

Words related to literature (Bradbury, Fahrenheit, Orwell, Huxley, Faulkner, Nabokov, Brodsky, Camus, Mann);

Concepts related to reading (read, publish, book, volume);

Terms and names related to physics (Universe, quantum, theory, Einstein, Newton, Hawking);
Words related to thought processes (thinking, memorizing).

Clusters with low scores (in green) include misspelled words, names of popular computer games, concepts related to military service (army, oath, etc.), horoscope terms (Aries, Sagittarius), and words related to driving and car accidents (collision, traffic police, wheels, tuning).

Smirnov calculated the coefficients for all 2.5 million words of the vector model and made them available for further study. Interestingly, even words that are rarely found in a training dataset can predict academic performance. For example, even if the name 'Newt' (as in the Harry Potter character, Newt Scamander) never appears in the training dataset, the model might assign a higher rating to posts that contain it. This will happen if the model learns that words from novel series are used by high-achieving students, and, through unsupervised learning, 'intuit' that that the name 'Newt' belongs to this category (that is, the word is closely situated to other concepts from Harry Potter in the vector space).

Only 4 percent of all cancer therapeutic drugs under development earn final approval by the U.S. Food and Drug Administration (FDA).

"That's because right now we can't match the right combination of drugs to the right patients in a smart way," said Trey Ideker, PhD, professor at University of California San Diego School of Medicine and Moores Cancer Center. "And especially for cancer, where we can't always predict which drugs will work best given the unique, complex inner workings of a person's tumor cells."

In a paper published October 20, 2020 in Cancer Cell, Ideker and Brent Kuenzi, PhD, and Jisoo Park, PhD, postdoctoral researchers in his lab, describe DrugCell, a new artificial intelligence (AI) system they created that not only matches tumors to the best drug combinations, but does so in a way that makes sense to humans.

"Most AI systems are 'black boxes' -- they can be very predictive, but we don't actually know all that much about how they work," said Ideker, who is also co-director of the Cancer Cell Map Initiative and the National Resource for Network Biology.

He gave the example of the way an internet image search for "cat" works. AI systems working behind the scenes are trained on existing cat images, but how they actually label a new image as "cat" and not "rat" or something else is unknown.

For AI to be useful in health care, Ideker said, we have to be able to see inside the black box to understand how the system comes to its conclusions. "We need to know why that decision is made, what pathways those recommended drugs are targeting and the reasons for a positive drug response or for its rejection."

The team's work on DrugCell began several years ago in yeast. In a previous study , they built an AI system called DCell using information about a yeast cell's genes and mutations. DCell predicted cellular behaviors, such as growth, all outside the "black box."

DrugCell, a next-generation version of DCell, was trained on more than 1,200 tumor cell lines and their responses to nearly 700 FDA-approved and experimental therapeutic drugs -- a total of more than 500,000 cell line/drug pairings. The researchers also validated some of DrugCell's conclusions in laboratory experiments.

With DrugCell, the team can input data about a tumor and the system returns the best known drug, the biological pathways that control response to that drug, and combinations of drugs to best treat the malignancy.

Precision cancer therapy is already available at Moores Cancer Center at UC San Diego Health, where patients may have a biopsy of their tumor sequenced for mutations and assessed by the Molecular Tumor Board, an interdisciplinary group of experts. The board recommends personalized therapies based on the patient's unique genomic alterations and other information. A recent study showed these patients have better outcomes. In a way, DrugCell simulates the human Molecular Tumor Board.

"We were surprised by how well DrugCell was able to translate from laboratory cell lines, which is what we trained the model on, to tumors in mice and patients, as well as clinical trial data," Kuenzi said.

The team's ultimate goal is to get DrugCell into clinics for the benefit of patients, but the study authors caution there's still a lot of work to do.

"While 1,200 cell lines is a good start, it's of course not representative of the full heterogeneity of cancer," Park said. "Our team is now adding more single-cell data and trying different drug structures. We also hope to partner with existing clinical studies to embed DrugCell as a diagnostic tool, testing it prospectively in the real world."

Poop is full of secrets. For scientists, digging into feces provides insights into animal diets and is particularly useful for understanding nocturnal or rare species. When animals eat, prey DNA travels all the way through animal digestive tracts and comes out again. Poop contains very precise information about the prey species consumed. At the Smithsonian Tropical Research Institute (STRI), a team explored the eating habits of the fringe-lipped bat (Trachops cirrhosus) by examining its poop.

Bats hunt at night. This makes it challenging to observe their foraging behavior in nature. Analyzing DNA traces in bat guano offers a more specific way to explore how bats feed in the wild and to study how bat behavior changes depending on their eating habits.

"Because bats forage at night, and in the dense forest, you can't observe what they are eating the way you can with a diurnal bird or mammal," said Patricia Jones, former STRI fellow, assistant professor of biology at Bowdoin College and main author of the study. "It feels so momentous, therefore, to have a glimpse into the diet of this species that we thought we knew so much about, to discover they are eating prey we had no idea were part of their diet."

The fringe-lipped bat, also known as the frog-eating bat, is well adjusted to hunting frogs. The bats' hearing is adapted to their low-frequency mating calls, and their salivary glands may neutralize the toxins in the skin of poisonous prey. Fringed-lipped bats also feed on insects, small reptiles or birds and other bats. Researchers knew that these bats often find their prey by eavesdropping on mating calls, but it was unknown if they could find prey that was silent.

As expected, most of the DNA recovered from the poop samples in the study belonged to frog species and plenty of lizards, but researchers also found evidence that the bats were eating other bats and even a hummingbird. In additional experiments, wild-caught fringe-lipped bats exposed to recordings of prey sounds and stationary prey models were able to detect silent, motionless prey, as well as prey that made sounds. This led researchers to conclude that the fringe-lipped bat is more capable of locating prey by echolocation than previously thought.

"This is interesting because we didn't know that these bats were able to detect silent, still prey," said May Dixon, STRI fellow, doctoral student at the University of Texas at Austin and co-author of the study. "Detecting silent, still prey in the cluttered jungle is thought to be a really hard task for echolocation. This is because when the bats echolocate in the jungle, the echoes of all the leaves and branches bounce back along with the echoes of their prey, and they 'mask' the prey."

These results may offer a new line of research on the sensory abilities and foraging ecology of T. cirrhosus. It also adds to a growing body of work that suggests that, in the tropics, bats may be important nocturnal predators on sleeping animals like birds. The team also found unexpected frog species among its common prey.

"We found T. cirrhosus were often eating frogs in the genus Pristimantis," Jones said. "I think this will open new avenues of research with T. cirrhosus, because Pristimantis call from the canopy and their calls are hard to localize, so if T. cirrhosus are consuming them it means that they are foraging differently than we understood before."

Going forward, this novel combination of dietary DNA analysis with behavioral experiments may be used by other ecologists interested in the foraging behaviors of a wide range of animal species.

"It's really exciting to see the doors that open when animal behavior is combined with metabarcoding," said STRI staff scientist Rachel Page. "Even though we have studied Trachops intensely for decades, we actually know very little about its behavior in the wild. It was completely surprising to see prey items show up in the diet that we never anticipated, such as frog species whose mating calls seemed to lack acoustic parameters helpful for localization and, more surprising, prey that it seems the bats must have detected by echolocation alone, like hummingbirds. This work makes us rethink the sensory mechanisms underlying this bat's foraging behavior, and it opens all kinds of new doors for future questions."

Older adults have suffered disproportionately from the COVID-19 pandemic, with increased risk of severe illness and death reported across the globe. A new report argues that one policy change made during the pandemic should remain in place after the novel coronavirus virus fades away: better access to home health services through Medicare.

In a new set of recommendations published by the Commonwealth Fund, researchers at Oregon Health & Science University and Duke University argue for regulatory changes to expand the Medicare home health benefit.

"Changes to the benefit could allow more Medicare beneficiaries to receive services in their own homes, rather than institutional settings, so they may reduce their exposure to COVID-19," they write.

The pandemic affords a unique opportunity to consider long-term improvements in health care for seniors, said Walt Dawson, D.Phil., an assistant professor of neurology in the OHSU School of Medicine, who co-authored the report with Courtney Harold Van Houtven, Ph.D., a professor of population health science in the Duke University School of Medicine.

"This is a real opportunity for change in our health care system," Dawson said. "It's an opportunity to rethink and readdress how we provide health care and how we pay for health care services, in particular for older adults."

"Bolstering the Medicare home health benefit could enable older adults to more easily receive care in the setting that most of them prefer - their homes," Van Houtven said. "Innovations could help the older adult with care needs and family caregivers who support them."

The temporary pandemic-era rules are a major benefit to seniors for whom traveling can be an ordeal, including the McCrary family in John Day, Oregon.

Margy McCrary said she and her husband, Eddie, a retired machinist living with a form of aphasia, recently completed an annual neurology checkup with an OHSU clinician by way of an hour-long video exam from the comfort of their own home, saving a five-hour trip into Portland.

"It was a Godsend," she said. "It's more comfortable for him, he's more at ease, the stress level's down. This is just such a relief. If anything good comes out of this COVID thing, doing these video appointments has been perfect."

New Medicare rules approved under the Coronavirus Aid, Relief, and Economic Security, or CARES, Act in March for the first time enabled nurse practitioners, clinical nurse specialists and physician assistants to certify a Medicare beneficiary's eligibility for home health services. Until then, only a physician could certify a patient's need for home health care. In addition, the act provided sweeping expanded access to telehealth services, albeit not for home health visits.

"Strengthening telehealth access could enable critical monitoring of patient status at a time when beneficiaries are not eager to have providers visit their homes," the authors write.

The new Medicare rules are a welcome relief for many patients in the same position as the McCrarys, said Allison Lindauer, Ph.D., N.P., assistant professor of neurology in the OHSU School of Medicine.

As a nurse practitioner, she now can certify home health for patients who need it.

"Advanced practice providers have been very limited in their ability to order home care services," Lindauer said. "I really believe in the value of home-based care and rehabilitation and am relieved I can now order this for my patients."

The report lays out three major policy recommendations:

Expand opportunities to provide care at home: The report suggests better integrating home health, health care and social care; expanding coverage of telehealth home health visits after discharge from skilled nursing facilities; and paying family caregivers to support COVID-19 patients' recovery at home.

Bolster the home health workforce: This would make permanent the scope of practice for nurse practitioners, physician assistants and clinical nurse specialties now allowed under the CARES Act. The report also recommends increasing wage and benefits for home health aides, who currently earn less than $12 an hour on average nationwide.

Enhance quality and oversight: The report recommends expanding regulatory oversight of home health agencies.

EMBARGOED FOR RELEASE UNTIL 7 A.M. ET, THURSDAY, OCT. 22, 2020

PITTSBURGH, Oct. 22, 2020 - A metabolite produced following consumption of dietary soy may decrease a key risk factor for dementia--with the help of the right bacteria, according to a new discovery led by researchers at the University of Pittsburgh Graduate School of Public Health.

Their study, published today in the journal Alzheimer's & Dementia: Translational Research & Clinical Interventions, reports that elderly Japanese men and women who produce equol--a metabolite of dietary soy created by certain types of gut bacteria--display lower levels of white matter lesions within the brain.

"White matter lesions are significant risk factors for cognitive decline, dementia and all-cause mortality," said lead author Akira Sekikawa, M.D., Ph.D., associate professor of epidemiology at Pitt Public Health. "We found 50% more white matter lesions in people who cannot produce equol compared to people who can produce it, which is a surprisingly huge effect."

To obtain this result, Sekikawa's research team measured equol levels within the blood of 91 elderly Japanese participants with normal cognition. Participants were sorted by their equol production status, and then six to nine years later underwent brain imaging to detect levels of white matter lesions and deposits of amyloid-beta, which is the suspected molecular cause of Alzheimer's disease.

The researchers found that while equol production did not appear to impact levels of amyloid-beta deposited within the brain, it was associated with reduced white matter lesion volumes. Sekikawa's team also discovered that high levels of isoflavones--soy nutrients that are metabolized into equol--had no effect on levels of white matter lesions or amyloid-beta when equol wasn't produced.

According to Sekikawa, the ability to produce equol from soy isoflavones may be the key to unlocking protective health benefits from a soy-rich diet, and his team has previously shown that equol production is associated with a lower risk of heart disease. As heart disease is strongly associated with cognitive decline and dementia, equol production could help protect the aging brain as well as the heart.

Epidemiological studies in Japan, where soy is regularly consumed, have shown that dietary intake of soy isoflavones has been linked to a lower risk for heart disease and dementia. However, most clinical trials in America have failed to show this.

Sekikawa believes that this discrepancy may be due to the microbiome--40-70% of Japanese harbor gut bacteria that can convert dietary isoflavones into equol compared to only 20-30% of Americans.

Sekikawa said that equol supplements could one day be combined with existing diet-based prevention strategies that appear to lower the risk of dementia, particularly the Dietary Approaches to Stop Hypertension (DASH) and Mediterranean diets.

Though Sekikawa hopes to evaluate the neuroprotective effects of equol supplements in a future randomized clinical trial, in the meantime, he urges caution to anyone who might be tempted to purchase equol supplements to stave off dementia.

"This type of study always catches people's attention, but we cannot prove that equol protects against dementia until we get a randomized clinical trial with sufficient evidence," he said.

Captured on Oct. 20, 2020 during the OSIRIS-REx mission's Touch-And-Go (TAG) sample collection event, this series of images shows the SamCam imager's field of view as the NASA spacecraft approaches and touches down on asteroid Bennu's surface, over 200 million miles (321 million km) away from Earth. The sampling event brought the spacecraft all the way down to sample site Nightingale, touching down within three feet (one meter) of the targeted location. The team on Earth received confirmation at 6:08 pm EDT that successful touchdown occurred. Preliminary data show the one-foot-wide (0.3-meter-wide) sampling head touched Bennu's surface for approximately 6 seconds, after which the spacecraft performed a back-away burn.

The spacecraft's sampling arm - called the Touch-And-Go Sample Acquisition Mechanism (TAGSAM) - is visible in the lower part of the frame. The round head at the end of TAGSAM is the only part of OSIRIS-REx that contacted the surface during the sample collection event. In the middle of the image sequence, the sampling head positions itself to contact the asteroid's surface head-on. Shortly after, the sampling head impacts site Nightingale and penetrates Bennu's regolith. Upon initial contact, the TAGSAM head appears to crush some of the porous rocks underneath it. One second later, the spacecraft fires a nitrogen gas bottle, which mobilizes a substantial amount of the sample site's material. Preliminary data show the spacecraft spent approximately 5 of the 6 seconds of contact collecting surface material, and the majority of sample collection occurred within the first 3 seconds.

The TAGSAM is designed to catch the agitated surface material, and the mission team will assess the amount of material collected through various spacecraft activities. After touchdown, the spacecraft fired its thrusters to back away from Bennu. As expected, this maneuver also disturbed the Nightingale site, and loose debris is visible near the end of the image sequence. Preliminary telemetry shows the spacecraft remains in good health. The spacecraft was traveling at 0.2 mph (10 cm/sec) when it contacted sample site Nightingale and then backed away at 0.9 mph (40 cm/sec).

These images were captured over approximately a five-minute period. The imaging sequence begins at about 82 feet (25 meters) above the surface, and runs through the back-away maneuver, with the last image in the sequence taken at approximately 43 feet (13 meters) in altitude - about 35 seconds after backing away. The sequence was created using 82 SamCam images, with 1.25 seconds between frames. For context, the images are oriented with Bennu's west at the top.

Both Taiwan and New Zealand have successfully eliminated COVID-19 with world-leading pandemic responses. By taking a particularly proactive approach, Taiwan's response was probably the most effective and least disruptive of any country's, researchers say.

In an article published in the international journal, The Lancet Regional Health: Western Pacific, researchers from the University of Otago in New Zealand, the National Taiwan University and the Taiwan Centers for Disease Control, examine the pandemic responses of the two island countries 9,000 kilometres apart.

Both countries mounted very effective responses to COVID-19 and both had successfully eliminated community transmission by early August, although New Zealand experienced a localised outbreak in the Auckland region shortly after.

The lead author of the research paper, Dr Jennifer Summers, from the University of Otago, Wellington, says the two countries used different approaches to respond to their first waves of COVID-19.

Taiwan acted very early to control the virus, introducing health screening of air passengers on the day the World Health Organization was informed of the outbreak in Wuhan on 31 December 2019.

"Despite Taiwan's closer proximity to Wuhan and its high population density it experienced a substantially lower incidence rate of 20.7 cases per million compared with New Zealand's 278 per million.

"Their timely and vigorous response allowed Taiwan to avoid the national lockdown used in New Zealand to eliminate community transmission."

In both countries, outbreaks of COVID-19 prompted public health officials to introduce a range of measures including contact tracing, testing and isolating of cases and quarantine of close contacts.

Fellow author Professor Michael Baker from the University of Otago, Wellington, says Taiwan benefited by having a Centers for Disease Control in place, as well as a National Health Command Center dedicated to responding to emerging threats such as pandemics. Because of historically low levels of investment in public health, New Zealand was forced to take a more reactive approach to the pandemic with a stringent national lockdown to eliminate COVID-19 transmission while essential response capacities were rapidly developed.

"Taiwan's pandemic response had been extensively planned, partly as a result of their experience in the SARS pandemic in 2003, and was set up so it could be rapidly adapted to new pathogens.

"As in many Asian countries that had experiences with SARS, Taiwan had an established culture of face mask use by the public, as well as a proactive policy of supporting production and distribution of masks to all residents."

Both countries provided social and financial support during the pandemic and have existing universal health coverage.

The researchers make a list of recommendations to other countries, particularly high-income nations, as they continue to respond to the current pandemic and prepare for the next one.

They include: establishing a national public health agency; developing a flexible pandemic plan; investing in resources and infrastructure to allow a rapid-response to disease threats; improving workforce training, including considering a field epidemiology training programme; auditing the pandemic response to date; and updating public health laws to enable pandemic control measures to be implemented while balancing the need to protect personal rights and liberties.

More detailed recommendations include the need to improve surveillance of disease outbreaks, develop effective border management policies, establish robust quarantine rules, further develop conventional and digital solutions to allow for contact tracing and quarantine and isolation monitoring and introduce an effective means of distributing face masks and promoting their use.

COVID-19 and America's response to it are likely to profoundly affect our families, work lives, relationships and gender roles for years, say 12 prominent scientists and authors who analyzed 90 research studies and used their expertise to evaluate our reaction to the pandemic and predict its aftermath.

The group, which included several UCLA researchers, foresees enduring psychological fallout from the crisis, even among those who haven't been infected. Their predictions and insights, published Oct. 22 in the journal Proceedings of the National Academy of Sciences, include:

Planned pregnancies will decrease in a disease-ridden world, birthrates will drop, and many couples will postpone marriage, said senior author and UCLA professor of psychology and communication studies Martie Haselton.

People who are single are less likely to start new relationships. Women who can afford to be on their own are likely to stay single longer, Haselton said.

With children home due to the pandemic, women are spending more time providing care and schooling, are less available for paying work and may come to rely more on male partners as breadwinners, Haselton said. This will push us toward socially conservative gender norms and potentially result in a backslide in gender equality.

Unlike many past crises, this pandemic is not bringing people closer together and, despite some exceptions, it is not producing an increase in kindness, empathy or compassion, especially in the U.S., said lead author Benjamin Seitz, a UCLA psychology doctoral student with expertise in behavioral neuroscience.

"Our species is not wired for seeking a precise understanding of the world as it actually is," the authors write, and our tribal predispositions toward groupthink are resulting in the large-scale spread of misinformation We tend to seek out data that supports our opinions, and we too often distrust health experts, they say.

"The psychological, social and societal consequences of COVID-19 will be very long-lasting," Haselton said. "The longer COVID-19 continues, the more entrenched these changes are likely to be."

COVID-19: A worldwide social experiment

As marriage rates plummet and people postpone reproduction in a virus-plagued world, some nations' populations will shrink and fall precipitously below "replacement level," the authors write. These birthrate drops, in turn, can have cascading social and economic consequences, affecting job opportunities, straining the ability of countries to provide a safety net for their aging populations and potentially leading to global economic contraction.

Research has shown that even before the pandemic, women were more stressed than men by family and job responsibilities. Now they are managing more household responsibilities related to child care and education. In medicine and other sciences, women scholars are already publishing substantially less research than they did a year ago, while men are showing increased productivity, Haselton said.

She and her co-authors foresee a shift toward social conservatism. A consequence of the pandemic could be less tolerance for legal abortion and the rights for sexual minorities who don't align with traditional gender roles. In addition, in a time of economic inequality, many women will sexualize themselves more to compete with one another for desirable men, Haselton said.

People who meet online will often be disappointed when they meet in person. "Does a couple have chemistry? You can't tell that over Zoom," Haselton said. In new relationships, people will miss cues, especially online, and the disappointing result will often be overidealization of a potential partner -- seeing the person the way you want the person to be rather than the way the person actually is.

The pandemic has become a worldwide social experiment, say the authors, whose areas of expertise include psychology, neuroscience, behavioral science, evolutionary biology, medicine, evolutionary social science and economics.

An evolutionary struggle

For the study, the authors used an evolutionary perspective to highlight the strategies the virus has evolved to use against us, the strategies we possess to combat it and the strategies we need to acquire.

Humans today are the products of social and genetic evolution in environments that look very little like our current world. These "evolutionary mismatches" are likely responsible for our frequent lack of alarm in response to the pandemic, the scientists write.

Americans in particular value individuality and the ability to challenge authority. "This combination does not work especially well in a pandemic," Seitz said. "This virus is exposing us and our weaknesses."

Haselton agreed, calling the virus "wily" for its ability to infect us through contact with people we love who seem to be healthy. "Our social features that define much of what it is to be human make us a prime target for viral exploitation," she said. "Policies asking us to isolate and distance profoundly affect our families, work lives, relationships and gender roles."

All infectious agents, including viruses, are under evolutionary pressure to manipulate the physiology and behavior of their hosts -- in this case, us -- in ways that enhance their survival and transmission. SARS-CoV-2, which causes COVID-19, may be altering human neural tissue to change our behavior, the authors say. It may be suppressing feelings of sickness, and perhaps even enhancing our social impulses, during times of peak transmissibility before symptoms appear. People who are infected but do not feel sick are more likely to go about their usual activities and come in contact with others whom they might infect.

Disgust is useful and motivates us to avoid people who display clear signs of disease -- such as blood, pale skin, lesions, yellow eyes or a runny nose. But with COVID-19 infections, this is not what most people see. Family, friends, co-workers and strangers can look perfectly healthy and be asymptomatic for days without knowing they are infected, the authors note.

It may sound counterintuitive, but normal brain development requires exposure to a diverse set of microbes to help prepare younger animals for a range of pathogenic dangers they may encounter in adulthood. But safer-at-home and quarantine health measures have temporarily halted social activities that would otherwise bring millions of adolescents into contact with new microbes. As a result, children and adolescents whose immune systems and brains would, in normal times, be actively shaped by microbial exposures may be adversely impacted by this change, the scientists say.

By understanding how SARS-CoV-2 is evolving and having behavioral and psychological effects on us that enhance its transmission, we will be better able to combat it so it becomes less harmful and less lethal, the authors write.

In an increasingly urbanized world, population density often leads to more deaths and injuries when floods, typhoons, landslides and other disasters strike cities.

But the risks to life and limb are compounded when earthquakes are the agent of destruction, because they not only kill and maim but can also cripple the hospitals needed to treat survivors.

Now, an international research team led by the Stanford Blume Center for Earthquake Engineering has developed a methodology to help disaster preparedness officials in large cities make contingency plans on a region-wide basis to make sure that emergency responders can get patients to the hospital facilities that are likeliest to remain in commission after a quake.

"Previously, most hospital preparedness plans could only look at smaller areas because they focused on single hospitals," said Anne Kiremidjian, professor of civil and environmental engineering at Stanford and a co-author, with colleague Greg Deierlein, of a paper published in Nature Communications.

Regional response to quakes is not completely new in quake-prone California, where after the 1994 Northridge earthquake the Los Angeles County Emergency Medical Services Agency used shortwave and ham radios to coordinate the movement of patients among 76 hospitals in the damage zone.

To assure hospital survivability, the California state legislature has mandated that all acute care hospitals are brought up to current seismic standards by 2030. "We need to ensure that hospitals remain operational to treat patients and avoid greater loss of life," Deierlein said.

The new research provides disaster response officials in seismically active countries like Turkey, Chile, Indonesia or Peru with an effective but relatively simple way to create regional contingency plans: Start by using statistical risk analysis models to estimate where deaths and injuries are likeliest to occur in populous metropolitan areas; apply building-specific performance assessment techniques to project how much damage different hospitals might suffer; and map out the best routes between hospitals should the need arise to move injured patients to less damaged facilities with available capacity.

The new regional planning methodology comes at a time when the world is awakening to the consequences of population growth and dense urbanization. When the researchers looked at 21,000 disasters that have occurred worldwide since 1900, half of those with the largest injury totals occurred during the last 20 years. For example, the 7.6 magnitude earthquake that struck Izmit, Turkey, caused approximately 50,000 injuries and disrupted 10 major hospitals.

Luis Ceferino, who coordinated the research as a PhD candidate in civil engineering at Stanford, said the paper focused on what happened in 2007, after an 8.0 magnitude earthquake struck the city of Pisco, about 150 miles from Lima, Peru. Pisco lost more than half its total number of hospital beds in a few minutes.

Ceferino also worked with two other two experts in hospital responses, professor Celso Bambarén from Universidad Peruana Cayetano Heredia in Peru and Judith Mitrani-Reiser of the U.S. National Institute of Standards and Technology, who gathered post-quake damage assessments from the Pisco temblor and the 8.8 magnitude temblor that occurred in 2010 near Maule on the central coast of Chile, data that also helps to inform the new methodology.

"Hospital systems are at the core of disaster resilience," said Ceferino, who will become an assistant professor of civil and urban engineering at New York University in 2021. "Cities need regional contingency plans to ensure that hospitals, doctors and medical teams are ready to care for our most vulnerable populations."

WEST LAFAYETTE, Ind. - Scientists estimate that nearly 60% of all cancer patients do not respond effectively to chemotherapy treatments. Even worse - many of those same patients experience toxic and sometimes deadly side effects.

Now, a Purdue University scientist and entrepreneur is working to use simple LED light to help determine if certain chemotherapy options will work for specific patients. The work is published in Scientific Reports.

"We are using a technique very similar to doppler radar used in weather to advance personalized medicine," said David Nolte, the Edward M. Purcell Distinguished Professor of Physics and Astronomy in Purdue's College of Science. "We take the LED light and shine it on biopsies. We then apply chemotherapy to the biopsies and analyze how the light scatters off the tissues."

Nolte, who also is a member of the Purdue University Center for Cancer Research, said the light scattering dynamics give scientists and doctors detailed information about the likelihood of a chemotherapy drug being effective for a patient. Nolte said they have results within 24 hours. This first trial looked at biodynamic imaging on human patients with ovarian cancer.

"We look for signs of apoptosis, or what we call the controlled death of cells," Nolte said. "Apoptosis is the signal that indicates the effectiveness of the chemotherapy for this patient's tissues and tumors. For some cancers, there are so many treatment options available that it's like a doctor is trying to fit square pegs in circular holes until a desired outcome is found. We want to make this process better for patients."

Nolte has worked with several groups within the Purdue entrepreneurial and commercialization ecosystem, including the Purdue Foundry, on business plan development and management searches. AniDyn, a medical technology startup, was spun out of Purdue by professors Nolte and John J. Turek. AniDyn is focused on the development and commercialization of live-tissue imaging platform technologies.

Nolte also works closely with the Purdue Research Foundation Office of Technology Commercialization to patent and license his technologies.

About Purdue Research Foundation

The Purdue Research Foundation is a private, nonprofit foundation created to advance the mission of Purdue University. Established in 1930, the foundation accepts gifts; administers trusts; funds scholarships and grants; acquires property; protects Purdue's intellectual property; and promotes entrepreneurial activities on behalf of Purdue. The foundation manages the Purdue Foundry, Purdue Office of Technology Commercialization, Purdue Research Park, Purdue Technology Centers and University Development Office. In 2020, the IPWatchdog Institute ranked Purdue third nationally in startup creation and in the top 20 for patents. The foundation received the 2019 Innovation and Economic Prosperity Universities Award for Place from the Association of Public and Land-grant Universities. For more information on licensing a Purdue innovation, contact the Purdue Office of Technology Commercialization at otcip@prf.org. For more information about involvement and investment opportunities in startups based on a Purdue innovation, contact the Purdue Foundry at foundry@prf.org.

About Purdue University

Purdue University is a top public research institution developing practical solutions to today's toughest challenges. Ranked the No. 5 Most Innovative University in the United States by U.S. News & World Report, Purdue delivers world-changing research and out-of-this-world discovery. Committed to hands-on and online, real-world learning, Purdue offers a transformative education to all. Committed to affordability and accessibility, Purdue has frozen tuition and most fees at 2012-13 levels, enabling more students than ever to graduate debt-free. See how Purdue never stops in the persistent pursuit of the next giant leap at purdue.edu.

Writer: Chris Adamcladam@prf.org

Source: David Noltenolte@purdue.edu

Researchers have found that a class of commonly-used heart drugs may also improve patients' responses to anti-cancer immunotherapies called PD(L)1 inhibitors, according to preliminary findings to be presented at the 32th EORTC-NCI-AACR [1] Symposium on Molecular Targets and Cancer Therapeutics, which is taking place online.

Angiotensin receptor II blockers (ARBs) are often prescribed for high blood pressure, heart failure, kidney failure and following a heart attack. They work by reducing the action of a chemical called angiotensin II, which plays a role in narrowing blood vessels and increasing blood pressure. ARBs block AT1 receptors that angiotensin II works on, and which are found in the heart, blood vessels and kidneys. [2]

Dr Julius Strauss, co-director of the clinical trials group at the Laboratory of Tumor Immunology and Biology, at the USA's National Cancer Institute's Center for Cancer Research, presented this latest research. He said: "There are data suggesting that when angiotensin II, a protein in the body, binds to one of its receptors, AT1R, it has the potential to increase the levels of other proteins, VEGF and TGF beta, both of which have been linked to cancer growth and resistance to the immune system."

The researchers thought that this overlap between the angiotensin II and the TGF beta pathways might mean that it plays a crucial role in the onset of cancer, its growth and also how cancer cells evade the immune system.

"We decided to look at all the medications our patients were taking to see if any common medication or class of drugs might increase the likelihood of responding to anti-PD(L)1 treatment. After an initial review, ARBs seemed to be the most promising," said Dr Strauss.

He analysed data from 597 patients being treated with anti-PD(L)1 drugs [3] in 20 clinical trials at the National Institutes of Health Clinical Center in the USA. The patients had more than three dozen different cancers, including prostate, lung, colon, ovarian, bladder and cervical cancers. Many were already taking ARBs or angiotensin-converting enzyme (ACE) inhibitors for heart problems unrelated to their cancer.

Dr Strauss compared 71 patients who were taking ARBs together with their PD(L)1 inhibitor with those who were not. He also compared 82 patients receiving ACE inhibitors with those who were not. [4]

"Patients who were taking ARBs seemed to respond better and more often to anti PD(L)1 therapy for their cancer than patients who were not. We found that ARBs were associated with a statistically significant increase in the objective response rate as well as the complete response rate, compared to patients not taking ARBs," he said.

Among patients taking ARBs, the objective response rate (ORR), meaning the cancer had shrunk at least 30%, was 34% compared to 17% in patients not taking ARBs, while the complete response (CR) rate, meaning the cancer had shrunk 100% and could no longer be seen on scans, was 11% in patients taking ARBS compared to 3% in those who were not. However, there was no statistically significant improvement in ORR or CR rates among patients taking ACE inhibitors compared to those who were not taking them.

Dr Strauss said: "The possible reason for the different effects seen with ARBs and ACE inhibitors might be that although angiotensin II increases levels of VEGF and TGF beta when it binds to the AT1R receptor, it can actually decrease levels of VEGF and TGF beta when it binds to another receptor, AT2R. Therefore, ARBs which selectively block just AT1R potentially work better at lowering VEGF and TGF beta levels than ACE inhibitors which block both AT1R and AT2R.

He continued: "In addition to ARBs potentially increasing the likelihood of responding to anti-PD(L)1 therapy, we also saw evidence that ARBs may help patients live longer. This beneficial effect of ARBS was seen in some cancer types more than others and was most notable in bladder cancer.

"However, these findings are very preliminary and other trials are needed to evaluate if ARBs may be beneficial to patients with cancer and to determine what, if any, cancer types may benefit the most, particularly in combination with anti-PD(L)1 therapy."

Professor Udai Banerji, a member of the scientific committee for the Symposium and Deputy Director of the Drug Development Unit at The Institute of Cancer Research and the Royal Marsden Hospital in London (UK), was not involved with this research. He commented: "This hypothesis-generating population-based study offers interesting insights into the role of the interaction of the immune and cardiovascular system in promoting cancer. There is room for improvement for the clinical efficacy of immune checkpoint inhibitors, such as anti-PD(L)1 therapies. If these findings are validated in preclinical experiments and clinical trials this would be a tremendous opportunity to repurpose existing cardiovascular drugs to be used in combination with immune checkpoint drugs to improve outcomes of cancer patients."

- Language is one of the most powerful tools available to humanity, and determining why and when language evolved is central to understand what it means to be human

- Being able to track relationships between words in a sentence, both next to one another and across a sentence, is foundational to language processing. This ability was examined in monkeys, apes and humans by researchers from the University of Warwick and University of Zurich.

- Apes and monkeys were able to track relationships between sounds the same way as humans, showing that this ability predates the evolution of language itself by at least 30-40 million years

The capacity for language is built upon our ability to understand combinations of words and the relationships between them, but the evolutionary history of this ability is little understood. Now, researchers from the University of Warwick have managed to date this capacity to at least 30-40 million years ago, the last common ancestor of monkeys, apes and humans.

Across the globe, humanity flourishes by sharing thoughts, culture, information and technology through language - an incredibly complex method of communication used by no other species. Determining why and when it evolved is, therefore, crucial to understanding what it means to be human.

In the paper, 'Non adjacent dependency processing in monkeys, apes and humans', published today in the journal Science Advances, an international consortium of researchers, led by Professor Simon Townsend at the University of Warwick, made a crucial advance in our understanding of when a key cognitive building block of language may have evolved.

Being able to process relationships between words in a sentence is one of the key cognitive abilities underpinning language, whether those words are next to one another, known as an 'adjacent dependency', or distant to one another, known as a 'non-adjacent dependency'. For example, in the sentence "the dog who bit the cat ran away" we understand that is it the dog who ran away rather than the cat, thanks to being able to process the relationship between the first and last phrases.

Dr. Stuart Watson, who carried out this work at the University of Zürich, explains:
"Most animals do not produce non-adjacent dependencies in their own natural communication systems, but we wanted to know whether they might nevertheless be able to understand them."

The research team used a novel experimental approach for their experiments: They created "artificial grammars" in which sequences made up of meaningless tones instead of words were used to examine the abilities of subjects to process the relationships between sounds. This made it possible to compare the ability to recognize non-contiguous dependencies between three different primate species, even though they do not share a common language. The experiments were carried out with common marmosets (a Brazilian monkey), chimpanzees and humans.

The researchers found that all three species were readily able to process the relationships between both adjacent and non-adjacent sound elements. Non-adjacent dependency processing is, therefore, widespread in the primate family.

The implications of this finding are significant, says Professor Townsend, "This indicates that this critical feature of language already existed in our ancient primate ancestors, predating the evolution of language itself by at least 30 - 40 million years."

New research suggests an algorithm could be used to help optimise the sharing of healthcare resources during the Covid-19 pandemic, preventing NHS intensive care units (ICU) from becoming overwhelmed.

The study, led by Queen Mary University of London, proposes a load balancing method to transfer critical ICU patients across hospitals and optimally allocate new patients, which could help to reduce stress on health systems in the second wave and potential subsequent waves to come.

The research team, which included scientists from the University of Exeter and the University of Bristol, tested the algorithm using available data from both the UK's NHS and Spanish health system. They showed that this mathematical approach could help redistribute up to 1000 ICU patients that otherwise likely wouldn't receive the appropriate intensive care.

During the pandemic, demand for ICUs varies across a country, with some hospitals receiving substantial numbers of patients early on in an outbreak whilst others are unaffected. These differences in demand create an opportunity to balance the load of patient admissions across hospitals, by rerouting patients from areas of high demand to local hospitals that have spare capacity.

Rerouting and load balancing solutions have a long history in areas such as computer networks, where usually different tasks are assigned to different interconnected servers and the servers can communicate and transfer tasks in order to minimise the global processing time. In this study, the researchers adopted a similar approach to manage ICU resources in hospital networks, where the "load" to be allocated is the amount of ICU patients or ventilators, and the rerouting takes place across hospitals.

Using the algorithm the researchers showed that when ICU demand is uniform across the country it is possible to enable access for up to 1000 additional cases in the UK in a single step of the algorithm, without needing to increase capacity. In more realistic scenarios, where we see differences in demand across hospitals or regions, the scientists found their new method could balance about 600 beds per step in the Spanish system when sharing resources locally, and over 1300 using countrywide sharing, potentially saving a large percentage of these lives that would otherwise not have access to ICUs.

It is hoped this mathematical approach could also be used to help reduce demand when the epidemic begins to decline, allowing hospitals to return back to normal as efficiently as possible.

Dr Leon Danon, Senior Lecturer in Data Analytics at the University of Exeter, said: "The current Covid-19 pandemic has put many national health systems under significant pressure, particularly for ICUs and ventilators. So far balancing patient loads in times of high demand has occurred spontaneously, for example with hospitals sharing daily information on demand and availability of resources with colleagues in other local hospitals. Whilst this quick action can help in the immediate, once multiple hospital become overwhelmed the pattern of demand becomes more complex and a more systematic approach is needed. Our load sharing methodology can help to prevent health services becoming overwhelmed by the excessive demand for intensive care, which is particularly critical when the second wave we are experiencing can now be coupled with the flu season."

Dr Lucas Lacasa, Reader in Applied Mathematics at Queen Mary, said: "We have validated that the method works with realistic data from the UK and Spain, and shown it can be used to load balance patients in real time. We are currently in the process of exploring how to operationalise the method within the healthcare system, and are developing a user-friendly interface for the NHS, or other health systems across the globe, to be able to embed this technology within the set of measures each country is already deploying to manage the pandemic."

"The method is easily portable to other countries as well, and whilst this load sharing algorithm has primarily been developed for the current pandemic, there's no reason a similar approach couldn't be used to load balance other healthcare resources."