Culture

A study published today in JAMA Network Open/Emergency Medicine supports evidence that older persons admitted to emergency departments (ED), and subsequently diagnosed positive for COVID-19, often present with delirium when they show no other typical COVID-19 symptoms, such as fever and cough. Sharon K. Inouye, M.D., M.P.H., Director of the Aging Brain Center in the Hinda and Arthur Marcus Institute for Aging Research at Hebrew SeniorLife and Professor of Medicine at Harvard Medical School, is senior author on the study. Co-first authors include Maura Kennedy, M.D., Assistant Professor of Emergency Medicine, Massachusetts General Hospital and Benjamin K. Helfand, M.D., Ph.D. (Cand.), University of Massachusetts Medical School and Warren Alpert Medical School, Brown University.

Although COVID-19 poses a risk at all ages, adults aged 65 years and older are at greatest risk of severe disease, hospitalization, intensive care use, and death. Persons older than 65 years comprise 16 percent of the United States population yet have accounted for more than 80 percent of deaths in the U.S.

Delirium is an acute state of confusion, characterized by an altered level of consciousness, disorientation, inattention, and other cognitive disturbances. Beyond COVID-19, delirium is known to be a common symptom in older adults with severe disease in the ED and is associated with extended hospitalization, and increased morbidity and mortality. Despite the threat delirium poses to older ED patients, it is undetected in two-thirds of cases.

Researchers involved in the study examined 817 patients 65 or older admitted to the ED and who were diagnosed with COVID-19. They found almost a third had delirium at the time they were seen in the ED. A delirium diagnosis was the main presenting symptom for 16 percent of those patients, and 37 percent had no typical COVID-19 symptoms; delirium was the sixth most common presenting symptoms in all patients. These findings suggest the clinical importance of including delirium on checklists of presenting signs and symptoms of COVID-19 that guide screening, testing, and evaluation.

According to Dr. Inouye, "This study demonstrates that delirium is not only a common symptom of COVID-19, but also may be the leading and possibly sole symptom in older persons. Thus, delirium should be considered an important presenting symptom of COVID-19."

Additional collaborating institutions on the study include:

St. Mary Mercy Livonia Hospital

Beth Israel Deaconess Medical Center

Maine Medical Center

Brigham and Women's Hospital

Yale School of Medicine

University of North Carolina Chapel Hill School of Medicine.

A collaborative research team from the University of Oklahoma, the Memorial Sloan Kettering Cancer Center
and Merck & Co. published an opinion article in the journal, Nature Chemical Biology, that addresses the gap in the discovery of new antibiotics.

"The rapid spread of antibiotic-resistant bacteria in clinics challenges our modern medicine and the traditional approaches to antibiotic discovery fail to generate new drugs needed for treatment of antibiotic resistant infections," Zgurskaya said. "The current COVID-19 pandemic further magnifies this problem because patients in intensive care units are particularly vulnerable to such infections ... (our) team is working on developing new tools to guide the discovery and optimization of new antibacterial agents."

Zgurskaya adds that the increasing frequency of antibiotic resistance has created a significant health care challenge and will progressively worsen without innovative solutions.

"In particular, Gram-negative pathogens present both biological and chemical challenges that hinder the discovery of new antibacterial drugs," Zgurskaya said. "As a result of these challenges, intensive screening campaigns have led to few successes, highlighting the need for new approaches to identify regions of chemical space that are specifically relevant to antibacterial drug discovery."

In the article, the research team provides an overview of emerging insights into this problem and outline a general approach for researchers and scientists to address it.

"The overall goal is to develop robust cheminformatic tools to predict Gram-negative permeation and efflux, which can then be used to guide medicinal chemistry campaigns and the design of antibacterial discovery libraries," Zgurskaya said.

Peer-reviewed / Systematic review and meta-analysis / People

Systematic review and meta-analysis of three human coronaviruses suggests that people infected with SARS-CoV-2 are most likely to be highly infectious in the first week after symptom onset, highlighting the need to identify and isolate cases early.

SARS-CoV-2 viral load appears to peak in the upper respiratory tract (which is thought to be the main source of transmission [1]) early in the disease course (from symptom onset to day five) while SARS-CoV and MERS-CoV viral load peak later, providing the likely explanation for why the COVID-19 pandemic spreads more rapidly in the community.

The evidence so far on SARS-CoV-2 points to a pattern of a nine-day period of infectiousness. As the study only looks at confirmed cases and not those who may have been exposed, it is unable to provide insight into the recommended duration of quarantine.

Although viral loads appear to be similar between people infected with SARS-CoV-2 who develop symptoms and those who do not, most studies indicate that asymptomatic individuals may clear the virus faster from their body and might be infectious for a shorter amount of time.

Although SARS-CoV-2 genetic material may still be detected in respiratory or stool samples for several weeks, no live virus (that can cause infection) was found in any type of sample collected beyond nine days of symptoms starting and people with SARS-CoV-2 are mostly likely to be highly infectious from symptom onset and the following five days, according to a systematic review and meta-analysis of three human coronaviruses published in The Lancet Microbe journal.

"This is the first systematic review and meta-analysis that has comprehensively examined and compared viral load and shedding for these three human coronaviruses. It provides a clear explanation for why SARS-CoV-2 spreads more efficiently than SARS-CoV and MERS-CoV and is so much more difficult to contain," says lead author Dr Muge Cevik of the University of St Andrews, UK.

"Our findings are in line with contact tracing studies which suggest the majority of viral transmission events occur very early, and especially within the first 5 days after symptom onset, indicating the importance of self-isolation immediately after symptoms start. We also need to raise public awareness about the range of symptoms linked with the disease, including mild symptoms that may occur earlier on in the course of the infection than those that are more prominent like cough or fever." [2]

This study specifically looked at people infected with SARS-CoV-2 and mainly those who were hospitalised, so the results are only relevant for the period of self-isolation for people with confirmed COVID-19, and do not apply to people quarantining who may or may not have been exposed after contact with someone infected. Many countries currently recommend that people with a SARS-CoV-2 infection should self-isolate for 10 days, which the authors say is in line with their findings, cautiously covering the period of infectiousness.

Understanding when patients are most likely to be infectious is of critical importance for informing effective public health measures to control the spread of SARS-CoV-2. This study looked at key factors involved in this: viral load (how the amount of the virus in the body changes throughout infection), viral RNA shedding (the length of time someone sheds viral genetic material (RNA), which does not necessarily indicate a person is infectious, as this is not necessarily able to replicate), and isolation of the live virus (a stronger indicator of a person's infectiousness, as the live virus is isolated and tested to see if it can successfully replicate in the laboratory).

The researchers included 98 studies that had five or more participants, cohort studies and randomised controlled trials; 79 focussed on SARS-CoV-2, 73 of which included hospitalised patients only; eight on SARS-CoV; and 11 on MERS-CoV infection. From these studies, the authors calculated the average length of viral RNA shedding and examined the changes in viral load and the success of isolating the live virus from different samples collected throughout an infection.

Analysing the results from the SARS-CoV-2 studies showed that the average length of time of viral RNA shedding into the upper respiratory tract, lower respiratory tract, stool and serum were 17 days, 14.6 days, 17.2 days and 16.6 days, respectively. The longest length of time that RNA shedding lasted was 83, 59, 35 and 60 days, respectively.

Of the eleven studies that attempted to isolate the live virus, all eight studies included that used respiratory samples successfully managed to culture viable virus within the first week of illness. Of the studies that also measured RNA viral load, these demonstrated a link between the success of isolating the live virus with viral load levels. No study included in this systematic review managed to successfully isolate live virus beyond day nine of symptoms in any type of sample, despite persistently high viral RNA loads. So far, only a few studies successfully isolated the live virus from stool samples despite prolonged RNA shedding, and the role of oral-faecal transmission for SARS-CoV-2 remains unclear.

"These findings suggest that in clinical practice, repeat PCR testing may not be needed to deem that a patient is no longer infectious, as this could remain positive for much longer and does not necessarily indicate they could pass on the virus to others. In patients with non-severe symptoms, their period of infectiousness could instead be counted as 10 days from symptom onset," says Dr Cevik. [2]

The highest viral load of SARS-CoV-2 RNA were detected early in the course of the disease - at the time symptoms begin, or before day five of symptoms. In contrast, the viral loads 8 and MERS-CoV peaked at 10-14 days and 7-10 days after symptom onset, respectively - explaining why transmission of these viruses can be effectively reduced by immediate identification, isolation and quarantine of people who show symptoms of the disease.

Only twelve studies reported on asymptomatic individuals infected with SARS-CoV-2 and of those, six also looked at how quickly people cleared the viral material out of their body.

"Although viral RNA loads appear to be largely similar between those with and without symptoms, a few studies suggest that asymptomatic individuals might clear the viral material from their bodies faster," says Dr Cevik. "Several studies have found that individuals with asymptomatic infection may clear the virus faster, suggesting that those without symptoms may be as infectious as those with symptoms at the beginning of infection, but may be infectious for a shorter period. However, at this stage, there are limited data available on the shedding of infectious virus in asymptomatic individuals to inform any policy change on quarantine duration in the absence of testing." [2]

This is the most comprehensive study of these three respiratory coronaviruses to date and is larger than the previous one meta-analysis on SARS-CoV-2, but the authors note some limitations. Many of the patients across the different studies included in the systematic review and meta-analysis were hospitalised and received a range of treatments that may affect the course of their infection, the studies included different populations who were followed up and managed differently, and in the interpretation of statistics used to measure the length of viral shedding. The period of infectiousness may also not exactly align with the successful culturing of the live virus from samples, although these are likely to broadly overlap.

"The majority of studies included in our review were performed in patients who were admitted to hospital. Therefore, our findings may not apply to people with milder infection although these results suggest those with milder cases may clear the virus faster from their body. Additionally, the increasing deployment of treatments, such as dexamethasone, remdesivir as well as other antivirals and immunomodulators in clinical trials are likely to influence viral shedding in hospitalised patients. Further studies on viral shedding in this context are needed" says senior author, Dr Antonia Ho of MRC-University of Glasgow Centre for Virus Research, UK. [2]

Announcing a new article publication for BIO Integration journal. In this article the authors Zhong, Cuiyu; Zhang, Lei; Huang, Jiandong; Huang, Songyin; Yao, Yandan from Sun Yat-sen University, Guangzhou, China; Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China and Shenzhen Institutes of Advanced Technology, Guangdong, China review antimicrobial peptides with anticancer properties.

There is considerable interest in a new class of anticancer molecules that is currently still under investigation termed the cationic antimicrobial peptides (AMPs). AMPs are a group of pervasive components of the innate immunity which can be found throughout all classes of life. The small innate peptides cover a broad spectrum of antibacterial activities due to their electrostatic interactions with the negatively charged bacterial membrane.

Compared with normal cells, cancer cells have increased proportions of negatively charged molecules, including phosphatidylserine, glycoproteins, and glycolipids, on the outer plasma membrane. This provides an opportunity for exploiting the interaction between AMPs and negatively charged cell membranes in developing unconventional anticancer strategies. Some AMPs may also be categorized into a group of potential anticancer agents called cationic anticancer peptides (ACPs) due to their relative selectivity in cell membrane penetration and lysis, which is similar to their interaction with bacterial membranes.

The authors review several examples of ACPs that are used in tumor therapy for their ability in penetrating or lysing tumor cell membrane and discuss recent advances and challenges in the application of ACPs.

The African crested rat (Lophiomys imhausi) is hardly the continent's most fearsome-looking creature--the rabbit-sized rodent resembles a gray puffball crossed with a skunk--yet its fur is packed with a poison so lethal it can fell an elephant and just a few milligrams can kill a human. In a Journal of Mammology paper published today, the University of Utah, Smithsonian Conservation Biology Institute, and National Museums of Kenya researchers found the African crested rat is the only mammal known to sequester plant toxins for chemical defense and uncovered an unexpected social life--the rats appear to be monogamous and may even form small family units with their offspring.

"It's considered a 'black box' of a rodent," said Sara Weinstein, lead author and Smithsonian-Mpala postdoctoral fellow and postdoctoral researcher at the University of Utah. "We initially wanted to confirm the toxin sequestration behavior was real and along the way discovered something completely unknown about social behavior. Our findings have conservation implications for this mysterious and elusive rat."

People in East Africa have long suspected the rat to be poisonous. A 2011 paper proposed these large rodents sequester toxins from the poison arrow tree (Acokanthera schimperi). A source of traditional arrow poisons, Acokanthera contains cardenolides, compounds similar to those found in monarch butterflies, cane toads and some human heart medications. Cardenolides, particularly the ones in Acokanthera, are highly toxic to most animals.

"The initial 2011 study observed this behavior in only a single individual. A main goal of our study was to determine how common this exceptional behavior was," said co-author Denise Dearing from the University of Utah.

When threatened, the African crested rat lives up to its name and erects a crest of hair on its back to reveal a warning on its flanks--black and white stripes running from neck-to-tail on each side of its body. The 2011 study hypothesized that the rats chew the Acokanthera bark and lick the plant toxins into specialized hairs at the center of these stripes.

In the new study, researchers trapped 25 African crested rats, the largest sample size of the species ever trapped. Using motion-activated cameras, they documented nearly 1,000 hours of rat behavior. For the first time, they recorded multiple rats sequestering Acokanthera toxins and discovered many traits that suggest the are social, and likely monogamous.

"Everyone thought it was a solitary animal. I've been researching this rat for more than ten years, so you would expect there to be fewer surprises," said Bernard Agwanda, curator of Mammals at the Museums of Kenya, co-author of this study and the 2011 paper. "This can carry over into conservation policy."

A rich social life

As a postdoctoral fellow at the Mpala Research Centre, Weinstein first searched for the rats with camera traps, but found that they rarely triggered the cameras. Weinstein was then joined by Katrina Nyawira, the paper's second author and now a graduate student at Oxford Brookes University. Together, they spent months experimenting with live traps to capture the elusive rodents.

"We talked to rangers and ranchers to ask whether they'd seen anything." said Nyawira. Eventually they figured out that loading the traps with smelly foods like fish, peanut butter and vanilla, did the trick. "Out of 30 traps, we finally got two animals. That was a win. This thing is really rare."

Those two animals changed the course of the study. They first caught an individual female, then caught a male at the same site two days later.

"We put these two rats together in the enclosure and they started purring and grooming each other. Which was a big surprise, since everyone we talked to thought that they were solitary," Weinstein said. "I realized that we had a chance to study their social interactions."

Weinstein and Nyawira transformed an abandoned cow shed into a research station, constructing stalls equipped with ladders and nest boxes to simulate their habitat in tree cavities. They placed cameras in strategic spots of each pen and then analyzed every second of their footage, tracking the total activity, movement and feeding behavior. The aim was to build a baseline of normal behavior before testing whether behavior changed after the rats chewed the toxin cardenolides from the poison arrow tree.

"They're herbivores, essentially rat-shaped little cows," Weinstein said. "They spend a lot of time eating, but they walk around, mate, groom, climb up the walls, sleep in the nest box."

The footage and behavioral observations strongly support a monogamous lifestyle. They share many of the traits common among monogamous animals: large size, a long life span and a slow reproductive rate. Additionally, the researchers trapped a few large juveniles in the same location as adult pairs, suggesting that offspring spend an extended period of time with their parents. In the pens, the paired rats spent more than half of their time touching each other, and frequently followed each other around. The researchers also recorded special squeaks, purrs and other communicative noises making up a wide vocal repertoire. Further behavioral studies and field observation would uncover more insights into their reproductive and family life.

After the researchers established a baseline of behavior, they offered rats branches from the poison arrow tree. Although rats did not sequester every time the plant was offered, 10 rats did at least once. They chewed it, mixed it with spit, and licked and chewed it into their specialized hairs. Exposure to the Acokanthera toxins did not alter rat behavior, and neither did eating milkweed, the same cardenolide-enriched plant used as chemical defense by monarch butterflies. Combined, these observations suggest that crested rats are uniquely resistant to these toxins.

"Most people think that it was a myth because of the potency of the tree," said Nyawira. "But we caught it on video! It was very crazy."

The rats were selective about using Acokanthera cardenolides, suggesting that rats may be picky about their toxin source, or that anointed toxins remain potent on the fur a long time, just like traditional arrow poisons from the same source.

African crested rat conservation

The African crested rat is listed as IUCN species of least concern, but there's little actual data on the animals. Agwanda has studied African crested rats for more than a decade--and sees indications that they're in trouble.

"We don't have accurate numbers, but we have inferences. There was a time in Nairobi when cars would hit them and there was roadkill everywhere," said Agwanda, who continues to monitor the populations. "Now encountering them is difficult. Our trapping rate is low. Their population is declining."

The research team is planning future studies to better understand their physiology and behavior. "We are particularly interested in exploring the genetic mechanisms that allow the crested rats and their parasites to withstand the toxic cardenolides" said co-author Jesús Maldonado of the Smithsonian Conservation Biology Institute and Weinstein's Smithsonian-Mpala Postdoctoral fellowship co-advisor.

"We are looking at a broad range of questions influenced by habitat change. Humans have cleared forests to make farms and roads. We need to understand how that impacts their survival," Agwanda said. Additionally, Agwanda is building an exhibit at the Museums of Kenya to raise awareness about this unique poisonous animal.

DALLAS (SMU) - A new study suggests that the Texas Research Incentive Program (TRIP) has succeeded in boosting the amount of private donations to public universities, indicating that policymakers can effectively leverage public investment to spur private donations.

The authors of the analysis, published in the American Educational Research Journal, note that further questions warrant study - such as whether the TRIP model increases institutional inequity over time.

Under the 2009 law that created TRIP, seven public "emerging research universities" were made eligible to receive matching funds from the state for gifts or endowment donations received from private sources: the University of Houston, University of North Texas, Texas Tech University and four of the University of Texas branch campuses. Texas State University was added to that list in 2013. TRIP-eligible colleges were selected based on a set of metrics such as the number of doctoral degrees awarded and faculty quality.

Researchers used data collected from 2006 to 2017 from the government's Integrated Postsecondary Education Data System, state-level data from the Census Bureau and the Texas Higher Education Coordinating Board to determine TRIP's effect on the eligible universities. The universities that adopted TRIP saw a 37.2 percent annual increase ($6.7 million more per year) in private gifts made by donors when compared to the amount similar non-TRIP institutions received. State funding for grants and contracts, which includes matching money for these gifts, also increased by $14 million among TRIP-eligible universities.

The program did not lead to a significant increase in long-term endowment assets, which indicates the donations are likely used for short-term funding.

"Our study provides new evidence that increased government support could stimulate monetary donations and help build universities' research capacity," said Denisa Gándara, co-author and assistant professor in SMU's Department of Education Policy and Leadership in the Simmons School of Education and Human Development. "Government support appears to signal two things to potential donors: one, that their dollar will be worth more given the matching funds and two, that their research for the eligible institutions is a valuable one."

The research team, which included Frank Fernandez at the University of Mississippi, stopped short of saying whether other states should adopt a similar program as Texas to boost research in public universities.

"One perspective is that TRIP is reducing inequality between the emerging research universities and two of the largest public universities for research in Texas--University of Texas at Austin and Texas A&M University," said lead author Xiaodan Hu, assistant professor in higher education at Northern Illinois University. "Another perspective is that the ascendance of emerging research universities could allow other public institutions in Texas, including minority-serving institutions, to fall further behind in terms of public funding and research capacity."

Finding the balance between efficiency and equity is therefore important to consider when adopting a research incentive policy statewide, Hu said.

Researchers were not able to isolate the amount of private donations specifically earmarked for research due to data limitations. They did, however, take multiple steps to ensure their findings were the result of TRIP and not some other reason. One of those measures was accounting for institution-specific trends that occurred before and after the program took effect in 2009 to ensure those trends were not a factor in their results.

The researchers also compared several non-TRIP colleges around the country to the eight universities that were studied.

Astronomers using data from the ongoing VLA Sky Survey (VLASS) have found a number of distant galaxies with supermassive black holes at their cores that have launched powerful, radio-emitting jets of material within the past two decades or so. The scientists compared data from VLASS with data from an earlier survey that also used the National Science Foundation's Karl G. Jansky Very Large Array (VLA) to reach their conclusion.

"We found galaxies that showed no evidence of jets before but now show clear indications of having young, compact jets," said Dr. Kristina Nyland, who is an NRC postdoctoral fellow in residence at the Naval Research Laboratory.

"Jets like these can strongly affect the growth and evolution of their galaxies, but we still don't understand all of the details. Catching newborn jets with surveys like VLASS provides a measure of the role of powerful radio jets in shaping the lives of the galaxies over billions of years," Nyland said.

VLASS is a project that will survey the sky visible from the VLA -- about 80 percent of the entire sky -- three times over seven years. The observations began in 2017 and the first of the three scans now is complete. Nyland and her colleagues compared data from this scan with data from the FIRST survey that used the VLA to observe a smaller portion of the sky between 1993 and 2011.

They found about 2,000 objects that appear in the VLASS images, but were not detected in the earlier FIRST survey. From these, they selected 26 objects that previously were categorized as galaxies with active nuclei -- powered by supermassive black holes -- by optical and infrared observations. The FIRST observations of the 26 objects had been made between 1994 and 2001. The VLASS observations were made in 2019. The intervals between observations of the objects thus ranged from 18 to 25 years.

They chose 14 of these galaxies for more detailed observations with the VLA. These observations provided higher-resolution images and also were done at multiple radio frequencies to get a more complete understanding of the objects' characteristics.

"The data from these detailed observations tell us that the most likely cause of the difference in radio brightness between the FIRST and the VLASS observations is that the 'engines' at the cores of these galaxies have launched new jets since the FIRST observations were made," explained Dillon Dong, from Caltech.

The black holes at the cores of galaxies are known to interact with the galaxies themselves, and the two evolve together. The jets launched from the regions near the black holes can affect the amount of star formation within the galaxy.

"Radio jets provide natural laboratories for learning about the extreme physics of supermassive black holes, whose formation and growth are believed to be intrinsically linked to that of the galaxy centers in which they reside," said Pallavi Patil, of the University of Virginia.

"Jets as young as the ones discovered in our study can provide us with a rare opportunity to gain new insights on how these interactions between the jets and their surroundings work," Nyland said.

"VLASS has proven to be a key tool for discovering such jets, and we eagerly await the results of its next two observing epochs," said Mark Lacy, of the National Radio Astronomy Observatory.

Nyland and her colleagues plan further studies of the galaxies using the Very Long Baseline Array (VLBA), the Chandra X-Ray Observatory, and visible-light and infrared telescopes. The paper has been accepted into publication by the Astrophysical Journal.

Increasingly, artificial intelligence systems known as deep learning neural networks are used to inform decisions vital to human health and safety, such as in autonomous driving or medical diagnosis. These networks are good at recognizing patterns in large, complex datasets to aid in decision-making. But how do we know they're correct? Alexander Amini and his colleagues at MIT and Harvard University wanted to find out.

They've developed a quick way for a neural network to crunch data, and output not just a prediction but also the model's confidence level based on the quality of the available data. The advance might save lives, as deep learning is already being deployed in the real world today. A network's level of certainty can be the difference between an autonomous vehicle determining that "it's all clear to proceed through the intersection" and "it's probably clear, so stop just in case."

Current methods of uncertainty estimation for neural networks tend to be computationally expensive and relatively slow for split-second decisions. But Amini's approach, dubbed "deep evidential regression," accelerates the process and could lead to safer outcomes. "We need the ability to not only have high-performance models, but also to understand when we cannot trust those models," says Amini, a PhD student in Professor Daniela Rus' group at the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL).

"This idea is important and applicable broadly. It can be used to assess products that rely on learned models. By estimating the uncertainty of a learned model, we also learn how much error to expect from the model, and what missing data could improve the model," says Rus.

Amini will present the research at next month's NeurIPS conference, along with Rus, who is the Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science, director of CSAIL, and deputy dean of research for the MIT Stephen A. Schwarzman College of Computing; and graduate students Wilko Schwarting of MIT and Ava Soleimany of MIT and Harvard.

Efficient uncertainty

After an up-and-down history, deep learning has demonstrated remarkable performance on a variety of tasks, in some cases even surpassing human accuracy. And nowadays, deep learning seems to go wherever computers go. It fuels search engine results, social media feeds, and facial recognition. "We've had huge successes using deep learning," says Amini. "Neural networks are really good at knowing the right answer 99 percent of the time." But 99 percent won't cut it when lives are on the line.

"One thing that has eluded researchers is the ability of these models to know and tell us when they might be wrong," says Amini. "We really care about that 1 percent of the time, and how we can detect those situations reliably and efficiently."

Neural networks can be massive, sometimes brimming with billions of parameters. So it can be a heavy computational lift just to get an answer, let alone a confidence level. Uncertainty analysis in neural networks isn't new. But previous approaches, stemming from Bayesian deep learning, have relied on running, or sampling, a neural network many times over to understand its confidence. That process takes time and memory, a luxury that might not exist in high-speed traffic.

The researchers devised a way to estimate uncertainty from only a single run of the neural network. They designed the network with bulked up output, producing not only a decision but also a new probabilistic distribution capturing the evidence in support of that decision. These distributions, termed evidential distributions, directly capture the model's confidence in its prediction. This includes any uncertainty present in the underlying input data, as well as in the model's final decision. This distinction can signal whether uncertainty can be reduced by tweaking the neural network itself, or whether the input data are just noisy.

Confidence check

To put their approach to the test, the researchers started with a challenging computer vision task. They trained their neural network to analyze a monocular color image and estimate a depth value (i.e. distance from the camera lens) for each pixel. An autonomous vehicle might use similar calculations to estimate its proximity to a pedestrian or to another vehicle, which is no simple task.

Their network's performance was on par with previous state-of-the-art models, but it also gained the ability to estimate its own uncertainty. As the researchers had hoped, the network projected high uncertainty for pixels where it predicted the wrong depth. "It was very calibrated to the errors that the network makes, which we believe was one of the most important things in judging the quality of a new uncertainty estimator," Amini says.

To stress-test their calibration, the team also showed that the network projected higher uncertainty for "out-of-distribution" data -- completely new types of images never encountered during training. After they trained the network on indoor home scenes, they fed it a batch of outdoor driving scenes. The network consistently warned that its responses to the novel outdoor scenes were uncertain. The test highlighted the network's ability to flag when users should not place full trust in its decisions. In these cases, "if this is a health care application, maybe we don't trust the diagnosis that the model is giving, and instead seek a second opinion," says Amini.

The network even knew when photos had been doctored, potentially hedging against data-manipulation attacks. In another trial, the researchers boosted adversarial noise levels in a batch of images they fed to the network. The effect was subtle -- barely perceptible to the human eye -- but the network sniffed out those images, tagging its output with high levels of uncertainty. This ability to sound the alarm on falsified data could help detect and deter adversarial attacks, a growing concern in the age of deepfakes.

Deep evidential regression is "a simple and elegant approach that advances the field of uncertainty estimation, which is important for robotics and other real-world control systems," says Raia Hadsell, an artificial intelligence researcher at DeepMind who was not involved with the work. "This is done in a novel way that avoids some of the messy aspects of other approaches -- e.g. sampling or ensembles -- which makes it not only elegant but also computationally more efficient -- a winning combination."

Deep evidential regression could enhance safety in AI-assisted decision making. "We're starting to see a lot more of these [neural network] models trickle out of the research lab and into the real world, into situations that are touching humans with potentially life-threatening consequences," says Amini. "Any user of the method, whether it's a doctor or a person in the passenger seat of a vehicle, needs to be aware of any risk or uncertainty associated with that decision." He envisions the system not only quickly flagging uncertainty, but also using it to make more conservative decision making in risky scenarios like an autonomous vehicle approaching an intersection.

"Any field that is going to have deployable machine learning ultimately needs to have reliable uncertainty awareness," he says.

Imagine if robots could learn from watching demonstrations: you could show a domestic robot how to do routine chores or set a dinner table. In the workplace, you could train robots like new employees, showing them how to perform many duties. On the road, your self-driving car could learn how to drive safely by watching you drive around your neighborhood.

Making progress on that vision, USC researchers have designed a system that lets robots autonomously learn complicated tasks from a very small number of demonstrations--even imperfect ones. The paper, titled Learning from Demonstrations Using Signal Temporal Logic, was presented at the Conference on Robot Learning (CoRL), Nov. 18.

The researchers' system works by evaluating the quality of each demonstration, so it learns from the mistakes it sees, as well as the successes. While current state-of-art methods need at least 100 demonstrations to nail a specific task, this new method allows robots to learn from only a handful of demonstrations. It also allows robots to learn more intuitively, the way humans learn from each other -- you watch someone execute a task, even imperfectly, then try yourself. It doesn't have to be a "perfect" demonstration for humans to glean knowledge from watching each other.

"Many machine learning and reinforcement learning systems require large amounts of data data and hundreds of demonstrations--you need a human to demonstrate over and over again, which is not feasible," said lead author Aniruddh Puranic, a Ph.D. student in computer science at the USC Viterbi School of Engineering.

"Also, most people don't have programming knowledge to explicitly state what the robot needs to do, and a human cannot possibly demonstrate everything that a robot needs to know. What if the robot encounters something it hasn't seen before? This is a key challenge."

Learning from demonstrations

Learning from demonstrations is becoming increasingly popular in obtaining effective robot control policies -- which control the robot's movements -- for complex tasks. But it is susceptible to imperfections in demonstrations and also raises safety concerns as robots may learn unsafe or undesirable actions.

Also, not all demonstrations are equal: some demonstrations are a better indicator of desired behavior than others and the quality of the demonstrations often depends on the expertise of the user providing the demonstrations.

To address these issues, the researchers integrated "signal temporal logic" or STL to evaluate the quality of demonstrations and automatically rank them to create inherent rewards.

In other words, even if some parts of the demonstrations do not make any sense based on the logic requirements, using this method, the robot can still learn from the imperfect parts. In a way, the system is coming to its own conclusion about the accuracy or success of a demonstration.

"Let's say robots learn from different types of demonstrations -- it could be a hands-on demonstration, videos, or simulations -- if I do something that is very unsafe, standard approaches will do one of two things: either, they will completely disregard it, or even worse, the robot will learn the wrong thing," said co-author Stefanos Nikolaidis, a USC Viterbi assistant professor of computer science.

"In contrast, in a very intelligent way, this work uses some common sense reasoning in the form of logic to understand which parts of the demonstration are good and which parts are not. In essence, this is exactly what also humans do."

Take, for example, a driving demonstration where someone skips a stop sign. This would be ranked lower by the system than a demonstration of a good driver. But, if during this demonstration, the driver does something intelligent -- for instance, applies their brakes to avoid a crash -- the robot will still learn from this smart action.

Adapting to human preferences

Signal temporal logic is an expressive mathematical symbolic language that enables robotic reasoning about current and future outcomes. While previous research in this area has used "linear temporal logic", STL is preferable in this case, said Jyo Deshmukh, a former Toyota engineer and USC Viterbi assistant professor of computer science .

"When we go into the world of cyber physical systems, like robots and self-driving cars, where time is crucial, linear temporal logic becomes a bit cumbersome, because it reasons about sequences of true/false values for variables, while STL allows reasoning about physical signals."

Puranic, who is advised by Deshmukh, came up with the idea after taking a hands-on robotics class with Nikolaidis, who has been working on developing robots to learn from YouTube videos. The trio decided to test it out. All three said they were surprised by the extent of the system's success and the professors both credit Puranic for his hard work.

"Compared to a state-of-the-art algorithm, being used extensively in many robotics applications, you see an order of magnitude difference in how many demonstrations are required," said Nikolaidis.

The system was tested using a Minecraft-style game simulator, but the researchers said the system could also learn from driving simulators and eventually even videos. Next, the researchers hope to try it out on real robots. They said this approach is well suited for applications where maps are known beforehand but there are dynamic obstacles in the map: robots in household environments, warehouses or even space exploration rovers.

"If we want robots to be good teammates and help people, first they need to learn and adapt to human preference very efficiently," said Nikolaidis. "Our method provides that."

"I'm excited to integrate this approach into robotic systems to help them efficiently learn from demonstrations, but also effectively help human teammates in a collaborative task."

Houston - (Nov 18, 2020) - On behalf of Childhood Liver Disease Research Network (ChiLDReN), Texas Children's Hospital and Baylor College of Medicine researchers report that prolonged treatment with Maraxilibat resulted in clinically meaningful improvements in debilitating itching (pruritus) and related quality of life outcomes in children with Alagille syndrome. This syndrome is a rare genetic systemic disorder in which problems with bile flow can cause significant liver injury and potential liver failure necessitating liver transplantation. The novel pharmacological approach addresses a major unfulfilled therapeutic need to control severe itching in pediatric patients with Alagille syndrome.

This was the first preliminary presentation of the data from the recently concluded multi-institutional clinical trial called IMAGINE II (ClinicalTrials.gov Identifier: NCT02117713). The results, presented as a late-breaker abstract, were shared by Dr. Benjamin Shneider, chief of Pediatric Gastroenterology, Hepatology and Nutrition at Texas Children's Hospital and professor of Pediatrics at Baylor College of Medicine, as an oral presentation on Nov. 15 at the Liver Meeting Digital Experience™, the virtual annual conference organized by the American Association for the Study of Liver Diseases (AASLD). The study was conducted under the auspices of the NIDDK-funded Childhood Liver Disease Research Network (ChiLDReN) in the context of a cooperative research and development agreement with Mirum Pharmaceuticals.

Severe cholestasis is common in children with Alagille Syndrome and can appear in infancy. In this condition, the flow of bile (fluid that helps digest fats) is reduced, presumably due to impaired development of bile ducts through which bile flows. Accumulation of bile in the liver leads to progressive damage in this critical organ. This genetic disorder can also lead to problems in the heart, kidneys, blood vessels, skeleton and others.

"Poor bile flow, which impacts a significant proportion of children with Alagille syndrome, manifests in part as debilitating itching. The urge to scratch is so strong and unrelenting that these young patients and their families are unable to sleep at night. Constant scratching can lead to bleeding and scarring of large swaths of skin, significant fatigue due to sleep deprivation and psychosocial effects, adversely impacting the quality of life," Shneider, who also holds the George Peterkin Endowed Chair at Baylor College of Medicine, said.

Standard and non-standard anti-itch medicines that are presently available have limited efficacy in children with Alagille Syndrome who have moderate to severe pruritus. Currently, the only effective treatment options beyond available medications for treating their pruritus involves complex invasive surgeries to either divert the bile flow away from the liver (e.g. the biliary diversion procedure) or liver transplantation. Even still, these are not perfect solutions. While transplantation may address the issue of itching, since Alagille is a systemic disorder affecting several organs, liver transplantation will not improve other health problems confronting these patients and undergoing the procedure carries its own risks.

The IMAGINE II clinical trial was designed to specifically address the problem of pruritus in Alagille patients. It was a follow-up to a previous study called ITCH, a 13-week randomized placebo-controlled trial, which was also led by Shneider and conducted under the auspices of the Childhood Liver Disease Network. The ITCH trial showed that maraxilibat was safe, generally well tolerated and, more importantly, provided the first evidence of short-term potential efficacy of this drug in treating pruritus in Alagille patients. At the conclusion of that study, all enrolled participants, irrespective of whether they received the drug or placebo, were offered the opportunity to rollover to the longer IMAGINE II trial. Since some patients had already received a short course of Maraxilibat in the previous ITCH trial, the results presented in this initial report are a combined analysis of the data from both trials.

ITCH and IMAGINE II trials were based on the hypothesis that since Maralixibat inhibits the sodium-dependent bile acid transporter protein that facilitates the enterohepatic circulation of bile acids, it may, pharmacologically, mimic the beneficial effects of a biliary diversion surgery. Maralixibat was granted Breakthrough Therapy Designation by the Food and Drug Administration (FDA) for Alagille syndrome in 2019.

Since it is difficult to quantify itching, researchers used two different qualitative scales to measure itching severity. ItchRO is a novel electronic diary based on caregiver's observation twice a day and a four-point clinician scratch scale (CSS) assessed by clinical investigators. In addition, they evaluated health-related quality of life outcomes using PedsQL and multidimension fatigue scale. A 'clinically meaningful' response was defined as one-point reduction in ItchRO and CSS and a five-point increase in PedsQL.

"At the end of >96-weeks of treatment, 90% and 80% of the participants who were able to receive maralixibat to that time point had clinically meaningful responses in ItchRO and CSS scales respectively. We were particularly excited to see 25% of participants showed dramatic four-point reduction in itching on the CSS scale. They went from severe itching (described as "cutaneous self-mutilation") to no features of scratching, which as one can imagine, dramatically improves the quality of life for patients and their families. Although further complex analyses of this data and others is still needed to determine the impact of maralixibat on other aspects of the liver disease in Alagille syndrome, finding a drug that effectively treats pruritus is truly a game-changer for children and families who struggle with Alagille Syndrome," Shneider concluded.

FINDINGS

UCLA scientists and colleagues found the use of long-acting antipsychotic medication combined with the use of cognitive training in group settings led to improved cognition and increased productivity.

Researchers say patients using a combination of long-acting antipsychotic medication and a multipronged cognitive remediation that taught memory and problem-solving skills had significant improvements in work and school function.

BACKGROUND

Schizophrenia is a serious mental illness that affects how a person thinks, feels and behaves. People with schizophrenia may appear to have lost touch with reality, which can cause distress for family and friends and lead to permanent disability. Treatments delivered in a sustained manner can help people with schizophrenia engage in school or work, achieve independence and enjoy personal relationships.

METHODS

During a 12-month randomized controlled trial, 60 patients from the UCLA Aftercare Program who recently experienced a first episode of schizophrenia were randomized to oral or long-acting injectable antipsychotic medication and to either cognitive remediation or healthy behavior training. Cognitive remediation involved training in attention, memory, and problem-solving skills to help navigate complex, life-like situations. The healthy behavior training focused on nutrition, stress management, and exercise, with equal treatment time. All patients were provided supported employment and education to encourage return to work or school.

IMPACT

Systematic cognitive training, when combined with consistent antipsychotic medication adherence, achieved in this case through the use of a long-acting medication, can significantly improve cognitive deficits in the initial period of schizophrenia. These therapies show a separate significant impact on improving work and school functioning.

Scientists are still solving the many puzzling aspects of how the novel coronavirus attacks the lungs and other parts of the body. One of the biggest and most life-threatening mysteries is how the virus causes "silent hypoxia," a condition when oxygen levels in the body are abnormally low, which can irreparably damage vital organs if gone undetected for too long. Now, thanks to computer models and comparisons with real patient data, Boston University biomedical engineers and collaborators from the University of Vermont have begun to crack the mystery.

Despite experiencing dangerously low levels of oxygen, many people infected with severe cases of COVID-19 sometimes show no symptoms of shortness of breath or difficulty breathing. Hypoxia's ability to quietly inflict damage is why it's been coined "silent." In coronavirus patients, it's thought that the infection first damages the lungs, rendering parts of them incapable of functioning properly. Those tissues lose oxygen and stop working, no longer infusing the blood stream with oxygen, causing silent hypoxia. But exactly how that domino effect occurs has not been clear until now.

"We didn't know [how this] was physiologically possible," says Bela Suki, a BU College of Engineering professor of biomedical engineering and of materials science and engineering and one of the authors of the study. Some coronavirus patients have experienced what some experts have described as levels of blood oxygen that are "incompatible with life." Disturbingly, Suki says, many of these patients showed little to no signs of abnormalities when they underwent lung scans.

To help get to the bottom of what causes silent hypoxia, BU biomedical engineers used computer modeling to test out three different scenarios that help explain how and why the lungs stop providing oxygen to the bloodstream. Their research, which has been published in Nature Communications, reveals that silent hypoxia is likely caused by a combination of biological mechanisms that may occur simultaneously in the lungs of COVID-19 patients, according to biomedical engineer Jacob Herrmann, a research postdoctoral associate in Suki's lab and the lead author of the new study.

Normally, the lungs perform the life-sustaining duty of gas exchange, providing oxygen to every cell in the body as we breathe in and ridding us of carbon dioxide each time we exhale. Healthy lungs keep the blood oxygenated at a level between 95 and 100 percent--if it dips below 92 percent, it's a cause for concern and a doctor might decide to intervene with supplemental oxygen. (Early in the coronavirus pandemic, when clinicians first started sounding the alarm about silent hypoxia, oximeters flew off store shelves as many people, worried that they or their family members might have to recover from milder cases of coronavirus at home, wanted to be able to monitor their blood oxygen levels.)

The researchers first looked at how COVID-19 impacts the lungs' ability to regulate where blood is directed. Normally, if areas of the lung aren't gathering much oxygen due to damage from infection, the blood vessels will constrict in those areas. This is actually a good thing that our lungs have evolved to do, because it forces blood to instead flow through lung tissue replete with oxygen, which is then circulated throughout the rest of the body.

But according to Herrmann, preliminary clinical data have suggested that the lungs of some COVID-19 patients had lost the ability of restricting blood flow to already damaged tissue, and in contrast, were potentially opening up those blood vessels even more--something that is hard to see or measure on a CT scan.

Using a computational lung model, Herrmann, Suki, and their team tested that theory, revealing that for blood oxygen levels to drop to the levels observed in COVID-19 patients, blood flow would indeed have to be much higher than normal in areas of the lungs that can no longer gather oxygen--contributing to low levels of oxygen throughout the entire body, they say.

Next, they looked at how blood clotting may impact blood flow in different regions of the lung. When the lining of blood vessels get inflamed from COVID-19 infection, tiny blood clots too small to be seen on medical scans can form inside the lungs. They found, using computer modeling of the lungs, that this could incite silent hypoxia, but alone it is likely not enough to cause oxygen levels to drop as low as the levels seen in patient data.

Last, the researchers used their computer model to find out if COVID-19 interferes with the normal ratio of air-to-blood flow that the lungs need to function normally. This type of mismatched air-to-blood flow ratio is something that happens in many respiratory illnesses, such as with asthma patients, Suki says, and it can be a possible contributor to the severe, silent hypoxia that has been observed in COVID-19 patients. Their models suggest that for this to be a cause of silent hypoxia, the mismatch must be happening in parts of the lung that don't appear injured or abnormal on lung scans.

Altogether, their findings suggest that a combination of all three factors are likely to be responsible for the severe cases of low oxygen in some COVID-19 patients. By having a better understanding of these underlying mechanisms, and how the combinations could vary from patient to patient, clinicians can make more informed choices about treating patients using measures like ventilation and supplemental oxygen. A number of interventions are currently being studied, including a low-tech intervention called prone positioning that flips patients over onto their stomachs, allowing for the back part of the lungs to pull in more oxygen and evening out the mismatched air-to-blood ratio.

"Different people respond to this virus so differently," says Suki. For clinicians, he says it's critical to understand all the possible reasons why a patient's blood oxygen might be low, so that they can decide on the proper form of treatment, including medications that could help constrict blood vessels, bust blood clots, or correct a mismatched air-to-blood flow ratio.

ORLANDO, Nov. 19, 2020 - New research from the University of Central Florida has identified physiological features that could make people super-spreaders of viruses such as COVID-19.

In a study appearing this month in the journal Physics of Fluids, researchers in UCF's Department of Mechanical and Aerospace Engineering used computer-generated models to numerically simulate sneezes in different types of people and determine associations between people's physiological features and how far their sneeze droplets travel and linger in the air.

They found that people's features, like a stopped-up nose or a full set of teeth, could increase their potential to spread viruses by affecting how far droplets travel when they sneeze.

According to the U.S. Centers for Disease Control and Prevention, the main way people are infected by the virus that causes COVID-19 is through exposure to respiratory droplets, such as from sneezes and coughs that are carrying infectious virus.

Knowing more about factors affecting how far these droplets travel can inform efforts to control their spread, says Michael Kinzel, an assistant professor with UCF's Department of Mechanical Engineering and study co-author.

"This is the first study that aims to understand the underlying 'why' of how far sneezes travel," Kinzel says. "We show that the human body has influencers, such as a complex duct system associated with the nasal flow that actually disrupts the jet from your mouth and prevents it from dispersing droplets far distances."

For instance, when people have a clear nose, such as from blowing it into a tissue, the speed and distance sneeze droplets travel decrease, according to the study.

This is because a clear nose provides a path in addition to the mouth for the sneeze to exit. But when people's noses are congested, the area that the sneeze can exit is restricted, thus causing sneeze droplets expelled from the mouth to increase in velocity.

Similarly, teeth also restrict the sneeze's exit area and cause droplets to increase in velocity.

"Teeth create a narrowing effect in the jet that makes it stronger and more turbulent," Kinzel says. "They actually appear to drive transmission. So, if you see someone without teeth, you can actually expect a weaker jet from the sneeze from them."

To perform the study, the researchers used 3D modeling and numerical simulations to recreate four mouth and nose types: a person with teeth and a clear nose; a person with no teeth and a clear nose; a person with no teeth and a congested nose; and a person with teeth and a congested nose.

When they simulated sneezes in the different models, they found that the spray distance of droplets expelled when a person has a congested nose and a full set of teeth is about 60 percent greater than when they do not.

The results indicate that when someone keeps their nose clear, such as by blowing it into a tissue, that they could be reducing the distance their germs travel.

The researchers also simulated three types of saliva: thin, medium and thick.

They found that thinner saliva resulted in sneezes comprised of smaller droplets, which created a spray and stayed in the air longer than medium and thick saliva.

For instance, three seconds after a sneeze, when thick saliva was reaching the ground and thus diminishing its threat, the thinner saliva was still floating in the air as a potential disease transmitter.

The work ties back to the researchers' project to create a COVID-19 cough drop that would give people thicker saliva to reduce the distance droplets from a sneeze or cough would travel, and thus decrease disease-transmission likelihood.

The findings yield novel insight into variability of exposure distance and indicate how physiological factors affect transmissibility rates, says Kareem Ahmed, an associate professor in UCF's Department of Mechanical and Aerospace Engineering and study co-author.

"The results show exposure levels are highly dependent on the fluid dynamics that can vary depending on several human features," Ahmed says. "Such features may be underlying factors driving superspreading events in the COVID-19 pandemic."

The researchers say they hope to move the work toward clinical studies next to compare their simulation findings with those from real people from varied backgrounds.

Study co-authors were Douglas Fontes, a postdoctoral researcher with the Florida Space Institute and the study's lead author, and Jonathan Reyes, a postdoctoral researcher in UCF's Department of Mechanical and Aerospace Engineering.

Fontes says to advance the findings of the study, the research team wants to investigate the interactions between gas flow, mucus film and tissue structures within the upper respiratory tract during respiratory events.

"Numerical models and experimental techniques should work side by side to provide accurate predictions of the primary breakup inside the upper respiratory tract during those events," he says.

"This research potentially will provide information for more accurate safety measures and solutions to reduce pathogen transmission, giving better conditions to deal with the usual diseases or with pandemics in the future," he says.

A new study from Tel Aviv University (TAU) and the Shamir Medical Center in Israel indicates that hyperbaric oxygen treatments (HBOT) in healthy aging adults can stop the aging of blood cells and reverse the aging process. In the biological sense, the adults' blood cells actually grow younger as the treatments progress.

The researchers found that a unique protocol of treatments with high-pressure oxygen in a pressure chamber can reverse two major processes associated with aging and its illnesses: the shortening of telomeres (protective regions located at both ends of every chromosome) and the accumulation of old and malfunctioning cells in the body. Focusing on immune cells containing DNA obtained from the participants' blood, the study discovered a lengthening of up to 38% of the telomeres, as well as a decrease of up to 37% in the presence of senescent cells.

The study was led by Professor Shai Efrati of the Sackler School of Medicine and the Sagol School of Neuroscience at TAU and Founder and Director of the Sagol Center of Hyperbaric Medicine at the Shamir Medical Center; and Dr. Amir Hadanny, Chief Medical Research Officer of the Sagol Center for Hyperbaric Medicine and Research at the Shamir Medical Center. The clinical trial was conducted as part of a comprehensive Israeli research program that targets aging as a reversible condition.

The paper was published in Aging on November 18, 2020.

"For many years our team has been engaged in hyperbaric research and therapy - treatments based on protocols of exposure to high-pressure oxygen at various concentrations inside a pressure chamber," Professor Efrati explains. "Our achievements over the years included the improvement of brain functions damaged by age, stroke or brain injury.

"In the current study we wished to examine the impact of HBOT on healthy and independent aging adults, and to discover whether such treatments can slow down, stop or even reverse the normal aging process at the cellular level."

The researchers exposed 35 healthy individuals aged 64 or over to a series of 60 hyperbaric sessions over a period of 90 days. Each participant provided blood samples before, during and at the end of the treatments as well as some time after the series of treatments concluded. The researchers then analyzed various immune cells in the blood and compared the results.

The findings indicated that the treatments actually reversed the aging process in two of its major aspects: The telomeres at the ends of the chromosomes grew longer instead of shorter, at a rate of 20%-38% for the different cell types; and the percentage of senescent cells in the overall cell population was reduced significantly - by 11%-37% depending on cell type.

"Today telomere shortening is considered the 'Holy Grail' of the biology of aging," Professor Efrati says. "Researchers around the world are trying to develop pharmacological and environmental interventions that enable telomere elongation. Our HBOT protocol was able to achieve this, proving that the aging process can in fact be reversed at the basic cellular-molecular level."

"Until now, interventions such as lifestyle modifications and intense exercise were shown to have some inhibiting effect on telomere shortening," Dr. Hadanny adds. "But in our study, only three months of HBOT were able to elongate telomeres at rates far beyond any currently available interventions or lifestyle modifications. With this pioneering study, we have opened a door for further research on the cellular impact of HBOT and its potential for reversing the aging process."

Researchers at UPF have analysed the relationship between civil society organizations and the Spanish science and technology system. The study has been published in Public Understanding of Science and conducted by Carolina Llorente and Gema Revuelta, at the Science, Communication and Society Studies Centre (CCS-UPF), and Mar Carrió, of the Health Sciences Educational Research Group (GRECS).

In recent decades, various movements have emerged promoting the inclusion of society in the research process in order to build more socially relevant science. This new model of scientific production is becoming established in Europe and increasingly worldwide. "Often, social participation does not take place individually, but through civil society organizations, so our study, for the first time in Spain, explores the interactions between these organizations and science", Carolina Llorente explains. "Understanding the perspectives of these organizations is useful for proposing effective tools to help strengthen relations between science and society", she adds. The concept of organized civil society includes non-profit organizations in which citizens are generally involved on a voluntary basis: patient and consumer associations, organizations working for the environment or animal rights, humanitarian associations, groups of minorities, etc.

The analysis was based on semi-structured interviews with managers of 31 Spanish organizations. Organizations were selected taking into account their characteristics and distribution across the country. In Spain, there are three so-called unique organizations, La ONCE, the Red Cross and Cáritas, which account for over 60% of the country's volunteers. There are also groups of organizations (federations), but what really makes up the bulk of volunteers are small, decentralized associations which are highly active at local level, but generally have few financial resources.

The study results show that a large number of organizations are not involved in science and technology, or in some cases, are not aware of their involvement. The most common type of collaboration is to act as research study subjects, for example in cases where social associations whose members are interviewed. Such is the case, for example, of investigations that examine the role of certain minorities (i.e., religious or linguistic) that contact organizations dealing with such matters to interview their members. To a lesser extent, organizations, usually patient organizations, fund research through calls to tender, prizes and awards, or they carry out research within the organization. In some cases, organizations also participate as advisors or in training targeting the researchers to transfer their sectoral knowledge to the academic environment.

Regarding hindrances for participation, interviewees agree that the main one is the lack of financial resources and personnel. But they also mention the lack of mutual knowledge: scientists do not know what the organizations are doing and the latter are not aware of what they can contribute or do not know how they can engage in scientific production.

In the words of Mar Carrió: "as a strategy to improve ties, we believe there is a need to encourage researchers to know how to integrate into the organizations and vice versa, for these groups to gain greater knowledge of how science works".

As for the ideal relationship that the associations wish to have with the system of science and technology, generally speaking, civil society organizations appear to be unaware of their own potential and what they can contribute to research. Nevertheless, the results indicate that these associations are willing to engage in scientific production, for example, proposing that they should be consulted from the outset to help approach research.

"In order to promote relations between science and society, there is a need to strengthen alliances between these two worlds. This could be done through better communication between academia and civil society organizations and, therefore, researchers require solid training in this field", Gema Revuelta affirms. "But, we also have to open channels that allow formal, stable relations between institutions and align the research goals with the expectations of society", she concludes.