Amazing Science

Extremely hot years will wipe out hundreds of thousands of tonnes of fish available for catch in a country's waters in this century, on top of projected decreases to fish stocks from long-term climate change, a new UBC study projects.

Researchers from the UBC Institute for the Oceans and Fisheries (IOF) used a complex model incorporating extreme annual ocean temperatures in Exclusive Economic Zones, where the majority of global fish catches occur, into climate-related projections for fish, fisheries and their dependent human communities.

Modeling a worst-case scenario where no action is taken to mitigate greenhouse gas emissions they projected a six percent drop in the amount of potential catches per year and 77 percent of exploited species are projected to decrease in biomass, or the amount of fish by weight in a given area, due to extremely hot years. These decreases are on top of those projected due to long-term decadal-scale climate change.

• In Pacific Canada, Sockeye salmon catches are projected to decrease by 26 percent on average during a high temperature event between 2000 and 2050, an annual loss of 260 to 520 tons of fish. With losses due to climate change, when a temperature extreme occurs in the 2050s, the total decrease in annual catch would be more than 50 percent or 530 to 1060 tons of fish.
• Peruvian anchoveta catches are projected to decline by 34 percent during an extreme high temperature event between 2000 and 2050, or more than 900,000 tons per year. With climate change, a temperature extreme is projected to cost Peruvian anchoveta fisheries more than 1.5 million tons of their potential catch.
• Overall, a high temperature extreme event is projected to cause a 25 percent drop in annual revenue for Peruvian anchoveta fisheries, or a loss of around US$600 million
• Nearly three million jobs in the Indonesian fisheries-related sector are projected to be lost when a high temperature extreme occurs in their waters between 2000 and 2050.
• Some stocks are projected to increase due to these extreme events, and climate change, but not enough to mitigate the losses

Lasers probe some of nature's most jealously guarded secrets. A newly published theoretical and computer modeling study suggests that the world's most powerful lasers might finally crack the elusive physics behind some of the most extreme phenomena in the universe—gamma ray bursts, pulsar magnetospheres, and more.

The international research team behind the study includes researchers from Lawrence Berkeley National Laboratory (Berkeley Lab) and France's Alternative Energies and Atomic Energy Commission (CEA-LIDYL). They report their findings in the prestigious journal Physical Review Letters.

The research team was led by CEA's Henri Vincenti, who proposed the main physical concept. Jean-Luc Vay and Andrew Myers, of Berkeley Lab's Accelerator Technology and Applied Physics (ATAP) Division and Computational Research Division, respectively, led development of the simulation code used for the research. (Vincenti previously worked at Berkeley Lab as a Marie Curie Research Fellow and remains an ATAP affiliate and frequent collaborator.) The theoretical and numerical work was led by Luca Fedeli from Vincenti's team at CEA.

The team's modeling study shows that petawatt (PW)-class lasers—juiced to even higher intensities via light-matter interactions—might provide a key to unlock the mysteries of the strong-field (SF) regime of quantum electrodynamics (QED). A petawatt is 1 times ten to the fifteenth power (that is, followed by 15 zeroes), or a quadrillion watts. The output of today's most powerful lasers is measured in petawatts.

"This is a powerful demonstration of how advanced simulation of complex systems can enable new paths for discovery science by integrating multiple physics processes—in this case, the laser interaction with a target and subsequent production of particles in a second target," said ATAP Division Director Cameron Geddes.

While QED is a cornerstone of modern physics that has withstood the rigor of experiment over many decades, probing SF-QED requires electromagnetic fields of an intensity many orders of magnitude beyond those normally available on Earth.

Researchers have tried side routes to SF-QED, such as using powerful particle beams from accelerators to observe particle interactions with the strong fields that are naturally present in some aligned crystals.

For a more direct approach, the highest electromagnetic fields available in a laboratory are delivered by PW-class lasers. A 10-PW laser (the world's most powerful at this time), focused down to a few microns, can reach intensities close to 1023 watts per square centimeter. The associated electric field values can be as high as 1014 volts per meter. Yet studying SF-QED requires even higher field amplitudes than that—orders of magnitude beyond what can be achieved with those lasers.

Deep learning has helped advance the state-of-the-art in multiple fields over the last decade, with scientific research as no exception.

The Kepler instrument is a space-based telescope designed to study and planets outside our solar system, aka exoplanets. The first exoplanet orbiting a star like our own was described by Didier Queloz and Michel Mayor in 1995, landing the pair the 2019 Nobel Prize in Physics. More than a decade later when Kepler was launched in 2009, the total number of known exoplanets was less than 400. The now-dormant telescope began operation in 2009, discovering more than 1,000 new exoplanets before a reaction wheel, a component used for precision pointing, failed in 2013.

This brought the primary phase of the mission to an end.

Some clever engineering changes allowed the telescope to begin a second period of data acquisition, termed K2. The data from K2 were noisier and limited to 80 days of continuous observation or less. These limitations pose challenges in identifying promising planetary candidates among the thousands of putative planetary signals, a task that had been previously handled nicely by a convolutional neural network (AstroNet) working with the data from Kepler’s primary data collection phase. Researchers at the University of Texas, Austin decided to try the same approach and derived AstroNet-K2 from the architecture of AstroNet to sort K2 planetary signals.

After training, AstroNet-K2 had a 98% accuracy rate in identifying confirmed exoplanets in the test set, with low false positives. The authors deemed this performance to be sufficient for use as an analysis tool rather than full automation, requiring human follow-up.

From the paper:

While the performance of our network is not quite at the level
required to generate fully automatic and uniform
planet candidate catalogs, it serves as a proof of
concept. — (Dattilo et al. 2019)

AstroNet-K2 receives this blog post’s coveted “Best Value” award for achieving a significant scientific bang-for-your-buck. Unlike the other two projects on this list that are more conceptual demonstrations, this project resulted in actual scientific progress, adding two new confirmed entries to the catalog of known exoplanets: EPIC 246151543 b and EPIC 246078672 b.

In addition to the intrinsic challenges of the K2 data, the signals for the planets were further confounded by Mars transiting the observiation window and by 5 days of missing data associated with a safe mode event. This is a pretty good example of effective machine learning in action: the authors took an existing conv-net with a proven track record and modified it to perform well on the given data, adding a couple new discoveries from a difficult observation run without re-inventing the wheel.

Worth noting is that the study’s lead author, Anne Dattilo, was an undergraduate at the time the work was completed. That’s a pretty good outcome for an undergraduate research project. The use of open-source software and building on previously developed architectures underlines the fact that deep learning is in a advanced readiness phase. The technology is not fully mature to the point of ubiquity, but the tools are all there on the shelf ready to be applied.

A Nature survey shows many scientists expect the virus that causes COVID-19 to become endemic, but it could pose less danger over time.

Nature asked more than 100 immunologists, infectious-disease researchers and virologists working on the coronavirus whether it could be eradicated. Almost 90% of respondents think that the coronavirus will become endemic — meaning that it will continue to circulate in pockets of the global population for years to come (see 'Endemic future').

“Eradicating this virus right now from the world is a lot like trying to plan the construction of a stepping-stone pathway to the Moon. It’s unrealistic,” says Michael Osterholm, an epidemiologist at the University of Minnesota in Minneapolis. But failure to eradicate the virus does not mean that death, illness or social isolation will continue on the scales seen so far. The future will depend heavily on the type of immunity people acquire through infection or vaccination and how the virus evolves. Influenza and the four human coronaviruses that cause common colds are also endemic: but a combination of annual vaccines and acquired immunity means that societies tolerate the seasonal deaths and illnesses they bring without requiring lockdowns, masks and social distancing.

More than one-third of the respondents to Nature’s survey thought that it would be possible to eliminate SARS-CoV-2 from some regions while it continued to circulate in others. In zero-COVID regions there would be a continual risk of disease outbreaks, but they could be quenched quickly by herd immunity if most people had been vaccinated. “I guess COVID will be eliminated from some countries, but with a continuing (and maybe seasonal) risk of reintroduction from places where vaccine coverage and public-health measures have not been good enough,” says Christopher Dye, an epidemiologist at the University of Oxford, UK.

Computers can now beat the best human minds in the most intellectually challenging games — like chess. They can also perform tasks that are difficult for adult humans to learn — like driving cars. Yet autonomous machines have difficulty learning to cooperate, something even young children do.

Human cooperation appears easy — but it’s very difficult to emulate because it relies on cultural norms, deeply rooted instincts, and social mechanisms that express disapproval of non-cooperative behavior.

Such common sense mechanisms aren’t easily built into machines. In fact, the same AI software programs that effectively play the board games of chess +  checkers, Atari video games, and the card game of poker — often fail to consistently cooperate when cooperation is necessary.

Other AI software often takes 100s of rounds of experience to learn to cooperate with each other, if they cooperate at all.  Can we build computers that cooperate with humans — the way humans cooperate with each other? Building on decades of research in AI, we built a new software program that learns to cooperate with other machines — simply by trying to maximize its own world.

We ran experiments that paired the AI with people in various social scenarios — including a “prisoner’s dilemma” challenge and a sophisticated block-sharing game. While the program consistently learns to cooperate with another computer — it doesn’t cooperate very well with people. But people didn’t cooperate much with each other either.

As we all know: humans can cooperate better if they can communicate their intentions through words + body language. So in hopes of creating an program that consistently learns to cooperate with people — we gave our AI a way to listen to people, and to talk to them.

We did that in a way that lets the AI play in previously unanticipated scenarios. The resulting algorithm achieved our goal. It consistently learns to cooperate with people as well as people do. Our results show that 2 computers make a much better team — better than 2 humans, and better than a human + a computer.

But the program isn’t a blind cooperator. In fact, the AI can get pretty angry if people don’t behave well. The historic computer scientist Alan Turing PhD believed machines could potentially demonstrate human-like intelligence. Since then, AI has been regularly portrayed as a threat to humanity or human jobs.

To protect people, programmers have tried to code AI to follow legal + ethical principles — like the 3 Laws of Robotics written by Isaac Asimov PhD. Our research demonstrates that a new path is possible.

Machines designed to selfishly maximize their pay-offs can — and should — make an autonomous choice to cooperate with humans across a wide range of situations. 2 humans — if they were honest with each other + loyal — would have done as well as 2 machines. About half of the humans lied at some point. So the AI is learning that moral characteristics are better — since it’s programmed to not lie — and it also learns to maintain cooperation once it emerges.

The goal is we need to understand the math behind cooperating with people — what attributes does AI need so it can develop social skills. AI must be able to respond to us — and articulate what it’s doing. It must interact with other people. This research could help humans with their relationships. In society, relationships break-down all the time. People that were friends for years all-of-a-sudden become enemies. Because the AI is often better at reaching these compromises than we are, it could teach us how to get-along better.

Researchers Rebecca Moore, Rachel Kaletsky, Chen Lesnik, from Coleen Murphy’s laboratory, demonstrated that the microscopic worm C. elegans uses a retrotransposon called Cer1 to transfer a learned behavior (avoidance of a pathogenic bacterium) between worms.

When an organism encounters a threat in its environment, it is to the species’ advantage to warn others of the peril. The microscopic roundworm C. elegans regularly encounters dangers in its environment such as the pathogenic bacterium P. aeruginosa, which seems like an appealing food source but can sicken worms if eaten. C. elegans isn’t equipped to shout out warnings as a human would, but new work by researchers from Princeton researcher Coleen Murphy’s laboratory shows that worms who encounter P. aeruginosa can help others avoid the danger, and identifies a crucial part of the mechanism by which this is done.

In earlier work, Murphy’s lab discovered that mother worms who are sickened by P. aeruginosa learn to avoid the bacterium, and that they can impress this avoidance behavior upon their offspring for the next four generations. Mother worms who’ve eaten P. aeruginosa absorb a bacterial small RNA called P11 through their intestines, which touches off a signal in the worm’s germ line reproductive cells that is then transmitted to a neuron that controls behavior. Afterwards, the new behavior is conveyed to future progeny via changes made to germ line cells.

In their new paper, co-first authors Rebecca Moore, Rachel Kaletsky, and Chen Lesnik, and colleagues show that avoidance behavior can also be conveyed from trained worms to other, naïve adult worms. “We found that one worm can learn to avoid this pathogenic bacterium and if we grind up that worm, or even just use the media the worms are swimming in, and give that media or the crushed-worm lysate to naive worms, those worms now ‘learn’ to avoid the pathogen as well,” explains Murphy.

This finding suggests that worms secrete some signal that, when picked up by other worms, can modify their behavior. Interestingly, the progeny of worms “educated” by receipt of this signal also avoid pathogenic P. aeruginosa for the following four generations. This suggests that the secreted signal touches off the same learning pathway in recipient worms as in those directly exposed to the pathogen. Murphy’s group sought to identify the secreted signal. “What we discovered is that a retrotransposon called Cer1 that forms viral-like particles seems to carry a memory not only between tissues (from the worm's germline to its neurons) but also between individuals,” says Murphy.

A retrotransposon is a genetic element, similar to a virus, that has inserted itself into a host animal’s DNA. The researchers found that Cer1 is present in the DNA of the worms’ germ line cells, and that mother worms in whom the retrotransposon was knocked down by RNA interference could not learn avoidance of P. aeruginosa via exposure to P11; convey avoidance behavior to offspring; or educate nearby worms. In addition, adult recipient worms needed Cer1 to be present in their genome in order to learn to avoid the pathogen. The authors found that two wild worm strains that naturally lack Cer1 are incapable of doing these things, suggesting that in these strains, Cer1 is needed to establish, transmit and receive this avoidance behavior.

“We think that Cer1 may give worms an advantage in their battle with pathogens, even though acquiring Cer1 in its genome can be deleterious for the worm under non-pathogenic conditions,” says Murphy.

“The findings by Murphy et al. are provocative,” says Dr. Craig Mello, Professor of molecular medicine at the University of Massachusetts and co-discoverer of RNA interference. “This is another intriguing episode in a growing number of studies that have implicated systemic RNA signals in influencing behavior transgenerationally, and if this study is correct, now even horizontally.” Although other studies have shown that animals such as the sea slug Aplysia are capable of transferring memories between individuals, the work by Moore, Kaletsky, Lesnik and colleagues  is the first to suggest a mechanism by which such transfer can occur in nature. However, this study also raises a number of urgent questions. For example, as Mello points out, it’s now well established that worms use RNA signals to pass information to offspring, but it is currently unclear what Cer1 contributes to this pathway.

Researchers from Kaunas universities, Lithuania developed a deep learning-based method that can predict the possible onset of Alzheimer's disease from brain images with an accuracy of over 99 per cent. The method was developed while analyzing functional MRI images obtained from 138 subjects and performed better in terms of accuracy, sensitivity and specificity than previously developed methods.

According to World Health Organization (WHO), Alzheimer's disease is the most frequent cause of dementia, contributing to up to 70 per cent of dementia cases. Worldwide, approximately 24 million people are affected, and this number is expected to double every 20 years. Owing to societal aging, the disease will become a costly public health burden in the years to come.

"Medical professionals all over the world attempt to raise awareness of an early Alzheimer's diagnosis, which provides the affected with a better chance of benefiting from treatment. This was one of the most important issues for choosing a topic for Modupe Odusami, a PhD student from Nigeria," says Rytis Maskeli'nas, a researcher at the Department of Multimedia Engineering, Faculty of Informatics, Kaunas University of Technology (KTU), Odusami's PhD supervisor.

In a discovery published in the journal Nature, an international team of researchers has described a novel molecular device with exceptional computing prowess. Reminiscent of the plasticity of connections in the human brain, the device can be reconfigured on the fly for different computational tasks by simply changing applied voltages. Furthermore, like nerve cells can store memories, the same device can also retain information for future retrieval and processing.

"The brain has the remarkable ability to change its wiring around by making and breaking connections between nerve cells. Achieving something comparable in a physical system has been extremely challenging," said Dr. R. Stanley Williams, professor in the Department of Electrical and Computer Engineering at Texas A&M University. "We have now created a molecular device with dramatic reconfigurability, which is achieved not by changing physical connections like in the brain, but by reprogramming its logic."

Dr. T. Venkatesan, director of the Center for Quantum Research and Technology (CQRT) at the University of Oklahoma, Scientific Affiliate at National Institute of Standards and Technology, Gaithersburg, and adjunct professor of electrical and computer engineering at the National University of Singapore, added that their molecular device might in the future help design next-generation processing chips with enhanced computational power and speed, but consuming significantly reduced energy.

Whether it is the familiar laptop or a sophisticated supercomputer, digital technologies face a common nemesis, the von Neumann bottleneck. This delay in computational processing is a consequence of current computer architectures, wherein the memory, containing data and programs, is physically separated from the processor. As a result, computers spend a significant amount of time shuttling information between the two systems, causing the bottleneck. Also, despite extremely fast processor speeds, these units can be idling for extended amounts of time during periods of information exchange.

As an alternative to conventional electronic parts used for designing memory units and processors, devices called memristors offer a way to circumvent the von Neumann bottleneck. Memristors, such as those made of niobium dioxide and vanadium dioxide, transition from being an insulator to a conductor at a set temperature. This property gives these types of memristors the ability to perform computations and store data.

Berkeley Lab scientists' surprising images of ghost particles could advance quantum computers and high-temperature superconductors.

Scientists have taken the clearest picture yet of electronic particles that make up a mysterious magnetic state called quantum spin liquid (QSL). The achievement could facilitate the development of superfast quantum computers and energy-efficient superconductors. The scientists are the first to capture an image of how electrons in a QSL decompose into spin-like particles called spinons and charge-like particles called chargons.

"Other studies have seen various footprints of this phenomenon, but we have an actual picture of the state in which the spinon lives. This is something new," said study leader Mike Crommie, a senior faculty scientist at Lawrence Berkeley National Laboratory (Berkeley Lab) and physics professor at UC.

"Spinons are like ghost particles. They are like the Big Foot of quantum physics -- people say that they've seen them, but it's hard to prove that they exist," said co-author Sung-Kwan Mo, a staff scientist at Berkeley Lab's Advanced Light Source. "With our method we've provided some of the best evidence to date."

Rare fossils preserving the brains of creatures living more than half a billion years ago shed new light on the evolution of arthropods such as insects and crustaceans.

Exquisitely preserved fossils left behind by creatures living more than half a billion years ago reveal in great detail identical structures that researchers have long hypothesized must have contributed to the archetypal brain that has been inherited by all arthropods. Arthropods are the most diverse and species-rich taxonomic group of animals and include insects, crustaceans, spiders and scorpions, as well as other, less familiar lineages such as millipedes and centipedes.

The fossils, belonging to an arthropod known as Leanchoilia, confirm the presence -- predicted by earlier studies in genetics and developmental biology of insect and spider embryos -- of an extreme frontal domain of the brain that is not segmented and is invisible in modern adult arthropods. Despite being invisible, this frontal domain gives rise to several crucial neural centers in the adult arthropod brain, including stem cells that eventually provide centers involved in decision-making and memory. This frontal domain was hypothesized to be distinct from the forebrain, midbrain and hindbrain seen in living arthropods, and it was given the name prosocerebrum ("proso" meaning "front").

Described in a recent paper in the journal Current Biology, the fossils provide the first evidence of the existence of this discrete prosocerebral brain region, which has a legacy that shows up during the embryonic development of modern arthropods, according to paper lead author Nicholas Strausfeld, a Regents Professor of Neuroscience at the University of Arizona. "The extraordinary fossils we describe are unlike anything that has been seen before," Strausfeld said. "Two nervous systems, already unique because they are identically preserved, show that half a billion years ago this most anterior brain region was present and structurally distinct before the evolutionary appearance of the three segmental ganglia that denote the fore-, mid- and hindbrain."

The term ganglion refers to a system of networks forming a nerve center that occurs in each segment of the nervous system of an arthropod. In living arthropods, the three ganglia that mark the three-part brain condensed together to form a solid mass, obscuring their evolutionary origin as segmented structures.

Using data from NASA’s Transiting Exoplanet Survey Satellite (TESS) and ground-based telescopes, astronomers have discovered five transiting companions near the hydrogen-burning mass limit in close orbits around main-sequence stars TOI-148, TOI-587, TOI-681, TOI-746, and TOI-1213.

Brown dwarfs are cool, dim objects that have masses in between gas giant planets, such as Jupiter or Saturn, and low-mass stars.

Sometimes called failed stars, these objects are too small to sustain hydrogen fusion reactions at their cores, yet they have star-like attributes. They are often defined with a lower limit of 13 Jupiter masses, the approximate mass at which an object can begin to ignite deuterium fusion in its core, and with an upper limit of 80 Jupiter masses, the approximate mass at which an object becomes sufficiently massive to fuse hydrogen nuclei into helium nuclei within its core (principal characteristic of a main-sequence star).

However, these boundaries are not clear-cut as the exact masses where deuterium and hydrogen fusion occur depend on the chemical composition of the object. A defining characteristic of brown dwarfs is their relative low occurrence rate (less than 1%) in close orbits (less than 5 AU) around main-sequence stars compared to giant planets and other stars, or the ‘brown dwarf desert.’

“We still do not know exactly where the mass limits of brown dwarfs lie, limits that allow them to be distinguished from low-mass stars that can burn hydrogen for many billions of years, whereas a brown dwarf will have a short burning stage and then a colder life,” said Dr. Nolan Grieves, an astronomer with the Observatoire de Genève at the Université de Genève. “These limits vary depending on the chemical composition of the brown dwarf, for example, or the way it formed, as well as its initial radius.”

In the new research, Dr. Grieves and colleagues discovered and characterized five transiting brown dwarf-like companions around five stars: TOI-148 (also known as UCAC4 260-199322), TOI-587 (HD 74162), TOI-681 (TYC 8911-00495-1), TOI-746 (TYC 9177-00082-1), and TOI-1213 (TYC 8970-00020-1).

These objects — TOI-148b, TOI-587b, TOI-681b, TOI-746b, and TOI-1213b — have orbital periods between 4.8 and 27.2 days, masses between 77 and 98 Jupiter masses, and radii between 0.81 and 1.66 Jupiter radii. Their masses are near the uncertain lower limit of hydrogen core fusion (73-96 Jupiter masses), which separates brown dwarfs and low-mass stars.

“Each new discovery reveals additional clues about the nature of brown dwarfs and gives us a better understanding of how they form and why they are so rare,” said Dr. Monika Lendl, also from the Observatoire de Genève at the Université de Genève.

Could the very timing of a mission help shield astronauts from dangerous radiation?

Sending human travelers to Mars would require scientists and engineers to overcome a range of technological and safety obstacles. One of them is the grave risk posed by particle radiation from the sun, distant stars and galaxies.

Answering two key questions would go a long way toward overcoming that hurdle: Would particle radiation pose too grave a threat to human life throughout a round trip to the red planet? And, could the very timing of a mission to Mars help shield astronauts and the spacecraft from the radiation?

In a recently article published in the peer-reviewed journal Space Weather, an international team of space scientists, including researchers from UCLA, answers those two questions with a “no” and a “yes.” That is, humans should be able to safely travel to and from Mars, provided that the spacecraft has sufficient shielding and the round trip is shorter than approximately four years. And the timing of a human mission to Mars would indeed make a difference: The scientists determined that the best time for a flight to leave Earth would be when solar activity is at its peak, known as the solar maximum.

The scientists' calculations demonstrate that it would be possible to shield a Mars-bound spacecraft from energetic particles from the sun because, during solar maximum, the most dangerous and energetic particles from distant galaxies are deflected by the enhanced solar activity. A trip of that length would be conceivable. The average flight to Mars takes about nine months, so depending on the timing of launch and available fuel, it is plausible that a human mission could reach the planet and return to Earth in less than two years, according to Yuri Shprits, a UCLA research geophysicist and co-author of the paper.

"This study shows that while space radiation imposes strict limitations on how heavy the spacecraft can be and the time of launch, and it presents technological difficulties for human missions to Mars, such a mission is viable," said Shprits, who also is head of space physics and space weather at GFZ Research Center for Geosciences in Potsdam, Germany.

The researchers recommend a mission not longer than four years because a longer journey would expose astronauts to a dangerously high amount of radiation during the round trip -- even assuming they went when it was relatively safer than at other times. They also report that the main danger to such a flight would be particles from outside of our solar system.

Shprits and colleagues from UCLA, MIT, Moscow's Skolkovo Institute of Science and Technology and GFZ Potsdam combined geophysical models of particle radiation for a solar cycle with models for how radiation would affect both human passengers -- including its varying effects on different bodily organs -- and a spacecraft. The modeling determined that having a spacecraft's shell built out of a relatively thick material could help protect astronauts from radiation, but that if the shielding is too thick, it could actually increase the amount of secondary radiation to which they are exposed.

The two main types of hazardous radiation in space are solar energetic particles and galactic cosmic rays; the intensity of each depends on solar activity. Galactic cosmic ray activity is lowest within the six to 12 months after the peak of solar activity, while solar energetic particles' intensity is greatest during solar maximum, Shprits said.

If authorized, the drug could be the first specialized oral drug that can prevent the worst of covid-19.

A pill that can effectively prevent the worst outcomes of covid-19 may finally be on the way. Just recently, pharmaceutical companies Merck and Ridgeback Biotherapeutics (FL) announced the preliminary results of a large trial testing out their experimental antiviral drug, called molnupiravir. The drug reportedly reduced the odds of later hospitalization or death by about 50% in high-risk individuals with mild to moderate illness—results so dramatically positive that the trial was stopped early. The companies now plan to seek an emergency use authorization for the drug, though the findings have yet to be vetted by outside scientists.

Molnupiravir is said to work by interfering with a virus’s ability to replicate inside a host’s cells, hopefully limiting viral load and enabling the immune system to clear the infection faster, without progressing to more severe illness. The drug had been in development prior to the pandemic as a potential treatment for the flu and other viral diseases. The Phase 3 randomized, double-blinded, and controlled trial of molnupiravir, called MOVe-OUT, was intended to involve around 1,500 unvaccinated patients who initially had mild to moderate covid-19 symptoms but were at higher risk of severe illness due to their preexisting health. As is commonplace, though, researchers conducted an interim analysis of the trial when only 775 patients had been treated. About 14% of those on placebo went on to become hospitalized or die within 30 days, compared to around 7% of those who took molnupiravir, No deaths at all were reported in the treatment group, compared to eight who died in the placebo group.

Clinical trials can be stopped early by an independent board of outside scientists because the treatment looks so unlikely to work that it would be unethical to continue. But they can also be stopped because the treatment appears so much better than standard care that it wouldn’t be right to keep enrolling participants to a control or placebo group. And that’s what the independent board agreed was the case here. The companies say that more than 90% of the trial had already been recruited by the time it was formally ended, though, so there will likely be more data to sift through.

“With the virus continuing to circulate widely, and because therapeutic options currently available are infused and/or require access to a healthcare facility, antiviral treatments that can be taken at home to keep people with COVID-19 out of the hospital are critically needed,” said Wendy Holman, CEO of Ridgeback Biotherapeutics, in a statement announcing the results.

Though molnupiravir has shown promise as a covid-19 treatment for some time now, there has been some controversy and failure surrounding it as well. Last year, federal official and eventual whistleblower Rick Bright alleged that the Trump administration retaliated against him for several decisions, including the reluctance by him and others to issue additional funding to the original founders of the drug at Emory University and later Ridgeback for their development of the drug, prior to and during the pandemic. Bright argued that the drug, while promising, was already getting enough resources, and he expressed concern that extra funding would subvert the normal process of research and development. He also noted that some animal studies had suggested that similar drugs could cause harmful mutations that could be passed onto to children.

In April 2021, Merck and Ridgeback Biotherapeutics also stopped one part of their MOVe-OUT trial, after it was determined that not enough evidence supported the use of molnupiravir for already hospitalized patients. In fairness, this has been a common pattern for many antivirals tested out during the pandemic and is at least partially due to the fact that severe illness from covid-19 tends to be caused by a destructive immune response, not the infection itself by that point. Moreover, studies of molnupiravir don’t seem to have found evidence of the harmful side effects Bright was concerned about, at least so far. Drugs suspected of causing mutagenic side effects have been approved in the past, usually with caveats against their use by currently pregnant or planning to be pregnant people.

Merck and Ridgeback are now planning to immediately submit the drug for emergency use authorization. Following that, the Food and Drug Administration and affiliated experts will be expected to pore over the safety and trial data and heavily discuss the drug’s potential risks and benefits. Should the drug win authorization, it may not be alone for long—several other antiviral pills for early covid-19 treatment and prevention are reaching the end of their clinical trials as well. The generic antidepressant fluvoxamine has also been shown to significantly prevent hospitalization from covid-19 in a large-scale but as yet not peer-reviewed trial.

Researchers from the Université de Montpellier, France, and the University of Pittsburgh, have published a study (“Mycobacteriophage-antibiotic therapy promotes enhanced clearance of drug-resistant Mycobacterium abscessus”) in Disease Models & Mechanisms that describes the antibacterial effects of treating infections caused by the antibiotic-resistant bacteria M. abscessus with a bacteriophage and an antibiotic.

“Infection by multidrug-resistant Mycobacterium abscessus is increasingly prevalent in cystic fibrosis (CF) patients, leaving clinicians with few therapeutic options. A compassionate study showed the clinical improvement of a CF patient with a disseminated M. abscessus (GD01) infection, following injection of a phage cocktail, including phage Muddy. Broadening the use of phage therapy in patients as a potential antibacterial alternative necessitates the development of biological models to improve the reliability and successful prediction of phage therapy in the clinic,” write the investigators.

“Herein, we demonstrate that Muddy very efficiently lyses GD01 in vitro, an effect substantially increased with standard drugs. Remarkably, this cooperative activity was retained in an M. abscessus model of infection in CFTR-depleted zebrafish, associated with a striking increase in larval survival and reduction in pathological signs. The activity of Muddy was lost in macrophage-ablated larvae, suggesting that successful phage therapy relies on functional innate immunity.

“CFTR-depleted zebrafish represent a practical model to rapidly assess phage treatment efficacy against M. abscessus isolates, allowing the identification of drug combinations accompanying phage therapy and treatment prediction in patients.”

Previously, the Pittsburgh team had identified one bacteriophage out of 10,000, known as “Muddy,” that efficiently kills bacteria in a petri dish and could be a candidate for treating these infections in humans. However, the team wanted to find an alternative to testing their new therapy in patients.

Knowing that human cystic fibrosis patients are particularly vulnerable to M. abscessus infections, Laurent Kremer, PhD, at the Université de Montpellier, and colleagues decided to test their new combination therapy on zebrafish carrying the key genetic mutation that causes cystic fibrosis in humans and mimics how our immune system responds to bacterial infections. Then the team obtained samples of an antibiotic-resistant form of M. abscessus from a cystic fibrosis patient to infect the cystic fibrosis zebrafish and test their new treatment.

First, they needed to find out how these cystic fibrosis zebrafish reacted to the M. abscessus infection. Monitoring the animals for 12 days, they found that the fish developed serious infections with abscesses and suffered a high death rate; only 20% survived.

Next the team tested how well the infected fish recovered when injected with Muddy, the antibacterial bacteriophage, over a period of 5 days. This time, the fish had much less severe infections, increased chances of survival (40%) and had fewer of the abscesses suffered by the fish during a severe infection.

Then the authors searched for an antibiotic to pair up with Muddy and found that rifabutin could treat the M. abscessus infection as effectively as the bacteriophage alone. After identifying rifabutin, Kremer and colleagues treated the infected fish for 5 days with the antibiotic and bacteriophage. With this combination treatment, the fishes’ infections were much less severe; the fishes’ survival rate reached 70% and they suffered far fewer abscesses. This is a significant improvement compared to fish treated with only the antibiotic, which had a 40% survival rate.

Extremophiles grown under a starlight simulator suggest that exoplanets orbiting red dwarf stars may have conditions ripe for photosynthesis, say researchers.

Our nearest astronomical neighbor is Proxima Centauri, a tiny red dwarf star some 4.25 light-years from here. In recent years, Proxima has become the focus of huge attention. In 2016, astronomers discovered it hosted an Earth-sized exoplanet in the habitable zone where conditions should be ripe for liquid water.

Then last year, astronomers spotted an unusual radio signal that appeared to be coming from that part of sky. The most likely source of the signal is radio interference on Earth but various astronomers have discussed the possibility that it could be a technosignature from a Proxima Centauri civilization.

All this excitement masks a much more basic and obvious question, which is whether a red dwarf could host life at all, given that the light it produces is much cooler, dimmer and redder than the light that supports life on Earth.

Now we get an answer of sorts thanks to the work of Riccardo Claudi at the Astronomical Observatory of Padova in Italy and colleagues who have recreated the red dwarf light spectrum and shown that bacteria can harvest it for photosynthesis. Their work suggests that, at least as far as the spectrum of light is concerned, red dwarfs have the capability to host photosynthetic life forms. In turn, this hints at the kind of biosignature these lifeforms might present to distant observers, such as ourselves.

A comparison of the medical histories of vaccinated and unvaccinated Israelis shows side effects from the Pfizer/BioNTech vaccine are rare and predominantly harmless.

Among 25 possible side effects explored in the study only four were more common among those that had been vaccinated than those that were not, and all remained uncommon. Meanwhile, infection raised the risk of far more serious conditions to a much greater extent. Myocarditis, inflammation of the heart muscle that can cause shortness of breath and irregular heartbeat, has been among the highest profile side effects of COVID-19 vaccination.

According to a new study in the New England Journal of Medicine of a substantial proportion of the Israeli population, it does occur at a higher rate among the vaccinated, but not by much. An extra 2.7 individuals in 100,000 were diagnosed with myocarditis compared to the unvaccinated population who hadn’t caught the disease. Most excess cases were among men aged 20 - 34. However, even if myocarditis was your only fear, it would still be advisable to get the vaccine anywhere COVID-19 is common. Among unvaccinated people who caught the disease the excess rate was 11 per 100,000 – four times as high.

The study found that easily the most common adverse event triggered by Pfizer vaccination is swelling of the lymph glands, which happens at an extra rate of 78 cases per 100,000. However, as a normal response to illness and something we will overcome many time in our lives, it's best not to risk death by virus in order to avoid. Likewise, the 16 additional cases per 100,000 of shingles (reactivation of past chickenpox virus infections) are unpleasant, but hardly life-threatening. The final and more serious side effect, appendicitis, occurs at just 5 excess cases per 100,000.

Meanwhile, a variety of other effects examined in the study were no more common among the vaccinated, but increased dramatically among unvaccinated people who caught COVID-19. These included kidney damage, pulmonary embolism, deep vein thrombosis and stroke with 125, 62, 43 and 14 excess cases per 100,000 respectively, along with several others. "These results show convincingly that this mRNA vaccine is very safe and that the alternative of 'natural' morbidity caused by the coronavirus puts a person at significant, higher and much more common risk of serious adverse events,” Professor Ran Balicer of the Clalit Research Institute said in a statement.

"To date, one of the main drivers of vaccine hesitancy has been a lack of information regarding potential side effects of the vaccine. This careful epidemiological study provides reliable information on vaccine safety, which we hope will be helpful to those who have not yet decided about vaccination,” added Harvard’s Dr Ben Reis.

If you open a biology textbook and run through the images depicting how DNA is organized in the cell's nucleus, chances are you'll start feeling hungry; the chains of DNA would seem like a bowl of ramen: long strings floating in liquid. However, according to two new studies—one experimental and the other theoretical—that are the outcome of the collaboration between the groups of Prof. Talila Volk of the Molecular Genetics Department and Prof. Sam Safran of the Chemical and Biological Physics Department at the Weizmann Institute of Science, this image should be reconsidered. Clarifying it is essential since DNA's spatial arrangement in the nucleus can affect the expression of genes contained within the DNA molecule, and hence the proteins found in the cell.

This story began when Volk was studying how mechanical forces influence cell nuclei in the muscle and found evidence that muscle contractions had an immediate effect on gene expression patterns. "We couldn't explore this further because existing methods relied on imaging of chemically preserved cells, so they failed to capture what happens in the cell nuclei of an actual working muscle," she says.

To address this issue, Dr. Dana Lorber, a research associate in Volk's group, led the design of a device that makes it possible to study muscle nuclei in live fruit fly larvae. The device holds the tiny, translucent larva within a groove that allows it to contract and relax its muscles but keeps its movement constrained so that it can be scanned by a fluorescence microscope. Using the device, the researchers obtained images of the internal, linearly-organized complexes of DNA and its proteins (known as chromatin), surrounded by the membrane of the muscle nuclei.

Expecting a bowl full of ramen, Lorber and Dr. Daria Amiad-Pavlov, a postdoctoral fellow in Volk's group, were in for a surprise. Rather than filling up the entire volume of the nucleus, the "noodles," or long chromatin molecules, were organized as a relatively thin layer, attached to its inner walls. Similar to the outcome of the interaction between oil and water, what is known as "phase separation," the chromatin separated itself from the bulk of the liquid inside of the nucleus and found its place at its outskirts, while most of the fluid medium remained at the center.

The researchers realized that they were on their way to addressing a fundamental biological question, that is—how is chromatin, and hence DNA, organized in the nucleus in a living organism. "But the findings were so unexpected, we had to make sure no error had crept in and that this organization was universal," Lorber says.

B-SOiD is an open source, unsupervised algorithm that can discover and identify behaviors without user input.

To Eric Yttri, assistant professor of biological sciences and Neuroscience Institute faculty at Carnegie Mellon University, the best way to understand the brain is to watch how organisms interact with the world. "Behavior drives everything we do," Yttri said. As a behavioral neuroscientist, Yttri studies what happens in the brain when animals walk, eat, sniff or do any action. This kind of research could help answer questions about neurological diseases or disorders like Parkinson's disease or stroke. But identifying and predicting animal behavior is extremely difficult.

Now, a new unsupervised machine learning algorithm developed by Yttri and Alex Hsu, a biological sciences Ph.D. candidate in his lab, makes studying behavior much easier and more accurate. The researchers published a paper on the new tool, B-SOiD (Behavioral segmentation of open field in DeepLabCut), in Nature Communications.

Previously, the standard method to capture animal behavior was to track very simple actions, like whether a trained mouse pressed a lever or whether an animal was eating food or not. Alternatively, the experimenter could spend hours and hours manually identifying behavior, usually frame by frame on a video, a process prone to human error and bias.

Hsu realized he could let an unsupervised learning algorithm do the time-consuming work. B-SOiD discovers behaviors by identifying patterns in the position of an animal's body. The algorithm works with computer vision software and can tell researchers what behavior is happening at every frame in a video. "It uses an equation to consistently determine when a behavior starts," Hsu explained. "Once you reach that threshold, the behavior is identified, every time. A human experimenter might toggle between two frames or several categories, try to decide where behavior begins and become fatigued over time."

Yttri said B-SOiD provides a huge improvement and opens up several avenues for new research. "It removes user bias and, more importantly, removes the time cost and arduous work," he said. "We can accurately process hours of data in a matter of minutes." Additionally, B-SOiD is very user friendly and openly available to any researcher. Yttri's lab and their collaborators have used the new algorithm in research on many important areas, including research to better understand chronic pain, obsessive compulsive disorder and more.

Collaborators have even begun to use B-SOiD to study human movement in Parkinson's disease. "We are beginning to see if this can be used as part of an objective test by a doctor to show how far a patient's disease has progressed. The hope is that a patient anywhere in the world would be diagnosed with one standardized metric," Yttri said. This is a breakthrough in how scientists can study natural behavior and how it changes rather than the overly simplistic or subjective measures that predominate neuroscience and ethology.

Scientists have long wondered why almost all animals sleep, despite the disadvantages to survival of being unconscious. Now, researchers led by a team from the University of Tsukuba have found new evidence of brain refreshing that takes place during a specific phase of sleep: rapid eye movement (REM) sleep, which is when you tend to dream a lot.

Previous studies have measured differences in blood flow in the brain between REM sleep, non-REM sleep, and wakefulness using various methods, with conflicting results. In their latest work, the Tsukuba-led team used a technique to directly visualize the movement of red blood cells in the brain capillaries (where nutrients and waste products are exchanged between brain cells and blood) of mice during awake and asleep states.

"We used a dye to make the brain blood vessels visible under fluorescent light, using a technique known as two-photon microscopy," says senior author of the study Professor Yu Hayashi. "In this way, we could directly observe the red blood cells in capillaries of the neocortex in non-anesthetized mice."

The researchers also measured electrical activity in the brain to identify REM sleep, non-REM sleep, and wakefulness, and looked for differences in blood flow between these phases. "We were surprised by the results," explains Professor Hayashi. "There was a massive flow of red blood cells through the brain capillaries during REM sleep, but no difference between non-REM sleep and the awake state, showing that REM sleep is a unique state"

The research team then disrupted the mice's sleep, resulting in "rebound" REM sleep -- a stronger form of REM sleep to compensate for the earlier disruption. Blood flow in the brain was further increased during rebound REM sleep, suggesting an association between blood flow and REM sleep strength. However, when the researchers repeated the same experiments in mice without adenosine A2a receptors (the receptors whose blockade makes you feel more awake after drinking coffee), there was less of an increase in blood flow during REM sleep, even during rebound REM sleep.

"These results suggest that adenosine A2a receptors may be responsible for at least some of the changes in blood flow in the brain during REM sleep," says Professor Hayashi. Given that reduced blood flow in the brain and decreased REM sleep are correlated with the development of Alzheimer's disease, which involves the buildup of waste products in the brain, it may be interesting to address whether increased blood flow in the brain capillaries during REM sleep is important for waste removal from the brain. This study lays preliminary groundwork for future investigations into the role of adenosine A2a receptors in this process, which could ultimately lead to the development of new treatments for conditions such as Alzheimer's disease.

Following four years of planning and research, the world's first 3D printed footbridge recently opened to the public in Europe.

The almost 40-foot bridge, unveiled last month, was built by Dutch company MX3D and will serve as a "living laboratory" in Amsterdam's city center.

Researchers and engineers at Imperial College London were able to 3D-print the bridge — which now serves pedestrians and cyclists crossing Amsterdam's Oudezijds Achterburgwal canal.

From Guns To Chocolate: The Possibilities Of 3-D Printing
"A 3D-printed metal structure large and strong enough to handle pedestrian traffic has never been constructed before," said Imperial College London professor Leroy Gardner in a news release.

A 12-meter 3D-printed pedestrian bridge designed by Joris Laarman and built by Dutch robotics company MX3D has been opened in Amsterdam six years after the project was launched.nAna Fernandez/SOPA Images/LightRocket via Gett Designers first created the concept for the bridge in 2015, with the goal of making an "exceptionally efficient structure," emphasizing both simplicity and safety, according to Popular Mechanics.

Ultrafast electron microscope opens up new avenues for the development of sensors and quantum devices. Everyone who has ever been to the Grand Canyon can relate to having strong feelings from being close to one of nature's edges. Similarly, scientists at the U.S. Department of Energy's (DOE) Argonne National Laboratory have discovered that nanoparticles of gold act unusually when close to the edge of a one-atom thick sheet of carbon, called graphene. This could have big implications for the development of new sensors and quantum devices.

This new discovery was made possible with a newly established ultrafast electron microscope (UEM) at Argonne's Center for Nanoscale Materials (CNM), a DOE Office of Science User Facility. The UEM enables the visualization and investigation of phenomena at the nanoscale and on time frames of less than a trillionth of a second. This discovery could make a splash in the growing field of plasmonics, which involves light striking a material surface and triggering waves of electrons, known as plasmonic fields.

"With these ultrafast capabilities, there is no telling what we might see as we tweak different materials and their properties." -- Haihua Liu, Argonne nanoscientist. For years, scientists have been pursuing development of plasmonic devices with a wide range of applications -- from quantum information processing to optoelectronics (which combine light-based and electronic components) to sensors for biological and medical purposes. To do so, they couple two-dimensional materials with atomic-level thickness, such as graphene, with nanosized metal particles. Understanding the combined plasmonic behavior of these two different types of materials requires understanding exactly how they are coupled.

In a recent study from Argonne, researchers used ultrafast electron microscopy to look directly at the coupling between gold nanoparticles and graphene. "Surface plasmons are light-induced electron oscillations on the surface of a nanoparticle or at an interface of a nanoparticle and another material," said Argonne nanoscientist Haihua Liu. "When we shine a light on the nanoparticle, it creates a short-lived plasmonic field. The pulsed electrons in our UEM interact with this short-lived field when the two overlap, and the electrons either gain or lose energy. Then, we collect those electrons that gain energy using an energy filter to map the plasmonic field distributions around the nanoparticle."

In studying the gold nanoparticles, Liu and his colleagues discovered an unusual phenomenon. When the nanoparticle sat on a flat sheet of graphene, the plasmonic field was symmetric. But when the nanoparticle was positioned close to a graphene edge, the plasmonic field concentrated much more strongly near the edge region. "It's a remarkable new way of thinking about how we can manipulate charge in the form of a plasmonic field and other phenomena using light at the nanoscale," Liu said. "With ultrafast capabilities, there's no telling what we might see as we tweak different materials and their properties."

One of the most important discoveries from the last two decades of planetary exploration has been the astrobiological potential of icy moons. Many of these moons harbor liquid-water reservoirs beneath their crusts, comprising a new class of solar system body: ocean worlds.

If biology requires carbon, water, and energy, then ocean worlds may offer the Solar System’s best chance for life beyond Earth.

Saturn’s hazy moon Titan is unique among ocean worlds in that carbon, water, and energy interact on the surface:

• complex, potentially tholin-like organic compounds cover most of the surface;
• crustal ice can be melted by impacts, and liquid water from the subsurface ocean may erupt in cryovolcanic flows;
• solar and chemical energy could power biochemistry.

Titan’s profusion of organic riches, especially when exposed to transient liquid water, has created potentially habitable environments, the remnants of which are available on the moon’s surface today.

“Titan represents an explorer’s utopia,” said Dragonfly co-investigator Dr. Alex Hayes, a researcher in the Department of Astronomy at Cornell University. “The science questions we have for Titan are very broad because we don’t know much about what is actually going on at the surface yet. For every question we answered during NASA’s Cassini mission’s exploration of Titan from Saturn orbit, we gained 10 new ones.”

Though Cassini has been orbiting Saturn for 13 years, the thick methane atmosphere on Titan made it impossible to reliably identify the materials on its surface. While Cassini’s radar enabled scientists to penetrate the atmosphere and identify Earth-like morphologic structures, including dunes, lakes and mountains, the data could not reveal their composition. “In fact, at the time Cassini was launched we didn’t even know if the surface of Titan was a global liquid ocean of methane and ethane, or a solid surface of water ice and solid organics,” Dr. Hayes said.