Scientist Study

A top goal in cosmology is to precisely measure the total amount of matter in the universe, a daunting exercise for even the most mathematically proficient. A team led by scientists at the University of California, Riverside, has now done just that.



Reporting in the Astrophysical Journal, the team determined that matter makes up 31% of the total amount of matter and energy in the universe, with the remainder consisting of dark energy.

"To put that amount of matter in context, if all the matter in the universe were spread out evenly across space, it would correspond to an average mass density equal to only about six hydrogen atoms per cubic meter," said first author Mohamed Abdullah, a graduate student in the UCR Department of Physics and Astronomy. "However, since we know 80% of matter is actually dark matter, in reality, most of this matter consists not of hydrogen atoms but rather of a type of matter which cosmologists don't yet understand."

Abdullah explained that one well-proven technique for determining the total amount of matter in the universe is to compare the observed number and mass of galaxy clusters per unit volume with predictions from numerical simulations. Because present-day galaxy clusters have formed from matter that has collapsed over billions of years under its own gravity, the number of clusters observed at the present time is very sensitive to cosmological conditions and, in particular, the total amount of matter.

Like Goldilocks, the team compared the number of galaxy clusters they measured with predictions from numerical simulations to determine which answer was "just right." Credit: Mohamed Abdullah, UC Riverside.

"A higher percentage of matter would result in more clusters," Abdullah said. "The 'Goldilocks' challenge for our team was to measure the number of clusters and then determine which answer was 'just right.' But it is difficult to measure the mass of any galaxy cluster accurately because most of the matter is dark so we can't see it with telescopes."

To overcome this difficulty, the UCR-led team of astronomers first developed "GalWeight", a cosmological tool to measure the mass of a galaxy cluster using the orbits of its member galaxies. The researchers then applied their tool to observations from the Sloan Digital Sky Survey (SDSS) to create "GalWCat19," a publicly available catalog of galaxy clusters. Finally, they compared the number of clusters in their new catalog with simulations to determine the total amount of matter in the universe.

"We have succeeded in making one of the most precise measurements ever made using the galaxy cluster technique," said coauthor Gillian Wilson, a professor of physics and astronomy at UCR in whose lab Abdullah works. "Moreover, this is the first use of the galaxy orbit technique which has obtained a value in agreement with those obtained by teams who used noncluster techniques such as cosmic microwave background anisotropies, baryon acoustic oscillations, Type Ia supernovae, or gravitational lensing."

"A huge advantage of using our GalWeight galaxy orbit technique was that our team was able to determine a mass for each cluster individually rather than rely on more indirect, statistical methods," said the third coauthor Anatoly Klypin, an expert in numerical simulations and cosmology.

By combining their measurement with those from the other teams that used different techniques, the UCR-led team was able to determine a best combined value, concluding that matter makes up 31.5±1.3% of the total amount of matter and energy in the universe.

The research paper is titled "Cosmological Constraints on Ωm and σ8 from Cluster Abundances using the GalWCat19 Optical-spectroscopic SDSS Catalog."

More information: 

Mohamed H. Abdullah et al, Cosmological Constraints on Ω m and σ 8 from Cluster Abundances Using the GalWCat19 Optical-spectroscopic SDSS Catalog, The Astrophysical Journal (2020). DOI: 10.3847/1538-4357/aba619

A new species of freshwater Crustacea has been discovered during an expedition of the desert Lut, known as the hottest place on Earth.

The newly identified species belongs to the genus Phallocryptus of which only four species were previously known from different arid and semiarid regions.



Dr Hossein Rajaei from the Stuttgart State Museum of Natural History and Dr Alexander V Rudov from Tehran University made the discovery during an expedition of Lut to better understand the desert’s ecology, biodiversity, geomorphology and paleontology.

Further scientific examinations of the specimens by co-author Dr Martin Schwentner, Crustacea specialist from the Natural History Museum of Vienna, stated that they belong to a new species of freshwater Crustacea.

Publishing their findings in Zoology in the Middle East, the biologists name the new species Phallocryptus fahimii, in honor of the Iranian conservation biologist, Hadi Fahimi, who took part in the 2017 expedition and sadly died in an airplane crash in 2018.

Dr Rajaei, an entomologist from State Museum of Natural History Stuttgart, who actually found the species in a small seasonal lake in southern part of the desert says the discovery is “sensational”.

“During an expedition to such an extreme place you are always on alert, in particular when finding water. Discovering crustaceans in this otherwise hot and dry environment was really sensational.”

The team’s study explains how Phallocryptus fahimii differs in its overall morphology and its genetics from all other known Phallocryptus species.

Dr Schwentner, who has worked with similar crustaceans from the Australian deserts in the past, adds: “These Crustaceans are able to survive for decades in the dried-out sediment and will hatch in an upcoming wet season, when the aquatic habitat refills. They are perfectly adapted to live in deserts environments. Their ability to survive even in the Lut desert highlights their resilience.”

The Lut desert – also known as Dasht-e Lut – is the second largest desert in Iran.

Located between 33° and 28° parallels and with its 51,800 km2 larger than Switzerland, this desert holds the current record for the highest ever-recorded surface temperature. Based on 2006 satellite measurements, the NASA reported a record surface temperature of 70.7°C, which more recently has been increased to even 80.3°C. Dark pebbles that heat up are one of the causes of these record temperatures. Mean daily temperatures range from -2.6°C in winter to 50.4°C in summer with annual precipitation not exceeding 30 mm per year.

Almost deprived of vegetation, the Lut desert harbors a diverse animal life, but no permanent aquatic biotops (such as ponds).

After rain falls, non-permanent astatic water bodies are filled including the Rud-e-Shur river from north-western Lut.

Here a diverse community of Archaea has been described but aquatic life in the Lut remains highly limited, which makes this find particularly rare.

Reference:

Martin Schwentner, Alexander V. Rudov, Hossein Rajaei. Some like it hot: Phallocryptus fahimii sp. n. (Crustacea: Anostraca: Thamnocephalidae) from the Lut desert, the hottest place on Earth. Zoology in the Middle East, 2020; 1
DOI: 10.1080/09397140.2020.1805139

Physicist Reinhold Bertlmann of the University of Vienna, Austria has published a review of the work of his late long-term collaborator John Stewart Bell of CERN, Geneva in EPJ H. This review, 'Real or Not Real: that is the question', explores Bell's inequalities and his concepts of reality and explains their relevance to quantum information and its applications.



John Stewart Bell's eponymous theorem and inequalities set out, mathematically, the contrast between quantum mechanical theories and local realism. They are used in quantum information, which has evolving applications in security, cryptography and quantum computing.

The distinguished quantum physicist John Stewart Bell (1928-1990) is best known for the eponymous theorem that proved current understanding of quantum mechanics to be incompatible with local hidden variable theories. Thirty years after his death, his long-standing collaborator Reinhold Bertlmann of the University of Vienna, Austria, has reviewed his thinking in a paper for EPJ H, 'Real or Not Real: That is the question'. In this historical and personal account, Bertlmann aims to introduce his readers to Bell's concepts of reality and contrast them with some of his own ideas of virtuality.

Bell spent most of his working life at CERN in Geneva, Switzerland, and Bertlmann first met him when he took up a short-term fellowship there in 1978. Bell had first presented his theorem in a seminal paper published in 1964, but this was largely neglected until the 1980s and the introduction of quantum information.

Bertlmann discusses the concept of Bell inequalities, which arise through thought experiments in which a pair of spin-½ particles propagate in opposite directions and are measured by independent observers, Alice and Bob. The Bell inequality distinguishes between local realism -- the 'common sense' view in which Alice's observations do not depend on Bob's, and vice versa -- and quantum mechanics, or, specifically, quantum entanglement. Two quantum particles, such as those in the Alice-Bob situation, are entangled when the state measured by one observer instantaneously influences that of the other. This theory is the basis of quantum information.

And quantum information is no longer just an abstruse theory. It is finding applications in fields as diverse as security protocols, cryptography and quantum computing. "Bell's scientific legacy can be seen in these, as well as in his contributions to quantum field theory," concludes Bertlmann. "And he will also be remembered for his critical thought, honesty, modesty and support for the underprivileged."

Reference:

Reinhold A. Bertlmann. Real or not real that is the question... The European Physical Journal H, 2020; DOI: 10.1140/epjh/e2020-10022-x

People infected by the novel coronavirus can have symptoms that range from mild to deadly. Now, two new analyses suggest that some life-threatening cases can be traced to weak spots in patients' immune systems.

At least 3.5 percent of study patients with severe COVID-19, the disease caused by the novel coronavirus, have mutations in genes involved in antiviral defense. And at least 10 percent of patients with severe disease create "auto-antibodies" that attack the immune system, instead of fighting the virus. The results, reported in two papers in the journal Science on September 24, 2020, identify some root causes of life-threatening COVID-19, says study leader Jean-Laurent Casanova, a Howard Hughes Medical Institute Investigator at The Rockefeller University.



Seeing these harmful antibodies in so many patients -- 101 out of 987 -- was "a stunning observation," he says. "These two papers provide the first explanation for why COVID-19 can be so severe in some people, while most others infected by the same virus are okay."

The work has immediate implications for diagnostics and treatment, Casanova says. If someone tests positive for the virus, they should "absolutely" be tested for the auto-antibodies, too, he adds, "with medical follow-up if those tests are positive." It's possible that removing such antibodies from the blood could ease symptoms of the disease.

A global effort

Casanova's team, in collaboration with clinicians around the world, first began enrolling COVID-19 patients in their study in February. At the time, they were seeking young people with severe forms of the disease to investigate whether these patients might have underlying weaknesses in their immune systems that made them especially vulnerable to the virus.

The plan was to scan patients' genomes -- in particular, a set of 13 genes involved in interferon immunity against influenza. In healthy people, interferon molecules act as the body's security system. They detect invading viruses and bacteria and sound the alarm, which brings other immune defenders to the scene.

Casanova's team has previously discovered genetic mutations that hinder interferon production and function. People with these mutations are more vulnerable to certain pathogens, including those that cause influenza. Finding similar mutations in people with COVID-19, the team thought, could help doctors identify patients at risk of developing severe forms of the disease. It could also point to new directions for treatment, he says.

In March, Casanova's team was aiming to enroll 500 patients with severe COVID-19 worldwide in their study. By August, they had more than 1,500, and they now have over 3,000. As the researchers began analyzing patient samples, they started to uncover harmful mutations, in people young and old. The team found that 23 out of 659 patients studied carried errors in genes involved in producing antiviral interferons.

Without a full complement of these antiviral defenders, COVID-19 patients wouldn't be able to fend off the virus, the researchers suspected. That thought sparked a new idea. Maybe other patients with severe COVID-19 also lacked interferons -- but for a different reason. Maybe some patients' bodies were harming these molecules themselves. As in autoimmune disorders such as type 1 diabetes and rheumatoid arthritis, some patients might be making antibodies that target the body. "That was the eureka moment for us," Casanova says.



The team's analysis of 987 patients with life-threatening COVID-19 revealed just that. At least 101 of the patients had auto-antibodies against an assortment of interferon proteins. "We said, 'bingo'!" Casanova remembers. These antibodies blocked interferon action and were not present in patients with mild COVID-19 cases, the researchers discovered.

"It's an unprecedented finding," says study co-author Isabelle Meyts, a pediatrician at the University Hospitals KU Leuven, in Belgium, who earlier this year helped enroll patients in the study, gather samples, and perform experiments. By testing for the presence of these antibodies, she says, "you can almost predict who will become severely ill."

The vast majority -- 94 percent -- of patients with the harmful antibodies were men, the team found. Men are more likely to develop severe forms of COVID-19, and this work offers one explanation for that gender variability, Meyts says.

Casanova's lab is now looking for the genetic driver behind those auto-antibodies. They could be linked to mutations on the X chromosome, he says. Such mutations might not affect women, because they have a second X chromosome to compensate for any defects in the first. But for men, who carry only a single X, even small genetic errors can be consequential.

Looking ahead Clinically, the team's new work could change how doctors and health officials think about vaccination distribution strategies, and even potential treatments. A clinical trial could examine, for instance, whether infected people who have the auto-antibodies benefit from treatment with one of the 17 interferons not neutralized by the auto-antibodies, or with plasmapheresis, a medical procedure that strips the antibodies from patients' blood. Either method could potentially counteract the effect of these harmful antibodies, Meyts says.

In addition to the current work, Meyts, Casanova, and hundreds of other scientists involved with an international consortium called the COVID Human Genetic Effort are working to understand a second piece of the coronavirus puzzle. Instead of hunting for factors that make patients especially vulnerable to COVID-19, they're looking for the opposite -- genetic factors that might be protective. They're now recruiting people from the households of patients with severe COVID-19 -- people who were exposed to the virus but did not develop the disease. "Our lab is currently running at full speed," Casanova says.

References:

Paul Bastard et al. Auto-antibodies against type I IFNs in patients with life-threatening COVID-19. Science, Sept. 24, 2010; DOI: 10.1126/science.abd4585

Qian Zhang et al. Inborn errors of type I IFN immunity in patients with life-threatening COVID-19. Science, Sept. 24, 2020; DOI: 10.1126/science.abd4570

Salt crystals can grow tiny legs to lift themselves away from certain hydrophobic surfaces, chemists from the Netherlands were surprised to find. This self-lifting behaviour could have implications for designing building materials that avoid damaging salt crystal growth.



White salt residues are often seen on brick or concrete structures. This efflorescence is caused by salty water migrating to the porous materials’ surface, where the water evaporates, leaving the salt behind. The process is unsightly at best and destructive at worst. Anti-efflorescence surface treatments, for example, can prevent salt escaping the stone, making it crystallise internally instead.

Although sodium chloride is the most common salt on Earth, little is known about how surface treatments affect its crystallisation dynamics. A team around Noushine Shahidzadeh from the University of Amsterdam has for the first time observed how salt crystals grow legs to avoid silanised surfaces.

The researchers placed salt water droplets on a heated, trichlorooctylsilane-treated glass slide. As the water evaporates, crystallites form at the water–air interface, sitting on their corners to minimise contact with the surface. As the evaporation proceeds, a number of tiny crystalline legs grow on the bottom of the structure, which lifts the entire crystal off the surface. At higher temperatures, more legs grow – and faster.

Time sequence of an aqueous sodium chloride droplet evaporating on a silanised surface that result in ‘legs’ that lift the crystal

Only on silanised glass, but not on other hydrophobic materials, did sodium chloride show this lift-off behaviour. Shahidzadeh and her team argue that this is because silanised glass is microscopically smooth unlike other silanised superamphiphobic coatings. Moreover, silanes block surface hydroxyl groups so they can’t act as water adsorbing sites, preventing salt nucleation where it usually happens at the water–solid interface.

Sodium chloride’s self-lifting crystallisation makes the silanised surface essentially self-cleaning. This could help scientists design coatings that prevent efflorescence on building materials without risking damage from internal crystallisation.

Reference:

Self-Lifting NaCl Crystals
Herish Salim, Paul Kolpakov, Daniel Bonn, and Noushine Shahidzade
J. Phys. Chem. Lett. 2020, 11, 17, 7388–7393
https://doi.org/10.1021/acs.jpclett.0c01871

By measuring brain signals, a neuroscience research group at the University of Tübingen has demonstrated for the first time that corvid songbirds possess subjective experiences. Simultaneously recording behavior and brain activity enabled the group headed by Professor Andreas Nieder to show that crows are capable of consciously perceiving sensory input. Until now this type of consciousness has only been witnessed in humans and other primates, which have completely different brain structures to birds. "The results of our study opens up a new way of looking at the evolution of awareness and its neurobiological constraints," says Nieder. The study has been published in the journal Science on September 24, 2020.



For humans and our nearest relatives in the animal kingdom, the nonhuman primates, our ability to perceive things consciously is localized in the cerebral cortex. Over many years research has discussed whether animals with brains that are structured completely differently, without a cerebral cortex, are also endowed with conscious perception. Until now however there has been no experimental neurological data to support such a claim.

In order to track conscious processes in birds, the Tübingen scientists trained two crows: they had to signal whether they had seen a stimulus on a screen by moving their heads. Most of the stimuli were perceptually unambiguous: different trials presented either bright figures or no stimulus at all, and the crows reliably signaled the presence or absence of these stimuli, respectively. However, some stimuli were so faint that they were at the threshold of perception: for the same faint stimulus, the crows sometimes indicated that they had seen it, whereas in other cases they reported that there was no stimulus. Here, the subjective perception of the crows came into play.

While the crows responded to the visual stimuli, the researchers simultaneously recorded the activity of individual nerve cells in the brain. When the crows reported having seen something, the nerve cells were active in the period between presentation of the stimulus and the behavioral response. If they did not perceive a stimulus, the nerve cells remained silent. Surprisingly, it was possible to predict the subjective experience of the crows with regard to the stimulus based on the activity of the nerve cells. "Nerve cells that represent visual input without subjective components are expected to respond in the same way to a visual stimulus of constant intensity," explains Nieder, "Our results, however, conclusively show that nerve cells at higher processing levels of the crow's brain are influenced by subjective experience, or more precisely, produce subjective experiences."

This means that in terms of evolutionary history the origins of consciousness could be far older and more widespread in the animal kingdom than previously thought. "The last common ancestors of humans and crows lived 320 million years ago," says Nieder. "It is possible that the consciousness of perception arose back then and has been passed down ever since." An alternative scenario is that the consciousness of perception developed entirely independently in these distantly related species, explains the neurobiologist, "In any case, the capability of conscious experience can be realized in differently structured brains and independently of the cerebral cortex."

Reference:

A neural correlate of sensory consciousness in a corvid bird.
Science  25 Sep 2020: Vol. 369, Issue 6511, pp. 1626-1629
DOI: 10.1126/science.abb1447

New findings by scientists at the National Institutes of Health and their collaborators help explain why some people with COVID-19 develop severe disease. The findings also may provide the first molecular explanation for why more men than women die from COVID-19.



The researchers found that more than 10% of people who develop severe COVID-19 have misguided antibodies―autoantibodies―that attack the immune system rather than the virus that causes the disease. Another 3.5% or more of people who develop severe COVID-19 carry a specific kind of genetic mutation that impacts immunity. Consequently, both groups lack effective immune responses that depend on type I interferon, a set of 17 proteins crucial for protecting cells and the body from viruses. Whether these proteins have been neutralized by autoantibodies or―because of a faulty gene―were produced in insufficient amounts or induced an inadequate antiviral response, their absence appears to be a commonality among a subgroup of people who suffer from life-threatening COVID-19 pneumonia.

These findings are the first published results from the COVID Human Genetic Effort, an international project spanning more than 50 genetic sequencing hubs and hundreds of hospitals. The effort is co-led by Helen Su, M.D., Ph.D., a senior investigator at the National Institute of Allergy and Infectious Diseases (NIAID), part of NIH; and Jean-Laurent Casanova, M.D., Ph.D., head of the St. Giles Laboratory of Human Genetics of Infectious Diseases at The Rockefeller University in New York. Major contributions were made by Luigi Notarangelo, M.D., chief of the NIAID Laboratory of Clinical Immunology and Microbiology (LCIM); Steven Holland, M.D., director of the NIAID Division of Intramural Research and senior investigator in the NIAID LCIM; clinicians and investigators in hospitals in the Italian cities of Brescia, Monza and Pavia, which were heavily hit by COVID-19; and researchers at the Uniformed Services University of the Health Sciences in Bethesda, Maryland.

The wide variation in the severity of disease caused by SARS-CoV-2, the virus behind COVID-19, has puzzled scientists and clinicians. SARS-CoV-2 can cause anything from a symptom-free infection to death, with many different outcomes in between. Since February 2020, Drs. Su and Casanova and their collaborators have enrolled thousands of COVID-19 patients to find out whether a genetic factor drives these disparate clinical outcomes.

The researchers discovered that among nearly 660 people with severe COVID-19, a significant number carried rare genetic variants in 13 genes known to be critical in the body’s defense against influenza virus, and more than 3.5% were completely missing a functioning gene. Further experiments showed that immune cells from those 3.5% did not produce any detectable type I interferons in response to SARS-CoV-2.

Examining nearly 1,000 patients with life-threatening COVID-19 pneumonia, the researchers also found that more than 10% had autoantibodies against interferons at the onset of their infection, and 95% of those patients were men. Biochemical experiments confirmed that the autoantibodies block the activity of interferon type I.

Reference: 

Zhang Q, Bastard P, Liu Z, et al. Inborn errors of type I IFN immunity in patients with life-threatening COVID-19. Science. 2020;eabd4570. doi: 10.1126/science.abd4570.

Quantum computers are the new frontier in advanced research technology, with potential applications such as performing critical calculations, protecting financial assets, or predicting molecular behavior in pharmaceuticals. Researchers from Osaka City University have now solved a major problem hindering large-scale quantum computers from practical use: precise and accurate predictions of atomic and molecular behavior.



They published their method to remove extraneous information from quantum chemical calculations on Sept. 17 as an advanced online article in Physical Chemistry Chemical Physics, a journal of the Royal Society of Chemistry.

"One of the most anticipated applications of quantum computers is electronic structure simulations of atoms and molecules," said paper authors Kenji Sugisaki, Lecturer and Takeji Takui, Professor Emeritus in the Department of Chemistry and Molecular Materials Science in Osaka City University's Graduate School of Science.

Quantum chemical calculations are ubiquitous across scientific disciplines, including pharmaceutical therapy development and materials research. All of the calculations are based on solving physicist Erwin Schrödinger's equation, which uses electronic and molecular interactions that result in a particular property to describe the state of a quantum-mechanical system.

"Schrödinger equations govern any behavior of electrons in molecules, including all chemical properties of molecules and materials, including chemical reactions," Sugisaki and Takui said.

On classical computers, such precise equations would take exponential time. On quantum computers, this precision is possible in realistic time, but it requires "cleaning" during the calculations to obtain the true nature of the system, according to them.

A quantum system at a specific moment in time, known as a wave function, has a property described as spin, which is the total of the spin of each electron in the system. Due to hardware faults or mathematical errors, there may be incorrect spins informing the system's spin calculation. To remove these 'spin contaminants,' the researchers implemented an algorithm that allows them to select the desired spin quantum number. This purifies the spin, removing contaminants during each calculation—a first on quantum computers, according to them.

"Quantum chemical calculations based on exactly solving Schrödinger equations for any behavior of atoms and molecules can afford predictions of their physical-chemical properties and complete interpretations on chemical reactions and processes," they said, noting that this is not possible with currently available classical computers and algorithms. "The present paper has given a solution by implementing a quantum algorithm on quantum computers."

The researchers next plan to develop and implement algorithms designed to determine the state of electrons in molecules with the same accuracy for both excited- or ground-state electrons.

More information: 

Kenji Sugisaki et al, A probabilistic spin annihilation method for quantum chemical calculations on quantum computers, Physical Chemistry Chemical Physics (2020). DOI: 10.1039/d0cp03745a