Genes could be key to new COVID-19 treatments, study finds

 Potential treatments for Covid-19 have been identified after the discovery of five genes associated with the most severe form of the disease.

Genetic evidence is second only to clinical trials as a way to tell which treatments will be effective in a disease. Existing drugs that target the actions of the genes reveal which drugs should be repurposed to treat Covid-19 in clinical trials, experts say.

Genes involved in two molecular processes -- antiviral immunity and lung inflammation -- were pinpointed. The breakthrough will help doctors understand how Covid-19 damages lungs at a molecular level.

Researchers from the University of Edinburgh made the discovery by studying the DNA of 2,700 patients in 208 intensive care units (ICUs) in the UK.

Researchers from the GenOMICC consortium -- a global collaboration to study genetics in critical illness -- compared the genetic information of Covid-19 patients in ICU with samples provided by healthy volunteers from other studies, such as UK Biobank, Generation Scotland and 100,000 Genomes.

The team found key differences in five genes of the ICU patients compared with samples provided by healthy volunteers. The genes -- IFNAR2, TYK2, OAS1, DPP9 and CCR2 -- partially explain why some people become desperately sick with Covid-19, while others are not affected.

Having highlighted the genes, the team were then able to predict the effect of drug treatments on patients, because some genetic variants respond in a similar way to particular drugs.

For example, they showed that a reduction in the activity of the TYK2 gene protects against Covid-19. A class of anti-inflammatory drugs called JAK inhibitors, which includes the drug baricitinib, produces this effect.

They also discovered that a boost in the activity of the gene INFAR2 is also likely to create protection, because it is likely to mimic the effect of treatment with interferon -- proteins released by cells of the immune system to defend against viruses. However, experts caution that to be effective, patients might need the treatment early in disease.

Based on the findings published in Nature, the researchers say that clinical trials should focus on drugs that target these specific antiviral and anti-inflammatory pathways.

Dr Kenneth Baillie, the project's chief investigator and Academic Consultant in Critical Care Medicine and Senior Research Fellow at University of Edinburgh's Roslin Institute, said: "This is a stunning realisation of the promise of human genetics to help understand critical illness. Just like in sepsis and influenza, in Covid-19, damage to the lungs is caused by our own immune system, rather than the virus itself. Our genetic results provide a roadmap through the complexity of immune signals, showing the route to key drug targets.

"Our results immediately highlight which drugs should be at the top of the list for clinical testing. We can only test a few drugs at a time, so making the right choices will save thousands of lives.

"This work is only possible because of the generous contribution of the patients themselves and their families, research teams in NHS hospitals across the country, and the generous funding we've received from the public and organisations."

GenOMICC (Genetics of Susceptibility and Mortality in Critical Care) started in 2015 as an open, global consortium of intensive care clinicians dedicated to understanding genetic factors that influence outcomes in intensive care from diseases such as SARS, influenza and sepsis. Throughout 2020 it has been focused on Covid-19 research in partnership with Genomics England.

This study is one of a number of COVID-19 studies that have been given urgent public health research status by the Chief Medical Officer and Deputy Chief Medical Officer for England.

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New type of atomic clock keeps time even more precisely

 

Clock and abstract background.

Atomic clocks are the most precise timekeepers in the world. These exquisite instruments use lasers to measure the vibrations of atoms, which oscillate at a constant frequency, like many microscopic pendulums swinging in sync. The best atomic clocks in the world keep time with such precision that, if they had been running since the beginning of the universe, they would only be off by about half a second today.

Still, they could be even more precise. If atomic clocks could more accurately measure atomic vibrations, they would be sensitive enough to detect phenomena such as dark matter and gravitational waves. With better atomic clocks, scientists could also start to answer some mind-bending questions, such as what effect gravity might have on the passage of time and whether time itself changes as the universe ages.

Now a new kind of atomic clock designed by MIT physicists may enable scientists explore such questions and possibly reveal new physics.

The researchers report in the journal Nature that they have built an atomic clock that measures not a cloud of randomly oscillating atoms, as state-of-the-art designs measure now, but instead atoms that have been quantumly entangled. The atoms are correlated in a way that is impossible according to the laws of classical physics, and that allows the scientists to measure the atoms' vibrations more accurately.

The new setup can achieve the same precision four times faster than clocks without entanglement.

"Entanglement-enhanced optical atomic clocks will have the potential to reach a better precision in one second than current state-of-the-art optical clocks," says lead author Edwin Pedrozo-Peñafiel, a postdoc in MIT's Research Laboratory of Electronics.

If state-of-the-art atomic clocks were adapted to measure entangled atoms the way the MIT team's setup does, their timing would improve such that, over the entire age of the universe, the clocks would be less than 100 milliseconds off.

The paper's other co-authors from MIT are Simone Colombo, Chi Shu, Albert Adiyatullin, Zeyang Li, Enrique Mendez, Boris Braverman, Akio Kawasaki, Saisuke Akamatsu, Yanhong Xiao, and Vladan Vuletic, the Lester Wolfe Professor of Physics.

Time limit

Since humans began tracking the passage of time, they have done so using periodic phenomena, such as the motion of the sun across the sky. Today, vibrations in atoms are the most stable periodic events that scientists can observe. Furthermore, one cesium atom will oscillate at exactly the same frequency as another cesium atom.

To keep perfect time, clocks would ideally track the oscillations of a single atom. But at that scale, an atom is so small that it behaves according to the mysterious rules of quantum mechanics: When measured, it behaves like a flipped coin that only when averaged over many flips gives the correct probabilities. This limitation is what physicists refer to as the Standard Quantum Limit.

"When you increase the number of atoms, the average given by all these atoms goes toward something that gives the correct value," says Colombo.

This is why today's atomic clocks are designed to measure a gas composed of thousands of the same type of atom, in order to get an estimate of their average oscillations. A typical atomic clock does this by first using a system of lasers to corral a gas of ultracooled atoms into a trap formed by a laser. A second, very stable laser, with a frequency close to that of the atoms' vibrations, is sent to probe the atomic oscillation and thereby keep track of time.

And yet, the Standard Quantum Limit is still at work, meaning there is still some uncertainty, even among thousands of atoms, regarding their exact individual frequencies. This is where Vuletic and his group have shown that quantum entanglement may help. In general, quantum entanglement describes a nonclassical physical state, in which atoms in a group show correlated measurement results, even though each individual atom behaves like the random toss of a coin.

The team reasoned that if atoms are entangled, their individual oscillations would tighten up around a common frequency, with less deviation than if they were not entangled. The average oscillations that an atomic clock would measure, therefore, would have a precision beyond the Standard Quantum Limit.

Entangled clocks

In their new atomic clock, Vuletic and his colleagues entangle around 350 atoms of ytterbium, which oscillates at the same very high frequency as visible light, meaning any one atom vibrates 100,000 times more often in one second than cesium. If ytterbium's oscillations can be tracked precisely, scientists can use the atoms to distinguish ever smaller intervals of time.

The group used standard techniques to cool the atoms and trap them in an optical cavity formed by two mirrors. They then sent a laser through the optical cavity, where it ping-ponged between the mirrors, interacting with the atoms thousands of times.

"It's like the light serves as a communication link between atoms," Shu explains. "The first atom that sees this light will modify the light slightly, and that light also modifies the second atom, and the third atom, and through many cycles, the atoms collectively know each other and start behaving similarly."

In this way, the researchers quantumly entangle the atoms, and then use another laser, similar to existing atomic clocks, to measure their average frequency. When the team ran a similar experiment without entangling atoms, they found that the atomic clock with entangled atoms reached a desired precision four times faster.

"You can always make the clock more accurate by measuring longer," Vuletic says. "The question is, how long do you need to reach a certain precision. Many phenomena need to be measured on fast timescales."

He says if today's state-of-the-art atomic clocks can be adapted to measure quantumly entangled atoms, they would not only keep better time, but they could help decipher signals in the universe such as dark matter and gravitational waves, and start to answer some age-old questions.

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Device mimics life's first steps in outer space

 A device developed by scientists at the CY Cergy Paris University and Paris Observatory promises insight into how the building blocks of life form in outer space.

In an article published in Review of Scientific Instruments, by AIP Publishing, the scientists detail how VENUS -- an acronym of the French phrase "Vers de Nouvelles Syntheses," which means "toward new syntheses" -- mimics how molecules come together in the freezing darkness of interstellar space.

"We try to simulate how complex organic molecules are formed in such a harsh environment," said Emanuele Congiu, one of the authors and an astrophysicist at the observatory. "Observatories can see a lot of molecules in space. What we do not understand yet, or fully, is how they formed in this harsh environment."

VENUS has a chamber designed to replicate the strong vacuum of space, while holding a frigid temperature that is set lower than minus 400 degrees Fahrenheit (10 kelvins). It uses up to five beams to deliver atoms or molecules onto a tiny sliver of ice without disturbing that environment.

That process, Congiu said, replicates how molecules form on the ice that sits atop tiny dust particles found inside interstellar clouds. VENUS is the first device to do the replication with more than three beams, which lets researchers simulate more complicated interactions.

Over the past 50 years, nearly 200 different molecular species have been discovered in the star-forming regions of space. Some of them, the so-called "prebiotic species," are believed by scientists to be involved in the processes that lead to the early forms of life.

A key use of the VENUS device will be working in concert with scientists who discover molecular reactions in space but need a fuller understanding of what they have observed. It specifically mentions NASA's launch of the James Webb Space Telescope, which is scheduled for 2021. The largest and most powerful space telescope ever launched, it is expected to dramatically expand scientists' knowledge of the universe.

"What we can do in the lab in one day takes thousands of years in space," Congiu said. "Our work in the lab can complement the wealth of data that comes from the space observatories. Otherwise, astronomers would not be able to interpret all of their observations. Researchers who make observations can ask us to simulate a certain reaction, to see if what they think they see is real or not."

From Science Daily

A pair of lonely planet-like objects born like stars

 Star-forming processes sometimes create mysterious astronomical objects called brown dwarfs, which are smaller and colder than stars, and can have masses and temperatures down to those of exoplanets in the most extreme cases. Just like stars, brown dwarfs often wander alone through space, but can also be seen in binary systems, where two brown dwarfs orbit one another and travel together in the galaxy.

Researchers led by Clémence Fontanive from the Center for Space and Habitability (CSH) and the NCCR PlanetS discovered a curious starless binary system of brown dwarfs. The system CFHTWIR-Oph 98 (or Oph 98 for short) consists of the two very low-mass objects Oph 98 A and Oph 98 B. It is located 450 light years away from Earth in the stellar association Ophiuchus. The researchers were surprised by the fact that Oph 98 A and B are orbiting each other from a strikingly large distance, about 5 times the distance between Pluto and the Sun, which corresponds to 200 times the distance between the Earth and the Sun. The study has just been published in The Astrophysical Journal Letters.

Extremely low masses and a very large separation

The pair is a rare example of two objects similar in many aspects to extra-solar giant planets, orbiting around each other with no parent star. The more massive component, Oph 98 A, is a young brown dwarf with a mass of 15 times that of Jupiter, which is almost exactly on the boundary separating brown dwarfs from planets. Its companion, Oph 98 B, is only 8 times heavier than Jupiter.

Components of binary systems are tied by an invisible link called gravitational binding energy, and this bond gets stronger when objects are more massive or closer to one another. With extremely low masses and a very large separation, Oph 98 has the weakest binding energy of any binary system known to date.

Discovery thanks to data from Hubble

Clémence Fontanive and her colleagues discovered the companion to Oph 98 A using images from the Hubble Space Telescope. Fontanive says: "Low-mass brown dwarfs are very cold and emit very little light, only through infrared thermal radiation. This heat glow is extremely faint and red, and brown dwarfs are hence only visible in infrared light." Furthermore, the stellar association in which the binary is located, Ophiuchus, is embedded in a dense, dusty cloud which scatters visible light. "Infrared observations are the only way to see through this dust," explains the lead researcher. "Detecting a system like Oph 98 also requires a camera with a very high resolution, as the angle separating Oph 98 A and B is a thousand times smaller than the size of the moon in the sky," she adds. The Hubble Space Telescope is among the few telescopes capable of observing objects as faint as these brown dwarfs, and able to resolve such tight angles.

Because brown dwarfs are cold enough, water vapor forms in their atmospheres, creating prominent features in the infrared that are commonly used to identify brown dwarfs. However, these water signatures cannot be easily detected from the surface of the Earth. Located above the atmosphere in the vacuum of space, Hubble allows to probe the existence of water vapor in astronomical objects. Fontanive explains: "Both objects looked very red and showed clear signs of water molecules. This immediately confirmed that the faint source we saw next to Oph 98 A was very likely to also be a cold brown dwarf, rather than a random star that happened to be aligned with the brown dwarf in the sky."

The team also found images in which the binary was visible, collected 14 years ago with the Canada-France-Hawaii Telescope (CFHT) in Hawaii. "We observed the system again this summer from another Hawaiian observatory, the United Kingdom Infra-Red Telescope. Using these data, we were able to confirm that Oph 98 A and B are moving together across the sky over time, relative to other stars located behind them, which is evidence that they are bound to each other in a binary pair," explains Fontanive.

An atypical result of star formation

The Oph 98 binary system formed only 3 million years ago in the nearby Ophiuchus stellar nursery, making it a newborn on astronomical timescales. The age of the system is much shorter than the typical time needed to build planets. Brown dwarfs like Oph 98 A are formed by the same mechanisms as stars. Despite Oph 98 B being the right size for a planet, the host Oph 98 A is too small to have a sufficiently large reservoir of material to build a planet that big. "This tells us that Oph 98 B, like its host, must have formed through the same mechanisms that produce stars and shows that the processes that create binary stars operate on scale-down versions all the way down to these planetary masses," comments Clémence Fontanive.

With the discovery of two planet-like worlds -- already uncommon products of star formation -- bound to each other in such an extreme configuration, "we are really witnessing an incredibly rare output of stellar formation processes," as Fontanive describes.

Bernese space exploration: With the world's elite since the first moon landing

When the second man, "Buzz" Aldrin, stepped out of the lunar module on July 21, 1969, the first task he did was to set up the Bernese Solar Wind Composition experiment (SWC) also known as the "solar wind sail" by planting it in the ground of the moon, even before the American flag. This experiment, which was planned and the results analysed by Prof. Dr. Johannes Geiss and his team from the Physics Institute of the University of Bern, was the first great highlight in the history of Bernese space exploration.

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The DNA regions in our brain that contribute to make us human

 With only 1% difference, the human and chimpanzee protein-coding genomes are remarkably similar. Understanding the biological features that make us human is part of a fascinating and intensely debated line of research. Researchers at the SIB Swiss Institute of Bioinformatics and the University of Lausanne have developed a new approach to pinpoint, for the first time, adaptive human-specific changes in the way genes are regulated in the brain. These results open new perspectives in the study of human evolution, developmental biology and neurosciences. The paper is published in Science Advances.

Gene expression, not gene sequence

To explain what sets human apart from their ape relatives, researchers have long hypothesized that it is not so much the DNA sequence, but rather the regulation of the genes (i.e. when, where and how strongly the gene is expressed), that plays the key role. However, precisely pinpointing the regulatory elements which act as 'gene dimmers' and are positively selected is a challenging task that has thus far defeated researchers (see box).

Marc Robinson-Rechavi, Group Leader at SIB and study co-author says: "To be able to answer such tantalizing questions, one has to be able identify the parts in the genome that have been under so called 'positive' selection [see box]. The answer is of great interest in addressing evolutionary questions, but also, ultimately, could help biomedical research as it offers a mechanistic view of how genes function."

A high proportion of the regulatory elements in the human brain have been positively selected

Researchers at SIB and the University of Lausanne have developed a new method which has enabled them to identify a large set of gene regulatory regions in the brain, selected throughout human evolution. Jialin Liu, Postdoctoral researcher and lead author of the study explains: "We show for the first time that the human brain has experienced a particularly high level of positive selection, as compared to the stomach or heart for instance. This is exciting, because we now have a way to identify genomic regions that might have contributed to the evolution of our cognitive abilities!"

To reach their conclusions, the two researchers combined machine learning models with experimental data on how strongly proteins involved in gene regulation bind to their regulatory sequences in different tissues, and then performed evolutionary comparisons between human, chimpanzee and gorilla. "We now know which are the positively selected regions controlling gene expression in the human brain. And the more we learn about the genes they are controlling, the more complete our understanding of cognition and evolution, and the more scope there will be to act on that understanding," concludes Marc Robinson-Rechavi.

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The human helpers of SARS-CoV-2

 Like all viruses, the novel coronavirus is dependent on help from the human host cell. Proteins are the functional units of the cell and enable the virus to enter the host cell or help the virus to replicate. Scientists from Charité -- Universitätsmedizin Berlin and from the Berlin Institute of Health (BIH), along with colleagues from the United Kingdom, Germany and the United States, have examined the corresponding genes of the helper proteins in a large study. They discovered numerous variants that influence the amount or function of the proteins as well as their ability to support the virus. The gene variants reveal potential target structures for new drugs. The researchers have now published their results in the journal Nature Communications.

An infection of the novel coronavirus SARS-CoV-2, just like any other viral infection, follows a specific pattern: The viruses first bind to receptor proteins on the surface of the human host cells in the throat, nose or lungs before entering the cell, where they replicate with the help of the host cell machinery. The newly formed virus particles cause the infected cell to burst and infect other cells. As soon as the immune system notices what is happening, a defense mechanism is activated with the goal of destroying and removing both the viruses and virus-infected cells. Under normal circumstances, the infection is over within two weeks at the most. For all these processes, however, the virus is dependent on human or host proteins.

"In severe courses of COVID-19, this regulated process gets out of control and the immune system causes an excessive inflammatory response that attacks not only virus-infected cells but also healthy tissue," says Prof. Dr. Claudia Langenberg, BIH Professor of Computational Medicine and head of the study now being published. "Naturally occurring variations in the genes that make up the blueprint for these human proteins can alter their concentration or function and may thus be responsible for the different course of the disease." The team is well versed in the discovery of genetic variants that not only affect specific proteins but also common complex diseases. "As molecular epidemiologists, we study the diversity of genes -- that is, the building instructions for proteins -- of entire population groups in order to uncover susceptibilities to diseases whose cause lies in the interaction of many small deviations," explains the epidemiologist, who joined the BIH from the Medical Research Council Epidemiology Unit at the University of Cambridge in September. "We wanted to use these experiences and data sets for the COVID-19 epidemic and make them available to the scientific community."

"We examined 179 proteins known to be involved in SARS-CoV-2 infection for their naturally occurring variants," reports Dr. Maik Pietzner, the study's lead author and a scientist in Prof. Langenberg's lab. "We were able to draw on findings which were based on samples of the first COVID-19 patients at Charité. " This was possible due to close collaboration with the research group led by Professor Dr. Markus Ralser, Director of the Institute of Biochemistry at Charité, which had previously reported these findings. The team of Prof. Langenberg was able to use data from the MRC Fenland Cohort, a large population study that contains information from more than 10,000 individuals. They discovered 38 targets for existing drugs as well as evidence that certain proteins that interact with the virus influence the immune system. "Our findings also help to better understand risk factors for severe courses of COVID-19. We were able to show that blood coagulation proteins are influenced by the same genetic variant that increases the risk of contracting COVID-19 and that determines blood group 0," reports Dr. Pietzner.

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Astronomers detect possible radio emission from exoplanet

 

Illustration of a 'hot Jupiter' exoplanet orbiting nearby star.

By monitoring the cosmos with a radio telescope array, an international team of scientists has detected radio bursts emanating from the constellation Boötes -- that could be the first radio emission collected from a planet beyond our solar system.

The team, led by Cornell postdoctoral researcher Jake D. Turner, Philippe Zarka of the Observatoire de Paris -- Paris Sciences et Lettres University and Jean-Mathias Griessmeier of the Université d'Orléans will publish their findings in the forthcoming research section of Astronomy & Astrophysics, on Dec. 16.

"We present one of the first hints of detecting an exoplanet in the radio realm," Turner said. "The signal is from the Tau Boötes system, which contains a binary star and an exoplanet. We make the case for an emission by the planet itself. From the strength and polarization of the radio signal and the planet's magnetic field, it is compatible with theoretical predictions."

Among the co-authors is Turner's postdoctoral advisor Ray Jayawardhana, the Harold Tanner Dean of the College of Arts and Sciences, and a professor of astronomy.

"If confirmed through follow-up observations," Jayawardhana said, "this radio detection opens up a new window on exoplanets, giving us a novel way to examine alien worlds that are tens of light-years away."

Using the Low Frequency Array (LOFAR), a radio telescope in the Netherlands, Turner and his colleagues uncovered emission bursts from a star-system hosting a so-called hot Jupiter, a gaseous giant planet that is very close to its own sun. The group also observed other potential exoplanetary radio-emission candidates in the 55 Cancri (in the constellation Cancer) and Upsilon Andromedae systems. Only the Tau Boötes exoplanet system -- about 51 light-years away -- exhibited a significant radio signature, a unique potential window on the planet's magnetic field.

Observing an exoplanet's magnetic field helps astronomers decipher a planet's interior and atmospheric properties, as well as the physics of star-planet interactions, said Turner, a member of Cornell's Carl Sagan Institute.

Earth's magnetic field protects it from solar wind dangers, keeping the planet habitable. "The magnetic field of Earth-like exoplanets may contribute to their possible habitability," Turner said, "by shielding their own atmospheres from solar wind and cosmic rays, and protecting the planet from atmospheric loss."

Two years ago, Turner and his colleagues examined the radio emission signature of Jupiter and scaled those emissions to mimic the possible signatures from a distant Jupiter-like exoplanet. Those results became the template for searching radio emission from exoplanets 40 to 100 light-years away.

After poring over nearly 100-hours of radio observations, the researchers were able to find the expected hot Jupiter signature in Tau Boötes. "We learned from our own Jupiter what this kind of detection looks like. We went searching for it and we found it," Turner said.

The signature, though, is weak. "There remains some uncertainty that the detected radio signal is from the planet. The need for follow-up observations is critical," he said.

Turner and his team have already begun a campaign using multiple radio telescopes to follow up on the signal from Tau Boötes.

Read more at Science Daily

The farthest galaxy in the universe

 A team of astronomers used the Keck I telescope to measure the distance to an ancient galaxy. They deduced the target galaxy GN-z11 is not only the oldest galaxy but also the most distant. It's so distant it defines the very boundary of the observable universe itself. The team hopes this study can shed light on a period of cosmological history when the universe was only a few hundred million years old.

We've all asked ourselves the big questions at times: "How big is the universe?" or "How and when did galaxies form?" Astronomers take these questions very seriously, and use fantastic tools that push the boundaries of technology to try and answer them. Professor Nobunari Kashikawa from the Department of Astronomy at the University of Tokyo is driven by his curiosity about galaxies. In particular, he sought the most distant one we can observe in order to find out how and when it came to be.

"From previous studies, the galaxy GN-z11 seems to be the farthest detectable galaxy from us, at 13.4 billion light years, or 134 nonillion kilometers (that's 134 followed by 30 zeros)," said Kashikawa. "But measuring and verifying such a distance is not an easy task."

Kashikawa and his team measured what's known as the redshift of GN-z11; this refers to the way light stretches out, becomes redder, the farther it travels. Certain chemical signatures, called emission lines, imprint distinct patterns in the light from distant objects. By measuring how stretched these telltale signatures are, astronomers can deduce how far the light must have traveled, thus giving away the distance from the target galaxy.

"We looked at ultraviolet light specifically, as that is the area of the electromagnetic spectrum we expected to find the redshifted chemical signatures," said Kashikawa. "The Hubble Space Telescope detected the signature multiple times in the spectrum of GN-z11. However, even the Hubble cannot resolve ultraviolet emission lines to the degree we needed. So we turned to a more up-to-date ground-based spectrograph, an instrument to measure emission lines, called MOSFIRE, which is mounted to the Keck I telescope in Hawaii."

The MOSFIRE captured the emission lines from GN-z11 in detail, which allowed the team to make a much better estimation on its distance than was possible from previous data. When working with distances at these scales, it is not sensible to use our familiar units of kilometers or even multiples of them; instead, astronomers use a value known as the redshift number denoted by z. Kashikawa and his team improved the accuracy of the galaxy's z value by a factor of 100. If subsequent observations can confirm this, then the astronomers can confidently say GN-z11 is the farthest galaxy ever detected in the universe.

From Science Daily

Researchers identify where giant jets from black holes discharge their energy

 The supermassive black holes at the centers of galaxies are the most massive objects in the universe. They range from about 1 million to upwards of 10 billion times the mass of the Sun. Some of these black holes also blast out gigantic, super-heated jets of plasma at nearly the speed of light. The primary way that the jets discharge this powerful motion energy is by converting it into extremely high-energy gamma rays. However, UMBC physics Ph.D. candidate Adam Leah Harvey says, "How exactly this radiation is created is an open question."

The jet has to discharge its energy somewhere, and previous work doesn't agree where. The prime candidates are two regions made of gas and light that encircle black holes, called the broad-line region and the molecular torus.

A black hole's jet has the potential to convert visible and infrared light in either region to high-energy gamma rays by giving away some of its energy. Harvey's new NASA-funded research sheds light on this controversy by offering strong evidence that the jets mostly release energy in the molecular torus, and not in the broad-line region. The study was published in Nature Communications and co-authored by UMBC physicists Markos Georganopoulos and Eileen Meyer.

Far out

The broad-line region is closer to the center of a black hole, at a distance of about 0.3 light-years. The molecular torus is much farther out -- more than 3 light-years. While all of these distances seem huge to a non-astronomer, the new work "tells us that we're getting energy dissipation far away from the black hole at the relevant scales," Harvey explains.

"The implications are extremely important for our understanding of jets launched by black holes," Harvey says. Which region primarily absorbs the jet's energy offers clues to how the jets initially form, pick up speed, and become column-shaped. For example, "It indicates that the jet is not accelerated enough at smaller scales to start to dissipate energy," Harvey says.

Other researchers have proposed contradictory ideas about the jets' structure and behavior. Because of the trusted methods Harvey used in their new work, however, they expect the results to be broadly accepted in the scientific community. "The results basically help to constrain those possibilities -- those different models -- of jet formation."

On solid footing

To come to their conclusions, Harvey applied a standard statistical technique called "bootstrapping" to data from 62 observations of black hole jets. "A lot of what came before this paper has been very model-dependent. Other papers have made a lot of very specific assumptions, whereas our method is extremely general," Harvey explains. "There isn't much to undermine the analysis. It's well-understood methods, and just using observational data. So the result should be correct."

A quantity called the seed factor was central to the analysis. The seed factor indicates where the light waves that the jet converts to gamma rays come from. If the conversion happens at the molecular torus, one seed factor is expected. If it happens at the broad-line region, the seed factor will be different.

Georganopolous, associate professor of physics and one of Harvey's advisors, originally developed the seed factor concept, but "applying the idea of the seed factor had to wait for someone with a lot of perseverance, and this someone was Adam Leah," Georganopolous says.

Harvey calculated the seed factors for all 62 observations. They found that the seed factors fell in a normal distribution aligned almost perfectly around the expected value for the molecular torus. That result strongly suggests that the energy from the jet is discharging into light waves in the molecular torus, and not in the broad-line region.

Tangents and searches

Harvey shares that the support of their mentors, Georganopoulos and Meyer, assistant professor of physics, was instrumental to the project's success. "I think that without them letting me go off on a lot of tangents and searches of how to do things, this would have never gotten to the level that it's at," Harvey says. "Because they allowed me to really dig into it, I was able to pull out a lot more from this project."

Harvey identifies as an "observational astronomer," but adds, "I'm really more of a data scientist and a statistician than I am a physicist." And the statistics has been the most exciting part of this work, they say.

Read more at Science Daily

To the brain, reading computer code is not the same as reading language

 In some ways, learning to program a computer is similar to learning a new language. It requires learning new symbols and terms, which must be organized correctly to instruct the computer what to do. The computer code must also be clear enough that other programmers can read and understand it.

In spite of those similarities, MIT neuroscientists have found that reading computer code does not activate the regions of the brain that are involved in language processing. Instead, it activates a distributed network called the multiple demand network, which is also recruited for complex cognitive tasks such as solving math problems or crossword puzzles.

However, although reading computer code activates the multiple demand network, it appears to rely more on different parts of the network than math or logic problems do, suggesting that coding does not precisely replicate the cognitive demands of mathematics either.

"Understanding computer code seems to be its own thing. It's not the same as language, and it's not the same as math and logic," says Anna Ivanova, an MIT graduate student and the lead author of the study.

Evelina Fedorenko, the Frederick A. and Carole J. Middleton Career Development Associate Professor of Neuroscience and a member of the McGovern Institute for Brain Research, is the senior author of the paper, which appears today in eLife. Researchers from MIT's Computer Science and Artificial Intelligence Laboratory and Tufts University were also involved in the study.

Language and cognition

A major focus of Fedorenko's research is the relationship between language and other cognitive functions. In particular, she has been studying the question of whether other functions rely on the brain's language network, which includes Broca's area and other regions in the left hemisphere of the brain. In previous work, her lab has shown that music and math do not appear to activate this language network.

"Here, we were interested in exploring the relationship between language and computer programming, partially because computer programming is such a new invention that we know that there couldn't be any hardwired mechanisms that make us good programmers," Ivanova says.

There are two schools of thought regarding how the brain learns to code, she says. One holds that in order to be good at programming, you must be good at math. The other suggests that because of the parallels between coding and language, language skills might be more relevant. To shed light on this issue, the researchers set out to study whether brain activity patterns while reading computer code would overlap with language-related brain activity.

The two programming languages that the researchers focused on in this study are known for their readability -- Python and ScratchJr, a visual programming language designed for children age 5 and older. The subjects in the study were all young adults proficient in the language they were being tested on. While the programmers lay in a functional magnetic resonance (fMRI) scanner, the researchers showed them snippets of code and asked them to predict what action the code would produce.

The researchers saw little to no response to code in the language regions of the brain. Instead, they found that the coding task mainly activated the so-called multiple demand network. This network, whose activity is spread throughout the frontal and parietal lobes of the brain, is typically recruited for tasks that require holding many pieces of information in mind at once, and is responsible for our ability to perform a wide variety of mental tasks.

"It does pretty much anything that's cognitively challenging, that makes you think hard," Ivanova says.

Previous studies have shown that math and logic problems seem to rely mainly on the multiple demand regions in the left hemisphere, while tasks that involve spatial navigation activate the right hemisphere more than the left. The MIT team found that reading computer code appears to activate both the left and right sides of the multiple demand network, and ScratchJr activated the right side slightly more than the left. This finding goes against the hypothesis that math and coding rely on the same brain mechanisms.

Effects of experience

The researchers say that while they didn't identify any regions that appear to be exclusively devoted to programming, such specialized brain activity might develop in people who have much more coding experience.

"It's possible that if you take people who are professional programmers, who have spent 30 or 40 years coding in a particular language, you may start seeing some specialization, or some crystallization of parts of the multiple demand system," Fedorenko says. "In people who are familiar with coding and can efficiently do these tasks, but have had relatively limited experience, it just doesn't seem like you see any specialization yet."

In a companion paper appearing in the same issue of eLife, a team of researchers from Johns Hopkins University also reported that solving code problems activates the multiple demand network rather than the language regions.

The findings suggest there isn't a definitive answer to whether coding should be taught as a math-based skill or a language-based skill. In part, that's because learning to program may draw on both language and multiple demand systems, even if -- once learned -- programming doesn't rely on the language regions, the researchers say.

"There have been claims from both camps -- it has to be together with math, it has to be together with language," Ivanova says. "But it looks like computer science educators will have to develop their own approaches for teaching code most effectively."

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