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September 18, The Day Leonhard Euler Died

September 18, The Day Leonhard Euler Died | Amazing Science | Scoop.it

Euler is easily the most prolific mathematician of all time. The range and volume of his output is simply staggering. He published over 850 papers, almost all of substantial length, and more than 25 books and treatises. In 1907 the Swiss Academy of Sciences established the Euler Commission with the charge of publishing the complete body of work consisting of all of his papers, manuscripts, and correspondence. This project, known as Opera Omnia, began in 1911 and is still ongoing. His scientific publications, not counting his correspondence, run to over 70 volumes, each between approximately 300 and 600 pages. Thousands of pages of handwritten manuscripts are still not in print. Euler was in constant communication with all the great scientists of his day, and his correspondence covers several thousand pages.


Euler's powers of memory and concentration were legendary. He could recite the entire Aeneid word-for-word. He was not troubled by interruptions or distractions; in fact, he did much of his work with his young children playing at his feet. He was able to do prodigious calculations in his head, a necessity after he went blind. The contemporary French mathematician Condorcet tells the story of two of Euler's students who had independently summed seventeen terms of a complicated infinite series, only to disagree in the fiftieth decimal place; Euler settled the dispute by recomputing the sum in his head.


Further reading: http://www.ams.org/bookstore/pspdf/euler-prev.pdf


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Unlimited, at-home coronavirus testing for your organization

Unlimited, at-home coronavirus testing for your organization | Amazing Science | Scoop.it

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Watch dolphins line up to self-medicate skin ailments at coral 'clinics'

Watch dolphins line up to self-medicate skin ailments at coral 'clinics' | Amazing Science | Scoop.it
If a human comes down with a rash, they might go to the doctor and come away with some ointment to put on it. Indo-Pacific bottlenose dolphins get skin conditions, too, but they come about their medication by queuing up nose-to-tail to rub themselves against corals. Researchers now show that these corals have medicinal properties, suggesting that the dolphins are using the marine invertebrates to medicate skin conditions.

 

Thirteen years ago, co-lead author Angela Ziltener, a wildlife biologist at the University of Zurich, Switzerland, first observed dolphins rubbing against coral in the Northern Red Sea, off the coast of Egypt. She and her team noticed that the dolphins were selective about which corals they rubbed against, and they wanted to understand why. "I hadn't seen this coral rubbing behavior described before, and it was clear that the dolphins knew exactly which coral they wanted to use," says Ziltener. "I thought, 'There must be a reason.'"

 

Most dolphin research is conducted from the surface of the water, but because Ziltener is a diver, she was able to study the dolphins up close. It took some time to earn the trust of the pod, which she was able to do in part because these dolphins weren't phased by the large bubbles released by the diving tanks and habituated towards divers. "Some dolphins, like spinner dolphins in the Southern Egyptian Red Sea, are shyer regarding bubbles," she says.

 

Once the pod allowed her to visit them regularly, she and her colleagues were able to identify and sample the corals that the dolphins were rubbing on. Ziltener and her team found that by repeatedly rubbing against the corals, Indo-Pacific bottlenose dolphins were agitating the tiny polyps that make up the coral community, and these invertebrates were releasing mucus. In order to understand what properties the mucus contained, the team collected samples of the coral.

 

When lead author Gertrud Morlock, an analytical chemist and food scientist at Justus Liebig University Gießen in Germany, and her team used planar separations combined with on-surface assays and high-resolution mass spectrometry to analyze samples of the gorgonian coral Rumphella aggregata, the leather coral Sarcophyton sp.,and the sponge Ircinia sp.,they found 17 active metabolites with antibacterial, antioxidative, hormonal, and toxic activities.

 

This discovery of these bioactive compounds led the team to believe that the mucus of the corals and sponges is serving to regulate the dolphin skin's microbiome and treat infections. "Repeated rubbing allows the active metabolites to come into contact with the skin of the dolphins," says Morlock. "These metabolites could help them achieve skin homeostasis and be useful for prophylaxis or auxiliary treatment against microbial infections."

 

The reefs where these corals are found are important places for the local dolphin populations. They head there to rest and to have fun. "Many people don't realize that these coral reefs are bedrooms for the dolphins, and playgrounds as well," says Ziltener. In between naps, the dolphins often wake to perform the coral rubbing behavior. "It's almost like they are showering, cleaning themselves before they go to sleep or get up for the day," she says.

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How to make our electronics smarter, faster, and more resilient – topology has the answer

How to make our electronics smarter, faster, and more resilient – topology has the answer | Amazing Science | Scoop.it

A new database and searchable tool reveals more than 90,000 known materials with electronic properties that remain unperturbed in the face of disruption.

 

Topology stems from a branch of mathematics that studies shapes that can be manipulated or deformed without losing certain core properties. A donut is a common example: If it were made of rubber, a donut could be twisted and squeezed into a completely new shape, such as a coffee mug, while retaining a key trait — namely, its center hole, which takes the form of the cup’s handle. The hole, in this case, is a topological trait, robust against certain deformations.

 

In recent years, scientists have applied concepts of topology to the discovery of materials with similarly robust electronic properties. In 2007, researchers predicted the first electronic topological insulators — materials in which electrons that behave in ways that are “topologically protected,” or persistent in the face of certain disruptions.

 

Since then, scientists have searched for more topological materials with the aim of building better, more robust electronic devices. Until recently, only a handful of such materials were identified, and were therefore assumed to be a rarity. Now researchers at MIT and elsewhere have discovered that, in fact, topological materials are everywhere, if you know how to look for them.

 

In a paper published today in Science, the team, led by Nicolas Regnault of Princeton University and the École Normale Supérieure Paris, reports harnessing the power of multiple supercomputers to map the electronic structure of more than 96,000 natural and synthetic crystalline materials. They applied sophisticated filters to determine whether and what kind of topological traits exist in each structure.

 

Overall, they found that 90 percent of all known crystalline structures contain at least one topological property, and more than 50 percent of all naturally occurring materials exhibit some sort of topological behavior. “We found there’s a ubiquity — topology is everywhere,” says Benjamin Wieder, the study’s co-lead, and a postdoc in MIT’s Department of Physics.

 

The team has compiled the newly identified materials into a new, freely accessible Topological Materials Database resembling a periodic table of topology. With this new library, scientists can quickly search materials of interest for any topological properties they might hold, and harness them to build ultra-low-power transistors, new magnetic memory storage, and other devices with robust electronic properties.

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New Precise Hubble Constant Measurement Adds to Mystery of Universe Expansion

New Precise Hubble Constant Measurement Adds to Mystery of Universe Expansion | Amazing Science | Scoop.it

Scientists have known for almost a century that the universe is expanding, meaning the distance between galaxies across the universe is becoming ever more vast every second. But exactly how fast space is stretching, a value known as the Hubble constant, has remained stubbornly elusive.

 

Now, University of Chicago professor Wendy Freedman and colleagues have a new measurement for the rate of expansion in the modern universe, suggesting the space between galaxies is stretching faster than scientists would expect. Freedman's is one of several recent studies that point to a nagging discrepancy between modern expansion measurements and predictions based on the universe as it was more than 13 billion years ago, as measured by the European Space Agency's Planck satellite.

 

As more research points to a discrepancy between predictions and observations, scientists are considering whether they may need to come up with a new model for the underlying physics of the universe in order to explain it.

 

"The Hubble constant is the cosmological parameter that sets the absolute scale, size and age of the universe; it is one of the most direct ways we have of quantifying how the universe evolves," said Freedman. "The discrepancy that we saw before has not gone away, but this new evidence suggests that the jury is still out on whether there is an immediate and compelling reason to believe that there is something fundamentally flawed in our current model of the universe.”

 

In a new paper accepted for publication in The Astrophysical Journal, Freedman and her team announced a new measurement of the Hubble constant using a kind of star known as a red giant. Their new observations, made using Hubble, indicate that the expansion rate for the nearby universe is just under 70 kilometers per second per megaparsec (km/sec/Mpc). One parsec is equivalent to 3.26 light-years distance. This measurement is slightly smaller than the value of 74 km/sec/Mpc recently reported by the Hubble SH0ES (Supernovae H0 for the Equation of State) team using Cepheid variables, which are stars that pulse at regular intervals that correspond to their peak brightness. This team, led by Adam Riess of the Johns Hopkins University and Space Telescope Science Institute, Baltimore, Maryland, recently reported refining their observations to the highest precision to date for their Cepheid distance measurement technique.

 

According to current understanding, the Hubble constant should be about 67.5 kilometers per second per Mpc, plus/minus 0.5. Any discrepancy shows that the evolution and expansion of the universe are more complicated than previously thought. There is still more to understand about how the universe is changing.

 

The new James Webb Space Telescope is likely to help clarifying the situation. Then, scientists should be able to view new mileposts that are even further away and in higher resolution as a result of this.

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Plastic nurdles are infiltrating our environment and polluting it for hundreds if not thousands of years

Plastic nurdles are infiltrating our environment and polluting it for hundreds if not thousands of years | Amazing Science | Scoop.it

A nurdle is a bead of pure plastic. It is the basic building block of almost all plastic products, like some sort of synthetic ore; their creators call them “pre-production plastic pellets” or “resins.” Every year, trillions of nurdles are produced from natural gas or oil, shipped to factories around the world, and then melted and poured into molds that churn out water bottles and sewage pipes and steering wheels and the millions of other plastic products we use every day. You are almost certainly reading this story on a device that is part nurdle. Most nurdles, being less than 5 millimeters in size, are a form of microplastic from the moment of its creation, something also known as a primary microplastic.

 

Not all nurdles make their way safely to the end of a production line. An estimated 200,000 metric tons of nurdles make their way into oceans annually. The beads are extremely light, around 20 milligrams each. That means, under current conditions, approximately 10 trillion nurdles are projected to infiltrate marine ecosystems around the world each year. Hundreds of fish species — including some eaten by humans — and at least 80 kinds of seabirds eat plastics. Researchers are concerned that animals that eat nurdles risk blocking their digestive tracts and starving to death. Just as concerning is what happens to the beads in the long term: Like most plastics, they do not biodegrade, but they do deteriorate over time, forming the second-largest source of ocean microplastics after tire dust.

 

There’s much we still don’t know about how plastics can harm the bodies of humans and animals alike, but recent research has shown that microplastics can be found in the blood of as much as 80 percent of all adult humans, where they can potentially harm our cells. We may not eat the plastic beads ourselves, but nurdles seem to have a way of finding their way back to us.

 

In most of the United States, the federal and local government respond to nurdle spills big and small in the same way: by doing practically nothing. Nurdles are not classified as pollutants or hazardous materials, so the Coast Guard, which usually handles cleanups of oil or other toxic substances that enter waterways, bears no responsibility for them.

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Unreal Engine 5 - Ultra-realistic video world creation

Neil deGrasse Tyson once said that we are either living in a simulation or on the verge of creating a simulation that others will live in. Imagine we become the agents of that VR into a world like that and interact with AI who might one day realize they aren't real and try to escape into our world.

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Machine-learning model can distinguish antibody targets

Machine-learning model can distinguish antibody targets | Amazing Science | Scoop.it

A new study shows that it is possible to use the genetic sequences of a person's antibodies to predict what pathogens those antibodies will target. Reported in the journal Immunity, the new approach successfully differentiates between antibodies against influenza and those attacking SARS-CoV-2, the virus that causes COVID-19.

 

"Our research is in a very early stage, but this proof-of-concept study shows that we can use machine learning to connect the sequence of an antibody to its function," said Nicholas Wu, a professor of biochemistry at the University of Illinois Urbana-Champaign who led the research with U. of I. biochemistry Ph.D. student Yiquan Wang; and Meng Yuan, a staff scientist at Scripps Research in La Jolla, California.

 

With enough data, scientists should be able to predict not only the virus an antibody will attack, but which features on the pathogen the antibody binds to, Wu said. For example, an antibody may attach to different parts of the spike protein on the SARS-CoV-2 virus. Knowing this will allow scientists to predict the strength of a person's immune defense, as some targets of a pathogen are more vulnerable than others.

 

The new approach was made possible by the abundance of data related to antibodies against SARS-CoV-2, Wu said. "In 20 years, scientists have discovered about 5,000 antibodies against the flu virus," he said. "But in just two years, people have identified 8,000 antibodies for COVID. This provides an opportunity that's never been seen before to study how antibodies work and to do this kind of prediction."

 

The researchers used antibody data from 88 published studies and 13 patents. The datasets were big enough to allow the researchers to train their model to make predictions based on the antibodies' genetic sequence. The model was designed to distinguish whether the sequences coded for antibodies targeting regions on the influenza virus or on the SARS-CoV-2 virus. The researchers then checked the accuracy of those predictions.

 

"The accuracy was close to 85% overall," Wang said. "I was actually quite surprised that it worked so well," Wu said. The team is working to improve its model so that it can more precisely determine which parts of the virus the antibodies attack. "If we can make these predictions based on antibody sequence, we might also be able to go back and design antibodies that bind to specific pathogens," Wu said. "This is not something that we can do now, but those are some implications for future study."

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Stanford scientist models landscape formation on Titan, revealing an Earth-like alien world

Stanford scientist models landscape formation on Titan, revealing an Earth-like alien world | Amazing Science | Scoop.it

Saturn’s moon Titan looks very much like Earth from space, with rivers, lakes, and seas filled by rain tumbling through a thick atmosphere. While these landscapes may look familiar, they are composed of materials that are undoubtedly different – liquid methane streams streak Titan’s icy surface and nitrogen winds build hydrocarbon sand dunes.

 

The presence of these materials – whose mechanical properties are vastly different from those of silicate-based substances that make up other known sedimentary bodies in our solar system – makes Titan’s landscape formation enigmatic. By identifying a process that would allow for hydrocarbon-based substances to form sand grains or bedrock depending on how often winds blow and streams flow, Stanford University geologist Mathieu Lapôtre and his colleagues have shown how Titan’s distinct dunes, plains, and labyrinth terrains could be formed.

 

Titan, which is a target for space exploration because of its potential habitability, is the only other body in our solar system known to have an Earth-like, seasonal liquid transport cycle today. The new model, recently published in Geophysical Research Letters, shows how that seasonal cycle drives the movement of grains over the moon’s surface.

 

“Our model adds a unifying framework that allows us to understand how all of these sedimentary environments work together,” said Lapôtre, an assistant professor of geological sciences at Stanford’s School of Earth, Energy & Environmental Sciences (Stanford Earth). “If we understand how the different pieces of the puzzle fit together and their mechanics, then we can start using the landforms left behind by those sedimentary processes to say something about the climate or the geological history of Titan – and how they could impact the prospect for life on Titan.”

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Turning back time – new technique rewinds the age of skin cells by 30 years

Turning back time – new technique rewinds the age of skin cells by 30 years | Amazing Science | Scoop.it

Research from the Babraham Institute has developed a method to ‘time jump’ human skin cells by 30 years, turning back the aging clock for cells without losing their specialized function. Work by researchers in the Institute’s Epigenetics research program has been able to partly restore the function of older cells, as well as rejuvenating the molecular measures of biological age. The research is published in the journal eLife and whilst at an early stage of exploration, it could revolutionize regenerative medicine.

 

How does it work?

As we age, our cells’ ability to function declines and the genome accumulates marks of aging. Regenerative biology aims to repair or replace cells including old ones. One of the most important tools in regenerative biology is our ability to create ‘induced’ stem cells. The process is a result of several steps, each erasing some of the marks that make cells specialized. In theory, these stem cells have the potential to become any cell type, but scientists aren’t yet able to reliably recreate the conditions to re-differentiate stem cells into all cell types.

 

The new method, based on the Nobel Prize winning technique scientists use to generate stem cells, overcomes the problem of entirely erasing cell identity by halting reprogramming part of the way through the whole process. This allowed researchers to find the precise balance between reprogramming cells, making them biologically younger, while still being able to regain their specialized cell function.

 

In 2007, Shinya Yamanaka was the first scientist to turn normal cells, which have a specific function, into stem cells which have the special ability to develop into any cell type. The full process of stem cell reprogramming takes around 50 days using four key molecules called the Yamanaka factors. The new method, called 'maturation phase transient reprogramming’, exposes cells to Yamanaka factors for just 13 days. At this point, age-related changes are removed and the cells have temporarily lost their identity. The partly reprogrammed cells were given time to grow under normal conditions, to observe whether their specific skin cell function returned. Genome analysis showed that cells had regained markers characteristic of skin cells (fibroblasts), and this was confirmed by observing collagen production in the reprogrammed cells.

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Me and my organoid: a step closer to tailored therapy

Me and my organoid: a step closer to tailored therapy | Amazing Science | Scoop.it

This is the story of the revolutionary development of mini-organs (organoids) and their countless applications on how they help us to develop and implement tailored therapy for each patient. A tale for the future of medicine from a group of scientists in Utrecht that started it all - out of wonder.

 

In 2009, Hans Clevers  external link, a stem cell biologist at Utrecht University, made a discovery that would forever transform healthcare. His lab at the Hubrecht Institute  external link had grown what, under the microscope, looked like a real gut outside the body (made from mouse intestinal cells). It was the first in a series of organs-in-a-dish that would revolutionize personalized medicine in every corner of the world. Today, the possibilities of these mini-organs are enormous: from finding the right treatment to otherwise lethal genetic diseases, numerous cancers and infectious diseases, to understanding furtive neurological disorders such as schizophrenia, bipolar disorder or autism without having to poke one’s brain. We also know deaths from organ donor shortages could soon be a thing of the past.

Welcome the organoids: mini-organs that could save your or your family’s life one day…

 

But how do organoids work exactly? What can you do with organoids now, and which doors will they open for patients and healthcare in the future? They may sound like science fiction to you, but organoids are already transforming patients’ reality.

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Wall of Birds - Evolution and Diversity

Wall of Birds - Evolution and Diversity | Amazing Science | Scoop.it
Interact with the epic mural, spanning 243 birds and 375 million years, at the Cornell Lab of Ornithology

Via Guilhes Damian, Dr. Stefan Gruenwald
Guilhes Damian's curator insight, March 16, 2016 10:40 AM

Wall of Birds - evolution and diversity of birds around the world in a beautiful map

Andreas Maniatis's curator insight, March 17, 2016 5:31 AM

An exemplary Interactive Visual Narration about evolution and diversity in the world of the birds

Julien Tesgui's curator insight, March 17, 2016 8:17 PM

An exemplary Interactive Visual Narration about evolution and diversity in the world of the birds

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Blood-brain barrier–penetrating single CRISPR-Cas9 nanocapsules for effective and safe glioblastoma gene therapy

Blood-brain barrier–penetrating single CRISPR-Cas9 nanocapsules for effective and safe glioblastoma gene therapy | Amazing Science | Scoop.it

A team of scientists designed a unique nanocapsule for efficient single CRISPR-Cas9 encapsulation, noninvasive brain delivery and tumor cell targeting, and was able to demonstrate an effective and safe strategy for glioblastoma gene therapy. Their newly developed CRISPR-Cas9 nanocapsules can easily be produced by encapsulating the single Cas9/sgRNA complex within a glutathione-sensitive polymer shell incorporating a dual-action ligand that facilitates BBB penetration, tumor cell targeting, and Cas9/sgRNA selective release. These nanocapsules provide promising glioblastoma tissue targeting that led to high PLK1 gene editing efficiency in a brain tumor (up to 38.1%) with negligible (less than 0.5%) off-target gene editing in high-risk tissues.

 

Treatment with nanocapsules extended the median survival time (68 days versus 24 days) in mice. Thus, this new CRISPR-Cas9 delivery system addresses various delivery challenges to demonstrate safe and tumor-specific delivery of gene editing Cas9 ribonucleoprotein for improved glioblastoma treatment that may potentially be therapeutically useful for several other brain diseases.

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Quantum Computing Algorithm Could Lead to Design of New Materials

Quantum Computing Algorithm Could Lead to Design of New Materials | Amazing Science | Scoop.it

A team of researchers at Columbia University have developed a new algorithm that could help quantum computers calculate molecular energy and lead to the design of new materials. The algorithm uses the most quantum bits to date to calculate ground state energy, which is the lowest-energy state in a quantum mechanical system. 


The new study was published in Nature.


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Long, Noncoding RNA Dysregulation in Glioblastoma Multiforme (GBM)

Long, Noncoding RNA Dysregulation in Glioblastoma Multiforme (GBM) | Amazing Science | Scoop.it

A new study by Deforzh et al. (2022) demonstrates how two long non-coding RNAs (lncRNAs) link a distal enhancer to the HOXD3/D4/miR-10b gene promoter, leading to transcriptional activation of the therapeutic target miR-10b in glioblastoma multiforme (GBM).

 

Developing effective therapies for GBM, the most common primary brain cancer, remains challenging due to the heterogeneity within tumors and therapeutic resistance that drives recurrence. Noncoding RNAs are transcribed from a large proportion of the genome and remain largely unexplored in their contribution to the evolution of GBM tumors. The current knowledge of the general mechanisms of long, noncoding RNAs and the current knowledge of how these RNAs impact heterogeneity and therapeutic resistance in GBM is shown in this review. However, better understanding of the molecular drivers required for these aggressive tumors is necessary to improve the management and outcomes of this challenging disease.

 

Transcription occurs across more than 70% of the human genome and more than half of currently annotated genes produce functional noncoding RNAs. Of these transcripts, the majority—long, noncoding RNAs (lncRNAs)—are greater than 200 nucleotides in length and are necessary for various roles in the cell. It is increasingly appreciated that these lncRNAs are relevant in both health and disease states, with the brain expressing the largest number of lncRNAs compared to other organs. The cooperation between genetic and epigenetic alterations drives rapid adaptation that allows therapeutic evasion and recurrence of GBM. Given the large repertoire of lncRNAs in normal brain tissue and the well-described roles of lncRNAs in molecular and cellular processes, these transcripts are important to consider in the context of GBM heterogeneity and treatment resistance. It is hoped that a detailed understanding of lncRNAs and their role in GBM will lead to efficient RNA-based therapeutics, some of which are currently under development by various academic and industrial entities.

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Novel Haptics Device Creates Realistic Virtual Textures

Novel Haptics Device Creates Realistic Virtual Textures | Amazing Science | Scoop.it
USC Viterbi computer scientists have created a user-driven haptics search that can generate dead-ringers for real-world textures.

 

Tactile sensation is an incredibly important part of how humans perceive their reality. Haptics or devices that can produce extremely specific vibrations that can mimic the sensation of touch are a way to bring that third sense to life. However, as far as haptics have come, humans are incredibly particular about whether or not something feels 'right,' and virtual textures don't always hit the mark. Now, researchers at the USC Viterbi School of Engineering have developed a new method for computers to achieve that true texture -- with the help of human beings. Called a preference-driven model, the framework uses our ability to distinguish between the details of certain textures as a tool in order to give these virtual counterparts a tune-up.

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AI predicts patients’ race from their medical images and experts don't know how it is done

AI predicts patients’ race from their medical images and experts don't know how it is done | Amazing Science | Scoop.it
MIT researchers find artificial intelligence can pick out racial identity from medical images — even when no clear indication of race is present.

 

MIT scientists have investigated another important, largely underexplored modality: medical images. Using both private and public datasets, the team found that AI can accurately predict self-reported race of patients from medical images alone. Using imaging data of chest X-rays, limb X-rays, chest CT scans, and mammograms, the team trained a deep learning model to identify race as white, Black, or Asian — even though the images themselves contained no explicit mention of the patient’s race. This is a feat even the most seasoned physicians cannot do, and it’s not clear how the model was able to do this. 

 

In an attempt to tease out and make sense of the enigmatic “how” of it all, the researchers ran a slew of experiments. To investigate possible mechanisms of race detection, they looked at variables like differences in anatomy, bone density, resolution of images — and many more, and the models still prevailed with high ability to detect race from chest X-rays. “These results were initially confusing, because the members of our research team could not come anywhere close to identifying a good proxy for this task,” says paper co-author Marzyeh Ghassemi, an assistant professor in the MIT Department of Electrical Engineering and Computer Science and the Institute for Medical Engineering and Science (IMES), who is an affiliate of the Computer Science and Artificial Intelligence Laboratory (CSAIL) and of the MIT Jameel Clinic. “Even when you filter medical images past where the images are recognizable as medical images at all, deep models maintain a very high performance. That is concerning because superhuman capacities are generally much more difficult to control, regulate, and prevent from harming people.”

 

In a clinical setting, algorithms can help tell us whether a patient is a candidate for chemotherapy, dictate the triage of patients, or decide if a movement to the ICU is necessary. “We think that the algorithms are only looking at vital signs or laboratory tests, but it’s possible they’re also looking at your race, ethnicity, sex, whether you're incarcerated or not — even if all of that information is hidden,” says paper co-author Leo Anthony Celi, principal research scientist in IMES at MIT and associate professor of medicine at Harvard Medical School. “Just because you have representation of different groups in your algorithms, that doesn’t guarantee it won't perpetuate or magnify existing disparities and inequities. Feeding the algorithms with more data with representation is not a panacea. This paper should make us pause and truly reconsider whether we are ready to bring AI to the bedside.” 

 

The study, “AI recognition of patient race in medical imaging: a modeling study,” was published in Lancet Digital Health on May 11, 2022.

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Footage of hypersonic metallic UFO revealed by Pentagon officials at historic hearing

Footage of hypersonic metallic UFO revealed by Pentagon officials at historic hearing | Amazing Science | Scoop.it
Pentagon officials speaking at the first public hearing on UFOs since the 1960s have shown previously classified footage of an unidentified aerial phenomenon (UAP).

 

The first well-known UFO sighting occurred in 1947, when businessman Kenneth Arnold claimed to see a group of nine high-speed objects near Mount Rainier in Washington while flying his small plane. Arnold estimated the speed of the crescent-shaped objects as several thousand miles per hour and said they moved “like saucers skipping on water.” In the newspaper report that followed, it was mistakenly stated that the objects were saucer-shaped, hence the term flying saucer.

 

Sightings of unidentified aerial phenomena increased, and in 1948 the U.S. Air Force began an investigation of these reports called Project Sign. The initial opinion of those involved with the project was that the UFOs were most likely sophisticated Soviet aircraft, although some researchers suggested that they might be spacecraft from other worlds, the so-called extraterrestrial hypothesis (ETH). Within a year, Project Sign was succeeded by Project Grudge, which in 1952 was itself replaced by the longest-lived of the official inquiries into UFOs, Project Blue Book, headquartered at Wright-Patterson Air Force Base in DaytonOhio.

 

From 1952 to 1969 Project Blue Book compiled reports of more than 12,000 sightings or events, each of which was ultimately classified as (1) “identified” with a known astronomical, atmospheric, or artificial (human-caused) phenomenon or (2) “unidentified.” The latter category, approximately 6 percent of the total, included cases for which there was insufficient information to make an identification with a known phenomenon.

 

An American obsession with the UFO phenomenon was under way. In the hot summer of 1952 a provocative series of radar and visual sightings occurred near National Airport in Washington, D.C. Although these events were attributed to temperature inversions in the air over the city, not everyone was convinced by this explanation. Meanwhile, the number of UFO reports had climbed to a record high. This led the Central Intelligence Agency to prompt the U.S. government to establish an expert panel of scientists to investigate the phenomena. The panel was headed by H.P. Robertson, a physicist at the California Institute of Technology in PasadenaCalifornia, and included other physicists, an astronomer, and a rocket engineer. The Robertson Panel met for three days in 1953 and interviewed military officers and the head of Project Blue Book. They also reviewed films and photographs of UFOs. Their conclusions were that (1) 90 percent of the sightings could be easily attributed to astronomical and meteorologic phenomena (e.g., bright planets and starsmeteorsauroras, ion clouds) or to such earthly objects as aircraft, balloons, birds, and searchlights, (2) there was no obvious security threat, and (3) there was no evidence to support the ETH. Parts of the panel’s report were kept classified until 1979, and this long period of secrecy helped fuel suspicions of a government cover-up.

 

A second committee was set up in 1966 at the request of the Air Force to review the most interesting material gathered by Project Blue Book. Two years later this committee, which made a detailed study of 59 UFO sightings, released its results as Scientific Study of Unidentified Flying Objects—also known as the Condon Report, named for Edward U. Condon, the physicist who headed the investigation. The Condon Report was reviewed by a special committee of the National Academy of Sciences. A total of 37 scientists wrote chapters or parts of chapters for the report, which covered investigations of the 59 UFO sightings in detail. Like the Robertson Panel, the committee concluded that there was no evidence of anything other than commonplace phenomena in the reports and that UFOs did not warrant further investigation. This, together with a decline in sighting activity, led to the dismantling of Project Blue Book in 1969.

 

Despite the failure of the ETH to make headway with the expert committees, a few scientists and engineers, most notably J. Allen Hynek, an astronomer at Northwestern University in EvanstonIllinois, who had been involved with projects Sign, Grudge, and Blue Book, concluded that a small fraction of the most-reliable UFO reports gave definite indications for the presence of extraterrestrial visitors. Hynek founded the Center for UFO Studies (CUFOS), which continues to investigate the phenomenon. Another major U.S. study of UFO sightings was the Advanced Aviation Threat Identification Program (AATIP), a secret project that ran from 2007 to 2012. When the existence of the AATIP was made public in December 2017, the most newsworthy aspect of it was a report that the U.S. government possessed alloys and compounds purportedly attained from UFOs that were of unidentifiable nature, but many scientists remained skeptical about this claim.

 

Aside from the American efforts, the only other official and fairly complete records of UFO sightings were kept in Canada, where they were transferred in 1968 from the Canadian Department of National Defense to the Canadian National Research Council. The Canadian records comprised about 750 sightings. Less-complete records have been maintained in the United KingdomSwedenDenmarkAustralia, and Greece. In the United States, CUFOS and the Mutual UFO Network in Bellvue, Colorado, continue to log sightings reported by the public.

 

In the Soviet Union, sightings of UFOs were often prompted by tests of secret military rockets. In order to obscure the true nature of the tests, the government sometimes encouraged the public’s belief that these rockets might be extraterrestrial craft but eventually decided that the descriptions themselves might give away too much information. UFO sightings in China have been similarly provoked by military activity that is unknown to the public.

 

UFO reports have varied widely in reliability, as judged by the number of witnesses, whether the witnesses were independent of each other, the observing conditions (e.g., foghaze, type of illumination), and the direction of sighting. Typically, witnesses who take the trouble to report a sighting consider the object to be of extraterrestrial origin or possibly a military craft but certainly under intelligent control. This inference is usually based on what is perceived as formation flying by sets of objects, unnatural—often sudden—motions, the lack of sound, changes in brightness or colour, and strange shapes.

 

That the unaided eye plays tricks is well known. A bright light, such as the planet Venus, often appears to move. Astronomical objects can also be disconcerting to drivers, as they seem to “follow” the car. Visual impressions of distance and speed of UFOs are also highly unreliable because they are based on an assumed size and are often made against a blank sky with no background object (cloudsmountains, etc.) to set a maximum distance. Reflections from windows and eyeglasses produce superimposed views, and complex optical systems, such as camera lenses, can turn point sources of light into apparently saucer-shaped phenomena. Such optical illusions and the psychological desire to interpret images are known to account for many visual UFO reports, and at least some sightings are known to be hoaxes. Radar sightings, while in certain respects more reliable, fail to discriminate between artificial objects and meteor trails, ionized gas, rain, or thermal discontinuities in the atmosphere.

 

“Contact events,” such as abductions, are often associated with UFOs because they are ascribed to extraterrestrial visitors. However, the credibility of the ETH as an explanation for abductions is disputed by most psychologists who have investigated this phenomenon. They suggest that a common experience known as “sleep paralysis” may be the culprit, as this causes sleepers to experience a temporary immobility and a belief that they are being watched.

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NASA’s James Webb Space Telescope's Sharper View Hints at New Possibilities for Science

NASA’s James Webb Space Telescope's Sharper View Hints at New Possibilities for Science | Amazing Science | Scoop.it

NASA’s James Webb Space Telescope is aligned across all four of its science instruments, as seen in a previous engineering image showing the observatory’s full field of view. Now, we take a closer look at that same image, focusing on Webb’s coldest instrument: the Mid-Infrared Instrument, or MIRI. The MIRI test image (at 7.7 microns) shows part of the Large Magellanic Cloud. This small satellite galaxy of the Milky Way provided a dense star field to test Webb’s performance.

 

Here, a close-up of the MIRI image is compared to a past image of the same target taken with NASA’s Spitzer Space Telescope’s Infrared Array Camera (at 8.0 microns). The retired Spitzer telescope was one of NASA’s Great Observatories and the first to provide high-resolution images of the near- and mid-infrared universe. Webb, with its significantly larger primary mirror and improved detectors, will allow us to see the infrared sky with improved clarity, enabling even more discoveries.

For example, Webb’s MIRI image shows the interstellar gas in unprecedented detail. Here, you can see the emission from “polycyclic aromatic hydrocarbons,” or molecules of carbon and hydrogen that play an important role in the thermal balance and chemistry of interstellar gas. When Webb is ready to begin science observations, studies such as these with MIRI will help give astronomers new insights into the birth of stars and proto-planetary systems.

 

In the meantime, the Webb team has begun the process of setting up and testing Webb’s instruments to begin science observations this summer. Today at 11 a.m., Webb experts will preview these next two months of instrument preparations in a teleconference for media. Listen to the audio stream live at nasa.gov/live.

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NASA’s InSight Records Monster Quake on Mars

NASA’s InSight Records Monster Quake on Mars | Amazing Science | Scoop.it
Estimated to be magnitude 5, the quake is the biggest ever detected on another planet.

 

NASA’s InSight Mars lander has detected the largest quake ever observed on another planet: an estimated magnitude 5 temblor that occurred on May 4, 2022, the 1,222nd Martian day, or sol, of the mission. This adds to the catalog of more than 1,313 quakes InSight has detected since landing on Mars in November 2018. The largest previously recorded quake was an estimated magnitude 4.2 detected Aug. 25, 2021.

 

InSight was sent to Mars with a highly sensitive seismometer, provided by France’s Centre National d’Études Spatiales (CNES), to study the deep interior of the planet. As seismic waves pass through or reflect off material in Mars’ crust, mantle, and core, they change in ways that seismologists can study to determine the depth and composition of these layers. What scientists learn about the structure of Mars can help them better understand the formation of all rocky worlds, including Earth and its Moon.

 

A magnitude 5 quake is a medium-size quake compared to those felt on Earth, but it’s close to the upper limit of what scientists hoped to see on Mars during InSight’s mission. The science team will need to study this new quake further before being able to provide details such as its location, the nature of its source, and what it might tell us about the interior of Mars.

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Hubble Sheds Light on How Supermassive Black Holes Form

Hubble Sheds Light on How Supermassive Black Holes Form | Amazing Science | Scoop.it

Astronomers have identified a rapidly growing black hole in the early universe that is considered a crucial "missing link" between young star-forming galaxies and the first supermassive black holes. They used data from NASA's Hubble Space Telescope to make this discovery. Until now, the monster, nicknamed GNz7q, had been lurking unnoticed in one of the best-studied areas of the night sky, the Great Observatories Origins Deep Survey-North (GOODS-North) field.

 

 

Archival Hubble data from Hubble's Advanced Camera for Surveys helped the team determine that GNz7q existed just 750 million years after the big bang. The team obtained evidence that GNz7q is a newly formed black hole. Hubble found a compact source of ultraviolet (UV) and infrared light. This couldn't be caused by emission from galaxies, but is consistent with the radiation expected from materials that are falling onto a black hole. Rapidly growing black holes in dusty, early star-forming galaxies are predicted by theories and computer simulations, but had not been observed until now.

 

"Our analysis suggests that GNz7q is the first example of a rapidly growing black hole in the dusty core of a starburst galaxy at an epoch close to the earliest supermassive black hole known in the universe," explained Seiji Fujimoto, an astronomer at the Niels Bohr Institute of the University of Copenhagen and lead author of the Nature paper describing this discovery. "The object's properties across the electromagnetic spectrum are in excellent agreement with predictions from theoretical simulations."

 

One of the outstanding mysteries in astronomy today is: How did supermassive black holes, weighing millions to billions of times the mass of the Sun, get to be so huge so fast? Current theories predict that supermassive black holes begin their lives in the dust-shrouded cores of vigorously star-forming "starburst" galaxies before expelling the surrounding gas and dust and emerging as extremely luminous quasars. While extremely rare, both these dusty starburst galaxies and luminous quasars have been detected in the early universe.

 

The team believes that GNz7q could be a missing link between these two classes of objects. GNz7q has exactly both aspects of the dusty starburst galaxy and the quasar, where the quasar light shows the dust reddened color. Also, GNz7q lacks various features that are usually observed in typical, very luminous quasars (corresponding to the emission from the accretion disk of the supermassive black hole), which is most likely explained that the central black hole in GN7q is still in a young and less massive phase. These properties perfectly match with the young, transition phase quasar that has been predicted in simulations, but never identified at similarly high-redshift universe as the very luminous quasars so far identified up to a redshift of 7.6.

 

 

"GNz7q provides a direct connection between these two rare populations and provides a new avenue toward understanding the rapid growth of supermassive black holes in the early days of the universe," continued Fujimoto. "Our discovery provides an example of precursors to the supermassive black holes we observe at later epochs."

 
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Ocean water samples yield treasure trove of RNA virus data

Ocean water samples yield treasure trove of RNA virus data | Amazing Science | Scoop.it

Ocean water samples collected around the world have yielded a treasure trove of new data about RNA viruses, expanding ecological research possibilities and reshaping our understanding of how these small but significant submicroscopic particles evolved.

 

Combining machine-learning analyses with traditional evolutionary trees, an international team of researchers has identified 5,500 new RNA virus species that represent all five known RNA virus phyla and suggest there are at least five new RNA virus phyla needed to capture them.

 

The most abundant collection of newly identified species belong to a proposed phylum researchers named Taraviricota, a nod to the source of the 35,000 water samples that enabled the analysis: the Tara Oceans Consortium, an ongoing global study onboard the schooner Tara of the impact of climate change on the world's oceans.

 

"There's so much new diversity here -- and an entire phylum, the Taraviricota,were found all over the oceans, which suggests they're ecologically important," said lead author Matthew Sullivan, professor of microbiology at The Ohio State University. "RNA viruses are clearly important in our world, but we usually only study a tiny slice of them -- the few hundred that harm humans, plants and animals. We wanted to systematically study them on a very big scale and explore an environment no one had looked at deeply, and we got lucky because virtually every species was new, and many were really new."

 

The study appears online today (April 7, 2022) in Science. While microbes are essential contributors to all life on the planet, viruses that infect or interact with them have a variety of influences on microbial functions. These types of viruses are believed to have three main functions: killing cells, changing how infected cells manage energy, and transferring genes from one host to another. Knowing more about virus diversity and abundance in the world's oceans will help explain marine microbes' role in ocean adaptation to climate change, the researchers say. Oceans absorb half of the human-generated carbon dioxide from the atmosphere, and previous research by this group has suggested that marine viruses are the "knob" on a biological pump affecting how carbon in the ocean is stored.

 

By taking on the challenge of classifying RNA viruses, the team entered waters still rippling from earlier taxonomy categorization efforts that focused mostly on RNA viral pathogens. Within the biological kingdom Orthornavirae, five phyla were recently recognized by the International Committee on Taxonomy of Viruses (ICTV).

 

Though the research team identified hundreds of new RNA virus species that fit into those existing divisions, their analysis identified thousands more species that they clustered into five new proposed phyla: Taraviricota, Pomiviricota, Paraxenoviricota, Wamoviricota and Arctiviricota,which, like Taraviricota, features highly abundant species -- at least in climate-critical Arctic Ocean waters, the area of the world where warming conditions wreak the most havoc.

 

Sullivan's team has long cataloged DNA virus species in the oceans, growing the numbers from a few thousand in 2015 and 2016 to 200,000 in 2019. For those studies, scientists had access to viral particles to complete the analysis. In these current efforts to detect RNA viruses, there were no viral particles to study. Instead, researchers extracted sequences from genes expressed in organisms floating in the sea, and narrowed the analysis to RNA sequences that contained a signature gene, called RdRp, which has evolved for billions of years in RNA viruses, and is absent from other viruses or cells.

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Flying dinosaurs (pterosaurs) could change the color of their feathers, research study finds

Flying dinosaurs (pterosaurs) could change the color of their feathers, research study finds | Amazing Science | Scoop.it

An international team of paleontologists has discovered remarkable new evidence that pterosaurs, the flying relatives of dinosaurs, were able to control the color of their feathers using melanin pigments.The new study is based on analyses of a new 115 million year old fossilized headcrest of the pterosaur Tupandactylus imperator from north-eastern Brazil. Pterosaurs lived side by side with dinosaurs, 230 to 66 million years ago.  This species of pterosaur is famous for its bizarre huge headcrest. The team discovered that the bottom of the crest had a fuzzy rim of feathers, with short wiry hair-like feathers and fluffy branched feathers. 

 

“We didn’t expect to see this at all”, said Dr Cincotta. “For decades paleontologists have argued about whether pterosaurs had feathers. The feathers in our specimen close off that debate for good as they are very clearly branched all the way along their length, just like birds today”.  The team then studied the feathers with high-powered electron microscopes and found preserved melanosomes – granules of the pigment melanin. Unexpectedly, the new study shows that the melanosomes in different feather types have different shapes. 

 

“In birds today, feather color is strongly linked to melanosome shape.” said Prof. McNamara. “Since the pterosaur feather types had different melanosome shapes, these animals must have had the genetic machinery to control the colors of their feathers. This feature is essential for color patterning and shows that coloration was a critical feature of even the very earliest feathers.”

 

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Artificial neurons go quantum with photonic circuits

Artificial neurons go quantum with photonic circuits | Amazing Science | Scoop.it

In recent years, artificial intelligence has become ubiquitous, with applications such as speech interpretation, image recognition, medical diagnosis, and many more. At the same time, quantum technology has been proven capable of computational power well beyond the reach of even the world’s largest supercomputer.

 

Quantum physicists at the University of Vienna have now demonstrated a new device, called quantum memristor, which may allow to combine these two worlds, thus unlocking unprecedented capabilities. The experiment, carried out in collaboration with the National Research Council (CNR) and the Politecnico di Milano in Italy, has been realized on an integrated quantum processor operating on single photons. The work is published in the current issue of the journal "Nature Photonics".

 

At the heart of all artificial intelligence applications are mathematical models called neural networks. These models are inspired by the biological structure of the human brain, made of interconnected nodes. Just like our brain learns by constantly rearranging the connections between neurons, neural networks can be mathematically trained by tuning their internal structure until they become capable of human-level tasks: recognizing our face, interpreting medical images for diagnosis, even driving our cars. Having integrated devices capable of performing the computations involved in neural networks quickly and efficiently has thus become a major research focus, both academic and industrial.

 

One of the major game changers in the field was the discovery of the memristor, made in 2008. This device changes its resistance depending on a memory of the past current, hence the name memory-resistor, or memristor. Immediately after its discovery, scientists realized that (among many other applications) the peculiar behavior of memristors was surprisingly similar to that of neural synapses. The memristor has thus become a fundamental building block of neuromorphic architectures.

 

By using single photons, i.e. single quantum particles of lights, and exploiting their unique ability to propagate simultaneously in a superposition of two or more paths, the physicists have overcome the challenge. In their experiment, single photons propagate along waveguides laser-written on a glass substrate and are guided on a superposition of several paths. One of these paths is used to measure the flux of photons going through the device and this quantity, through a complex electronic feedback scheme, modulates the transmission on the other output, thus achieving the desired memristive behavior. Besides demonstrating the quantum memristor, the researchers have provided simulations showing that optical networks with quantum memristor can be used to learn on both classical and quantum tasks, hinting at the fact that the quantum memristor may be the missing link between artificial intelligence and quantum computing.

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How Do Gene Drives Work?

How Do Gene Drives Work? | Amazing Science | Scoop.it

Synthetic gene drive technology is a method of genetic engineering through which certain desired traits can be introduced to almost all individuals in a population. Researchers can either eliminate a species or alter the genetic makeup of living organisms through gene drive technology. Most gene drives are genetic elements that can quickly spread through populations of organisms and have nearly a 100% chance of passing the genes they carry to the next generation. 


How are gene drives generated?

Naturally occurring gene drives are found in almost all animals, including humans, plants, fungi and bacteria. They are selfish genetic elements that spread through inheritance from one generation to another. For example, homing endonuclease genes (HEGs) are site-specific selfish genes that spread by cleaving a homologous wild-type chromosome and copying themselves into the cut site through homology-directed repair (HDR). Meiotic drive is an intragenomic mechanism that interferes with meiotic processes so that the transmission of one or more alleles is favored over another. Manipulation of transposable elements, i.e., small DNA sequences that can move from one location in the genome to another, can also generate gene drives.

 

Earlier attempts to generate synthetic gene drives involved gene-editing techniques such as zinc-finger nucleases (ZFNs) and transcription activator-like effector nucleases (TALENs). However, mutations occurring in the repetitive elements limited the use of these technologies for the generation of gene drives, as they were often inactivated before being passed on to the next generation.

How do CRISPR-Cas9 gene drives work?

CRISPR-Cas9 gene drives consist of a drive allele, i.e., a genetic construct carrying genes encoding the desired trait, Cas9, and a guide RNA (gRNA), as well as flanking arms homologous to the sequences surrounding the target site in the wild type chromosome. When a homozygous gene drive-modified individual mates with an unmodified individual, the resulting offspring inherits one drive allele from the gene drive-modified parent and one non-modified version of the corresponding allele from the wild-type parent. The gRNA and the Cas9 genes are subsequently expressed in the cell, and the gRNA guides Cas9 to make a double-strand break in the wild-type chromosome at the target site. The drive allele then acts as a template for HDR, and the entire drive allele - including the gene of interest - is inserted into the wild-type chromosome. The cell is now homozygous for the drive allele, which will be passed to all gametes after meiosis, thus spreading the desired trait in the population.

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Scientists create an algorithm to assign a label to every pixel in the world, without human supervision

Scientists create an algorithm to assign a label to every pixel in the world, without human supervision | Amazing Science | Scoop.it

Labeling data can be a chore. It's the main source of sustenance for computer-vision models; without it, they'd have a lot of difficulty identifying objects, people, and other important image characteristics. Yet producing just an hour of tagged and labeled data can take a whopping 800 hours of human time. Our high-fidelity understanding of the world develops as machines can better perceive and interact with our surroundings. But they need more help.

 

Scientists from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), Microsoft, and Cornell University have attempted to solve this problem plaguing vision models by creating "STEGO," an algorithm that can jointly discover and segment objects without any human labels at all, down to the pixel.

 

STEGO learns something called "semantic segmentation"—fancy speak for the process of assigning a label to every pixel in an image. Semantic segmentation is an important skill for today's computer-vision systems because images can be cluttered with objects. Even more challenging is that these objects don't always fit into literal boxes; algorithms tend to work better for discrete "things" like people and cars as opposed to "stuff" like vegetation, sky, and mashed potatoes. A previous system might simply perceive a nuanced scene of a dog playing in the park as just a dog, but by assigning every pixel of the image a label, STEGO can break the image into its main ingredients: a dog, sky, grass, and its owner.

 

Assigning every single pixel of the world a label is ambitious—especially without any kind of feedback from humans. The majority of algorithms today get their knowledge from mounds of labeled data, which can take painstaking human-hours to source. Just imagine the excitement of labeling every pixel of 100,000 images. To discover these objects without a human's helpful guidance, STEGO looks for similar objects that appear throughout a dataset. It then associates these similar objects together to construct a consistent view of the world across all of the images it learns from.

 

Seeing the world

Machines that can "see" are crucial for a wide array of new and emerging technologies like self-driving cars and predictive modeling for medical diagnostics. Since STEGO can learn without labels, it can detect objects in many different domains, even those that humans don't yet understand fully.

 

"If you're looking at oncological scans, the surface of planets, or high-resolution biological images, it's hard to know what objects to look for without expert knowledge. In emerging domains, sometimes even human experts don't know what the right objects should be," says Mark Hamilton, a Ph.D. student in electrical engineering and computer science at MIT, research affiliate of MIT CSAIL, software engineer at Microsoft, and lead author on a new paper about STEGO. "In these types of situations where you want to design a method to operate at the boundaries of science, you can't rely on humans to figure it out before machines do."

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First Covid-19 Breath Test Authorized by FDA

First Covid-19 Breath Test Authorized by FDA | Amazing Science | Scoop.it

The US Food and Drug Administration has granted emergency use authorization to the first Covid-19 test that spots chemical compounds associated with the coronavirus in breath, the agency said Thursday.  The FDA said the InspectIR Covid-19 Breathalyzer, which is about the size of a piece of carry-on luggage, can be used in medical offices and mobile testing sites. It can give results in less than three minutes. The system separates and identifies chemical mixtures to detect five compounds associated with SARS-CoV-2 infection.

 

A study of the InspectIR Breathalyzer found that it accurately identified more than 91% of positive samples and nearly 100% of negative samples. Similar sensitivity was found in another study that focused on the Omicron coronavirus variant. However, a positive result should be confirmed with a PCR test, the FDA said. "It's another tool, and the FDA announcement suggests it's reasonably accurate and a relatively user-friendly tool," Dr. Emily Volk, president of the College of American Pathologists, a board-certified anatomic and clinical pathologist, said Friday. "It waits to be seen how widely this will be adopted," Volk said. "That could rely on how expensive it is." In an email to CNN on Friday, InspectIR Systems said it is not releasing the price of the machine or when it will be available. 

 

The agency's authorization "is yet another example of the rapid innovation occurring with diagnostic tests for COVID-19," Dr. Jeff Shuren, director of the FDA's Center for Devices and Radiological Health, said in a statement. "The FDA continues to support the development of novel COVID-19 tests with the goal of advancing technologies that can help address the current pandemic and better position the U.S. for the next public health emergency."

 

FDA Press Release (April 14, 2022):

https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-first-covid-19-diagnostic-test-using-breath-samples 

 

FDA Letter of Authorization (April 14, 2022):

https://www.fda.gov/media/157720/download?utm_medium=email&utm_source=govdelivery 


Via Juan Lama
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