Developed by an international collaboration led by Northwestern University, the new system automates the entire search for new supernovae across the night sky—effectively removing humans from the process. Not only does this rapidly accelerate the process of analyzing and classifying new supernova candidates, it also bypasses human error.
The team alerted the astronomical community to the launch and success of the new tool, called the Bright Transient Survey Bot (BTSbot), this week. In the past six years, humans have spent an estimated total of 2,200 hours visually inspecting and classifying supernova candidates. With the new tool now officially online, researchers can redirect this precious time toward other responsibilities in order to accelerate the pace of discovery.
"For the first time ever, a series of robots and AI algorithms has observed, then identified, then communicated with another telescope to finally confirm the discovery of a supernova," said Northwestern's Adam Miller, who led the work. "This represents an important step forward as further refinement of models will allow the robots to isolate specific subtypes of stellar explosions. Ultimately, removing humans from the loop provides more time for the research team to analyze their observations and develop new hypotheses to explain the origin of the cosmic explosions that we observe. We achieved the world's first fully automatic detection, identification and classification of a supernova," added Northwestern's Nabeel Rehemtulla, who co-led the technology development with Miller.
"This significantly streamlines large studies of supernovae, helping us better understand the life cycles of stars and the origin of elements supernovae create, like carbon, iron and gold." Miller is an assistant professor of physics and astronomy at Northwestern's Weinberg College of Arts and Sciences and a member of the Center for Interdisciplinary Exploration and Research in Astrophysics (CIERA). Rehemtulla is an astronomy graduate student in Miller's research group.
Researchers at North Carolina State University and global collaborators have mapped the mosquito's tree of life, a major step toward understanding important traits, such as how the insects choose their hosts, feed on blood and spread disease. The findings will help researchers make better predictions to model disease transmission and understand what makes some mosquitoes better disease carriers than others.
The research suggests that mosquito evolution over the past 200 million years mirrors the Earth's history of shifting land masses and changing host organisms, says Dr. Brian Wiegmann, William Neal Reynolds Professor of Entomology at NC State and corresponding author of a paper describing the mosquito family tree, published in Nature Communications.
"This ongoing project builds a big-data resource that mines the academic literature with published observations of the sources of blood mosquitoes drink, from animals as diverse as fish to humans," Wiegmann said. "It focuses explicitly on data collection to infer aspects of mosquito biology in a contextualized way. That means linking up the family, or phylogenetic, tree with the narrative of life on Earth: geologic history, climate history and organism history."
While the researchers pored over the academic literature to capture as much published information about mosquitoes as possible, new genomic sequencing techniques also allowed them to take decades-old mosquitoes—some held in place by pins inside insect collections—and capture a great deal of information on their genetic similarities from just fragments of their genetic blueprints, or genomes.
"A lot of research goes into the important mosquitoes and there's not much known about the incredible mosquito diversity across the globe," Wiegmann said. "We now have the tools to sample genetic information more rapidly and very thoroughly. And so the time was right to take a big stab at putting the disease vectors and the well-known mosquitoes into the context they evolved in."
Piecing the genetic and published information together gave the researchers a few notable findings and these can be evaluated against current patterns and distributions. Mosquitoes are an ancient group—around 217 million years old—that probably originated in South America before it was South America, on one big land mass called Gondwana that hadn't yet split apart. "Major events like continental drift certainly influenced the diversification of mosquitoes," Wiegmann said.
Skin organoids offer a powerful platform for drug discovery in the ongoing fight against the virus formerly known as monkeypox. A new model system for studying mpox virus infections in the laboratory is providing valuable insights into the virus's mechanisms of attack on skin cells, offering a potential catalyst in the quest to discover innovative drugs to combat this emerging pathogen. An international research team that included KAUST scientists has demonstrated that lab-grown human skin — stem cell-derived 3D structures called organoids — can effectively facilitate the active replication of mpox virus, the virus formerly known as monkeypox virus, that spread rapidly during a major outbreak in 2022.
"Researchers can now use this model to study how the mpox virus causes disease and to test new therapeutics," says Intikhab Alam, a bioinformatician who contributed to the study along with his colleague Roberto Incitti, both from KAUST.
People infected with the mpox virus typically develop rashes and skin lesions, often leading to scarring and disfigurement — and the lab-grown skin organoids now help show why. KAUST's Alam and Incitti collaborated with Qiuwei Abdullah Pan and his team from the Erasmus MC-University Medical Center in Rotterdam to report that the virus takes up residence inside keratinocytes, the predominant cell type in the skin's outer layer. There, the virus undergoes its four steps of assembly, a process that the researchers could observe under high-power microscopes.
Gene expression analyses conducted by the researchers revealed that numerous viral genes become activated in the days following infection. This activation, in turn, appears to induce changes in host cells, leading to alterations in the activity of multiple human genes associated with immunity and cell death. These genetic alterations likely compromise the skin's protective barrier, resulting in the characteristic lesions observed in infected people. The observed effects could be reversed through use of an antiviral drug called tecovirimat.
In the infected organoids, this drug proved highly effective in halting virus replication and thwarting the subversion of host cells. The findings validate the mpox-inhibiting potential of tecovirimat, a drug approved to treat infections with the related smallpox virus. They also underscore the potential of the organoid system as a versatile platform with which to screen for novel substances with similar properties. Notably, the impact of mpox extends beyond skin-related issues. In severe cases, the virus can wreak havoc on internal organs. The same KAUST-affiliated research team previously developed a kidney organoid system designed to study mpox infections in renal tissues. Other groups have investigated mpox dynamics within colon and brain organoids. Collectively, the efforts in organoid models — which the KAUST researchers and their collaborators are now extending to other viral infection systems as well — should "help to combat the current mpox outbreak and enhance pandemic preparedness for the future," Incitti says.
Studies published in Nature Microbiology (Oct. 13, 2023):
The reaction-diffusion principle imagined by Alan Turing in an attempt to explain the structuring of living organisms is leveraged in this recent work for the procedural synthesis of radiating metasurfaces. The adaptation of this morphogenesis technique ensures the growth of anisotropic cellular patterns automatically arranged to satisfy local electromagnetic constraints, facilitating the radiation of waves controlled in frequency, space, and polarization.
Experimental validations of this method are presented, designing morphogenetic metasurfaces radiating far-field circularly polarized beams and generating a polarization-multiplexed hologram in the radiative near-field zone. The exploitation of morphogenesis-inspired models proves particularly well suited for solving generative design problems, converting global physical constraints into local interactions of simulated chemical reactants ensuring the emergence of self-organizing meta-atoms.
ALPHA-g determines that antimatter falls downwards as expected. It took longer than anticipated, but now we have the result. Observation of the effect of gravity on the motion of antimatter: Antimatter falls down with (0.75 ± 0.13 (statistical + systematic) ± 0.16 (simulation)) g, compatible with the expected 1 g and ruling out -1 g.
Einstein’s general theory of relativity from 19151 remains the most successful description of gravitation. From the 1919 solar eclipse2 to the observation of gravitational waves3, the theory has passed many crucial experimental tests. However, the evolving concepts of dark matter and dark energy illustrate that there is much to be learned about the gravitating content of the universe.
Singularities in the general theory of relativity and the lack of a quantum theory of gravity suggest that our picture is incomplete. It is thus prudent to explore gravity in exotic physical systems. Antimatter was unknown to Einstein in 1915.
Dirac’s theory4 appeared in 1928; the positron was observed5 in 1932. There has since been much speculation about gravity and antimatter. The theoretical consensus is that any laboratory mass must be attracted6 by the Earth, although some authors have considered the cosmological consequences if antimatter should be repelled by matter7,8,9,10. In the general theory of relativity, the weak equivalence principle (WEP) requires that all masses react identically to gravity, independent of their internal structure.
Scientists now show that antihydrogen atoms, released from magnetic confinement in the ALPHA-g apparatus, behave in a way consistent with gravitational attraction to the Earth. Repulsive ‘antigravity’ is ruled out in this case. This experiment paves the way for precision studies of the magnitude of the gravitational acceleration between anti-atoms and the Earth to test the WEP.
The gyroid was discovered in 1970 by NASA scientist Alan Schoen. He calculated the angle of association and gave a convincing demonstration of pictures of intricate plastic models, but did not provide a proof of embeddedness. Schoen noted that the gyroid contains neither straight lines nor planar symmetries. Karcher gave a different, more contemporary treatment of the surface in 1989 using conjugate surface construction. In 1996 Große-Brauckmann and Wohlgemuth proved that it is embedded, and in 1997 Große-Brauckmann provided CMC (constant mean curvature) variants of the gyroid and made further numerical investigations about the volume fractions of the minimal and CMC gyroids.
The gyroid separates space into two oppositely congruent labyrinths of passages. The gyroid has space groupI4132 (no. 214). Channels run through the gyroid labyrinths in the (100) and (111) directions; passages emerge at 70.5 degree angles to any given channel as it is traversed, the direction at which they do so gyrating down the channel, giving rise to the name "gyroid". One way to visualize the surface is to picture the "square catenoids" of the P surface (formed by two squares in parallel planes, with a nearly circular waist); rotation about the edges of the square generate the P surface. In the associate family, these square catenoids "open up" (similar to the way the catenoid "opens up" to a helicoid) to form gyrating ribbons, then finally become the Schwarz D surface. For one value of the associate family parameter the gyrating ribbons lie in precisely the locations required to have an embedded surface.
EVEscape uses evolutionary and biological information to predict how a virus could change to escape the immune system.
The COVID-19 pandemic seemed like a never-ending parade of SARS-CoV-2 variants, each equipped with new ways to evade the immune system, leaving the world bracing for what would come next. But what if there were a way to make predictions about new viral variants before they actually emerge?
A new artificial intelligence tool named EVEscape, developed by researchers at Harvard Medical School and the University of Oxford, can do just that. The tool has two elements: A model of evolutionary sequences that predicts changes that can occur to a virus, and detailed biological and structural information about the virus. Together, they allow EVEscape to make predictions about the variants most likely to occur as the virus evolves.
In a recent study published in Nature, the researchers show that had it been deployed at the start of the COVID-19 pandemic, EVEscape would have predicted the most frequent mutations and identified the most concerning variants for SARS-CoV-2. The tool also made accurate predictions about other viruses, including HIV and influenza. The researchers are now using EVEscape to look ahead at SARS-CoV-2 and predict future variants of concern; every two weeks, they release a ranking of new variants. Eventually, this information could help scientists develop more effective vaccines and therapies. The team is also broadening the work to include more viruses.
“We wanted to know if we can anticipate the variation in viruses and forecast new variants — because if we can, that’s going to be extremely important for designing vaccines and therapies,” said senior author Debora Marks, professor of systems biology in the Blavatnik Institute at HMS.
From EVE to EVEscape
The researchers first developed EVE, short for evolutionary model of variant effect, in a different context: gene mutations that cause human diseases. The core of EVE is a generative model that learns to predict the functionality of proteins based on large-scale evolutionary data across species.
“Viruses are flexible — it’s almost like they’ve evolved to evolve.”
explains Debora Marks, Blavatnik Institute at Harvard Medical School. “You can use these generative models to learn amazing things from evolutionary information — the data have hidden secrets that you can reveal,” Marks said.
As the COVID-19 pandemic hit and progressed, the world was caught off guard by SARS-CoV-2’s impressive ability to evolve. The virus kept morphing, changing its structure in ways subtle and substantial to slip past vaccines and therapies designed to defeat it. “We underestimate the ability of things to mutate when they’re under pressure and have a large population in which to do so,” Marks said. “Viruses are flexible — it’s almost like they’ve evolved to evolve.”
Watching the pandemic unfold, Marks and her team saw an opportunity to help: They rebuilt EVE into a new tool called EVEscape for the purpose of predicting viral variants. They took the generative model from EVE — which can predict mutations in viral proteins that won’t interfere with the virus’s function — and added biological and structural details about the virus, including information about regions most easily targeted by the immune system.
“We’re taking biological information about how the immune system works and layering it on our learnings from the broader evolutionary history of the virus,” explained co-lead author Nicole Thadani, a former research fellow in the Marks lab.
Artificial intelligence takes a lot of compute power, and Microsoft is putting together a road map for powering that computation with small nuclear reactors. That’s according to a job description Microsoft posted Thursday seeking a nuclear technology expert to lead the company’s technical assessment for integrating small modular nuclear reactors and microreactors “to power the datacenters that the Microsoft Cloud and AI reside on,” the job posting reads.
Specifically, Microsoft is looking to hire a “principal program manager for nuclear technology” and that person “will be responsible for maturing and implementing a global Small Modular Reactor (SMR) and microreactor energy strategy,” the job posting reads. Microsoft is looking to generate energy with nuclear fission, which is when an atom splits and releases energy as a result of that splitting.
News of this job description was first reported on DCD, a website about data centers. In January 2023, Microsoft announced a multiyear, multibillion-dollar investment in OpenAI, maker of viral AI chatbot ChatGPT. Bill Gates, Microsoft’s co-founder, is also the chairman of the board of TerraPower, a nuclear innovation company in the process of developing and scaling small modular reactor designs. TerraPower “does not currently have any agreements to sell reactors to Microsoft,” a spokesperson told CNBC. However, Microsoft has publicly committed to pursuing nuclear energy from an innovator in the fusion space.
In May, Microsoft announced it signed a power purchase agreement with Helion, a nuclear fusion startup, to buy electricity from it in 2028. Sam Altman, CEO of OpenAI, is an early and significant investor in Helion. Nuclear fusion occurs when two smaller atomic nuclei smash together to form a heavier atom and release tremendous quantities of energy in the process. It is the way in which the sun makes power. Fusion has not yet been recreated at scale here on earth, but many venture-backed startups are working to make it a reality due to the potential promise of virtually unlimited clean energy.
Interest in nuclear energy has increased alongside concerns about climate change in recent years, as nuclear reactors generate electricity without releasing virtually any carbon dioxide emissions.
The existing fleet of nuclear reactors in the U.S. was largely built between 1970 and 1990, and currently generates about 18% of the total electricity in the U.S., according to the U.S. Energy Information Administration. Nuclear energy also makes up 47% of America’s carbon-free electricity in 2022, according to the U.S. Department of Energy.
Much of the hope for the next generation of nuclear reactor technology in the U.S. is pinned on smaller nuclear reactors, which Microsoft’s job posting indicates the company is interested in using to power its data centers.
Germinal centers (GCs) are distinct microanatomical structures that form in the secondary lymphoid organs of endothermic vertebrates (i.e., mammals and some birds). Within GCs, B cells undergo a Darwinian selection process to identify clones which can respond to pathogen insult as well as affinity mature the B cell repertoire. The GC response ultimately generates memory B cells and bone marrow plasma cells which facilitate humoral immunological memory, the basis for successful vaccination programs.
GCs have not been observed in the secondary lymphoid organs of ectothermic jawed vertebrates (i.e., fishes, reptiles, and amphibians). However, abundant research over the past decades has indicated these organisms can produce antigen specific B cell responses and some degree of affinity maturation.
This current review examines data demonstrating that the fundamentals of B cell selection may be more conserved across vertebrate phylogeny than previously anticipated. Further, research in both conventional mammalian model systems and comparative models raises the question of what evolutionary benefit GCs provide endotherms if they are seemingly unnecessary for generating the basic functional components of jawed vertebrate humoral adaptive immune responses.
Using the full capabilities of the Quantinuum H1-1 quantum computer, researchers from the Department of Energy's Oak Ridge National Laboratory not only demonstrated best practices for scientific computing on current quantum systems but also produced an intriguing scientific result. By modeling singletfission—in which absorption of a single photon of light by a molecule produces two excited states—the team confirmed that the linear H4 molecule's energetic levels match the fission process's requirements. The linear H4 molecule is, simply, a molecule made of four hydrogen atoms arranged in a linear fashion.
A molecule's energetic levels are the energies of each quantum state involved in a phenomenon, such as singlet fission, and how they relate and compare with one another. The fact that the linear molecule's energetic levels are conducive to singlet fission could prove to be useful knowledge in the overall effort to develop more efficient solar panels.
"This is one of the leading motivating factors behind singlet fission—conventional solar cells have a theoretical maximum efficiency of about 33%, but it has been postulated that materials that exhibit singlet fission can break that limit and can be more efficient," said Daniel Claudino, a research scientist in ORNL's Quantum Computational Science group and the project's principal investigator. "The downside is that to understand fundamentally whether a certain material exhibits singlet fission is very hard. There is a specific energetic requirement, and it's difficult to find materials that fulfill it."
With its high accuracy for a manageable computational cost, the ORNL team's approach to using a quantum computer provides an effective simulation method to identify molecules that demonstrate singlet fission properties while bypassing approximations commonly found in techniques used for classical computers. The results of its work were published in The Journal of Physical Chemistry Letters.
Singlet fission is a multistate phenomenon, so the ORNL team needed a computational method that could describe all the process's quantum states on an equal footing to calculate accurate energetics numbers. They turned to PDS, which is a quantum solver based on the Peeters-Devreese-Soldatov approach and developed at Pacific Northwest National Laboratory.
Previous research has indicated that when flying at night, birds (and many other animals) use Earth's magnetic field for navigation. Because solar events disrupt the magnetic field — as well as produce auroras — birds have more difficulty navigating during them. The new study analyzed images taken from 37 NEXRAD Doppler weather radar stations, which can detect groups of migrating birds, as well as data from ground-based magnetometers, to study 23 years of bird migration across the U.S. Great Plains. The 1,000-mile (1,600-kilometer) span from North Dakota to Texas is considered a major migratory corridor for birds.
"The biggest challenge was trying to distill such a large dataset — years and years of ground magnetic field observations — into a geomagnetic disturbance index for each radar site," Daniel Welling, University of Michigan space scientist said in a statement. "There was a lot of heavy lifting in terms of assessing data quality and validating our final data product to ensure that it was appropriate for this study."
The work paid off. The researchers discovered that the number of migrating birds in this region decreases by 9 to 17 percent during severe space weather events. They also noticed increased rates of birds becoming lost during migration, a phenomenon known as migratory bird vagrancy.
The researchers posit four stages of Earth's past and possible future to illustrate how planetary intelligence might play a role in humanity's long-term future. They also show how these stages of evolution driven by planetary intelligence may be a feature of any planet in the galaxy that evolves life and a sustainable technological civilization.
Stage 1—Immature biosphere: Characteristic of very early Earth, billions of years ago and before a technological species, when microbes were present but vegetation had not yet come about. There were few global feedbacks because life couldn't exert forces on Earth's atmosphere, hydrosphere, and other planetary systems.
Stage 2—Mature biosphere: Characteristic of Earth, also before a technological species, from about 2.5 billion to 540 million years ago. Stable continents formed, vegetation and photosynthesis developed, oxygen built up in the atmosphere, and the ozone layer emerged. The biosphere exerted a strong influence on the Earth, perhaps helping to maintain Earth's habitability.
Stage 3—Immature technosphere: Characteristic of Earth now, with interlinked systems of communication, transportation, technology, electricity, and computers. The technosphere is still immature, however, because it is not integrated into other Earth systems, such as the atmosphere. Instead, it draws matter and energy from Earth's systems in ways that will drive the whole into a new state that likely doesn't include the technosphere itself. Our current technosphere is, in the long run, working against itself.
Stage 4—Mature technosphere: Where Earth should aim to be in the future, Frank says, with technological systems in place that benefit the entire planet, including globally harvesting energy in forms like solar that do not harm the biosphere. The mature technosphere is one that has co-evolved with the biosphere into a form that allows both the technosphere and the biosphere to thrive.
"Planets evolve through immature and mature stages, and planetary intelligence is indicative of when you get to a mature planet," Frank says. "The million-dollar question is figuring out what planetary intelligence looks like and means for us in practice because we don't know how to move to a mature technosphere yet."
The complex system of planetary intelligence Although we don't yet know specifically how planetary intelligence might manifest itself, the researchers note that a mature technosphere involves integrating technological systems with Earth through a network of feedback loops that make up a complex system.
Put simply, a complex system is anything built from smaller parts that interact in such a fashion that the overall behavior of the system is entirely dependent on the interaction. That is, the sum is more than the whole of its parts. Examples of complex systems include forests, the Internet, financial markets, and the human brain.
By its very nature, a complex system has entirely new properties that emerge when individual pieces are interacting. It is difficult to discern the personality of a human being, for instance, solely by examining the neurons in her brain.
That means it is difficult to predict exactly what properties might emerge when individuals form a planetary intelligence. However, a complex system like planetary intelligence will, according to the researchers, have two defining characteristics: It will have emergent behavior and will need to be self-maintaining.
"The biosphere figured out how to host life by itself billions of years ago by creating systems for moving around nitrogen and transporting carbon," Frank says. "Now we have to figure out how to have the same kind of self-maintaining characteristics with the technosphere."
If new particles are out there, the Large Hadron Collider (LHC) is the ideal place to search for them.
The theory of supersymmetry suggests that a whole new family of partner particles exists for each of the known fundamental particles. While this might seem extravagant, these partner particles could address various shortcomings in current scientific knowledge, such as the source of the mysterious dark matter in the Universe, the “unnaturally” small mass of the Higgs boson, the anomalous way that the muon spins and even the relationship between the various forces of nature. But if these supersymmetric particles exist, where might they be hiding?
This is what physicists at the LHC have been trying to find out, and in a recent study of proton–proton collision data from Run 2 of the LHC (2015–2018), the ATLAS collaboration provides the most comprehensive overview yet of its searches for some of the most elusive types of supersymmetric particles – those that would only rarely be produced through the “weak” nuclear force or the electromagnetic force. The lightest of these weakly interacting supersymmetric particles could be the source of dark matter.
The increased collision energy and the higher collision rate provided by Run 2, as well as new search algorithms and machine-learning techniques, have allowed for deeper exploration into this difficult-to-reach territory of supersymmetry.
ATLAS physicists have pulled together results from eight searches, each seeking evidence for supersymmetric particles in a different way. The combined power and sensitivity of the different search strategies has allowed ATLAS researchers to study tens of thousands of supersymmetry models, each with different predictions about the masses of supersymmetric particles.
These ATLAS searches have unprecedented sensitivity and explore a wide range of supersymmetric-particle masses. The ATLAS physicists looked for evidence of “lab-made” dark matter – that is, dark matter created in LHC collisions. Their searches have proved complementary to other experiments seeking natural, “relic” dark matter left over from the Big Bang. Unlike collider searches, which don’t need to see the dark matter to infer its presence, the latter experiments rely on the sufficiently large probability of dark matter particles hitting normal materials and therefore being detected.
One of the most significant findings of this combination of searches is that some regions for supersymmetric-particle masses that were previously viewed favourably, where the dark matter particle has about half the mass of the Z boson or the Higgs boson, have now been almost totally ruled out.
Another benefit of such a comprehensive study is an understanding of which supersymmetry models have not yet been probed. ATLAS has presented examples of such surviving models, which can be used to optimise future searches. Though possible hiding places for supersymmetric particles are being systematically reduced, many models remain stubbornly evasive.
Improving the sensitivity of ATLAS searches to these models will require more collision data and further clever developments in search strategy.
The U.S. Fish and Wildlife Service on Monday finalized a rule removing 21 species from the list of threatened and endangered species under the Endangered Species Act because of extinction, including a tiny fish found only in Texas.
The San Marcos gambusia hasn’t been seen since 1983. The tiny species of fish was once found in only a half-mile stretch of the San Marcos River.
It joins a list of species that includes eight types of honeycreepers from Hawaii, the bridled white-eye and the little Mariana fruit bat from Guam, and nine southeastern mussels found mostly in the South.
A new Penn Medicine study finds components of the SARS-CoV-2 virus remain in the gut of some long COVID patients, causing persistent inflammation, vagus nerve dysfunction, and neurological symptoms. Patients with long COVID—the long-term symptoms like brain fog, fatigue, or memory loss in the months or years following COVID-19—can exhibit a reduction in circulating levels of the neurotransmitter serotonin, according to new research published in Cell. The study, led by researchers from the Perelman School of Medicine, sheds new light on the mechanisms of how persistent inflammation after contracting the SARS-CoV-2 virus can cause long-term neurological symptoms. “Many aspects of the basic biology underlying long COVID have remained unclear. As a result, we are lacking effective tools for the diagnosis and treatment of the disease,” says senior author Maayan Levy,an assistant professor of microbiology at Penn Medicine. “Our findings may not only help to untangle some of the mechanisms that contribute to long COVID, but also provide us with biomarkers that can help clinicians diagnose patients and objectively measure their response to individual treatments.”
In a collaboration between Penn’s departments of Microbiology, Pathology and Laboratory Medicine, and Physical Medicine and Rehabilitations’Post COVID Assessment and Recovery Clinic, researchers evaluated the effects of long COVID in blood and stool samples from various clinical studies and in small animal models. The researchers found that when tryptophan absorption is reduced by persistent viral inflammation, serotonin is depleted, leading to disrupted vagus nerve signaling, which in turn can cause several of the symptoms associated with long COVID, such as memory loss. “Clinicians treating patients with long COVID have been relying on personal reports from those patients to determine if their symptoms are improving. Now, our research shows that there are biomarkers we may be able to use to match patients to treatments or clinical trials that address the specific causes of their long COVID symptoms, and more effectively assess their progress,” says co-senior author, Sara Cherry, a professor of pathology and laboratory medicine. The authors took this insight one step further, to identify if replenishing tryptophan or serotonin in patients who exhibit deficiencies could treat long COVID symptoms. They demonstrated that serotonin levels could be restored, and memory impairment reversed, through treatment with serotonin precursors or selective serotonin reuptake inhibitors.
The genome of the SARS-CoV-2 virus encodes 29 proteins, one of which is an ion channel called E. This channel, which transports protons and calcium ions, induces infected cells to launch an inflammatory response that damages tissues and contributes to the symptoms of Covid-19. MIT chemists have now discovered the structure of the “open” state of this channel, which allows ions to flow through. This structure, combined with the “closed” state structure that was reported by the same lab in 2020, could help scientists figure out what triggers the channel to open and close. These structures could also guide researchers in developing antiviral drugs that block the channel and help prevent inflammation. “The E channel is an antiviral drug target. If you can stop the channel from sending calcium into the cytoplasm, then you have a way to reduce the cytotoxic effects of the virus,” says Mei Hong, an MIT professor of chemistry and the senior author of the study. MIT postdoc Joao Medeiros-Silva is the lead author of the study, which appears today in Science Advances. MIT postdocs Aurelio Dregni and Pu Duan and graduate student Noah Somberg are also authors of the paper.
Open and closed
Hong has extensive experience in studying the structures of proteins that are embedded in cell membranes, so when the Covid-19 pandemic began in 2020, she turned her attention to the coronavirus E channel. When SARS-CoV-2 infects cells, the E channel embeds itself inside the membrane that surrounds a cellular organelle called the ER-Golgi intermediate compartment (ERGIC). The ERGIC interior has a high concentration of protons and calcium ions, which the E channel transports out of ERGIC and into the cell cytoplasm. That influx of protons and calcium leads to the formation of multiprotein complexes called inflammasomes, which induce inflammation. To study membrane-embedded proteins such as ion channels, Hong has developed techniques that use nuclear magnetic resonance (NMR) spectroscopy to reveal the atomic-level structures of those proteins. In previous work, her lab used these techniques to discover the structure of an influenza protein known as the M2 proton channel, which, like the coronavirus E protein, consists of a bundle of several helical proteins. Early in the pandemic, Hong’s lab used NMR to analyze the structure of the coronavirus E channel at neutral pH. The resulting structure, reported in 2020, consisted of five helices tightly bundled together in what appeared to be the closed state of the channel. “By 2020, we had matured all the NMR technologies to solve the structure of this kind of alpha-helical bundles in the membrane, so we were able to solve the closed E structure in about six months,” Hong says.
Once they established the closed structure, the researchers set out to determine the structure of the open state of the channel. To induce the channel to take the open conformation, the researchers exposed it to a more acidic environment, along with higher calcium ion levels. They found that under these conditions, the top opening of the channel (the part that would extend into the ERGIC) became wider and coated with water molecules. That coating of water makes the channel more inviting for ions to enter. That pore opening also contains amino acids with hydrophilic side chains that dangle from the channel and help to attract positively charged ions. The researchers also found that while the closed channel has a very narrow opening at the top and a broader opening at the bottom, the open state is the opposite: broader at the top and narrower at the bottom. The opening at the bottom also contains hydrophilic amino acids that help draw ions through a narrow “hydrophobic gate” in the middle of the channel, allowing the ions to eventually exit into the cytoplasm. Near the hydrophobic gate, the researchers also discovered a tight “belt,” which consists of three copies of phenylalanine, an amino acid with an aromatic side chain. Depending on how these phenylalanines are arranged, the side chains can either extend into the channel to block it or swing open to allow ions to pass through. “We think the side chain conformation of these three regularly spaced phenylalanine residues plays an important role in regulating the closed and open state,” Hong says.
Viral targeting
Previous research has shown that when SARS-CoV-2 viruses are mutated so that they don’t produce the E channel, the viruses generate much less inflammation and cause less damage to host cells. Working with collaborators at the University of California at San Francisco, Hong is now developing molecules that could bind to the E channel and prevent ions from traveling through it, in hopes of generating antiviral drugs that would reduce the inflammation produced by SARS-CoV-2. Her lab is also planning to investigate how mutations in subsequent variants of SARS-CoV-2 might affect the structure and function of the E channel. In the Omicron variant, one of the hydrophilic, or polar, amino acids found in the pore opening is mutated to a hydrophobic amino acid called isoleucine. “The E variant in Omicron is something we want to study next,” Hong says. “We can make a mutant and see how disruption of that polar network changes the structural and dynamical aspect of this protein.”
The research was funded by the National Institutes of Health and the MIT School of Science Sloan Fund.
REsearc published in Science Advances (Oct. 13, 2023):
Initial studies of the 4.5-billion-year-old asteroid Bennu sample collected in space and brought to Earth by NASA show evidence of high-carbon content and water, which together could indicate the building blocks of life on Earth may be found in the rock. NASA made the news Wednesday from its Johnson Space Center in Houston where leadership and scientists showed off the asteroid material for the first time since it landed in September.
This finding was part of a preliminary assessment of NASA’s OSIRIS-REx (Origins, Spectral Interpretation, Resource Identification and Security – Regolith Explorer) science team. “The OSIRIS-REx sample is the biggest carbon-rich asteroid sample ever delivered to Earth and will help scientists investigate the origins of life on our own planet for generations to come,” said NASA Administrator Bill Nelson. “Almost everything we do at NASA seeks to answer questions about who we are and where we come from. NASA missions like OSIRIS-REx will improve our understanding of asteroids that could threaten Earth while giving us a glimpse into what lies beyond. The sample has made it back to Earth, but there is still so much science to come – science like we’ve never seen before.”
Although more work is needed to understand the nature of the carbon compounds found, the initial discovery bodes well for future analyses of the asteroid sample. The secrets held within the rocks and dust from the asteroid will be studied for decades to come, offering insights into how our solar system was formed, how the precursor materials to life may have been seeded on Earth, and what precautions need to be taken to avoid asteroid collisions with our home planet.
Bonus sample material
The goal of the OSIRIS-REx sample collection was 60 grams of asteroid material. Curation experts at NASA Johnson, working in new clean rooms built especially for the mission, have spent 10 days so far carefully disassembling the sample return hardware to obtain a glimpse at the bulk sample within. When the science canister lid was first opened, scientists discovered bonus asteroid material covering the outside of the collector head, canister lid, and base. There was so much extra material it slowed down the careful process of collecting and containing the primary sample.
“Our labs were ready for whatever Bennu had in store for us,” said Vanessa Wyche, director, NASA Johnson.
“We’ve had scientists and engineers working side-by-side for years to develop specialized gloveboxes and tools to keep the asteroid material pristine and to curate the samples so researchers now and decades from now can study this precious gift from the cosmos.”
Within the first two weeks, scientists performed “quick-look” analyses of that initial material, collecting images from a scanning electron microscope, infrared measurements, X-ray diffraction, and chemical element analysis. X-ray computed tomography was also used to produce a 3D computer model of one of the particles, highlighting its diverse interior. This early glimpse provided the evidence of abundant carbon and water in the sample.
Singularity: The Dark Side of AI (100% AI Generated Non-Fiction Film)
In a world increasingly shaped by artificial intelligence, humanity stands at a crossroads. As AI technology advances rapidly, we must consider both its benefits and dangers. In this video, we will explore the negative aspects of AI, discussing the potential risks and serious consequences of its uncontrolled use. We will explore the hidden dangers and face the uncomfortable truths about our world that is becoming more and more reliant on AI.
Created by Maksim Shmeljov using several neural networks:
On a spring day 66 million years ago, paddlefish and sturgeon swam in a river that meandered through a flourishing landscape populated by mighty dinosaurs and small mammals at North America's southwestern corner. Death came from outer space that day.
Scientists examined well-preserved fish fossils to get a deeper understanding of one of the worst days in the history of life on Earth and shedding light on the global calamity triggered by an asteroid 7.5 miles (12 km) wide striking Mexico's Yucatan Peninsula. The ensuing mass extinction erased about three-quarters of Earth's species, including the dinosaurs at the end of the Cretaceous Period, paving the way for mammals - eventually humans - to become dominant on the planet.
The researchers determined that it was springtime at the fossil site called the Tanis deposit - and throughout the Northern hemisphere, including the spot where the asteroid hit - based on sophisticated examinations of bones from three paddlefishes and three sturgeons that died within about 30 minutes of the impact that occurred 2,200 miles (3500 km) away.
They found evidence that a hail of glass pelted the site, finding small spherules - molten material blasted by the impact into space that crystallized before falling back to Earth - embedded in fish gills. The Tanis fossils also indicated that a huge standing wave of water swept through after the impact, burying the local denizens alive. Among the dinosaurs living in the Tanis area was apex predator Tyrannosaurus rex.
"Every living thing in Tanis on that day saw nothing coming and was killed almost instantaneously," said Melanie During, a paleontology doctoral student at Uppsala University in Sweden and lead author of the research published in the journal Nature. During compared the fossils deposited at Tanis to "a car crash frozen in place."
Multiple lines of evidence pointed to a springtime impact. Annual growth rings in certain fish bones - resembling those in tree trunks - showed increased growth levels associated with springtime after reduced growth in leaner winter months. Chemical evidence from one of the paddlefishes indicated that food availability was increasing as it does in springtime, but not at peak summer levels.
Springtime marks a time of growth and reproduction for many organisms. "This season is crucial for the survival of species," said study co-author Sophie Sanchez, an Uppsala University senior lecturer in paleohistology. In the southern hemisphere, it was autumn at the time, Sanchez noted, a season when many creatures prepare for the deprivations of winter. Dinosaurs - aside from their bird descendants - went extinct, as did major marine groups, including the carnivorous reptiles that dominated the seas. Among the survivors were paddlefishes and sturgeons, which survive to this day.
The Tanis fossils helped the researchers better understand the events following the impact, which left a crater about 110 miles (180 km) wide at a Yucatan site called Chicxulub. The asteroid rocked the continental plate, generated earthquakes, sparked extensive wildfires, unleashed a massive shockwave in the air and seismic waves on the ground, and spawned massive standing waves called seiche waves - perhaps hundreds of yards tall - in water bodies. These waves, carrying immense amounts of sediment and debris, inundated the Tanis site within approximately 15 to 30 minutes after the impact, burying alive all the inhabitants, including the fish whose fossils were studied.
The peril did not end that day. A cloud of dust enrobed Earth, precipitating a climate catastrophe akin to a "nuclear winter" that blocked sunlight for perhaps years, condemning countless species to oblivion. "Although most of the extinction unfolded during the aftermath of the impact, which lasted much longer, zero hour - the exact timing of the impact - determined the course of the mass extinction," said study co-author Jeroen van der Lubbe, a geochemist and paleoclimatologist at Vrije Universiteit Amsterdam in the Netherlands.
Adobe Illustrator is a widely used vector graphics tool for graphic artists and it’s about to join the generative AI era with the launch of the Firefly Vector Model at Adobe’s MAX conference today. Adobe describes the new model as “the world’s first generative AI model focused on producing vector graphics.” Like Firefly for creating images and photos, Firefly for Illustrator will be able to create entire vector graphics from scratch. And like the other Firefly models, the vector model, too, was trained on data from Adobe Stock.
In its beta, Illustrator will now let you create entire scenes through a text prompt. What’s nifty here is that those scenes can consist of multiple objects. So this isn’t just a jumble of vectors that make up the overall graphic but Illustrator will automatically generate these different objects and you can manipulate them individually to your heart’s content, just like any other group or layer in Illustrator.
Alexandru Costin, Adobe’s VP for generative AI and Sensei, told me the company used tens of millions of vector images in Adobe Stock to train Firefly to enable this new capability. Costin described the process as “a journey” and since there hasn’t been as much work done on using generative AI to create vector drawings compared to the work on creating other images, this surely took a bit more work on the team’s part. He noted that the team focused on creating a model that could generate these images with the fewest possible points, too.
Another new feature that’s coming to Illustrator is called Mockup, which allows Illustrator users to take any 3D scene and then take any vector art and apply it to that 3D scene. That could be a design for a drink can, for example, or a mockup of a new logo on a t-shirt. “Mockup is really exciting to show your customers the art in context so they understand what they’re buying when they contract you as a freelancer,” Costin explained. Also new is Retype, which converts static text in images to editable text — and it’ll find matching fonts, too — and Illustrator is now available on the web, too!
The universe is humming with gravitational radiation—a very low-frequency rumble that rhythmically stretches and compresses spacetime and the matter embedded in it. That is the conclusion of several groups of researchers from around the world who simultaneously published a slew of journal articles in June describing more than 15 years of observations of millisecond pulsars within our corner of the Milky Way galaxy. At least one group—the North American Nanohertz Observatory for Gravitational Waves (NANOGrav) collaboration—has found compelling evidence that the precise rhythms of these pulsars are affected by the stretching and squeezing of spacetime by these long-wavelength gravitational waves.
"This is key evidence for gravitational waves at very low frequencies," says Vanderbilt University's Stephen Taylor, who co-led the search and is the current chair of the collaboration. "After years of work, NANOGrav is opening an entirely new window on the gravitational-wave universe."
Gravitational waves were first detected by the Laser Interferometer Gravitational-Wave Observatory (LIGO) in 2015. The short-wavelength fluctuations in spacetime were caused by the merger of smaller black holes, or occasionally neutron stars, all of them weighing in at less than a few hundred solar masses. The question now is: Are the long-wavelength gravitational waves—with periods from years to decades—also produced by black holes?
In one recent paper from the NANOGrav consortium, published in The Astrophysical Journal Letters, University of California, Berkeley, physicist Luke Zoltan Kelley and the NANOGrav team argued that the hum is likely produced by hundreds of thousands of pairs of supermassive black holes—each weighing billions of times the mass of our sun—that over the history of the universe have gotten close enough to one another to merge. The team produced simulations of supermassive black hole binary populations containing billions of sources and compared the predicted gravitational wave signatures with NANOGrav's most recent observations.
The black holes' orbital dance prior to merging vibrates spacetime analogous to the way waltzing dancers rhythmically vibrate a dance floor. Such mergers over the 13.8-billion-year age of the universe produced gravitational waves that today overlap, like the ripples from a handful of pebbles tossed into a pond, to produce the background hum. Because the wavelengths of these gravitational waves are measured in light years, detecting them required a galaxy-sized array of antennas—a collection of millisecond pulsars.
"I guess the elephant in the room is we're still not 100% sure that it's produced by supermassive black hole binaries. That is definitely our best guess, and it's fully consistent with the data, but we're not positive," said Kelley, UC Berkeley assistant adjunct professor of astronomy. "If it is binaries, then that's the first time that we've actually confirmed that supermassive black hole binaries exist, which has been a huge puzzle for more than 50 years now."
A new study highlights both the promise and the limitations of gene editing, as a highly lethal form of avian influenza continues to spread around the world.
Scientists have used the gene-editing technology known as CRISPR to create chickens that have some resistance to avian influenza, according to a new study that was published in the journal Nature Communications on Tuesday. The study suggests that genetic engineering could potentially be one tool for reducing the toll of bird flu, a group of viruses that pose grave dangers to both animals and humans. But the study also highlights the limitations and potential risks of the approach, scientists said. Some breakthrough infections still occurred, especially when gene-edited chickens were exposed to very high doses of the virus, the researchers found. And when the scientists edited just one chicken gene, the virus quickly adapted.
The findings suggest that creating flu-resistant chickens will require editing multiple genes and that scientists will need to proceed carefully to avoid driving further evolution of the virus, the study’s authors said. The research is “proof of concept that we can move toward making chickens resistant to the virus,” Wendy Barclay, a virologist at Imperial College London and an author of the study, said at a news briefing. “But we’re not there yet.” Some scientists who were not involved in the research had a different takeaway. “It’s an excellent study,” said Dr. Carol Cardona, an expert on bird flu and avian health at the University of Minnesota. But to Dr. Cardona, the results illustrate how difficult it will be to engineer a chicken that can stay a step ahead of the flu, a virus known for its ability to evolve swiftly. “There’s no such thing as an easy button for influenza,” Dr. Cardona said. “It replicates quickly, and it adapts quickly.”
What to Know About Avian Flu
The spread of H5N1. A new variant of this strain of the avian flu has spread widely through bird populations in recent years. It has taken an unusually heavy toll on wild birds and repeatedly spilled over into mammals, including minks, foxes and bears.
Here’s what to know about the virus:
What is avian influenza? Better known as the bird flu, avian influenza is a group of flu viruses that is well adapted to birds. Some strains, like the version of H5N1 that is currently spreading, are frequently fatal to chickens and turkeys. It spreads via nasal secretions, saliva and fecal droppings, which experts say makes it difficult to contain.
Should humans be worried about being infected? Although the danger to the public is currently low, people who are in close contact with sick birds can and have been infected. The virus is primarily a threat to birds, but infections in mammals increase the odds that the virus could mutate in ways that make it more of a risk to humans, experts say.
How can we stop the spread? The U.S. Department of Agriculture has urged poultry growers to tighten their farms’ biosecurity measures, but experts say the virus is so contagious that there is little choice but to cull infected flocks. The Biden administration has been contemplating a mass vaccination campaign for poultry.
Is it safe to eat poultry and eggs? The Agriculture Department has said that properly prepared and cooked poultry and eggs should not pose a risk to consumers. The chance of infected poultry entering the food chain is “extremely low,” according to the agency.
Can I expect to pay more for poultry products? Egg prices soared when an outbreak ravaged the United States in 2014 and 2015.
The current outbreak of the virus — paired with inflation and other factors — has contributed to an egg supply shortage and record-high prices in some parts of the country. Avian influenza refers to a group of flu viruses that are adapted to spread in birds. Over the last several years, a highly lethal version of a bird flu virus known as H5N1 has spread rapidly around the globe, killing countless farmed and wild birds. It has also repeatedly infected wild mammals and been detected in a small number of people. Although the virus remains adapted to birds, scientists worry that it could acquire mutations that help it spread more easily among humans, potentially setting off a pandemic. Many nations have tried to stamp out the virus by increasing biosecurity on farms, quarantining infected premises and culling infected flocks. But the virus has become so widespread in wild birds that it has proved impossible to contain, and some nations have begun vaccinating poultry, although that endeavor presents some logistic and economic challenges.
If scientists could engineer resistance into chickens, farmers would not need to routinely vaccinate new batches of birds. Gene editing “promises a new way to make permanent changes in the disease resistance of an animal,” Mike McGrew, an embryologist at the University of Edinburgh’s Roslin Institute and an author of the new study, said at the briefing. “This can be passed down through all the gene-edited animals, to all the offspring.” CRISPR, the gene-editing technology used in the study, is a molecular toolthat allows scientists to make targeted edits in DNA, changing the genetic code at a precise point in the genome. In the new study, the researchers used this approach to tweak a chicken gene that codes for a protein known as ANP32A, which the flu virus hijacks to copy itself. The tweaks were designed to prevent the virus from binding to the protein — and therefore keep it from replicating inside chickens. The edits did not appear to have negative health consequences for the chickens, the researchers said. “We observed that they were healthy, and that the gene-edited hens also laid eggs normally,” said Dr. Alewo Idoko-Akoh, who conducted the research as a postdoctoral researcher at the University of Edinburgh.
The researchers then sprayed a dose of flu virus into the nasal cavities of 10 chickens that had not been genetically edited, to serve as the control. (The researchers used a mild version of the virus different from the one that has been causing major outbreaks in recent years.) All of the control chickens were infected with the virus, which they then transmitted to other control chickens they were housed with. When the researchers administered flu virus directly into the nasal cavities of 10 gene-edited chickens, just one of the birds became infected. It had low levels of the virus and did not pass the virus on to other gene-edited birds. “But having seen that, we felt that it would be the responsible thing to be more rigorous, to stress test this and ask, ‘Are these chickens truly resistant?’” Dr. Barclay said. “‘What if they were to somehow encounter a much, much higher dose?’” When the scientists gave the gene-edited chickens a flu dose that was 1,000 times higher, half of the birds became infected. The researchers found, however, that they generally shed lower levels of the virus than control chickens exposed to the same high dose.
The researchers then studied samples of the virus from the gene-edited birds that had been infected. These samples had several notable mutations, which appeared to allow the virus to use the edited ANP32A protein to replicate, they found. Some of these mutations also helped the virus replicate better in human cells, although the researchers noted that those mutations in isolation would not be enough to create a virus that was well adapted to humans. Seeing those mutations is “not ideal,” said Richard Webby, who is a bird flu expert at St. Jude Children’s Research Hospital and was not involved in the research. “But when you get to the weeds of these particular changes, then it doesn’t concern me quite so much.” The mutated flu virus was also able to replicate even in the complete absence of the ANP32A protein by using two other proteins in the same family, the researchers found. When they created chicken cells that lacked all three of these proteins, the virus was not able to replicate. Those chicken cells were also resistant to the highly lethal version of H5N1 that has been spreading around the world the last several years. The researchers are now working to create chickens with edits in all three of the genes for the protein family. The big question, Dr. Webby said, was whether chickens with edits in all three genes would still develop normally and grow as fast as poultry producers needed. But the idea of gene editing chickens had enormous promise, he said. “Absolutely, we’re going to get to a point where we can manipulate the host genome to make them less susceptible to flu,” he said. “That’ll be a win for public health.”
Research cited published in Nature Comm. (Oct. 10, 2023):
Some asteroids have measured densities higher than those of any elements known to exist on Earth. This suggests that they are at least partly composed of unknown types of "ultradense" matter that cannot be studied by conventional physics. Jan Rafelski and his team at the Department of Physics, The University of Arizona, Tucson, U.S., suggest that this could consist of superheavy elements with atomic number (Z) higher than the limit of the current periodic table. They modeled the properties of such elements using the Thomas-Fermi model of atomic structure, concentrating particularly on a proposed "island of nuclear stability" at and around Z=164 and extending their method further to include more exotic types of ultra-dense material. This work has now been published in The European Physical Journal Plus.
Superheavy elements are defined as those with a very high number of protons (high atomic number), generally considered to be those with Z>104. They can be divided into two groups. Those with atomic numbers between 105 and 118 have been made experimentally but are radioactive and unstable with very short half-lives and, therefore, are only of academic and research interest. Elements with Z>118 have not yet been observed, but properties have been predicted for some of them. In particular, an "island of nuclear stability" is predicted at about Z=164. And as, in general, the density of elements tends to rise with their atomic mass, these superheavy elements can be expected to be extremely dense.
The densest stable element is the rare platinoid metal osmium (Z=76); its density of 22.59 g/cm3 is about twice that of lead. Objects—typically, astronomical bodies—with densities higher than that are considered "compact ultradense objects" or CUDOs. The most extreme example known is the asteroid named 33 Polyhymnia, which is located in the main belt between Mars and Jupiter; its density has been calculated as about 75 g/cm3. Rafelski proposes that Polyhymnia and similar objects may be composed of elements above Z=118, possibly with other types of ultradense matter.
Rafelski and his two student co-workers, Evan LaForge and Will Price set out to calculate the microscopic atomic structure and properties of ultraheavy elements using the relativistic Thomas-Fermi model of the atom. "We chose this model, despite its relative imprecision, because it allows the systematic exploration of atomic behavior as a function of atomic number beyond the known periodic table," Rafelski explains. "A further consideration is that it also enabled us to explore many atoms in the short time available to Evan [LaForge], our brilliant undergraduate student."
The researchers' calculations confirmed the prediction that atoms with around 164 protons in their nuclei were likely to be stable, and, furthermore, suggested that a stable element with Z=164 would have a density between 36.0 and 68.4 g/cm3: a range that approaches the expected value for asteroid Polyhymnia.
As their model used the charge distribution in the atomic nucleus as one of its inputs, it could be extended to simulate still more exotic substances including alpha matter: a condensate composed entirely of isolated helium nuclei (alpha particles).
The idea that some asteroids may be composed of materials unknown on Earth is further motivating potential "space miners" who are planning to exploit the precious metals, including gold, that are expected to lie close to the surface of others.
"All super-heavy elements—those that are highly unstable as well as those that are simply unobserved—have been lumped together as 'unobtainium,'" concludes Rafelski. "The idea that some of these might be stable enough to be obtained from within our solar system is an exciting one."
A virtual cell modeling system, powered by AI, will lead to breakthroughs in our understanding of diseases, argue the cofounders of the Chan Zuckerberg Initiative.
As the smallest living units, cells are key to understanding disease—and yet so much about them remains unknown. We do not know, for example, how billions of biomolecules—like DNA, proteins, and lipids—come together to act as one cell. Nor do we know how our many types of cells interact within our bodies. We have limited understanding of how cells, tissues, and organs become diseased and what it takes for them to be healthy.
AI can help us answer these questions and apply that knowledge to improve health and well-being worldwide—if researchers can access and harness these powerful new technologies. Imagine if we had a way to represent every cell state and cell type using AI models. A “virtual cell” could simulate the appearance and known characteristics of any cell type in our body—from the rods and cones that detect light in our retinas to the cardiomyocytes that keep our hearts beating.
Scientists could use such a simulator to predict how cells might respond to specific conditions and stimuli: how an immune cell responds to an infection, what happens at the cellular level when a child is born with a rare disease, or even how a patient’s body will respond to a new medication. Scientific discovery, patient diagnosis, and treatment decisions would all become faster, safer, and more efficient. At the Chan Zuckerberg Initiative, we’re helping to generate the scientific data and build out the computing infrastructure to make this a reality—and give scientists the tools they need to take advantage of new advances in AI to help end disease.
Advances in AI coupled with large volumes of scientific data have already predicted the structure of nearly all known proteins. DeepMind trained AlphaFold on 50 years’ worth of carefully collected data, and in just five years, they solved the mystery of protein structure. ESM, another AI system which was developed at Meta, is a protein language model trained not on words but on over 60 million protein sequences. It is used for a wide range of applications, like predicting protein structures and the effects of mutations from single sequences.
A virtual cell modeling system will also require large amounts of data. Since 2016, CZI has supported researchers globally in efforts to generate and annotate data about cells and their components, built tools to integrate these large data sets, and made them widely available for researchers to learn from and build upon. A global consortium of researchers has been building a reference map of every cell type in the body, and our San Francisco Biohub is creating whole-organism cell atlases. Together, these data sets are yielding the first draft of the open-source Human Cell Atlas, which will chart cell types in the body from development to adulthood. Our SF Biohub and the Chan Zuckerberg Imaging Institute are partnering on OpenCell, which maps the locations of different proteins in our cells.
Eric Schmidt: This is how AI will transform the way science gets done Science is about to become much more exciting—and that will affect us all, argues Google's former CEO.
Researchers are also using machine-learning models like Geneformer and scGPT to explore large amounts of data about genes and cells—including data generated from CELLxGENE, the open-source software platform that CZI’s science and technology teams created to speed up single-cell research. Similarly, with a new prototype data portal for cryo-electron tomography, our Imaging Institute and our science and technology teams are engaging machine-learning experts to develop automated annotations of microscopy data. This will speed up data processing time from months or even years to just weeks.
We are making the data as representative as possible to make sure scientific breakthroughs benefit everyone. This includes incorporating pediatric data into the Human Cell Atlas, filling gaps in our knowledge about the cellular mechanisms of diseases that arise in childhood. With our Ancestry Networks grants, we are also supporting researchers generating reference data about cells based on tissue samples from Black, Latino, Southeast Asian, and Indigenous people, among others from understudied racial, ethnic, and ancestral backgrounds.
Already, research teams have made discoveries using these well-curated data sets. One discovered that the broken gene linked to cystic fibrosis is expressed by a type of cell scientists had never come across before, while another identified the respiratory cells that are most vulnerable to SARS-CoV-2. Others are using the data to discover new options for splicing genes to potentially correct disease-causing mutations in specific cells. These discoveries are the first step in developing treatments for diseases—and we believe that AI can significantly speed up researchers’ rate of discoveries going forward.
How to compute a virtual cell?
To create a virtual cell, we’re building a high-performance computing cluster with 1000+ H100 GPUs that will enable us to develop new AI models trained on various large data sets about cells and biomolecules—including those generated by our scientific institutes. Over time, we hope, this will enable scientists to simulate every cell type in both healthy and diseased states, and query those simulations to see how elusive biological phenomena likely play out—including how cells come into being, how they interact across the body, and how exactly disease-causing changes affect them. The computing cluster won’t be as large as those used in the private sector for commercial products, but once it’s up and running, it will be one of the world’s largest AI clusters for nonprofit scientific research. This will be an important resource for academic teams that are ready to use data sets in new ways but are held back by the prohibitive cost of accessing the latest AI technology. Like our other tools, these digital cell models, and their associated data and applications, will be openly accessible to researchers worldwide.
A new report lays out a modern way to search for E.T., calling for better use of big data and machine learning techniques.
Humanity has wondered whether we are alone for millennia. The discovery of life elsewhere in the Universe, particularly intelligent life, would have profound effects, comparable to those of recognizing that the Earth is not the center of the Universe and that humans evolved from previous species.
There has been rapid growth in the fields of extrasolar planets and data-driven astronomy. In a relatively short interval, we have seen a change from knowing of no extrasolar planets to now knowing more potentially habitable extrasolar planets than there are planets in our Solar System. In approximately the same interval, astronomy has transitioned to a field in which sky surveys can generate 1 PB or more of informative data.
The Data-Driven Approaches to Searches for the Technosignatures of Advanced Civilizations is now ongoing. Data-driven searches, being able to process volumes of data much greater than a human could, and in a reproducible manner, can identify *anomalies* that could be clues to the presence of technosignatures. Experts agree that technosignature searches should be conducted in a manner consistent with Freeman Dyson's "First Law of SETI Investigations," namely "every search for alien civilizations should be planned to give interesting results even when no aliens are discovered." This approach to technosignatures is commensurate with NASA's approach to biosignatures in that no single observation or measurement can be taken as providing full certainty for the detection of life. Areas of particular promise identified during one of the recent workshop were (*) Data Mining of Large Sky Surveys, (*) All-Sky Survey at Far-Infrared Wavelengths, (*) Surveys with Radio Astronomical Interferometers, and (*) Artifacts in the Solar System.
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