Amazing Science

Graphene has properties almost as if out of a picture book. It is simultaneously strong and flexible, it permeates water but filters gases, it is transparent like glass but at the same time conducts current better than a metal – and on top of it all, it is as thin as can be. Graphene consists just of a single layer of atoms. No surprise that interest in this wonder material (Nobel Prize 2010) explodes. Unfortunately, graphene displays all of these properties only when it is essentially defect free, and this is exactly what limits commercial production today.

Recently, highest-quality graphene films could be produced at copper catalysts. The gist was to melt the copper above 1100° degrees, so that the film growth occurs above the liquid metal surface. Yet, why these extreme conditions favor the formation of defect-free graphene is largely unknown. Not least the high temperatures and gas flows during growth hamper gaining the necessary atomic-level insights. Much hope is therefore placed on methods of AI/machine learning that can accelerate highest-accuracy quantum mechanical predictions to a level that allows so-called molecular dynamics simulations to correctly account for the high mobility of atoms at the liquid copper surface. Up to now, there is very little experience as to the reliability of these AI approaches though.

As an important benchmark, scientists at the Fritz Haber Institute (FHI) predicted the height of a growing graphene layer above the liquid copper catalyst using these novel approaches, and compared it against measurements from high-level synchrotron experiments achieved within a European consortium. The result is striking. The machines were right down to 10-11 m, or within less than one millionth the width of a hair. This high precision, called “sub-Ångstrøm“ in the jargon of the field, demonstrates the impressive capabilities of the novel AI approaches to acquire detailed insights into the microscopic growth process. “Our results nicely show the unprecedented possibilities”, summarizes the leader of the FHI-team Dr. Heenen proudly. “Intriguingly, the data on adsorption height suggest an essentially identical chemical interaction of graphene with solid and liquid copper. This renders the superior synthesis above the liquid metal surface even more mysterious.”

The Hubble Space Telescope identified its most distant single star to date, whose light has taken 12.9 billion years to reach Earth.

The most distant single star seen yet dates back to less than 1 billion years after the universe's birth in the Big Bang, and may shed light on the earliest stars in the cosmos, a new study finds.

The scientists nicknamed the star "Earendel," from an Old English word meaning "morning star" or "rising light." Earendel, whose technical designation is WHL0137-LS, is at least 50 times the mass of the sun and millions of times as bright.

This newfound star, detected by NASA's Hubble Space Telescope, is so far away that its light has taken 12.9 billion years to reach Earth, appearing to us as it was when the universe was about 900 million years old, just 7% of its current age. Until now, the most distant single star detected, discovered by Hubble in 2018, existed when the universe was about 4 billion years old, or 30% of its current age.

Normally, even a star as brilliant as Earendel would be impossible to see from Earth given the vast divide between the two. Previously, the smallest objects seen at such a great distance were clusters of stars embedded inside early galaxies.

Scientists detected Earendel with the help of a huge galaxy cluster, WHL0137-08, sitting between Earth and the newfound star. The gravitational pull of this enormous galaxy cluster warped the fabric of space and time, resulting in a powerful natural magnifying glass that greatly amplified the light from distant objects behind the galaxy, such as Earendel. This gravitational lensing has distorted the light from the galaxy hosting Earendel into a long crescent the researchers named the Sunrise Arc.

The rare way in which Earendel aligned with WHL0137-08 meant that the star appeared directly on, or extremely close to, a curve in spacetime that provided maximum brightening, causing Earendel to stand out from the general glow of its home galaxy. This effect is analogous to the rippled surface of a swimming pool creating patterns of bright light on the bottom of the pool on a sunny day — the ripples on the surface act as lenses and focus sunlight to maximum brightness on the pool floor.  Welch emphasized this is not the most distant object scientists have ever discovered. "Hubble has observed galaxies at greater distances," he explained. "However, we see the light from their millions of stars all blended together. This is the most distant object where we can identify light from an individual star."

He also noted this star was distant, but not old. "We see the star as it was 12.8 billion years ago, but that does not mean the star is 12.8 billion years old," Welch said. Instead, it's probably just a few million years old and never reached old age.  "Given its mass, it almost certainly has not survived to today, as more massive stars tend to burn through their fuel faster and thus explode, or collapse into black holes, sooner," he added of Earendel. "The oldest stars known would have formed at a similar time, but they are much less massive, so they have continued to shine until today."

Many details about Earendel remain uncertain, such as its mass, brightness, temperature and type. Scientists are not even sure yet if Earendel is one star or two — most stars of Earendel's mass usually do have a smaller, dimmer companion, and it's possible that Earendel is outshining its partner. Scientists intend to conduct followup observations with NASA's recently launched James Webb Space Telescope to analyze Earendel's infrared light and pin down many of its features. Such information in turn could help shed light on the first stars in the universe, which formed before the universe was filled with the heavy elements produced by successive generations of massive stars.

The exponential accumulation of digital data is expected to outstrip magnetic and optical storage media.

Scientists are training a gargantuan one-trillion-parameter generative AI system dubbed 'ScienceGPT' based on scientific data from the newly established Aurora supercomputer.

The AuroraGPT AI model, which is being trained by researchers at the Argonne National Lab (ALN) in Illinois, USA, is powered by Intel's Ponte Vecchio GPUs which provide the main computing power, and is being backed by the US government. Training could take months to complete, according to HPC Wire, with training currently limited to 256 of the roughly 10,000 nodes of the Aurora supercomputer, before this is scaled up over time. Even given this limitation, Intel and ANL are only testing the model training on a string of 64 nodes, with caution due to Aurora's unique design as a supercomputer.

At one trillion parameters, ScienceGPT will be one of the largest LLMs out there. While it won't quite hit the size of the reported 1.7-trillion-parameter GPT-4, developed by OpenAI, it'll be almost twice as large as the 560-billion-parameter Pathways Language Model, which powers Google's Bard. “It combines all the text, codes, specific scientific results, papers, into the model that science can use to speed up research,” said Ogi Brkic, vice president and general manager for data center and HPC solutions, in a press briefing. It'll operate like ChatGPT, but it's yet unclear at the moment whether it will be multimodal, in that it will generate different kinds of media like text, images, and video. 

The landmark decision could transform the treatment of sickle-cell disease and β-thalassaemia — but the technology is expensive.

In a world first, the UK medicines regulator has approved a therapy that uses the CRISPR–Cas9 gene-editing tool as a treatment. The decision marks another high point for a biotechnology that has been lauded as revolutionary in the decade since its discovery.

The therapy, called Casgevy, will treat the blood conditions sickle-cell disease and β-thalassaemia. Sickle-cell disease, also known as sickle-cell anaemia, can cause debilitating pain, and people with β-thalassaemia often require regular blood transfusions.

“This is a landmark approval which opens the door for further applications of CRISPR therapies in the future for the potential cure of many genetic diseases,” said Kay Davies, a geneticist at the University of Oxford, UK, in comments to the UK Science Media Centre (SMC).

Nature magazine explains the research behind the treatment and explores what’s next.

What research led to the approval?

The approval by the Medicines and Healthcare products Regulatory Agency (MHRA) follows promising results from clinical trials that tested a one-time treatment, which is administered by intravenous infusion. The therapy was developed by the pharmaceutical company Vertex Pharmaceuticals in Boston, Massachusetts, and biotechnology company CRISPR Therapeutics in Zug, Switzerland.

The trial for sickle-cell disease has followed 29 out of 45 participants long enough to draw interim results. Casgevy completely relieved 28 of those people of debilitating episodes of pain for at least one year after treatment. Researchers also tested the treatment for a severe form of β-thalassaemia, which is conventionally treated with blood transfusions roughly once a month. In this trial, 54 people received Casgevy, of which 42 participated for long enough to provide interim results. Among those 42 participants, 39 did not need a red-blood-cell transfusion for at least one year. The remaining three had their need for blood transfusions reduced by more than a 70%.

The Chinese government will accelerate the widespread production of advanced humanoid robots by funding more startups in the robotics field.

Integrating neurons into digital systems may enable performance infeasible with silicon alone. A team of neuroscientists have recently developped DishBrain, a system that harnesses the inherent adaptive computation of neurons in a structured environment. In vitro neural networks from human or rodent origins are integrated with in silico computing via a high-density multielectrode array. Through electrophysiological stimulation and recording, cultures are embedded in a simulated game-world, mimicking the arcade game “Pong.” Applying implications from the theory of active inference via the free energy principle, the researchers find apparent learning within five minutes of real-time gameplay not observed in control conditions. Further experiments demonstrate the importance of closed-loop structured feedback in eliciting learning over time. Cultures display the ability to self-organize activity in a goal-directed manner in response to sparse sensory information about the consequences of their actions, which creates synthetic biological intelligence. Future applications may provide further insights into the cellular correlates of intelligence.

Terrible to terrific: A new antifungal molecule tweaks a powerful drug to harness its power against infection while doing away with its toxicity.

A new antifungal molecule, devised by tweaking the structure of prominent antifungal drug Amphotericin B, has the potential to harness the drug’s power against fungal infections while doing away with its toxicity, researchers at the University of Illinois Urbana-Champaign and collaborators at the University of Wisconsin-Madison report in the journal Nature.

Amphotericin B, a naturally occurring small molecule produced by bacteria, is a drug used as a last resort to treat fungal infections. While AmB excels at killing fungi, it is reserved as a last line of defense because it also is toxic to the human patient – particularly the kidneys. 

“Fungal infections are a public health crisis that is only getting worse. And they have the potential, unfortunately, of breaking out and having an exponential impact, kind of like COVID-19 did. So let’s take one of the powerful tools that nature developed to combat fungi and turn it into a powerful ally,” said research leader Dr. Martin D. Burke, an Illinois professor of chemistry, a professor in the Carle Illinois College of Medicine and also a medical doctor. 

“This work is a demonstration that, by going deep into the fundamental science, you can take a billion-year head start from nature and turn it into something that hopefully is going to have a big impact on human health,” Burke said. 

Burke’s group has spent years exploring AmB in hopes of making a derivative that can kill fungi without harm to humans. In previous studies, they developed and leveraged a building block-based approach to molecular synthesis and teamed up with a group specializing in molecular imaging tools called solid-state nuclear magnetic resonance, led by professor Chad Rienstra at the University of Wisconsin-Madison. Together, the teams uncovered the mechanism of the drug: AmB kills fungi by acting like a sponge to extract ergosterol from fungal cells. 

In the recent work, Burke’s group worked again with Rienstra’s group to find that AmB similarly kills human kidney cells by extracting cholesterol, the most common sterol in people. The researchers also resolved the atomic-level structure of AmB sponges when bound to both ergosterol and to cholesterol. 

“The atomic resolution models were really the key to zoom in and identify these very subtle differences in binding interactions between AmB and each of these sterols,” said Illinois graduate student Corinne Soutar, a co-first author of the paper. “Using this structural information along with functional and computational studies, we achieved a significant breakthrough in understanding how AmB functions as a potent fungicidal drug,” Rienstra said. “This provided the insights to modify AmB and tune its binding properties, reducing its interaction with cholesterol and thereby reducing the toxicity.” 

Deep within every piece of magnetic material, electrons dance to the invisible tune of quantum mechanics. Their spins, akin to tiny atomic tops, dictate the magnetic behavior of the material they inhabit. This microscopic ballet is the cornerstone of magnetic phenomena, and it's these spins that a team of JILA researchers—headed by JILA Fellows and University of Colorado Boulder professors Margaret Murnane and Henry Kapteyn—has learned to control with remarkable precision, potentially redefining the future of electronics and data storage.

In a Science Advances publication, the JILA team—along with collaborators from universities in Sweden, Greece, and Germany—probed the spin dynamics within a special material known as a Heusler compound: a mixture of metals that behaves like a single magnetic material.

For this study, the researchers utilized a compound of cobalt, manganese, and gallium, which behaved as a conductor for electrons whose spins were aligned upwards and as an insulator for electrons whose spins were aligned downwards. Using a form of light called extreme ultraviolet high-harmonic generation (EUV HHG) as a probe, the researchers could track the re-orientations of the spins inside the compound after exciting it with a femtosecond laser, which caused the sample to change its magnetic properties. The key to accurately interpreting the spin re-orientations was the ability to tune the color of the EUV HHG probe light.

"In the past, people haven't done this color tuning of HHG," explained co-first author and JILA graduate student Sinéad Ryan. "Usually, scientists only measured the signal at a few different colors, maybe one or two per magnetic element at most." In a monumental first, the JILA team tuned their EUV HHG light probe across the magnetic resonances of each element within the compound to track the spin changes with a precision down to femtoseconds (a quadrillionth of a second).

"On top of that, we also changed the laser excitation fluence, so we were changing how much power we used to manipulate the spins," Ryan elaborated, highlighting that that step was also an experimental first for this type of research.

Established in 1964, the IUCN Red List of Threatened Species has evolved to become the world’s most comprehensive information source on the global conservation status of animal, fungi and plant species.

In addition to species changing status, The IUCN Red List grows larger with each update as newly described species and species from the less well-known groups are assessed for the first time (Figure 1). IUCN and its partners are working to expand the number of taxonomic groups that have full and complete Red List assessments in order to improve our knowledge of the status of the world's biodiversity; see the Barometer of Life page for more information about this work.

Not all taxonomic groups have been completely assessed (see Table 1 and Figure 2). It is very important to consider this when looking at the numbers of species in each Red List Category and the proportions of threatened species within each group; although The IUCN Red List gives a good snapshot of the current status of species, it should not be interpreted as a full and complete assessment of the world's biodiversity. For more information the work underway to expand taxonomic coverage on The IUCN Red List, see the Barometer of Life page.

How many species are threatened?

Species assessed as Critically Endangered (CR), Endangered (EN), or Vulnerable (VU) are referred to as "threatened" species. However, Extinct in the Wild (EW) species can move into the threatened categories following successful reintroduction. Therefore, EW species should be included when reporting proportions of threatened species.

Reporting the proportion of threatened species on The IUCN Red List is complicated because:

• not all species groups have been fully evaluated, and
• some species have so little information available that they can only be assessed as Data Deficient (DD).

For many of the incompletely evaluated groups, assessment efforts have focused on those species that are likely to be threatened; therefore any percentage of threatened species for these groups would be heavily biased (i.e., the % threatened species would likely be an overestimate).

For those groups that have been comprehensively evaluated, the proportion of threatened species can be calculated, but the number of these species is often uncertain because it is not known whether DD species are actually threatened or not. Some taxonomic groups are much better known that others (i.e., they will have fewer DD species), and therefore a more accurate figure can be calculated. Other, less well known groups have a large proportion of DD species, which brings uncertainty into the estimate.

An experimental gene therapy has restored the hearing of a child who was born deaf, the pharmaceutical giant Eli Lilly said in a statement. The child, who was 11 years old at the time the therapy was administered, experienced restored hearing within 30 days of treatment, Eli Lilly said in a release. The child participating in the clinical study was the first individual in the U.S. to receive the therapy for a genetic form of hearing loss, the company said.

The gene therapy, AK-OTOF, is being developed for the treatment of hearing loss due to mutations in the otoferlin gene. added AK-OTOF to its portfolio through its , a genetic-medicine company focused on inner-ear conditions.

Doctors and scientists have been pursuing gene therapy for hearing loss for more than 20 years, and “these initial results show that it may restore hearing better than many thought possible,” Dr. John Germiller, director of clinical research in the otolaryngology department at the Children’s Hospital of Philadelphia and principal investigator in the clinical trial, said in a statement.

The child’s hearing was restored across all tested frequencies and was within a normal range at some frequencies at 30 days after the treatment, Eli Lilly said.

Children with hearing problems due to otoferlin gene mutations are often born with profound hearing loss, but most of them have not had the genetic testing needed for a definitive diagnosis, Dr. Oliver Haag, head of otolaryngology at Sant Joan de Deu Hospital in Barcelona and an Akouos study investigator, said in a statement.

In observations of the planets Kepler-1625b and Kepler-1708b from the Kepler and Hubble space telescopes, researchers had discovered traces of such moons for the first time. A new study now raises doubts about these previous claims. As scientists from the Max Planck Institute for Solar System Research and the Sonnenberg Observatory, both in Germany, report in the journal Nature Astronomy, "planet-only" interpretations of the observations are more conclusive. For their analysis, the researchers used their newly developed computer algorithm Pandora, which facilitates and accelerates the search for exomoons. They also investigated what kind of exomoons can be found in principle in modern space-based astronomical observations. Their answer is quite shocking.

In our Solar System, the fact that a planet is orbited by one or more moons is rather the rule than the exception: apart from Mercury and Venus, all other planets have such companions; in the case of the gas giant Saturn researchers have found 140 natural satellites until today. Scientists therefore consider it likely that planets in distant star systems also harbor moons. So far, however, there has only been evidence of such exomoons in two cases: Kepler-1625b and Kepler-1708b. This low yield is not surprising. After all, distant satellites are naturally much smaller than their home worlds - and therefore much harder to find. And it is extremely time-consuming to comb through the observational data of thousands of exoplanets for evidence of moons.

To make the search easier and faster, the authors of the new study rely on a search algorithm they developed and optimized themselves for the search for exomoons.

They published their method last year and the algorithm is available to all researchers as open source code. When applied to the observational data from Kepler-1625b and Kepler-1708b, the results were astonishing. "We would have liked to confirm the discovery of exomoons around Kepler-1625b and Kepler-1708b," says first author of the new study, MPS scientist Dr. René Heller. "But unfortunately, our analyses show otherwise," he adds.

Scientists found the cells in mice — and say they could lead to a better understanding of human appetite.

In Tokyo, engineer Moju Zhao has developed a transformative drone, named DRAGON, that can change its shape mid-flight to navigate tight spaces. The acronym DRAGON stands for "Dual-rotor embedded multilink Robot with the Ability of multi-deGree-of-freedom aerial transformatiON."

Made of multiple modules connected by battery-powered hinged joints, the drone can autonomously decide on its shape formations. Currently, it can stay airborne for three minutes, but the team aims to add more modules and grippers for object manipulation. The long-term vision is for the DRAGON to transition between flying and walking. Its design, reminiscent of serpentine shapes, is inspired by ancient Asian dragon mythology. This aligns with Japan's futuristic drone roadmap which encompasses applications in delivery, farming, and unique solutions such as drone-powered parasols. Meanwhile, MIT has developed insect-sized drones that use soft actuators mimicking the agility of bugs.

These micro-drones are resilient, capable of withstanding collisions, and even perform aerial somersaults. The drones have potential applications ranging from pollinating crops and inspecting machinery to search and rescue missions. The soft actuators are made of thin rubber cylinders coated in carbon nanotubes. When voltage is applied, an electrostatic force is produced, causing the rubber to expand and contract, resulting in wing flapping. MIT's fabrication process involves layering elastomer and electrode, each as thin as a red blood cell, leading to power-efficient and resilient drones.

If our eyes could see high-energy radiation called gamma rays, the Moon would appear brighter than the Sun! That’s how NASA’s Fermi Gamma-ray Space Telescope has seen our neighbor in space for the past decade. Gamma-ray observations are not sensitive enough to clearly see the shape of the Moon’s disk or any surface features. Instead, Fermi’s Large Area Telescope (LAT) detects a prominent glow centered on the Moon’s position in the sky.

Mario Nicola Mazziotta and Francesco Loparco, both at Italy’s National Institute of Nuclear Physics in Bari, have been analyzing the Moon’s gamma-ray glow as a way of better understanding another type of radiation from space: fast-moving particles called cosmic rays. “Cosmic rays are mostly protons accelerated by some of the most energetic phenomena in the universe, like the blast waves of exploding stars and jets produced when matter falls into black holes,” explained Mazziotta.

Because the particles are electrically charged, they’re strongly affected by magnetic fields, which the Moon lacks. As a result, even low-energy cosmic rays can reach the surface, turning the Moon into a handy space-based particle detector. When cosmic rays strike, they interact with the powdery surface of the Moon, called the regolith, to produce gamma-ray emission. The Moon absorbs most of these gamma rays, but some of them escape.

Mazziotta and Loparco analyzed Fermi LAT lunar observations to show how the view has improved during the mission. They rounded up data for gamma rays with energies above 31 million electron volts — more than 10 million times greater than the energy of visible light — and organized them over time, showing how longer exposures improve the view.

“Seen at these energies, the Moon would never go through its monthly cycle of phases and would always look full,” said Loparco. As NASA sets its sights on sending humans to the Moon by 2024 through the Artemis program, with the eventual goal of sending astronauts to Mars, understanding various aspects of the lunar environment take on new importance. These gamma-ray observations are a reminder that astronauts on the Moon will require protection from the same cosmic rays that produce this high-energy gamma radiation.

While the Moon’s gamma-ray glow is surprising and impressive, the Sun does shine brighter in gamma rays with energies higher than 1 billion electron volts. Cosmic rays with lower energies do not reach the Sun because its powerful magnetic field screens them out. But much more energetic cosmic rays can penetrate this magnetic shield and strike the Sun’s denser atmosphere, producing gamma rays that can reach Fermi.

Although the gamma-ray Moon doesn’t show a monthly cycle of phases, its brightness does change over time. Fermi LAT data show that the Moon’s brightness varies by about 20% over the Sun’s 11-year activity cycle. Variations in the intensity of the Sun’s magnetic field during the cycle change the rate of cosmic rays reaching the Moon, altering the production of gamma rays.

Download the graphic and related multimedia in HD formats from NASA Goddard’s Scientific Visualization Studio

East China Normal University’s Dr. Yi-Hsuan Pan and colleagues showed that human ancestors went through a severe population bottleneck with about 1,280 breeding individuals between around 930,000 and 813,000 years ago.

Today, there are more than 8 billion human beings on the planet. We dominate Earth’s landscapes, and our activities are driving large numbers of other species to extinction. Had a researcher looked at the world sometime between 800,000 and 900,000 years ago, however, the picture would have been quite different. Hu et al. used a newly developed coalescent model to predict past human population sizes from more than 3000 present-day human genomes (see the Perspective by Ashton and Stringer). The model detected a reduction in the population size of our ancestors from about 100,000 to about 1000 individuals, which persisted for about 100,000 years. The decline appears to have coincided with both major climate change and subsequent speciation events. —Sacha Vignieri

Quantum communications have rapidly progressed toward practical, large-scale networks based on quantum key distributions that spearhead the process. Quantum key distribution systems typically include a sender "Alice," a receiver "Bob," who generate a shared secret from quantum measurements for secure communication. Although fiber-based systems are well-suited for metropolitan scale, a suitable fiber infrastructure might not always be in place.

In a new report in npj Quantum Information, Andrej Kržič and a team of scientists developed an entanglement-based, free-space quantum network. The platform offered a practical and efficient alternative for metropolitan applications. The team introduced a free-space quantum key distribution system to demonstrate its use in realistic applications in anticipation of the work to establish free-space networks as a viable solution for metropolitan applications in the future global quantum internet.

Quantum communication network

Quantum communication typically aims to distribute quantum information between two or more parties. A series of revolutionary applications of quantum networks have provided a roadmap towards engineering a full-blown quantum internet. The proposed invention provides a heterogeneous network of special purpose sub-networks with diverse links and interconnects. The concept of quantum key distribution networks have driven this development to pave the way for other distributed quantum information processing methods to benchmark the technological maturity of quantum networks in general.

In this work, Kržič and colleagues described a metropolitan free-space network architecture to secure communications at summits, conferences and other events, with the added capacity to complement an already existing network infrastructure in the absence of end-to-end fiber connections. The quantum physicists built the architecture around a central entanglement server to stream the entangled photons to the users of the network.

The largest extinction in Earth’s history marked the end of the Permian period, some 252 million years ago. Long before dinosaurs, our planet was populated with plants and animals that were mostly obliterated after a series of massive volcanic eruptions in Siberia. Fossils in ancient seafloor rocks display a thriving and diverse marine ecosystem, then a swath of corpses. Some 96 percent of marine species were wiped out during the “Great Dying,” followed by millions of years when life had to multiply and diversify once more.

What has been debated until now is exactly what made the oceans inhospitable to life – the high acidity of the water, metal and sulfide poisoning, a complete lack of oxygen, or simply higher temperatures.

New research from the University of Washington and Stanford University combines models of ocean conditions and animal metabolism with published lab data and paleoceanographic records to show that the Permian mass extinction in the oceans was caused by global warming that left animals unable to breathe. As temperatures rose and the metabolism of marine animals sped up, the warmer waters could not hold enough oxygen for them to survive.

COVID-19, the disease caused by SARS-CoV-2, has claimed approximately 5 million lives and 257 million cases reported globally. This virus and disease have significantly affected people worldwide, whether directly and/or indirectly, with a virulent pathogen that continues to evolve as we race to learn how to prevent, control, or cure COVID-19. The focus of this review is on the SARS-CoV-2 virus’ mechanism of infection and its proclivity at adapting and restructuring the intracellular environment to support viral replication. We highlight current knowledge and how scientific communities with expertize in viral, cellular, and clinical biology have contributed to increase our understanding of SARS-CoV-2, and how these findings may help explain the widely varied clinical observations of COVID-19 patients.