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Researchers have developed a groundbreaking cell culture platform that enables the formation of two distinct but interconnected vascular networks. Their breakthrough holds tremendous promise for advancing biomedical research. Organ-on-chips are microfluidic cell cultures that replicate human physiology, significantly reducing the costs of drug development, minimizing the need for animal testing and enabling personalized treatment.

Smart CCTV systems trained to spot blockages in urban waterways could become an important future tool in flood prevention, new research has found.

Using peptides and a snippet of the large molecules in plastics, materials scientists have developed materials made of tiny, flexible nano-sized ribbons that can be charged just like a battery to store energy or record digital information.

Using peptides and a snippet of the large molecules in plastics, materials scientists have developed materials made of tiny, flexible nano-sized ribbons that can be charged just like a battery to store energy or record digital information.

Researchers have developed a soft robotic 'finger' with a sophisticated sense of touch that can perform routine doctor office examinations, including taking a patient's pulse and checking for abnormal lumps.

161,979 new RNA viruses have been discovered using a machine learning tool that researchers believe will vastly improve the mapping of life on Earth and could aid in the identification of many millions more viruses yet to be characterized.

Quantum physicists have tapped into a kind of ghostly interaction, known as entanglement, to improve the precision of optical atomic clocks, which measure time through the natural 'ticking' of atoms.

Researchers recently developed electronic tongue capable of identifying differences in similar liquids, such as milk with varying water content; diverse products, including soda types and coffee blends; signs of spoilage in fruit juices; and instances of food safety concerns. They found that results were even more accurate when artificial intelligence used its own assessment parameters to interpret the data generated by the electronic tongue.

Researchers recently developed electronic tongue capable of identifying differences in similar liquids, such as milk with varying water content; diverse products, including soda types and coffee blends; signs of spoilage in fruit juices; and instances of food safety concerns. They found that results were even more accurate when artificial intelligence used its own assessment parameters to interpret the data generated by the electronic tongue.

The discovery that certain smells can be linked to specific neurons is helping us understand how the brain encodes concepts

We might not be able to cool the world down again after overshooting the 1.5°C warming limit – and even if we can, a lot of irreversible damage will have been done

The discovery that a small blue blob of neurons, the locus coeruleus, controls your mode of thinking suggests ways to increase learning, creativity, focus and alertness

Today’s Jesus and Mo strip, called “crazier,” is going to get the artist in trouble!

If gravity is a truly quantum entity, something as simple as measuring the strength of an object’s gravitational field should change its quantum state

We still have a few batches of photos from readers, but I’m rationing them out. PLEASE send your good wildlife photos.  The death of this section would be a blow to me.

Today’s photos come from Rik Gern of Austin, Texas, showing various bits of plants. The captions are Rik’s, and you can enlarge the photos by clicking on them.

Here is a collection of  nuts and seed pods found while taking walks around the neighborhood. I have a habit of picking them up, marveling at them, sticking them in my pocket, and then making little displays or shelf decorations with them when I get home. That was starting to get out of hand, so I decided it was time take some pictures of them before cleaning house and returning them to nature.

This exotic item is a Magnolia seed pod (Magnolia grandiflora). It looks very large in these close-up photos, but in reality the body is a little over two inches long and about an inch and a half wide. The stem is one inch long.

This picture makes it look like some sort of strange sleeping mammal:

Here is a cluster that includes the seed pod from a Red Yucca (Hesperaloe parviflora), along with acorns from Post Oak (Quercus stellata) and Burr Oak (Quercus macrocarpa) trees:

Viewed up close, the Red Yucca seed pod almost looks like pale green skin with veins under the surface.

The Pecans (Carya illinoinensis) are the most at home in this collection since the background consists of Pecan bark and leaves. Pecans are very common around here and are fun to harvest in the fall.

This strange looking object is called a gum drop and is a seed pod for the American Sweetgum tree (Liquidambar styraciflua). The seeds are long gone and all that remains is the woody pod. People like to use these as decorations or tree ornaments, and it is not uncommon to see them spray painted or dipped in glitter.

If you squint your eyes it’s easy to see faces in them, so I enhanced the effect by playing with saturation, contrast, and a few other variables to make this grouping look like a spooky wooden caterpillar.

Speaking of faces, here’s a ghostly looking old Black Walnut shell (Juglans nigra) lying among some gum drops, giving the collection an appropriately autumnal feel:

Well, I missed a day, but the other two Nobel Prizes in science—Chemistry and Physics—were awarded.

The Chemistry Prize, well deserved since I know about the work, went to three people: David Baker (University of Washington), Demis Hassabis (“a British computer scientist and artificial intelligence researcher”), and John M. Jumper (“an American senior research scientist at DeepMind Technologies”) for both designing proteins and predicting their three-dimensional structure simply from the sequence of amino acids—an endeavor that had largely defied previous attempts. Now you can feed the AA sequence into a computer and, lo, get the structure. And the 3D structure is immensely important in understanding protein function and figuring out how to modify proteins (and hence DNA) to act in different ways. From the Nobel Press release:

They cracked the code for proteins’ amazing structures

The Nobel Prize in Chemistry 2024 is about pro­teins, life’s ingenious chemical tools. David Baker has succeeded with the almost impossible feat of building entirely new kinds of proteins. Demis Hassabis and John Jumper have developed an AI model to solve a 50-year-old problem: predicting proteins’ complex structures. These discoveries hold enormous potential.

The diversity of life testifies to proteins’ amazing capacity as chemical tools. They control and drive all the chemi­cal reactions that together are the basis of life. Proteins also function as hormones, signal substances, antibodies and the building blocks of different tissues.

“One of the discoveries being recognised this year concerns the construction of spectacular proteins. The other is about fulfilling a 50-year-old dream: predicting protein structures from their amino acid sequences. Both of these discoveries open up vast possibilities,” says Heiner Linke, Chair of the Nobel Committee for Chemistry.

Proteins generally consist of 20 different amino acids, which can be described as life’s building blocks. In 2003, David Baker succeeded in using these blocks to design a new protein that was unlike any other protein. Since then, his research group has produced one imaginative protein creation after another, including proteins that can be used as pharmaceuticals, vaccines, nanomaterials and tiny sensors.

The second discovery concerns the prediction of protein structures. In proteins, amino acids are linked together in long strings that fold up to make a three-dimensional structure, which is decisive for the protein’s function. Since the 1970s, researchers had tried to predict protein structures from amino acid sequences, but this was notoriously difficult. However, four years ago, there was a stunning breakthrough.

In 2020, Demis Hassabis and John Jumper presented an AI model called AlphaFold2. With its help, they have been able to predict the structure of virtually all the 200 million proteins that researchers have identified. Since their breakthrough, AlphaFold2 has been used by more than two million people from 190 countries. Among a myriad of scientific applications, researchers can now better understand antibiotic resistance and create images of enzymes that can decompose plastic.

Life could not exist without proteins. That we can now predict protein structures and design our own proteins confers the greatest benefit to humankind.

Reader Simon found two tweets from the AlaphFold program showing how the protein structures come out when the amino acid sequence is fed in:

Let’s take a closer look at this protein structure determined using AlphaFold2. This protein structure is part of a huge molecular structure in the human body. More than a thousand proteins form a pore through the membrane surrounding the cell nucleus.

Animation: ©Terezia… pic.twitter.com/840RqbJrJD

— The Nobel Prize (@NobelPrize) October 9, 2024

And a petulant tweet by Oded Rechavi (I think it’s an unfair comparison):

Could ChatGPT win a Nobel in literature and economics?
(and in the future AGI might win the Peace Nobel)

— Oded Rechavi (@OdedRechavi) October 9, 2024

And this year’s Nobel Prize in Physics went to John Hopfield (emeritus professor at Princeton) and Geoffrey Hinton (emeritus professor at Toronto) who together developed models for neural networks of the kind used in the recent set of papers on decoding the fly brain.  From the press release:

They trained artificial neural networks using physics

This year’s two Nobel Laureates in Physics have used tools from physics to develop methods that are the foundation of today’s powerful machine learning. John Hopfield created an associative memory that can store and reconstruct images and other types of patterns in data. Geoffrey Hinton invented a method that can autonomously find properties in data, and so perform tasks such as identifying specific elements in pictures.

When we talk about artificial intelligence, we often mean machine learning using artificial neural networks. This technology was originally inspired by the structure of the brain. In an artificial neural network, the brain’s neurons are represented by nodes that have different values. These nodes influence each other through con­nections that can be likened to synapses and which can be made stronger or weaker. The network is trained, for example by developing stronger connections between nodes with simultaneously high values. This year’s laureates have conducted important work with artificial neural networks from the 1980s onward.

John Hopfield invented a network that uses a method for saving and recreating patterns. We can imagine the nodes as pixels. The Hopfield network utilises physics that describes a material’s characteristics due to its atomic spin – a property that makes each atom a tiny magnet. The network as a whole is described in a manner equivalent to the energy in the spin system found in physics, and is trained by finding values for the connections between the nodes so that the saved images have low energy. When the Hopfield network is fed a distorted or incomplete image, it methodically works through the nodes and updates their values so the network’s energy falls. The network thus works stepwise to find the saved image that is most like the imperfect one it was fed with.

Geoffrey Hinton used the Hopfield network as the foundation for a new network that uses a different method: the Boltzmann machine. This can learn to recognise characteristic elements in a given type of data. Hinton used tools from statistical physics, the science of systems built from many similar components. The machine is trained by feeding it examples that are very likely to arise when the machine is run. The Boltzmann machine can be used to classify images or create new examples of the type of pattern on which it was trained. Hinton has built upon this work, helping initiate the current explosive development of machine learning.

“The laureates’ work has already been of the greatest benefit. In physics we use artificial neural networks in a vast range of areas, such as developing new materials with specific properties,” says Ellen Moons, Chair of the Nobel Committee for Physics.

Both prizes show the power of AI, but it isn’t AI that decided to tackle both the chemistry and physics problems; rather, it was AI that was a tool used to solve important scientific questions.

And we have a (sort-of) winner. Though nobody guessed the Physics winners, reader Luke correctly guessed two of the three Chemistry winners (he gave only two names, Jumper and Hasabis, but I’ll let the absence of a third winner slide), and so wins an autographed book.  I ask Luke to get in touch with me to obtain his prize.

As comets travel along their orbit they dump material along the way. A stream of debris known as the Taurid swarm has been keeping astronomers attention. It’s thought the debris is the remains of comet Encke which has also been fuelling the Taurid meteor shower. The swarm is believed to be composed of mostly harmless, tiny objects but there has been concern that there may be some larger, kilometre size chunks. Thankfully, new observations reveal there are of the order of 9-14 of these 1km rocks. 

Planets, minor planets, asteroids and of course comets are the occupants of our Solar System. The comets are small objects composed largely of ice and dust or rocky material. A wonderful and accurate description of these icy wanderers is dirty snowballs. Imagine picking up a handful of snow and ice on a wintry day, you are likely to get bits of soil and stone mixed in with the snow and it’s this that earns them this name. They originate from the remote parts of the Solar System, notably the Kuiper Belt and Oort Cloud. As they approach the Sun, the warmth causes the ice to sublimate to a gas creating the gaseous coma and long tail. As the come travels along its orbit, the sublimation of ice releases dust and debris along the path. 

Comet image from Hubble

One such comet is known as Comet Encke, a short period comet with an orbital period of 3.3 years. It was first detected in 1786 by Pierre Mechain and its orbit calculated by Johnann Franz Encke in the late 19th Century. Whilst most comets originate from the Kuiper Belt or Oort Cloud, Encke seems to have found its way closer to the Sun making frequent predictable visits. Like all comets, Encke deposits debris along the way and this leads to the Taurid meteor shower which is visible in late October/early November. 

Comet Encke imaged from NASA’s Mercury MESSENGER spacecraft. Credit: NASA

A team of astronomers using the Zwicky Transient Facility (ZTF) telescope explored swathes of sky to investigate the stream of debris which is thought to have drifted from the main Taurid stream. Thought to be the remains of Comet Encke, this drifting swarm has been long puzzled astronomers and raised concerns of potential rocks heading to Earth. That is, until now. 

The study follows from previous efforts to analyse the swarm and had identified a significant number of kilometre-class rocks. Objects of this size would pose a significant threat to Earth. Back in 2013 we were reminded of such dangers by the Chelyabinsk asteroid that exploded over Russia and injured over 1,600 people. 

This image of a vapor trail was captured about 125 miles (200 kilometers) from the Chelyabinsk meteor event, about one minute after the house-sized asteroid entered Earth’s atmosphere. Credits: Alex Alishevskikh

The team announced their findings at the American Astronomical Society Division for Planetary Sciences annual meeting. They confirmed that contrary to the expectations, there are only a handful of the asteroids maybe up to 14 which are of kilometre size. Assistant research scientists Quanzhi Ye explained ‘Judging from our findings, the parent object that originally created the swarm was probably closer to 10 kilometres in diameter rather than a massive 100 kilometre object. We still need to be vigilant about asteroid impacts but we can probably sleep better now knowing these results.’

Studying features like the Taurid swarm enable us to learn more about smaller objects in the Solar System and how they break apart over time. The study will also help future asteroid detection and defence planning exercises for when real threats are identified. As for the Taurid swarm, follow up observations will be completed in future years when the swarm passes close by Earth again. 

Source : New study eases concerns over possible “doomsday” asteroid swarm

The post Good News. Comet Encke Only Threw a Handful of Giant Space Rocks in our Direction appeared first on Universe Today.

The 2024 Nobel prize in physiology or medicine goes to two researchers, Victor Ambros and Gary Ruvkun, for their work on microRNA. They began their research in the same lab in the late 1980s as postdoctoral fellow, and then continued to collaborate after they each started their own labs. Their research involves a key question about multicellular life. Every cell in the […]

The post microRNA – 2024 Nobel in Physiology or Medicine first appeared on Science-Based Medicine.

NASA has sent a whole host of spacecraft across the Solar System and even beyond. They range from crewed ships to orbit and to the Moon to robotic explorers. Among them are a range of mission classes from Flagships to Discovery Class programs. Now a new category has been announced: Probe Explorers. This new category will fill the gap between Flagship and smaller missions. Among them are two proposed missions; the Advanced X-ray Imaging Satellite and the Probe Far-Infrared Mission for Astrophysics. 

NASA’s new Probe Explorers program aims to cultivate creative ideas to explore the Universe. The category is one of the largest astrophysics program from the American space agency. Nicola Fox, NASA’s associate administrator of Science Mission Directorate said of the category ‘..it has taken creativity to new heights,’ adding ‘selected concepts could enable ground breaking science responsive to the top astrophysics priorities of the decade, develop key technologies for future flagship missions, and offer opportunities for the entire community.’

The two projects that have been proposed are now due for additional scrutiny. They will each received $5million to undertake a 12 month concept study. After this period, a detailed evaluation will be undertaken to select one of the proposals in 2026 to launch in 2032. The chosen mission will become the first of NASA’s Probe Explorer program.

The Advanced X-ray Imaging Satellite is planned to be a large, flat field-of-view giving a high level of spatial resolution. It’s perfectly suited to the study of supermassive black holes and how galaxies evolve. It’s principle investigator Christopher Reynolds from the University of Maryland is keen to see it build on the results of previous X-ray observatories in understanding the power sources of a number of violent events across the Universe. 

This image shows Hercules A, a galaxy in the Hercules constellation. The X-ray observations show superheated gas, and the radio observations show jets of particles streaming away from the AGN at the center of the galaxy. The jets are almost 1 million light-years long. Image Credits: X-ray: NASA/CXC/SAO; visual: NASA/STScI; radio: NSF/NRAO/VLA.

The other mission in with a chance of the 2032 launch is the Probe Far-Infrared Mission for Astrophysics. The observatory would be a 1.8 metre telescope designed to study the far-infrared radiation that is permeating space. The James Webb Space Telescope has an infrared capability but this new proposal will help to cover the electromagnetic spectrum which is between the JWST and radio telescopes.  Managed by the Jet Propulsion Laboratory, it will attempt to answer questions about the origins of planets, of supermassive black holes, stars and cosmic dust. 

Annotated image of Digel Cloud 2S captured by Webb’s NIRCam (Near-Infrared Camera) and MIRI (Mid-Infrared Instrument), with compass arrows, a scale bar, colour key, and graphic overlays for reference. The north and east compass arrows show the orientation of the image on the sky. Note that the relationship between north and east on the sky (as seen from below) is flipped relative to direction arrows on a map of the ground (as seen from above). The scale bar is labelled in light-years and arcseconds. One light-year is equal to about 9.46 trillion kilometres. One arcsecond is equal to 1/3600 of one degree of arc (the full Moon has an angular diameter of about 0.5 degrees). The actual size of an object that covers one arcsecond on the sky depends on its distance from the telescope. This image shows invisible near- and mid-infrared wavelengths of light that have been translated into visible-light colours. The colour key shows which NIRCam and MIRI filters were used when collecting the light. The colour of each filter name is the visible light colour used to represent the infrared light that passes through that filter. In the main cluster are five white arrows, which highlight the paths of five protostar jets.

The Explorers Program launched in 1958 and the Probe Explorer is just a small part is this the oldest NASA program still running today. Its main objective is to provide low cost access to space with frequent launches. Missions are science led and must be relevant to NASA’s Science Mission Directorate’s astrophysics and heliophysics program. There has been significant success from the Explorers Program in the decades since its inception from the discovery of the Earth’s radiation belts to the launch of more than 90 science led missions.

Source : NASA Establishes New Class of Astrophysics Missions, Selects Studies

The post NASA Announces a New Class of Space Missions: Probe Explorers appeared first on Universe Today.

David Baker, Demis Hassabis and John Jumper have been awarded the 2024 Nobel prize in chemistry for research on predicting protein structures and designing new proteins