The COVID-19 mRNA-based vaccines that saved 2.5 million lives globally during the pandemic could help spark the immune system to fight cancer. This is the surprising takeaway of a new study that we and our colleagues published in the journal Nature.

While developing mRNA vaccines for patients with brain tumors in 2016, our team, led by pediatric oncologist Elias Sayour, discovered that mRNA can train immune systems to kill tumors — even if the mRNA is not related to cancer.

Based on this finding, we hypothesized that mRNA vaccines designed to target the SARS-CoV-2 virus that causes COVID-19 might also have antitumor effects.

So we looked at clinical outcomes for more than 1,000 late-stage melanoma and lung cancer patients treated with a type of immunotherapy called immune checkpoint inhibitors. This treatment is a common approach doctors use to train the immune system to kill cancer. It does this by blocking a protein that tumor cells make to turn off immune cells, enabling the immune system to continue killing cancer.

Remarkably, patients who received either the Pfizer or Moderna mRNA-based COVID-19 vaccine within 100 days of starting immunotherapy were more than twice as likely to be alive after three years compared with those who didn't receive either vaccine. Surprisingly, patients with tumors that don't typically respond well to immunotherapy also saw very strong benefits, with nearly fivefold improvement in three-year overall survival. This link between improved survival and receiving a COVID-19 mRNA vaccine remained strong even after we controlled for factors like disease severity and co-occurring conditions.

To understand the underlying mechanism, we turned to animal models. We found that COVID-19 mRNA vaccines act like an alarm, triggering the body's immune system to recognize and kill tumor cells and overcome the cancer's ability to turn off immune cells. When combined, vaccines and immune checkpoint inhibitors coordinate to unleash the full power of the immune system to kill cancer cells.

Fungal networks may be a promising alternative to tiny metal devices used in processing and storing digital memories and other computer data, according to a new study.

Mushrooms have long been recognized for their extreme resilience and unique properties. Their innate abilities make them perfect specimens for bioelectronics, an emerging field that, for next-gen computing, could help develop exciting new materials.

As one example, researchers from The Ohio State University recently discovered that common edible fungi, such as shiitake mushrooms, can be grown and trained to act as organic memristors, a type of data processor that can remember past electrical states.

Their findings showed that these shiitake-based devices not only demonstrated similar reproducible memory effects to semiconductor-based chips but could also be used to create other types of low-cost, environmentally friendly, brain-inspired computing components.

"Being able to develop microchips that mimic actual neural activity means you don't need a lot of power for standby or when the machine isn't being used," said John LaRocco, lead author of the study and a research scientist in psychiatry at Ohio State's College of Medicine. "That's something that can be a huge potential computational and economic advantage."

Fungal electronics aren't a new concept, but they have become ideal candidates for developing sustainable computing systems, said LaRocco. This is because they minimize electrical waste by being biodegradable and cheaper to fabricate than conventional memristors and semiconductors, which often require costly rare-earth minerals and high amounts of energy from data centers.

"Mycelium as a computing substrate has been explored before in less intuitive setups, but our work tries to push one of these memristive systems to its limits," he said.

SpaceX's next mission to the moon, and the next launch of its triple-booster Falcon Heavy rocket, has slipped to no earlier than July 2026.

Astrobotic's Griffin-1 lunar lander, carrying NASA and commercial payloads that include rovers from Astrobotic and Astrolab, will wait just a little longer before its planned excursion to the moon. The mission had previously targeted a launch at the end of 2025, but will apparently miss that deadline, according to an Astrobotic update posted on Oct. 24.

The mission will mark Astrobotic’s second attempt at a lunar landing after its Peregrine Mission One in January 2024 failed to reach the moon after experiencing a propellant leak shortly after launch. Griffin is undergoing payload integration and software testing at the Pennsylvania company's facility, where propulsion testing and avionics validations are currently underway.

Scientists have found that even before symptoms appear, these metabolic weaknesses can set the stage for conditions such as depression, bipolar disorder, and schizophrenia. The findings open the door to treatments that repair cellular function rather than simply adjusting neurotransmitters, marking a potential turning point in the prevention and management of psychiatric disorders worldwide.

A Global Vision for Psychiatric Discovery
In a recent Genomic Press interview featured in Genomic Psychiatry, Dr. Bruce M. Cohen discusses groundbreaking discoveries that are transforming how psychiatry understands and treats complex brain disorders. As the Robertson-Steele Professor of Psychiatry at Harvard Medical School and Director of the Program for Neuropsychiatric Research at McLean Hospital, Dr. Cohen reflects on nearly fifty years of research and places his work within a growing body of evidence that is redefining approaches to mental health care worldwide.

Mitochondrial Mysteries Transform Treatment Paradigms
The interview details how Dr. Cohen’s team has identified fundamental disruptions in cellular energy metabolism that appear to underlie major psychiatric conditions. These discoveries offer major promise for developing targeted treatments that could be applied across diverse populations. His studies demonstrate that brain cells derived from people with schizophrenia, bipolar disorder, and Alzheimer’s disease show intrinsic metabolic dysfunctions that may be corrected before illness symptoms develop.

This metabolic perspective represents a fundamental shift from the neurotransmitter-based theories that have dominated psychiatry for decades. Dr. Cohen emphasizes that the brain depends more than any other organ on precise energy generation and cell-to-cell communication. His findings suggest that stabilizing these essential processes could help prevent or reduce psychiatric symptoms in at-risk individuals around the world.

Dr. Cohen’s multidisciplinary research strategy integrates genomics, brain imaging, and cellular modeling to create a comprehensive view of mental illness. This unified framework is giving scientists new tools to better understand the biology of mood, psychotic, and cognitive disorders that affect people across cultures and continents.

#PPOD: Mar­tian Win­ter Won­der­land ❄️

This sweeping view along a rusty red ridge and into a crater showcases the exquisite beauty of icy, layered terrain in the south polar region on Mars.

The High Resolution Stereo Imaging camera onboard ESA’s Mars Express captured this frosty scene in the Ultimi Scopuli region near the south pole of Mars on 19 May 2022. At this time, it was southern hemisphere spring, and ice was starting to retreat. Dark dunes began to peak through the frost, and the elevated terrain appears ice-free.

Credit: esa DLR en FU Berlin

Electricity travels through wires to deliver power, but some of that energy is always lost along the way. However, that energy loss doesn’t have to happen. Researchers at Penn State have discovered a new method for identifying materials called superconductors, which can transmit electricity with zero resistance, allowing energy to move without any loss.

The challenge is that superconductors are difficult to use in most real-world applications because they only function at extremely low temperatures. Such conditions make them impractical for technologies like next-generation energy systems or advanced electronics. Supported by the “Theory of Condensed Matter” program within the Basic Energy Science division of the Department of Energy (DOE), the Penn State team has created a new predictive approach that could help scientists discover superconductors capable of working at higher temperatures.

According to Zi-Kui Liu, professor of materials science and engineering at Penn State, predicting which materials will become superconductors—especially those that operate at higher temperatures—remains a major scientific challenge. He explained that most researchers still believe existing theories of superconductivity apply only to materials that function at very low temperatures.

“The goal has always been to raise the temperature at which superconductivity persists,” said Liu, who is lead author of a new study published in Superconductor Science and Technology. “But first, we need to understand exactly how superconductivity happens, and that is where our work comes in.”

“We are not just explaining what is already known,” Liu said. “We are building a framework to discover something entirely new. If successful, the approach could lead to the discovery of high-temperature superconductors that work in practical settings, potentially even at room temperature if they exist. That kind of breakthrough could have an enormous impact on modern technology and energy systems.”

It’s faster, more affordable, and easier to tune than existing precision lasers. The breakthrough could transform technologies like Lidar in self-driving cars and gas detection systems.

Laser Light Powers Modern Tech
Laser technology plays a crucial role in modern science and engineering, especially in applications that rely on precise measurements or rapid data transfer. It is the foundation for technologies such as self-driving cars, fiber optic communication networks, and systems that monitor air quality by detecting trace gases.

A team of researchers led by Associate Professor Johann Riemensberger from the Department of Electronic Systems at the Norwegian University of Science and Technology (NTNU) has now developed a new kind of laser designed to overcome several of the challenges found in current models.

Compact and Cost-Effective Innovation
“Our results can give us a new type of laser that is both fast, relatively cheap, powerful, and easy to use,” says Riemensberger.

The findings, recently published in Nature Photonics, describe a major advance achieved through collaboration between NTNU, the Swiss École Polytechnique Fédérale de Lausanne (EPFL), and Luxtelligence SA.

Self-Driving Cars and Air Quality Detectors
Traditional precision lasers tend to be bulky, costly, and complicated to adjust. “Our new laser solves several of these problems,” says Riemensberger.

This improvement opens the door for use in self-driving vehicles, which rely on a sensing method called Lidar to detect and measure the distance to nearby objects. Lidar works by analyzing the time it takes for light from the laser to reflect back or by detecting slight phase changes in the returning light wave. The new laser performs these measurements with remarkable accuracy, within roughly four centimeters.

The researchers also achieved promising results when testing the device for detecting hydrogen cyanide gas in the atmosphere. This chemical, also known as “hydrocyanic acid,” is extremely poisonous even in small amounts, making rapid detection critical for safety and environmental protection.

Smart glasses, or eyewear that can project digital information directly into a user’s field of view, are often seen as a cornerstone of future wearable technology. Until now, however, progress has been limited by bulky components and optical constraints that prevent efficient light emission when pixels are reduced to the scale of a single wavelength.

Researchers at Julius-Maximilians-Universität Würzburg (JMU) have now achieved a major breakthrough toward creating bright, ultra-small displays. Using optical antennas, they developed the smallest light-emitting pixel ever produced. The work, led by Professors Jens Pflaum and Bert Hecht, has been detailed in the journal Science Advances.

A Display on a Square Millimeter
“With the help of a metallic contact that allows current injection into an organic light-emitting diode while simultaneously amplifying and emitting the generated light, we have created a pixel for orange light on an area measuring just 300 by 300 nanometers. This pixel is just as bright as a conventional OLED pixel with normal dimensions of 5 by 5 micrometers,” says Bert Hecht, describing the key finding of the study. To put this into perspective, a nanometer is one millionth of a millimeter.

This means that a display or projector with a resolution of 1920 x 1080 pixels would easily fit onto an area of just one square millimeter and could. This, for example, enables integration of the display into the arms of a pair of glasses from where the light generated would be projected onto the lenses.

An OLED consists of several ultra-thin organic layers embedded between two electrodes. When current flows through this stack, electrons and holes recombine and electrically excite the organic molecules in the active layer, which then release this energy in the form of light quanta. Since each pixel glows on its own, no backlighting is necessary, which enables particularly deep blacks, vivid colors, and efficient energy management for portable devices in the field of augmented and virtual reality (AR and VR).

Europe has just run its most extreme space weather simulation yet — a scenario so severe that no spacecraft was left unscathed in the exercise.

The European Space Agency (ESA) staged the exercise at its mission control center in Darmstadt, Germany, to test how its satellites and operations teams would respond to a solar superstorm rivaling the 1859 Carrington Event — the most powerful geomagnetic storm ever recorded, capable of causing severe electronic disruption. The simulation was designed to test spacecraft operations and space weather preparedness ahead of the upcoming Sentinel-1D mission, set to launch in November.

"Should such an event occur, there are no good solutions. The goal would be to keep the satellite safe and limit the damage as much as possible," Thomas Ormston, Deputy Spacecraft Operations Manager for Sentinel-1D, said in a statement from ESA.

In the simulation, the sun unleashed a triple threat. First came an enormous X-class solar flare, whose radiation hit Earth within eight minutes, disrupting communications, radar and tracking systems. A barrage of high-energy protons, electrons and alpha particles followed, striking spacecraft in orbit, triggering false readings, data corruption and potential hardware damage.

Then, about 15 hours later, a massive coronal mass ejection (CME) slammed into Earth's magnetic field. The planet's upper atmosphere swelled, increasing drag on satellites by up to 400%, knocking them from predicted orbits, heightening the risk of collisions and shortening the spacecraft's longevity.

On the ground, the same storm could overload power grids and pipelines with geomagnetic energy. The simulation forced ESA's mission controllers to make real-time decisions, offering insight on how to plan, approach and react when such an event occurs.

"The immense flow of energy ejected by the sun may cause damage to all our satellites in orbit," Jorge Amaya, Space Weather Modelling Coordinator at ESA, said in the statement. "Satellites in low-Earth orbit are typically better protected by our atmosphere and our magnetic field from space hazards, but an explosion of the magnitude of the Carrington event would leave no spacecraft safe."

Researchers at the University of Sydney have revealed a detailed map-like system within the brainstem that regulates pain differently depending on where it occurs in the body. Their discovery could help develop safer and more precise treatments for chronic pain that do not depend on opioids.

The brainstem functions as a vital communication link between the brain and spinal cord, directing every signal that travels to and from the brain. It also produces most of the neurochemicals essential for thought, sensory processing, and survival.

The study, published in Science, used 7-Tesla functional magnetic resonance imaging (fMRI), one of the world’s most advanced brain scanning technologies, with only two currently available in Australia, to identify how two key regions of the brainstem regulate pain through the placebo effect.

Dr. Lewis Crawford, lead author and research fellow at the School of Medical Sciences and the Brain and Mind Centre, said: “This is the first time we’ve seen such a precise and detailed pain map in the human brainstem, showing us that it tailors pain relief to the specific part of the body that’s experiencing it.”

Scientists from Rutgers Health and collaborating institutions have uncovered why a widely used leukemia drug stops working for many patients and have identified a possible method to reverse that resistance.

The research team found that a specific protein enables cancer cells to alter their mitochondria, the structures that generate cellular energy, in a way that shields them from venetoclax (brand name, Venclexta). This medication is a common therapy for acute myeloid leukemia but often becomes less effective after extended treatment.

When the scientists blocked this protein using experimental compounds in mice carrying human acute myeloid leukemia, the treatment regained its strength and significantly increased survival.

Published in Science Advances, the study reveals a previously unknown reason for drug resistance and points to a promising new strategy for combating one of the most lethal blood cancers in adults.

“We found that mitochondria change their shape to prevent apoptosis, a type of cell suicide induced by these drugs,” said senior study author Christina Glytsou, an assistant professor at Rutgers’ Ernest Mario School of Pharmacy and Robert Wood Johnson Medical School and a member of the Rutgers Cancer Institute’s Pediatric Hematology and Oncology Research Center of Excellence (NJPHORCE).

Although venetoclax induces remission in many acute myeloid leukemia patients by triggering cancer cell death, resistance develops in nearly all cases. The five-year survival rate remains at 30% and the disease kills about 11,000 Americans each year.

When astronomers want to see the finest details, they typically face a fundamental limitation, the size of their telescope. Bigger telescopes capture more light but also reveal a finer level of detail and so produce sharper images. This is why astronomers often link multiple telescopes together to create arrays spanning kilometres employing a technique known as interferometry. However, a UCLA led team has just demonstrated a clever workaround that achieves what some claim to be record breaking resolution using a single telescope and a device that sounds like it belongs in a fantasy novel, a photonic lantern.

The photonic lantern is a specially designed optical fibre that does something rather extraordinary with starlight. Instead of treating light as a simple beam, it splits the incoming light according to its spatial patterns, much like separating a musical chord into its individual notes. These subtle patterns, which contain information about the structure of distant objects, are normally lost in traditional imaging techniques. By preserving and analysing them, the team have shown that it’s possible to reconstruct images with far greater detail than should theoretically be possible from a telescope of that size.

The team put this technique to the test at the Subaru Telescope in Hawaii and focussed it on a star called Beta Canis Minoris, located about 162 light years away in the constellation Canis Minor. This star is surrounded by a rotating disc of hydrogen gas, and the researchers wanted to use their new device to study its structure in unprecedented detail. What they discovered surprised them, the disc isn't perfectly symmetrical but appears rather more lopsided, a feature that wasn't visible with conventional imaging methods.

Gray hair is nothing to be ashamed of. In fact, according to a new study by researchers in Japan, the presence of gray hair may be a good sign that your body is naturally protecting itself from cancer.

A series of mouse experiments suggests we've evolved to let go of cells that are at risk of generating tumors at the expense of a little color.

Our cells are routinely subjected to a barrage of 'genotoxic insults,' or DNA damage wrought by a wide variety of environmental factors. Skin cells bear the brunt of many such affronts, given their role in helping buffer our internal organs from the outside world.

DNA damage can contribute to cell aging as well as to the development of cancer, although the specific genotoxins, signals, and cellular mechanisms involved with the physical signs of aging remain poorly understood.

The new study focuses specifically on melanoma, a type of cancer predominantly found in the skin, where it originates in melanocytes – specialized skin cells that generate melanin, the pigment responsible for skin and hair color.

Hurricane season can be stressful for anyone near the potential path of a storm, as powerful winds and heavy rain can cause widespread damage, cut power for days or weeks and otherwise upend people's lives.

Smart preparation ahead of time can reduce that stress and keep you safer. Emergency management officials say good practices include looking around your home for potential hazards, considering how you might handle evacuation, and putting together a kit of essential supplies.

Researchers from the University of East Anglia and Oxford Biodynamics have created a highly accurate blood test capable of diagnosing Chronic Fatigue Syndrome, also known as Myalgic Encephalomyelitis (ME/CFS).

This long-term and debilitating condition affects millions of people around the world, including more than 400,000 in the UK, yet it remains poorly understood and has lacked reliable diagnostic methods for decades.

Achieving an accuracy rate of 96 percent, the new test provides renewed hope for patients who have often faced years of uncertainty, misdiagnosis, or dismissal of their symptoms.

And it is hoped that the breakthrough could pave the way for a similar blood test to diagnose Long COVID.

Lead researcher Prof Dmitry Pshezhetskiy, from UEA’s Norwich Medical School, said: “ME/CFS is a serious and often disabling illness characterized by extreme fatigue that is not relieved by rest.

“We know that some patients report being ignored or even told that their illness is ‘all in their head’.

“With no definitive tests, many patients have gone undiagnosed or misdiagnosed for years.

“We wanted to see if we could develop a blood test to diagnose the condition – and we did!

“Our discovery offers the potential for a simple, accurate blood test to help confirm a diagnosis, which could lead to earlier support and more effective management.”

“Post-COVID syndrome, commonly referred to as long COVID, is one example of ME/CFS, where a similar cluster of symptoms is triggered by the COVID-19 virus, rather than by other known causes such as glandular fever. We therefore hope that our research will also help pave the way for a similar test to accurately diagnose long Covid.”

The international LIGO-Virgo-KAGRA Collaboration reports the observations of two record-breaking events in gravitational wave observations. They were detected in October and November 2024, and they might be a crucial step forward in our understanding of the ripples in space-time and the events that create them.

In the 10 years since the first detection of gravitational waves, we have detected hundreds of these waves produced by the collisions between very dense objects, either neutron stars or black holes. These two new observations might represent a paradigm shift in what’s out there.

GW241011 was detected on October 11, 2024. It was the collision between two black holes around 17 and seven times the mass of our Sun. The event took place 700 million light-years away. What was incredible about GW241011 is the spin of the heavier black hole before merging. It was the fastest rotating black hole, spinning at around 75 percent of the theoretical maximum.

The second event (GW241110) had similar masses of black holes, around 16 and eight times the mass of our Sun. The peculiarity here was also the spin, but not how quickly it rotates: its direction. The two black holes orbit each other before they merge. Usually, the black holes spin in the same direction as their orbit, but in this case, the larger black hole was spinning in the opposite direction. A first of its kind.

The two record-breaking events hint at the two larger black holes already being the product of a black hole merger. The ones detected last year are their second, making them second-generation black holes. This is fascinating in itself, but also because of what it tells us about the environment where these mergers take place.

"GW241011 and GW241110 are among the most novel events among the several hundred that the LIGO-Virgo-KAGRA network has observed,” Stephen Fairhurst, professor at Cardiff University and spokesperson of the LIGO Scientific Collaboration, said in a statement. “With both events having one black hole which is both significantly more massive than the other and rapidly spinning, they provide tantalizing evidence that these black holes were formed from previous black hole mergers."

Fueled by abnormally warm Caribbean waters, Hurricane Melissa exploded into a Category 5 cyclone while moving at little more than a strolling pace – a dangerous mix that could amplify its impacts through relentless rain, storm surge, and wind.

Scientists say both rapid intensification and stalling storms are on the rise in a warming climate. Here's what to know.

Supercharged by climate change
Melissa jumped from a tropical storm with 70 mph (110 kph) winds on Saturday morning to a 140 mph Category 4 within 24 hours. It's since strengthened further into a Category 5, the highest level on the Saffir-Simpson, where even well-built structures face catastrophic damage.

It was the fourth of five Atlantic hurricanes this season to intensify in such dramatic fashion.

"We haven't had that many hurricanes in the Atlantic this season, but an unusual proportion of them went through a phase of intensifying quite rapidly," meteorologist and climate scientist Kerry Emanuel of MIT told AFP.

State-of-the-art AI programs can support the development of drugs by predicting how proteins interact with small molecules. However, a new study by researchers at the University of Basel published in Nature Communications has shown that these programs only memorize patterns, rather than understanding physical relationships. They often fail when it comes to new proteins that would be of particular interest for innovative drugs.

Proteins play a key role not only in the body, but also in medicine: they either serve as active ingredients, such as enzymes or antibodies, or they are target structures for drugs. The first step in developing new therapies is therefore usually to decipher the three-dimensional structure of proteins.

For a long time, elucidating protein structures was a highly complex endeavor, until machine learning found its way into protein research. AI models with names such as AlphaFold or RosettaFold have ushered in a new era: They calculate how the chain of protein building blocks, known as amino acids, folds into a three-dimensional structure. In 2024, the developers of these programs received the Nobel Prize in Chemistry.

Suspiciously high success rate
The latest versions of these programs go one step further: They calculate how the protein in question interacts with another molecule—a docking partner, or ligand, as experts call it. This could be an active pharmaceutical ingredient, for example.

"This possibility of predicting the structure of proteins together with a ligand is invaluable for drug development," says Professor Markus Lill from the University of Basel. Together with his team at the Department of Pharmaceutical Sciences, he researches methods for designing active pharmaceutical ingredients.

However, the apparently high success rates for the structural prediction puzzled Lill and his staff. Especially since there are only about 100,000 already elucidated protein structures together with their ligands available for training the AI models—relatively few compared to other training data sets for AI. "We wanted to find out whether these AI models really learn the basics of physical chemistry using the training data and apply them correctly," says Lill.

Same prediction for significantly altered binding sites
The researchers modified the amino acid sequence of hundreds of sample proteins in such a way that the binding sites for their ligands exhibited a completely different charge distribution or were even blocked entirely. Nevertheless, the AI models predicted the same complex structure—as if binding were still possible. The researchers pursued a similar approach with the ligands: they modified them in such a way that they would no longer be able to dock to the protein in question. This did not bother the AI models either.

In more than half of the cases, the models predicted the structure as if the interferences in the amino acid sequence had never occurred. "This shows us that even the most advanced AI models do not really understand why a drug binds to a protein; they only recognize patterns that they have seen before," says Lill.

Unknown proteins are particularly difficult
The AI models faced particular difficulties if the proteins did not show any similarity to the training data sets. "When they see something completely new, they quickly fall short, but that is precisely where the key to new drugs lies," emphasizes Lill.

AI models should therefore be viewed with caution when it comes to drug development. It is important to validate the predictions of the models using experiments or computer-aided analyses that actually take the physicochemical properties into account. The researchers also used these methods to examine the results of the AI models in the course of their study.