Singularity HUB

Dark matter is a ghostly substance that astronomers have failed to detect for decades, yet which we know has an enormous influence on normal matter in the universe, such as stars and galaxies. Through the massive gravitational pull it exerts on galaxies, it spins them up, gives them an extra push along their orbits, or even rips them apart.

Like a cosmic carnival mirror, it also bends the light from distant objects to create distorted or multiple images, a process which is called gravitational lensing.

And recent research suggests it may create even more drama than this, by producing stars that explode.

For all the havoc it plays with galaxies, not much is known about whether dark matter can interact with itself, other than through gravity. If it experiences other forces, they must be very weak, otherwise they would have been measured.

A possible candidate for a dark matter particle, made up of a hypothetical class of weakly interacting massive particles (or WIMPs), has been studied intensely, so far with no observational evidence.

Recently, other types of particles, also weakly interacting but extremely light, have become the focus of attention. These particles, called axions, were first proposed in late 1970s to solve a quantum problem, but they may also fit the bill for dark matter.

Unlike WIMPs, which cannot “stick” together to form small objects, axions can do so. Because they are so light, a huge number of axions would have to account for all the dark matter, which means they would have to be crammed together. But because they are a type of subatomic particle known as a boson, they don’t mind.

In fact, calculations show axions could be packed so closely that they start behaving strangely—collectively acting like a wave—according to the rules of quantum mechanics, the theory which governs the microworld of atoms and particles. This state is called a Bose-Einstein condensate, and it may, unexpectedly, allow axions to form “stars” of their own.

This would happen when the wave moves on its own, forming what physicists call a “soliton,” which is a localized lump of energy that can move without being distorted or dispersed. This is often seen on Earth in vortexes and whirlpools, or the bubble rings that dolphins enjoy underwater.

The new study provides calculations which show that such solitons would end up growing in size, becoming a star, similar in size to, or larger than, a normal star. But finally, they become unstable and explode.

The energy released from one such explosion (dubbed a “bosenova”) would rival that of a supernova (an exploding normal star). Given that dark matter far outweighs the visible matter in the universe, this would surely leave a sign in our observations of the sky. We have yet to find such scars, but the new study gives us something to look for.

The researchers behind the study say that the surrounding gas, made of normal matter, would absorb this extra energy from the explosion and emit some of it back. Since most of this gas is made of hydrogen, we know this light should be in radio frequencies.

Excitingly, future observations with the Square Kilometer Array radio telescope may be able to pick it up.

Artist’s impression of the SKA telescope. Image Credit: Wikipedia, CC BY-SA

So, while the fireworks from dark star explosions may be hidden from our view, we might be able to find their aftermath in the visible matter. What’s great about this is that such a discovery would help us work out what dark matter is actually made of—in this case, most likely axions.

What if observations do not detect the predicted signal? That probably won’t rule out this theory completely, as other “axion-like” particles are still possible. A failure of detection may indicate, however, that the masses of these particles are very different, or that they do not couple with radiation as strongly as we thought.

In fact, this has happened before. Originally, it was thought that axions would couple so strongly that they would be able to cool the gas inside stars. But since models of star cooling showed stars were just fine without this mechanism, the axion coupling strength had to be lower than originally assumed.

Of course, there is no guarantee that dark matter is made of axions. WIMPs are still contenders in this race, and there are others too.

Incidentally, some studies suggest that WIMP-like dark matter may also form “dark stars.” In this case, the stars would still be normal (made of hydrogen and helium), with dark matter just powering them.

These WIMP-powered dark stars are predicted to be supermassive and to live only for a short time in the early universe. But they could be observed by the James Webb Space Telescope. A recent study has claimed three such discoveries, although the jury is still out on whether that’s really the case.

Nevertheless, the excitement about axions is growing, and there are many plans to detect them. For example, axions are expected to convert into photons when they pass through a magnetic field, so observations of photons with a certain energy are targeting stars with magnetic fields, such as neutron stars, or even the sun.

On the theoretical front, there are efforts to refine the predictions for what the universe would look like with different types of dark matter. For example, axions may be distinguished from WIMPs by the way they bend the light through gravitational lensing.

With better observations and theory, we are hoping that the mystery of dark matter will soon be unlocked.

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Image Credit: ESA/Webb, NASA & CSA, A. Martel

8 Google Employees Invented Modern AI. Here’s the Inside Story
Steven Levy | Wired
“They met by chance, got hooked on an idea, and wrote the ‘Transformers’ paper—the most consequential tech breakthrough in recent history. …Approaching its seventh anniversary, the ‘Attention’ paper has attained legendary status. The authors started with a thriving and improving technology—a variety of AI called neural networks—and made it into something else: a digital system so powerful that its output can feel like the product of an alien intelligence.”

Surgeons Transplant Pig Kidney Into a Patient, a Medical Milestone
Roni Caryn Rabin | The New York Times
“Surgeons in Boston have transplanted a kidney from a genetically engineered pig into an ailing 62-year-old man, the first procedure of its kind. If successful, the breakthrough offers hope to hundreds of thousands of Americans whose kidneys have failed. …If kidneys from genetically modified animals can be transplanted on a large scale, dialysis ‘will become obsolete,’ said Dr. Leonardo V. Riella, medical director for kidney transplantation at Mass General.”

CRISPR Could Disable and Cure HIV, Suggests Promising Lab Experiment
Clare Wilson | New Scientist
“A new way to eradicate HIV from the body could one day be turned into a cure for infection by this virus, although it hasn’t yet been shown to work in people. Several groups are investigating using CRISPR that targets a gene in HIV as a way of disabling dormant virus. Now, Carrillo and her team have shown that, when tested on immune cells in a dish, their CRISPR system could disable all virus, eliminating it from these cells.”

Microsoft Deal, Apple-Google Talks Show Tech Giants Need AI Help
Dina Bass and Jackie Davalos | Bloomberg
“The moves suggest that despite pouring billions of dollars into partnerships, investments and product development, Microsoft and Google are struggling to figure out how to capitalize on generative artificial intelligence. Neither company is moving fast enough to field consumer products that generate revenue and grab market share, and, despite their size and power, they remain vulnerable to being disrupted.”

The US Government Seems Serious About Developing a Lunar Economy
Eric Berger | Ars Technica
“For the first time ever, the United States is getting serious about fostering an economy on the moon. …In recent months, [DARPA] has stepped in to help. In December, DARPA announced that it was working with 14 different companies under LunA-10, including major space players such as Northrop Grumman and SpaceX, as well as non-space firms such as Nokia. These companies are assessing how services such as power and communications could be established on the Moon, and they’re due to provide a final report by June.”

Video: Giant Robotic Arm 3D-Prints a Two-Story House
Michael Franco | New Atlas
“A new 3D construction printer from Icon can whip out two-story concrete buildings faster and cheaper than its previous Vulcan printer. It has already been used to build a 27-ft-high structure called Phoenix House, now on display in Austin, Texas.”

Elon Musk Just Added a Wrinkle to the AI Race
Matteo Wong | The Atlantic
“Yesterday afternoon, Elon Musk fired the latest shot in his feud with OpenAI: His new AI venture, xAI, now allows anyone to download and use the computer code for its flagship software. No fees, no restrictions, just Grok, a large language model that Musk has positioned against OpenAI’s GPT-4, the model powering the most advanced version of ChatGPT.”

Hackers Found a Way to Open Any of 3 Million Hotel Keycard Locks in Seconds
Andy Greenberg | Wired
“At one private event in 2022, a select group of researchers were actually invited to hack a Vegas hotel room, competing in a suite crowded with their laptops and cans of Red Bull to find digital vulnerabilities in every one of the room’s gadgets, from its TV to its bedside VoIP phone. …Now, more than a year and a half later, they’re finally bringing to light the results of that work: a technique they discovered that would allow an intruder to open any of millions of hotel rooms worldwide in seconds, with just two taps.”

OpenAI’s Chatbot Store Is Filling Up With Spam
Kyle Wiggers | TechCrunch
“TechCrunch found that the GPT Store, OpenAI’s official marketplace for GPTs, is flooded with bizarre, potentially copyright-infringing GPTs that imply a light touch where it concerns OpenAI’s moderation efforts. A cursory search pulls up GPTs that purport to generate art in the style of Disney and Marvel properties, but serve as little more than funnels to third-party paid services, and advertise themselves as being able to bypass AI content detection tools such as Turnitin and Copyleaks.”

Image Credit: Pawel Czerwinski / Unsplash

Robotic exoskeletons could help disabled people regain their mobility, factory workers lift heavier loads, or athletes run faster. So far, they’ve been largely restricted to the lab due to the need to painstakingly calibrate them for each user, but a new universal controller could soon change that.

While the word “exoskeleton” might evoke sci-fi images from movies like Alien and Avatar, the technology is edging its way towards the real world. Exoskeletons have been tested as a way to prevent injuries in car factories, let soldiers lug around heavy packs for longer, and even help people with Parkinson’s stay mobile.

But the software controlling how much power to apply in support of a user’s limbs typically has to be carefully tweaked to fit each individual. Also, it normally only helps with a few predetermined movements it’s specially designed for.

A new approach by researchers at the Georgia Institute of Technology uses neural networks to seamlessly adapt an exoskeleton’s movements to each user’s particular posture and gait. The team says this could help get the technology out of the lab and start aiding people in everyday life.

“What’s so cool about this is that it adjusts to each person’s internal dynamics without any tuning or heuristic adjustments, which is a huge difference from a lot of work in the field,” Aaron Young, who led the research, said in a press release.

Exoskeletons use electric motors to provide extra power to a user’s limbs when carrying out strenuous activities. Most control schemes have focused on assisting well-defined activities, such as walking or climbing stairs.

A common approach, the researchers say, is to have a high-level algorithm predict what action the user is trying to take and then, when that activity is detected, initiate a special control scheme designed for that kind of movement.

This means the exoskeleton can only assist specific activities, and even if the device supports several different ones, users often have to toggle between them by pressing a button. What’s more, it means the device needs to be carefully adjusted so its control scheme matches the unique shape and dynamics of each user’s limbs.

The new approach designed by the Georgia Tech team and described in a paper in Science Robotics, instead focuses on what a user’s joints and muscles are doing at any particular point in time and providing powered support to them continuously. Their approach was tested in a hip exoskeleton, which the researchers say is useful in a wide range of scenarios.

A neural network running on a GPU chip reads data from several sensors on the exoskeleton that measure the angle of different joints and the user’s direction and speed. It uses this information to predict what movements the user is making and then directs the exoskeleton’s motors to apply just the right amount of torque to take some of the load off the relevant muscles.

The team trained the neural network on data from 25 participants walking in a variety of contexts while wearing the exoskeleton. This helped the algorithm gain a general understanding of how sensor data related to muscle movements, making it possible to automatically adapt to new users without being tailored to their idiosyncrasies.

The study showed the resulting system could significantly reduce the amount of energy users expended in a variety of activities. While the reduction in energy use was similar to previous approaches, crucially, it was not restricted to particular actions and could provide continuous support no matter what the user was doing.

While the researchers say it’s too early to know if the approach will translate to other kinds of exoskeletons, it seems the overarching idea is relatively adaptable. That suggests exoskeletons could soon become an “off-the-shelf” product assisting people in a wide range of strenuous activities.

Image Credit: Candler Hobbs, Georgia Institute of Technology

When my uncle was diagnosed with glioblastoma, I knew he was on borrowed time.

The deadliest form of brain cancer, it rapidly spreads through the brain with limited treatment options. Rounds of chemotherapy temporarily kept the aggressive tumors at bay. But they also wrecked his mind and immune system. He held on for 13 months—longer than the average survival timeline of most patients after diagnosis.

His story is just one of tens of thousands in the US alone. Despite decades spent looking for a therapy, glioblastoma remains a terrible, untreatable foe.

But hope may come from within. This month, two studies genetically engineered the body’s own immune cells to hunt down and wipe out glioblastoma brain tumors.

Therapies using these CAR (chimeric antigen receptor) T cells have been revolutionary in tackling previously untreatable blood cancers, such as leukemia. Since 2017, six CAR T-based therapies have been approved by the US Food and Drug Administration for multiple types of blood cancers. Rather than a last resort, they have now entered the therapeutic mainstream.

But CAR T therapies have always struggled to battle solid tumors. Glioblastomas are an even harder challenge. The cancerous cells form connections with neurons, rewiring neural networks to progressively change how the brain functions and eventually robbing it of cognitive function. This also makes it nearly impossible to surgically remove the tumors without harming the brain.

The new clinical trials offer a glimmer of hope that the therapy could slow the disease down.

One, led by Dr. Bryan Choi at Massachusetts General Hospital, found a single infusion of CAR T cells shrank the tumors in three people with recurrent glioblastoma. Another from the University of Pennsylvania Perelman School of Medicine used a different CAR T formulation to similarly reduce the size of brain tumors in six participants.

Though promising, the treatment wasn’t a cure. The tumors reoccurred in several people after six months. However, one man remained cancer-free beyond that point.

To be clear, these are only interim results from a small handful of participants. Both studies are still actively recruiting to further assess their results.

But to Choi, it’s a step toward expanding CAR T therapies beyond blood cancers. “It lends credence to the potential power of CAR T cells to make a difference in solid tumors, especially the brain,” he told Nature.

Cancer cells are sneaky. Our body’s immune system is constantly scouting for them, but the cells rapidly mutate to escape surveillance.

T cells are one of the main immune cell types keeping an eye out for cancer. In the past decade, scientists have given them an artificial boost with genetic engineering. These gene-edited T cells, used in CAR T therapies, can better hunt down cancerous blood cells.

Here’s how it usually works.

Physicians isolate a person’s T cells and genetically add extra protein “hooks” on their surfaces to help them better locate cancer cells. Like all cells, cancerous ones have many protein “beacons” dotted along their exteriors, some specific to each cancer. In CAR T therapy the new hooks are designed to easily grab onto those proteins, or antigens. After re-infusing the boosted cells back into the body, they can now more effectively seek and destroy cancerous cells.

While the strategy has been game-changing for blood cancers, it has faltered for solid tumors—such as those that grow in organs like the breasts, lungs, or brain. One challenge is finding the right antigens. Unlike leukemia, solid tumors are often made up of a mix of cells, each with a different antigen fingerprint. Reprogramming T cells to target just one antigen often means they miss other cancerous cells, lowering the efficacy of the treatment.

“The challenge with GBM [glioblastoma] and other solid tumors is tumor heterogeneity, meaning not all cells within a GBM tumor are the same or have the same antigen that a CAR T cell is engineered to attack,” Dr. Stephen Bagley, who led the University of Pennsylvania clinical trial, said in a press release. “Every person’s GBM is unique to them, so a treatment that works for one patient might not be as effective for another.”

So, why not add an extra “hook” to CAR T cells?

Both of the new studies used the dual-target method.

Choi’s team zeroed in on a protein called epidermal growth factor receptor (EGFR). The protein is essential to the developing brain but can lead to glioblastoma in its normal and mutated forms. The problem is the protein also occurs in other healthy tissues, such as the skin, lungs, and gut. As a workaround, the team added an “engager” protein to tether T cells to their target.

In three participants, a single infusion directly into the brain decreased the size of their tumors in a few days. The effects were “dramatic and rapid,” wrote the team. The cancer came back in two people. But in one person, a 72-year-old man, the treatment slashed his brain tumor by over 60 percent and lasted more than six months.

The Penn Medicine team also targeted EGFR. In addition, their CAR T cell recipe grabbed onto another protein that’s estimated to mark over 75 percent of glioblastomas. In the 48 hours after a direct infusion into the brain, the tumors shrank in all six participants, with the effects lasting at least two months in some. Aged 33 to 71, each person had at least one relapse of tumor growth before starting the treatment.

“We are energized by these results, and are eager to continue our trial, which will give us a better understanding of how this dual-target CAR T cell therapy affects a wider range of individuals with recurrent GBM [glioblastoma],” lead study author Dr. Donald O’Rourke said in the press release.

The treatment did have side effects. Even at a lower dose, it damaged neurons, a complication that had to be managed with a heavy dose of other medications.

Unlike previous CAR T therapies, which are infused into the bloodstream, both studies require direct injection into the brain. While potentially more effective because the engineered cells have direct contact with their target, brain surgery is never ideal.

Both teams are now dialing in their formulations to reduce side effects and make the therapies last longer. The Penn Medicine team will also map the CAR T cells’ infiltration of brain tumors over time. The dual targeting method could make it more difficult for cancer cells to evolve resistance to the therapy. By better understanding these interactions, it’s possible researchers can build better CAR T formulations for glioblastoma and other solid tumors.

It’s not a home run. But for deadly brain tumors, the studies offer a ray of hope.

Image Credit: NIAID