Could a psychedelic drug help the brain recover from mild injuries? New research suggests that psilocybin, the mind-bending ingredient in magic mushrooms, might protect the brain from the damage caused by minor head impacts.

Even mild head impacts that don't count as concussions can raise the risk of neurodegenerative disorders such as chronic traumatic encephalopathy (CTE), so finding an effective treatment for these blows could be useful for warding off debilitating conditions down the line.

The new research, published in the journal Communications Biology, included only lab rats, so there's more work to be done to translate the findings to humans. But the early results hint at a new application for psilocybin — a drug that's already been explored for a range of other conditions, including depression, PTSD and anorexia.

Live Science spoke with study co-author Argel Aguilar-Valles, an associate professor of neuroscience at Carleton University in Ontario, about the new study and how the research might eventually translate to treatments for repetitive head injuries.

If humanity intends to engage in interstellar exploration in the near future, lightsails are currently the best option. This technology, consisting of laser arrays pushing a reflective sail and tiny spacecraft to relativistic speeds (a fraction of the speed of light), is presently the only promising method for sending missions to the nearest stars within a human lifetime. Alas, several major hurdles need to be overcome and technological developments made before any such missions are possible.

These range from developing space-based laser systems and creating materials that can survive the journey through interstellar space to testing proof of concepts in space. According to recently published results, engineers at Cornell University's Space System Design Studio (SDSS) successfully deployed two lightsail experiments - Alpha CubeSat and Sailing to the Stars - from the International Space Station (ISS).

The missions were created as part of the Museum of Science Fiction’s 2016 CubeSat Competition, a design competition for next-generation spacecraft concepts using off-the-shelf technologies. The experiments were funded by NASA's CubeSat Launch Initiative, which launched to the ISS in late 2025 aboard the NG-23 and Crew-11 missions, respectively. Both consist of origami-style lightsails and chip satellites (ChipSat) that were folded for launch (to conserve room for other payloads) and unfurled upon deployment...

Everything that’s swept the world since the 2022 release of ChatGPT — “the AI economy”; data centers; chatbots acting as best friends, doctors, and mathematicians; talk of existential risk — it all starts, in some sense, with an intern in a University of Montreal lab named Dzmitry Bahdanau.

It was 2014. The 23-year-old Belarusian, who had been coding competitively since he was a kid but hadn’t done academic research before, was asked to help figure out how to get a computer to translate sentences from English to French. Bahdanau was working with artificial neural networks, which had already shown promise in pattern-recognition tasks such as deciphering handwriting and identifying objects in photos. The networks learn to recognize patterns by strengthening and weakening connections between nodes in response to training data. Bahdanau quietly doubted their potential to achieve anything like human-level intelligence, but his adviser, the computer scientist Yoshua Bengio, and the postdoc on the project, Kyunghyun Cho, were believers. And translation was widely seen as a formidable and interesting problem for neural networks to try to solve.

Translation is not as simple as swapping each English word for a French one. Languages have different grammatical structures and are riddled with idioms and connotations, all of which had long stymied attempts to automate the process. You can’t simply implement rules of translation because there are none. But neural networks seemed promising because they learn by example. They can be trained on huge databases of paired English and French sentences to, eventually, absorb the quasi-rules, exceptions, and subtleties.

Results had been mediocre, though; the longer the sentence, the worse neural networks performed. That’s because researchers were trying to cram each sentence’s data into a fixed amount of memory before decoding the sentence in the target language. It was a bottleneck that limited how complex and sophisticated translations could be. The network architecture just wasn’t right.

So Bahdanau tried something different. “It was just obviously the right thing to do — one of these things that happens once in a while in science where it’s just very clear to someone who is not very experienced in the field,” he recalled, speaking to me from Montreal, where he still works in AI. “And it just worked. From the very first attempt.”

Bahdanau’s trick, a mathematical operation that he, Cho, and Bengio referred to as “attention,” enabled their neural network to translate long sentences just as well as short ones. That meant the approach was scalable. Other AI researchers at the time quickly integrated attention into their neural network designs. Then, in 2017, a team at Google devised a new kind of neural network architecture called a transformer that supercharged the attention method and stripped away everything else. The team’s paper, “Attention Is All You Need,” reported that transformers achieved state-of-the-art translation while requiring a fraction of the computation needed to train prior models. The paper, which has since been cited more than 250,000 times, was a watershed moment in AI. Large language models such as ChatGPT and Claude followed.

Given the staggering power that’s been unleashed, it’s worth asking what this attention mechanism is exactly, why it is “all you need,” and why machine translation was the task that unlocked it all. Attention is a way for us to understand how a single AI model can converse with us, diagnose diseases, generate realistic videos, solve long-standing math problems, and more. Is it somehow at the heart of intelligence — artificial and otherwise?

Imagine a medicine that stops seizures at their source, switches off instructions that keep a cancerous tumor growing and prevents Alzheimer's from stealing memories and wreaking havoc on the brain.

The basis for such treatment is already here. Known as oligonucleotides [pronounced ah-lee-go-noo-klee-oh-tides], these drugs are made from small bits of DNA or RNA—the blueprint cells use to make proteins.

While most drugs act on the finished products, oligonucleotides cut to the chase and intervene upstream, before the proteins have a chance to roll off the cellular assembly line. They can block production of harmful proteins or help cells make ones they need by tinkering with the instructions.

There's one big catch, however.

"Knowing what gene to target is only part of the problem," said Northeastern chemistry and chemical biology professor Ke Zhang, who is developing ways to make oligonucleotides more effective. "The other part is getting the drug to the right place in the right cells."

In the Journal of the American Chemical Society, Zhang and his colleagues present research that suggests a new way to get oligonucleotides into body tissues. The molecular structures his lab is developing shuttle the drugs to their destinations.

They resemble tiny bottlebrushes, with bristles that protect the medicines attached to them. The secret to their success lies in a short sequence of chemical building blocks incorporated into their structure. It acts as a set of delivery instructions to steer the medicine toward particular tissues.

By helping genetic medicines reach their target, this approach could unlock their potential to tackle diseases that are currently untreatable...

When Christopher Columbus made landfall in the Americas on Oct. 12, 1492, he encountered Indigenous Lucayans living on the Bahamian island now called San Salvador. Columbus wrote in his diary about "great multitudes of men" who greeted him that day, bartered with him and told him about other groups who lived on nearby islands.

But within a few decades after Columbus' arrival, the Indigenous people of the Americas were decimated by what anthropologist Eric Wolf called the "Great Dying" — a combination of epidemic disease, warfare and enslavement that led to a rapid decline in the Native population.

For centuries, researchers have been trying to figure out how many Indigenous people lived in the Americas just prior to the fateful arrival of European colonizers.

The answer to that question has been surprisingly elusive, and estimates based on historical censuses, archaeological sites and land carrying capacity in the Western Hemisphere have varied wildly.

Recent research into Native American demography has revealed that the population peaked several centuries before Europeans showed up on the shores of North America — and that if Europeans had arrived at that peak, the entire history of the continent may have been different...

After five-and-a-half years on Mars, NASA's Perseverance Rover has set a distance record for travel on another world. Since landing in Mars' Jezero Crater, an ancient paleolake, on February 18, 2021, Perseverance has travelled 45.22 km, or 28.10 miles. That puts it slightly ahead of NASA's Opportunity rover, which travelled 45.16 kilometers (28.06 miles) during its mission. It must be noted, however, that Perseverance took only 5.5 years to travel this far, while Opportunity required almost 15 years.

Comparing the plutonium-powered Perseverance to the solar-powered Opportunity is unfair. But in any case, Perseverance deserves recognition for this milestone.

“The original mission called for no more than 12.4 miles of driving. We’ve blown well past that..." - Steven Lee, Perseverance and Curiosity project manager, JPL/NASA.

Perseverance is currently in a region named “Lac de Charmes,” which is off the western end of Jezero Crater. It reached its new milestone while heading toward a feature named "Idubi," a scientific target notable for its ancient rocks. On Earth, there are no rocks as old as these because they've all been destroyed by plate tectonics.

Perseverance has found igneous rocks, a surprising result considering that scientists expected to find mostly sedimentary rocks. In fact, a primary reason Jezero Crater was chosen as the mission's landing site is because sedimentary rocks are good at preserving evidence of ancient life. While the rover found plenty of sedimentary rocks, it found igneous rocks, along with fluorite, which forms when rock interacts with heated water. This is evidence of hydrothermal activity, and scientists are hoping Perseverance will find more traces of ancient hydrothermal systems at Idubi...