However, additional studies involving aging animals will be required to determine whether LASSS is safe and effective in vivo.
A Possible Strategy for Preserving Muscle
The discovery could support the development of new approaches for maintaining muscle repair during aging, extended bed rest, and other conditions that involve long periods of inactivity.
💬 Artificial intelligence and big data are flooding discovery pipelines with high-potential drug candidates, but this rapid innovation has created a new challenge. Simply put, our capability to design miracle molecules is vastly outstripping our technology to mass-manufacture them safely for the global public. Moving drug making from the scale of lab flasks to commercial bioreactors introduces non-linear biological and engineering shifts that can undermine tasks like purification.
⚡In this New Scientist CoLab podcast, experts from global life sciences leader Cytiva explain the hidden, high-stakes science of purification that is required to close the gap between drug discovery and the pharmacy shelf.
Fifteen years ago, I interviewed Charlie Stross about a short story called “Lobsters.”
This spring, a thousand people queued outside Tencent’s Shenzhen headquarters to raise one.
June 2011, Singularity 1 on 1. Back then, “singularity” was a word most people filed under astrophysics, not #AI. Charlie’s 2001 story “Lobsters,” which grew into Accelerando, was one of the sharpest early maps of what happens when intelligence stops being exclusively biological. Uploaded minds. Post-scarcity economics. Legal personhood for software. An economy run by optimization processes no human fully follows.
He wrote it six years before the iPhone.
Now look at 2026. OpenClaw, the open source agent built by Austrian developer Peter Steinberger, now at OpenAI, became the fastest-growing project in GitHub history. In China, installing it is called 养龙虾, “raising lobsters,” after the red logo. Shenzhen, Wuxi and Changshu rushed out subsidy packages. Retirees, schoolkids and office workers lined up for help. A grey market of house-call technicians appeared within days.
Any connection to Charlie’s story? None. The logo is a claw pun on Claude.
Chuck Brooks is the president of Brooks Consulting International and one of Executive Mosaic’s GovCon Experts.
The convergence of AI and quantum tech is creating a new frontier of innovation and risk.
This trend is evident from the White House’s FY27 research and development goals that put Artificial intelligence and quantum technologies at the center of the national agenda.
Take a blood sample from someone in the dead of winter. Take another in midsummer. Same person, same laboratory. And yet, at the level of gene activity, the molecular picture can look surprisingly different. This is not an anomaly. This, a new Nature Communications study argues, is simply how human biology works, and it has significant implications for the way biomarkers have traditionally been studied.
Researchers from Kiel University’s Excellence Cluster PMI, KU Leuven and the German Center for Neurodegenerative Diseases (DZNE) in Bonn tracked 333 volunteers in Flanders over six months, drawing blood three times and measuring the activity of roughly 14,000 genes on each occasion.
What they found suggests that an important source of biological variation has been underappreciated in many clinical studies: in 85% of all genes, the variation within a single person over time is larger than the variation between different people. In other words, for most genes, the largest differences are observed between two time points in the same individual rather than between different individuals.
Manchester’s quantum researchers are building on the Ferranti Mark I legacy, using ultra-pure silicon and single atoms to move quantum computing closer to real-world impact.
In February 1951, a machine the size of a room arrived at the University of Manchester.
The Ferranti Mark I, the world’s first commercially available general-purpose computer, came with 4,000 vacuum tubes, 100,000 soldered joints and six miles (10 kilometers) of wires. The 27 kilowatts of power it needed to operate is the equivalent of running roughly 600 midrange laptops today, yet at the time, it must have felt miraculous.
In May 2026, OpenAI released a new math result that sent shock waves throughout the world of mathematical research. A major unsolved problem called the “unit distance conjecture” had just been resolved by generative AI.
Since then, there has been a steady drumbeat of new results that either partially or completely leverage artificial intelligence to solve research-level mathematics problems. However, most new math results published in any given month are still generated by humans.
So where is this going? How good, and how quickly, will AI capabilities grow? Will most mathematical research be predominantly artificial intelligence? Or, as some mathematicians suggest, will AI combine with human ingenuity and other computer tools to create a golden age of mathematics?
Astronomers searching for signs of extraterrestrial intelligence may have been missing alien signals in part of the radio spectrum that has not recently been explored.
Most radio SETI (Search for Extraterrestrial Intelligence) surveys have focused on frequencies between 1.42 and 1.66 GHz. This range is known as the “water hole” because it lies between the natural radio frequencies emitted by hydrogen and hydroxyl, two molecules whose combination forms water.
Scientists have long thought that this relatively quiet part of the radio spectrum would be a logical place to communicate, as a technologically advanced civilization might recognize the significance of hydrogen and hydroxyl and be likely to transmit and listen there.