Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog – Page 5

Get the latest international news and world events from around the world.

Log in for authorized contributors

Each protein in the epigenome produces a different pattern of gene expression, study finds

A new study finds the proteins responsible for controlling which genes are expressed in a genome do more than simply turn a gene on or off. Essentially, each type of protein that interacts with a gene produces different behaviors—a finding with ramifications for everything from biomedical therapeutics to biological computing. A paper on the study, “Epigenome Regulators Imbue a Single Eukaryotic Promoter with Diverse Gene Expression Dynamics,” is published in the journal iScience.

At issue are “epigenome regulators.” Every organism’s genome is made up of DNA. But that DNA is bound up with many different proteins into very compact structures. The proteins that are bound to the DNA are called the epigenome, and they control which parts of the DNA get expressed. Your blood cells, nerve cells, and skin cells all have the same DNA, but perform very different functions. That’s because different parts of the DNA sequence are being expressed in each cell—and that is largely controlled by which proteins are bound to different parts of the DNA in each cell.

“We already knew that the proteins in the epigenome control the way DNA is expressed,” says Albert Keung, corresponding author of the study and an associate professor of chemical and biomolecular engineering at North Carolina State University. “Our goal here was to look at a single gene and quantify the full range of ways that the gene could be expressed by different proteins.” Keung is the Goodnight Distinguished Scholar in Innovation in Biotechnology and Biomolecular Engineering and director of biotechnology programs in NC State’s Integrative Sciences Initiative.

Six new isolated millisecond pulsars discovered with FAST

Using the Five-hundred-meter Aperture Spherical radio Telescope (FAST), Chinese astronomers have inspected two nearby galactic globular clusters, namely NGC 6517 and NGC 7078. The study resulted in the discovery of six new millisecond pulsars in these clusters, which are isolated and faint. The finding was detailed in a paper published April 9 on the arXiv pre-print server.

The physics of brain development: How cells pull together to form the neural tube

In about one out of every 1,000 pregnancies, the neural tube, a key nervous system structure, fails to close properly. Georgia Tech physicists are now helping explain why this happens, having uncovered the physics that drive neural tube closure in a pregnancy’s earliest stages.

Working with collaborators at University College London (UCL), Georgia Tech researchers used computer models to reveal how, during early development, forces generated by cells physically pull the neural tube closed—like a drawstring. This discovery offers new insight into a critical process that—when disrupted—can result in severe birth defects such as spina bifida.

“Understanding a complex developmental process like neural tube closure requires a highly interdisciplinary approach,” said Shiladitya Banerjee, an associate professor in the School of Physics. “By combining advanced biological imaging with theoretical physics, we were able to uncover the mechanical rules that drive cells to close the tube. My lab builds computational models to uncover the physical rules of living systems. The neural tube is an ideal focus because its formation requires incredible mechanical coordination.”

AI model ‘reads’ protein pairs, unlocking new insights into disease and drug discovery

Researchers have developed a new artificial intelligence (AI) model that can more accurately predict how proteins interact with one another—an advancement that could accelerate drug discovery and deepen insights into diseases such as cancer.

Led by Professor Zhang Yang, Senior Principal Investigator from the Cancer Science Institute of Singapore (CSI Singapore) at the National University of Singapore, and published in Nature Communications, the study introduces a paired protein language model (PPLM) that learns from two interacting proteins simultaneously, rather than analyzing them in isolation. This marks a significant shift in how AI is applied to biology, enabling more accurate prediction of protein–protein interactions that underpin nearly all cellular processes.

A truly invisible device that does not disturb its surroundings and its metamaterial shell

Metamaterials are carefully engineered materials that possess desirable properties and can be used to manipulate electromagnetic, acoustic, or other types of waves in interesting ways. Some materials scientists and engineers have been trying to use these materials to develop so-called invisible devices, or, in other words, devices that do not disturb the environment around them or reveal their presence to other technologies nearby.

Most proposed approaches for realizing invisible devices entail surrounding devices with a metamaterial shell that prevents scattering. While devices created using these strategies do not disturb their surrounding environment, they still distort what is happening within the metamaterial shell, thus they remain partly visible.

Researchers at Fudan University have introduced a new approach to realize devices that are truly and entirely invisible using metamaterials. Their proposed solution, outlined in a paper published in Physical Review Letters, was found to eliminate scattering effects both outside and inside a metamaterial cloaking shell.

World’s largest collection of Olympiad-level math problems now available to everyone

Every year, the countries competing in the International Mathematical Olympiad arrive with a booklet of their best, most original problems. Those booklets get shared among delegations, then quietly disappear. No one had ever collected them systematically, cleaned them, and made them available—not for AI researchers testing the limits of mathematical reasoning, and not for the students around the world training for these competitions largely on their own.

Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), King Abdullah University of Science and Technology (KAUST), and HUMAIN have now done exactly that.

MathNet is the largest high-quality dataset of proof-based math problems ever created, and it is not closed. Comprising more than 30,000 expert-authored problems and solutions spanning 47 countries, 17 languages, and 143 competitions, it is five times larger than the next biggest dataset of its kind. The work will be presented at the International Conference on Learning Representations (ICLR 2026) in Brazil later this month.

What makes Mars’ magnetotail flap? Two spacecraft point to magnetic reconnection

The sun continuously blasts charged, magnetic field-carrying particles, or plasma, in all directions. This solar wind interacts with the magnetic fields and atmospheres of several of our solar system’s planets and other bodies, sculpting long magnetic tails of charged particles—magnetotails—that stretch into space behind them.

Magnetotails contain thin layers of electric current-carrying plasma sheets, which sometimes “flap” in an up-and-down waving motion. Spacecraft observations have revealed that flapping in Earth’s magnetotail can be driven by a process called magnetic reconnection, in which magnetic field lines rapidly break and then snap together in a new configuration, releasing stored energy. However, whether reconnection plays this same role beyond Earth has thus far been a mystery.

Yuanzheng Wen and colleagues report the first evidence that magnetic reconnection may also trigger magnetotail flapping at Mars. Their findings are published in the journal AGU Advances.

AI model accurately predicts the spread of wildfires in real time

USC researchers are developing a computational model that combines satellite data and physics-based simulations to forecast a wildfire’s path, intensity, and growth rate. If you’ve ever been evacuated from your home during a wildfire, you’ll be aware of the terrifying unpredictability of the situation. From your location on the ground—rapidly gathering a few vital belongings and attempting to identify the best route to safety—there’s no way of knowing how fast a fire is growing or which direction it’s likely to take.

That was the experience of Assad Oberai, Hughes Professor of aerospace and mechanical engineering at the USC Viterbi School of Engineering. He was evacuated from his home during the Eaton Fire in January 2025—one of the most destructive wildfires in Southern California history, burning for 24 days before full containment and leaving more than 9,400 structures destroyed and over 1,000 damaged.

“Due to changing climate, we’re seeing more of these extremely intense fires—those that burn very fast and very bright,” he reflected. “We have the data at our fingertips. It all comes down to how we put it to use.”

/* */