New digital asset class emerges globally and locally as successful YouTube channels are not just digital content outlets, but lean media businesses.
Get the latest international news and world events from around the world.
Nanoparticle injection reprograms NK immune cells to fight cancer and autoimmune disorders
MIT engineers have developed a new way to program natural killer (NK) immune cells to target cancerous T cells or T cells that have become autoreactive, leading to diseases such as lymphoma and autoimmune hepatitis.
Using their new technique, the researchers can reprogram NK cells to target diseased T cells without ever removing the NK cells from the patient’s body. Instead, they use lipid nanoparticles to deliver messenger RNA directly to NK cells. These mRNA molecules encode proteins that allow the NK cells to seek and destroy the dysfunctional T cells.
Known as CAR NK cells, these cells could be deployed against a variety of diseases. The MIT team’s new approach could bypass one of the major obstacles to using these cells, which is the time and expense of manufacturing them outside the body.
A high-resolution protein-RNA binding atlas for structure-aware interaction prediction and post-transcriptional regulatory modeling
The Goodarzi lab is on fire!
RNA-binding proteins (RBPs) recognize RNA by sequence and shape, but which matters varies by site. Introducing Pythia, an interpretable AI model trained on a new high-resolution atlas of 67 RBPs—a collaboration between Genophoria, Chan Zuckerberg Biohub, UCSF, Calico, & Vector Institute.
What if an AI could look at a strand of RNA, predict how it folds in 3D, and instantly tell you which proteins will attach to it? A groundbreaking new dataset and neural network are doing just that—bringing high-resolution clarity to the invisible mechanics of gene regulation.
Decoding how proteins shape our RNA: a new atlas and AI tool for cellular control.
Inside our cells, DNA serves as the master blueprint, but RNA acts as the working copy that delivers instructions to build proteins. Once RNA is made, it is heavily managed by a special class of molecules called RNA-binding proteins (RBPs). These proteins dictate how long an RNA molecule lasts, where it travels inside the cell, and how efficiently it is translated into functional proteins.
Despite their importance, scientists have lacked high-resolution, uniform maps showing exactly where these proteins bind across the entire human genome.
To bridge this gap, a team of researchers has developed a powerful suite of new experimental and computational tools to decode how proteins and RNA interact.
Key Breakthroughs of the Study.
Built to solve your hardest problems
It’s official: Gemini 4 Argon is no longer just for early preview—it’s rolling out globally today! 🌍🚀
🔥 Just when you thought the first drop was massive, Google just flipped the switch on a massive update: Gemini 4 Argon is now globally available for everyone.
While the first announcement was all about the initial preview, today’s official update means developers, enterprises, and everyday users can actually get their hands on it right now. It is rolling out globally through the API in AI Studio and the Gemini platform, for Google AI Ultra subscribers in Google Antigravity, and for Google AI Ultra/Pro users inside the Gemini app and AI Mode in Search!
Google’s benchmarks show it ranking #1 on the Vals Index for high-stakes economic sectors like finance, coding, legal, and tax work. Real-world teams are already using it to autonomously refactor massive legacy codebases (like cutting Chrome’s browser feature separation down from months to weeks) and slash memory prep times by 40%.
Even better? It launches at an aggressive introductory price point for devs ($2 per million input tokens, $10 per million output tokens, with cached input tokens at 95% off).
The full ecosystem just unlocked.
#Gemini4Argon #GoogleAI #GoogleDeepMind #artificialintelligence
AI tool reveals what attracts immune cells to tumors and what keeps them away
Researchers at The University of Texas MD Anderson Cancer Center and collaborating institutions in Texas developed an artificial intelligence (AI) model that helps explain how immune cells find their way to specific locations in the body and why they avoid others. The findings could help scientists better understand cancer, autoimmune diseases and treatment response.
The study, published in Nature Biomedical Engineering, was co-led by Tao Wang, Ph.D., associate professor of bioinformatics and computational biology, and Linghua Wang, M.D., Ph.D., professor of genomic medicine, executive director and head of the Center for Cellular Language Intelligence, associate member of the James P. Allison Institute and focus area co-lead with the Institute for Data Science in Oncology.
“While spatial technologies can show where immune cells are located, this new tool helps us investigate why they gather in certain areas and how they reach and recognize tumor cells,” Tao Wang said. “By identifying local signals that attract immune cells as well as potential barriers that may keep them out, we may be able to identify biomarkers and therapeutic targets that could be used to improve patient outcomes.”
Quantum Teleportation Inspired by Black Holes Produces a Surprise
Beyond a black hole’s event horizon, information as we know it meets a mysterious fate.
There, in one of the most extreme environments in the Universe, quantum information is thought to become scrambled almost beyond recognition, dispersed into a bewildering tangle of quantum interactions.
Connect two such monsters to each other via an umbilical wormhole, however, and something incredible becomes possible.
