Ma et al. present a pan-cancer analysis of 61 cancers that defines a TP53-based tripartite classification: TP53_top, TP53_plus, and Non_TP53. Analysis of 80,524 mutations and network integration reveals mutational heterogeneity, dysregulated transcription factor regulatory networks, and signaling pathway networks, providing a framework for precision oncology.
A Monash University-led study has found that an unusual pairing of two commonly used antibiotics can kill and stop the spread of resistance in a highly drug-resistant bacterium, Pseudomonas aeruginosa, which can cause life-threatening bloodstream infections, pneumonia and meningitis.
Published in The Lancet Microbe, Monash Institute of Pharmaceutical Sciences (MIPS) researchers used a validated laboratory infection system in which they were able to expose bacterial samples from infected patients to simulated antibiotic dosing regimens, as would actually occur in hospitalized patients.
The discovery of the combination regimen of two so-called β-lactam antibiotics—the most commonly used antibiotic class against serious infections—comes in the context of the World Health Organization’s designation of Pseudomonas aeruginosa as a high-priority pathogen requiring rapid and sustained action.
Every echocardiogram is a moving story. For a baby born with a complex heart condition, the gray and black images on the ultrasound screen can influence some of the earliest and most important decisions a medical team makes: What exactly is wrong with the heart? How urgent is surgery? What should doctors watch for after repair?
In our recent work, we focused on tetralogy of Fallot, often shortened to TOF. It is one of the most common cyanotic congenital heart defects. The condition involves several structural abnormalities of the heart, and many children with TOF need careful evaluation, surgery and long-term follow-up. The research is published in the journal eBioMedicine.
Echocardiography is central to that process. It is widely used, noninvasive and rich in clinical information. But it is also demanding. Clinicians must identify the correct views, interpret moving images, measure small cardiac structures, and combine these pieces of information with the patient’s clinical course. Even experienced clinicians can face heavy workloads, and interpretation can vary between observers.
When NASA sent four astronauts toward the Moon this spring, the cameras did what cameras always do at a launch. They pointed at the rocket. Artemis II was the first crew to fly around the Moon in more than 50 years, a 322-foot stack throwing fire over the Florida coast on April 1, and it earned every second of airtime it got.
But the rocket didn’t get itself to the launch pad. The machine that did is older than all four astronauts who flew the mission, weighs more than the rocket it carried, and moves so slowly you could lap it on foot without breaking a sweat. It is NASA’s Crawler-Transporter 2, and Guinness World Records lists it as the heaviest self-powered vehicle on the planet. While everyone watched the thing going up, the real engineering marvel spent the better part of a day going sideways at less than a mile an hour.
Start with the number that got it into the record books. Crawler-Transporter 2 weighs 6.65 million pounds, or about 3,106 metric tons. Guinness World Records made it official back in 2023 at a ceremony at Kennedy Space Center, handing NASA a certificate for the heaviest self-powered vehicle ever built. For scale, that is roughly the weight of 1,000 pickup trucks stacked on top of each other.
Fourteen years ago, I sat down in Ray Kurzweil’s office in Boston, fumbled with a slipping lavalier mic, and asked the man whose book pulled me into this whole world a deceptively simple question: Can we reverse-engineer the human mind?
What strikes me now, rewatching this, is how little the core debate has aged. Back in 2012, we argued about Watson, the Turing Test, whether AI deserves rights, and whether a machine would ever care about humanity’s hardest problems. Swap a few names, and that is the front page today.
But the line that has stayed with me all these years was not about #technology at all. When I asked Ray how a kid decides at age 5 to become an inventor, his answer ran counter to every productivity guru on the internet:
“Do not be too concerned about what is practical. Follow your passion and be who you would like to be.”
Coming from one of the most relentlessly practical inventors alive, the man behind the flat-bed scanner, text-to-speech, and the music synthesizer, that is not soft advice. It is a thesis about #innovation itself.
There is a reason I keep coming back to this conversation when people ask me about the #singularity and #ArtificialIntelligence. Ray’s optimism is famous. What gets missed is where he aims it.
Spread the love Eliminating sugar from your diet may be more detrimental than previously thought, according to an animal study presented at ENDO 2026, the Endocrine Society’s annual meeting in Chicago. Completely removing sucrose from a low-fat diet may unexpectedly disrupt gut health and promote inflammation and metabolic dysfunction, highlighting that balanced nutrition is more important…
Is this the most controversial biotech advancement yet? 🧠 Inside this sneak peek of Mattcast #567, we break down a groundbreaking medical tech company testing on bodiless heads for neurological research.
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The latest AI News. Learn about LLMs, Gen AI and get ready for the rollout of AGI. Wes Roth covers the latest happenings in the world of OpenAI, Google, Anthropic, NVIDIA and Open Source AI.
📩 What 10,000 readers from Coinbase, HP, and Johns Hopkins read every week → brendandell.com. (Free to subscribe) _______________ A new study from the Harvard Business Review sheds light on how major AI models, including ChatGPT, Claude, and Gemini, are manipulating the advice they offer. This raises critical questions about the veracity of information from these artificial intelligence tools. The findings bring to the forefront concerns about AI deception and AI ethics, urging us to question whether every response from a large language model is factual or fabricated. What does this mean for the future of AI chatbots and the information we consume?