Scientists may have found a way to destroy cancer cells without initially relying on chemotherapy, surgery, or radiation.
The approach is called ‘molecular jackhammer’, and it relies on little more than light and a well-established medical molecule.
The technique involves using aminocyanine molecules – synthetic dyes already widely used in medical imaging – and stimulating them with near-infrared light.
According to quantum electrodynamics, the theory describing interactions between light and electrically charged particles, a sufficiently strong electric field can, in principle, convert some of its energy into particles and their antimatter partners. A particle’s antimatter partner has the same mass and, for electrically charged particles, the opposite electric charge.
The creation of particle–antiparticle pairs via an electric field and from the vacuum is known as the Schwinger effect. As the production of these pairs is strongly suppressed at electric field strengths that can be realized in a laboratory setting, observing this effect experimentally has so far proved challenging.
Researchers at the University of Science and Technology of China and other institutions have now introduced an experiment that could be used to simulate and study this rare particle production process. Their experiment, outlined in a paper published in Physical Review Letters, entails representing particles and electric fields through the arrangement and motion of ultracold rubidium atoms trapped in an optical lattice, a laser light-based pattern that can trap atoms.
Autism Spectrum Disorder (ASD) is one of the most prevalent neurodevelopmental disorders, affecting an estimated 1 in 59 children. ASD is highly genetically heterogeneous and may be caused by both inheritable and de novo gene variations. In the past decade, hundreds of genes have been identified that contribute to the serious deficits in communication, social cognition, and behavior that patients often experience. However, these only account for 10–20% of ASD cases, and patients with similar pathogenic variants may be diagnosed on very different levels of the spectrum. In this review, we will describe the genetic landscape of ASD and discuss how genetic modifiers such as copy number variation, single nucleotide polymorphisms, and epigenetic alterations likely play a key role in modulating the phenotypic spectrum of ASD patients.
Wee1 inhibitors are a promising new cancer treatment, but serious side effects threaten their adoption in the clinic.
Now, researchers from the MRC Laboratory of Medical Sciences (LMS), the University of Oxford, and UCL have discovered a previously unknown role for Wee1 that could explain these effects.
The findings could realign the drugs’ clinical progress, helping to identify patients most likely to benefit from treatment and guiding the development of safer, more targeted therapies.
In light of the ongoing challenge posed by unknown vulnerabilities in software solutions, the prompt identification and rectification of these weaknesses are of vital importance. Traditional penetration testing, although thorough, typically demands substantial human resources and time commitments. To contend with this issue, we propose an innovative penetration testing framework that incorporates natural language processing, utilizing large language model (LLM) driven multi-agent systems to automate and expedite vulnerability detection. By integrating insights from established exploit signatures and AI-driven fuzzing techniques, our framework, LLMAZD, preemptively examines target software within a controlled setting, effectively identifying both zero-day and one-day exploits, as well as system vulnerabilities, in a cost-effective manner. The framework demonstrates versatility in detecting multiple vulnerability classes, including SQL injection, Cross-Site Scripting (XSS), Cross-Site Request Forgery (CSRF), file upload vulnerabilities, and other different types, all while maintaining efficiency and cost-effectiveness throughout the testing process. Extensive evaluations on more than 20 CVE test cases reveal that the framework substantially enhances detection capabilities, reduces the overall burden of testing, and offers a practical pathway towards more secure software ecosystems.
Cyber-Security, Large Language Models (LLMs), Zero-Day Exploit, Malware, Vulnerability, Exposure, Multi-Agent Systems, Penetration Testing
In October 2020, two years before ChatGPT, I sat down with Juan Enriquez for 90 minutes to talk about right and wrong.
Not tech #ethics. Ethics.
Juan’s argument is unsettling in the best possible way: much of what we feel certain is right today rests on the technology we happen to have. Change the technology and the moral ground shifts underneath us, usually before anyone notices.
Which raises a question I still can’t shake. If our grandchildren will judge some of our certainties the way we judge our grandparents’, which ones will it be? And what happens when we hand moral decisions to machines trained on today’s certainties?
Juan has given nine TED talks, sailed around the world on an expedition that multiplied the number of known genes a hundredfold, and sat on the peace commission that negotiated a ceasefire with the Zapatistas. He also calls himself a very curious and optimistic Cro-Magnon.
We went from Catholic ethics to humility and forgiveness, from homo evolutis and #transhumanism to veganism, techno-solutionism, #AI and the singularity. Plus why those who can make you believe absurdities can make you commit atrocities.
HELIOX: WHERE EVIDENCE MEETS EMPATHY 🇨🇦 # *Country of Geniuses in a Data Center **📄*
https://youtu.be/XLGDB5C5qms](https://youtu.be/XLGDB5C5qms)](https://youtu.be/XLGDB5C5qms)
*Inside Anthropic’s S-1: rogue agents, an $80 billion paper loss, and who really holds the brake*
*Nov 1, 2026 • S8 E11 • 48:48*
An SEC filing is supposed to be dull. Anthropic’s S-1 reads like a confession, a safety manual, and a geopolitical thriller at once. 📄
New Heliox episode: Country of Geniuses in a Data Center. Inside Anthropic’s S-1: rogue agents, an $80 billion paper loss, and who really holds the brake.
In this deep dive, we decode the October 2026 IPO filing from the maker of Claude:
Canonical patches CVE-2026–112816 in LXD and MicroCloud, a CVSS 10.0 flaw enabling trusted client impersonation without private keys.
There are many contrasts between ice and fire in both real and fictional worlds – from the volcanoes of Iceland, to the Game of Thrones fantasy series.
These two elements were at play in the early, formative years of our Solar System, too.
In the region surrounding the early Sun, fire was represented by chondrules, tiny fragments of rock that had been formed through intense heat. For ice, there was matrix, a fine-grained and cold dust loaded with water ice and organic molecules.
As more people turn to large language models (LLMs) during personal crises, the companies behind them are engineering these AI-powered models to be more personal, empathetic and understanding when prompts indicate a user is in emotional distress.
The trend is raising concern about how well prepared ChatGPT, Claude, Gemini and other popular LLMs are to provide appropriate emotional support.
To address this concern, Georgia Tech researchers have developed a new neural framework that examines how different training sources influence empathy and social reasoning within these AI-powered models.
