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.
Gathering lithium, a crucial element in batteries for smartphones, electric cars and the electrical grid, is a time-consuming and energy-intensive process, but new technology could make it much easier.
Researchers at The University of Texas at Austin developed a new way to separate lithium from other co-occurring elements, potentially speeding up extraction of this critical element and increasing domestic supply. They developed nanoscale, artificial channels, inspired by the natural doors that let ions and molecules in and out of living cells, that allow lithium to pass through while restricting other competing ions that typically come with it.
These channels, tiny pores that sit inside membranes, were two to five times more selective for lithium compared with other recently developed lithium transporters. The researchers say their channels are among the most selective ever created.
Autoimmune diseases (AIDs), including systemic lupus erythematosus (SLE), anti-synthetase syndrome (ASS), systemic sclerosis (SSc), and multiple sclerosis (MS), are triggered by abnormal adaptive immunity and have various clinical manifestations. In these patients, immune intolerance to antigens leads to the formation of autoreactive T and B cells, which attack their own organs1,2 (Fig. 1). Additionally, AIDs are associated with inadequate negative regulation of abnormal immune responses by regulatory T cells (Tregs) 3. AIDs affect approximately 10% of the global population and rank among the leading causes of disability and mortality. A substantial proportion of patients present with severe, complex, and rapidly progressive disease for which curative therapies are lacking, representing a long-standing clinical challenge 4. AID can be classified into systemic and organ-specific according to their cumulative range. Examples of systemic AIDs include SLE, SSc, Sjögren Syndrome (SS), and rheumatoid arthritis (RA). Common organ-specific AIDs include multiple sclerosis (MS), neuromyelitis optica spectrum disorder (NMOSD), autoimmune encephalomyelitis (AE), and autoimmune cholangitis 5.
Immunosuppressants, including corticosteroids and disease-modifying anti-rheumatic drugs, are commonly used to treat AIDs. They suppress the immune system by inhibiting the inflammatory cascade, reducing disease severity, and slowing its progression; however, they do not cure the disease 6. Given the critical role of B cells in the development of AIDs, B cell depletion may be a potential cure. Monoclonal antibodies and antibody-drug conjugates targeting B cell surface antigens are also currently used in AID therapy but have shown limited efficacy 7.
Conventional autologous hematopoietic stem cell transplantation (ASCT) relies on high-dose chemotherapy ± total-body irradiation to eradicate aberrantly activated autoreactive T and B lymphocytes and force an immune-system “reset.” The reconstructed immune system may restore tolerance to autoantigens, thereby reducing or terminating autoimmune responses. ASCT may induce long-term remission or even functional cure in various refractory diseases. However, its substantial treatment-related toxicity—encompassing transplant-related mortality, severe infections, and disease relapse—coupled with rigorous patient-selection criteria, confines ASCT to a narrow, carefully chosen population 8. Chimeric antigen receptor T cells (CAR-T) were first used for the treatment of hematological malignancies. In vitro gene editing technology enables CAR-T cells to express chimeric antigen receptors (CAR).
New simulations suggest that powerful internal magnetic fields could allow some white dwarfs to grow far beyond a long-established stellar mass limit.
New research suggests that some white dwarfs, the incredibly dense remnants of dead stars, could grow far heavier than a fundamental limit in astrophysics predicts. Computer simulations show that powerful internal magnetic fields may allow these objects to reach about 2.4 times the Sun’s mass, well beyond the conventional limit of roughly 1.4 solar masses.
The findings, published in The Astrophysical Journal Letters, offer a possible explanation for unusually bright stellar explosions and could have implications for how astronomers measure the expansion of the universe. They also demonstrate a potential evolutionary path through which these exceptionally massive stars could form.
