OpenAI CEO Sam Altman is confident that in the very near future, AI will surpass human capabilities.
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Unique pan-cancer immunotherapy destroys tumors without attacking healthy tissue
A new, highly potent class of immunotherapeutics with unique Velcro-like binding properties can kill diverse cancer types without harming normal tissue, University of California, Irvine cancer researchers have demonstrated.
A team led by Michael Demetriou, MD, Ph.D., has reported that by targeting cancer-associated complex carbohydrate chains called glycans with binding proteins, they could penetrate the protective shields of tumor cells and trigger their death without toxicity to surrounding tissue.
Their biologically engineered immunotherapies—glycan-dependent T cell recruiter (GlyTR, pronounced ‘glitter’) compounds, GlyTR1 and GlyTR 2—proved safe and effective in models for a spectrum of cancers, including those of the breast, colon, lung, ovaries, pancreas and prostate, the researchers report in the journal Cell.
Childhood stress strongly linked to chronic disease in adulthood, researchers report
Research published by Duke University researchers has found a strong link between higher stress in children and adverse health conditions for them later in life. Appearing in the journal Proceedings of the National Academy of Sciences, the study used measurable metrics of health over time to create a more quantitative view of how stress early in life affects health.
“We’ve had an idea for a long time, since the ’80s at least, that when children have adversity in their lives, it affects how their bodies work, not just psychologically, but also physiologically. It gets underneath the skin, and it becomes embodied in the way your body handles stress,” said co-author Herman Pontzer, Duke professor of evolutionary anthropology and global health.
Researchers focused on allostatic load (AL), which refers to the wear and tear on the body because of chronic stress. The researchers “tested associations between childhood AL and adult cardiometabolic health,” relying on biomarkers that included antibodies of C-reactive protein, which is a marker of inflammation in the body; and the Epstein-Barr virus, which is common and highly contagious; body mass index; and blood pressure.
New protein interaction map sheds light on how brain cell communication breaks down in Alzheimer’s disease
A new study led by the Icahn School of Medicine at Mount Sinai offers one of the most comprehensive views yet of how brain cells interact in Alzheimer’s disease, mapping protein networks that reveal communication failures and point to new therapeutic opportunities.
Published online in Cell, the study analyzed protein activity in brain tissue from nearly 200 individuals.
The researchers discovered that disruptions in communication between neurons and supporting brain cells called glia—specifically astrocytes and microglia—are closely linked to the progression of Alzheimer’s disease. One protein in particular, called AHNAK, was identified as a top driver of these harmful interactions.
Functional connectomics reveals general wiring rule in mouse visual cortex
The MICrONS mouse visual cortex dataset shows that neurons with similar response properties preferentially connect, a pattern that emerges within and across brain areas and layers, and independently emerges in artificial neural networks where these ‘like-to-like’ connections prove important for task performance.
Study of the world’s longest-lived person reveals rare genes and good bacteria are among the keys to a long life
What is the secret of supercentenarians? While there is no magical “elixir of life” that allows us to live forever, this incredibly rare group of people who live to be 110 years or older appears to have some biological advantage. To identify the factors that underlie extreme longevity, scientists conducted a comprehensive study of Maria Branyas, who was the world’s oldest verified living person at the time of the study.
Chatbot connections: New study reveals the truth about AI boyfriends
Advances in AI technology have ushered in a new era of digital romance, where people are forming intimate emotional connections with chatbots. For many, these AI companions are a crucial lifeline, helping to combat feelings of loneliness. Yet, despite a rapidly evolving social trend that has attracted widespread interest, it has been largely understudied by researchers.
A new analysis of the popular Reddit community, r/MyBoyfriendIsAI, is addressing the gap by providing the first in-depth insights into how intimate human–AI relationships begin, evolve and affect users.
Researchers from the Massachusetts Institute of Technology (MIT) studied 1,506 of the most popular posts from this Reddit community, which has more than 27,000 members. First, they used AI tools to read all the conversations and sorted them into six main themes, such as coping with loss. Then they used custom-built AI classifiers to review the posts again and measure specific details within them.
Compact camera uses 25 color channels for high-speed, high-definition hyperspectral video
A traditional digital camera splits an image into three channels—red, green and blue—mirroring how the human eye perceives color. But those are just three discrete points along a continuous spectrum of wavelengths. Specialized “spectral” cameras go further by sequentially capturing dozens, or even hundreds, of these divisions across the spectrum.
This process is slow, however, meaning that hyperspectral cameras can only take still images, or videos with very low frame rates, or frames per second (fps). But what if a high-fps video camera could capture dozens of wavelengths at once, revealing details invisible to the naked eye?
Now, researchers at the University of Utah’s John and Marcia Price College of Engineering have developed a new way of taking a high-definition snapshot that encodes spectral data into images, much like a traditional camera encodes color. Instead of a filter that divides light into three color channels, their specialized filter divides it into 25. Each pixel stores compressed spectral information along with its spatial information, which computer algorithms can later reconstruct into a “cube” of 25 separate images—each representing a distinct slice of the visible spectrum.