Using data and samples from volunteers, including Kaiser Permanente Washington members participating in the Adult Changes in Thought Study (ACT Study), the researchers used advanced genomic technologies and machine learning models to create a timeline of the cellular and molecular changes caused by…
Mapping the disease at the cellular level identifies possible new treatment targets.
Researchers in the Nanoscience Center at the University of Jyväskylä, Finland, have used machine learning and supercomputer simulations to investigate how tiny gold nanoparticles bind to blood proteins. The studies discovered that favorable nanoparticle-protein interactions can be predicted from machine learning models that are trained from atom-scale molecular dynamics simulations. The new methodology opens ways to simulate the efficacy of gold nanoparticles as targeted drug delivery systems in precision nanomedicine.
Hybrid nanostructures between biomolecules and inorganic nanomaterials constitute a largely unexplored field of research, with the potential for novel applications in bioimaging, biosensing, and nanomedicine. Developing such applications relies critically on understanding the dynamical properties of the nano–bio interface.
Modeling the properties of the nano-bio interface is demanding since the important processes such as electronic charge transfer, chemical reactions or restructuring of the biomolecule surface can take place in a wide range of length and time scales, and the atomistic simulations need to be run in the appropriate aqueous environment.
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The book “Intelciety. Intelligent Society. Are We Ready for the Challenge?” explores the profound changes that artificial intelligence (AI) and other emerging technologies are causing in modern society. Vicente Ferreira da Silva addresses how these technologies are transforming various fields, from medicine and biotechnology to robotics and nanotechnology, and questions whether we are truly prepared to deal with these advances.
Called Evo, the AI was inspired by the large language models, or LLMs, underlying popular chatbots such as OpenAI’s ChatGPT and Anthropic’s Claude. These models have taken the world by storm for their prowess at generating human-like responses. From simple tasks, such as defining an obtuse word, to summarizing scientific papers or spewing verses fit for a rap battle, LLMs have entered our everyday lives.
If LLMs can master written languages—could they do the same for the language of life?
This month, a team from Stanford University and the Arc Institute put the theory to the test. Rather than training Evo on content scraped from the internet, they trained the AI on nearly three million genomes—amounting to billions of lines of genetic code—from various microbes and bacteria-infecting viruses.
Elon Musk has predicted that AI will surpass doctors and lawyers after a study revealed OpenAI’s ChatGPT-4 outperformed medical professionals in diagnosing illnesses.
What Happened: A study reported by The New York Times revealed that AI achieved a 90% accuracy rate, compared to 76% for doctors using ChatGPT as a tool and 74% for doctors relying on traditional resources.
Following the publication of the report, Bindu Reddy, CEO of Abacus. AI, stated that an AI doctor with access to all lab reports would be able to diagnose problems and suggest remedies better than most human doctors.
A series of studies on humans and mice examined sex differences in reactions to anesthetics, revealing that female brains are more resistant to the hypnotic effects of these drugs. Testosterone administration increased sensitivity to anesthetics in mice, while castration enhanced anesthetic resistance. In humans, females regained consciousness and recovered cognitive function faster than males after identical exposure to anesthetics. The study was published in Neuroscience.
General anesthetics are drugs that induce a reversible loss of consciousness, primarily used during surgical procedures to block pain and prevent awareness. They are essential in medicine because they enable complex surgeries that would otherwise be intolerable due to pain, allowing patients to undergo invasive procedures safely and comfortably.
The history of general anesthesia dates back to the 19th century, with the first successful public demonstration by Dr. William Morton in 1846. Before anesthetics, surgery was excruciating and dangerous, often performed only in dire cases due to the severe pain and risks. Over time, safer and more effective agents, such as chloroform and eventually modern inhaled and intravenous anesthetics, were developed. Today, general anesthesia is administered by specialized professionals called anesthesiologists, who monitor and adjust the dosage to ensure patient safety.
Brain-Computer Interfaces fascinate the sci-fi and medical communities in equal measure. Here’s how close the transformative technology is to everyday use.
Researchers at Tampere University have developed the world’s first soft touchpad that can sense the force, area and location of contact without electricity. The device utilises pneumatic channels, enabling its use in environments such as MRI machines and other conditions that are unsuitable for electronic devices. Soft devices like soft robots and rehabilitation aids could also benefit from this new technology.
Researchers at Tampere University have developed the world’s first soft touchpad that is able to sense the force, area and location of contact without electricity.
That has traditionally required electronic sensors, but the newly developed touchpad does not need electricity as it uses pneumatic channels embedded in the device for detection.