Lifeboat Foundation

If you’ve ever opened a box from IKEA and wished the pieces inside could somehow spontaneously merge to form a table or chair, then a simple virus could have a thing or two to teach you. Self-assembly of complex molecules is essential for a wide array of biological structures, including proteins, cell membranes, or even entire viruses. Supramolecular chemistry is a field of study that attempts to build large molecules out of a discrete number of…

Researchers went ‘bioprospecting’ in marine microbes, looking for those that can perform helpful functions like eating plastic or generating antibiotics. | Earth And The Environment.

Summary: A new study using artificial intelligence has provided novel insights into how the brain predicts future events and processes information. Researchers discovered that the brain’s spontaneous activity, even without external stimuli, plays a critical role in how we think and feel.

By analyzing local field potentials (LFPs), they uncovered how the brain remains active in anticipating possible scenarios, even in a resting state. These findings could lead to better diagnostic tools and treatments for neurological diseases.

Marfan syndrome is a genetic disorder that leads to a greater risk of aneurysms developing in a patient’s aorta. Early detection is key to survival. Researchers at Yale School of Medicine studied the use of artificial intelligence in the diagnostic process. The results could eventually lead to an easier and more accessible test.

Related: Future moon astronauts may 3D-print their supplies using lunar minerals

“With the printing of the first metal 3D shape in space, ESA Exploration teams have achieved a significant milestone in establishing in-orbit manufacturing capabilities. This accomplishment, made possible by an international and multidisciplinary team, paves the way for long-distance and long-duration missions where creating spare parts, construction components, and tools on demand will be essential,” said Daniel Neuenschwander, director of Human and Robotic Exploration at ESA, in a statement.

This groundbreaking technology continues to expand its applications on Earth, revolutionizing fields such as medicine, fashion, art, construction, food production and manufacturing. In space, as long-duration missions to the moon and potentially Mars take shape, astronauts will need a means of independently repairing or creating tools or parts for machinery or structures that would be difficult to carry onboard a spacecraft, which have limited capacity.

She’s been doing stem cell therapy for 8 years. She is 53.

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Humans have been trying to cheat death for thousands of years. Myths about elixirs promising immortality span various cultures, as do real concoctions that often did more harm than good. One of the most misguided attempts at creating a potion for immortality involved the first emperor of China and mercury pills. In his obsession with finding a formula that would grant him eternal life, Qin Shi Huang downed mercury and other toxic substances nearly two millennia ago, believing his alchemists had hit upon the perfect magical tonic. Unsurprisingly, he died prematurely at age 49.

Archeologists have discovered another 2,000-year-old “elixir for immortality” that sheds light on the true cost of chasing down eternal life.

While excavating the tomb of a Western Han noble family in China’s Henan province in 2018, researchers unearthed a bronze pot. At first, the team thought the liquid inside was wine, but more recently determined that it was an alchemist’s formulation: a yellow liquid containing potassium nitrate and alunite. These two ingredients are cited in ancient Taoist texts as ingredients for immortality. Potassium nitrate is an inorganic salt used today as a natural source of nitrate, and is a useful ingredient in food preservatives, fertilizer, and fireworks. Alunite is a mineral that forms in volcanic or sedimentary environments when sulfur-rich minerals oxidize. It has historically been used to make alum, which is important for water purification, tanning, and dyeing.

Australian physicists resolve time travel paradox, showing it could be possible according to einstein’s theory.

Australian physicists have demonstrated that time travel could be theoretically possible by resolving the classic grandfather paradox. By aligning Einstein’s theory of general relativity with classical dynamics, researchers at the University of Queensland showed that time travel scenarios, such as altering past events, can coexist without resulting in logical inconsistencies. They used a model involving the coronavirus pandemic to illustrate how events would adjust themselves to avoid paradoxes. This research suggests that time travel, while complex, does not inherently create contradictions and could be feasible according to current mathematical models.

After reading the article, a Reddit user named Harry gained more than 524 upvotes with this comment: Isn’t the problem with time travel that it is also space travel? The earth isn’t in the same spot now as it was when you first started reading my comment, the earth travels very fast in space so wouldn’t you also have to find out where in space the earth was in 1950 (chose random date) in order to physically travel there? And how could we know where in physical space the earth was in 1950?

We present the first open-source benchmark to evaluate LLMs in their ability to operate as agents in simulated clinical environments. Diagnosing and managing a patient is a complex, sequential decision making process that requires physicians to obtain information—such as which tests to perform—and to act upon it. Recent advances in artificial intelligence (AI) and large language models (LLMs) promise to profoundly impact clinical care. However, current evaluation schemes overrely on static medical question-answering benchmarks, falling short on interactive decision-making that is required in real-life clinical work. Here, we present AgentClinic: a multimodal benchmark to evaluate LLMs in their ability to operate as agents in simulated clinical environments. In our benchmark, the doctor agent must uncover the patient’s diagnosis through dialogue and active data collection. We present two open benchmarks: a multimodal image and dialogue environment, AgentClinic-NEJM, and a dialogue-only environment, AgentClinic-MedQA. Agents in AgentClinic-MedQA are grounded in cases from the US Medical Licensing Exam~(USMLE) and AgentClinic-NEJM are grounded in multimodal New England Journal of Medicine (NEJM) case challenges. We embed cognitive and implicit biases both in patient and doctor agents to emulate realistic interactions between biased agents. We find that introducing bias leads to large reductions in diagnostic accuracy of the doctor agents, as well as reduced compliance, confidence, and follow-up consultation willingness in patient agents. Evaluating a suite of state-of-the-art LLMs, we find that several models that excel in benchmarks like MedQA are performing poorly in AgentClinic-MedQA. We find that the LLM used in the patient agent is an important factor for performance in the AgentClinic benchmark. We show that both having limited interactions as well as too many interaction reduces diagnostic accuracy in doctor agents.