Lifeboat Foundation

The projects are poised to offer unprecedented insights into human genetic diversity and improve treatment of disease.

Persistent chronic inflammation – also recognized as metaflammation or inflammaging – emerges as a consistent factor in ailing populations, in conditions correlated with age-related deterioration and even in ostensibly robust individuals. This phenomenon has been correlated with the onset of autoimmune disorders such as psoriasis and lupus, as well as chronic diseases including diabetes, cardiovascular disease, Alzheimer’s and Parkinson’s, among others. Investigations have substantiated that environmental and lifestyle variables such as smoking, a poor diet, physical inactivity and lack of or poor quality sleep can contribute to the perpetuation of chronic underlying inflammation.

Nicotinamide adenine dinucleotide (NAD+) is a critical coenzyme; vital for the functionality of all living cells, the preservation of intracellular NAD+ pools plays a crucial role in supporting cellular and metabolic processes. Key among these processes is the production of cellular energy, adenosine triphosphate (ATP), and DNA repair. Research indicates that a decrease in NAD+ levels is linked to compromised inflammatory responses and innate immune dysfunction. This implies that the levels of NAD+ may play a critical role in the operational efficacy of immune cells.

NR is an efficient NAD⁺ precursor; clinically proven to increase NAD⁺ safely and effectively it has become a popular supplement, and there is a growing body of clinical evidence demonstrating the anti-inflammatory effects of NR supplementation (either alone or in combination with other ingredients) for healthy, older adults, or those with inflammation-related disorders [4]. Indeed, NR supplementation has potential for more robust effects among the elderly and diseased populations as they tend to have compromised NAD⁺ and a higher inflammatory status.

A team of scientists in Basel believes this will open up new lines of research.

Scientists introduce Zman-seq, a method revolutionizing our understanding of dynamic cellular changes in the human body over time. Read more about this groundbreaking study.

In a recent study published in Cell, scientists led by Prof. Ido Amit at the Weizmann Institute of Science have introduced Zman-seq. This revolutionary method breaks through the temporal barriers of cellular analysis.

Continue reading “Breaking temporal barriers: Zman-seq’s journey into cellular dynamics” »

Hard-to-detect colorectal pre-cancerous lesions known as serrated polyps, and the aggressive tumors that develop from them, depend heavily on the ramped-up production of cholesterol, according to a preclinical study from researchers at Weill Cornell Medicine. The finding points to the possibility of using cholesterol-lowering drugs to prevent or treat such tumors.

In the study, published Oct. 13 in Nature Communications, the researchers analyzed mice that develop serrated polyps and tumors, detailing the chain of molecular events in these tissues that leads to increased cholesterol production.

They confirmed their findings in analyses of human serrated polyps and tumors, and showed in mouse models that replicate the human cancer that blocking cholesterol production prevented the progression of these types of intestinal tumors.

Scientists have discovered a new way to destroy cancer cells. Stimulating aminocyanine molecules with near-infrared light caused them to vibrate in sync, enough to break apart the membranes of cancer cells.

Aminocyanine molecules are already used in bioimaging as synthetic dyes. Commonly used in low doses to detect cancer, they stay stable in water and are very good at attaching themselves to the outside of cells.

The research team from Rice University, Texas A&M University, and the University of Texas, says the new approach is a marked improvement over another kind of cancer-killing molecular machine previously developed, called Feringa-type motors, which could also break the structures of problematic cells.

Highly transmissible and dubbed the Zombie Deer disease, scientists are closely monitoring this new infection as they fear it will spread to humans.

To effectively assist humans in real-world settings, robots should be able to learn new skills and adapt their actions based on what users require them to do at different times. One way to achieve this would be to design computational approaches that allow robots to learn from human demonstrations, for instance observing videos of a person washing dishes and learning to repeat the same sequence of actions.

Researchers at University of British Columbia, Carnegie Mellon University, Monash University and University of Victoria recently set out to gather more reliable data to train robots via demonstrations. Their paper, posted to the arXiv preprint server, shows that the data they gathered can significantly improve the efficiency with which robots learn from the demonstrations of human users.

“Robots can build cars, gather the items for shopping orders in busy warehouses, vacuum floors, and keep the hospital shelves stocked with supplies,” Maram Sakr, one of the researchers who carried out the study, told Tech Xplore. “Traditional robot programming systems require an expert programmer to develop a robot controller that is capable of such tasks while responding to any situation the robot may face.”

Large language models (LLMs) are advanced deep learning algorithms that can process written or spoken prompts and generate texts in response to these prompts. These models have recently become increasingly popular and are now helping many users to create summaries of long documents, gain inspiration for brand names, find quick answers to simple queries, and generate various other types of texts.

Researchers at the University of Georgia and Mayo Clinic recently set out to assess the biological knowledge and reasoning skills of different LLMs. Their paper, pre-published on the arXiv server, suggests that OpenAI’s model GPT-4 performs better than the other predominant LLMs on the market on reasoning biology problems.

“Our recent publication is a testament to the significant impact of AI on biological research,” Zhengliang Liu, co-author of the recent paper, told Tech Xplore. “This study was born out of the rapid adoption and evolution of LLMs, especially following the notable introduction of ChatGPT in November 2022. These advancements, perceived as critical steps towards Artificial General Intelligence (AGI), marked a shift from traditional biotechnological approaches to an AI-focused methodology in the realm of biology.”