Lifeboat Foundation

We know little about how embryonic development in animals evolved from single-celled ancestors, but simple organisms with a multicellular life stage offer intriguing clues.

By Claire Ainsworth

Venki Ramakrishnan’s is the real-deal ‘pivot story’ — ‘pivoting’ being quite the fancy thing to do today. Born in Chidambaram in Tamil Nadu in 1952, Venki wanted to be a physicist, and by the time he decided to do something about his passion for Biology, he was already a PhD in Physics from Ohio University, USA. He then ‘pivoted’ and studied Biology at the University of California, San Diego, before he began his post-doctoral work at Yale University.

He went on to win the Nobel Prize in Chemistry in 2009 for his work on cellular particles called ribosomes. His first book, Gene Machine, captures this journey with the kind of honesty and self-deprecation one does not expect from an award-winning scientist.

With similar candour, in his second book, he examines recent scientific breakthroughs in longevity and ageing and raises uncomfortable questions about the ethical aspects of the research as well as the biological purpose of death.

I found this on NewsBreak:

To study living organisms at ever smaller length scales, scientists must devise new techniques to overcome the so-called diffraction limit. This is the intrinsic limitation on a microscope’s ability to focus on objects smaller than the wavelength of light being used.

CWI senior researcher Sander Bohté started working on neuromorphic computing already in 1998 as a PhD-student, when the subject was barely on the map. In recent years, Bohté and his CWI-colleagues have realized a number of algorithmic breakthroughs in spiking neural networks (SNNs) that make neuromorphic computing finally practical: in theory many AI-applications can become a factor of a hundred to a thousand more energy-efficient. This means that it will be possible to put much more AI into chips, allowing applications to run on a smartwatch or a smartphone. Examples are speech recognition, gesture recognition and the classification of electrocardiograms (ECG).

“I am really grateful that CWI, and former group leader Han La Poutré in particular, gave me the opportunity to follow my interest, even though at the end of the 1990s neural networks and neuromorphic computing were quite unpopular”, says Bohté. “It was high-risk work for the long haul that is now bearing fruit.”

Spiking neural networks (SNNs) more closely resemble the biology of the brain. They process pulses instead of the continuous signals in classical neural networks. Unfortunately, that also makes them mathematically much more difficult to handle. For many years SNNs were therefore very limited in the number of neurons they could handle. But thanks to clever algorithmic solutions Bohté and his colleagues have managed to scale up the number of trainable spiking neurons first to thousands in 2021, and then to tens of millions in 2023.

Imagine a world where machines aren’t confined to pre-programmed tasks but operate with human-like autonomy and competence. A world where computer minds pilot self-driving cars, delve into complex scientific research, provide personalized customer service and even explore the unknown.

This is the potential of artificial general intelligence (AGI), a hypothetical technology that may be poised to revolutionize nearly every aspect of human life and work. While AGI remains theoretical, organizations can take proactive steps to prepare for its arrival by building a robust data infrastructure and fostering a collaborative environment where humans and AI work together seamlessly.

AGI, sometimes referred to as strong AI, is the science-fiction version of artificial intelligence (AI), where artificial machine intelligence achieves human-level learning, perception and cognitive flexibility. But, unlike humans, AGIs don’t experience fatigue or have biological needs and can constantly learn and process information at unimaginable speeds. The prospect of developing synthetic minds that can learn and solve complex problems promises to revolutionize and disrupt many industries as machine intelligence continues to assume tasks once thought the exclusive purview of human intelligence and cognitive abilities.

A recent USC study provides new information about why SARS-CoV-2, the virus behind the COVID-19 pandemic, may elicit mild symptoms at first but then, for a subset of patients, turn potentially fatal a week or so after infection. The researchers showed that distinct stages of illness correspond with the coronavirus acting differently in two different populations of cells.

The study, published in Nature Cell Biology, may provide a roadmap for addressing cytokine storms and other excessive immune reactions that drive serious COVID-19.

The team found that when SARS-CoV-2 infects its first-phase targets, cells in the lining of the lung, two viral proteins circulate within those cells—one that works to activate the immune system and a second that, paradoxically, blocks that signal, resulting in little or no inflammation.

Researchers in the Yale Department of Cell Biology have created a new microscopy technique that will help unlock the inner workings of cells 100 times faster than current technology allows – and at a fraction of the cost.

Writing in the journal Cell, the Yale team says their FLASH-PAINT technique…

While current microscopy techniques image only a few intracellular molecules at a time, a new technique developed by Yale scientists can help researchers.

Continue reading “Advanced Microscopy Technique Offers a New Look Inside Cells” »

A landmark new study confirms that growing a human being in nine months takes a toll—and multiple pregnancies can have a cumulative effect.

Modern biology textbooks assert that only bacteria can take nitrogen from the atmosphere and convert it into a form that is usable for life. Plants that fix nitrogen, such as legumes, do so by harboring symbiotic bacteria in root nodules. But a recent discovery upends that rule.