Lifeboat Foundation

When something goes wrong in mitochondria, the tiny organelles that power cells, it can cause a bewildering variety of symptoms such as poor growth, fatigue and weakness, seizures, developmental and cognitive disabilities, and vision problems. The culprit could be a defect in any of the 1,300 or so proteins that make up mitochondria, but scientists have very little idea what many of those proteins do, making it difficult to identify the faulty protein and treat the condition.

Researchers at Washington University School of Medicine in St. Louis and the University of Wisconsin–Madison systematically analyzed dozens of mitochondrial proteins of unknown function and suggested functions for many of them. Using these data as a starting point, they identified the genetic causes of three mitochondrial diseases and proposed another 20 possibilities for further investigation. The findings, published May 25 in Nature, indicate that understanding how mitochondria’s hundreds of proteins work together to generate power and perform the organelles’ other functions could be a promising path to finding better ways to diagnose and treat such conditions.

“We have a parts list for mitochondria, but we don’t know what many of the parts do,” said co-senior author David J. Pagliarini, Ph.D., the Hugo F. and Ina C. Urbauer Professor and a BJC Investigator at Washington University. “It’s similar to if you had a problem with your car, and you brought it to a mechanic, and upon opening the hood they said, ‘We’ve never seen half of these parts before.’ They wouldn’t know how to fix it. This study is an attempt to define the functions of as many of those mitochondrial parts as we can so we have a better understanding of what happens when they don’t work and, ultimately, a better chance at devising therapeutics to rectify those problems.”

Summary: New software can perform computerized image editing using only input from electrical activity in the human brain.

Source: University of Copenhagen.

Soon, we won’t need to use the Help function. The computer will sense that we have a problem and come to the rescue by itself. This is one of the possible implications of new research at University of Copenhagen and University of Helsinki.

If you look different to your close relatives, you may have felt separate from your family. As a child, during particularly stormy fall outs you might have even hoped it was a sign that you were adopted.

As our new research shows, appearances can be deceptive when it comes to family. New DNA technology is shaking up the family trees of many plants and animals.

Continue reading “New DNA Technology Is Shaking Up The Branches of The Evolutionary Tree” »

https://youtube.com/watch?v=ALPLNwwubHw

Professor Pattie Maes deep insights working with her research team of Joanne Leong, Pat Pataranutaporn, Valdemar Danry are world leading in their translational research on tech-human interaction. Their highly interdisciplinary work covering decades of MIT Lab pioneering inventions integrates human computer interaction (HCI), sensor technologies, AI / machine learning, nano-tech, brain computer interfaces, design and HCI, psychology, neuroscience and much more. I participated in their day-long workshop and followed-up with more than three hours of interviews of which over an hour is transcribed in this article. All insights in this article stem from my daily pro bono work with (now) more than 400,000 CEOs, investors, scientists/experts. MIT Media Lab Fluid Interfaces research team work is particularly key with the June 21 announcement of the Metaverse Standards Forum, a open standards group, with big tech supporting such as Microsoft and Meta, chaired by Neil Trevett, Khronos President and VP Developer Ecosystems at NVIDIA. I have a follow-up interview with Neil and Forbes article in the works. In addition, these recent announcements also highlight why Pattie Maes work is so important: Deep Mind’s Gato multi-modal, multi-task, single generalist agent foundational to artificial general intelligence (AGI); Google’s LaMDA Language Model for Dialogue Applications which can engage in free-flowing dialogue; Microsoft’s Build Conference announcements on Azure AI and OpenAI practical tools / solutions and responsible AI; OpenAI’s DALL-E 2 producing realistic images and art from natural language descriptions.

Full Story:

New research has identified an important molecular analogy that could explain the remarkable intelligence of these fascinating invertebrates.

An exceptional organism with an extremely complex brain and cognitive abilities makes the octopus very unique among invertebrates. So much so that it resembles vertebrates more than invertebrates in several aspects. The neural and cognitive complexity of these animals could originate from a molecular analogy with the human brain, as discovered by a research paper that was recently published in BMC Biology and coordinated by Remo Sanges from Scuola Internazionale Superiore di Studi Avanzati (SISSA) of Trieste and by Graziano Fiorito from Stazione Zoologica Anton Dohrn of Naples.

This research shows that the same ‘jumping genes’ are active both in the human brain and in the brain of two species, Octopus vulgaris, the common octopus, and Octopus bimaculoides, the Californian octopus. A discovery that could help us understand the secret of the intelligence of these remarkable organisms.

Early diagnosis of neurodevelopmental conditions, such as Attention Deficit Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD), is critical for treatment and symptom management processes.

Now, a team of researchers from the University of South Australia has found that recordings from the retina may be used to distinguish unique signals for both ADHD and ASD, offering a possible biomarker for each disorder. According to a press release published by the institution, The team used the “electroretinogram” (ERG), a diagnostic test that measures the electrical activity of the retina in response to light, and found out that children with ASD showed less ERG energy while children with ADHD displayed more ERG energy.

#brain on #acid LSD #conscious #experience #science #trippy #reality #mind #wow #neuroscience #amazing #dopamine #seretonin

Outer Space, Inner Space, and the Future of Networks.
Synopsis: Does the History, Dynamics, and Structure of our Universe give any evidence that it is inherently “Good”? Does it appear to be statistically protective of adapted complexity and intelligence? Which aspects of the big history of our universe appear to be random? Which are predictable? What drives universal and societal accelerating change, and why have they both been so stable? What has developed progressively in our universe, as opposed to merely evolving randomly? Will humanity’s future be to venture to the stars (outer space) or will we increasingly escape our physical universe, into physical and virtual inner space (the transcension hypothesis)? In Earth’s big history, what can we say about what has survived and improved? Do we see any progressive improvement in humanity’s thoughts or actions? When is anthropogenic risk existential or developmental (growing pains)? In either case, how can we minimize such risk? What values do well-built networks have? What can we learn about the nature of our most adaptive complex networks, to improve our personal, team, organizational, societal, global, and universal futures? I’ll touch on each of these vital questions, which I’ve been researching and writing about since 1999, and discussing with a community of scholars at Evo-Devo Universe (join us!) since 2008.

For fun background reading, see John’s Goodness of the Universe post on Centauri Dreams, and “Evolutionary Development: A Universal Perspective”, 2019.

Continue reading “The Goodness of the Universe — John Smart” »

Summary: Human cortical networks have evolved a novel neural network that relies on abundant connections between inhibitory interneurons.

Source: Max Planck Institute.

The analysis of the human brain is a central goal of neuroscience. However, for methodological reasons, research has largely focused on model organisms, in particular the mouse.