Lifeboat Foundation

Researchers have discovered how a cell surface protein called Aplp1 can play a role in spreading material responsible for Parkinson’s disease from cell-to-cell in the brain.

Promisingly, an FDA-approved cancer drug that targets another protein called Lag3 – which interacts with Aplp1 – blocks the spread in mice, suggesting a potential therapy may already exist.

In a recent paper, an international team of scientists describes how the two proteins work together to help harmful alpha-synuclein protein clumps get into brain cells.

Researchers highlight LXRβ as a potential target for treating depression, anxiety, and autism. While promising, further studies are needed to confirm its effectiveness in humans.

In a state-of-the-art Bench to Bedside review published in the journal Brain Medicine (Genomic Press), Dr. Xiaoyu Song from the University of Houston and Professor Jan-Åke Gustafsson from Sweden’s Karolinska Institute explore the therapeutic potential of liver X receptor beta (LXRβ) in treating depression and anxiety. Their comprehensive analysis represents a major advancement in understanding the molecular mechanisms underlying mental health disorders, with the potential to transform future treatment approaches.

LXRβ, a nuclear receptor initially known for its role in cholesterol metabolism and inflammation, is now emerging as a crucial player in neuroscience and psychiatry. The review synthesizes recent breakthroughs in understanding LXRβ’s regulation and function in behaviors relevant to depression and anxiety, derived from studies using animal models that capture specific features of these disorders.

Summary: Scientists have identified how genetic variants influence the risk of neurological and psychiatric disorders, including schizophrenia and autism. Using live neural cells and DNA sequencing, researchers discovered thousands of “non-coding” genetic variants with context-dependent functions, activated during brain development.

These variants act like switches, turning genes on or off depending on cellular pathways. This research offers new insights into the biological mechanisms behind psychiatric disorders and could lead to personalized treatments based on genetic profiles.

The primary question we will attempt to investigate in this article is whether consciousness is a fundamental property of nature, or is it an emergent phenomenon. The nature of consciousness is shrouded in mystery. Although we understand a lot about how the world works from a third person perspective, we don’t understand the source of consciousness, even though everything we know is due to consciousness. Our conclusion is that consciousness is likely an emergent phenomenon. Consciousness emerges from physical matter (due to the arrangement of and interactions between physical matter), and ordered complexity is simply a fortunate product of random processes. We claim that defining consciousness as a fundamental property of the universe is not scientific. We also provide some evidence as to why it is likely that consciousness is emergent from physical matter.

In this article, we will also be addressing the question of whether we need fundamentally new kinds of laws to explain complex phenomena, or can extensions of the existing laws governing simpler phenomena successfully explain more complex phenomena. It is crucial to understand this question in order to obtain a better understanding of the way complexity arises from simplicity. This question is interdisciplinary in nature and would possibly have an effect on less fundamental sciences (like medical sciences), other than physics. The question involves chaos theory, emergence and many other concepts.

Gene therapy shows promise in repairing damaged brain tissue from strokes.

From the NIH Director’s Blog by Dr. Francis Collins.

It’s a race against time when someone suffers a stroke caused by a blockage of a blood vessel supplying the brain. Unless clot-busting treatment is given within a few hours after symptoms appear, vast numbers of the brain’s neurons die, often leading to paralysis or other disabilities. It would be great to have a way to replace those lost neurons. Thanks to gene therapy, some encouraging strides are now being made.

Continue reading “Gene therapy shows promise repairing brain tissue damaged by stroke” »

Machines won’t become intelligent unless they incorporate certain features of the human brain. Here are three of them.

Our brains constantly work to make predictions about what’s going on around us, for instance to ensure that we can attend to and consider the unexpected. A new study examines how this works during consciousness and also breaks down under general anesthesia. The results add evidence for the idea that conscious thought requires synchronized communication—mediated by brain rhythms in specific frequency bands—between basic sensory and higher-order cognitive regions of the brain.

Previously, members of the research team in The Picower Institute for Learning and Memory at MIT and at Vanderbilt University had described how brain rhythms enable the brain to remain prepared to attend to surprises.

Cognition-oriented brain regions (generally at the front of the brain), use relatively low frequency alpha and beta rhythms to suppress processing by sensory regions (generally toward the back of the brain) of stimuli that have become familiar and mundane in the environment (e.g. your co-worker’s music). When sensory regions detect a surprise (e.g. the office fire alarm), they use faster frequency gamma rhythms to tell the higher regions about it and the higher regions process that at gamma frequencies to decide what to do (e.g. exit the building).

Next-generation technologies, such as leading-edge memory storage solutions and brain-inspired neuromorphic computing systems, could touch nearly every aspect of our lives — from the gadgets we use daily to the solutions for major global challenges. These advances rely on specialized materials, including ferroelectrics — materials with switchable electric properties that enhance performance and energy efficiency.

A research team led by scientists at the Department of Energy’s Oak Ridge National Laboratory has developed a novel technique for creating precise atomic arrangements in ferroelectrics, establishing a robust framework for advancing powerful new technologies. The findings are published in Nature Nanotechnology (“On-demand nanoengineering of in-plane ferroelectric topologies”).

“Local modification of the atoms and electric dipoles that form these materials is crucial for new information storage, alternative computation methodologies or devices that convert signals at high frequencies,” said ORNL’s Marti Checa, the project’s lead researcher. “Our approach fosters innovations by facilitating the on-demand rearrangement of atomic orientations into specific configurations known as topological polarization structures that may not naturally occur.” In this context, polarization refers to the orientation of small, internal permanent electric fields in the material that are known as ferroelectric dipoles.

Neuromorphic engineering is a cutting-edge field that focuses on developing computer hardware and software systems inspired by the structure, function, and behavior of the human brain. The ultimate goal is to create computing systems that are significantly more energy-efficient, scalable, and adaptive than conventional computer systems, capable of solving complex problems in a manner reminiscent of the brain’s approach.

This interdisciplinary field draws upon expertise from various domains, including neuroscience, computer science, electronics, nanotechnology, and materials science. Neuromorphic engineers strive to develop computer chips and systems incorporating artificial neurons and synapses, designed to process information in a parallel and distributed manner, akin to the brain’s functionality.

Key challenges in neuromorphic engineering encompass developing algorithms and hardware capable of performing intricate computations with minimal energy consumption, creating systems that can learn and adapt over time, and devising methods to control the behavior of artificial neurons and synapses in real-time.