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Pain-detecting nerve cells could yield new way to manage lung scarring

Researchers at the University of Calgary studying a lethal lung disease called pulmonary fibrosis have found that neurons known to help detect pain are also critical for reducing harmful lung inflammation that leads to the disease.

Pulmonary fibrosis, also called lung scarring, is uncommon but it’s hard to treat and most people die within five years of diagnosis. Research to date has focused on how the lung lining gets damaged and the body’s attempts to repair the issue. The role of neurons—a complex network of cells within the nervous system that send messages between the brain, and through the body—and the immune system has received less study.

Now a research team led by Cumming School of Medicine (CSM) physician-scientist Dr. Bryan Yipp, MD, has found specific that normally detect pain also help control inflammation during lung fibrosis.

Guava’s secret molecule could fight liver cancer

New research by William Chain, associate professor in the University of Delaware’s Department of Chemistry and Biochemistry, and his lab, uses a molecule found in a tropical fruit to offer hope in the fight against liver-related cancers, one of the world’s top causes of cancer deaths.

Using a process called natural product total synthesis, Chain and his lab group have invented a pathway that uses widely available chemicals to create molecules found in a guava plant that are known to fight these deadly cancers. The work was published in one of the leading chemistry publications, the international journal Angewandte Chemie.

The research provides scientists around the world with an easy and low cost method to create large amounts of the naturally-occurring molecules, and opens doors to more effective and cheaper treatments.

Nature has long been the source of lifesaving medicines, from willow bark’s natural aspirin to new discoveries in tropical fruits. Now, chemists at the University of Delaware have pioneered a way to recreate powerful molecules from guava plants that show promise against liver cancer. Their method provides a low-cost, scalable recipe for scientists worldwide, sparking collaboration and potentially transforming cancer treatment.

Project Overview ‹ AlterEgo

AlterEgo is a non-invasive, wearable, peripheral neural interface that allows humans to converse in natural language with machines, artificial intelligence assistants, services, and other people without any voice—without opening their mouth, and without externally observable movements—simply by articulating words internally. The feedback to the user is given through audio, via bone conduction, without disrupting the user’s usual auditory perception, and making the interface closed-loop. This enables a human-computer interaction that is subjectively experienced as completely internal to the human user—like speaking to one’s self.

A primary focus of this project is to help support communication for people with speech disorders including conditions like ALS (amyotrophic lateral sclerosis) and MS (multiple sclerosis). Beyond that, the system has the potential to seamlessly integrate humans and computers—such that computing, the Internet, and AI would weave into our daily life as a “second self” and augment our cognition and abilities.

The wearable system captures peripheral neural signals when internal speech articulators are volitionally and neurologically activated, during a user’s internal articulation of words. This enables a user to transmit and receive streams of information to and from a computing device or any other person without any observable action, in discretion, without unplugging the user from her environment, without invading the user’s privacy.

Neuromorphic Intelligence Leverages Dynamical Systems Theory To Model Inference And Learning In Sustainable, Adaptable Systems

The pursuit of artificial intelligence increasingly focuses on replicating the efficiency and adaptability of the human brain, and a new approach, termed neuromorphic intelligence, offers a promising path forward. Marcel van Gerven from Radboud University and colleagues demonstrate how brain-inspired systems can achieve significantly greater energy efficiency than conventional digital computers. This research establishes a unifying theoretical framework, rooted in dynamical systems theory, to integrate insights from diverse fields including neuroscience, physics, and artificial intelligence. By harnessing noise as a learning resource and employing differential genetic programming, the team advances the development of truly adaptive and sustainable artificial intelligence, paving the way for emergent intelligence arising directly from physical substrates.

Researchers demonstrate that applying dynamical systems theory, a mathematical framework describing change over time, to artificial intelligence enables the creation of more sustainable and adaptable systems by harnessing noise as a learning tool and allowing intelligence to emerge from the physical properties of the system itself.

How Tesla’s New Products Will Change Energy Forever

Tesla’s new energy products, such as the Mega Pack and Megablock, have the potential to revolutionize energy storage and generation, drive decentralization and grid resilience, and support widespread AI adoption, potentially driving its energy business to $50 billion in revenue and generating $10 billion in annual gross margin ## Questions to inspire discussion.

Energy Storage and Grid Management.

🔋 Q: How does Tesla’s Mega Pack improve energy storage? A: Tesla’s Mega Pack offers 20% more energy density and 25% more energy per unit, providing 8 hours of storage to expand the total addressable market for renewable energy.

⚡ Q: What is the Mega Block and how does it enhance efficiency? A: The Mega Block is a transformer and switchgear all-in-one unit that simplifies processes, reduces cabling and on-site assembly, making the product more streamlined and efficient.

🔌 Q: How do battery storage systems compare to traditional grid power? A: Battery storage is significantly more capable at dumping power instantly compared to the grid, which needs to spool up and down, making it better for managing wild swings in data center load profiles.

Data centers and AI energy demands.

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