Lifeboat Foundation

Summary: Utilizing a classic neural network, researchers have created a new artificial intelligence model based on recent biological findings that shows improved memory performance.

Source: OIST

Computer models are an important tool for studying how the brain makes and stores memories and other types of complex information. But creating such models is a tricky business. Somehow, a symphony of signals – both biochemical and electrical – and a tangle of connections between neurons and other cell types creates the hardware for memories to take hold. Yet because neuroscientists don’t fully understand the underlying biology of the brain, encoding the process into a computer model in order to study it further has been a challenge.

Aromatic bonds, particularly strong chemical bonds which form in some ring-shaped molecules, are a crucial building block of the world around us. They appear in everything from proteins to aspirin, and literally millions of natural and synthetic substances in between.

The bonds are very hard to break and to control, and their properties have puzzled chemists for more than a century.

Which is just the motivation chemists needed to break and control them, and now a group of UK researchers has figured out how to twist an aromatic bond until it breaks.

The development represents “an important advance in extraterrestrial research, in which biology has often lagged behind chemistry and geology.”

A new study has revealed a new way to enhance the search for aliens on Mars by teaching artificial intelligence to detect sites that could contain “biosignatures.”

And so, the researchers trained a deep learning framework to map biosignatures in a three-square-kilometer area of Chile’s Atacama Desert… More.

Continue reading “New AI tool can aid scientists in hunting for life on Mars” »

A team of biologists has discovered how to awaken neural stem cells and reactivate them in adult mice.

Some areas of the adult brain contain quiescent, or dormant, neural stem cells that can potentially be reactivated to form new neurons. However, the transition from quiescence to proliferation is still poorly understood. A team led by scientists from the Universities of Geneva (UNIGE) and Lausanne (UNIL) has discovered the importance of cell metabolism in this process and identified how to wake up these neural stem cells and reactivate them. Biologists succeeded in increasing the number of new neurons in the brain of adult and even elderly mice. These results, promising for the treatment of neurodegenerative diseases, are to be discovered in the journal Science Advances.

<em>Science Advances</em> is a peer-reviewed, open-access scientific journal that is published by the American Association for the Advancement of Science (AAAS). It was launched in 2015 and covers a wide range of topics in the natural sciences, including biology, chemistry, earth and environmental sciences, materials science, and physics.

Lipid nanoparticles (LNPs) transport small molecules into the body. The most well-known LNP cargo is mRNA, the key constituent of some of the early vaccines against COVID-19. But that is just one application: LNPs can carry many different types of payload, and have applications beyond vaccines.

Barbara Mui has been working on LNPs (and their predecessors, liposomes) since she was a PhD student in Pieter Cullis’s group in the 1990s. “In those days, LNPs encapsulated anti-cancer drugs,” says Mui, who is currently a senior scientist at Acuitas, the company that developed the LNPs used in the Pfizer-BioNTech mRNA vaccine against SARS-CoV-2. She says it soon became clear that LNPs worked even better as carriers of polynucleotides. “The first one that worked really well was encapsulating small RNAs,” Mui recalls.

But it was mRNA where LNPs proved most effective, primarily because LNPs are comprised of positively charged lipid nanoparticles that encapsulate negatively charged mRNA. Once in the body, LNPs enter cells via endocytosis into endosomes and are released into the cytoplasm. “Without the specially designed chemistry, the LNP and mRNA would be degraded in the endosome,” says Kathryn Whitehead, professor in the departments of chemical engineering and biomedical engineering at Carnegie Mellon University.

Brave new world let’s create happiness for everyone by putting microelectrode arrays in our brains but be careful not to create a situation like death by ecstacy by Larry Niven.

In the brain, pleasure is generated by a handful of brain regions called, “hedonic hotspots.” If you were to stimulate these regions directly, you would likely feel pleasurable sensations. However, not all of the hedonic hotspots are the same–some generate the raw sensations of pleasure whereas others are responsible for consciously interpreting and elaborating on the raw pleasure produced by the other hotspots. In this video, in addition to exploring the neuroscience of pleasure, we’ll see how understanding pleasure, happiness, meaning, and purpose can help us live better lives.

Continue reading “PLEASURE GENERATORS in the Brain: The Neuroscience of Pleasure Explained” »

A new program can streamline the process of creating, launching and analysing computational chemistry experiments. This piece of software, called AQME, is distributed for free under an open source licence, and could contribute to making calculations more efficient, as well as accelerating automated analyses.

‘We estimate time savings of around 70% in routine computational chemistry protocols,’ explains lead author Juan Vicente Alegre Requena, at the Institute of Chemical Synthesis and Homogeneous Catalysis (ISQCH) in Zaragoza, Spain. ‘In modern molecular simulations, studying a single reaction usually involves more than 500 calculations,’ he explains. ‘Generating all the input files, launching the calculations and analysing the results requires an extraordinary amount of time, especially when unexpected errors appear.’

Therefore, Alegre and his colleagues decided to code a piece of software to skip several steps and streamline calculations. Among other advantages, AQME works with simple inputs, instead of the optimised 3D chemical structures usually required by other solutions. ‘It’s exceptionally easy,’ says Alegre. ‘AQME is installed in a couple of minutes, then the only indispensable input is as a simple Smiles string.’ Smiles is a system developed by chemist and coder Dave Weininger in the late 1980s, which converts complex chemical structures into a succession of letters and numbers that is machine readable. This cross-compatibility could allow integration with chemical databases and machine-learning solutions, most of which include datasets in Smiles format, explains Alegre.

Dedicated to ending the HIV epidemic — dr. moupali das, MD, MPH, executive director, HIV clinical research, gilead sciences.

Dr. Moupali Das, MD, MPH, is Executive Director, HIV Clinical Research, in the Virology Therapeutic Area, at Gilead Sciences (https://www.gilead.com/), where she leads the pre-exposure prophylaxis (PrEP) clinical drug development program, including evaluating the safety and efficacy of a long-acting, twice yearly, subcutaneous injection being studied for HIV prevention. Her responsibilities also include expanding the populations who may benefit from PrEP.

Continue reading “Dr. Moupali Das, MD, MPH — Gilead Sciences — Dedicated To Ending The HIV Epidemic” »

Computer models are an important tool for studying how the brain makes and stores memories and other types of complex information. But creating such models is a tricky business. Somehow, a symphony of signals—both biochemical and electrical—and a tangle of connections between neurons and other cell types creates the hardware for memories to take hold. Yet because neuroscientists don’t fully understand the underlying biology of the brain, encoding the process into a computer model in order to study it further has been a challenge.

Now, researchers at the Okinawa Institute of Science and Technology (OIST) have altered a commonly used computer model of memory called a Hopfield network in a way that improves performance by taking inspiration from biology. They found that not only does the new network better reflect how neurons and other cells wire up in the brain, it can also hold dramatically more memories.

The complexity added to the network is what makes it more realistic, says Thomas Burns, a Ph.D. student in the group of Professor Tomoki Fukai, who heads OIST’s Neural Coding and Brain Computing Unit. “Why would biology have all this complexity? Memory capacity might be a reason,” Mr. Burns says.