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Scientists Identify Interferon-gamma as Potential SARS-CoV-2 Antiviral

Conditioning the lungs with interferon-gamma, a natural immune system protein (cytokine) best known for fighting bacterial infections, appears to be a strong antiviral for SARS-CoV-2, according to National Institutes of Health scientists and colleagues. Their new study, published in Nature Communications, shows in two different mouse models that when a bacterial infection triggers the release of interferon-gamma in the lungs, those animals subsequently are protected from infection by SARS-CoV-2, the virus that causes COVID-19. The investigators further report that using recombinant interferon-gamma in the nose of study mice at the time of viral exposure substantially reduces SARS-CoV-2 infection and COVID disease.

The lead project scientists suggest testing interferon-gamma further, alone and in combination with other treatments, to limit early SARS-CoV-2 infection in people. They also hypothesize that people with prior bacterial infections that naturally release interferon-gamma in their lungs may be less susceptible to COVID-19.

NIH’s National Institute of Allergy and Infectious Diseases (NIAID) led the project with collaborators at Malaghan Institute of Medical Research in New Zealand.

New brain-computer interface allows people to play a game using their thoughts

😀 Amazing breakthrough face_with_colon_three


A group of Spanish researchers have developed a brain-computer interface based on electroencephalograms that allowed a group of 22 users to play a simple multiplayer game. The interface was 94% accurate in translating players’ thoughts into game moves, with each move taking just over 5 seconds. The study was published in Frontiers in Human Neuroscience.

A brain-computer interface is a technology that enables direct communication between the human brain and external devices, such as computers or prosthetic limbs. Brain-computer interfaces work by detecting and interpreting neural signals, typically through electrodes placed on the user’s head. These signals are then translated into actionable commands, allowing individuals to control computers, devices, or applications using their thoughts.

Brain-computer interfaces offer significant potential in medicine, from helping paralyzed individuals regain environmental control to treating neurological disorders. However, their broader adoption is hindered by challenges in accuracy and the extended time required to interpret brain signals.

Cyborg computer with living brain organoid aces machine learning tests

Scientists have grown a tiny brain-like organoid out of human stem cells, hooked it up to a computer, and demonstrated its potential as a kind of organic machine learning chip, showing it can quickly pick up speech recognition and math predictions.

As incredible as recent advances have been in machine learning, artificial intelligence still lags way behind the human brain in some important ways. For example, the brain happily learns and adapts all day long on an energy budget of about 20 watts, where a comparably powerful artificial neural network needs about 8 million watts to achieve anything remotely comparable.

What’s more, the human brain’s neural plasticity, its ability to grow new nervous tissue and expand existing connective channels, has granted it an ability to learn from noisy, low-quality data streams, with minimal training and energy expenditure. What AI systems accomplish with brute force and massive energy, the brain achieves with an effortless elegance. It’s a credit to the billions of years of high-stakes trial and error that delivered the human brain to the state it’s in today, in which it’s chiefly used to watch vast numbers of other people dancing while we’re on the toilet.

Scientists Grew ‘Mini Brains’ From Stem Cells. Then, The Brains Sort-of Developed Eyes

Mini brains grown in a lab from stem cells spontaneously developed rudimentary eye structures, scientists reported in a fascinating paper in 2021.

On tiny, human-derived brain organoids grown in dishes, two bilaterally symmetrical optic cups were seen to grow, mirroring the development of eye structures in human embryos.

This incredible result will help us to better understand the process of eye differentiation and development, as well as eye diseases.

Using solid-state nanopores and DNA barcoding to identify misfolded proteins in neurodegenerative disorders

A team of chemists, microbiologists and physicists at the University of Cambridge in the U.K. has developed a way to use solid-state nanopores and multiplexed DNA barcoding to identify misfolded proteins such as those involved in neurodegenerative disorders in blood samples. In their study, reported in the Journal of the American Chemical Society, the group used multiplexed DNA barcoding techniques to overcome problems with nanopore filtering techniques for isolating harmful oligomers.

Prior research has shown that the presence of harmful oligomers in the brain can lead to misfolding of proteins associated with neurodegenerative diseases such as Parkinson’s and Alzheimer’s disease. Medical researchers have been looking for a way to detect them in the blood as a way to diagnose neurodegenerative disease and to track the progression once it has been confirmed.

Unfortunately, finding them in complex mixtures such as blood has proven to be a daunting task. One approach has shown promise—using sensors—but to date, they cannot track target oligomers as they speed through customizable solid-state nanopore sensors. In this new effort, the research team overcame this problem by using customizable DNA nanostructures.