Selective serotonin reuptake inhibitor (SSRI) antidepressants are some of the most widely prescribed drugs in the world, and new research suggests they could also protect against serious infections and life-threatening sepsis. Scientists at the Salk Institute studying a mouse model of sepsis uncovered how the SSRI fluoxetine can regulate the immune system and defend against infectious disease, and found that this protection is independent to peripheral serotonin. The findings could encourage additional research into the potential therapeutic uses of SSRIs during infection.
“When treating an infection, the optimal treatment strategy would be one that kills the bacteria or virus while also protecting our tissues and organs,” commented professor Janelle Ayres, PhD, holder of the Salk Institute Legacy Chair and Howard Hughes Medical Institute Investigator. “Most medications we have in our toolbox kill pathogens, but we were thrilled to find that fluoxetine can protect tissues and organs, too. It’s essentially playing offense and defense, which is ideal, and especially exciting to see in a drug that we already know is safe to use in humans.”
Ayres is senior author of the team’s report in Science Advances. In their paper, titled “Fluoxetine promotes IL-10–dependent metabolic defenses to protect from sepsis-induced lethality,” the investigators stated, “Our work reveals a beneficial ‘off-target’ effect of fluoxetine, and reveals a protective immunometabolic defense mechanism with therapeutic potential.”
Artificial intelligence (AI) has the potential to revolutionize the drug discovery process, offering improved efficiency, accuracy, and speed. However, the successful application of AI is dependent on the availability of high-quality data, the addressing of ethical concerns, and the recognition of the limitations of AI-based approaches. In this article, the benefits, challenges, and drawbacks of AI in this field are reviewed, and possible strategies and approaches for overcoming the present obstacles are proposed. The use of data augmentation, explainable AI, and the integration of AI with traditional experimental methods, as well as the potential advantages of AI in pharmaceutical research, are also discussed. Overall, this review highlights the potential of AI in drug discovery and provides insights into the challenges and opportunities for realizing its potential in this field.
Summary: A new study reveals how AI-driven deep learning models can decode the genetic regulatory switches that define brain cell types across species. By analyzing human, mouse, and chicken brains, researchers found that some brain cell types remain highly conserved over 320 million years, while others have evolved uniquely.
This regulatory code not only sheds light on brain evolution but also provides new tools for studying gene regulation in health and disease. The findings highlight how AI can identify preserved and divergent genetic instructions controlling brain function across species.
The study also has implications for understanding neurological disorders by linking genetic variants to cognitive traits. Researchers are now expanding their models to study the brains of various animals and human disease states like Parkinson’s.
Summary: Researchers have mapped over 70,000 synaptic connections in rat neurons using a silicon chip with 4,096 microhole electrodes, significantly advancing neuronal recording technology. Unlike traditional electron microscopy, which only visualizes synapses, this method also measures connection strength, providing deeper insight into brain network function.
The chip mimics patch-clamp electrodes but at a massive scale, enabling highly sensitive intracellular recordings from thousands of neurons simultaneously. Compared to their previous nanoneedle design, this new approach captured 200 times more synaptic connections, revealing detailed characteristics of each link.
The technology could revolutionize neural mapping, offering a powerful tool for studying brain function and diseases. Researchers are now working to apply this system in live brains to further understand real-time neural communication.
A few decades later, the neuropsychologists Roger Sperry and Michael Gazzaniga studied more of these so-called split-brain patients and discovered that each half of the brain processed information independently. Each could make its own decisions and control its own behaviours. In a sense, the surgery had created two separate selves. In some of these patients, one side of their body (controlled by one hemisphere) would do one thing, while the other half (controlled by the other hemisphere) would do the opposite. For example, one hand would button their shirt while the other hand would unbutton it.
So why didn’t these split-brain patients, post-surgery, feel like they had two selves? The answer is that their brains fooled them into thinking that only one self existed and that it was in charge. When one of their hands did something unexpected, they made up a story to explain why. I changed my mind. I didn’t like the way that shirt looked.
These stories or confabulations show the power of the illusion of selfhood – a feeling that evolutionary psychologists believe evolved because it is adaptively useful. What better way to ensure that the physical package carrying and protecting the information in our DNA – namely, our bodies – survives long enough to pass on that code to the next generation? The illusion of the self makes us feel unique and provides us with a goal-oriented purpose to our lives.
Researchers investigated cerebral small vessel disease, a precursor to dementia, by analyzing data from thousands of participants spanning four distinct groups of middle-aged to older adults. Their study confirmed the validity of a biomarker that could aid in advancing research on potential treatments.
A recent study conducted by the Keck School of Medicine of USC
<span class=””>Founded in 1880, the <em>University of Southern California</em> is one of the world’s leading private research universities. It is located in the heart of Los Angeles.</span>
Northwestern Medicine scientists have discovered new details about how the human genome produces instructions for creating proteins and cells, the building blocks of life, according to a pioneering new study published in Science Advances.
While it’s understood that genes function as a set of instructions for creating RNA, and thus proteins and cells, the fundamental process by which this occurs has not been well-studied due to technological limitations, said Vadim Backman, Ph.D., the Sachs Family Professor of Biomedical Engineering and Medicine, who was senior author of the study.
“It is still not fully understood how, despite having the same set of genes, cells turn into neurons, bones, skin, heart, or roughly 200 other kinds of cells, and then exhibit stable cellular behavior over a human lifespan which can last for more than a century—or why aging degrades this process,” said Backman, who directs the Center for Physical Genomics and Engineering at Northwestern. “This has been a long-standing open question in biology.”