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How gut microbiota impacts childhood obesity

Mechanisms underlying gut microbiota’s role in obesity

Energy absorption and short-chain fatty acids

Gut microbiota regulate energy metabolism through short-chain fatty acids (SCFAs) like acetate, butyrate, and propionate, which are products of fiber fermentation. While butyrate promotes insulin sensitivity and reduces inflammation, propionate may trigger overeating. Dysregulated SCFA production can contribute to obesity by enhancing energy absorption, disrupting appetite regulation, and promoting fat accumulation. Recent findings suggest that modulating SCFA production through dietary interventions can help regulate energy balance and improve metabolic health. Maintaining SCFA balance through diet or microbial modulation holds promise for obesity management.

Cori Cycle: How Your Body Recycles Energy During Exercise

Dive into the fascinating world of the Cori Cycle, also known as the lactic acid cycle! 🏋️‍♂️💡 In this video, we’ll explore how your body manages energy during intense exercise by recycling lactate from muscles back into glucose in the liver.
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Drawing a line from the gut microbiome to inflammation and depression

It’s become increasingly clear that the gut microbiome can affect human health, including mental health. Which bacterial species influence the development of disease and how they do so, however, is only just starting to be unraveled.

For instance, some studies have found compelling links between one species of gut bacteria, Morganella morganii, and major depressive disorder. But until now, no one could tell whether this bacterium somehow helps drive the disorder, the disorder alters the microbiome, or something else is at play.

Harvard Medical School researchers have now pinpointed a biologic mechanism that strengthens the evidence that M. morganii influences brain health and provides a plausible explanation for how it does so.

BREAKING: Trump—Flanked By Larry Ellison, Sam Altman, & Masayoshi Son—Announces Project Stargate

Trump—flanked by larry ellison, sam altman, & masayoshi son—announces project stargate.

Trump announces Project Stargate, a $500 billion initiative backed by major tech leaders, aimed at revolutionizing U.S. AI infrastructure, creating jobs, and enhancing healthcare through advanced technologies. AI Infrastructure and Economic Impact.

🏗️Project Stargate, a $500+ billion AI infrastructure initiative, aims to construct colossal data centers and physical campuses across the US, potentially creating over 100,000 American jobs.

🌐The project will build physical and virtual infrastructure to power next-generation AI advancements, with Oracle, SoftBank, and Microsoft as key partners, establishing a new US-centered industry. ## Healthcare Applications.

S AI will enhance healthcare by providing doctors with condition-specific treatment plans based on data from top hospitals like Memorial Sloan Kettering and Stanford. ” + s cancer research focuses on early detection via blood tests, personalized vaccines designed using AI in 48 hours, and robotically-produced mRNA vaccines. ” +## Technological Advancements.

S AI-driven approach promises to accelerate cancer treatment development, potentially leading to unprecedented cure rates. ” + 📊The initiative will leverage AI to improve electronic health records, benefiting patients in underserved areas like Indian River Reservation.

New water purification technology helps turn seawater into drinking water without tons of chemicals

As humans age, their brain function can progressively decline and they become more vulnerable to developing neurodegenerative diseases, such as dementia. Dementia and other progressive neurological conditions can significantly impair their memory, thinking skills and daily functioning, significantly reducing their quality of life.

Many psychology and neurological studies have tried to identify biological markers and lifestyle factors that can contribute to the development of dementia. Yet the contribution of psychological characteristics (e.g., traits, emotional well-being and cognitive resilience) to a decline in mental functions remains poorly understood.

Researchers at University of Barcelona, University College London (UCL), Normandy University and other institutes across Europe recently set out to fill this gap in the literature, by trying to determine whether specific sets of psychological characteristics relate to brain health in middle and late adulthood. Their paper, published in Nature Mental Health, identified three key psychological profiles that were linked to different cognitive and trajectories after middle-age.

Papers: I have published quite a number of academic papers in the past 7–8 years

It has gotten to the point now that I find myself trying to make sense of them all. If you were to read them, what would you learn about me and my beliefs? Are there any coherent themes and patterns within these papers? I think there are and this is my attempt to hunt them out. I’m sure this will seem self-indulgent to some of you. I can only apologise. It is a deliberately self-indulgent exercise, but hopefully the thematic organisation is of interest to people other than myself, and some of the arguments may be intriguing or pique your curiosity. I’m going to keep this overview updated.

Reading note: There is some overlap in content between the sections below since some papers belonged to more than one theme. Also, clicking on the titles of the papers will take you directly to an open access version of them.

GLP-1 Drugs Offer Brain Benefits but May Pose Other Health Risks

Summary: A study analyzing data from over 2 million veterans found that GLP-1 receptor agonists, popular weight-loss drugs like Ozempic and Wegovy, provide significant neurological and behavioral health benefits, including reduced risks of addiction, Alzheimer’s, and dementia. However, they also pose risks for pancreatitis and kidney conditions, emphasizing the need for careful monitoring.

The drugs mimic hormones that curb appetite and aid weight loss but may act on brain regions tied to impulse control and inflammation, explaining their broad effects. Researchers stress that while the benefits are modest, they may be impactful for conditions with limited treatment options, highlighting both their potential and limitations.

Bacteria in polymers create cable-like structures that grow into living gels

Scientists at Caltech and Princeton University have discovered that bacterial cells growing in a solution of polymers, such as mucus, form long cables that buckle and twist on each other, building a kind of “living Jell-O.”

The finding could be particularly important to the study and treatment of diseases such as cystic fibrosis, in which the mucus that lines the lungs becomes more concentrated, often causing bacterial infections that take hold in that mucus to become life threatening. This discovery could also have implications in studies of polymer-secreting conglomerations of bacteria known as biofilms—the slippery goo on river rocks, for example—and in industrial applications where they can cause equipment malfunctions and health hazards.

The work is described in a paper published on January 17 in the journal Science Advances.

Ultra-small neuromorphic chip learns and corrects errors autonomously

Existing computer systems have separate data processing and storage devices, making them inefficient for processing complex data like AI. A KAIST research team has developed a memristor-based integrated system similar to the way our brain processes information. It is now ready for application in various devices, including smart security cameras, allowing them to recognize suspicious activity immediately without having to rely on remote cloud servers, and medical devices with which it can help analyze health data in real time.

The joint research team of Professor Shinhyun Choi and Professor Young-Gyu Yoon of the School of Electrical Engineering has developed the next-generation neuromorphic semiconductor-based ultra-small computing chip that can learn and correct errors on its own. The research is published in the journal Nature Electronics.

What is special about this computing chip is that it can learn and correct errors that occur due to non-ideal characteristics that were difficult to solve in existing neuromorphic devices. For example, when processing a , the chip learns to automatically separate a moving object from the background, and it becomes better at this task over time.