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Scientists Discover Game-Changing New Way To Treat High Cholesterol

Scientists are rethinking how to treat a widespread genetic cholesterol disorder by targeting particle production instead of removal.

Familial hypercholesterolemia (FH) disrupts one of the body’s most important cleanup systems. Normally, low-density lipoprotein (LDL), often called “bad” cholesterol, is removed from the bloodstream by LDL receptors (LDLR) in the liver. These receptors act like docking stations, pulling cholesterol into cells where it can be broken down. In people with FH, mutations in the LDLR gene weaken or disable this process.

As a result, cholesterol builds up in the blood for decades, often without obvious symptoms until it leads to heart attacks or other cardiovascular problems. About 1 in 200 adults carries this genetic change, making it one of the most common inherited disorders worldwide.

Spatiotemporal molecular profiling of macrophage-fibroblast crosstalk defines checkpoints orchestrating onset and resolution of inflammation

Weishaupt, Chambers, et al. combine single-cell transcriptomic and epigenomic profiling with in vivo models to map the temporal dynamics of macrophage-fibroblast communication during inflammatory arthritis. They show that fibroblasts initiate inflammation, whereas monocyte-derived macrophages undergo transcriptional reprogramming into SPP1+ cells that actively promote resolution by restraining fibroblast pathogenicity.

Systolic Blood Pressure Trajectory and Outcomes in Acute Intracerebral HemorrhagePooled Analysis of the 4 INTERACT and ATACH-II Clinical Trials

Systolic blood pressure trajectory and outcomes in acute intracerebral hemorrhage: pooled analysis of the 4 INTERACT and ATACH-II clinical trials.

Background and Objectives.

Scientists capture superconductivity’s ‘dancing pairs’ for first time, revealing missing pieces in a decades-old theory

For the first time, scientists have directly imaged the quantum process underlying superconductivity, a phenomenon in which paired electrons cause electric current to flow without resistance at sufficiently low temperatures. The results weren’t quite what they expected.

In the study, published April 15 in Physical Review Letters, the scientists directly imaged individual atoms pairing up in a special gas cooled nearly to absolute zero—the unreachable limit to how cold things can get. The type of gas, called a Fermi gas, allows scientists to substitute electrons with atoms and probe the physics of superconductors in a controlled way.

Surprisingly, the scientists found that after pairing up, the atoms moved in a synchronized dance, with their positions dependent on those of other pairs—a phenomenon not predicted by the 70-year-old, Nobel-prize-winning theory of superconductivity.

Multitasking quantum sensors can measure several properties at once

A special class of sensors leverages quantum properties to measure tiny signals at levels that would be impossible using classical sensors alone. Such quantum sensors are currently being used to study the inner workings of cells and the outer depths of our universe.

Particularly promising are solid-state quantum sensors, which can operate at room temperature. Unfortunately, most solid-state quantum sensors today only measure one physical quantity at a time—such as the magnetic field, temperature, or strain in a material. Trying to measure both the magnetic field and temperature of a material at the same time causes their signals to get mixed up and measurements to become unreliable.

Now, MIT researchers have created a way to simultaneously measure multiple physical quantities with a solid-state quantum sensor. They achieved this by exploiting entanglement, where particles become correlated into a single quantum state. In a new paper, the team demonstrated its approach in a commonly used quantum sensor at room temperature, measuring the amplitude, frequency, and phase of a microwave field in a single measurement. They also showed the approach works better than sequentially measuring each property or using traditional sensors.

AI chatbot teaches AI ‘student’ to love owls, even after data is scrubbed

Large language models (LLMs) can teach other algorithms unwanted traits, which can persist even when training data has been scrubbed of the original trait, according to new research published in Nature. In one example, a model seems to transmit a preference for owls to other models via hidden signals in data. The findings demonstrate that more thorough safety checks are needed when producing LLMs.

LLMs can generate datasets to train other models through a process called distillation, in which a “student” model is taught to mimic the outputs of a “teacher” model. While this process can be used to produce cheaper versions of an LLM, it is unclear which properties of the teacher model are transferred to the student.

Alex Cloud and colleagues used GPT-4.1, which was prompted to have traits unrelated to a core task (a preference for owls or certain trees, for instance), to train a student model with output consisting only of numerical data, with no references to the trait. When the resulting student was subsequently prompted, it mentioned the teacher’s favorite animal or tree over 60% of the time, compared to 12% for a student trained by a teacher with no favorite animal or tree. This effect was also observed when the student was trained on a teacher’s output that contained code instead of numbers.

Abstract: Immune signaling and function in neurodegeneration:

Yvonne L. Latour & Dorian B. McGavern contribute a Review to the JCI Series on Neurodegeneration, discussing signaling pathways, cellular players, and immune responses shared across multiple neurodegenerative diseases, while considering external factors that may influence CNS disease progression. Neurodegeneration.

Viral Immunology and Intravital Imaging Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, Maryland, USA.

Intranasal Human NSC‐Derived EVs Therapy Can Restrain Inflammatory Microglial Transcriptome, and NLRP3 and cGAS‐STING Signalling, in Aged Hippocampus

Tiny “fires” of inflammation smolder deep within the brain’s memory center, creating a persistent brain fog that makes it harder to think, form new memories or even adapt to new environments, all the while increasing the risk to disorders like Alzheimer’s disease.

Scientists call this slow burn “neuroinflammaging,” and for decades it was thought to be the inevitable price of growing older.

Until now.

A landmark study from researchers at the Texas A&M University Naresh K. Vashisht College of Medicine suggests the inflammatory tide responsible for brain aging and brain fog might actually be reversible. And the solution doesn’t involve brain surgery, but a simple nasal spray.

Led by Dr. Ashok Shetty, university distinguished professor and associate director of the Institute for Regenerative Medicine, along with senior research scientists Dr. Madhu Leelavathi Narayana and Dr. Maheedhar Kodali, the team developed a nasal spray that, with just two doses, dramatically reduced brain inflammation, restored the brain’s cellular power plants and significantly improved memory.

The most surprising part? It all happened within weeks and lasted for months.

The findings, published in the Journal of Extracellular Vesicles, could reshape the future of neurodegenerative therapies and may even change how scientists think about brain aging itself.

Continue reading “Intranasal Human NSC‐Derived EVs Therapy Can Restrain Inflammatory Microglial Transcriptome, and NLRP3 and cGAS‐STING Signalling, in Aged Hippocampus” | >
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