Camille Boutin, Laurent Kodjabachian et al. describe an inducible multiciliated cell line well suited for advanced microscopy and proteomic approaches. The study provides a detailed proteomic profiling of MCC during their differentiation.
Boutin et al., describe an inducible multiciliated cell line well suited for advanced microscopy and proteomic approaches. The study provides a detailed pr.
Researchers at Washington University School of Medicine in St. Louis have developed a method to predict when someone is likely to develop symptoms of Alzheimer’s disease using a single blood test. In a study published in Nature Medicine, the researchers demonstrated that their models predicted the onset of Alzheimer’s symptoms within a margin of three to four years.
This method could have implications both for clinical trials developing preventive Alzheimer’s treatments and for eventually identifying individuals likely to benefit from these treatments.
More than seven million Americans live with Alzheimer’s disease, with health and long-term care costs for Alzheimer’s and other forms of dementia projected to reach nearly $400 billion in 2025, according to the Alzheimer’s Association. This massive public health burden currently has no cure, but predictive models could help efforts to develop treatments that prevent or slow the onset of Alzheimer’s symptoms.
As aging populations and rising diabetes rates drive an increase in chronic wounds, more patients face the risk of amputations. UC Riverside researchers have developed an oxygen-delivering gel capable of healing injuries that might otherwise progress to limb loss.
Injuries that fail to heal for more than a month are considered chronic wounds. They affect an estimated 12 million people annually worldwide, and around 4.5 million in the U.S. Of these, about one in five patients will ultimately require a life-altering amputation.
The new gel, tested in animal models, targets what researchers believe is a root cause of many chronic wounds: a lack of oxygen in the deepest layers of the damaged tissue. Without sufficient oxygen, wounds languish in a prolonged state of inflammation, allowing bacteria to flourish and tissue to deteriorate rather than regenerate.
Traumatic injury is the third leading cause of death in the state of Texas, surpassing strokes, Alzheimer’s disease and diabetes, according to the Centers for Disease Control and Prevention. A massive number of these deaths are the result of uncontrolled bleeding. “Severe blood loss can rapidly lead to hemorrhagic shock,” said Dr. Akhilesh Gaharwar, a biomedical engineering professor at Texas A&M University. “Many patients die within one to two hours of injury. This critical period is often referred to as the ‘golden hour.’”
Gaharwar and his fellow researchers in the biomedical engineering department have found a way to extend this golden hour—using clay.
Gaharwar, Dr. Duncan Maitland and Dr. Taylor Ware are developing a suite of injectable hemostatic bandages —biomedical materials that stop bleeding and promote blood to clot faster. Their research is specifically targeting deep internal bleeding where traditional methods like compression are not possible.
Can you design a mechanism that will trace out the shape of a heart? How about the shape of a moon, or a star? Mechanism design—the art of assembling linkages and joints to create machines with prescribed motion—is one of the quintessential activities of mechanical engineers, but has resisted automation for almost two centuries.
In his seminal 1841 book Principles of Mechanisms, Oxford professor Robert Willis famously noted, “When the mind of a mechanician is occupied with the contrivance of a machine, he must wait until, in the midst of his meditations, some happy combination presents itself to his mind which may answer his purpose.”
Almost 200 years later, we still teach machine design mostly by apprenticeship. While we can simulate machines of almost any complexity, systematic methods for design are known only for the most trivial contraptions.
Within the STRUCTURES Cluster of Excellence, two research teams at the Interdisciplinary Center for Scientific Computing (IWR) have refined a computing process, long held to be unreliable, such that it delivers precise results and reliably establishes a physically meaningful solution. The findings are published in the Journal of the American Chemical Society.
Why molecular electron densities matter
How electrons are distributed in a molecule determines its chemical properties—from its stability and reactivity to its biological effect. Reliably calculating this electron distribution and the resulting energy is one of the central functions of quantum chemistry. These calculations form the basis of many applications in which molecules must be specifically understood and designed, such as for new drugs, better batteries, materials for energy conversion, or more efficient catalysts.
Researchers at UC San Francisco have discovered a mechanism that could explain how exercise improves cognition by shoring up the brain’s protective barrier. With age, the network of blood vessels—called the blood–brain barrier—gets leaky, letting harmful compounds enter the brain. This causes inflammation, which is associated with cognitive decline and is seen in conditions like Alzheimer’s disease. The research is published in the journal Cell.
Six years ago, the team identified a brain-rejuvenating enzyme called GPLD1 that mice produced in their livers when they exercised. But they couldn’t understand how it worked, because it cannot get into the brain.
The new study answers that question. Researchers discovered that GPLD1 was working through another protein called TNAP. As the mice age, the cells that form the blood-brain barrier accumulate TNAP, which makes it leaky. But when mice exercise, their livers produce GPLD1. It travels to the vessels that surround the brain and trims TNAP off the cells.
A team led by Northwestern University and Shirley Ryan AbilityLab scientists have developed a new technology that can eavesdrop on the hidden electrical dialogues unfolding inside miniature, lab-grown human brain-like tissues. Known as human neural organoids—and sometimes called “mini brains”—these millimeter-sized structures are powerful models of brain development and disease. But until now, scientists could only record and stimulate activity from a small fraction of their neurons—missing network-wide dynamics that give rise to coordinated rhythms, information processing and the complex patterns of activity that define brain function.
For the first time, the new technology overcomes that stubborn limitation. The soft, three-dimensional (3D) electronic framework wraps around an organoid like a breathable, high-tech mesh. Rather than sampling select regions, it delivers near-complete, shape-conforming coverage with hundreds of miniaturized electrodes. That dense, three-dimensional interfacing enables scientists to map and manipulate neural activity across almost the entire organoid.
By moving from localized probing to true whole-network mapping, the work brings organoid research closer to capturing how real human brains develop, function and even fail.
A research team led by the U.S. National Science Foundation National Center for Atmospheric Research (NSF NCAR) has published a foundational inventory of emissions produced by structures destroyed by fires in the wildland-urban interface (WUI). Previously, researchers suspected that fires in WUI areas—spaces where human development and undeveloped wildland meet—produce emissions that are likely more harmful than those produced by forest or grass fires. However, the amount of emissions had not been quantified.
This new study, published in Nature Communications, provides the first inventory of emissions from structure fires in WUI areas. The results definitively reveal structure fires as a major source of air pollution.
WUI fires are becoming increasingly more common in the U.S. and have destroyed more than 100,000 homes since 2005. Because these events are intensely concentrated both in time and space, they can produce exceptionally high local pollution, which has important implications for the air quality and public health of nearby urban areas.