A 14-protein extracellular matrix aging clock derived from circulating matrisome proteins predicts chronological and biological age across cohorts and biofluids, distinguishes health from disease, an…
In a cross-sectional study of adults aged 25–49 years in the US, colorectal cancer (CRC) mortality rose from 1994 to 2023, primarily among those with 15 or fewer years of education, and educational disparities in mortality widened over time. More on the study.
Researchers analyze trends in colorectal cancer mortality among adults aged 25–49 years in a study spanning about three decades.
A South Pole neutrino experiment has measured radio waves induced by cosmic rays—thus demonstrating that its detection method works.
Detection of high-energy neutrinos, elusive particles produced in supernovae and other astrophysical events, is opening up a new window on the Universe. One way to spot them is to search for signals of neutrino collisions with molecules in large sheets of polar ice. An international collaboration working in Antarctica has now reported the detection of ice-traversing radio waves that originate from cosmic-ray-induced particle showers [1]. Even though the radio waves were generated by cosmic rays rather than neutrinos, the result establishes a proof of principle that the technique should work for neutrinos too.
Ice-sheet-based detection of cosmic neutrinos has been reported previously from the IceCube Neutrino Observatory at the South Pole [2]. In that experiment, neutrino collisions with water molecules produce flashes of visible light, called Cherenkov radiation, generated by fast-moving collision by-products. This method becomes challenging for neutrinos of extremely high energy (around 1018 electron volts, or 1 exa-electron-volt) because these neutrinos are expected to be exceedingly rare. Researchers would need detectors spread over hundreds of cubic kilometers of ice to have a chance of seeing Cherenkov radiation from such a rare exa-electron-volt event.
Using a renewable energy source has multiple benefits, including reducing harmful emissions and dependence on fossil fuels while increasing efficiency. But many renewable energy sources have a higher cost than fossil fuels due to the materials needed to make them usable, such as platinum group metals (PGMs), and the high cost of storage.
A team of researchers led by Gang Wu, a professor of energy, environmental and chemical engineering at the McKelvey School of Engineering at Washington University in St. Louis is working to change that. The team is creating a heterostructure catalyst for an anion-exchange membrane water electrolyzer (AEMWE) that splits water into hydrogen and oxygen using electricity from renewable sources. They created the catalyst with two phosphides that gave them an efficient method to extract hydrogen, a valuable yet low-cost source of zero-emissions fuel. The study is published in the Journal of the American Chemical Society.
Wu’s team has been looking for alternatives to catalysts that use expensive platinum group metals. In this research, their idea began with using sunlight, wind or water to create electricity that they could then use to separate hydrogen from water.
An AI model informed by calculations from a quantum computer can better predict the behavior of a complex physical system over the long term than current best models that use only conventional computers, according to a new study led by UCL (University College London) researchers. The findings, published in the journal Science Advances, could improve models predicting how liquids and gases move and interact (fluid dynamics), used in areas ranging from climate science to transport, medicine and energy generation.
The researchers say the improved performance is linked to a quantum device’s ability to hold a large amount of information more efficiently. That is because instead of bits that are switched on or off, 1 or 0, as in a classical computer, the quantum computer’s qubits can be 1, 0, or any state in between, and each qubit can affect any of the other qubits—meaning a few qubits can generate a vast number of possible states.
Senior author Professor Peter Coveney, based in UCL Chemistry and the Advanced Research Computing Center at UCL, said, To make predictions about complex systems, we can either run a full simulation, which might take weeks—often too long to be useful—or we can use an AI model, which is quicker but more unreliable over longer time scales.
Bacterial sensors usually rely on emitting light to transfer information about what they’re sensing, but that method isn’t practical in many settings. That’s why most information transmission is done via electricity. And while electricity-emitting bacteria exist, manipulating them into useful sensors has been quite challenging. Rice University professor Caroline Ajo-Franklin’s group, working in collaboration with researchers from Tufts University and Baylor College of Medicine, recently developed a flexible bioelectrical sensor system called electroactive co-culture sensing system (e-COSENS). The study is published in Nature Biotechnology.
“Bioelectrical sensing is by no means a new concept,” said Ajo-Franklin, the Ralph and Dorothy Looney Professor of Biosciences and corresponding author on this paper. “But e-COSENS is the first system that allows us to easily engineer bioelectronic sensors in a modular manner, like assembling Legos, allowing us to potentially use them to monitor everything from human health to environmental contaminants.”
Bioelectrical sensing requires bacteria that produce electricity and are easy for researchers to manipulate to respond to different substances. Ideally, the bacteria would be able to live in a variety of different places so that the system could be used in environments ranging from rivers to milk.
European astronomers have used the Atacama Large Millimeter Array (ALMA) and the James Webb Space Telescope (JWST) to observe a recently discovered giant disk galaxy known as ADF22.1. Results of the new observations, published April 8 on the arXiv preprint server, shed more light on the formation and evolution of this galaxy.
ADF22.1, also known as ADF22.A1, is a giant disk barred spiral galaxy residing in a proto-cluster known as SSA22 at a redshift of 3.09. It has an effective radius of some 22,800 light years and a stellar mass of about 100 billion solar masses. Previous observations have found that it is a dusty star-forming galaxy (DSFG) hosting an intrinsically bright yet heavily obscured active galactic nucleus (AGN).
Giant disk galaxies with high stellar masses, like ADF22.1, are generally expected to be quiescent, bulge-dominated systems. Given that ADF22.1 is a starburst galaxy, it is perceived by astronomers as a unique laboratory to explore how early universe galaxies and supermassive black holes (SMBHs) accumulate their mass and ultimately evolve into the most massive elliptical galaxies.
Infections from antibiotic-resistant bacteria are difficult to treat and are responsible for over 2.8 million infections and more than 35,000 deaths in the U.S. each year. A new study in Nature Communications reports that a drug used to lower blood pressure could also be the basis of a promising new treatment for methicillin-resistant Staphylococcus aureus (MRSA).
“MRSA commonly causes infections in both hospitals and the community. It infects people in different ways and can survive even when antibiotics are used, which makes treatment extremely difficult,” said corresponding author Eleftherios Mylonakis, M.D., Ph.D., chair, Houston Methodist Charles W. Duncan Jr. Department of Medicine.
“Scientists around the world are looking at various ways to provide treatment options outside of established antibiotics. The high cost of developing new drugs, and the time it takes to do so, led our team to explore the possibility of using existing medications, approved for other uses, to treat bacterial infections.”
For the first time, a research team at the Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) has succeeded in reducing the size of, or even completely removing, chromosomes in plants with large genomes, such as wheat. They achieved this by using the CRISPR/Cas gene-editing tool to target highly repetitive sections of DNA. The results of the study, published today in the journal Plant Communications, could significantly accelerate breeding processes.
While the targeted manipulation of entire chromosomes is well established in model organisms such as Arabidopsis thaliana, it has posed a significant challenge in crops with large genomes, such as wheat. The IPK research team has now set out to determine whether highly repetitive DNA sequences known as satellite DNA are suitable targets for the CRISPR gene-editing system. The idea was that cutting many of these identical sequences simultaneously could affect the entire chromosome. The team introduced CRISPR components into the plants using a virus-based system. This approach bypasses lengthy traditional transformation processes and enables highly efficient chromosomal modifications.
“In our study, we were actually able to demonstrate for the first time that chromosomes can be efficiently reduced in size by making targeted cuts in satellite DNA,” says Dr. Jianyong Chen, the study’s first author. This is a significant breakthrough, as such changes had previously only occurred by chance. You can think of it like a rope. If you cut a rope in several places at once, it becomes unstable and eventually snaps. The same thing happens to chromosomes when many cuts are made simultaneously.
Wearable technologies are starting to reshape how people manage health. Continuous glucose monitors that measure blood sugar levels in diabetes patients have already shown the power of tracking an important molecule in real time. The next leap is to track other medically important molecules. However, doing so is far more difficult because most of those molecules are present at much lower concentrations than glucose.
One area such wearable technologies could transform is drug therapy. Many powerful medications are still managed through blood tests that offer only occasional snapshots of how a patient’s body is processing treatment. For drugs that must be dosed precisely to avoid harm, clinicians can miss the point at which dosing becomes ineffective or begins to threaten the organs responsible for processing the drug.
A UCLA-led research team has now developed a microneedle sensor platform designed to address that problem through continuous, minimally invasive monitoring in skin. In a study published in Science Translational Medicine, the researchers showed in rats that the sensors could operate continuously for six days, track drug concentrations over time and provide insight into kidney and liver function by measuring how quickly the body cleared those drugs.