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Nanoparticles show potential for rheumatoid arthritis prevention and flare control

As a chronic condition, rheumatoid arthritis (RA) can’t be cured, so treatment focuses on managing the disease and controlling its progression. Although current treatments help control RA symptoms in most people, they cannot prevent the onset of RA or painful flare-ups.

Now, researchers publishing in ACS Central Science have developed nanoparticles that could slow and reduce flare severity, based on results from tests with and mice models with RA-like disease.

For a person diagnosed with RA, their attacks tissue that makes up the joints, causing inflammation, swelling and pain. However, as the disease progresses, serious cartilage and bone damage can occur if left uncontrolled.

Lipid nanoparticle stereochemistry shapes mRNA delivery safety and efficacy, study reveals

A team from the Max-Planck-Institut für Kohlenforschung, Hokkaido University, and Osaka University has discovered that subtle differences in molecular structure can have a major impact on the performance of mRNA-based drugs. Their findings, published in the Journal of the American Chemical Society, open the door to the development of safer and more effective vaccines and therapies.

To deliver therapeutic nucleic acids like mRNA into cells, scientists rely on (LNPs)—tiny, fat-based carriers that protect fragile genetic material, enabling it to survive in the body and reach target cells. A key component of these LNPs are ionizable lipids, which help mRNA enter cells and then release it effectively. One such lipid, ALC-315, was notably used in the Pfizer/BioNTech COVID-19 vaccine, a medical breakthrough that played a critical role in controlling the global pandemic.

Light-powered nano-motor winds molecular strands into chain-like structures

Threads or ropes can easily be used for braiding, knotting, and weaving. In chemistry, however, processing molecular strands in this way is an almost impossible task. This is because molecules are not only tiny, they are also constantly in motion and therefore cannot be easily touched, held or precisely shaped.

A research group at the Institute of Chemistry at Humboldt-Universität zu Berlin (HU) led by Dr. Michael Kathan has now succeeded in precisely winding two molecular strands around each other using an artificial, light-driven molecular motor, thereby creating a particularly complex structure: a catenane (from Latin “catena” = chain). Catenanes consist of two ring-shaped molecules that are intertwined like the links of a chain—without being chemically bonded to each other. The research results are published in the journal Science.

“What we have developed is basically a mini-machine that is powered by light and rotates in one direction,” says Kathan.

New imaging method reveals how light and heat generate electricity in nanomaterials

UC Riverside researchers have unveiled a powerful new imaging technique that exposes how cutting-edge materials used in solar panels and light sensors convert light into electricity—offering a path to better, faster, and more efficient devices.

The breakthrough, published in the journal Science Advances, could lead to improvements in solar energy systems and optical communications technology. The study title is “Deciphering photocurrent mechanisms at the nanoscale in van der Waals interfaces for enhanced optoelectronic applications.”

The research team, led by associate professors Ming Liu and Ruoxue Yan of UCR’s Bourns College of Engineering, developed a three-dimensional imaging method that distinguishes between two fundamental processes by which light is transformed into electric current in quantum materials.

Nanotechnology in AI: Building Faster, Smaller, and Smarter Systems

As artificial intelligence (AI) rapidly advances, the physical limitations of conventional semiconductor hardware have become increasingly apparent. AI models today demand vast computational resources, high-speed processing, and extreme energy efficiency—requirements that traditional silicon-based systems struggle to meet. However, nanotechnology is stepping in to reshape the future of AI by offering solutions that are faster, smaller, and smarter at the atomic scale.

The recent article published by AZoNano provides a compelling overview of how nanotechnology is revolutionizing the design and operation of AI systems, pushing beyond the constraints of Moore’s Law and Dennard scaling. Through breakthroughs in neuromorphic computing, advanced memory devices, spintronics, and thermal management, nanomaterials are enabling the next generation of intelligent systems.

Taming Heat in Quantum Tech

Many quantum technologies function only at ultralow temperatures. Managing the flow of heat in these systems is crucial for protecting their sensitive components. Now Matteo Pioldi and his colleagues at the CNR Institute of Nanoscience and the Scuola Normale Superiore, both in Pisa, Italy, have devised a thermal analogue of a transistor that could facilitate this heat management [1]. Just as a transistor can control electric currents, the new device has the potential to control heat currents in cryogenic quantum systems.

The most common type of transistor has three electrical terminals: the source, the gate, and the drain. Adjusting the voltage applied to the gate alters the strength of the electric current flowing from the source to the drain. In the proposed device, a semiconductor-based thermal reservoir serves as the source, and metallic thermal reservoirs serve as the gate and the drain. A second semiconductor-based reservoir exchanges heat with the source through photons and with the gate and the drain through electrons. Changing the gate’s temperature affects how easily heat flows through the device and, in turn, alters the strength of the heat current flowing from the source to the drain.

Pioldi and his colleagues performed numerical simulations of their device in a realistic setup at ultralow temperatures. They found that a small change in the strength of the heat current coming from the gate could cause the strength of the current between the source and the drain to increase by an amount that was 15 times larger. They say that their device could improve heat management in quantum circuits and thus help optimize quantum sensors, quantum computers, and other temperature-sensitive quantum systems.

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