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Fever temperatures rev up immune cell metabolism, proliferation and activity, but they also — in a particular subset of T cells — cause mitochondrial stress, DNA damage and cell death, Vanderbilt University Medical Center researchers have discovered.

The findings, published Sept. 20 in the journal Science Immunology, offer a mechanistic understanding for how cells respond to heat and could explain how chronic inflammation contributes to the development of cancer.

The impact of fever temperatures on cells is a relatively understudied area, said Jeff Rathmell, PhD, Cornelius Vanderbilt Professor of Immunobiology and corresponding author of the new study. Most of the existing temperature-related research relates to agriculture and how extreme temperatures impact crops and livestock, he noted. It’s challenging to change the temperature of animal models without causing stress, and cells in the laboratory are generally cultured in incubators that are set at human body temperature: 37 degrees Celsius (98.6 degrees Fahrenheit).

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New research done at NASA’s Jet Propulsion Laboratory reveals potential signs of a rocky, volcanic moon orbiting an exoplanet 635 light-years from Earth. The biggest clue is a sodium cloud that the findings suggest is close to but slightly out of sync with the exoplanet, a Saturn-size gas giant named WASP-49 b, although additional research is needed to confirm the cloud’s behavior. Within our solar system, gas emissions from Jupiter’s volcanic moon Io create a similar phenomenon.

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Research on superconductivity has taken a significant leap with Princeton Universitys exploration of edge supercurrents in topological superconductors like molybdenum telluride.

Initially elusive, these supercurrents have been observed and enhanced through experiments with niobium, leading to intriguing phenomena such as stochastic switching and anti-hysteresis, altering the understanding of electron behavior in superconductors.

Superconductivity and Topological Materials.

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Researchers at Freie Universität Berlin, University of Maryland and NIST, Google AI, and Abu Dhabi set out to robustly estimate the free Hamiltonian parameters of bosonic excitations in a superconducting quantum simulator. The protocols they developed, outlined in a paper pre-published on arXiv, could contribute to the realization of highly precise quantum simulations that reach beyond the limits of classical computers.

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All proteins are composed of chains of amino acids, which generally fold up into compact globules with specific shapes. The folding process is governed by interactions between the different amino acids—for example, some of them carry electrical charges—so the sequence determines the structure. Because the structure in turn defines a protein’s function, deducing a protein’s structure is vital for understanding many processes in molecular biology, as well as for identifying drug molecules that might bind to and alter a protein’s activity.

Protein structures have traditionally been determined by experimental methods such as x-ray crystallography and electron microscopy. But researchers have long wished to be able to predict a structure purely from its sequence—in other words, to understand and predict the process of protein folding.

For many years, computational methods such as molecular dynamics simulations struggled with the complexity of that problem. But AlphaFold bypassed the need to simulate the folding process. Instead, the algorithm could be trained to recognize correlations between sequence and structure in known protein structures and then to generalize those relationships to predict unknown structures.

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OLED performance depends on the behavior of electron–hole pairs, or excitons, that form within the emissive layer of the device. High efficiencies can be obtained when most of the excitons produce light as they decay, but some excitons can be lost without emitting light through a process known as exciton–polaron quenching (EPQ).

EPQ was believed to occur mainly within the bulk of the emissive layer, but recent studies have suggested that significant quenching can take place at the interface with the adjacent device layers. To isolate this energy-loss channel, the researchers designed a series of bilayer devices that allowed them to identify three physical factors that govern interfacial EPQ in any OLED device. They found that the dominant factor is the effect of the energy barriers experienced by electrons and holes at the interfaces: A barrier higher than about 0.2 eV leads to greater interfacial EPQ, which causes a significant drop in emission efficiency.

Armed with this knowledge the researchers engineered OLED devices to minimize losses from interfacial EPQ, which resulted in efficiency enhancements for red, green, and blue devices of 70%, 47%, and 66%, respectively. The loss mitigation also increased the lifetime of blue OLEDs by as much as 67%, an important result for creating long-lived full-color displays.

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