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Blog – Page 11

Proteins in cells are highly flexible and often exist in multiple conformations, each with unique abilities to bind ligands. These conformations are regulated by the organism to control protein function. Currently, most studies on protein structure and activity are conducted using purified proteins in vitro, which cannot fully replicate the complexity of the intracellular environment and may be influenced by the purification process or buffer conditions.

In a study published in the Journal of the American Chemical Society, a team led by Prof. Wang Fangjun from the Dalian Institute of Chemical Physics of the Chinese Academy of Sciences (CAS), collaborating with Prof. Huang Guangming from the University of Science and Technology of China of CAS, developed a new method for in-cell characterization of proteins using vacuum ultraviolet photodissociation top-down (UVPD-TDMS), providing an innovative technology for analyzing the heterogeneity of intracellular protein in situ with MS.

Researchers combined in-cell MS with 193-nm UVPD to directly analyze protein structures within cells. This method employed induced electrospray ionization, which ionizes intracellular proteins with minimal structural perturbation.

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Deciphering some people’s writing can be a major challenge—especially when that writing is cuneiform characters imprinted onto 3,000-year-old tablets.

Now, Middle East scholars can use (AI) to identify and copy over cuneiform characters from photos of tablets, letting them read complicated scripts with ease.

Along with Egyptian hieroglyphs, cuneiform is one of the oldest known forms of writing, and consists of more than 1,000 unique characters. The appearance of these characters can vary across eras, cultures, geography and even individual writers, making them difficult to interpret. Researchers from Cornell and Tel Aviv University (TAU) have developed an approach called ProtoSnap that “snaps” into place a prototype of a character to fit the individual variations imprinted on a tablet.

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The human brain continuously processes the wide range of information it acquires from the outside world. Over time, this information is organized into mental representations, referred to as “schema,” which help us to understand what is happening at a given time and make predictions about what will happen next.

Temporal schemas are that specifically outline the order in which specific events occur. For instance, when attending a wedding, temporal schemas could allow us to anticipate the order in which different parts of the ritual (e.g., the arrival of the bride, the exchange of vows, etc.) will take place.

Researchers at Tilburg University and Princeton University recently carried out a study aimed at further exploring how the brain represents these structured sequences of events.

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3D printing is revolutionizing microbial electrochemical systems (MES) by enabling precise reactor design, custom electrode fabrication, and enhanced bioprinting applications. These innovations optimize pollutant degradation and energy production, with significant implications for sustainability and environmental management.

Microbial electrochemical systems (MES) are emerging as a promising technology for addressing environmental challenges by leveraging microorganisms to transfer electrons. These systems can simultaneously degrade pollutants and generate electricity, making them valuable for sustainable wastewater treatment and energy production.

However, conventional methods for constructing MES components often lack design flexibility, limiting performance optimization. To overcome these limitations and enhance MES efficiency, innovative fabrication techniques are needed—ones that allow precise control over reactor structures and functions.

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Deep within certain magnetic molecules, atoms arrange their spins in a spiral pattern, forming structures called chiral helimagnets. These helical spin patterns have intrigued researchers for years due to their potential for powering next-generation electronics. But decoding their properties has remained a mystery—until now.

Researchers at the University of California San Diego have developed a to accurately model and predict these complex spin structures using quantum mechanics calculations. Their work was published on Feb. 19 in Advanced Functional Materials.

“The helical spin structures in two-dimensional layered materials have been experimentally observed for over 40 years. It has been a longstanding challenge to predict them with precision,” said Kesong Yang, professor in the Aiiso Yufeng Li Family Department of Chemical and Nano Engineering at the UC San Diego Jacobs School of Engineering and senior author of the study. “The helical period in the layered compound extends up to 48 nanometers, making it extremely difficult to accurately calculate all the electron and spin interactions at this scale.”

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In the quest for ultra-secure, long-range quantum communication, two major challenges stand in the way: the unpredictable nature of atmospheric turbulence and the limitations of current optical wavefront correction techniques. Researchers at the University of Ottawa, under the supervision of Professor Ebrahim Karimi, the director of Nexus for Quantum Technologies, in collaboration with the National Research Council Canada (NRC) and the Max Planck Institute for the Science of Light (Germany), have made significant advances in overcoming both obstacles.

Their two latest breakthroughs—an AI-powered forecasting tool called TAROQQO and a high-speed Adaptive Optics (AO) system for correcting turbulence in quantum channels—represent a turning point in developing free-space quantum networks.

These advancements, published in Optics Express and Communication Physics, offer complementary solutions to the fundamental issue of atmospheric turbulence that distorts and diminishes photonic quantum states as they traverse through the air.

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Two-photon vision is an emerging technique with significant potential for the future of ophthalmic diagnostics. While it offers many advantages, certain aspects still require refinement. Scientists at ICTER have advanced this technology, enhancing its capabilities and expanding its potential applications in ocular medicine.

Imagine looking through a kaleidoscope that reveals a spectrum of colors beyond human vision, where invisible light is brought into focus. In conventional sight, photons—the fleeting messengers of light—typically appear alone. However, in the phenomenon of two-photon vision, they work in pairs, allowing the human eye to perceive infrared laser pulses instead of visible light, unlocking access to an otherwise invisible world.

A crucial aspect of understanding two-photon vision is measuring the brightness of these stimuli. Until now, this was only possible for visible light. Scientists at the International Centre for Eye Research (ICTER) have achieved a groundbreaking milestone by determining the luminance value of infrared light using photometric units (cd/m²). This discovery has enabled them to connect the brightness of two-photon stimuli to a newly defined physical quantity: two-photon retinal illumination, a key factor in understanding perceived brightness.

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Threat actors deploying the Black Basta and CACTUS ransomware families have been found to rely on the same BackConnect (BC) module for maintaining persistent control over infected hosts, a sign that affiliates previously associated with Black Basta may have transitioned to CACTUS.

“Once infiltrated, it grants attackers a wide range of remote control capabilities, allowing them to execute commands on the infected machine,” Trend Micro said in a Monday analysis. “This enables them to steal sensitive data, such as login credentials, financial information, and personal files.”

It’s worth noting that details of the BC module, which the cybersecurity company is tracking as QBACKCONNECT owing to overlaps with the QakBot loader, was first documented in late January 2025 by both Walmart’s Cyber Intelligence team and Sophos, the latter of which has designated the cluster the name STAC5777.

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