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The immune system fights germs on the skin, in the tissues of the body, and in bodily fluids such as blood. It is made up of the innate (general) immune system and the adaptive (specialized) immune system. These two systems work closely together and take on different tasks.

The innate immune system is the body’s first line of defense against intruders. It responds in the same way to all germs and foreign substances, which is why it is sometimes referred to as the “non-specific” immune system. It acts very quickly – for instance, it makes sure that bacteria that have entered the skin through a small wound are detected and destroyed on the spot within a few hours. But the innate immune system can’t always stop germs from spreading.

This Review explores how experimental models of metastasis, such as mouse models and cell cultures, can complement the (multi)omics analysis of human metastasis samples, thereby filling knowledge gaps left by model studies and validating the findings from human sequencing data.

Aging is a complex, progressive, and irreversible biological process that entails numerous structural and functional changes in the organism. These changes affect all bodily systems, reducing their ability to respond and adapt to the environment. Chronic inflammation is one of the key factors driving the development of age-related diseases, ultimately causing a substantial decline in the functional abilities of older individuals. This persistent inflammatory state (commonly known as “inflammaging”) is characterized by elevated levels of pro-inflammatory cytokines, an increase in oxidative stress, and a perturbation of immune homeostasis. Several factors, including cellular senescence, contribute to this inflammatory milieu, thereby amplifying conditions such as cardiovascular disease, neurodegeneration, and metabolic disorders.

A new AI framework inspired by human memory could make machines more efficient, adaptive, and capable of reasoning. A recent paper published in the journal Engineering presents a novel approach to artificial intelligence by modeling it after how human memory functions. The research aims to overco

Physicists at the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory and Stony Brook University (SBU) have shown that particles produced in collimated sprays called jets retain information about their origins in subatomic particle smashups. The study was recently published as an Editor’s Suggestion in the journal Physical Review Letters.

“Despite extensive research, the connection between a jet’s initial conditions and its final particle distribution has remained elusive,” said Charles Joseph Naim, a research associate at the Center for Frontiers in Nuclear Science (CFNS) in SBU’s Department of Physics and Astronomy. “This study, for the first time, establishes a direct connection between the ‘entanglement entropy’ at the earliest stage of jet formation and the particles that emerge as a jet evolves.”

The evidence comes from an analysis of jet particles emerging from captured by the ATLAS experiment at the Large Hadron Collider, a 17-mile-circumference circular collider located at CERN, the European Organization for Nuclear Research. In these powerful collisions, the individual building blocks of the colliding protons, known as quarks and gluons, scatter off one another and sometimes get knocked free with enormous amounts of energy. But quarks can’t stay free for long. They and the gluons that normally hold them together immediately begin to split and reconnect through a branching process called fragmentation. The result is the formation of many new composite particles made of pairs or triplicates of quarks—collectively known as hadrons—that spray out of the collision in a coordinated way, that is, as a jet.

When exploring their surroundings, communicating with others and expressing themselves, humans can perform a wide range of body motions. The ability to realistically replicate these motions, applying them to human and humanoid characters, could be highly valuable for the development of video games and the creation of animations, content that can be viewed using virtual reality (VR) headsets and training videos for professionals.

Researchers at Peking University’s Institute for Artificial Intelligence (AI) and the State Key Laboratory of General AI recently introduced new models that could simplify the generation of realistic motions for human characters or avatars. The work is published on the arXiv preprint server.

Their proposed approach for the generation of human motions, outlined in a paper presented at CVPR 2025, relies on a data augmentation technique called MotionCutMix and a diffusion model called MotionReFit.

A combined team of metallurgists, materials scientists and engineers from the Chinese Academy of Sciences, Shandong University and the Georgia Institute of Technology has developed a way to make stainless steel more resistant to metal fatigue. In their study published in the journal Science, the group developed a new twisting technique that functions as an “anti-crash wall” in the steel, giving it much more strength and resistance to cyclic creep.

Metal can experience when bent many times, leading to breaking. When this occurs in critical applications, it can result in catastrophic accidents such as bridge failures. Because of that, scientists have for many years been working to reduce or prevent stress levels in metals. In this new effort, the researchers found a way to dramatically improve the strength of a type of stainless steel while also boosting its resistance to what is known as cycle creep, where fatigue occurs due to ratcheting, a form of repeated bending.

The new technique involved repeatedly twisting a sample of 304 austenitic stainless steel in a machine in certain ways. This led to spatially grading the cells that made up the metal, resulting in the build-up of what the team describes as a submicron-scale, three-dimensional, anti-crash wall. Under a microscope, the researchers found an ultra-fine, sub-10 nanometer, coherent lamellar structure that slowed dislocation by preventing stacking faults.