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First 3D views of human cone opsins reveal how daylight vision reacts so fast

The retina of the human eye contains 6–7 million cone cells. These cells contain light-sensitive proteins known as cone opsins. They enable us to perceive our surroundings in detail in daylight. They allow us to see the world in thousands of colors: red strawberries, green leaves, the blue sky. They also enable us to see all the objects around us clearly. And they allow us to perceive fast movements, such as the rush of a train or the flight of a dragonfly.

Often, however, these all-rounders of daylight vision are also involved in retinal diseases. Impairment of cone receptor function, caused by genetic mutations or other degenerative processes, can lead to disorders such as color blindness and age-related macular degeneration (AMD), a disease affecting the central retina and causing progressive vision loss.

In a new study, Polina Isaikina and Sarah L. Schmidt, two researchers from the Center for Life Sciences at PSI, have succeeded for the first time in determining the three-dimensional structure of human cone opsins in their dark state and showing how their molecular architecture enables their rapid activation by light.

Proteomic analysis of dental enamel from 20 Homo naledi individuals shows no male markers

The morphological homogeneity of the middle Pleistocene hominin Homo naledi is reflected in its dental proteome, with no evidence supporting confident identification of male individuals, and the detection of both derived and ancestral amino acid substitutions in Homo naledi.

Preventing the next pandemic using AI-designed vaccines

For most of human history, infectious diseases were the main causes of morbidity and mortality. Advances in sanitation, antibiotics, vaccines, and public health dramatically shifted that balance, particularly in high-income countries, where life expectancy has increased by nearly 40 years over the past century. Yet the COVID-19 pandemic provided a stark reminder that infectious threats can still reshape societies almost overnight. Between 2019 and 2021 alone, life expectancy in the US fell by more than two years, and recent modelling suggests there is roughly a 50 percent chance of another COVID-scale pandemic occurring within the next 25 years.

Historically, the vaccine development model has been largely reactive and variant-driven, but the industry is now actively shifting toward proactive and universal vaccinology to get ahead of evolving pathogens. Recent results from a first-in-human clinical trial led by the University of Cambridge and its spin-out DIOSynVax, published in the Journal of Infection, provide early clinical evidence of this shift, demonstrating the safety of an AI-designed “super-antigen” intended to provide broad viral coverage.

Teaching AI to Invent Enzymes Nature Never Imagined

Evolution is an extraordinary engine for enzymatic diversity, yet the chemistry it has explored remains a narrow slice of what DNA can encode. Deep generative models can design new proteins that bind ligands, but none have created enzymes without pre-specifying catalytic residues.

In this webinar, Chenghao Liu and Jarrid Brooks from the Arnold Lab at Caltech will introduce DISCO (DIffusion for Sequence-structure CO-design). This multimodal model co-designs protein sequence and 3D structure around arbitrary biomolecules, as well as inference-time scaling methods that optimize objectives across both modalities. Conditioned solely on reactive intermediates, DISCO designs diverse heme enzymes with novel active-site geometries. These enzymes catalyze new-to-nature carbene-transfer reactions, including alkene cyclopropanation, spirocyclopropanation, B-H, and C(sp^3)-H insertions, with high activities exceeding those of engineered enzymes. Random mutagenesis of a selected design further confirmed that enzyme activity can be improved through directed evolution. By providing a scalable route to evolvable enzymes, DISCO broadens the potential scope of genetically encodable transformations.

Matlab-deep-learning/pose-estimation-3D-with-stereo-camera: This demo uses a deep neural network and two generic cameras to perform 3D pose estimation

This demo uses a deep neural network and two generic cameras to perform 3D pose estimation. — matlab-deep-learning/pose-estimation-3D-with-stereo-camera

Laser pulses capture unexplored polaronic states

In an international experiment, researchers observed Jahn–Teller polarons—quasiparticles that could play an important role in future ultrafast spintronic devices. These polarons emerged within the crystal lattice of cobalt oxide that had been activated by carefully tailored laser pulses.

When a cobalt oxide crystal is exposed to carefully tailored laser pulses, they induce specific local distortions of the crystal lattice that strongly affect the material’s structural, electrical and magnetic properties. The correlative experimental approaches that revealed these unexpected properties of cobalt oxide were carried out by a large international team of scientists from the University of Pavia (Italy), the Swiss Federal Institute of Technology Lausanne, the Paul Scherrer Institute (Switzerland), the University of Texas at Austin, the Massachusetts Institute of Technology and Northeastern University (U.S.). The theoretical description of the phenomenon, which made it possible to uncover the nature of the observed oscillations, was developed by physicists from the Institute of Nuclear Physics of the Polish Academy of Sciences (IFJ PAN) in Cracow.

Chemical catalysts, battery electrodes, photovoltaic cells and semiconductor gas sensors—these are just some of the modern applications of cobalt oxide (Co₃O₄). Despite its simple chemical formula, the unit cell of its crystal lattice consists of 56 atoms: 24 cobalt and 32 oxygen. Depending on their position within the unit cell, the cobalt atoms exist here in two oxidation states.

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