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V-STARS pioneers neuroscience at ESA’s Orbital Robotics Lab

As part of the ESA Academy Experiments Programme, Team V-STARS carried out the first experiment with human participants in the Orbital Robotics Lab, investigating how microgravity affects the perception of verticality.

The V-STARS team, a collaboration between Birkbeck, University of London, and the University of Kent (UK), was selected to join the ESA Academy Experiments Programme in February 2025. After obtaining ethical approval from the United Kingdom and authorisation from the ESA Medical Board, the team was permitted to carry out their experiment in the Orbital Robotics Lab (ORL), located at ESTEC, the ESA site in the Netherlands.

The campaign involved test subjects seated on the ORL’s floating platform, wearing VR headsets while performing gravity-related perceptual tasks. The project investigates the use of Vestibular Stochastic Resonance — a phenomenon in which controlled noise enhances the sensitivity of a sensory system — to improve perception and potentially accelerate adaptation to microgravity. Over two weeks, the team tested more than 20 participants and has now returned to their universities to analyse the results.

A new medium for canine stem cells that doesn’t contain any human components

Canine induced pluripotent stem (iPS) cells possess the ability to differentiate into any type of cell, making them a useful tool for investigating common canine diseases and disease states, including those of humans.

When culturing iPS cells, a culture substrate is required to serve as a scaffold for the cells, which adhere to it and proliferate. Without the scaffold, the cells die or fail to differentiate.

Currently, recombinant proteins derived primarily from humans are used as culture substrates for canine iPS cells. However, these human-derived elements are an alien substance for dog cells, leading to immune rejection and making clinical use difficult.

New High-Resolution Imaging Reveals How the Flu Virus Invades Cells

Scientists have captured an unprecedented, real-time view of influenza viruses as they move across and slip inside human cells. The footage reveals that cells are far from passive targets and instead push and pull against the virus in a surprisingly active struggle. Viewing Influenza Infection W.

Winter virus season so far is not too bad, but doctors worry about suffering to come

It may feel like you are surrounded by sniffles and coughs, but flu season activity is still low in many parts of the U.S.

New government data posted Friday shows that as of last week, flu activity was high in four states—Colorado, Louisiana, New Jersey and New York—and minimal or low in most others. Severity indicators are increasing but are still within the boundaries of a “mild” season, said officials at the U.S. Centers for Disease Control and Prevention.

A number of diseases tend to peak in the winter, thanks to indoor gatherings that help germs spread. The list includes not only colds and flu but also norovirus—a highly infectious cause of vomiting and diarrhea. Norovirus cases have generally been trending up in the last month.

Video NeuroImage: Stereotypic Motor Behaviors in a Patient With Pantothenate Kinase–Associated Neurodegeneration

A 24-year-old woman with pantothenate kinase–associated neurodegeneration (PKAN) presented with a 5-year history of psychiatric symptoms followed by prominent stereotypic motor behaviors, including repetitive touching of her mouth and leg, object manipulation, and tip-toe walking (Video 1). Examination revealed severe depression and anxiety, mild speech dysfluency, and the stereotypic movements. Previous symptomatic treatments provided limited benefit. Brain magnetic resonance imaging demonstrated the pathognomonic “eye-of-the-tiger” sign, indicative of iron deposition in the bilateral globus pallidus (Figure). Genetic testing identified compound heterozygous variants in the PANK2 gene: a known pathogenic variant (c.401AG) and a novel likely pathogenic variant (c.1465CG).

This Photonic AI Chip is the FUTURE of Computer Vision

This AI chip doesn’t use electricity to compute — it uses light.

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Engineers at the University of Pennsylvania have built a photonic neural network capable of classifying nearly 2 billion images per second, operating at speeds millions of times faster than today’s electronic computer vision systems.

In this video, we explore how photonic neural networks work, why traditional image recognition is so computationally expensive, and how light-based hardware could overcome fundamental limits of GPUs and silicon. We go over how convolution layers, weighted sums, and activation functions are implemented directly on a photonic chip — without memory, clock cycles, or digital logic.

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