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Category: computing – Page 6

Frontiers: Information storage and transfer in the brain require a high computational power

Neuronal network display various local or global mechanisms to allow information storage and transfer in the brain. From synaptic to intrinsic plasticity, the rules of input–output function modulation have been well characterized in neurons. In the past years, astrocytes have been suggested to increase the computational power of the brain and we are only just starting to uncover their role in information processing. Astrocytes maintain a close bidirectional communication with neurons to modify neuronal network excitability, transmission, axonal conduction, and plasticity through various mechanisms including the release of gliotransmitters or local ion homeostasis. Astrocytes have been significantly studied in the context of long-term or short-term synaptic plasticity, but this is not the only mechanism involved in memory formation. Plasticity of intrinsic neuronal excitability also participates in memory storage through regulation of voltage-gated ion channels or axonal morphological changes. Yet, the contribution of astrocytes to these other forms of non-synaptic plasticity remains to be investigated. In this review, we summarized the recent advances on the role of astrocytes in different forms of plasticity and discuss new directions and ideas to be explored regarding astrocytes-neuronal communication and regulation of plasticity.

The rules governing changes in synaptic and intrinsic plasticity are diverse and complex, sometimes synergistic and sometimes not (Debanne et al., 2019). Most studies have been neuro-centric, despite growing evidence that astrocytes can intervene or interact to modify or modulate synaptic transmission (Araque et al., 1998; Jourdain et al., 2007; Bonansco et al., 2011), input integration, neuronal excitability (Tan et al., 2017), spike waveform or axonal conductivity (Sasaki et al., 2011; Lezmy et al., 2021). Astrocytes can detect neuronal activity, and depending on the firing rate of action potentials (APs), they can not only release gliotransmitters such as adenosine or glutamate (Hamilton et al., 2008; Lezmy et al., 2021), but also trigger intracellular calcium ([Ca2+]i) oscillations at different frequencies (Pasti et al., 1997).

No exotic physics needed: A new formation mechanism of skyrmions inside magnets

Skyrmions, in which electron spins inside a magnet are arranged like vortices, are a key structure in next-generation spintronics technology. KAIST researchers have shown that skyrmions can form using only the fundamental physical interactions within magnets, without requiring special physical conditions.

This finding, published in the journal Physical Review Letters, expands the possibility of realizing skyrmions in a wide range of magnetic materials and suggests new potential for developing next-generation ultra-low-power information devices with data storage densities tens to hundreds of times higher than current technologies.

A research team led by Professor Se Kwon Kim from the Department of Physics has proposed a new theoretical framework showing that vortex-like magnetic structures can naturally emerge solely through magnetoelastic coupling —the interaction between magnetism and lattice structure.

‘Mini earthquakes’ turn tiny chips into radio signal powerhouses

From GPS satellites to mobile networks, modern technology relies on ultra-precise radio signals. Engineers have long tried to generate them on chips using interactions between light and sound, but the effect was too weak. University of Twente researchers now show in a paper published in Nature Photonics that a thin glass layer creates “mini-earthquake” surface acoustic waves, which make the effect more than 200 times stronger. This enables ultra-pure signals and record-sharp filters on a device thousands of times smaller.

Every time you make a phone call, your signal is filtered out of a crowded radio spectrum using radio frequency filters. These components let through only the frequencies you want and block everything else. The sharper the filter, the cleaner the call. The same principle applies in radar, satellite navigation and future wireless networks like 6G.

Topology helps build more robust photonic networks

Penn-led researchers have shown for the first time that multiple, information-carrying light signals can be safely guided through chip-based, reconfigurable networks using topology, the esoteric branch of mathematics that says donuts and mugs are identical. Because topological properties remain stable even when objects are deformed—hence the field equating mugs and donuts, since both have one opening—the advance could help make light-based technologies for computing and communications more powerful and reliable.

“We already knew how to guide light using topology,” says Liang Feng, Professor in Materials Science and Engineering (MSE) with a secondary appointment in Electrical and Systems Engineering (ESE) within Penn Engineering and senior author of a study in Nature Physics describing the result. “But we had never been able to guide multiple, concurrent signals before.”

That opens the door to building networks of chips that communicate using light while taking advantage of the robustness topology provides. “Signals guided by these principles can be extremely reliable,” says Feng. “It’s like building a highway for light where even large potholes have no effect on traffic—it’s as if the defects simply aren’t there.”

Superconductor advancement could unlock ultra-energy-efficient electronics

Superconducting materials could play a crucial role in the energy-efficient applications of the future. However, several technical challenges still stand in the way of their practical use. Now, researchers at Chalmers University of Technology in Sweden have developed a new material design that addresses a major obstacle in the field: enabling superconductivity to operate at higher temperatures while also withstanding strong magnetic fields. This breakthrough could pave the way for far more energy-efficient electronics and quantum technologies.

Digital devices, data centers and information and communications technology (ICT) networks currently account for approximately 6% to 12% of global electricity consumption. There is a substantial and growing need for more energy-efficient electronics and this is where superconducting materials have emerged as a promising solution. Unlike conventional electronics, which lose energy as heat, superconductors can conduct electricity with zero energy loss. Thus, superconductors have the potential to make power grids, electronics and quantum technologies hundreds of times more energy efficient.

However, the path to real-world applications is still blocked by several key challenges. One major obstacle is that superconducting states often require extremely low temperatures—down to around −200°C. Cooling to such temperatures is complex and energy-intensive. Another major challenge is that superconductivity can be weakened or destroyed by strong magnetic fields. This is a critical limitation, as magnetic fields are often present in advanced electronic devices and are essential to many quantum technologies.

Terahertz spin waves can be converted into computer signals, study shows

What will the computers of tomorrow look like? Chances are good that spintronics will play a decisive role in the next generation of computers. In spintronics, the intrinsic angular momentum of an electron (the spin) is used to store, process and transmit data. This technology is already in use today, for example in hard drives. However, the scope of what is possible extends much further: More recent approaches aim at using not just individual spins, but entire spin waves made up of partly hundreds of trillions of spins. Such collective spin excitations are known as magnons. They could enable extremely energy-efficient data transmission—even in the terahertz range.

So far, so good. But how can these spin waves be coupled to today’s technology? “If we develop a concept to perform computer calculations with magnons, it must be compatible with the technology we currently use,” says physicist Davide Bossini from the University of Konstanz. “To reach this goal, you have to convert the spin wave into an electrical charge signal.” This spin-to-charge conversion is one of the major challenges of spintronics.

Most mass spectrometers can process just a few molecules at once: Reengineered prototype does a billion simultaneously

Mass spectrometry is already a powerful tool for determining what kind and how many molecules are present in a given sample. But most instruments still analyze their molecules one or just a few at a time, an approach that is inefficient and costly, and in which rare, but significant molecules can easily fall between the cracks.

A more powerful version of the technology could one day allow scientists to read the full molecular contents of a single cell, track thousands of chemical reactions at once, and ultimately accelerate efforts like drug development.

Now, a new study describes the first big step in that direction by producing a prototype, dubbed MultiQ-IT, that’s capable of handling vast numbers of molecules at once. The findings, published in the journal Science Advances, offer a blueprint for faster, more sensitive instruments that could position mass spectrometry for the kind of transformation that reshaped genomics and computing.

New “Giant Superatoms” Could Solve Quantum Computing’s Biggest Problem

A new quantum system called giant superatoms could protect quantum information and enable entanglement between multiple qubits. The concept merges giant atoms and superatoms to improve stability and scalability for future quantum technologies. Scientists at Chalmers University of Technology in Sw

Abstract: Decoding neurodegeneration one cell at a time

https://doi.org/10.1172/JCI199841 As part of the JCI’s Review Series on Neurodegeneration, Olivia Gautier, Thao P. Nguyen & Aaron D. Gitler explore the molecular basis for selective neuronal vulnerability and degeneration and summarize recent advances and applications of single-cell genomic approaches.

How do we decide whether we should choose single-cell or single-nucleus sequencing? This depends on sample types and biological applications. Single-cell sequencing is typically applied to fresh, readily dissociable tissues or cultured cells to study intact cell populations. Because it captures both cytoplasmic and nuclear transcripts, scRNA-seq provides a comprehensive view of cellular gene expression. However, tissue dissociation can induce stress-related transcriptional artifacts and introduce substantial cell-type bias. Large or fragile neurons are often lost during dissociation, whereas smaller cell types, such as astrocytes and oligodendrocytes, tend to be overrepresented. In contrast, single-nucleus sequencing is commonly used for frozen samples or for tissues that are difficult to dissociate, including the brain and spinal cord. Although fresh or fresh-frozen samples are typically used, snRNA-seq is compatible with formalin-fixed, paraffin-embedded (FFPE) samples, enabling the analysis of archived human specimens. A key limitation is that snRNA-seq does not capture cytoplasmic transcripts and is therefore biased toward nuclear, often premature, mRNA species.

Spatial transcriptomics does not require tissue dissociation and enables examination of cellular transcriptomes within their native tissue niches. Some spatial transcriptomic technologies are now compatible with FFPE samples, allowing analyses of preserved clinical specimens along with fixed-frozen and fresh-frozen samples. These technologies can be broadly classified into two main categories: imaging-based and sequencing-based (Figure 2B). Imaging-based approaches, like multiplexed error-robust fluorescence in situ hybridization (MERFISH), spatially resolved transcript amplicon readout mapping (STARmap), and 10x Genomics Xenium, rely on probe hybridization and multiplexed imaging to detect and visualize transcripts at high spatial resolution, often achieving single-cell or even subcellular resolution (17, 18). Although whole-transcriptome measurements are possible, MERFISH typically targets predefined gene panels due to the constraints of iterative hybridization and imaging. In contrast, sequencing-based approaches, including NanoString GeoMx and 10x Genomics Visium, capture RNA on spatially barcoded tissue slides or nanobeads followed by next-generation sequencing. These methods generally recover a broader range of transcripts than imaging-based approaches but, in most cases, do not yet achieve true single-cell resolution. Instead, they measure gene expression within spatial “spots” that encompass multiple cells and therefore rely on computational deconvolution to infer cell-type composition. Newer spatial transcriptomic methods, like spatial enhanced resolution omics sequencing (Stereo-seq) and reverse-padlock amplicon-encoding fluorescence in situ hybridization (RAEFISH), are approaching single-cell and single-molecule resolution (19 – 21).

In this Review, we summarize recent advances and applications of single-cell genomics approaches to study neurodegenerative disorders, including Alzheimer disease (AD), Parkinson disease (PD), amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), and Huntington disease (HD). We focus on how these approaches provide insight into the unique vulnerabilities of specific neuronal populations, define novel disease-associated cellular states, and reveal contributions of non-neuronal cells to disease pathogenesis. We then look to the future, envisioning how these technologies will empower genetic screens to uncover modifiers of neurodegeneration and new therapeutic targets.

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