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Alzheimer’s disease (AD) is a debilitating neurodegenerative disorder associated with a progressive decline in memory and mental abilities, which can significantly hinder people’s ability to complete daily tasks. Past studies found that patients diagnosed with AD, as well as some other neurodegenerative disorders, exhibit an abnormal accumulation of tau protein in their neurons.

Tau protein is a microtubule-associated protein (MAP) known to stabilize the internal structure of neurons, binding to microtubules. These are microscopic tubular structures that support the transport of nutrients, proteins and other vital molecules within individual neurons or other cells.

Recent findings suggest that tau proteins interact with extracellular vesicles (EVs), small membrane-bound particles secreted by cells that carry molecules and deliver them to other cells. While the research hints at a connection between these vesicles and tau proteins in AD, the link between the two is not yet fully understood.

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Scientists know biological neurons are more complex than the artificial neurons employed in deep learning algorithms, but it’s an open question just how much more complex.

In a fascinating paper published recently in the journal Neuron, a team of researchers from the Hebrew University of Jerusalem tried to get us a little closer to an answer. While they expected the results would show biological neurons are more complex—they were surprised at just how much more complex they actually are.

In the study, the team found it took a five-to eight-layer neural network, or nearly 1,000 artificial neurons, to mimic the behavior of a single biological neuron from the brain’s cortex.

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Monitoring electrical potentials with high recording site density and micrometer spatial resolution in liquid is critical in biosensing. Organic electronic materials have driven remarkable advances in the field because of their unique material properties, yet limitations in spatial resolution and recording density remain. Here, we introduce organic electro-scattering antennas (OCEANs) for wireless, light-based probing of electrical signals with micrometer spatial resolution, potentially from thousands of sites. The technology relies on the unique dependence of poly(3,4-ethylenedioxythiophene):polystyrene sulfonate light scattering properties to its doping level. Electro-optic characteristics of individual antennas varying in diameters and operating voltages were systematically characterized in saline solution. Signal-to-noise ratios up to 48 were achieved in response to 100-mV stimuli, with 2.5-mV detection limits. OCEANs demonstrated millisecond time constants and exceptional long-term stability, enabling continuous recordings over 10 hours. By offering spatial resolution of 5 μm and a recording density of 4 × 106 cm−2, OCEANs unlock new readout capabilities, potentially accelerating fundamental and clinical research.

Sci. Adv. 10, eadr8380 (2024). DOI:10.1126/sciadv.adr8380

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Macquarie University researchers have demonstrated how ordinary supermarket grapes can enhance the performance of quantum sensors, potentially leading to more efficient quantum technologies.

The study, published in Physical Review Applied on 20 December 2024, shows that pairs of grapes can create strong localized magnetic field hotspots of microwaves which are used in quantum sensing applications—a finding that could help develop more compact and cost-effective quantum devices.

“While previous studies looked at the causing the plasma effect, we showed that grape pairs can also enhance magnetic fields, which are crucial for quantum sensing applications,” says lead author Ali Fawaz, a quantum physics Ph.D. candidate at Macquarie University.

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The Large Hadron Collider (LHC), the world’s largest and most powerful particle accelerator, is also the largest single machine operating in the world today that uses superconductivity. The proton beams inside the LHC are bent and focused around the accelerator ring using superconducting electromagnets. These electromagnets are built from coils, made of niobium–titanium (Nb–Ti) cables, that have to operate at a temperature colder than that of outer space in order to be superconducting. This allows the current to flow without any resistance or loss of energy. The High-Luminosity LHC (HL-LHC), an upgrade of the LHC, will for the first time feature innovative electrical transfer lines known as the “Superconducting Links”

Recently, CERN’s SM18 magnet test facility witnessed the successful integration of the first series of magnesium diboride superconducting cables into a novel, flexible cryostat. Together with high-temperature superconducting (HTS) magnesium diboride (MgB2) cables, they will form a unique superconducting transfer line to power the HL-LHC inner triplet magnets. The triplets are the focusing magnets that focus the beam, right before collisions, to a diameter as narrow as 5 micrometres.

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Bioconvergence — Bridging Science And Nature To Shape Tomorrow — Dr. Nina Siragusa Ph.D. — Merck KGaA, Darmstadt, Germany

#NinaSiragusa #MerckGroup #Darmstadt.

Dr. Nina Siragusa, Ph.D., MBA, is the Strategy, Business, and Data & Digital Lead within the global R&D organization of Merck Healthcare KGaA, Darmstadt, Germany. In this role, she leads strategic projects, manages business operations, and drives digital transformation.

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NASA’s Parker Solar Probe is set to achieve its most dangerous feat yet tomorrow, December 24, 2024. After a six-year journey of spiraling closer to the star at the heart of our solar system, the spacecraft is expected to come within 3.8 million miles of the Sun’s surface.

This tiny distance in cosmic terms lets scientists capture a new type of information, revealing secrets about solar winds, extreme heat, and magnetic fields.

Engineers have spent years carefully adjusting Parker’s flight path using multiple Venus gravity assists. These flybys reshape the spacecraft’s orbit and tighten its looping path around the Sun.

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Showing how far AI engineering has come, a new aerospike engine burning oxygen and kerosene capable of 1,100 lb (5,000 N) of thrust has successfully been hot-fired for 11 seconds. It was designed from front to back using an advanced Large Computational Engineering Model.

Designing and developing advanced aerospace engines is generally a complicated affair taking years of modeling, testing, revision, prototyping, rinsing and repeating. With their ability to discern patterns, carry out complex analysis, create virtual prototypes, and run models thousands of times, engineering AIs are altering the aerospace industry in some surprising ways – provided, of course, they are properly programmed and trained.

Otherwise, it’s garbage in, garbage out, which has been the Golden Rule of computers since they ran on radio valves and electromechanical relays.

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