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The new findings could help improve vaccine effectiveness in some immunocompromised patients. Researchers at the University of Colorado Anschutz Medical Campus have uncovered a critical, previously underappreciated role for B cells in vaccine protection. Best known for producing antibodies, B cells also guide other immune cells, specifically CD8 T cells, teaching them how to mount lasting defenses after vaccination.

The study was recently published in The Journal of Clinical Investigation.

“Think of CD8 T cells as rookie firefighters,” said lead author Jared Klarquist, PhD, assistant research professor of immunology and microbiology at the University of Colorado School of Medicine. “B cells teach the class on pacing. Without them, the rookies rush in, fight hard, and quit. They don’t save anything for the next fire.”

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In an experiment reminiscent of the Transformers movie franchise, engineers at Princeton University have created a type of material that can expand, assume new shapes, move and follow electromagnetic commands like a remotely controlled robot even though it lacks any motor or internal gears.

“You can transform between a material and a robot, and it is controllable with an external magnetic field,” said researcher Glaucio Paulino, the Margareta Engman Augustine Professor of Engineering at Princeton.

In an article published April 23 in the journal Nature, the researchers describe how they drew inspiration from the folding art of origami to create a structure that blurs the lines between robotics and materials. The invention is a metamaterial, which is a material engineered to feature new and unusual properties that depend on the material’s physical structure rather than its chemical composition. In this case, the researchers built their metamaterial using a combination of simple plastics and custom-made magnetic composites. Using a magnetic field, the researchers changed the metamaterial’s structure, causing it to expand, move and deform in different directions, all remotely without touching the metamaterial.

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Countries in the Global South risk being left out of the quantum revolution — along with its economic, technological and security benefits — due to growing export controls, siloed research initiatives and national security concerns, a new policy analysis argues.

In the first of a series of articles on quantum technologies published by the policy journal Just Securit y, researchers Michael Karanicolas, of Dalhousie University, and Alessia Zornetta, of UCLA Law, examine how the geopolitics of emerging quantum technologies are replicating long-standing patterns of technological exclusion. The authors argue that absent meaningful interventions, quantum could become another engine of global inequality, one that threatens to lock poorer nations out of the next era of technological and economic development.

The authors trace the roots of this divide to export control regimes that are quickly expanding in response to the strategic potential of quantum systems. Since 2020, governments in the U.S., EU and China have implemented targeted restrictions on quantum-enabling hardware, software, and communications systems.

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For years, quantum computing has been the tech world’s version of “almost there”. But now, engineers at MIT have pulled off something that might change the game. They’ve made a critical leap in quantum error correction, bringing us one step closer to reliable, real-world quantum computers.

In a traditional computer, everything runs on bits —zeroes and ones that flip on and off like tiny digital switches. Quantum computers, on the other hand, use qubits. These are bizarre little things that can be both 0 and 1 at the same time, thanks to a quantum property called superposition. They’re also capable of entanglement, meaning one qubit can instantly influence another, even at a distance.

All this weirdness gives quantum computers enormous potential power. They could solve problems in seconds that might take today’s fastest supercomputers years. Think of it like having thousands of parallel universes doing your math homework at once. But there’s a catch.

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RIKEN chemists have hit upon a fast and easy way to combine so-called nanobelts of carbon with sulfur-containing functional groups. The work is published in the journal Nature Communications.

This new material has intriguing properties that make it promising for use in novel optoelectronic devices.

Ever since their discovery in 1991, carbon nanotubes—tiny hollow cylinders made entirely from carbon atoms—have been attracting a lot of interest, being used in applications ranging from electronics to medicine.

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Introduction One thing newcomers to machine learning (ML) and many experienced practitioners often don’t realize is that ML doesn’t extrapolate. After training an ML model on compounds with µM potency, people frequently ask why none of the molecules they designed were predicted to have nM potency. If you’re new to drug discovery, 1nM = 0.001µM. A lower potency value is usually better. It’s important to remember that a model can only predict values within the range of the training set. If we’ve trained a model on compounds with IC50s between 5 and 100 µM, the model won’t be able to predict an IC50 of 0.1 µM. I’d like to illustrate this with a simple example. As always, all the code that accompanies this post is available on GitHub.

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Digger wasps make a short burrow for each egg, stocking it with food and returning a few days later to provide more. A new study reveals that mother wasps can remember the locations of up to nine separate nests at once, rarely making mistakes, despite the fact nests are dug in bare sand containing hundreds belonging to other females.

The paper is published in the journal Current Biology and is titled “Memory and the scheduling of parental care in an in the wild.”

Mothers feed their young in age order, adjusting the order if one dies, and they can even delay feeding offspring that had more food at the first visit. Their intricate scheduling reduces the chance that offspring starve.

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