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Summary: New research has revealed the diverse assembly and regulation of Type-A GABA receptors (GABAARs), which are crucial for balancing brain activity. Using cryogenic electron microscopy, researchers identified over 324,000 potential receptor structures, shaped by subunit combinations and their relative arrangement.

These variations influence receptor function, drug binding, and the brain’s response to stressors like pregnancy or chronic drug use. The findings pave the way for targeted therapies that enhance receptor-specific functions without inducing tolerance or dependence.

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Scientists discovered a way to encode more data into light by creating light vortices with quasicrystals. This method could potentially increase data transmission rates through optic fibers by up to 16 times, marking a significant advancement in telecommunications technology.

Modern life relies heavily on efficiently encoding information for transmission. A common method involves encoding data in laser light and sending it through fiber optic cables. As demand for data capacity grows, finding more advanced encoding methods is essential.

Breakthrough in Light Vortex Creation.

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The parallels between human memory and vector databases go deeper than simple retrieval. Both excel at compression, reducing complex information into manageable patterns. Both organize information hierarchically, from specific instances to general concepts. And both excel at finding similarities and patterns that might not be obvious at first glance.

This isn’t just about professional efficiency — it’s about preparing for a fundamental shift in how we interact with information and technology. Just as literacy transformed human society, these evolved communication skills will be essential for full participation in the AI-augmented economy. But unlike previous technological revolutions that sometimes replaced human capabilities, this one is about enhancement. Vector databases and AI systems, no matter how advanced, lack the uniquely human qualities of creativity, intuition, and emotional intelligence.

The future belongs to those who understand how to think and communicate in vectors — not to replace human thinking, but to enhance it. Just as vector databases combine precise mathematical representation with intuitive pattern matching, successful professionals will blend human creativity with AI’s analytical power. This isn’t about competing with AI or simply learning new tools — it’s about evolving our fundamental communication skills to work in harmony with these new cognitive technologies.

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Alzheimer’s disease is marked by the gradual degeneration of nerve cells, resulting in memory and cognitive decline. A research team at KU Leuven and VIB investigated the molecular sequence driving this cellular breakdown, discovering specific inhibitors that can prevent nerve cell loss in various mouse models of the disease.

The findings open up new research avenues in the search for therapies that could halt or prevent the accumulation of brain damage occurring in Alzheimer’s.

Alzheimer’s disease, the leading cause of dementia, affects over 55 million people worldwide. The disease is characterized by the buildup of amyloid-beta plaques and tau protein tangles in the brain, which disrupt cell communication and lead to the widespread death of nerve cells. The consequences of this massive cell loss are the heartbreaking cognitive decline and memory loss for which the condition is well known.

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Research by scientists at the University of Sydney has identified a constituent in the cannabis plant that improves sleep. Their report is the first to use objective measures to show the component, known as cannabinol (CBN), increases sleep in rats.

The study has been published in Neuropsychopharmacology.

“For decades, cannabis folklore has suggested that aged cannabis makes consumers sleepy via the build-up of CBN, however there was no convincing evidence for this,” said lead author on the study Professor Jonathon Arnold, Director of Preclinical Research, at the Lambert Initiative for Cannabinoid Therapeutics and the Sydney Pharmacy School.

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Researchers from the University of Bonn have trained an AI process to predict potential active ingredients with special properties. Therefore, they derived a chemical language model — a kind of ChatGPT for molecules. Following a training phase, the AI was able to exactly reproduce the chemical structures of compounds with known dual-target activity that may be particularly effective medications. The study has now been published in Cell Reports Physical Science.

Anyone who wants to delight their granny with a poem on her 90th birthday doesn’t need to be a poet nowadays: A short prompt in ChatGPT is all it takes, and within a few seconds the AI spits out a long list of words that rhyme with the birthday girl’s name. It can even produce a sonnet to go with it if you like.

Researchers at the University of Bonn have implemented a similar model in their study — known as a chemical language model. This does not, however, produce rhymes. Instead, the AI displays the structural formulas of chemical compounds that may have a particularly desirable property: They are able to bind to two different target proteins. In the organism, this means, for example, they can inhibit two enzymes at once.

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Our brains—and specifically, our brain cells—are commonly known to store memories. However, a team of scientists has discovered that cells from other parts of the body also play a role in memory, opening new pathways for understanding how memory functions and creating potential for enhancing learning and treating memory-related conditions.

“Learning and memory are generally associated with brains and brain cells alone, but our study shows that other cells in the body can learn and form memories, too,” explains New York University ’s Nikolay V. Kukushkin, the lead author of the study, which appears in the journal Nature Communications.

The research sought to better understand if non-brain cells help with memory by borrowing from a long-established neurological property—the massed-spaced effect—which shows that we tend to retain information better when studied in spaced intervals rather than in a single, intensive session—better known as cramming for a test.

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VMware has announced that its VMware Fusion and VMware Workstation desktop hypervisors are now free to everyone for commercial, educational, and personal use.

In May, the company also made VMware Workstation Pro and Fusion Pro free for personal use, allowing students and home users to set up virtualized test labs and experiment with other OSs by running virtual machines and Kubernetes clusters on Windows, Linux, and macOS devices.

Starting this week, the Pro versions and the two products will no longer be available under a paid subscription model.

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