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However, this picture, which depicts the evolution of man, may actually pose a danger to our general understanding of how evolution plays out on the planet. One might interpret the picture as: Evolution is a unidirectional, progressive process for the betterment of species. This, in fact could not be farther from the truth.

So, what is evolution exactly?

Compared to those of us who live at sea level, the 2 million people worldwide who live above 4,500 meters (or 14,764 feet) of elevation—about the height of Mount Rainier, Mount Whitney, and many Colorado and Alaska peaks—have lower rates of metabolic diseases such as diabetes, coronary artery disease, hypercholesterolemia, and obesity.

Now, researchers at Gladstone Institutes have shed light on this phenomenon. They showed how chronically , such as those experienced at , rewire how mice burn sugars and fats. The work, published in the journal Cell Metabolism, not only helps explain the metabolic differences of people who live at high altitude, but could also lead to new treatments for metabolic disease.

“When an organism is exposed to chronically low levels of , we found that different organs reshuffle their fuel sources and their energy-producing pathways in various ways,” says Gladstone Assistant Investigator Isha Jain, Ph.D., senior author of the new study. “We hope these findings will help us identify metabolic switches that might be beneficial for metabolism even outside of low-oxygen environments.”

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As part of a one of a kind project, the first flying taxis will be utilized during the 2024 Olympic Games in France and will be used to drive passengers around. This project is supervised by the Paris Transportation Network and the general manager of France for Commercial Air.

Few months prior to the Paris 2024 Olympic Games, a series of test will commence and will examine the service. If the tests prove successful, this will allow airlines to develop a similar service during 2028–2030, according to a report by Maariv news.

A one-year, placebo-controlled trial of oral nicotinamide (vitamin B3) therapy by the University of Sydney did not lead to lower rates of skin cancer in organ transplant recipients. The result is in striking contrast to a previous trial in which oral nicotinamide was concluded to be effective in reducing the rates of new nonmelanoma skin cancers and actinic keratoses in high-risk patients.

In the previous trial, “A Phase 3 Randomized Trial of Nicotinamide for Skin-Cancer Chemoprevention,” participants were ineligible if they were immunosuppressed. Results showed an estimated 23% lower overall rate of new nonmelanoma skin cancers, with similar reductions of both new basal-cell and squamous-cell carcinomas. Interestingly, the previous trial found five rare, more aggressive carcinomas (two morphoeic, three poorly differentiated) in the nicotinamide group, while the placebo control had zero.

Transplant recipients are commonly given immunosuppressant drugs to prevent the body’s immune system from attacking the new organ tissues. These patients are approximately 100 times more likely than the to develop , according to a Swedish study. A higher risk of developing combined with lower survival rates means transplant patients urgently need a safe and effective way to lessen the risk.

Summary: Utilizing a classic neural network, researchers have created a new artificial intelligence model based on recent biological findings that shows improved memory performance.

Source: OIST

Computer models are an important tool for studying how the brain makes and stores memories and other types of complex information. But creating such models is a tricky business. Somehow, a symphony of signals – both biochemical and electrical – and a tangle of connections between neurons and other cell types creates the hardware for memories to take hold. Yet because neuroscientists don’t fully understand the underlying biology of the brain, encoding the process into a computer model in order to study it further has been a challenge.

New technologies can greatly advance research in various fields, including medicine and neuroscience. In recent years, for instance, engineers have created increasingly sophisticated devices to record brain activity and other biological signals with high precision.

A multi-disciplinary research team at University of California, Los Angeles (UCLA) and other institutes in the U.S. have recently developed the Neuro-stack, a new wearable technology that can record the activity of single neurons in the as a human being is walking or moving. This device, presented in a paper published in Nature Neuroscience, could help to gather valuable insight about neuronal activity during walking, while also potentially improving treatments for brain disorders.

“Our study was motivated by the need for smaller size and more for clinical neuroscience,” Dejan Markovic, one of the researchers who carried out the study, told Medical Xpress. “Our primary objectives were to make a device that is small enough to be wearable, for mobile experiments, and to provide broadband recordings including local field potentials and single units.”

As the use of machine learning (ML) algorithms continues to grow, computer scientists worldwide are constantly trying to identify and address ways in which these algorithms could be used maliciously or inappropriately. Due to their advanced data analysis capabilities, in fact, ML approaches have the potential to enable third parties to access private data or carry out cyberattacks quickly and effectively.

Morteza Varasteh, a researcher at the University of Essex in the U.K., has recently identified new type of inference attack that could potentially compromise confidential user data and share it with other parties. This attack, which is detailed in a paper pre-published on arXiv, exploits vertical federated learning (VFL), a distributed ML scenario in which two different parties possess different information about the same individuals (clients).

“This work is based on my previous collaboration with a colleague at Nokia Bell Labs, where we introduced an approach for extracting private user information in a data center, referred to as the passive party (e.g., an ),” Varasteh told Tech Xplore. “The passive party collaborates with another , referred to as the active party (e.g., a bank), to build an ML algorithm (e.g., a credit approval algorithm for the bank).”

Researchers are coming to understand that the best performing materials in sustainable energy applications, such as converting sunlight or waste heat to electricity, often use collective fluctuations of clusters of atoms within a much larger structure. This process is often referred to as “dynamic disorder.”

Understanding dynamic disorder in materials could lead to more energy-efficient thermoelectric devices, such as solid-state refrigerators and , and also to better recovery of useful energy from , such as car exhausts and power station exhausts, by converting it directly to electricity. A was able to take heat from radioactive plutonium and convert it to electricity to power the Mars Rover when there was not enough sunlight.

When materials function inside an operating device, they can behave as if they are alive and dancing—parts of the material respond and change in amazing and unexpected ways. This dynamic disorder is difficult to study because the clusters are not only so small and disordered, but they also fluctuate in time. In addition, there is “boring” non-fluctuating disorder in materials that researchers aren’t interested in because the disorder doesn’t improve properties. Until now, it has been impossible to see the relevant dynamic disorder from the background of less relevant static disorder.