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Though Elon Musk’s Neuralink put wireless brain implants in the spotlight — in early 2024, Musk announced his company’s first implant was successful — the research and development of these devices has spanned decades. The BrainGate clinical trials have been underway for 20 years, and the consortium’s wireless implant marks the first time a person has used an implant with high bandwidth capabilities.

Wireless technologies are opening doors in neuroscience, enabling new capabilities in communication, treatment, and research. Because wireless implants can monitor the brain for long periods of time, they offer a unique opportunity to examine neural dynamics, increasing our understanding of the human mind. Their cord-free design also benefits people hoping to use these devices outside a research setting and improve their quality of life.

The first brain implant is credited to neurologist Phil Kennedy, who had the device surgically affixed to his brain. Today, wired implants are less invasive and widely used. They can help prevent seizures, manage OCD symptoms, and treat movement disorders.

When you stare for long enough into the heart of a galaxy to try to catch a glimpse of the black hole that lurks therein, that may not be all you catch.

When a huge collaboration directed telescopes around the world to the heart of galaxy M87 in 2018 in an ultimately successful effort to capture detail of its supermassive black hole, they also managed to observe some of the wild shenanigans such a black hole engages in.

Now, astronomers discovered that one of those shenanigans was a colossal belch – a gamma-ray eruption from one of the powerful jets of plasma launched from the black hole’s poles as it feeds.

Quantum calculations of molecular systems often require extraordinary amounts of computing power; these calculations are typically performed on the world’s largest supercomputers to better understand real-world products such as batteries and semiconductors.

Now, UC Berkeley and Lawrence Berkeley National Laboratory (Berkeley Lab) researchers have developed a new machine learning method that significantly speeds up by improving model scalability. This approach reduces the computing memory required for simulations by more than fivefold compared to existing models and delivers results over ten times faster.

Their research has been accepted at Neural Information Processing Systems (NeurIPS) 2024, a conference and publication venue in artificial intelligence and machine learning. They will present their work at the conference on December 13, and a version of their paper is available on the arXiv preprint server.

The study offers new genetic insights into dietary preferences and suggests the potential to target SI as a means to selectively decrease sucrose consumption on a population scale.

The study was led by Dr. Peter Aldiss, now a group leader in the School of Medicine at the University of Nottingham, alongside Assistant Professor Mette K Andersen, at the Novo Nordisk Foundation Centre for Basic Metabolic Research in Copenhagen and Professor Mauro D’Amato at CIC bioGUNE in Spain and LUM University in Italy. It also involves scientists internationally from Copenhagen, Greenland, Italy, and Spain as part of the ‘Sucrase-isomaltase working group’

“Our data support early resistance rehabilitation as a promising treatment to increase bone formation, bone healing strength, and promote full restoration of mechanical properties to pre-injury levels,” said Dr. Bob Guldberg.


How can implantable sensors help patients during their recovery? This is what a recent study published in npj Regenerative Medicine hopes to address as a team of researchers led by the University of Oregon investigated the use of implantable strain sensors to aid bone healing during rehabilitation from bone defect injuries. This study holds the potential to help provide patients with improved options regarding bone defect injuries while significantly reducing their rehabilitation time.

When it comes to rehabilitation, patients and doctors have always tried to find a middle-ground regarding the amount of strain needed to achieve the most desired outcomes, commonly called the “Goldilocks” principle. Therefore, this new study developed implantable sensors designed to monitor bone healing and determine if resistance training is a sufficient rehabilitation tool for patients. The researchers conducted an 8-week trial with laboratory rats split into three groups: resistance-trained, sedentary (inactive), and non-resistance.

In the end, the researchers found that while all three groups exhibited bone healing after the trial, the resistance-trained rats not only exhibited early signs of bone healing, but also exhibited increased tissue density, as well.

Dr. Marta di Forti: “Our study indicates that daily users of high potency cannabis are at increased risk of developing psychosis independently from their polygenic risk score for schizophrenia.”


Is there a connection between cannabis use and developing psychosis? This is what a recent study published in Psychological Medicine hopes to address as an international team of researchers investigated how frequent cannabis use combined with a genetic predisposition for schizophrenia could lead to developing psychosis later in life. This study holds the potential to help researchers, medical professionals, and the public better understand how to identify the signs of psychosis in cannabis users and take necessary steps to address them as soon as possible.

For the study, the researchers conducted an observational study by obtaining data records of almost 150,000 individuals registered in United Kingdom and European Union medical databanks, one of which was the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI), to examine records regarding patients who self-reported use and psychosis diagnoses. In the end, the researchers discovered a connection between individuals who self-reported lifetime frequent cannabis use and psychosis diagnoses, specifically regarding high potency cannabis which contains 10 percent or greater Delta-9 tetrahydrocannabinol (THC).

“These are important findings at a time of increasing use and potency of cannabis worldwide,” said Dr. Marta di Forti, who is a Professor of Drug use, Genetics, and Psychosis at King’s College London and a co-author on the study. “Our study indicates that daily users of high potency cannabis are at increased risk of developing psychosis independently from their polygenic risk score for schizophrenia. Nevertheless, the polygenic risk score for schizophrenia might, in the near future, become useful to identify those at risk for psychosis among less frequent users to enable early preventative measures to be put in place.”

In the world of science, even a small twist may carry immense implications for materials. Researchers at City University of Hong Kong have uncovered how a subtle rotation in 2D layers can give rise to a vortex electric field. This finding, published in Science, has the potential to impact electronic, magnetic, and optical devices as well as new applications in quantum computing, spintronics, and nanotechnology. According to Professor Ly Thuc Hue of CityUHK’s Department of Chemistry, the study demonstrates how “a simple twist in bilayer 2D materials” can induce this electric field, bypassing the need for costly thin-film deposition techniques.

Akin to solving intricate technical puzzles, researchers had to ensure clean, precisely aligned layers of material—a notoriously difficult challenge in the world of 2D materials. Twisted bilayers are made by stacking two thin layers of a material at a slight angle, creating unique electronic properties.

However, traditional methods of synthesizing these bilayers often limit the range of twist angles, particularly at smaller degrees, making exploration of their full potential nearly impossible. To address this, the team at City University of Hong Kong developed an ice-assisted transfer technique that uses a thin sheet of ice to align and transfer bilayers with precision.

Large-scale protein and gene profiling have massively expanded the landscape of cancer-associated proteins and gene mutations, but it has been difficult to discern whether they play an active role in the disease or are innocent bystanders. In a study published in Nature Cancer, researchers at Baylor College of Medicine revealed a powerful and unbiased machine learning-based approach called FunMap for assessing the role of cancer-associated mutations and understudied proteins, with broad implications for advancing cancer biology and informing therapeutic strategies.

“Gaining functional information on the genes and proteins associated with cancer is an important step toward better understanding the disease and identifying potential therapeutic targets,” said corresponding author Dr. Bing Zhang, professor of molecular and human genetics and part of the Lester and Sue Smith Breast Center at Baylor.

“Our approach to gain functional insights into these genes and proteins involved using machine learning to develop a network mapping their functional relationships,” said Zhang, member of Baylor’s Dan L Duncan Comprehensive Cancer Center and a McNair Scholar. “It’s like, I may not know anything about you, but if I know your LinkedIn connections, I can infer what you do.”