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In a small study, researchers at the National Institutes of Health have found that positron emission tomography (PET) scans of the heart may identify people who will go on to develop Parkinson’s disease or Lewy body dementia among those at-risk for these diseases.

The findings, published in the Journal of Clinical Investigation and led by scientists at the National Institute of Neurological Disorders and Stroke (NINDS), part of NIH, may advance efforts to detect the earliest changes that years later lead to Parkinson’s disease and Lewy body dementia.

In 34 people with Parkinson’s disease risk factors, researchers conducted PET scans of the heart to gain insight into levels of the neurotransmitter norepinephrine. They found that the scans could distinguish individuals who would later be diagnosed with Parkinson’s or Lewy body dementia—both are brain diseases caused by abnormal deposits of the protein alpha-synuclein that form clumps known as Lewy bodies. The research was conducted at the NIH Clinical Center, currently the only location for 18 F-dopamine PET scanning.

Squamous cell lung cancer is a lung cancer subtype that is particularly difficult to treat. A new study now has revealed a novel genetic alteration that occurs in some cases in this type of tumor and that may expose a weakness of the tumor for therapeutic intervention.

The University of Cologne researchers led by Professor Roman Thomas, director of the Department of Translational Genomics, was able to show that a certain genetic change occurs during tumor formation and that a previously unknown oncogene is produced. Oncogenes are genes that promote the growth of tumors. In some cases, they can be inhibited by targeted drug treatments.

This approach is often accompanied by a higher success rate and lower side effects compared to conventional chemotherapy. The scientists’ discovery could therefore be a first step toward a more successful therapy of this particular type of cancer.

In a world first, artificial intelligence demonstrated the ability to negotiate a contract autonomously with another artificial intelligence without any human involvement.

British AI firm Luminance developed an AI system based on its own proprietary large language model (LLM) to automatically analyze and make changes to contracts. LLMs are a type of AI algorithm that can achieve general-purpose language processing and generation.

Jaeger Glucina, chief of staff and managing director of Luminance, said the company’s new AI aimed to eliminate much of the paperwork that lawyers typically need to complete on a day-to-day basis.

Stem cell biologist Helen Blau of Stanford University School of Medicine and colleagues previously found that blocking 15-PGDH in old mice restored their withered muscles and improved their strength after a month of treatment. On the flip side, young mice lost muscle and became weaker after their levels of this enzyme were increased for a month.

Blau’s team has now found that 15-PGDH accumulates in the muscles of old mice as the connections that allow communication between muscles and nerves are lost, another consequence of aging. Treating old mice for one month with a drug that inhibits 15-PGDH restored these connections, called synapses, between muscle fibers and motor nerve cells, and boosted the animals’ strength, the team reports in the Oct. 11 Science Translational Medicine. Those synapses are how the brain directs muscles to move.

The findings suggest that blocking the gerozyme 15-PGDH may be a way to help recover strength that has diminished due to nerve injuries, motor nerve cell diseases or aging.

A susceptibility to gain weight may be written into molecular processes of human cells, a Washington State University study indicates.

The proof-of-concept study with a set of 22 found an epigenetic signature in buccal or cheek cells appearing only for the twins who were obese compared to their thinner siblings. With more research, the findings could lead to a simple cheek swab test for an obesity biomarker and enable earlier prevention methods for a condition that effects 50% of U.S. adults, the researchers said.

“Obesity appears to be more complex than simple consumption of food. Our work indicates there’s a susceptibility for this disease and molecular markers that are changing for it,” said Michael Skinner, a WSU professor of biology and corresponding author of the study published in the journal Epigenetics.

The team’s research, including their code, data, and models, is now publicly available on GitHub. This open-source approach encourages the broader AI community to continue this line of exploration, potentially leading to further advancements in machine learning.

The advent of LeMa represents a major milestone in AI, suggesting that machines’ learning (ML) processes can be made more akin to human learning. This development could revolutionize sectors heavily reliant on AI, such as healthcare, finance, and autonomous vehicles, where error correction and continuous learning are critical.

As the AI field continues to evolve rapidly, the integration of human-like learning processes, such as learning from mistakes, appears to be an essential factor in developing more efficient and effective AI systems.