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Lung cancer is the leading cause of cancer-related deaths in the United States. Some tumors are extremely small and hide deep within lung tissue, making it difficult for surgeons to reach them. To address this challenge, UNC–Chapel Hill and Vanderbilt University researchers have been working on an extremely bendy but sturdy robot capable of traversing lung tissue.

Their research has reached a new milestone. In a new paper, published in Science Robotics, Ron Alterovitz, Ph.D., in the UNC Department of Computer Science, and Jason Akulian, MD MPH, in the UNC Department of Medicine, have proven that their robot can autonomously go from “Point A” to “Point B” while avoiding important structures, such as tiny airways and blood vessels, in a living laboratory model.

“This technology allows us to reach targets we can’t otherwise reach with a standard or even robotic bronchoscope,” said Dr. Akulian, co-author on the paper and Section Chief of Interventional Pulmonology and Pulmonary Oncology in the UNC Division of Pulmonary Disease and Critical Care Medicine. “It gives you that extra few centimeters or few millimeters even, which would help immensely with pursuing small targets in the lungs.”

Many of the genetic mutations that directly cause a condition, such as those responsible for cystic fibrosis and sickle-cell disease, tend to change the amino acid sequence of the protein that they encode. But researchers have observed only a few million of these single-letter ‘missense mutations’. Of the more than 70 million such mutations that can occur in the human genome, only a sliver have been linked conclusively to disease, and most seem to have no ill effect on health.

So when researchers and doctors find a missense mutation that they’ve never seen before, it can be difficult to know what to make of it. To help interpret such ‘variants of unknown significance’, researchers have developed dozens of computational tools that can predict whether a variant is likely to cause disease. AlphaMissense incorporates existing approaches to the problem, which are increasingly being addressed with machine learning.

Jacopo Pantaleoni joined Nvidia in 2001 when the company had less than 500 employees. He worked on what was then a small research project to improve Nvidia’s graphics processing units so they could better render images on computers and gaming consoles.

More than two decades later, Nvidia has more than 26,000 employees and its GPUs are at the center of the generative AI explosion. Pantaleoni had climbed the ranks to become a principal engineer and research scientist, one of the highest ranking positions for an individual contributor, he says. Then, in July, as Nvidia boomed like no other company, Pantaleoni says he resigned, giving up a substantial amount of unvested stock units, after coming to a realization.

“This market of machine learning, artificial intelligence” is “almost entirely driven by the big players— Googles, Amazons, Metas”—that have the “enormous amounts of data and enormous amounts of capital” to develop AI at scale. Those companies are also Nvidia’s biggest customers. “This was not the world I wanted to help build,” he said.

This isn’t good. I feel for anyone in the human trials.


Documents viewed as part of a new investigation by Wired, however, as well as testimony from a former employee, contradict Musk’s claims entirely — and the details are as upsetting as they are damning, adding to a mounting case against the safety of Neuralink’s devices.

And the timing couldn’t be more exigent either, with Neuralink announcing on Wednesday that it’s recruiting subjects for human trials.

Here’s the harrowing casualty report, per veterinary records obtained by Wired from the California National Primate Research Center (CNPRC) at UC Davis, the site of the Neuralink primate research. Up to a dozen monkeys suffered grisly fates after receiving a Neuralink implant, including brain swelling and partial paralysis.

An international research team led by scientists in the Center for Genetic Epidemiology at the Keck School of Medicine of USC and USC Norris Comprehensive Cancer Center has singled out mutations in 11 genes that are associated with aggressive forms of prostate cancer.

These findings come from the largest-scale prostate cancer study ever exploring the exome—that is, the key sections of the genetic code that contain the instructions to make proteins. The scientists analyzed samples from about 17,500 .

Today, oncologists customize care for certain individuals with with help from genetic tests. The results can inform treatment, as one class of targeted therapies has proved effective against some inherited prostate cancers. Test findings also can lead to genetic screening among patients’ family members, so they have the chance to take measures that reduce risk and to work with their doctors to be more vigilant in early detection.

The types of cancer that occur in children often are different from those in adults. Childhood cancers usually are not linked to lifestyle or environmental risk factors, as is often the case in adults. Nonetheless, cancer is the second-leading cause of death in children 1 to 14 years old, according to the American Cancer Society. Nearly 10,000 children in the U.S. under the age of 15 will be diagnosed with cancer in 2023, and about 1,000 children are expected to die of the disease.

September is Childhood Cancer Awareness Month, which makes this a good time to learn about three of the most common types of cancer in children: acute lymphocytic leukemia, neuroblastoma and pediatric brain tumors.

Acute lymphocytic leukemia is a cancer of the blood and bone marrow. It’s the most common type of cancer in children, and treatments result in a good chance for a cure. Acute lymphocytic leukemia also can occur in adults, though the chance of a cure is greatly reduced.