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A new artificial intelligence model finds that X-ray images collected during routine medical care can provide warning signs for diabetes, even in patients who don’t meet the guidelines for elevated risk. The model could help physicians detect the disease earlier and prevent complications, says a multi-institutional team which published the findings in Nature Communications.

Applying the computational method known as deep learning to images and electronic health record data, the researchers developed a model that successfully flagged elevated diabetes risk in a retrospective analysis, often years before patients were diagnosed with the disease. That’s significant, the researchers say, given the prevalence of diabetes in the U.S. has more than doubled over the past 35 years.

Current guidelines suggest screening patients for type 2 diabetes if they are between 35 and 70 years old and have a body mass index (BMI) in the overweight to obese range.

A research team consisting of the National Institute for Materials Science (NIMS) and the Tokyo University of Science has developed the fastest electric double layer transistor using a highly ion-conductive ceramic thin film and a diamond thin film.

This transistor may be used to develop energy-efficient, high-speed edge AI devices with a wide range of applications, including future event prediction and pattern recognition/determination in images (including facial recognition), voices and odors. This research was published in the June 16, 2023, issue of Materials Today Advances.

An electric double layer transistor works as a switch using electrical resistance changes caused by the charge and discharge of an electric double layer formed at the interface between the electrolyte and semiconductor. Because this transistor is able to mimic the electrical response of human cerebral neurons (i.e., acting as a neuromorphic transistor), its use in AI devices is potentially promising.

A common metal paper clip will stick to a magnet. Scientists classify such iron-containing materials as ferromagnets. A little over a century ago, physicists Albert Einstein and Wander de Haas reported a surprising effect with a ferromagnet. If you suspend an iron cylinder from a wire and expose it to a magnetic field, it will start rotating if you simply reverse the direction of the magnetic field.

“Einstein and de Haas’s experiment is almost like a magic show,” said Haidan Wen, a physicist in the Materials Science and X-ray Science divisions of the U.S. Department of Energy’s (DOE) Argonne National Laboratory. “You can cause a cylinder to rotate without ever touching it.”

In Nature, a team of researchers from Argonne and other U.S. national laboratories and universities now report an analogous yet different effect in an “anti”-ferromagnet. This could have important applications in devices requiring ultra-precise and ultrafast motion control. One example is high-speed nanomotors for biomedical applications, such as use in nanorobots for minimally invasive diagnosis and surgery.

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Upload multiple files, suggested prompts and replies, and a whole lot more. OpenAI just released a bevy of updates for ChatGPT.

Warfarin, a widely used blood thinner, appears to have potent anti-cancer properties, according to a study by Columbia University researchers. The study, conducted in human cells and in mice, found that warfarin stops tumors from interfering with a self-destruct mechanism that cells initiate when they detect mutations or other abnormalities.

“Our findings suggest that warfarin, which is already approved by the FDA, could be repurposed to treat a variety of cancers, including pancreatic cancer,” says study leader Wei Gu, Ph.D., the Abraham and Mildred Goldstein Professor of Pathology & Cell Biology (in the Institute for Cancer Genetics) at Columbia University Vagelos College of Physicians and Surgeons.

The study is titled “Regulation of VKORC1L1 is critical for p53-mediated tumor suppression through vitamin K metabolism,” and it was published July 18 in Cell Metabolism. Postdoctoral researcher scientists Xin Yang, Ph.D., and Zhe Wang, Ph.D., contributed equally as first authors.

Earlier today, SpaceX partially fueled Booster 9, continuing a series of tests before its eventual static fire test.

The appetite for hardware to train AI models is voracious.

AI chips are forecast to account for up to 20% of the $450 billion total semiconductor market by 2025, according to McKinsey. And The Insight Partners projects that sales of AI chips will climb to $83.3 billion in 2027 from $5.7 billion in 2018, a compound annual growth rate 35%. (That’s close to 10 times the forecast growth rate for non-AI chips.)

Case in point, Tenstorrent, the AI hardware startup helmed by engineering luminary Jim Keller, this week announced that it raised $100 million in a convertible note funding round co-led by Hyundai Motor Group and Samsung Catalyst Fund.

Scientists claim to have uncovered the “missing link” that could pave the way for wearable electronic devices to control genes.

Wearable devices utilize biosensors to gather an individual’s data, including heart rate, blood pressure, sleep patterns, activity, and temperature, among other metrics.

Wearable electronic devices are playing an increasingly significant role in personalized medicine. However, they’re not yet capable of directly programming gene-based therapies, as explained in an article by a group of researchers from ETH Zurich, a public research university in Zürich, Switzerland.