Health Medicine Stinky'rotten egg' gas could fight nail infections Don't worry, scientists are working on the odor. Breakthroughs, discoveries, and DIY tips sent every weekday. If you have ever let a container of hardboiled eggs spoil or visited a volcano that is spewing lava and gas, you've likely taken a whiff of hydrogen sulfide. This colorless and flammable gas has a uniquely unpleasant rotten egg smell. However that nasty smell (and the gas it belongs to) could have a new use treating pesky infections.

Randomized Controlled Trials (RCTs) are the gold standard for evaluating the effect of new medical treatments. Treatments must pass stringent regulatory conditions in order to be approved for widespread use, yet even after the regulatory barriers are crossed, real-world challenges might arise: Who should get the treatment? What is its true clinical utility? Are there discrepancies in the treatment effectiveness across diverse and under-served populations? We introduce two new objectives for future clinical trials that integrate regulatory constraints and treatment policy value for both the entire population and under-served populations, thus answering some of the questions above in advance. Designed to meet these objectives, we formulate Randomize First Augment Next (RFAN), a new framework for designing Phase III clinical trials. Our framework consists of a standard randomized component followed by an adaptive one, jointly meant to efficiently and safely acquire and assign patients into treatment arms during the trial. Then, we propose strategies for implementing RFAN based on causal, deep Bayesian active learning. Finally, we empirically evaluate the performance of our framework using synthetic and real-world semi-synthetic datasets.

Fox News anchor Bret Baier has the latest on the Murdoch Children's Research Institute's partnership with the Gladstone Institutes for the'Decoding Broken Hearts' initiative on'Special Report.' Australia's Murdoch Children's Research Institute is helping scientists use stem cell medicine and artificial intelligence to develop precision therapies for pediatric heart disease, the leading cause of death and disability in children. Around 260,000 children die from heart disease around the world each year. In the U.S., a child is born with a heart defect every 15 minutes. "We're really interested in understanding how kids develop heart disease and where we can interfere to stop it progressing," Murdoch Children's Research Institute (MCRI) Heart Disease Group Leader David Elliott said.

Scientists have identified a probiotic in dairy fermentation that may help alleviate and reverse some autism symptoms. Currently patients can only use antipsychotics, antidepressants, stimulants and anti-anxiety medications for treatments, but the new study suggests a natural method could just as effective. The discovery was made using genetically modified mice that were prone to autism-like symptoms. When modified, the mice exhibited symptoms of the disorder like a reduced interest in social interactions and an imbalance in the key neurotransmitters crucial for functions like learning, memory and cognitive processes. Researchers gave the animals a daily dose of the probiotic Lactobacillus murinus (a type of bacteria commonly found in dairy products like cheese and yogurt) for one month.

An estimated 610,000 people in the US died from cancer last year. That's almost the same amount of people who perished in the country's four-year civil war. At least two million more people were diagnosed with some form of cancer in 2024, a figure that's climbed in recent years. Early detection remains one of the single biggest factors that determine whether or not someone ultimately survives cancer and, luckily, advances in medical treatment can help. Researchers and medical scientists believe artificial intelligence models could play a key role in that early detection process.

Researchers may have found a new way to target the sources of certain brain disorders. In a study led by scientists at Mass General Brigham, deep brain stimulation (DBS) was able to pinpoint dysfunctions in the brain that are responsible for four cognitive disorders: Parkinson's disease, dystonia (a muscle disorder condition that causes repetitive or twisting movements), obsessive compulsive disorder (OCD) and Tourette's syndrome. The discovery, published in Nature Neuroscience on Feb. 22, could potentially help doctors determine new treatments for these disorders. The study included 261 patients worldwide -- 70 had dystonia, 127 were Parkinson's disease patients, 50 had been diagnosed with OCD and 14 had Tourette's syndrome. The researchers implanted electrodes into the brains of each participant and used special software to determine which brain circuits were dysfunctional in each of the four disorders.

We address the Individualized continuous treatment effect (ICTE) estimation problem where we predict the effect of any continuous-valued treatment on an individual using observational data. The main challenge in this estimation task is the potential confounding of treatment assignment with an individual's covariates in the training data, whereas during inference ICTE requires prediction on independently sampled treatments. In contrast to prior work that relied on regularizers or unstable GAN training, we advocate the direct approach of augmenting training individuals with independently sampled treatments and inferred counterfactual outcomes. We infer counterfactual outcomes using a two-pronged strategy: a Gradient Interpolation for close-to-observed treatments, and a Gaussian Process based Kernel Smoothing which allows us to downweigh high variance inferences. We evaluate our method on five benchmarks and show that our method outperforms six state-of-the-art methods on the counterfactual estimation error. We analyze the superior performance of our method by showing that (1) our inferred counterfactual responses are more accurate, and (2) adding them to the training data reduces the distributional distance between the confounded training distribution and test distribution where treatment is independent of covariates. Our proposed method is model-agnostic and we show that it improves ICTE accuracy of several existing models.

AI is being used in many areas of human biology, including genetics, drug development, and medical imaging. One potential advancement that could be achieved with the use of AI in human biology is the ability to personalize medical treatments based on an individual's genetic makeup. By analyzing an individual's DNA, AI algorithms could identify specific genetic variations that may make them more or less responsive to certain drugs. This could lead to more effective treatments with fewer side effects. Another area where AI is being tested is in the early detection of diseases.

Science and technology have a growing impact on our lives, from food and medicine to communication and entertainment. There's an argument to be made that we have already entered our cyborg era, having enhanced our abilities through computers and the internet. It seems almost inevitable that we'll eventually make our relationship with technology official by melding tech with our biological bodies. In it, Grey Trace -- played by Logan Marshall-Green -- is paralyzed during an automobile accident. Later, under pressure from a wealthy inventor, he accepts an AI implant which allows him to regain function in his limbs.

In what may lead to the development of new treatments for heart diseases, researchers have created a novel artificial intelligence (AI) technique that can detect plaque erosion in heart arteries. The technique uses optical coherence tomography (OCT) images to monitor arterial plaque. The finding is crucial as the disintegration of the plaque can serve as a prelude to a heart attack or other severe heart diseases. The OCT, which is an optical imaging technique, can be used within blood vessels to produce 3D pictures of the coronary arteries that carry blood to the heart muscles. The OCT technique has been in use for spotting plaque erosion.