After combing through 4,000 existing medications, an artificial intelligence tool helped uncover one that saved the life of a patient with idiopathic multicentric Castleman's disease (iMCD). This rare disease has an especially poor survival rate and few treatment options. The patient could be the first of many to have their lives saved by an AI prediction system, which could potentially apply to other rare conditions.

Tuberculosis is a serious global health threat that infected more than 10 million people in 2022. Spread through the air and into the lungs, the pathogen that causes "TB" can lead to chronic cough, chest pains, fatigue, fever and weight loss. While infections are more extensive in other parts of the world, a serious tuberculosis outbreak currently unfolding in Kansas has led to two deaths and has become one of the largest on record in the United States.

Many people would like to delay or even stop the aging process. Previous clinical studies have shown that a reduced calorie intake can slow down the aging process in humans. Taking vitamin D or omega-3 fatty acids has also shown promising results in slowing biological aging in animals. However, it was unclear whether these measures would also work in humans.

Secondary prevention medications for cardiovascular diseases (CVD) are underused globally and additional strategies to increase their use are needed to improve CVD management and reduce premature mortality rates, according to study published today in JACC, the flagship journal of the American College of Cardiology. The study observed participants with CVD from 17 countries over 12 years and found that medication use remains low with little improvement.

For the last 10 years, the only effective treatment for hypophosphatasia (HPP) has been an enzyme replacement therapy that must be delivered by injection three-to-six times each week.

"It's been a tremendous success and has proven to be a lifesaving treatment," said José Luis Millán, PhD, professor in the Human Genetics Program at Sanford Burnham Prebys.

Antibiotic resistance is a global public health crisis responsible for more than a million deaths annually. By 2050, the World Health Organization estimates it could surpass cancer and heart disease as the leading cause of death as more bacteria develop defenses to the drugs designed to combat them.

Now Tulane University researchers have identified a unique genetic signature in bacteria that can predict their likelihood of developing antibiotic resistance, according to a new study published in Nature Communications.

Biomedical engineers at Duke University have developed an AI-based platform that designs short proteins, termed peptides, capable of binding and destroying previously undruggable disease-causing proteins. Inspired by OpenAI’s image generation model, their new algorithm can rapidly prioritize peptides for experimental testing.

The work appeared Jan. 22 in the journal Science Advances.