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Research published in Science Advances is the first to use a sophisticated human tissue model to explore the interaction between host and pathogen for six common species that cause urinary tract infections. The findings suggest that the “one size fits all” approach to diagnosis and treatment currently used in most health care systems is inadequate.

Urinary tract infection (UTI) is a growing problem, with around 400 million global cases per year and an estimated 250,000 UTI-related deaths associated with antimicrobial resistance (AMR). Although UTI is often perceived as a simple bacterial infection, 25–30% of UTIs recur within six months despite antibiotic therapy for reasons that are poorly understood.

A condition that primarily affects women, UTI has been historically understudied and underfunded, with no improved anti-infective treatments introduced since Alexander Fleming discovered antibiotics nearly a century ago. Diagnosis primarily rests on the midstream urine culture method (dipstick test), an early 20th century technique that is known to miss many infections.

Researchers at Weill Cornell Medicine have uncovered a novel route to stimulate the growth of healthy insulin-producing pancreatic beta cells in a preclinical model of diabetes. The findings hold promise for future therapeutics that will improve the lives of individuals with type 2 diabetes—a condition that affects more than half a billion people worldwide.

This study, published in the Journal of Clinical Investigation on Sept. 15, demonstrated that activating a pathway to promote cell division not only expanded the population of insulin-producing cells, but surprisingly, it also enhanced the cells’ function.

“That’s reassuring because there is a long-standing belief in the field that proliferation can lead to ‘de-differentiation’ and a loss of cell function,” said study senior author Dr. Laura Alonso, chief of the division of endocrinology, diabetes and metabolism, director of the Weill Center for Metabolic Health, and the E. Hugh Luckey Distinguished Professor in Medicine at Weill Cornell Medicine. “Our result flies in the face of that dogma and suggests if we can find a way to trigger replication of the beta cells in the body, we won’t impair their ability to produce and secrete insulin.”

Thyrotoxicosis was associated with 39% higher risk for cognitive disorders.

Thyrotoxicosis, defined as a low level of serum thyroid-stimulating hormone (TSH), can result from either a primary thyroid disorder (endogenous) or overtreatment of hypothyroidism (exogenous). Evidence suggests that thyrotoxicosis is a risk factor for dementia. In this U.S. longitudinal cohort study, researchers used data from electronic health records for 66,000 people (median age, 68) without low TSH levels or cognitive disorders at baseline and evaluated whether development of thyrotoxicosis was associated with excess risk for cognitive disorders.

During the study period (2014 to 2023), 2,700 patients had low TSH levels (60% exogenous), and 4,800 patients received diagnoses of cognitive disorders. The incidence of cognitive disorders among patients with and without thyrotoxicosis were 11% and 6% at age 75, and 34% and 26% at age 85. Adjusted for multiple variables, all-cause thyrotoxicosis was associated with a significant 39% excess risk for cognitive disorders. Exogenous thyrotoxicosis — and in particular, severe exogenous thyrotoxicosis (TSH 0.1 mIU/L) — were associated most strongly with excess risk for cognitive disorders.

“You can see a very strong modulation, which is always there. As the modulation gets to be more profound, it eventually flattens out, and that’s when the brain reaches the deeper state,” Brown says.

When the amount of drug was reduced, the amplitude of the alpha waves began to increase again.

The researchers also found a distinctive pattern in the slow and delta waves seen in the patients’ EEG readings. Slow and delta oscillations are the slowest brain waves, and as the amount of drug was increased, the frequency of these waves became slower and slower, reflecting a decrease in brain activity.

The prediction stems from a project to translate tests currently used in research into aids for routine diagnosis in hospitals.

The human brain is three times bigger than a chimp’s and more spherical than a Neanderthal’s. Within a maze of bumps and grooves, neurons converse in distinct patterns that give humans unique cognitive abilities.

Scientists haven’t fully deciphered those patterns. But researchers at UT Southwestern Medical Center are determined to solve the molecular mystery of what makes us human.

In a study published in the journal Nature, they compared brain cell types and activities among humans, chimpanzees and rhesus monkeys. Human brains had more of a kind of cell that may help them adapt based on new experience and heal from injury. Certain human neurons also had more of a gene that affects language development.

While we all aspire for a long lifespan, what is most coveted is a long period of vigor and health, or “healthspan,” that precedes the inevitable decline of advancing age. Researchers at UC Santa Barbara have discovered that instruments of death that cells use to commit suicide when things go wrong contribute to making a longer and healthier life by revitalizing the specialized cellular compartments called mitochondria.

Mitochondria generate the energy for all of our activities, from movement to thought. These power plants inside our cells descended from what were once free-living bacteria.

“We are a sort of hybrid creature that arose from two independent evolutionary lineages: mitochondria, which were once bacteria, and the rest of the cell surrounding them,” notes Joel Rothman, a professor of molecular biology whose lab conducted the research.

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A combined team of biomedical researchers from Novartis Institutes for Biomedical Research and Microsoft Research AI4Science has made inroads into teaching AI systems how to find new medicines. In their study, reported in the journal Nature Communications, the group used feedback from chemists in the field to provide intuition guidelines for an AI model.

Finding new medicines is a notoriously difficult and laborious task. The process for finding new therapies typically involves experts in a variety of fields working on different parts of the problem. Doctors and other medical researchers, for example, must first uncover the roots of a given illness to find its cause. Chemists or other medical researchers must then find a chemical that might reverse the problem or stop it from happening in the first place.

Both parts of the process take time and effort. In this new project, the research team sought to determine whether AI applications might make the second part easier.