Sam Berns was my friend. With the wisdom of a sage, he inspired me and many others about how to make the most of life. Afflicted with the rare disease called progeria, his body aged at a rapid rate, and he died of heart failure at just 17, a brave life cut much too short. My lab discovered the genetic cause of Sam's illness two decades ago: Just one DNA letter gone awry, a T that should have been a C in a critical gene called lamin A. The same misspelling is found in almost all of the 200 individuals around the world with progeria. This story is from the WIRED World in 2025, our annual trends briefing.

Diagnosing blood disorders relies on a century-old method of using optical microscopes to analyze and classify samples of bone marrow cells. The method used to look for rare, but diagnostically important, cells is well-established, albeit laborious and time-consuming. Artificial intelligence (AI) has the potential to improve this method. However, training an AI algorithm requires a large amount of high-quality data. Now a team has used a data set of more than 170,000 microscopic images to train neural networks to identify bone marrow cells with high accuracy.

Myelodysplastic syndrome (MDS) is a disease of the stem cells in the bone marrow, which disturbs the maturing and differentiation of blood cells. Annually, some 200 Finns are diagnosed with MDS, which can develop into acute leukaemia. Globally, the incidence of MDS is 4 cases per 100,000 person years. To diagnose MDS, a bone marrow sample is needed to also investigate genetic changes in bone marrow cells. The syndrome is classified into groups to determine the nature of the disorder in more detail.

Myelodysplastic syndrome (MDS) is a disease of the stem cells in the bone marrow, which disturbs the maturing and differentiation of blood cells. Annually, some 200 Finns are diagnosed with MDS, which can develop into acute leukemia. Globally, the incidence of MDS is 4 cases per 100,000 person years. To diagnose MDS, a bone marrow sample is needed to also investigate genetic changes in bone marrow cells. The syndrome is classified into groups to determine the nature of the disorder in more detail.