Pregnant women who were given H1N1 influenza vaccine in 2009 were less likely to face adverse fetal outcomes such as preterm birth. Also, they gave birth to heavier infants. These are the conclusions of a study published on Clinical Infectious Diseases, coordinated by Dr. Saad Omer, of the Rollins School of Public Health at Emory University, Atlanta. He and his colleagues conducted a retrospective cohort study of live births during the period of 2009 influenza A (H1N1) virus circulation, finding that infants of vaccinated mothers had 37% lower probability of being born preterm than infants of unvaccinated mothers. As for the birth weight difference, infants of vaccinated mothers weighed 45.1 grams more than those with unvaccinated mothers.
Vaccines and pregnancy
prossimo articolo
Why have neural networks won the Nobel Prizes in Physics and Chemistry?

This year, Artificial Intelligence played a leading role in the Nobel Prizes for Physics and Chemistry. More specifically, it would be better to say machine learning and neural networks, thanks to whose development we now have systems ranging from image recognition to generative AI like Chat-GPT. In this article, Chiara Sabelli tells the story of the research that led physicist and biologist John J. Hopfield and computer scientist and neuroscientist Geoffrey Hinton to lay the foundations of current machine learning.
Image modified from the article "Biohybrid and Bioinspired Magnetic Microswimmers" https://onlinelibrary.wiley.com/doi/epdf/10.1002/smll.201704374
The 2024 Nobel Prize in Physics was awarded to John J. Hopfield, an American physicist and biologist from Princeton University, and to Geoffrey Hinton, a British computer scientist and neuroscientist from the University of Toronto, for utilizing tools from statistical physics in the development of methods underlying today's powerful machine learning technologies.