Artificial Intelligence in Lung Cancer Imaging: From Data to Therapy.

Lung cancer remains a global health challenge, leading to substantial morbidity and mortality. While prevention and early detection strategies have improved, the need for precise diagnosis, prognosis, and treatment remains crucial. In this comprehensive review article, we explore the role of artificial intelligence (AI) in reshaping the management of lung cancer.

Memories of a young student: the early days of splicing regulation with François Gros.

I joined the laboratory of François Gros as a young student in the mid-1980s and worked on the characterization of the -tropomyosin gene in chicken and the regulation of alternative splicing of its transcript, under the supervision of Marc Fiszman. In particular, I was interested in how secondary structures of the RNA influence the recognition of exons specifically used in muscle cells. I will recall a few memories on how interacting with François on this project shaped my perception of the scientific process and of the relationships between models and data.

RNase H2 degrades toxic RNA:DNA hybrids behind stalled forks to promote replication restart.

R-loops represent a major source of replication stress, but the mechanism by which these structures impede fork progression remains unclear. To address this question, we monitored fork progression, arrest, and restart in Saccharomyces cerevisiae cells lacking RNase H1 and H2, two enzymes responsible for degrading RNA:DNA hybrids. We found that while RNase H-deficient cells could replicate their chromosomes normally under unchallenged growth conditions, their replication was impaired when exposed to hydroxyurea (HU) or methyl methanesulfonate (MMS).