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Different gametogenesis states uniquely impact longevity in Caenorhabditis elegans
In Caenorhabditis elegans, ablation of germline stem cells leads to extended lifespan and increased fat storage. Here the authors show that disrupting distinct gametogenesis programs and germline progression in C. elegans triggers molecular responses that affect fat metabolism, stress resilience, and lifespan.
A viable therapeutic target pancreatic ductal adenocarcinoma
This issue’s cover features work by Adrian M. Seifert & team on Nectin-4’s connection to poor outcome and immune suppression in patients with PDAC, and targeting Nectin-4 with the antibody-drug conjugate enfortumab vedotin inhibited tumor growth in PDAC organoids:
The cover image shows high Nectin-4 immunohistochemistry staining (brown) in human PDAC.
1Department of Visceral, Thoracic and Vascular Surgery, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.
2National Center for Tumor Diseases (NCT), Dresden, Germany.
3German Cancer Research Center (DKFZ), Heidelberg, Germany.
Stress-testing AI vision systems: Rethinking how adversarial images are generated
Deep neural networks (DNNs) have become a cornerstone of modern AI technology, driving a thriving field of research in image-related tasks. These systems have found applications in medical diagnosis, automated data processing, computer vision, and various forms of industrial automation, to name a few.
As reliance on AI models grows, so does the need to test them thoroughly using adversarial examples. Simply put, adversarial examples are images that have been strategically modified with noise to trick an AI into making a mistake. Understanding adversarial image generation techniques is essential for identifying vulnerabilities in DNNs and for developing more secure, reliable systems.
GNSS-only method delivers stable positioning for autonomous vehicles in urban areas
Global navigation satellite systems (GNSS) are vital for positioning autonomous vehicles, buses, drones, and outdoor robots. Yet its accuracy often degrades in dense urban areas due to signal blockage and reflections.
Now, researchers have developed a GNSS-only method that delivers stable, accurate positioning without relying on fragile carrier-phase ambiguity resolution. Tested across six challenging urban scenarios, the approach consistently outperformed existing methods, enabling safer and more reliable autonomous navigation.