Zika virus (ZIKV) infection is a major public health concern, particularly due to the severe brain development defects it can cause in fetuses when pregnant women are infected. One of the most serious outcomes is microcephaly—a condition in which newborns exhibit abnormally small heads. Currently, there are no approved treatments or vaccines for ZIKV, largely because the mechanisms behind the disease remain poorly understood.  

Until now, mouse models have been used to study ZIKV infection. However, these models come with significant limitations in terms of number of animals required, technical challenges, high costs, and ethical considerations.  

At the Institut National de la Recherche Scientifique (INRS), Professors Laurent Chatel-Chaix and Kessen Patten combined their expertise in virology and neurodegenerative diseases, respectively, to explore an alternative animal infection model based on zebrafish. This collaboration has led to new insights into how Zika virus affects the developing brain.  

Together with Aïcha Sow, a PhD student in virology and immunology, the researchers, who are also Pasteur Network members, developed a zebrafish model that allows them to study ZIKV infection at early developmental stages at the levels of the whole organism, tissues, cells, and molecules.  

This research, which constitutes the core Sow’s doctoral thesis, was recently published in PLOS Pathogens. The student is also planning to begin a postdoctoral fellowship at the Institut Pasteur in France in the near future. 

The El Niño-Southern Oscillation (ENSO) cycle moves between warmer-than-average Pacific Ocean surface water temperatures during El Niño phases to colder-than-average surface water temperatures during La Niña phases. Scientists have observed that the surface temperatures of water in the central and eastern Pacific affect the number and strength of tropical cyclones (TCs) that develop in the North Atlantic Ocean and the probability those TCs will make landfall. Researchers recently investigated the effects of El Niño and La Niña dissipation events on and factors that contribute to TC development in the North Atlantic Ocean.

In a paper published in SCIENCE CHINA Earth Sciences, an international team of researchers present the new details about the enhancement of aragonite precipitation during photosynthesis in Skeletonema costatum in artificial and natural seawater. By directly measuring cell surfaces, it reveals the mechanism of diatom-mediated promotion of CaCO₃ precipitation. Based on this mechanism, it suggests that diatom-mediated calcification can occur in the oceans, which is supported by relevant phenomena. The newly found calcification pathway connects particulate inorganic and organic carbon flux, facilitating the reassessment of marine carbon export fluxes and CO₂ sequestration efficiency. And this discovery may have significant implications for evaluating marine carbon cycling and predicting the impacts of future ocean acidification.

How can we precisely control microscale surfaces using magnetic fields?

Researchers from Sun Yat-sen University, Worcester Polytechnic Institute, and others propose a unified framework for designing magnetically responsive microstructured surfaces (MRMFSs).

Published in International Journal of Extreme Manufacturing, this review outlines advances in structure, fabrication, and actuation, with future potential in micro-manipulation, soft robotics, sensing, and smart materials.

Researchers Wooyoung Jin and Hyungyeon Cha from the Ulsan Advanced Energy Technology R&D Center at the Korea Institute of Energy Research (KIER, President Chang-Keun Yi) have resolved a long-standing challenge in high-Ni cathode materials, a key component of next-generation electric vehicle (EV) batteries.

In a paper published in Science China Earth Sciences, a team of scientists present a novel application of data-driven AI model to real-time predictions of the 2023–2024 climate conditions in the tropical Pacific. As configured, this AI-based model can adequately represent the coupled ocean-atmosphere interactions, with its prediction procedure being executed in a rolling manner, in which the related key fields during multi-month time intervals (TIs) are taken for input predictors serving as initial conditions. Sensitivity experiments are conducted to examine how prediction skills are affected by the input predictor specifications, including TIs. A comparison with other dynamic coupled models is also made to demonstrate the prediction performance for the 2023–2024 El Niño event.