Study deepens understanding of cell migration, important for potential medical advances
Peer-Reviewed Publication
Updates every hour. Last Updated: 11-Sep-2025 16:11 ET (11-Sep-2025 20:11 GMT/UTC)
A new study in iScience integrated mathematical modeling with advanced imaging to discover that the physical shape of the fruit fly egg chamber, combined with chemical signals, significantly influences how cells move. Cell migration is critical in wound healing, immune responses, and cancer metastasis, so the work has potential to advance a range of medical treatments. To the authors’ knowledge, this is the first study that actively considers the role of both chemical and structural signals in cell migration.
Whether designing new proteins or mapping DNA structure, these scientists aim to shed light on these fundamental questions through large-scale data collection, mathematical modeling, and quantitative analysis.
Astrophysicist Kyu-Hyun Chae at Sejong University (Seoul, South Korea) has developed a new method of measuring gravity with all three components of the velocities (3D velocities) of wide binary stars, as a major improvement over existing statistical methods relying on sky-projected 2D velocities. The new method based on the Bayes theorem derives directly the probability distribution of a gravity parameter (a parameter that measures the extent to which the data departs from standard gravitational dynamics) through the Markov Chain Monte Carlo simulation of the relative 3D velocity between the stars in a binary. When the method is applied to a sample of about 300 highest-quality wide binaries selected from European Space Agency's Gaia Data Release 3, the results indicate a 4.2σ discrepancy with standard gravity at acceleration lower than about 1 nanometer per second squared. Much improved results are expected in the near future with upcoming data of precise velocities of stars in the line-of-sight (radial) direction.
The EQUALITY project brings together scientists, innovators, and prominent industrial players to develop advanced quantum computer algorithms to tackle strategic industrial problems in areas such as energy storage, aerodynamics, and space mission optimisation. This upcoming webinar series will highlight some of the project's most promising results. Topics include novel quantum approaches to optimisation, analysis of noise in quantum bits and its impact on applied computations, tailoring of quantum circuits, and more — all with a focus on real-world industrial relevance.