Publications by authors named "Gabriella Gagliano"
Article Synopsis
- Multi-target single-molecule super-resolution fluorescence microscopy helps researchers study multiple subcellular structures at a nanoscale, but traditional techniques face challenges like high background noise and slow speeds in 3D imaging.
- This study presents an innovative solution called soTILT3D, which uses a steerable light sheet and microfluidic systems to minimize fluorescence background and optimize imaging of whole mammalian cells.
- The platform incorporates advanced technologies such as deep learning for analyzing complex data, specialized techniques for precise localization of molecules, and methods for efficient long-term imaging, ultimately enhancing the speed and accuracy of multi-target imaging in a 3D space.
Article Synopsis
- Multi-target single-molecule super-resolution fluorescence microscopy helps visualize interactions between subcellular structures at the nanoscale but faces challenges like high background noise and slow speed.
- The authors developed a new optical system using a steerable, dithered light sheet to enhance image quality and a microfluidic fabrication technique that includes reflective optics for consistent sample delivery.
- By integrating these advancements with advanced imaging techniques such as deep learning and stabilization methods, the study achieves faster and more precise 3D imaging of multiple targets within whole mammalian cells.
The function of the neuronal synapse depends on the dynamics and interactions of individual molecules at the nanoscale. With the development of single-molecule super-resolution microscopy over the last decades, researchers now have a powerful and versatile imaging tool for mapping the molecular mechanisms behind the biological function. However, imaging of thicker samples, such as mammalian cells and tissue, in all three dimensions is still challenging due to increased fluorescence background and imaging volumes.
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