Dr. Yan Nie wins Helmholtz Imaging Award
On 31.05.2022, the award for the best scientific image was presented at the Helmholtz Imaging Conference 2022 in Berlin. Yan Nie from the Department of Polymers in Regeneration at the Hereon-Institute of Active Polymers in Teltow, won the first public choice prize with "Cells on the Move". The image will be shown as part of a touring exhibition at the different Helmholtz Centers and published together with eleven other images in the Helmholtz Imaging Calendar.
„Cells on the Move"
Photo: Hereon/Yan Nie
The contest recognizes images that are considered scientifically outstanding and interesting. The assessment criteria take into account, among others, the scientific significance, originality and artistic as well as visual impact of the submitted images. Nie's "Cells on the Move" reveals the usually invisible cytoskeleton of how cell navigates and migrates in a particular direction.
"Cells are constantly on the move in responding to the external signal. Unlike the human skeleton, which stays the same arrangement throughout our lives, the cellular cytoskeleton is highly dynamic and continuously changing. In the image, we reveal the usually invisible cellular components of human keratinocyte cells, which initiate migration and control the movement. The major components of the cytoskeleton were visualized taking advantage of immunofluorescence staining: Microfilaments in red, microtubules in green and intermediate filaments in magenta. The cell nucleus was counterstained in blue," says Yan Nie.
Dr. Yan Nie
Photo: Hereon/Lisa Depenbrock
The Helmholtz Imaging Platform (HIP) connects people from science and engineering in the Helmholtz Association to promote imaging research and strengthen synergies between methods and applications within the research community. Imaging spans the entire process from data acquisition and data preparation to data management and data analysis.
"High-resolution images help us to understand the complex processes inside cells and can provide the crucial data to predict cell behaviors under different conditions."