Journal of Microscopy announces Early Career Researcher ‘Best Paper’ prize winners

The Editors of the Journal of Microscopy are pleased to announce the winners of the inaugural ‘Best Paper’ awards for Early Career Researchers in 2023.

Each prize was £200 and was judged by General Editor, Professor Michelle Peckham, Deputy Editor Professor Pete Nellist and our team of Scientific Editors.

For life sciences, Dr Charlotte Pain has been awarded ‘Best Paper’ for the paper intER-ACTINg: The structure and dynamics of ER and actin are interlinked. Charlotte is a post-doctoral researcher in the department of Biological and Medical Sciences at Oxford Brookes University.

For physical sciences, Dr Alex W. Robinson has been awarded ‘Best Paper’ for the paper Towards real-time STEM simulations through targeted subsampling strategies. Alex is a post-doctoral research associate at the University of Liverpool, and Research Lead at SenseAI innovations.

Life Sciences winner - Dr Charlotte Pain

Scientific Editor, Dr Ulla Neumann said: “The study by Charlotte Pain and colleagues beautifully shows the intricate relationship between the actin cytoskeleton and the endoplasmic reticulum in plants. High-quality confocal microscopy combined with solid image analysis and data quantification clearly show that changing one of the two partners in the plant ER-actin relationship inevitably alters the other. It also makes the point that the choice of a specific actin marker is crucial when it comes to studying organelle structure and dynamics. Congratulations to Charlotte and her colleagues for winning the ERC Best Paper prize in the Life Sciences.”

Professor Peckham added: “This is comprehensive study that demonstrates the strong interaction between the actin cytoskeleton and the endoplasmic reticulum (ER) in plants. The images are great, have been expertly quantified, and the work additionally demonstrates how choice of fluorescent probe for actin and ER in important in avoiding off target effects.”

Physical sciences winner - Dr Alex W. Robinson

Scientific Editor, Professor Mark Rainforth said: “Scanning transmission electron microscopy images can be complex to interpret at the atomic scale as the contrast is sensitive to many variables such as sample thickness, composition, the presence of defects, and of course, aberrations. This paper took a new approach where the manner in which the signal was sampled was changed, providing a more accurate and efficient method for STEM simulations. The paper won because of the novelty and quality of the work undertaken.”

Professor Nellist added: “This paper brings together simulations of scanning transmission electron microscope (STEM) images with the emerging field of compressive sensing.  Simulations of images are a vital tool to allow the inversion of STEM data to meaningful, quantitative measurements.  These simulations are, however, computationally demanding which can limit the range of models and parameters that can be explored.  Compressive sensing has been used for in-painting data from sub-sampled experimental data, but the innovation in this paper is its use for sub-sampling of modelling parameters in simulations with the aim of making simulations real time.”

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