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The 'Bridging Imaging Users to Imaging Analysis' survey was conducted in 2022 by the Center for Open Bioimage Analysis (COBA), BioImaging North America (BINA) and the Royal Microscopical Society Data Analysis in Imaging Section (RMS DAIM) to understand the needs of the imaging community. Through multichoice and open‐ended questions, the survey inquired about demographics, image analysis experiences, future needs and suggestions on the role of tool developers and users. Participants of the survey were from diverse roles and domains of the life and physical sciences. To our knowledge, this is the first attempt to survey cross‐community to bridge knowledge gaps between physical and life sciences imaging. Survey results indicate that respondents' overarching needs are documentation, detailed tutorials on the usage of image analysis tools, user‐friendly intuitive software, and better solutions for segmentation, ideally in a format tailored to their specific use cases. The tool creators suggested the users familiarise themselves with the fundamentals of image analysis, provide constant feedback and report the issues faced during image analysis while the users would like more documentation and an emphasis on tool friendliness. Regardless of the computational experience, there is a strong preference for 'written tutorials' to acquire knowledge on image analysis. We also observed that the interest in having 'office hours' to get an expert opinion on their image analysis methods has increased over the years. The results also showed less‐than‐expected usage of online discussion forums in the imaging community for solving image analysis problems. Surprisingly, we also observed a decreased interest among the survey respondents in deep/machine learning despite the increasing adoption of artificial intelligence in biology. In addition, the community suggests the need for a common repository for the available image analysis tools and their applications. The opinions and suggestions of the community, released here in full, will help the image analysis tool creation and education communities to design and deliver the resources accordingly. [ABSTRACT FROM AUTHOR]

Cell-cell junctions are dynamic structures that maintain cell cohesion and shape in epithelial tissues. During development, junctions undergo extensive rearrangements to drive the epithelial remodelling required for morphogenesis. This is particularly evident during axis elongation, where neighbour exchanges, cell-cell rearrangements and oriented cell divisions lead to large-scale alterations in tissue shape. Polarised vesicle trafficking of junctional components by the exocyst complex has been proposed to promote junctional rearrangements during epithelial remodelling, but the receptors that allow exocyst docking to the target membranes remain poorly understood. Here, we show that the adherens junction component Ras Association domain family 8 (RASSF8) is required for the epithelial re-ordering that occurs during Drosophila pupal wing proximo-distal elongation. We identify the exocyst component Sec15 as a RASSF8 interactor. Loss of RASSF8 elicits cytoplasmic accumulation of Sec15 and Rab11-containing vesicles. These vesicles also contain the nectin-like homophilic adhesion molecule Echinoid, the depletion of which phenocopies the wing elongation and epithelial packing defects observed in RASSF8 mutants. Thus, our results suggest that RASSF8 promotes exocyst-dependent docking of Echinoid-containing vesicles during morphogenesis. [ABSTRACT FROM AUTHOR]

The productivity of an industrial fermentation process involving a filamentous microbe is heavily dependent on the morphological form adopted by the organism. The development of systems capable of rapidly and accurately characterizing morphology within a given process represents a significant challenge, as the complex phenotypes that are manifested are not easily quantified. Conventional parameters employed in these analyses are often of limited value, as they reveal little about the branching behavior of the organism; an important consideration given the demonstrated link between branching frequency and metabolite production. In this study, the influence of branching behavior on the spatial distribution of mycelia grown in silico is examined through fractal analysis. It is demonstrated that fractal dimension, quantified based on the frequency distribution of parameterized boundary curves, and lacunarity act as robust estimators of branching behavior. The analysis can, in theory, be applied to any morphological form, providing universally applicable process parameters for more complete data acquisition. Biotechnol. Bioeng. 2013; 110: 437-447. © 2012 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]