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The study of cellular and developmental processes in physiologically relevant three-dimensional (3D) systems facilitates an understanding of mechanisms underlying cell fate, disease and injury. While cuttingedge microscopy technologies permit the routine acquisition of 3D datasets, there is currently a limited number of open-source software packages to analyse such images. Here, we describe General Image Analysis of Nuclei-based Images (GIANI; https://djpbarry.github.io/Giani), new software for the analysis of 3D images. The design primarily facilitates segmentation of nuclei and cells, followed by quantification of morphology and protein expression. GIANI enables routine and reproducible batch-processing of large numbers of images, and comes with scripting and command line tools. We demonstrate the utility of GIANI by quantifying cell morphology and protein expression in confocal images of mouse early embryos and by segmenting nuclei from light-sheet microscopy images of the flour beetle embryo. We also validate the performance of the software using simulated data. More generally, we anticipate that GIANI will be a useful tool for researchers in a variety of biomedical fields. [ABSTRACT FROM AUTHOR]

Highlights • A method for deriving new safety knowledge from flight data is proposed. • Machine learning method is demonstrated on over 1 million flights. • Method successfully detected safety occurrences missed by current methods. Abstract The aim of this work is to investigate the possibility of using machine learning (ML) methods in order to generate novel, safety-relevant knowledge from existing flight data. Airlines routinely generate vast amounts of flight data from routine monitoring, but the concept of extracting safety knowledge from this data is still based on detecting exceedances of expert-defined thresholds. This system is conceptually unable to detect novel occurrences for which no such filters exist. ML techniques are able to close this gap. This paper first reviews the literature to select an appropriate ML method. A form of unsupervised learning called "Local Outlier Probability" is selected. Next, an appropriate feature space is developed and implemented in the flight data monitoring system of a supporting airline to generate the dataset. This dataset is cleaned and the outlier calculation performed. The results are statistically analysed. Furthermore, the top outliers are reviewed by the airline's review pilots in the same way as the traditional exceedance events. Last, the severities and safety relevance of both types of events are compared. This work successfully shows that the chosen approach is able to reduce the number of undetected safety-relevant occurrences by finding novel occurrence types which were undetected by a contemporary and mature flight data monitoring system. This research builds on recent literature by developing a novel method which can be scaled to work in an airline production environment with large datasets, as demonstrated by the efficient analysis of 1.2 million flights. [ABSTRACT FROM AUTHOR]

The murine leukaemia virus (MLV) Gag cleavage product, p12, is essential for both early and late steps in viral replication. The N-terminal domain of p12 binds directly to capsid (CA) and stabilises the mature viral core, whereas defects in the C-terminal domain (CTD) of p12 can be rescued by addition of heterologous chromatin binding sequences (CBSs). We and others hypothesised that p12 tethers the pre-integration complex (PIC) to host chromatin ready for integration. Using confocal microscopy, we have observed for the first time that CA localises to mitotic chromatin in infected cells in a p12-dependent manner. GST-tagged p12 alone, however, did not localise to chromatin and mass-spectrometry analysis of its interactions identified only proteins known to bind the p12 region of Gag. Surprisingly, the ability to interact with chromatin was conferred by a single amino acid change, M63I, in the p12 CTD. Interestingly, GST-p12_M63I showed increased phosphorylation in mitosis relative to interphase, which correlated with an increased interaction with mitotic chromatin. Mass-spectrometry analysis of GST-p12_M63I revealed nucleosomal histones as primary interactants. Direct binding of MLV p12_M63I peptides to histones was confirmed by biolayer-interferometry (BLI) assays using highly-avid recombinant poly-nucleosomal arrays. Excitingly, using this method, we also observed binding between MLV p12_WT and nucleosomes. Nucleosome binding was additionally detected with p12 orthologs from feline and gibbon ape leukemia viruses using both pull-down and BLI assays, indicating that this a common feature of gammaretroviral p12 proteins. Importantly, p12 peptides were able to block the binding of the prototypic foamy virus CBS to nucleosomes and vice versa, implying that their docking sites overlap and suggesting a conserved mode of chromatin tethering for different retroviral genera. We propose that p12 is acting in a similar capacity to CPSF6 in HIV-1 infection by facilitating initial chromatin targeting of CA-containing PICs prior to integration. [ABSTRACT FROM AUTHOR]

Cell migration is frequently accompanied by changes in cell morphology (morphodynamics) on a range of spatial and temporal scales. Despite recent advances in imaging techniques, the application of unbiased computational image analysis methods for morphodynamic quantification is rare. For example, manual analysis using kymographs is still commonplace, often caused by lack of access to user-friendly, automated tools. We now describe software designed for the automated quantification of cell migration and morphodynamics. Implemented as a plug-in for the open-source platform, ImageJ, ADAPT is capable of rapid, automated analysis of migration and membrane protrusions, together with associated fluorescently labeled proteins, across multiple cells. We demonstrate the ability of the software by quantifying variations in cell population migration rates on different extracellular matrices. We also show that ADAPT can detect and morphologically profile filopodia. Finally, we have used ADAPT to compile an unbiased description of a "typical" bleb formed at the plasma membrane and quantify the effect of Arp2/3 complex inhibition on bleb retraction. [ABSTRACT FROM AUTHOR]

Mycelial morphology is a critically important process property in industrial fermentations of filamentous micro-organisms, as particular phenotypes are associated with maximum productivity. However, the accurate quantification of complex morphologies still represents a significant challenge in elucidating this relationship. A system has been developed for high-resolution characterisation of filamentous fungal growth on a solid substrate, using membrane immobilization and fully-automatic plug-ins developed for the public domain, Java-based, image-processing software, ImageJ. The system has been used to quantify the microscopic development of Aspergillus oryzae on malt agar, by measuring spore projected area and circularity, the total length of a hyphal element, the number of tips per element, and the hyphal growth unit. Two different stages of growth are described, from the swelling of a population of conidiospores up to fully developed, branched hyphae 24 h after inoculation. Spore swelling expressed as an increase in mean equivalent spore diameter was found to be approximately linear with time. Widespread germination of spores was observed by 8 h after inoculation. From approximately 12 h, the number of tips was found to increase exponentially. The specific growth rate of a population of hyphae was calculated as approximately 0.24–0.27 h−1. A wide variation in growth kinetics was found within the population. The robustness of the image-analysis system was verified by testing the effect of small variations in the input data. [ABSTRACT FROM AUTHOR]

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]

• Bayesian networks can be learnt from airborne recorded flight data. • Bayesian networks can be used to quantify airline risks. • Greedy Thick Thinning is marginally preferable to Bayesian Search. • Bayesian networks should be used in airline safety management to assess risk. Risk assessments in airline operations are mostly qualitative, despite abundant data from programmes such as flight data monitoring (FDM) and flight operations quality assurance (FOQA). In this paper, features relating to runway excursion causal factors are extracted from flight data from over 310,448 flights from Airbus A320 series aircraft flown on a European network. The data is combined with meteorological data to provide additional features. Bayesian networks are then learnt from the feature set, and two network learning algorithms are compared, Bayesian Search and Greedy Thick Thinning (GTT). Cross-validation of the resulting networks shows both algorithms produce similarly performing networks, and a subjective analysis concludes that the GTT algorithm is marginally preferred. The resulting networks produce relative probabilities, which airlines can use to quantitatively assess runway veer-off risk under different scenarios, such as different meteorological conditions and unstable approaches. This paper's main finding is that by utilising existing data sources, such as FDM and weather databases, airlines can create and use Bayesian networks alongside their existing qualitative risk assessment methods to provide quantitative risk assessment and understand the effect of different conditions on those risks. This is not possible with current methods in use by airlines. The method described can be extended to other operational safety risks, such as runway overrun. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented regarding convulsive status epilepticus (CSE) as a common component in tiagabine overdose.

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 higher-order patterning of extra-cellular matrix in normal and pathological tissues has profound consequences on tissue function. Whilst studies have documented both how fibroblasts create and maintain individual matrix fibers and how cell migration is altered by the fibers they interact with, a model unifying these two aspects of tissue organization is lacking. Here we use computational modelling to understand the effect of this interconnectivity between fibroblasts and matrix at the mesoscale level. We created a unique adaptation to the Vicsek flocking model to include feedback from a second layer representing the matrix, and use experimentation to parameterize our model and validate model-driven hypotheses. Our two-layer model demonstrates that feedback between fibroblasts and matrix increases matrix diversity creating higher-order patterns. The model can quantitatively recapitulate matrix patterns of tissues in vivo. Cells follow matrix fibers irrespective of when the matrix fibers were deposited, resulting in feedback with the matrix acting as temporal 'memory' to collective behaviour, which creates diversity in topology. We also establish conditions under which matrix can be remodelled from one pattern to another. Our model elucidates how simple rules defining fibroblast-matrix interactions are sufficient to generate complex tissue patterns. The organization of extracellular matrix in the body is diverse and often becomes dysregulated in cancer. How such patterns emerge is poorly understood, in particular how the interplay between the fibroblasts, which produce the matrix fibers, and the fibers themselves affects emergent organization. We created a unique adaptation to the Vicsek flocking model to include feedback from a second layer representing the matrix. Fibroblasts were able to deposit, degrade and rearrange fibers and the fibers could also contribute to the vector of cell migration. We find that this feedback is sufficient to generate many complex tissue patterns, as seen in vivo. The model is able to encapsulate key fibroblast and matrix properties without compromising on scale, providing an insight into the co-evolution of two crucial components of tissues at the scale of millimeters. [ABSTRACT FROM AUTHOR]

Summary Ena/VASP proteins and the WAVE regulatory complex (WRC) regulate cell motility by virtue of their ability to independently promote actin polymerization. We demonstrate that Ena/VASP and the WRC control actin polymerization in a cooperative manner through the interaction of the Ena/VASP EVH1 domain with an extended proline rich motif in Abi. This interaction increases cell migration and enables VASP to cooperatively enhance WRC stimulation of Arp2/3 complex-mediated actin assembly in vitro in the presence of Rac. Loss of this interaction in Drosophila macrophages results in defects in lamellipodia formation, cell spreading, and redistribution of Ena to the tips of filopodia-like extensions. Rescue experiments of abi mutants also reveals a physiological requirement for the Abi:Ena interaction in photoreceptor axon targeting and oogenesis. Our data demonstrate that the activities of Ena/VASP and the WRC are intimately linked to ensure optimal control of actin polymerization during cell migration and development. [ABSTRACT FROM AUTHOR]