Publications by authors named "Sage D"

This manuscript showcases the latest advancements in deepImageJ, a pivotal Fiji/ImageJ plugin for bioimage analysis in life sciences. The plugin, known for its user-friendly interface, facilitates the application of diverse pre-trained convolutional neural networks to custom data. The manuscript demonstrates several deepImageJ capabilities, particularly in deploying complex pipelines, three-dimensional (3D) image analysis, and processing large images.

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  • * The group organizes MiFoBio conferences that feature lectures and hands-on workshops, allowing specialists to share insights and reflect on the evolution of microscopy over the years.
  • * The 2023 conference included retrospective talks on key topics like multicellular imaging and advancements in imaging technologies, with summaries available on the ImaBio YouTube channel for further learning.
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  • Machine learning is changing image processing and analysis, especially in microscopy, by automating tasks and uncovering visual patterns.
  • The review examines the importance of data characteristics like quantity and content in choosing the right ML models for microscopy applications.
  • It also discusses the uses of ML in cell biology, including data curation and prediction, while addressing challenges and risks, suggesting ways to mitigate them.
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Super-resolution structured-illumination microscopy (SIM) is a powerful technique that allows one to surpass the diffraction limit by up to a factor two. Yet, its practical use is hampered by its sensitivity to imaging conditions which makes it prone to reconstruction artefacts. In this work, we present FlexSIM, a flexible SIM reconstruction method capable to handle highly challenging data.

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Quantification of Mycobacterium tuberculosis (Mtb) growth dynamics in cell-based in vitro infection models is traditionally carried out by measurement of colony forming units (CFU). However, Mtb being an extremely slow growing organism (16-24 h doubling time), this approach requires at least 3 weeks of incubation to obtain measurable readouts. In this chapter, we describe an alternative approach based on time-lapse microscopy and quantitative image analysis that allows faster quantification of Mtb growth dynamics in host cells.

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  • A new study aims to determine how common child abuse is in sports across six European countries, focusing specifically on various types of interpersonal violence against children involved in organized sports.
  • Researchers surveyed over 10,000 young adults aged 18-30 who played sports before age 18, utilizing a questionnaire (IVACS-Q) to measure experiences of neglect, psychological violence, physical violence, and sexual violence.
  • Findings revealed high prevalence rates of violence in sports, with psychological violence being the most common (65%) and notable differences in reported experiences between males and females; this underscores the need for better prevention strategies in the sports sector.
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Solid organ transplantation represents the best (and in many cases only) treatment option for patients with end-stage organ failure. The effectiveness and functioning life of these transplants has improved each decade due to surgical and clinical advances, and accurate histocompatibility assessment. Patient exposure to alloantigen from another individual is a common occurrence and takes place through pregnancies, blood transfusions or previous transplantation.

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WDR5 is a critical chromatin cofactor of MYC. WDR5 interacts with MYC through the WBM pocket and is hypothesized to anchor MYC to chromatin through its WIN site. Blocking the interaction of WDR5 and MYC impairs the recruitment of MYC to its target genes and disrupts the oncogenic function of MYC in cancer development, thus providing a promising strategy for the treatment of MYC-dysregulated cancers.

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Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasing resolution and throughput. Artificial intelligence, deep neural networks, and machine learning are all niche terms describing computational methods that have gained a pivotal role in microscopy-based research over the past decade. This Roadmap is written collectively by prominent researchers and encompasses selected aspects of how machine learning is applied to microscopy image data, with the aim of gaining scientific knowledge by improved image quality, automated detection, segmentation, classification and tracking of objects, and efficient merging of information from multiple imaging modalities.

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Single-molecule localization microscopy (SMLM) generates data in the form of coordinates of localized fluorophores. Cluster analysis is an attractive route for extracting biologically meaningful information from such data and has been widely applied. Despite a range of cluster analysis algorithms, there exists no consensus framework for the evaluation of their performance.

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WD repeat domain 5 (WDR5) is a member of the WD40-repeat protein family that plays a critical role in multiple processes. It is also a prominent target for pharmacological inhibition in diseases such as cancer, aging, and neurodegenerative disorders. Interactions between WDR5 and various partners are essential for sustaining its function.

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Given the great importance of cobalt catalysts supported by benchmark bis(imino)pyridine in the (oligo)polymerization, a series of dibenzopyran-incorporated symmetrical 2,6-bis(imino) pyridyl cobalt complexes (-) are designed and prepared using a one-pot template approach. The structures of the resulting complexes are well characterized by a number of techniques. After activation with either methylaluminoxane (MAO) or modified MAO (MMAO), the complexes - are highly active for ethylene polymerization with a maximum activity of up to 7.

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  • Photoactivated localization microscopy (PALM) generates localization coordinates using photoactivatable fluorescent proteins, but suffers from issues like multiple blinking and localization errors, leading to false clustering in data.
  • A new 'model-based correction' (MBC) workflow enhances accuracy by estimating blinking dynamics and refining clustering, yielding more precise localization coordinates that outperform current methods.
  • The corrected data enables reliable tests for spatial randomness and quantitative analysis of fluorophore clusters, validated with simulated and experimental data, revealing clustering of an adapter protein at the T cell immunological synapse.
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Motivation: Rotated template matching is an efficient and versatile algorithm to analyze microscopy images, as it automates the detection of stereotypical structures, such as organelles that can appear at any orientation. Its performance however quickly degrades in noisy image data.

Results: We introduce Steer'n'Detect, an ImageJ plugin implementing a recently published algorithm to detect patterns of interest at any orientation with high accuracy from a single template in 2D images.

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DeepImageJ is a user-friendly solution that enables the generic use of pre-trained deep learning models for biomedical image analysis in ImageJ. The deepImageJ environment gives access to the largest bioimage repository of pre-trained deep learning models (BioImage Model Zoo). Hence, nonexperts can easily perform common image processing tasks in life-science research with deep learning-based tools including pixel and object classification, instance segmentation, denoising or virtual staining.

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All UK H&I laboratories and transplant units operate under a single national kidney offering policy, but there have been variations in approach regarding when to undertake the pre-transplant crossmatch test. In order to minimize cold ischaemia times for deceased donor kidney transplantation we sought to find ways to be able to report a crossmatch result as early as possible in the donation process. A panel of experts in transplant surgery, nephrology, specialist nursing in organ donation and H&I (all relevant UK laboratories represented) assessed evidence and opinion concerning five factors that relate to the effectiveness of the crossmatch process, as follows: when the result should be ready for reporting; what level of donor HLA typing is needed; crossmatch sample type and availability; fairness and equity; risks and patient safety.

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The avoidance of antibody-mediated rejection (AMR) attributed to human leucocyte antigen (HLA) antibody incompatibility remains an essential function of clinical Histocompatibility and Immunogenetics (H&I) laboratories who are supporting solid organ transplantation. Developments in HLA antibody identification assays over the past thirty years have greatly reduced unexpected positive cellular crossmatches and improved solid organ transplant outcomes. For sensitized patients, the decision to register unacceptable HLA antigen mismatches is often heavily influenced by results from solid phase antibody assays, particularly the Luminex Single Antigen Bead (SAB) assays, although the clinical relevance of antibodies identified solely by these assays remains unclear.

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Patient-Derived Xenografts (PDXs) are the preclinical models which best recapitulate inter- and intra-patient complexity of human breast malignancies, and are also emerging as useful tools to study the normal breast epithelium. However, data analysis generated with such models is often confounded by the presence of host cells and can give rise to data misinterpretation. For instance, it is important to discriminate between xenografted and host cells in histological sections prior to performing immunostainings.

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Platelet transfusion refractoriness results in adverse outcomes and increased health care costs. Managing refractoriness resulting from HLA alloimmunization necessitates the use of HLA antigen-matched platelets but requires a large platelet donor pool and does not guarantee full matching. We report the first randomized, double-blind, noninferiority, crossover trial comparing HLA epitope-matched (HEM) platelets with HLA standard antigen-matched (HSM) platelet transfusions.

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Circadian clocks operative in pancreatic islets participate in the regulation of insulin secretion in humans and, if compromised, in the development of type 2 diabetes (T2D) in rodents. Here we demonstrate that human islet α- and β-cells that bear attenuated clocks exhibit strongly disrupted insulin and glucagon granule docking and exocytosis. To examine whether compromised clocks play a role in the pathogenesis of T2D in humans, we quantified parameters of molecular clocks operative in human T2D islets at population, single islet, and single islet cell levels.

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Aims/objectives: To explore the impact of Human Leucocyte Antigen (HLA)-A and B epitope-matched platelets on the outcome of platelet transfusions in alloimmunised patients with aplastic anaemia (AA). The relevance of HLA-C epitope mismatches was also investigated.

Background: Patients who become immunologically refractory (IR) to random platelet transfusions can experience an adequate rise in platelet count through the provision of HLA-compatible platelets using an antigen-matching algorithm.

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In the version of this paper originally published, Figure 4a contained errors that were introduced during typesetting. The bottom 11° ThunderSTORM image is an xz view but was incorrectly labeled as xy, and the low x-axis value in the four line profiles was incorrectly set as -60 instead of -50. These errors have been corrected in the PDF and HTML versions of the paper.

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With the widespread uptake of two-dimensional (2D) and three-dimensional (3D) single-molecule localization microscopy (SMLM), a large set of different data analysis packages have been developed to generate super-resolution images. In a large community effort, we designed a competition to extensively characterize and rank the performance of 2D and 3D SMLM software packages. We generated realistic simulated datasets for popular imaging modalities-2D, astigmatic 3D, biplane 3D and double-helix 3D-and evaluated 36 participant packages against these data.

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