bia-binder: A web-native cloud compute service for the bioimage analysis community.

We introduce bia-binder (BioImage Archive Binder), an open-source, cloud-architectured, and web-based coding environment tailored to bioimage analysis that is freely accessible to all researchers. The service generates easy-to-use Jupyter Notebook coding environments hosted on EMBL-EBI's Embassy Cloud, which provides significant computational resources. The bia-binder architecture is free, open-source and publicly available for deployment.

A spatial human thymus cell atlas mapped to a continuous tissue axis.

T cells develop from circulating precursor cells, which enter the thymus and migrate through specialized subcompartments that support their maturation and selection. In humans, this process starts in early fetal development and is highly active until thymic involution in adolescence. To map the microanatomical underpinnings of this process in pre- and early postnatal stages, we established a quantitative morphological framework for the thymus-the Cortico-Medullary Axis-and used it to perform a spatially resolved analysis.

Making the most of bioimaging data through interdisciplinary interactions.

The increasing technical complexity of all aspects involving bioimages, ranging from their acquisition to their analysis, has led to a diversification in the expertise of scientists engaged at the different stages of the discovery process. Although this diversity of profiles comes with the major challenge of establishing fruitful interdisciplinary collaboration, such collaboration also offers a superb opportunity for scientific discovery. In this Perspective, we review the different actors within the bioimaging research universe and identify the primary obstacles that hinder their interactions.

A spatial human thymus cell atlas mapped to a continuous tissue axis.

T cells develop from circulating precursors, which enter the thymus and migrate throughout specialised sub-compartments to support maturation and selection. This process starts already in early fetal development and is highly active until the involution of the thymus in adolescence. To map the micro-anatomical underpinnings of this process in pre- vs.

Simulating structurally variable nuclear pore complexes for microscopy.

Motivation: The nuclear pore complex (NPC) is the only passageway for macromolecules between nucleus and cytoplasm, and an important reference standard in microscopy: it is massive and stereotypically arranged. The average architecture of NPC proteins has been resolved with pseudoatomic precision, however observed NPC heterogeneities evidence a high degree of divergence from this average. Single-molecule localization microscopy (SMLM) images NPCs at protein-level resolution, whereupon image analysis software studies NPC variability.

Embryo-uterine interaction coordinates mouse embryogenesis during implantation.

Embryo implantation into the uterus marks a key transition in mammalian development. In mice, implantation is mediated by the trophoblast and is accompanied by a morphological transition from the blastocyst to the egg cylinder. However, the roles of trophoblast-uterine interactions in embryo morphogenesis during implantation are poorly understood due to inaccessibility in utero and the remaining challenges to recapitulate it ex vivo from the blastocyst.

A biologist's guide to planning and performing quantitative bioimaging experiments.

Technological advancements in biology and microscopy have empowered a transition from bioimaging as an observational method to a quantitative one. However, as biologists are adopting quantitative bioimaging and these experiments become more complex, researchers need additional expertise to carry out this work in a rigorous and reproducible manner. This Essay provides a navigational guide for experimental biologists to aid understanding of quantitative bioimaging from sample preparation through to image acquisition, image analysis, and data interpretation.

Made to measure: An introduction to quantifying microscopy data in the life sciences.

Images are at the core of most modern biological experiments and are used as a major source of quantitative information. Numerous algorithms are available to process images and make them more amenable to be measured. Yet the nature of the quantitative output that is useful for a given biological experiment is uniquely dependent upon the question being investigated.

MorphoFeatures for unsupervised exploration of cell types, tissues, and organs in volume electron microscopy.

Electron microscopy (EM) provides a uniquely detailed view of cellular morphology, including organelles and fine subcellular ultrastructure. While the acquisition and (semi-)automatic segmentation of multicellular EM volumes are now becoming routine, large-scale analysis remains severely limited by the lack of generally applicable pipelines for automatic extraction of comprehensive morphological descriptors. Here, we present a novel unsupervised method for learning cellular morphology features directly from 3D EM data: a neural network delivers a representation of cells by shape and ultrastructure.

Steer'n'Detect: fast 2D template detection with accurate orientation estimation.

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.

Deep learning for bioimage analysis in developmental biology.

Deep learning has transformed the way large and complex image datasets can be processed, reshaping what is possible in bioimage analysis. As the complexity and size of bioimage data continues to grow, this new analysis paradigm is becoming increasingly ubiquitous. In this Review, we begin by introducing the concepts needed for beginners to understand deep learning.

REMBI: Recommended Metadata for Biological Images-enabling reuse of microscopy data in biology.

Bioimaging data have significant potential for reuse, but unlocking this potential requires systematic archiving of data and metadata in public databases. We propose draft metadata guidelines to begin addressing the needs of diverse communities within light and electron microscopy. We hope this publication and the proposed Recommended Metadata for Biological Images (REMBI) will stimulate discussions about their implementation and future extension.

Principled Design and Implementation of Steerable Detectors.

We provide a complete pipeline for the detection of patterns of interest in an image. In our approach, the patterns are assumed to be adequately modeled by a known template, and are located at unknown positions and orientations that we aim at retrieving. We propose a continuous-domain additive image model, where the analyzed image is the sum of the patterns to localize and a background with self-similar isotropic power-spectrum.

Impact of psychiatric distress and physical disability on quality of life in neuromyelitis optica spectrum disorder and chronic autoimmune demyelinating polyneuropathies.

Background: Determinants of quality of life (QoL) in demyelinating disorders have been investigated predominantly for multiple sclerosis, especially with regard to "soft clinical signs" such as psychiatric distress. In this exploratory study, we aimed to identify common determinants of QoL for both central and peripheral demyelination in the understudied disease entities of neuromyelitis optica spectrum disorder (NMOSD) and chronic autoimmune demyelinating polyneuropathy (CADP).

Methods: 20 NMOSD and 16 CADP patients were evaluated for physical disability (EDSS and INCAT ODSS), cognitive dysfunction (neuropsychological test battery), psychiatric distress (SCL-90-R), depression (BDI), fatigue (FSMC) and quality of life (EQ-5D-3 L).

Support and approximation properties of Hermite splines.

In this paper, we formally investigate two mathematical aspects of Hermite splines that are relevant to practical applications. We first demonstrate that Hermite splines are maximally localized, in the sense that the size of their support is minimal among pairs of functions with identical reproduction properties. Then, we precisely quantify the approximation power of Hermite splines for the reconstruction of functions and their derivatives.

Patients with chronic autoimmune demyelinating polyneuropathies exhibit cognitive deficits which might be associated with CSF evidence of blood-brain barrier disturbance.

Background: Chronic autoimmune demyelinating polyneuropathies (CADP) result in impaired sensorimotor function. However, anecdotal clinical observations suggest the development of cognitive deficits during the course of disease.

Methods: We tested 16 patients with CADP (11 patients with chronic inflammatory demyelinating polyneuropathy, 4 patients with multifocal motor neuropathy and 1 patient with multifocal acquired demyelinating sensory and motor neuropathy) and 40 healthy controls (HC) with a neuropsychological test battery.

Supervised learning to quantify amyloidosis in whole brains of an Alzheimer's disease mouse model acquired with optical projection tomography.

Alzheimer's disease (AD) is characterized by amyloidosis of brain tissues. This phenomenon is studied with genetically-modified mouse models. We propose a method to quantify amyloidosis in whole 5xFAD mouse brains, a model of AD.

Multimodal imaging and high-throughput image-processing for drug screening on living organisms on-chip.

A major step for the validation of medical drugs is the screening on whole organisms, which gives the systemic information that is missing when using cellular models. Caenorhabditis elegans is a soil worm that catches the interest of researchers who study systemic physiopathology (e.g.

DiversePathsJ: diverse shortest paths for bioimage analysis.

Motivation: We introduce a formulation for the general task of finding diverse shortest paths between two end-points. Our approach is not linked to a specific biological problem and can be applied to a large variety of images thanks to its generic implementation as a user-friendly ImageJ/Fiji plugin. It relies on the introduction of additional layers in a Viterbi path graph, which requires slight modifications to the standard Viterbi algorithm rules.

FlyLimbTracker: An active contour based approach for leg segment tracking in unmarked, freely behaving Drosophila.

Understanding the biological underpinnings of movement and action requires the development of tools for quantitative measurements of animal behavior. Drosophila melanogaster provides an ideal model for developing such tools: the fly has unparalleled genetic accessibility and depends on a relatively compact nervous system to generate sophisticated limbed behaviors including walking, reaching, grooming, courtship, and boxing. Here we describe a method that uses active contours to semi-automatically track body and leg segments from video image sequences of unmarked, freely behaving D.

Multiresolution Subdivision Snakes.

We present a new family of snakes that satisfy the property of multiresolution by exploiting subdivision schemes. We show in a generic way how to construct such snakes based on an admissible subdivision mask. We derive the necessary energy formulations and provide the formulas for their efficient computation.

Hermite Snakes With Control of Tangents.

We introduce a new model of parametric contours defined in a continuous fashion. Our curve model relies on Hermite spline interpolation and can easily generate curves with sharp discontinuities; it also grants direct access to the tangent at each location. With these two features, the Hermite snake distinguishes itself from classical spline-snake models and allows one to address certain bioimaging problems in a more efficient way.