Atlas Toolkit: Fast registration of 3D morphological datasets in the absence of landmarks

Enhancing SEM positioning precision with a LEGO®-based sample fitting system

Scanning electron microscopy (SEM) is a precious tool in materials science and morphology sciences, enabling detailed examination of materials at the nanoscale. However, precise and accurate sample repositioning during different observation sessions remains a significant challenge, impacting the quality and repeatability of SEM analyses. This study aimed to develop and evaluate a LEGO®-based sample positioning system for SEM analysis. The system was designed to consistently identify and align features across multiple repositioning cycles, maintain accurate positioning along the z-axis, minimize distortion, and provide repeatable and reliable results. The results indicated a high degree of precision and accuracy in the repositioning process, as evidenced by the minimal displacements, deviations in scaling and shearing, and the highly significant results (p < 0.001) obtained from the analysis of absolute translations and rotations. Moreover, the analyses were consistently replicated across six repetitions, underscoring the reliability of the observed results. While the findings suggest that the LEGO-based sample positioning system is promising for enhancing SEM analyses' quality and repeatability, further studies are needed to optimize the system's design and evaluate its performance in different SEM applications. Ultimately, this study contributes to the ongoing efforts to develop cost-effective, customizable, and accurate solutions for sample positioning in SEM, contributing to the advancement of materials science research and all SEM analysis requiring overtime observations of the same sample. RESEARCH HIGHLIGHTS: This study focused on the development and evaluation of a novel LEGO-based sample positioning system specifically designed for SEM analysis. One of the standout features of this system is its ability to consistently identify and align features across multiple repositioning cycles, showcasing its precision and reliability. To further understand the mechanical aspects of the SEM stage, we employed the Rambold Kontroll comparator, which provided a baseline understanding of its mechanical tolerance. The registration process results were particularly noteworthy, as they revealed high accuracy with minimal displacements. Furthermore, the consistent outcomes observed across multiple repetitions emphasize the reliability and robustness of the methods we employed in this research.

μMatch: 3D Shape Correspondence for Biological Image Data

Modern microscopy technologies allow imaging biological objects in 3D over a wide range of spatial and temporal scales, opening the way for a quantitative assessment of morphology. However, establishing a correspondence between objects to be compared, a first necessary step of most shape analysis workflows, remains challenging for soft-tissue objects without striking features allowing them to be landmarked. To address this issue, we introduce the μMatch 3D shape correspondence pipeline. μMatch implements a state-of-the-art correspondence algorithm initially developed for computer graphics and packages it in a streamlined pipeline including tools to carry out all steps from input data pre-processing to classical shape analysis routines. Importantly, μMatch does not require any landmarks on the object surface and establishes correspondence in a fully automated manner. Our open-source method is implemented in Python and can be used to process collections of objects described as triangular meshes. We quantitatively assess the validity of μMatch relying on a well-known benchmark dataset and further demonstrate its reliability by reproducing published results previously obtained through manual landmarking.

Fijiyama: a registration tool for 3D multimodal time-lapse imaging

SUMMARY

The increasing interest of animal and plant research communities for biomedical 3D imaging devices results in the emergence of new topics. The anatomy, structure and function of tissues can be observed non-destructively in time-lapse multimodal imaging experiments by combining the outputs of imaging devices such as X-ray CT and MRI scans. However, living samples cannot remain in these devices for a long period. Manual positioning and natural growth of the living samples induce variations in the shape, position and orientation in the acquired images that require a preprocessing step of 3D registration prior to analyses. This registration step becomes more complex when combining observations from devices that highlight various tissue structures. Identifying image invariants over modalities is challenging and can result in intractable problems. Fijiyama, a Fiji plugin built upon biomedical registration algorithms, is aimed at non-specialists to facilitate automatic alignment of 3D images acquired either at successive times and/or with different imaging systems. Its versatility was assessed on four case studies combining multimodal and time series data, spanning from micro to macro scales.

AVAILABILITY AND IMPLEMENTATION

Fijiyama is an open source software (GPL license) implemented in Java. The plugin is available through the official Fiji release. An extensive documentation is available at the official page: https://imagej.github.io/Fijiyama.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The Pax6 master control gene initiates spontaneous retinal development via a self-organising Turing network

Understanding how complex organ systems are assembled from simple embryonic tissues is a major challenge. Across the animal kingdom a great diversity of visual organs are initiated by a 'master control gene' called Pax6, which is both necessary and sufficient for eye development. Yet precisely how Pax6 achieves this deeply homologous function is poorly understood. Using the chick as a model organism, we show that vertebrate Pax6 interacts with a pair of morphogen-coding genes, Tgfb2 and Fst, to form a putative Turing network, which we have computationally modelled. Computer simulations suggest that this gene network is sufficient to spontaneously polarise the developing retina, establishing the first organisational axis of the eye and prefiguring its further development. Our findings reveal how retinal self-organisation may be initiated independently of the highly ordered tissue interactions that help to assemble the eye in vivo These results help to explain how stem cell aggregates spontaneously self-organise into functional eye-cups in vitro We anticipate these findings will help to underpin retinal organoid technology, which holds much promise as a platform for disease modelling, drug development and regenerative therapies.

Multimodal assessments of Zika virus immune pathophysiological responses in marmosets

Animal models that recapitulate the human pathophysiology have been developed as useful research tools. Although laboratory mice are widely used, they are phylogenetically “distant” to humans. New world monkeys, such as the common marmoset (Callithrix jacchus) have steadily gained prominence. In this report, marmosets are explored as an alternate in vivo model to investigate infection and immunity of Zika virus (ZIKV). Multimodal platforms, including ultrasound and magnetic resonance imaging (MRI), flow cytometry, and multiplex microbead immunoassays were established to comprehensively decipher immune responses and pathophysiological outcomes. While ZIKV-infected marmosets had detectable ZIKV RNA load in various body fluids, animals did not develop any observable lesions in their testes and brains as shown by ultrasound and MRI. Immune-phenotyping detected differences in the numbers of B cells, CD8+ T cells and HLADR+ NK cells during the first two weeks of infection. Neutralizing ZIKV-specific antibodies were elicited to high levels and targeted epitopes in the E protein. This study presents a one-stop-shop platform to study infection and pathophysiology in marmosets. While marmoset-specific research tools are being refined, the research values of these animals present them as a good model for immune-based therapies.

The Early Stages of Heart Development: Insights from Chicken Embryos

The heart is the first functioning organ in the developing embryo and a detailed understanding of the molecular and cellular mechanisms involved in its formation provides insights into congenital malformations affecting its function and therefore the survival of the organism. Because many developmental mechanisms are highly conserved, it is possible to extrapolate from observations made in invertebrate and vertebrate model organisms to humans. This review will highlight the contributions made through studying heart development in avian embryos, particularly the chicken. The major advantage of chick embryos is their accessibility for surgical manipulation and functional interference approaches, both gain- and loss-of-function. In addition to experiments performed in ovo, the dissection of tissues for ex vivo culture, genomic, or biochemical approaches is straightforward. Furthermore, embryos can be cultured for time-lapse imaging, which enables tracking of fluorescently labeled cells and detailed analysis of tissue morphogenesis. Owing to these features, investigations in chick embryos have led to important discoveries, often complementing genetic studies in mice and zebrafish. As well as including some historical aspects, we cover here some of the crucial advances made in understanding early heart development using the chicken model.