The rapid increase in lipidomic studies has led to a collaborative effort within the community to establish standards and criteria for producing, documenting, and disseminating data. Creating a dynamic easy-to-use checklist that condenses key information about lipidomic experiments into common terminology will enhance the field's consistency, comparability, and repeatability. Here, we describe the structure and rationale of the established Lipidomics Minimal Reporting Checklist to increase transparency in lipidomics research.
It is so far unclear how the COVID-19 winter waves started and what should be done to prevent possible future waves. In this study, we deciphered the dynamic course of a winter wave in 2021 in Saxony, a state in Eastern Germany neighbouring the Czech Republic and Poland. The study was carried out through the integration of multiple virus genomic epidemiology approaches to track transmission chains, identify emerging variants and investigate dynamic changes in transmission clusters. For identified local variants of interest, functional evaluations were performed. Multiple long-lasting community transmission clusters have been identified acting as driving force for the winter wave 2021. Analysis of the dynamic courses of two representative clusters indicated a similar transmission pattern. However, the transmission cluster caused by a locally occurring new Delta variant AY.36.1 showed a distinct transmission pattern, and functional analyses revealed a replication advantage of it. This study indicated that long-lasting community transmission clusters starting since early autumn caused by imported or locally occurring variants all contributed to the development of the 2021 winter wave. The information we achieved might help future pandemic prevention.
- MeSH
- COVID-19 * epidemiologie přenos virologie MeSH
- lidé MeSH
- roční období * MeSH
- SARS-CoV-2 * genetika MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Německo MeSH
Progress in mass spectrometry lipidomics has led to a rapid proliferation of studies across biology and biomedicine. These generate extremely large raw datasets requiring sophisticated solutions to support automated data processing. To address this, numerous software tools have been developed and tailored for specific tasks. However, for researchers, deciding which approach best suits their application relies on ad hoc testing, which is inefficient and time consuming. Here we first review the data processing pipeline, summarizing the scope of available tools. Next, to support researchers, LIPID MAPS provides an interactive online portal listing open-access tools with a graphical user interface. This guides users towards appropriate solutions within major areas in data processing, including (1) lipid-oriented databases, (2) mass spectrometry data repositories, (3) analysis of targeted lipidomics datasets, (4) lipid identification and (5) quantification from untargeted lipidomics datasets, (6) statistical analysis and visualization, and (7) data integration solutions. Detailed descriptions of functions and requirements are provided to guide customized data analysis workflows.
Cortical projection neurons polarize and form an axon while migrating radially. Even though these dynamic processes are closely interwoven, they are regulated separately-the neurons terminate their migration when reaching their destination, the cortical plate, but continue to grow their axons. Here, we show that in rodents, the centrosome distinguishes these processes. Newly developed molecular tools modulating centrosomal microtubule nucleation combined with in vivo imaging uncovered that dysregulation of centrosomal microtubule nucleation abrogated radial migration without affecting axon formation. Tightly regulated centrosomal microtubule nucleation was required for periodic formation of the cytoplasmic dilation at the leading process, which is essential for radial migration. The microtubule nucleating factor γ-tubulin decreased at neuronal centrosomes during the migratory phase. As distinct microtubule networks drive neuronal polarization and radial migration, this provides insight into how neuronal migratory defects occur without largely affecting axonal tracts in human developmental cortical dysgeneses, caused by mutations in γ-tubulin.
- MeSH
- axony metabolismus MeSH
- centrozom MeSH
- lidé MeSH
- mikrotubuly metabolismus MeSH
- mozek metabolismus MeSH
- neurony * fyziologie MeSH
- tubulin * metabolismus MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- MeSH
- hmotnostní spektrometrie MeSH
- kontrolní seznam * MeSH
- lipidomika * MeSH
- metabolismus lipidů MeSH
- Publikační typ
- časopisecké články MeSH
Automatic detection and segmentation of biological objects in 2D and 3D image data is central for countless biomedical research questions to be answered. While many existing computational methods are used to reduce manual labeling time, there is still a huge demand for further quality improvements of automated solutions. In the natural image domain, spatial embedding-based instance segmentation methods are known to yield high-quality results, but their utility to biomedical data is largely unexplored. Here we introduce EmbedSeg, an embedding-based instance segmentation method designed to segment instances of desired objects visible in 2D or 3D biomedical image data. We apply our method to four 2D and seven 3D benchmark datasets, showing that we either match or outperform existing state-of-the-art methods. While the 2D datasets and three of the 3D datasets are well known, we have created the required training data for four new 3D datasets, which we make publicly available online. Next to performance, also usability is important for a method to be useful. Hence, EmbedSeg is fully open source (https://github.com/juglab/EmbedSeg), offering (i) tutorial notebooks to train EmbedSeg models and use them to segment object instances in new data, and (ii) a napari plugin that can also be used for training and segmentation without requiring any programming experience. We believe that this renders EmbedSeg accessible to virtually everyone who requires high-quality instance segmentations in 2D or 3D biomedical image data.
- MeSH
- algoritmy * MeSH
- lidé MeSH
- mikroskopie * metody MeSH
- počítačové zpracování obrazu metody MeSH
- zobrazování trojrozměrné metody MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
For decades, biologists have relied on software to visualize and interpret imaging data. As techniques for acquiring images increase in complexity, resulting in larger multidimensional datasets, imaging software must adapt. ImageJ is an open-source image analysis software platform that has aided researchers with a variety of image analysis applications, driven mainly by engaged and collaborative user and developer communities. The close collaboration between programmers and users has resulted in adaptations to accommodate new challenges in image analysis that address the needs of ImageJ's diverse user base. ImageJ consists of many components, some relevant primarily for developers and a vast collection of user-centric plugins. It is available in many forms, including the widely used Fiji distribution. We refer to this entire ImageJ codebase and community as the ImageJ ecosystem. Here we review the core features of this ecosystem and highlight how ImageJ has responded to imaging technology advancements with new plugins and tools in recent years. These plugins and tools have been developed to address user needs in several areas such as visualization, segmentation, and tracking of biological entities in large, complex datasets. Moreover, new capabilities for deep learning are being added to ImageJ, reflecting a shift in the bioimage analysis community towards exploiting artificial intelligence. These new tools have been facilitated by profound architectural changes to the ImageJ core brought about by the ImageJ2 project. Therefore, we also discuss the contributions of ImageJ2 to enhancing multidimensional image processing and interoperability in the ImageJ ecosystem.
- MeSH
- lidé MeSH
- lipidomika * MeSH
- metabolomika * MeSH
- řízení kvality MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- dopisy MeSH
- komentáře MeSH
- práce podpořená grantem MeSH
- Research Support, N.I.H., Extramural MeSH
Constriction of the cytokinetic ring, a circular structure of actin filaments, is an essential step during cell division. Mechanical forces driving the constriction are attributed to myosin motor proteins, which slide actin filaments along each other. However, in multiple organisms, ring constriction has been reported to be myosin independent. How actin rings constrict in the absence of motor activity remains unclear. Here, we demonstrate that anillin, a non-motor actin crosslinker, indispensable during cytokinesis, autonomously propels the contractility of actin bundles. Anillin generates contractile forces of tens of pico-Newtons to maximise the lengths of overlaps between bundled actin filaments. The contractility is enhanced by actin disassembly. When multiple actin filaments are arranged into a ring, this contractility leads to ring constriction. Our results indicate that passive actin crosslinkers can substitute for the activity of molecular motors to generate contractile forces in a variety of actin networks, including the cytokinetic ring.
- MeSH
- aktiny metabolismus MeSH
- aktomyosin metabolismus MeSH
- buněčné dělení MeSH
- cytokineze MeSH
- Drosophila melanogaster metabolismus MeSH
- kontraktilní proteiny genetika metabolismus MeSH
- lidé MeSH
- mikrofilamenta metabolismus MeSH
- mikrofilamentové proteiny MeSH
- myosiny metabolismus MeSH
- zvířata MeSH
- Check Tag
- lidé MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Neocortex expansion during human evolution provides a basis for our enhanced cognitive abilities. Yet, which genes implicated in neocortex expansion are actually responsible for higher cognitive abilities is unknown. The expression of human-specific ARHGAP11B in embryonic/foetal mouse, ferret and marmoset neocortex was previously found to promote basal progenitor proliferation, upper-layer neuron generation and neocortex expansion during development, features commonly thought to contribute to increased cognitive abilities. However, a key question is whether this phenotype persists into adulthood and if so, whether cognitive abilities are indeed increased. Here, we generated a transgenic mouse line with physiological ARHGAP11B expression that exhibits increased neocortical size and upper-layer neuron numbers persisting into adulthood. Adult ARHGAP11B-transgenic mice showed altered neurobehaviour, notably increased memory flexibility and a reduced anxiety level. Our data are consistent with the notion that neocortex expansion by ARHGAP11B, a gene implicated in human evolution, underlies some of the altered neurobehavioural features observed in the transgenic mice, such as the increased memory flexibility, a neocortex-associated trait, with implications for the increase in cognitive abilities during human evolution.
- MeSH
- biologická evoluce MeSH
- kognice fyziologie MeSH
- lidé MeSH
- myši inbrední C57BL MeSH
- myši transgenní MeSH
- myši MeSH
- neokortex metabolismus fyziologie MeSH
- neurogeneze fyziologie MeSH
- neurony metabolismus fyziologie MeSH
- paměť fyziologie MeSH
- proliferace buněk fyziologie MeSH
- proteiny aktivující GTPasu metabolismus MeSH
- úzkost metabolismus patofyziologie MeSH
- zvířata MeSH
- Check Tag
- lidé MeSH
- mužské pohlaví MeSH
- myši MeSH
- ženské pohlaví MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
