The Cell Tracking Challenge is an ongoing benchmarking initiative that has become a reference in cell segmentation and tracking algorithm development. Here, we present a significant number of improvements introduced in the challenge since our 2017 report. These include the creation of a new segmentation-only benchmark, the enrichment of the dataset repository with new datasets that increase its diversity and complexity, and the creation of a silver standard reference corpus based on the most competitive results, which will be of particular interest for data-hungry deep learning-based strategies. Furthermore, we present the up-to-date cell segmentation and tracking leaderboards, an in-depth analysis of the relationship between the performance of the state-of-the-art methods and the properties of the datasets and annotations, and two novel, insightful studies about the generalizability and the reusability of top-performing methods. These studies provide critical practical conclusions for both developers and users of traditional and machine learning-based cell segmentation and tracking algorithms.
Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing.
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- big data * MeSH
- glioblastom * MeSH
- lidé MeSH
- šíření informací MeSH
- strojové učení MeSH
- vzácné nemoci MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- Research Support, N.I.H., Extramural MeSH
New approaches in regenerative medicine and vasculogenesis have generated a demand for sufficient numbers of human endothelial cells (ECs). ECs and their progenitors reside on the interior surface of blood and lymphatic vessels or circulate in peripheral blood; however, their numbers are limited, and they are difficult to expand after isolation. Recent advances in human induced pluripotent stem cell (hiPSC) research have opened possible avenues to generate unlimited numbers of ECs from easily accessible cell sources, such as the peripheral blood. In this study, we reprogrammed peripheral blood mononuclear cells, human umbilical vein endothelial cells (HUVECs), and human saphenous vein endothelial cells (HSVECs) into hiPSCs and differentiated them into ECs. The phenotype profiles, functionality, and genome stability of all hiPSC-derived ECs were assessed and compared with HUVECs and HSVECs. hiPSC-derived ECs resembled their natural EC counterparts, as shown by the expression of the endothelial surface markers CD31 and CD144 and the results of the functional analysis. Higher expression of endothelial progenitor markers CD34 and kinase insert domain receptor (KDR) was measured in hiPSC-derived ECs. An analysis of phosphorylated histone H2AX (γH2AX) foci revealed that an increased number of DNA double-strand breaks upon reprogramming into pluripotent cells. However, differentiation into ECs restored a normal number of γH2AX foci. Our hiPSCs retained a normal karyotype, with the exception of the HSVEC-derived hiPSC line, which displayed mosaicism due to a gain of chromosome 1. Peripheral blood from adult donors is a suitable source for the unlimited production of patient-specific ECs through the hiPSC interstage. hiPSC-derived ECs are fully functional and comparable to natural ECs. The protocol is eligible for clinical applications in regenerative medicine, if the genomic stability of the pluripotent cell stage is closely monitored.
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- biologické markery metabolismus MeSH
- buněčná diferenciace fyziologie MeSH
- endoteliální buňky pupečníkové žíly (lidské) cytologie metabolismus MeSH
- endoteliální buňky cytologie metabolismus MeSH
- fibroblasty cytologie metabolismus MeSH
- fyziologická neovaskularizace fyziologie MeSH
- indukované pluripotentní kmenové buňky cytologie metabolismus MeSH
- kultivované buňky MeSH
- leukocyty mononukleární cytologie metabolismus MeSH
- lidé MeSH
- regenerativní lékařství metody MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Ribosomal RNA genes (rDNA) have been used as valuable experimental systems in numerous studies. Here, we focus on elucidating the spatiotemporal organisation of rDNA replication in Arabidopsis thaliana To determine the subnuclear distribution of rDNA and the progression of its replication during the S phase, we apply 5-ethynyl-2'-deoxyuridine (EdU) labelling, fluorescence-activated cell sorting, fluorescence in situ hybridization and structured illumination microscopy. We show that rDNA is replicated inside and outside the nucleolus, where active transcription occurs at the same time. Nascent rDNA shows a maximum of nucleolar associations during early S phase. In addition to EdU patterns typical for early or late S phase, we describe two intermediate EdU profiles characteristic for mid S phase. Moreover, the use of lines containing mutations in the chromatin assembly factor-1 gene fas1 and wild-type progeny of fas1xfas2 crosses depleted of inactive copies allows for selective observation of the replication pattern of active rDNA. High-resolution data are presented, revealing the culmination of replication in the mid S phase in the nucleolus and its vicinity. Taken together, our results provide a detailed snapshot of replication of active and inactive rDNA during S phase progression.
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- Arabidopsis cytologie genetika MeSH
- buněčné jadérko metabolismus MeSH
- deoxyuridin analogy a deriváty metabolismus MeSH
- genetická transkripce MeSH
- kořeny rostlin metabolismus MeSH
- replikace DNA genetika MeSH
- ribozomální DNA genetika MeSH
- S fáze genetika MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Cell-autonomous induction of type I interferon must be stringently regulated. Rapid induction is key to control virus infection, whereas proper limitation of signaling is essential to prevent immunopathology and autoimmune disease. Using unbiased kinome-wide RNAi screening followed by thorough validation, we identified 22 factors that regulate RIG-I/IRF3 signaling activity. We describe a negative-feedback mechanism targeting RIG-I activity, which is mediated by death associated protein kinase 1 (DAPK1). RIG-I signaling triggers DAPK1 kinase activation, and active DAPK1 potently inhibits RIG-I stimulated IRF3 activity and interferon-beta production. DAPK1 phosphorylates RIG-I in vitro at previously reported as well as other sites that limit 5'ppp-dsRNA sensing and virtually abrogate RIG-I activation.
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- buňky A549 MeSH
- fosforylace MeSH
- HEK293 buňky MeSH
- kultivované buňky MeSH
- lidé MeSH
- malá interferující RNA genetika MeSH
- myši MeSH
- proteinkinasy asociované se smrtí metabolismus MeSH
- proteinkinasy metabolismus MeSH
- receptory kyseliny retinové metabolismus MeSH
- signální transdukce MeSH
- zpětná vazba fyziologická MeSH
- zvířata MeSH
- Check Tag
- lidé MeSH
- myši MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
Tracking motile cells in time-lapse series is challenging and is required in many biomedical applications. Cell tracks can be mathematically represented as acyclic oriented graphs. Their vertices describe the spatio-temporal locations of individual cells, whereas the edges represent temporal relationships between them. Such a representation maintains the knowledge of all important cellular events within a captured field of view, such as migration, division, death, and transit through the field of view. The increasing number of cell tracking algorithms calls for comparison of their performance. However, the lack of a standardized cell tracking accuracy measure makes the comparison impracticable. This paper defines and evaluates an accuracy measure for objective and systematic benchmarking of cell tracking algorithms. The measure assumes the existence of a ground-truth reference, and assesses how difficult it is to transform a computed graph into the reference one. The difficulty is measured as a weighted sum of the lowest number of graph operations, such as split, delete, and add a vertex and delete, add, and alter the semantics of an edge, needed to make the graphs identical. The measure behavior is extensively analyzed based on the tracking results provided by the participants of the first Cell Tracking Challenge hosted by the 2013 IEEE International Symposium on Biomedical Imaging. We demonstrate the robustness and stability of the measure against small changes in the choice of weights for diverse cell tracking algorithms and fluorescence microscopy datasets. As the measure penalizes all possible errors in the tracking results and is easy to compute, it may especially help developers and analysts to tune their algorithms according to their needs.
Reliable 3D detection of diffraction-limited spots in fluorescence microscopy images is an important task in subcellular observation. Generally, fluorescence microscopy images are heavily degraded by noise and non-specifically stained background, making reliable detection a challenging task. In this work, we have studied the performance and parameter sensitivity of eight recent methods for 3D spot detection. The study is based on both 3D synthetic image data and 3D real confocal microscopy images. The synthetic images were generated using a simulator modeling the complete imaging setup, including the optical path as well as the image acquisition process. We studied the detection performance and parameter sensitivity under different noise levels and under the influence of uneven background signal. To evaluate the parameter sensitivity, we propose a novel measure based on the gradient magnitude of the F1 score. We measured the success rate of the individual methods for different types of the image data and found that the type of image degradation is an important factor. Using the F1 score and the newly proposed sensitivity measure, we found that the parameter sensitivity is not necessarily proportional to the success rate of a method. This also provided an explanation why the best performing method for synthetic data was outperformed by other methods when applied to the real microscopy images. On the basis of the results obtained, we conclude with the recommendation of the HDome method for data with relatively low variations in quality, or the Sorokin method for image sets in which the quality varies more. We also provide alternative recommendations for high-quality images, and for situations in which detailed parameter tuning might be deemed expensive.
Aberrant fibroblast growth factor (FGF) signaling disturbs chondrocyte differentiation in skeletal dysplasia, but the mechanisms underlying this process remain unclear. Recently, FGF was found to activate canonical WNT/β-catenin pathway in chondrocytes via Erk MAP kinase-mediated phosphorylation of WNT co-receptor Lrp6. Here, we explore the cellular consequences of such a signaling interaction. WNT enhanced the FGF-mediated suppression of chondrocyte differentiation in mouse limb bud micromass and limb organ cultures, leading to inhibition of cartilage nodule formation in micromass cultures, and suppression of growth in cultured limbs. Simultaneous activation of the FGF and WNT/β-catenin pathways resulted in loss of chondrocyte extracellular matrix, expression of genes typical for mineralized tissues and alteration of cellular shape. WNT enhanced the FGF-mediated downregulation of chondrocyte proteoglycan and collagen extracellular matrix via inhibition of matrix synthesis and induction of proteinases involved in matrix degradation. Expression of genes regulating RhoA GTPase pathway was induced by FGF in cooperation with WNT, and inhibition of the RhoA signaling rescued the FGF/WNT-mediated changes in chondrocyte cellular shape. Our results suggest that aberrant FGF signaling cooperates with WNT/β-catenin in suppression of chondrocyte differentiation.
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- beta-katenin genetika metabolismus MeSH
- biologické modely MeSH
- buněčná diferenciace účinky léků genetika MeSH
- chondrocyty účinky léků metabolismus MeSH
- chrupavka cytologie účinky léků metabolismus MeSH
- fibroblastové růstové faktory farmakologie MeSH
- fibroblastový růstový faktor 2 farmakologie MeSH
- HEK293 buňky MeSH
- končetinové pupeny účinky léků embryologie metabolismus MeSH
- konfokální mikroskopie MeSH
- krysa rodu rattus MeSH
- kultivované buňky MeSH
- LDL receptor related protein 6 genetika metabolismus MeSH
- lidé MeSH
- nádorové buněčné linie MeSH
- polymerázová řetězová reakce s reverzní transkripcí MeSH
- protein Wnt3A farmakologie MeSH
- proteiny Wnt genetika metabolismus farmakologie MeSH
- receptory fibroblastových růstových faktorů genetika metabolismus MeSH
- signální transdukce účinky léků genetika MeSH
- synergismus léků MeSH
- transkriptom účinky léků genetika MeSH
- western blotting MeSH
- zvířata MeSH
- Check Tag
- krysa rodu rattus MeSH
- lidé MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
MOTIVATION: Automatic tracking of cells in multidimensional time-lapse fluorescence microscopy is an important task in many biomedical applications. A novel framework for objective evaluation of cell tracking algorithms has been established under the auspices of the IEEE International Symposium on Biomedical Imaging 2013 Cell Tracking Challenge. In this article, we present the logistics, datasets, methods and results of the challenge and lay down the principles for future uses of this benchmark. RESULTS: The main contributions of the challenge include the creation of a comprehensive video dataset repository and the definition of objective measures for comparison and ranking of the algorithms. With this benchmark, six algorithms covering a variety of segmentation and tracking paradigms have been compared and ranked based on their performance on both synthetic and real datasets. Given the diversity of the datasets, we do not declare a single winner of the challenge. Instead, we present and discuss the results for each individual dataset separately. AVAILABILITY AND IMPLEMENTATION: The challenge Web site (http://www.codesolorzano.com/celltrackingchallenge) provides access to the training and competition datasets, along with the ground truth of the training videos. It also provides access to Windows and Linux executable files of the evaluation software and most of the algorithms that competed in the challenge.
