Multicut Algorithms for Neurite Segmentation

Correlation clustering, or multicut partitioning is widely used for image segmentation and graph partitioning. Given an undirected edge weighted graph with positive and negative weights, correlation clustering partitions the graph such that the sum of cut edge weights is minimized. Since the optimal number of clusters is automatically chosen, multicut partitioning is well suited for clustering neural structures in EM connectomics datasets where the optimal number of clusters is unknown a-priori. Due to the NP-hardness of optimizing the multicut objective, exact solvers do not scale and approximative solvers often give unsatisfactory results. In chapter 2 we investigate scalable methods for correlation clustering. To this end we define fusion moves for the multicut objective function which iteratively fuses the current and a proposed partitioning and monotonously improves the partitioning. Fusion moves scale to larger datasets, give near optimal solutions and at the same time show state of the art anytime performance. In chapter 3 we generalize the fusion moves frameworks for the lifted multicut ob- jective, a generalization of the multicut objective which can penalize or reward all decompositions of a graph for which any given pair of nodes are in distinct compo- nents. The proposed framework scales well to large datasets and has a cutting edge anytime performance. In chapter 4 we propose a framework for automatic segmentation of neural structures in 3D EM connectomics data where a membrane probability is predicted for each pixel with a neural network and superpixels are computed based on this probability map. Finally the superpixels are merged to neurites using the techniques described in chapter 3. The proposed pipeline is validated with an extensive set of experiments and a detailed lesion study. This work substantially narrows the accuracy gap between humans and computers for neurite segmentation. In chapter 5 we summarize the software written for this thesis. The provided imple- mentations for algorithms and techniques described in chapters 2 to 4 and many other algorithms resulted in a software library for graph partitioning, image segmentation and discrete optimization

A Generalized Framework for Agglomerative Clustering of Signed Graphs applied to Instance Segmentation

We propose a novel theoretical framework that generalizes algorithms for hierarchical agglomerative clustering to weighted graphs with both attractive and repulsive interactions between the nodes. This framework defines GASP, a Generalized Algorithm for Signed graph Partitioning, and allows us to explore many combinations of different linkage criteria and cannot-link constraints. We prove the equivalence of existing clustering methods to some of those combinations, and introduce new algorithms for combinations which have not been studied. An extensive comparison is performed to evaluate properties of the clustering algorithms in the context of instance segmentation in images, including robustness to noise and efficiency. We show how one of the new algorithms proposed in our framework outperforms all previously known agglomerative methods for signed graphs, both on the competitive CREMI 2016 EM segmentation benchmark and on the CityScapes dataset.Comment: 19 pages, 8 figures, 6 table

ilastik: interactive machine learning for (bio)image analysis

We present ilastik, an easy-to-use interactive tool that brings machine-learning-based (bio)image analysis to end users without substantial computational expertise. It contains pre-defined workflows for image segmentation, object classification, counting and tracking. Users adapt the workflows to the problem at hand by interactively providing sparse training annotations for a nonlinear classifier. ilastik can process data in up to five dimensions (3D, time and number of channels). Its computational back end runs operations on-demand wherever possible, allowing for interactive prediction on data larger than RAM. Once the classifiers are trained, ilastik workflows can be applied to new data from the command line without further user interaction. We describe all ilastik workflows in detail, including three case studies and a discussion on the expected performance

Negative Regulation of Bone Formation by the Transmembrane Wnt Antagonist Kremen-2

Wnt signalling is a key pathway controlling bone formation in mice and humans. One of the regulators of this pathway is Dkk1, which antagonizes Wnt signalling through the formation of a ternary complex with the transmembrane receptors Krm1/2 and Lrp5/6, thereby blocking the induction of Wnt signalling by the latter ones. Here we show that Kremen-2 (Krm2) is predominantly expressed in bone, and that its osteoblast-specific over-expression in transgenic mice (Col1a1-Krm2) results in severe osteoporosis. Histomorphometric analysis revealed that osteoblast maturation and bone formation are disturbed in Col1a1-Krm2 mice, whereas bone resorption is increased. In line with these findings, primary osteoblasts derived from Col1a1-Krm2 mice display a cell-autonomous differentiation defect, impaired canonical Wnt signalling and decreased production of the osteoclast inhibitory factor Opg. To determine whether the observed effects of Krm2 on bone remodeling are physiologically relevant, we analyzed the skeletal phenotype of 24 weeks old Krm2-deficient mice and observed high bone mass caused by a more than three-fold increase in bone formation. Taken together, these data identify Krm2 as a regulator of bone remodeling and raise the possibility that antagonizing KRM2 might prove beneficial in patients with bone loss disorders

CERT1 mutations perturb human development by disrupting sphingolipid homeostasis

Neural differentiation, synaptic transmission, and action potential propagation depend on membrane sphingolipids, whose metabolism is tightly regulated. Mutations in the ceramide transporter CERT (CERT1), which is involved in sphingolipid biosynthesis, are associated with intellectual disability, but the pathogenic mechanism remains obscure. Here, we characterize 31 individuals with de novo missense variants in CERT1. Several variants fall into a previously uncharacterized dimeric helical domain that enables CERT homeostatic inactivation, without which sphingolipid production goes unchecked. The clinical severity reflects the degree to which CERT autoregulation is disrupted, and inhibiting CERT pharmacologically corrects morphological and motor abnormalities in a Drosophila model of the disease, which we call ceramide transporter (CerTra) syndrome. These findings uncover a central role for CERT autoregulation in the control of sphingolipid biosynthetic flux, provide unexpected insight into the structural organization of CERT, and suggest a possible therapeutic approach for patients with CerTra syndrome.This work was supported by the National Institute of Neurological Disorders and Stroke (NINDS), NIH (R01NS109858, to VAG); the Paul A. Marks Scholar Program at the Columbia University Vagelos College of Physicians and Surgeons (to VAG); a TIGER grant from the TAUB Institute at the Columbia Vagelos College of Physicians and Scientists (to VAG); the Swiss National Science Foundation (SNF 31003A-179371, to TH); the European Joint Program on Rare Diseases (EJP RD+SNF 32ER30-187505, to TH); the Swiss Cancer League (KFS-4999-02-2020, to GD); the EPFL institutional fund (to GD); the Kristian Gerhard Jebsen Foundation (to GD); the Swiss National Science Foundation (SNSF) (310030_184926, to GD); the Swiss Foundation for Research on Muscle Disease (FSRMM, to MAL); the Natural Science and Engineering Research Council of Canada (Discovery Grant 2020-04241, to JEB); the Italian Ministry of Health Young Investigator Grant (GR-2011-02347754, to EL); the Fondazione Istituto di Ricerca Pediatrica – Città della Speranza (18-04, to EL); the Wroclaw Medical University (SUB.E160.21.004, to RS); the National Science Centre, Poland (2017/27/B/NZ5/0222, to RS); Telethon Undiagnosed Diseases Program (TUDP) (GSP15001); the Temple Street Foundation/Children’s Health Foundation Ireland (RPAC 19-02, to IK); the Deutsche Forschungsgemeinschaft (DFG) (PO2366/2–1, to BP); the Instituto de Salud Carlos III, Spain (to ELM, EBS, and BMD); the National Natural Science Foundation of China (81871079 and 81730036, to HG and KX); and the National Institutes of Diabetes and Digestive and Kidney Diseases (NIDDK), NIH (R01 DK115574, to SSC).The DEFIDIAG study is funded by grants from the French Ministry of Health in the framewok of the national French initiative for genomic medicine. The funders were not involved in the study design, data acquisition, analysis, or writing of the manuscript. Funding for the DECIPHER project was provided by Wellcome. The DDD study presents independent research commissioned by the Health Innovation Challenge Fund (grant number HICF-1009-003), a parallel funding partnership between Wellcome and the Department of Health, and the Wellcome Sanger Institute (grant number WT098051). The views expressed in this publication are those of the author(s) and not necessarily those of Wellcome or the Department of Health. The study has UK Research Ethics Committee approval (10/H0305/83, granted by the Cambridge South REC, and GEN/284/12, granted by the Republic of Ireland REC). The research team acknowledges the support of the National Institute for Health Research, through the Comprehensive Clinical Research Network.S

How specialised and integrated relationship management responsibilities foster new ventures' network development

Even though developing a new venture's network is recognised as a necessity for successfully developing a new venture, still little is known about how it may be effectively accomplished. Building on prior research, this paper develops and tests three hypotheses about how young ventures' network development may benefit from specialising and integrating relationship management responsibilities. Our results, based on a sample of 117 young ventures, provide strong support for our hypotheses. They show that new ventures' members that apply the basic means of organisation design to their management of external relations develop more new network relationships, dissolve more existing ones, and have larger networks in total

Forming Potential of Current Dual-Phase Steel Developments with Strengths of 800 MPa

Modern car bodies are constantly relying on higher proportions of high- and ultra-high-strength steels. In the past, the increase in material strengths led to a conflict regarding the complexity of component geometries. Limits of material formability were reached, and compromises had to be made in part design. By integrating application-oriented problems into the material development, these limits are expanded with respect to the given requirements. Within the present study, for three dual-phase steels with a tensile strength of 800 MPa, practical laboratory tests are presented and their benefits in component manufacture are discussed. In particular, the material ductility has an essential role for the forming process

Effects of Microstructural Properties on Damage Evolution and Edge Crack Sensitivity of DP1000 Steels

In the present work, the microstructural damage behavior of two DP1000 steel test subjects through various stress states was studied to thoroughly learn the interaction between microstructure, damage evolution, and edge stretchability. In addition, microstructural changes at the fracture sites and fracture surfaces were observed using a scanning electron microscope. The distinctive mechanical and damage behaviors of the materials were revealed. However, the steels were slightly different in chemical composition, microstructural characteristics, and yield stress. The results showed that when microstructural and mechanical properties of phases were more similar, i.e., the microstructure was more homogenous, the damage was initiated by cracking at ferrite-martensite interfaces, and it propagated along the loading direction. This allowed the material to represent high local formability and significant necking. In contrast, by increasing the dissimilarity between ferrite and martensite phases, damage propagated by the shear linking of the voids hindered local deformation of the material and led it to sudden fracture after negligible necking. These distinct damage evolutions noticeably influenced the materials’ edge stretchability. Since higher local formability favors the edges with higher resistance to cracking, the hole expansion ratio increases, as clearly observed throughout the current study

Effects of Microstructural Properties on Damage Evolution and Edge Crack Sensitivity of DP1000 Steels

In the present work, the microstructural damage behavior of two DP1000 steel test subjects through various stress states was studied to thoroughly learn the interaction between microstructure, damage evolution, and edge stretchability. In addition, microstructural changes at the fracture sites and fracture surfaces were observed using a scanning electron microscope. The distinctive mechanical and damage behaviors of the materials were revealed. However, the steels were slightly different in chemical composition, microstructural characteristics, and yield stress. The results showed that when microstructural and mechanical properties of phases were more similar, i.e., the microstructure was more homogenous, the damage was initiated by cracking at ferrite-martensite interfaces, and it propagated along the loading direction. This allowed the material to represent high local formability and significant necking. In contrast, by increasing the dissimilarity between ferrite and martensite phases, damage propagated by the shear linking of the voids hindered local deformation of the material and led it to sudden fracture after negligible necking. These distinct damage evolutions noticeably influenced the materials’ edge stretchability. Since higher local formability favors the edges with higher resistance to cracking, the hole expansion ratio increases, as clearly observed throughout the current study

Elevated expression of periostin in human osteoarthritic cartilage and its potential role in matrix degradation via matrix metalloproteinase-13

We investigated the role of periostin, an extracellular matrix protein, in the pathophysiology of osteoarthritis (OA). In OA, dysregulated gene expression and phenotypic changes in articular chondrocytes culminate in progressive loss of cartilage from the joint surface. The molecular mechanisms underlying this process are poorly understood. We examined periostin expression by immunohistochemical analysis of lesional and nonlesional cartilage from human and rodent OA knee cartilage. In addition, we used small interfering (si)RNA and adenovirus transduction of chondrocytes to knock down and upregulate periostin levels, respectively, and analyzed its effect on matrix metalloproteinase (MMP)-13, a disintegrin and MMP with thrombospondin motifs (ADAMTS)-4, and type II collagen expression. We found high periostin levels in human and rodent OA cartilage. Periostin increased MMP-13 expression dose [1-10 mg/ml (EC50 0.5-1 mg/ml)] and time (24-72 h) dependently, significantly enhanced expression of ADAMTS4 mRNA, and promoted cartilage degeneration through collagen and proteoglycan degradation. Periostin induction of MMP-13 expression was inhibited by CCT031374 hydrobromide, an inhibitor of the canonical Wnt/b-catenin signaling pathway. In addition, siRNA-mediated knockdown of endogenous periostin blocked constitutive MMP-13 expression. These findings implicate periostin as a catabolic protein that promotes cartilage degeneration in OA by upregulating MMP-13 through canonical Wnt signaling.-Attur, M., Yang, Q., Shimada, K., Tachida, Y., Nagase, H., Mignatti, P., Statman, L., Palmer, G., Kirsch, T., Beier, F., Abramson, A. B. Elevated expression of periostin in human osteoarthritic cartilage and its potential role in matrix degradation via matrix metalloproteinase-13. FASEB J. 29, 4107-4121 (2015). www.fasebj.org