[Colocalization of nucleoli in cell nuclei of HeLa line].

PubMed

Petrov, Iu P; Neguliaev, Iu A; Tsupkina, N V

2014-01-01

The pattern of localization of nucleoli relative to each other and to cell nucleus was studied in M-HeLa cell line. For this puspose, the following morphometric parameters were introduced. For the two-nucleolar cells: 1) the ratio of the nucleus long axis to the length of a segment between the centers of the nucleoli, and 2) the angle between the segment connecting the centers of the nucleoli and a longitudinal axis of cell nucleus. For the three-nucleolar cells: the ratio perimeter of the nucleus to perimeter of a triangle with vertexes in the centre of nucleoli. We have shown that the values of these parameters are individual for each cell but their values remain constant for the cell in spite of the changes in cell shape. These results allow us to conclude that, on the one hand, the nucleoli colocalization is individual for each cell, and, on the other hand, location of nucleoli in relation to nucleus is not changed during interphase. Thereby, the distance between nucleoli increases proportionally with nucleus growth.

Automated segmentation of retinal pigment epithelium cells in fluorescence adaptive optics images.

PubMed

Rangel-Fonseca, Piero; Gómez-Vieyra, Armando; Malacara-Hernández, Daniel; Wilson, Mario C; Williams, David R; Rossi, Ethan A

2013-12-01

Adaptive optics (AO) imaging methods allow the histological characteristics of retinal cell mosaics, such as photoreceptors and retinal pigment epithelium (RPE) cells, to be studied in vivo. The high-resolution images obtained with ophthalmic AO imaging devices are rich with information that is difficult and/or tedious to quantify using manual methods. Thus, robust, automated analysis tools that can provide reproducible quantitative information about the cellular mosaics under examination are required. Automated algorithms have been developed to detect the position of individual photoreceptor cells; however, most of these methods are not well suited for characterizing the RPE mosaic. We have developed an algorithm for RPE cell segmentation and show its performance here on simulated and real fluorescence AO images of the RPE mosaic. Algorithm performance was compared to manual cell identification and yielded better than 91% correspondence. This method can be used to segment RPE cells for morphometric analysis of the RPE mosaic and speed the analysis of both healthy and diseased RPE mosaics.

Image segmentation and dynamic lineage analysis in single-cell fluorescence microscopy.

PubMed

Wang, Quanli; Niemi, Jarad; Tan, Chee-Meng; You, Lingchong; West, Mike

2010-01-01

An increasingly common component of studies in synthetic and systems biology is analysis of dynamics of gene expression at the single-cell level, a context that is heavily dependent on the use of time-lapse movies. Extracting quantitative data on the single-cell temporal dynamics from such movies remains a major challenge. Here, we describe novel methods for automating key steps in the analysis of single-cell, fluorescent images-segmentation and lineage reconstruction-to recognize and track individual cells over time. The automated analysis iteratively combines a set of extended morphological methods for segmentation, and uses a neighborhood-based scoring method for frame-to-frame lineage linking. Our studies with bacteria, budding yeast and human cells, demonstrate the portability and usability of these methods, whether using phase, bright field or fluorescent images. These examples also demonstrate the utility of our integrated approach in facilitating analyses of engineered and natural cellular networks in diverse settings. The automated methods are implemented in freely available, open-source software.

Object Segmentation and Ground Truth in 3D Embryonic Imaging.

PubMed

Rajasekaran, Bhavna; Uriu, Koichiro; Valentin, Guillaume; Tinevez, Jean-Yves; Oates, Andrew C

2016-01-01

Many questions in developmental biology depend on measuring the position and movement of individual cells within developing embryos. Yet, tools that provide this data are often challenged by high cell density and their accuracy is difficult to measure. Here, we present a three-step procedure to address this problem. Step one is a novel segmentation algorithm based on image derivatives that, in combination with selective post-processing, reliably and automatically segments cell nuclei from images of densely packed tissue. Step two is a quantitative validation using synthetic images to ascertain the efficiency of the algorithm with respect to signal-to-noise ratio and object density. Finally, we propose an original method to generate reliable and experimentally faithful ground truth datasets: Sparse-dense dual-labeled embryo chimeras are used to unambiguously measure segmentation errors within experimental data. Together, the three steps outlined here establish a robust, iterative procedure to fine-tune image analysis algorithms and microscopy settings associated with embryonic 3D image data sets.

Object Segmentation and Ground Truth in 3D Embryonic Imaging

PubMed Central

Rajasekaran, Bhavna; Uriu, Koichiro; Valentin, Guillaume; Tinevez, Jean-Yves; Oates, Andrew C.

2016-01-01

Many questions in developmental biology depend on measuring the position and movement of individual cells within developing embryos. Yet, tools that provide this data are often challenged by high cell density and their accuracy is difficult to measure. Here, we present a three-step procedure to address this problem. Step one is a novel segmentation algorithm based on image derivatives that, in combination with selective post-processing, reliably and automatically segments cell nuclei from images of densely packed tissue. Step two is a quantitative validation using synthetic images to ascertain the efficiency of the algorithm with respect to signal-to-noise ratio and object density. Finally, we propose an original method to generate reliable and experimentally faithful ground truth datasets: Sparse-dense dual-labeled embryo chimeras are used to unambiguously measure segmentation errors within experimental data. Together, the three steps outlined here establish a robust, iterative procedure to fine-tune image analysis algorithms and microscopy settings associated with embryonic 3D image data sets. PMID:27332860

Image Segmentation for Connectomics Using Machine Learning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tasdizen, Tolga; Seyedhosseini, Mojtaba; Liu, TIng

Reconstruction of neural circuits at the microscopic scale of individual neurons and synapses, also known as connectomics, is an important challenge for neuroscience. While an important motivation of connectomics is providing anatomical ground truth for neural circuit models, the ability to decipher neural wiring maps at the individual cell level is also important in studies of many neurodegenerative diseases. Reconstruction of a neural circuit at the individual neuron level requires the use of electron microscopy images due to their extremely high resolution. Computational challenges include pixel-by-pixel annotation of these images into classes such as cell membrane, mitochondria and synaptic vesiclesmore » and the segmentation of individual neurons. State-of-the-art image analysis solutions are still far from the accuracy and robustness of human vision and biologists are still limited to studying small neural circuits using mostly manual analysis. In this chapter, we describe our image analysis pipeline that makes use of novel supervised machine learning techniques to tackle this problem.« less

Boundary-to-Marker Evidence-Controlled Segmentation and MDL-Based Contour Inference for Overlapping Nuclei.

PubMed

Song, Jie; Xiao, Liang; Lian, Zhichao

2017-03-01

This paper presents a novel method for automated morphology delineation and analysis of cell nuclei in histopathology images. Combining the initial segmentation information and concavity measurement, the proposed method first segments clusters of nuclei into individual pieces, avoiding segmentation errors introduced by the scale-constrained Laplacian-of-Gaussian filtering. After that a nuclear boundary-to-marker evidence computing is introduced to delineate individual objects after the refined segmentation process. The obtained evidence set is then modeled by the periodic B-splines with the minimum description length principle, which achieves a practical compromise between the complexity of the nuclear structure and its coverage of the fluorescence signal to avoid the underfitting and overfitting results. The algorithm is computationally efficient and has been tested on the synthetic database as well as 45 real histopathology images. By comparing the proposed method with several state-of-the-art methods, experimental results show the superior recognition performance of our method and indicate the potential applications of analyzing the intrinsic features of nuclei morphology.

Multiplex Quantitative Histologic Analysis of Human Breast Cancer Cell Signaling and Cell Fate

DTIC Science & Technology

2010-05-01

Breast cancer, cell signaling, cell proliferation, histology, image analysis 15. NUMBER OF PAGES - 51 16. PRICE CODE 17. SECURITY CLASSIFICATION...revealed by individual stains in multiplex combinations; and (3) software (FARSIGHT) for automated multispectral image analysis that (i) segments...Task 3. Develop computational algorithms for multispectral immunohistological image analysis FARSIGHT software was developed to quantify intrinsic

Coupled Segmentation of Nuclear and Membrane-bound Macromolecules through Voting and Multiphase Level Set

PubMed Central

Wen, Quan

2014-01-01

Membrane-bound macromolecules play an important role in tissue architecture and cell-cell communication, and is regulated by almost one-third of the genome. At the optical scale, one group of membrane proteins expresses themselves as linear structures along the cell surface boundaries, while others are sequestered; and this paper targets the former group. Segmentation of these membrane proteins on a cell-by-cell basis enables the quantitative assessment of localization for comparative analysis. However, such membrane proteins typically lack continuity, and their intensity distributions are often very heterogeneous; moreover, nuclei can form large clump, which further impedes the quantification of membrane signals on a cell-by-cell basis. To tackle these problems, we introduce a three-step process to (i) regularize the membrane signal through iterative tangential voting, (ii) constrain the location of surface proteins by nuclear features, where clumps of nuclei are segmented through a delaunay triangulation approach, and (iii) assign membrane-bound macromolecules to individual cells through an application of multi-phase geodesic level-set. We have validated our method using both synthetic data and a dataset of 200 images, and are able to demonstrate the efficacy of our approach with superior performance. PMID:25530633

Isolation of a single rice chromosome by optical micromanipulation

NASA Astrophysics Data System (ADS)

Wang, Haowei; Liu, Xiaohui; Li, Yinmei; Han, Bin; Lou, Liren; Wang, Kangjun

2004-01-01

A new method based on optical tweezers technology is reported for the isolation of a single chromosome. A rice cell suspended in liquid was first fragmented by laser pulses (optical scalpel). Then a single released chromosome from the cell was manipulated and pulled away from other cells and oddments by optical tweezers without any direct mechanical contact. Finally the isolated single chromosome was extracted individually into a glass capillary nearby. After molecular cloning of the isolated chromosome, we obtained some specific DNA segments from the single chromosome. All these segments can be used for rice genomic sequencing. Different methods of extracting a single chromosome are compared. The advantages of optical micromanipulation method are summarized.

Automatic detection and analysis of cell motility in phase-contrast time-lapse images using a combination of maximally stable extremal regions and Kalman filter approaches.

PubMed

Kaakinen, M; Huttunen, S; Paavolainen, L; Marjomäki, V; Heikkilä, J; Eklund, L

2014-01-01

Phase-contrast illumination is simple and most commonly used microscopic method to observe nonstained living cells. Automatic cell segmentation and motion analysis provide tools to analyze single cell motility in large cell populations. However, the challenge is to find a sophisticated method that is sufficiently accurate to generate reliable results, robust to function under the wide range of illumination conditions encountered in phase-contrast microscopy, and also computationally light for efficient analysis of large number of cells and image frames. To develop better automatic tools for analysis of low magnification phase-contrast images in time-lapse cell migration movies, we investigated the performance of cell segmentation method that is based on the intrinsic properties of maximally stable extremal regions (MSER). MSER was found to be reliable and effective in a wide range of experimental conditions. When compared to the commonly used segmentation approaches, MSER required negligible preoptimization steps thus dramatically reducing the computation time. To analyze cell migration characteristics in time-lapse movies, the MSER-based automatic cell detection was accompanied by a Kalman filter multiobject tracker that efficiently tracked individual cells even in confluent cell populations. This allowed quantitative cell motion analysis resulting in accurate measurements of the migration magnitude and direction of individual cells, as well as characteristics of collective migration of cell groups. Our results demonstrate that MSER accompanied by temporal data association is a powerful tool for accurate and reliable analysis of the dynamic behaviour of cells in phase-contrast image sequences. These techniques tolerate varying and nonoptimal imaging conditions and due to their relatively light computational requirements they should help to resolve problems in computationally demanding and often time-consuming large-scale dynamical analysis of cultured cells. © 2013 The Authors Journal of Microscopy © 2013 Royal Microscopical Society.

Cell segmentation in phase contrast microscopy images via semi-supervised classification over optics-related features.

PubMed

Su, Hang; Yin, Zhaozheng; Huh, Seungil; Kanade, Takeo

2013-10-01

Phase-contrast microscopy is one of the most common and convenient imaging modalities to observe long-term multi-cellular processes, which generates images by the interference of lights passing through transparent specimens and background medium with different retarded phases. Despite many years of study, computer-aided phase contrast microscopy analysis on cell behavior is challenged by image qualities and artifacts caused by phase contrast optics. Addressing the unsolved challenges, the authors propose (1) a phase contrast microscopy image restoration method that produces phase retardation features, which are intrinsic features of phase contrast microscopy, and (2) a semi-supervised learning based algorithm for cell segmentation, which is a fundamental task for various cell behavior analysis. Specifically, the image formation process of phase contrast microscopy images is first computationally modeled with a dictionary of diffraction patterns; as a result, each pixel of a phase contrast microscopy image is represented by a linear combination of the bases, which we call phase retardation features. Images are then partitioned into phase-homogeneous atoms by clustering neighboring pixels with similar phase retardation features. Consequently, cell segmentation is performed via a semi-supervised classification technique over the phase-homogeneous atoms. Experiments demonstrate that the proposed approach produces quality segmentation of individual cells and outperforms previous approaches. Copyright © 2013 Elsevier B.V. All rights reserved.

3D Reconstruction of Coronary Artery Vascular Smooth Muscle Cells

PubMed Central

Luo, Tong; Chen, Huan; Kassab, Ghassan S.

2016-01-01

Aims The 3D geometry of individual vascular smooth muscle cells (VSMCs), which are essential for understanding the mechanical function of blood vessels, are currently not available. This paper introduces a new 3D segmentation algorithm to determine VSMC morphology and orientation. Methods and Results A total of 112 VSMCs from six porcine coronary arteries were used in the analysis. A 3D semi-automatic segmentation method was developed to reconstruct individual VSMCs from cell clumps as well as to extract the 3D geometry of VSMCs. A new edge blocking model was introduced to recognize cell boundary while an edge growing was developed for optimal interpolation and edge verification. The proposed methods were designed based on Region of Interest (ROI) selected by user and interactive responses of limited key edges. Enhanced cell boundary features were used to construct the cell’s initial boundary for further edge growing. A unified framework of morphological parameters (dimensions and orientations) was proposed for the 3D volume data. Virtual phantom was designed to validate the tilt angle measurements, while other parameters extracted from 3D segmentations were compared with manual measurements to assess the accuracy of the algorithm. The length, width and thickness of VSMCs were 62.9±14.9μm, 4.6±0.6μm and 6.2±1.8μm (mean±SD). In longitudinal-circumferential plane of blood vessel, VSMCs align off the circumferential direction with two mean angles of -19.4±9.3° and 10.9±4.7°, while an out-of-plane angle (i.e., radial tilt angle) was found to be 8±7.6° with median as 5.7°. Conclusions A 3D segmentation algorithm was developed to reconstruct individual VSMCs of blood vessel walls based on optical image stacks. The results were validated by a virtual phantom and manual measurement. The obtained 3D geometries can be utilized in mathematical models and leads a better understanding of vascular mechanical properties and function. PMID:26882342

Automated segmentation and tracking for large-scale analysis of focal adhesion dynamics.

PubMed

Würflinger, T; Gamper, I; Aach, T; Sechi, A S

2011-01-01

Cell adhesion, a process mediated by the formation of discrete structures known as focal adhesions (FAs), is pivotal to many biological events including cell motility. Much is known about the molecular composition of FAs, although our knowledge of the spatio-temporal recruitment and the relative occupancy of the individual components present in the FAs is still incomplete. To fill this gap, an essential prerequisite is a highly reliable procedure for the recognition, segmentation and tracking of FAs. Although manual segmentation and tracking may provide some advantages when done by an expert, its performance is usually hampered by subjective judgement and the long time required in analysing large data sets. Here, we developed a model-based segmentation and tracking algorithm that overcomes these problems. In addition, we developed a dedicated computational approach to correct segmentation errors that may arise from the analysis of poorly defined FAs. Thus, by achieving accurate and consistent FA segmentation and tracking, our work establishes the basis for a comprehensive analysis of FA dynamics under various experimental regimes and the future development of mathematical models that simulate FA behaviour. © 2010 The Authors Journal of Microscopy © 2010 The Royal Microscopical Society.

Robust nuclei segmentation in cyto-histopathological images using statistical level set approach with topology preserving constraint

NASA Astrophysics Data System (ADS)

Taheri, Shaghayegh; Fevens, Thomas; Bui, Tien D.

2017-02-01

Computerized assessments for diagnosis or malignancy grading of cyto-histopathological specimens have drawn increased attention in the field of digital pathology. Automatic segmentation of cell nuclei is a fundamental step in such automated systems. Despite considerable research, nuclei segmentation is still a challenging task due noise, nonuniform illumination, and most importantly, in 2D projection images, overlapping and touching nuclei. In most published approaches, nuclei refinement is a post-processing step after segmentation, which usually refers to the task of detaching the aggregated nuclei or merging the over-segmented nuclei. In this work, we present a novel segmentation technique which effectively addresses the problem of individually segmenting touching or overlapping cell nuclei during the segmentation process. The proposed framework is a region-based segmentation method, which consists of three major modules: i) the image is passed through a color deconvolution step to extract the desired stains; ii) then the generalized fast radial symmetry transform is applied to the image followed by non-maxima suppression to specify the initial seed points for nuclei, and their corresponding GFRS ellipses which are interpreted as the initial nuclei borders for segmentation; iii) finally, these nuclei border initial curves are evolved through the use of a statistical level-set approach along with topology preserving criteria for segmentation and separation of nuclei at the same time. The proposed method is evaluated using Hematoxylin and Eosin, and fluorescent stained images, performing qualitative and quantitative analysis, showing that the method outperforms thresholding and watershed segmentation approaches.

Segmental neurofibromatosis and cancer: report of triple malignancy in a woman with mosaic Neurofibromatosis 1 and review of neoplasms in segmental neurofibromatosis.

PubMed

Cohen, Philip R

2016-07-15

BackgroundSegmental neurofibromatosis, referred to as mosaic neurofibromatosis 1, patients present with neurofibromas or café au lait macules or both in a unilateral segment of the body.PurposeA woman with segmental neurofibromatosis and triple cancer (renal cell carcinoma, mixed thyroid carcinoma, and lentigo maligna) is described and cancers observed in patients with segmental neurofibromatosis are reviewed.MethodsPubMed was used to search the following terms, separately and in combination: cancer, malignancy, mosaic, neoplasm, neurofibroma, neurofibromatosis, segment, segmental, tumor.ResultsMalignancy (13 cancers) has been observed in 11 segmental neurofibromatosis patients; one patient had three different cancers. The most common neoplasms were of neural crest origin {malignant peripheral nerve sheath tumor (3 patients) and melanoma (3 patients)] and gastrointestinal tract origin [colon (1 patient) and gastric (1 patient)]. Breast cancer, Hodgkin lymphoma, lung cancer, kidney cancer, and thyroid cancer each occurred in one patient.ConclusionsSimilar to patients with von Recklinghausen neurofibromatosis 1, individuals with segmental neurofibromatosis also have a genodermatosis-associated increased risk of developing cancer.

Ins and Outs of Multipartite Positive-Strand RNA Plant Viruses: Packaging versus Systemic Spread

PubMed Central

Dall’Ara, Mattia; Ratti, Claudio; Bouzoubaa, Salah E.; Gilmer, David

2016-01-01

Viruses possessing a non-segmented genome require a specific recognition of their nucleic acid to ensure its protection in a capsid. A similar feature exists for viruses having a segmented genome, usually consisting of viral genomic segments joined together into one viral entity. While this appears as a rule for animal viruses, the majority of segmented plant viruses package their genomic segments individually. To ensure a productive infection, all viral particles and thereby all segments have to be present in the same cell. Progression of the virus within the plant requires as well a concerted genome preservation to avoid loss of function. In this review, we will discuss the “life aspects” of chosen phytoviruses and argue for the existence of RNA-RNA interactions that drive the preservation of viral genome integrity while the virus progresses in the plant. PMID:27548199

NeuroSeg: automated cell detection and segmentation for in vivo two-photon Ca2+ imaging data.

PubMed

Guan, Jiangheng; Li, Jingcheng; Liang, Shanshan; Li, Ruijie; Li, Xingyi; Shi, Xiaozhe; Huang, Ciyu; Zhang, Jianxiong; Pan, Junxia; Jia, Hongbo; Zhang, Le; Chen, Xiaowei; Liao, Xiang

2018-01-01

Two-photon Ca 2+ imaging has become a popular approach for monitoring neuronal population activity with cellular or subcellular resolution in vivo. This approach allows for the recording of hundreds to thousands of neurons per animal and thus leads to a large amount of data to be processed. In particular, manually drawing regions of interest is the most time-consuming aspect of data analysis. However, the development of automated image analysis pipelines, which will be essential for dealing with the likely future deluge of imaging data, remains a major challenge. To address this issue, we developed NeuroSeg, an open-source MATLAB program that can facilitate the accurate and efficient segmentation of neurons in two-photon Ca 2+ imaging data. We proposed an approach using a generalized Laplacian of Gaussian filter to detect cells and weighting-based segmentation to separate individual cells from the background. We tested this approach on an in vivo two-photon Ca 2+ imaging dataset obtained from mouse cortical neurons with differently sized view fields. We show that this approach exhibits superior performance for cell detection and segmentation compared with the existing published tools. In addition, we integrated the previously reported, activity-based segmentation into our approach and found that this combined method was even more promising. The NeuroSeg software, including source code and graphical user interface, is freely available and will be a useful tool for in vivo brain activity mapping.

Automated analysis of high-throughput B-cell sequencing data reveals a high frequency of novel immunoglobulin V gene segment alleles.

PubMed

Gadala-Maria, Daniel; Yaari, Gur; Uduman, Mohamed; Kleinstein, Steven H

2015-02-24

Individual variation in germline and expressed B-cell immunoglobulin (Ig) repertoires has been associated with aging, disease susceptibility, and differential response to infection and vaccination. Repertoire properties can now be studied at large-scale through next-generation sequencing of rearranged Ig genes. Accurate analysis of these repertoire-sequencing (Rep-Seq) data requires identifying the germline variable (V), diversity (D), and joining (J) gene segments used by each Ig sequence. Current V(D)J assignment methods work by aligning sequences to a database of known germline V(D)J segment alleles. However, existing databases are likely to be incomplete and novel polymorphisms are hard to differentiate from the frequent occurrence of somatic hypermutations in Ig sequences. Here we develop a Tool for Ig Genotype Elucidation via Rep-Seq (TIgGER). TIgGER analyzes mutation patterns in Rep-Seq data to identify novel V segment alleles, and also constructs a personalized germline database containing the specific set of alleles carried by a subject. This information is then used to improve the initial V segment assignments from existing tools, like IMGT/HighV-QUEST. The application of TIgGER to Rep-Seq data from seven subjects identified 11 novel V segment alleles, including at least one in every subject examined. These novel alleles constituted 13% of the total number of unique alleles in these subjects, and impacted 3% of V(D)J segment assignments. These results reinforce the highly polymorphic nature of human Ig V genes, and suggest that many novel alleles remain to be discovered. The integration of TIgGER into Rep-Seq processing pipelines will increase the accuracy of V segment assignments, thus improving B-cell repertoire analyses.

Non-rigid estimation of cell motion in calcium time-lapse images

NASA Astrophysics Data System (ADS)

Hachi, Siham; Lucumi Moreno, Edinson; Desmet, An-Sofie; Vanden Berghe, Pieter; Fleming, Ronan M. T.

2016-03-01

Calcium imaging is a widely used technique in neuroscience permitting the simultaneous monitoring of electro- physiological activity of hundreds of neurons at single cell resolution. Identification of neuronal activity requires rapid and reliable image analysis techniques, especially when neurons fire and move simultaneously over time. Traditionally, image segmentation is performed to extract individual neurons in the first frame of a calcium sequence. Thereafter, the mean intensity is calculated from the same region of interest in each frame to infer calcium signals. However, when cells move, deform and fire, this segmentation on its own generates artefacts and therefore biased neuronal activity. Therefore, there is a pressing need to develop a more efficient cell tracking technique. We hereby present a novel vision-based cell tracking scheme using a thin-plate spline deformable model. The thin-plate spline warping is based on control points detected using the Fast from Accelerated Segment Test descriptor and tracked using the Lucas-Kanade optical flow. Our method is able to track neurons in calcium time-series, even when there are large changes in intensity, such as during a firing event. The robustness and efficiency of the proposed approach is validated on real calcium time-lapse images of a neuronal population.

Consistency of Border-Ownership Cells across Artificial Stimuli, Natural Stimuli, and Stimuli with Ambiguous Contours.

PubMed

Hesse, Janis K; Tsao, Doris Y

2016-11-02

Segmentation and recognition of objects in a visual scene are two problems that are hard to solve separately from each other. When segmenting an ambiguous scene, it is helpful to already know the present objects and their shapes. However, for recognizing an object in clutter, one would like to consider its isolated segment alone to avoid confounds from features of other objects. Border-ownership cells (Zhou et al., 2000) appear to play an important role in segmentation, as they signal the side-of-figure of artificial stimuli. The present work explores the role of border-ownership cells in dorsal macaque visual areas V2 and V3 in the segmentation of natural object stimuli and locally ambiguous stimuli. We report two major results. First, compared with previous estimates, we found a smaller percentage of cells that were consistent across artificial stimuli used previously. Second, we found that the average response of those neurons that did respond consistently to the side-of-figure of artificial stimuli also consistently signaled, as a population, the side-of-figure for borders of single faces, occluding faces and, with higher latencies, even stimuli with illusory contours, such as Mooney faces and natural faces completely missing local edge information. In contrast, the local edge or the outlines of the face alone could not always evoke a significant border-ownership signal. Our results underscore that border ownership is coded by a population of cells, and indicate that these cells integrate a variety of cues, including low-level features and global object context, to compute the segmentation of the scene. To distinguish different objects in a natural scene, the brain must segment the image into regions corresponding to objects. The so-called "border-ownership" cells appear to be dedicated to this task, as they signal for a given edge on which side the object is that owns it. Here, we report that individual border-ownership cells are unreliable when tested across a battery of artificial stimuli used previously but can signal border-ownership consistently as a population. We show that these border-ownership population signals are also suited for signaling border-ownership for natural objects and at longer latency, even for stimuli without local edge information. Our results suggest that border-ownership cells integrate both local, low-level and global, high-level cues to segment the scene. Copyright © 2016 the authors 0270-6474/16/3611338-12$15.00/0.

Diesel exhaust augments allergen-induced lower airway inflammation in allergic individuals: a controlled human exposure study.

PubMed

Carlsten, Chris; Blomberg, Anders; Pui, Mandy; Sandstrom, Thomas; Wong, Sze Wing; Alexis, Neil; Hirota, Jeremy

2016-01-01

Traffic-related air pollution has been shown to augment allergy and airway disease. However, the enhancement of allergenic effects by diesel exhaust in particular is unproven in vivo in the human lung, and underlying details of this apparent synergy are poorly understood. To test the hypothesis that a 2 h inhalation of diesel exhaust augments lower airway inflammation and immune cell activation following segmental allergen challenge in atopic subjects. 18 blinded atopic volunteers were exposed to filtered air or 300 µg PM(2.5)/m(3) of diesel exhaust in random fashion. 1 h post-exposure, diluent-controlled segmental allergen challenge was performed; 2 days later, samples from the challenged segments were obtained by bronchoscopic lavage. Samples were analysed for markers and modifiers of allergic inflammation (eosinophils, Th2 cytokines) and adaptive immune cell activation. Mixed effects models with ordinal contrasts compared effects of single and combined exposures on these end points. Diesel exhaust augmented the allergen-induced increase in airway eosinophils, interleukin 5 (IL-5) and eosinophil cationic protein (ECP) and the GSTT1 null genotype was significantly associated with the augmented IL-5 response. Diesel exhaust alone also augmented markers of non-allergic inflammation and monocyte chemotactic protein (MCP)-1 and suppressed activity of macrophages and myeloid dendritic cells. Inhalation of diesel exhaust at environmentally relevant concentrations augments allergen-induced allergic inflammation in the lower airways of atopic individuals and the GSTT1 genotype enhances this response. Allergic individuals are a susceptible population to the deleterious airway effects of diesel exhaust. NCT01792232. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Segmentation of the Clustered Cells with Optimized Boundary Detection in Negative Phase Contrast Images

PubMed Central

Wang, Yuliang; Zhang, Zaicheng; Wang, Huimin; Bi, Shusheng

2015-01-01

Cell image segmentation plays a central role in numerous biology studies and clinical applications. As a result, the development of cell image segmentation algorithms with high robustness and accuracy is attracting more and more attention. In this study, an automated cell image segmentation algorithm is developed to get improved cell image segmentation with respect to cell boundary detection and segmentation of the clustered cells for all cells in the field of view in negative phase contrast images. A new method which combines the thresholding method and edge based active contour method was proposed to optimize cell boundary detection. In order to segment clustered cells, the geographic peaks of cell light intensity were utilized to detect numbers and locations of the clustered cells. In this paper, the working principles of the algorithms are described. The influence of parameters in cell boundary detection and the selection of the threshold value on the final segmentation results are investigated. At last, the proposed algorithm is applied to the negative phase contrast images from different experiments. The performance of the proposed method is evaluated. Results show that the proposed method can achieve optimized cell boundary detection and highly accurate segmentation for clustered cells. PMID:26066315

In Situ 3D Segmentation of Individual Plant Leaves Using a RGB-D Camera for Agricultural Automation.

PubMed

Xia, Chunlei; Wang, Longtan; Chung, Bu-Keun; Lee, Jang-Myung

2015-08-19

In this paper, we present a challenging task of 3D segmentation of individual plant leaves from occlusions in the complicated natural scene. Depth data of plant leaves is introduced to improve the robustness of plant leaf segmentation. The low cost RGB-D camera is utilized to capture depth and color image in fields. Mean shift clustering is applied to segment plant leaves in depth image. Plant leaves are extracted from the natural background by examining vegetation of the candidate segments produced by mean shift. Subsequently, individual leaves are segmented from occlusions by active contour models. Automatic initialization of the active contour models is implemented by calculating the center of divergence from the gradient vector field of depth image. The proposed segmentation scheme is tested through experiments under greenhouse conditions. The overall segmentation rate is 87.97% while segmentation rates for single and occluded leaves are 92.10% and 86.67%, respectively. Approximately half of the experimental results show segmentation rates of individual leaves higher than 90%. Nevertheless, the proposed method is able to segment individual leaves from heavy occlusions.

In Situ 3D Segmentation of Individual Plant Leaves Using a RGB-D Camera for Agricultural Automation

PubMed Central

Xia, Chunlei; Wang, Longtan; Chung, Bu-Keun; Lee, Jang-Myung

2015-01-01

In this paper, we present a challenging task of 3D segmentation of individual plant leaves from occlusions in the complicated natural scene. Depth data of plant leaves is introduced to improve the robustness of plant leaf segmentation. The low cost RGB-D camera is utilized to capture depth and color image in fields. Mean shift clustering is applied to segment plant leaves in depth image. Plant leaves are extracted from the natural background by examining vegetation of the candidate segments produced by mean shift. Subsequently, individual leaves are segmented from occlusions by active contour models. Automatic initialization of the active contour models is implemented by calculating the center of divergence from the gradient vector field of depth image. The proposed segmentation scheme is tested through experiments under greenhouse conditions. The overall segmentation rate is 87.97% while segmentation rates for single and occluded leaves are 92.10% and 86.67%, respectively. Approximately half of the experimental results show segmentation rates of individual leaves higher than 90%. Nevertheless, the proposed method is able to segment individual leaves from heavy occlusions. PMID:26295395

Cell nuclei and cytoplasm joint segmentation using the sliding band filter.

PubMed

Quelhas, Pedro; Marcuzzo, Monica; Mendonça, Ana Maria; Campilho, Aurélio

2010-08-01

Microscopy cell image analysis is a fundamental tool for biological research. In particular, multivariate fluorescence microscopy is used to observe different aspects of cells in cultures. It is still common practice to perform analysis tasks by visual inspection of individual cells which is time consuming, exhausting and prone to induce subjective bias. This makes automatic cell image analysis essential for large scale, objective studies of cell cultures. Traditionally the task of automatic cell analysis is approached through the use of image segmentation methods for extraction of cells' locations and shapes. Image segmentation, although fundamental, is neither an easy task in computer vision nor is it robust to image quality changes. This makes image segmentation for cell detection semi-automated requiring frequent tuning of parameters. We introduce a new approach for cell detection and shape estimation in multivariate images based on the sliding band filter (SBF). This filter's design makes it adequate to detect overall convex shapes and as such it performs well for cell detection. Furthermore, the parameters involved are intuitive as they are directly related to the expected cell size. Using the SBF filter we detect cells' nucleus and cytoplasm location and shapes. Based on the assumption that each cell has the same approximate shape center in both nuclei and cytoplasm fluorescence channels, we guide cytoplasm shape estimation by the nuclear detections improving performance and reducing errors. Then we validate cell detection by gathering evidence from nuclei and cytoplasm channels. Additionally, we include overlap correction and shape regularization steps which further improve the estimated cell shapes. The approach is evaluated using two datasets with different types of data: a 20 images benchmark set of simulated cell culture images, containing 1000 simulated cells; a 16 images Drosophila melanogaster Kc167 dataset containing 1255 cells, stained for DNA and actin. Both image datasets present a difficult problem due to the high variability of cell shapes and frequent cluster overlap between cells. On the Drosophila dataset our approach achieved a precision/recall of 95%/69% and 82%/90% for nuclei and cytoplasm detection respectively and an overall accuracy of 76%.

Automatic Cell Segmentation in Fluorescence Images of Confluent Cell Monolayers Using Multi-object Geometric Deformable Model.

PubMed

Yang, Zhen; Bogovic, John A; Carass, Aaron; Ye, Mao; Searson, Peter C; Prince, Jerry L

2013-03-13

With the rapid development of microscopy for cell imaging, there is a strong and growing demand for image analysis software to quantitatively study cell morphology. Automatic cell segmentation is an important step in image analysis. Despite substantial progress, there is still a need to improve the accuracy, efficiency, and adaptability to different cell morphologies. In this paper, we propose a fully automatic method for segmenting cells in fluorescence images of confluent cell monolayers. This method addresses several challenges through a combination of ideas. 1) It realizes a fully automatic segmentation process by first detecting the cell nuclei as initial seeds and then using a multi-object geometric deformable model (MGDM) for final segmentation. 2) To deal with different defects in the fluorescence images, the cell junctions are enhanced by applying an order-statistic filter and principal curvature based image operator. 3) The final segmentation using MGDM promotes robust and accurate segmentation results, and guarantees no overlaps and gaps between neighboring cells. The automatic segmentation results are compared with manually delineated cells, and the average Dice coefficient over all distinguishable cells is 0.88.

Visual-servoing optical microscopy

DOEpatents

Callahan, Daniel E.; Parvin, Bahram

2009-06-09

The present invention provides methods and devices for the knowledge-based discovery and optimization of differences between cell types. In particular, the present invention provides visual servoing optical microscopy, as well as analysis methods. The present invention provides means for the close monitoring of hundreds of individual, living cells over time: quantification of dynamic physiological responses in multiple channels; real-time digital image segmentation and analysis; intelligent, repetitive computer-applied cell stress and cell stimulation; and the ability to return to the same field of cells for long-term studies and observation. The present invention further provides means to optimize culture conditions for specific subpopulations of cells.

Visual-servoing optical microscopy

DOEpatents

Callahan, Daniel E [Martinez, CA; Parvin, Bahram [Mill Valley, CA

2011-05-24

The present invention provides methods and devices for the knowledge-based discovery and optimization of differences between cell types. In particular, the present invention provides visual servoing optical microscopy, as well as analysis methods. The present invention provides means for the close monitoring of hundreds of individual, living cells over time; quantification of dynamic physiological responses in multiple channels; real-time digital image segmentation and analysis; intelligent, repetitive computer-applied cell stress and cell stimulation; and the ability to return to the same field of cells for long-term studies and observation. The present invention further provides means to optimize culture conditions for specific subpopulations of cells.

Visual-servoing optical microscopy

DOEpatents

Callahan, Daniel E; Parvin, Bahram

2013-10-01

The present invention provides methods and devices for the knowledge-based discovery and optimization of differences between cell types. In particular, the present invention provides visual servoing optical microscopy, as well as analysis methods. The present invention provides means for the close monitoring of hundreds of individual, living cells over time; quantification of dynamic physiological responses in multiple channels; real-time digital image segmentation and analysis; intelligent, repetitive computer-applied cell stress and cell stimulation; and the ability to return to the same field of cells for long-term studies and observation. The present invention further provides means to optimize culture conditions for specific subpopulations of cells.

CP-CHARM: segmentation-free image classification made accessible.

PubMed

Uhlmann, Virginie; Singh, Shantanu; Carpenter, Anne E

2016-01-27

Automated classification using machine learning often relies on features derived from segmenting individual objects, which can be difficult to automate. WND-CHARM is a previously developed classification algorithm in which features are computed on the whole image, thereby avoiding the need for segmentation. The algorithm obtained encouraging results but requires considerable computational expertise to execute. Furthermore, some benchmark sets have been shown to be subject to confounding artifacts that overestimate classification accuracy. We developed CP-CHARM, a user-friendly image-based classification algorithm inspired by WND-CHARM in (i) its ability to capture a wide variety of morphological aspects of the image, and (ii) the absence of requirement for segmentation. In order to make such an image-based classification method easily accessible to the biological research community, CP-CHARM relies on the widely-used open-source image analysis software CellProfiler for feature extraction. To validate our method, we reproduced WND-CHARM's results and ensured that CP-CHARM obtained comparable performance. We then successfully applied our approach on cell-based assay data and on tissue images. We designed these new training and test sets to reduce the effect of batch-related artifacts. The proposed method preserves the strengths of WND-CHARM - it extracts a wide variety of morphological features directly on whole images thereby avoiding the need for cell segmentation, but additionally, it makes the methods easily accessible for researchers without computational expertise by implementing them as a CellProfiler pipeline. It has been demonstrated to perform well on a wide range of bioimage classification problems, including on new datasets that have been carefully selected and annotated to minimize batch effects. This provides for the first time a realistic and reliable assessment of the whole image classification strategy.

Using simulated fluorescence cell micrographs for the evaluation of cell image segmentation algorithms.

PubMed

Wiesmann, Veit; Bergler, Matthias; Palmisano, Ralf; Prinzen, Martin; Franz, Daniela; Wittenberg, Thomas

2017-03-18

Manual assessment and evaluation of fluorescent micrograph cell experiments is time-consuming and tedious. Automated segmentation pipelines can ensure efficient and reproducible evaluation and analysis with constant high quality for all images of an experiment. Such cell segmentation approaches are usually validated and rated in comparison to manually annotated micrographs. Nevertheless, manual annotations are prone to errors and display inter- and intra-observer variability which influence the validation results of automated cell segmentation pipelines. We present a new approach to simulate fluorescent cell micrographs that provides an objective ground truth for the validation of cell segmentation methods. The cell simulation was evaluated twofold: (1) An expert observer study shows that the proposed approach generates realistic fluorescent cell micrograph simulations. (2) An automated segmentation pipeline on the simulated fluorescent cell micrographs reproduces segmentation performances of that pipeline on real fluorescent cell micrographs. The proposed simulation approach produces realistic fluorescent cell micrographs with corresponding ground truth. The simulated data is suited to evaluate image segmentation pipelines more efficiently and reproducibly than it is possible on manually annotated real micrographs.

Peristaltic pump noise: A nemesis conquered

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burns, D.A.

1994-12-31

Continuous-flow analyzers (CFA), and especially Segmented Flow Analyzers (SFA), typically employ peristaltic pumps to generate a carrier stream and add reagents thereto. The resulting pump {open_quotes}noise{close_quotes} usually limits precision, and is generally deemed unavoidable. Although the problem is partially solved by hydraulic debubbling, most modern instruments employ bubble thru the flow-cell (BTTFC) technology and electronic debubbling. The authors have developed an algorithm that can significantly reduce this source of noise, even when the individual segments in the SFA stream are of varying volumes and/or concentrations. It does this, without any modifications to the pump, by examining each individual segment asmore » it passes thru the flowcell. The Alpkem model 304 multichannel pump, for example, can be set to produce 90 bubbles/minutes (and therefore 90 segments/minute), so one has 667 msec in which to gather sufficient information to identify a {open_quotes}bad{close_quotes} segment and modify its value. This hardware includes a Hewlett Packard model 8452A diode array spectrophotometer fitted with fiber optics leading to/from a flowcell (5 mm path length X 1mm ID). Each segment remains in the flowcell 300-500 msec. With a data sampling rate of 10/sec (100 msec integration time), the authors can acquire 3-5 intensity values for each segment and convert these to absorbance values. The software to perform all this was written in QuickBASIC 4.5 and incorporates a few routines from Hewlett Packard`s library. The program will be described in some detail so that analytical chemists who use BTTFC can obtain higher precision.« less

Segmentation of clustered cells in negative phase contrast images with integrated light intensity and cell shape information.

PubMed

Wang, Y; Wang, C; Zhang, Z

2018-05-01

Automated cell segmentation plays a key role in characterisations of cell behaviours for both biology research and clinical practices. Currently, the segmentation of clustered cells still remains as a challenge and is the main reason for false segmentation. In this study, the emphasis was put on the segmentation of clustered cells in negative phase contrast images. A new method was proposed to combine both light intensity and cell shape information through the construction of grey-weighted distance transform (GWDT) within preliminarily segmented areas. With the constructed GWDT, the clustered cells can be detected and then separated with a modified region skeleton-based method. Moreover, a contour expansion operation was applied to get optimised detection of cell boundaries. In this paper, the working principle and detailed procedure of the proposed method are described, followed by the evaluation of the method on clustered cell segmentation. Results show that the proposed method achieves an improved performance in clustered cell segmentation compared with other methods, with 85.8% and 97.16% accuracy rate for clustered cells and all cells, respectively. © 2017 The Authors Journal of Microscopy © 2017 Royal Microscopical Society.

Effects of spaceflight on the immunoglobulin repertoire of unimmunized C57BL/6 mice

NASA Astrophysics Data System (ADS)

Ward, Claire; Rettig, Trisha A.; Hlavacek, Savannah; Bye, Bailey A.; Pecaut, Michael J.; Chapes, Stephen K.

2018-02-01

Spaceflight has been shown to suppress the adaptive immune response, altering the distribution and function of lymphocyte populations. B lymphocytes express highly specific and highly diversified receptors, known as immunoglobulins (Ig), that directly bind and neutralize pathogens. Ig diversity is achieved through the enzymatic splicing of gene segments within the genomic DNA of each B cell in a host. The collection of Ig specificities within a host, or Ig repertoire, has been increasingly characterized in both basic research and clinical settings using high-throughput sequencing technology (HTS). We utilized HTS to test the hypothesis that spaceflight affects the B-cell repertoire. To test this hypothesis, we characterized the impact of spaceflight on the unimmunized Ig repertoire of C57BL/6 mice that were flown aboard the International Space Station (ISS) during the Rodent Research One validation flight in comparison to ground controls. Individual gene segment usage was similar between ground control and flight animals, however, gene segment combinations and the junctions in which gene segments combine was varied among animals within and between treatment groups. We also found that spontaneous somatic mutations in the IgH and Igκ gene loci were not increased. These data suggest that space flight did not affect the B cell repertoire of mice flown and housed on the ISS over a short period of time.

Virtual modeling of polycrystalline structures of materials using particle packing algorithms and Laguerre cells

NASA Astrophysics Data System (ADS)

Morfa, Carlos Recarey; Farias, Márcio Muniz de; Morales, Irvin Pablo Pérez; Navarra, Eugenio Oñate Ibañez de; Valera, Roberto Roselló

2018-04-01

The influence of the microstructural heterogeneities is an important topic in the study of materials. In the context of computational mechanics, it is therefore necessary to generate virtual materials that are statistically equivalent to the microstructure under study, and to connect that geometrical description to the different numerical methods. Herein, the authors present a procedure to model continuous solid polycrystalline materials, such as rocks and metals, preserving their representative statistical grain size distribution. The first phase of the procedure consists of segmenting an image of the material into adjacent polyhedral grains representing the individual crystals. This segmentation allows estimating the grain size distribution, which is used as the input for an advancing front sphere packing algorithm. Finally, Laguerre diagrams are calculated from the obtained sphere packings. The centers of the spheres give the centers of the Laguerre cells, and their radii determine the cells' weights. The cell sizes in the obtained Laguerre diagrams have a distribution similar to that of the grains obtained from the image segmentation. That is why those diagrams are a convenient model of the original crystalline structure. The above-outlined procedure has been used to model real polycrystalline metallic materials. The main difference with previously existing methods lies in the use of a better particle packing algorithm.

Spatial distribution of neurons innervated by chandelier cells.

PubMed

Blazquez-Llorca, Lidia; Woodruff, Alan; Inan, Melis; Anderson, Stewart A; Yuste, Rafael; DeFelipe, Javier; Merchan-Perez, Angel

2015-09-01

Chandelier (or axo-axonic) cells are a distinct group of GABAergic interneurons that innervate the axon initial segments of pyramidal cells and are thus thought to have an important role in controlling the activity of cortical circuits. To examine the circuit connectivity of chandelier cells (ChCs), we made use of a genetic targeting strategy to label neocortical ChCs in upper layers of juvenile mouse neocortex. We filled individual ChCs with biocytin in living brain slices and reconstructed their axonal arbors from serial semi-thin sections. We also reconstructed the cell somata of pyramidal neurons that were located inside the ChC axonal trees and determined the percentage of pyramidal neurons whose axon initial segments were innervated by ChC terminals. We found that the total percentage of pyramidal neurons that were innervated by a single labeled ChC was 18-22 %. Sholl analysis showed that this percentage peaked at 22-35 % for distances between 30 and 60 µm from the ChC soma, decreasing to lower percentages with increasing distances. We also studied the three-dimensional spatial distribution of the innervated neurons inside the ChC axonal arbor using spatial statistical analysis tools. We found that innervated pyramidal neurons are not distributed at random, but show a clustered distribution, with pockets where almost all cells are innervated and other regions within the ChC axonal tree that receive little or no innervation. Thus, individual ChCs may exert a strong, widespread influence on their local pyramidal neighbors in a spatially heterogeneous fashion.

Survey statistics of automated segmentations applied to optical imaging of mammalian cells.

PubMed

Bajcsy, Peter; Cardone, Antonio; Chalfoun, Joe; Halter, Michael; Juba, Derek; Kociolek, Marcin; Majurski, Michael; Peskin, Adele; Simon, Carl; Simon, Mylene; Vandecreme, Antoine; Brady, Mary

2015-10-15

The goal of this survey paper is to overview cellular measurements using optical microscopy imaging followed by automated image segmentation. The cellular measurements of primary interest are taken from mammalian cells and their components. They are denoted as two- or three-dimensional (2D or 3D) image objects of biological interest. In our applications, such cellular measurements are important for understanding cell phenomena, such as cell counts, cell-scaffold interactions, cell colony growth rates, or cell pluripotency stability, as well as for establishing quality metrics for stem cell therapies. In this context, this survey paper is focused on automated segmentation as a software-based measurement leading to quantitative cellular measurements. We define the scope of this survey and a classification schema first. Next, all found and manually filteredpublications are classified according to the main categories: (1) objects of interests (or objects to be segmented), (2) imaging modalities, (3) digital data axes, (4) segmentation algorithms, (5) segmentation evaluations, (6) computational hardware platforms used for segmentation acceleration, and (7) object (cellular) measurements. Finally, all classified papers are converted programmatically into a set of hyperlinked web pages with occurrence and co-occurrence statistics of assigned categories. The survey paper presents to a reader: (a) the state-of-the-art overview of published papers about automated segmentation applied to optical microscopy imaging of mammalian cells, (b) a classification of segmentation aspects in the context of cell optical imaging, (c) histogram and co-occurrence summary statistics about cellular measurements, segmentations, segmented objects, segmentation evaluations, and the use of computational platforms for accelerating segmentation execution, and (d) open research problems to pursue. The novel contributions of this survey paper are: (1) a new type of classification of cellular measurements and automated segmentation, (2) statistics about the published literature, and (3) a web hyperlinked interface to classification statistics of the surveyed papers at https://isg.nist.gov/deepzoomweb/resources/survey/index.html.

Nucleus detection using gradient orientation information and linear least squares regression

NASA Astrophysics Data System (ADS)

Kwak, Jin Tae; Hewitt, Stephen M.; Xu, Sheng; Pinto, Peter A.; Wood, Bradford J.

2015-03-01

Computerized histopathology image analysis enables an objective, efficient, and quantitative assessment of digitized histopathology images. Such analysis often requires an accurate and efficient detection and segmentation of histological structures such as glands, cells and nuclei. The segmentation is used to characterize tissue specimens and to determine the disease status or outcomes. The segmentation of nuclei, in particular, is challenging due to the overlapping or clumped nuclei. Here, we propose a nuclei seed detection method for the individual and overlapping nuclei that utilizes the gradient orientation or direction information. The initial nuclei segmentation is provided by a multiview boosting approach. The angle of the gradient orientation is computed and traced for the nuclear boundaries. Taking the first derivative of the angle of the gradient orientation, high concavity points (junctions) are discovered. False junctions are found and removed by adopting a greedy search scheme with the goodness-of-fit statistic in a linear least squares sense. Then, the junctions determine boundary segments. Partial boundary segments belonging to the same nucleus are identified and combined by examining the overlapping area between them. Using the final set of the boundary segments, we generate the list of seeds in tissue images. The method achieved an overall precision of 0.89 and a recall of 0.88 in comparison to the manual segmentation.

Identifying Developmental Zones in Maize Lateral Root Cell Length Profiles using Multiple Change-Point Models

PubMed Central

Moreno-Ortega, Beatriz; Fort, Guillaume; Muller, Bertrand; Guédon, Yann

2017-01-01

The identification of the limits between the cell division, elongation and mature zones in the root apex is still a matter of controversy when methods based on cellular features, molecular markers or kinematics are compared while methods based on cell length profiles have been comparatively underexplored. Segmentation models were developed to identify developmental zones within a root apex on the basis of epidermal cell length profiles. Heteroscedastic piecewise linear models were estimated for maize lateral roots of various lengths of both wild type and two mutants affected in auxin signaling (rtcs and rum-1). The outputs of these individual root analyses combined with morphological features (first root hair position and root diameter) were then globally analyzed using principal component analysis. Three zones corresponding to the division zone, the elongation zone and the mature zone were identified in most lateral roots while division zone and sometimes elongation zone were missing in arrested roots. Our results are consistent with an auxin-dependent coordination between cell flux, cell elongation and cell differentiation. The proposed segmentation models could extend our knowledge of developmental regulations in longitudinally organized plant organs such as roots, monocot leaves or internodes. PMID:29123533

Segmentation and Quantitative Analysis of Apoptosis of Chinese Hamster Ovary Cells from Fluorescence Microscopy Images.

PubMed

Du, Yuncheng; Budman, Hector M; Duever, Thomas A

2017-06-01

Accurate and fast quantitative analysis of living cells from fluorescence microscopy images is useful for evaluating experimental outcomes and cell culture protocols. An algorithm is developed in this work to automatically segment and distinguish apoptotic cells from normal cells. The algorithm involves three steps consisting of two segmentation steps and a classification step. The segmentation steps are: (i) a coarse segmentation, combining a range filter with a marching square method, is used as a prefiltering step to provide the approximate positions of cells within a two-dimensional matrix used to store cells' images and the count of the number of cells for a given image; and (ii) a fine segmentation step using the Active Contours Without Edges method is applied to the boundaries of cells identified in the coarse segmentation step. Although this basic two-step approach provides accurate edges when the cells in a given image are sparsely distributed, the occurrence of clusters of cells in high cell density samples requires further processing. Hence, a novel algorithm for clusters is developed to identify the edges of cells within clusters and to approximate their morphological features. Based on the segmentation results, a support vector machine classifier that uses three morphological features: the mean value of pixel intensities in the cellular regions, the variance of pixel intensities in the vicinity of cell boundaries, and the lengths of the boundaries, is developed for distinguishing apoptotic cells from normal cells. The algorithm is shown to be efficient in terms of computational time, quantitative analysis, and differentiation accuracy, as compared with the use of the active contours method without the proposed preliminary coarse segmentation step.

Training echo state networks for rotation-invariant bone marrow cell classification.

PubMed

Kainz, Philipp; Burgsteiner, Harald; Asslaber, Martin; Ahammer, Helmut

2017-01-01

The main principle of diagnostic pathology is the reliable interpretation of individual cells in context of the tissue architecture. Especially a confident examination of bone marrow specimen is dependent on a valid classification of myeloid cells. In this work, we propose a novel rotation-invariant learning scheme for multi-class echo state networks (ESNs), which achieves very high performance in automated bone marrow cell classification. Based on representing static images as temporal sequence of rotations, we show how ESNs robustly recognize cells of arbitrary rotations by taking advantage of their short-term memory capacity. The performance of our approach is compared to a classification random forest that learns rotation-invariance in a conventional way by exhaustively training on multiple rotations of individual samples. The methods were evaluated on a human bone marrow image database consisting of granulopoietic and erythropoietic cells in different maturation stages. Our ESN approach to cell classification does not rely on segmentation of cells or manual feature extraction and can therefore directly be applied to image data.

Smart markers for watershed-based cell segmentation.

PubMed

Koyuncu, Can Fahrettin; Arslan, Salim; Durmaz, Irem; Cetin-Atalay, Rengul; Gunduz-Demir, Cigdem

2012-01-01

Automated cell imaging systems facilitate fast and reliable analysis of biological events at the cellular level. In these systems, the first step is usually cell segmentation that greatly affects the success of the subsequent system steps. On the other hand, similar to other image segmentation problems, cell segmentation is an ill-posed problem that typically necessitates the use of domain-specific knowledge to obtain successful segmentations even by human subjects. The approaches that can incorporate this knowledge into their segmentation algorithms have potential to greatly improve segmentation results. In this work, we propose a new approach for the effective segmentation of live cells from phase contrast microscopy. This approach introduces a new set of "smart markers" for a marker-controlled watershed algorithm, for which the identification of its markers is critical. The proposed approach relies on using domain-specific knowledge, in the form of visual characteristics of the cells, to define the markers. We evaluate our approach on a total of 1,954 cells. The experimental results demonstrate that this approach, which uses the proposed definition of smart markers, is quite effective in identifying better markers compared to its counterparts. This will, in turn, be effective in improving the segmentation performance of a marker-controlled watershed algorithm.

Comparison of segmentation algorithms for fluorescence microscopy images of cells.

PubMed

Dima, Alden A; Elliott, John T; Filliben, James J; Halter, Michael; Peskin, Adele; Bernal, Javier; Kociolek, Marcin; Brady, Mary C; Tang, Hai C; Plant, Anne L

2011-07-01

The analysis of fluorescence microscopy of cells often requires the determination of cell edges. This is typically done using segmentation techniques that separate the cell objects in an image from the surrounding background. This study compares segmentation results from nine different segmentation techniques applied to two different cell lines and five different sets of imaging conditions. Significant variability in the results of segmentation was observed that was due solely to differences in imaging conditions or applications of different algorithms. We quantified and compared the results with a novel bivariate similarity index metric that evaluates the degree of underestimating or overestimating a cell object. The results show that commonly used threshold-based segmentation techniques are less accurate than k-means clustering with multiple clusters. Segmentation accuracy varies with imaging conditions that determine the sharpness of cell edges and with geometric features of a cell. Based on this observation, we propose a method that quantifies cell edge character to provide an estimate of how accurately an algorithm will perform. The results of this study will assist the development of criteria for evaluating interlaboratory comparability. Published 2011 Wiley-Liss, Inc.

Generation of a variety of stable Influenza A reporter viruses by genetic engineering of the NS gene segment

PubMed Central

Reuther, Peter; Göpfert, Kristina; Dudek, Alexandra H.; Heiner, Monika; Herold, Susanne; Schwemmle, Martin

2015-01-01

Influenza A viruses (IAV) pose a constant threat to the human population and therefore a better understanding of their fundamental biology and identification of novel therapeutics is of upmost importance. Various reporter-encoding IAV were generated to achieve these goals, however, one recurring difficulty was the genetic instability especially of larger reporter genes. We employed the viral NS segment coding for the non-structural protein 1 (NS1) and nuclear export protein (NEP) for stable expression of diverse reporter proteins. This was achieved by converting the NS segment into a single open reading frame (ORF) coding for NS1, the respective reporter and NEP. To allow expression of individual proteins, the reporter genes were flanked by two porcine Teschovirus-1 2A peptide (PTV-1 2A)-coding sequences. The resulting viruses encoding luciferases, fluorescent proteins or a Cre recombinase are characterized by a high genetic stability in vitro and in mice and can be readily employed for antiviral compound screenings, visualization of infected cells or cells that survived acute infection. PMID:26068081

Effects of spaceflight on the immunoglobulin repertoire of unimmunized C57BL/6 mice.

PubMed

Ward, Claire; Rettig, Trisha A; Hlavacek, Savannah; Bye, Bailey A; Pecaut, Michael J; Chapes, Stephen K

2018-02-01

Spaceflight has been shown to suppress the adaptive immune response, altering the distribution and function of lymphocyte populations. B lymphocytes express highly specific and highly diversified receptors, known as immunoglobulins (Ig), that directly bind and neutralize pathogens. Ig diversity is achieved through the enzymatic splicing of gene segments within the genomic DNA of each B cell in a host. The collection of Ig specificities within a host, or Ig repertoire, has been increasingly characterized in both basic research and clinical settings using high-throughput sequencing technology (HTS). We utilized HTS to test the hypothesis that spaceflight affects the B-cell repertoire. To test this hypothesis, we characterized the impact of spaceflight on the unimmunized Ig repertoire of C57BL/6 mice that were flown aboard the International Space Station (ISS) during the Rodent Research One validation flight in comparison to ground controls. Individual gene segment usage was similar between ground control and flight animals, however, gene segment combinations and the junctions in which gene segments combine was varied among animals within and between treatment groups. We also found that spontaneous somatic mutations in the IgH and Igκ gene loci were not increased. These data suggest that space flight did not affect the B cell repertoire of mice flown and housed on the ISS over a short period of time. Copyright © 2017 The Committee on Space Research (COSPAR). Published by Elsevier Ltd. All rights reserved.

Segmented Detector Calibration Techniques for the PROSPECT Experiment

NASA Astrophysics Data System (ADS)

Davee, Daniel; Prospect Collaboration

2016-03-01

PROSPECT will make the most precise measurement of the 235U anti-neutrino spectrum to date and search for eV-scale sterile neutrinos. The proposed detector is composed of 120 6Li loaded liquid scintillator filled cells, and uses Inverse Beta Decay (IBD) ν + p -->e+ + n to detect reactor anti-neutrinos. Because the positron produced in IBD carries most of the ν energy, the response throughout the entire segmented detector to electron-like energy depositions must be determined with high precision via an extensive calibration program. To this end the detector is designed to allow for the insertion of both optical and radioactive sources to test each performance of cell individually without changing the optical response. In addition to these measures, cosmogenic sources will be used to probe energy response of the detector at high energies.

Introduced T cell receptor variable region gene segments recombine in pre-B cells: evidence that B and T cells use a common recombinase.

PubMed

Yancopoulos, G D; Blackwell, T K; Suh, H; Hood, L; Alt, F W

1986-01-31

We have recently proposed that a common recombinase performs all of the many variable region gene assembly events in B and T cells, and that the specificity of these joining events is mediated by regulating the "accessibility" of the involved gene segments. To test this possibility, we have introduced "accessible" T cell receptor (TCR) variable region gene segments into a pre-B cell line capable of recombining endogenous and transfected immunoglobulin (Ig) variable region gene segments. Although the corresponding "inaccessible" endogenous TCR gene segments do not rearrange in this line or in B cells in general, the introduced TCR gene segments join very frequently and, in fact, closely resemble introduced Ig gene segments in their recombination characteristics. These observations suggest a new role for conventional Ig transcriptional enhancers--recombinational enhancement. Our studies provide insight into additional aspects of the joining mechanism such as N region insertion, aberrant joining, and recombination-recognition sequence requirements for joining.

Computer Aided Solution for Automatic Segmenting and Measurements of Blood Leucocytes Using Static Microscope Images.

PubMed

Abdulhay, Enas; Mohammed, Mazin Abed; Ibrahim, Dheyaa Ahmed; Arunkumar, N; Venkatraman, V

2018-02-17

Blood leucocytes segmentation in medical images is viewed as difficult process due to the variability of blood cells concerning their shape and size and the difficulty towards determining location of Blood Leucocytes. Physical analysis of blood tests to recognize leukocytes is tedious, time-consuming and liable to error because of the various morphological components of the cells. Segmentation of medical imagery has been considered as a difficult task because of complexity of images, and also due to the non-availability of leucocytes models which entirely captures the probable shapes in each structures and also incorporate cell overlapping, the expansive variety of the blood cells concerning their shape and size, various elements influencing the outer appearance of the blood leucocytes, and low Static Microscope Image disparity from extra issues outcoming about because of noise. We suggest a strategy towards segmentation of blood leucocytes using static microscope images which is a resultant of three prevailing systems of computer vision fiction: enhancing the image, Support vector machine for segmenting the image, and filtering out non ROI (region of interest) on the basis of Local binary patterns and texture features. Every one of these strategies are modified for blood leucocytes division issue, in this manner the subsequent techniques are very vigorous when compared with its individual segments. Eventually, we assess framework based by compare the outcome and manual division. The findings outcome from this study have shown a new approach that automatically segments the blood leucocytes and identify it from a static microscope images. Initially, the method uses a trainable segmentation procedure and trained support vector machine classifier to accurately identify the position of the ROI. After that, filtering out non ROI have proposed based on histogram analysis to avoid the non ROI and chose the right object. Finally, identify the blood leucocytes type using the texture feature. The performance of the foreseen approach has been tried in appearing differently in relation to the system against manual examination by a gynaecologist utilizing diverse scales. A total of 100 microscope images were used for the comparison, and the results showed that the proposed solution is a viable alternative to the manual segmentation method for accurately determining the ROI. We have evaluated the blood leucocytes identification using the ROI texture (LBP Feature). The identification accuracy in the technique used is about 95.3%., with 100 sensitivity and 91.66% specificity.

An Energy-Based Three-Dimensional Segmentation Approach for the Quantitative Interpretation of Electron Tomograms

PubMed Central

Bartesaghi, Alberto; Sapiro, Guillermo; Subramaniam, Sriram

2006-01-01

Electron tomography allows for the determination of the three-dimensional structures of cells and tissues at resolutions significantly higher than that which is possible with optical microscopy. Electron tomograms contain, in principle, vast amounts of information on the locations and architectures of large numbers of subcellular assemblies and organelles. The development of reliable quantitative approaches for the analysis of features in tomograms is an important problem, and a challenging prospect due to the low signal-to-noise ratios that are inherent to biological electron microscopic images. This is, in part, a consequence of the tremendous complexity of biological specimens. We report on a new method for the automated segmentation of HIV particles and selected cellular compartments in electron tomograms recorded from fixed, plastic-embedded sections derived from HIV-infected human macrophages. Individual features in the tomogram are segmented using a novel robust algorithm that finds their boundaries as global minimal surfaces in a metric space defined by image features. The optimization is carried out in a transformed spherical domain with the center an interior point of the particle of interest, providing a proper setting for the fast and accurate minimization of the segmentation energy. This method provides tools for the semi-automated detection and statistical evaluation of HIV particles at different stages of assembly in the cells and presents opportunities for correlation with biochemical markers of HIV infection. The segmentation algorithm developed here forms the basis of the automated analysis of electron tomograms and will be especially useful given the rapid increases in the rate of data acquisition. It could also enable studies of much larger data sets, such as those which might be obtained from the tomographic analysis of HIV-infected cells from studies of large populations. PMID:16190467

Quantitative Cell Cycle Analysis Based on an Endogenous All-in-One Reporter for Cell Tracking and Classification.

PubMed

Zerjatke, Thomas; Gak, Igor A; Kirova, Dilyana; Fuhrmann, Markus; Daniel, Katrin; Gonciarz, Magdalena; Müller, Doris; Glauche, Ingmar; Mansfeld, Jörg

2017-05-30

Cell cycle kinetics are crucial to cell fate decisions. Although live imaging has provided extensive insights into this relationship at the single-cell level, the limited number of fluorescent markers that can be used in a single experiment has hindered efforts to link the dynamics of individual proteins responsible for decision making directly to cell cycle progression. Here, we present fluorescently tagged endogenous proliferating cell nuclear antigen (PCNA) as an all-in-one cell cycle reporter that allows simultaneous analysis of cell cycle progression, including the transition into quiescence, and the dynamics of individual fate determinants. We also provide an image analysis pipeline for automated segmentation, tracking, and classification of all cell cycle phases. Combining the all-in-one reporter with labeled endogenous cyclin D1 and p21 as prime examples of cell-cycle-regulated fate determinants, we show how cell cycle and quantitative protein dynamics can be simultaneously extracted to gain insights into G1 phase regulation and responses to perturbations. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

A spectral k-means approach to bright-field cell image segmentation.

PubMed

Bradbury, Laura; Wan, Justin W L

2010-01-01

Automatic segmentation of bright-field cell images is important to cell biologists, but difficult to complete due to the complex nature of the cells in bright-field images (poor contrast, broken halo, missing boundaries). Standard approaches such as level set segmentation and active contours work well for fluorescent images where cells appear as round shape, but become less effective when optical artifacts such as halo exist in bright-field images. In this paper, we present a robust segmentation method which combines the spectral and k-means clustering techniques to locate cells in bright-field images. This approach models an image as a matrix graph and segment different regions of the image by computing the appropriate eigenvectors of the matrix graph and using the k-means algorithm. We illustrate the effectiveness of the method by segmentation results of C2C12 (muscle) cells in bright-field images.

Monosynaptic rabies virus reveals premotor network organization and synaptic specificity of cholinergic partition cells.

PubMed

Stepien, Anna E; Tripodi, Marco; Arber, Silvia

2010-11-04

Movement is the behavioral output of neuronal activity in the spinal cord. Motor neurons are grouped into motor neuron pools, the functional units innervating individual muscles. Here we establish an anatomical rabies virus-based connectivity assay in early postnatal mice. We employ it to study the connectivity scheme of premotor neurons, the neuronal cohorts monosynaptically connected to motor neurons, unveiling three aspects of organization. First, motor neuron pools are connected to segmentally widely distributed yet stereotypic interneuron populations, differing for pools innervating functionally distinct muscles. Second, depending on subpopulation identity, interneurons take on local or segmentally distributed positions. Third, cholinergic partition cells involved in the regulation of motor neuron excitability segregate into ipsilaterally and bilaterally projecting populations, the latter exhibiting preferential connections to functionally equivalent motor neuron pools bilaterally. Our study visualizes the widespread yet precise nature of the connectivity matrix for premotor interneurons and reveals exquisite synaptic specificity for bilaterally projecting cholinergic partition cells. Copyright © 2010 Elsevier Inc. All rights reserved.

Tracking cells in Life Cell Imaging videos using topological alignments.

PubMed

Mosig, Axel; Jäger, Stefan; Wang, Chaofeng; Nath, Sumit; Ersoy, Ilker; Palaniappan, Kannap-pan; Chen, Su-Shing

2009-07-16

With the increasing availability of live cell imaging technology, tracking cells and other moving objects in live cell videos has become a major challenge for bioimage informatics. An inherent problem for most cell tracking algorithms is over- or under-segmentation of cells - many algorithms tend to recognize one cell as several cells or vice versa. We propose to approach this problem through so-called topological alignments, which we apply to address the problem of linking segmentations of two consecutive frames in the video sequence. Starting from the output of a conventional segmentation procedure, we align pairs of consecutive frames through assigning sets of segments in one frame to sets of segments in the next frame. We achieve this through finding maximum weighted solutions to a generalized "bipartite matching" between two hierarchies of segments, where we derive weights from relative overlap scores of convex hulls of sets of segments. For solving the matching task, we rely on an integer linear program. Practical experiments demonstrate that the matching task can be solved efficiently in practice, and that our method is both effective and useful for tracking cells in data sets derived from a so-called Large Scale Digital Cell Analysis System (LSDCAS). The source code of the implementation is available for download from http://www.picb.ac.cn/patterns/Software/topaln.

Tension, cell shape and triple-junction angle anisotropy in the Drosophila germband

NASA Astrophysics Data System (ADS)

Lacy, Monica; Hutson, M. Shane; Meyer, Christian; McDonald, Xena

In the field of tissue mechanics, the embryonic development of Drosophila melanogaster offers many opportunities for study. One of Drosophila's most crucial morphogenetic stages is the retraction of an epithelial tissue called the germband. During retraction, the segments of the retracting germband, as well as the individual germband cells, elongate in response to forces from a connected tissue, the amnioserosa. Modeling of this elongation, based on tissue responses to laser wounding, has plotted the internal germband tension against the external amnioserosa stress, creating a phase space to determine points and regions corresponding to stable elongation. Although the resulting fits indicate a necessary opposition of internal and external forces, they are inconclusive regarding the exact balance. We will present results testing the model predictions by measuring cell shapes and the correlations between cell-edge directions and triple-junction angles. These measures resolve the ambiguity in pinpointing the internal-external force balance for each germband segment. Research was supported by NIH Grant Numbers 1R01GM099107 and 1R21AR068933.

Individual bone structure segmentation and labeling from low-dose chest CT

NASA Astrophysics Data System (ADS)

Liu, Shuang; Xie, Yiting; Reeves, Anthony P.

2017-03-01

The segmentation and labeling of the individual bones serve as the first step to the fully automated measurement of skeletal characteristics and the detection of abnormalities such as skeletal deformities, osteoporosis, and vertebral fractures. Moreover, the identified landmarks on the segmented bone structures can potentially provide relatively reliable location reference to other non-rigid human organs, such as breast, heart and lung, thereby facilitating the corresponding image analysis and registration. A fully automated anatomy-directed framework for the segmentation and labeling of the individual bone structures from low-dose chest CT is presented in this paper. The proposed system consists of four main stages: First, both clavicles are segmented and labeled by fitting a piecewise cylindrical envelope. Second, the sternum is segmented under the spatial constraints provided by the segmented clavicles. Third, all ribs are segmented and labeled based on 3D region growing within the volume of interest defined with reference to the spinal canal centerline and lungs. Fourth, the individual thoracic vertebrae are segmented and labeled by image intensity based analysis in the spatial region constrained by the previously segmented bone structures. The system performance was validated with 1270 lowdose chest CT scans through visual evaluation. Satisfactory performance was obtained respectively in 97.1% cases for the clavicle segmentation and labeling, in 97.3% cases for the sternum segmentation, in 97.2% cases for the rib segmentation, in 94.2% cases for the rib labeling, in 92.4% cases for vertebra segmentation and in 89.9% cases for the vertebra labeling.

Meckelin 3 Is Necessary for Photoreceptor Outer Segment Development in Rat Meckel Syndrome

PubMed Central

Tiwari, Sarika; Hudson, Scott; Gattone, Vincent H.; Miller, Caroline; Chernoff, Ellen A. G.; Belecky-Adams, Teri L.

2013-01-01

Ciliopathies lead to multiorgan pathologies that include renal cysts, deafness, obesity and retinal degeneration. Retinal photoreceptors have connecting cilia joining the inner and outer segment that are responsible for transport of molecules to develop and maintain the outer segment process. The present study evaluated meckelin (MKS3) expression during outer segment genesis and determined the consequences of mutant meckelin on photoreceptor development and survival in Wistar polycystic kidney disease Wpk/Wpk rat using immunohistochemistry, analysis of cell death and electron microscopy. MKS3 was ubiquitously expressed throughout the retina at postnatal day 10 (P10) and P21. However, in the mature retina, MKS3 expression was restricted to photoreceptors and the retinal ganglion cell layer. At P10, both the wild type and homozygous Wpk mutant retina had all retinal cell types. In contrast, by P21, cells expressing rod- and cone-specific markers were fewer in number and expression of opsins appeared to be abnormally localized to the cell body. Cell death analyses were consistent with the disappearance of photoreceptor-specific markers and showed that the cells were undergoing caspase-dependent cell death. By electron microscopy, P10 photoreceptors showed rudimentary outer segments with an axoneme, but did not develop outer segment discs that were clearly present in the wild type counterpart. At p21 the mutant outer segments appeared much the same as the P10 mutant outer segments with only a short axoneme, while the wild-type controls had developed outer segments with many well-organized discs. We conclude that MKS3 is not important for formation of connecting cilium and rudimentary outer segments, but is critical for the maturation of outer segment processes. PMID:23516626

Event segmentation improves event memory up to one month later.

PubMed

Flores, Shaney; Bailey, Heather R; Eisenberg, Michelle L; Zacks, Jeffrey M

2017-08-01

When people observe everyday activity, they spontaneously parse it into discrete meaningful events. Individuals who segment activity in a more normative fashion show better subsequent memory for the events. If segmenting events effectively leads to better memory, does asking people to attend to segmentation improve subsequent memory? To answer this question, participants viewed movies of naturalistic activity with instructions to remember the activity for a later test, and in some conditions additionally pressed a button to segment the movies into meaningful events or performed a control condition that required button-pressing but not attending to segmentation. In 5 experiments, memory for the movies was assessed at intervals ranging from immediately following viewing to 1 month later. Performing the event segmentation task led to superior memory at delays ranging from 10 min to 1 month. Further, individual differences in segmentation ability predicted individual differences in memory performance for up to a month following encoding. This study provides the first evidence that manipulating event segmentation affects memory over long delays and that individual differences in event segmentation are related to differences in memory over long delays. These effects suggest that attending to how an activity breaks down into meaningful events contributes to memory formation. Instructing people to more effectively segment events may serve as a potential intervention to alleviate everyday memory complaints in aging and clinical populations. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Segmentation of whole cells and cell nuclei from 3-D optical microscope images using dynamic programming.

PubMed

McCullough, D P; Gudla, P R; Harris, B S; Collins, J A; Meaburn, K J; Nakaya, M A; Yamaguchi, T P; Misteli, T; Lockett, S J

2008-05-01

Communications between cells in large part drive tissue development and function, as well as disease-related processes such as tumorigenesis. Understanding the mechanistic bases of these processes necessitates quantifying specific molecules in adjacent cells or cell nuclei of intact tissue. However, a major restriction on such analyses is the lack of an efficient method that correctly segments each object (cell or nucleus) from 3-D images of an intact tissue specimen. We report a highly reliable and accurate semi-automatic algorithmic method for segmenting fluorescence-labeled cells or nuclei from 3-D tissue images. Segmentation begins with semi-automatic, 2-D object delineation in a user-selected plane, using dynamic programming (DP) to locate the border with an accumulated intensity per unit length greater that any other possible border around the same object. Then the two surfaces of the object in planes above and below the selected plane are found using an algorithm that combines DP and combinatorial searching. Following segmentation, any perceived errors can be interactively corrected. Segmentation accuracy is not significantly affected by intermittent labeling of object surfaces, diffuse surfaces, or spurious signals away from surfaces. The unique strength of the segmentation method was demonstrated on a variety of biological tissue samples where all cells, including irregularly shaped cells, were accurately segmented based on visual inspection.

What is a segment?

PubMed

Hannibal, Roberta L; Patel, Nipam H

2013-12-17

Animals have been described as segmented for more than 2,000 years, yet a precise definition of segmentation remains elusive. Here we give the history of the definition of segmentation, followed by a discussion on current controversies in defining a segment. While there is a general consensus that segmentation involves the repetition of units along the anterior-posterior (a-p) axis, long-running debates exist over whether a segment can be composed of only one tissue layer, whether the most anterior region of the arthropod head is considered segmented, and whether and how the vertebrate head is segmented. Additionally, we discuss whether a segment can be composed of a single cell in a column of cells, or a single row of cells within a grid of cells. We suggest that 'segmentation' be used in its more general sense, the repetition of units with a-p polarity along the a-p axis, to prevent artificial classification of animals. We further suggest that this general definition be combined with an exact description of what is being studied, as well as a clearly stated hypothesis concerning the specific nature of the potential homology of structures. These suggestions should facilitate dialogue among scientists who study vastly differing segmental structures.

Induction plasma tube

DOEpatents

Hull, D.E.

1982-07-02

An induction plasma tube having a segmented, fluid-cooled internal radiation shield is disclosed. The individual segments are thick in cross-section such that the shield occupies a substantial fraction of the internal volume of the plasma enclosure, resulting in improved performance and higher sustainable plasma temperatures. The individual segments of the shield are preferably cooled by means of a counterflow fluid cooling system wherein each segment includes a central bore and a fluid supply tube extending into the bore. The counterflow cooling system results in improved cooling of the individual segments and also permits use of relatively larger shield segments which permit improved electromagnetic coupling between the induction coil and a plasma located inside the shield. Four embodiments of the invention, each having particular advantages, are disclosed.

Induction plasma tube

DOEpatents

Hull, Donald E.

1984-01-01

An induction plasma tube having a segmented, fluid-cooled internal radiation shield is disclosed. The individual segments are thick in cross-section such that the shield occupies a substantial fraction of the internal volume of the plasma enclosure, resulting in improved performance and higher sustainable plasma temperatures. The individual segments of the shield are preferably cooled by means of a counterflow fluid cooling system wherein each segment includes a central bore and a fluid supply tube extending into the bore. The counterflow cooling system results in improved cooling of the individual segments and also permits use of relatively larger shield segments which permit improved electromagnetic coupling between the induction coil and a plasma located inside the shield. Four embodiments of the invention, each having particular advantages, are disclosed.

Segmentation of fluorescence microscopy cell images using unsupervised mining.

PubMed

Du, Xian; Dua, Sumeet

2010-05-28

The accurate measurement of cell and nuclei contours are critical for the sensitive and specific detection of changes in normal cells in several medical informatics disciplines. Within microscopy, this task is facilitated using fluorescence cell stains, and segmentation is often the first step in such approaches. Due to the complex nature of cell issues and problems inherent to microscopy, unsupervised mining approaches of clustering can be incorporated in the segmentation of cells. In this study, we have developed and evaluated the performance of multiple unsupervised data mining techniques in cell image segmentation. We adapt four distinctive, yet complementary, methods for unsupervised learning, including those based on k-means clustering, EM, Otsu's threshold, and GMAC. Validation measures are defined, and the performance of the techniques is evaluated both quantitatively and qualitatively using synthetic and recently published real data. Experimental results demonstrate that k-means, Otsu's threshold, and GMAC perform similarly, and have more precise segmentation results than EM. We report that EM has higher recall values and lower precision results from under-segmentation due to its Gaussian model assumption. We also demonstrate that these methods need spatial information to segment complex real cell images with a high degree of efficacy, as expected in many medical informatics applications.

Recognition and classification of colon cells applying the ensemble of classifiers.

PubMed

Kruk, M; Osowski, S; Koktysz, R

2009-02-01

The paper presents the application of an ensemble of classifiers for the recognition of colon cells on the basis of the microscope colon image. The solved task include: segmentation of the individual cells from the image using the morphological operations, the preprocessing stages, leading to the extraction of features, selection of the most important features, and the classification stage applying the classifiers arranged in the form of ensemble. The paper presents and discusses the results concerning the recognition of four most important colon cell types: eosinophylic granulocyte, neutrophilic granulocyte, lymphocyte and plasmocyte. The proposed system is able to recognize the cells with the accuracy comparable to the human expert (around 5% of discrepancy of both results).

Application of differential interference contrast with inverted microscopes to the in vitro perfused nephron.

PubMed

Horster, M; Gundlach, H

1979-12-01

The study of in vitro perfused individual nephron segments requires a microscope which provides: (1) easy access to the specimen for measurement of cellular solute flux and voltage; (2) an image with high resolution and contrast; (3) optical sectioning of the object at different levels; and (4) rapid recording of the morphological phenomena. This paper describes an example of commercially available apparatus meeting the above requirements, and illustrates its efficiency. The microscope is of the inverted type (Zeiss IM 35) equipped with differential-interference-contrast (DIC) with a long working distance, and an automatically controlled camera system. The microscopic image exhibits cellular and intercellular details in the unstained transporting mammalian nephron segments despite their tubular structure and great thickness and makes obvious function-structure correlations (e.g. cell volume changes); luminal and contraluminal cell borders are well resolved for controlled microelectrode impalement.

Long-term tracking of budding yeast cells in brightfield microscopy: CellStar and the Evaluation Platform.

PubMed

Versari, Cristian; Stoma, Szymon; Batmanov, Kirill; Llamosi, Artémis; Mroz, Filip; Kaczmarek, Adam; Deyell, Matt; Lhoussaine, Cédric; Hersen, Pascal; Batt, Gregory

2017-02-01

With the continuous expansion of single cell biology, the observation of the behaviour of individual cells over extended durations and with high accuracy has become a problem of central importance. Surprisingly, even for yeast cells that have relatively regular shapes, no solution has been proposed that reaches the high quality required for long-term experiments for segmentation and tracking (S&T) based on brightfield images. Here, we present CellStar , a tool chain designed to achieve good performance in long-term experiments. The key features are the use of a new variant of parametrized active rays for segmentation, a neighbourhood-preserving criterion for tracking, and the use of an iterative approach that incrementally improves S&T quality. A graphical user interface enables manual corrections of S&T errors and their use for the automated correction of other, related errors and for parameter learning. We created a benchmark dataset with manually analysed images and compared CellStar with six other tools, showing its high performance, notably in long-term tracking. As a community effort, we set up a website, the Yeast Image Toolkit, with the benchmark and the Evaluation Platform to gather this and additional information provided by others. © 2017 The Authors.

Long-term tracking of budding yeast cells in brightfield microscopy: CellStar and the Evaluation Platform

PubMed Central

Versari, Cristian; Stoma, Szymon; Batmanov, Kirill; Llamosi, Artémis; Mroz, Filip; Kaczmarek, Adam; Deyell, Matt

2017-01-01

With the continuous expansion of single cell biology, the observation of the behaviour of individual cells over extended durations and with high accuracy has become a problem of central importance. Surprisingly, even for yeast cells that have relatively regular shapes, no solution has been proposed that reaches the high quality required for long-term experiments for segmentation and tracking (S&T) based on brightfield images. Here, we present CellStar, a tool chain designed to achieve good performance in long-term experiments. The key features are the use of a new variant of parametrized active rays for segmentation, a neighbourhood-preserving criterion for tracking, and the use of an iterative approach that incrementally improves S&T quality. A graphical user interface enables manual corrections of S&T errors and their use for the automated correction of other, related errors and for parameter learning. We created a benchmark dataset with manually analysed images and compared CellStar with six other tools, showing its high performance, notably in long-term tracking. As a community effort, we set up a website, the Yeast Image Toolkit, with the benchmark and the Evaluation Platform to gather this and additional information provided by others. PMID:28179544

ESC-Track: A computer workflow for 4-D segmentation, tracking, lineage tracing and dynamic context analysis of ESCs.

PubMed

Fernández-de-Manúel, Laura; Díaz-Díaz, Covadonga; Jiménez-Carretero, Daniel; Torres, Miguel; Montoya, María C

2017-05-01

Embryonic stem cells (ESCs) can be established as permanent cell lines, and their potential to differentiate into adult tissues has led to widespread use for studying the mechanisms and dynamics of stem cell differentiation and exploring strategies for tissue repair. Imaging live ESCs during development is now feasible due to advances in optical imaging and engineering of genetically encoded fluorescent reporters; however, a major limitation is the low spatio-temporal resolution of long-term 3-D imaging required for generational and neighboring reconstructions. Here, we present the ESC-Track (ESC-T) workflow, which includes an automated cell and nuclear segmentation and tracking tool for 4-D (3-D + time) confocal image data sets as well as a manual editing tool for visual inspection and error correction. ESC-T automatically identifies cell divisions and membrane contacts for lineage tree and neighborhood reconstruction and computes quantitative features from individual cell entities, enabling analysis of fluorescence signal dynamics and tracking of cell morphology and motion. We use ESC-T to examine Myc intensity fluctuations in the context of mouse ESC (mESC) lineage and neighborhood relationships. ESC-T is a powerful tool for evaluation of the genealogical and microenvironmental cues that maintain ESC fitness.

Cell cycle progression is required for zebrafish somite morphogenesis but not segmentation clock function

PubMed Central

Zhang, Lixia; Kendrick, Christina; Jülich, Dörthe; Holley, Scott A.

2010-01-01

Summary Cell division, differentiation and morphogenesis are coordinated during embryonic development and frequently in disarray in pathologies such as cancer. Here, we present a zebrafish mutant that ceases mitosis at the beginning of gastrulation, but undergoes axis elongation and develops blood, muscle and a beating heart. We identify the mutation as being in early mitotic inhibitor 1 (emi1), a negative regulator of the Anaphase Promoting Complex, and utilize the mutant to examine the role of the cell cycle in somitogenesis. The mutant phenotype indicates that axis elongation during the segmentation period is substantially driven by cell migration. We find that the segmentation clock, which regulates somitogenesis, functions normally in the absence of cell cycle progression and observe that mitosis is a modest source of noise for the clock. Somite morphogenesis involves the epithelialization of the somite border cells around a core of mesenchyme. As in wild-type embryos, somite boundary cells are polarized along a Fibronectin matrix in emi1−/−. The mutants also display evidence of segment polarity. However, in the absence of a normal cell cycle, somites appear to hyper-epithelialize as the internal mesenchymal cells exit the core of the somite after initial boundary formation. Thus, cell cycle progression is not required during the segmentation period for segmentation clock function but is necessary for normal segmental arrangement of epithelial borders and internal mesenchymal cells. PMID:18480162

Cell segmentation in histopathological images with deep learning algorithms by utilizing spatial relationships.

PubMed

Hatipoglu, Nuh; Bilgin, Gokhan

2017-10-01

In many computerized methods for cell detection, segmentation, and classification in digital histopathology that have recently emerged, the task of cell segmentation remains a chief problem for image processing in designing computer-aided diagnosis (CAD) systems. In research and diagnostic studies on cancer, pathologists can use CAD systems as second readers to analyze high-resolution histopathological images. Since cell detection and segmentation are critical for cancer grade assessments, cellular and extracellular structures should primarily be extracted from histopathological images. In response, we sought to identify a useful cell segmentation approach with histopathological images that uses not only prominent deep learning algorithms (i.e., convolutional neural networks, stacked autoencoders, and deep belief networks), but also spatial relationships, information of which is critical for achieving better cell segmentation results. To that end, we collected cellular and extracellular samples from histopathological images by windowing in small patches with various sizes. In experiments, the segmentation accuracies of the methods used improved as the window sizes increased due to the addition of local spatial and contextual information. Once we compared the effects of training sample size and influence of window size, results revealed that the deep learning algorithms, especially convolutional neural networks and partly stacked autoencoders, performed better than conventional methods in cell segmentation.

Cell nuclei segmentation in fluorescence microscopy images using inter- and intra-region discriminative information.

PubMed

Song, Yang; Cai, Weidong; Feng, David Dagan; Chen, Mei

2013-01-01

Automated segmentation of cell nuclei in microscopic images is critical to high throughput analysis of the ever increasing amount of data. Although cell nuclei are generally visually distinguishable for human, automated segmentation faces challenges when there is significant intensity inhomogeneity among cell nuclei or in the background. In this paper, we propose an effective method for automated cell nucleus segmentation using a three-step approach. It first obtains an initial segmentation by extracting salient regions in the image, then reduces false positives using inter-region feature discrimination, and finally refines the boundary of the cell nuclei using intra-region contrast information. This method has been evaluated on two publicly available datasets of fluorescence microscopic images with 4009 cells, and has achieved superior performance compared to popular state of the art methods using established metrics.

Improved Estimation of Cardiac Function Parameters Using a Combination of Independent Automated Segmentation Results in Cardiovascular Magnetic Resonance Imaging.

PubMed

Lebenberg, Jessica; Lalande, Alain; Clarysse, Patrick; Buvat, Irene; Casta, Christopher; Cochet, Alexandre; Constantinidès, Constantin; Cousty, Jean; de Cesare, Alain; Jehan-Besson, Stephanie; Lefort, Muriel; Najman, Laurent; Roullot, Elodie; Sarry, Laurent; Tilmant, Christophe; Frouin, Frederique; Garreau, Mireille

2015-01-01

This work aimed at combining different segmentation approaches to produce a robust and accurate segmentation result. Three to five segmentation results of the left ventricle were combined using the STAPLE algorithm and the reliability of the resulting segmentation was evaluated in comparison with the result of each individual segmentation method. This comparison was performed using a supervised approach based on a reference method. Then, we used an unsupervised statistical evaluation, the extended Regression Without Truth (eRWT) that ranks different methods according to their accuracy in estimating a specific biomarker in a population. The segmentation accuracy was evaluated by estimating six cardiac function parameters resulting from the left ventricle contour delineation using a public cardiac cine MRI database. Eight different segmentation methods, including three expert delineations and five automated methods, were considered, and sixteen combinations of the automated methods using STAPLE were investigated. The supervised and unsupervised evaluations demonstrated that in most cases, STAPLE results provided better estimates than individual automated segmentation methods. Overall, combining different automated segmentation methods improved the reliability of the segmentation result compared to that obtained using an individual method and could achieve the accuracy of an expert.

Improved Estimation of Cardiac Function Parameters Using a Combination of Independent Automated Segmentation Results in Cardiovascular Magnetic Resonance Imaging

PubMed Central

Lebenberg, Jessica; Lalande, Alain; Clarysse, Patrick; Buvat, Irene; Casta, Christopher; Cochet, Alexandre; Constantinidès, Constantin; Cousty, Jean; de Cesare, Alain; Jehan-Besson, Stephanie; Lefort, Muriel; Najman, Laurent; Roullot, Elodie; Sarry, Laurent; Tilmant, Christophe

2015-01-01

This work aimed at combining different segmentation approaches to produce a robust and accurate segmentation result. Three to five segmentation results of the left ventricle were combined using the STAPLE algorithm and the reliability of the resulting segmentation was evaluated in comparison with the result of each individual segmentation method. This comparison was performed using a supervised approach based on a reference method. Then, we used an unsupervised statistical evaluation, the extended Regression Without Truth (eRWT) that ranks different methods according to their accuracy in estimating a specific biomarker in a population. The segmentation accuracy was evaluated by estimating six cardiac function parameters resulting from the left ventricle contour delineation using a public cardiac cine MRI database. Eight different segmentation methods, including three expert delineations and five automated methods, were considered, and sixteen combinations of the automated methods using STAPLE were investigated. The supervised and unsupervised evaluations demonstrated that in most cases, STAPLE results provided better estimates than individual automated segmentation methods. Overall, combining different automated segmentation methods improved the reliability of the segmentation result compared to that obtained using an individual method and could achieve the accuracy of an expert. PMID:26287691

What is a segment?

PubMed Central

2013-01-01

Animals have been described as segmented for more than 2,000 years, yet a precise definition of segmentation remains elusive. Here we give the history of the definition of segmentation, followed by a discussion on current controversies in defining a segment. While there is a general consensus that segmentation involves the repetition of units along the anterior-posterior (a-p) axis, long-running debates exist over whether a segment can be composed of only one tissue layer, whether the most anterior region of the arthropod head is considered segmented, and whether and how the vertebrate head is segmented. Additionally, we discuss whether a segment can be composed of a single cell in a column of cells, or a single row of cells within a grid of cells. We suggest that ‘segmentation’ be used in its more general sense, the repetition of units with a-p polarity along the a-p axis, to prevent artificial classification of animals. We further suggest that this general definition be combined with an exact description of what is being studied, as well as a clearly stated hypothesis concerning the specific nature of the potential homology of structures. These suggestions should facilitate dialogue among scientists who study vastly differing segmental structures. PMID:24345042

A fast and efficient segmentation scheme for cell microscopic image.

PubMed

Lebrun, G; Charrier, C; Lezoray, O; Meurie, C; Cardot, H

2007-04-27

Microscopic cellular image segmentation schemes must be efficient for reliable analysis and fast to process huge quantity of images. Recent studies have focused on improving segmentation quality. Several segmentation schemes have good quality but processing time is too expensive to deal with a great number of images per day. For segmentation schemes based on pixel classification, the classifier design is crucial since it is the one which requires most of the processing time necessary to segment an image. The main contribution of this work is focused on how to reduce the complexity of decision functions produced by support vector machines (SVM) while preserving recognition rate. Vector quantization is used in order to reduce the inherent redundancy present in huge pixel databases (i.e. images with expert pixel segmentation). Hybrid color space design is also used in order to improve data set size reduction rate and recognition rate. A new decision function quality criterion is defined to select good trade-off between recognition rate and processing time of pixel decision function. The first results of this study show that fast and efficient pixel classification with SVM is possible. Moreover posterior class pixel probability estimation is easy to compute with Platt method. Then a new segmentation scheme using probabilistic pixel classification has been developed. This one has several free parameters and an automatic selection must dealt with, but criteria for evaluate segmentation quality are not well adapted for cell segmentation, especially when comparison with expert pixel segmentation must be achieved. Another important contribution in this paper is the definition of a new quality criterion for evaluation of cell segmentation. The results presented here show that the selection of free parameters of the segmentation scheme by optimisation of the new quality cell segmentation criterion produces efficient cell segmentation.

21 CFR 640.15 - Segments for testing.

Code of Federal Regulations, 2014 CFR

2014-04-01

... cells. (c) All segments accompanying a unit of Red Blood Cells shall be filled at the time the blood is... ADDITIONAL STANDARDS FOR HUMAN BLOOD AND BLOOD PRODUCTS Red Blood Cells § 640.15 Segments for testing... provided with each unit of Whole Blood or Red Blood Cells when issued or reissued. (b) Before they are...

21 CFR 640.15 - Segments for testing.

Code of Federal Regulations, 2011 CFR

2011-04-01

... cells. (c) All segments accompanying a unit of Red Blood Cells shall be filled at the time the blood is... ADDITIONAL STANDARDS FOR HUMAN BLOOD AND BLOOD PRODUCTS Red Blood Cells § 640.15 Segments for testing... provided with each unit of Whole Blood or Red Blood Cells when issued or reissued. (b) Before they are...

21 CFR 640.15 - Segments for testing.

Code of Federal Regulations, 2013 CFR

2013-04-01

... cells. (c) All segments accompanying a unit of Red Blood Cells shall be filled at the time the blood is... ADDITIONAL STANDARDS FOR HUMAN BLOOD AND BLOOD PRODUCTS Red Blood Cells § 640.15 Segments for testing... provided with each unit of Whole Blood or Red Blood Cells when issued or reissued. (b) Before they are...

21 CFR 640.15 - Segments for testing.

Code of Federal Regulations, 2012 CFR

2012-04-01

... cells. (c) All segments accompanying a unit of Red Blood Cells shall be filled at the time the blood is... ADDITIONAL STANDARDS FOR HUMAN BLOOD AND BLOOD PRODUCTS Red Blood Cells § 640.15 Segments for testing... provided with each unit of Whole Blood or Red Blood Cells when issued or reissued. (b) Before they are...

21 CFR 640.15 - Segments for testing.

Code of Federal Regulations, 2010 CFR

2010-04-01

... ADDITIONAL STANDARDS FOR HUMAN BLOOD AND BLOOD PRODUCTS Red Blood Cells § 640.15 Segments for testing... provided with each unit of Whole Blood or Red Blood Cells when issued or reissued. (b) Before they are... cells. (c) All segments accompanying a unit of Red Blood Cells shall be filled at the time the blood is...

Physiological roles of claudins in kidney tubule paracellular transport.

PubMed

Muto, Shigeaki

2017-01-01

The paracellular pathways in renal tubular epithelia such as the proximal tubules, which reabsorb the largest fraction of filtered solutes and water and are leaky epithelia, are important routes for transepithelial transport of solutes and water. Movement occurs passively via an extracellular route through the tight junction between cells. The characteristics of paracellular transport vary among different nephron segments with leaky or tighter epithelia. Claudins expressed at tight junctions form pores and barriers for paracellular transport. Claudins are from a multigene family, comprising at least 27 members in mammals. Multiple claudins are expressed at tight junctions of individual nephron segments in a nephron segment-specific manner. Over the last decade, there have been advances in our understanding of the structure and functions of claudins. This paper is a review of our current knowledge of claudins, with special emphasis on their physiological roles in proximal tubule paracellular solute and water transport. Copyright © 2017 the American Physiological Society.

Rapid in situ hybridization technique using 16S rRNA segments for detecting and differentiating the closely related gram-positive organisms Bacillus polymyxa and Bacillus macerans

NASA Technical Reports Server (NTRS)

Jurtshuk, R. J.; Blick, M.; Bresser, J.; Fox, G. E.; Jurtshuk, P. Jr

1992-01-01

A rapid, sensitive, inexpensive in situ hybridization technique, using 30-mer 16S rRNA probes, can specifically differentiate two closely related Bacillus spp., B. polymyxa and B. macerans. The 16S rRNA probes were labeled with a rhodamine derivative (Texas Red), and quantitative fluorescence measurements were made on individual bacterial cells. The microscopic fields analyzed were selected by phase-contrast microscopy, and the fluorescence imaging analyses were performed on 16 to 67 individual cells. The labeled 16S rRNA probe, POL, whose sequence was a 100% match with B. polymyxa 16S rRNA but only a 60% match with B. macerans 16S rRNA, gave quantitative fluorescence ratio measurements that were 34.8-fold higher for B. polymyxa cells than for B. macerans cells. Conversely, the labeled probe, MAC, which matched B. polymyxa 16S rRNA in 86.6% of its positions and B. macerans 16S rRNA in 100% of its positions, gave quantitative fluorescence measurements that were 59.3-fold higher in B. macerans cells than in B. polymyxa cells. Control probes, whose 16S rRNA sequence segment (P-M) was present in both B. polymyxa and B. macerans as well as a panprokaryotic probe (16S), having a 100% match with all known bacteria, hybridized equally well with both organisms. These latter hybridizations generated very high fluorescence signals, but their comparative fluorescence ratios (the differences between two organisms) were low. The control paneukaryotic probe (28S), which had less than 30% identity for both B. macerans and B. polymyxa, did not hybridize with either organism.

Multiscale image analysis reveals structural heterogeneity of the cell microenvironment in homotypic spheroids.

PubMed

Schmitz, Alexander; Fischer, Sabine C; Mattheyer, Christian; Pampaloni, Francesco; Stelzer, Ernst H K

2017-03-03

Three-dimensional multicellular aggregates such as spheroids provide reliable in vitro substitutes for tissues. Quantitative characterization of spheroids at the cellular level is fundamental. We present the first pipeline that provides three-dimensional, high-quality images of intact spheroids at cellular resolution and a comprehensive image analysis that completes traditional image segmentation by algorithms from other fields. The pipeline combines light sheet-based fluorescence microscopy of optically cleared spheroids with automated nuclei segmentation (F score: 0.88) and concepts from graph analysis and computational topology. Incorporating cell graphs and alpha shapes provided more than 30 features of individual nuclei, the cellular neighborhood and the spheroid morphology. The application of our pipeline to a set of breast carcinoma spheroids revealed two concentric layers of different cell density for more than 30,000 cells. The thickness of the outer cell layer depends on a spheroid's size and varies between 50% and 75% of its radius. In differently-sized spheroids, we detected patches of different cell densities ranging from 5 × 10 5 to 1 × 10 6  cells/mm 3 . Since cell density affects cell behavior in tissues, structural heterogeneities need to be incorporated into existing models. Our image analysis pipeline provides a multiscale approach to obtain the relevant data for a system-level understanding of tissue architecture.

Joint level-set and spatio-temporal motion detection for cell segmentation.

PubMed

Boukari, Fatima; Makrogiannis, Sokratis

2016-08-10

Cell segmentation is a critical step for quantification and monitoring of cell cycle progression, cell migration, and growth control to investigate cellular immune response, embryonic development, tumorigenesis, and drug effects on live cells in time-lapse microscopy images. In this study, we propose a joint spatio-temporal diffusion and region-based level-set optimization approach for moving cell segmentation. Moving regions are initially detected in each set of three consecutive sequence images by numerically solving a system of coupled spatio-temporal partial differential equations. In order to standardize intensities of each frame, we apply a histogram transformation approach to match the pixel intensities of each processed frame with an intensity distribution model learned from all frames of the sequence during the training stage. After the spatio-temporal diffusion stage is completed, we compute the edge map by nonparametric density estimation using Parzen kernels. This process is followed by watershed-based segmentation and moving cell detection. We use this result as an initial level-set function to evolve the cell boundaries, refine the delineation, and optimize the final segmentation result. We applied this method to several datasets of fluorescence microscopy images with varying levels of difficulty with respect to cell density, resolution, contrast, and signal-to-noise ratio. We compared the results with those produced by Chan and Vese segmentation, a temporally linked level-set technique, and nonlinear diffusion-based segmentation. We validated all segmentation techniques against reference masks provided by the international Cell Tracking Challenge consortium. The proposed approach delineated cells with an average Dice similarity coefficient of 89 % over a variety of simulated and real fluorescent image sequences. It yielded average improvements of 11 % in segmentation accuracy compared to both strictly spatial and temporally linked Chan-Vese techniques, and 4 % compared to the nonlinear spatio-temporal diffusion method. Despite the wide variation in cell shape, density, mitotic events, and image quality among the datasets, our proposed method produced promising segmentation results. These results indicate the efficiency and robustness of this method especially for mitotic events and low SNR imaging, enabling the application of subsequent quantification tasks.

Analysis of Agreement of Retinal-Layer Thickness Measures Derived from the Segmentation of Horizontal and Vertical Spectralis OCT Macular Scans.

PubMed

Gonzalez Caldito, Natalia; Antony, Bhavna; He, Yufan; Lang, Andrew; Nguyen, James; Rothman, Alissa; Ogbuokiri, Esther; Avornu, Ama; Balcer, Laura; Frohman, Elliot; Frohman, Teresa C; Bhargava, Pavan; Prince, Jerry; Calabresi, Peter A; Saidha, Shiv

2018-03-01

Optical coherence tomography (OCT) is a reliable method used to quantify discrete layers of the retina. Spectralis OCT is a device used for this purpose. Spectralis OCT macular scan imaging acquisition can be obtained on either the horizontal or vertical plane. The vertical protocol has been proposed as favorable, due to postulated reduction in confound of Henle's fibers on segmentation-derived metrics. Yet, agreement of the segmentation measures of horizontal and vertical macular scans remains unexplored. Our aim was to determine this agreement. Horizontal and vertical macular scans on Spectralis OCT were acquired in 20 healthy controls (HCs) and 20 multiple sclerosis (MS) patients. All scans were segmented using Heidelberg software and a Johns Hopkins University (JHU)-developed method. Agreement was analyzed using Bland-Altman analyses and intra-class correlation coefficients (ICCs). Using both segmentation techniques, mean differences (agreement at the cohort level) in the thicknesses of all macular layers derived from both acquisition protocols in MS patients and HCs were narrow (<1 µm), while the limits of agreement (LOA) (agreement at the individual level) were wider. Using JHU segmentation mean differences (and LOA) for the macular retinal nerve fiber layer (RNFL) and ganglion cell layer + inner plexiform layer (GCIP) in MS were 0.21 µm (-1.57-1.99 µm) and -0.36 µm (-1.44-1.37 µm), respectively. OCT segmentation measures of discrete retinal-layer thicknesses derived from both vertical and horizontal protocols on Spectralis OCT agree excellently at the cohort level (narrow mean differences), but only moderately at the individual level (wide LOA). This suggests patients scanned using either protocol should continue to be scanned with the same protocol. However, due to excellent agreement at the cohort level, measures derived from both acquisitions can be pooled for outcome purposes in clinical trials.

Automatic Cell Segmentation Using a Shape-Classification Model in Immunohistochemically Stained Cytological Images

NASA Astrophysics Data System (ADS)

Shah, Shishir

This paper presents a segmentation method for detecting cells in immunohistochemically stained cytological images. A two-phase approach to segmentation is used where an unsupervised clustering approach coupled with cluster merging based on a fitness function is used as the first phase to obtain a first approximation of the cell locations. A joint segmentation-classification approach incorporating ellipse as a shape model is used as the second phase to detect the final cell contour. The segmentation model estimates a multivariate density function of low-level image features from training samples and uses it as a measure of how likely each image pixel is to be a cell. This estimate is constrained by the zero level set, which is obtained as a solution to an implicit representation of an ellipse. Results of segmentation are presented and compared to ground truth measurements.

Efficient globally optimal segmentation of cells in fluorescence microscopy images using level sets and convex energy functionals.

PubMed

Bergeest, Jan-Philip; Rohr, Karl

2012-10-01

In high-throughput applications, accurate and efficient segmentation of cells in fluorescence microscopy images is of central importance for the quantification of protein expression and the understanding of cell function. We propose an approach for segmenting cell nuclei which is based on active contours using level sets and convex energy functionals. Compared to previous work, our approach determines the global solution. Thus, the approach does not suffer from local minima and the segmentation result does not depend on the initialization. We consider three different well-known energy functionals for active contour-based segmentation and introduce convex formulations of these functionals. We also suggest a numeric approach for efficiently computing the solution. The performance of our approach has been evaluated using fluorescence microscopy images from different experiments comprising different cell types. We have also performed a quantitative comparison with previous segmentation approaches. Copyright © 2012 Elsevier B.V. All rights reserved.

Establishment of segment polarity in the ectoderm of the leech Helobdella

NASA Technical Reports Server (NTRS)

Seaver, E. C.; Shankland, M.

2001-01-01

The segmented ectoderm and mesoderm of the leech arise via a stereotyped cell lineage from embryonic stem cells called teloblasts. Each teloblast gives rise to a column of primary blast cell daughters, and the blast cells generate descendant clones that serve as the segmental repeats of their particular teloblast lineage. We have examined the mechanism by which the leech primary blast cell clones acquire segment polarity - i.e. a fixed sequence of positional values ordered along the anteroposterior axis of the segmental repeat. In the O and P teloblast lineages, the earliest divisions of the primary blast cell segregate anterior and posterior cell fates along the anteroposterior axis. Using a laser microbeam, we ablated single cells from both o and p blast cell clones at stages when the clone was two to four cells in length. The developmental fate of the remaining cells was characterized with rhodamine-dextran lineage tracer. Twelve different progeny cells were ablated, and in every case the ablation eliminated the normal descendants of the ablated cell while having little or no detectable effect on the developmental fate of the remaining cells. This included experiments in which we specifically ablated those blast cell progeny that are known to express the engrailed gene, or their lineal precursors. These findings confirm and extend a previous study by showing that the establishment of segment polarity in the leech ectoderm is largely independent of cell interactions conveyed along the anteroposterior axis. Both intercellular signaling and engrailed expression play an important role in the segment polarity specification of the Drosophila embryo, and our findings suggest that there may be little or no conservation of this developmental mechanism between those two organisms.

Comparing Individual Tree Segmentation Based on High Resolution Multispectral Image and Lidar Data

NASA Astrophysics Data System (ADS)

Xiao, P.; Kelly, M.; Guo, Q.

2014-12-01

This study compares the use of high-resolution multispectral WorldView images and high density Lidar data for individual tree segmentation. The application focuses on coniferous and deciduous forests in the Sierra Nevada Mountains. The tree objects are obtained in two ways: a hybrid region-merging segmentation method with multispectral images, and a top-down and bottom-up region-growing method with Lidar data. The hybrid region-merging method is used to segment individual tree from multispectral images. It integrates the advantages of global-oriented and local-oriented region-merging strategies into a unified framework. The globally most-similar pair of regions is used to determine the starting point of a growing region. The merging iterations are constrained within the local vicinity, thus the segmentation is accelerated and can reflect the local context. The top-down region-growing method is adopted in coniferous forest to delineate individual tree from Lidar data. It exploits the spacing between the tops of trees to identify and group points into a single tree based on simple rules of proximity and likely tree shape. The bottom-up region-growing method based on the intensity and 3D structure of Lidar data is applied in deciduous forest. It segments tree trunks based on the intensity and topological relationships of the points, and then allocate other points to exact tree crowns according to distance. The accuracies for each method are evaluated with field survey data in several test sites, covering dense and sparse canopy. Three types of segmentation results are produced: true positive represents a correctly segmented individual tree, false negative represents a tree that is not detected and assigned to a nearby tree, and false positive represents that a point or pixel cluster is segmented as a tree that does not in fact exist. They respectively represent correct-, under-, and over-segmentation. Three types of index are compared for segmenting individual tree from multispectral image and Lidar data: recall, precision and F-score. This work explores the tradeoff between the expensive Lidar data and inexpensive multispectral image. The conclusion will guide the optimal data selection in different density canopy areas for individual tree segmentation, and contribute to the field of forest remote sensing.

Comparison of parameter-adapted segmentation methods for fluorescence micrographs.

PubMed

Held, Christian; Palmisano, Ralf; Häberle, Lothar; Hensel, Michael; Wittenberg, Thomas

2011-11-01

Interpreting images from fluorescence microscopy is often a time-consuming task with poor reproducibility. Various image processing routines that can help investigators evaluate the images are therefore useful. The critical aspect for a reliable automatic image analysis system is a robust segmentation algorithm that can perform accurate segmentation for different cell types. In this study, several image segmentation methods were therefore compared and evaluated in order to identify the most appropriate segmentation schemes that are usable with little new parameterization and robustly with different types of fluorescence-stained cells for various biological and biomedical tasks. The study investigated, compared, and enhanced four different methods for segmentation of cultured epithelial cells. The maximum-intensity linking (MIL) method, an improved MIL, a watershed method, and an improved watershed method based on morphological reconstruction were used. Three manually annotated datasets consisting of 261, 817, and 1,333 HeLa or L929 cells were used to compare the different algorithms. The comparisons and evaluations showed that the segmentation performance of methods based on the watershed transform was significantly superior to the performance of the MIL method. The results also indicate that using morphological opening by reconstruction can improve the segmentation of cells stained with a marker that exhibits the dotted surface of cells. Copyright © 2011 International Society for Advancement of Cytometry.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Renslow, Ryan S.; Lindemann, Stephen R.; Cole, Jessica K.

EElucidating nutrient exchange in microbial communities is an important step in understanding the relationships between microbial systems and global biogeochemical cycles, but these communities are complex and the interspecies interactions that occur within them are not well understood. Phototrophic consortia are useful and relevant experimental systems to investigate such interactions as they are not only prevalent in the environment, but some are cultivable in vivo and amenable to controlled scientific experimentation. High spatial resolution secondary ion mass spectrometry (NanoSIMS) is a powerful tool capable of visualizing the metabolic activities of single cells within a biofilm, but quantitative analysis of themore » resulting data has typically been a manual process, resulting in a task that is both laborious and susceptible to human error. Here, we describe the creation and application of a semi-automated image-processing pipeline that can analyze NanoSIMS-generated data of phototrophic biofilms. The tool employs an image analysis process, which includes both elemental and morphological segmentation, producing a final segmented image that allows for discrimination between autotrophic and heterotrophic biomass, the detection of individual cyanobacterial filaments and heterotrophic cells, the quantification of isotopic incorporation of individual heterotrophic cells, and calculation of relevant population statistics. We demonstrate the functionality of the tool by using it to analyze the uptake of 15N provided as either nitrate or ammonium through the unicyanobacterial consortium UCC-O and imaged via NanoSIMS. We found that the degree of 15N incorporation by individual cells was highly variable when labeled with 15NH4 +, but much more even when biofilms were labeled with 15NO3-. In the 15NH4 +-amended biofilms, the heterotrophic distribution of 15N incorporation was highly skewed, with a large population showing moderate 15N incorporation and a small number of organisms displaying very high 15N uptake. The results showed that analysis of NanoSIMS data can be performed in a way that allows for quantitation of the elemental uptake of individual cells, a technique necessary for advancing research into the metabolic networks that exist within biofilms with statistical analyses that are supported by automated, user-friendly processes.« less

Automated MRI segmentation for individualized modeling of current flow in the human head.

PubMed

Huang, Yu; Dmochowski, Jacek P; Su, Yuzhuo; Datta, Abhishek; Rorden, Christopher; Parra, Lucas C

2013-12-01

High-definition transcranial direct current stimulation (HD-tDCS) and high-density electroencephalography require accurate models of current flow for precise targeting and current source reconstruction. At a minimum, such modeling must capture the idiosyncratic anatomy of the brain, cerebrospinal fluid (CSF) and skull for each individual subject. Currently, the process to build such high-resolution individualized models from structural magnetic resonance images requires labor-intensive manual segmentation, even when utilizing available automated segmentation tools. Also, accurate placement of many high-density electrodes on an individual scalp is a tedious procedure. The goal was to develop fully automated techniques to reduce the manual effort in such a modeling process. A fully automated segmentation technique based on Statical Parametric Mapping 8, including an improved tissue probability map and an automated correction routine for segmentation errors, was developed, along with an automated electrode placement tool for high-density arrays. The performance of these automated routines was evaluated against results from manual segmentation on four healthy subjects and seven stroke patients. The criteria include segmentation accuracy, the difference of current flow distributions in resulting HD-tDCS models and the optimized current flow intensities on cortical targets. The segmentation tool can segment out not just the brain but also provide accurate results for CSF, skull and other soft tissues with a field of view extending to the neck. Compared to manual results, automated segmentation deviates by only 7% and 18% for normal and stroke subjects, respectively. The predicted electric fields in the brain deviate by 12% and 29% respectively, which is well within the variability observed for various modeling choices. Finally, optimized current flow intensities on cortical targets do not differ significantly. Fully automated individualized modeling may now be feasible for large-sample EEG research studies and tDCS clinical trials.

Cell and current collector felt arrangement for solid oxide electrochemical cell combinations

DOEpatents

Reichner, Philip

1988-01-01

A solid electrolyte electrochemical cell combination 1 is made, comprising an annular, axially elongated, inner electrode 2 containing at least one interior gas feed conduit 3; annular solid electrolyte segments 4 around and covering portions of the inner electrode; annular outer electrode segments 6 around and covering portions of the electrolyte segments; electronically conducting, non-porous, interconnection material 5 disposed between electrolyte segments and in contact with the inner electrode, and electronically conducting, porous, metal fiber current collector felts 7 disposed on top of the non-porous interconnect material and outer electrode segments, where both the non-porous interconnect material and the porous metal felts are disposed circumferentially about the cell, transversely to the axial length of the cell and the inner electrode is continuous for the entire axial length of the cell combination.

A proposed framework for consensus-based lung tumour volume auto-segmentation in 4D computed tomography imaging

NASA Astrophysics Data System (ADS)

Martin, Spencer; Brophy, Mark; Palma, David; Louie, Alexander V.; Yu, Edward; Yaremko, Brian; Ahmad, Belal; Barron, John L.; Beauchemin, Steven S.; Rodrigues, George; Gaede, Stewart

2015-02-01

This work aims to propose and validate a framework for tumour volume auto-segmentation based on ground-truth estimates derived from multi-physician input contours to expedite 4D-CT based lung tumour volume delineation. 4D-CT datasets of ten non-small cell lung cancer (NSCLC) patients were manually segmented by 6 physicians. Multi-expert ground truth (GT) estimates were constructed using the STAPLE algorithm for the gross tumour volume (GTV) on all respiratory phases. Next, using a deformable model-based method, multi-expert GT on each individual phase of the 4D-CT dataset was propagated to all other phases providing auto-segmented GTVs and motion encompassing internal gross target volumes (IGTVs) based on GT estimates (STAPLE) from each respiratory phase of the 4D-CT dataset. Accuracy assessment of auto-segmentation employed graph cuts for 3D-shape reconstruction and point-set registration-based analysis yielding volumetric and distance-based measures. STAPLE-based auto-segmented GTV accuracy ranged from (81.51  ±  1.92) to (97.27  ±  0.28)% volumetric overlap of the estimated ground truth. IGTV auto-segmentation showed significantly improved accuracies with reduced variance for all patients ranging from 90.87 to 98.57% volumetric overlap of the ground truth volume. Additional metrics supported these observations with statistical significance. Accuracy of auto-segmentation was shown to be largely independent of selection of the initial propagation phase. IGTV construction based on auto-segmented GTVs within the 4D-CT dataset provided accurate and reliable target volumes compared to manual segmentation-based GT estimates. While inter-/intra-observer effects were largely mitigated, the proposed segmentation workflow is more complex than that of current clinical practice and requires further development.

A proposed framework for consensus-based lung tumour volume auto-segmentation in 4D computed tomography imaging.

PubMed

Martin, Spencer; Brophy, Mark; Palma, David; Louie, Alexander V; Yu, Edward; Yaremko, Brian; Ahmad, Belal; Barron, John L; Beauchemin, Steven S; Rodrigues, George; Gaede, Stewart

2015-02-21

This work aims to propose and validate a framework for tumour volume auto-segmentation based on ground-truth estimates derived from multi-physician input contours to expedite 4D-CT based lung tumour volume delineation. 4D-CT datasets of ten non-small cell lung cancer (NSCLC) patients were manually segmented by 6 physicians. Multi-expert ground truth (GT) estimates were constructed using the STAPLE algorithm for the gross tumour volume (GTV) on all respiratory phases. Next, using a deformable model-based method, multi-expert GT on each individual phase of the 4D-CT dataset was propagated to all other phases providing auto-segmented GTVs and motion encompassing internal gross target volumes (IGTVs) based on GT estimates (STAPLE) from each respiratory phase of the 4D-CT dataset. Accuracy assessment of auto-segmentation employed graph cuts for 3D-shape reconstruction and point-set registration-based analysis yielding volumetric and distance-based measures. STAPLE-based auto-segmented GTV accuracy ranged from (81.51  ±  1.92) to (97.27  ±  0.28)% volumetric overlap of the estimated ground truth. IGTV auto-segmentation showed significantly improved accuracies with reduced variance for all patients ranging from 90.87 to 98.57% volumetric overlap of the ground truth volume. Additional metrics supported these observations with statistical significance. Accuracy of auto-segmentation was shown to be largely independent of selection of the initial propagation phase. IGTV construction based on auto-segmented GTVs within the 4D-CT dataset provided accurate and reliable target volumes compared to manual segmentation-based GT estimates. While inter-/intra-observer effects were largely mitigated, the proposed segmentation workflow is more complex than that of current clinical practice and requires further development.

Automated profiling of individual cell-cell interactions from high-throughput time-lapse imaging microscopy in nanowell grids (TIMING).

PubMed

Merouane, Amine; Rey-Villamizar, Nicolas; Lu, Yanbin; Liadi, Ivan; Romain, Gabrielle; Lu, Jennifer; Singh, Harjeet; Cooper, Laurence J N; Varadarajan, Navin; Roysam, Badrinath

2015-10-01

There is a need for effective automated methods for profiling dynamic cell-cell interactions with single-cell resolution from high-throughput time-lapse imaging data, especially, the interactions between immune effector cells and tumor cells in adoptive immunotherapy. Fluorescently labeled human T cells, natural killer cells (NK), and various target cells (NALM6, K562, EL4) were co-incubated on polydimethylsiloxane arrays of sub-nanoliter wells (nanowells), and imaged using multi-channel time-lapse microscopy. The proposed cell segmentation and tracking algorithms account for cell variability and exploit the nanowell confinement property to increase the yield of correctly analyzed nanowells from 45% (existing algorithms) to 98% for wells containing one effector and a single target, enabling automated quantification of cell locations, morphologies, movements, interactions, and deaths without the need for manual proofreading. Automated analysis of recordings from 12 different experiments demonstrated automated nanowell delineation accuracy >99%, automated cell segmentation accuracy >95%, and automated cell tracking accuracy of 90%, with default parameters, despite variations in illumination, staining, imaging noise, cell morphology, and cell clustering. An example analysis revealed that NK cells efficiently discriminate between live and dead targets by altering the duration of conjugation. The data also demonstrated that cytotoxic cells display higher motility than non-killers, both before and during contact. broysam@central.uh.edu or nvaradar@central.uh.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Platelet adhesion and human umbilical vein endothelial cell cytocompatibility of biodegradable segmented polyurethanes prepared with 4,4'-methylene bis(cyclohexyl isocyanate), poly(caprolactone) diol and butanediol or dithioerythritol as chain extenders.

PubMed

Chan-Chan, L H; Vargas-Coronado, R F; Cervantes-Uc, J M; Cauich-Rodríguez, J V; Rath, R; Phelps, E A; García, A J; San Román Del Barrio, J; Parra, J; Merhi, Y; Tabrizian, M

2013-08-01

Biodegradable segmented polyurethanes were prepared with poly(caprolactone) diol as a soft segment, 4,4'-methylene bis(cyclohexyl isocyanate) (HMDI) and either butanediol or dithioerythritol as chain extenders. Platelet adhesion was similar in all segmented polyurethanes studied and not different from Tecoflex® although an early stage of activation was observed on biodegradable segmented polyurethane prepared with dithioerythritol. Relative viability was higher than 80% on human umbilical vein endothelial cells in contact with biodegradable segmented polyurethane extracts after 1, 2 and 7 days. Furthermore, both biodegradable segmented polyurethane materials supported human umbilical vein endothelial cell adhesion, spreading, and viability similar to Tecoflex® medical-grade polyurethane. These biodegradable segmented polyurethanes represent promising materials for cardiovascular applications.

Leech segmental repeats develop normally in the absence of signals from either anterior or posterior segments

NASA Technical Reports Server (NTRS)

Seaver, E. C.; Shankland, M.

2000-01-01

We have investigated whether the development of segmental repeats is autonomous in the embryo of the leech Helobdella robusta. The segmental tissues of the germinal band arise from progeny of five stem cells called teloblasts. Asymmetric divisions of the teloblasts form chains of segment founder cells (called primary blast cells) that divide in a stereotypical manner to produce differentiated descendants. Using two distinct techniques, we have looked for potential interactions between neighboring blast cell clones along the anterior-posterior axis. In one technique, we prevented the birth of primary blast cells by injection of DNase I into the teloblast, thereby depriving the last blast cell produced before the ablation of its normal posterior neighbors. We also ablated single blast cells with a laser microbeam, which allowed us to assess potential signals acting on either more anterior or more posterior primary blast cell clones. Our results suggest that interactions along the anterior-posterior axis between neighboring primary blast cell clones are not required for development of normal segmental organization within the blast cell clone. We also examined the possibility that blast cells receive redundant signals from both anterior and posterior neighboring clones and that either is sufficient for normal development. Using double blast cell laser ablations to isolate a primary blast cell clone by removal of both its anterior and its posterior neighbor, we found that the isolated clone still develops normally. These results reveal that the fundamental segmental repeat in the leech embryo, the primary blast cell clone, can develop normally in the apparent absence of signals from adjacent repeats along the anterior-posterior axis.

Fast globally optimal segmentation of cells in fluorescence microscopy images.

PubMed

Bergeest, Jan-Philip; Rohr, Karl

2011-01-01

Accurate and efficient segmentation of cells in fluorescence microscopy images is of central importance for the quantification of protein expression in high-throughput screening applications. We propose a new approach for segmenting cell nuclei which is based on active contours and convex energy functionals. Compared to previous work, our approach determines the global solution. Thus, the approach does not suffer from local minima and the segmentation result does not depend on the initialization. We also suggest a numeric approach for efficiently computing the solution. The performance of our approach has been evaluated using fluorescence microscopy images of different cell types. We have also performed a quantitative comparison with previous segmentation approaches.

Metric Learning to Enhance Hyperspectral Image Segmentation

NASA Technical Reports Server (NTRS)

Thompson, David R.; Castano, Rebecca; Bue, Brian; Gilmore, Martha S.

2013-01-01

Unsupervised hyperspectral image segmentation can reveal spatial trends that show the physical structure of the scene to an analyst. They highlight borders and reveal areas of homogeneity and change. Segmentations are independently helpful for object recognition, and assist with automated production of symbolic maps. Additionally, a good segmentation can dramatically reduce the number of effective spectra in an image, enabling analyses that would otherwise be computationally prohibitive. Specifically, using an over-segmentation of the image instead of individual pixels can reduce noise and potentially improve the results of statistical post-analysis. In this innovation, a metric learning approach is presented to improve the performance of unsupervised hyperspectral image segmentation. The prototype demonstrations attempt a superpixel segmentation in which the image is conservatively over-segmented; that is, the single surface features may be split into multiple segments, but each individual segment, or superpixel, is ensured to have homogenous mineralogy.

AutoCellSeg: robust automatic colony forming unit (CFU)/cell analysis using adaptive image segmentation and easy-to-use post-editing techniques.

PubMed

Khan, Arif Ul Maula; Torelli, Angelo; Wolf, Ivo; Gretz, Norbert

2018-05-08

In biological assays, automated cell/colony segmentation and counting is imperative owing to huge image sets. Problems occurring due to drifting image acquisition conditions, background noise and high variation in colony features in experiments demand a user-friendly, adaptive and robust image processing/analysis method. We present AutoCellSeg (based on MATLAB) that implements a supervised automatic and robust image segmentation method. AutoCellSeg utilizes multi-thresholding aided by a feedback-based watershed algorithm taking segmentation plausibility criteria into account. It is usable in different operation modes and intuitively enables the user to select object features interactively for supervised image segmentation method. It allows the user to correct results with a graphical interface. This publicly available tool outperforms tools like OpenCFU and CellProfiler in terms of accuracy and provides many additional useful features for end-users.

Robust Nucleus/Cell Detection and Segmentation in Digital Pathology and Microscopy Images: A Comprehensive Review.

PubMed

Xing, Fuyong; Yang, Lin

2016-01-01

Digital pathology and microscopy image analysis is widely used for comprehensive studies of cell morphology or tissue structure. Manual assessment is labor intensive and prone to interobserver variations. Computer-aided methods, which can significantly improve the objectivity and reproducibility, have attracted a great deal of interest in recent literature. Among the pipeline of building a computer-aided diagnosis system, nucleus or cell detection and segmentation play a very important role to describe the molecular morphological information. In the past few decades, many efforts have been devoted to automated nucleus/cell detection and segmentation. In this review, we provide a comprehensive summary of the recent state-of-the-art nucleus/cell segmentation approaches on different types of microscopy images including bright-field, phase-contrast, differential interference contrast, fluorescence, and electron microscopies. In addition, we discuss the challenges for the current methods and the potential future work of nucleus/cell detection and segmentation.

Automatic cell detection and segmentation from H and E stained pathology slides using colorspace decorrelation stretching

NASA Astrophysics Data System (ADS)

Peikari, Mohammad; Martel, Anne L.

2016-03-01

Purpose: Automatic cell segmentation plays an important role in reliable diagnosis and prognosis of patients. Most of the state-of-the-art cell detection and segmentation techniques focus on complicated methods to subtract foreground cells from the background. In this study, we introduce a preprocessing method which leads to a better detection and segmentation results compared to a well-known state-of-the-art work. Method: We transform the original red-green-blue (RGB) space into a new space defined by the top eigenvectors of the RGB space. Stretching is done by manipulating the contrast of each pixel value to equalize the color variances. New pixel values are then inverse transformed to the original RGB space. This altered RGB image is then used to segment cells. Result: The validation of our method with a well-known state-of-the-art technique revealed a statistically significant improvement on an identical validation set. We achieved a mean F1-score of 0.901. Conclusion: Preprocessing steps to decorrelate colorspaces may improve cell segmentation performances.

Colonization of dodder, Cuscuta indecora, by 'Candidatus Liberibacter asiaticus' and 'Ca. L. americanus'.

PubMed

Hartung, John S; Paul, Cristina; Achor, Diann; Brlansky, R H

2010-08-01

Huanglongbing, or citrus greening, threatens the global citrus industry. The presumptive pathogens, 'Candidatus Liberibacter asiaticus' and 'Ca. L. americanus' can be transferred from citrus to more easily studied experimental hosts by using holoparasitic dodder plants. However, the interaction between 'Candidatus Liberibacter' spp. and the dodder has not been studied. We combined quantitative polymerase chain reaction with electron microscopy to show that only 65% of tendrils of Cuscuta indecora grown on 'Ca. Liberibacter' spp.-infected host plants had detectable levels of the pathogen. Among tendrils that were colonized by Liberibacter in at least one 2 cm segment, most were not colonized in all segments. Furthermore, the estimated population levels of the pathogen present in serial 2 cm segments of dodder tendrils varied widely and without any consistent pattern. Thus, there was generally not a concentration gradient of the pathogen from the source plant towards the recipient and populations of the pathogen were sometimes found in the distal segments of the dodder plant but not in the proximal or middle segments. Populations of the pathogens ranged from 2 x 10(2) to 3.0 x 10(8) cells per 2 cm segment. On a fresh weight basis, populations as high as 1.4 x 10(10) cells per g of tissue were observed demonstrating that 'Ca. Liberibacter' spp. multiplies well in Cuscuta indecora. However, 55% of individual stem segments did not contain detectable levels of the pathogen, consistent with a pattern of nonuniform colonization similar to that observed in the much more anatomically complex citrus tree. Colonization of dodder by the pathogen is also nonuniform at the ultrastructural level, with adjacent phloem vessel elements being completely full of the pathogen or free of the pathogen. We also observed bacteria in the phloem vessels that belonged to two distinct size classes based on the diameters of cross sections of cells. In other sections from the same tendrils we observed single bacterial cells that were apparently in the process of differentiating between the large and round forms to the long and thin forms (or vice versa). The process controlling this morphological differentiation of the pathogen is not known. The highly reduced and simplified anatomy of the dodder plant as well as its rapid growth rate compared with citrus, and the ability of the plant to support multiplication of the pathogen to high levels, makes it an interesting host plant for further studies of host-pathogen interactions.

Integrated Quantitative Transcriptome Maps of Human Trisomy 21 Tissues and Cells

PubMed Central

Pelleri, Maria Chiara; Cattani, Chiara; Vitale, Lorenza; Antonaros, Francesca; Strippoli, Pierluigi; Locatelli, Chiara; Cocchi, Guido; Piovesan, Allison; Caracausi, Maria

2018-01-01

Down syndrome (DS) is due to the presence of an extra full or partial chromosome 21 (Hsa21). The identification of genes contributing to DS pathogenesis could be the key to any rational therapy of the associated intellectual disability. We aim at generating quantitative transcriptome maps in DS integrating all gene expression profile datasets available for any cell type or tissue, to obtain a complete model of the transcriptome in terms of both expression values for each gene and segmental trend of gene expression along each chromosome. We used the TRAM (Transcriptome Mapper) software for this meta-analysis, comparing transcript expression levels and profiles between DS and normal brain, lymphoblastoid cell lines, blood cells, fibroblasts, thymus and induced pluripotent stem cells, respectively. TRAM combined, normalized, and integrated datasets from different sources and across diverse experimental platforms. The main output was a linear expression value that may be used as a reference for each of up to 37,181 mapped transcripts analyzed, related to both known genes and expression sequence tag (EST) clusters. An independent example in vitro validation of fibroblast transcriptome map data was performed through “Real-Time” reverse transcription polymerase chain reaction showing an excellent correlation coefficient (r = 0.93, p < 0.0001) with data obtained in silico. The availability of linear expression values for each gene allowed the testing of the gene dosage hypothesis of the expected 3:2 DS/normal ratio for Hsa21 as well as other human genes in DS, in addition to listing genes differentially expressed with statistical significance. Although a fraction of Hsa21 genes escapes dosage effects, Hsa21 genes are selectively over-expressed in DS samples compared to genes from other chromosomes, reflecting a decisive role in the pathogenesis of the syndrome. Finally, the analysis of chromosomal segments reveals a high prevalence of Hsa21 over-expressed segments over the other genomic regions, suggesting, in particular, a specific region on Hsa21 that appears to be frequently over-expressed (21q22). Our complete datasets are released as a new framework to investigate transcription in DS for individual genes as well as chromosomal segments in different cell types and tissues. PMID:29740474

A Fast, Automatic Segmentation Algorithm for Locating and Delineating Touching Cell Boundaries in Imaged Histopathology

PubMed Central

Qi, Xin; Xing, Fuyong; Foran, David J.; Yang, Lin

2013-01-01

Summary Background Automated analysis of imaged histopathology specimens could potentially provide support for improved reliability in detection and classification in a range of investigative and clinical cancer applications. Automated segmentation of cells in the digitized tissue microarray (TMA) is often the prerequisite for quantitative analysis. However overlapping cells usually bring significant challenges for traditional segmentation algorithms. Objectives In this paper, we propose a novel, automatic algorithm to separate overlapping cells in stained histology specimens acquired using bright-field RGB imaging. Methods It starts by systematically identifying salient regions of interest throughout the image based upon their underlying visual content. The segmentation algorithm subsequently performs a quick, voting based seed detection. Finally, the contour of each cell is obtained using a repulsive level set deformable model using the seeds generated in the previous step. We compared the experimental results with the most current literature, and the pixel wise accuracy between human experts' annotation and those generated using the automatic segmentation algorithm. Results The method is tested with 100 image patches which contain more than 1000 overlapping cells. The overall precision and recall of the developed algorithm is 90% and 78%, respectively. We also implement the algorithm on GPU. The parallel implementation is 22 times faster than its C/C++ sequential implementation. Conclusion The proposed overlapping cell segmentation algorithm can accurately detect the center of each overlapping cell and effectively separate each of the overlapping cells. GPU is proven to be an efficient parallel platform for overlapping cell segmentation. PMID:22526139

Comparison of volume estimation methods for pancreatic islet cells

NASA Astrophysics Data System (ADS)

Dvořák, JiřÃ.­; Å vihlík, Jan; Habart, David; Kybic, Jan

2016-03-01

In this contribution we study different methods of automatic volume estimation for pancreatic islets which can be used in the quality control step prior to the islet transplantation. The total islet volume is an important criterion in the quality control. Also, the individual islet volume distribution is interesting -- it has been indicated that smaller islets can be more effective. A 2D image of a microscopy slice containing the islets is acquired. The input of the volume estimation methods are segmented images of individual islets. The segmentation step is not discussed here. We consider simple methods of volume estimation assuming that the islets have spherical or ellipsoidal shape. We also consider a local stereological method, namely the nucleator. The nucleator does not rely on any shape assumptions and provides unbiased estimates if isotropic sections through the islets are observed. We present a simulation study comparing the performance of the volume estimation methods in different scenarios and an experimental study comparing the methods on a real dataset.

Multi-scale Gaussian representation and outline-learning based cell image segmentation.

PubMed

Farhan, Muhammad; Ruusuvuori, Pekka; Emmenlauer, Mario; Rämö, Pauli; Dehio, Christoph; Yli-Harja, Olli

2013-01-01

High-throughput genome-wide screening to study gene-specific functions, e.g. for drug discovery, demands fast automated image analysis methods to assist in unraveling the full potential of such studies. Image segmentation is typically at the forefront of such analysis as the performance of the subsequent steps, for example, cell classification, cell tracking etc., often relies on the results of segmentation. We present a cell cytoplasm segmentation framework which first separates cell cytoplasm from image background using novel approach of image enhancement and coefficient of variation of multi-scale Gaussian scale-space representation. A novel outline-learning based classification method is developed using regularized logistic regression with embedded feature selection which classifies image pixels as outline/non-outline to give cytoplasm outlines. Refinement of the detected outlines to separate cells from each other is performed in a post-processing step where the nuclei segmentation is used as contextual information. We evaluate the proposed segmentation methodology using two challenging test cases, presenting images with completely different characteristics, with cells of varying size, shape, texture and degrees of overlap. The feature selection and classification framework for outline detection produces very simple sparse models which use only a small subset of the large, generic feature set, that is, only 7 and 5 features for the two cases. Quantitative comparison of the results for the two test cases against state-of-the-art methods show that our methodology outperforms them with an increase of 4-9% in segmentation accuracy with maximum accuracy of 93%. Finally, the results obtained for diverse datasets demonstrate that our framework not only produces accurate segmentation but also generalizes well to different segmentation tasks.

Multi-scale Gaussian representation and outline-learning based cell image segmentation

PubMed Central

2013-01-01

Background High-throughput genome-wide screening to study gene-specific functions, e.g. for drug discovery, demands fast automated image analysis methods to assist in unraveling the full potential of such studies. Image segmentation is typically at the forefront of such analysis as the performance of the subsequent steps, for example, cell classification, cell tracking etc., often relies on the results of segmentation. Methods We present a cell cytoplasm segmentation framework which first separates cell cytoplasm from image background using novel approach of image enhancement and coefficient of variation of multi-scale Gaussian scale-space representation. A novel outline-learning based classification method is developed using regularized logistic regression with embedded feature selection which classifies image pixels as outline/non-outline to give cytoplasm outlines. Refinement of the detected outlines to separate cells from each other is performed in a post-processing step where the nuclei segmentation is used as contextual information. Results and conclusions We evaluate the proposed segmentation methodology using two challenging test cases, presenting images with completely different characteristics, with cells of varying size, shape, texture and degrees of overlap. The feature selection and classification framework for outline detection produces very simple sparse models which use only a small subset of the large, generic feature set, that is, only 7 and 5 features for the two cases. Quantitative comparison of the results for the two test cases against state-of-the-art methods show that our methodology outperforms them with an increase of 4-9% in segmentation accuracy with maximum accuracy of 93%. Finally, the results obtained for diverse datasets demonstrate that our framework not only produces accurate segmentation but also generalizes well to different segmentation tasks. PMID:24267488

Using wavelet denoising and mathematical morphology in the segmentation technique applied to blood cells images.

PubMed

Boix, Macarena; Cantó, Begoña

2013-04-01

Accurate image segmentation is used in medical diagnosis since this technique is a noninvasive pre-processing step for biomedical treatment. In this work we present an efficient segmentation method for medical image analysis. In particular, with this method blood cells can be segmented. For that, we combine the wavelet transform with morphological operations. Moreover, the wavelet thresholding technique is used to eliminate the noise and prepare the image for suitable segmentation. In wavelet denoising we determine the best wavelet that shows a segmentation with the largest area in the cell. We study different wavelet families and we conclude that the wavelet db1 is the best and it can serve for posterior works on blood pathologies. The proposed method generates goods results when it is applied on several images. Finally, the proposed algorithm made in MatLab environment is verified for a selected blood cells.

Fast and robust segmentation of white blood cell images by self-supervised learning.

PubMed

Zheng, Xin; Wang, Yong; Wang, Guoyou; Liu, Jianguo

2018-04-01

A fast and accurate white blood cell (WBC) segmentation remains a challenging task, as different WBCs vary significantly in color and shape due to cell type differences, staining technique variations and the adhesion between the WBC and red blood cells. In this paper, a self-supervised learning approach, consisting of unsupervised initial segmentation and supervised segmentation refinement, is presented. The first module extracts the overall foreground region from the cell image by K-means clustering, and then generates a coarse WBC region by touching-cell splitting based on concavity analysis. The second module further uses the coarse segmentation result of the first module as automatic labels to actively train a support vector machine (SVM) classifier. Then, the trained SVM classifier is further used to classify each pixel of the image and achieve a more accurate segmentation result. To improve its segmentation accuracy, median color features representing the topological structure and a new weak edge enhancement operator (WEEO) handling fuzzy boundary are introduced. To further reduce its time cost, an efficient cluster sampling strategy is also proposed. We tested the proposed approach with two blood cell image datasets obtained under various imaging and staining conditions. The experiment results show that our approach has a superior performance of accuracy and time cost on both datasets. Copyright © 2018 Elsevier Ltd. All rights reserved.

Multiple Hypotheses Image Segmentation and Classification With Application to Dietary Assessment

PubMed Central

Zhu, Fengqing; Bosch, Marc; Khanna, Nitin; Boushey, Carol J.; Delp, Edward J.

2016-01-01

We propose a method for dietary assessment to automatically identify and locate food in a variety of images captured during controlled and natural eating events. Two concepts are combined to achieve this: a set of segmented objects can be partitioned into perceptually similar object classes based on global and local features; and perceptually similar object classes can be used to assess the accuracy of image segmentation. These ideas are implemented by generating multiple segmentations of an image to select stable segmentations based on the classifier’s confidence score assigned to each segmented image region. Automatic segmented regions are classified using a multichannel feature classification system. For each segmented region, multiple feature spaces are formed. Feature vectors in each of the feature spaces are individually classified. The final decision is obtained by combining class decisions from individual feature spaces using decision rules. We show improved accuracy of segmenting food images with classifier feedback. PMID:25561457

Multiple hypotheses image segmentation and classification with application to dietary assessment.

PubMed

Zhu, Fengqing; Bosch, Marc; Khanna, Nitin; Boushey, Carol J; Delp, Edward J

2015-01-01

We propose a method for dietary assessment to automatically identify and locate food in a variety of images captured during controlled and natural eating events. Two concepts are combined to achieve this: a set of segmented objects can be partitioned into perceptually similar object classes based on global and local features; and perceptually similar object classes can be used to assess the accuracy of image segmentation. These ideas are implemented by generating multiple segmentations of an image to select stable segmentations based on the classifier's confidence score assigned to each segmented image region. Automatic segmented regions are classified using a multichannel feature classification system. For each segmented region, multiple feature spaces are formed. Feature vectors in each of the feature spaces are individually classified. The final decision is obtained by combining class decisions from individual feature spaces using decision rules. We show improved accuracy of segmenting food images with classifier feedback.

Classification of Normal and Apoptotic Cells from Fluorescence Microscopy Images Using Generalized Polynomial Chaos and Level Set Function.

PubMed

Du, Yuncheng; Budman, Hector M; Duever, Thomas A

2016-06-01

Accurate automated quantitative analysis of living cells based on fluorescence microscopy images can be very useful for fast evaluation of experimental outcomes and cell culture protocols. In this work, an algorithm is developed for fast differentiation of normal and apoptotic viable Chinese hamster ovary (CHO) cells. For effective segmentation of cell images, a stochastic segmentation algorithm is developed by combining a generalized polynomial chaos expansion with a level set function-based segmentation algorithm. This approach provides a probabilistic description of the segmented cellular regions along the boundary, from which it is possible to calculate morphological changes related to apoptosis, i.e., the curvature and length of a cell's boundary. These features are then used as inputs to a support vector machine (SVM) classifier that is trained to distinguish between normal and apoptotic viable states of CHO cell images. The use of morphological features obtained from the stochastic level set segmentation of cell images in combination with the trained SVM classifier is more efficient in terms of differentiation accuracy as compared with the original deterministic level set method.

U.S. Army Custom Segmentation System

DTIC Science & Technology

2007-06-01

segmentation is individual or intergroup differences in response to marketing - mix variables. Presumptions about segments: •different demands in a...product or service category, •respond differently to changes in the marketing mix Criteria for segments: •The segments must exist in the environment

Creation of Rift Valley Fever Viruses with Four-Segmented Genomes Reveals Flexibility in Bunyavirus Genome Packaging

PubMed Central

Oreshkova, Nadia; Moormann, Rob J. M.; Kortekaas, Jeroen

2014-01-01

ABSTRACT Bunyavirus genomes comprise a small (S), a medium (M), and a large (L) RNA segment of negative polarity. Although the untranslated regions have been shown to comprise signals required for transcription, replication, and encapsidation, the mechanisms that drive the packaging of at least one S, M, and L segment into a single virion to generate infectious virus are largely unknown. One of the most important members of the Bunyaviridae family that causes devastating disease in ruminants and occasionally humans is the Rift Valley fever virus (RVFV). We studied the flexibility of RVFV genome packaging by splitting the glycoprotein precursor gene, encoding the (NSm)GnGc polyprotein, into two individual genes encoding either (NSm)Gn or Gc. Using reverse genetics, six viruses with a segmented glycoprotein precursor gene were rescued, varying from a virus comprising two S-type segments in the absence of an M-type segment to a virus consisting of four segments (RVFV-4s), of which three are M-type. Despite that all virus variants were able to grow in mammalian cell lines, they were unable to spread efficiently in cells of mosquito origin. Moreover, in vivo studies demonstrated that RVFV-4s is unable to cause disseminated infection and disease in mice, even in the presence of the main virulence factor NSs, but induced a protective immune response against a lethal challenge with wild-type virus. In summary, splitting bunyavirus glycoprotein precursor genes provides new opportunities to study bunyavirus genome packaging and offers new methods to develop next-generation live-attenuated bunyavirus vaccines. IMPORTANCE Rift Valley fever virus (RVFV) causes devastating disease in ruminants and occasionally humans. Virions capable of productive infection comprise at least one copy of the small (S), medium (M), and large (L) RNA genome segments. The M segment encodes a glycoprotein precursor (GPC) protein that is cotranslationally cleaved into Gn and Gc, which are required for virus entry and fusion. We studied the flexibility of RVFV genome packaging and developed experimental live-attenuated vaccines by applying a unique strategy based on the splitting of the GnGc open reading frame. Several RVFV variants, varying from viruses comprising two S-type segments to viruses consisting of four segments (RVFV-4s), of which three are M-type, could be rescued and were shown to induce a rapid protective immune response. Altogether, the segmentation of bunyavirus GPCs provides a new method for studying bunyavirus genome packaging and facilitates the development of novel live-attenuated bunyavirus vaccines. PMID:25008937

Creation of Rift Valley fever viruses with four-segmented genomes reveals flexibility in bunyavirus genome packaging.

PubMed

Wichgers Schreur, Paul J; Oreshkova, Nadia; Moormann, Rob J M; Kortekaas, Jeroen

2014-09-01

Bunyavirus genomes comprise a small (S), a medium (M), and a large (L) RNA segment of negative polarity. Although the untranslated regions have been shown to comprise signals required for transcription, replication, and encapsidation, the mechanisms that drive the packaging of at least one S, M, and L segment into a single virion to generate infectious virus are largely unknown. One of the most important members of the Bunyaviridae family that causes devastating disease in ruminants and occasionally humans is the Rift Valley fever virus (RVFV). We studied the flexibility of RVFV genome packaging by splitting the glycoprotein precursor gene, encoding the (NSm)GnGc polyprotein, into two individual genes encoding either (NSm)Gn or Gc. Using reverse genetics, six viruses with a segmented glycoprotein precursor gene were rescued, varying from a virus comprising two S-type segments in the absence of an M-type segment to a virus consisting of four segments (RVFV-4s), of which three are M-type. Despite that all virus variants were able to grow in mammalian cell lines, they were unable to spread efficiently in cells of mosquito origin. Moreover, in vivo studies demonstrated that RVFV-4s is unable to cause disseminated infection and disease in mice, even in the presence of the main virulence factor NSs, but induced a protective immune response against a lethal challenge with wild-type virus. In summary, splitting bunyavirus glycoprotein precursor genes provides new opportunities to study bunyavirus genome packaging and offers new methods to develop next-generation live-attenuated bunyavirus vaccines. Rift Valley fever virus (RVFV) causes devastating disease in ruminants and occasionally humans. Virions capable of productive infection comprise at least one copy of the small (S), medium (M), and large (L) RNA genome segments. The M segment encodes a glycoprotein precursor (GPC) protein that is cotranslationally cleaved into Gn and Gc, which are required for virus entry and fusion. We studied the flexibility of RVFV genome packaging and developed experimental live-attenuated vaccines by applying a unique strategy based on the splitting of the GnGc open reading frame. Several RVFV variants, varying from viruses comprising two S-type segments to viruses consisting of four segments (RVFV-4s), of which three are M-type, could be rescued and were shown to induce a rapid protective immune response. Altogether, the segmentation of bunyavirus GPCs provides a new method for studying bunyavirus genome packaging and facilitates the development of novel live-attenuated bunyavirus vaccines. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

A new level set model for cell image segmentation

NASA Astrophysics Data System (ADS)

Ma, Jing-Feng; Hou, Kai; Bao, Shang-Lian; Chen, Chun

2011-02-01

In this paper we first determine three phases of cell images: background, cytoplasm and nucleolus according to the general physical characteristics of cell images, and then develop a variational model, based on these characteristics, to segment nucleolus and cytoplasm from their relatively complicated backgrounds. In the meantime, the preprocessing obtained information of cell images using the OTSU algorithm is used to initialize the level set function in the model, which can speed up the segmentation and present satisfactory results in cell image processing.

Using Cell-ID 1.4 with R for Microscope-Based Cytometry

PubMed Central

Bush, Alan; Chernomoretz, Ariel; Yu, Richard; Gordon, Andrew

2012-01-01

This unit describes a method for quantifying various cellular features (e.g., volume, total and subcellular fluorescence localization) from sets of microscope images of individual cells. It includes procedures for tracking cells over time. One purposefully defocused transmission image (sometimes referred to as bright-field or BF) is acquired to segment the image and locate each cell. Fluorescent images (one for each of the color channels to be analyzed) are then acquired by conventional wide-field epifluorescence or confocal microscopy. This method uses the image processing capabilities of Cell-ID (Gordon et al., 2007, as updated here) and data analysis by the statistical programming framework R (R-Development-Team, 2008), which we have supplemented with a package of routines for analyzing Cell-ID output. Both Cell-ID and the analysis package are open-source. PMID:23026908

In Vivo Imaging of Human Cone Photoreceptor Inner Segments

PubMed Central

Scoles, Drew; Sulai, Yusufu N.; Langlo, Christopher S.; Fishman, Gerald A.; Curcio, Christine A.; Carroll, Joseph; Dubra, Alfredo

2014-01-01

Purpose. An often overlooked prerequisite to cone photoreceptor gene therapy development is residual photoreceptor structure that can be rescued. While advances in adaptive optics (AO) retinal imaging have recently enabled direct visualization of individual cone and rod photoreceptors in the living human retina, these techniques largely detect strongly directionally-backscattered (waveguided) light from normal intact photoreceptors. This represents a major limitation in using existing AO imaging to quantify structure of remnant cones in degenerating retina. Methods. Photoreceptor inner segment structure was assessed with a novel AO scanning light ophthalmoscopy (AOSLO) differential phase technique, that we termed nonconfocal split-detector, in two healthy subjects and four subjects with achromatopsia. Ex vivo preparations of five healthy donor eyes were analyzed for comparison of inner segment diameter to that measured in vivo with split-detector AOSLO. Results. Nonconfocal split-detector AOSLO reveals the photoreceptor inner segment with or without the presence of a waveguiding outer segment. The diameter of inner segments measured in vivo is in good agreement with histology. A substantial number of foveal and parafoveal cone photoreceptors with apparently intact inner segments were identified in patients with the inherited disease achromatopsia. Conclusions. The application of nonconfocal split-detector to emerging human gene therapy trials will improve the potential of therapeutic success, by identifying patients with sufficient retained photoreceptor structure to benefit the most from intervention. Additionally, split-detector imaging may be useful for studies of other retinal degenerations such as AMD, retinitis pigmentosa, and choroideremia where the outer segment is lost before the remainder of the photoreceptor cell. PMID:24906859

On the importance of FIB-SEM specific segmentation algorithms for porous media

DOE Office of Scientific and Technical Information (OSTI.GOV)

Salzer, Martin, E-mail: martin.salzer@uni-ulm.de; Thiele, Simon, E-mail: simon.thiele@imtek.uni-freiburg.de; Zengerle, Roland, E-mail: zengerle@imtek.uni-freiburg.de

2014-09-15

A new algorithmic approach to segmentation of highly porous three dimensional image data gained by focused ion beam tomography is described which extends the key-principle of local threshold backpropagation described in Salzer et al. (2012). The technique of focused ion beam tomography has shown to be capable of imaging the microstructure of functional materials. In order to perform a quantitative analysis on the corresponding microstructure a segmentation task needs to be performed. However, algorithmic segmentation of images obtained with focused ion beam tomography is a challenging problem for highly porous materials if filling the pore phase, e.g. with epoxy resin,more » is difficult. The gray intensities of individual voxels are not sufficient to determine the phase represented by them and usual thresholding methods are not applicable. We thus propose a new approach to segmentation that pays respect to the specifics of the imaging process of focused ion beam tomography. As an application of our approach, the segmentation of three dimensional images for a cathode material used in polymer electrolyte membrane fuel cells is discussed. We show that our approach preserves significantly more of the original nanostructure than a thresholding approach. - Highlights: • We describe a new approach to the segmentation of FIB-SEM images of porous media. • The first and last occurrences of structures are detected by analysing the z-profiles. • The algorithm is validated by comparing it to a manual segmentation. • The new approach shows significantly less artifacts than a thresholding approach. • A structural analysis also shows improved results for the obtained microstructure.« less

Gonad establishment during asexual reproduction in the annelid Pristina leidyi.

PubMed

Özpolat, B Duygu; Bely, Alexandra E

2015-09-01

Animals that can reproduce by both asexual agametic reproduction and sexual reproduction must transmit or re-establish their germ line post-embryonically. Although such a dual reproductive mode has evolved repeatedly among animals, how asexually produced individuals establish their germ line remains poorly understood in most groups. We investigated germ line development in the annelid Pristina leidyi, a species that typically reproduces asexually by paratomic fission, intercalating a new tail and head in the middle of the body followed by splitting. We found that in fissioning individuals, gonads occur in anterior segments in the anterior-most individual as well as in new heads forming within fission zones. Homologs of the germ line/multipotency genes piwi, vasa, and nanos are expressed in the gonads, as well as in proliferative tissues including the posterior growth zone, fission zone, and regeneration blastema. In fissioning animals, certain cells on the ventral nerve cord express a homolog of piwi, are abundant near fission zones, and sometimes make contact with gonads. Such cells are typically undetectable near the blastema and posterior growth zone. Time-lapse imaging provides direct evidence that cells on the ventral nerve cord migrate preferentially towards fission zones. Our findings indicate that gonads form routinely in fissioning individuals, that a population of piwi-positive cells on the ventral nerve cord is associated with fission and gonads, and that cells resembling these piwi-positive cells migrate along the ventral nerve cord. We suggest that the piwi-positive ventral cells are germ cells that transmit the germ line across asexually produced individuals via migration along the ventral nerve cord. Copyright © 2015 Elsevier Inc. All rights reserved.

Automated MRI Segmentation for Individualized Modeling of Current Flow in the Human Head

PubMed Central

Huang, Yu; Dmochowski, Jacek P.; Su, Yuzhuo; Datta, Abhishek; Rorden, Christopher; Parra, Lucas C.

2013-01-01

Objective High-definition transcranial direct current stimulation (HD-tDCS) and high-density electroencephalography (HD-EEG) require accurate models of current flow for precise targeting and current source reconstruction. At a minimum, such modeling must capture the idiosyncratic anatomy of brain, cerebrospinal fluid (CSF) and skull for each individual subject. Currently, the process to build such high-resolution individualized models from structural magnetic resonance images (MRI) requires labor-intensive manual segmentation, even when leveraging available automated segmentation tools. Also, accurate placement of many high-density electrodes on individual scalp is a tedious procedure. The goal was to develop fully automated techniques to reduce the manual effort in such a modeling process. Approach A fully automated segmentation technique based on Statical Parametric Mapping 8 (SPM8), including an improved tissue probability map (TPM) and an automated correction routine for segmentation errors, was developed, along with an automated electrode placement tool for high-density arrays. The performance of these automated routines was evaluated against results from manual segmentation on 4 healthy subjects and 7 stroke patients. The criteria include segmentation accuracy, the difference of current flow distributions in resulting HD-tDCS models and the optimized current flow intensities on cortical targets. Main results The segmentation tool can segment out not just the brain but also provide accurate results for CSF, skull and other soft tissues with a field of view (FOV) extending to the neck. Compared to manual results, automated segmentation deviates by only 7% and 18% for normal and stroke subjects, respectively. The predicted electric fields in the brain deviate by 12% and 29% respectively, which is well within the variability observed for various modeling choices. Finally, optimized current flow intensities on cortical targets do not differ significantly. Significance Fully automated individualized modeling may now be feasible for large-sample EEG research studies and tDCS clinical trials. PMID:24099977

Automated MRI segmentation for individualized modeling of current flow in the human head

NASA Astrophysics Data System (ADS)

Huang, Yu; Dmochowski, Jacek P.; Su, Yuzhuo; Datta, Abhishek; Rorden, Christopher; Parra, Lucas C.

2013-12-01

Objective. High-definition transcranial direct current stimulation (HD-tDCS) and high-density electroencephalography require accurate models of current flow for precise targeting and current source reconstruction. At a minimum, such modeling must capture the idiosyncratic anatomy of the brain, cerebrospinal fluid (CSF) and skull for each individual subject. Currently, the process to build such high-resolution individualized models from structural magnetic resonance images requires labor-intensive manual segmentation, even when utilizing available automated segmentation tools. Also, accurate placement of many high-density electrodes on an individual scalp is a tedious procedure. The goal was to develop fully automated techniques to reduce the manual effort in such a modeling process. Approach. A fully automated segmentation technique based on Statical Parametric Mapping 8, including an improved tissue probability map and an automated correction routine for segmentation errors, was developed, along with an automated electrode placement tool for high-density arrays. The performance of these automated routines was evaluated against results from manual segmentation on four healthy subjects and seven stroke patients. The criteria include segmentation accuracy, the difference of current flow distributions in resulting HD-tDCS models and the optimized current flow intensities on cortical targets.Main results. The segmentation tool can segment out not just the brain but also provide accurate results for CSF, skull and other soft tissues with a field of view extending to the neck. Compared to manual results, automated segmentation deviates by only 7% and 18% for normal and stroke subjects, respectively. The predicted electric fields in the brain deviate by 12% and 29% respectively, which is well within the variability observed for various modeling choices. Finally, optimized current flow intensities on cortical targets do not differ significantly.Significance. Fully automated individualized modeling may now be feasible for large-sample EEG research studies and tDCS clinical trials.

Estimation of carbon storage based on individual tree detection in Pinus densiflora stands using a fusion of aerial photography and LiDAR data.

PubMed

Kim, So-Ra; Kwak, Doo-Ahn; Lee, Woo-Kyun; oLee, Woo-Kyun; Son, Yowhan; Bae, Sang-Won; Kim, Choonsig; Yoo, Seongjin

2010-07-01

The objective of this study was to estimate the carbon storage capacity of Pinus densiflora stands using remotely sensed data by combining digital aerial photography with light detection and ranging (LiDAR) data. A digital canopy model (DCM), generated from the LiDAR data, was combined with aerial photography for segmenting crowns of individual trees. To eliminate errors in over and under-segmentation, the combined image was smoothed using a Gaussian filtering method. The processed image was then segmented into individual trees using a marker-controlled watershed segmentation method. After measuring the crown area from the segmented individual trees, the individual tree diameter at breast height (DBH) was estimated using a regression function developed from the relationship observed between the field-measured DBH and crown area. The above ground biomass of individual trees could be calculated by an image-derived DBH using a regression function developed by the Korea Forest Research Institute. The carbon storage, based on individual trees, was estimated by simple multiplication using the carbon conversion index (0.5), as suggested in guidelines from the Intergovernmental Panel on Climate Change. The mean carbon storage per individual tree was estimated and then compared with the field-measured value. This study suggested that the biomass and carbon storage in a large forest area can be effectively estimated using aerial photographs and LiDAR data.

White blood cell segmentation by color-space-based k-means clustering.

PubMed

Zhang, Congcong; Xiao, Xiaoyan; Li, Xiaomei; Chen, Ying-Jie; Zhen, Wu; Chang, Jun; Zheng, Chengyun; Liu, Zhi

2014-09-01

White blood cell (WBC) segmentation, which is important for cytometry, is a challenging issue because of the morphological diversity of WBCs and the complex and uncertain background of blood smear images. This paper proposes a novel method for the nucleus and cytoplasm segmentation of WBCs for cytometry. A color adjustment step was also introduced before segmentation. Color space decomposition and k-means clustering were combined for segmentation. A database including 300 microscopic blood smear images were used to evaluate the performance of our method. The proposed segmentation method achieves 95.7% and 91.3% overall accuracy for nucleus segmentation and cytoplasm segmentation, respectively. Experimental results demonstrate that the proposed method can segment WBCs effectively with high accuracy.

Droplet microfluidics with magnetic beads: a new tool to investigate drug-protein interactions.

PubMed

Lombardi, Dario; Dittrich, Petra S

2011-01-01

In this study, we give the proof of concept for a method to determine binding constants of compounds in solution. By implementing a technique based on magnetic beads with a microfluidic device for segmented flow generation, we demonstrate, for individual droplets, fast, robust and complete separation of the magnetic beads. The beads are used as a carrier for one binding partner and hence, any bound molecule is separated likewise, while the segmentation into small microdroplets ensures fast mixing, and opens future prospects for droplet-wise analysis of drug candidate libraries. We employ the method for characterization of drug-protein binding, here warfarin to human serum albumin. The approach lays the basis for a microfluidic droplet-based screening device aimed at investigating the interactions of drugs with specific targets including enzymes and cells. Furthermore, the continuous method could be employed for various applications, such as binding assays, kinetic studies, and single cell analysis, in which rapid removal of a reactive component is required.

Intestinal morphology of the wild Atlantic salmon (Salmo salar).

PubMed

Løkka, Guro; Austbø, Lars; Falk, Knut; Bjerkås, Inge; Koppang, Erling Olaf

2013-08-01

The worldwide-industrialized production of Atlantic salmon (Salmo salar) has increased dramatically during the last decades, followed by diseases related to the on-going domestication process as a growing concern. Even though the gastrointestinal tract seems to be a target for different disorders in farmed fish, a description of the normal intestinal status in healthy, wild salmon is warranted. Here, we provide such information in addition to suggesting a referable anatomical standardization for the intestine. In this study, two groups of wild Atlantic salmon were investigated, consisting of post smolts on feed caught in the sea and of sexually mature, starved individuals sampled from a river. The two groups represent different stages in the anadromous salmon life cycle, which also are part of the production cycle of farmed salmon. Selected regions of gastrointestinal tract were subjected to morphological investigations including immunohistochemical, scanning electron microscopic, and morphometric analyses. A morphology-based nomenclature was established, defining the cardiac part of the stomach and five different regions of the Atlantic salmon intestine, including pyloric caeca, first segment of the mid-intestine with pyloric caeca, first segment of the mid-intestine posterior to pyloric caeca, second segment of the mid-intestine and posterior intestinal segment. In each of the above described regions, for both groups of fish, morphometrical measurements and regional histological investigations were performed with regards to magnitude and direction of mucosal folding as well as the composition of the intestinal wall. Additionally, immunohistochemistry showing cells positive for cytokeratins, α-actin and proliferating cell nuclear antigen, in addition to alkaline phosphatase reactivity in the segments is presented. Copyright © 2013 Wiley Periodicals, Inc., a Wiley Company.

THE STRUCTURE AND CONCENTRATION OF SOLIDS IN PHOTORECEPTOR CELLS STUDIED BY REFRACTOMETRY AND INTERFERENCE MICROSCOPY

PubMed Central

Sidman, Richard L.

1957-01-01

Fragments of freshly obtained retinas of several vertebrate species were studied by refractometry, with reference to the structure of the rods and cones. The findings allowed a reassessment of previous descriptions based mainly on fixed material. The refractometric method was used also to measure the refractice indices and to calculate the concentrations of solids and water in the various cell segments. The main quantitative data were confirmed by interference microscopy. When examined by the method of refractometry the outer segments of freshly prepared retinal rods appear homogeneous. Within a few minutes a single eccentric longitudinal fiber appears, and transverse striations may develop. These changes are attributed to imbibition of water and swelling in structures normally too small for detection by light microscopy. The central "core" of outer segments and the chromophobic disc between outer and inner segments appear to be artifacts resulting from shrinkage during dehydration. The fresh outer segments of cones, and the inner segments of rods and cones also are described and illustrated. The volumes, refractive indices, concentrations of solids, and wet and dry weights of various segments of the photoreceptor cells were tabulated. Rod outer segments of the different species vary more than 100-fold in volume and mass but all have concentrations of solids of 40 to 43 per cent. Cone outer segments contain only about 30 per cent solids. The myoids, paraboloids, and ellipsoids of the inner segments likewise have characteristic refractive indices and concentrations of solids. Some of the limitations and particular virtues of refractometry as a method for quantitative analysis of living cells are discussed in comparison with more conventional biochemical techniques. Also the shapes and refractive indices of the various segments of photoreceptor cells are considered in relation to the absorption and transmission of light. The Stiles-Crawford effect can be accounted for on the basis of the structure of cone cells. PMID:13416308

Robust Nucleus/Cell Detection and Segmentation in Digital Pathology and Microscopy Images: A Comprehensive Review

PubMed Central

Xing, Fuyong; Yang, Lin

2016-01-01

Digital pathology and microscopy image analysis is widely used for comprehensive studies of cell morphology or tissue structure. Manual assessment is labor intensive and prone to inter-observer variations. Computer-aided methods, which can significantly improve the objectivity and reproducibility, have attracted a great deal of interest in recent literatures. Among the pipeline of building a computer-aided diagnosis system, nucleus or cell detection and segmentation play a very important role to describe the molecular morphological information. In the past few decades, many efforts have been devoted to automated nucleus/cell detection and segmentation. In this review, we provide a comprehensive summary of the recent state-of-the-art nucleus/cell segmentation approaches on different types of microscopy images including bright-field, phase-contrast, differential interference contrast (DIC), fluorescence, and electron microscopies. In addition, we discuss the challenges for the current methods and the potential future work of nucleus/cell detection and segmentation. PMID:26742143

Laser ablation of persistent twist cells in Drosophila: muscle precursor fate is not segmentally restricted

NASA Technical Reports Server (NTRS)

Farrell, E. R.; Keshishian, H.

1999-01-01

In Drosophila the precursors of the adult musculature arise during embryogenesis. These precursor cells have been termed Persistent Twist Cells (PTCs), as they continue to express the transcription factor Twist after that gene ceases expression elsewhere in the mesoderm. In the larval abdomen, the PTCs are associated with peripheral nerves in stereotypic ventral, dorsal, and lateral clusters, which give rise, respectively, to the ventral, dorsal, and lateral muscle fiber groups of the adult. We tested the developmental potential of the PTCs by using a microbeam laser to ablate specific clusters in larvae. We found that the ablation of a single segmental PTC cluster does not usually result in the deletion of the corresponding adult fibers of that segment. Instead, normal or near normal numbers of adult fibers can form after the ablation. Examination of pupae following ablation showed that migrating PTCs from adjacent segments are able to invade the affected segment, replenishing the ablated cells. However, the ablation of homologous PTCs in multiple segments does result in the deletion of the corresponding adult muscle fibers. These data indicate that the PTCs in an abdominal segment can contribute to the formation of muscle fibers in adjacent abdominal segments, and thus are not inherently restricted to the formation of muscle fibers within their segment of origin.

General Staining and Segmentation Procedures for High Content Imaging and Analysis.

PubMed

Chambers, Kevin M; Mandavilli, Bhaskar S; Dolman, Nick J; Janes, Michael S

2018-01-01

Automated quantitative fluorescence microscopy, also known as high content imaging (HCI), is a rapidly growing analytical approach in cell biology. Because automated image analysis relies heavily on robust demarcation of cells and subcellular regions, reliable methods for labeling cells is a critical component of the HCI workflow. Labeling of cells for image segmentation is typically performed with fluorescent probes that bind DNA for nuclear-based cell demarcation or with those which react with proteins for image analysis based on whole cell staining. These reagents, along with instrument and software settings, play an important role in the successful segmentation of cells in a population for automated and quantitative image analysis. In this chapter, we describe standard procedures for labeling and image segmentation in both live and fixed cell samples. The chapter will also provide troubleshooting guidelines for some of the common problems associated with these aspects of HCI.

Automated segmentation and tracking of non-rigid objects in time-lapse microscopy videos of polymorphonuclear neutrophils.

PubMed

Brandes, Susanne; Mokhtari, Zeinab; Essig, Fabian; Hünniger, Kerstin; Kurzai, Oliver; Figge, Marc Thilo

2015-02-01

Time-lapse microscopy is an important technique to study the dynamics of various biological processes. The labor-intensive manual analysis of microscopy videos is increasingly replaced by automated segmentation and tracking methods. These methods are often limited to certain cell morphologies and/or cell stainings. In this paper, we present an automated segmentation and tracking framework that does not have these restrictions. In particular, our framework handles highly variable cell shapes and does not rely on any cell stainings. Our segmentation approach is based on a combination of spatial and temporal image variations to detect moving cells in microscopy videos. This method yields a sensitivity of 99% and a precision of 95% in object detection. The tracking of cells consists of different steps, starting from single-cell tracking based on a nearest-neighbor-approach, detection of cell-cell interactions and splitting of cell clusters, and finally combining tracklets using methods from graph theory. The segmentation and tracking framework was applied to synthetic as well as experimental datasets with varying cell densities implying different numbers of cell-cell interactions. We established a validation framework to measure the performance of our tracking technique. The cell tracking accuracy was found to be >99% for all datasets indicating a high accuracy for connecting the detected cells between different time points. Copyright © 2014 Elsevier B.V. All rights reserved.

Colour image segmentation using unsupervised clustering technique for acute leukemia images

NASA Astrophysics Data System (ADS)

Halim, N. H. Abd; Mashor, M. Y.; Nasir, A. S. Abdul; Mustafa, N.; Hassan, R.

2015-05-01

Colour image segmentation has becoming more popular for computer vision due to its important process in most medical analysis tasks. This paper proposes comparison between different colour components of RGB(red, green, blue) and HSI (hue, saturation, intensity) colour models that will be used in order to segment the acute leukemia images. First, partial contrast stretching is applied on leukemia images to increase the visual aspect of the blast cells. Then, an unsupervised moving k-means clustering algorithm is applied on the various colour components of RGB and HSI colour models for the purpose of segmentation of blast cells from the red blood cells and background regions in leukemia image. Different colour components of RGB and HSI colour models have been analyzed in order to identify the colour component that can give the good segmentation performance. The segmented images are then processed using median filter and region growing technique to reduce noise and smooth the images. The results show that segmentation using saturation component of HSI colour model has proven to be the best in segmenting nucleus of the blast cells in acute leukemia image as compared to the other colour components of RGB and HSI colour models.

Array tomography: characterizing FAC-sorted populations of zebrafish immune cells by their 3D ultrastructure.

PubMed

Wacker, Irene; Chockley, Peter; Bartels, Carolin; Spomer, Waldemar; Hofmann, Andreas; Gengenbach, Ulrich; Singh, Sachin; Thaler, Marlene; Grabher, Clemens; Schröder, Rasmus R

2015-08-01

For 3D reconstructions of whole immune cells from zebrafish, isolated from adult animals by FAC-sorting we employed array tomography on hundreds of serial sections deposited on silicon wafers. Image stacks were either recorded manually or automatically with the newly released ZEISS Atlas 5 Array Tomography platform on a Zeiss FEGSEM. To characterize different populations of immune cells, organelle inventories were created by segmenting individual cells. In addition, arrays were used for quantification of cell populations with respect to the various cell types they contained. The detection of immunological synapses in cocultures of cell populations from thymus or WKM with cancer cells helped to identify the cytotoxic nature of these cells. Our results demonstrate the practicality and benefit of AT for high-throughput ultrastructural imaging of substantial volumes. © 2015 The Authors Journal of Microscopy © 2015 Royal Microscopical Society.

A Method for the Evaluation of Thousands of Automated 3D Stem Cell Segmentations

PubMed Central

Bajcsy, Peter; Simon, Mylene; Florczyk, Stephen; Simon, Carl G.; Juba, Derek; Brady, Mary

2016-01-01

There is no segmentation method that performs perfectly with any data set in comparison to human segmentation. Evaluation procedures for segmentation algorithms become critical for their selection. The problems associated with segmentation performance evaluations and visual verification of segmentation results are exaggerated when dealing with thousands of 3D image volumes because of the amount of computation and manual inputs needed. We address the problem of evaluating 3D segmentation performance when segmentation is applied to thousands of confocal microscopy images (z-stacks). Our approach is to incorporate experimental imaging and geometrical criteria, and map them into computationally efficient segmentation algorithms that can be applied to a very large number of z-stacks. This is an alternative approach to considering existing segmentation methods and evaluating most state-of-the-art algorithms. We designed a methodology for 3D segmentation performance characterization that consists of design, evaluation and verification steps. The characterization integrates manual inputs from projected surrogate “ground truth” of statistically representative samples and from visual inspection into the evaluation. The novelty of the methodology lies in (1) designing candidate segmentation algorithms by mapping imaging and geometrical criteria into algorithmic steps, and constructing plausible segmentation algorithms with respect to the order of algorithmic steps and their parameters, (2) evaluating segmentation accuracy using samples drawn from probability distribution estimates of candidate segmentations, and (3) minimizing human labor needed to create surrogate “truth” by approximating z-stack segmentations with 2D contours from three orthogonal z-stack projections and by developing visual verification tools. We demonstrate the methodology by applying it to a dataset of 1253 mesenchymal stem cells. The cells reside on 10 different types of biomaterial scaffolds, and are stained for actin and nucleus yielding 128 460 image frames (on average 125 cells/scaffold × 10 scaffold types × 2 stains × 51 frames/cell). After constructing and evaluating six candidates of 3D segmentation algorithms, the most accurate 3D segmentation algorithm achieved an average precision of 0.82 and an accuracy of 0.84 as measured by the Dice similarity index where values greater than 0.7 indicate a good spatial overlap. A probability of segmentation success was 0.85 based on visual verification, and a computation time was 42.3 h to process all z-stacks. While the most accurate segmentation technique was 4.2 times slower than the second most accurate algorithm, it consumed on average 9.65 times less memory per z-stack segmentation. PMID:26268699

Workflow for high-content, individual cell quantification of fluorescent markers from universal microscope data, supported by open source software.

PubMed

Stockwell, Simon R; Mittnacht, Sibylle

2014-12-16

Advances in understanding the control mechanisms governing the behavior of cells in adherent mammalian tissue culture models are becoming increasingly dependent on modes of single-cell analysis. Methods which deliver composite data reflecting the mean values of biomarkers from cell populations risk losing subpopulation dynamics that reflect the heterogeneity of the studied biological system. In keeping with this, traditional approaches are being replaced by, or supported with, more sophisticated forms of cellular assay developed to allow assessment by high-content microscopy. These assays potentially generate large numbers of images of fluorescent biomarkers, which enabled by accompanying proprietary software packages, allows for multi-parametric measurements per cell. However, the relatively high capital costs and overspecialization of many of these devices have prevented their accessibility to many investigators. Described here is a universally applicable workflow for the quantification of multiple fluorescent marker intensities from specific subcellular regions of individual cells suitable for use with images from most fluorescent microscopes. Key to this workflow is the implementation of the freely available Cell Profiler software(1) to distinguish individual cells in these images, segment them into defined subcellular regions and deliver fluorescence marker intensity values specific to these regions. The extraction of individual cell intensity values from image data is the central purpose of this workflow and will be illustrated with the analysis of control data from a siRNA screen for G1 checkpoint regulators in adherent human cells. However, the workflow presented here can be applied to analysis of data from other means of cell perturbation (e.g., compound screens) and other forms of fluorescence based cellular markers and thus should be useful for a wide range of laboratories.

Effect of DNA sequence of Fab fragment on yield characteristics and cell growth of E. coli.

PubMed

Kulmala, Antti; Huovinen, Tuomas; Lamminmäki, Urpo

2017-06-19

Codon usage is one of the factors influencing recombinant protein expression. We were interested in the codon usage of an antibody Fab fragment gene exhibiting extreme toxicity in the E. coli host. The toxic synthetic human Fab gene contained domains optimized by the "one amino acid-one codon" method. We redesigned five segments of the Fab gene with a "codon harmonization" method described by Angov et al. and studied the effects of these changes on cell viability, Fab yield and display on filamentous phage using different vectors and bacterial strains. The harmonization considerably reduced toxicity, increased Fab expression from negligible levels to 10 mg/l, and restored the display on phage. Testing the impact of the individual redesigned segments revealed that the most significant effects were conferred by changes in the constant domain of the light chain. For some of the Fab gene variants, we also observed striking differences in protein yields when cloned from a chloramphenicol resistant vector into an identical vector, except with ampicillin resistance. In conclusion, our results show that the expression of a heterodimeric secretory protein can be improved by harmonizing selected DNA segments by synonymous codons and reveal additional complexity involved in heterologous protein expression.

Tracking flow of leukocytes in blood for drug analysis

NASA Astrophysics Data System (ADS)

Basharat, Arslan; Turner, Wesley; Stephens, Gillian; Badillo, Benjamin; Lumpkin, Rick; Andre, Patrick; Perera, Amitha

2011-03-01

Modern microscopy techniques allow imaging of circulating blood components under vascular flow conditions. The resulting video sequences provide unique insights into the behavior of blood cells within the vasculature and can be used as a method to monitor and quantitate the recruitment of inflammatory cells at sites of vascular injury/ inflammation and potentially serve as a pharmacodynamic biomarker, helping screen new therapies and individualize dose and combinations of drugs. However, manual analysis of these video sequences is intractable, requiring hours per 400 second video clip. In this paper, we present an automated technique to analyze the behavior and recruitment of human leukocytes in whole blood under physiological conditions of shear through a simple multi-channel fluorescence microscope in real-time. This technique detects and tracks the recruitment of leukocytes to a bioactive surface coated on a flow chamber. Rolling cells (cells which partially bind to the bioactive matrix) are detected counted, and have their velocity measured and graphed. The challenges here include: high cell density, appearance similarity, and low (1Hz) frame rate. Our approach performs frame differencing based motion segmentation, track initialization and online tracking of individual leukocytes.

Automated segmentation and isolation of touching cell nuclei in cytopathology smear images of pleural effusion using distance transform watershed method

NASA Astrophysics Data System (ADS)

Win, Khin Yadanar; Choomchuay, Somsak; Hamamoto, Kazuhiko

2017-06-01

The automated segmentation of cell nuclei is an essential stage in the quantitative image analysis of cell nuclei extracted from smear cytology images of pleural fluid. Cell nuclei can indicate cancer as the characteristics of cell nuclei are associated with cells proliferation and malignancy in term of size, shape and the stained color. Nevertheless, automatic nuclei segmentation has remained challenging due to the artifacts caused by slide preparation, nuclei heterogeneity such as the poor contrast, inconsistent stained color, the cells variation, and cells overlapping. In this paper, we proposed a watershed-based method that is capable to segment the nuclei of the variety of cells from cytology pleural fluid smear images. Firstly, the original image is preprocessed by converting into the grayscale image and enhancing by adjusting and equalizing the intensity using histogram equalization. Next, the cell nuclei are segmented using OTSU thresholding as the binary image. The undesirable artifacts are eliminated using morphological operations. Finally, the distance transform based watershed method is applied to isolate the touching and overlapping cell nuclei. The proposed method is tested with 25 Papanicolaou (Pap) stained pleural fluid images. The accuracy of our proposed method is 92%. The method is relatively simple, and the results are very promising.

Segmentation of white blood cells and comparison of cell morphology by linear and naïve Bayes classifiers.

PubMed

Prinyakupt, Jaroonrut; Pluempitiwiriyawej, Charnchai

2015-06-30

Blood smear microscopic images are routinely investigated by haematologists to diagnose most blood diseases. However, the task is quite tedious and time consuming. An automatic detection and classification of white blood cells within such images can accelerate the process tremendously. In this paper we propose a system to locate white blood cells within microscopic blood smear images, segment them into nucleus and cytoplasm regions, extract suitable features and finally, classify them into five types: basophil, eosinophil, neutrophil, lymphocyte and monocyte. Two sets of blood smear images were used in this study's experiments. Dataset 1, collected from Rangsit University, were normal peripheral blood slides under light microscope with 100× magnification; 555 images with 601 white blood cells were captured by a Nikon DS-Fi2 high-definition color camera and saved in JPG format of size 960 × 1,280 pixels at 15 pixels per 1 μm resolution. In dataset 2, 477 cropped white blood cell images were downloaded from CellaVision.com. They are in JPG format of size 360 × 363 pixels. The resolution is estimated to be 10 pixels per 1 μm. The proposed system comprises a pre-processing step, nucleus segmentation, cell segmentation, feature extraction, feature selection and classification. The main concept of the segmentation algorithm employed uses white blood cell's morphological properties and the calibrated size of a real cell relative to image resolution. The segmentation process combined thresholding, morphological operation and ellipse curve fitting. Consequently, several features were extracted from the segmented nucleus and cytoplasm regions. Prominent features were then chosen by a greedy search algorithm called sequential forward selection. Finally, with a set of selected prominent features, both linear and naïve Bayes classifiers were applied for performance comparison. This system was tested on normal peripheral blood smear slide images from two datasets. Two sets of comparison were performed: segmentation and classification. The automatically segmented results were compared to the ones obtained manually by a haematologist. It was found that the proposed method is consistent and coherent in both datasets, with dice similarity of 98.9 and 91.6% for average segmented nucleus and cell regions, respectively. Furthermore, the overall correction rate in the classification phase is about 98 and 94% for linear and naïve Bayes models, respectively. The proposed system, based on normal white blood cell morphology and its characteristics, was applied to two different datasets. The results of the calibrated segmentation process on both datasets are fast, robust, efficient and coherent. Meanwhile, the classification of normal white blood cells into five types shows high sensitivity in both linear and naïve Bayes models, with slightly better results in the linear classifier.

Superpixel-based segmentation of muscle fibers in multi-channel microscopy.

PubMed

Nguyen, Binh P; Heemskerk, Hans; So, Peter T C; Tucker-Kellogg, Lisa

2016-12-05

Confetti fluorescence and other multi-color genetic labelling strategies are useful for observing stem cell regeneration and for other problems of cell lineage tracing. One difficulty of such strategies is segmenting the cell boundaries, which is a very different problem from segmenting color images from the real world. This paper addresses the difficulties and presents a superpixel-based framework for segmentation of regenerated muscle fibers in mice. We propose to integrate an edge detector into a superpixel algorithm and customize the method for multi-channel images. The enhanced superpixel method outperforms the original and another advanced superpixel algorithm in terms of both boundary recall and under-segmentation error. Our framework was applied to cross-section and lateral section images of regenerated muscle fibers from confetti-fluorescent mice. Compared with "ground-truth" segmentations, our framework yielded median Dice similarity coefficients of 0.92 and higher. Our segmentation framework is flexible and provides very good segmentations of multi-color muscle fibers. We anticipate our methods will be useful for segmenting a variety of tissues in confetti fluorecent mice and in mice with similar multi-color labels.

The Memory Cytotoxic T-Lymphocyte (CTL) Response to Human Cytomegalovirus Infection Contains Individual Peptide-Specific CTL Clones That Have Undergone Extensive Expansion In Vivo

PubMed Central

Weekes, Michael P.; Wills, Mark R.; Mynard, Kim; Carmichael, Andrew J.; Sissons, J. G. Patrick

1999-01-01

Human cytomegalovirus (HCMV)-specific CD8+ cytotoxic T lymphocytes (CTL) appear to play an important role in the control of virus replication and in protection against HCMV-related disease. We have previously reported high frequencies of memory CTL precursors (CTLp) specific to the HCMV tegument protein pp65 in the peripheral blood of healthy virus carriers. In some individuals, the CTL response to this protein is focused on only a single epitope, whereas in other virus carriers CTL recognized multiple epitopes which we identified by using synthetic peptides. We have analyzed the clonal composition of the memory CTL response to four of these pp65 epitopes by sequencing the T-cell receptors (TCR) of multiple independently derived epitope-specific CTL clones, which were derived by formal single-cell cloning or from clonal CTL microcultures. In all cases, we have observed a high degree of clonal focusing: the majority of CTL clones specific to a defined pp65 peptide from any one virus carrier use only one or two different TCRs at the level of the nucleotide sequence. Among virus carriers who have the same major histocompatibility complex (MHC) class I allele, we observed that CTL from different donors that recognize the same peptide-MHC complex often used the same Vβ segment, although other TCR gene segments and CDR3 length were not in general conserved. We have also examined the clonal composition of CTL specific to pp65 peptides in asymptomatic human immunodeficiency virus-infected individuals. We have observed a similarly focused peptide-specific CTL response. Thus, the large population of circulating HCMV peptide-specific memory CTLp in virus carriers in fact contains individual CTL clones that have undergone extensive clonal expansion in vivo. PMID:9971792

Caudal migration and proliferation of renal progenitors regulates early nephron segment size in zebrafish.

PubMed

Naylor, Richard W; Dodd, Rachel C; Davidson, Alan J

2016-10-19

The nephron is the functional unit of the kidney and is divided into distinct proximal and distal segments. The factors determining nephron segment size are not fully understood. In zebrafish, the embryonic kidney has long been thought to differentiate in situ into two proximal tubule segments and two distal tubule segments (distal early; DE, and distal late; DL) with little involvement of cell movement. Here, we overturn this notion by performing lineage-labelling experiments that reveal extensive caudal movement of the proximal and DE segments and a concomitant compaction of the DL segment as it fuses with the cloaca. Laser-mediated severing of the tubule, such that the DE and DL are disconnected or that the DL and cloaca do not fuse, results in a reduction in tubule cell proliferation and significantly shortens the DE segment while the caudal movement of the DL is unaffected. These results suggest that the DL mechanically pulls the more proximal segments, thereby driving both their caudal extension and their proliferation. Together, these data provide new insights into early nephron morphogenesis and demonstrate the importance of cell movement and proliferation in determining initial nephron segment size.

Clonal expansion of T-cell receptor beta gene segment in the retrocochlear lesions of EAE mice.

PubMed

Cheng, K C; Lee, K M; Yoo, T J

1998-01-01

It has been reported that the T cell receptor V beta 8.2 (TcrbV8.2) gene segment is predominantly expressed in encephalomyelitic T cells responding to myelin basic protein (MBP) in experimental allergic encephalomyelitis (EAE) mice. We have demonstrated retrocochlear hearing loss in EAE mice in previous studies. Administration of a monoclonal antibody specific to the T cell receptor V beta 8 (TcrbV8) subfamily prevented both this type of hearing loss and the central nerve disease. In this study, we examined the role of the TcrbV8.2 gene segment in the retrocochlear lesions of EAE mice. A clonal expression of T cell receptor beta chain gene segment (TcrbV8.2-TcrbD2-TcrbJ2.7) was identified in the retrocochlear lesions. The TcrbV8.2 gene segment appears to recombine only with TcrbJ2.1 (32.1%) and TcrbJ2.7 (67.9%) gene segments. The TcrbJ2.7 gene segment has also been previously identified as the dominant TcrbJ gene in the lymph nodes of EAE mice. Only TcrbD2, with a length of 4 amino acids, was observed recombining with these TcrbV8.2 sequences. G and C nucleotides are predominantly expressed at the N regions between the V-D and D-J junctions. This dominant TcrbV gene segment (TcrbV8.2-TcrbD2-TcrbJ2.7) observed in the retrocochlear lesions has been identified in the MBP-specific T cells from the lymph nodes of EAE mice. These results suggest that a small subset of antigen-specific T cells migrate to, and expand at, the retrocochlear lesions, which leads to hearing loss.

[Development of non-invasive clinical examination methods for the anterior segment of the eye and their clinical significance].

PubMed

Sawa, Mitsuru

2011-03-01

1. Slit-lamp microscopy is a principal ophthalmic clinical method, because it provides microscopic findings of the anterior segment of the eye noninvasively. Its findings, however, are qualitative and there are large inter-observer variations in their evaluation. Furthermore, slit-lamp microscopy provides morphological findings, but a functional evaluation is difficult. We developed two novel methods that establish a qualitative methodology of the slit-lamp microscope and the pathophysiology of the anterior segment of the eye. One is the flare-cell photometer to evaluate flare and cells in the aqueous humor of the eye and the other is an immunohistochemical examination method using tear fluid to evaluate ocular surface disorders. The comprehensive evaluation of these studies is herein overviewed. 2. INNOVATION OF THE FLARE-CELL PHOTOMETER AND ITS CLINICAL SIGNIFICANCE: The breakdown of the blood-aqueous barrier (BAB) causes an increase in protein (flare) and leakage of blood cells (cell) into the aqueous humor of the eye and the severity of BAB breakdown has a positive correlation with the intensity of flare and cells. The flare and cells in the aqueous can be observed qualitatively by slit-lamp microscopy. These findings are primarily distinguished in optics by light scattering. Therefore, detection of the intensity of light scattering due to flare and cells can evaluate the BAB function. The flare-cell photometer comprises 3 novel components: a laser beam system as an incident light, a photomultiplier to detect scattered light intensity and a computer-assisted system to operate the whole system and analyze detected scattered light signals due to flare and cells. The instrument enables us to quantitatively analyze the flare and cells non-invasively and accurately with a wide dynamic measurement range, resulting in a repeated examination of each individual case. It also enables the evaluation of inflammation in the aqueous not only postoperatively but also in endogenous uveitis, evaluation of the effects of anti-inflammatory drugs on BAB and evaluation of aqueous humor dynamics. Furthermore, repeating the examination can minimize inter-individual variations and reduce the number of animals in animal experiments. 3. Sampling of tears can be performed noninvasively, but the obtainable volume is limited. Therefore, a determination of targeting biomarkers and a development of their micro-volume analysis methods play a crucial role in pathophysiological studies of the ocular surface. Targeting biomarkers should be determined according to the various specified bioactive substances such as eosinophil cationic protein (ECP), cytokines and others. A number of microvolume analysis methods, such as chemiluminescent enzyme immunoassay, immunochromatography, micro-array system and polymerase chain reaction method are used. Objective disorders in the studies include allergic conjunctivitis and infectious diseases such as herpetic keratitis. Quantitative evaluation methods for ECP concentration, antigen-specific secretory IgA in allergic diseases and herpetic keratitis, herpes simplex virus-DNA and cytokine and chemokine profile in tear fluid sampled by filter paper method were investigated. We developed a clinically applicable quantitative immunochemical method for ECP concentration in tear fluid. The results revealed that tear fluid analysis using the above mentioned methods is a clinically useful to investigate the pathophysiology of the ocular surface. 4. Laser flare-cell photometer and tear fluid analysis are potent clinical quantitative methods to investigate the pathophysiology of the anterior segment of the eye.

Cell Identity Switching Regulated by Retinoic Acid Signaling Maintains Homogeneous Segments in the Hindbrain.

PubMed

Addison, Megan; Xu, Qiling; Cayuso, Jordi; Wilkinson, David G

2018-06-04

The patterning of tissues to form subdivisions with distinct and homogeneous regional identity is potentially disrupted by cell intermingling. Transplantation studies suggest that homogeneous segmental identity in the hindbrain is maintained by identity switching of cells that intermingle into another segment. We show that switching occurs during normal development and is mediated by feedback between segment identity and the retinoic acid degrading enzymes, cyp26b1 and cyp26c1. egr2, which specifies the segmental identity of rhombomeres r3 and r5, underlies the lower expression level of cyp26b1 and cyp26c1 in r3 and r5 compared with r2, r4, and r6. Consequently, r3 or r5 cells that intermingle into adjacent segments encounter cells with higher cyp26b1/c1 expression, which we find is required for downregulation of egr2b expression. Furthermore, egr2b expression is regulated in r2, r4, and r6 by non-autonomous mechanisms that depend upon the number of neighbors that express egr2b. These findings reveal that a community regulation of retinoid signaling maintains homogeneous segmental identity. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Segmentation of White Blood Cells From Microscopic Images Using a Novel Combination of K-Means Clustering and Modified Watershed Algorithm.

PubMed

Ghane, Narjes; Vard, Alireza; Talebi, Ardeshir; Nematollahy, Pardis

2017-01-01

Recognition of white blood cells (WBCs) is the first step to diagnose some particular diseases such as acquired immune deficiency syndrome, leukemia, and other blood-related diseases that are usually done by pathologists using an optical microscope. This process is time-consuming, extremely tedious, and expensive and needs experienced experts in this field. Thus, a computer-aided diagnosis system that assists pathologists in the diagnostic process can be so effective. Segmentation of WBCs is usually a first step in developing a computer-aided diagnosis system. The main purpose of this paper is to segment WBCs from microscopic images. For this purpose, we present a novel combination of thresholding, k-means clustering, and modified watershed algorithms in three stages including (1) segmentation of WBCs from a microscopic image, (2) extraction of nuclei from cell's image, and (3) separation of overlapping cells and nuclei. The evaluation results of the proposed method show that similarity measures, precision, and sensitivity respectively were 92.07, 96.07, and 94.30% for nucleus segmentation and 92.93, 97.41, and 93.78% for cell segmentation. In addition, statistical analysis presents high similarity between manual segmentation and the results obtained by the proposed method.

Recombinant cells that highly express chromosomally-integrated heterologous genes

DOEpatents

Ingram, L.O.; Ohta, Kazuyoshi; Wood, B.E.

1998-10-13

Recombinant host cells are obtained that comprise (A) a heterologous, polypeptide-encoding polynucleotide segment, stably integrated into a chromosome, which is under transcriptional control of an endogenous promoter and (B) a mutation that effects increased expression of the heterologous segment, resulting in enhanced production by the host cells of each polypeptide encoded by that segment, relative to production of each polypeptide by the host cells in the absence of the mutation. The increased expression thus achieved is retained in the absence of conditions that select for cells displaying such increased expression. When the integrated segment comprises, for example, ethanol-production genes from an efficient ethanol producer like Zymomonas mobilis, recombinant Escherichia coli and other enteric bacterial cells within the present invention are capable of converting a wide range of biomass-derived sugars efficiently to ethanol. 13 figs.

Recombinant cells that highly express chromosomally-integrated heterologous genes

DOEpatents

Ingram, Lonnie O.; Ohta, Kazuyoshi; Wood, Brent E.

1998-01-01

Recombinant host cells are obtained that comprise (A) a heterologous, polypeptide-encoding polynucleotide segment, stably integrated into a chromosome, which is under transcriptional control of an endogenous promoter and (B) a mutation that effects increased expression of the heterologous segment, resulting in enhanced production by the host cells of each polypeptide encoded by that segment, relative to production of each polypeptide by the host cells in the absence of the mutation. The increased expression thus achieved is retained in the absence of conditions that select for cells displaying such increased expression. When the integrated segment comprises, for example, ethanol-production genes from an efficient ethanol producer like Zymomonas mobilis, recombinant Escherichia coli and other enteric bacterial cells within the present invention are capable of converting a wide range of biomass-derived sugars efficiently to ethanol.

Recombinant cells that highly express chromosomally-integrated heterologous gene

DOEpatents

Ingram, Lonnie O.; Ohta, Kazuyoshi; Wood, Brent E.

2007-03-20

Recombinant host cells are obtained that comprise (A) a heterologous, polypeptide-encoding polynucleotide segment, stably integrated into a chromosome, which is under transcriptional control of an endogenous promoter and (B) a mutation that effects increased expression of the heterologous segment, resulting in enhanced production by the host cells of each polypeptide encoded by that segment, relative to production of each polypeptide by the host cells in the absence of the mutation. The increased expression thus achieved is retained in the absence of conditions that select for cells displaying such increased expression. When the integrated segment comprises, for example, ethanol-production genes from an efficient ethanol producer like Zymomonas mobilis, recombinant Escherichia coli and other enteric bacterial cells within the present invention are capable of converting a wide range of biomass-derived sugars efficiently to ethanol.

Recombinant cells that highly express chromosomally-integrated heterologous genes

DOEpatents

Ingram, Lonnie O.; Ohta, Kazuyoshi; Wood, Brent E.

2000-08-22

Recombinant host cells are obtained that comprise (A) a heterologous, polypeptide-encoding polynucleotide segment, stably integrated into a chromosome, which is under transcriptional control of an endogenous promoter and (B) a mutation that effects increased expression of the heterologous segment, resulting in enhanced production by the host cells of each polypeptide encoded by that segment, relative to production of each polypeptide by the host cells in the absence of the mutation. The increased expression thus achieved is retained in the absence of conditions that select for cells displaying such increased expression. When the integrated segment comprises, for example, ethanol-production genes from an efficient ethanol producer like Zymomonas mobilis, recombinant Escherichia coli and other enteric bacterial cells within the present invention are capable of converting a wide range of biomass-derived sugars efficiently to ethanol.

A note on the stability and discriminability of graph-based features for classification problems in digital pathology

NASA Astrophysics Data System (ADS)

Cruz-Roa, Angel; Xu, Jun; Madabhushi, Anant

2015-01-01

Nuclear architecture or the spatial arrangement of individual cancer nuclei on histopathology images has been shown to be associated with different grades and differential risk for a number of solid tumors such as breast, prostate, and oropharyngeal. Graph-based representations of individual nuclei (nuclei representing the graph nodes) allows for mining of quantitative metrics to describe tumor morphology. These graph features can be broadly categorized into global and local depending on the type of graph construction method. While a number of local graph (e.g. Cell Cluster Graphs) and global graph (e.g. Voronoi, Delaunay Triangulation, Minimum Spanning Tree) features have been shown to associated with cancer grade, risk, and outcome for different cancer types, the sensitivity of the preceding segmentation algorithms in identifying individual nuclei can have a significant bearing on the discriminability of the resultant features. This therefore begs the question as to which features while being discriminative of cancer grade and aggressiveness are also the most resilient to the segmentation errors. These properties are particularly desirable in the context of digital pathology images, where the method of slide preparation, staining, and type of nuclear segmentation algorithm employed can all dramatically affect the quality of the nuclear graphs and corresponding features. In this paper we evaluated the trade off between discriminability and stability of both global and local graph-based features in conjunction with a few different segmentation algorithms and in the context of two different histopathology image datasets of breast cancer from whole-slide images (WSI) and tissue microarrays (TMA). Specifically in this paper we investigate a few different performance measures including stability, discriminability and stability vs discriminability trade off, all of which are based on p-values from the Kruskal-Wallis one-way analysis of variance for local and global graph features. Apart from identifying the set of local and global features that satisfied the trade off between stability and discriminability, our most interesting finding was that a simple segmentation method was sufficient to identify the most discriminant features for invasive tumour detection in TMAs, whereas for tumour grading in WSI, the graph based features were more sensitive to the accuracy of the segmentation algorithm employed.

[The segmentation of urinary cells--a first step in the automated processing in urine cytology (author's transl)].

PubMed

Liedtke, C E; Aeikens, B

1980-01-01

By segmentation of cell images we understand the automated decomposition of microscopic cell scenes into nucleus, plasma and background. A segmentation is achieved by using information from the microscope image and prior knowledge about the content of the scene. Different algorithms have been investigated and applied to samples of urothelial cells. A particular algorithm based on a histogram approach which can be easily implemented in hardware is discussed in more detail.

Cellular image segmentation using n-agent cooperative game theory

NASA Astrophysics Data System (ADS)

Dimock, Ian B.; Wan, Justin W. L.

2016-03-01

Image segmentation is an important problem in computer vision and has significant applications in the segmentation of cellular images. Many different imaging techniques exist and produce a variety of image properties which pose difficulties to image segmentation routines. Bright-field images are particularly challenging because of the non-uniform shape of the cells, the low contrast between cells and background, and imaging artifacts such as halos and broken edges. Classical segmentation techniques often produce poor results on these challenging images. Previous attempts at bright-field imaging are often limited in scope to the images that they segment. In this paper, we introduce a new algorithm for automatically segmenting cellular images. The algorithm incorporates two game theoretic models which allow each pixel to act as an independent agent with the goal of selecting their best labelling strategy. In the non-cooperative model, the pixels choose strategies greedily based only on local information. In the cooperative model, the pixels can form coalitions, which select labelling strategies that benefit the entire group. Combining these two models produces a method which allows the pixels to balance both local and global information when selecting their label. With the addition of k-means and active contour techniques for initialization and post-processing purposes, we achieve a robust segmentation routine. The algorithm is applied to several cell image datasets including bright-field images, fluorescent images and simulated images. Experiments show that the algorithm produces good segmentation results across the variety of datasets which differ in cell density, cell shape, contrast, and noise levels.

Behavioural properties of chick somitic mesoderm and lateral plate when explanted in vitro.

PubMed

Bellairs, R; Sanders, E J; Portch, P A

1980-04-01

Tissue culture, time-lapse cinematographic and electron microscopic techniques have been used to study the properties of chick mesoderm at several stages of differentiation. Lateral plate, unsegmented mesoderm (segmental plate), and newly formed somites were dissected from stage-12 embryos, whilst dermo-myotomes and sclerotomes were dissected from stage-18 embryos. Each type of mesoderm was found to exhibit a characteristic pattern of behaviour. The explants from the unsegmented mesoderm from the newly formed somites and from the older embryos could be placed in a developmental sequence; with increasing differentiation they settled and spread on the substrate more readily, whether explanted as pieces of tissue or as individual cells, and it was concluded that this implied an increased adhesion to the substrate. Similarly, with increasing differentiation, the cells segmented at a faster rate. No significant differences could be discerned in the internal structure of the different types of cells, although differences in the general shape were apparent. The lateral plate mesoderm cells, which bear some resemblances to the unsegmented mesoderm cells in the embryo, also show some morphological resemblances to them in vitro. However, the lateral plate cells had a much greater success in attaching to glass or platic substrates. They were also found to have the highest speed of locomotion of all the tissues studied, whereas the unsegmented had the lowest. It is concluded therefore, that although cells may look similar to one another morphologically, their behaviour may differ greatly, probably because they are already partially determined.

Segmentation of nuclear images in automated cervical cancer screening

NASA Astrophysics Data System (ADS)

Dadeshidze, Vladimir; Olsson, Lars J.; Domanik, Richard A.

1995-08-01

This paper describes an efficient method of segmenting cell nuclei from complex scenes based upon the use of adaptive region growing in conjuction with nucleus-specific filters. Results of segmenting potentially abnormal (cancer or neoplastic) cell nuclei in Papanicolaou smears from 0.8 square micrometers resolution images are also presented.

ANAlyte: A modular image analysis tool for ANA testing with indirect immunofluorescence.

PubMed

Di Cataldo, Santa; Tonti, Simone; Bottino, Andrea; Ficarra, Elisa

2016-05-01

The automated analysis of indirect immunofluorescence images for Anti-Nuclear Autoantibody (ANA) testing is a fairly recent field that is receiving ever-growing interest from the research community. ANA testing leverages on the categorization of intensity level and fluorescent pattern of IIF images of HEp-2 cells to perform a differential diagnosis of important autoimmune diseases. Nevertheless, it suffers from tremendous lack of repeatability due to subjectivity in the visual interpretation of the images. The automatization of the analysis is seen as the only valid solution to this problem. Several works in literature address individual steps of the work-flow, nonetheless integrating such steps and assessing their effectiveness as a whole is still an open challenge. We present a modular tool, ANAlyte, able to characterize a IIF image in terms of fluorescent intensity level and fluorescent pattern without any user-interactions. For this purpose, ANAlyte integrates the following: (i) Intensity Classifier module, that categorizes the intensity level of the input slide based on multi-scale contrast assessment; (ii) Cell Segmenter module, that splits the input slide into individual HEp-2 cells; (iii) Pattern Classifier module, that determines the fluorescent pattern of the slide based on the pattern of the individual cells. To demonstrate the accuracy and robustness of our tool, we experimentally validated ANAlyte on two different public benchmarks of IIF HEp-2 images with rigorous leave-one-out cross-validation strategy. We obtained overall accuracy of fluorescent intensity and pattern classification respectively around 85% and above 90%. We assessed all results by comparisons with some of the most representative state of the art works. Unlike most of the other works in the recent literature, ANAlyte aims at the automatization of all the major steps of ANA image analysis. Results on public benchmarks demonstrate that the tool can characterize HEp-2 slides in terms of intensity and fluorescent pattern with accuracy better or comparable with the state of the art techniques, even when such techniques are run on manually segmented cells. Hence, ANAlyte can be proposed as a valid solution to the problem of ANA testing automatization. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Algorithm for Automatic Segmentation of Nuclear Boundaries in Cancer Cells in Three-Channel Luminescent Images

NASA Astrophysics Data System (ADS)

Lisitsa, Y. V.; Yatskou, M. M.; Apanasovich, V. V.; Apanasovich, T. V.

2015-09-01

We have developed an algorithm for segmentation of cancer cell nuclei in three-channel luminescent images of microbiological specimens. The algorithm is based on using a correlation between fluorescence signals in the detection channels for object segmentation, which permits complete automation of the data analysis procedure. We have carried out a comparative analysis of the proposed method and conventional algorithms implemented in the CellProfiler and ImageJ software packages. Our algorithm has an object localization uncertainty which is 2-3 times smaller than for the conventional algorithms, with comparable segmentation accuracy.

Phenotypic feature quantification of patient derived 3D cancer spheroids in fluorescence microscopy image

NASA Astrophysics Data System (ADS)

Kang, Mi-Sun; Rhee, Seon-Min; Seo, Ji-Hyun; Kim, Myoung-Hee

2017-03-01

Patients' responses to a drug differ at the cellular level. Here, we present an image-based cell phenotypic feature quantification method for predicting the responses of patient-derived glioblastoma cells to a particular drug. We used high-content imaging to understand the features of patient-derived cancer cells. A 3D spheroid culture formation resembles the in vivo environment more closely than 2D adherent cultures do, and it allows for the observation of cellular aggregate characteristics. However, cell analysis at the individual level is more challenging. In this paper, we demonstrate image-based phenotypic screening of the nuclei of patient-derived cancer cells. We first stitched the images of each well of the 384-well plate with the same state. We then used intensity information to detect the colonies. The nuclear intensity and morphological characteristics were used for the segmentation of individual nuclei. Next, we calculated the position of each nucleus that is appeal of the spatial pattern of cells in the well environment. Finally, we compared the results obtained using 3D spheroid culture cells with those obtained using 2D adherent culture cells from the same patient being treated with the same drugs. This technique could be applied for image-based phenotypic screening of cells to determine the patient's response to the drug.

Semi-automated discrimination of retinal pigmented epithelial cells in two-photon fluorescence images of mouse retinas.

PubMed

Alexander, Nathan S; Palczewska, Grazyna; Palczewski, Krzysztof

2015-08-01

Automated image segmentation is a critical step toward achieving a quantitative evaluation of disease states with imaging techniques. Two-photon fluorescence microscopy (TPM) has been employed to visualize the retinal pigmented epithelium (RPE) and provide images indicating the health of the retina. However, segmentation of RPE cells within TPM images is difficult due to small differences in fluorescence intensity between cell borders and cell bodies. Here we present a semi-automated method for segmenting RPE cells that relies upon multiple weak features that differentiate cell borders from the remaining image. These features were scored by a search optimization procedure that built up the cell border in segments around a nucleus of interest. With six images used as a test, our method correctly identified cell borders for 69% of nuclei on average. Performance was strongly dependent upon increasing retinosome content in the RPE. TPM image analysis has the potential of providing improved early quantitative assessments of diseases affecting the RPE.

Xeno-free culture of human pluripotent stem cells on oligopeptide-grafted hydrogels with various molecular designs

PubMed Central

Chen, Yen-Ming; Chen, Li-Hua; Li, Meng-Pei; Li, Hsing-Fen; Higuchi, Akon; Kumar, S. Suresh; Ling, Qing-Dong; Alarfaj, Abdullah A.; Munusamy, Murugan A.; Chang, Yung; Benelli, Giovanni; Murugan, Kadarkarai; Umezawa, Akihiro

2017-01-01

Establishing cultures of human embryonic (ES) and induced pluripotent (iPS) stem cells in xeno-free conditions is essential for producing clinical-grade cells. Development of cell culture biomaterials for human ES and iPS cells is critical for this purpose. We designed several structures of oligopeptide-grafted poly (vinyl alcohol-co-itaconic acid) hydrogels with optimal elasticity, and prepared them in formations of single chain, single chain with joint segment, dual chain with joint segment, and branched-type chain. Oligopeptide sequences were selected from integrin- and glycosaminoglycan-binding domains of the extracellular matrix. The hydrogels grafted with vitronectin-derived oligopeptides having a joint segment or a dual chain, which has a storage modulus of 25 kPa, supported the long-term culture of human ES and iPS cells for over 10 passages. The dual chain and/or joint segment with cell adhesion molecules on the hydrogels facilitated the proliferation and pluripotency of human ES and iPS cells. PMID:28332572

Xeno-free culture of human pluripotent stem cells on oligopeptide-grafted hydrogels with various molecular designs.

PubMed

Chen, Yen-Ming; Chen, Li-Hua; Li, Meng-Pei; Li, Hsing-Fen; Higuchi, Akon; Kumar, S Suresh; Ling, Qing-Dong; Alarfaj, Abdullah A; Munusamy, Murugan A; Chang, Yung; Benelli, Giovanni; Murugan, Kadarkarai; Umezawa, Akihiro

2017-03-23

Establishing cultures of human embryonic (ES) and induced pluripotent (iPS) stem cells in xeno-free conditions is essential for producing clinical-grade cells. Development of cell culture biomaterials for human ES and iPS cells is critical for this purpose. We designed several structures of oligopeptide-grafted poly (vinyl alcohol-co-itaconic acid) hydrogels with optimal elasticity, and prepared them in formations of single chain, single chain with joint segment, dual chain with joint segment, and branched-type chain. Oligopeptide sequences were selected from integrin- and glycosaminoglycan-binding domains of the extracellular matrix. The hydrogels grafted with vitronectin-derived oligopeptides having a joint segment or a dual chain, which has a storage modulus of 25 kPa, supported the long-term culture of human ES and iPS cells for over 10 passages. The dual chain and/or joint segment with cell adhesion molecules on the hydrogels facilitated the proliferation and pluripotency of human ES and iPS cells.

Automatic Segmentation of High-Throughput RNAi Fluorescent Cellular Images

PubMed Central

Yan, Pingkum; Zhou, Xiaobo; Shah, Mubarak; Wong, Stephen T. C.

2010-01-01

High-throughput genome-wide RNA interference (RNAi) screening is emerging as an essential tool to assist biologists in understanding complex cellular processes. The large number of images produced in each study make manual analysis intractable; hence, automatic cellular image analysis becomes an urgent need, where segmentation is the first and one of the most important steps. In this paper, a fully automatic method for segmentation of cells from genome-wide RNAi screening images is proposed. Nuclei are first extracted from the DNA channel by using a modified watershed algorithm. Cells are then extracted by modeling the interaction between them as well as combining both gradient and region information in the Actin and Rac channels. A new energy functional is formulated based on a novel interaction model for segmenting tightly clustered cells with significant intensity variance and specific phenotypes. The energy functional is minimized by using a multiphase level set method, which leads to a highly effective cell segmentation method. Promising experimental results demonstrate that automatic segmentation of high-throughput genome-wide multichannel screening can be achieved by using the proposed method, which may also be extended to other multichannel image segmentation problems. PMID:18270043

Cell segmentation in time-lapse fluorescence microscopy with temporally varying sub-cellular fusion protein patterns.

PubMed

Bunyak, Filiz; Palaniappan, Kannappan; Chagin, Vadim; Cardoso, M

2009-01-01

Fluorescently tagged proteins such as GFP-PCNA produce rich dynamically varying textural patterns of foci distributed in the nucleus. This enables the behavioral study of sub-cellular structures during different phases of the cell cycle. The varying punctuate patterns of fluorescence, drastic changes in SNR, shape and position during mitosis and abundance of touching cells, however, require more sophisticated algorithms for reliable automatic cell segmentation and lineage analysis. Since the cell nuclei are non-uniform in appearance, a distribution-based modeling of foreground classes is essential. The recently proposed graph partitioning active contours (GPAC) algorithm supports region descriptors and flexible distance metrics. We extend GPAC for fluorescence-based cell segmentation using regional density functions and dramatically improve its efficiency for segmentation from O(N(4)) to O(N(2)), for an image with N(2) pixels, making it practical and scalable for high throughput microscopy imaging studies.

Block design reconstruction skills: not a good candidate for an endophenotypic marker in autism research.

PubMed

de Jonge, Maretha; Kemner, Chantal; Naber, Fabienne; van Engeland, Herman

2009-04-01

Superior performance on block design tasks is reported in autistic individuals, although it is not consistently found in high-functioning individuals or individuals with Asperger Syndrome. It is assumed to reflect weak central coherence: an underlying cognitive deficit, which might also be part of the genetic makeup of the disorder. We assessed block design reconstruction skills in high-functioning individuals with autism spectrum disorders (ASD) from multi-incidence families and in their parents. Performance was compared to relevant matched control groups. We used a task that was assumed to be highly sensitive to subtle performance differences. We did not find individuals with ASD to be significantly faster on this task than the matched control group, not even when the difference between reconstruction time of segmented and pre-segmented designs was compared. However, we found individuals with ASD to make fewer errors during the process of reconstruction which might indicate some dexterity in mental segmentation. However, parents of individuals with ASD did not perform better on the task than control parents. Therefore, based on our data, we conclude that mental segmentation ability as measured with a block design reconstruction task is not a neurocognitive marker or endophenotype useful in genetic studies.

Aberration correction in wide-field fluorescence microscopy by segmented-pupil image interferometry.

PubMed

Scrimgeour, Jan; Curtis, Jennifer E

2012-06-18

We present a new technique for the correction of optical aberrations in wide-field fluorescence microscopy. Segmented-Pupil Image Interferometry (SPII) uses a liquid crystal spatial light modulator placed in the microscope's pupil plane to split the wavefront originating from a fluorescent object into an array of individual beams. Distortion of the wavefront arising from either system or sample aberrations results in displacement of the images formed from the individual pupil segments. Analysis of image registration allows for the local tilt in the wavefront at each segment to be corrected with respect to a central reference. A second correction step optimizes the image intensity by adjusting the relative phase of each pupil segment through image interferometry. This ensures that constructive interference between all segments is achieved at the image plane. Improvements in image quality are observed when Segmented-Pupil Image Interferometry is applied to correct aberrations arising from the microscope's optical path.

Individual Rocks Segmentation in Terrestrial Laser Scanning Point Cloud Using Iterative Dbscan Algorithm

NASA Astrophysics Data System (ADS)

Walicka, A.; Jóźków, G.; Borkowski, A.

2018-05-01

The fluvial transport is an important aspect of hydrological and geomorphologic studies. The knowledge about the movement parameters of different-size fractions is essential in many applications, such as the exploration of the watercourse changes, the calculation of the river bed parameters or the investigation of the frequency and the nature of the weather events. Traditional techniques used for the fluvial transport investigations do not provide any information about the long-term horizontal movement of the rocks. This information can be gained by means of terrestrial laser scanning (TLS). However, this is a complex issue consisting of several stages of data processing. In this study the methodology for individual rocks segmentation from TLS point cloud has been proposed, which is the first step for the semi-automatic algorithm for movement detection of individual rocks. The proposed algorithm is executed in two steps. Firstly, the point cloud is classified as rocks or background using only geometrical information. Secondly, the DBSCAN algorithm is executed iteratively on points classified as rocks until only one stone is detected in each segment. The number of rocks in each segment is determined using principal component analysis (PCA) and simple derivative method for peak detection. As a result, several segments that correspond to individual rocks are formed. Numerical tests were executed on two test samples. The results of the semi-automatic segmentation were compared to results acquired by manual segmentation. The proposed methodology enabled to successfully segment 76 % and 72 % of rocks in the test sample 1 and test sample 2, respectively.

Validity of segmental bioelectrical impedance analysis for estimating fat-free mass in children including overweight individuals.

PubMed

Ohta, Megumi; Midorikawa, Taishi; Hikihara, Yuki; Masuo, Yoshihisa; Sakamoto, Shizuo; Torii, Suguru; Kawakami, Yasuo; Fukunaga, Tetsuo; Kanehisa, Hiroaki

2017-02-01

This study examined the validity of segmental bioelectrical impedance (BI) analysis for predicting the fat-free masses (FFMs) of whole-body and body segments in children including overweight individuals. The FFM and impedance (Z) values of arms, trunk, legs, and whole body were determined using a dual-energy X-ray absorptiometry and segmental BI analyses, respectively, in 149 boys and girls aged 6 to 12 years, who were divided into model-development (n = 74), cross-validation (n = 35), and overweight (n = 40) groups. Simple regression analysis was applied to (length) 2 /Z (BI index) for each of the whole-body and 3 segments to develop the prediction equations of the measured FFM of the related body part. In the model-development group, the BI index of each of the 3 segments and whole body was significantly correlated to the measured FFM (R 2 = 0.867-0.932, standard error of estimation = 0.18-1.44 kg (5.9%-8.7%)). There was no significant difference between the measured and predicted FFM values without systematic error. The application of each equation derived in the model-development group to the cross-validation and overweight groups did not produce significant differences between the measured and predicted FFM values and systematic errors, with an exception that the arm FFM in the overweight group was overestimated. Segmental bioelectrical impedance analysis is useful for predicting the FFM of each of whole-body and body segments in children including overweight individuals, although the application for estimating arm FFM in overweight individuals requires a certain modification.

Cell stimulus and lysis in a microfluidic device with segmented gas-liquid flow.

PubMed

El-Ali, Jamil; Gaudet, Suzanne; Günther, Axel; Sorger, Peter K; Jensen, Klavs F

2005-06-01

We describe a microfluidic device with rapid stimulus and lysis of mammalian cells for resolving fast transient responses in cell signaling networks. The device uses segmented gas-liquid flow to enhance mixing and has integrated thermoelectric heaters and coolers to control the temperature during cell stimulus and lysis. Potential negative effects of segmented flow on cell responses are investigated in three different cell types, with no morphological changes and no activation of the cell stress-sensitive mitogen activated protein kinases observed. Jurkat E6-1 cells are stimulated in the device using alpha-CD3, and the resulting activations of ERK and JNK are presented for different time points. Stimulation of cells performed on chip results in pathway activation identical to that of conventionally treated cells under the same conditions.

An Automatic Segmentation Method Combining an Active Contour Model and a Classification Technique for Detecting Polycomb-group Proteinsin High-Throughput Microscopy Images.

PubMed

Gregoretti, Francesco; Cesarini, Elisa; Lanzuolo, Chiara; Oliva, Gennaro; Antonelli, Laura

2016-01-01

The large amount of data generated in biological experiments that rely on advanced microscopy can be handled only with automated image analysis. Most analyses require a reliable cell image segmentation eventually capable of detecting subcellular structures.We present an automatic segmentation method to detect Polycomb group (PcG) proteins areas isolated from nuclei regions in high-resolution fluorescent cell image stacks. It combines two segmentation algorithms that use an active contour model and a classification technique serving as a tool to better understand the subcellular three-dimensional distribution of PcG proteins in live cell image sequences. We obtained accurate results throughout several cell image datasets, coming from different cell types and corresponding to different fluorescent labels, without requiring elaborate adjustments to each dataset.

Clinical Prognosis of Superior Versus Basal Segment Stage I Non-Small Cell Lung Cancer.

PubMed

Handa, Yoshinori; Tsutani, Yasuhiro; Tsubokawa, Norifumi; Misumi, Keizo; Hanaki, Hideaki; Miyata, Yoshihiro; Okada, Morihito

2017-12-01

Despite its extensive size, variations in the clinicopathologic features of tumors in the lower lobe have been little studied. The present study investigated the prognostic differences in tumors originating from the superior and basal segments of the lower lobe in patients with non-small cell lung cancer. Data of 134 patients who underwent lobectomy or segmentectomy with systematic nodal dissection for clinical stage I, radiologically solid-dominant, non-small cell lung cancer in the superior segment (n = 60) or basal segment (n = 74) between April 2007 and December 2015 were retrospectively reviewed. Factors affecting survival were assessed by the Kaplan-Meier method and Cox regression analyses. Prognosis in the superior segment group was worse than that in the basal segment group (5-year overall survival rates 62.6% versus 89.9%, p = 0.0072; and 5-year recurrence-free survival rates 54.4% versus 75.7%, p = 0.032). In multivariable Cox regression analysis, a superior segment tumor was an independent factor for poor overall survival (hazard ratio 3.33, 95% confidence interval: 1.22 to 13.5, p = 0.010) and recurrence-free survival (hazard ratio 2.90, 95% confidence interval: 1.20 to 7.00, p = 0.008). The superior segment group tended to have more pathologic mediastinal lymph node metastases than the basal segment group (15.0% versus 5.4%, p = 0.080). Tumor location was a prognostic factor for clinical stage I non-small cell lung cancer in the lower lobe. Patients with superior segment tumors had worse prognosis than patients with basal segment tumors, with more metastases in mediastinal lymph nodes. Copyright © 2017 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Segmentation of the zebrafish axial skeleton relies on notochord sheath cells and not on the segmentation clock

PubMed Central

Lleras Forero, Laura; Narayanan, Rachna; Huitema, Leonie FA; VanBergen, Maaike; Apschner, Alexander; Peterson-Maduro, Josi; Logister, Ive; Valentin, Guillaume

2018-01-01

Segmentation of the axial skeleton in amniotes depends on the segmentation clock, which patterns the paraxial mesoderm and the sclerotome. While the segmentation clock clearly operates in teleosts, the role of the sclerotome in establishing the axial skeleton is unclear. We severely disrupt zebrafish paraxial segmentation, yet observe a largely normal segmentation process of the chordacentra. We demonstrate that axial entpd5+ notochord sheath cells are responsible for chordacentrum mineralization, and serve as a marker for axial segmentation. While autonomous within the notochord sheath, entpd5 expression and centrum formation show some plasticity and can respond to myotome pattern. These observations reveal for the first time the dynamics of notochord segmentation in a teleost, and are consistent with an autonomous patterning mechanism that is influenced, but not determined by adjacent paraxial mesoderm. This behavior is not consistent with a clock-type mechanism in the notochord. PMID:29624170

Semi-automated segmentation of neuroblastoma nuclei using the gradient energy tensor: a user driven approach

NASA Astrophysics Data System (ADS)

Kromp, Florian; Taschner-Mandl, Sabine; Schwarz, Magdalena; Blaha, Johanna; Weiss, Tamara; Ambros, Peter F.; Reiter, Michael

2015-02-01

We propose a user-driven method for the segmentation of neuroblastoma nuclei in microscopic fluorescence images involving the gradient energy tensor. Multispectral fluorescence images contain intensity and spatial information about antigene expression, fluorescence in situ hybridization (FISH) signals and nucleus morphology. The latter serves as basis for the detection of single cells and the calculation of shape features, which are used to validate the segmentation and to reject false detections. Accurate segmentation is difficult due to varying staining intensities and aggregated cells. It requires several (meta-) parameters, which have a strong influence on the segmentation results and have to be selected carefully for each sample (or group of similar samples) by user interactions. Because our method is designed for clinicians and biologists, who may have only limited image processing background, an interactive parameter selection step allows the implicit tuning of parameter values. With this simple but intuitive method, segmentation results with high precision for a large number of cells can be achieved by minimal user interaction. The strategy was validated on handsegmented datasets of three neuroblastoma cell lines.

Attributed relational graphs for cell nucleus segmentation in fluorescence microscopy images.

PubMed

Arslan, Salim; Ersahin, Tulin; Cetin-Atalay, Rengul; Gunduz-Demir, Cigdem

2013-06-01

More rapid and accurate high-throughput screening in molecular cellular biology research has become possible with the development of automated microscopy imaging, for which cell nucleus segmentation commonly constitutes the core step. Although several promising methods exist for segmenting the nuclei of monolayer isolated and less-confluent cells, it still remains an open problem to segment the nuclei of more-confluent cells, which tend to grow in overlayers. To address this problem, we propose a new model-based nucleus segmentation algorithm. This algorithm models how a human locates a nucleus by identifying the nucleus boundaries and piecing them together. In this algorithm, we define four types of primitives to represent nucleus boundaries at different orientations and construct an attributed relational graph on the primitives to represent their spatial relations. Then, we reduce the nucleus identification problem to finding predefined structural patterns in the constructed graph and also use the primitives in region growing to delineate the nucleus borders. Working with fluorescence microscopy images, our experiments demonstrate that the proposed algorithm identifies nuclei better than previous nucleus segmentation algorithms.

Note: An automated image analysis method for high-throughput classification of surface-bound bacterial cell motions.

PubMed

Shen, Simon; Syal, Karan; Tao, Nongjian; Wang, Shaopeng

2015-12-01

We present a Single-Cell Motion Characterization System (SiCMoCS) to automatically extract bacterial cell morphological features from microscope images and use those features to automatically classify cell motion for rod shaped motile bacterial cells. In some imaging based studies, bacteria cells need to be attached to the surface for time-lapse observation of cellular processes such as cell membrane-protein interactions and membrane elasticity. These studies often generate large volumes of images. Extracting accurate bacterial cell morphology features from these images is critical for quantitative assessment. Using SiCMoCS, we demonstrated simultaneous and automated motion tracking and classification of hundreds of individual cells in an image sequence of several hundred frames. This is a significant improvement from traditional manual and semi-automated approaches to segmenting bacterial cells based on empirical thresholds, and a first attempt to automatically classify bacterial motion types for motile rod shaped bacterial cells, which enables rapid and quantitative analysis of various types of bacterial motion.

The Use of a Human Breast Tumor Progression Series and a 3-D Culture Model to Determine if Nuclear Structure Could Provide a Molecular and Therapeutic Marker

DTIC Science & Technology

2000-01-01

organization with cell phenotype. (In manuscript form) C Ortiz de Solorzano, R . Malladi , SA Leli~vre, and SJ Lockett. Segmentation of nuclei and cells...Ortiz de Solorzano, R . Malladi , SA Leli~vre, and SJ Lockett. "Segmentation of nuclei and cells using membrane related protein markers." (Submitted) 6...specificity Segmentation of Nuclei and Cells using Membrane Related Protein Markers C. Ortiz de Solorzano, R . Malladi , S!/•Lelievre, S.J. Lockett Lawrence

Resegmentation in the Mexican axolotl, Ambystoma mexicanum.

PubMed

Piekarski, Nadine; Olsson, Lennart

2014-02-01

The segmental series of somites in the vertebrate embryo gives rise to the axial skeleton. In amniote models, single vertebrae are derived from the sclerotome of two adjacent somites. This process, known as resegmentation, is well-studied using the quail-chick chimeric system, but the presumed generality of resegmentation across vertebrates remains poorly evaluated. Resegmentation has been questioned in anamniotes, given that the sclerotome is much smaller and lacks obvious differentiation between cranial and caudal portions. Here, we provide the first experimental evidence that resegmentation does occur in a species of amphibian. Fate mapping of individual somites in the Mexican axolotl (Ambystoma mexicanum) revealed that individual vertebrae receive cells from two adjacent somites as in the chicken. These findings suggest that large size and segmentation of the sclerotome into distinct cranial and caudal portions are not requirements for resegmentation. Our results, in addition to those for zebrafish, indicate that resegmentation is a general process in building the vertebral column in vertebrates, although it may be achieved in different ways in different groups. Copyright © 2013 Wiley Periodicals, Inc.

Expression and Significance of Neuroligins in Myenteric Cells of Cajal in Hirschsprung's Disease

PubMed Central

Wang, Jian; Mou, Yaru; Zhang, Qiangye; Zhang, Fan; Yang, Hongchao; Zhang, Wentong; Li, Aiwu

2013-01-01

Purpose The aim of this study was to investigate the expression and significance of neuroligins in myenteric cells of Cajal (ICC-MY) in Hirschsprung’s disease (HSCR). Methods Longitudinal muscle with adherent myenteric plexus (LMMP) from surgical excision waste colon of HSCR children were prepared by peeling off the mucous layer, sub-mucosal layer and circular muscle. Neuroligins, c-Kit (c-Kit-immunoreactivity representing ICC) and their relationship were assessed by double labeling immunofluorescence staining. ICC-MY were dissociated and cultured from LMMP by enzymolysis method, and were purified and analyzed using a combination of magnetic-activated cell sorting (MACS) and flow cytometry (FCM). Western-blot analysis was applied to compare and evaluate the expression levels of neuroligins in ICC-MY which were dissociated from different segments of HSCR (ganglionic colonic segment, transitional colonic segment and aganglionic colonic segment). Results Neuroligins and c-Kit were expressed on the same cells (ICC-MY); ICC-MY were dissociated, cultured and purified. For HSCR, neuroligins were expressed significantly in ICC-MY from ganglionic colonic segments, moderately in those from transitional colonic segments and down-regulated significantly in those from aganglionic colonic segments. Conclusions Neuroligins were expressed in ICC-MY of human beings, and the expression varies from different segments of HSCR. This abnormal expression might play an important role in the pathogenesis of this disease through affecting the synaptic function of ICC-MY. PMID:23840625

The Consequences of Reconfiguring the Ambisense S Genome Segment of Rift Valley Fever Virus on Viral Replication in Mammalian and Mosquito Cells and for Genome Packaging

PubMed Central

Elliott, Richard M.

2014-01-01

Rift Valley fever virus (RVFV, family Bunyaviridae) is a mosquito-borne pathogen of both livestock and humans, found primarily in Sub-Saharan Africa and the Arabian Peninsula. The viral genome comprises two negative-sense (L and M segments) and one ambisense (S segment) RNAs that encode seven proteins. The S segment encodes the nucleocapsid (N) protein in the negative-sense and a nonstructural (NSs) protein in the positive-sense, though NSs cannot be translated directly from the S segment but rather from a specific subgenomic mRNA. Using reverse genetics we generated a virus, designated rMP12:S-Swap, in which the N protein is expressed from the NSs locus and NSs from the N locus within the genomic S RNA. In cells infected with rMP12:S-Swap NSs is expressed at higher levels with respect to N than in cells infected with the parental rMP12 virus. Despite NSs being the main interferon antagonist and determinant of virulence, growth of rMP12:S-Swap was attenuated in mammalian cells and gave a small plaque phenotype. The increased abundance of the NSs protein did not lead to faster inhibition of host cell protein synthesis or host cell transcription in infected mammalian cells. In cultured mosquito cells, however, infection with rMP12:S-Swap resulted in cell death rather than establishment of persistence as seen with rMP12. Finally, altering the composition of the S segment led to a differential packaging ratio of genomic to antigenomic RNA into rMP12:S-Swap virions. Our results highlight the plasticity of the RVFV genome and provide a useful experimental tool to investigate further the packaging mechanism of the segmented genome. PMID:24550727

The fine structure of the terminal segment of the bovine seminiferous tubule.

PubMed

Wrobel, K H; Sinowatz, F; Mademann, R

1982-01-01

The intratesticular excurrent duct system of the bull is composed of rete testis, tubuli recti, and the terminal segment of the seminiferous tubules. Each terminal segment is surrounded by a vascular plexus and may be subdivided into a transitional region, middle portion, and terminal plug. The modified supporting cells of the middle portion and the terminal plug no longer display the typical Sertoli-Sertoli junctions seen in the transitional region and the seminiferous tubule proper. In the region of the terminal plug a distinct central lumen is generally not observed: spermatozoa and tubular fluid must pass through an intricate system of communicating clefts between the apices of the closely attached modified supporting cells. Vacuoles in the supranuclear region of the cells in the middle portion indicate strong transepithelial fluid transport. In analogy to the epithelium of rete testis and tubuli recti, the supporting cells of the terminal segment are capable of phagocytosing spermatozoa. The vascular plexus investing the terminal segment serves a dual purpose: it is a regulatory device for fluid and sperm transport, as well as an area of increased diapedesis for white blood cells.

Morphophysiological study of digestive system litter-feeding termite Cornitermes cumulans (Kollar, 1832).

PubMed

de Sousa, Géssica; Dos Santos, Vânia Cristina; de Figueiredo Gontijo, Nelder; Constantino, Reginaldo; de Oliveira Paiva E Silva, Gabriela; Bahia, Ana Cristina; Gomes, Fabio Mendonça; de Alcantara Machado, Ednildo

2017-06-01

Termites are the major decomposers of lignocellulosic biomass on Earth and are commonly considered as biological reactor models for lignocellulose degradation. Despite their biotechnological potential, few studies have focused on the morphophysiological aspects of the termite digestive system. We therefore analyze the morphology, ultrastructure and gut luminal pH of the digestive system in workers of the litter-feeding termite Cornitermes cumulans (Blattodea: Termitidae). Their digestive system is composed of salivary glands and an alimentary canal with a pH ranging from neutral to alkaline. The salivary glands have an acinar structure and present cells with secretory characteristics. The alimentary canal is differentiated into the foregut, midgut, mixed segment and hindgut, which comprises the ileum (p1), enteric valve (p2), paunch (p3), colon (p4) and rectum (p5) segments. The foregut has a well-developed chewing system. The midgut possesses a tubular peritrophic membrane and two cell types: digestive cells with secretory and absorptive features and several regenerative cells in mitosis, both cell types being organized into regenerative crypts. The mixed segment exhibits cells rich in glycogen granules. Hindgut p1, p4 and p5 segments have flattened cells with a few apical invaginations related to mitochondria and a thick cuticular lining. Conversely, the hindgut p3 segment contains large cuboid cells with extensive apical invaginations associated with numerous mitochondria. These new insights into the morphophysiology of the digestive system of C. cumulans reveal that it mobilizes lignocellulose components as a nutritional source by means of a highly compartmentalized organization with specialized segments and complex microenvironments.

Event Segmentation Improves Event Memory up to One Month Later

ERIC Educational Resources Information Center

Flores, Shaney; Bailey, Heather R.; Eisenberg, Michelle L.; Zacks, Jeffrey M.

2017-01-01

When people observe everyday activity, they spontaneously parse it into discrete meaningful events. Individuals who segment activity in a more normative fashion show better subsequent memory for the events. If segmenting events effectively leads to better memory, does asking people to attend to segmentation improve subsequent memory? To answer…

Claudins and renal salt transport.

PubMed

Muto, Shigeaki; Furuse, Mikio; Kusano, Eiji

2012-02-01

Tight junctions (TJs) are the most apical component of junctional complexes and regulate the movement of electrolytes and solutes by the paracellular pathway across epithelia. The defining ultrastructural features of TJs are strands of transmembrane protein particles that adhere to similar strands on adjacent cells. These strands are mainly composed of linearly polymerized integral membrane proteins called claudins. Claudins comprise a multigene family consisting of more than 20 members in mammals. Recent work has shown that claudins form barriers, determined by the paracellular electrical resistance and charge selectivity, and pores in the TJ strands. The paracellular pathways in renal tubular epithelia such as the proximal tubule, which reabsorbs the largest fraction of filtered NaCl and water, are important routes for the transport of electrolytes and water. Their transport characteristics vary among different nephron segments. Multiple claudins are expressed at TJs of individual nephron segments in a nephron segment-specific manner. Among them, claudin-2 is highly expressed at TJs of proximal tubules, which are leaky epithelia. Overexpression and knockdown of claudin-2 in epithelial cell lines, and knockout of the claudin-2 gene in mice, have demonstrated that claudin-2 forms high-conductance cation-selective pores in the proximal tubule. Here, we review the renal physiology of paracellular transport and the physiological roles of claudins in kidney function, especially claudin-2 and proximal tubule paracellular NaCl transport.

Sandia Simple Particle Tracking (Sandia SPT) v. 1.0

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anthony, Stephen M.

2015-06-15

Sandia SPT is designed as software to accompany a book chapter being published a methods chapter which provides an introduction on how to label and track individual proteins. The Sandia Simple Particle Tracking code uses techniques common to the image processing community, where its value is that it facilitates implementing the methods described in the book chapter by providing the necessary open-source code. The code performs single particle spot detection (or segmentation and localization) followed by tracking (or connecting the detected particles into trajectories). The book chapter, which along with the headers in each file, constitutes the documentation for themore » code is: Anthony, S.M.; Carroll-Portillo, A.; Timlon, J.A., Dynamics and Interactions of Individual Proteins in the Membrane of Living Cells. In Anup K. Singh (Ed.) Single Cell Protein Analysis Methods in Molecular Biology. Springer« less

Ethanol synthesis and aerobic respiration in the laboratory by leader segments of Douglas-fir seedlings from winter and spring.

PubMed

Joseph, Gladwin; Kelsey, Rick G

2004-05-01

Stem segments from terminal leaders of Douglas-fir, Pseudotsuga menziesii (Mirb.) Franco, seedlings were sampled in mid-December when cambial cells were dormant. The residual, debudded leaders were resampled again in early May when the cambium was metabolically active. May stems had higher constitutive ethanol concentrations than December stems. This was not the result of cambial hypoxia generated by rapid spring respiration rates, because when aerobic respiration was stimulated by incubating the stems in air at 30 degrees C ethanol production was induced in December, but not in May. Rapid respiration rates at 30 degrees C may have depleted O(2) supplies and induced ethanol production in December stems because dormant, thick-walled cambial cells may be less permeable to CO(2) and O(2), compared with metabolically active, thin-walled cambial cells in May. December stem segments incubated in a N(2) atmosphere at 30 degrees C synthesized 1.8 times more ethanol than segments from May, most likely because spring growth had reduced the soluble sugars available for fermentation. CO(2) efflux from May stems (after 5.5 h of incubation at 30 degrees C) was equal to December stems per unit volume, but greater than December stems per unit surface area. N(2)-induced ethanol concentrations were positively related with CO(2) efflux per unit volume, indicating that rapidly respiring leaders can maintain rapid fermentation rates, provided soluble sugars are readily available. N(2)-induced ethanol and CO(2) efflux per unit volume declined with increasing leader diameter in both seasons, whereas there were no relationships between CO(2) efflux per unit surface area and diameter. Cambium physiology and phenology influence the induction of fermentation and concentrations of ethanol produced in terminal leaders of Douglas-fir, and probably other conifers as well. This needs to be considered when comparing fermentation among species, or comparing individuals from different seasons, or disparate ages within a species.

Segmental duplications and evolutionary acquisition of UV damage response in the SPATA31 gene family of primates and humans.

PubMed

Bekpen, Cemalettin; Künzel, Sven; Xie, Chen; Eaaswarkhanth, Muthukrishnan; Lin, Yen-Lung; Gokcumen, Omer; Akdis, Cezmi A; Tautz, Diethard

2017-03-06

Segmental duplications are an abundant source for novel gene functions and evolutionary adaptations. This mechanism of generating novelty was very active during the evolution of primates particularly in the human lineage. Here, we characterize the evolution and function of the SPATA31 gene family (former designation FAM75A), which was previously shown to be among the gene families with the strongest signal of positive selection in hominoids. The mouse homologue for this gene family is a single copy gene expressed during spermatogenesis. We show that in primates, the SPATA31 gene duplicated into SPATA31A and SPATA31C types and broadened the expression into many tissues. Each type became further segmentally duplicated in the line towards humans with the largest number of full-length copies found for SPATA31A in humans. Copy number estimates of SPATA31A based on digital PCR show an average of 7.5 with a range of 5-11 copies per diploid genome among human individuals. The primate SPATA31 genes also acquired new protein domains that suggest an involvement in UV response and DNA repair. We generated antibodies and show that the protein is re-localized from the nucleolus to the whole nucleus upon UV-irradiation suggesting a UV damage response. We used CRISPR/Cas mediated mutagenesis to knockout copies of the gene in human primary fibroblast cells. We find that cell lines with reduced functional copies as well as naturally occurring low copy number HFF cells show enhanced sensitivity towards UV-irradiation. The acquisition of new SPATA31 protein functions and its broadening of expression may be related to the evolution of the diurnal life style in primates that required a higher UV tolerance. The increased segmental duplications in hominoids as well as its fast evolution suggest the acquisition of further specific functions particularly in humans.

Development Status of Adjustable X-Ray Optics with 0.5 Arcsecond Resolution

NASA Technical Reports Server (NTRS)

Reid, P. B.; ODell, Stephen; Elsner, Ron; Ramsey, Brian; Gubarev, Misha; Aldcroft, T.; Allured, R.; Cotroneo, V.; Johnson-Wilke, R. L.; McMuldroch, S.;

Quantitative Analysis of Statics and Dynamics of Actin Cables in Fission Yeast

NASA Astrophysics Data System (ADS)

Yusuf, Eddy; Wu, Jian-Qiu; Vavylonis, Dimitrios

2010-03-01

The assembly of actin and tubulin proteins into long filaments and bundles, i.e. closely-packed filaments, underlies important cellular processes such as cell motility, intracellular transport, and cell division. Recent theoretical and experimental work has addressed the nonequilibrium dynamics of single microtubules within live cells [1]. Actin filaments usually form dense networks that prevents microscopic imaging of individual filaments or bundles. Here, we studied actin dynamics using fission yeast that has low-density actin cytoskeleton consisting of actin cables (actin bundles aligned along the long axis of the cell) and ``actin patches.'' Yeast cells expressing GFP-CHD were imaged by 3D confocal microscopy. Stretching open active contours [2] were used to segment and track individual actin cables. We analyzed their curvature distribution, the tangent correlation, and the temporal bending amplitude fluctuations. We contrast our findings to equilibrium fluctuating semiflexible polymers and to microtubules in cells. We calculate the important time and length scales for the actin cables. We also discuss our findings within the broad context of understanding actin assembly in cells. [1] C. P. Brangwynne et. al., Phys. Rev. Lett. 100, 118104 (2008) [2] H. Li et. al., Proc. of the IEEE Int'l Symposium on Biomedical Imaging: From Nano to Macro, ISBI'09

Accurate Morphology Preserving Segmentation of Overlapping Cells based on Active Contours

PubMed Central

Molnar, Csaba; Jermyn, Ian H.; Kato, Zoltan; Rahkama, Vesa; Östling, Päivi; Mikkonen, Piia; Pietiäinen, Vilja; Horvath, Peter

2016-01-01

The identification of fluorescently stained cell nuclei is the basis of cell detection, segmentation, and feature extraction in high content microscopy experiments. The nuclear morphology of single cells is also one of the essential indicators of phenotypic variation. However, the cells used in experiments can lose their contact inhibition, and can therefore pile up on top of each other, making the detection of single cells extremely challenging using current segmentation methods. The model we present here can detect cell nuclei and their morphology even in high-confluency cell cultures with many overlapping cell nuclei. We combine the “gas of near circles” active contour model, which favors circular shapes but allows slight variations around them, with a new data model. This captures a common property of many microscopic imaging techniques: the intensities from superposed nuclei are additive, so that two overlapping nuclei, for example, have a total intensity that is approximately double the intensity of a single nucleus. We demonstrate the power of our method on microscopic images of cells, comparing the results with those obtained from a widely used approach, and with manual image segmentations by experts. PMID:27561654

The cascaded moving k-means and fuzzy c-means clustering algorithms for unsupervised segmentation of malaria images

NASA Astrophysics Data System (ADS)

Abdul-Nasir, Aimi Salihah; Mashor, Mohd Yusoff; Halim, Nurul Hazwani Abd; Mohamed, Zeehaida

2015-05-01

Malaria is a life-threatening parasitic infectious disease that corresponds for nearly one million deaths each year. Due to the requirement of prompt and accurate diagnosis of malaria, the current study has proposed an unsupervised pixel segmentation based on clustering algorithm in order to obtain the fully segmented red blood cells (RBCs) infected with malaria parasites based on the thin blood smear images of P. vivax species. In order to obtain the segmented infected cell, the malaria images are first enhanced by using modified global contrast stretching technique. Then, an unsupervised segmentation technique based on clustering algorithm has been applied on the intensity component of malaria image in order to segment the infected cell from its blood cells background. In this study, cascaded moving k-means (MKM) and fuzzy c-means (FCM) clustering algorithms has been proposed for malaria slide image segmentation. After that, median filter algorithm has been applied to smooth the image as well as to remove any unwanted regions such as small background pixels from the image. Finally, seeded region growing area extraction algorithm has been applied in order to remove large unwanted regions that are still appeared on the image due to their size in which cannot be cleaned by using median filter. The effectiveness of the proposed cascaded MKM and FCM clustering algorithms has been analyzed qualitatively and quantitatively by comparing the proposed cascaded clustering algorithm with MKM and FCM clustering algorithms. Overall, the results indicate that segmentation using the proposed cascaded clustering algorithm has produced the best segmentation performances by achieving acceptable sensitivity as well as high specificity and accuracy values compared to the segmentation results provided by MKM and FCM algorithms.

Empirical gradient threshold technique for automated segmentation across image modalities and cell lines.

PubMed

Chalfoun, J; Majurski, M; Peskin, A; Breen, C; Bajcsy, P; Brady, M

2015-10-01

New microscopy technologies are enabling image acquisition of terabyte-sized data sets consisting of hundreds of thousands of images. In order to retrieve and analyze the biological information in these large data sets, segmentation is needed to detect the regions containing cells or cell colonies. Our work with hundreds of large images (each 21,000×21,000 pixels) requires a segmentation method that: (1) yields high segmentation accuracy, (2) is applicable to multiple cell lines with various densities of cells and cell colonies, and several imaging modalities, (3) can process large data sets in a timely manner, (4) has a low memory footprint and (5) has a small number of user-set parameters that do not require adjustment during the segmentation of large image sets. None of the currently available segmentation methods meet all these requirements. Segmentation based on image gradient thresholding is fast and has a low memory footprint. However, existing techniques that automate the selection of the gradient image threshold do not work across image modalities, multiple cell lines, and a wide range of foreground/background densities (requirement 2) and all failed the requirement for robust parameters that do not require re-adjustment with time (requirement 5). We present a novel and empirically derived image gradient threshold selection method for separating foreground and background pixels in an image that meets all the requirements listed above. We quantify the difference between our approach and existing ones in terms of accuracy, execution speed, memory usage and number of adjustable parameters on a reference data set. This reference data set consists of 501 validation images with manually determined segmentations and image sizes ranging from 0.36 Megapixels to 850 Megapixels. It includes four different cell lines and two image modalities: phase contrast and fluorescent. Our new technique, called Empirical Gradient Threshold (EGT), is derived from this reference data set with a 10-fold cross-validation method. EGT segments cells or colonies with resulting Dice accuracy index measurements above 0.92 for all cross-validation data sets. EGT results has also been visually verified on a much larger data set that includes bright field and Differential Interference Contrast (DIC) images, 16 cell lines and 61 time-sequence data sets, for a total of 17,479 images. This method is implemented as an open-source plugin to ImageJ as well as a standalone executable that can be downloaded from the following link: https://isg.nist.gov/. © 2015 The Authors Journal of Microscopy © 2015 Royal Microscopical Society.

Segmentation of Pollen Tube Growth Videos Using Dynamic Bi-Modal Fusion and Seam Carving.

PubMed

Tambo, Asongu L; Bhanu, Bir

2016-05-01

The growth of pollen tubes is of significant interest in plant cell biology, as it provides an understanding of internal cell dynamics that affect observable structural characteristics such as cell diameter, length, and growth rate. However, these parameters can only be measured in experimental videos if the complete shape of the cell is known. The challenge is to accurately obtain the cell boundary in noisy video images. Usually, these measurements are performed by a scientist who manually draws regions-of-interest on the images displayed on a computer screen. In this paper, a new automated technique is presented for boundary detection by fusing fluorescence and brightfield images, and a new efficient method of obtaining the final cell boundary through the process of Seam Carving is proposed. This approach takes advantage of the nature of the fusion process and also the shape of the pollen tube to efficiently search for the optimal cell boundary. In video segmentation, the first two frames are used to initialize the segmentation process by creating a search space based on a parametric model of the cell shape. Updates to the search space are performed based on the location of past segmentations and a prediction of the next segmentation.Experimental results show comparable accuracy to a previous method, but significant decrease in processing time. This has the potential for real time applications in pollen tube microscopy.

A dual-modal retinal imaging system with adaptive optics.

PubMed

Meadway, Alexander; Girkin, Christopher A; Zhang, Yuhua

2013-12-02

An adaptive optics scanning laser ophthalmoscope (AO-SLO) is adapted to provide optical coherence tomography (OCT) imaging. The AO-SLO function is unchanged. The system uses the same light source, scanning optics, and adaptive optics in both imaging modes. The result is a dual-modal system that can acquire retinal images in both en face and cross-section planes at the single cell level. A new spectral shaping method is developed to reduce the large sidelobes in the coherence profile of the OCT imaging when a non-ideal source is used with a minimal introduction of noise. The technique uses a combination of two existing digital techniques. The thickness and position of the traditionally named inner segment/outer segment junction are measured from individual photoreceptors. In-vivo images of healthy and diseased human retinas are demonstrated.

Reproduction in the male honey possum (Tarsipes rostratus: Marsupialia): the epididymis.

PubMed

Cummins, J M; Temple-Smith, P D; Renfree, M B

1986-11-01

The epididymis of the adult honey possum, Tarsipes rostratus, is enclosed by a heavily pigmented tunica vaginalis and lies with the testis in a prominent prepenile scrotum. It is connected to the testis by a single ductus efferentis and is lined by approximately equal numbers of cuboidal ciliated and principal cells. It is unusual for marsupials in having no well-defined compartments or fibrous septae and in having extensive convolutions of the duct only at the caudal flexure. Three principal functional zones (initial, middle, and terminal segments) were identified in the epididymis, based on epithelial type and ultrastructural evidence of sperm maturation. Luminal diameter increases progressively throughout the tract, and epithelial height variations (from about 2 to 20 microns) are greatest in the terminal segment. The epithelium itself is remarkably low (maximum of 21.6 microns) compared with that seen in the epididymis of other mammals. The thickness of the peritubular smooth muscle coat increases close to the junction of the epididymis and ductus deferens. Sperm concentrations were estimated from counts of sperm nuclei and thus can be no more than approximations. The figures are consistent, however, with a rapid increase in concentration in the initial segment, indicating extensive fluid resorption. Sperm concentrations appear to peak in the distal zone of the terminal segment, although sampling problems and wide variations in count make such a conclusion only tentative. Principal and basal cells are the predominant cell types in the epididymal epithelium. Basal cells are most abundant in the initial and distal middle segment. Principal cells show structural evidence of active exchange with the luminal contents and have abundant apical stereocilia, the structure of which depends on the epididymal zone. Other cell types occur less commonly in the epithelium. Lipid-rich and phagocytic principal cells are restricted to the middle and distal zones of the middle segment, respectively. Clear cells, restricted to the terminal segment, and halo cells were found in very low numbers. As in some other marsupials, principal cells (possibly specialized for this function) selectively remove cytoplasmic droplets and probably other cellular debris from the luminal contents. In Tarsipes, however, this process is not very efficient, and many discarded droplets pass through to the terminal segment where they form large masses of debris associated with aggregates of degenerating spermatozoa.

Facilitative glucose transporter Glut1 is actively excluded from rod outer segments.

PubMed

Gospe, Sidney M; Baker, Sheila A; Arshavsky, Vadim Y

2010-11-01

Photoreceptors are among the most metabolically active cells in the body, relying on both oxidative phosphorylation and glycolysis to satisfy their high energy needs. Local glycolysis is thought to be particularly crucial in supporting the function of the photoreceptor's light-sensitive outer segment compartment, which is devoid of mitochondria. Accordingly, it has been commonly accepted that the facilitative glucose transporter Glut1 responsible for glucose entry into photoreceptors is localized in part to the outer segment plasma membrane. However, we now demonstrate that Glut1 is entirely absent from the rod outer segment and is actively excluded from this compartment by targeting information present in its cytosolic C-terminal tail. Our data indicate that glucose metabolized in the outer segment must first enter through other parts of the photoreceptor cell. Consequently, the entire energy supply of the outer segment is dependent on diffusion of energy-rich substrates through the thin connecting cilium that links this compartment to the rest of the cell.

ICTV Virus Taxonomy Profile: Chrysoviridae.

PubMed

Ghabrial, Said A; Castón, José R; Coutts, Robert H A; Hillman, Bradley I; Jiang, Daohong; Kim, Dae-Hyun; Moriyama, Hiromitsu; Ictv Report Consortium

2018-01-01

The Chrysoviridae is a family of small, isometric, non-enveloped viruses (40 nm in diameter) with segmented dsRNA genomes (typically four segments). The genome segments are individually encapsidated and together comprise 11.5-12.8 kbp. The single genus Chrysovirus includes nine species. Chrysoviruses lack an extracellular phase to their life cycle; they are transmitted via intracellular routes within an individual during hyphal growth, in asexual or sexual spores, or between individuals via hyphal anastomosis. There are no known natural vectors for chrysoviruses. This is a summary of the International Committee on Taxonomy of Viruses (ICTV) Report on the taxonomy of the Chrysoviridae, which is available at www.ictv.global/report/chrysoviridae.

Dynamic changes in cortical tensions in multiple cell types during germband retraction

NASA Astrophysics Data System (ADS)

Hutson, M. Shane; Lacy, Monica E.; McCleery, W. Tyler

The process of germband retraction in Drosophila embryogenesis involves the coordinated mechanics of both germband and amnioserosa cells. These two tissues simultaneously and coordinately uncurl from their interlocking U-like shapes. As tissue-level retraction proceeds, individual cells change shape in stereotypical ways. Using time-lapse confocal images, analysis of dynamic cellular triple-junction angles, and whole-embryo finite-element models, we have quantified dynamic changes in cortical tensions - including their anisotropy - in both germband and amnioserosa cells. We find a strong transition midway through the two-hour course of retraction at which point tensions and anisotropies undergo a near step change. These changes take place among amnioserosa cells, in multiple segments of the germband, and at the interface between these two tissues. Research was supported by NIH Grant Numbers 1R01GM099107 and 1R21AR068933.

Automatic segmentation of closed-contour features in ophthalmic images using graph theory and dynamic programming.

PubMed

Chiu, Stephanie J; Toth, Cynthia A; Bowes Rickman, Catherine; Izatt, Joseph A; Farsiu, Sina

2012-05-01

This paper presents a generalized framework for segmenting closed-contour anatomical and pathological features using graph theory and dynamic programming (GTDP). More specifically, the GTDP method previously developed for quantifying retinal and corneal layer thicknesses is extended to segment objects such as cells and cysts. The presented technique relies on a transform that maps closed-contour features in the Cartesian domain into lines in the quasi-polar domain. The features of interest are then segmented as layers via GTDP. Application of this method to segment closed-contour features in several ophthalmic image types is shown. Quantitative validation experiments for retinal pigmented epithelium cell segmentation in confocal fluorescence microscopy images attests to the accuracy of the presented technique.

Automatic segmentation of closed-contour features in ophthalmic images using graph theory and dynamic programming

PubMed Central

Chiu, Stephanie J.; Toth, Cynthia A.; Bowes Rickman, Catherine; Izatt, Joseph A.; Farsiu, Sina

2012-01-01

This paper presents a generalized framework for segmenting closed-contour anatomical and pathological features using graph theory and dynamic programming (GTDP). More specifically, the GTDP method previously developed for quantifying retinal and corneal layer thicknesses is extended to segment objects such as cells and cysts. The presented technique relies on a transform that maps closed-contour features in the Cartesian domain into lines in the quasi-polar domain. The features of interest are then segmented as layers via GTDP. Application of this method to segment closed-contour features in several ophthalmic image types is shown. Quantitative validation experiments for retinal pigmented epithelium cell segmentation in confocal fluorescence microscopy images attests to the accuracy of the presented technique. PMID:22567602

Semi-automatic segmentation of brain tumors using population and individual information.

PubMed

Wu, Yao; Yang, Wei; Jiang, Jun; Li, Shuanqian; Feng, Qianjin; Chen, Wufan

2013-08-01

Efficient segmentation of tumors in medical images is of great practical importance in early diagnosis and radiation plan. This paper proposes a novel semi-automatic segmentation method based on population and individual statistical information to segment brain tumors in magnetic resonance (MR) images. First, high-dimensional image features are extracted. Neighborhood components analysis is proposed to learn two optimal distance metrics, which contain population and patient-specific information, respectively. The probability of each pixel belonging to the foreground (tumor) and the background is estimated by the k-nearest neighborhood classifier under the learned optimal distance metrics. A cost function for segmentation is constructed through these probabilities and is optimized using graph cuts. Finally, some morphological operations are performed to improve the achieved segmentation results. Our dataset consists of 137 brain MR images, including 68 for training and 69 for testing. The proposed method overcomes segmentation difficulties caused by the uneven gray level distribution of the tumors and even can get satisfactory results if the tumors have fuzzy edges. Experimental results demonstrate that the proposed method is robust to brain tumor segmentation.

Segmentation of the zebrafish axial skeleton relies on notochord sheath cells and not on the segmentation clock.

PubMed

Lleras Forero, Laura; Narayanan, Rachna; Huitema, Leonie Fa; VanBergen, Maaike; Apschner, Alexander; Peterson-Maduro, Josi; Logister, Ive; Valentin, Guillaume; Morelli, Luis G; Oates, Andrew C; Schulte-Merker, Stefan

2018-04-06

Segmentation of the axial skeleton in amniotes depends on the segmentation clock, which patterns the paraxial mesoderm and the sclerotome. While the segmentation clock clearly operates in teleosts, the role of the sclerotome in establishing the axial skeleton is unclear. We severely disrupt zebrafish paraxial segmentation, yet observe a largely normal segmentation process of the chordacentra. We demonstrate that axial entpd5+ notochord sheath cells are responsible for chordacentrum mineralization, and serve as a marker for axial segmentation. While autonomous within the notochord sheath, entpd5 expression and centrum formation show some plasticity and can respond to myotome pattern. These observations reveal for the first time the dynamics of notochord segmentation in a teleost, and are consistent with an autonomous patterning mechanism that is influenced, but not determined by adjacent paraxial mesoderm. This behavior is not consistent with a clock-type mechanism in the notochord. © 2018, Lleras Forero et al.

Layer stacking: A novel algorithm for individual forest tree segmentation from LiDAR point clouds

Treesearch

Elias Ayrey; Shawn Fraver; John A. Kershaw; Laura S. Kenefic; Daniel Hayes; Aaron R. Weiskittel; Brian E. Roth

2017-01-01

As light detection and ranging (LiDAR) technology advances, it has become common for datasets to be acquired at a point density high enough to capture structural information from individual trees. To process these data, an automatic method of isolating individual trees from a LiDAR point cloud is required. Traditional methods for segmenting trees attempt to isolate...

New robust algorithm for tracking cells in videos of Drosophila morphogenesis based on finding an ideal path in segmented spatio-temporal cellular structures.

PubMed

Bellaïche, Yohanns; Bosveld, Floris; Graner, François; Mikula, Karol; Remesíková, Mariana; Smísek, Michal

2011-01-01

In this paper, we present a novel algorithm for tracking cells in time lapse confocal microscopy movie of a Drosophila epithelial tissue during pupal morphogenesis. We consider a 2D + time video as a 3D static image, where frames are stacked atop each other, and using a spatio-temporal segmentation algorithm we obtain information about spatio-temporal 3D tubes representing evolutions of cells. The main idea for tracking is the usage of two distance functions--first one from the cells in the initial frame and second one from segmented boundaries. We track the cells backwards in time. The first distance function attracts the subsequently constructed cell trajectories to the cells in the initial frame and the second one forces them to be close to centerlines of the segmented tubular structures. This makes our tracking algorithm robust against noise and missing spatio-temporal boundaries. This approach can be generalized to a 3D + time video analysis, where spatio-temporal tubes are 4D objects.

Automatic segmentation of fluorescence lifetime microscopy images of cells using multiresolution community detection--a first study.

PubMed

Hu, D; Sarder, P; Ronhovde, P; Orthaus, S; Achilefu, S; Nussinov, Z

2014-01-01

Inspired by a multiresolution community detection based network segmentation method, we suggest an automatic method for segmenting fluorescence lifetime (FLT) imaging microscopy (FLIM) images of cells in a first pilot investigation on two selected images. The image processing problem is framed as identifying segments with respective average FLTs against the background in FLIM images. The proposed method segments a FLIM image for a given resolution of the network defined using image pixels as the nodes and similarity between the FLTs of the pixels as the edges. In the resulting segmentation, low network resolution leads to larger segments, and high network resolution leads to smaller segments. Furthermore, using the proposed method, the mean-square error in estimating the FLT segments in a FLIM image was found to consistently decrease with increasing resolution of the corresponding network. The multiresolution community detection method appeared to perform better than a popular spectral clustering-based method in performing FLIM image segmentation. At high resolution, the spectral segmentation method introduced noisy segments in its output, and it was unable to achieve a consistent decrease in mean-square error with increasing resolution. © 2013 The Authors Journal of Microscopy © 2013 Royal Microscopical Society.

Automatic Segmentation of Fluorescence Lifetime Microscopy Images of Cells Using Multi-Resolution Community Detection -A First Study

PubMed Central

Hu, Dandan; Sarder, Pinaki; Ronhovde, Peter; Orthaus, Sandra; Achilefu, Samuel; Nussinov, Zohar

2014-01-01

Inspired by a multi-resolution community detection (MCD) based network segmentation method, we suggest an automatic method for segmenting fluorescence lifetime (FLT) imaging microscopy (FLIM) images of cells in a first pilot investigation on two selected images. The image processing problem is framed as identifying segments with respective average FLTs against the background in FLIM images. The proposed method segments a FLIM image for a given resolution of the network defined using image pixels as the nodes and similarity between the FLTs of the pixels as the edges. In the resulting segmentation, low network resolution leads to larger segments, and high network resolution leads to smaller segments. Further, using the proposed method, the mean-square error (MSE) in estimating the FLT segments in a FLIM image was found to consistently decrease with increasing resolution of the corresponding network. The MCD method appeared to perform better than a popular spectral clustering based method in performing FLIM image segmentation. At high resolution, the spectral segmentation method introduced noisy segments in its output, and it was unable to achieve a consistent decrease in MSE with increasing resolution. PMID:24251410

Nephron segment-specific gene expression using AAV vectors.

PubMed

Asico, Laureano D; Cuevas, Santiago; Ma, Xiaobo; Jose, Pedro A; Armando, Ines; Konkalmatt, Prasad R

2018-02-26

AAV9 vector provides efficient gene transfer in all segments of the renal nephron, with minimum expression in non-renal cells, when administered retrogradely via the ureter. It is important to restrict the transgene expression to the desired cell type within the kidney, so that the physiological endpoints represent the function of the transgene expressed in that specific cell type within kidney. We hypothesized that segment-specific gene expression within the kidney can be accomplished using the highly efficient AAV9 vectors carrying the promoters of genes that are expressed exclusively in the desired segment of the nephron in combination with administration by retrograde infusion into the kidney via the ureter. We constructed AAV vectors carrying eGFP under the control of: kidney-specific cadherin (KSPC) gene promoter for expression in the entire nephron; Na + /glucose co-transporter (SGLT2) gene promoter for expression in the S1 and S2 segments of the proximal tubule; sodium, potassium, 2 chloride co-transporter (NKCC2) gene promoter for expression in the thick ascending limb of Henle's loop (TALH); E-cadherin (ECAD) gene promoter for expression in the collecting duct (CD); and cytomegalovirus (CMV) early promoter that provides expression in most of the mammalian cells, as control. We tested the specificity of the promoter constructs in vitro for cell type-specific expression in mouse kidney cells in primary culture, followed by retrograde infusion of the AAV vectors via the ureter in the mouse. Our data show that AAV9 vector, in combination with the segment-specific promoters administered by retrograde infusion via the ureter, provides renal nephron segment-specific gene expression. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

A novel measure and significance testing in data analysis of cell image segmentation.

PubMed

Wu, Jin Chu; Halter, Michael; Kacker, Raghu N; Elliott, John T; Plant, Anne L

2017-03-14

Cell image segmentation (CIS) is an essential part of quantitative imaging of biological cells. Designing a performance measure and conducting significance testing are critical for evaluating and comparing the CIS algorithms for image-based cell assays in cytometry. Many measures and methods have been proposed and implemented to evaluate segmentation methods. However, computing the standard errors (SE) of the measures and their correlation coefficient is not described, and thus the statistical significance of performance differences between CIS algorithms cannot be assessed. We propose the total error rate (TER), a novel performance measure for segmenting all cells in the supervised evaluation. The TER statistically aggregates all misclassification error rates (MER) by taking cell sizes as weights. The MERs are for segmenting each single cell in the population. The TER is fully supported by the pairwise comparisons of MERs using 106 manually segmented ground-truth cells with different sizes and seven CIS algorithms taken from ImageJ. Further, the SE and 95% confidence interval (CI) of TER are computed based on the SE of MER that is calculated using the bootstrap method. An algorithm for computing the correlation coefficient of TERs between two CIS algorithms is also provided. Hence, the 95% CI error bars can be used to classify CIS algorithms. The SEs of TERs and their correlation coefficient can be employed to conduct the hypothesis testing, while the CIs overlap, to determine the statistical significance of the performance differences between CIS algorithms. A novel measure TER of CIS is proposed. The TER's SEs and correlation coefficient are computed. Thereafter, CIS algorithms can be evaluated and compared statistically by conducting the significance testing.

CellShape: A user-friendly image analysis tool for quantitative visualization of bacterial cell factories inside.

PubMed

Goñi-Moreno, Ángel; Kim, Juhyun; de Lorenzo, Víctor

2017-02-01

Visualization of the intracellular constituents of individual bacteria while performing as live biocatalysts is in principle doable through more or less sophisticated fluorescence microscopy. Unfortunately, rigorous quantitation of the wealth of data embodied in the resulting images requires bioinformatic tools that are not widely extended within the community-let alone that they are often subject to licensing that impedes software reuse. In this context we have developed CellShape, a user-friendly platform for image analysis with subpixel precision and double-threshold segmentation system for quantification of fluorescent signals stemming from single-cells. CellShape is entirely coded in Python, a free, open-source programming language with widespread community support. For a developer, CellShape enhances extensibility (ease of software improvements) by acting as an interface to access and use existing Python modules; for an end-user, CellShape presents standalone executable files ready to open without installation. We have adopted this platform to analyse with an unprecedented detail the tridimensional distribution of the constituents of the gene expression flow (DNA, RNA polymerase, mRNA and ribosomal proteins) in individual cells of the industrial platform strain Pseudomonas putida KT2440. While the CellShape first release version (v0.8) is readily operational, users and/or developers are enabled to expand the platform further. Copyright © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Regional differences in BMP-dependence of dorsoventral patterning in the leech Helobdella.

PubMed

Kuo, Dian-Han; Shankland, Marty; Weisblat, David A

2012-08-01

In the leech Helobdella, the ectoderm exhibits a high degree of morphological homonomy between body segments, but pattern elements in lateral ectoderm arise via distinct cell lineages in the segments of the rostral and midbody regions. In each of the four rostral segments, a complete set of ventrolateral (O fate) and dorsolateral (P fate) ectodermal pattern elements arises from a single founder cell, op. In the 28 midbody and caudal segments, however, there are two initially indeterminate o/p founder cells; the more dorsal of these is induced to adopt the P fate by BMP5-8 emanating from the dorsalmost ectoderm, while the more ventral cell assumes the O fate. Previous work has suggested that the dorsoventral patterning of O and P fates differs in the rostral region, but the role of BMP signaling in those segments has not been investigated. We show here that suppression of dorsal BMP5-8 signaling (which effects a P-to-O fate change in the midbody) has no effect on the patterning of O and P fates in the rostral region. Furthermore, ectopic expression of BMP5-8 in the ventral ectoderm (which induces an O-to-P fate change in the midbody) has no effect in the rostral region. Finally, expression of a dominant-negative BMP receptor (which induces a P-to-O fate change in the midbody) fails to affect O/P patterning in the rostral region. Thus, the rostral segments appear to use some mechanism other than BMP signaling to pattern O and P cell fates along the dorsoventral axis. From a mechanistic standpoint, the OP lineage of the rostral segments and the O-P equivalence group of the midbody and caudal segments constitute distinct developmental modules that rely to differing degrees on positional cues from surrounding ectoderm in order to specify homonomous cell fates. Copyright © 2012 Elsevier Inc. All rights reserved.

A probabilistic approach to joint cell tracking and segmentation in high-throughput microscopy videos.

PubMed

Arbelle, Assaf; Reyes, Jose; Chen, Jia-Yun; Lahav, Galit; Riklin Raviv, Tammy

2018-04-22

We present a novel computational framework for the analysis of high-throughput microscopy videos of living cells. The proposed framework is generally useful and can be applied to different datasets acquired in a variety of laboratory settings. This is accomplished by tying together two fundamental aspects of cell lineage construction, namely cell segmentation and tracking, via a Bayesian inference of dynamic models. In contrast to most existing approaches, which aim to be general, no assumption of cell shape is made. Spatial, temporal, and cross-sectional variation of the analysed data are accommodated by two key contributions. First, time series analysis is exploited to estimate the temporal cell shape uncertainty in addition to cell trajectory. Second, a fast marching (FM) algorithm is used to integrate the inferred cell properties with the observed image measurements in order to obtain image likelihood for cell segmentation, and association. The proposed approach has been tested on eight different time-lapse microscopy data sets, some of which are high-throughput, demonstrating promising results for the detection, segmentation and association of planar cells. Our results surpass the state of the art for the Fluo-C2DL-MSC data set of the Cell Tracking Challenge (Maška et al., 2014). Copyright © 2018 Elsevier B.V. All rights reserved.

Segmentation of Image Data from Complex Organotypic 3D Models of Cancer Tissues with Markov Random Fields

PubMed Central

Robinson, Sean; Guyon, Laurent; Nevalainen, Jaakko; Toriseva, Mervi

2015-01-01

Organotypic, three dimensional (3D) cell culture models of epithelial tumour types such as prostate cancer recapitulate key aspects of the architecture and histology of solid cancers. Morphometric analysis of multicellular 3D organoids is particularly important when additional components such as the extracellular matrix and tumour microenvironment are included in the model. The complexity of such models has so far limited their successful implementation. There is a great need for automatic, accurate and robust image segmentation tools to facilitate the analysis of such biologically relevant 3D cell culture models. We present a segmentation method based on Markov random fields (MRFs) and illustrate our method using 3D stack image data from an organotypic 3D model of prostate cancer cells co-cultured with cancer-associated fibroblasts (CAFs). The 3D segmentation output suggests that these cell types are in physical contact with each other within the model, which has important implications for tumour biology. Segmentation performance is quantified using ground truth labels and we show how each step of our method increases segmentation accuracy. We provide the ground truth labels along with the image data and code. Using independent image data we show that our segmentation method is also more generally applicable to other types of cellular microscopy and not only limited to fluorescence microscopy. PMID:26630674

White blood cell counting analysis of blood smear images using various segmentation strategies

NASA Astrophysics Data System (ADS)

Safuan, Syadia Nabilah Mohd; Tomari, Razali; Zakaria, Wan Nurshazwani Wan; Othman, Nurmiza

2017-09-01

In white blood cell (WBC) diagnosis, the most crucial measurement parameter is the WBC counting. Such information is widely used to evaluate the effectiveness of cancer therapy and to diagnose several hidden infection within human body. The current practice of manual WBC counting is laborious and a very subjective assessment which leads to the invention of computer aided system (CAS) with rigorous image processing solution. In the CAS counting work, segmentation is the crucial step to ensure the accuracy of the counted cell. The optimal segmentation strategy that can work under various blood smeared image acquisition conditions is remain a great challenge. In this paper, a comparison between different segmentation methods based on color space analysis to get the best counting outcome is elaborated. Initially, color space correction is applied to the original blood smeared image to standardize the image color intensity level. Next, white blood cell segmentation is performed by using combination of several color analysis subtraction which are RGB, CMYK and HSV, and Otsu thresholding. Noises and unwanted regions that present after the segmentation process is eliminated by applying a combination of morphological and Connected Component Labelling (CCL) filter. Eventually, Circle Hough Transform (CHT) method is applied to the segmented image to estimate the number of WBC including the one under the clump region. From the experiment, it is found that G-S yields the best performance.

Segmentation of Image Data from Complex Organotypic 3D Models of Cancer Tissues with Markov Random Fields.

PubMed

Robinson, Sean; Guyon, Laurent; Nevalainen, Jaakko; Toriseva, Mervi; Åkerfelt, Malin; Nees, Matthias

2015-01-01

Organotypic, three dimensional (3D) cell culture models of epithelial tumour types such as prostate cancer recapitulate key aspects of the architecture and histology of solid cancers. Morphometric analysis of multicellular 3D organoids is particularly important when additional components such as the extracellular matrix and tumour microenvironment are included in the model. The complexity of such models has so far limited their successful implementation. There is a great need for automatic, accurate and robust image segmentation tools to facilitate the analysis of such biologically relevant 3D cell culture models. We present a segmentation method based on Markov random fields (MRFs) and illustrate our method using 3D stack image data from an organotypic 3D model of prostate cancer cells co-cultured with cancer-associated fibroblasts (CAFs). The 3D segmentation output suggests that these cell types are in physical contact with each other within the model, which has important implications for tumour biology. Segmentation performance is quantified using ground truth labels and we show how each step of our method increases segmentation accuracy. We provide the ground truth labels along with the image data and code. Using independent image data we show that our segmentation method is also more generally applicable to other types of cellular microscopy and not only limited to fluorescence microscopy.

Automated identification of abnormal metaphase chromosome cells for the detection of chronic myeloid leukemia using microscopic images

NASA Astrophysics Data System (ADS)

Wang, Xingwei; Zheng, Bin; Li, Shibo; Mulvihill, John J.; Chen, Xiaodong; Liu, Hong

2010-07-01

Karyotyping is an important process to classify chromosomes into standard classes and the results are routinely used by the clinicians to diagnose cancers and genetic diseases. However, visual karyotyping using microscopic images is time-consuming and tedious, which reduces the diagnostic efficiency and accuracy. Although many efforts have been made to develop computerized schemes for automated karyotyping, no schemes can get be performed without substantial human intervention. Instead of developing a method to classify all chromosome classes, we develop an automatic scheme to detect abnormal metaphase cells by identifying a specific class of chromosomes (class 22) and prescreen for suspicious chronic myeloid leukemia (CML). The scheme includes three steps: (1) iteratively segment randomly distributed individual chromosomes, (2) process segmented chromosomes and compute image features to identify the candidates, and (3) apply an adaptive matching template to identify chromosomes of class 22. An image data set of 451 metaphase cells extracted from bone marrow specimens of 30 positive and 30 negative cases for CML is selected to test the scheme's performance. The overall case-based classification accuracy is 93.3% (100% sensitivity and 86.7% specificity). The results demonstrate the feasibility of applying an automated scheme to detect or prescreen the suspicious cancer cases.

Threshold-based segmentation of fluorescent and chromogenic images of microglia, astrocytes and oligodendrocytes in FIJI.

PubMed

Healy, Sinead; McMahon, Jill; Owens, Peter; Dockery, Peter; FitzGerald, Una

2018-02-01

Image segmentation is often imperfect, particularly in complex image sets such z-stack micrographs of slice cultures and there is a need for sufficient details of parameters used in quantitative image analysis to allow independent repeatability and appraisal. For the first time, we have critically evaluated, quantified and validated the performance of different segmentation methodologies using z-stack images of ex vivo glial cells. The BioVoxxel toolbox plugin, available in FIJI, was used to measure the relative quality, accuracy, specificity and sensitivity of 16 global and 9 local threshold automatic thresholding algorithms. Automatic thresholding yields improved binary representation of glial cells compared with the conventional user-chosen single threshold approach for confocal z-stacks acquired from ex vivo slice cultures. The performance of threshold algorithms varies considerably in quality, specificity, accuracy and sensitivity with entropy-based thresholds scoring highest for fluorescent staining. We have used the BioVoxxel toolbox to correctly and consistently select the best automated threshold algorithm to segment z-projected images of ex vivo glial cells for downstream digital image analysis and to define segmentation quality. The automated OLIG2 cell count was validated using stereology. As image segmentation and feature extraction can quite critically affect the performance of successive steps in the image analysis workflow, it is becoming increasingly necessary to consider the quality of digital segmenting methodologies. Here, we have applied, validated and extended an existing performance-check methodology in the BioVoxxel toolbox to z-projected images of ex vivo glia cells. Copyright © 2017 Elsevier B.V. All rights reserved.

Morphology of the kidney of adult bowfin, Amia calva, with emphasis on "renal chloride cells" in the tubule.

PubMed

Youson, J H; Butler, D G

1988-05-01

The nephron of adult bowfin, Amia calva, was described using light and electron microscopic techniques. The kidney of the bowfin possesses an abundant supply of renal corpuscles with each consisting of a glomerulus and a Bowman's capsule of visceral (podocyte) and parietal layers. No juxtaglomerular apparatus is present. The epithelium of the tubule is continuous with the parietal epithelium and is divisible in descending order into neck, first proximal, second proximal, first distal, second distal, and collecting segments. The tubules drain into a complex system of collecting ducts that ultimately unite with the main excretory duct, the archinephric duct. Mucous cells are the dominant cell throughout the entire ductular system. Nephrostomes are dispersed along the kidney capsule. The neck segment has a ciliated epithelium, and while both proximal segments possess a prominent brush border, the fine structure of the first implies involvement in protein absorption and the second in the transport and reabsorption of solutes. The cells of the first distal segment are characterized by deep infolding of the plasma membrane and a rich supply of mitochondria suggesting the presence of a mechanism for ion transport. The second distal segment is composed of cells resembling the chloride cells of fishes and these cells are present in progressively decreasing numbers in the collecting segment and duct system so that only a few are present in the epithelium of the archinephric duct. The "renal chloride cells" possess an abundant network of smooth tubules and numerous mitochondria with a rich supply of cristae. Glycogen is also a conspicuous component of these cells. The presence of "renal chloride cells" in this freshwater holostean, in other relatively primitive freshwater teleosts, and in larval and adult lampreys is discussed with reference to both phylogeny and the need for a special mechanism for renal ion conservation through absorption.

Extraction and analysis of neuron firing signals from deep cortical video microscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kerekes, Ryan A; Blundon, Jay

We introduce a method for extracting and analyzing neuronal activity time signals from video of the cortex of a live animal. The signals correspond to the firing activity of individual cortical neurons. Activity signals are based on the changing fluorescence of calcium indicators in the cells over time. We propose a cell segmentation method that relies on a user-specified center point, from which the signal extraction method proceeds. A stabilization approach is used to reduce tissue motion in the video. The extracted signal is then processed to flatten the baseline and detect action potentials. We show results from applying themore » method to a cortical video of a live mouse.« less

Influenza A induced cellular signal transduction pathways

PubMed Central

Michael, Paul; Brabant, Danielle; Bleiblo, Farag; Ramana, Chilakamarti V.; Rutherford, Michael; Khurana, Sandhya; Tai, T.C.; Kumar, Anand

2013-01-01

Influenza A is a negative sense single stranded RNA virus that belongs to the Orthomyxoviridae Family. This enveloped virus contains 8 segments of viral RNA which encodes 11 viral proteins. Influenza A infects humans and is the causative agent of the flu. Annually it infects approximately 5% to 15% of the population world wide and results in an estimated 250,000 to 500,000 deaths a year. The nature of influenza A replication results in a high mutation rate which results in the need for seasonal vaccinations. In addition the zoonotic nature of the influenza virus allows for recombination of viral segments from different strains creating new variants that have not been encountered before. This type of mutation is the method by which pandemic strains of the flu arises. Infection with influenza results in a respiratory illness that for most individuals is self limiting. However in susceptible populations which include individuals with pre-existing pulmonary or cardiac conditions, the very young and the elderly fatal complications may arise. The most serious of these is the development of viral pneumonia which may be accompanied by secondary bacterial infections. Progression of pneumonia leads to the development of acute respiratory distress syndrome (ARDS), acute lung injury (ALI) and potentially respiratory failure. This progression is a combined effect of the host immune system response to influenza infection and the viral infection itself. This review will focus on molecular aspects of viral replication in alveolar cells and their response to infection. The response of select innate immune cells and their contribution to viral clearance and lung epithelial damage will also be discussed. Molecular aspects of antiviral response in the cells in particular the protein kinase RNA dependent response, and the oligoadenylate synthetase RNAse L system in relation to influenza infection. PMID:23977434

Automated classification of bone marrow cells in microscopic images for diagnosis of leukemia: a comparison of two classification schemes with respect to the segmentation quality

NASA Astrophysics Data System (ADS)

Krappe, Sebastian; Benz, Michaela; Wittenberg, Thomas; Haferlach, Torsten; Münzenmayer, Christian

2015-03-01

The morphological analysis of bone marrow smears is fundamental for the diagnosis of leukemia. Currently, the counting and classification of the different types of bone marrow cells is done manually with the use of bright field microscope. This is a time consuming, partly subjective and tedious process. Furthermore, repeated examinations of a slide yield intra- and inter-observer variances. For this reason an automation of morphological bone marrow analysis is pursued. This analysis comprises several steps: image acquisition and smear detection, cell localization and segmentation, feature extraction and cell classification. The automated classification of bone marrow cells is depending on the automated cell segmentation and the choice of adequate features extracted from different parts of the cell. In this work we focus on the evaluation of support vector machines (SVMs) and random forests (RFs) for the differentiation of bone marrow cells in 16 different classes, including immature and abnormal cell classes. Data sets of different segmentation quality are used to test the two approaches. Automated solutions for the morphological analysis for bone marrow smears could use such a classifier to pre-classify bone marrow cells and thereby shortening the examination duration.

Lateral Motion and Bending of Microtubules Studied with a New Single-Filament Tracking Routine in Living Cells

PubMed Central

Pallavicini, Carla; Levi, Valeria; Wetzler, Diana E.; Angiolini, Juan F.; Benseñor, Lorena; Despósito, Marcelo A.; Bruno, Luciana

2014-01-01

The cytoskeleton is involved in numerous cellular processes such as migration, division, and contraction and provides the tracks for transport driven by molecular motors. Therefore, it is very important to quantify the mechanical behavior of the cytoskeletal filaments to get a better insight into cell mechanics and organization. It has been demonstrated that relevant mechanical properties of microtubules can be extracted from the analysis of their motion and shape fluctuations. However, tracking individual filaments in living cells is extremely complex due, for example, to the high and heterogeneous background. We introduce a believed new tracking algorithm that allows recovering the coordinates of fluorescent microtubules with ∼9 nm precision in in vitro conditions. To illustrate potential applications of this algorithm, we studied the curvature distributions of fluorescent microtubules in living cells. By performing a Fourier analysis of the microtubule shapes, we found that the curvatures followed a thermal-like distribution as previously reported with an effective persistence length of ∼20 μm, a value significantly smaller than that measured in vitro. We also verified that the microtubule-associated protein XTP or the depolymerization of the actin network do not affect this value; however, the disruption of intermediate filaments decreased the persistence length. Also, we recovered trajectories of microtubule segments in actin or intermediate filament-depleted cells, and observed a significant increase of their motion with respect to untreated cells showing that these filaments contribute to the overall organization of the microtubule network. Moreover, the analysis of trajectories of microtubule segments in untreated cells showed that these filaments presented a slower but more directional motion in the cortex with respect to the perinuclear region, and suggests that the tracking routine would allow mapping the microtubule dynamical organization in cells. PMID:24940780

Transcriptomic insights into citrus segment membrane's cell wall components relating to fruit sensory texture.

PubMed

Wang, Xun; Lin, Lijin; Tang, Yi; Xia, Hui; Zhang, Xiancong; Yue, Maolan; Qiu, Xia; Xu, Ke; Wang, Zhihui

2018-04-23

During fresh fruit consumption, sensory texture is one factor that affects the organoleptic qualities. Chemical components of plant cell walls, including pectin, cellulose, hemicellulose and lignin, play central roles in determining the textural qualities. To explore the genes and regulatory pathways involved in fresh citrus' perceived sensory texture, we performed mRNA-seq analyses of the segment membranes of two citrus cultivars, Shiranui and Kiyomi, with different organoleptic textures. Segment membranes were sampled at two developmental stages of citrus fruit, the beginning and end of the expansion period. More than 3000 differentially expressed genes were identified. The gene ontology analysis revealed that more categories were significantly enriched in 'Shiranui' than in 'Kiyomi' at both developmental stages. In total, 108 significantly enriched pathways were obtained, with most belonging to metabolism. A detailed transcriptomic analysis revealed potential critical genes involved in the metabolism of cell wall structures, for example, GAUT4 in pectin synthesis, CESA1, 3 and 6, and SUS4 in cellulose synthesis, CSLC5, XXT1 and XXT2 in hemicellulose synthesis, and CSE in lignin synthesis. Low levels, or no expression, of genes involved in cellulose and hemicellulose, such as CESA4, CESA7, CESA8, IRX9 and IRX14, confirmed that secondary cell walls were negligible or absent in citrus segment membranes. A chemical component analysis of the segment membranes from mature fruit revealed that the pectin, cellulose and lignin contents, and the segment membrane's weight (% of segment) were greater in 'Kiyomi'. Organoleptic quality of citrus is easily overlooked. It is mainly determined by sensory texture perceived in citrus segment membrane properties. We performed mRNA-seq analyses of citrus segment membranes to explore the genes and regulatory pathways involved in fresh citrus' perceived sensory texture. Transcriptomic data showed high repeatability between two independent biological replicates. The expression levels of genes involved in cell wall structure metabolism, including pectin, cellulose, hemicellulose and lignin, were investigated. Meanwhile, chemical component contents of the segment membranes from mature fruit were analyzed. This study provided detailed transcriptional regulatory profiles of different organoleptic citrus qualities and integrated insights into the mechanisms affecting citrus' sensory texture.

Evolutionary Origin of Body Axis Segmentation in Annelids and Arthropods

NASA Technical Reports Server (NTRS)

Shankland, S. Martin

2003-01-01

During the period of this report, we have made a number of important discoveries. To date this work has led to 4 peer-reviewed publications in primary research journals plus 1 minireview and 1 chapter in the proceedings of a meeting. Publications resulting from this grant support are enumerated at the end of the report. Two additional, on-going studies also described. 1. Using laser cell ablation, we have obtained evidence that an annelid - the leech Helobdella robusta - patterns the anteroposterior (AP) polarity of its nascent segment primordia independent of cell interactions oriented along the AP axis. 2. We cloned a Helobdella homologue (hro-hh) of the Drosophila segment polarity gene hedgehog, and used in situ hybridization and northern blots to characterize its expression in the embryo. 3. We have used laser cell ablations to examine the possible role of cell interactions during the developmental patterning of the 4 rostralmost "head" segments of the leech Helobdella robusta.

Image analysis applied to luminescence microscopy

NASA Astrophysics Data System (ADS)

Maire, Eric; Lelievre-Berna, Eddy; Fafeur, Veronique; Vandenbunder, Bernard

1998-04-01

We have developed a novel approach to study luminescent light emission during migration of living cells by low-light imaging techniques. The equipment consists in an anti-vibration table with a hole for a direct output under the frame of an inverted microscope. The image is directly captured by an ultra low- light level photon-counting camera equipped with an image intensifier coupled by an optical fiber to a CCD sensor. This installation is dedicated to measure in a dynamic manner the effect of SF/HGF (Scatter Factor/Hepatocyte Growth Factor) both on activation of gene promoter elements and on cell motility. Epithelial cells were stably transfected with promoter elements containing Ets transcription factor-binding sites driving a luciferase reporter gene. Luminescent light emitted by individual cells was measured by image analysis. Images of luminescent spots were acquired with a high aperture objective and time exposure of 10 - 30 min in photon-counting mode. The sensitivity of the camera was adjusted to a high value which required the use of a segmentation algorithm dedicated to eliminate the background noise. Hence, image segmentation and treatments by mathematical morphology were particularly indicated in these experimental conditions. In order to estimate the orientation of cells during their migration, we used a dedicated skeleton algorithm applied to the oblong spots of variable intensities emitted by the cells. Kinetic changes of luminescent sources, distance and speed of migration were recorded and then correlated with cellular morphological changes for each spot. Our results highlight the usefulness of the mathematical morphology to quantify kinetic changes in luminescence microscopy.

3D segmentations of neuronal nuclei from confocal microscope image stacks

PubMed Central

LaTorre, Antonio; Alonso-Nanclares, Lidia; Muelas, Santiago; Peña, José-María; DeFelipe, Javier

2013-01-01

In this paper, we present an algorithm to create 3D segmentations of neuronal cells from stacks of previously segmented 2D images. The idea behind this proposal is to provide a general method to reconstruct 3D structures from 2D stacks, regardless of how these 2D stacks have been obtained. The algorithm not only reuses the information obtained in the 2D segmentation, but also attempts to correct some typical mistakes made by the 2D segmentation algorithms (for example, under segmentation of tightly-coupled clusters of cells). We have tested our algorithm in a real scenario—the segmentation of the neuronal nuclei in different layers of the rat cerebral cortex. Several representative images from different layers of the cerebral cortex have been considered and several 2D segmentation algorithms have been compared. Furthermore, the algorithm has also been compared with the traditional 3D Watershed algorithm and the results obtained here show better performance in terms of correctly identified neuronal nuclei. PMID:24409123

3D segmentations of neuronal nuclei from confocal microscope image stacks.

PubMed

Latorre, Antonio; Alonso-Nanclares, Lidia; Muelas, Santiago; Peña, José-María; Defelipe, Javier

2013-01-01

In this paper, we present an algorithm to create 3D segmentations of neuronal cells from stacks of previously segmented 2D images. The idea behind this proposal is to provide a general method to reconstruct 3D structures from 2D stacks, regardless of how these 2D stacks have been obtained. The algorithm not only reuses the information obtained in the 2D segmentation, but also attempts to correct some typical mistakes made by the 2D segmentation algorithms (for example, under segmentation of tightly-coupled clusters of cells). We have tested our algorithm in a real scenario-the segmentation of the neuronal nuclei in different layers of the rat cerebral cortex. Several representative images from different layers of the cerebral cortex have been considered and several 2D segmentation algorithms have been compared. Furthermore, the algorithm has also been compared with the traditional 3D Watershed algorithm and the results obtained here show better performance in terms of correctly identified neuronal nuclei.

Using multimodal information for the segmentation of fluorescent micrographs with application to virology and microbiology.

PubMed

Held, Christian; Wenzel, Jens; Webel, Rike; Marschall, Manfred; Lang, Roland; Palmisano, Ralf; Wittenberg, Thomas

2011-01-01

In order to improve reproducibility and objectivity of fluorescence microscopy based experiments and to enable the evaluation of large datasets, flexible segmentation methods are required which are able to adapt to different stainings and cell types. This adaption is usually achieved by the manual adjustment of the segmentation methods parameters, which is time consuming and challenging for biologists with no knowledge on image processing. To avoid this, parameters of the presented methods automatically adapt to user generated ground truth to determine the best method and the optimal parameter setup. These settings can then be used for segmentation of the remaining images. As robust segmentation methods form the core of such a system, the currently used watershed transform based segmentation routine is replaced by a fast marching level set based segmentation routine which incorporates knowledge on the cell nuclei. Our evaluations reveal that incorporation of multimodal information improves segmentation quality for the presented fluorescent datasets.

Hepatic Arterial Configuration in Relation to the Segmental Anatomy of the Liver; Observations on MDCT and DSA Relevant to Radioembolization Treatment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hoven, Andor F. van den, E-mail: a.f.vandenhoven@umcutrecht.nl; Leeuwen, Maarten S. van, E-mail: m.s.vanleeuwen@umcutrecht.nl; Lam, Marnix G. E. H., E-mail: m.lam@umcutrecht.nl

PurposeCurrent anatomical classifications do not include all variants relevant for radioembolization (RE). The purpose of this study was to assess the individual hepatic arterial configuration and segmental vascularization pattern and to develop an individualized RE treatment strategy based on an extended classification.MethodsThe hepatic vascular anatomy was assessed on MDCT and DSA in patients who received a workup for RE between February 2009 and November 2012. Reconstructed MDCT studies were assessed to determine the hepatic arterial configuration (origin of every hepatic arterial branch, branching pattern and anatomical course) and the hepatic segmental vascularization territory of all branches. Aberrant hepatic arteries weremore » defined as hepatic arterial branches that did not originate from the celiac axis/CHA/PHA. Early branching patterns were defined as hepatic arterial branches originating from the celiac axis/CHA.ResultsThe hepatic arterial configuration and segmental vascularization pattern could be assessed in 110 of 133 patients. In 59 patients (54 %), no aberrant hepatic arteries or early branching was observed. Fourteen patients without aberrant hepatic arteries (13 %) had an early branching pattern. In the 37 patients (34 %) with aberrant hepatic arteries, five also had an early branching pattern. Sixteen different hepatic arterial segmental vascularization patterns were identified and described, differing by the presence of aberrant hepatic arteries, their respective vascular territory, and origin of the artery vascularizing segment four.ConclusionsThe hepatic arterial configuration and segmental vascularization pattern show marked individual variability beyond well-known classifications of anatomical variants. We developed an individualized RE treatment strategy based on an extended anatomical classification.« less

Automatic and hierarchical segmentation of the human skeleton in CT images.

PubMed

Fu, Yabo; Liu, Shi; Li, Harold; Yang, Deshan

2017-04-07

Accurate segmentation of each bone of the human skeleton is useful in many medical disciplines. The results of bone segmentation could facilitate bone disease diagnosis and post-treatment assessment, and support planning and image guidance for many treatment modalities including surgery and radiation therapy. As a medium level medical image processing task, accurate bone segmentation can facilitate automatic internal organ segmentation by providing stable structural reference for inter- or intra-patient registration and internal organ localization. Even though bones in CT images can be visually observed with minimal difficulty due to the high image contrast between the bony structures and surrounding soft tissues, automatic and precise segmentation of individual bones is still challenging due to the many limitations of the CT images. The common limitations include low signal-to-noise ratio, insufficient spatial resolution, and indistinguishable image intensity between spongy bones and soft tissues. In this study, a novel and automatic method is proposed to segment all the major individual bones of the human skeleton above the upper legs in CT images based on an articulated skeleton atlas. The reported method is capable of automatically segmenting 62 major bones, including 24 vertebrae and 24 ribs, by traversing a hierarchical anatomical tree and by using both rigid and deformable image registration. The degrees of freedom of femora and humeri are modeled to support patients in different body and limb postures. The segmentation results are evaluated using the Dice coefficient and point-to-surface error (PSE) against manual segmentation results as the ground-truth. The results suggest that the reported method can automatically segment and label the human skeleton into detailed individual bones with high accuracy. The overall average Dice coefficient is 0.90. The average PSEs are 0.41 mm for the mandible, 0.62 mm for cervical vertebrae, 0.92 mm for thoracic vertebrae, and 1.45 mm for pelvis bones.

Automatic and hierarchical segmentation of the human skeleton in CT images

NASA Astrophysics Data System (ADS)

Fu, Yabo; Liu, Shi; Li, H. Harold; Yang, Deshan

2017-04-01

Accurate segmentation of each bone of the human skeleton is useful in many medical disciplines. The results of bone segmentation could facilitate bone disease diagnosis and post-treatment assessment, and support planning and image guidance for many treatment modalities including surgery and radiation therapy. As a medium level medical image processing task, accurate bone segmentation can facilitate automatic internal organ segmentation by providing stable structural reference for inter- or intra-patient registration and internal organ localization. Even though bones in CT images can be visually observed with minimal difficulty due to the high image contrast between the bony structures and surrounding soft tissues, automatic and precise segmentation of individual bones is still challenging due to the many limitations of the CT images. The common limitations include low signal-to-noise ratio, insufficient spatial resolution, and indistinguishable image intensity between spongy bones and soft tissues. In this study, a novel and automatic method is proposed to segment all the major individual bones of the human skeleton above the upper legs in CT images based on an articulated skeleton atlas. The reported method is capable of automatically segmenting 62 major bones, including 24 vertebrae and 24 ribs, by traversing a hierarchical anatomical tree and by using both rigid and deformable image registration. The degrees of freedom of femora and humeri are modeled to support patients in different body and limb postures. The segmentation results are evaluated using the Dice coefficient and point-to-surface error (PSE) against manual segmentation results as the ground-truth. The results suggest that the reported method can automatically segment and label the human skeleton into detailed individual bones with high accuracy. The overall average Dice coefficient is 0.90. The average PSEs are 0.41 mm for the mandible, 0.62 mm for cervical vertebrae, 0.92 mm for thoracic vertebrae, and 1.45 mm for pelvis bones.

Multi-atlas segmentation of subcortical brain structures via the AutoSeg software pipeline

PubMed Central

Wang, Jiahui; Vachet, Clement; Rumple, Ashley; Gouttard, Sylvain; Ouziel, Clémentine; Perrot, Emilie; Du, Guangwei; Huang, Xuemei; Gerig, Guido; Styner, Martin

2014-01-01

Automated segmenting and labeling of individual brain anatomical regions, in MRI are challenging, due to the issue of individual structural variability. Although atlas-based segmentation has shown its potential for both tissue and structure segmentation, due to the inherent natural variability as well as disease-related changes in MR appearance, a single atlas image is often inappropriate to represent the full population of datasets processed in a given neuroimaging study. As an alternative for the case of single atlas segmentation, the use of multiple atlases alongside label fusion techniques has been introduced using a set of individual “atlases” that encompasses the expected variability in the studied population. In our study, we proposed a multi-atlas segmentation scheme with a novel graph-based atlas selection technique. We first paired and co-registered all atlases and the subject MR scans. A directed graph with edge weights based on intensity and shape similarity between all MR scans is then computed. The set of neighboring templates is selected via clustering of the graph. Finally, weighted majority voting is employed to create the final segmentation over the selected atlases. This multi-atlas segmentation scheme is used to extend a single-atlas-based segmentation toolkit entitled AutoSeg, which is an open-source, extensible C++ based software pipeline employing BatchMake for its pipeline scripting, developed at the Neuro Image Research and Analysis Laboratories of the University of North Carolina at Chapel Hill. AutoSeg performs N4 intensity inhomogeneity correction, rigid registration to a common template space, automated brain tissue classification based skull-stripping, and the multi-atlas segmentation. The multi-atlas-based AutoSeg has been evaluated on subcortical structure segmentation with a testing dataset of 20 adult brain MRI scans and 15 atlas MRI scans. The AutoSeg achieved mean Dice coefficients of 81.73% for the subcortical structures. PMID:24567717

Segmentation and classification of cell cycle phases in fluorescence imaging.

PubMed

Ersoy, Ilker; Bunyak, Filiz; Chagin, Vadim; Cardoso, M Christina; Palaniappan, Kannappan

2009-01-01

Current chemical biology methods for studying spatiotemporal correlation between biochemical networks and cell cycle phase progression in live-cells typically use fluorescence-based imaging of fusion proteins. Stable cell lines expressing fluorescently tagged protein GFP-PCNA produce rich, dynamically varying sub-cellular foci patterns characterizing the cell cycle phases, including the progress during the S-phase. Variable fluorescence patterns, drastic changes in SNR, shape and position changes and abundance of touching cells require sophisticated algorithms for reliable automatic segmentation and cell cycle classification. We extend the recently proposed graph partitioning active contours (GPAC) for fluorescence-based nucleus segmentation using regional density functions and dramatically improve its efficiency, making it scalable for high content microscopy imaging. We utilize surface shape properties of GFP-PCNA intensity field to obtain descriptors of foci patterns and perform automated cell cycle phase classification, and give quantitative performance by comparing our results to manually labeled data.

[The effect of 18beta-glycyrrhetinic acid on gap junction among cerebral arteriolar smooth muscle cells in Wistar rat and spontaneously hypertensive rat].

PubMed

Chen, Xin-Yan; Si, Jun-Qiang; Li, Li; Zhao, Lei; Wei, Li-Li; Jiang, Xue-Wei; Ma, Ke-Tao

2013-05-01

This study compared Wistar rat with spontaneously hypertensive rat (SHR) on the electrophysiology and coupling force of the smooth muscle cells in the cerebral arteriolar segments and observe the influence of 18beta-glycyrrhetinic acid(18beta-GA) on the gap junctions between the arterial smooth muscle cells. The outer layer's connective tissue of the cerebral arteriolar segments was removed. Whole-cell patch clamp recordings were used to observe the 18beta-GA's impaction on the arteriolar segment membrane's input capacitance (C(input)), input conductance (G(input)) and input resistance (R(input)) of the smooth muscle cells. (1) The C(input) and G(input) of the SHR arteriolar segment smooth muscle cells was much higher than the Wistar rats, there was significant difference (P < 0.05). (2) 18beta-GA concentration-dependently reduced C(input) and G(input) (or increase R(input)) on smooth muscle cells in arteriolar segment. IC50 of 18beta-GA suppression's G(input) of the Wistar rat and SHR were 1.7 and 2.0 micromol/L respectively, there was not significant difference (P > 0.05). After application of 18beta-GA concentration > or = 100 micrmol/L, the C(input), G(input) and R(input) of the single smooth muscle cells was very close. Gap junctional coupling is enhanced in the SHR cerebral arterial smooth muscle cells. 18beta-GA concentration-dependent inhibits Wistar rat's and SHR cerebral arteriolar gap junctions between arterial smooth muscle cells. The inhibitory potency is similar between the two different rats. When 18beta-GA concentration is > or = 100 micromol/L, it can completely block gap junctions between arteriolar smooth muscle cells.

Effects of ionizing radiation on the light sensing elements of the retina. [Structural and physiological effects of carbon, helium, and neon ions on rods and cones of salamanders and mice

DOE Office of Scientific and Technical Information (OSTI.GOV)

Malachowski, M.J.

1978-07-01

This investigation was undertaken to quantitate possible morphological and physiological effects of particles of high linear energy transfer on the retina, in comparison with x-ray effects. The particles used were accelerated atomic nuclei of helium, carbon, and neon at kinetic energies of several hundred MeV/nucleon. For morphological studies, scanning and transmission electron microscopy and light microscopy were used. Physiological studies consisted of autoradiographic data of the rate of incorporation of labeled protein in the structures (opsin) of the outer segment of visual cells. Structural changes were found in the nuclei, as well as the inner and outer segments of visualmore » cells, rods and cones. At a low dose of 10 rad, x rays and helium had no statistically significant morphological effects, but carbon and neon beams did cause significant degeneration of individual cells, pointing to the existence of a linear dose--effect relationship. At high doses of several hundred rads, a Pathologic Index determined the relative biological effectiveness of neon against alpha particles to have a value of greater than 6. The severity of effects per particle increased with atomic number. Labeling studies demonstrated a decreased rate of incorporation of labeled proteins in the structural organization of the outer segments of visual rods. The rate of self-renewal of visual rod discs was punctuated by irradiation and the structures themselves were depleted of amino acids. A model of rod discs (metabolic and catabolic) was postulated for correlated early and late effects to high and low doses.« less

Unsupervised sputum color image segmentation for lung cancer diagnosis based on a Hopfield neural network

NASA Astrophysics Data System (ADS)

Sammouda, Rachid; Niki, Noboru; Nishitani, Hiroshi; Nakamura, S.; Mori, Shinichiro

1997-04-01

The paper presents a method for automatic segmentation of sputum cells with color images, to develop an efficient algorithm for lung cancer diagnosis based on a Hopfield neural network. We formulate the segmentation problem as a minimization of an energy function constructed with two terms, the cost-term as a sum of squared errors, and the second term a temporary noise added to the network as an excitation to escape certain local minima with the result of being closer to the global minimum. To increase the accuracy in segmenting the regions of interest, a preclassification technique is used to extract the sputum cell regions within the color image and remove those of the debris cells. The former is then given with the raw image to the input of Hopfield neural network to make a crisp segmentation by assigning each pixel to label such as background, cytoplasm, and nucleus. The proposed technique has yielded correct segmentation of complex scene of sputum prepared by ordinary manual staining method in most of the tested images selected from our database containing thousands of sputum color images.

The border-to-border distribution method for analysis of cytoplasmic particles and organelles.

PubMed

Yacovone, Shalane K; Ornelles, David A; Lyles, Douglas S

2016-02-01

Comparing the distribution of cytoplasmic particles and organelles between different experimental conditions can be challenging due to the heterogeneous nature of cell morphologies. The border-to-border distribution method was created to enable the quantitative analysis of fluorescently labeled cytoplasmic particles and organelles of multiple cells from images obtained by confocal microscopy. The method consists of four steps: (1) imaging of fluorescently labeled cells, (2) division of the image of the cytoplasm into radial segments, (3) selection of segments of interest, and (4) population analysis of fluorescence intensities at the pixel level either as a function of distance along the selected radial segments or as a function of angle around an annulus. The method was validated using the well-characterized effect of brefeldin A (BFA) on the distribution of the vesicular stomatitis virus G protein, in which intensely labeled Golgi membranes are redistributed within the cytoplasm. Surprisingly, in untreated cells, the distribution of fluorescence in Golgi membrane-containing radial segments was similar to the distribution of fluorescence in other G protein-containing segments, indicating that the presence of Golgi membranes did not shift the distribution of G protein towards the nucleus compared to the distribution of G protein in other regions of the cell. Treatment with BFA caused only a slight shift in the distribution of the brightest G protein-containing segments which had a distribution similar to that in untreated cells. Instead, the major effect of BFA was to alter the annular distribution of G protein in the perinuclear region.

Min-cut segmentation of cursive handwriting in tabular documents

NASA Astrophysics Data System (ADS)

Davis, Brian L.; Barrett, William A.; Swingle, Scott D.

2015-01-01

Handwritten tabular documents, such as census, birth, death and marriage records, contain a wealth of information vital to genealogical and related research. Much work has been done in segmenting freeform handwriting, however, segmentation of cursive handwriting in tabular documents is still an unsolved problem. Tabular documents present unique segmentation challenges caused by handwriting overlapping cell-boundaries and other words, both horizontally and vertically, as "ascenders" and "descenders" overlap into adjacent cells. This paper presents a method for segmenting handwriting in tabular documents using a min-cut/max-flow algorithm on a graph formed from a distance map and connected components of handwriting. Specifically, we focus on line, word and first letter segmentation. Additionally, we include the angles of strokes of the handwriting as a third dimension to our graph to enable the resulting segments to share pixels of overlapping letters. Word segmentation accuracy is 89.5% evaluating lines of the data set used in the ICDAR2013 Handwriting Segmentation Contest. Accuracy is 92.6% for a specific application of segmenting first and last names from noisy census records. Accuracy for segmenting lines of names from noisy census records is 80.7%. The 3D graph cutting shows promise in segmenting overlapping letters, although highly convoluted or overlapping handwriting remains an ongoing challenge.

The membrane current of single rod outer segments.

PubMed

Baylor, D A; Lamb, T D; Yau, K W

1979-03-01

1. Outer segments of individual rods in the retina of the toad, Bufo marinus, were drawn into a glass pipette to record the membrane current. 2. Light flashes evoked transient outward currents. The peak response amplitude was related to flash intensity by a Michaelis equation with half-saturating intensity about 1 photon mum-2. 3. The saturating response amplitude ranged up to 27 pA and corresponded closely to complete suppression of the steady inward current present in darkness. 4. For a given cell the saturating response amplitude varied linearly with the length of outer segment within the pipette. This is consistent with a uniform density of light-sensitive channels and negligible gradient of membrane potential along the outer segment. 5. Responses to bright flashes never showed the relaxation from an initial peak seen previously in intracellular voltage recordings, suggesting that the conductance change responsible for the relaxation does not occur in the outer segment. 6. Responses to local illumination of only the recorded outer segment were very similar to those obtained with diffuse light at the same intensity, indicating that peripheral rods made little contribution to the responses. 7. The spectral sensitivity of 'red' rods was consistent with a retinal1-based pigment with lambda max = 498 +/- 2 nm. 8. The kinetics of the response were consistent with four stages of delay affecting action of the internal transmitter. Responses were faster at the basal end of the outer segment than at the distal tip. 9. Background light reduced the sensitivity to a superposed dim test flash and shortened the time course of the response, indicating that adapting light modifies the kinetics and gain of the transduction mechanism within the outer segment. 10. Responses to dim lights exhibited pronounced fluctuations which are attributed in the succeeding paper (Baylor, Lamb & Yau, 1979) to the quantal nature of light.

Axonal trajectories of the nucleus reticularis gigantocellularis neurons in the C2-C3 segments in cats.

PubMed

Sasaki, S; Iwamoto, Y

1999-04-02

Axonal trajectories in the C2-C3 segments of the nucleus reticularis gigantocellularis neurons projecting to the lower cervical cord (C-RSNs) and excited monosynaptically from cortico- and tectofugal fibers were studied by mapping thresholds of antidromic excitation and intra-axonal staining in cats. The C-RSNs descended in various sites of the spinal funiculi, and the projection area of individual cells varied with the funicular location of the stem axon. C-RSNs descending in the ventrolateral funiculus (inRSNs) projected mainly to lamina VIII-IX, those descending in the lateral funiculus (IRSNs) mainly to laminae VI-VIII, and those descending in the contralateral funiculus (coRSNs) chiefly to laminae VIII-IX on that side. It is suggested that inRSNs and coRSNs mediate disynaptic effects from cortico- and tectofugal fibers to dorsal neck motoneurons bilaterally.

Preferential V beta gene usage and lack of junctional sequence conservation among human T cell receptors specific for a tetanus toxin- derived peptide: evidence for a dominant role of a germline-encoded V region in antigen/major histocompatibility complex recognition

PubMed Central

1992-01-01

To investigate the structural and genetic basis of the T cell response to defined peptide/major histocompatibility (MHC) class II complexes in humans, we established a large panel of T cell clones (61) from donors of different HLA-DR haplotypes and reactive with a tetanus toxin- derived peptide (tt830-844) recognized in association with most DR molecules (universal peptide). By using a bacterial enterotoxin-based proliferation assay and cDNA sequencing, we found preferential use of a particular V beta region gene segment, V beta 2.1, in three of the individuals studied (64%, n = 58), irrespective of whether the peptide was presented by the DR6wcI, DR4w4, or DRw11.1 and DRw11.2 alleles, demonstrating that shared MHC class II antigens are not required for shared V beta gene use by T cell receptors (TCRs) specific for this peptide. V alpha gene use was more heterogeneous, with at least seven different V alpha segments derived from five distinct families encoding alpha chains able to pair with V beta 2.1 chains to form a tt830-844/DR- specific binding site. Several cases were found of clones restricted to different DR alleles that expressed identical V beta and (or very closely related) V alpha gene segments and that differed only in their junctional sequences. Thus, changes in the putative complementary determining region 3 (CDR3) of the TCR may, in certain cases, alter MHC specificity and maintain peptide reactivity. Finally, in contrast to what has been observed in other defined peptide/MHC systems, a striking heterogeneity was found in the junctional regions of both alpha and beta chains, even for TCRs with identical V alpha and/or V beta gene segments and the same restriction. Among 14 anti-tt830-844 clones using the V beta 2.1 gene segment, 14 unique V beta-D-J beta junctions were found, with no evident conservation in length and/or amino acid composition. One interpretation for this apparent lack of coselection of specific junctional sequences in the context of a common V element, V beta 2.1, is that this V region plays a dominant role in the recognition of the tt830-844/DR complex. PMID:1371303

The Impact of Manual Segmentation of CT Images on Monte Carlo Based Skeletal Dosimetry

NASA Astrophysics Data System (ADS)

Frederick, Steve; Jokisch, Derek; Bolch, Wesley; Shah, Amish; Brindle, Jim; Patton, Phillip; Wyler, J. S.

2004-11-01

Radiation doses to the skeleton from internal emitters are of importance in both protection of radiation workers and patients undergoing radionuclide therapies. Improved dose estimates involve obtaining two sets of medical images. The first image provides the macroscopic boundaries (spongiosa volume and cortical shell) of the individual skeletal sites. A second, higher resolution image of the spongiosa microstructure is also obtained. These image sets then provide the geometry for a Monte Carlo radiation transport code. Manual segmentation of the first image is required in order to provide the macrostructural data. For this study, multiple segmentations of the same CT image were performed by multiple individuals. The segmentations were then used in the transport code and the results compared in order to determine the impact of differing segmentations on the skeletal doses. This work has provided guidance on the extent of training required of the manual segmenters. (This work was supported by a grant from the National Institute of Health.)

Hydrophilic polyurethane matrix promotes chondrogenesis of mesenchymal stem cells.

PubMed

Nalluri, Sandeep M; Krishnan, G Rajesh; Cheah, Calvin; Arzumand, Ayesha; Yuan, Yuan; Richardson, Caley A; Yang, Shuying; Sarkar, Debanjan

2015-09-01

Segmental polyurethanes exhibit biphasic morphology and can control cell fate by providing distinct matrix guided signals to increase the chondrogenic potential of mesenchymal stem cells (MSCs). Polyethylene glycol (PEG) based hydrophilic polyurethanes can deliver differential signals to MSCs through their matrix phases where hard segments are cell-interactive domains and PEG based soft segments are minimally interactive with cells. These coordinated communications can modulate cell-matrix interactions to control cell shape and size for chondrogenesis. Biphasic character and hydrophilicity of polyurethanes with gel like architecture provide a synthetic matrix conducive for chondrogenesis of MSCs, as evidenced by deposition of cartilage-associated extracellular matrix. Compared to monophasic hydrogels, presence of cell interactive domains in hydrophilic polyurethanes gels can balance cell-cell and cell-matrix interactions. These results demonstrate the correlation between lineage commitment and the changes in cell shape, cell-matrix interaction, and cell-cell adhesion during chondrogenic differentiation which is regulated by polyurethane phase morphology, and thus, represent hydrophilic polyurethanes as promising synthetic matrices for cartilage regeneration. Copyright © 2015 Elsevier B.V. All rights reserved.

The development of a 3D mesoscopic model of metallic foam based on an improved watershed algorithm

NASA Astrophysics Data System (ADS)

Zhang, Jinhua; Zhang, Yadong; Wang, Guikun; Fang, Qin

2018-06-01

The watershed algorithm has been used widely in the x-ray computed tomography (XCT) image segmentation. It provides a transformation defined on a grayscale image and finds the lines that separate adjacent images. However, distortion occurs in developing a mesoscopic model of metallic foam based on XCT image data. The cells are oversegmented at some events when the traditional watershed algorithm is used. The improved watershed algorithm presented in this paper can avoid oversegmentation and is composed of three steps. Firstly, it finds all of the connected cells and identifies the junctions of the corresponding cell walls. Secondly, the image segmentation is conducted to separate the adjacent cells. It generates the lost cell walls between the adjacent cells. Optimization is then performed on the segmentation image. Thirdly, this improved algorithm is validated when it is compared with the image of the metallic foam, which shows that it can avoid the image segmentation distortion. A mesoscopic model of metallic foam is thus formed based on the improved algorithm, and the mesoscopic characteristics of the metallic foam, such as cell size, volume and shape, are identified and analyzed.

Synthesis and activity of novel analogs of hemiasterlin as inhibitors of tubulin polymerization: modification of the A segment.

PubMed

Yamashita, Ayako; Norton, Emily B; Kaplan, Joshua A; Niu, Chuan; Loganzo, Frank; Hernandez, Richard; Beyer, Carl F; Annable, Tami; Musto, Sylvia; Discafani, Carolyn; Zask, Arie; Ayral-Kaloustian, Semiramis

2004-11-01

Analogs of hemiasterlin (1) and HTI-286 (2), which contain various aromatic rings in the A segment, were synthesized as potential inhibitors of tubulin polymerization. The structure-activity relationships related to stereo- and regio-chemical effects of substituents on the aromatic ring in the A segment were studied. Analogs, which carry a meta-substituted phenyl ring in the A segment show comparable activity for inhibition of tubulin polymerization to 2, as well as in the cell proliferation assay using KB cells containing P-glycoprotein, compared to those of 1 and 2.

The mechanisms of renal tubule electrolyte and water absorption, 100 years after Carl Ludwig.

PubMed

Greger, R

1996-01-01

Some 154 years after Carl Ludwig's Habilitationsschrift "Contributions to the theory of the mechanism of urine secretion" renal physiology has come a long way. The mechanisms of urine formation are now understood as the result of glomerular filtration and tubule absorption of most of the filtrate. The detailed understanding of tubule transport processes has become possible with the invention of several refined techniques such as the micropuncture techniques; the microchemical analysis of nanolitre tubule fluid samples; the in vitro perfusion of isolated tubule segments of defined origin; electrophysiological analysis of electrolyte transport including micropuncture and patch-clamp techniques; transport studies in membrane vesicle preparations; recordings of intracellular electrolyte concentrations and cloning techniques of the individual membrane transport proteins. With this wealth of information we are now starting to build an integrative understanding of the function of the individual nephron segments, the regulatory processes, the integrated function of the nephron and hence the formation of the final urine. Like anatomists of previous centuries we still state that the kidney is an "organum mirable" and we recognize that basic research in this area has fertilized the analysis of the function of a large number of other organs and cells.

A three-dimensional image processing program for accurate, rapid, and semi-automated segmentation of neuronal somata with dense neurite outgrowth

PubMed Central

Ross, James D.; Cullen, D. Kacy; Harris, James P.; LaPlaca, Michelle C.; DeWeerth, Stephen P.

2015-01-01

Three-dimensional (3-D) image analysis techniques provide a powerful means to rapidly and accurately assess complex morphological and functional interactions between neural cells. Current software-based identification methods of neural cells generally fall into two applications: (1) segmentation of cell nuclei in high-density constructs or (2) tracing of cell neurites in single cell investigations. We have developed novel methodologies to permit the systematic identification of populations of neuronal somata possessing rich morphological detail and dense neurite arborization throughout thick tissue or 3-D in vitro constructs. The image analysis incorporates several novel automated features for the discrimination of neurites and somata by initially classifying features in 2-D and merging these classifications into 3-D objects; the 3-D reconstructions automatically identify and adjust for over and under segmentation errors. Additionally, the platform provides for software-assisted error corrections to further minimize error. These features attain very accurate cell boundary identifications to handle a wide range of morphological complexities. We validated these tools using confocal z-stacks from thick 3-D neural constructs where neuronal somata had varying degrees of neurite arborization and complexity, achieving an accuracy of ≥95%. We demonstrated the robustness of these algorithms in a more complex arena through the automated segmentation of neural cells in ex vivo brain slices. These novel methods surpass previous techniques by improving the robustness and accuracy by: (1) the ability to process neurites and somata, (2) bidirectional segmentation correction, and (3) validation via software-assisted user input. This 3-D image analysis platform provides valuable tools for the unbiased analysis of neural tissue or tissue surrogates within a 3-D context, appropriate for the study of multi-dimensional cell-cell and cell-extracellular matrix interactions. PMID:26257609

3D Clumped Cell Segmentation Using Curvature Based Seeded Watershed.

PubMed

Atta-Fosu, Thomas; Guo, Weihong; Jeter, Dana; Mizutani, Claudia M; Stopczynski, Nathan; Sousa-Neves, Rui

2016-12-01

Image segmentation is an important process that separates objects from the background and also from each other. Applied to cells, the results can be used for cell counting which is very important in medical diagnosis and treatment, and biological research that is often used by scientists and medical practitioners. Segmenting 3D confocal microscopy images containing cells of different shapes and sizes is still challenging as the nuclei are closely packed. The watershed transform provides an efficient tool in segmenting such nuclei provided a reasonable set of markers can be found in the image. In the presence of low-contrast variation or excessive noise in the given image, the watershed transform leads to over-segmentation (a single object is overly split into multiple objects). The traditional watershed uses the local minima of the input image and will characteristically find multiple minima in one object unless they are specified (marker-controlled watershed). An alternative to using the local minima is by a supervised technique called seeded watershed, which supplies single seeds to replace the minima for the objects. Consequently, the accuracy of a seeded watershed algorithm relies on the accuracy of the predefined seeds. In this paper, we present a segmentation approach based on the geometric morphological properties of the 'landscape' using curvatures. The curvatures are computed as the eigenvalues of the Shape matrix, producing accurate seeds that also inherit the original shape of their respective cells. We compare with some popular approaches and show the advantage of the proposed method.

Formation of rings from segments of HeLa-cell nuclear deoxyribonucleic acid

PubMed Central

Hardman, Norman

1974-01-01

Duplex segments of HeLa-cell nuclear DNA were generated by cleavage with DNA restriction endonuclease from Haemophilus influenzae. About 20–25% of the DNA segments produced, when partly degraded with exonuclease III and annealed, were found to form rings visible in the electron microscope. A further 5% of the DNA segments formed structures that were branched in configuration. Similar structures were generated from HeLa-cell DNA, without prior treatment with restriction endonuclease, when the complementary polynucleotide chains were exposed by exonuclease III action at single-chain nicks. After exposure of an average single-chain length of 1400 nucleotides per terminus at nicks in HeLa-cell DNA by exonuclease III, followed by annealing, the physical length of ring closures was estimated and found to be 0.02–0.1μm, or 50–300 base pairs. An almost identical distribution of lengths was recorded for the regions of complementary base sequence responsible for branch formation. It is proposed that most of the rings and branches are formed from classes of reiterated base sequence with an average length of 180 base pairs arranged intermittenly in HeLa-cell DNA. From the rate of formation of branched structures when HeLa-cell DNA segments were heat-denatured and annealed, it is estimated that the reiterated sequences are in families containing approximately 2400–24000 copies. ImagesPLATE 2PLATE 1 PMID:4462738

Resolving mixed mechanisms of protein subdiffusion at the T cell plasma membrane

NASA Astrophysics Data System (ADS)

Golan, Yonatan; Sherman, Eilon

2017-06-01

The plasma membrane is a complex medium where transmembrane proteins diffuse and interact to facilitate cell function. Membrane protein mobility is affected by multiple mechanisms, including crowding, trapping, medium elasticity and structure, thus limiting our ability to distinguish them in intact cells. Here we characterize the mobility and organization of a short transmembrane protein at the plasma membrane of live T cells, using single particle tracking and photoactivated-localization microscopy. Protein mobility is highly heterogeneous, subdiffusive and ergodic-like. Using mobility characteristics, we segment individual trajectories into subpopulations with distinct Gaussian step-size distributions. Particles of low-to-medium mobility consist of clusters, diffusing in a viscoelastic and fractal-like medium and are enriched at the centre of the cell footprint. Particles of high mobility undergo weak confinement and are more evenly distributed. This study presents a methodological approach to resolve simultaneous mixed subdiffusion mechanisms acting on polydispersed samples and complex media such as cell membranes.

Measuring single-cell gene expression dynamics in bacteria using fluorescence time-lapse microscopy

PubMed Central

Young, Jonathan W; Locke, James C W; Altinok, Alphan; Rosenfeld, Nitzan; Bacarian, Tigran; Swain, Peter S; Mjolsness, Eric; Elowitz, Michael B

2014-01-01

Quantitative single-cell time-lapse microscopy is a powerful method for analyzing gene circuit dynamics and heterogeneous cell behavior. We describe the application of this method to imaging bacteria by using an automated microscopy system. This protocol has been used to analyze sporulation and competence differentiation in Bacillus subtilis, and to quantify gene regulation and its fluctuations in individual Escherichia coli cells. The protocol involves seeding and growing bacteria on small agarose pads and imaging the resulting microcolonies. Images are then reviewed and analyzed using our laboratory's custom MATLAB analysis code, which segments and tracks cells in a frame-to-frame method. This process yields quantitative expression data on cell lineages, which can illustrate dynamic expression profiles and facilitate mathematical models of gene circuits. With fast-growing bacteria, such as E. coli or B. subtilis, image acquisition can be completed in 1 d, with an additional 1–2 d for progressing through the analysis procedure. PMID:22179594

Lectin-based food poisoning: a new mechanism of protein toxicity.

PubMed

Miyake, Katsuya; Tanaka, Toru; McNeil, Paul L

2007-08-01

Ingestion of the lectins present in certain improperly cooked vegetables can result in acute GI tract distress, but the mechanism of toxicity is unknown. In vivo, gut epithelial cells are constantly exposed to mechanical and other stresses and consequently individual cells frequently experience plasma membrane disruptions. Repair of these cell surface disruptions allows the wounded cell to survive: failure results in necrotic cell death. Plasma membrane repair is mediated, in part, by an exocytotic event that adds a patch of internal membrane to the defect site. Lectins are known to inhibit exocytosis. We therefore tested the novel hypothesis that lectin toxicity is due to an inhibitory effect on plasma membrane repair. Repair of plasma membrane disruptions and exocytosis of mucus was assessed after treatment of cultured cell models and excised segments of the GI tract with lectins. Plasma membrane disruptions were produced by focal irradiation of individual cells, using a microscope-based laser, or by mechanical abrasion of multiple cells, using a syringe needle. Repair was then assessed by monitoring the cytosolic penetration of dyes incapable of crossing the intact plasma membrane. We found that cell surface-bound lectins potently inhibited plasma membrane repair, and the exocytosis of mucus that normally accompanies the repair response. Lectins potently inhibit plasma membrane repair, and hence are toxic to wounded cells. This represents a novel form of protein-based toxicity, one that, we propose, is the basis of plant lectin food poisoning.

Robust and automated three-dimensional segmentation of densely packed cell nuclei in different biological specimens with Lines-of-Sight decomposition.

PubMed

Mathew, B; Schmitz, A; Muñoz-Descalzo, S; Ansari, N; Pampaloni, F; Stelzer, E H K; Fischer, S C

2015-06-08

Due to the large amount of data produced by advanced microscopy, automated image analysis is crucial in modern biology. Most applications require reliable cell nuclei segmentation. However, in many biological specimens cell nuclei are densely packed and appear to touch one another in the images. Therefore, a major difficulty of three-dimensional cell nuclei segmentation is the decomposition of cell nuclei that apparently touch each other. Current methods are highly adapted to a certain biological specimen or a specific microscope. They do not ensure similarly accurate segmentation performance, i.e. their robustness for different datasets is not guaranteed. Hence, these methods require elaborate adjustments to each dataset. We present an advanced three-dimensional cell nuclei segmentation algorithm that is accurate and robust. Our approach combines local adaptive pre-processing with decomposition based on Lines-of-Sight (LoS) to separate apparently touching cell nuclei into approximately convex parts. We demonstrate the superior performance of our algorithm using data from different specimens recorded with different microscopes. The three-dimensional images were recorded with confocal and light sheet-based fluorescence microscopes. The specimens are an early mouse embryo and two different cellular spheroids. We compared the segmentation accuracy of our algorithm with ground truth data for the test images and results from state-of-the-art methods. The analysis shows that our method is accurate throughout all test datasets (mean F-measure: 91%) whereas the other methods each failed for at least one dataset (F-measure≤69%). Furthermore, nuclei volume measurements are improved for LoS decomposition. The state-of-the-art methods required laborious adjustments of parameter values to achieve these results. Our LoS algorithm did not require parameter value adjustments. The accurate performance was achieved with one fixed set of parameter values. We developed a novel and fully automated three-dimensional cell nuclei segmentation method incorporating LoS decomposition. LoS are easily accessible features that ensure correct splitting of apparently touching cell nuclei independent of their shape, size or intensity. Our method showed superior performance compared to state-of-the-art methods, performing accurately for a variety of test images. Hence, our LoS approach can be readily applied to quantitative evaluation in drug testing, developmental and cell biology.

Post-mortem quetiapine concentrations in hair segments of psychiatric patients - Correlation between hair concentration, dose and concentration in blood.

PubMed

Günther, Kamilla Nyborg; Johansen, Sys Stybe; Nielsen, Marie Katrine Klose; Wicktor, Petra; Banner, Jytte; Linnet, Kristian

2018-04-01

Drug analysis in hair is useful when seeking to establish drug intake over a period of months to years. Segmental hair analysis can also document whether psychiatric patients are receiving a stable intake of antipsychotics. This study describes segmental analysis of the antipsychotic drug quetiapine in post-mortem hair samples from long-term quetiapine users by ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) analysis. The aim was to obtain more knowledge on quetiapine concentrations in hair and to relate the concentration in hair to the administered dose and the post-mortem concentration in femoral blood. We analyzed hair samples from 22 deceased quetiapine-treated individuals, who were divided into two groups: natural hair colour and dyed/bleached hair. Two to six 1cm long segments were analyzed per individual, depending on the length of the hair, with 6cm corresponding to the last six months before death. The average daily quetiapine dose and average concentration in hair for the last six months prior to death were examined for potential correlation. Estimated doses ranged from 45 to 1040mg quetiapine daily over the period, and the average concentration in hair ranged from 0.18 to 13ng/mg. A significant positive correlation was observed between estimated daily dosage of quetiapine and average concentration in hair for individuals with natural hair colour (p=0.00005), but statistical significance was not reached for individuals with dyed/bleached hair (p=0.31). The individual coefficient of variation (CV) of the quetiapine concentrations between segments ranged from 3 to 34% for individuals with natural hair colour and 22-62% for individuals with dyed/bleached hair. Dose-adjusted concentrations in hair were significantly lower in females with dyed/bleached hair than in individuals with natural hair colour. The quetiapine concentrations in post-mortem femoral blood and in the proximal hair segment, segment 1 (S1), representing the last month before death were also investigated for correlation. A significant positive correlation was observed between quetiapine concentrations in blood at the time of death and concentrations in S1 for individuals with natural hair colour (p=0.003) but not for individuals with dyed/bleached hair (p=0.31). The blood concentrations of quetiapine ranged from 0.006 to 1.9mg/kg, and the quetiapine concentrations in S1 ranged from 0.22 to 24ng/mg. The results of this study suggest a positive correlation of quetiapine between both concentrations in hair and doses, and between proximal hair (S1) and blood concentrations, when conditions such as hair treatments are taken into consideration. Copyright © 2018 Elsevier B.V. All rights reserved.

Analysis of in vivo single cell behavior by high throughput, human-in-the-loop segmentation of three-dimensional images.

PubMed

Chiang, Michael; Hallman, Sam; Cinquin, Amanda; de Mochel, Nabora Reyes; Paz, Adrian; Kawauchi, Shimako; Calof, Anne L; Cho, Ken W; Fowlkes, Charless C; Cinquin, Olivier

2015-11-25

Analysis of single cells in their native environment is a powerful method to address key questions in developmental systems biology. Confocal microscopy imaging of intact tissues, followed by automatic image segmentation, provides a means to conduct cytometric studies while at the same time preserving crucial information about the spatial organization of the tissue and morphological features of the cells. This technique is rapidly evolving but is still not in widespread use among research groups that do not specialize in technique development, perhaps in part for lack of tools that automate repetitive tasks while allowing experts to make the best use of their time in injecting their domain-specific knowledge. Here we focus on a well-established stem cell model system, the C. elegans gonad, as well as on two other model systems widely used to study cell fate specification and morphogenesis: the pre-implantation mouse embryo and the developing mouse olfactory epithelium. We report a pipeline that integrates machine-learning-based cell detection, fast human-in-the-loop curation of these detections, and running of active contours seeded from detections to segment cells. The procedure can be bootstrapped by a small number of manual detections, and outperforms alternative pieces of software we benchmarked on C. elegans gonad datasets. Using cell segmentations to quantify fluorescence contents, we report previously-uncharacterized cell behaviors in the model systems we used. We further show how cell morphological features can be used to identify cell cycle phase; this provides a basis for future tools that will streamline cell cycle experiments by minimizing the need for exogenous cell cycle phase labels. High-throughput 3D segmentation makes it possible to extract rich information from images that are routinely acquired by biologists, and provides insights - in particular with respect to the cell cycle - that would be difficult to derive otherwise.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reshetenko, T. V.; Bender, G.; Bethune, K.

The overall current density that is measured in a proton exchange membrane fuel cell (PEMFC) represents the average of the local reaction rates. The overall and local PEMFC performances are determined by several primary loss mechanisms, namely activation, ohmic, and mass transfer. Spatial performance and loss variabilities are significant and depend on the cell design and operating conditions. A segmented cell system was used to quantify different loss distributions along the gas channel to understand the effects of gas humidification. A reduction in the reactant stream humidification decreased cell performance and resulted in non-uniform distributions of overpotentials and performance alongmore » the flow field. Activation and ohmic overpotentials increased with a relative humidity decrease due to insufficient membrane and catalyst layer hydration. The relative humidity of the cathode had a strong impact on the mass transfer overpotential due to a lower oxygen permeability through the dry Nafion film covering the catalyst surface. The mass transfer loss distribution was non-uniform, and the mass transfer overpotential increased for the outlet segments due to the oxygen consumption at the inlet segments, which reduced the oxygen concentration downstream, and a progressive water accumulation from upstream segments. Electrochemical impedance spectroscopy (EIS) and an equivalent electric circuit (EEC) facilitated the analysis and interpretation of the segmented cell data.« less

Single-Molecule FISH Reveals Non-selective Packaging of Rift Valley Fever Virus Genome Segments

PubMed Central

Wichgers Schreur, Paul J.; Kortekaas, Jeroen

2016-01-01

The bunyavirus genome comprises a small (S), medium (M), and large (L) RNA segment of negative polarity. Although genome segmentation confers evolutionary advantages by enabling genome reassortment events with related viruses, genome segmentation also complicates genome replication and packaging. Accumulating evidence suggests that genomes of viruses with eight or more genome segments are incorporated into virions by highly selective processes. Remarkably, little is known about the genome packaging process of the tri-segmented bunyaviruses. Here, we evaluated, by single-molecule RNA fluorescence in situ hybridization (FISH), the intracellular spatio-temporal distribution and replication kinetics of the Rift Valley fever virus (RVFV) genome and determined the segment composition of mature virions. The results reveal that the RVFV genome segments start to replicate near the site of infection before spreading and replicating throughout the cytoplasm followed by translocation to the virion assembly site at the Golgi network. Despite the average intracellular S, M and L genome segments approached a 1:1:1 ratio, major differences in genome segment ratios were observed among cells. We also observed a significant amount of cells lacking evidence of M-segment replication. Analysis of two-segmented replicons and four-segmented viruses subsequently confirmed the previous notion that Golgi recruitment is mediated by the Gn glycoprotein. The absence of colocalization of the different segments in the cytoplasm and the successful rescue of a tri-segmented variant with a codon shuffled M-segment suggested that inter-segment interactions are unlikely to drive the copackaging of the different segments into a single virion. The latter was confirmed by direct visualization of RNPs inside mature virions which showed that the majority of virions lack one or more genome segments. Altogether, this study suggests that RVFV genome packaging is a non-selective process. PMID:27548280

Multimedia Learning and Individual Differences: Mediating the Effects of Working Memory Capacity with Segmentation

ERIC Educational Resources Information Center

Lusk, Danielle L.; Evans, Amber D.; Jeffrey, Thomas R.; Palmer, Keith R.; Wikstrom, Chris S.; Doolittle, Peter E.

2009-01-01

Research in multimedia learning lacks an emphasis on individual difference variables, such as working memory capacity (WMC). The effects of WMC and the segmentation of multimedia instruction were examined by assessing the recall and application of low (n = 66) and high (n = 67) working memory capacity students randomly assigned to either a…

Lung lobe modeling and segmentation with individualized surface meshes

NASA Astrophysics Data System (ADS)

Blaffert, Thomas; Barschdorf, Hans; von Berg, Jens; Dries, Sebastian; Franz, Astrid; Klinder, Tobias; Lorenz, Cristian; Renisch, Steffen; Wiemker, Rafael

2008-03-01

An automated segmentation of lung lobes in thoracic CT images is of interest for various diagnostic purposes like the quantification of emphysema or the localization of tumors within the lung. Although the separating lung fissures are visible in modern multi-slice CT-scanners, their contrast in the CT-image often does not separate the lobes completely. This makes it impossible to build a reliable segmentation algorithm without additional information. Our approach uses general anatomical knowledge represented in a geometrical mesh model to construct a robust lobe segmentation, which even gives reasonable estimates of lobe volumes if fissures are not visible at all. The paper describes the generation of the lung model mesh including lobes by an average volume model, its adaptation to individual patient data using a special fissure feature image, and a performance evaluation over a test data set showing an average segmentation accuracy of 1 to 3 mm.

Individual muscle segmentation in MR images: A 3D propagation through 2D non-linear registration approaches.

PubMed

Ogier, Augustin; Sdika, Michael; Foure, Alexandre; Le Troter, Arnaud; Bendahan, David

2017-07-01

Manual and automated segmentation of individual muscles in magnetic resonance images have been recognized as challenging given the high variability of shapes between muscles and subjects and the discontinuity or lack of visible boundaries between muscles. In the present study, we proposed an original algorithm allowing a semi-automatic transversal propagation of manually-drawn masks. Our strategy was based on several ascending and descending non-linear registration approaches which is similar to the estimation of a Lagrangian trajectory applied to manual masks. Using several manually-segmented slices, we have evaluated our algorithm on the four muscles of the quadriceps femoris group. We mainly showed that our 3D propagated segmentation was very accurate with an averaged Dice similarity coefficient value higher than 0.91 for the minimal manual input of only two manually-segmented slices.

Hydrophilic polyurethane matrix promotes chondrogenesis of mesenchymal stem cells☆

PubMed Central

Nalluri, Sandeep M.; Krishnan, G. Rajesh; Cheah, Calvin; Arzumand, Ayesha; Yuan, Yuan; Richardson, Caley A.; Yang, Shuying; Sarkar, Debanjan

2016-01-01

Segmental polyurethanes exhibit biphasic morphology and can control cell fate by providing distinct matrix guided signals to increase the chondrogenic potential of mesenchymal stem cells (MSCs). Polyethylene glycol (PEG) based hydrophilic polyurethanes can deliver differential signals to MSCs through their matrix phases where hard segments are cell-interactive domains and PEG based soft segments are minimally interactive with cells. These coordinated communications can modulate cell–matrix interactions to control cell shape and size for chondrogenesis. Biphasic character and hydrophilicity of polyurethanes with gel like architecture provide a synthetic matrix conducive for chondrogenesis of MSCs, as evidenced by deposition of cartilage-associated extracellular matrix. Compared to monophasic hydrogels, presence of cell interactive domains in hydrophilic polyurethanes gels can balance cell–cell and cell–matrix interactions. These results demonstrate the correlation between lineage commitment and the changes in cell shape, cell–matrix interaction, and cell–cell adhesion during chondrogenic differentiation which is regulated by polyurethane phase morphology, and thus, represent hydrophilic polyurethanes as promising synthetic matrices for cartilage regeneration. PMID:26046282

Stress relaxation of cell walls and the yield threshold for growth: demonstration and measurement by micro-pressure probe and psychrometer techniques.

PubMed

Cosgrove, D J; Van Volkenburgh, E; Cleland, R E

1984-01-01

Theory predicts that, for growing plant cells isolated from a supply of water, stress relaxation of the cell wall should decrease cell turgor pressure (P) until the yield threshold for cell explanation is reached. This prediction was tested by direct P measurements of pea (Pisum sativum L.) stem cortical cells before and after excision of the growing region and isolation of the growing tissue from an external water supply. Cell P was measured with the micro-pressure probe under conditions which eliminated transpiration. Psychrometric measurements of water potential confirmed the pressure-probe measurements. Following excision, P of the growing cells decreased in 1 h by an average of 1.8 bar to a mean plateau value of 2.8 bar, and remained constant thereafter. Treatment with 10(-5) M indole-3-acetic acid or 10(-5) M fusicoccin (known growth stimulants) accelerated the rate of P relaxation, whereas various treatments which inhibit growth slowed down or completely stopped P relaxation in apical segments. In contrast, P of basal (nongrowing) segments gradually increased because of absorption of solutes from the cell-wall free space of the tissue. Such solute absorption also occurred in apical segments, but wall relaxation held P at the yield threshold in those segments which were isolated from an external water supply. These results provide a new and rapid method for measuring the yield threshold and they show that P in intact growing pea stems exceeds the yield threshold by about 2 bar. Wall relaxation is shown here to affect the water potential and turgor pressure of excised growing segments. In addition, solute release and absorption upon excision may influence the water potential and turgor pressure of nongrowing excised plant tissues.

The Encapsidated Genome of Microplitis demolitor Bracovirus Integrates into the Host Pseudoplusia includens ▿ ‡

PubMed Central

Beck, Markus H.; Zhang, Shu; Bitra, Kavita; Burke, Gaelen R.; Strand, Michael R.

2011-01-01

Polydnaviruses (PDVs) are symbionts of parasitoid wasps that function as gene delivery vehicles in the insects (hosts) that the wasps parasitize. PDVs persist in wasps as integrated proviruses but are packaged as circularized and segmented double-stranded DNAs into the virions that wasps inject into hosts. In contrast, little is known about how PDV genomic DNAs persist in host cells. Microplitis demolitor carries Microplitis demolitor bracovirus (MdBV) and parasitizes the host Pseudoplusia includens. MdBV infects primarily host hemocytes and also infects a hemocyte-derived cell line from P. includens called CiE1 cells. Here we report that all 15 genomic segments of the MdBV encapsidated genome exhibited long-term persistence in CiE1 cells. Most MdBV genes expressed in hemocytes were persistently expressed in CiE1 cells, including members of the glc gene family whose products transformed CiE1 cells into a suspension culture. PCR-based integration assays combined with cloning and sequencing of host-virus junctions confirmed that genomic segments J and C persisted in CiE1 cells by integration. These genomic DNAs also rapidly integrated into parasitized P. includens. Sequence analysis of wasp-viral junction clones showed that the integration of proviral segments in M. demolitor was associated with a wasp excision/integration motif (WIM) known from other bracoviruses. However, integration into host cells occurred in association with a previously unknown domain that we named the host integration motif (HIM). The presence of HIMs in most MdBV genomic DNAs suggests that the integration of each genomic segment into host cells occurs through a shared mechanism. PMID:21880747

Impact assisted segmented cutterhead

DOEpatents

Morrell, Roger J.; Larson, David A.; Ruzzi, Peter L.

1992-01-01

An impact assisted segmented cutterhead device is provided for cutting various surfaces from coal to granite. The device comprises a plurality of cutting bit segments deployed in side by side relationship to form a continuous cutting face and a plurality of impactors individually associated with respective cutting bit segments. An impactor rod of each impactor connects that impactor to the corresponding cutting bit segment. A plurality of shock mounts dampening the vibration from the associated impactor. Mounting brackets are used in mounting the cutterhead to a base machine.

Revised classification/nomenclature of vitiligo and related issues: the Vitiligo Global Issues Consensus Conference

PubMed Central

Ezzedine, K.; Lim, H. W.; Suzuki, T.; Katayama, I.; Hamzavi, I.; Lan, C. C. E.; Goh, B. K.; Anbar, T.; de Castro, C. Silva; Lee, A. Y.; Parsad, D.; van Geel, N.; Le Poole, I. C.; Oiso, N.; Benzekri, L.; Spritz, R.; Gauthier, Y.; Hann, S. K.; Picardo, M.; Taieb, A.

2012-01-01

Summary During the 2011 International Pigment Cell Conference (IPCC), the Vitiligo European Taskforce (VETF) convened a consensus conference on issues of global importance for vitiligo clinical research. As suggested by an international panel of experts, the conference focused on four topics: classification and nomenclature; definition of stable disease; definition of Koebner’s phenomenon (KP); and ‘autoimmune vitiligo’. These topics were discussed in seven working groups representing different geographical regions. A consensus emerged that segmental vitiligo be classified separately from all other forms of vitiligo and that the term ‘vitiligo’ be used as an umbrella term for all non-segmental forms of vitiligo, including ‘mixed vitiligo’ in which segmental and non-segmental vitiligo are combined and which is considered a subgroup of vitiligo. Further, the conference recommends that disease stability be best assessed based on the stability of individual lesions rather than the overall stability of the disease as the latter is difficult to define precisely and reliably. The conference also endorsed the classification of KP for vitiligo as proposed by the VETF (history based, clinical observation based, or experimentally induced). Lastly, the conference agreed that ‘autoimmune vitiligo’ should not be used as a separate classification as published evidence indicates that the pathophysiology of all forms of vitiligo likely involves autoimmune or inflammatory mechanisms. PMID:22417114

Revised classification/nomenclature of vitiligo and related issues: the Vitiligo Global Issues Consensus Conference.

PubMed

Ezzedine, K; Lim, H W; Suzuki, T; Katayama, I; Hamzavi, I; Lan, C C E; Goh, B K; Anbar, T; Silva de Castro, C; Lee, A Y; Parsad, D; van Geel, N; Le Poole, I C; Oiso, N; Benzekri, L; Spritz, R; Gauthier, Y; Hann, S K; Picardo, M; Taieb, A

2012-05-01

During the 2011 International Pigment Cell Conference (IPCC), the Vitiligo European Taskforce (VETF) convened a consensus conference on issues of global importance for vitiligo clinical research. As suggested by an international panel of experts, the conference focused on four topics: classification and nomenclature; definition of stable disease; definition of Koebner's phenomenon (KP); and 'autoimmune vitiligo'. These topics were discussed in seven working groups representing different geographical regions. A consensus emerged that segmental vitiligo be classified separately from all other forms of vitiligo and that the term 'vitiligo' be used as an umbrella term for all non-segmental forms of vitiligo, including 'mixed vitiligo' in which segmental and non-segmental vitiligo are combined and which is considered a subgroup of vitiligo. Further, the conference recommends that disease stability be best assessed based on the stability of individual lesions rather than the overall stability of the disease as the latter is difficult to define precisely and reliably. The conference also endorsed the classification of KP for vitiligo as proposed by the VETF (history based, clinical observation based, or experimentally induced). Lastly, the conference agreed that 'autoimmune vitiligo' should not be used as a separate classification as published evidence indicates that the pathophysiology of all forms of vitiligo likely involves autoimmune or inflammatory mechanisms. © 2012 John Wiley & Sons A/S.

Atomic structures of fibrillar segments of hIAPP suggest tightly mated β-sheets are important for cytotoxicity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krotee, Pascal; Rodriguez, Jose A.; Sawaya, Michael R.

2017-01-03

hIAPP fibrils are associated with Type-II Diabetes, but the link of hIAPP structure to islet cell death remains elusive. Here we observe that hIAPP fibrils are cytotoxic to cultured pancreatic β-cells, leading us to determine the structure and cytotoxicity of protein segments composing the amyloid spine of hIAPP. Using the cryoEM method MicroED, we discover that one segment, 19–29 S20G, forms pairs of β-sheets mated by a dry interface that share structural features with and are similarly cytotoxic to full-length hIAPP fibrils. In contrast, a second segment, 15–25 WT, forms non-toxic labile β-sheets. These segments possess different structures and cytotoxicmore » effects, however, both can seed full-length hIAPP, and cause hIAPP to take on the cytotoxic and structural features of that segment. These results suggest that protein segment structures represent polymorphs of their parent protein and that segment 19–29 S20G may serve as a model for the toxic spine of hIAPP.« less

Spine Patterning Is Guided by Segmentation of the Notochord Sheath.

PubMed

Wopat, Susan; Bagwell, Jennifer; Sumigray, Kaelyn D; Dickson, Amy L; Huitema, Leonie F A; Poss, Kenneth D; Schulte-Merker, Stefan; Bagnat, Michel

2018-02-20

The spine is a segmented axial structure made of alternating vertebral bodies (centra) and intervertebral discs (IVDs) assembled around the notochord. Here, we show that, prior to centra formation, the outer epithelial cell layer of the zebrafish notochord, the sheath, segments into alternating domains corresponding to the prospective centra and IVD areas. This process occurs sequentially in an anteroposterior direction via the activation of Notch signaling in alternating segments of the sheath, which transition from cartilaginous to mineralizing domains. Subsequently, osteoblasts are recruited to the mineralized domains of the notochord sheath to form mature centra. Tissue-specific manipulation of Notch signaling in sheath cells produces notochord segmentation defects that are mirrored in the spine. Together, our findings demonstrate that notochord sheath segmentation provides a template for vertebral patterning in the zebrafish spine. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Applying the RUSLE and the USLE-M on hillslopes where runoff production during an erosion event is spatially variable

NASA Astrophysics Data System (ADS)

Kinnell, P. I. A.

2014-11-01

The assumption that runoff is produced uniformly over the eroding area underlies the traditional use of Universal Soil Loss Equation (USLE) and the revised version of it, the RUSLE. However, although the application of the USLE/RUSLE to segments on one dimensional hillslopes and cells on two-dimensional hillslopes is based on the assumption that each segment or cell is spatially uniform, factors such as soil infiltration, and hence runoff production, may vary spatially between segments or cells. Results from equations that focus on taking account of spatially variable runoff when applying the USLE/RUSLE and the USLE-M, the modification of the USLE/RUSLE that replaces the EI30 index by the product of EI30 and the runoff ratio, in hillslopes during erosion events where runoff is not produced uniformly were compared on a hypothetical a 300 m long one-dimensional hillslope with a spatially uniform gradient. Results were produced for situations where all the hillslope was tilled bare fallow and where half of the hillslope was cropped with corn and half was tilled bare fallow. Given that the erosive stress within a segment or cell depends on the volume of surface water flowing through the segment or cell, soil loss can be expected to increase not only with distance from the point where runoff begins but also directly with runoff when it varies about the average for the slope containing the segment or cell. The latter effect was achieved when soil loss was predicted using the USLE-M but not when the USLE/RUSLE slope length factor for a segment using an effective upslope length that varies with the ratio of the upslope runoff coefficient and the runoff coefficient for the slope to the bottom of the segment or cell was used. The USLE-M also predicted deposition to occur in a segment containing corn when an area with tilled bare fallow soil existed immediately upslope of it because the USLE-M models erosion on runoff and soil loss plots as a transport limited system. In a comparison of the USLE-M and RUSLE2, the form of the RUSLE that uses a daily time step in modeling rainfall erosion on one-dimensional hillslopes in the USA, on a 300 m long 9% hillslope where management changed from bare fallow to corn midway down the slope, the USLE-M predicted greater deposition in the bottom segment than predicted by RUSLE2. In addition, the USLE-M approach predicted that the deposition that occurred when the slope gradient changed from 9% to 4.5% midway down the slope was much greater than the amount predicted using RUSLE2.

Automatic trajectory measurement of large numbers of crowded objects

NASA Astrophysics Data System (ADS)

Li, Hui; Liu, Ye; Chen, Yan Qiu

2013-06-01

Complex motion patterns of natural systems, such as fish schools, bird flocks, and cell groups, have attracted great attention from scientists for years. Trajectory measurement of individuals is vital for quantitative and high-throughput study of their collective behaviors. However, such data are rare mainly due to the challenges of detection and tracking of large numbers of objects with similar visual features and frequent occlusions. We present an automatic and effective framework to measure trajectories of large numbers of crowded oval-shaped objects, such as fish and cells. We first use a novel dual ellipse locator to detect the coarse position of each individual and then propose a variance minimization active contour method to obtain the optimal segmentation results. For tracking, cost matrix of assignment between consecutive frames is trainable via a random forest classifier with many spatial, texture, and shape features. The optimal trajectories are found for the whole image sequence by solving two linear assignment problems. We evaluate the proposed method on many challenging data sets.

Indexing amyloid peptide diffraction from serial femtosecond crystallography: New algorithms for sparse patterns

DOE PAGES

Brewster, Aaron S.; Sawaya, Michael R.; Rodriguez, Jose; ...

2015-01-23

Still diffraction patterns from peptide nanocrystals with small unit cells are challenging to index using conventional methods owing to the limited number of spots and the lack of crystal orientation information for individual images. New indexing algorithms have been developed as part of the Computational Crystallography Toolbox( cctbx) to overcome these challenges. Accurate unit-cell information derived from an aggregate data set from thousands of diffraction patterns can be used to determine a crystal orientation matrix for individual images with as few as five reflections. These algorithms are potentially applicable not only to amyloid peptides but also to any set ofmore » diffraction patterns with sparse properties, such as low-resolution virus structures or high-throughput screening of still images captured by raster-scanning at synchrotron sources. As a proof of concept for this technique, successful integration of X-ray free-electron laser (XFEL) data to 2.5 Å resolution for the amyloid segment GNNQQNY from the Sup35 yeast prion is presented.« less

Automatic choroid cells segmentation and counting in fluorescence microscopic image

NASA Astrophysics Data System (ADS)

Fei, Jianjun; Zhu, Weifang; Shi, Fei; Xiang, Dehui; Lin, Xiao; Yang, Lei; Chen, Xinjian

2016-03-01

In this paper, we proposed a method to automatically segment and count the rhesus choroid-retinal vascular endothelial cells (RF/6A) in fluorescence microscopic images which is based on shape classification, bottleneck detection and accelerated Dijkstra algorithm. The proposed method includes four main steps. First, a thresholding filter and morphological operations are applied to reduce the noise. Second, a shape classifier is used to decide whether a connected component is needed to be segmented. In this step, the AdaBoost classifier is applied with a set of shape features. Third, the bottleneck positions are found based on the contours of the connected components. Finally, the cells segmentation and counting are completed based on the accelerated Dijkstra algorithm with the gradient information between the bottleneck positions. The results show the feasibility and efficiency of the proposed method.

Study of flow behavior in all-vanadium redox flow battery using spatially resolved voltage distribution

NASA Astrophysics Data System (ADS)

Bhattarai, Arjun; Wai, Nyunt; Schweiss, Rüdiger; Whitehead, Adam; Scherer, Günther G.; Ghimire, Purna C.; Nguyen, Tam D.; Hng, Huey Hoon

2017-08-01

Uniform flow distribution through the porous electrodes in a flow battery cell is very important for reducing Ohmic and mass transport polarization. A segmented cell approach can be used to obtain in-situ information on flow behaviour, through the local voltage or current mapping. Lateral flow of current within the thick felts in the flow battery can hamper the interpretation of the data. In this study, a new method of segmenting a conventional flow cell is introduced, which for the first time, splits up both the porous felt as well as the current collector. This dual segmentation results in higher resolution and distinct separation of voltages between flow inlet to outlet. To study the flow behavior for an undivided felt, monitoring the OCV is found to be a reliable method, instead of voltage or current mapping during charging and discharging. Our approach to segmentation is simple and applicable to any size of the cell.

Characteristics of Urban Sidewalks/Streets and Objectively Measured Physical Activity

PubMed Central

Heinrich, Katie M.; Poston, Walker S.C.; Hyder, Melissa; Pyle, Sara

2007-01-01

Several studies have found significant relationships between environmental characteristics (e.g., number of destinations, aesthetics) and physical activity. While a few of these studies verified that the physical activities assessed were performed in the environments examined, none have done this in an urban, neighborhood setting. This information will help efforts to inform policy decisions regarding the design of more “physically active” communities. Fourteen environmental characteristics of 60, 305-m-long segments, located in an urban, residential setting, were directly measured using standardized procedures. The number of individuals walking, jogging, and biking in the segments was assessed using an observation technique. The segments were heterogeneous with regards to several of the environmental characteristics. A total of 473 individuals were seen walking, bicycling, or jogging in the segments during 3,600 min of observation (60 min/segment). Of the 473 seen, 315 were walking, 116 bicycling, and 42 jogging. A greater number of individuals were seen walking in segments with more traffic, sidewalk defects, graffiti, and litter and less desirable property aesthetics. Only one environmental characteristic was associated with bicycling and none were significantly related with jogging. This study provides further evidence that environmental characteristics and walking are related. It also adds new information regarding the importance of scale (e.g., micro, macro) and how some environmental characteristics of urban, residential sidewalks and streets relate to physical activity. PMID:18161026

Volume measurements of individual muscles in human quadriceps femoris using atlas-based segmentation approaches.

PubMed

Le Troter, Arnaud; Fouré, Alexandre; Guye, Maxime; Confort-Gouny, Sylviane; Mattei, Jean-Pierre; Gondin, Julien; Salort-Campana, Emmanuelle; Bendahan, David

2016-04-01

Atlas-based segmentation is a powerful method for automatic structural segmentation of several sub-structures in many organs. However, such an approach has been very scarcely used in the context of muscle segmentation, and so far no study has assessed such a method for the automatic delineation of individual muscles of the quadriceps femoris (QF). In the present study, we have evaluated a fully automated multi-atlas method and a semi-automated single-atlas method for the segmentation and volume quantification of the four muscles of the QF and for the QF as a whole. The study was conducted in 32 young healthy males, using high-resolution magnetic resonance images (MRI) of the thigh. The multi-atlas-based segmentation method was conducted in 25 subjects. Different non-linear registration approaches based on free-form deformable (FFD) and symmetric diffeomorphic normalization algorithms (SyN) were assessed. Optimal parameters of two fusion methods, i.e., STAPLE and STEPS, were determined on the basis of the highest Dice similarity index (DSI) considering manual segmentation (MSeg) as the ground truth. Validation and reproducibility of this pipeline were determined using another MRI dataset recorded in seven healthy male subjects on the basis of additional metrics such as the muscle volume similarity values, intraclass coefficient, and coefficient of variation. Both non-linear registration methods (FFD and SyN) were also evaluated as part of a single-atlas strategy in order to assess longitudinal muscle volume measurements. The multi- and the single-atlas approaches were compared for the segmentation and the volume quantification of the four muscles of the QF and for the QF as a whole. Considering each muscle of the QF, the DSI of the multi-atlas-based approach was high 0.87 ± 0.11 and the best results were obtained with the combination of two deformation fields resulting from the SyN registration method and the STEPS fusion algorithm. The optimal variables for FFD and SyN registration methods were four templates and a kernel standard deviation ranging between 5 and 8. The segmentation process using a single-atlas-based method was more robust with DSI values higher than 0.9. From the vantage of muscle volume measurements, the multi-atlas-based strategy provided acceptable results regarding the QF muscle as a whole but highly variable results regarding individual muscle. On the contrary, the performance of the single-atlas-based pipeline for individual muscles was highly comparable to the MSeg, thereby indicating that this method would be adequate for longitudinal tracking of muscle volume changes in healthy subjects. In the present study, we demonstrated that both multi-atlas and single-atlas approaches were relevant for the segmentation of individual muscles of the QF in healthy subjects. Considering muscle volume measurements, the single-atlas method provided promising perspectives regarding longitudinal quantification of individual muscle volumes.

A New Strategy for Dealing with Social Loafers on the Group Project: The Segment Manager Method

ERIC Educational Resources Information Center

Dommeyer, Curt J.

2012-01-01

Professors often give members of a group project the same grade or they use peer evaluations to provide individualized grades. Unfortunately, both these methods have shortcomings. This article describes the segment manager method (SMM), a method for assigning individualized grades on the group project that does not rely on peer evaluations. A…

Individual tree crown delineation using localized contour tree method and airborne LiDAR data in coniferous forests

NASA Astrophysics Data System (ADS)

Wu, Bin; Yu, Bailang; Wu, Qiusheng; Huang, Yan; Chen, Zuoqi; Wu, Jianping

2016-10-01

Individual tree crown delineation is of great importance for forest inventory and management. The increasing availability of high-resolution airborne light detection and ranging (LiDAR) data makes it possible to delineate the crown structure of individual trees and deduce their geometric properties with high accuracy. In this study, we developed an automated segmentation method that is able to fully utilize high-resolution LiDAR data for detecting, extracting, and characterizing individual tree crowns with a multitude of geometric and topological properties. The proposed approach captures topological structure of forest and quantifies topological relationships of tree crowns by using a graph theory-based localized contour tree method, and finally segments individual tree crowns by analogy of recognizing hills from a topographic map. This approach consists of five key technical components: (1) derivation of canopy height model from airborne LiDAR data; (2) generation of contours based on the canopy height model; (3) extraction of hierarchical structures of tree crowns using the localized contour tree method; (4) delineation of individual tree crowns by segmenting hierarchical crown structure; and (5) calculation of geometric and topological properties of individual trees. We applied our new method to the Medicine Bow National Forest in the southwest of Laramie, Wyoming and the HJ Andrews Experimental Forest in the central portion of the Cascade Range of Oregon, U.S. The results reveal that the overall accuracy of individual tree crown delineation for the two study areas achieved 94.21% and 75.07%, respectively. Our method holds great potential for segmenting individual tree crowns under various forest conditions. Furthermore, the geometric and topological attributes derived from our method provide comprehensive and essential information for forest management.

RNase non-sensitive and endocytosis independent siRNA delivery system: delivery of siRNA into tumor cells and high efficiency induction of apoptosis

NASA Astrophysics Data System (ADS)

Jiang, Xinglu; Wang, Guobao; Liu, Ru; Wang, Yaling; Wang, Yongkui; Qiu, Xiaozhong; Gao, Xueyun

2013-07-01

To date, RNase degradation and endosome/lysosome trapping are still serious problems for siRNA-based molecular therapy, although different kinds of delivery formulations have been tried. In this report, a cell penetrating peptide (CPP, including a positively charged segment, a linear segment, and a hydrophobic segment) and a single wall carbon nanotube (SWCNT) are applied together by a simple method to act as a siRNA delivery system. The siRNAs first form a complex with the positively charged segment of CPP via electrostatic forces, and the siRNA-CPP further coats the surface of the SWCNT via hydrophobic interactions. This siRNA delivery system is non-sensitive to RNase and can avoid endosome/lysosome trapping in vitro. When this siRNA delivery system is studied in Hela cells, siRNA uptake was observed in 98% Hela cells, and over 70% mRNA of mammalian target of rapamycin (mTOR) is knocked down, triggering cell apoptosis on a significant scale. Our siRNA delivery system is easy to handle and benign to cultured cells, providing a very efficient approach for the delivery of siRNA into the cell cytosol and cleaving the target mRNA therein.

SuperSegger: robust image segmentation, analysis and lineage tracking of bacterial cells.

PubMed

Stylianidou, Stella; Brennan, Connor; Nissen, Silas B; Kuwada, Nathan J; Wiggins, Paul A

2016-11-01

Many quantitative cell biology questions require fast yet reliable automated image segmentation to identify and link cells from frame-to-frame, and characterize the cell morphology and fluorescence. We present SuperSegger, an automated MATLAB-based image processing package well-suited to quantitative analysis of high-throughput live-cell fluorescence microscopy of bacterial cells. SuperSegger incorporates machine-learning algorithms to optimize cellular boundaries and automated error resolution to reliably link cells from frame-to-frame. Unlike existing packages, it can reliably segment microcolonies with many cells, facilitating the analysis of cell-cycle dynamics in bacteria as well as cell-contact mediated phenomena. This package has a range of built-in capabilities for characterizing bacterial cells, including the identification of cell division events, mother, daughter and neighbouring cells, and computing statistics on cellular fluorescence, the location and intensity of fluorescent foci. SuperSegger provides a variety of postprocessing data visualization tools for single cell and population level analysis, such as histograms, kymographs, frame mosaics, movies and consensus images. Finally, we demonstrate the power of the package by analyzing lag phase growth with single cell resolution. © 2016 John Wiley & Sons Ltd.

Ferritin trends do not predict changes in total body iron in patients with transfusional iron overload.

PubMed

Puliyel, Mammen; Sposto, Richard; Berdoukas, Vasilios A; Hofstra, Thomas C; Nord, Anne; Carson, Susan; Wood, John; Coates, Thomas D

2014-04-01

Ferritin levels and trends are widely used to manage iron overload and assess the efficacy of prescribed iron chelation in patients with transfusional iron loading. A retrospective cohort study was conducted in 134 patients with transfusion-dependent anemia, over a period of up to 9 years. To determine whether the trends in ferritin adequately reflect the changes in total body iron, changes in ferritin between consecutive liver iron measurements by magnetic resonance imaging (MRI) were compared to changes in liver iron concentrations (LIC), a measure of total body iron. The time period between two consecutive LIC measurements was defined as a segment. Trends in ferritin were considered to predict the change in LIC within a segment if the change in one parameter was less than twofold that of the other, and was in the same direction. Using the exclusion criteria detailed in methods, the trends in ferritin were compared to changes in LIC in 358 segments. An agreement between ferritin trends and LIC changes was found in only 38% of the 358 segments examined. Furthermore, the change in ferritin was in opposite direction to that of LIC in 26% of the segments. Trends in ferritin were a worse predictor of changes in LIC in sickle cell disease than in thalassemia (P < 0.01). While ferritin is a convenient measure of iron status; ferritin trends were unable to predict changes in LIC in individual patients. Ferritin trends need to be interpreted with caution and confirmed by direct measurement of LIC. Copyright © 2013 Wiley Periodicals, Inc.

Synthetic transcripts of double-stranded Birnavirus genome are infectious.

PubMed Central

Mundt, E; Vakharia, V N

1996-01-01

We have developed a system for generation of infectious bursal disease virus (IBDV), a segmented double-stranded RNA virus of the Birnaviridae family, with the use of synthetic transcripts derived from cloned cDNA. Independent full-length cDNA clones were constructed that contained the entire coding and noncoding regions of RNA segments A and B of two distinguishable IBDV strains of serotype I. Segment A encodes all of the structural (VP2, VP4, and VP3) and nonstructural (VP5) proteins, whereas segment B encodes the RNA-dependent RNA polymerase (VP1). Synthetic RNAs of both segments were produced by in vitro transcription of linearized plasmids with T7 RNA polymerase. Transfection of Vero cells with combined plus-sense transcripts of both segments generated infectious virus as early as 36 hr after transfection. The infectivity and specificity of the recovered chimeric virus was ascertained by the appearance of cytopathic effect in chicken embryo cells, by immunofluorescence staining of infected Vero cells with rabbit anti-IBDV serum, and by nucleotide sequence analysis of the recovered virus, respectively. In addition, transfectant viruses containing genetically tagged sequences in either segment A or segment B of IBDV were generated to confirm the feasibility of this system. The development of a reverse genetics system for double-stranded RNA viruses will greatly facilitate studies of the regulation of viral gene expression, pathogenesis, and design of a new generation of live vaccines. Images Fig. 2 Fig. 3 Fig. 4 PMID:8855321

PolNet: A Tool to Quantify Network-Level Cell Polarity and Blood Flow in Vascular Remodeling.

PubMed

Bernabeu, Miguel O; Jones, Martin L; Nash, Rupert W; Pezzarossa, Anna; Coveney, Peter V; Gerhardt, Holger; Franco, Claudio A

2018-05-08

In this article, we present PolNet, an open-source software tool for the study of blood flow and cell-level biological activity during vessel morphogenesis. We provide an image acquisition, segmentation, and analysis protocol to quantify endothelial cell polarity in entire in vivo vascular networks. In combination, we use computational fluid dynamics to characterize the hemodynamics of the vascular networks under study. The tool enables, to our knowledge for the first time, a network-level analysis of polarity and flow for individual endothelial cells. To date, PolNet has proven invaluable for the study of endothelial cell polarization and migration during vascular patterning, as demonstrated by two recent publications. Additionally, the tool can be easily extended to correlate blood flow with other experimental observations at the cellular/molecular level. We release the source code of our tool under the Lesser General Public License. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Polymer mobility in cell walls of cucumber hypocotyls

NASA Technical Reports Server (NTRS)

Fenwick, K. M.; Apperley, D. C.; Cosgrove, D. J.; Jarvis, M. C.

1999-01-01

Cell walls were prepared from the growing region of cucumber (Cucumis sativus) hypocotyls and examined by solid-state 13C NMR spectroscopy, in both enzymically active and inactivated states. The rigidity of individual polymer segments within the hydrated cell walls was assessed from the proton magnetic relaxation parameter, T2, and from the kinetics of cross-polarisation from 1H to 13C. The microfibrils, including most of the xyloglucan in the cell wall, as well as cellulose, behaved as very rigid solids. A minor xyloglucan fraction, which may correspond to cross-links between microfibrils, shared a lower level of rigidity with some of the pectic galacturonan. Other pectins, including most of the galactan side-chain residues of rhamnogalacturonan I, were much more mobile and behaved in a manner intermediate between the solid and liquid states. The only difference observed between the enzymically active and inactive cell walls, was the loss of a highly mobile, methyl-esterified galacturonan fraction, as the result of pectinesterase activity.

Monosomy 21 seen in live born is unlikely to represent true monosomy 21: a case report and review of the literature.

PubMed

Burgess, Trent; Downie, Lilian; Pertile, Mark D; Francis, David; Glass, Melissa; Nouri, Sara; Pszczola, Rosalynn

2014-01-01

We report a case of a neonate who was shown with routine chromosome analysis on peripheral blood lymphocytes to have full monosomy 21. Further investigation on fibroblast cells using conventional chromosome and FISH analysis revealed two additional mosaic cell lines; one is containing a ring chromosome 21 and the other a double ring chromosome 21. In addition, chromosome microarray analysis (CMA) on fibroblasts showed a mosaic duplication of chromosome region 21q11.2q22.13 with approximately 45% of cells showing three copies of the proximal long arm segment, consistent with the presence of a mosaic ring chromosome 21 with ring instability. The CMA also showed complete monosomy for an 8.8 Mb terminal segment (21q22.13q22.3). Whilst this patient had a provisional clinical diagnosis of trisomy 21, the patient also had phenotypic features consistent with monosomy 21, such as prominent epicanthic folds, broad nasal bridge, anteverted nares, simple ears, and bilateral overlapping fifth fingers, features which can also be present in individuals with Down syndrome. The patient died at 4.5 months of age. This case highlights the need for additional studies using multiple tissue types and molecular testing methodologies in patients provisionally diagnosed with monosomy 21, in particular if detected in the neonatal period.

Segmented inlet nozzle for gas turbine, and methods of installation

DOEpatents

Klompas, Nicholas

1985-01-01

A gas turbine nozzle guide vane assembly is formed of individual arcuate nozzle segments. The arcuate nozzle segments are elastically joined to each other to form a complete ring, with edges abutted to prevent leakage. The resultant nozzle ring is included within the overall gas turbine stationary structure and secured by a mounting arrangement which permits relative radial movement at both the inner and outer mountings. A spline-type outer mounting provides circumferential retention. A complete rigid nozzle ring with freedom to "float" radially results. Specific structures are disclosed for the inner and outer mounting arrangements. A specific tie-rod structure is also disclosed for elastically joining the individual nozzle segments. Also disclosed is a method of assembling the nozzle ring subassembly-by-subassembly into a gas turbine employing temporary jacks.

Rescue of compromised lysosomes enhances degradation of photoreceptor outer segments and reduces lipofuscin-like autofluorescence in retinal pigmented epithelial cells.

PubMed

Guha, Sonia; Liu, Ji; Baltazar, Gabe; Laties, Alan M; Mitchell, Claire H

2014-01-01

Healthful cell maintenance requires the efficient degradative processing and removal of waste material. Retinal pigmented epithelial (RPE) cells have the onerous task of degrading both internal cellular debris generated through autophagy as well as phagocytosed photoreceptor outer segments. We propose that the inadequate processing material with the resulting accumulation of cellular waste contributes to the downstream pathologies characterized as age-related macular degeneration (AMD). The lysosomal enzymes responsible for clearance function optimally over a narrow range of acidic pH values; elevation of lysosomal pH by compounds like chloroquine or A2E can impair degradative enzyme activity and lead to a lipofuscin-like autofluorescence. Restoring acidity to the lysosomes of RPE cells can enhance activity of multiple degradative enzymes and is therefore a logical target in early AMD. We have identified several approaches to reacidify lysosomes of compromised RPE cells; stimulation of beta-adrenergic, A2A adenosine and D5 dopamine receptors each lowers lysosomal pH and improves degradation of outer segments. Activation of the CFTR chloride channel also reacidifies lysosomes and increases degradation. These approaches also restore the lysosomal pH of RPE cells from aged ABCA4(-/-) mice with chronically high levels of A2E, suggesting that functional signaling pathways to reacidify lysosomes are retained in aged cells like those in patients with AMD. Acidic nanoparticles transported to RPE lysosomes also lower pH and improve degradation of outer segments. In summary, the ability of diverse approaches to lower lysosomal pH and enhance outer segment degradation support the proposal that lysosomal acidification can prevent the accumulation of lipofuscin-like material in RPE cells.

Comparison of the expressed porcine Vβ and Jβ repertoire of thymocytes and peripheral T cells

PubMed Central

Butler, John E; Wertz, Nancy; Sun, Jishan; Sacco, Randy E

2005-01-01

Transcripts of more than 300 unique T-cell receptor-β (TCR-β) V-D-J rearrangements recovered from porcine thymocytes and peripheral T cells were compared. We identified 19 groups (families) of porcine Vβ genes in seven supergroups and provisionally named 17 groups based on their sequence similarity with recognized human Vβ gene families. TRBV4S, 5S, 7S and 12S accounted for > 80% of all Vβ usage, and usage of these groups by thymocytes and peripheral T cells was highly correlated. No TRBV group was uniquely expressed in significant numbers in thymocytes, although small numbers of TRBV groups 2S, 9S and 15S were only recovered from T cells. Usage of Jβ segments from the 5′ D-J-C duplicon in thymocytes and peripheral T cells directly correlated with their 5′ position in the locus, and Jβ1·1, 1·2 and 1·3 accounted for ≥ 35% of all Jβ usage in both cell types. This contrasts with the usage of Jβ2 segments in that Jβ2·4, 2·5 and 2·7 accounted for ≈ 30% of Jβ usage by T cells and thymocytes. Jβ2·7 was threefold more frequent among T cells than thymocytes. The Vβ/Jβ combination was not random. Jβ1·1 and 1·2 were used in 29% of rearrangements with high frequency among the major Vβ groups. Combinations of TRBV4 and V12 with Jβ2·7 were only found in T cells and accounted for half of all Jβ2·7 usage. These studies show that unlike porcine heavy chain VH genes, the occurrence and relative usage of porcine TCR-Vβ groups resembles that of humans. Thus, highly related gene systems can individually diverge within a species. PMID:15667563

Computational efficient segmentation of cell nuclei in 2D and 3D fluorescent micrographs

NASA Astrophysics Data System (ADS)

De Vylder, Jonas; Philips, Wilfried

2011-02-01

This paper proposes a new segmentation technique developed for the segmentation of cell nuclei in both 2D and 3D fluorescent micrographs. The proposed method can deal with both blurred edges as with touching nuclei. Using a dual scan line algorithm its both memory as computational efficient, making it interesting for the analysis of images coming from high throughput systems or the analysis of 3D microscopic images. Experiments show good results, i.e. recall of over 0.98.

Economic Analysis. Volume V. Course Segments 65-79.

ERIC Educational Resources Information Center

Sterling Inst., Washington, DC. Educational Technology Center.

The fifth volume of the multimedia, individualized course in economic analysis produced for the United States Naval Academy covers segments 65-79 of the course. Included in the volume are discussions of monopoly markets, monopolistic competition, oligopoly markets, and the theory of factor demand and supply. Other segments of the course, the…

Direct Detection of Insertion/Deletion Polymorphisms in an Autosomal Region by Analyzing High-Density Markers in Individual Spermatozoa

PubMed Central

Pramanik, Sreemanta; Li, Honghua

2002-01-01

Direct polymerase chain reaction (PCR) detection of insertion/deletion (indel) polymorphisms requires sample homozygosity. For the indel polymorphisms that have the deletion allele with a relatively low frequency in the autosomal regions, direct PCR detection becomes difficult or impossible. The present study is, to our knowledge, the first designed to directly detect indel polymorphisms in a human autosomal region (i.e., the immunoglobulin VH region), through use of single haploid sperm cells as subjects. Unique marker sequences (n=32), spaced at ∼5-kb intervals, were selected near the 3′ end of the VH region. A two-round multiplex PCR protocol was used to amplify these sequences from single sperm samples from nine unrelated healthy donors. The parental haplotypes of the donors were determined by examining the presence or absence of these markers. Seven clustered markers in 6 of the 18 haplotypes were missing and likely represented a 35–40-kb indel polymorphism. The genotypes of the donors, with respect to this polymorphism, perfectly matched the expectation under Hardy-Weinberg equilibrium. Three VH gene segments, of which two are functional, are affected by this polymorphism. According to these results, >10% of individuals in the human population may not have these gene segments in their genome, and ∼44% may have only one copy of these gene segments. The biological impact of this polymorphism would be very interesting to study. The approach used in the present study could be applied to understand the physical structure and diversity of all other autosomal regions. PMID:12442231

Mapping and characterizing selected canopy tree species at the Angkor World Heritage site in Cambodia using aerial data.

PubMed

Singh, Minerva; Evans, Damian; Tan, Boun Suy; Nin, Chan Samean

2015-01-01

At present, there is very limited information on the ecology, distribution, and structure of Cambodia's tree species to warrant suitable conservation measures. The aim of this study was to assess various methods of analysis of aerial imagery for characterization of the forest mensuration variables (i.e., tree height and crown width) of selected tree species found in the forested region around the temples of Angkor Thom, Cambodia. Object-based image analysis (OBIA) was used (using multiresolution segmentation) to delineate individual tree crowns from very-high-resolution (VHR) aerial imagery and light detection and ranging (LiDAR) data. Crown width and tree height values that were extracted using multiresolution segmentation showed a high level of congruence with field-measured values of the trees (Spearman's rho 0.782 and 0.589, respectively). Individual tree crowns that were delineated from aerial imagery using multiresolution segmentation had a high level of segmentation accuracy (69.22%), whereas tree crowns delineated using watershed segmentation underestimated the field-measured tree crown widths. Both spectral angle mapper (SAM) and maximum likelihood (ML) classifications were applied to the aerial imagery for mapping of selected tree species. The latter was found to be more suitable for tree species classification. Individual tree species were identified with high accuracy. Inclusion of textural information further improved species identification, albeit marginally. Our findings suggest that VHR aerial imagery, in conjunction with OBIA-based segmentation methods (such as multiresolution segmentation) and supervised classification techniques are useful for tree species mapping and for studies of the forest mensuration variables.

Mapping and Characterizing Selected Canopy Tree Species at the Angkor World Heritage Site in Cambodia Using Aerial Data

PubMed Central

Singh, Minerva; Evans, Damian; Tan, Boun Suy; Nin, Chan Samean

2015-01-01

At present, there is very limited information on the ecology, distribution, and structure of Cambodia’s tree species to warrant suitable conservation measures. The aim of this study was to assess various methods of analysis of aerial imagery for characterization of the forest mensuration variables (i.e., tree height and crown width) of selected tree species found in the forested region around the temples of Angkor Thom, Cambodia. Object-based image analysis (OBIA) was used (using multiresolution segmentation) to delineate individual tree crowns from very-high-resolution (VHR) aerial imagery and light detection and ranging (LiDAR) data. Crown width and tree height values that were extracted using multiresolution segmentation showed a high level of congruence with field-measured values of the trees (Spearman’s rho 0.782 and 0.589, respectively). Individual tree crowns that were delineated from aerial imagery using multiresolution segmentation had a high level of segmentation accuracy (69.22%), whereas tree crowns delineated using watershed segmentation underestimated the field-measured tree crown widths. Both spectral angle mapper (SAM) and maximum likelihood (ML) classifications were applied to the aerial imagery for mapping of selected tree species. The latter was found to be more suitable for tree species classification. Individual tree species were identified with high accuracy. Inclusion of textural information further improved species identification, albeit marginally. Our findings suggest that VHR aerial imagery, in conjunction with OBIA-based segmentation methods (such as multiresolution segmentation) and supervised classification techniques are useful for tree species mapping and for studies of the forest mensuration variables. PMID:25902148

Extrusion die and method

DOEpatents

Lipp, G. Daniel

1994-04-26

A method and die apparatus for manufacturing a honeycomb body of rhombic cell cross-section by extrusion through an extrusion die of triangular cell discharge slot configuration, the die incorporating feedholes at selected slot intersections only, such that slot segments communicating directly with the feedholes discharge web material and slot segments not so connected do not discharge web material, whereby a rhombic cell cross-section in the extruded body is provided.

Automated red blood cells extraction from holographic images using fully convolutional neural networks.

PubMed

Yi, Faliu; Moon, Inkyu; Javidi, Bahram

2017-10-01

In this paper, we present two models for automatically extracting red blood cells (RBCs) from RBCs holographic images based on a deep learning fully convolutional neural network (FCN) algorithm. The first model, called FCN-1, only uses the FCN algorithm to carry out RBCs prediction, whereas the second model, called FCN-2, combines the FCN approach with the marker-controlled watershed transform segmentation scheme to achieve RBCs extraction. Both models achieve good segmentation accuracy. In addition, the second model has much better performance in terms of cell separation than traditional segmentation methods. In the proposed methods, the RBCs phase images are first numerically reconstructed from RBCs holograms recorded with off-axis digital holographic microscopy. Then, some RBCs phase images are manually segmented and used as training data to fine-tune the FCN. Finally, each pixel in new input RBCs phase images is predicted into either foreground or background using the trained FCN models. The RBCs prediction result from the first model is the final segmentation result, whereas the result from the second model is used as the internal markers of the marker-controlled transform algorithm for further segmentation. Experimental results show that the given schemes can automatically extract RBCs from RBCs phase images and much better RBCs separation results are obtained when the FCN technique is combined with the marker-controlled watershed segmentation algorithm.

Automated red blood cells extraction from holographic images using fully convolutional neural networks

PubMed Central

Yi, Faliu; Moon, Inkyu; Javidi, Bahram

2017-01-01

In this paper, we present two models for automatically extracting red blood cells (RBCs) from RBCs holographic images based on a deep learning fully convolutional neural network (FCN) algorithm. The first model, called FCN-1, only uses the FCN algorithm to carry out RBCs prediction, whereas the second model, called FCN-2, combines the FCN approach with the marker-controlled watershed transform segmentation scheme to achieve RBCs extraction. Both models achieve good segmentation accuracy. In addition, the second model has much better performance in terms of cell separation than traditional segmentation methods. In the proposed methods, the RBCs phase images are first numerically reconstructed from RBCs holograms recorded with off-axis digital holographic microscopy. Then, some RBCs phase images are manually segmented and used as training data to fine-tune the FCN. Finally, each pixel in new input RBCs phase images is predicted into either foreground or background using the trained FCN models. The RBCs prediction result from the first model is the final segmentation result, whereas the result from the second model is used as the internal markers of the marker-controlled transform algorithm for further segmentation. Experimental results show that the given schemes can automatically extract RBCs from RBCs phase images and much better RBCs separation results are obtained when the FCN technique is combined with the marker-controlled watershed segmentation algorithm. PMID:29082078

Glycolytic reliance promotes anabolism in photoreceptors

PubMed Central

Chinchore, Yashodhan; Begaj, Tedi; Wu, David; Drokhlyansky, Eugene; Cepko, Constance L

2017-01-01

Vertebrate photoreceptors are among the most metabolically active cells, exhibiting a high rate of ATP consumption. This is coupled with a high anabolic demand, necessitated by the diurnal turnover of a specialized membrane-rich organelle, the outer segment, which is the primary site of phototransduction. How photoreceptors balance their catabolic and anabolic demands is poorly understood. Here, we show that rod photoreceptors in mice rely on glycolysis for their outer segment biogenesis. Genetic perturbations targeting allostery or key regulatory nodes in the glycolytic pathway impacted the size of the outer segments. Fibroblast growth factor signaling was found to regulate glycolysis, with antagonism of this pathway resulting in anabolic deficits. These data demonstrate the cell autonomous role of the glycolytic pathway in outer segment maintenance and provide evidence that aerobic glycolysis is part of a metabolic program that supports the biosynthetic needs of a normal neuronal cell type. DOI: http://dx.doi.org/10.7554/eLife.25946.001 PMID:28598329

Functional analysis of rhomboid proteases during Toxoplasma invasion.

PubMed

Shen, Bang; Buguliskis, Jeffrey S; Lee, Tobie D; Sibley, L David

2014-10-21

Host cell invasion by Toxoplasma gondii and other apicomplexan parasites requires transmembrane adhesins that mediate binding to receptors on the substrate and host cell to facilitate motility and invasion. Rhomboid proteases (ROMs) are thought to cleave adhesins within their transmembrane segments, thus allowing the parasite to disengage from receptors and completely enter the host cell. To examine the specific roles of individual ROMs during invasion, we generated single, double, and triple knockouts for the three ROMs expressed in T. gondii tachyzoites. Analysis of these mutants demonstrated that ROM4 is the primary protease involved in adhesin processing and host cell invasion, whereas ROM1 or ROM5 plays negligible roles in these processes. Deletion of ROM4 blocked the shedding of adhesins such as MIC2 (microneme protein 2), causing them to accumulate on the surface of extracellular parasites. Increased surface adhesins led to nonproductive attachment, altered gliding motility, impaired moving junction formation, and reduced invasion efficiency. Despite the importance of ROM4 for efficient invasion, mutants lacking all three ROMs were viable and MIC2 was still efficiently removed from the surface of invaded mutant parasites, implying the existence of ROM-independent mechanisms for adhesin removal during invasion. Collectively, these results suggest that although ROM processing of adhesins is not absolutely essential, it is important for efficient host cell invasion by T. gondii. Importance: Apicomplexan parasites such as Toxoplasma gondii express surface proteins that bind host cell receptors to aid invasion. Many of these adhesins are subject to cleavage by rhomboid proteases (ROMs) within their transmembrane segments during invasion. Previous studies have demonstrated the importance of adhesin cleavage for parasite invasion and proposed that the ROMs responsible for processing would be essential for parasite survival. In T. gondii, ROM5 was thought to be the critical ROM for adhesin shedding due to its robust protease activity in vitro and posterior localization on the parasite surface. Here, we knocked out all three ROMs in T. gondii tachyzoites and found that ROM4, but not ROM5, was key for adhesin cleavage. However, none of the ROMs individually or in combination was essential for cell entry, further emphasizing that essential pathways such as invasion typically rely on redundant pathways to ensure survival. Copyright © 2014 Shen et al.

In-plane structuring of proton exchange membrane fuel cell cathodes: Effect of ionomer equivalent weight structuring on performance and current density distribution

NASA Astrophysics Data System (ADS)

Herden, Susanne; Riewald, Felix; Hirschfeld, Julian A.; Perchthaler, Markus

2017-07-01

Within the active area of a fuel cell inhomogeneous operating conditions occur, however, state of the art electrodes are homogenous over the complete active area. This study uses current density distribution measurements to analyze which ionomer equivalent weight (EW) shows locally the highest current densities. With this information a segmented cathode electrode is manufactured by decal transfer. The segmented electrode shows better performance especially at high current densities compared to homogenous electrodes. Furthermore this segmented catalyst coated membrane (CCM) performs optimal in wet as well as dry conditions, both operating conditions arise in automotive fuel cell applications. Thus, cathode electrodes with an optimized ionomer EW distribution might have a significant impact on future automotive fuel cell development.

A multi-atlas based method for automated anatomical Macaca fascicularis brain MRI segmentation and PET kinetic extraction.

PubMed

Ballanger, Bénédicte; Tremblay, Léon; Sgambato-Faure, Véronique; Beaudoin-Gobert, Maude; Lavenne, Franck; Le Bars, Didier; Costes, Nicolas

2013-08-15

MRI templates and digital atlases are needed for automated and reproducible quantitative analysis of non-human primate PET studies. Segmenting brain images via multiple atlases outperforms single-atlas labelling in humans. We present a set of atlases manually delineated on brain MRI scans of the monkey Macaca fascicularis. We use this multi-atlas dataset to evaluate two automated methods in terms of accuracy, robustness and reliability in segmenting brain structures on MRI and extracting regional PET measures. Twelve individual Macaca fascicularis high-resolution 3DT1 MR images were acquired. Four individual atlases were created by manually drawing 42 anatomical structures, including cortical and sub-cortical structures, white matter regions, and ventricles. To create the MRI template, we first chose one MRI to define a reference space, and then performed a two-step iterative procedure: affine registration of individual MRIs to the reference MRI, followed by averaging of the twelve resampled MRIs. Automated segmentation in native space was obtained in two ways: 1) Maximum probability atlases were created by decision fusion of two to four individual atlases in the reference space, and transformation back into the individual native space (MAXPROB)(.) 2) One to four individual atlases were registered directly to the individual native space, and combined by decision fusion (PROPAG). Accuracy was evaluated by computing the Dice similarity index and the volume difference. The robustness and reproducibility of PET regional measurements obtained via automated segmentation was evaluated on four co-registered MRI/PET datasets, which included test-retest data. Dice indices were always over 0.7 and reached maximal values of 0.9 for PROPAG with all four individual atlases. There was no significant mean volume bias. The standard deviation of the bias decreased significantly when increasing the number of individual atlases. MAXPROB performed better when increasing the number of atlases used. When all four atlases were used for the MAXPROB creation, the accuracy of morphometric segmentation approached that of the PROPAG method. PET measures extracted either via automatic methods or via the manually defined regions were strongly correlated, with no significant regional differences between methods. Intra-class correlation coefficients for test-retest data were over 0.87. Compared to single atlas extractions, multi-atlas methods improve the accuracy of region definition. They also perform comparably to manually defined regions for PET quantification. Multiple atlases of Macaca fascicularis brains are now available and allow reproducible and simplified analyses. Copyright © 2013 Elsevier Inc. All rights reserved.

A semi-Markov model for mitosis segmentation in time-lapse phase contrast microscopy image sequences of stem cell populations.

PubMed

Liu, An-An; Li, Kang; Kanade, Takeo

2012-02-01

We propose a semi-Markov model trained in a max-margin learning framework for mitosis event segmentation in large-scale time-lapse phase contrast microscopy image sequences of stem cell populations. Our method consists of three steps. First, we apply a constrained optimization based microscopy image segmentation method that exploits phase contrast optics to extract candidate subsequences in the input image sequence that contains mitosis events. Then, we apply a max-margin hidden conditional random field (MM-HCRF) classifier learned from human-annotated mitotic and nonmitotic sequences to classify each candidate subsequence as a mitosis or not. Finally, a max-margin semi-Markov model (MM-SMM) trained on manually-segmented mitotic sequences is utilized to reinforce the mitosis classification results, and to further segment each mitosis into four predefined temporal stages. The proposed method outperforms the event-detection CRF model recently reported by Huh as well as several other competing methods in very challenging image sequences of multipolar-shaped C3H10T1/2 mesenchymal stem cells. For mitosis detection, an overall precision of 95.8% and a recall of 88.1% were achieved. For mitosis segmentation, the mean and standard deviation for the localization errors of the start and end points of all mitosis stages were well below 1 and 2 frames, respectively. In particular, an overall temporal location error of 0.73 ± 1.29 frames was achieved for locating daughter cell birth events.

Retinal Layer Abnormalities as Biomarkers of Schizophrenia.

PubMed

Samani, Niraj N; Proudlock, Frank A; Siram, Vasantha; Suraweera, Chathurie; Hutchinson, Claire; Nelson, Christopher P; Al-Uzri, Mohammed; Gottlob, Irene

2018-06-06

Schizophrenia is associated with several brain deficits, as well as visual processing deficits, but clinically useful biomarkers are elusive. We hypothesized that retinal layer changes, noninvasively visualized using spectral-domain optical coherence tomography (SD-OCT), may represent a possible "window" to these abnormalities. A Leica EnvisuTM SD-OCT device was used to obtain high-resolution central foveal B-scans in both eyes of 35 patients with schizophrenia and 50 demographically matched controls. Manual retinal layer segmentation was performed to acquire individual and combined layer thickness measurements in 3 macular regions. Contrast sensitivity was measured at 3 spatial frequencies in a subgroup of each cohort. Differences were compared using adjusted linear models and significantly different layer measures in patients underwent Spearman Rank correlations with contrast sensitivity, quantified symptoms severity, disease duration, and antipsychotic medication dose. Total retinal and photoreceptor complex thickness was reduced in all regions in patients (P < .0001). Segmentation revealed consistent thinning of the outer nuclear layer (P < .001) and inner segment layer (P < .05), as well as a pattern of parafoveal ganglion cell changes. Low spatial frequency contrast sensitivity was reduced in patients (P = .002) and correlated with temporal parafoveal ganglion cell complex thinning (R = .48, P = .01). Negative symptom severity was inversely correlated with foveal photoreceptor complex thickness (R = -.54, P = .001) and outer nuclear layer thickness (R = -.47, P = .005). Our novel findings demonstrate considerable retinal layer abnormalities in schizophrenia that are related to clinical features and visual function. With time, SD-OCT could provide easily-measurable biomarkers to facilitate clinical assessment and further our understanding of the disease.

Segmentation of Vasculature from Fluorescently Labeled Endothelial Cells in Multi-Photon Microscopy Images.

PubMed

Bates, Russell; Irving, Benjamin; Markelc, Bostjan; Kaeppler, Jakob; Brown, Graham; Muschel, Ruth J; Brady, Sir Michael; Grau, Vicente; Schnabel, Julia A

2017-08-09

Vasculature is known to be of key biological significance, especially in the study of tumors. As such, considerable effort has been focused on the automated segmentation of vasculature in medical and pre-clinical images. The majority of vascular segmentation methods focus on bloodpool labeling methods, however, particularly in the study of tumors it is of particular interest to be able to visualize both perfused and non-perfused vasculature. Imaging vasculature by highlighting the endothelium provides a way to separate the morphology of vasculature from the potentially confounding factor of perfusion. Here we present a method for the segmentation of tumor vasculature in 3D fluorescence microscopy images using signals from the endothelial and surrounding cells. We show that our method can provide complete and semantically meaningful segmentations of complex vasculature using a supervoxel-Markov Random Field approach. We show that in terms of extracting meaningful segmentations of the vasculature, our method out-performs both a state-ofthe- art method, specific to these data, as well as more classical vasculature segmentation methods.

Serially connected solid oxide fuel cells having monolithic cores

DOEpatents

Herceg, Joseph E.

1987-01-01

A solid oxide fuel cell for electrochemically combining fuel and oxidant for generating galvanic output, wherein the cell core has an array of cell segments electrically serially connected in the flow direction, each segment consisting of electrolyte walls and interconnect that are substantially devoid of any composite inert materials for support. Instead, the core is monolithic, where each electrolyte wall consists of thin layers of cathode and anode materials sandwiching a thin layer of electrolyte material therebetween. Means direct the fuel to the anode-exposed core passageways and means direct the oxidant to the cathode-exposed core passageways; and means also direct the galvanic output to an exterior circuit. Each layer of the electrolyte composite materials is of the order of 0.002-0.01 cm thick; and each layer of the cathode and anode materials is of the order of 0.002-0.05 cm thick. Between 2 and 50 cell segments may be connected in series.

Segments from red blood cell units should not be used for quality testing.

PubMed

Kurach, Jayme D R; Hansen, Adele L; Turner, Tracey R; Jenkins, Craig; Acker, Jason P

2014-02-01

Nondestructive testing of blood components could permit in-process quality control and reduce discards. Tubing segments, generated during red blood cell (RBC) component production, were tested to determine their suitability as a sample source for quality testing. Leukoreduced RBC components were produced from whole blood (WB) by two different methods: WB filtration and buffy coat (BC). Components and their corresponding segments were tested on Days 5 and 42 of hypothermic storage (HS) for spun hematocrit (Hct), hemoglobin (Hb) content, percentage hemolysis, hematologic indices, and adenosine triphosphate concentration to determine whether segment quality represents unit quality. Segment samples overestimated hemolysis on Days 5 and 42 of HS in both BC- and WB filtration-produced RBCs (p < 0.001 for all). Hct and Hb levels in the segments were also significantly different from the units at both time points for both production methods (p < 0.001 for all). Indeed, for all variables tested different results were obtained from segment and unit samples, and these differences were not consistent across production methods. The quality of samples from tubing segments is not representative of the quality of the corresponding RBC unit. Segments are not suitable surrogates with which to assess RBC quality. © 2013 American Association of Blood Banks.

Iris segmentation using an edge detector based on fuzzy sets theory and cellular learning automata.

PubMed

Ghanizadeh, Afshin; Abarghouei, Amir Atapour; Sinaie, Saman; Saad, Puteh; Shamsuddin, Siti Mariyam

2011-07-01

Iris-based biometric systems identify individuals based on the characteristics of their iris, since they are proven to remain unique for a long time. An iris recognition system includes four phases, the most important of which is preprocessing in which the iris segmentation is performed. The accuracy of an iris biometric system critically depends on the segmentation system. In this paper, an iris segmentation system using edge detection techniques and Hough transforms is presented. The newly proposed edge detection system enhances the performance of the segmentation in a way that it performs much more efficiently than the other conventional iris segmentation methods.

Solar harvesting by a heterostructured cell with built-in variable width quantum wells

NASA Astrophysics Data System (ADS)

Brooks, W.; Wang, H.; Mil'shtein, S.

2018-02-01

We propose cascaded heterostructured p-i-n solar cells, where inside of the i-region is a set of Quantum Wells (QWs) with variable thicknesses to enhance absorption of different photonic energies and provide quick relaxation for high energy carriers. Our p-i-n heterostructure carries top p-type and bottom n-type 11.3 Å thick AlAs layers, which are doped by acceptors and donor densities up to 1019/cm3. The intrinsic region is divided into 10 segments where each segment carries ten QWs of the same width and the width of the QWs in each subsequent segment gradually increases. The top segment consists of 10 QWs with widths of 56.5Å, followed by a segment with 10 wider QWs with widths of 84.75Å, followed by increasing QW widths until the last segment has 10 QWs with widths of 565Å, bringing the total number of QWs to 100. The QW wall height is controlled by alternating AlAs and GaAs layers, where the AlAs layers are all 11.3Å thick, throughout the entire intrinsic region. Configuration of variable width QWs prescribes sets of energy levels which are suitable for absorption of a wide range of photon energies and will dissipate high electron-hole energies rapidly, reducing the heat load on the solar cell. We expect that the heating of the solar cell will be reduced by 8-11%, enhancing efficiency. The efficiency of the designed solar cell is 43.71%, the Fill Factor is 0.86, the density of short circuit current (ISC) will not exceed 338 A/m2 and the open circuit voltage (VOC) is 1.51V.

Reprogramming cells and tissue patterning via bioelectrical pathways: molecular mechanisms and biomedical opportunities.

PubMed

Levin, Michael

2013-01-01

Transformative impact in regenerative medicine requires more than the reprogramming of individual cells: advances in repair strategies for birth defects or injuries, tumor normalization, and the construction of bioengineered organs and tissues all require the ability to control large-scale anatomical shape. Much recent work has focused on the transcriptional and biochemical regulation of cell behavior and morphogenesis. However, exciting new data reveal that bioelectrical properties of cells and their microenvironment exert a profound influence on cell differentiation, proliferation, and migration. Ion channels and pumps expressed in all cells, not just excitable nerve and muscle, establish resting potentials that vary across tissues and change with significant developmental events. Most importantly, the spatiotemporal gradients of these endogenous transmembrane voltage potentials (Vmem ) serve as instructive patterning cues for large-scale anatomy, providing organ identity, positional information, and prepattern template cues for morphogenesis. New genetic and pharmacological techniques for molecular modulation of bioelectric gradients in vivo have revealed the ability to initiate complex organogenesis, change tissue identity, and trigger regeneration of whole vertebrate appendages. A large segment of the spatial information processing that orchestrates individual cells' programs toward the anatomical needs of the host organism is electrical; this blurs the line between memory and decision-making in neural networks and morphogenesis in nonneural tissues. Advances in cracking this bioelectric code will enable the rational reprogramming of shape in whole tissues and organs, revolutionizing regenerative medicine, developmental biology, and synthetic bioengineering. Copyright © 2013 Wiley Periodicals, Inc.

Optimization-based interactive segmentation interface for multiregion problems

PubMed Central

Baxter, John S. H.; Rajchl, Martin; Peters, Terry M.; Chen, Elvis C. S.

2016-01-01

Abstract. Interactive segmentation is becoming of increasing interest to the medical imaging community in that it combines the positive aspects of both manual and automated segmentation. However, general-purpose tools have been lacking in terms of segmenting multiple regions simultaneously with a high degree of coupling between groups of labels. Hierarchical max-flow segmentation has taken advantage of this coupling for individual applications, but until recently, these algorithms were constrained to a particular hierarchy and could not be considered general-purpose. In a generalized form, the hierarchy for any given segmentation problem is specified in run-time, allowing different hierarchies to be quickly explored. We present an interactive segmentation interface, which uses generalized hierarchical max-flow for optimization-based multiregion segmentation guided by user-defined seeds. Applications in cardiac and neonatal brain segmentation are given as example applications of its generality. PMID:27335892

Granular cells in the presence of magnetic field

NASA Astrophysics Data System (ADS)

Jurčák, J.; Lemmerer, B.; van Noort, M.

2017-10-01

We present a statistical study of the dependencies of the shapes and sizes of the photospheric convective cells on the magnetic field properties. This analysis is based on a 2.5 hour long SST observations of active region NOAA 11768. We have blue continuum images taken with a cadence of 5.6 sec that are used for segmentation of individual granules and 270 maps of spectropolarimetric CRISP data allowing us to determine the properties of the magnetic field along with the line-of-sight velocities. The sizes and shapes of the granular cells are dependent on the the magnetic field strength, where the granules tend to be smaller in regions with stronger magnetic field. In the presence of highly inclined magnetic fields, the eccentricity of granules is high and we do not observe symmetric granules in these regions. The mean up-flow velocities in granules as well as the granules intensities decrease with increasing magnetic field strength.

Development and validation of primary human myometrial cell culture models to study pregnancy and labour.

PubMed

Mosher, Andrea A; Rainey, Kelly J; Bolstad, Seunghwa S; Lye, Stephen J; Mitchell, Bryan F; Olson, David M; Wood, Stephen L; Slater, Donna M

2013-01-01

The development of the in vitro cell culture model has greatly facilitated the ability to study gene expression and regulation within human tissues. Within the human uterus, the upper (fundal) segment and the lower segment may provide distinct functions throughout pregnancy and during labour. We have established primary cultured human myometrial cells, isolated from both upper and lower segment regions of the pregnant human uterus, and validated them for the purpose of studying human pregnancy and labour. The specific objectives of this study were to monitor the viability and characterize the expression profile using selected cellular, contractile and pregnancy associated markers in the primary cultured human myometrial cells. Labour has been described as an inflammatory process; therefore, the ability of these cells to respond to an inflammatory stimulus was also investigated. Myometrial cells isolated from paired upper segment (US) and lower segment (LS) biopsies, obtained from women undergoing Caesarean section deliveries at term prior to the onset of labour, were used to identify expression of; α smooth muscle actin, calponin, caldesmon, connexin 43, cyclo-oxygenase-2 (COX-2), oxytocin receptor, tropomyosin and vimentin, by RT-PCR and/or immunocytochemistry. Interleukin (IL)-1β was used to treat cells, subsequently expression of COX-2 mRNA and release of interleukin-8 (CXCL8), were measured. ANOVA followed by Bonferroni's multiple comparisons test was performed. We demonstrate that US and LS human myometrial cells stably express all markers examined to at least passage ten (p10). Connexin 43, COX-2 and vimentin mRNA expression were significantly higher in LS cells compared to US cells. Both cell populations respond to IL-1β, demonstrated by a robust release of CXCL8 and increased expression of COX-2 mRNA from passage one (p1) through to p10. Isolated primary myometrial cells maintain expression of smooth muscle and pregnancy-associated markers and retain their ability to respond to an inflammatory stimulus. These distinct myometrial cell models will provide a useful tool to investigate mechanisms underlying the process of human labour and the concept of functional regionalization of the pregnant uterus.

Diurnal migration of Echinostoma caproni (Digenea: Echinostomatidae) in ICR mice.

PubMed

Platt, Thomas R; Graf, Emily; Kammrath, Anna; Zelmer, Derek A

2010-12-01

Twenty-four female ICR mice, 12 acclimated to a 12 ∶ 12 light-dark cycle and 12 to a 12 ∶ 12 dark-light cycle for 7 days, were each infected with 10 metacercariae of Echinostoma caproni. Infected mice were maintained on their respective lighting regimes for 28 days. Six mice (3 from each group) were necropsied at 4-hr intervals beginning at 0700 hr. The small intestine was removed, opened, and the position of individual worms and worm clusters was measured to the nearest 0.1 cm. Each intestine was subsequently divided into 20 equal segments and individual worms and worm clusters were assigned to the appropriate segment based on the original measurements. All worms were found in the posterior 55% of the intestine (ileum). All posterior segments (10-20), with the exception of segment 18, harbored at least 1 worm at some time. A Monte Carlo simulation of worm abundance in segments 10-17 over all time periods indicated a random distribution, while the same analysis of segments 10-20 indicated a non-random distribution due to large numbers of worms in segment 20 and to the absence of worms in segment 18. To analyze temporal changes in worm distribution, mice were grouped by time of necropsy as follows: night (1900 and 2300 hr), morning (0300 and 0700 hr), and day (1100 and 1500 hr). During the night and morning, E. caproni was heavily concentrated in segments 10-17 and, during the day, worms were located more posteriorly, with a heavy concentration in the last segment (20).

A combined learning algorithm for prostate segmentation on 3D CT images.

PubMed

Ma, Ling; Guo, Rongrong; Zhang, Guoyi; Schuster, David M; Fei, Baowei

2017-11-01

Segmentation of the prostate on CT images has many applications in the diagnosis and treatment of prostate cancer. Because of the low soft-tissue contrast on CT images, prostate segmentation is a challenging task. A learning-based segmentation method is proposed for the prostate on three-dimensional (3D) CT images. We combine population-based and patient-based learning methods for segmenting the prostate on CT images. Population data can provide useful information to guide the segmentation processing. Because of inter-patient variations, patient-specific information is particularly useful to improve the segmentation accuracy for an individual patient. In this study, we combine a population learning method and a patient-specific learning method to improve the robustness of prostate segmentation on CT images. We train a population model based on the data from a group of prostate patients. We also train a patient-specific model based on the data of the individual patient and incorporate the information as marked by the user interaction into the segmentation processing. We calculate the similarity between the two models to obtain applicable population and patient-specific knowledge to compute the likelihood of a pixel belonging to the prostate tissue. A new adaptive threshold method is developed to convert the likelihood image into a binary image of the prostate, and thus complete the segmentation of the gland on CT images. The proposed learning-based segmentation algorithm was validated using 3D CT volumes of 92 patients. All of the CT image volumes were manually segmented independently three times by two, clinically experienced radiologists and the manual segmentation results served as the gold standard for evaluation. The experimental results show that the segmentation method achieved a Dice similarity coefficient of 87.18 ± 2.99%, compared to the manual segmentation. By combining the population learning and patient-specific learning methods, the proposed method is effective for segmenting the prostate on 3D CT images. The prostate CT segmentation method can be used in various applications including volume measurement and treatment planning of the prostate. © 2017 American Association of Physicists in Medicine.

Impact of the accuracy of automatic segmentation of cell nuclei clusters on classification of thyroid follicular lesions.

PubMed

Jung, Chanho; Kim, Changick

2014-08-01

Automatic segmentation of cell nuclei clusters is a key building block in systems for quantitative analysis of microscopy cell images. For that reason, it has received a great attention over the last decade, and diverse automatic approaches to segment clustered nuclei with varying levels of performance under different test conditions have been proposed in literature. To the best of our knowledge, however, so far there is no comparative study on the methods. This study is a first attempt to fill this research gap. More precisely, the purpose of this study is to present an objective performance comparison of existing state-of-the-art segmentation methods. Particularly, the impact of their accuracy on classification of thyroid follicular lesions is also investigated "quantitatively" under the same experimental condition, to evaluate the applicability of the methods. Thirteen different segmentation approaches are compared in terms of not only errors in nuclei segmentation and delineation, but also their impact on the performance of system to classify thyroid follicular lesions using different metrics (e.g., diagnostic accuracy, sensitivity, specificity, etc.). Extensive experiments have been conducted on a total of 204 digitized thyroid biopsy specimens. Our study demonstrates that significant diagnostic errors can be avoided using more advanced segmentation approaches. We believe that this comprehensive comparative study serves as a reference point and guide for developers and practitioners in choosing an appropriate automatic segmentation technique adopted for building automated systems for specifically classifying follicular thyroid lesions. © 2014 International Society for Advancement of Cytometry.

Monitoring Change Through Hierarchical Segmentation of Remotely Sensed Image Data

NASA Technical Reports Server (NTRS)

Tilton, James C.; Lawrence, William T.

2005-01-01

NASA's Goddard Space Flight Center has developed a fast and effective method for generating image segmentation hierarchies. These segmentation hierarchies organize image data in a manner that makes their information content more accessible for analysis. Image segmentation enables analysis through the examination of image regions rather than individual image pixels. In addition, the segmentation hierarchy provides additional analysis clues through the tracing of the behavior of image region characteristics at several levels of segmentation detail. The potential for extracting the information content from imagery data based on segmentation hierarchies has not been fully explored for the benefit of the Earth and space science communities. This paper explores the potential of exploiting these segmentation hierarchies for the analysis of multi-date data sets, and for the particular application of change monitoring.

Segmentation of vessels cluttered with cells using a physics based model.

PubMed

Schmugge, Stephen J; Keller, Steve; Nguyen, Nhat; Souvenir, Richard; Huynh, Toan; Clemens, Mark; Shin, Min C

2008-01-01

Segmentation of vessels in biomedical images is important as it can provide insight into analysis of vascular morphology, topology and is required for kinetic analysis of flow velocity and vessel permeability. Intravital microscopy is a powerful tool as it enables in vivo imaging of both vasculature and circulating cells. However, the analysis of vasculature in those images is difficult due to the presence of cells and their image gradient. In this paper, we provide a novel method of segmenting vessels with a high level of cell related clutter. A set of virtual point pairs ("vessel probes") are moved reacting to forces including Vessel Vector Flow (VVF) and Vessel Boundary Vector Flow (VBVF) forces. Incorporating the cell detection, the VVF force attracts the probes toward the vessel, while the VBVF force attracts the virtual points of the probes to localize the vessel boundary without being distracted by the image features of the cells. The vessel probes are moved according to Newtonian Physics reacting to the net of forces applied on them. We demonstrate the results on a set of five real in vivo images of liver vasculature cluttered by white blood cells. When compared against the ground truth prepared by the technician, the Root Mean Squared Error (RMSE) of segmentation with VVF and VBVF was 55% lower than the method without VVF and VBVF.

DRhoGEF2 and Diaphanous Regulate Contractile Force during Segmental Groove Morphogenesis in the Drosophila Embryo

PubMed Central

Mulinari, Shai; Barmchi, Mojgan Padash

2008-01-01

Morphogenesis of the Drosophila embryo is associated with dynamic rearrangement of the actin cytoskeleton mediated by small GTPases of the Rho family. These GTPases act as molecular switches that are activated by guanine nucleotide exchange factors. One of these factors, DRhoGEF2, plays an important role in the constriction of actin filaments during pole cell formation, blastoderm cellularization, and invagination of the germ layers. Here, we show that DRhoGEF2 is equally important during morphogenesis of segmental grooves, which become apparent as tissue infoldings during mid-embryogenesis. Examination of DRhoGEF2-mutant embryos indicates a role for DRhoGEF2 in the control of cell shape changes during segmental groove morphogenesis. Overexpression of DRhoGEF2 in the ectoderm recruits myosin II to the cell cortex and induces cell contraction. At groove regression, DRhoGEF2 is enriched in cells posterior to the groove that undergo apical constriction, indicating that groove regression is an active process. We further show that the Formin Diaphanous is required for groove formation and strengthens cell junctions in the epidermis. Morphological analysis suggests that Dia regulates cell shape in a way distinct from DRhoGEF2. We propose that DRhoGEF2 acts through Rho1 to regulate acto-myosin constriction but not Diaphanous-mediated F-actin nucleation during segmental groove morphogenesis. PMID:18287521

Pharmacological and histological examinations of regional differences of guinea-pig lung: a role of pleural surface smooth muscle in lung strip contraction.

PubMed Central

Wong, W. S.; Bloomquist, S. L.; Bendele, A. M.; Fleisch, J. H.

1992-01-01

1. Parenchymal lung strip preparations have been widely used as an in vitro model of peripheral airway smooth muscle. The present study examined functional responses of 4 consecutive guinea-pig lung parenchymal strips isolated from the central region (segment 1) to the distal edge (segment 4) of the lower lung lobe. The middle two segments were designated as segments 2 and 3. 2. Lung segments 1 and 4 exhibited significantly greater contraction than the other 2 segments to KCl when responses were expressed as mg force per mg tissue weight. Contractile responses to bronchospastic agents including histamine, carbachol, endothelin-1, leukotrienes (LT) B4 and D4, and the thromboxane A2-mimetic U46619 demonstrated no significant difference in EC50 values among the 4 lung segments. 3. Contractile responses of segments 1 and 4 to antigen-challenge (ovalbumin), ionophore A23187 and substance P were significantly greater than the other 2 segments with respect to either sensitivity or maximum responsiveness. 4. U46619-induced contractions of the 4 lung segments were relaxed in similar manner by papaverine and theophylline up to 100%, salbutamol up to 80%, and sodium nitroprusside by only 20%. In contrast, sodium nitroprusside markedly reversed U46619-induced contraction of pulmonary arterial rings and bronchial rings. 5. Histological studies identified 2-4 layers of smooth muscle cells underlying the lung pleural surface. Mast cells were prominent in this area. Moreover, morphometric studies showed that segment 4 possessed the least amount of smooth muscle structures from bronchial/bronchiolar wall and vasculatures as compared to the other 3 segments, and a significant difference in this respect was evident between segment 1 and segment 4.(ABSTRACT TRUNCATED AT 250 WORDS) Images Figure 1 Figure 6 PMID:1378341

Deciphering the evolutionary history and developmental mechanisms of a complex sexual ornament: the abdominal appendages of Sepsidae (Diptera).

PubMed

Bowsher, Julia H; Ang, Yuchen; Ferderer, Tanner; Meier, Rudolf

2013-04-01

Male abdomen appendages are a novel trait found within Sepsidae (Diptera). Here we demonstrate that they are likely to have evolved once, were lost three times, and then secondarily gained in one lineage. The developmental basis of these appendages was investigated by counting the number of histoblast cells in each abdominal segment in four species: two that represented the initial instance of appendage evolution, one that has secondarily gained appendages, and one species that did not have appendages. Males of all species with appendages have elevated cell counts for the fourth segment, which gives rise to the appendages. In Perochaeta dikowi, which reacquired the trait, the females also have elevated cell count on the fourth segment despite the fact that females do not develop appendages. The species without appendages has similar cell counts in all segments regardless of sex. These results suggest that the basis for appendage development is shared in males across all species, but the sexual dimorphism is regulated differently in P. dikowi. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.

Segmentation and Morphometric Analysis of Cells from Fluorescence Microscopy Images of Cytoskeletons

PubMed Central

Ujihara, Yoshihiro; Nakamura, Masanori; Miyazaki, Hiroshi; Wada, Shigeo

2013-01-01

We developed a method to reconstruct cell geometry from confocal fluorescence microscopy images of the cytoskeleton. In the method, region growing was implemented twice. First, it was applied to the extracellular regions to differentiate them from intracellular noncytoskeletal regions, which both appear black in fluorescence microscopy imagery, and then to cell regions for cell identification. Analysis of morphological parameters revealed significant changes in cell shape associated with cytoskeleton disruption, which offered insight into the mechanical role of the cytoskeleton in maintaining cell shape. The proposed segmentation method is promising for investigations on cell morphological changes with respect to internal cytoskeletal structures. PMID:23762186

Segmentation and morphometric analysis of cells from fluorescence microscopy images of cytoskeletons.

PubMed

Ujihara, Yoshihiro; Nakamura, Masanori; Miyazaki, Hiroshi; Wada, Shigeo

2013-01-01

We developed a method to reconstruct cell geometry from confocal fluorescence microscopy images of the cytoskeleton. In the method, region growing was implemented twice. First, it was applied to the extracellular regions to differentiate them from intracellular noncytoskeletal regions, which both appear black in fluorescence microscopy imagery, and then to cell regions for cell identification. Analysis of morphological parameters revealed significant changes in cell shape associated with cytoskeleton disruption, which offered insight into the mechanical role of the cytoskeleton in maintaining cell shape. The proposed segmentation method is promising for investigations on cell morphological changes with respect to internal cytoskeletal structures.

Constraining eye movement in individuals with Parkinson's disease during walking turns.

PubMed

Ambati, V N Pradeep; Saucedo, Fabricio; Murray, Nicholas G; Powell, Douglas W; Reed-Jones, Rebecca J

2016-10-01

Walking and turning is a movement that places individuals with Parkinson's disease (PD) at increased risk for fall-related injury. However, turning is an essential movement in activities of daily living, making up to 45 % of the total steps taken in a given day. Hypotheses regarding how turning is controlled suggest an essential role of anticipatory eye movements to provide feedforward information for body coordination. However, little research has investigated control of turning in individuals with PD with specific consideration for eye movements. The purpose of this study was to examine eye movement behavior and body segment coordination in individuals with PD during walking turns. Three experimental groups, a group of individuals with PD, a group of healthy young adults (YAC), and a group of healthy older adults (OAC), performed walking and turning tasks under two visual conditions: free gaze and fixed gaze. Whole-body motion capture and eye tracking characterized body segment coordination and eye movement behavior during walking trials. Statistical analysis revealed significant main effects of group (PD, YAC, and OAC) and visual condition (free and fixed gaze) on timing of segment rotation and horizontal eye movement. Within group comparisons, revealed timing of eye and head movement was significantly different between the free and fixed gaze conditions for YAC (p < 0.001) and OAC (p < 0.05), but not for the PD group (p > 0.05). In addition, while intersegment timings (reflecting segment coordination) were significantly different for YAC and OAC during free gaze (p < 0.05), they were not significantly different in PD. These results suggest individuals with PD do not make anticipatory eye and head movements ahead of turning and that this may result in altered segment coordination during turning. As such, eye movements may be an important addition to training programs for those with PD, possibly promoting better coordination during turning and potentially reducing the risk of falls.

Sinu Virus, a Novel and divergent Orthomyxovirus Related to Members of the Genus Thogotovirus, Isolated from Mosquitoes in Colombia

PubMed Central

Contreras-Gutiérrez, María Angélica; Nunes, Marcio R.T.; Guzman, Hilda; Uribe, Sandra; Gómez, Juan Carlos Gallego; Vasco, Juan David Suaza; Cardoso, Jedson F.; Popov, Vsevolod L.; Widen, Steven G.; Wood, Thomas G.; Vasilakis, Nikos; Tesh, Robert B.

2016-01-01

The genome and structural organization of a novel insect-specific orthomyxovirus, designated Sinu virus, is described. Sinu virus (SINUV) was isolated in cultures of C6/36 cells from a pool of mosquitoes collected in northwestern Colombia. The virus has six negative-sense ssRNA segments. Genetic analysis of each segment demonstrated the presence of six distinct ORFs encoding the following genes: PB2 (Segment 1), PB1, (Segment 2), PA protein (Segment 3), envelope GP gene (Segment 4), the NP (Segment 5), and M-like gene (Segment 6). Phylogenetically, SINUV appears to be most closed related to viruses in the genus Thogotovirus. PMID:27936462

Morphology and innervation pattern of the feline urogenital junction.

PubMed

Wrobel, K H; Gürtler, A

2004-12-01

The feline urogenital junction is situated between the extratesticular rete and the spacious initial segments of the efferent ductules. The rete epithelium is cuboidal to low columnar. The rete cells forming the junction rest on a wavy basal lamina, display deep mutual invaginations, possess central nuclei with several infoldings and form a distinct border with the columnar epithelial cells of the initial segments of the ductuli efferentes. The epithelium of the initial segments is composed of ciliated cells and non-ciliated principal cells. The latter are the dominating type and characterized by an apical brush-border and a supranuclear endocytotic apparatus. The stroma of the extratesticular rete contains an abundance of collagen whereas contractile cells are here generally absent. In contrast, the initial segments of the efferent ductules are surrounded by elastic fibres and a layer of contractile cells. All nerves for the feline urogenital junction come from the nervus spermaticus superior. In the epididymal head, small nerve bundles deviate into the septa between the ductules. Single fibres establish a dense network within the muscular coat of the ductuli. At the transition to the extratesticular rete, this network ends abruptly. Nerve fibres in the confines of the rete are associated with blood vessels or proceed to the testicular interior, but establish no relationships with the rete epithelium or the myofibroblasts of the mediastinum. The nervous network in the walls of the efferent ductules and their initial segments is not only composed of sympathetic but also parasympathetic, non-myelinated fibres. Particularly noteworthy is the abundance of calcitonin gene-related peptide (CGRP)- and substance P (SP)-containing axons around the initial segments. Both neuroproteins are consistent markers for sensory neurones. Taken together, it can be assumed that the entry of seminal fluid and spermatozoa into the efferent ductules is controlled by a regulatory nervous chain provided with afferent and efferent components.

Centered reduced moments and associate density functions applied to alkaline comet assay.

PubMed

Castaneda, Roman; Pelaez, Alejandro; Marquez, Maria-Elena; Abad, Pablo

2005-01-01

The single cell gel electrophoresis assay is a sensitive, rapid, and visual technique for deoxyribonucleic acid (DNA) strand-break detection in individual mammalian cells, whose application has significantly increased in the past few years. The cells are embedded in agarose on glass slides followed by lyses of the cell membrane. Thereafter, damaged DNA strands are electrophoresed away from the nucleus towards the anode giving the appearance of a comet tail. Nowadays, charge coupled device cameras are attached at optical microscopes for recording the images of the cells, and digital image processing is applied for obtaining quantitative descriptors. However, the conventional software is usually expensive, inflexible and, in many cases, can only provide low-order descriptors based in image segmentation, determination of centers of mass, and Euclidean distances. Associated density functions and centered reduced moments offer an effective and flexible alternative for quantitative analysis of the comet cells. We will show how the position of the center of mass, the lengths and orientation of the main semiaxes, and the eccentricity of such images can be accurately determined by this method.

Lateral motion and bending of microtubules studied with a new single-filament tracking routine in living cells.

PubMed

Pallavicini, Carla; Levi, Valeria; Wetzler, Diana E; Angiolini, Juan F; Benseñor, Lorena; Despósito, Marcelo A; Bruno, Luciana

2014-06-17

The cytoskeleton is involved in numerous cellular processes such as migration, division, and contraction and provides the tracks for transport driven by molecular motors. Therefore, it is very important to quantify the mechanical behavior of the cytoskeletal filaments to get a better insight into cell mechanics and organization. It has been demonstrated that relevant mechanical properties of microtubules can be extracted from the analysis of their motion and shape fluctuations. However, tracking individual filaments in living cells is extremely complex due, for example, to the high and heterogeneous background. We introduce a believed new tracking algorithm that allows recovering the coordinates of fluorescent microtubules with ∼9 nm precision in in vitro conditions. To illustrate potential applications of this algorithm, we studied the curvature distributions of fluorescent microtubules in living cells. By performing a Fourier analysis of the microtubule shapes, we found that the curvatures followed a thermal-like distribution as previously reported with an effective persistence length of ∼20 μm, a value significantly smaller than that measured in vitro. We also verified that the microtubule-associated protein XTP or the depolymerization of the actin network do not affect this value; however, the disruption of intermediate filaments decreased the persistence length. Also, we recovered trajectories of microtubule segments in actin or intermediate filament-depleted cells, and observed a significant increase of their motion with respect to untreated cells showing that these filaments contribute to the overall organization of the microtubule network. Moreover, the analysis of trajectories of microtubule segments in untreated cells showed that these filaments presented a slower but more directional motion in the cortex with respect to the perinuclear region, and suggests that the tracking routine would allow mapping the microtubule dynamical organization in cells. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

A JOINT FRAMEWORK FOR 4D SEGMENTATION AND ESTIMATION OF SMOOTH TEMPORAL APPEARANCE CHANGES.

PubMed

Gao, Yang; Prastawa, Marcel; Styner, Martin; Piven, Joseph; Gerig, Guido

2014-04-01

Medical imaging studies increasingly use longitudinal images of individual subjects in order to follow-up changes due to development, degeneration, disease progression or efficacy of therapeutic intervention. Repeated image data of individuals are highly correlated, and the strong causality of information over time lead to the development of procedures for joint segmentation of the series of scans, called 4D segmentation. A main aim was improved consistency of quantitative analysis, most often solved via patient-specific atlases. Challenging open problems are contrast changes and occurance of subclasses within tissue as observed in multimodal MRI of infant development, neurodegeneration and disease. This paper proposes a new 4D segmentation framework that enforces continuous dynamic changes of tissue contrast patterns over time as observed in such data. Moreover, our model includes the capability to segment different contrast patterns within a specific tissue class, for example as seen in myelinated and unmyelinated white matter regions in early brain development. Proof of concept is shown with validation on synthetic image data and with 4D segmentation of longitudinal, multimodal pediatric MRI taken at 6, 12 and 24 months of age, but the methodology is generic w.r.t. different application domains using serial imaging.

Robust pulmonary lobe segmentation against incomplete fissures

NASA Astrophysics Data System (ADS)

Gu, Suicheng; Zheng, Qingfeng; Siegfried, Jill; Pu, Jiantao

2012-03-01

As important anatomical landmarks of the human lung, accurate lobe segmentation may be useful for characterizing specific lung diseases (e.g., inflammatory, granulomatous, and neoplastic diseases). A number of investigations showed that pulmonary fissures were often incomplete in image depiction, thereby leading to the computerized identification of individual lobes a challenging task. Our purpose is to develop a fully automated algorithm for accurate identification of individual lobes regardless of the integrity of pulmonary fissures. The underlying idea of the developed lobe segmentation scheme is to use piecewise planes to approximate the detected fissures. After a rotation and a global smoothing, a number of small planes were fitted using local fissures points. The local surfaces are finally combined for lobe segmentation using a quadratic B-spline weighting strategy to assure that the segmentation is smooth. The performance of the developed scheme was assessed by comparing with a manually created reference standard on a dataset of 30 lung CT examinations. These examinations covered a number of lung diseases and were selected from a large chronic obstructive pulmonary disease (COPD) dataset. The results indicate that our scheme of lobe segmentation is efficient and accurate against incomplete fissures.

Public antibodies to malaria antigens generated by two LAIR1 insertion modalities.

PubMed

Pieper, Kathrin; Tan, Joshua; Piccoli, Luca; Foglierini, Mathilde; Barbieri, Sonia; Chen, Yiwei; Silacci-Fregni, Chiara; Wolf, Tobias; Jarrossay, David; Anderle, Marica; Abdi, Abdirahman; Ndungu, Francis M; Doumbo, Ogobara K; Traore, Boubacar; Tran, Tuan M; Jongo, Said; Zenklusen, Isabelle; Crompton, Peter D; Daubenberger, Claudia; Bull, Peter C; Sallusto, Federica; Lanzavecchia, Antonio

2017-08-31

In two previously described donors, the extracellular domain of LAIR1, a collagen-binding inhibitory receptor encoded on chromosome 19 (ref. 1), was inserted between the V and DJ segments of an antibody. This insertion generated, through somatic mutations, broadly reactive antibodies against RIFINs, a type of variant antigen expressed on the surface of Plasmodium falciparum-infected erythrocytes. To investigate how frequently such antibodies are produced in response to malaria infection, we screened plasma from two large cohorts of individuals living in malaria-endemic regions. Here we report that 5-10% of malaria-exposed individuals, but none of the European blood donors tested, have high levels of LAIR1-containing antibodies that dominate the response to infected erythrocytes without conferring enhanced protection against febrile malaria. By analysing the antibody-producing B cell clones at the protein, cDNA and gDNA levels, we characterized additional LAIR1 insertions between the V and DJ segments and discovered a second insertion modality whereby the LAIR1 exon encoding the extracellular domain and flanking intronic sequences are inserted into the switch region. By exon shuffling, this mechanism leads to the production of bispecific antibodies in which the LAIR1 domain is precisely positioned at the elbow between the VH and CH1 domains. Additionally, in one donor the genomic DNA encoding the VH and CH1 domains was deleted, leading to the production of a camel-like LAIR1-containing antibody. Sequencing of the switch regions of memory B cells from European blood donors revealed frequent templated inserts originating from transcribed genes that, in rare cases, comprised exons with orientations and frames compatible with expression. These results reveal different modalities of LAIR1 insertion that lead to public and dominant antibodies against infected erythrocytes and suggest that insertion of templated DNA represents an additional mechanism of antibody diversification that can be selected in the immune response against pathogens and exploited for B cell engineering.

Lineage mapper: A versatile cell and particle tracker

NASA Astrophysics Data System (ADS)

Chalfoun, Joe; Majurski, Michael; Dima, Alden; Halter, Michael; Bhadriraju, Kiran; Brady, Mary

2016-11-01

The ability to accurately track cells and particles from images is critical to many biomedical problems. To address this, we developed Lineage Mapper, an open-source tracker for time-lapse images of biological cells, colonies, and particles. Lineage Mapper tracks objects independently of the segmentation method, detects mitosis in confluence, separates cell clumps mistakenly segmented as a single cell, provides accuracy and scalability even on terabyte-sized datasets, and creates division and/or fusion lineages. Lineage Mapper has been tested and validated on multiple biological and simulated problems. The software is available in ImageJ and Matlab at isg.nist.gov.

Real-Time Three-Dimensional Cell Segmentation in Large-Scale Microscopy Data of Developing Embryos.

PubMed

Stegmaier, Johannes; Amat, Fernando; Lemon, William C; McDole, Katie; Wan, Yinan; Teodoro, George; Mikut, Ralf; Keller, Philipp J

2016-01-25

We present the Real-time Accurate Cell-shape Extractor (RACE), a high-throughput image analysis framework for automated three-dimensional cell segmentation in large-scale images. RACE is 55-330 times faster and 2-5 times more accurate than state-of-the-art methods. We demonstrate the generality of RACE by extracting cell-shape information from entire Drosophila, zebrafish, and mouse embryos imaged with confocal and light-sheet microscopes. Using RACE, we automatically reconstructed cellular-resolution tissue anisotropy maps across developing Drosophila embryos and quantified differences in cell-shape dynamics in wild-type and mutant embryos. We furthermore integrated RACE with our framework for automated cell lineaging and performed joint segmentation and cell tracking in entire Drosophila embryos. RACE processed these terabyte-sized datasets on a single computer within 1.4 days. RACE is easy to use, as it requires adjustment of only three parameters, takes full advantage of state-of-the-art multi-core processors and graphics cards, and is available as open-source software for Windows, Linux, and Mac OS. Copyright © 2016 Elsevier Inc. All rights reserved.

Multistage morphological segmentation of bright-field and fluorescent microscopy images

NASA Astrophysics Data System (ADS)

Korzyńska, A.; Iwanowski, M.

2012-06-01

This paper describes the multistage morphological segmentation method (MSMA) for microscopic cell images. The proposed method enables us to study the cell behaviour by using a sequence of two types of microscopic images: bright field images and/or fluorescent images. The proposed method is based on two types of information: the cell texture coming from the bright field images and intensity of light emission, done by fluorescent markers. The method is dedicated to the image sequences segmentation and it is based on mathematical morphology methods supported by other image processing techniques. The method allows for detecting cells in image independently from a degree of their flattening and from presenting structures which produce the texture. It makes use of some synergic information from the fluorescent light emission image as the support information. The MSMA method has been applied to images acquired during the experiments on neural stem cells as well as to artificial images. In order to validate the method, two types of errors have been considered: the error of cell area detection and the error of cell position using artificial images as the "gold standard".

Recovery of choline oxidase activity by in vitro recombination of individual segments.

PubMed

Heinze, Birgit; Hoven, Nina; O'Connell, Timothy; Maurer, Karl-Heinz; Bartsch, Sebastian; Bornscheuer, Uwe T

2008-11-01

Initial attempts to express a choline oxidase from Arthrobacter pascens (APChO-syn) in Escherichia coli starting from a synthetic gene only led to inactive protein. However, activity was regained by the systematic exchange of individual segments of the gene with segments from a choline oxidase-encoding gene from Arthrobacter globiformis yielding a functional chimeric enzyme. Next, a sequence alignment of the exchanged segment with other choline oxidases revealed a mutation in the APChO-syn, showing that residue 200 was a threonine instead of an asparagine, which is, thus, crucial for confering enzyme activity and, hence, provides an explanation for the initial lack of activity. The active recombinant APChO-syn-T200N variant was biochemically characterized showing an optimum at pH 8.0 and at 37 degrees C. Furthermore, the substrate specificity was examined using N,N-dimethylethanolamine, N-methylethanolamine and 3,3-dimethyl-1-butanol.

Photoreceptor Cells With Profound Structural Deficits Can Support Useful Vision in Mice

PubMed Central

Thompson, Stewart; Blodi, Frederick R.; Lee, Swan; Welder, Chris R.; Mullins, Robert F.; Tucker, Budd A.; Stasheff, Steven F.; Stone, Edwin M.

2014-01-01

Purpose. In animal models of degenerative photoreceptor disease, there has been some success in restoring photoreception by transplanting stem cell–derived photoreceptor cells into the subretinal space. However, only a small proportion of transplanted cells develop extended outer segments, considered critical for photoreceptor cell function. The purpose of this study was to determine whether photoreceptor cells that lack a fully formed outer segment could usefully contribute to vision. Methods. Retinal and visual function was tested in wild-type and Rds mice at 90 days of age (RdsP90). Photoreceptor cells of mice homozygous for the Rds mutation in peripherin 2 never develop a fully formed outer segment. The electroretinogram and multielectrode recording of retinal ganglion cells were used to test retinal responses to light. Three distinct visual behaviors were used to assess visual capabilities: the optokinetic tracking response, the discrimination-based visual water task, and a measure of the effect of vision on wheel running. Results. RdsP90 mice had reduced but measurable electroretinogram responses to light, and exhibited light-evoked responses in multiple types of retinal ganglion cells, the output neurons of the retina. In optokinetic and discrimination-based tests, acuity was measurable but reduced, most notably when contrast was decreased. The wheel running test showed that RdsP90 mice needed 3 log units brighter luminance than wild type to support useful vision (10 cd/m2). Conclusions. Photoreceptors that lack fully formed outer segments can support useful vision. This challenges the idea that normal cellular structure needs to be completely reproduced for transplanted cells to contribute to useful vision. PMID:24569582

Scanning and transmission electron microscopic analysis of ampullary segment of oviduct during estrous cycle in caprines.

PubMed

Sharma, R K; Singh, R; Bhardwaj, J K

2015-01-01

The ampullary segment of the mammalian oviduct provides suitable milieu for fertilization and development of zygote before implantation into uterus. It is, therefore, in the present study, the cyclic changes in the morphology of ampullary segment of goat oviduct were studied during follicular and luteal phases using scanning and transmission electron microscopy techniques. Topographical analysis revealed the presence of uniformly ciliated ampullary epithelia, concealing apical processes of non-ciliated cells along with bulbous secretory cells during follicular phase. The luteal phase was marked with decline in number of ciliated cells with increased occurrence of secretory cells. The ultrastructure analysis has demonstrated the presence of indented nuclear membrane, supranuclear cytoplasm, secretory granules, rough endoplasmic reticulum, large lipid droplets, apically located glycogen masses, oval shaped mitochondria in the secretory cells. The ciliated cells were characterized by the presence of elongated nuclei, abundant smooth endoplasmic reticulum, oval or spherical shaped mitochondria with crecentric cristae during follicular phase. However, in the luteal phase, secretory cells were possessing highly indented nucleus with diffused electron dense chromatin, hyaline nucleosol, increased number of lipid droplets. The ciliated cells had numerous fibrous granules and basal bodies. The parallel use of scanning and transmission electron microscopy techniques has enabled us to examine the cyclic and hormone dependent changes occurring in the topography and fine structure of epithelium of ampullary segment and its cells during different reproductive phases that will be great help in understanding major bottle neck that limits success rate in vitro fertilization and embryo transfer technology. © Wiley Periodicals, Inc.

Automatic classification of atypical lymphoid B cells using digital blood image processing.

PubMed

Alférez, S; Merino, A; Mujica, L E; Ruiz, M; Bigorra, L; Rodellar, J

2014-08-01

There are automated systems for digital peripheral blood (PB) cell analysis, but they operate most effectively in nonpathological blood samples. The objective of this work was to design a methodology to improve the automatic classification of abnormal lymphoid cells. We analyzed 340 digital images of individual lymphoid cells from PB films obtained in the CellaVision DM96:150 chronic lymphocytic leukemia (CLL) cells, 100 hairy cell leukemia (HCL) cells, and 90 normal lymphocytes (N). We implemented the Watershed Transformation to segment the nucleus, the cytoplasm, and the peripheral cell region. We extracted 44 features and then the clustering Fuzzy C-Means (FCM) was applied in two steps for the lymphocyte classification. The images were automatically clustered in three groups, one of them with 98% of the HCL cells. The set of the remaining cells was clustered again using FCM and texture features. The two new groups contained 83.3% of the N cells and 71.3% of the CLL cells, respectively. The approach has been able to automatically classify with high precision three types of lymphoid cells. The addition of more descriptors and other classification techniques will allow extending the classification to other classes of atypical lymphoid cells. © 2013 John Wiley & Sons Ltd.

A motivation-based explanatory model of street drinking among young people.

PubMed

Martín-Santana, Josefa D; Beerli-Palacio, Asunción; Fernández-Monroy, Margarita

2014-01-01

This social marketing study focuses on street drinking behavior among young people. The objective is to divide the market of young people who engage in this activity into segments according to their motivations. For the three segments identified, a behavior model is created using the beliefs, attitudes, behavior, and social belonging of young people who engage in street drinking. The methodology used individual questionnaires filled in by a representative sample of young people. The results show that the behavior model follows the sequence of attitudes-beliefs-behavior and that social belonging influences these three variables. Similarly, differences are observed in the behavior model depending on the segment individuals belong to.

Multi-resolution cell orientation congruence descriptors for epithelium segmentation in endometrial histology images.

PubMed

Li, Guannan; Raza, Shan E Ahmed; Rajpoot, Nasir M

2017-04-01

It has been recently shown that recurrent miscarriage can be caused by abnormally high ratio of number of uterine natural killer (UNK) cells to the number of stromal cells in human female uterus lining. Due to high workload, the counting of UNK and stromal cells needs to be automated using computer algorithms. However, stromal cells are very similar in appearance to epithelial cells which must be excluded in the counting process. To exclude the epithelial cells from the counting process it is necessary to identify epithelial regions. There are two types of epithelial layers that can be encountered in the endometrium: luminal epithelium and glandular epithelium. To the best of our knowledge, there is no existing method that addresses the segmentation of both types of epithelium simultaneously in endometrial histology images. In this paper, we propose a multi-resolution Cell Orientation Congruence (COCo) descriptor which exploits the fact that neighbouring epithelial cells exhibit similarity in terms of their orientations. Our experimental results show that the proposed descriptors yield accurate results in simultaneously segmenting both luminal and glandular epithelium. Copyright © 2017 Elsevier B.V. All rights reserved.

Mammogram segmentation using maximal cell strength updation in cellular automata.

PubMed

Anitha, J; Peter, J Dinesh

2015-08-01

Breast cancer is the most frequently diagnosed type of cancer among women. Mammogram is one of the most effective tools for early detection of the breast cancer. Various computer-aided systems have been introduced to detect the breast cancer from mammogram images. In a computer-aided diagnosis system, detection and segmentation of breast masses from the background tissues is an important issue. In this paper, an automatic segmentation method is proposed to identify and segment the suspicious mass regions of mammogram using a modified transition rule named maximal cell strength updation in cellular automata (CA). In coarse-level segmentation, the proposed method performs an adaptive global thresholding based on the histogram peak analysis to obtain the rough region of interest. An automatic seed point selection is proposed using gray-level co-occurrence matrix-based sum average feature in the coarse segmented image. Finally, the method utilizes CA with the identified initial seed point and the modified transition rule to segment the mass region. The proposed approach is evaluated over the dataset of 70 mammograms with mass from mini-MIAS database. Experimental results show that the proposed approach yields promising results to segment the mass region in the mammograms with the sensitivity of 92.25% and accuracy of 93.48%.

FISH Finder: a high-throughput tool for analyzing FISH images

PubMed Central

Shirley, James W.; Ty, Sereyvathana; Takebayashi, Shin-ichiro; Liu, Xiuwen; Gilbert, David M.

2011-01-01

Motivation: Fluorescence in situ hybridization (FISH) is used to study the organization and the positioning of specific DNA sequences within the cell nucleus. Analyzing the data from FISH images is a tedious process that invokes an element of subjectivity. Automated FISH image analysis offers savings in time as well as gaining the benefit of objective data analysis. While several FISH image analysis software tools have been developed, they often use a threshold-based segmentation algorithm for nucleus segmentation. As fluorescence signal intensities can vary significantly from experiment to experiment, from cell to cell, and within a cell, threshold-based segmentation is inflexible and often insufficient for automatic image analysis, leading to additional manual segmentation and potential subjective bias. To overcome these problems, we developed a graphical software tool called FISH Finder to automatically analyze FISH images that vary significantly. By posing the nucleus segmentation as a classification problem, compound Bayesian classifier is employed so that contextual information is utilized, resulting in reliable classification and boundary extraction. This makes it possible to analyze FISH images efficiently and objectively without adjustment of input parameters. Additionally, FISH Finder was designed to analyze the distances between differentially stained FISH probes. Availability: FISH Finder is a standalone MATLAB application and platform independent software. The program is freely available from: http://code.google.com/p/fishfinder/downloads/list Contact: gilbert@bio.fsu.edu PMID:21310746

Reprogramming cells and tissue patterning via bioelectrical pathways: molecular mechanisms and biomedical opportunities

PubMed Central

Levin, Michael

2013-01-01

Transformative impact in regenerative medicine requires more than the reprogramming of individual cells: advances in repair strategies for birth defects or injuries, tumor normalization, and the construction of bioengineered organs and tissues all require the ability to control large-scale anatomical shape. Much recent work has focused on the transcriptional and biochemical regulation of cell behaviour and morphogenesis. However, exciting new data reveal that bioelectrical properties of cells and their microenvironment exert a profound influence on cell differentiation, proliferation, and migration. Ion channels and pumps expressed in all cells, not just excitable nerve and muscle, establish resting potentials that vary across tissues and change with significant developmental events. Most importantly, the spatio-temporal gradients of these endogenous transmembrane voltage potentials (Vmem) serve as instructive patterning cues for large-scale anatomy, providing organ identity, positional information, and prepattern template cues for morphogenesis. New genetic and pharmacological techniques for molecular modulation of bioelectric gradients in vivo have revealed the ability to initiate complex organogenesis, change tissue identity, and trigger regeneration of whole vertebrate appendages. A large segment of the spatial information processing that orchestrates individual cells’ programs towards the anatomical needs of the host organism is electrical; this blurs the line between memory and decision-making in neural networks and morphogenesis in non-neural tissues. Advances in cracking this bioelectric code will enable the rational reprogramming of shape in whole tissues and organs, revolutionizing regenerative medicine, developmental biology, and synthetic bioengineering. PMID:23897652

Allergic asthma is distinguished by sensitivity of allergen-specific CD4+ T cells and airway structural cells to type 2 inflammation.

PubMed

Cho, Josalyn L; Ling, Morris F; Adams, David C; Faustino, Lucas; Islam, Sabina A; Afshar, Roshi; Griffith, Jason W; Harris, Robert S; Ng, Aylwin; Radicioni, Giorgia; Ford, Amina A; Han, Andre K; Xavier, Ramnik; Kwok, William W; Boucher, Richard; Moon, James J; Hamilos, Daniel L; Kesimer, Mehmet; Suter, Melissa J; Medoff, Benjamin D; Luster, Andrew D

2016-10-05

Despite systemic sensitization, not all allergic individuals develop asthma symptoms upon airborne allergen exposure. Determination of the factors that lead to the asthma phenotype in allergic individuals could guide treatment and identify novel therapeutic targets. We used segmental allergen challenge of allergic asthmatics (AA) and allergic nonasthmatic controls (AC) to determine whether there are differences in the airway immune response or airway structural cells that could drive the development of asthma. Both groups developed prominent allergic airway inflammation in response to allergen. However, asthmatic subjects had markedly higher levels of innate type 2 receptors on allergen-specific CD4 + T cells recruited into the airway. There were also increased levels of type 2 cytokines, increased total mucin, and increased mucin MUC5AC in response to allergen in the airways of AA subjects. Furthermore, type 2 cytokine levels correlated with the mucin response in AA but not AC subjects, suggesting differences in the airway epithelial response to inflammation. Finally, AA subjects had increased airway smooth muscle mass at baseline measured in vivo using novel orientation-resolved optical coherence tomography. Our data demonstrate that the development of allergic asthma is dependent on the responsiveness of allergen-specific CD4 + T cells to innate type 2 mediators as well as increased sensitivity of airway epithelial cells and smooth muscle to type 2 inflammation. Copyright © 2016, American Association for the Advancement of Science.

Regulation of proximal-distal intercalation during limb regeneration in the axolotl (Ambystoma mexicanum).

PubMed

Satoh, Akira; Cummings, Gillian M C; Bryant, Susan V; Gardiner, David M

2010-12-01

Intercalation is the process whereby cells located at the boundary of a wound interact to stimulate proliferation and the restoration of the structures between the boundaries that were lost during wounding. Thus, intercalation is widely considered to be the mechanism of regeneration. When a salamander limb is amputated, the entire cascade of regeneration events is activated, and the missing limb segments and their boundaries (joints) as well as the structures within each segment are regenerated. Therefore, in an amputated limb it is not possible to distinguish between intersegmental regeneration (formation of new segments/joints) and intrasegmental regeneration (formation of structures within a given segment), and it is not possible to study the differential regulation of these two processes. We have used two models for regeneration that allow us to study these two processes independently, and report that inter- and intrasegmental regeneration are different processes regulated by different signaling pathways. New limb segments/joints can be regenerated from cells that dedifferentiate to form blastema cells in response to signaling that is mediated in part by fibroblast growth factor. © 2010 The Authors. Journal compilation © 2010 Japanese Society of Developmental Biologists.

Hybrid video-assisted thoracic surgery with segmental-main bronchial sleeve resection for non-small cell lung cancer.

PubMed

Li, Shuben; Chai, Huiping; Huang, Jun; Zeng, Guangqiao; Shao, Wenlong; He, Jianxing

2014-04-01

The purpose of the current study is to present the clinical and surgical results in patients who underwent hybrid video-assisted thoracic surgery with segmental-main bronchial sleeve resection. Thirty-one patients, 27 men and 4 women, underwent segmental-main bronchial sleeve anastomoses for non-small cell lung cancer between May 2004 and May 2011. Twenty-six (83.9%) patients had squamous cell carcinoma, and 5 patients had adenocarcinoma. Six patients were at stage IIB, 24 patients at stage IIIA, and 1 patient at stage IIIB. Secondary sleeve anastomosis was performed in 18 patients, and Y-shaped multiple sleeve anastomosis was performed in 8 patients. Single segmental bronchiole anastomosis was performed in 5 cases. The average time for chest tube removal was 5.6 days. The average length of hospital stay was 11.8 days. No anastomosis fistula developed in any of the patients. The 1-, 2-, and 3-year survival rates were 83.9%, 71.0%, and 41.9%, respectively. Hybrid video-assisted thoracic surgery with segmental-main bronchial sleeve resection is a complex technique that requires training and experience, but it is an effective and safe operation for selected patients.

Color edges extraction using statistical features and automatic threshold technique: application to the breast cancer cells.

PubMed

Ben Chaabane, Salim; Fnaiech, Farhat

2014-01-23

Color image segmentation has been so far applied in many areas; hence, recently many different techniques have been developed and proposed. In the medical imaging area, the image segmentation may be helpful to provide assistance to doctor in order to follow-up the disease of a certain patient from the breast cancer processed images. The main objective of this work is to rebuild and also to enhance each cell from the three component images provided by an input image. Indeed, from an initial segmentation obtained using the statistical features and histogram threshold techniques, the resulting segmentation may represent accurately the non complete and pasted cells and enhance them. This allows real help to doctors, and consequently, these cells become clear and easy to be counted. A novel method for color edges extraction based on statistical features and automatic threshold is presented. The traditional edge detector, based on the first and the second order neighborhood, describing the relationship between the current pixel and its neighbors, is extended to the statistical domain. Hence, color edges in an image are obtained by combining the statistical features and the automatic threshold techniques. Finally, on the obtained color edges with specific primitive color, a combination rule is used to integrate the edge results over the three color components. Breast cancer cell images were used to evaluate the performance of the proposed method both quantitatively and qualitatively. Hence, a visual and a numerical assessment based on the probability of correct classification (PC), the false classification (Pf), and the classification accuracy (Sens(%)) are presented and compared with existing techniques. The proposed method shows its superiority in the detection of points which really belong to the cells, and also the facility of counting the number of the processed cells. Computer simulations highlight that the proposed method substantially enhances the segmented image with smaller error rates better than other existing algorithms under the same settings (patterns and parameters). Moreover, it provides high classification accuracy, reaching the rate of 97.94%. Additionally, the segmentation method may be extended to other medical imaging types having similar properties.

Anatomical variations in lymphatic drainage of the right lung: applications in lung cancer surgery.

PubMed

Ndiaye, Assane; Di-Marino, V; Ba, P S; Ndiaye, Aï; Gaye, M; Nazarian, S

2016-12-01

To specify the topography and variations in lymphatic drainage of the right lung to the mediastinum and their therapeutic implications in non-small cell lung cancers (NSCLC). We injected a dye into the subpleural lymphatic vessels in 65 right lung segments, followed by dissection in 22 subjects. At the upper lobe, we had injected 32 segments. We noted extrasegmental overflow in one case; extrasegmental and extralobar drainage in two cases; drainage to the lymph nodes of another lobe in one case. Fifty-six percent of the segments drained directly (skipping intrapulmonary and hilar lymph nodes) into the right paratracheal lymph nodes, and one dorsal segment drained into the thoracic duct. A ventral segment drained into the inferior tracheobronchial lymph nodes. A contralateral drainage to the recurrent chain was observed in two cases. Sixteen segments of the middle lobe were injected and mainly drained into the inferior tracheobronchial lymph nodes with six direct paths; one medial segment drained into the right anterior mediastinal chain. We noted three contralateral drainages and eight downward abdominal drainages. Out of the 17 segments of the lower lobe injected, 6 segments drained into the lymph nodes of another lobe, 5 segments showed a direct route to the lower quadrant chains. We noted one time a drainage into the paraesophageal lymph nodes. The variations in lymphatic drainage of the right lung require to carry out systematically a radical mediastinal lymphadenectomy during the removal of non-small cell lung cancers and to associate an adjuvant treatment.

Cell Motility Dynamics: A Novel Segmentation Algorithm to Quantify Multi-Cellular Bright Field Microscopy Images

PubMed Central

Zaritsky, Assaf; Natan, Sari; Horev, Judith; Hecht, Inbal; Wolf, Lior; Ben-Jacob, Eshel; Tsarfaty, Ilan

2011-01-01

Confocal microscopy analysis of fluorescence and morphology is becoming the standard tool in cell biology and molecular imaging. Accurate quantification algorithms are required to enhance the understanding of different biological phenomena. We present a novel approach based on image-segmentation of multi-cellular regions in bright field images demonstrating enhanced quantitative analyses and better understanding of cell motility. We present MultiCellSeg, a segmentation algorithm to separate between multi-cellular and background regions for bright field images, which is based on classification of local patches within an image: a cascade of Support Vector Machines (SVMs) is applied using basic image features. Post processing includes additional classification and graph-cut segmentation to reclassify erroneous regions and refine the segmentation. This approach leads to a parameter-free and robust algorithm. Comparison to an alternative algorithm on wound healing assay images demonstrates its superiority. The proposed approach was used to evaluate common cell migration models such as wound healing and scatter assay. It was applied to quantify the acceleration effect of Hepatocyte growth factor/scatter factor (HGF/SF) on healing rate in a time lapse confocal microscopy wound healing assay and demonstrated that the healing rate is linear in both treated and untreated cells, and that HGF/SF accelerates the healing rate by approximately two-fold. A novel fully automated, accurate, zero-parameters method to classify and score scatter-assay images was developed and demonstrated that multi-cellular texture is an excellent descriptor to measure HGF/SF-induced cell scattering. We show that exploitation of textural information from differential interference contrast (DIC) images on the multi-cellular level can prove beneficial for the analyses of wound healing and scatter assays. The proposed approach is generic and can be used alone or alongside traditional fluorescence single-cell processing to perform objective, accurate quantitative analyses for various biological applications. PMID:22096600

Cell motility dynamics: a novel segmentation algorithm to quantify multi-cellular bright field microscopy images.

PubMed

Zaritsky, Assaf; Natan, Sari; Horev, Judith; Hecht, Inbal; Wolf, Lior; Ben-Jacob, Eshel; Tsarfaty, Ilan

2011-01-01

Confocal microscopy analysis of fluorescence and morphology is becoming the standard tool in cell biology and molecular imaging. Accurate quantification algorithms are required to enhance the understanding of different biological phenomena. We present a novel approach based on image-segmentation of multi-cellular regions in bright field images demonstrating enhanced quantitative analyses and better understanding of cell motility. We present MultiCellSeg, a segmentation algorithm to separate between multi-cellular and background regions for bright field images, which is based on classification of local patches within an image: a cascade of Support Vector Machines (SVMs) is applied using basic image features. Post processing includes additional classification and graph-cut segmentation to reclassify erroneous regions and refine the segmentation. This approach leads to a parameter-free and robust algorithm. Comparison to an alternative algorithm on wound healing assay images demonstrates its superiority. The proposed approach was used to evaluate common cell migration models such as wound healing and scatter assay. It was applied to quantify the acceleration effect of Hepatocyte growth factor/scatter factor (HGF/SF) on healing rate in a time lapse confocal microscopy wound healing assay and demonstrated that the healing rate is linear in both treated and untreated cells, and that HGF/SF accelerates the healing rate by approximately two-fold. A novel fully automated, accurate, zero-parameters method to classify and score scatter-assay images was developed and demonstrated that multi-cellular texture is an excellent descriptor to measure HGF/SF-induced cell scattering. We show that exploitation of textural information from differential interference contrast (DIC) images on the multi-cellular level can prove beneficial for the analyses of wound healing and scatter assays. The proposed approach is generic and can be used alone or alongside traditional fluorescence single-cell processing to perform objective, accurate quantitative analyses for various biological applications.

A cloned DNA segment from the telomeric region of human chromosome 4p is not detectably rearranged in Huntington disease patients

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pritchard, C.; Casher, D.; Myers, R.M.

1990-09-01

Genetic linkage studies have mapped the Huntington disease (HD) mutation to the distal region of the short arm of human chromosome 4. Analysis of recombination events in this region has produced contradictory locations for HD. One possible location is in the region distal to the D4S90 marker, which is located within 300 kilobases of the telomere. Other crossover events predict a more centromeric position for HD. Here the authors analyze the telomeric region of 4p in detail. Cloned DNA segments were derived from this region by utilizing a radiation-induced somatic cell hybrid as a source of DNA combined with preparativemore » pulsed-field gel electrophoresis to enrich for the telmoeric fraction. Additional DNA was obtained by using the cloned segments as multiple start points for cosmid walks. This strategy proved to be an effective method for cloning 250 kilobases of DNA in the region telomeric to D4S90. Hybridization analysis with the cloned DNA did not provide any evidence for the presence of rearrangements of 100 base pairs or greater in the DNA of individuals affected with HD. They also found no charge in the size or structure of the 4p telomere in these samples.« less

A hierarchical 3D segmentation method and the definition of vertebral body coordinate systems for QCT of the lumbar spine.

PubMed

Mastmeyer, André; Engelke, Klaus; Fuchs, Christina; Kalender, Willi A

2006-08-01

We have developed a new hierarchical 3D technique to segment the vertebral bodies in order to measure bone mineral density (BMD) with high trueness and precision in volumetric CT datasets. The hierarchical approach starts with a coarse separation of the individual vertebrae, applies a variety of techniques to segment the vertebral bodies with increasing detail and ends with the definition of an anatomic coordinate system for each vertebral body, relative to which up to 41 trabecular and cortical volumes of interest are positioned. In a pre-segmentation step constraints consisting of Boolean combinations of simple geometric shapes are determined that enclose each individual vertebral body. Bound by these constraints viscous deformable models are used to segment the main shape of the vertebral bodies. Volume growing and morphological operations then capture the fine details of the bone-soft tissue interface. In the volumes of interest bone mineral density and content are determined. In addition, in the segmented vertebral bodies geometric parameters such as volume or the length of the main axes of inertia can be measured. Intra- and inter-operator precision errors of the segmentation procedure were analyzed using existing clinical patient datasets. Results for segmented volume, BMD, and coordinate system position were below 2.0%, 0.6%, and 0.7%, respectively. Trueness was analyzed using phantom scans. The bias of the segmented volume was below 4%; for BMD it was below 1.5%. The long-term goal of this work is improved fracture prediction and patient monitoring in the field of osteoporosis. A true 3D segmentation also enables an accurate measurement of geometrical parameters that may augment the clinical value of a pure BMD analysis.

MITK-based segmentation of co-registered MRI for subject-related regional anesthesia simulation

NASA Astrophysics Data System (ADS)

Teich, Christian; Liao, Wei; Ullrich, Sebastian; Kuhlen, Torsten; Ntouba, Alexandre; Rossaint, Rolf; Ullisch, Marcus; Deserno, Thomas M.

2008-03-01

With a steadily increasing indication, regional anesthesia is still trained directly on the patient. To develop a virtual reality (VR)-based simulation, a patient model is needed containing several tissues, which have to be extracted from individual magnet resonance imaging (MRI) volume datasets. Due to the given modality and the different characteristics of the single tissues, an adequate segmentation can only be achieved by using a combination of segmentation algorithms. In this paper, we present a framework for creating an individual model from MRI scans of the patient. Our work splits in two parts. At first, an easy-to-use and extensible tool for handling the segmentation task on arbitrary datasets is provided. The key idea is to let the user create a segmentation for the given subject by running different processing steps in a purposive order and store them in a segmentation script for reuse on new datasets. For data handling and visualization, we utilize the Medical Imaging Interaction Toolkit (MITK), which is based on the Visualization Toolkit (VTK) and the Insight Segmentation and Registration Toolkit (ITK). The second part is to find suitable segmentation algorithms and respectively parameters for differentiating the tissues required by the RA simulation. For this purpose, a fuzzy c-means clustering algorithm combined with mathematical morphology operators and a geometric active contour-based approach is chosen. The segmentation process itself aims at operating with minimal user interaction, and the gained model fits the requirements of the simulation. First results are shown for both, male and female MRI of the pelvis.

Distribution of immunoglobulin G antibody secretory cells in small intestine of Bactrian camels (Camelus bactrianus).

PubMed

Zhang, Wang-Dong; Wang, Wen-Hui; Jia, Shuai

2015-08-25

To explore the morphological evidence of immunoglobulin G (IgG) participating in intestinal mucosal immunity, 8 healthy adult Bactrian camels used. First, IgG was successfully isolated from their serum and rabbit antibody against Bactrian camels IgG was prepared. The IgG antibody secretory cells (ASCs) in small intestine were particularly observed through immumohistochemical staining, then after were analyzed by statistical methods. The results showed that the IgG ASCs were scattered in the lamina propria (LP) and some of them aggregated around of the intestinal glands. The IgG ASCs density was the highest from middle segment of duodenum to middle segment of jejunum, and then in ended segment of jejunum and initial segment of ileum, the lowest was in initial segment of duodenum, in middle and ended segment of ileum. It was demonstrated that the IgG ASCs mainly scattered in the effector sites of the mucosal immunity, though the density of IgG ASCs was different in different segment of small intestine. Moreover, this scatted distribution characteristic would provide a morphology basis for research whether IgG form a full-protection and immune surveillance in mucosal immunity homeostasis of integral intestine.

A Genealogical Look at Shared Ancestry on the X Chromosome.

PubMed

Buffalo, Vince; Mount, Stephen M; Coop, Graham

2016-09-01

Close relatives can share large segments of their genome identical by descent (IBD) that can be identified in genome-wide polymorphism data sets. There are a range of methods to use these IBD segments to identify relatives and estimate their relationship. These methods have focused on sharing on the autosomes, as they provide a rich source of information about genealogical relationships. We hope to learn additional information about recent ancestry through shared IBD segments on the X chromosome, but currently lack the theoretical framework to use this information fully. Here, we fill this gap by developing probability distributions for the number and length of X chromosome segments shared IBD between an individual and an ancestor k generations back, as well as between half- and full-cousin relationships. Due to the inheritance pattern of the X and the fact that X homologous recombination occurs only in females (outside of the pseudoautosomal regions), the number of females along a genealogical lineage is a key quantity for understanding the number and length of the IBD segments shared among relatives. When inferring relationships among individuals, the number of female ancestors along a genealogical lineage will often be unknown. Therefore, our IBD segment length and number distributions marginalize over this unknown number of recombinational meioses through a distribution of recombinational meioses we derive. By using Bayes' theorem to invert these distributions, we can estimate the number of female ancestors between two relatives, giving us details about the genealogical relations between individuals not possible with autosomal data alone. Copyright © 2016 by the Genetics Society of America.

Reperfusion injury intensifies the adaptive human T cell alloresponse in a human-mouse chimeric artery model.

PubMed

Yi, Tai; Fogal, Birgit; Hao, Zhengrong; Tobiasova, Zuzana; Wang, Chen; Rao, Deepak A; Al-Lamki, Rafia S; Kirkiles-Smith, Nancy C; Kulkarni, Sanjay; Bradley, John R; Bothwell, Alfred L M; Sessa, William C; Tellides, George; Pober, Jordan S

2012-02-01

Perioperative nonimmune injuries to an allograft can decrease graft survival. We have developed a model for studying this process using human materials. Human artery segments were transplanted as infrarenal aortic interposition grafts into an immunodeficient mouse host, allowed to "heal in" for 30 days, and then retransplanted into a second mouse host. To induce a reperfusion injury, the healed-in artery segments were incubated for 3 hours under hypoxic conditions ex vivo before retransplantation. To induce immunologic rejection, the animals receiving the retransplanted artery segment were adoptively transferred with human peripheral blood mononuclear cells or purified T cells from a donor allogeneic to the artery 1 week before surgery. To compare rejection of injured versus healthy tissues, these manipulations were combined. Results were analyzed ex vivo by histology, morphometry, immunohistochemistry, and mRNA quantitation or in vivo by ultrasound. Our results showed that reperfusion injury, which otherwise heals with minimal sequelae, intensifies the degree of allogeneic T cell-mediated injury to human artery segments. We developed a new human-mouse chimeric model demonstrating interactions of reperfusion injury and alloimmunity using human cells and tissues that may be adapted to study other forms of nonimmune injury and other types of adaptive immune responses.

Constraint factor graph cut-based active contour method for automated cellular image segmentation in RNAi screening.

PubMed

Chen, C; Li, H; Zhou, X; Wong, S T C

2008-05-01

Image-based, high throughput genome-wide RNA interference (RNAi) experiments are increasingly carried out to facilitate the understanding of gene functions in intricate biological processes. Automated screening of such experiments generates a large number of images with great variations in image quality, which makes manual analysis unreasonably time-consuming. Therefore, effective techniques for automatic image analysis are urgently needed, in which segmentation is one of the most important steps. This paper proposes a fully automatic method for cells segmentation in genome-wide RNAi screening images. The method consists of two steps: nuclei and cytoplasm segmentation. Nuclei are extracted and labelled to initialize cytoplasm segmentation. Since the quality of RNAi image is rather poor, a novel scale-adaptive steerable filter is designed to enhance the image in order to extract long and thin protrusions on the spiky cells. Then, constraint factor GCBAC method and morphological algorithms are combined to be an integrated method to segment tight clustered cells. Compared with the results obtained by using seeded watershed and the ground truth, that is, manual labelling results by experts in RNAi screening data, our method achieves higher accuracy. Compared with active contour methods, our method consumes much less time. The positive results indicate that the proposed method can be applied in automatic image analysis of multi-channel image screening data.

Speech segmentation in aphasia

PubMed Central

Peñaloza, Claudia; Benetello, Annalisa; Tuomiranta, Leena; Heikius, Ida-Maria; Järvinen, Sonja; Majos, Maria Carmen; Cardona, Pedro; Juncadella, Montserrat; Laine, Matti; Martin, Nadine; Rodríguez-Fornells, Antoni

2017-01-01

Background Speech segmentation is one of the initial and mandatory phases of language learning. Although some people with aphasia have shown a preserved ability to learn novel words, their speech segmentation abilities have not been explored. Aims We examined the ability of individuals with chronic aphasia to segment words from running speech via statistical learning. We also explored the relationships between speech segmentation and aphasia severity, and short-term memory capacity. We further examined the role of lesion location in speech segmentation and short-term memory performance. Methods & Procedures The experimental task was first validated with a group of young adults (n = 120). Participants with chronic aphasia (n = 14) were exposed to an artificial language and were evaluated in their ability to segment words using a speech segmentation test. Their performance was contrasted against chance level and compared to that of a group of elderly matched controls (n = 14) using group and case-by-case analyses. Outcomes & Results As a group, participants with aphasia were significantly above chance level in their ability to segment words from the novel language and did not significantly differ from the group of elderly controls. Speech segmentation ability in the aphasic participants was not associated with aphasia severity although it significantly correlated with word pointing span, a measure of verbal short-term memory. Case-by-case analyses identified four individuals with aphasia who performed above chance level on the speech segmentation task, all with predominantly posterior lesions and mild fluent aphasia. Their short-term memory capacity was also better preserved than in the rest of the group. Conclusions Our findings indicate that speech segmentation via statistical learning can remain functional in people with chronic aphasia and suggest that this initial language learning mechanism is associated with the functionality of the verbal short-term memory system and the integrity of the left inferior frontal region. PMID:28824218

Estimating the weight of crown segments for old-growth Douglas-fir and western hemlock.

Treesearch

J.A. Kendall Snell; Timothy A. Max

1985-01-01

The purpose of this study was to develop and validate estimators to predict total crown weight and weight of any segment of crown for old-growth felled and bucked Douglas-fir and western hemlock trees. Equations were developed for predicting weight of continuous live crown, total live crown, dead crown, any segment of live crown, and individual branches for old-growth...

A fourth order PDE based fuzzy c- means approach for segmentation of microscopic biopsy images in presence of Poisson noise for cancer detection.

PubMed

Kumar, Rajesh; Srivastava, Subodh; Srivastava, Rajeev

2017-07-01

For cancer detection from microscopic biopsy images, image segmentation step used for segmentation of cells and nuclei play an important role. Accuracy of segmentation approach dominate the final results. Also the microscopic biopsy images have intrinsic Poisson noise and if it is present in the image the segmentation results may not be accurate. The objective is to propose an efficient fuzzy c-means based segmentation approach which can also handle the noise present in the image during the segmentation process itself i.e. noise removal and segmentation is combined in one step. To address the above issues, in this paper a fourth order partial differential equation (FPDE) based nonlinear filter adapted to Poisson noise with fuzzy c-means segmentation method is proposed. This approach is capable of effectively handling the segmentation problem of blocky artifacts while achieving good tradeoff between Poisson noise removals and edge preservation of the microscopic biopsy images during segmentation process for cancer detection from cells. The proposed approach is tested on breast cancer microscopic biopsy data set with region of interest (ROI) segmented ground truth images. The microscopic biopsy data set contains 31 benign and 27 malignant images of size 896 × 768. The region of interest selected ground truth of all 58 images are also available for this data set. Finally, the result obtained from proposed approach is compared with the results of popular segmentation algorithms; fuzzy c-means, color k-means, texture based segmentation, and total variation fuzzy c-means approaches. The experimental results shows that proposed approach is providing better results in terms of various performance measures such as Jaccard coefficient, dice index, Tanimoto coefficient, area under curve, accuracy, true positive rate, true negative rate, false positive rate, false negative rate, random index, global consistency error, and variance of information as compared to other segmentation approaches used for cancer detection. Copyright © 2017 Elsevier B.V. All rights reserved.

Robust Segmentation of Overlapping Cells in Histopathology Specimens Using Parallel Seed Detection and Repulsive Level Set

PubMed Central

Qi, Xin; Xing, Fuyong; Foran, David J.; Yang, Lin

2013-01-01

Automated image analysis of histopathology specimens could potentially provide support for early detection and improved characterization of breast cancer. Automated segmentation of the cells comprising imaged tissue microarrays (TMA) is a prerequisite for any subsequent quantitative analysis. Unfortunately, crowding and overlapping of cells present significant challenges for most traditional segmentation algorithms. In this paper, we propose a novel algorithm which can reliably separate touching cells in hematoxylin stained breast TMA specimens which have been acquired using a standard RGB camera. The algorithm is composed of two steps. It begins with a fast, reliable object center localization approach which utilizes single-path voting followed by mean-shift clustering. Next, the contour of each cell is obtained using a level set algorithm based on an interactive model. We compared the experimental results with those reported in the most current literature. Finally, performance was evaluated by comparing the pixel-wise accuracy provided by human experts with that produced by the new automated segmentation algorithm. The method was systematically tested on 234 image patches exhibiting dense overlap and containing more than 2200 cells. It was also tested on whole slide images including blood smears and tissue microarrays containing thousands of cells. Since the voting step of the seed detection algorithm is well suited for parallelization, a parallel version of the algorithm was implemented using graphic processing units (GPU) which resulted in significant speed-up over the C/C++ implementation. PMID:22167559

Motor carrier safety performance profile.

DOT National Transportation Integrated Search

2004-02-01

This report provides a summary of the safety performance of carriers across all the individual segments in the industry. It includes summaries for both for-hire and private carriers in each segment and is drawn from measures that are collected as par...

An objective comparison of cell-tracking algorithms.

PubMed

Ulman, Vladimír; Maška, Martin; Magnusson, Klas E G; Ronneberger, Olaf; Haubold, Carsten; Harder, Nathalie; Matula, Pavel; Matula, Petr; Svoboda, David; Radojevic, Miroslav; Smal, Ihor; Rohr, Karl; Jaldén, Joakim; Blau, Helen M; Dzyubachyk, Oleh; Lelieveldt, Boudewijn; Xiao, Pengdong; Li, Yuexiang; Cho, Siu-Yeung; Dufour, Alexandre C; Olivo-Marin, Jean-Christophe; Reyes-Aldasoro, Constantino C; Solis-Lemus, Jose A; Bensch, Robert; Brox, Thomas; Stegmaier, Johannes; Mikut, Ralf; Wolf, Steffen; Hamprecht, Fred A; Esteves, Tiago; Quelhas, Pedro; Demirel, Ömer; Malmström, Lars; Jug, Florian; Tomancak, Pavel; Meijering, Erik; Muñoz-Barrutia, Arrate; Kozubek, Michal; Ortiz-de-Solorzano, Carlos

2017-12-01

We present a combined report on the results of three editions of the Cell Tracking Challenge, an ongoing initiative aimed at promoting the development and objective evaluation of cell segmentation and tracking algorithms. With 21 participating algorithms and a data repository consisting of 13 data sets from various microscopy modalities, the challenge displays today's state-of-the-art methodology in the field. We analyzed the challenge results using performance measures for segmentation and tracking that rank all participating methods. We also analyzed the performance of all of the algorithms in terms of biological measures and practical usability. Although some methods scored high in all technical aspects, none obtained fully correct solutions. We found that methods that either take prior information into account using learning strategies or analyze cells in a global spatiotemporal video context performed better than other methods under the segmentation and tracking scenarios included in the challenge.

Longitudinal analysis of the peripheral B cell repertoire reveals unique effects of immunization with a new influenza virus strain.

PubMed

Cortina-Ceballos, Bernardo; Godoy-Lozano, Elizabeth Ernestina; Téllez-Sosa, Juan; Ovilla-Muñoz, Marbella; Sámano-Sánchez, Hugo; Aguilar-Salgado, Andrés; Gómez-Barreto, Rosa Elena; Valdovinos-Torres, Humberto; López-Martínez, Irma; Aparicio-Antonio, Rodrigo; Rodríguez, Mario H; Martínez-Barnetche, Jesús

2015-11-25

Despite the potential to produce antibodies that can neutralize different virus (heterotypic neutralization), there is no knowledge of why vaccination against influenza induces protection predominantly against the utilized viral strains (homotypic response). Identification of structural patterns of the B cell repertoire associated to heterotypic neutralization may contribute to identify relevant epitopes for a universal vaccine against influenza. Blood samples were collected from volunteers immunized with 2008/2009 trivalent inactivated vaccine (TIV), pandemic H1N1 (pdmH1N1) monovalent inactivated vaccine (MIV) and the 2014/2015 TIV. Neutralization was assessed by hemagglutination and microneutralization test. IgG V(H) amplicons derived from peripheral blood RNA from pre-immune and 7 days post vaccination were subjected to 454-Roche sequencing. Full reconstruction of the sampled repertoires was done with ImmunediveRsity. The TIV induced a predominantly homotypic neutralizing serologic response, while the 09 MIV induced a heterotypic neutralizing seroconversion in 17% of the individuals. Both the 08/09 and the 14/15 TIV were associated with a reduction in clonotypic diversity, whereas 09 MIV was the opposite. Moreover, TIV and MIV induced distinctive patterns of IGHV segment use that are consistent with B cell selection by conserved antigenic determinants shared by the pre-pandemic and the pandemic strains. However, low somatic hypermutation rates in IgG after 09 MIV immunization, but not after 08/09 and 14/15 TIV immunization were observed. Furthermore, no evidence of the original antigenic sin was found in the same individuals after vaccination with the three vaccines. Immunization with a new influenza virus strain (2009 pdmH1N1) induced unique effects in the peripheral B cell repertoire clonal structure, a stereotyped response involving distinctive IGHV segment use and low somatic hypermutation levels. These parameters were contrastingly different to those observed in response to pre-pandemic and post-pandemic vaccination, and may be the result of clonal selection of common antigenic determinants, as well as germinal center-independent responses that wane as the pandemic strain becomes seasonal. Our findings may contribute in the understanding of the structural and cellular basis required to develop a universal influenza vaccine.

Identification of the Genome Segments of Bluetongue Virus Serotype 26 (Isolate KUW2010/02) that Restrict Replication in a Culicoides sonorensis Cell Line (KC Cells).

PubMed

Pullinger, Gillian D; Guimerà Busquets, Marc; Nomikou, Kyriaki; Boyce, Mark; Attoui, Houssam; Mertens, Peter P

2016-01-01

Bluetongue virus (BTV) can infect most ruminant species and is usually transmitted by adult, vector-competent biting midges (Culicoides spp.). Infection with BTV can cause severe clinical signs and can be fatal, particularly in naïve sheep and some deer species. Although 24 distinct BTV serotypes were recognized for several decades, additional 'types' have recently been identified, including BTV-25 (from Switzerland), BTV-26 (from Kuwait) and BTV-27 from France (Corsica). Although BTV-25 has failed to grow in either insect or mammalian cell cultures, BTV-26 (isolate KUW2010/02), which can be transmitted horizontally between goats in the absence of vector insects, does not replicate in a Culicoides sonorensis cell line (KC cells) but can be propagated in mammalian cells (BSR cells). The BTV genome consists of ten segments of linear dsRNA. Mono-reassortant viruses were generated by reverse-genetics, each one containing a single BTV-26 genome segment in a BTV-1 genetic-background. However, attempts to recover a mono-reassortant containing genome-segment 2 (Seg-2) of BTV-26 (encoding VP2), were unsuccessful but a triple-reassortant was successfully generated containing Seg-2, Seg-6 and Seg-7 (encoding VP5 and VP7 respectively) of BTV-26. Reassortants were recovered and most replicated well in mammalian cells (BSR cells). However, mono-reassortants containing Seg-1 or Seg-3 of BTV-26 (encoding VP1, or VP3 respectively) and the triple reassortant failed to replicate, while a mono-reassortant containing Seg-7 of BTV-26 only replicated slowly in KC cells.

Serially connected solid oxide fuel cells having monolithic cores

DOEpatents

Herceg, J.E.

1985-05-20

Disclosed is a solid oxide fuel cell for electrochemically combining fuel and oxidant for generating galvanic output. The cell core has an array of cell segments electrically serially connected in the flow direction, each segment consisting of electrolyte walls and interconnect that are substantially devoid of any composite inert materials for support. Instead, the core is monolithic, where each electrolyte wall consists of thin layers of cathode and anode materials sandwiching a thin layer of electrolyte material therebetween. Means direct the fuel to the anode-exposed core passageways and means direct the oxidant to the cathode-exposed core passageways; and means also direct the galvanic output to an exterior circuit. Each layer of the electrolyte composite materials is of the order of 0.002 to 0.01 cm thick; and each layer of the cathode and anode materials is of the order of 0.002 to 0.05 cm thick. Between 2 and 50 cell segments may be connected in series.

Automatic choroid cells segmentation and counting based on approximate convexity and concavity of chain code in fluorescence microscopic image

NASA Astrophysics Data System (ADS)

Lu, Weihua; Chen, Xinjian; Zhu, Weifang; Yang, Lei; Cao, Zhaoyuan; Chen, Haoyu

2015-03-01

In this paper, we proposed a method based on the Freeman chain code to segment and count rhesus choroid-retinal vascular endothelial cells (RF/6A) automatically for fluorescence microscopy images. The proposed method consists of four main steps. First, a threshold filter and morphological transform were applied to reduce the noise. Second, the boundary information was used to generate the Freeman chain codes. Third, the concave points were found based on the relationship between the difference of the chain code and the curvature. Finally, cells segmentation and counting were completed based on the characteristics of the number of the concave points, the area and shape of the cells. The proposed method was tested on 100 fluorescence microscopic cell images, and the average true positive rate (TPR) is 98.13% and the average false positive rate (FPR) is 4.47%, respectively. The preliminary results showed the feasibility and efficiency of the proposed method.

Semi-automated Neuron Boundary Detection and Nonbranching Process Segmentation in Electron Microscopy Images

PubMed Central

Jurrus, Elizabeth; Watanabe, Shigeki; Giuly, Richard J.; Paiva, Antonio R. C.; Ellisman, Mark H.; Jorgensen, Erik M.; Tasdizen, Tolga

2013-01-01

Neuroscientists are developing new imaging techniques and generating large volumes of data in an effort to understand the complex structure of the nervous system. The complexity and size of this data makes human interpretation a labor-intensive task. To aid in the analysis, new segmentation techniques for identifying neurons in these feature rich datasets are required. This paper presents a method for neuron boundary detection and nonbranching process segmentation in electron microscopy images and visualizing them in three dimensions. It combines both automated segmentation techniques with a graphical user interface for correction of mistakes in the automated process. The automated process first uses machine learning and image processing techniques to identify neuron membranes that deliniate the cells in each two-dimensional section. To segment nonbranching processes, the cell regions in each two-dimensional section are connected in 3D using correlation of regions between sections. The combination of this method with a graphical user interface specially designed for this purpose, enables users to quickly segment cellular processes in large volumes. PMID:22644867

Semi-Automated Neuron Boundary Detection and Nonbranching Process Segmentation in Electron Microscopy Images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jurrus, Elizabeth R.; Watanabe, Shigeki; Giuly, Richard J.

2013-01-01

Neuroscientists are developing new imaging techniques and generating large volumes of data in an effort to understand the complex structure of the nervous system. The complexity and size of this data makes human interpretation a labor-intensive task. To aid in the analysis, new segmentation techniques for identifying neurons in these feature rich datasets are required. This paper presents a method for neuron boundary detection and nonbranching process segmentation in electron microscopy images and visualizing them in three dimensions. It combines both automated segmentation techniques with a graphical user interface for correction of mistakes in the automated process. The automated processmore » first uses machine learning and image processing techniques to identify neuron membranes that deliniate the cells in each two-dimensional section. To segment nonbranching processes, the cell regions in each two-dimensional section are connected in 3D using correlation of regions between sections. The combination of this method with a graphical user interface specially designed for this purpose, enables users to quickly segment cellular processes in large volumes.« less

A novel multiphoton microscopy images segmentation method based on superpixel and watershed.

PubMed

Wu, Weilin; Lin, Jinyong; Wang, Shu; Li, Yan; Liu, Mingyu; Liu, Gaoqiang; Cai, Jianyong; Chen, Guannan; Chen, Rong

2017-04-01

Multiphoton microscopy (MPM) imaging technique based on two-photon excited fluorescence (TPEF) and second harmonic generation (SHG) shows fantastic performance for biological imaging. The automatic segmentation of cellular architectural properties for biomedical diagnosis based on MPM images is still a challenging issue. A novel multiphoton microscopy images segmentation method based on superpixels and watershed (MSW) is presented here to provide good segmentation results for MPM images. The proposed method uses SLIC superpixels instead of pixels to analyze MPM images for the first time. The superpixels segmentation based on a new distance metric combined with spatial, CIE Lab color space and phase congruency features, divides the images into patches which keep the details of the cell boundaries. Then the superpixels are used to reconstruct new images by defining an average value of superpixels as image pixels intensity level. Finally, the marker-controlled watershed is utilized to segment the cell boundaries from the reconstructed images. Experimental results show that cellular boundaries can be extracted from MPM images by MSW with higher accuracy and robustness. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Automated cell analysis tool for a genome-wide RNAi screen with support vector machine based supervised learning

NASA Astrophysics Data System (ADS)

Remmele, Steffen; Ritzerfeld, Julia; Nickel, Walter; Hesser, Jürgen

2011-03-01

RNAi-based high-throughput microscopy screens have become an important tool in biological sciences in order to decrypt mostly unknown biological functions of human genes. However, manual analysis is impossible for such screens since the amount of image data sets can often be in the hundred thousands. Reliable automated tools are thus required to analyse the fluorescence microscopy image data sets usually containing two or more reaction channels. The herein presented image analysis tool is designed to analyse an RNAi screen investigating the intracellular trafficking and targeting of acylated Src kinases. In this specific screen, a data set consists of three reaction channels and the investigated cells can appear in different phenotypes. The main issue of the image processing task is an automatic cell segmentation which has to be robust and accurate for all different phenotypes and a successive phenotype classification. The cell segmentation is done in two steps by segmenting the cell nuclei first and then using a classifier-enhanced region growing on basis of the cell nuclei to segment the cells. The classification of the cells is realized by a support vector machine which has to be trained manually using supervised learning. Furthermore, the tool is brightness invariant allowing different staining quality and it provides a quality control that copes with typical defects during preparation and acquisition. A first version of the tool has already been successfully applied for an RNAi-screen containing three hundred thousand image data sets and the SVM extended version is designed for additional screens.

PaCeQuant: A Tool for High-Throughput Quantification of Pavement Cell Shape Characteristics1[OPEN

PubMed Central

Poeschl, Yvonne; Plötner, Romina

2017-01-01

Pavement cells (PCs) are the most frequently occurring cell type in the leaf epidermis and play important roles in leaf growth and function. In many plant species, PCs form highly complex jigsaw-puzzle-shaped cells with interlocking lobes. Understanding of their development is of high interest for plant science research because of their importance for leaf growth and hence for plant fitness and crop yield. Studies of PC development, however, are limited, because robust methods are lacking that enable automatic segmentation and quantification of PC shape parameters suitable to reflect their cellular complexity. Here, we present our new ImageJ-based tool, PaCeQuant, which provides a fully automatic image analysis workflow for PC shape quantification. PaCeQuant automatically detects cell boundaries of PCs from confocal input images and enables manual correction of automatic segmentation results or direct import of manually segmented cells. PaCeQuant simultaneously extracts 27 shape features that include global, contour-based, skeleton-based, and PC-specific object descriptors. In addition, we included a method for classification and analysis of lobes at two-cell junctions and three-cell junctions, respectively. We provide an R script for graphical visualization and statistical analysis. We validated PaCeQuant by extensive comparative analysis to manual segmentation and existing quantification tools and demonstrated its usability to analyze PC shape characteristics during development and between different genotypes. PaCeQuant thus provides a platform for robust, efficient, and reproducible quantitative analysis of PC shape characteristics that can easily be applied to study PC development in large data sets. PMID:28931626

Behavior-Dependent Activity and Synaptic Organization of Septo-hippocampal GABAergic Neurons Selectively Targeting the Hippocampal CA3 Area.

PubMed

Joshi, Abhilasha; Salib, Minas; Viney, Tim James; Dupret, David; Somogyi, Peter

2017-12-20

Rhythmic medial septal (MS) GABAergic input coordinates cortical theta oscillations. However, the rules of innervation of cortical cells and regions by diverse septal neurons are unknown. We report a specialized population of septal GABAergic neurons, the Teevra cells, selectively innervating the hippocampal CA3 area bypassing CA1, CA2, and the dentate gyrus. Parvalbumin-immunopositive Teevra cells show the highest rhythmicity among MS neurons and fire with short burst duration (median, 38 ms) preferentially at the trough of both CA1 theta and slow irregular oscillations, coincident with highest hippocampal excitability. Teevra cells synaptically target GABAergic axo-axonic and some CCK interneurons in restricted septo-temporal CA3 segments. The rhythmicity of their firing decreases from septal to temporal termination of individual axons. We hypothesize that Teevra neurons coordinate oscillatory activity across the septo-temporal axis, phasing the firing of specific CA3 interneurons, thereby contributing to the selection of pyramidal cell assemblies at the theta trough via disinhibition. VIDEO ABSTRACT. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

A Lidar Point Cloud Based Procedure for Vertical Canopy Structure Analysis And 3D Single Tree Modelling in Forest

PubMed Central

Wang, Yunsheng; Weinacker, Holger; Koch, Barbara

2008-01-01

A procedure for both vertical canopy structure analysis and 3D single tree modelling based on Lidar point cloud is presented in this paper. The whole area of research is segmented into small study cells by a raster net. For each cell, a normalized point cloud whose point heights represent the absolute heights of the ground objects is generated from the original Lidar raw point cloud. The main tree canopy layers and the height ranges of the layers are detected according to a statistical analysis of the height distribution probability of the normalized raw points. For the 3D modelling of individual trees, individual trees are detected and delineated not only from the top canopy layer but also from the sub canopy layer. The normalized points are resampled into a local voxel space. A series of horizontal 2D projection images at the different height levels are then generated respect to the voxel space. Tree crown regions are detected from the projection images. Individual trees are then extracted by means of a pre-order forest traversal process through all the tree crown regions at the different height levels. Finally, 3D tree crown models of the extracted individual trees are reconstructed. With further analyses on the 3D models of individual tree crowns, important parameters such as crown height range, crown volume and crown contours at the different height levels can be derived. PMID:27879916

Functional delivery of synthetic naked siRNA to the human trabecular meshwork in perfused organ cultures.

PubMed

Comes, Nuria; Borrás, Teresa

2007-08-01

To investigate whether naked short-interfering RNA (siRNA) molecules could be directly delivered to perfused intact human trabecular meshwork (TM) tissue, whether this siRNA could silence a trabecular meshwork preferred gene, and whether it could counteract the downstream effect of a deleterious agent (dexamethasone, DEX) by silencing its receptor. Anterior segments from post-mortem normal human donors were perfused at 3.4+/-0.3 microl/min-constant flow or 15 mmHg-constant pressure to stable baseline (outflow facility, C=0.22+/-0.19 microl/min/mmHg; n=14). Commercial siRNAs were diluted in DMEM (Dulbecco's Modified Eagle's Medium) perfusion medium and used without coupling to transfection reagents ("naked"). Perfusion of Cy3-labeled siRNA was performed at 100 nM for 48 h followed by 24 h with DMEM medium (two pairs). Perfusions of Matrix GLA protein (MGP) siRNA (100 nM; right eye [Oculus Dexter]; OD) and scramble-siRNA (control; left eye [Oculus Sinster]; OS) were performed for 48 h (two pairs). Perfusions of glucocorticoid receptor (GR)-siRNA (OD) and scramble-control (OS) were performed for 48 h and continued by adding 100 nM DEX to the perfusion media for an additional 24 h (two pairs). Frozen sections of labeled anterior segments were analyzed by confocal fluorescence microscopy. Differential expression of GR, MGP, myocilin (MYOC), cornea-derived transcript 6 (CDT6), and 18S genes was determined by reverse-transcriptase TaqMan polymerase chain reacion (RT-TaqMan PCR) on RNA extracted from dissected trabecular meshwork. Primary human trabecular meshwork cells were generated from single individuals and transfected using the nucleofector electroporator with program T-23. Levels of secreted MYOC in the effluents were analyzed by western blot. Histological evaluation of anterior segments perfused with Cy3 labeled siRNA followed by unlabeled medium showed intense fluorescence in the trabecular meshwork region. MGP gene expression was silenced in the trabecular meshwork perfused with naked MGP siRNA. MGP transcripts were reduced 94.7% +/- 0.62 (individual 3) and 93.6% +/- 0.13 (individual 4) from those present in the contralateral eye perfused with the scramble control. Pretreatment of GR siRNA followed by DEX treatment caused a reduction of the MYOC and CDT6 gene expressions when compared with eyes pretreated with scramble-control (percent silencing: 99.3% +/- 0.005 and 97.3% +/- 0.25, respectively, for individual 5 and 98.2% +/- 0.06 and 85.6% +/- 0.88, respectively, for individual 6). Western blots revealed the decrease of MYOC secreted by GR siRNA-treated cell and organ cultures. Readily available siRNA can be delivered to the intact human trabecular meshwork by intracameral perfusion. The delivered naked siRNA is functional, inhibiting not only the targeted gene but also their downstream effectors. This functional intracameral delivery might be of use to protect the trabecular meshwork from unwanted insults and could have important therapeutic applications.

Segmentation and Quantitative Analysis of Epithelial Tissues.

PubMed

Aigouy, Benoit; Umetsu, Daiki; Eaton, Suzanne

2016-01-01

Epithelia are tissues that regulate exchanges with the environment. They are very dynamic and can acquire virtually any shape; at the cellular level, they are composed of cells tightly connected by junctions. Most often epithelia are amenable to live imaging; however, the large number of cells composing an epithelium and the absence of informatics tools dedicated to epithelial analysis largely prevented tissue scale studies. Here we present Tissue Analyzer, a free tool that can be used to segment and analyze epithelial cells and monitor tissue dynamics.

Annual Industrial Capabilities Report to Congress

DTIC Science & Technology

2008-03-01

61 5.1 Aircraft Sector Industrial Summary...basis, key contractor workforce capabilities necessary for successful programs. Industry segment-level baseline assessments ( aircraft ; command, control...monitored representative individual corporate divisions for each major industry segment ( aircraft parts and components, water craft, ground vehicles

Automated analysis of time-lapse fluorescence microscopy images: from live cell images to intracellular foci.

PubMed

Dzyubachyk, Oleh; Essers, Jeroen; van Cappellen, Wiggert A; Baldeyron, Céline; Inagaki, Akiko; Niessen, Wiro J; Meijering, Erik

2010-10-01

Complete, accurate and reproducible analysis of intracellular foci from fluorescence microscopy image sequences of live cells requires full automation of all processing steps involved: cell segmentation and tracking followed by foci segmentation and pattern analysis. Integrated systems for this purpose are lacking. Extending our previous work in cell segmentation and tracking, we developed a new system for performing fully automated analysis of fluorescent foci in single cells. The system was validated by applying it to two common tasks: intracellular foci counting (in DNA damage repair experiments) and cell-phase identification based on foci pattern analysis (in DNA replication experiments). Experimental results show that the system performs comparably to expert human observers. Thus, it may replace tedious manual analyses for the considered tasks, and enables high-content screening. The described system was implemented in MATLAB (The MathWorks, Inc., USA) and compiled to run within the MATLAB environment. The routines together with four sample datasets are available at http://celmia.bigr.nl/. The software is planned for public release, free of charge for non-commercial use, after publication of this article.

Essential roles for lines in mediating leg and antennal proximodistal patterning and generating a stable Notch signaling interface at segment borders.

PubMed

Greenberg, Lina; Hatini, Victor

2009-06-01

The Drosophila leg imaginal disc provides a paradigm with which to understand the fundamental developmental mechanisms that generate an intricate appendage structure. Leg formation depends on the subdivision of the leg proximodistal (PD) axis into broad domains by the leg gap genes. The leg gap genes act combinatorially to initiate the expression of the Notch ligands Delta (Dl) and Serrate (Ser) in a segmental pattern. Dl and Ser induce the expression of a set of transcriptional regulators along the segment border, which mediate leg segment growth and joint morphogenesis. Here we show that Lines accumulates in nuclei in the presumptive tarsus and the inter-joints of proximal leg segments and governs the formation of these structures by destabilizing the nuclear protein Bowl. Across the presumptive tarsus, lines modulates the opposing expression landscapes of the leg gap gene dachshund (dac) and the tarsal PD genes, bric-a-brac 2 (bab), apterous (ap) and BarH1 (Bar). In this manner, lines inhibits proximal tarsal fates and promotes medial and distal tarsal fates. Across proximal leg segments, lines antagonizes bowl to promote Dl expression by relief-of-repression. In turn, Dl signals asymmetrically to stabilize Bowl in adjacent distal cells. Bowl, then, acts cell-autonomously, together with one or more redundant factors, to repress Dl expression. Together, lines and bowl act as a binary switch to generate a stable Notch signaling interface between Dl-expressing cells and adjacent distal cell. lines plays analogous roles in developing antennae, which are serially homologous to legs, suggesting evolutionarily conserved roles for lines in ventral appendage formation.

Creation of Mice Bearing a Partial Duplication of HPRT Gene Marked with a GFP Gene and Detection of Revertant Cells In Situ as GFP-Positive Somatic Cells.

PubMed

Noda, Asao; Suemori, Hirofumi; Hirai, Yuko; Hamasaki, Kanya; Kodama, Yoshiaki; Mitani, Hiroshi; Landes, Reid D; Nakamura, Nori

2015-01-01

It is becoming clear that apparently normal somatic cells accumulate mutations. Such accumulations or propagations of mutant cells are thought to be related to certain diseases such as cancer. To better understand the nature of somatic mutations, we developed a mouse model that enables in vivo detection of rare genetically altered cells via GFP positive cells. The mouse model carries a partial duplication of 3' portion of X-chromosomal HPRT gene and a GFP gene at the end of the last exon. In addition, although HPRT gene expression was thought ubiquitous, the expression level was found insufficient in vivo to make the revertant cells detectable by GFP positivity. To overcome the problem, we replaced the natural HPRT-gene promoter with a CAG promoter. In such animals, termed HPRT-dup-GFP mouse, losing one duplicated segment by crossover between the two sister chromatids or within a single molecule of DNA reactivates gene function, producing hybrid HPRT-GFP proteins which, in turn, cause the revertant cells to be detected as GFP-positive cells in various tissues. Frequencies of green mutant cells were measured using fixed and frozen sections (liver and pancreas), fixed whole mount (small intestine), or by means of flow cytometry (unfixed splenocytes). The results showed that the frequencies varied extensively among individuals as well as among tissues. X-ray exposure (3 Gy) increased the frequency moderately (~2 times) in the liver and small intestine. Further, in two animals out of 278 examined, some solid tissues showed too many GFP-positive cells to score (termed extreme jackpot mutation). Present results illustrated a complex nature of somatic mutations occurring in vivo. While the HPRT-dup-GFP mouse may have a potential for detecting tissue-specific environmental mutagens, large inter-individual variations of mutant cell frequency cause the results unstable and hence have to be reduced. This future challenge will likely involve lowering the background mutation frequency, thus reducing inter-individual variation.

Differences in neural crest sensitivity to ethanol account for the infrequency of anterior segment defects in the eye compared with craniofacial anomalies in a zebrafish model of fetal alcohol syndrome.

PubMed

Eason, Jessica; Williams, Antionette L; Chawla, Bahaar; Apsey, Christian; Bohnsack, Brenda L

2017-09-01

Ethanol (ETOH) exposure during pregnancy is associated with craniofacial and neurologic abnormalities, but infrequently disrupts the anterior segment of the eye. In these studies, we used zebrafish to investigate differences in the teratogenic effect of ETOH on craniofacial, periocular, and ocular neural crest. Zebrafish eye and neural crest development was analyzed by means of live imaging, TUNEL (terminal deoxynucleotidyl transferase dUTP nick end labeling) assay, immunostaining, detection of reactive oxygen species, and in situ hybridization. Our studies demonstrated that foxd3-positive neural crest cells in the periocular mesenchyme and developing eye were less sensitive to ETOH than sox10-positive craniofacial neural crest cells that form the pharyngeal arches and jaw. ETOH increased apoptosis in the retina, but did not affect survival of periocular and ocular neural crest cells. ETOH also did not increase reactive oxygen species within the eye. In contrast, ETOH increased ventral neural crest apoptosis and reactive oxygen species production in the facial mesenchyme. In the eye and craniofacial region, sod2 showed high levels of expression in the anterior segment and in the setting of Sod2 knockdown, low levels of ETOH decreased migration of foxd3-positive neural crest cells into the developing eye. However, ETOH had minimal effect on the periocular and ocular expression of transcription factors (pitx2 and foxc1) that regulate anterior segment development. Neural crest cells contributing to the anterior segment of the eye exhibit increased ability to withstand ETOH-induced oxidative stress and apoptosis. These studies explain the rarity of anterior segment dysgenesis despite the frequent craniofacial abnormalities in fetal alcohol syndrome. Birth Defects Research 109:1212-1227, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Predicting Future Morphological Changes of Lesions from Radiotracer Uptake in 18F-FDG-PET Images

PubMed Central

Bagci, Ulas; Yao, Jianhua; Miller-Jaster, Kirsten; Chen, Xinjian; Mollura, Daniel J.

2013-01-01

We introduce a novel computational framework to enable automated identification of texture and shape features of lesions on 18F-FDG-PET images through a graph-based image segmentation method. The proposed framework predicts future morphological changes of lesions with high accuracy. The presented methodology has several benefits over conventional qualitative and semi-quantitative methods, due to its fully quantitative nature and high accuracy in each step of (i) detection, (ii) segmentation, and (iii) feature extraction. To evaluate our proposed computational framework, thirty patients received 2 18F-FDG-PET scans (60 scans total), at two different time points. Metastatic papillary renal cell carcinoma, cerebellar hemongioblastoma, non-small cell lung cancer, neurofibroma, lymphomatoid granulomatosis, lung neoplasm, neuroendocrine tumor, soft tissue thoracic mass, nonnecrotizing granulomatous inflammation, renal cell carcinoma with papillary and cystic features, diffuse large B-cell lymphoma, metastatic alveolar soft part sarcoma, and small cell lung cancer were included in this analysis. The radiotracer accumulation in patients' scans was automatically detected and segmented by the proposed segmentation algorithm. Delineated regions were used to extract shape and textural features, with the proposed adaptive feature extraction framework, as well as standardized uptake values (SUV) of uptake regions, to conduct a broad quantitative analysis. Evaluation of segmentation results indicates that our proposed segmentation algorithm has a mean dice similarity coefficient of 85.75±1.75%. We found that 28 of 68 extracted imaging features were correlated well with SUVmax (p<0.05), and some of the textural features (such as entropy and maximum probability) were superior in predicting morphological changes of radiotracer uptake regions longitudinally, compared to single intensity feature such as SUVmax. We also found that integrating textural features with SUV measurements significantly improves the prediction accuracy of morphological changes (Spearman correlation coefficient = 0.8715, p<2e-16). PMID:23431398

Model-Based Segmentation of Cortical Regions of Interest for Multi-subject Analysis of fMRI Data

NASA Astrophysics Data System (ADS)

Engel, Karin; Brechmann, Andr'e.; Toennies, Klaus

The high inter-subject variability of human neuroanatomy complicates the analysis of functional imaging data across subjects. We propose a method for the correct segmentation of cortical regions of interest based on the cortical surface. First results on the segmentation of Heschl's gyrus indicate the capability of our approach for correct comparison of functional activations in relation to individual cortical patterns.

A fully automated cell segmentation and morphometric parameter system for quantifying corneal endothelial cell morphology.

PubMed

Al-Fahdawi, Shumoos; Qahwaji, Rami; Al-Waisy, Alaa S; Ipson, Stanley; Ferdousi, Maryam; Malik, Rayaz A; Brahma, Arun

2018-07-01

Corneal endothelial cell abnormalities may be associated with a number of corneal and systemic diseases. Damage to the endothelial cells can significantly affect corneal transparency by altering hydration of the corneal stroma, which can lead to irreversible endothelial cell pathology requiring corneal transplantation. To date, quantitative analysis of endothelial cell abnormalities has been manually performed by ophthalmologists using time consuming and highly subjective semi-automatic tools, which require an operator interaction. We developed and applied a fully-automated and real-time system, termed the Corneal Endothelium Analysis System (CEAS) for the segmentation and computation of endothelial cells in images of the human cornea obtained by in vivo corneal confocal microscopy. First, a Fast Fourier Transform (FFT) Band-pass filter is applied to reduce noise and enhance the image quality to make the cells more visible. Secondly, endothelial cell boundaries are detected using watershed transformations and Voronoi tessellations to accurately quantify the morphological parameters of the human corneal endothelial cells. The performance of the automated segmentation system was tested against manually traced ground-truth images based on a database consisting of 40 corneal confocal endothelial cell images in terms of segmentation accuracy and obtained clinical features. In addition, the robustness and efficiency of the proposed CEAS system were compared with manually obtained cell densities using a separate database of 40 images from controls (n = 11), obese subjects (n = 16) and patients with diabetes (n = 13). The Pearson correlation coefficient between automated and manual endothelial cell densities is 0.9 (p < 0.0001) and a Bland-Altman plot shows that 95% of the data are between the 2SD agreement lines. We demonstrate the effectiveness and robustness of the CEAS system, and the possibility of utilizing it in a real world clinical setting to enable rapid diagnosis and for patient follow-up, with an execution time of only 6 seconds per image. Copyright © 2018 Elsevier B.V. All rights reserved.

Superpixel guided active contour segmentation of retinal layers in OCT volumes

NASA Astrophysics Data System (ADS)

Bai, Fangliang; Gibson, Stuart J.; Marques, Manuel J.; Podoleanu, Adrian

2018-03-01

Retinal OCT image segmentation is a precursor to subsequent medical diagnosis by a clinician or machine learning algorithm. In the last decade, many algorithms have been proposed to detect retinal layer boundaries and simplify the image representation. Inspired by the recent success of superpixel methods for pre-processing natural images, we present a novel framework for segmentation of retinal layers in OCT volume data. In our framework, the region of interest (e.g. the fovea) is located using an adaptive-curve method. The cell layer boundaries are then robustly detected firstly using 1D superpixels, applied to A-scans, and then fitting active contours in B-scan images. Thereafter the 3D cell layer surfaces are efficiently segmented from the volume data. The framework was tested on healthy eye data and we show that it is capable of segmenting up to 12 layers. The experimental results imply the effectiveness of proposed method and indicate its robustness to low image resolution and intrinsic speckle noise.

Notochord segmentation may lay down the pathway for the development of the vertebral bodies in the Atlantic salmon.

PubMed

Grotmol, Sindre; Kryvi, Harald; Nordvik, Kari; Totland, Geir K

2003-12-01

This study indicates that the development of the vertebrae in the Atlantic salmon requires the orchestration of two sources of metameric patterning, derived from the notochord and the somite rows, respectively. Before segmentation of the salmon notochord, chordoblasts exhibit a well-defined cell axis that is uniformly aligned with the cranio-caudal axis. The morphology of these cells is characterised by a foot-like basal projection that rests on the notochordal sheath. Notochordal segments are initially formed within the chordoblast layer by metameric change in the axial orientation of groups of chordoblasts. This process results in the formation of circular bands of chordoblasts, with feet perpendicular to the cranio-caudal axis, the original chordoblast orientation. Each vertebra is defined by two such chordoblast bands, at the cranial and caudal borders, respectively. Formation of the chordoblast segments closely precedes formation of the chordacentra, which form as calcified rings within the adjacent notochordal sheath. Sclerotomal osteoblasts then differentiate on the surface of the chordacentra, using them as foundations for further vertebral growth. Thus, the morphogenesis of the rudiments of the vertebral bodies is initiated by a generation of segments within the chordoblast layer. This dual segmentation model for salmon, in which the segmental patterns of the neural and haemal arches are somite-derived, while the vertebral segments seem to be notochord-derived, contrasts with current models for avians and mammals.

Automated intraretinal layer segmentation of optical coherence tomography images using graph-theoretical methods

NASA Astrophysics Data System (ADS)

Roy, Priyanka; Gholami, Peyman; Kuppuswamy Parthasarathy, Mohana; Zelek, John; Lakshminarayanan, Vasudevan

2018-02-01

Segmentation of spectral-domain Optical Coherence Tomography (SD-OCT) images facilitates visualization and quantification of sub-retinal layers for diagnosis of retinal pathologies. However, manual segmentation is subjective, expertise dependent, and time-consuming, which limits applicability of SD-OCT. Efforts are therefore being made to implement active-contours, artificial intelligence, and graph-search to automatically segment retinal layers with accuracy comparable to that of manual segmentation, to ease clinical decision-making. Although, low optical contrast, heavy speckle noise, and pathologies pose challenges to automated segmentation. Graph-based image segmentation approach stands out from the rest because of its ability to minimize the cost function while maximising the flow. This study has developed and implemented a shortest-path based graph-search algorithm for automated intraretinal layer segmentation of SD-OCT images. The algorithm estimates the minimal-weight path between two graph-nodes based on their gradients. Boundary position indices (BPI) are computed from the transition between pixel intensities. The mean difference between BPIs of two consecutive layers quantify individual layer thicknesses, which shows statistically insignificant differences when compared to a previous study [for overall retina: p = 0.17, for individual layers: p > 0.05 (except one layer: p = 0.04)]. These results substantiate the accurate delineation of seven intraretinal boundaries in SD-OCT images by this algorithm, with a mean computation time of 0.93 seconds (64-bit Windows10, core i5, 8GB RAM). Besides being self-reliant for denoising, the algorithm is further computationally optimized to restrict segmentation within the user defined region-of-interest. The efficiency and reliability of this algorithm, even in noisy image conditions, makes it clinically applicable.

Development of the caudal exoskeleton of the pliomerid trilobite Hintzeia plicamarginis new species

USGS Publications Warehouse

Simpson, A.G.; Hughes, N.C.; Kopaska-Merkel, D. C.; Ludvigsen, R.

2005-01-01

The later juvenile ontogeny of the caudal plate of the early Ordovician pliomerid trilobite Hintzeia plicamarginis new species likely comprised an initial phase during which the rate of appearance of new segments subterminally exceeded that of segment release into the thorax, a short phase of constant segment numbers, and a later phase during which release occurred but in which no new segments appeared. A distinct terminal region became manifest in the second phase. During the second and third phases growth coefficients for individual segments were about 1.1-1.2 per instar. Although the shapes of segments varied during growth, the pattern of ontogenetic shape change appears to have been broadly similar among segments. This suggests an homonomous trunk segment morphology regardless of thoracic or caudal identity in maturity. These results imply that control of trunk exoskeletal segment appearance and articulation were decoupled in this trilobite, and that the terminal region had a distinct mature morphology. H. plicamarginis is described as a new species. ?? Blackwell Publishing, Inc.

Validation of simplified centre of mass models during gait in individuals with chronic stroke.

PubMed

Huntley, Andrew H; Schinkel-Ivy, Alison; Aqui, Anthony; Mansfield, Avril

2017-10-01

The feasibility of using a multiple segment (full-body) kinematic model in clinical gait assessment is difficult when considering obstacles such as time and cost constraints. While simplified gait models have been explored in healthy individuals, no such work to date has been conducted in a stroke population. The aim of this study was to quantify the errors of simplified kinematic models for chronic stroke gait assessment. Sixteen individuals with chronic stroke (>6months), outfitted with full body kinematic markers, performed a series of gait trials. Three centre of mass models were computed: (i) 13-segment whole-body model, (ii) 3 segment head-trunk-pelvis model, and (iii) 1 segment pelvis model. Root mean squared error differences were compared between models, along with correlations to measures of stroke severity. Error differences revealed that, while both models were similar in the mediolateral direction, the head-trunk-pelvis model had less error in the anteroposterior direction and the pelvis model had less error in the vertical direction. There was some evidence that the head-trunk-pelvis model error is influenced in the mediolateral direction for individuals with more severe strokes, as a few significant correlations were observed between the head-trunk-pelvis model and measures of stroke severity. These findings demonstrate the utility and robustness of the pelvis model for clinical gait assessment in individuals with chronic stroke. Low error in the mediolateral and vertical directions is especially important when considering potential stability analyses during gait for this population, as lateral stability has been previously linked to fall risk. Copyright © 2017 Elsevier Ltd. All rights reserved.

Statistical modelling of subdiffusive dynamics in the cytoplasm of living cells: A FARIMA approach

NASA Astrophysics Data System (ADS)

Burnecki, K.; Muszkieta, M.; Sikora, G.; Weron, A.

2012-04-01

Golding and Cox (Phys. Rev. Lett., 96 (2006) 098102) tracked the motion of individual fluorescently labelled mRNA molecules inside live E. coli cells. They found that in the set of 23 trajectories from 3 different experiments, the automatically recognized motion is subdiffusive and published an intriguing microscopy video. Here, we extract the corresponding time series from this video by image segmentation method and present its detailed statistical analysis. We find that this trajectory was not included in the data set already studied and has different statistical properties. It is best fitted by a fractional autoregressive integrated moving average (FARIMA) process with the normal-inverse Gaussian (NIG) noise and the negative memory. In contrast to earlier studies, this shows that the fractional Brownian motion is not the best model for the dynamics documented in this video.

Extracting Fluorescent Reporter Time Courses of Cell Lineages from High-Throughput Microscopy at Low Temporal Resolution

PubMed Central

Downey, Mike J.; Jeziorska, Danuta M.; Ott, Sascha; Tamai, T. Katherine; Koentges, Georgy; Vance, Keith W.; Bretschneider, Till

2011-01-01

The extraction of fluorescence time course data is a major bottleneck in high-throughput live-cell microscopy. Here we present an extendible framework based on the open-source image analysis software ImageJ, which aims in particular at analyzing the expression of fluorescent reporters through cell divisions. The ability to track individual cell lineages is essential for the analysis of gene regulatory factors involved in the control of cell fate and identity decisions. In our approach, cell nuclei are identified using Hoechst, and a characteristic drop in Hoechst fluorescence helps to detect dividing cells. We first compare the efficiency and accuracy of different segmentation methods and then present a statistical scoring algorithm for cell tracking, which draws on the combination of various features, such as nuclear intensity, area or shape, and importantly, dynamic changes thereof. Principal component analysis is used to determine the most significant features, and a global parameter search is performed to determine the weighting of individual features. Our algorithm has been optimized to cope with large cell movements, and we were able to semi-automatically extract cell trajectories across three cell generations. Based on the MTrackJ plugin for ImageJ, we have developed tools to efficiently validate tracks and manually correct them by connecting broken trajectories and reassigning falsely connected cell positions. A gold standard consisting of two time-series with 15,000 validated positions will be released as a valuable resource for benchmarking. We demonstrate how our method can be applied to analyze fluorescence distributions generated from mouse stem cells transfected with reporter constructs containing transcriptional control elements of the Msx1 gene, a regulator of pluripotency, in mother and daughter cells. Furthermore, we show by tracking zebrafish PAC2 cells expressing FUCCI cell cycle markers, our framework can be easily adapted to different cell types and fluorescent markers. PMID:22194797

Collecting Duct Intercalated Cell Function and Regulation

PubMed Central

Roy, Ankita; Al-bataineh, Mohammad M.

2015-01-01

Intercalated cells are kidney tubule epithelial cells with important roles in the regulation of acid-base homeostasis. However, in recent years the understanding of the function of the intercalated cell has become greatly enhanced and has shaped a new model for how the distal segments of the kidney tubule integrate salt and water reabsorption, potassium homeostasis, and acid-base status. These cells appear in the late distal convoluted tubule or in the connecting segment, depending on the species. They are most abundant in the collecting duct, where they can be detected all the way from the cortex to the initial part of the inner medulla. Intercalated cells are interspersed among the more numerous segment-specific principal cells. There are three types of intercalated cells, each having distinct structures and expressing different ensembles of transport proteins that translate into very different functions in the processing of the urine. This review includes recent findings on how intercalated cells regulate their intracellular milieu and contribute to acid-base regulation and sodium, chloride, and potassium homeostasis, thus highlighting their potential role as targets for the treatment of hypertension. Their novel regulation by paracrine signals in the collecting duct is also discussed. Finally, this article addresses their role as part of the innate immune system of the kidney tubule. PMID:25632105

Investigation of dynamic driving cycle effect on the degradation of proton exchange membrane fuel cell by segmented cell technology

NASA Astrophysics Data System (ADS)

Lin, R.; Xiong, F.; Tang, W. C.; Técher, L.; Zhang, J. M.; Ma, J. X.

2014-08-01

Durability is one of the most important limiting factors for the commercialization of proton exchange membrane fuel cell (PEMFC). Fuel cells are more vulnerable to degradation under operating conditions as dynamic load cycle or start up/shut down. The purpose of this study is to evaluate influences of driving cycles on the durability of fuel cells through analyzing the degradation mechanism of a segmented cell in real time. This study demonstrates that the performance of the fuel cell significantly decreases after 200 cycles. The segmented cell technology is used to measure the local current density distribution, which shows that the current density at the exit region and the inlet region declines much faster than the other parts. Meanwhile, electro-chemical impedance spectroscopy (EIS) reveals that after 200 cycles the ohmic resistance of fuel cell increases, especially at the cathode, and electro-chemical surface area (ESA) decreases from 392 to 307 cm2 mg-1. Furthermore, scanning electron microscopy (SEM) images of the membrane-electrode assembly (MEA) in cross-section demonstrate crackle flaw on the surface of the catalyst layer and the delamination of the electrodes from the membrane. Transmission electron microscope (TEM) results also show that the Pt particle size increases distinctly after driving cycles.

Current and temperature distributions in-situ acquired by electrode-segmentation along a microtubular solid oxide fuel cell operating with syngas

NASA Astrophysics Data System (ADS)

Aydın, Özgür; Nakajima, Hironori; Kitahara, Tatsumi

2015-10-01

Addressing the fuel distribution and endothermic cooling by the internal reforming, we have measured longitudinal current/temperature variations by ;Electrode-segmentation; in a microtubular solid oxide fuel cell operated with syngas (50% pre-reformed methane) and equivalent H2/N2 (100% conversion of syngas to H2) at three different flow rates. Regardless of the syngas flow rates, currents and temperatures show irregular fluctuations with varying amplitudes from upstream to downstream segment. Analysis of the fluctuations suggests that the methane steam reforming reaction is highly affected by the H2 partial pressure. Current-voltage curves plotted for the syngas and equivalent H2/N2 flow rates reveal that the fuel depletion is enhanced toward the downstream during the syngas operation, resulting in a larger performance degradation. All the segments exhibit temperature drops with the syngas flow compared with the equivalent H2/N2 flow due to the endothermic cooling by the methane steam reforming reaction. Despite the drops, the segment temperatures remain above the furnace temperature; besides, the maximum temperature difference along the cell diminishes. The MSR reaction rate does not consistently increase with the decreasing gas inlet velocity (increasing residence time on the catalyst); which we ascribe to the dominating impact of the local temperatures.

Impacts of fast food and the food retail environment on overweight and obesity in China: a multilevel latent class cluster approach.

PubMed

Zhang, Xiaoyong; van der Lans, Ivo; Dagevos, Hans

2012-01-01

To simultaneously identify consumer segments based on individual-level consumption and community-level food retail environment data and to investigate whether the segments are associated with BMI and dietary knowledge in China. A multilevel latent class cluster model was applied to identify consumer segments based not only on their individual preferences for fast food, salty snack foods, and soft drinks and sugared fruit drinks, but also on the food retail environment at the community level. The data came from the China Health and Nutrition Survey (CHNS) conducted in 2006 and two questionnaires for adults and communities were used. A total sample of 9788 adults living in 218 communities participated in the CHNS. We successfully identified four consumer segments. These four segments were embedded in two types of food retail environment: the saturated food retail environment and the deprived food retail environment. A three-factor solution was found for consumers' dietary knowledge. The four consumer segments were highly associated with consumers' dietary knowledge and a number of sociodemographic variables. The widespread discussion about the relationships between fast-food consumption and overweight/obesity is irrelevant for Chinese segments that do not have access to fast food. Factors that are most associated with segments with a higher BMI are consumers' (incorrect) dietary knowledge, the food retail environment and sociodemographics. The results provide valuable insight for policy interventions on reducing overweight/obesity in China. This study also indicates that despite the breathtaking changes in modern China, the impact of 'obesogenic' environments should not be assessed too strictly from a 'Western' perspective.

Interpreting CARS images of tissue within the C-H-stretching region

NASA Astrophysics Data System (ADS)

Dietzek, Benjamin; Meyer, Tobias; Medyukhina, Anna; Bergner, Norbert; Krafft, Christoph; Romeike, Bernd F. M.; Reichart, Rupert; Kalff, Rolf; Schmitt, Michael; Popp, Jürgen

2014-03-01

Single band coherent anti-Stokes Raman scattering (CARS) microscopy within the CH-stretching region is applied to detect individual cells and nuclei of human brain tissue and brain tumors - an information which allows for histopathologic grading of the tissue. The CARS image contrast within the C-H-stretching region correlated to the tissue composition. Based on the specific application example of identifying nuclei within (coherent) Raman images of neurotissue sections, we shall derive general design parameters for lasers optimally suited to serve in a clinical environment and discuss the potential of recently developed methods to analyze spectrally resolved CARS images and image segmentation algorithms.

Temporal segmentation of animal trajectories informed by habitat use

USGS Publications Warehouse

van Toor, Marielle L.; Newman, Scott H.; Takekawa, John Y.; Wegmann, Martin; Safi, Kamran

2016-01-01

Most animals live in seasonal environments and experience very different conditions throughout the year. Behavioral strategies like migration, hibernation, and a life cycle adapted to the local seasonality help to cope with fluctuations in environmental conditions. Thus, how an individual utilizes the environment depends both on the current availability of habitat and the behavioral prerequisites of the individual at that time. While the increasing availability and richness of animal movement data has facilitated the development of algorithms that classify behavior by movement geometry, changes in the environmental correlates of animal movement have so far not been exploited for a behavioral annotation. Here, we suggest a method that uses these changes in individual–environment associations to divide animal location data into segments of higher ecological coherence, which we term niche segmentation. We use time series of random forest models to evaluate the transferability of habitat use over time to cluster observational data accordingly. We show that our method is able to identify relevant changes in habitat use corresponding to both changes in the availability of habitat and how it was used using simulated data, and apply our method to a tracking data set of common teal (Anas crecca). The niche segmentation proved to be robust, and segmented habitat suitability outperformed models neglecting the temporal dynamics of habitat use. Overall, we show that it is possible to classify animal trajectories based on changes of habitat use similar to geometric segmentation algorithms. We conclude that such an environmentally informed classification of animal trajectories can provide new insights into an individuals' behavior and enables us to make sensible predictions of how suitable areas might be connected by movement in space and time.

A statistical pixel intensity model for segmentation of confocal laser scanning microscopy images.

PubMed

Calapez, Alexandre; Rosa, Agostinho

2010-09-01

Confocal laser scanning microscopy (CLSM) has been widely used in the life sciences for the characterization of cell processes because it allows the recording of the distribution of fluorescence-tagged macromolecules on a section of the living cell. It is in fact the cornerstone of many molecular transport and interaction quantification techniques where the identification of regions of interest through image segmentation is usually a required step. In many situations, because of the complexity of the recorded cellular structures or because of the amounts of data involved, image segmentation either is too difficult or inefficient to be done by hand and automated segmentation procedures have to be considered. Given the nature of CLSM images, statistical segmentation methodologies appear as natural candidates. In this work we propose a model to be used for statistical unsupervised CLSM image segmentation. The model is derived from the CLSM image formation mechanics and its performance is compared to the existing alternatives. Results show that it provides a much better description of the data on classes characterized by their mean intensity, making it suitable not only for segmentation methodologies with known number of classes but also for use with schemes aiming at the estimation of the number of classes through the application of cluster selection criteria.

Segmentation and analysis of mouse pituitary cells with graphic user interface (GUI)

NASA Astrophysics Data System (ADS)

González, Erika; Medina, Lucía.; Hautefeuille, Mathieu; Fiordelisio, Tatiana

2018-02-01

In this work we present a method to perform pituitary cell segmentation in image stacks acquired by fluorescence microscopy from pituitary slice preparations. Although there exist many procedures developed to achieve cell segmentation tasks, they are generally based on the edge detection and require high resolution images. However in the biological preparations that we worked on, the cells are not well defined as experts identify their intracellular calcium activity due to fluorescence intensity changes in different regions over time. This intensity changes were associated with time series over regions, and because they present a particular behavior they were used into a classification procedure in order to perform cell segmentation. Two logistic regression classifiers were implemented for the time series classification task using as features the area under the curve and skewness in the first classifier and skewness and kurtosis in the second classifier. Once we have found both decision boundaries in two different feature spaces by training using 120 time series, the decision boundaries were tested over 12 image stacks through a python graphical user interface (GUI), generating binary images where white pixels correspond to cells and the black ones to background. Results show that area-skewness classifier reduces the time an expert dedicates in locating cells by up to 75% in some stacks versus a 92% for the kurtosis-skewness classifier, this evaluated on the number of regions the method found. Due to the promising results, we expect that this method will be improved adding more relevant features to the classifier.

Smooth muscle cells in atherosclerosis originate from the local vessel wall and not circulating progenitor cells in ApoE knockout mice.

PubMed

Bentzon, Jacob F; Weile, Charlotte; Sondergaard, Claus S; Hindkjaer, Johnny; Kassem, Moustapha; Falk, Erling

2006-12-01

Recent studies of bone marrow (BM)-transplanted apoE knockout (apoE-/-) mice have concluded that a substantial fraction of smooth muscle cells (SMCs) in atherosclerosis arise from circulating progenitor cells of hematopoietic origin. This pathway, however, remains controversial. In the present study, we reexamined the origin of plaque SMCs in apoE-/- mice by a series of BM transplantations and in a novel model of atherosclerosis induced in surgically transferred arterial segments. We analyzed plaques in lethally irradiated apoE-/- mice reconstituted with sex-mismatched BM cells from eGFP+ apoE-/- mice, which ubiquitously express enhanced green fluorescent protein (eGFP), but did not find a single SMC of donor BM origin among approximately 10,000 SMC profiles analyzed. We then transplanted arterial segments between eGFP+ apoE-/- and apoE-/- mice (isotransplantation except for the eGFP transgene) and induced atherosclerosis focally within the graft by a recently invented collar technique. No eGFP+ SMCs were found in plaques that developed in apoE-/- artery segments grafted into eGFP+ apoE-/- mice. Concordantly, 96% of SMCs were eGFP+ in plaques induced in eGFP+ apoE-/- artery segments grafted into apoE-/- mice. These experiments show that SMCs in atherosclerotic plaques are exclusively derived from the local vessel wall in apoE-/- mice.

Three-Dimensional Imaging and Numerical Reconstruction of Graphite/Epoxy Composite Microstructure Based on Ultra-High Resolution X-Ray Computed Tomography

NASA Technical Reports Server (NTRS)

Czabaj, M. W.; Riccio, M. L.; Whitacre, W. W.

2014-01-01

A combined experimental and computational study aimed at high-resolution 3D imaging, visualization, and numerical reconstruction of fiber-reinforced polymer microstructures at the fiber length scale is presented. To this end, a sample of graphite/epoxy composite was imaged at sub-micron resolution using a 3D X-ray computed tomography microscope. Next, a novel segmentation algorithm was developed, based on concepts adopted from computer vision and multi-target tracking, to detect and estimate, with high accuracy, the position of individual fibers in a volume of the imaged composite. In the current implementation, the segmentation algorithm was based on Global Nearest Neighbor data-association architecture, a Kalman filter estimator, and several novel algorithms for virtualfiber stitching, smoothing, and overlap removal. The segmentation algorithm was used on a sub-volume of the imaged composite, detecting 508 individual fibers. The segmentation data were qualitatively compared to the tomographic data, demonstrating high accuracy of the numerical reconstruction. Moreover, the data were used to quantify a) the relative distribution of individual-fiber cross sections within the imaged sub-volume, and b) the local fiber misorientation relative to the global fiber axis. Finally, the segmentation data were converted using commercially available finite element (FE) software to generate a detailed FE mesh of the composite volume. The methodology described herein demonstrates the feasibility of realizing an FE-based, virtual-testing framework for graphite/fiber composites at the constituent level.

Quantitative analysis of retina layer elasticity based on automatic 3D segmentation (Conference Presentation)

NASA Astrophysics Data System (ADS)

He, Youmin; Qu, Yueqiao; Zhang, Yi; Ma, Teng; Zhu, Jiang; Miao, Yusi; Humayun, Mark; Zhou, Qifa; Chen, Zhongping

2017-02-01

Age-related macular degeneration (AMD) is an eye condition that is considered to be one of the leading causes of blindness among people over 50. Recent studies suggest that the mechanical properties in retina layers are affected during the early onset of disease. Therefore, it is necessary to identify such changes in the individual layers of the retina so as to provide useful information for disease diagnosis. In this study, we propose using an acoustic radiation force optical coherence elastography (ARF-OCE) system to dynamically excite the porcine retina and detect the vibrational displacement with phase resolved Doppler optical coherence tomography. Due to the vibrational mechanism of the tissue response, the image quality is compromised during elastogram acquisition. In order to properly analyze the images, all signals, including the trigger and control signals for excitation, as well as detection and scanning signals, are synchronized within the OCE software and are kept consistent between frames, making it possible for easy phase unwrapping and elasticity analysis. In addition, a combination of segmentation algorithms is used to accommodate the compromised image quality. An automatic 3D segmentation method has been developed to isolate and measure the relative elasticity of every individual retinal layer. Two different segmentation schemes based on random walker and dynamic programming are implemented. The algorithm has been validated using a 3D region of the porcine retina, where individual layers have been isolated and analyzed using statistical methods. The errors compared to manual segmentation will be calculated.

Rapid analysis and exploration of fluorescence microscopy images.

PubMed

Pavie, Benjamin; Rajaram, Satwik; Ouyang, Austin; Altschuler, Jason M; Steininger, Robert J; Wu, Lani F; Altschuler, Steven J

2014-03-19

Despite rapid advances in high-throughput microscopy, quantitative image-based assays still pose significant challenges. While a variety of specialized image analysis tools are available, most traditional image-analysis-based workflows have steep learning curves (for fine tuning of analysis parameters) and result in long turnaround times between imaging and analysis. In particular, cell segmentation, the process of identifying individual cells in an image, is a major bottleneck in this regard. Here we present an alternate, cell-segmentation-free workflow based on PhenoRipper, an open-source software platform designed for the rapid analysis and exploration of microscopy images. The pipeline presented here is optimized for immunofluorescence microscopy images of cell cultures and requires minimal user intervention. Within half an hour, PhenoRipper can analyze data from a typical 96-well experiment and generate image profiles. Users can then visually explore their data, perform quality control on their experiment, ensure response to perturbations and check reproducibility of replicates. This facilitates a rapid feedback cycle between analysis and experiment, which is crucial during assay optimization. This protocol is useful not just as a first pass analysis for quality control, but also may be used as an end-to-end solution, especially for screening. The workflow described here scales to large data sets such as those generated by high-throughput screens, and has been shown to group experimental conditions by phenotype accurately over a wide range of biological systems. The PhenoBrowser interface provides an intuitive framework to explore the phenotypic space and relate image properties to biological annotations. Taken together, the protocol described here will lower the barriers to adopting quantitative analysis of image based screens.

Sampling-based ensemble segmentation against inter-operator variability

NASA Astrophysics Data System (ADS)

Huo, Jing; Okada, Kazunori; Pope, Whitney; Brown, Matthew

2011-03-01

Inconsistency and a lack of reproducibility are commonly associated with semi-automated segmentation methods. In this study, we developed an ensemble approach to improve reproducibility and applied it to glioblastoma multiforme (GBM) brain tumor segmentation on T1-weigted contrast enhanced MR volumes. The proposed approach combines samplingbased simulations and ensemble segmentation into a single framework; it generates a set of segmentations by perturbing user initialization and user-specified internal parameters, then fuses the set of segmentations into a single consensus result. Three combination algorithms were applied: majority voting, averaging and expectation-maximization (EM). The reproducibility of the proposed framework was evaluated by a controlled experiment on 16 tumor cases from a multicenter drug trial. The ensemble framework had significantly better reproducibility than the individual base Otsu thresholding method (p<.001).

Optimization of the short-circuit current in an InP nanowire array solar cell through opto-electronic modeling.

PubMed

Chen, Yang; Kivisaari, Pyry; Pistol, Mats-Erik; Anttu, Nicklas

2016-09-23

InP nanowire arrays with axial p-i-n junctions are promising devices for next-generation photovoltaics, with a demonstrated efficiency of 13.8%. However, the short-circuit current in such arrays does not match their absorption performance. Here, through combined optical and electrical modeling, we study how the absorption of photons and separation of the resulting photogenerated electron-hole pairs define and limit the short-circuit current in the nanowires. We identify how photogenerated minority carriers in the top n segment (i.e. holes) diffuse to the ohmic top contact where they recombine without contributing to the short-circuit current. In our modeling, such contact recombination can lead to a 60% drop in the short-circuit current. To hinder such hole diffusion, we include a gradient doping profile in the n segment to create a front surface barrier. This approach leads to a modest 5% increase in the short-circuit current, limited by Auger recombination with increased doping. A more efficient approach is to switch the n segment to a material with a higher band gap, like GaP. Then, a much smaller number of holes is photogenerated in the n segment, strongly limiting the amount that can diffuse and disappear into the top contact. For a 500 nm long top segment, the GaP approach leads to a 50% higher short-circuit current than with an InP top segment. Such a long top segment could facilitate the fabrication and contacting of nanowire array solar cells. Such design schemes for managing minority carriers could open the door to higher performance in single- and multi-junction nanowire-based solar cells.

PaCeQuant: A Tool for High-Throughput Quantification of Pavement Cell Shape Characteristics.

PubMed

Möller, Birgit; Poeschl, Yvonne; Plötner, Romina; Bürstenbinder, Katharina

2017-11-01

Pavement cells (PCs) are the most frequently occurring cell type in the leaf epidermis and play important roles in leaf growth and function. In many plant species, PCs form highly complex jigsaw-puzzle-shaped cells with interlocking lobes. Understanding of their development is of high interest for plant science research because of their importance for leaf growth and hence for plant fitness and crop yield. Studies of PC development, however, are limited, because robust methods are lacking that enable automatic segmentation and quantification of PC shape parameters suitable to reflect their cellular complexity. Here, we present our new ImageJ-based tool, PaCeQuant, which provides a fully automatic image analysis workflow for PC shape quantification. PaCeQuant automatically detects cell boundaries of PCs from confocal input images and enables manual correction of automatic segmentation results or direct import of manually segmented cells. PaCeQuant simultaneously extracts 27 shape features that include global, contour-based, skeleton-based, and PC-specific object descriptors. In addition, we included a method for classification and analysis of lobes at two-cell junctions and three-cell junctions, respectively. We provide an R script for graphical visualization and statistical analysis. We validated PaCeQuant by extensive comparative analysis to manual segmentation and existing quantification tools and demonstrated its usability to analyze PC shape characteristics during development and between different genotypes. PaCeQuant thus provides a platform for robust, efficient, and reproducible quantitative analysis of PC shape characteristics that can easily be applied to study PC development in large data sets. © 2017 American Society of Plant Biologists. All Rights Reserved.

The next generation of LASIK patients.

PubMed

Freeman, J Christopher; Chuck, Roy S

2009-07-01

With baby boomers aging, and despite a growing global population, there is a decreasing number of potential laser vision correction patients. Some believe that the worldwide economic downturn of these times will limit the number of potential patients as well. This article highlights looking to an alternative segment of the population to identify potential laser vision correction patients and the limitations of reaching this group. The group known as generation Y contains a large number of individuals who may be candidates for laser vision correction. Traditional marketing efforts present challenges in reaching this particular population segment. Many individuals in this group are already patients of eye doctors for contact lenses and glasses and can be reached by these eye doctors to address candidacy and education of laser vision correction. Generation Y represents a large population segment that contains technology-embracing individuals who, although hard to reach with traditional marketing efforts, may be reached by fellow eye doctors already managing these patients. There are many in this age group who would be good laser vision correction candidates.

Polysaccharide compositions of collenchyma cell walls from celery (Apium graveolens L.) petioles.

PubMed

Chen, Da; Harris, Philip J; Sims, Ian M; Zujovic, Zoran; Melton, Laurence D

2017-06-15

Collenchyma serves as a mechanical support tissue for many herbaceous plants. Previous work based on solid-state NMR and immunomicroscopy suggested collenchyma cell walls (CWs) may have similar polysaccharide compositions to those commonly found in eudicotyledon parenchyma walls, but no detailed chemical analysis was available. In this study, compositions and structures of cell wall polysaccharides of peripheral collenchyma from celery petioles were investigated. This is the first detailed investigation of the cell wall composition of collenchyma from any plant. Celery petioles were found to elongate throughout their length during early growth, but as they matured elongation was increasingly confined to the upper region, until elongation ceased. Mature, fully elongated, petioles were divided into three equal segments, upper, middle and lower, and peripheral collenchyma strands isolated from each. Cell walls (CWs) were prepared from the strands, which also yielded a HEPES buffer soluble fraction. The CWs were sequentially extracted with CDTA, Na 2 CO 3 , 1 M KOH and 4 M KOH. Monosaccharide compositions of the CWs showed that pectin was the most abundant polysaccharide [with homogalacturonan (HG) more abundant than rhamnogalacturonan I (RG-I) and rhamnogalacturonan II (RG-II)], followed by cellulose, and other polysaccharides, mainly xyloglucans, with smaller amounts of heteroxylans and heteromannans. CWs from different segments had similar compositions, but those from the upper segments had slightly more pectin than those from the lower two segments. Further, the pectin in the CWs of the upper segment had a higher degree of methyl esterification than the other segments. In addition to the anticipated water-soluble pectins, the HEPES-soluble fractions surprisingly contained large amounts of heteroxylans. The CDTA and Na 2 CO 3 fractions were rich in HG and RG-I, the 1 M KOH fraction had abundant heteroxylans, the 4 M KOH fraction was rich in xyloglucan and heteromannans, and cellulose was predominant in the final residue. The structures of the xyloglucans, heteroxylans and heteromannans were deduced from the linkage analysis and were similar to those present in most eudicotyledon parenchyma CWs. Cross polarization with magic angle spinning (CP/MAS) NMR spectroscopy showed no apparent difference in the rigid and semi-rigid polysaccharides in the CWs of the three segments. Single-pulse excitation with magic-angle spinning (SPE/MAS) NMR spectroscopy, which detects highly mobile polysaccharides, showed the presence of arabinan, the detailed structure of which varied among the cell walls from the three segments. Celery collenchyma CWs have similar polysaccharide compositions to most eudicotyledon parenchyma CWs. However, celery collenchyma CWs have much higher XG content than celery parenchyma CWs. The degree of methyl esterification of pectin and the structures of the arabinan side chains of RG-I show some variation in the collenchyma CWs from the different segments. Unexpectedly, the HEPES-soluble fraction contained a large amount of heteroxylans.

Unsupervised fuzzy segmentation of 3D magnetic resonance brain images

NASA Astrophysics Data System (ADS)

Velthuizen, Robert P.; Hall, Lawrence O.; Clarke, Laurence P.; Bensaid, Amine M.; Arrington, J. A.; Silbiger, Martin L.

1993-07-01

Unsupervised fuzzy methods are proposed for segmentation of 3D Magnetic Resonance images of the brain. Fuzzy c-means (FCM) has shown promising results for segmentation of single slices. FCM has been investigated for volume segmentations, both by combining results of single slices and by segmenting the full volume. Different strategies and initializations have been tried. In particular, two approaches have been used: (1) a method by which, iteratively, the furthest sample is split off to form a new cluster center, and (2) the traditional FCM in which the membership grade matrix is initialized in some way. Results have been compared with volume segmentations by k-means and with two supervised methods, k-nearest neighbors and region growing. Results of individual segmentations are presented as well as comparisons on the application of the different methods to a number of tumor patient data sets.

A Typology of Middle School Girls: Audience Segmentation Related to Physical Activity

PubMed Central

Staten, Lisa K.; Birnbaum, Amanda S.; Jobe, Jared B.; Elder, John P.

2008-01-01

The Trial of Activity for Adolescent Girls (TAAG) combines social ecological and social marketing approaches to promote girls’ participation in physical activity programs implemented at 18 middle schools throughout the United States. Key to the TAAG approach is targeting materials to a variety of audience segments. TAAG segments are individuals who share one or more common characteristic that is expected to correlate with physical activity. Thirteen focus groups with seventh and eighth grade girls were conducted to identify and characterize segments. Potential messages and channels of communication were discussed for each segment. Based on participant responses, six primary segments were identified: athletic, preppy, quiet, rebel, smart, and tough. The focus group information was used to develop targeted promotional tools to appeal to a diversity of girls. Using audience segmentation for targeting persuasive communication is potentially useful for intervention programs but may be sensitive; therefore, ethical issues must be critically examined. PMID:16397160

Development of the segment alignment maintenance system (SAMS) for the Hobby-Eberly Telescope

NASA Astrophysics Data System (ADS)

Booth, John A.; Adams, Mark T.; Ames, Gregory H.; Fowler, James R.; Montgomery, Edward E.; Rakoczy, John M.

2000-07-01

A sensing and control system for maintaining optical alignment of ninety-one 1-meter mirror segments forming the Hobby-Eberly Telescope (HET) primary mirror array is now under development. The Segment Alignment Maintenance System (SAMS) is designed to sense relative shear motion between each segment edge pair and calculated individual segment tip, tilt, and piston position errors. Error information is sent to the HET primary mirror control system, which corrects the physical position of each segment as often as once per minute. Development of SAMS is required to meet optical images quality specifications for the telescope. Segment misalignment over time is though to be due to thermal inhomogeneity within the steel mirror support truss. Challenging problems of sensor resolution, dynamic range, mechanical mounting, calibration, stability, robust algorithm development, and system integration must be overcome to achieve a successful operational solution.

A typology of middle school girls: audience segmentation related to physical activity.

PubMed

Staten, Lisa K; Birnbaum, Amanda S; Jobe, Jared B; Elder, John P

2006-02-01

The Trial of Activity for Adolescent Girls (TAAG) combines social ecological and social marketing approaches to promote girls' participation in physical activity programs implemented at 18 middle schools throughout the United States. Key to the TAAG approach is targeting materials to a variety of audience segments. TAAG segments are individuals who share one or more common characteristic that is expected to correlate with physical activity. Thirteen focus groups with seventh and eighth grade girls were conducted to identify and characterize segments. Potential messages and channels of communication were discussed for each segment. Based on participant responses, six primary segments were identified: athletic, preppy, quiet, rebel, smart, and tough. The focus group information was used to develop targeted promotional tools to appeal to a diversity of girls. Using audience segmentation for targeting persuasive communication is potentially useful for intervention programs but may be sensitive; therefore, ethical issues must be critically examined.

A flexible and robust approach for segmenting cell nuclei from 2D microscopy images using supervised learning and template matching

PubMed Central

Chen, Cheng; Wang, Wei; Ozolek, John A.; Rohde, Gustavo K.

2013-01-01

We describe a new supervised learning-based template matching approach for segmenting cell nuclei from microscopy images. The method uses examples selected by a user for building a statistical model which captures the texture and shape variations of the nuclear structures from a given dataset to be segmented. Segmentation of subsequent, unlabeled, images is then performed by finding the model instance that best matches (in the normalized cross correlation sense) local neighborhood in the input image. We demonstrate the application of our method to segmenting nuclei from a variety of imaging modalities, and quantitatively compare our results to several other methods. Quantitative results using both simulated and real image data show that, while certain methods may work well for certain imaging modalities, our software is able to obtain high accuracy across several imaging modalities studied. Results also demonstrate that, relative to several existing methods, the template-based method we propose presents increased robustness in the sense of better handling variations in illumination, variations in texture from different imaging modalities, providing more smooth and accurate segmentation borders, as well as handling better cluttered nuclei. PMID:23568787

Impacts of Chromatin States and Long-Range Genomic Segments on Aging and DNA Methylation

PubMed Central

Sun, Dan; Yi, Soojin V.

2015-01-01

Understanding the fundamental dynamics of epigenome variation during normal aging is critical for elucidating key epigenetic alterations that affect development, cell differentiation and diseases. Advances in the field of aging and DNA methylation strongly support the aging epigenetic drift model. Although this model aligns with previous studies, the role of other epigenetic marks, such as histone modification, as well as the impact of sampling specific CpGs, must be evaluated. Ultimately, it is crucial to investigate how all CpGs in the human genome change their methylation with aging in their specific genomic and epigenomic contexts. Here, we analyze whole genome bisulfite sequencing DNA methylation maps of brain frontal cortex from individuals of diverse ages. Comparisons with blood data reveal tissue-specific patterns of epigenetic drift. By integrating chromatin state information, divergent degrees and directions of aging-associated methylation in different genomic regions are revealed. Whole genome bisulfite sequencing data also open a new door to investigate whether adjacent CpG sites exhibit coordinated DNA methylation changes with aging. We identified significant ‘aging-segments’, which are clusters of nearby CpGs that respond to aging by similar DNA methylation changes. These segments not only capture previously identified aging-CpGs but also include specific functional categories of genes with implications on epigenetic regulation of aging. For example, genes associated with development are highly enriched in positive aging segments, which are gradually hyper-methylated with aging. On the other hand, regions that are gradually hypo-methylated with aging (‘negative aging segments’) in the brain harbor genes involved in metabolism and protein ubiquitination. Given the importance of protein ubiquitination in proteome homeostasis of aging brains and neurodegenerative disorders, our finding suggests the significance of epigenetic regulation of this posttranslational modification pathway in the aging brain. Utilizing aging segments rather than individual CpGs will provide more comprehensive genomic and epigenomic contexts to understand the intricate associations between genomic neighborhoods and developmental and aging processes. These results complement the aging epigenetic drift model and provide new insights. PMID:26091484

Multi-segment foot kinematics and ground reaction forces during gait of individuals with plantar fasciitis.

PubMed

Chang, Ryan; Rodrigues, Pedro A; Van Emmerik, Richard E A; Hamill, Joseph

2014-08-22

Clinically, plantar fasciitis (PF) is believed to be a result and/or prolonged by overpronation and excessive loading, but there is little biomechanical data to support this assertion. The purpose of this study was to determine the differences between healthy individuals and those with PF in (1) rearfoot motion, (2) medial forefoot motion, (3) first metatarsal phalangeal joint (FMPJ) motion, and (4) ground reaction forces (GRF). We recruited healthy (n=22) and chronic PF individuals (n=22, symptomatic over three months) of similar age, height, weight, and foot shape (p>0.05). Retro-reflective skin markers were fixed according to a multi-segment foot and shank model. Ground reaction forces and three dimensional kinematics of the shank, rearfoot, medial forefoot, and hallux segment were captured as individuals walked at 1.35 ms(-1). Despite similarities in foot anthropometrics, when compared to healthy individuals, individuals with PF exhibited significantly (p<0.05) (1) greater total rearfoot eversion, (2) greater forefoot plantar flexion at initial contact, (3) greater total sagittal plane forefoot motion, (4) greater maximum FMPJ dorsiflexion, and (5) decreased vertical GRF during propulsion. These data suggest that compared to healthy individuals, individuals with PF exhibit significant differences in foot kinematics and kinetics. Consistent with the theoretical injury mechanisms of PF, we found these individuals to have greater total rearfoot eversion and peak FMPJ dorsiflexion, which may put undue loads on the plantar fascia. Meanwhile, increased medial forefoot plantar flexion at initial contact and decreased propulsive GRF are suggestive of compensatory responses, perhaps to manage pain. Copyright © 2014 Elsevier Ltd. All rights reserved.

Automatic real time evaluation of red blood cell elasticity by optical tweezers

NASA Astrophysics Data System (ADS)

Moura, Diógenes S.; Silva, Diego C. N.; Williams, Ajoke J.; Bezerra, Marcos A. C.; Fontes, Adriana; de Araujo, Renato E.

2015-05-01

Optical tweezers have been used to trap, manipulate, and measure individual cell properties. In this work, we show that the association of a computer controlled optical tweezers system with image processing techniques allows rapid and reproducible evaluation of cell deformability. In particular, the deformability of red blood cells (RBCs) plays a key role in the transport of oxygen through the blood microcirculation. The automatic measurement processes consisted of three steps: acquisition, segmentation of images, and measurement of the elasticity of the cells. An optical tweezers system was setup on an upright microscope equipped with a CCD camera and a motorized XYZ stage, computer controlled by a Labview platform. On the optical tweezers setup, the deformation of the captured RBC was obtained by moving the motorized stage. The automatic real-time homemade system was evaluated by measuring RBCs elasticity from normal donors and patients with sickle cell anemia. Approximately 150 erythrocytes were examined, and the elasticity values obtained by using the developed system were compared to the values measured by two experts. With the automatic system, there was a significant time reduction (60 × ) of the erythrocytes elasticity evaluation. Automated system can help to expand the applications of optical tweezers in hematology and hemotherapy.

Development of an ultralow-light-level luminescence image analysis system for dynamic measurements of transcriptional activity in living and migrating cells.

PubMed

Maire, E; Lelièvre, E; Brau, D; Lyons, A; Woodward, M; Fafeur, V; Vandenbunder, B

2000-04-10

We have developed an approach to study in single living epithelial cells both cell migration and transcriptional activation, which was evidenced by the detection of luminescence emission from cells transfected with luciferase reporter vectors. The image acquisition chain consists of an epifluorescence inverted microscope, connected to an ultralow-light-level photon-counting camera and an image-acquisition card associated to specialized image analysis software running on a PC computer. Using a simple method based on a thin calibrated light source, the image acquisition chain has been optimized following comparisons of the performance of microscopy objectives and photon-counting cameras designed to observe luminescence. This setup allows us to measure by image analysis the luminescent light emitted by individual cells stably expressing a luciferase reporter vector. The sensitivity of the camera was adjusted to a high value, which required the use of a segmentation algorithm to eliminate the background noise. Following mathematical morphology treatments, kinetic changes of luminescent sources were analyzed and then correlated with the distance and speed of migration. Our results highlight the usefulness of our image acquisition chain and mathematical morphology software to quantify the kinetics of luminescence changes in migrating cells.

The effects of segmentation algorithms on the measurement of 18F-FDG PET texture parameters in non-small cell lung cancer.

PubMed

Bashir, Usman; Azad, Gurdip; Siddique, Muhammad Musib; Dhillon, Saana; Patel, Nikheel; Bassett, Paul; Landau, David; Goh, Vicky; Cook, Gary

2017-12-01

Measures of tumour heterogeneity derived from 18-fluoro-2-deoxyglucose positron emission tomography/computed tomography ( 18 F-FDG PET/CT) scans are increasingly reported as potential biomarkers of non-small cell lung cancer (NSCLC) for classification and prognostication. Several segmentation algorithms have been used to delineate tumours, but their effects on the reproducibility and predictive and prognostic capability of derived parameters have not been evaluated. The purpose of our study was to retrospectively compare various segmentation algorithms in terms of inter-observer reproducibility and prognostic capability of texture parameters derived from non-small cell lung cancer (NSCLC) 18 F-FDG PET/CT images. Fifty three NSCLC patients (mean age 65.8 years; 31 males) underwent pre-chemoradiotherapy 18 F-FDG PET/CT scans. Three readers segmented tumours using freehand (FH), 40% of maximum intensity threshold (40P), and fuzzy locally adaptive Bayesian (FLAB) algorithms. Intraclass correlation coefficient (ICC) was used to measure the inter-observer variability of the texture features derived by the three segmentation algorithms. Univariate cox regression was used on 12 commonly reported texture features to predict overall survival (OS) for each segmentation algorithm. Model quality was compared across segmentation algorithms using Akaike information criterion (AIC). 40P was the most reproducible algorithm (median ICC 0.9; interquartile range [IQR] 0.85-0.92) compared with FLAB (median ICC 0.83; IQR 0.77-0.86) and FH (median ICC 0.77; IQR 0.7-0.85). On univariate cox regression analysis, 40P found 2 out of 12 variables, i.e. first-order entropy and grey-level co-occurence matrix (GLCM) entropy, to be significantly associated with OS; FH and FLAB found 1, i.e., first-order entropy. For each tested variable, survival models for all three segmentation algorithms were of similar quality, exhibiting comparable AIC values with overlapping 95% CIs. Compared with both FLAB and FH, segmentation with 40P yields superior inter-observer reproducibility of texture features. Survival models generated by all three segmentation algorithms are of at least equivalent utility. Our findings suggest that a segmentation algorithm using a 40% of maximum threshold is acceptable for texture analysis of 18 F-FDG PET in NSCLC.

Ground truth crop proportion summaries for US segments, 1976-1979

NASA Technical Reports Server (NTRS)

Horvath, R. (Principal Investigator); Rice, D.; Wessling, T.

1981-01-01

The original ground truth data was collected, digitized, and registered to LANDSAT data for use in the LACIE and AgRISTARS projects. The numerous ground truth categories were consolidated into fewer classes of crops or crop conditions and counted occurrences of these classes for each segment. Tables are presented in which the individual entries are the percentage of total segment area assigned to a given class. The ground truth summaries were prepared from a 20% sample of the scene. An analysis indicates that this size of sample provides sufficient accuracy for use of the data in initial segment screening.

The impact of spatial and temporal patterns on multi-cellular behavior

NASA Astrophysics Data System (ADS)

Nikolic, Djordje L.

What makes a fruit fly a fruit fly? Essentially this question stems from one of the most fascinating problems in biology: how a single cell (fertilized egg) can give rise to a fully grown animal. To be able to answer this question, the importance to how spatial and temporal patterns of gene and protein expression influence the development of an organism must be understood. After all, fruit fly larvae are segmented, while fertilized eggs are not. Pattern formation is fundamental to establishing this organization of the developing embryo with the ultimate goal being the precise arrangements of specialized cells and tissues within each organ in an adult organism. The research presented here showcases the examples of studies that assess the impact spatial and temporal protein patterns have on the behavior of a collection of cells. By introducing new experimental, non-traditional techniques we developed model systems that allowed us to examine the dependence of the strength of adhesion of cells on the protein organization on sub-cellular, micron length scales, and to investigate how epithelial cell sheets coordinate their migration incorporating individual cell locomotion, molecular signal propagation and different boundary conditions. The first part of this dissertation presents a photolithography-based silanization patterning technique that allowed us to homogeneously pattern large areas with high precision. This method is then applied to organizing cell adhesion-promoting proteins on surfaces for the purposes of studying and manipulating cell behavior. We show how the strength of adhesion is dependent on high local density of an adhesive extracellular matrix protein fibronectin. The varied appeal of this technique is exhibited by showing its applicability to pattern stretched DNA, too. The second part of this dissertation focuses on the impact of spatial and temporal propagation of a molecular signal (ERK 1/2 MAPK) in migrating epithelial sheets during wound healing. By tracking the motion of individual cells within the sheet under the three constructed conditions, we show how the dynamics of the individual cells' motion is responsible for the coordinated migration of the sheet in accordance with the activation of ERK 1/2 MAPK.

The retinal morphology and retinal histochemistry of a twilight fish Corydoras paleatus (J.).

PubMed

Yew, D T; Woo, H H

1976-01-01

1. The retinas of Corydoras paleatus were studied by histology (HE) and histochemistry (PAS and Nucleic acid). 2. Three types of visual cells were observed, namely rod, single cone and twin cone. All of them are PAS positive. 3. The histochemical PAS pattern of these visual cells differs from those species which are not of a twilight habitat. 4. Significant amount of RNA were not detected in the inner segments of visual cells in this species indicating a possible slow renewal of outer segments.

Morphology of the utricular otolith organ in the toadfish, Opsanus tau.

PubMed

Boyle, Richard; Ehsanian, Reza; Mofrad, Alireza; Popova, Yekaterina; Varelas, Joseph

2018-06-15

The utricle provides the vestibular reflex pathways with the sensory codes of inertial acceleration of self-motion and head orientation with respect to gravity to control balance and equilibrium. Here we present an anatomical description of this structure in the adult oyster toadfish and establish a morphological basis for interpretation of subsequent functional studies. Light, scanning, and transmission electron microscopy techniques were applied to visualize the sensory epithelium at varying levels of detail, its neural innervation and its synaptic organization. Scanning electron microscopy was used to visualize otolith mass and morphological polarization patterns of hair cells. Afferent nerve fibers were visualized following labeling with biocytin, and light microscope images were used to make three-dimensional (3-D) reconstructions of individual labeled afferents to identify dendritic morphology with respect to epithelial location. Transmission electron micrographs were compiled to create a serial 3-D reconstruction of a labeled afferent over a segment of its dendritic field and to examine the cell-afferent synaptic contacts. Major observations are: a well-defined striola, medial and lateral extra-striolar regions with a zonal organization of hair bundles; prominent lacinia projecting laterally; dependence of hair cell density on macular location; narrow afferent dendritic fields that follow the hair bundle polarization; synaptic specializations issued by afferents are typically directed towards a limited number of 7-13 hair cells, but larger dendritic fields in the medial extra-striola can be associated with > 20 hair cells also; and hair cell synaptic bodies can be confined to only an individual afferent or can synapse upon several afferents. © 2018 Wiley Periodicals, Inc.

Quantitative image cytometry measurements of lipids, DNA, CD45 and cytokeratin for circulating tumor cell identification in a model system

NASA Astrophysics Data System (ADS)

Futia, Gregory L.; Qamar, Lubna; Behbakht, Kian; Gibson, Emily A.

2016-04-01

Circulating tumor cell (CTC) identification has applications in both early detection and monitoring of solid cancers. The rarity of CTCs, expected at ~1-50 CTCs per million nucleated blood cells (WBCs), requires identifying methods based on biomarkers with high sensitivity and specificity for accurate identification. Discovery of biomarkers with ever higher sensitivity and specificity to CTCs is always desirable to potentially find more CTCs in cancer patients thus increasing their clinical utility. Here, we investigate quantitative image cytometry measurements of lipids with the biomarker panel of DNA, Cytokeratin (CK), and CD45 commonly used to identify CTCs. We engineered a device for labeling suspended cell samples with fluorescent antibodies and dyes. We used it to prepare samples for 4 channel confocal laser scanning microscopy. The total data acquired at high resolution from one sample is ~ 1.3 GB. We developed software to perform the automated segmentation of these images into regions of interest (ROIs) containing individual cells. We quantified image features of total signal, spatial second moment, spatial frequency second moment, and their product for each ROI. We performed measurements on pure WBCs, cancer cell line MCF7 and mixed samples. Multivariable regressions and feature selection were used to determine combination features that are more sensitive and specific than any individual feature separately. We also demonstrate that computation of spatial characteristics provides higher sensitivity and specificity than intensity alone. Statistical models allowed quantification of the required sensitivity and specificity for detecting small levels of CTCs in a human blood sample.

Effect of dietary fat on the distribution of mucosal mass and cell proliferation along the small intestine.

PubMed Central

Jenkins, A P; Thompson, R P

1992-01-01

This study investigated how substitution of long chain triglycerides for glucose in a mixed diet affects the overall small intestinal mucosal mass and the distribution of mucosal mass and cell proliferation along the small intestine. Four groups of eight female Wistar rats (180-200 g) were isocalorically fed mixed diets containing the essential fatty acid rich oil Efamol substituted for glucose at concentrations of 1.2%, 10%, 25%, and 50% total calories for 20 to 23 days. The small intestine was divided into three equal length segments and whole gut weights, mucosal weights, protein and DNA determined. Cell proliferation was estimated from the two hour accumulation of vincristine arrested metaphases in microdissected crypts at points 0%, 17%, 33%, 50%, 66%, and 100% small intestinal length. There were no differences between groups in parameters of overall small intestinal or distal segment mucosal mass. With increasing levels of fat, however, there was a significant trend for the mucosal mass of the proximal segment to fall and that of the middle segment to rise. The pattern of two hour metaphase accumulation reflected these changes. These regional changes in mucosal mass and cell proliferation may reflect differences in the sites of absorption of fat and glucose. PMID:1541418

MIR Solar Array Return Experiment: Power Performance Measurements and Molecular Contamination Analysis Results

NASA Technical Reports Server (NTRS)

Visentine, James; Kinard, William; Brinker, David; Scheiman, David; Banks, Bruce; Albyn, Keith; Hornung, Steve; See, Thomas

2001-01-01

A solar array segment was recently removed from the Mir core module and returned for ground-based analysis. The segment, which is similar to the ones the Russians have provided for the FGB and Service Modules, was microscopically examined and disassembled by US and Russian science teams. Laboratory analyses have shown the segment to he heavily contaminated by an organic silicone coating, which was converted to an organic silicate film by reactions with atomic oxygen within the. orbital flight environment. The source of the contaminant was a silicone polymer used by the Russians as an adhesive and bonding agent during segment construction. During its life cycle, the array experienced a reduction in power performance from approx. 12%, when it was new and first deployed, to approx. 5%, when it was taken out of service. However, current-voltage measurements of three contaminated cells and three pristine, Russian standard cells have shown that very little degradation in solar array performance was due to the silicate contaminants on the solar cell surfaces. The primary sources of performance degradation is attributed to "thermal hot-spotting" or electrical arcing; orbital debris and micrometeoroid impacts; and possibly to the degradation of the solar cells and interconnects caused by radiation damage from high energy protons and electrons.

Effect of dietary fat on the distribution of mucosal mass and cell proliferation along the small intestine.

PubMed

Jenkins, A P; Thompson, R P

1992-02-01

This study investigated how substitution of long chain triglycerides for glucose in a mixed diet affects the overall small intestinal mucosal mass and the distribution of mucosal mass and cell proliferation along the small intestine. Four groups of eight female Wistar rats (180-200 g) were isocalorically fed mixed diets containing the essential fatty acid rich oil Efamol substituted for glucose at concentrations of 1.2%, 10%, 25%, and 50% total calories for 20 to 23 days. The small intestine was divided into three equal length segments and whole gut weights, mucosal weights, protein and DNA determined. Cell proliferation was estimated from the two hour accumulation of vincristine arrested metaphases in microdissected crypts at points 0%, 17%, 33%, 50%, 66%, and 100% small intestinal length. There were no differences between groups in parameters of overall small intestinal or distal segment mucosal mass. With increasing levels of fat, however, there was a significant trend for the mucosal mass of the proximal segment to fall and that of the middle segment to rise. The pattern of two hour metaphase accumulation reflected these changes. These regional changes in mucosal mass and cell proliferation may reflect differences in the sites of absorption of fat and glucose.

Global Linking of Cell Tracks Using the Viterbi Algorithm

PubMed Central

Jaldén, Joakim; Gilbert, Penney M.; Blau, Helen M.

2016-01-01

Automated tracking of living cells in microscopy image sequences is an important and challenging problem. With this application in mind, we propose a global track linking algorithm, which links cell outlines generated by a segmentation algorithm into tracks. The algorithm adds tracks to the image sequence one at a time, in a way which uses information from the complete image sequence in every linking decision. This is achieved by finding the tracks which give the largest possible increases to a probabilistically motivated scoring function, using the Viterbi algorithm. We also present a novel way to alter previously created tracks when new tracks are created, thus mitigating the effects of error propagation. The algorithm can handle mitosis, apoptosis, and migration in and out of the imaged area, and can also deal with false positives, missed detections, and clusters of jointly segmented cells. The algorithm performance is demonstrated on two challenging datasets acquired using bright-field microscopy, but in principle, the algorithm can be used with any cell type and any imaging technique, presuming there is a suitable segmentation algorithm. PMID:25415983

Investigating the Flow and Biomechanics of the Embryonic Zebrafish Heart

NASA Astrophysics Data System (ADS)

Johnson, Brennan; Garrity, Deborah; Dasi, Lakshmi

2010-11-01

Understanding flow and kinematic characteristics of the embryonic heart is a prerequisite to devise early intervention or detection methods in the context of congenital heart defects. In this study, the kinematics and fluid dynamics of the embryonic zebrafish heart were analyzed through the early stages of cardiac development (24-48 hours post-fertilization) in vivo using optical microscopy and high-speed video. Endocardial walls and individual blood cells were segmented from raw images and were tracked through the cardiac cycle. Particle tracking velocimetry analysis yielded quantitative blood cell velocity field, chamber volume, and flow rate information. It was seen that the pumping mechanism starts as a combined peristaltic and suction pump while the heart is in the tube configuration and transforms into a positive displacement pump after cardiac looping. Strong two-phase nature of the fluid is evident. This work provides us new understanding of the spatio-temporal characteristics of kinematics and blood cell velocity field inside the developing heart.

Clinical evaluation of multi-atlas based segmentation of lymph node regions in head and neck and prostate cancer patients.

PubMed

Sjöberg, Carl; Lundmark, Martin; Granberg, Christoffer; Johansson, Silvia; Ahnesjö, Anders; Montelius, Anders

2013-10-03

Semi-automated segmentation using deformable registration of selected atlas cases consisting of expert segmented patient images has been proposed to facilitate the delineation of lymph node regions for three-dimensional conformal and intensity-modulated radiotherapy planning of head and neck and prostate tumours. Our aim is to investigate if fusion of multiple atlases will lead to clinical workload reductions and more accurate segmentation proposals compared to the use of a single atlas segmentation, due to a more complete representation of the anatomical variations. Atlases for lymph node regions were constructed using 11 head and neck patients and 15 prostate patients based on published recommendations for segmentations. A commercial registration software (Velocity AI) was used to create individual segmentations through deformable registration. Ten head and neck patients, and ten prostate patients, all different from the atlas patients, were randomly chosen for the study from retrospective data. Each patient was first delineated three times, (a) manually by a radiation oncologist, (b) automatically using a single atlas segmentation proposal from a chosen atlas and (c) automatically by fusing the atlas proposals from all cases in the database using the probabilistic weighting fusion algorithm. In a subsequent step a radiation oncologist corrected the segmentation proposals achieved from step (b) and (c) without using the result from method (a) as reference. The time spent for editing the segmentations was recorded separately for each method and for each individual structure. Finally, the Dice Similarity Coefficient and the volume of the structures were used to evaluate the similarity between the structures delineated with the different methods. For the single atlas method, the time reduction compared to manual segmentation was 29% and 23% for head and neck and pelvis lymph nodes, respectively, while editing the fused atlas proposal resulted in time reductions of 49% and 34%. The average volume of the fused atlas proposals was only 74% of the manual segmentation for the head and neck cases and 82% for the prostate cases due to a blurring effect from the fusion process. After editing of the proposals the resulting volume differences were no longer statistically significant, although a slight influence by the proposals could be noticed since the average edited volume was still slightly smaller than the manual segmentation, 9% and 5%, respectively. Segmentation based on fusion of multiple atlases reduces the time needed for delineation of lymph node regions compared to the use of a single atlas segmentation. Even though the time saving is large, the quality of the segmentation is maintained compared to manual segmentation.

Cascaded Segmentation-Detection Networks for Word-Level Text Spotting.

PubMed

Qin, Siyang; Manduchi, Roberto

2017-11-01

We introduce an algorithm for word-level text spotting that is able to accurately and reliably determine the bounding regions of individual words of text "in the wild". Our system is formed by the cascade of two convolutional neural networks. The first network is fully convolutional and is in charge of detecting areas containing text. This results in a very reliable but possibly inaccurate segmentation of the input image. The second network (inspired by the popular YOLO architecture) analyzes each segment produced in the first stage, and predicts oriented rectangular regions containing individual words. No post-processing (e.g. text line grouping) is necessary. With execution time of 450 ms for a 1000 × 560 image on a Titan X GPU, our system achieves good performance on the ICDAR 2013, 2015 benchmarks [2], [1].

Segmentation of multiple heart cavities in 3-D transesophageal ultrasound images.

PubMed

Haak, Alexander; Vegas-Sánchez-Ferrero, Gonzalo; Mulder, Harriët W; Ren, Ben; Kirişli, Hortense A; Metz, Coert; van Burken, Gerard; van Stralen, Marijn; Pluim, Josien P W; van der Steen, Antonius F W; van Walsum, Theo; Bosch, Johannes G

2015-06-01

Three-dimensional transesophageal echocardiography (TEE) is an excellent modality for real-time visualization of the heart and monitoring of interventions. To improve the usability of 3-D TEE for intervention monitoring and catheter guidance, automated segmentation is desired. However, 3-D TEE segmentation is still a challenging task due to the complex anatomy with multiple cavities, the limited TEE field of view, and typical ultrasound artifacts. We propose to segment all cavities within the TEE view with a multi-cavity active shape model (ASM) in conjunction with a tissue/blood classification based on a gamma mixture model (GMM). 3-D TEE image data of twenty patients were acquired with a Philips X7-2t matrix TEE probe. Tissue probability maps were estimated by a two-class (blood/tissue) GMM. A statistical shape model containing the left ventricle, right ventricle, left atrium, right atrium, and aorta was derived from computed tomography angiography (CTA) segmentations by principal component analysis. ASMs of the whole heart and individual cavities were generated and consecutively fitted to tissue probability maps. First, an average whole-heart model was aligned with the 3-D TEE based on three manually indicated anatomical landmarks. Second, pose and shape of the whole-heart ASM were fitted by a weighted update scheme excluding parts outside of the image sector. Third, pose and shape of ASM for individual heart cavities were initialized by the previous whole heart ASM and updated in a regularized manner to fit the tissue probability maps. The ASM segmentations were validated against manual outlines by two observers and CTA derived segmentations. Dice coefficients and point-to-surface distances were used to determine segmentation accuracy. ASM segmentations were successful in 19 of 20 cases. The median Dice coefficient for all successful segmentations versus the average observer ranged from 90% to 71% compared with an inter-observer range of 95% to 84%. The agreement against the CTA segmentations was slightly lower with a median Dice coefficient between 85% and 57%. In this work, we successfully showed the accuracy and robustness of the proposed multi-cavity segmentation scheme. This is a promising development for intraoperative procedure guidance, e.g., in cardiac electrophysiology.

Extracting oil palm crown from WorldView-2 satellite image

NASA Astrophysics Data System (ADS)

Korom, A.; Phua, M.-H.; Hirata, Y.; Matsuura, T.

2014-02-01

Oil palm (OP) is the most commercial crop in Malaysia. Estimating the crowns is important for biomass estimation from high resolution satellite (HRS) image. This study examined extraction of individual OP crown from a WorldView-2 image using twofold algorithms, i.e., masking of Non-OP pixels and detection of individual OP crown based on the watershed segmentation of greyscale images. The study site was located in Beluran district, central Sabah, where matured OPs with the age ranging from 15 to 25 years old have been planted. We examined two compound vegetation indices of (NDVI+1)*DVI and NDII for masking non-OP crown areas. Using kappa statistics, an optimal threshold value was set with the highest accuracy at 90.6% for differentiating OP crown areas from Non-OP areas. After the watershed segmentation of OP crown areas with additional post-procedures, about 77% of individual OP crowns were successfully detected in comparison to the manual based delineation. Shape and location of each crown segment was then assessed based on a modified version of the goodness measures of Möller et al which was 0.3, indicating an acceptable CSGM (combined segmentation goodness measures) agreements between the automated and manually delineated crowns (perfect case is '1').

Investigating the relative importance of individual differences on the work-family interface and the moderating role of boundary preference for segmentation.

PubMed

Michel, Jesse S; Clark, Malissa A

2013-10-01

This study examines the relative importance of individual differences in relation to perceptions of work-family conflict and facilitation, as well as the moderating role of boundary preference for segmentation on these relationships. Relative importance analyses, based on a diverse sample of 380 employees from the USA, revealed that individual differences were consistently predictive of self-reported work-family conflict and facilitation. Conscientiousness, neuroticism, negative affect and core self-evaluations were consistently related to both directions of work-family conflict, whereas agreeableness predicted significant variance in family-to-work conflict only. Positive affect and core self-evaluations were consistently related to both directions of work-family facilitation, whereas agreeableness and neuroticism predicted significant variance in family-to-work facilitation only. Collectively, individual differences explained 25-28% of the variance in work-family conflict (primarily predicted by neuroticism and negative affect) and 11-18% of the variance in work-family facilitation (primarily predicted by positive affect and core self-evaluations). Moderated regression analyses showed that boundary preference for segmentation strengthened many of the relationships between individual differences and work-family conflict and facilitation. Implications for addressing the nature of work and family are discussed. Copyright © 2012 John Wiley & Sons, Ltd.

Visualization of Arenavirus RNA Species in Individual Cells by Single-Molecule Fluorescence In Situ Hybridization Suggests a Model of Cyclical Infection and Clearance during Persistence.

PubMed

King, Benjamin R; Samacoits, Aubin; Eisenhauer, Philip L; Ziegler, Christopher M; Bruce, Emily A; Zenklusen, Daniel; Zimmer, Christophe; Mueller, Florian; Botten, Jason

2018-06-15

Lymphocytic choriomeningitis mammarenavirus (LCMV) is an enveloped, negative-strand RNA virus that causes serious disease in humans but establishes an asymptomatic, lifelong infection in reservoir rodents. Different models have been proposed to describe how arenaviruses regulate the replication and transcription of their bisegmented, single-stranded RNA genomes, particularly during persistent infection. However, these models were based largely on viral RNA profiling data derived from entire populations of cells. To better understand LCMV replication and transcription at the single-cell level, we established a high-throughput, single-molecule fluorescence in situ hybridization (smFISH) image acquisition and analysis pipeline and examined viral RNA species at discrete time points from virus entry through the late stages of persistent infection in vitro We observed the transcription of viral nucleoprotein and polymerase mRNAs from the incoming S and L segment genomic RNAs, respectively, within 1 h of infection, whereas the transcription of glycoprotein mRNA from the S segment antigenome required ∼4 to 6 h. This confirms the temporal separation of viral gene expression expected due to the ambisense coding strategy of arenaviruses and also suggests that antigenomic RNA contained in virions is not transcriptionally active upon entry. Viral replication and transcription peaked at 36 h postinfection, followed by a progressive loss of viral RNAs over the next several days. During persistence, the majority of cells showed repeating cyclical waves of viral transcription and replication followed by the clearance of viral RNA. Thus, our data support a model of LCMV persistence whereby infected cells can spontaneously clear infection and become reinfected by viral reservoir cells that remain in the population. IMPORTANCE Arenaviruses are human pathogens that can establish asymptomatic, lifelong infections in their rodent reservoirs. Several models have been proposed to explain how arenavirus spread is restricted within host rodents, including the periodic accumulation and loss of replication-competent, but transcriptionally incompetent, viral genomes. A limitation of previous studies was the inability to enumerate viral RNA species at the single-cell level. We developed a high-throughput, smFISH assay and used it to quantitate lymphocytic choriomeningitis mammarenavirus (LCMV) replicative and transcriptional RNA species in individual cells at distinct time points following infection. Our findings support a model whereby productively infected cells can clear infection, including viral RNAs and antigen, and later be reinfected. This information improves our understanding of the timing and possible regulation of LCMV genome replication and transcription during infection. Importantly, the smFISH assay and data analysis pipeline developed here is easily adaptable to other RNA viruses. Copyright © 2018 American Society for Microbiology.

Ocular Manifestations of Acquired Immunodeficiency Syndrome.

PubMed

Kim, Young Shin; Sun, Hae Jung; Kim, Tae Hyong; Kang, Kui Dong; Lee, Sung Jin

2015-08-01

To investigate the patterns and risk factors of the ocular manifestations of acquired immunodeficiency syndrome (AIDS) and their correlation with CD4+ count in the era of highly active antiretroviral therapy (HAART). This retrospective study examined 127 AIDS patients who presented to Soonchunhyang University Hospital. Data were collected from patient interviews, clinical examinations, and laboratory investigations. Ophthalmologic examinations included the best-corrected visual acuity, intraocular pressure, anterior segment and adnexal examination, and dilated fundus examination. Of the 127 patients with AIDS, 118 were on HAART and 9 were not. The mean CD4+ count was 266.7 ± 209.1 cells/µL. There were ocular manifestations in 61 patients (48.0%). The incidence of anterior segment manifestations was higher than posterior segment manifestations at 28.3% and 19.7%, respectively. The mean CD4+ count was significantly (p < 0.05) lower in the patients with posterior versus anterior segment ocular manifestations. The most common ocular manifestation was retinal microvasculopathy (15.0%), followed by keratoconjunctivitis sicca (14.2%), conjunctival microvasculopathy (9.4%), cytomegalovirus retinitis (3.1%), herpes zoster ophthalmicus (2.4%), and blepharitis (1.6%). Retinal microvasculopathy and cytomegalovirus retinitis were common in patients with CD4+ counts <200 cells/µL, while keratoconjunctivitis sicca and conjunctival microvasculopathy were common in patients with CD4+ counts of 200 to 499 cells/µL. There was a significant (p < 0.05) association between ocular manifestation and CD4+ count or age. The introduction of HAART has changed the landscape of ocular presentations in patients with AIDS. In this study, anterior segment and external ocular manifestations occurred more frequently than posterior segment manifestations. Also, the mean CD4+ count was significantly lower in patients with posterior segment ocular manifestations versus anterior segment ocular manifestations. We found that CD4+ count and age >35 years were independent risk factors for developing ocular manifestations.

Ocular Manifestations of Acquired Immunodeficiency Syndrome

PubMed Central

Kim, Young Shin; Sun, Hae Jung; Kim, Tae Hyong; Kang, Kui Dong

2015-01-01

Purpose To investigate the patterns and risk factors of the ocular manifestations of acquired immunodeficiency syndrome (AIDS) and their correlation with CD4+ count in the era of highly active antiretroviral therapy (HAART). Methods This retrospective study examined 127 AIDS patients who presented to Soonchunhyang University Hospital. Data were collected from patient interviews, clinical examinations, and laboratory investigations. Ophthalmologic examinations included the best-corrected visual acuity, intraocular pressure, anterior segment and adnexal examination, and dilated fundus examination. Results Of the 127 patients with AIDS, 118 were on HAART and 9 were not. The mean CD4+ count was 266.7 ± 209.1 cells/µL. There were ocular manifestations in 61 patients (48.0%). The incidence of anterior segment manifestations was higher than posterior segment manifestations at 28.3% and 19.7%, respectively. The mean CD4+ count was significantly (p < 0.05) lower in the patients with posterior versus anterior segment ocular manifestations. The most common ocular manifestation was retinal microvasculopathy (15.0%), followed by keratoconjunctivitis sicca (14.2%), conjunctival microvasculopathy (9.4%), cytomegalovirus retinitis (3.1%), herpes zoster ophthalmicus (2.4%), and blepharitis (1.6%). Retinal microvasculopathy and cytomegalovirus retinitis were common in patients with CD4+ counts <200 cells/µL, while keratoconjunctivitis sicca and conjunctival microvasculopathy were common in patients with CD4+ counts of 200 to 499 cells/µL. There was a significant (p < 0.05) association between ocular manifestation and CD4+ count or age. Conclusions The introduction of HAART has changed the landscape of ocular presentations in patients with AIDS. In this study, anterior segment and external ocular manifestations occurred more frequently than posterior segment manifestations. Also, the mean CD4+ count was significantly lower in patients with posterior segment ocular manifestations versus anterior segment ocular manifestations. We found that CD4+ count and age >35 years were independent risk factors for developing ocular manifestations. PMID:26240508

Mixed vitiligo of Blaschko lines: a newly discovered presentation of vitiligo responsive to combination treatment.

PubMed

Kovacevic, Maja; Stanimirovic, Andrija; Vucic, Majda; Goren, Andy; Situm, Mirna; Lukinovic Skudar, Vesna; Lotti, Torello

2016-07-01

Vitiligo, depigmenting disorder of the skin and mucous membranes, affects up to 1% of the population worldwide. It is classified into four major types: segmental, non-segmental, mixed, and unclassified type. Non-segmental vitiligo refers to non-dermatomal distribution of lesions, while dermatomal distribution of lesions is present in patients with segmental vitiligo. Segmental vitiligo can also follow Blaschko lines - pathways of epidermal cell migration and proliferation during the development of the fetus. Here, we present patient with segmental and non-segmental vitiligo following Blaschko lines with excellent therapeutic response to combined therapy. Prior to our report, a case of segmental and non-segmental vitiligo followed by Blaschko lines was never described, therefore we suggest the term "mixed vitiligo of Blaschko lines" to describe this entity. This is also a rare case in which 90% repigmentation was achieved in patient with segmental and nonsegmental vitiligo following Blaschko lines in only 2 months of combined therapy. © 2016 Wiley Periodicals, Inc.

Denoising and segmentation of retinal layers in optical coherence tomography images

NASA Astrophysics Data System (ADS)

Dash, Puspita; Sigappi, A. N.

2018-04-01

Optical Coherence Tomography (OCT) is an imaging technique used to localize the intra-retinal boundaries for the diagnostics of macular diseases. Due to speckle noise, low image contrast and accurate segmentation of individual retinal layers is difficult. Due to this, a method for retinal layer segmentation from OCT images is presented. This paper proposes a pre-processing filtering approach for denoising and segmentation methods for segmenting retinal layers OCT images using graph based segmentation technique. These techniques are used for segmentation of retinal layers for normal as well as patients with Diabetic Macular Edema. The algorithm based on gradient information and shortest path search is applied to optimize the edge selection. In this paper the four main layers of the retina are segmented namely Internal limiting membrane (ILM), Retinal pigment epithelium (RPE), Inner nuclear layer (INL) and Outer nuclear layer (ONL). The proposed method is applied on a database of OCT images of both ten normal and twenty DME affected patients and the results are found to be promising.

KSC-07pd3457

NASA Image and Video Library

2007-11-27

KENNEDY SPACE CENTER, FLA. -- Workers oversee the placement of a solid rocket booster segment onto a railroad car at the railroad yard at NASA's Kennedy Space Center. The spent segment is part of the booster used to launch space shuttle Discovery in October. The segment will be placed on the car and covered for the long trip back to Utah. After a mission, the spent boosters are recovered, cleaned, disassembled, refurbished and reused after each launch. After hydrolasing the interior of each segment, they are placed on flatbed trucks. The individual booster segments are transferred to a railhead located at the railroad yard at NASA's Kennedy Space Center. The long train of segments is part of the twin solid rocket boosters used to launch space shuttle Discovery in October. The NASA Railroad locomotive backs up the rail cars and the segment is lowered onto the car. The covered segments are moved to Titusville for interchange with Florida East Coast Railway to begin the trip back to Utah. Photo credit: NASA/Amanda Diller

Reflective photovoltaics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lentine, Anthony L.; Nielson, Gregory N.; Cruz-Campa, Jose Luis

A photovoltaic module includes colorized reflective photovoltaic cells that act as pixels. The colorized reflective photovoltaic cells are arranged so that reflections from the photovoltaic cells or pixels visually combine into an image on the photovoltaic module. The colorized photovoltaic cell or pixel is composed of a set of 100 to 256 base color sub-pixel reflective segments or sub-pixels. The color of each pixel is determined by the combination of base color sub-pixels forming the pixel. As a result, each pixel can have a wide variety of colors using a set of base colors, which are created, from sub-pixel reflectivemore » segments having standard film thicknesses.« less

Changes in cell proliferation and morphology in the large intestine of normal and DMH-treated rats following colostomy.

PubMed

Barkla, D H; Tutton, P J

1987-04-01

Colostomies were formed in the midcolon of normal and DMH-treated rats. Changes in cell proliferation in the mucosa adjacent to the colostomy and in the defunctioned distal segment were measured at seven, 14, 30, and 72 days using a stathmokinetic technique. Animals were given intraperitoneal injections of vinblastine and sacrificed three hours later; counts of mitotic and nonmitotic cells were made in tissue sections, and three-hour accumulated mitotic indexes were estimated. The results show that, except at seven days in DMH-treated rats, cell proliferation was unchanged in the colon proximal to the colostomy. Morphologic evidence of hyperplasia was seen in some animals at seven and 14 days. The defunctioned segment showed rapid atrophy of both mucosa and muscularis and a gradual but progressive decrease in cell proliferation. The morphology of the mucosa adjacent to the suture line in both functioning and defunctioned segments in normal and DMH-treated rats was abnormal in many animals. Abnormalities that were seen included collections of dysplastic epithelial cells in the submucosa, focal adenomatous changes, and intramural carcinoma formation. Aggregates of lymphoid tissue often were associated with carcinomas.

Towards automated segmentation of cells and cell nuclei in nonlinear optical microscopy.

PubMed

Medyukhina, Anna; Meyer, Tobias; Schmitt, Michael; Romeike, Bernd F M; Dietzek, Benjamin; Popp, Jürgen

2012-11-01

Nonlinear optical (NLO) imaging techniques based e.g. on coherent anti-Stokes Raman scattering (CARS) or two photon excited fluorescence (TPEF) show great potential for biomedical imaging. In order to facilitate the diagnostic process based on NLO imaging, there is need for an automated calculation of quantitative values such as cell density, nucleus-to-cytoplasm ratio, average nuclear size. Extraction of these parameters is helpful for the histological assessment in general and specifically e.g. for the determination of tumor grades. This requires an accurate image segmentation and detection of locations and boundaries of cells and nuclei. Here we present an image processing approach for the detection of nuclei and cells in co-registered TPEF and CARS images. The algorithm developed utilizes the gray-scale information for the detection of the nuclei locations and the gradient information for the delineation of the nuclear and cellular boundaries. The approach reported is capable for an automated segmentation of cells and nuclei in multimodal TPEF-CARS images of human brain tumor samples. The results are important for the development of NLO microscopy into a clinically relevant diagnostic tool. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Carbon limitation patterns in buried and open urban streams

EPA Science Inventory

Urban streams alternate between darkened buried segments dominated by heterotrophic processes and lighted open segments dominated by autotrophic processes. We hypothesized that labile carbon leaking from autotrophic cells would reduce heterotrophic carbon limitation in open chan...

Parietal Epithelial Cells Participate in the Formation of Sclerotic Lesions in Focal Segmental Glomerulosclerosis

PubMed Central

Smeets, Bart; Kuppe, Christoph; Sicking, Eva-Maria; Fuss, Astrid; Jirak, Peggy; van Kuppevelt, Toin H.; Endlich, Karlhans; Wetzels, Jack F.M.; Gröne, Hermann-Josef; Floege, Jürgen

2011-01-01

The pathogenesis of the development of sclerotic lesions in focal segmental glomerulosclerosis (FSGS) remains unknown. Here, we selectively tagged podocytes or parietal epithelial cells (PECs) to determine whether PECs contribute to sclerosis. In three distinct models of FSGS (5/6-nephrectomy + DOCA-salt; the murine transgenic chronic Thy1.1 model; or the MWF rat) and in human biopsies, the primary injury to induce FSGS associated with focal activation of PECs and the formation of cellular adhesions to the capillary tuft. From this entry site, activated PECs invaded the affected segment of the glomerular tuft and deposited extracellular matrix. Within the affected segment, podocytes were lost and mesangial sclerosis developed within the endocapillary compartment. In conclusion, these results demonstrate that PECs contribute to the development and progression of the sclerotic lesions that define FSGS, but this pathogenesis may be relevant to all etiologies of glomerulosclerosis. PMID:21719782

Improved brain tumor segmentation by utilizing tumor growth model in longitudinal brain MRI

NASA Astrophysics Data System (ADS)

Pei, Linmin; Reza, Syed M. S.; Li, Wei; Davatzikos, Christos; Iftekharuddin, Khan M.

2017-03-01

In this work, we propose a novel method to improve texture based tumor segmentation by fusing cell density patterns that are generated from tumor growth modeling. To model tumor growth, we solve the reaction-diffusion equation by using Lattice-Boltzmann method (LBM). Computational tumor growth modeling obtains the cell density distribution that potentially indicates the predicted tissue locations in the brain over time. The density patterns is then considered as novel features along with other texture (such as fractal, and multifractal Brownian motion (mBm)), and intensity features in MRI for improved brain tumor segmentation. We evaluate the proposed method with about one hundred longitudinal MRI scans from five patients obtained from public BRATS 2015 data set, validated by the ground truth. The result shows significant improvement of complete tumor segmentation using ANOVA analysis for five patients in longitudinal MR images.

Improved brain tumor segmentation by utilizing tumor growth model in longitudinal brain MRI.

PubMed

Pei, Linmin; Reza, Syed M S; Li, Wei; Davatzikos, Christos; Iftekharuddin, Khan M

2017-02-11

In this work, we propose a novel method to improve texture based tumor segmentation by fusing cell density patterns that are generated from tumor growth modeling. In order to model tumor growth, we solve the reaction-diffusion equation by using Lattice-Boltzmann method (LBM). Computational tumor growth modeling obtains the cell density distribution that potentially indicates the predicted tissue locations in the brain over time. The density patterns is then considered as novel features along with other texture (such as fractal, and multifractal Brownian motion (mBm)), and intensity features in MRI for improved brain tumor segmentation. We evaluate the proposed method with about one hundred longitudinal MRI scans from five patients obtained from public BRATS 2015 data set, validated by the ground truth. The result shows significant improvement of complete tumor segmentation using ANOVA analysis for five patients in longitudinal MR images.

FLIS Procedures Manual. Document Identifier Code Input/Output Formats (Fixed Length). Volume 8.

DTIC Science & Technology

1997-04-01

DATA ELE- MENTS. SEGMENT R MAY BE REPEATED A MAXIMUM OF THREE (3) TIMES IN ORDER TO ACQUIRE THE REQUIRED MIX OF SEGMENTS OR INDIVIDUAL DATA ELEMENTS TO...preceding record. Marketing input DICs. QI Next DRN of appropriate segment will be QF The assigned NSN or PSCN being can- reflected in accordance with Table...Classified KFC Notification of Possible Duplicate (Sub- KRP Characteristics Data mitter) Follow-Up Interrogation LFU Notification of Return, SSR Transaction

A Study of the Effectiveness of the Army’s National Advertising Expenditures. Volume 3. Appendices.

DTIC Science & Technology

1981-08-31

N W Ayer Incorpor- ated to study the effectiveness of the Army’s national recruitment advertising . N W Ayer’s Marketing Services Department undertook...Army priorities for the quality of the recruit mix required investigating the differential impact of advertising on key market segments. Segmentation... market segment. Three key considerations in specifying the advertising variables are that 𔄃’ *individual media components were analyzed to account for

Multiparametric Analysis of the Tumor Microenvironment: Hypoxia Markers and Beyond.

PubMed

Mayer, Arnulf; Vaupel, Peter

2017-01-01

We have established a novel in situ protein analysis pipeline, which is built upon highly sensitive, multichannel immunofluorescent staining of paraffin sections of human and xenografted tumor tissue. Specimens are digitized using slide scanners equipped with suitable light sources and fluorescence filter combinations. Resulting digital images are subsequently subjected to quantitative image analysis using a primarily object-based approach, which comprises segmentation of single cells or higher-order structures (e.g., blood vessels), cell shape approximation, measurement of signal intensities in individual fluorescent channels and correlation of these data with positional information for each object. Our approach could be particularly useful for the study of the hypoxic tumor microenvironment as it can be utilized to systematically explore the influence of spatial factors on cell phenotypes, e.g., the distance of a given cell type from the nearest blood vessel on the cellular expression of hypoxia-associated biomarkers and other proteins reflecting their specific state of activation or function. In this report, we outline the basic methodology and provide an outlook on possible use cases.

Alterations of the outer retina in non-arteritic anterior ischaemic optic neuropathy detected using spectral-domain optical coherence tomography.

PubMed

Ackermann, Philipp; Brachert, Maike; Albrecht, Philipp; Ringelstein, Marius; Finis, David; Geerling, Gerd; Aktas, Orhan; Guthoff, Rainer

2017-07-01

A characteristic disease pattern may be reflected by retinal layer thickness changes in non-arteritic anterior ischaemic optic neuropathy measured using spectraldomain optical coherence tomography. Retinal layer segmentation is enabled by advanced software. In this study, retinal layer thicknesses in acute and chronic non-arteritic anterior ischaemic optic neuropathy were compared. A single-centre cross-sectional analysis was used. A total of 27 patients (20 age-matched healthy eyes) were included: 14 with acute (<7 days) and 13 patients with chronic non-arteritic anterior ischaemic optic neuropathy. Macular volume and 12° peripapillary ring optical coherence tomography scans were used. The peripapillary thicknesses of the following layers were determined by manual segmentation: retinal nerve fibres, ganglion cells + inner plexiform layer, inner nuclear layer + outer plexiform layer, outer nuclear layer + inner segments of the photoreceptors and outer segments of the photoreceptors to Bruch's membrane. Macular retinal layer thicknesses were automatically determined in volume cubes centred on the fovea. Peripapillary retinal swelling in acute nonarteritic anterior ischaemic optic neuropathy was attributable to retinal nerve fibre layer, ganglion cell layer/inner plexiform layer and outer nuclear layer/segments of the photoreceptors thickening. In chronic cases, peripapillary retinal nerve fibre layer, macular ganglion cell layer and inner plexiform layer thinning were observed. In acute non-arteritic anterior ischaemic optic neuropathy, the inner and outer peripapillary retinal layers are affected by thickness changes. In chronic cases, atrophy of the ganglion cells and their axons and dendrites is evident by inner retinal layer thinning. © 2017 Royal Australian and New Zealand College of Ophthalmologists.

Towards comprehensive cell lineage reconstructions in complex organisms using light-sheet microscopy.

PubMed

Amat, Fernando; Keller, Philipp J

2013-05-01

Understanding the development of complex multicellular organisms as a function of the underlying cell behavior is one of the most fundamental goals of developmental biology. The ability to quantitatively follow cell dynamics in entire developing embryos is an indispensable step towards such a system-level understanding. In recent years, light-sheet fluorescence microscopy has emerged as a particularly promising strategy for recording the in vivo data required to realize this goal. Using light-sheet fluorescence microscopy, entire complex organisms can be rapidly imaged in three dimensions at sub-cellular resolution, achieving high temporal sampling and excellent signal-to-noise ratio without damaging the living specimen or bleaching fluorescent markers. The resulting datasets allow following individual cells in vertebrate and higher invertebrate embryos over up to several days of development. However, the complexity and size of these multi-terabyte recordings typically preclude comprehensive manual analyses. Thus, new computational approaches are required to automatically segment cell morphologies, accurately track cell identities and systematically analyze cell behavior throughout embryonic development. We review current efforts in light-sheet microscopy and bioimage informatics towards this goal, and argue that comprehensive cell lineage reconstructions are finally within reach for many key model organisms, including fruit fly, zebrafish and mouse. © 2013 The Authors Development, Growth & Differentiation © 2013 Japanese Society of Developmental Biologists.

Automation of 3D reconstruction of neural tissue from large volume of conventional serial section transmission electron micrographs.

PubMed

Mishchenko, Yuriy

2009-01-30

We describe an approach for automation of the process of reconstruction of neural tissue from serial section transmission electron micrographs. Such reconstructions require 3D segmentation of individual neuronal processes (axons and dendrites) performed in densely packed neuropil. We first detect neuronal cell profiles in each image in a stack of serial micrographs with multi-scale ridge detector. Short breaks in detected boundaries are interpolated using anisotropic contour completion formulated in fuzzy-logic framework. Detected profiles from adjacent sections are linked together based on cues such as shape similarity and image texture. Thus obtained 3D segmentation is validated by human operators in computer-guided proofreading process. Our approach makes possible reconstructions of neural tissue at final rate of about 5 microm3/manh, as determined primarily by the speed of proofreading. To date we have applied this approach to reconstruct few blocks of neural tissue from different regions of rat brain totaling over 1000microm3, and used these to evaluate reconstruction speed, quality, error rates, and presence of ambiguous locations in neuropil ssTEM imaging data.

Tortuous Pore Path Through the Glaucomatous Lamina Cribrosa.

PubMed

Wang, Bo; Lucy, Katie A; Schuman, Joel S; Sigal, Ian A; Bilonick, Richard A; Lu, Chen; Liu, Jonathan; Grulkowski, Ireneusz; Nadler, Zachary; Ishikawa, Hiroshi; Kagemann, Larry; Fujimoto, James G; Wollstein, Gadi

2018-05-08

The lamina cribrosa is a primary site of damage in glaucoma. While mechanical distortion is hypothesized to cause reduction of axoplasmic flow, little is known about how the pores, which contains the retinal ganglion cell axons, traverse the lamina cribrosa. We investigated lamina cribrosa pore paths in vivo to quantify differences in tortuosity of pore paths between healthy and glaucomatous eyes. We imaged 16 healthy, 23 glaucoma suspect and 48 glaucomatous eyes from 70 subjects using a swept source optical coherence tomography system. The lamina cribrosa pores were automatically segmented using a previously described segmentation algorithm. Individual pore paths were automatically tracked through the depth of the lamina cribrosa using custom software. Pore path convergence to the optic nerve center and tortuosity was quantified for each eye. We found that lamina cribrosa pore pathways traverse the lamina cribrosa closer to the optic nerve center along the depth of the lamina cribrosa regardless of disease severity or diagnostic category. In addition, pores of glaucoma eyes take a more tortuous path through the lamina cribrosa compared to those of healthy eyes, suggesting a potential mechanism for reduction of axoplasmic flow in glaucoma.

Accurate Segmentation of Cervical Cytoplasm and Nuclei Based on Multiscale Convolutional Network and Graph Partitioning.

PubMed

Song, Youyi; Zhang, Ling; Chen, Siping; Ni, Dong; Lei, Baiying; Wang, Tianfu

2015-10-01

In this paper, a multiscale convolutional network (MSCN) and graph-partitioning-based method is proposed for accurate segmentation of cervical cytoplasm and nuclei. Specifically, deep learning via the MSCN is explored to extract scale invariant features, and then, segment regions centered at each pixel. The coarse segmentation is refined by an automated graph partitioning method based on the pretrained feature. The texture, shape, and contextual information of the target objects are learned to localize the appearance of distinctive boundary, which is also explored to generate markers to split the touching nuclei. For further refinement of the segmentation, a coarse-to-fine nucleus segmentation framework is developed. The computational complexity of the segmentation is reduced by using superpixel instead of raw pixels. Extensive experimental results demonstrate that the proposed cervical nucleus cell segmentation delivers promising results and outperforms existing methods.

Segmental Analysis of Chlorprothixene and Desmethylchlorprothixene in Postmortem Hair.

PubMed

Günther, Kamilla Nyborg; Johansen, Sys Stybe; Wicktor, Petra; Banner, Jytte; Linnet, Kristian

2018-06-26

Analysis of drugs in hair differs from their analysis in other tissues due to the extended detection window, as well as the opportunity that segmental hair analysis offers for the detection of changes in drug intake over time. The antipsychotic drug chlorprothixene is widely used, but few reports exist on chlorprothixene concentrations in hair. In this study, we analyzed hair segments from 20 deceased psychiatric patients who had undergone chronic chlorprothixene treatment, and we report hair concentrations of chlorprothixene and its metabolite desmethylchlorprothixene. Three to six 1-cm long segments were analyzed per individual, corresponding to ~3-6 months of hair growth before death, depending on the length of the hair. We used a previously published and fully validated liquid chromatography-tandem mass spectrometry method for the hair analysis. The 10th-90th percentiles of chlorprothixene and desmethylchlorprothixene concentrations in all hair segments were 0.05-0.84 ng/mg and 0.06-0.89 ng/mg, respectively, with medians of 0.21 and 0.24 ng/mg, and means of 0.38 and 0.43 ng/mg. The estimated daily dosages ranged from 28 mg/day to 417 mg/day. We found a significant positive correlation between the concentration in hair and the estimated daily doses for both chlorprothixene (P = 0.0016, slope = 0.0044 [ng/mg hair]/[mg/day]) and the metabolite desmethylchlorprothixene (P = 0.0074). Concentrations generally decreased throughout the hair shaft from proximal to distal segments, with an average reduction in concentration from segment 1 to segment 3 of 24% for all cases, indicating that most of the individuals had been compliant with their treatment. We have provided some guidance regarding reference levels for chlorprothixene and desmethylchlorprothixene concentrations in hair from patients undergoing long-term chlorprothixene treatment.

Biomechanics and muscle coordination of human walking. Part I: introduction to concepts, power transfer, dynamics and simulations.

PubMed

Zajac, Felix E; Neptune, Richard R; Kautz, Steven A

2002-12-01

Current understanding of how muscles coordinate walking in humans is derived from analyses of body motion, ground reaction force and EMG measurements. This is Part I of a two-part review that emphasizes how muscle-driven dynamics-based simulations assist in the understanding of individual muscle function in walking, especially the causal relationships between muscle force generation and walking kinematics and kinetics. Part I reviews the strengths and limitations of Newton-Euler inverse dynamics and dynamical simulations, including the ability of each to find the contributions of individual muscles to the acceleration/deceleration of the body segments. We caution against using the concept of biarticular muscles transferring power from one joint to another to infer muscle coordination principles because energy flow among segments, even the adjacent segments associated with the joints, cannot be inferred from computation of joint powers and segmental angular velocities alone. Rather, we encourage the use of dynamical simulations to perform muscle-induced segmental acceleration and power analyses. Such analyses have shown that the exchange of segmental energy caused by the forces or accelerations induced by a muscle can be fundamentally invariant to whether the muscle is shortening, lengthening, or neither. How simulation analyses lead to understanding the coordination of seated pedaling, rather than walking, is discussed in this first part because the dynamics of pedaling are much simpler, allowing important concepts to be revealed. We elucidate how energy produced by muscles is delivered to the crank through the synergistic action of other non-energy producing muscles; specifically, that a major function performed by a muscle arises from the instantaneous segmental accelerations and redistribution of segmental energy throughout the body caused by its force generation. Part II reviews how dynamical simulations provide insight into muscle coordination of walking.

Fabrication, testing and modeling of a new flexible armor inspired from natural fish scales and osteoderms.

PubMed

Chintapalli, Ravi Kiran; Mirkhalaf, Mohammad; Dastjerdi, Ahmad Khayer; Barthelat, Francois

2014-09-01

Crocodiles, armadillo, turtles, fish and many other animal species have evolved flexible armored skins in the form of hard scales or osteoderms, which can be described as hard plates of finite size embedded in softer tissues. The individual hard segments provide protection from predators, while the relative motion of these segments provides the flexibility required for efficient locomotion. In this work, we duplicated these broad concepts in a bio-inspired segmented armor. Hexagonal segments of well-defined size and shape were carved within a thin glass plate using laser engraving. The engraved plate was then placed on a soft substrate which simulated soft tissues, and then punctured with a sharp needle mounted on a miniature loading stage. The resistance of our segmented armor was significantly higher when smaller hexagons were used, and our bio-inspired segmented glass displayed an increase in puncture resistance of up to 70% compared to a continuous plate of glass of the same thickness. Detailed structural analyses aided by finite elements revealed that this extraordinary improvement is due to the reduced span of individual segments, which decreases flexural stresses and delays fracture. This effect can however only be achieved if the plates are at least 1000 stiffer than the underlying substrate, which is the case for natural armor systems. Our bio-inspired system also displayed many of the attributes of natural armors: flexible, robust with 'multi-hit' capabilities. This new segmented glass therefore suggests interesting bio-inspired strategies and mechanisms which could be systematically exploited in high-performance flexible armors. This study also provides new insights and a better understanding of the mechanics of natural armors such as scales and osteoderms.

Maxillary segmental distraction in children with unilateral clefts of lip, palate, and alveolus.

PubMed

Zemann, Wolfgang; Pichelmayer, Margit

2011-06-01

Alveolar clefts are commonly closed by a bone grafting procedure. In cases of wide clefts the deficiency of soft tissue in the cleft area may lead to wound dehiscence and loss of the bony graft. Segmental maxillary bony transfer has been mentioned to be useful in such cases. Standard distraction devices allow unidirectional movement of the transported segment. Ideally the distraction should strictly follow the dental arch. The aim of this study was to analyze distraction devices that were adapted to the individual clinical situation of the patients. The goal was to achieve a distraction strictly parallel to the dental arch. Six children with unilateral clefts of lip, palate, and alveolus between 12 and 13 years of age were included in the study. The width of the cleft was between 7 and 19 mm. Dental cast models were used to manufacture individual distraction devices that should allow a segmental bony transport strictly parallel to the dental arch. Segmental osteotomy was performed under general anesthesia. Distraction was started 5 days after surgery. All distracters were tooth fixed but supported by palatal inserted orthodontic miniscrews. In all patients, a closure of the alveolar cleft was achieved. Two patients required additional bone grafting after the distraction procedure. The distraction was strictly parallel to the dental arch in all cases. In 1 case a slight cranial displacement of the transported maxillary segment could be noticed, leading to minor modifications of the following distractors. Distraction osteogenesis is a proper method to close wide alveolar clefts. Linear segmental transport is required in the posterior part of the dental arch, whereas in the frontal part the bony transport should run strictly parallel to the dental arch. An exact guided segmental transport may reduce the postoperative orthodontic complexity. Copyright © 2011 Mosby, Inc. All rights reserved.

Segmental dilatation of sigmoid colon in a neonate: atypical presentation and histology.

PubMed

Mahadevaiah, Shubha Attibele; Panjwani, Poonam; Kini, Usha; Mohanty, Suravi; Das, Kanishka

2011-03-01

Segmental dilatation of the colon is a rare disorder of colonic motility in children, often presenting with severe constipation in older infants, children, and occasionally adults. It may mimic the commoner Hirschsprung disease clinicoradiologically but differs in that the ganglion cell morphology and distribution are typically normal in the colon. We report a neonate with segmental dilatation of the sigmoid colon who had an atypical clinical presentation and describe certain abnormalities in bowel histology (hypertrophied muscularis propria, nerve plexus, and ganglion cells located within the circular layer rather than the normal myenteric location), for the first time in the English literature. Copyright © 2011 Elsevier Inc. All rights reserved.

An automated approach to the segmentation of HEp-2 cells for the indirect immunofluorescence ANA test.

PubMed

Tonti, Simone; Di Cataldo, Santa; Bottino, Andrea; Ficarra, Elisa

2015-03-01

The automatization of the analysis of Indirect Immunofluorescence (IIF) images is of paramount importance for the diagnosis of autoimmune diseases. This paper proposes a solution to one of the most challenging steps of this process, the segmentation of HEp-2 cells, through an adaptive marker-controlled watershed approach. Our algorithm automatically conforms the marker selection pipeline to the peculiar characteristics of the input image, hence it is able to cope with different fluorescent intensities and staining patterns without any a priori knowledge. Furthermore, it shows a reduced sensitivity to over-segmentation errors and uneven illumination, that are typical issues of IIF imaging. Copyright © 2015 Elsevier Ltd. All rights reserved.

Individualized cattle copy number and segmental duplication maps using next generation sequencing

USDA-ARS?s Scientific Manuscript database

Copy Number Variations (CNVs) affect a wide range of phenotypic traits; however, CNVs in or near segmental duplication regions are often intractable. Using a read depth approach based on next generation sequencing, we examined genome-wide copy number differences among five taurine (three Angus, one ...

HapFABIA: Identification of very short segments of identity by descent characterized by rare variants in large sequencing data

PubMed Central

Hochreiter, Sepp

2013-01-01

Identity by descent (IBD) can be reliably detected for long shared DNA segments, which are found in related individuals. However, many studies contain cohorts of unrelated individuals that share only short IBD segments. New sequencing technologies facilitate identification of short IBD segments through rare variants, which convey more information on IBD than common variants. Current IBD detection methods, however, are not designed to use rare variants for the detection of short IBD segments. Short IBD segments reveal genetic structures at high resolution. Therefore, they can help to improve imputation and phasing, to increase genotyping accuracy for low-coverage sequencing and to increase the power of association studies. Since short IBD segments are further assumed to be old, they can shed light on the evolutionary history of humans. We propose HapFABIA, a computational method that applies biclustering to identify very short IBD segments characterized by rare variants. HapFABIA is designed to detect short IBD segments in genotype data that were obtained from next-generation sequencing, but can also be applied to DNA microarray data. Especially in next-generation sequencing data, HapFABIA exploits rare variants for IBD detection. HapFABIA significantly outperformed competing algorithms at detecting short IBD segments on artificial and simulated data with rare variants. HapFABIA identified 160 588 different short IBD segments characterized by rare variants with a median length of 23 kb (mean 24 kb) in data for chromosome 1 of the 1000 Genomes Project. These short IBD segments contain 752 000 single nucleotide variants (SNVs), which account for 39% of the rare variants and 23.5% of all variants. The vast majority—152 000 IBD segments—are shared by Africans, while only 19 000 and 11 000 are shared by Europeans and Asians, respectively. IBD segments that match the Denisova or the Neandertal genome are found significantly more often in Asians and Europeans but also, in some cases exclusively, in Africans. The lengths of IBD segments and their sharing between continental populations indicate that many short IBD segments from chromosome 1 existed before humans migrated out of Africa. Thus, rare variants that tag these short IBD segments predate human migration from Africa. The software package HapFABIA is available from Bioconductor. All data sets, result files and programs for data simulation, preprocessing and evaluation are supplied at http://www.bioinf.jku.at/research/short-IBD. PMID:24174545

Revisiting the segmental organization of the human spinal cord.

PubMed

Leijnse, J N; D'Herde, K

2016-09-01

In classic anatomic atlases, the spinal cord is standardly represented in its anatomical form with symmetrically emerging anterior and posterior roots, which at the level of the intervertebral foramen combine into the spinal nerves. The parts of the cord delimited by the boundaries of the roots are called segments or myelomeres. Associated with their regular repetitive appearance is the notion that the cord is segmentally organized. This segmental view is reinforced by clinical practice. Spinal cord roots innervate specific body parts. The level of cord trauma is diagnosed by the de-innervation symptoms of these parts. However, systemically, the case for a segmentally organized cord is not so clear. To date, developmental and genetic research points to a regionally rather than a segmentally organized cord. In the present study, to what degree the fila radicularia are segmentally implanted along the cord was investigated. The research hypothesis was that if the fila radicularia were non-segmentally implanted at the cord surface, it would be unlikely that the internal neuron stratum would be segmented. The visual segmented aspect of the myelomeres would then be the consequence of the necessary bundling of axons towards the vertebral foramen as the only exits of the vertebral canal, rather than of an underlying segment organization of the cord itself. To investigate the research hypothesis, the fila radicularia in the cervical-upper thoracic part of five spinal cords were detached from their spinal nerves and dissected in detail. The principal research question was if the fila radicularia are separated from their spinal nerves and dissected from their connective tissues up to the cord, would it be possible to reconstruct the original spinal segments from the morphology and interspaces of the fila? The dissections revealed that the anterior fila radicularia emerge from the cord at regular regionally modulated interspaces without systematic segmental delineations. The posterior fila radicularia are somewhat more segmentally implanted, but the pattern is individually inconsistent. The posterior and anterior roots have notable morphological differences, and hypotheses are presented to help explain these. The macroscopic observations are consistent with a regionally but not a segmentally organized cord. This conclusion was visually summarized in photographs of spinal cords with ipsilateral intact roots and contralateral individually dissected fila radicularia. It was suggested that this dual view of the spinal cord be added to the standard anatomic textbooks to counterbalance the current possibly biased view of a segmented cord. © 2016 Anatomical Society.

Do Chinese Readers Follow the National Standard Rules for Word Segmentation during Reading?

PubMed Central

Liu, Ping-Ping; Li, Wei-Jun; Lin, Nan; Li, Xing-Shan

2013-01-01

We conducted a preliminary study to examine whether Chinese readers’ spontaneous word segmentation processing is consistent with the national standard rules of word segmentation based on the Contemporary Chinese language word segmentation specification for information processing (CCLWSSIP). Participants were asked to segment Chinese sentences into individual words according to their prior knowledge of words. The results showed that Chinese readers did not follow the segmentation rules of the CCLWSSIP, and their word segmentation processing was influenced by the syntactic categories of consecutive words. In many cases, the participants did not consider the auxiliary words, adverbs, adjectives, nouns, verbs, numerals and quantifiers as single word units. Generally, Chinese readers tended to combine function words with content words to form single word units, indicating they were inclined to chunk single words into large information units during word segmentation. Additionally, the “overextension of monosyllable words” hypothesis was tested and it might need to be corrected to some degree, implying that word length have an implicit influence on Chinese readers’ segmentation processing. Implications of these results for models of word recognition and eye movement control are discussed. PMID:23408981

Automatic segmentation and supervised learning-based selection of nuclei in cancer tissue images.

PubMed

Nandy, Kaustav; Gudla, Prabhakar R; Amundsen, Ryan; Meaburn, Karen J; Misteli, Tom; Lockett, Stephen J

2012-09-01

Analysis of preferential localization of certain genes within the cell nuclei is emerging as a new technique for the diagnosis of breast cancer. Quantitation requires accurate segmentation of 100-200 cell nuclei in each tissue section to draw a statistically significant result. Thus, for large-scale analysis, manual processing is too time consuming and subjective. Fortuitously, acquired images generally contain many more nuclei than are needed for analysis. Therefore, we developed an integrated workflow that selects, following automatic segmentation, a subpopulation of accurately delineated nuclei for positioning of fluorescence in situ hybridization-labeled genes of interest. Segmentation was performed by a multistage watershed-based algorithm and screening by an artificial neural network-based pattern recognition engine. The performance of the workflow was quantified in terms of the fraction of automatically selected nuclei that were visually confirmed as well segmented and by the boundary accuracy of the well-segmented nuclei relative to a 2D dynamic programming-based reference segmentation method. Application of the method was demonstrated for discriminating normal and cancerous breast tissue sections based on the differential positioning of the HES5 gene. Automatic results agreed with manual analysis in 11 out of 14 cancers, all four normal cases, and all five noncancerous breast disease cases, thus showing the accuracy and robustness of the proposed approach. Published 2012 Wiley Periodicals, Inc.

Rod-Coil Block Polyimide Copolymers

NASA Technical Reports Server (NTRS)

Meador, Mary Ann B. (Inventor); Kinder, James D. (Inventor)

2005-01-01

This invention is a series of rod-coil block polyimide copolymers that are easy to fabricate into mechanically resilient films with acceptable ionic or protonic conductivity at a variety of temperatures. The copolymers consist of short-rigid polyimide rod segments alternating with polyether coil segments. The rods and coil segments can be linear, branched or mixtures of linear and branched segments. The highly incompatible rods and coil segments phase separate, providing nanoscale channels for ion conduction. The polyimide segments provide dimensional and mechanical stability and can be functionalized in a number of ways to provide specialized functions for a given application. These rod-coil black polyimide copolymers are particularly useful in the preparation of ion conductive membranes for use in the manufacture of fuel cells and lithium based polymer batteries.

Distinct functions for IFT140 and IFT20 in opsin transport.

PubMed Central

Crouse, Jacquelin A.; Lopes, Vanda S.; SanAgustin, Jovenal T.; Keady, Brian T.; Williams, David S.; Pazour, Gregory J.

2014-01-01

In the vertebrate retina, light is detected by the outer segments of photoreceptor rods and cones, which are highly modified cilia. Like other cilia, outer segments have no protein synthetic capacity and depend on proteins made in the cell body for their formation and maintenance. The mechanism of transport into the outer segment is not fully understood but intraflagellar transport (IFT) is thought to be a major mechanism for moving protein from the cell body into the cilium. In the case of photoreceptor cells, the high density of receptors and the disk turnover that occurs daily necessitates much higher rates of transport than would be required in other cilia. In this work, we show that the IFT complex A protein IFT140 is required for development and maintenance of outer segments. In earlier work we found that acute deletion of Ift20 caused opsin to accumulate at the Golgi complex. In this work we find that acute deletion of Ift140 does not cause opsin to accumulate at the Golgi complex but rather it accumulates in the plasma membrane of the inner segments. This work is strong support of a model of opsin transport where IFT20 is involved in the movement from the Golgi complex to the base of the cilium. Then, once at the base, the opsin is carried through the connecting cilium by an IFT complex that includes IFT140. PMID:24619649

Evidence against the involvement of ionically bound cell wall proteins in pea epicotyl growth

NASA Technical Reports Server (NTRS)

Melan, M. A.; Cosgrove, D. J.

1988-01-01

Ionically bound cell wall proteins were extracted from 7 day old etiolated pea (Pisum sativum L. cv Alaska) epicotyls with 3 molar LiCl. Polyclonal antiserum was raised in rabbits against the cell wall proteins. Growth assays showed that treatment of growing region segments (5-7 millimeters) of peas with either dialyzed serum, serum globulin fraction, affinity purified immunoglobulin, or papain-cleaved antibody fragments had no effect on growth. Immunofluorescence microscopy confirmed antibody binding to cell walls and penetration of the antibodies into the tissues. Western blot analysis, immunoassay results, and affinity chromatography utilizing Sepharose-bound antibodies confirmed recognition of the protein preparation by the antibodies. Experiments employing in vitro extension as a screening measure indicated no effect upon extension by antibodies, by 50 millimolar LiCl perfusion of the apoplast or by 3 molar LiCl extraction. Addition of cell wall protein to protease pretreated segments did not restore extension nor did addition of cell wall protein to untreated segments increase extension. It is concluded that, although evidence suggests that protein is responsible for the process of extension, the class(es) of proteins which are extracted from pea cell walls with 3 molar LiCl are probably not involved in this process.

Ferromagnetic nanowires: Field-induced self-assembly, magnetotransport and biological applications

NASA Astrophysics Data System (ADS)

Tanase, Monica

In this dissertation, a series of experiments on magnetic nanowires are described. Magnetic nanowires suspended in fluid solutions can be assembled and ordered by taking advantage of their large shape anisotropy. Magnetic manipulation and assembly techniques were developed, using electrodeposited Ni nanowires. Preorienting nanowires in a small magnetic field induced their self-assembly in continuous chains. A new technique of magnetic trapping allowed capture of single nanowires from fluid suspension on lithographically fabricated micromagnets. As described herein, the presence of an external magnetic field plays a fundamental role in all fluid assembly methods used. The dynamics of both chaining and trapping processes is described quantitatively in terms of the interplay of magnetic forces and fluid drag at low Reynolds number. Lithographic methods for addressing single nanowires for transport characterization were developed. Magnetotransport measurements were performed on individual straight and bent PtNiPt nanowires. The Pt end segments provided an oxide-free interface to the magnetic central segment. In straight nanowires, domain reversal was observed to occur via curling mode initiated in a small nucleation volume. Magnetotransport in bent nanowires allowed the investigation of a domain wall trapped at the bend. Magnetic trapping of nanowires on pre-fabricated electrodes was adapted as a successful alternative contacting technique to lithography. The self-assembly and manipulation techniques were adapted for manipulation of cells as nanowires were found to bind to cells through nonspecific adhesion mechanisms. Ni nanowires were found to outperform superparamagnetic beads in magnetic cell separations. Additionally, the large remnant magnetization of the nanowires allowed for low-field manipulation techniques. Self-assembled chains of cells were formed and single cells were localized on substrates patterned with micromagnets. A fluid flow method was developed to controllably introduce the cells in the proximity of arrays of micromagnets. Cells decorated the arrays forming patterns described well by dipolar interactions between the magnetic elements and the nanowires. Calculations of the locations favorable for trapping were performed by evaluating the energy of interaction between the array and the nanowires. A second-order mechanism of cell capture was also identified, i.e. chaining by wire-wire dipolar interaction.

A structure-based approach for colon gland segmentation in digital pathology

NASA Astrophysics Data System (ADS)

Ben Cheikh, Bassem; Bertheau, Philippe; Racoceanu, Daniel

2016-03-01

The morphology of intestinal glands is an important and significant indicator of the level of the severity of an inflammatory bowel disease, and has also been used routinely by pathologists to evaluate the malignancy and the prognosis of colorectal cancers such as adenocarcinomas. The extraction of meaningful information describing the morphology of glands relies on an accurate segmentation method. In this work, we propose a novel technique based on mathematical morphology that characterizes the spatial positioning of nuclei for intestinal gland segmentation in histopathological images. According to their appearance, glands can be divided into two types: hallow glands and solid glands. Hallow glands are composed of lumen and/or goblet cells cytoplasm, or filled with abscess in some advanced stages of the disease, while solid glands are composed of bunches of cells clustered together and can also be filled with necrotic debris. Given this scheme, an efficient characterization of the spatial distribution of cells is sufficient to carry out the segmentation. In this approach, hallow glands are first identified as regions empty of nuclei and surrounded by thick layers of epithelial cells, then solid glands are identified by detecting regions crowded of nuclei. First, cell nuclei are identified by color classification. Then, morphological maps are generated by the mean of advanced morphological operators applied to nuclei objects in order to interpret their spatial distribution and properties to identify candidates for glands central-regions and epithelial layers that are combined to extract the glandular structures.

Estimation of Total Length of Femur from its Proximal and Distal Segmental Measurements of Disarticulated Femur Bones of Nepalese Population using Regression Equation Method.

PubMed

Khanal, Laxman; Shah, Sandip; Koirala, Sarun

2017-03-01

Length of long bones is taken as an important contributor for estimating one of the four elements of forensic anthropology i.e., stature of the individual. Since physical characteristics of the individual differ among different groups of population, population specific studies are needed for estimating the total length of femur from its segment measurements. Since femur is not always recovered intact in forensic cases, it was the aim of this study to derive regression equations from measurements of proximal and distal fragments in Nepalese population. A cross-sectional study was done among 60 dry femora (30 from each side) without sex determination in anthropometry laboratory. Along with maximum femoral length, four proximal and four distal segmental measurements were measured following the standard method with the help of osteometric board, measuring tape and digital Vernier's caliper. Bones with gross defects were excluded from the study. Measured values were recorded separately for right and left side. Statistical Package for Social Science (SPSS version 11.5) was used for statistical analysis. The value of segmental measurements were different between right and left side but statistical difference was not significant except for depth of medial condyle (p=0.02). All the measurements were positively correlated and found to have linear relationship with the femoral length. With the help of regression equation, femoral length can be calculated from the segmental measurements; and then femoral length can be used to calculate the stature of the individual. The data collected may contribute in the analysis of forensic bone remains in study population.

Automatic vision-based grain optimization and analysis of multi-crystalline solar wafers using hierarchical region growing

NASA Astrophysics Data System (ADS)

Fan, Shu-Kai S.; Tsai, Du-Ming; Chuang, Wei-Che

2017-04-01

Solar power has become an attractive alternative source of energy. The multi-crystalline solar cell has been widely accepted in the market because it has a relatively low manufacturing cost. Multi-crystalline solar wafers with larger grain sizes and fewer grain boundaries are higher quality and convert energy more efficiently than mono-crystalline solar cells. In this article, a new image processing method is proposed for assessing the wafer quality. An adaptive segmentation algorithm based on region growing is developed to separate the closed regions of individual grains. Using the proposed method, the shape and size of each grain in the wafer image can be precisely evaluated. Two measures of average grain size are taken from the literature and modified to estimate the average grain size. The resulting average grain size estimate dictates the quality of the crystalline solar wafers and can be considered a viable quantitative indicator of conversion efficiency.

Low-Cost Space Structure (LCSS) Experiment. Volume I of II.

DTIC Science & Technology

1996-06-01

Cell Multiline laser - 2 100 Hold spots at BSM2 (tilts optica Tilt spots fixed offset path of (1/segment) w.r.t. 1 segment only) each other with off...Piston/Fine Piston Sensor Multiline Laser 3 Piston 1 BSM2 (pistons LEC segment w.r.t. optical path of other to 1 segment only) increase sharpness 7 LGSS...independent steering and pistoning of one beamline with respect to the other with the fixed mirror M2 and tilt/piston mirror BSM2 pair. The telescope

Boundary segmentation for fluorescence microscopy using steerable filters

NASA Astrophysics Data System (ADS)

Ho, David Joon; Salama, Paul; Dunn, Kenneth W.; Delp, Edward J.

2017-02-01

Fluorescence microscopy is used to image multiple subcellular structures in living cells which are not readily observed using conventional optical microscopy. Moreover, two-photon microscopy is widely used to image structures deeper in tissue. Recent advancement in fluorescence microscopy has enabled the generation of large data sets of images at different depths, times, and spectral channels. Thus, automatic object segmentation is necessary since manual segmentation would be inefficient and biased. However, automatic segmentation is still a challenging problem as regions of interest may not have well defined boundaries as well as non-uniform pixel intensities. This paper describes a method for segmenting tubular structures in fluorescence microscopy images of rat kidney and liver samples using adaptive histogram equalization, foreground/background segmentation, steerable filters to capture directional tendencies, and connected-component analysis. The results from several data sets demonstrate that our method can segment tubular boundaries successfully. Moreover, our method has better performance when compared to other popular image segmentation methods when using ground truth data obtained via manual segmentation.

Optical Amplifier for Space Applications

NASA Technical Reports Server (NTRS)

Fork, Richard L.; Cole, Spencer T.; Gamble, Lisa J.; Diffey, William M.; Keys, Andrew S.

1999-01-01

We describe an optical amplifier designed to amplify a spatially sampled component of an optical wavefront to kilowatt average power. The goal is means for implementing a strategy of spatially segmenting a large aperture wavefront, amplifying the individual segments, maintaining the phase coherence of the segments by active means, and imaging the resultant amplified coherent field. Applications of interest are the transmission of space solar power over multi-megameter distances, as to distant spacecraft, or to remote sites with no preexisting power grid.

The spatial and temporal expression of Ch-en, the engrailed gene in the polychaete Chaetopterus, does not support a role in body axis segmentation

NASA Technical Reports Server (NTRS)

Seaver, E. C.; Paulson, D. A.; Irvine, S. Q.; Martindale, M. Q.

2001-01-01

We are interested in understanding whether the annelids and arthropods shared a common segmented ancestor and have approached this question by characterizing the expression pattern of the segment polarity gene engrailed (en) in a basal annelid, the polychaete Chaetopterus. We have isolated an en gene, Ch-en, from a Chaetopterus cDNA library. Genomic Southern blotting suggests that this is the only en class gene in this animal. The predicted protein sequence of the 1.2-kb cDNA clone contains all five domains characteristic of en proteins in other taxa, including the en class homeobox. Whole-mount in situ hybridization reveals that Ch-en is expressed throughout larval life in a complex spatial and temporal pattern. The Ch-en transcript is initially detected in a small number of neurons associated with the apical organ and in the posterior portion of the prototrochophore. At later stages, Ch-en is expressed in distinct patterns in the three segmented body regions (A, B, and C) of Chaetopterus. In all segments, Ch-en is expressed in a small set of segmentally iterated cells in the CNS. In the A region, Ch-en is also expressed in a small group of mesodermal cells at the base of the chaetal sacs. In the B region, Ch-en is initially expressed broadly in the mesoderm that then resolves into one band/segment coincident with morphological segmentation. The mesodermal expression in the B region is located in the anterior region of each segment, as defined by the position of ganglia in the ventral nerve cord, and is involved in the morphogenesis of segment-specific feeding structures late in larval life. We observe banded mesodermal and ectodermal staining in an anterior-posterior sequence in the C region. We do not observe a segment polarity pattern of expression of Ch-en in the ectoderm, as is observed in arthropods. Copyright 2001 Academic Press.

Confidence-based ensemble for GBM brain tumor segmentation

NASA Astrophysics Data System (ADS)

Huo, Jing; van Rikxoort, Eva M.; Okada, Kazunori; Kim, Hyun J.; Pope, Whitney; Goldin, Jonathan; Brown, Matthew

2011-03-01

It is a challenging task to automatically segment glioblastoma multiforme (GBM) brain tumors on T1w post-contrast isotropic MR images. A semi-automated system using fuzzy connectedness has recently been developed for computing the tumor volume that reduces the cost of manual annotation. In this study, we propose a an ensemble method that combines multiple segmentation results into a final ensemble one. The method is evaluated on a dataset of 20 cases from a multi-center pharmaceutical drug trial and compared to the fuzzy connectedness method. Three individual methods were used in the framework: fuzzy connectedness, GrowCut, and voxel classification. The combination method is a confidence map averaging (CMA) method. The CMA method shows an improved ROC curve compared to the fuzzy connectedness method (p < 0.001). The CMA ensemble result is more robust compared to the three individual methods.

One size does not fit all: how the tobacco industry has altered cigarette design to target consumer groups with specific psychological and psychosocial needs.

PubMed

Cook, Benjamin Lê; Wayne, Geoffrey Ferris; Keithly, Lois; Connolly, Gregory

2003-11-01

To identify whether the tobacco industry has targeted cigarette product design towards individuals with varying psychological/psychosocial needs. Internal industry documents were identified through searches of an online archival document research tool database using relevancy criteria of consumer segmentation and needs assessment. The industry segmented consumer markets based on psychological needs (stress relief, behavioral arousal, performance enhancement, obesity reduction) and psychosocial needs (social acceptance, personal image). Associations between these segments and smoking behaviors, brand and design preferences were used to create cigarette brands targeting individuals with these needs. Cigarette brands created to address the psychological/psychosocial needs of smokers may increase the likelihood of smoking initiation and addiction. Awareness of targeted product development will improve smoking cessation and prevention efforts.

Serotonin projection patterns to the cochlear nucleus.

PubMed

Thompson, A M; Thompson, G C

2001-07-13

The cochlear nucleus is well known as an obligatory relay center for primary auditory nerve fibers. Perhaps not so well known is the neural input to the cochlear nucleus from cells containing serotonin that reside near the midline in the midbrain raphe region. Although the specific locations of the main, if not sole, sources of serotonin within the dorsal cochlear nucleus subdivision are known to be the dorsal and median raphe nuclei, sources of serotonin located within other cochlear nucleus subdivisions are not currently known. Anterograde tract tracing was used to label fibers originating from the dorsal and median raphe nuclei while fluorescence immunohistochemistry was used to simultaneously label specific serotonin fibers in cat. Biotinylated dextran amine was injected into the dorsal and median raphe nuclei and was visualized with Texas Red, while serotonin was visualized with fluorescein. Thus, double-labeled fibers were unequivocally identified as serotoninergic and originating from one of the labeled neurons within the dorsal and median raphe nuclei. Double-labeled fiber segments, typically of fine caliber with oval varicosities, were observed in many areas of the cochlear nucleus. They were found in the molecular layer of the dorsal cochlear nucleus, in the small cell cap region, and in the granule cell and external regions of the cochlear nuclei, bilaterally, of all cats. However, the density of these double-labeled fiber segments varied considerably depending upon the exact region in which they were found. Fiber segments were most dense in the dorsal cochlear nucleus (especially in the molecular layer) and the large spherical cell area of the anteroventral cochlear nucleus; they were moderately dense in the small cell cap region; and fiber segments were least dense in the octopus and multipolar cell regions of the posteroventral cochlear nucleus. Because of the presence of labeled fiber segments in subdivisions of the cochlear nucleus other than the dorsal cochlear nucleus, we concluded that the serotoninergic projection pattern to the cochlear nucleus is divergent and non-specific. Double-labeled fiber segments were also present, but sparse, in the superior olive, localized mainly in periolivary regions; this indicated that the divergence of dorsal and median raphe neurons that extends throughout regions of the cochlear nucleus also extended well beyond the cochlear nucleus to include at least the superior olivary complex as well.

Vectorization of optically sectioned brain microvasculature: learning aids completion of vascular graphs by connecting gaps and deleting open-ended segments.

PubMed

Kaufhold, John P; Tsai, Philbert S; Blinder, Pablo; Kleinfeld, David

2012-08-01

A graph of tissue vasculature is an essential requirement to model the exchange of gasses and nutriments between the blood and cells in the brain. Such a graph is derived from a vectorized representation of anatomical data, provides a map of all vessels as vertices and segments, and may include the location of nonvascular components, such as neuronal and glial somata. Yet vectorized data sets typically contain erroneous gaps, spurious endpoints, and spuriously merged strands. Current methods to correct such defects only address the issue of connecting gaps and further require manual tuning of parameters in a high dimensional algorithm. To address these shortcomings, we introduce a supervised machine learning method that (1) connects vessel gaps by "learned threshold relaxation"; (2) removes spurious segments by "learning to eliminate deletion candidate strands"; and (3) enforces consistency in the joint space of learned vascular graph corrections through "consistency learning." Human operators are only required to label individual objects they recognize in a training set and are not burdened with tuning parameters. The supervised learning procedure examines the geometry and topology of features in the neighborhood of each vessel segment under consideration. We demonstrate the effectiveness of these methods on four sets of microvascular data, each with >800(3) voxels, obtained with all optical histology of mouse tissue and vectorization by state-of-the-art techniques in image segmentation. Through statistically validated sampling and analysis in terms of precision recall curves, we find that learning with bagged boosted decision trees reduces equal-error error rates for threshold relaxation by 5-21% and strand elimination performance by 18-57%. We benchmark generalization performance across datasets; while improvements vary between data sets, learning always leads to a useful reduction in error rates. Overall, learning is shown to more than halve the total error rate, and therefore, human time spent manually correcting such vectorizations. Copyright © 2012 Elsevier B.V. All rights reserved.

Vectorization of optically sectioned brain microvasculature: Learning aids completion of vascular graphs by connecting gaps and deleting open-ended segments

PubMed Central

Kaufhold, John P.; Tsai, Philbert S.; Blinder, Pablo; Kleinfeld, David

2012-01-01

A graph of tissue vasculature is an essential requirement to model the exchange of gasses and nutriments between the blood and cells in the brain. Such a graph is derived from a vectorized representation of anatomical data, provides a map of all vessels as vertices and segments, and may include the location of nonvascular components, such as neuronal and glial somata. Yet vectorized data sets typically contain erroneous gaps, spurious endpoints, and spuriously merged strands. Current methods to correct such defects only address the issue of connecting gaps and further require manual tuning of parameters in a high dimensional algorithm. To address these shortcomings, we introduce a supervised machine learning method that (1) connects vessel gaps by “learned threshold relaxation”; (2) removes spurious segments by “learning to eliminate deletion candidate strands”; and (3) enforces consistency in the joint space of learned vascular graph corrections through “consistency learning.” Human operators are only required to label individual objects they recognize in a training set and are not burdened with tuning parameters. The supervised learning procedure examines the geometry and topology of features in the neighborhood of each vessel segment under consideration. We demonstrate the effectiveness of these methods on four sets of microvascular data, each with > 8003 voxels, obtained with all optical histology of mouse tissue and vectorization by state-of-the-art techniques in image segmentation. Through statistically validated sampling and analysis in terms of precision recall curves, we find that learning with bagged boosted decision trees reduces equal-error error rates for threshold relaxation by 5 to 21 % and strand elimination performance by 18 to 57 %. We benchmark generalization performance across datasets; while improvements vary between data sets, learning always leads to a useful reduction in error rates. Overall, learning is shown to more than halve the total error rate, and therefore, human time spent manually correcting such vectorizations. PMID:22854035

Optimization of GaAs Nanowire Pin Junction Array Solar Cells by Using AlGaAs/GaAs Heterojunctions

NASA Astrophysics Data System (ADS)

Wu, Yao; Yan, Xin; Wei, Wei; Zhang, Jinnan; Zhang, Xia; Ren, Xiaomin

2018-04-01

We optimized the performance of GaAs nanowire pin junction array solar cells by introducing AlGaAs/GaAs heterejunctions. AlGaAs is used for the p type top segment for axial junctions and the p type outer shell for radial junctions. The AlGaAs not only serves as passivation layers for GaAs nanowires but also confines the optical generation in the active regions, reducing the recombination loss in heavily doped regions and the minority carrier recombination at the top contact. The results show that the conversion efficiency of GaAs nanowires can be greatly enhanced by using AlGaAs for the p segment instead of GaAs. A maximum efficiency enhancement of 8.42% has been achieved in this study. And for axial nanowire, by using AlGaAs for the top p segment, a relatively long top segment can be employed without degenerating device performance, which could facilitate the fabrication and contacting of nanowire array solar cells. While for radial nanowires, AlGaAs/GaAs nanowires show better tolerance to p-shell thickness and surface condition.

Optimization of GaAs Nanowire Pin Junction Array Solar Cells by Using AlGaAs/GaAs Heterojunctions.

PubMed

Wu, Yao; Yan, Xin; Wei, Wei; Zhang, Jinnan; Zhang, Xia; Ren, Xiaomin

2018-04-25

We optimized the performance of GaAs nanowire pin junction array solar cells by introducing AlGaAs/GaAs heterejunctions. AlGaAs is used for the p type top segment for axial junctions and the p type outer shell for radial junctions. The AlGaAs not only serves as passivation layers for GaAs nanowires but also confines the optical generation in the active regions, reducing the recombination loss in heavily doped regions and the minority carrier recombination at the top contact. The results show that the conversion efficiency of GaAs nanowires can be greatly enhanced by using AlGaAs for the p segment instead of GaAs. A maximum efficiency enhancement of 8.42% has been achieved in this study. And for axial nanowire, by using AlGaAs for the top p segment, a relatively long top segment can be employed without degenerating device performance, which could facilitate the fabrication and contacting of nanowire array solar cells. While for radial nanowires, AlGaAs/GaAs nanowires show better tolerance to p-shell thickness and surface condition.

Background fluorescence estimation and vesicle segmentation in live cell imaging with conditional random fields.

PubMed

Pécot, Thierry; Bouthemy, Patrick; Boulanger, Jérôme; Chessel, Anatole; Bardin, Sabine; Salamero, Jean; Kervrann, Charles

2015-02-01

Image analysis applied to fluorescence live cell microscopy has become a key tool in molecular biology since it enables to characterize biological processes in space and time at the subcellular level. In fluorescence microscopy imaging, the moving tagged structures of interest, such as vesicles, appear as bright spots over a static or nonstatic background. In this paper, we consider the problem of vesicle segmentation and time-varying background estimation at the cellular scale. The main idea is to formulate the joint segmentation-estimation problem in the general conditional random field framework. Furthermore, segmentation of vesicles and background estimation are alternatively performed by energy minimization using a min cut-max flow algorithm. The proposed approach relies on a detection measure computed from intensity contrasts between neighboring blocks in fluorescence microscopy images. This approach permits analysis of either 2D + time or 3D + time data. We demonstrate the performance of the so-called C-CRAFT through an experimental comparison with the state-of-the-art methods in fluorescence video-microscopy. We also use this method to characterize the spatial and temporal distribution of Rab6 transport carriers at the cell periphery for two different specific adhesion geometries.