Fuzzy C-mean clustering on kinetic parameter estimation with generalized linear least square algorithm in SPECT

NASA Astrophysics Data System (ADS)

Choi, Hon-Chit; Wen, Lingfeng; Eberl, Stefan; Feng, Dagan

2006-03-01

Dynamic Single Photon Emission Computed Tomography (SPECT) has the potential to quantitatively estimate physiological parameters by fitting compartment models to the tracer kinetics. The generalized linear least square method (GLLS) is an efficient method to estimate unbiased kinetic parameters and parametric images. However, due to the low sensitivity of SPECT, noisy data can cause voxel-wise parameter estimation by GLLS to fail. Fuzzy C-Mean (FCM) clustering and modified FCM, which also utilizes information from the immediate neighboring voxels, are proposed to improve the voxel-wise parameter estimation of GLLS. Monte Carlo simulations were performed to generate dynamic SPECT data with different noise levels and processed by general and modified FCM clustering. Parametric images were estimated by Logan and Yokoi graphical analysis and GLLS. The influx rate (K I), volume of distribution (V d) were estimated for the cerebellum, thalamus and frontal cortex. Our results show that (1) FCM reduces the bias and improves the reliability of parameter estimates for noisy data, (2) GLLS provides estimates of micro parameters (K I-k 4) as well as macro parameters, such as volume of distribution (Vd) and binding potential (BP I & BP II) and (3) FCM clustering incorporating neighboring voxel information does not improve the parameter estimates, but improves noise in the parametric images. These findings indicated that it is desirable for pre-segmentation with traditional FCM clustering to generate voxel-wise parametric images with GLLS from dynamic SPECT data.

Image Segmentation Method Using Fuzzy C Mean Clustering Based on Multi-Objective Optimization

NASA Astrophysics Data System (ADS)

Chen, Jinlin; Yang, Chunzhi; Xu, Guangkui; Ning, Li

2018-04-01

Image segmentation is not only one of the hottest topics in digital image processing, but also an important part of computer vision applications. As one kind of image segmentation algorithms, fuzzy C-means clustering is an effective and concise segmentation algorithm. However, the drawback of FCM is that it is sensitive to image noise. To solve the problem, this paper designs a novel fuzzy C-mean clustering algorithm based on multi-objective optimization. We add a parameter λ to the fuzzy distance measurement formula to improve the multi-objective optimization. The parameter λ can adjust the weights of the pixel local information. In the algorithm, the local correlation of neighboring pixels is added to the improved multi-objective mathematical model to optimize the clustering cent. Two different experimental results show that the novel fuzzy C-means approach has an efficient performance and computational time while segmenting images by different type of noises.

Adaptive fuzzy system for 3-D vision

NASA Technical Reports Server (NTRS)

Mitra, Sunanda

1993-01-01

An adaptive fuzzy system using the concept of the Adaptive Resonance Theory (ART) type neural network architecture and incorporating fuzzy c-means (FCM) system equations for reclassification of cluster centers was developed. The Adaptive Fuzzy Leader Clustering (AFLC) architecture is a hybrid neural-fuzzy system which learns on-line in a stable and efficient manner. The system uses a control structure similar to that found in the Adaptive Resonance Theory (ART-1) network to identify the cluster centers initially. The initial classification of an input takes place in a two stage process; a simple competitive stage and a distance metric comparison stage. The cluster prototypes are then incrementally updated by relocating the centroid positions from Fuzzy c-Means (FCM) system equations for the centroids and the membership values. The operational characteristics of AFLC and the critical parameters involved in its operation are discussed. The performance of the AFLC algorithm is presented through application of the algorithm to the Anderson Iris data, and laser-luminescent fingerprint image data. The AFLC algorithm successfully classifies features extracted from real data, discrete or continuous, indicating the potential strength of this new clustering algorithm in analyzing complex data sets. The hybrid neuro-fuzzy AFLC algorithm will enhance analysis of a number of difficult recognition and control problems involved with Tethered Satellite Systems and on-orbit space shuttle attitude controller.

Efficient architecture for spike sorting in reconfigurable hardware.

PubMed

Hwang, Wen-Jyi; Lee, Wei-Hao; Lin, Shiow-Jyu; Lai, Sheng-Ying

2013-11-01

This paper presents a novel hardware architecture for fast spike sorting. The architecture is able to perform both the feature extraction and clustering in hardware. The generalized Hebbian algorithm (GHA) and fuzzy C-means (FCM) algorithm are used for feature extraction and clustering, respectively. The employment of GHA allows efficient computation of principal components for subsequent clustering operations. The FCM is able to achieve near optimal clustering for spike sorting. Its performance is insensitive to the selection of initial cluster centers. The hardware implementations of GHA and FCM feature low area costs and high throughput. In the GHA architecture, the computation of different weight vectors share the same circuit for lowering the area costs. Moreover, in the FCM hardware implementation, the usual iterative operations for updating the membership matrix and cluster centroid are merged into one single updating process to evade the large storage requirement. To show the effectiveness of the circuit, the proposed architecture is physically implemented by field programmable gate array (FPGA). It is embedded in a System-on-Chip (SOC) platform for performance measurement. Experimental results show that the proposed architecture is an efficient spike sorting design for attaining high classification correct rate and high speed computation.

Ozone levels in the Empty Quarter of Saudi Arabia--application of adaptive neuro-fuzzy model.

PubMed

Rahman, Syed Masiur; Khondaker, A N; Khan, Rouf Ahmad

2013-05-01

In arid regions, primary pollutants may contribute to the increase of ozone levels and cause negative effects on biotic health. This study investigates the use of adaptive neuro-fuzzy inference system (ANFIS) for ozone prediction. The initial fuzzy inference system is developed by using fuzzy C-means (FCM) and subtractive clustering (SC) algorithms, which determines the important rules, increases generalization capability of the fuzzy inference system, reduces computational needs, and ensures speedy model development. The study area is located in the Empty Quarter of Saudi Arabia, which is considered as a source of huge potential for oil and gas field development. The developed clustering algorithm-based ANFIS model used meteorological data and derived meteorological data, along with NO and NO₂ concentrations and their transformations, as inputs. The root mean square error and Willmott's index of agreement of the FCM- and SC-based ANFIS models are 3.5 ppbv and 0.99, and 8.9 ppbv and 0.95, respectively. Based on the analysis of the performance measures and regression error characteristic curves, it is concluded that the FCM-based ANFIS model outperforms the SC-based ANFIS model.

Semisupervised GDTW kernel-based fuzzy c-means algorithm for mapping vegetation dynamics in mining region using normalized difference vegetation index time series

NASA Astrophysics Data System (ADS)

Jia, Duo; Wang, Cangjiao; Lei, Shaogang

2018-01-01

Mapping vegetation dynamic types in mining areas is significant for revealing the mechanisms of environmental damage and for guiding ecological construction. Dynamic types of vegetation can be identified by applying interannual normalized difference vegetation index (NDVI) time series. However, phase differences and time shifts in interannual time series decrease mapping accuracy in mining regions. To overcome these problems and to increase the accuracy of mapping vegetation dynamics, an interannual Landsat time series for optimum vegetation growing status was constructed first by using the enhanced spatial and temporal adaptive reflectance fusion model algorithm. We then proposed a Markov random field optimized semisupervised Gaussian dynamic time warping kernel-based fuzzy c-means (FCM) cluster algorithm for interannual NDVI time series to map dynamic vegetation types in mining regions. The proposed algorithm has been tested in the Shengli mining region and Shendong mining region, which are typical representatives of China's open-pit and underground mining regions, respectively. Experiments show that the proposed algorithm can solve the problems of phase differences and time shifts to achieve better performance when mapping vegetation dynamic types. The overall accuracies for the Shengli and Shendong mining regions were 93.32% and 89.60%, respectively, with improvements of 7.32% and 25.84% when compared with the original semisupervised FCM algorithm.

A dynamic fuzzy genetic algorithm for natural image segmentation using adaptive mean shift

NASA Astrophysics Data System (ADS)

Arfan Jaffar, M.

2017-01-01

In this paper, a colour image segmentation approach based on hybridisation of adaptive mean shift (AMS), fuzzy c-mean and genetic algorithms (GAs) is presented. Image segmentation is the perceptual faction of pixels based on some likeness measure. GA with fuzzy behaviour is adapted to maximise the fuzzy separation and minimise the global compactness among the clusters or segments in spatial fuzzy c-mean (sFCM). It adds diversity to the search process to find the global optima. A simple fusion method has been used to combine the clusters to overcome the problem of over segmentation. The results show that our technique outperforms state-of-the-art methods.

Optimizing Energy Consumption in Vehicular Sensor Networks by Clustering Using Fuzzy C-Means and Fuzzy Subtractive Algorithms

NASA Astrophysics Data System (ADS)

Ebrahimi, A.; Pahlavani, P.; Masoumi, Z.

2017-09-01

Traffic monitoring and managing in urban intelligent transportation systems (ITS) can be carried out based on vehicular sensor networks. In a vehicular sensor network, vehicles equipped with sensors such as GPS, can act as mobile sensors for sensing the urban traffic and sending the reports to a traffic monitoring center (TMC) for traffic estimation. The energy consumption by the sensor nodes is a main problem in the wireless sensor networks (WSNs); moreover, it is the most important feature in designing these networks. Clustering the sensor nodes is considered as an effective solution to reduce the energy consumption of WSNs. Each cluster should have a Cluster Head (CH), and a number of nodes located within its supervision area. The cluster heads are responsible for gathering and aggregating the information of clusters. Then, it transmits the information to the data collection center. Hence, the use of clustering decreases the volume of transmitting information, and, consequently, reduces the energy consumption of network. In this paper, Fuzzy C-Means (FCM) and Fuzzy Subtractive algorithms are employed to cluster sensors and investigate their performance on the energy consumption of sensors. It can be seen that the FCM algorithm and Fuzzy Subtractive have been reduced energy consumption of vehicle sensors up to 90.68% and 92.18%, respectively. Comparing the performance of the algorithms implies the 1.5 percent improvement in Fuzzy Subtractive algorithm in comparison.

Research on the lesion segmentation of breast tumor MR images based on FCM-DS theory

NASA Astrophysics Data System (ADS)

Zhang, Liangbin; Ma, Wenjun; Shen, Xing; Li, Yuehua; Zhu, Yuemin; Chen, Li; Zhang, Su

2017-03-01

Magnetic resonance imaging (MRI) plays an important role in the treatment of breast tumor by high intensity focused ultrasound (HIFU). The doctors evaluate the scale, distribution and the statement of benign or malignancy of breast tumor by analyzing variety modalities of MRI, such as the T2, DWI and DCE images for making accurate preoperative treatment plan and evaluating the effect of the operation. This paper presents a method of lesion segmentation of breast tumor based on FCM-DS theory. Fuzzy c-means clustering (FCM) algorithm combined with Dempster-Shafer (DS) theory is used to process the uncertainty of information, segmenting the lesion areas on DWI and DCE modalities of MRI and reducing the scale of the uncertain parts. Experiment results show that FCM-DS can fuse the DWI and DCE images to achieve accurate segmentation and display the statement of benign or malignancy of lesion area by Time-Intensity Curve (TIC), which could be beneficial in making preoperative treatment plan and evaluating the effect of the therapy.

An adaptive Fuzzy C-means method utilizing neighboring information for breast tumor segmentation in ultrasound images.

PubMed

Feng, Yuan; Dong, Fenglin; Xia, Xiaolong; Hu, Chun-Hong; Fan, Qianmin; Hu, Yanle; Gao, Mingyuan; Mutic, Sasa

2017-07-01

Ultrasound (US) imaging has been widely used in breast tumor diagnosis and treatment intervention. Automatic delineation of the tumor is a crucial first step, especially for the computer-aided diagnosis (CAD) and US-guided breast procedure. However, the intrinsic properties of US images such as low contrast and blurry boundaries pose challenges to the automatic segmentation of the breast tumor. Therefore, the purpose of this study is to propose a segmentation algorithm that can contour the breast tumor in US images. To utilize the neighbor information of each pixel, a Hausdorff distance based fuzzy c-means (FCM) method was adopted. The size of the neighbor region was adaptively updated by comparing the mutual information between them. The objective function of the clustering process was updated by a combination of Euclid distance and the adaptively calculated Hausdorff distance. Segmentation results were evaluated by comparing with three experts' manual segmentations. The results were also compared with a kernel-induced distance based FCM with spatial constraints, the method without adaptive region selection, and conventional FCM. Results from segmenting 30 patient images showed the adaptive method had a value of sensitivity, specificity, Jaccard similarity, and Dice coefficient of 93.60 ± 5.33%, 97.83 ± 2.17%, 86.38 ± 5.80%, and 92.58 ± 3.68%, respectively. The region-based metrics of average symmetric surface distance (ASSD), root mean square symmetric distance (RMSD), and maximum symmetric surface distance (MSSD) were 0.03 ± 0.04 mm, 0.04 ± 0.03 mm, and 1.18 ± 1.01 mm, respectively. All the metrics except sensitivity were better than that of the non-adaptive algorithm and the conventional FCM. Only three region-based metrics were better than that of the kernel-induced distance based FCM with spatial constraints. Inclusion of the pixel neighbor information adaptively in segmenting US images improved the segmentation performance. The results demonstrate the potential application of the method in breast tumor CAD and other US-guided procedures. © 2017 American Association of Physicists in Medicine.

Query by example video based on fuzzy c-means initialized by fixed clustering center

NASA Astrophysics Data System (ADS)

Hou, Sujuan; Zhou, Shangbo; Siddique, Muhammad Abubakar

2012-04-01

Currently, the high complexity of video contents has posed the following major challenges for fast retrieval: (1) efficient similarity measurements, and (2) efficient indexing on the compact representations. A video-retrieval strategy based on fuzzy c-means (FCM) is presented for querying by example. Initially, the query video is segmented and represented by a set of shots, each shot can be represented by a key frame, and then we used video processing techniques to find visual cues to represent the key frame. Next, because the FCM algorithm is sensitive to the initializations, here we initialized the cluster center by the shots of query video so that users could achieve appropriate convergence. After an FCM cluster was initialized by the query video, each shot of query video was considered a benchmark point in the aforesaid cluster, and each shot in the database possessed a class label. The similarity between the shots in the database with the same class label and benchmark point can be transformed into the distance between them. Finally, the similarity between the query video and the video in database was transformed into the number of similar shots. Our experimental results demonstrated the performance of this proposed approach.

A Spacecraft Electrical Characteristics Multi-Label Classification Method Based on Off-Line FCM Clustering and On-Line WPSVM

PubMed Central

Li, Ke; Liu, Yi; Wang, Quanxin; Wu, Yalei; Song, Shimin; Sun, Yi; Liu, Tengchong; Wang, Jun; Li, Yang; Du, Shaoyi

2015-01-01

This paper proposes a novel multi-label classification method for resolving the spacecraft electrical characteristics problems which involve many unlabeled test data processing, high-dimensional features, long computing time and identification of slow rate. Firstly, both the fuzzy c-means (FCM) offline clustering and the principal component feature extraction algorithms are applied for the feature selection process. Secondly, the approximate weighted proximal support vector machine (WPSVM) online classification algorithms is used to reduce the feature dimension and further improve the rate of recognition for electrical characteristics spacecraft. Finally, the data capture contribution method by using thresholds is proposed to guarantee the validity and consistency of the data selection. The experimental results indicate that the method proposed can obtain better data features of the spacecraft electrical characteristics, improve the accuracy of identification and shorten the computing time effectively. PMID:26544549

Inhomogeneity compensation for MR brain image segmentation using a multi-stage FCM-based approach.

PubMed

Szilágyi, László; Szilágyi, Sándor M; Dávid, László; Benyó, Zoltán

2008-01-01

Intensity inhomogeneity or intensity non-uniformity (INU) is an undesired phenomenon that represents the main obstacle for MR image segmentation and registration methods. Various techniques have been proposed to eliminate or compensate the INU, most of which are embedded into clustering algorithms. This paper proposes a multiple stage fuzzy c-means (FCM) based algorithm for the estimation and compensation of the slowly varying additive or multiplicative noise, supported by a pre-filtering technique for Gaussian and impulse noise elimination. The slowly varying behavior of the bias or gain field is assured by a smoothening filter that performs a context dependent averaging, based on a morphological criterion. The experiments using 2-D synthetic phantoms and real MR images show, that the proposed method provides accurate segmentation. The produced segmentation and fuzzy membership values can serve as excellent support for 3-D registration and segmentation techniques.

Comparison of optimized algorithms in facility location allocation problems with different distance measures

NASA Astrophysics Data System (ADS)

Kumar, Rakesh; Chandrawat, Rajesh Kumar; Garg, B. P.; Joshi, Varun

2017-07-01

Opening the new firm or branch with desired execution is very relevant to facility location problem. Along the lines to locate the new ambulances and firehouses, the government desires to minimize average response time for emergencies from all residents of cities. So finding the best location is biggest challenge in day to day life. These type of problems were named as facility location problems. A lot of algorithms have been developed to handle these problems. In this paper, we review five algorithms that were applied to facility location problems. The significance of clustering in facility location problems is also presented. First we compare Fuzzy c-means clustering (FCM) algorithm with alternating heuristic (AH) algorithm, then with Particle Swarm Optimization (PSO) algorithms using different type of distance function. The data was clustered with the help of FCM and then we apply median model and min-max problem model on that data. After finding optimized locations using these algorithms we find the distance from optimized location point to the demanded point with different distance techniques and compare the results. At last, we design a general example to validate the feasibility of the five algorithms for facilities location optimization, and authenticate the advantages and drawbacks of them.

Short-term prediction of solar energy in Saudi Arabia using automated-design fuzzy logic systems

PubMed Central

2017-01-01

Solar energy is considered as one of the main sources for renewable energy in the near future. However, solar energy and other renewable energy sources have a drawback related to the difficulty in predicting their availability in the near future. This problem affects optimal exploitation of solar energy, especially in connection with other resources. Therefore, reliable solar energy prediction models are essential to solar energy management and economics. This paper presents work aimed at designing reliable models to predict the global horizontal irradiance (GHI) for the next day in 8 stations in Saudi Arabia. The designed models are based on computational intelligence methods of automated-design fuzzy logic systems. The fuzzy logic systems are designed and optimized with two models using fuzzy c-means clustering (FCM) and simulated annealing (SA) algorithms. The first model uses FCM based on the subtractive clustering algorithm to automatically design the predictor fuzzy rules from data. The second model is using FCM followed by simulated annealing algorithm to enhance the prediction accuracy of the fuzzy logic system. The objective of the predictor is to accurately predict next-day global horizontal irradiance (GHI) using previous-day meteorological and solar radiation observations. The proposed models use observations of 10 variables of measured meteorological and solar radiation data to build the model. The experimentation and results of the prediction are detailed where the root mean square error of the prediction was approximately 88% for the second model tuned by simulated annealing compared to 79.75% accuracy using the first model. This results demonstrate a good modeling accuracy of the second model despite that the training and testing of the proposed models were carried out using spatially and temporally independent data. PMID:28806754

Short-term prediction of solar energy in Saudi Arabia using automated-design fuzzy logic systems.

PubMed

Almaraashi, Majid

2017-01-01

Solar energy is considered as one of the main sources for renewable energy in the near future. However, solar energy and other renewable energy sources have a drawback related to the difficulty in predicting their availability in the near future. This problem affects optimal exploitation of solar energy, especially in connection with other resources. Therefore, reliable solar energy prediction models are essential to solar energy management and economics. This paper presents work aimed at designing reliable models to predict the global horizontal irradiance (GHI) for the next day in 8 stations in Saudi Arabia. The designed models are based on computational intelligence methods of automated-design fuzzy logic systems. The fuzzy logic systems are designed and optimized with two models using fuzzy c-means clustering (FCM) and simulated annealing (SA) algorithms. The first model uses FCM based on the subtractive clustering algorithm to automatically design the predictor fuzzy rules from data. The second model is using FCM followed by simulated annealing algorithm to enhance the prediction accuracy of the fuzzy logic system. The objective of the predictor is to accurately predict next-day global horizontal irradiance (GHI) using previous-day meteorological and solar radiation observations. The proposed models use observations of 10 variables of measured meteorological and solar radiation data to build the model. The experimentation and results of the prediction are detailed where the root mean square error of the prediction was approximately 88% for the second model tuned by simulated annealing compared to 79.75% accuracy using the first model. This results demonstrate a good modeling accuracy of the second model despite that the training and testing of the proposed models were carried out using spatially and temporally independent data.

A possibilistic approach to clustering

NASA Technical Reports Server (NTRS)

Krishnapuram, Raghu; Keller, James M.

1993-01-01

Fuzzy clustering has been shown to be advantageous over crisp (or traditional) clustering methods in that total commitment of a vector to a given class is not required at each image pattern recognition iteration. Recently fuzzy clustering methods have shown spectacular ability to detect not only hypervolume clusters, but also clusters which are actually 'thin shells', i.e., curves and surfaces. Most analytic fuzzy clustering approaches are derived from the 'Fuzzy C-Means' (FCM) algorithm. The FCM uses the probabilistic constraint that the memberships of a data point across classes sum to one. This constraint was used to generate the membership update equations for an iterative algorithm. Recently, we cast the clustering problem into the framework of possibility theory using an approach in which the resulting partition of the data can be interpreted as a possibilistic partition, and the membership values may be interpreted as degrees of possibility of the points belonging to the classes. We show the ability of this approach to detect linear and quartic curves in the presence of considerable noise.

Possibilistic clustering for shape recognition

NASA Technical Reports Server (NTRS)

Keller, James M.; Krishnapuram, Raghu

1993-01-01

Clustering methods have been used extensively in computer vision and pattern recognition. Fuzzy clustering has been shown to be advantageous over crisp (or traditional) clustering in that total commitment of a vector to a given class is not required at each iteration. Recently fuzzy clustering methods have shown spectacular ability to detect not only hypervolume clusters, but also clusters which are actually 'thin shells', i.e., curves and surfaces. Most analytic fuzzy clustering approaches are derived from Bezdek's Fuzzy C-Means (FCM) algorithm. The FCM uses the probabilistic constraint that the memberships of a data point across classes sum to one. This constraint was used to generate the membership update equations for an iterative algorithm. Unfortunately, the memberships resulting from FCM and its derivatives do not correspond to the intuitive concept of degree of belonging, and moreover, the algorithms have considerable trouble in noisy environments. Recently, the clustering problem was cast into the framework of possibility theory. Our approach was radically different from the existing clustering methods in that the resulting partition of the data can be interpreted as a possibilistic partition, and the membership values may be interpreted as degrees of possibility of the points belonging to the classes. An appropriate objective function whose minimum will characterize a good possibilistic partition of the data was constructed, and the membership and prototype update equations from necessary conditions for minimization of our criterion function were derived. The ability of this approach to detect linear and quartic curves in the presence of considerable noise is shown.

Possibilistic clustering for shape recognition

NASA Technical Reports Server (NTRS)

Keller, James M.; Krishnapuram, Raghu

1992-01-01

Clustering methods have been used extensively in computer vision and pattern recognition. Fuzzy clustering has been shown to be advantageous over crisp (or traditional) clustering in that total commitment of a vector to a given class is not required at each iteration. Recently fuzzy clustering methods have shown spectacular ability to detect not only hypervolume clusters, but also clusters which are actually 'thin shells', i.e., curves and surfaces. Most analytic fuzzy clustering approaches are derived from Bezdek's Fuzzy C-Means (FCM) algorithm. The FCM uses the probabilistic constraint that the memberships of a data point across classes sum to one. This constraint was used to generate the membership update equations for an iterative algorithm. Unfortunately, the memberships resulting from FCM and its derivatives do not correspond to the intuitive concept of degree of belonging, and moreover, the algorithms have considerable trouble in noisy environments. Recently, we cast the clustering problem into the framework of possibility theory. Our approach was radically different from the existing clustering methods in that the resulting partition of the data can be interpreted as a possibilistic partition, and the membership values may be interpreted as degrees of possibility of the points belonging to the classes. We constructed an appropriate objective function whose minimum will characterize a good possibilistic partition of the data, and we derived the membership and prototype update equations from necessary conditions for minimization of our criterion function. In this paper, we show the ability of this approach to detect linear and quartic curves in the presence of considerable noise.

Artificial bee colony algorithm with dynamic multi-population

NASA Astrophysics Data System (ADS)

Zhang, Ming; Ji, Zhicheng; Wang, Yan

2017-07-01

To improve the convergence rate and make a balance between the global search and local turning abilities, this paper proposes a decentralized form of artificial bee colony (ABC) algorithm with dynamic multi-populations by means of fuzzy C-means (FCM) clustering. Each subpopulation periodically enlarges with the same size during the search process, and the overlapping individuals among different subareas work for delivering information acting as exploring the search space with diffusion of solutions. Moreover, a Gaussian-based search equation with redefined local attractor is proposed to further accelerate the diffusion of the best solution and guide the search towards potential areas. Experimental results on a set of benchmarks demonstrate the competitive performance of our proposed approach.

Network intrusion detection based on a general regression neural network optimized by an improved artificial immune algorithm.

PubMed

Wu, Jianfa; Peng, Dahao; Li, Zhuping; Zhao, Li; Ling, Huanzhang

2015-01-01

To effectively and accurately detect and classify network intrusion data, this paper introduces a general regression neural network (GRNN) based on the artificial immune algorithm with elitist strategies (AIAE). The elitist archive and elitist crossover were combined with the artificial immune algorithm (AIA) to produce the AIAE-GRNN algorithm, with the aim of improving its adaptivity and accuracy. In this paper, the mean square errors (MSEs) were considered the affinity function. The AIAE was used to optimize the smooth factors of the GRNN; then, the optimal smooth factor was solved and substituted into the trained GRNN. Thus, the intrusive data were classified. The paper selected a GRNN that was separately optimized using a genetic algorithm (GA), particle swarm optimization (PSO), and fuzzy C-mean clustering (FCM) to enable a comparison of these approaches. As shown in the results, the AIAE-GRNN achieves a higher classification accuracy than PSO-GRNN, but the running time of AIAE-GRNN is long, which was proved first. FCM and GA-GRNN were eliminated because of their deficiencies in terms of accuracy and convergence. To improve the running speed, the paper adopted principal component analysis (PCA) to reduce the dimensions of the intrusive data. With the reduction in dimensionality, the PCA-AIAE-GRNN decreases in accuracy less and has better convergence than the PCA-PSO-GRNN, and the running speed of the PCA-AIAE-GRNN was relatively improved. The experimental results show that the AIAE-GRNN has a higher robustness and accuracy than the other algorithms considered and can thus be used to classify the intrusive data.

Use of genetic algorithm for the selection of EEG features

NASA Astrophysics Data System (ADS)

Asvestas, P.; Korda, A.; Kostopoulos, S.; Karanasiou, I.; Ouzounoglou, A.; Sidiropoulos, K.; Ventouras, E.; Matsopoulos, G.

2015-09-01

Genetic Algorithm (GA) is a popular optimization technique that can detect the global optimum of a multivariable function containing several local optima. GA has been widely used in the field of biomedical informatics, especially in the context of designing decision support systems that classify biomedical signals or images into classes of interest. The aim of this paper is to present a methodology, based on GA, for the selection of the optimal subset of features that can be used for the efficient classification of Event Related Potentials (ERPs), which are recorded during the observation of correct or incorrect actions. In our experiment, ERP recordings were acquired from sixteen (16) healthy volunteers who observed correct or incorrect actions of other subjects. The brain electrical activity was recorded at 47 locations on the scalp. The GA was formulated as a combinatorial optimizer for the selection of the combination of electrodes that maximizes the performance of the Fuzzy C Means (FCM) classification algorithm. In particular, during the evolution of the GA, for each candidate combination of electrodes, the well-known (Σ, Φ, Ω) features were calculated and were evaluated by means of the FCM method. The proposed methodology provided a combination of 8 electrodes, with classification accuracy 93.8%. Thus, GA can be the basis for the selection of features that discriminate ERP recordings of observations of correct or incorrect actions.

Research on the precise positioning of customers in large data environment

NASA Astrophysics Data System (ADS)

Zhou, Xu; He, Lili

2018-04-01

Customer positioning has always been a problem that enterprises focus on. In this paper, FCM clustering algorithm is used to cluster customer groups. However, due to the traditional FCM clustering algorithm, which is susceptible to the influence of the initial clustering center and easy to fall into the local optimal problem, the short board of FCM is solved by the gray optimization algorithm (GWO) to achieve efficient and accurate handling of a large number of retailer data.

Network Intrusion Detection Based on a General Regression Neural Network Optimized by an Improved Artificial Immune Algorithm

PubMed Central

Wu, Jianfa; Peng, Dahao; Li, Zhuping; Zhao, Li; Ling, Huanzhang

2015-01-01

To effectively and accurately detect and classify network intrusion data, this paper introduces a general regression neural network (GRNN) based on the artificial immune algorithm with elitist strategies (AIAE). The elitist archive and elitist crossover were combined with the artificial immune algorithm (AIA) to produce the AIAE-GRNN algorithm, with the aim of improving its adaptivity and accuracy. In this paper, the mean square errors (MSEs) were considered the affinity function. The AIAE was used to optimize the smooth factors of the GRNN; then, the optimal smooth factor was solved and substituted into the trained GRNN. Thus, the intrusive data were classified. The paper selected a GRNN that was separately optimized using a genetic algorithm (GA), particle swarm optimization (PSO), and fuzzy C-mean clustering (FCM) to enable a comparison of these approaches. As shown in the results, the AIAE-GRNN achieves a higher classification accuracy than PSO-GRNN, but the running time of AIAE-GRNN is long, which was proved first. FCM and GA-GRNN were eliminated because of their deficiencies in terms of accuracy and convergence. To improve the running speed, the paper adopted principal component analysis (PCA) to reduce the dimensions of the intrusive data. With the reduction in dimensionality, the PCA-AIAE-GRNN decreases in accuracy less and has better convergence than the PCA-PSO-GRNN, and the running speed of the PCA-AIAE-GRNN was relatively improved. The experimental results show that the AIAE-GRNN has a higher robustness and accuracy than the other algorithms considered and can thus be used to classify the intrusive data. PMID:25807466

Eigenspace-based fuzzy c-means for sensing trending topics in Twitter

NASA Astrophysics Data System (ADS)

Muliawati, T.; Murfi, H.

2017-07-01

As the information and communication technology are developed, the fulfillment of information can be obtained through social media, like Twitter. The enormous number of internet users has triggered fast and large data flow, thus making the manual analysis is difficult or even impossible. An automated methods for data analysis is needed, one of which is the topic detection and tracking. An alternative method other than latent Dirichlet allocation (LDA) is a soft clustering approach using Fuzzy C-Means (FCM). FCM meets the assumption that a document may consist of several topics. However, FCM works well in low-dimensional data but fails in high-dimensional data. Therefore, we propose an approach where FCM works on low-dimensional data by reducing the data using singular value decomposition (SVD). Our simulations show that this approach gives better accuracies in term of topic recall than LDA for sensing trending topic in Twitter about an event.

Thermogram breast cancer prediction approach based on Neutrosophic sets and fuzzy c-means algorithm.

PubMed

Gaber, Tarek; Ismail, Gehad; Anter, Ahmed; Soliman, Mona; Ali, Mona; Semary, Noura; Hassanien, Aboul Ella; Snasel, Vaclav

2015-08-01

The early detection of breast cancer makes many women survive. In this paper, a CAD system classifying breast cancer thermograms to normal and abnormal is proposed. This approach consists of two main phases: automatic segmentation and classification. For the former phase, an improved segmentation approach based on both Neutrosophic sets (NS) and optimized Fast Fuzzy c-mean (F-FCM) algorithm was proposed. Also, post-segmentation process was suggested to segment breast parenchyma (i.e. ROI) from thermogram images. For the classification, different kernel functions of the Support Vector Machine (SVM) were used to classify breast parenchyma into normal or abnormal cases. Using benchmark database, the proposed CAD system was evaluated based on precision, recall, and accuracy as well as a comparison with related work. The experimental results showed that our system would be a very promising step toward automatic diagnosis of breast cancer using thermograms as the accuracy reached 100%.

A research of road centerline extraction algorithm from high resolution remote sensing images

NASA Astrophysics Data System (ADS)

Zhang, Yushan; Xu, Tingfa

2017-09-01

Satellite remote sensing technology has become one of the most effective methods for land surface monitoring in recent years, due to its advantages such as short period, large scale and rich information. Meanwhile, road extraction is an important field in the applications of high resolution remote sensing images. An intelligent and automatic road extraction algorithm with high precision has great significance for transportation, road network updating and urban planning. The fuzzy c-means (FCM) clustering segmentation algorithms have been used in road extraction, but the traditional algorithms did not consider spatial information. An improved fuzzy C-means clustering algorithm combined with spatial information (SFCM) is proposed in this paper, which is proved to be effective for noisy image segmentation. Firstly, the image is segmented using the SFCM. Secondly, the segmentation result is processed by mathematical morphology to remover the joint region. Thirdly, the road centerlines are extracted by morphology thinning and burr trimming. The average integrity of the centerline extraction algorithm is 97.98%, the average accuracy is 95.36% and the average quality is 93.59%. Experimental results show that the proposed method in this paper is effective for road centerline extraction.

Fuzzy C-means classification for corrosion evolution of steel images

NASA Astrophysics Data System (ADS)

Trujillo, Maite; Sadki, Mustapha

2004-05-01

An unavoidable problem of metal structures is their exposure to rust degradation during their operational life. Thus, the surfaces need to be assessed in order to avoid potential catastrophes. There is considerable interest in the use of patch repair strategies which minimize the project costs. However, to operate such strategies with confidence in the long useful life of the repair, it is essential that the condition of the existing coatings and the steel substrate can be accurately quantified and classified. This paper describes the application of fuzzy set theory for steel surfaces classification according to the steel rust time. We propose a semi-automatic technique to obtain image clustering using the Fuzzy C-means (FCM) algorithm and we analyze two kinds of data to study the classification performance. Firstly, we investigate the use of raw images" pixels without any pre-processing methods and neighborhood pixels. Secondly, we apply Gaussian noise to the images with different standard deviation to study the FCM method tolerance to Gaussian noise. The noisy images simulate the possible perturbations of the images due to the weather or rust deposits in the steel surfaces during typical on-site acquisition procedures

Infrared Ship Target Segmentation Based on Spatial Information Improved FCM.

PubMed

Bai, Xiangzhi; Chen, Zhiguo; Zhang, Yu; Liu, Zhaoying; Lu, Yi

2016-12-01

Segmentation of infrared (IR) ship images is always a challenging task, because of the intensity inhomogeneity and noise. The fuzzy C-means (FCM) clustering is a classical method widely used in image segmentation. However, it has some shortcomings, like not considering the spatial information or being sensitive to noise. In this paper, an improved FCM method based on the spatial information is proposed for IR ship target segmentation. The improvements include two parts: 1) adding the nonlocal spatial information based on the ship target and 2) using the spatial shape information of the contour of the ship target to refine the local spatial constraint by Markov random field. In addition, the results of K -means are used to initialize the improved FCM method. Experimental results show that the improved method is effective and performs better than the existing methods, including the existing FCM methods, for segmentation of the IR ship images.

Automated fibroglandular tissue segmentation and volumetric density estimation in breast MRI using an atlas-aided fuzzy C-means method

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

Wu, Shandong; Weinstein, Susan P.; Conant, Emily F.

Purpose: Breast magnetic resonance imaging (MRI) plays an important role in the clinical management of breast cancer. Studies suggest that the relative amount of fibroglandular (i.e., dense) tissue in the breast as quantified in MR images can be predictive of the risk for developing breast cancer, especially for high-risk women. Automated segmentation of the fibroglandular tissue and volumetric density estimation in breast MRI could therefore be useful for breast cancer risk assessment. Methods: In this work the authors develop and validate a fully automated segmentation algorithm, namely, an atlas-aided fuzzy C-means (FCM-Atlas) method, to estimate the volumetric amount of fibroglandularmore » tissue in breast MRI. The FCM-Atlas is a 2D segmentation method working on a slice-by-slice basis. FCM clustering is first applied to the intensity space of each 2D MR slice to produce an initial voxelwise likelihood map of fibroglandular tissue. Then a prior learned fibroglandular tissue likelihood atlas is incorporated to refine the initial FCM likelihood map to achieve enhanced segmentation, from which the absolute volume of the fibroglandular tissue (|FGT|) and the relative amount (i.e., percentage) of the |FGT| relative to the whole breast volume (FGT%) are computed. The authors' method is evaluated by a representative dataset of 60 3D bilateral breast MRI scans (120 breasts) that span the full breast density range of the American College of Radiology Breast Imaging Reporting and Data System. The automated segmentation is compared to manual segmentation obtained by two experienced breast imaging radiologists. Segmentation performance is assessed by linear regression, Pearson's correlation coefficients, Student's pairedt-test, and Dice's similarity coefficients (DSC). Results: The inter-reader correlation is 0.97 for FGT% and 0.95 for |FGT|. When compared to the average of the two readers’ manual segmentation, the proposed FCM-Atlas method achieves a correlation ofr = 0.92 for FGT% and r = 0.93 for |FGT|, and the automated segmentation is not statistically significantly different (p = 0.46 for FGT% and p = 0.55 for |FGT|). The bilateral correlation between left breasts and right breasts for the FGT% is 0.94, 0.92, and 0.95 for reader 1, reader 2, and the FCM-Atlas, respectively; likewise, for the |FGT|, it is 0.92, 0.92, and 0.93, respectively. For the spatial segmentation agreement, the automated algorithm achieves a DSC of 0.69 ± 0.1 when compared to reader 1 and 0.61 ± 0.1 for reader 2, respectively, while the DSC between the two readers’ manual segmentation is 0.67 ± 0.15. Additional robustness analysis shows that the segmentation performance of the authors' method is stable both with respect to selecting different cases and to varying the number of cases needed to construct the prior probability atlas. The authors' results also show that the proposed FCM-Atlas method outperforms the commonly used two-cluster FCM-alone method. The authors' method runs at ∼5 min for each 3D bilateral MR scan (56 slices) for computing the FGT% and |FGT|, compared to ∼55 min needed for manual segmentation for the same purpose. Conclusions: The authors' method achieves robust segmentation and can serve as an efficient tool for processing large clinical datasets for quantifying the fibroglandular tissue content in breast MRI. It holds a great potential to support clinical applications in the future including breast cancer risk assessment.« less

Automated fibroglandular tissue segmentation and volumetric density estimation in breast MRI using an atlas-aided fuzzy C-means method

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

Wu, Shandong; Weinstein, Susan P.; Conant, Emily F.

2013-12-15

Purpose: Breast magnetic resonance imaging (MRI) plays an important role in the clinical management of breast cancer. Studies suggest that the relative amount of fibroglandular (i.e., dense) tissue in the breast as quantified in MR images can be predictive of the risk for developing breast cancer, especially for high-risk women. Automated segmentation of the fibroglandular tissue and volumetric density estimation in breast MRI could therefore be useful for breast cancer risk assessment. Methods: In this work the authors develop and validate a fully automated segmentation algorithm, namely, an atlas-aided fuzzy C-means (FCM-Atlas) method, to estimate the volumetric amount of fibroglandularmore » tissue in breast MRI. The FCM-Atlas is a 2D segmentation method working on a slice-by-slice basis. FCM clustering is first applied to the intensity space of each 2D MR slice to produce an initial voxelwise likelihood map of fibroglandular tissue. Then a prior learned fibroglandular tissue likelihood atlas is incorporated to refine the initial FCM likelihood map to achieve enhanced segmentation, from which the absolute volume of the fibroglandular tissue (|FGT|) and the relative amount (i.e., percentage) of the |FGT| relative to the whole breast volume (FGT%) are computed. The authors' method is evaluated by a representative dataset of 60 3D bilateral breast MRI scans (120 breasts) that span the full breast density range of the American College of Radiology Breast Imaging Reporting and Data System. The automated segmentation is compared to manual segmentation obtained by two experienced breast imaging radiologists. Segmentation performance is assessed by linear regression, Pearson's correlation coefficients, Student's pairedt-test, and Dice's similarity coefficients (DSC). Results: The inter-reader correlation is 0.97 for FGT% and 0.95 for |FGT|. When compared to the average of the two readers’ manual segmentation, the proposed FCM-Atlas method achieves a correlation ofr = 0.92 for FGT% and r = 0.93 for |FGT|, and the automated segmentation is not statistically significantly different (p = 0.46 for FGT% and p = 0.55 for |FGT|). The bilateral correlation between left breasts and right breasts for the FGT% is 0.94, 0.92, and 0.95 for reader 1, reader 2, and the FCM-Atlas, respectively; likewise, for the |FGT|, it is 0.92, 0.92, and 0.93, respectively. For the spatial segmentation agreement, the automated algorithm achieves a DSC of 0.69 ± 0.1 when compared to reader 1 and 0.61 ± 0.1 for reader 2, respectively, while the DSC between the two readers’ manual segmentation is 0.67 ± 0.15. Additional robustness analysis shows that the segmentation performance of the authors' method is stable both with respect to selecting different cases and to varying the number of cases needed to construct the prior probability atlas. The authors' results also show that the proposed FCM-Atlas method outperforms the commonly used two-cluster FCM-alone method. The authors' method runs at ∼5 min for each 3D bilateral MR scan (56 slices) for computing the FGT% and |FGT|, compared to ∼55 min needed for manual segmentation for the same purpose. Conclusions: The authors' method achieves robust segmentation and can serve as an efficient tool for processing large clinical datasets for quantifying the fibroglandular tissue content in breast MRI. It holds a great potential to support clinical applications in the future including breast cancer risk assessment.« less

Breast density quantification with cone-beam CT: A post-mortem study

PubMed Central

Johnson, Travis; Ding, Huanjun; Le, Huy Q.; Ducote, Justin L.; Molloi, Sabee

2014-01-01

Forty post-mortem breasts were imaged with a flat-panel based cone-beam x-ray CT system at 50 kVp. The feasibility of breast density quantification has been investigated using standard histogram thresholding and an automatic segmentation method based on the fuzzy c-means algorithm (FCM). The breasts were chemically decomposed into water, lipid, and protein immediately after image acquisition was completed. The percent fibroglandular volume (%FGV) from chemical analysis was used as the gold standard for breast density comparison. Both image-based segmentation techniques showed good precision in breast density quantification with high linear coefficients between the right and left breast of each pair. When comparing with the gold standard using %FGV from chemical analysis, Pearson’s r-values were estimated to be 0.983 and 0.968 for the FCM clustering and the histogram thresholding techniques, respectively. The standard error of the estimate (SEE) was also reduced from 3.92% to 2.45% by applying the automatic clustering technique. The results of the postmortem study suggested that breast tissue can be characterized in terms of water, lipid and protein contents with high accuracy by using chemical analysis, which offers a gold standard for breast density studies comparing different techniques. In the investigated image segmentation techniques, the FCM algorithm had high precision and accuracy in breast density quantification. In comparison to conventional histogram thresholding, it was more efficient and reduced inter-observer variation. PMID:24254317

Automatic quantitative analysis of in-stent restenosis using FD-OCT in vivo intra-arterial imaging.

PubMed

Mandelias, Kostas; Tsantis, Stavros; Spiliopoulos, Stavros; Katsakiori, Paraskevi F; Karnabatidis, Dimitris; Nikiforidis, George C; Kagadis, George C

2013-06-01

A new segmentation technique is implemented for automatic lumen area extraction and stent strut detection in intravascular optical coherence tomography (OCT) images for the purpose of quantitative analysis of in-stent restenosis (ISR). In addition, a user-friendly graphical user interface (GUI) is developed based on the employed algorithm toward clinical use. Four clinical datasets of frequency-domain OCT scans of the human femoral artery were analyzed. First, a segmentation method based on fuzzy C means (FCM) clustering and wavelet transform (WT) was applied toward inner luminal contour extraction. Subsequently, stent strut positions were detected by utilizing metrics derived from the local maxima of the wavelet transform into the FCM membership function. The inner lumen contour and the position of stent strut were extracted with high precision. Compared to manual segmentation by an expert physician, the automatic lumen contour delineation had an average overlap value of 0.917 ± 0.065 for all OCT images included in the study. The strut detection procedure achieved an overall accuracy of 93.80% and successfully identified 9.57 ± 0.5 struts for every OCT image. Processing time was confined to approximately 2.5 s per OCT frame. A new fast and robust automatic segmentation technique combining FCM and WT for lumen border extraction and strut detection in intravascular OCT images was designed and implemented. The proposed algorithm integrated in a GUI represents a step forward toward the employment of automated quantitative analysis of ISR in clinical practice.

Joint inversion of multiple geophysical and petrophysical data using generalized fuzzy clustering algorithms

NASA Astrophysics Data System (ADS)

Sun, Jiajia; Li, Yaoguo

2017-02-01

Joint inversion that simultaneously inverts multiple geophysical data sets to recover a common Earth model is increasingly being applied to exploration problems. Petrophysical data can serve as an effective constraint to link different physical property models in such inversions. There are two challenges, among others, associated with the petrophysical approach to joint inversion. One is related to the multimodality of petrophysical data because there often exist more than one relationship between different physical properties in a region of study. The other challenge arises from the fact that petrophysical relationships have different characteristics and can exhibit point, linear, quadratic, or exponential forms in a crossplot. The fuzzy c-means (FCM) clustering technique is effective in tackling the first challenge and has been applied successfully. We focus on the second challenge in this paper and develop a joint inversion method based on variations of the FCM clustering technique. To account for the specific shapes of petrophysical relationships, we introduce several different fuzzy clustering algorithms that are capable of handling different shapes of petrophysical relationships. We present two synthetic and one field data examples and demonstrate that, by choosing appropriate distance measures for the clustering component in the joint inversion algorithm, the proposed joint inversion method provides an effective means of handling common petrophysical situations we encounter in practice. The jointly inverted models have both enhanced structural similarity and increased petrophysical correlation, and better represent the subsurface in the spatial domain and the parameter domain of physical properties.

Effect of segmentation algorithms on the performance of computerized detection of lung nodules in CT

PubMed Central

Guo, Wei; Li, Qiang

2014-01-01

Purpose: The purpose of this study is to reveal how the performance of lung nodule segmentation algorithm impacts the performance of lung nodule detection, and to provide guidelines for choosing an appropriate segmentation algorithm with appropriate parameters in a computer-aided detection (CAD) scheme. Methods: The database consisted of 85 CT scans with 111 nodules of 3 mm or larger in diameter from the standard CT lung nodule database created by the Lung Image Database Consortium. The initial nodule candidates were identified as those with strong response to a selective nodule enhancement filter. A uniform viewpoint reformation technique was applied to a three-dimensional nodule candidate to generate 24 two-dimensional (2D) reformatted images, which would be used to effectively distinguish between true nodules and false positives. Six different algorithms were employed to segment the initial nodule candidates in the 2D reformatted images. Finally, 2D features from the segmented areas in the 24 reformatted images were determined, selected, and classified for removal of false positives. Therefore, there were six similar CAD schemes, in which only the segmentation algorithms were different. The six segmentation algorithms included the fixed thresholding (FT), Otsu thresholding (OTSU), fuzzy C-means (FCM), Gaussian mixture model (GMM), Chan and Vese model (CV), and local binary fitting (LBF). The mean Jaccard index and the mean absolute distance (Dmean) were employed to evaluate the performance of segmentation algorithms, and the number of false positives at a fixed sensitivity was employed to evaluate the performance of the CAD schemes. Results: For the segmentation algorithms of FT, OTSU, FCM, GMM, CV, and LBF, the highest mean Jaccard index between the segmented nodule and the ground truth were 0.601, 0.586, 0.588, 0.563, 0.543, and 0.553, respectively, and the corresponding Dmean were 1.74, 1.80, 2.32, 2.80, 3.48, and 3.18 pixels, respectively. With these segmentation results of the six segmentation algorithms, the six CAD schemes reported 4.4, 8.8, 3.4, 9.2, 13.6, and 10.4 false positives per CT scan at a sensitivity of 80%. Conclusions: When multiple algorithms are available for segmenting nodule candidates in a CAD scheme, the “optimal” segmentation algorithm did not necessarily lead to the “optimal” CAD detection performance. PMID:25186393

Weak imposition of frictionless contact constraints on automatically recovered high-order, embedded interfaces using the finite cell method

NASA Astrophysics Data System (ADS)

Bog, Tino; Zander, Nils; Kollmannsberger, Stefan; Rank, Ernst

2018-04-01

The finite cell method (FCM) is a fictitious domain approach that greatly simplifies simulations involving complex structures. Recently, the FCM has been applied to contact problems. The current study continues in this field by extending the concept of weakly enforced boundary conditions to inequality constraints for frictionless contact. Furthermore, it formalizes an approach that automatically recovers high-order contact surfaces of (implicitly defined) embedded geometries by means of an extended Marching Cubes algorithm. To further improve the accuracy of the discretization, irregularities at the boundary of contact zones are treated with multi-level hp-refinements. Numerical results and a systematic study of h-, p- and hp-refinements show that the FCM can efficiently provide accurate results for problems involving contact.

Analysis of Intergrade Variables In The Fuzzy C-Means And Improved Algorithm Cat Swarm Optimization(FCM-ISO) In Search Segmentation

NASA Astrophysics Data System (ADS)

Saragih, Jepronel; Salim Sitompul, Opim; Situmorang, Zakaria

2017-12-01

One of the techniques known in Data Mining namely clustering. Image segmentation process does not always represent the actual image which is caused by a combination of algorithms as long as it has not been able to obtain optimal cluster centers. In this research will search for the smallest error with the counting result of a Fuzzy C Means process optimized with Cat swam Algorithm Optimization that has been developed by adding the weight of the energy in the process of Tracing Mode.So with the parameter can be determined the most optimal cluster centers and most closely with the data will be made the cluster. Weigh inertia in this research, namely: (0.1), (0.2), (0.3), (0.4), (0.5), (0.6), (0.7), (0.8) and (0.9). Then compare the results of each variable values inersia (W) which is different and taken the smallest results. Of this weighting analysis process can acquire the right produce inertia variable cost function the smallest.

Two generalizations of Kohonen clustering

NASA Technical Reports Server (NTRS)

Bezdek, James C.; Pal, Nikhil R.; Tsao, Eric C. K.

1993-01-01

The relationship between the sequential hard c-means (SHCM), learning vector quantization (LVQ), and fuzzy c-means (FCM) clustering algorithms is discussed. LVQ and SHCM suffer from several major problems. For example, they depend heavily on initialization. If the initial values of the cluster centers are outside the convex hull of the input data, such algorithms, even if they terminate, may not produce meaningful results in terms of prototypes for cluster representation. This is due in part to the fact that they update only the winning prototype for every input vector. The impact and interaction of these two families with Kohonen's self-organizing feature mapping (SOFM), which is not a clustering method, but which often leads ideas to clustering algorithms is discussed. Then two generalizations of LVQ that are explicitly designed as clustering algorithms are presented; these algorithms are referred to as generalized LVQ = GLVQ; and fuzzy LVQ = FLVQ. Learning rules are derived to optimize an objective function whose goal is to produce 'good clusters'. GLVQ/FLVQ (may) update every node in the clustering net for each input vector. Neither GLVQ nor FLVQ depends upon a choice for the update neighborhood or learning rate distribution - these are taken care of automatically. Segmentation of a gray tone image is used as a typical application of these algorithms to illustrate the performance of GLVQ/FLVQ.

Pomegranate MR images analysis using ACM and FCM algorithms

NASA Astrophysics Data System (ADS)

Morad, Ghobad; Shamsi, Mousa; Sedaaghi, M. H.; Alsharif, M. R.

2011-10-01

Segmentation of an image plays an important role in image processing applications. In this paper segmentation of pomegranate magnetic resonance (MR) images has been explored. Pomegranate has healthy nutritional and medicinal properties for which the maturity indices and quality of internal tissues play an important role in the sorting process in which the admissible determination of features mentioned above cannot be easily achieved by human operator. Seeds and soft tissues are the main internal components of pomegranate. For research purposes, such as non-destructive investigation, in order to determine the ripening index and the percentage of seeds in growth period, segmentation of the internal structures should be performed as exactly as possible. In this paper, we present an automatic algorithm to segment the internal structure of pomegranate. Since its intensity of stem and calyx is close to the internal tissues, the stem and calyx pixels are usually labeled to the internal tissues by segmentation algorithm. To solve this problem, first, the fruit shape is extracted from its background using active contour model (ACM). Then stem and calyx are removed using morphological filters. Finally the image is segmented by fuzzy c-means (FCM). The experimental results represent an accuracy of 95.91% in the presence of stem and calyx, while the accuracy of segmentation increases to 97.53% when stem and calyx are first removed by morphological filters.

Breast density quantification using magnetic resonance imaging (MRI) with bias field correction: A postmortem study

PubMed Central

Ding, Huanjun; Johnson, Travis; Lin, Muqing; Le, Huy Q.; Ducote, Justin L.; Su, Min-Ying; Molloi, Sabee

2013-01-01

Purpose: Quantification of breast density based on three-dimensional breast MRI may provide useful information for the early detection of breast cancer. However, the field inhomogeneity can severely challenge the computerized image segmentation process. In this work, the effect of the bias field in breast density quantification has been investigated with a postmortem study. Methods: T1-weighted images of 20 pairs of postmortem breasts were acquired on a 1.5 T breast MRI scanner. Two computer-assisted algorithms were used to quantify the volumetric breast density. First, standard fuzzy c-means (FCM) clustering was used on raw images with the bias field present. Then, the coherent local intensity clustering (CLIC) method estimated and corrected the bias field during the iterative tissue segmentation process. Finally, FCM clustering was performed on the bias-field-corrected images produced by CLIC method. The left–right correlation for breasts in the same pair was studied for both segmentation algorithms to evaluate the precision of the tissue classification. Finally, the breast densities measured with the three methods were compared to the gold standard tissue compositions obtained from chemical analysis. The linear correlation coefficient, Pearson's r, was used to evaluate the two image segmentation algorithms and the effect of bias field. Results: The CLIC method successfully corrected the intensity inhomogeneity induced by the bias field. In left–right comparisons, the CLIC method significantly improved the slope and the correlation coefficient of the linear fitting for the glandular volume estimation. The left–right breast density correlation was also increased from 0.93 to 0.98. When compared with the percent fibroglandular volume (%FGV) from chemical analysis, results after bias field correction from both the CLIC the FCM algorithms showed improved linear correlation. As a result, the Pearson's r increased from 0.86 to 0.92 with the bias field correction. Conclusions: The investigated CLIC method significantly increased the precision and accuracy of breast density quantification using breast MRI images by effectively correcting the bias field. It is expected that a fully automated computerized algorithm for breast density quantification may have great potential in clinical MRI applications. PMID:24320536

Breast density quantification using magnetic resonance imaging (MRI) with bias field correction: a postmortem study.

PubMed

Ding, Huanjun; Johnson, Travis; Lin, Muqing; Le, Huy Q; Ducote, Justin L; Su, Min-Ying; Molloi, Sabee

2013-12-01

Quantification of breast density based on three-dimensional breast MRI may provide useful information for the early detection of breast cancer. However, the field inhomogeneity can severely challenge the computerized image segmentation process. In this work, the effect of the bias field in breast density quantification has been investigated with a postmortem study. T1-weighted images of 20 pairs of postmortem breasts were acquired on a 1.5 T breast MRI scanner. Two computer-assisted algorithms were used to quantify the volumetric breast density. First, standard fuzzy c-means (FCM) clustering was used on raw images with the bias field present. Then, the coherent local intensity clustering (CLIC) method estimated and corrected the bias field during the iterative tissue segmentation process. Finally, FCM clustering was performed on the bias-field-corrected images produced by CLIC method. The left-right correlation for breasts in the same pair was studied for both segmentation algorithms to evaluate the precision of the tissue classification. Finally, the breast densities measured with the three methods were compared to the gold standard tissue compositions obtained from chemical analysis. The linear correlation coefficient, Pearson's r, was used to evaluate the two image segmentation algorithms and the effect of bias field. The CLIC method successfully corrected the intensity inhomogeneity induced by the bias field. In left-right comparisons, the CLIC method significantly improved the slope and the correlation coefficient of the linear fitting for the glandular volume estimation. The left-right breast density correlation was also increased from 0.93 to 0.98. When compared with the percent fibroglandular volume (%FGV) from chemical analysis, results after bias field correction from both the CLIC the FCM algorithms showed improved linear correlation. As a result, the Pearson's r increased from 0.86 to 0.92 with the bias field correction. The investigated CLIC method significantly increased the precision and accuracy of breast density quantification using breast MRI images by effectively correcting the bias field. It is expected that a fully automated computerized algorithm for breast density quantification may have great potential in clinical MRI applications.

Improved fuzzy clustering algorithms in segmentation of DC-enhanced breast MRI.

PubMed

Kannan, S R; Ramathilagam, S; Devi, Pandiyarajan; Sathya, A

2012-02-01

Segmentation of medical images is a difficult and challenging problem due to poor image contrast and artifacts that result in missing or diffuse organ/tissue boundaries. Many researchers have applied various techniques however fuzzy c-means (FCM) based algorithms is more effective compared to other methods. The objective of this work is to develop some robust fuzzy clustering segmentation systems for effective segmentation of DCE - breast MRI. This paper obtains the robust fuzzy clustering algorithms by incorporating kernel methods, penalty terms, tolerance of the neighborhood attraction, additional entropy term and fuzzy parameters. The initial centers are obtained using initialization algorithm to reduce the computation complexity and running time of proposed algorithms. Experimental works on breast images show that the proposed algorithms are effective to improve the similarity measurement, to handle large amount of noise, to have better results in dealing the data corrupted by noise, and other artifacts. The clustering results of proposed methods are validated using Silhouette Method.

SPEQTACLE: An automated generalized fuzzy C-means algorithm for tumor delineation in PET

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

Lapuyade-Lahorgue, Jérôme; Visvikis, Dimitris; Hatt, Mathieu, E-mail: hatt@univ-brest.fr

Purpose: Accurate tumor delineation in positron emission tomography (PET) images is crucial in oncology. Although recent methods achieved good results, there is still room for improvement regarding tumors with complex shapes, low signal-to-noise ratio, and high levels of uptake heterogeneity. Methods: The authors developed and evaluated an original clustering-based method called spatial positron emission quantification of tumor—Automatic Lp-norm estimation (SPEQTACLE), based on the fuzzy C-means (FCM) algorithm with a generalization exploiting a Hilbertian norm to more accurately account for the fuzzy and non-Gaussian distributions of PET images. An automatic and reproducible estimation scheme of the norm on an image-by-image basismore » was developed. Robustness was assessed by studying the consistency of results obtained on multiple acquisitions of the NEMA phantom on three different scanners with varying acquisition parameters. Accuracy was evaluated using classification errors (CEs) on simulated and clinical images. SPEQTACLE was compared to another FCM implementation, fuzzy local information C-means (FLICM) and fuzzy locally adaptive Bayesian (FLAB). Results: SPEQTACLE demonstrated a level of robustness similar to FLAB (variability of 14% ± 9% vs 14% ± 7%, p = 0.15) and higher than FLICM (45% ± 18%, p < 0.0001), and improved accuracy with lower CE (14% ± 11%) over both FLICM (29% ± 29%) and FLAB (22% ± 20%) on simulated images. Improvement was significant for the more challenging cases with CE of 17% ± 11% for SPEQTACLE vs 28% ± 22% for FLAB (p = 0.009) and 40% ± 35% for FLICM (p < 0.0001). For the clinical cases, SPEQTACLE outperformed FLAB and FLICM (15% ± 6% vs 37% ± 14% and 30% ± 17%, p < 0.004). Conclusions: SPEQTACLE benefitted from the fully automatic estimation of the norm on a case-by-case basis. This promising approach will be extended to multimodal images and multiclass estimation in future developments.« less

Study of Burn Scar Extraction Automatically Based on Level Set Method using Remote Sensing Data

PubMed Central

Liu, Yang; Dai, Qin; Liu, JianBo; Liu, ShiBin; Yang, Jin

2014-01-01

Burn scar extraction using remote sensing data is an efficient way to precisely evaluate burn area and measure vegetation recovery. Traditional burn scar extraction methodologies have no well effect on burn scar image with blurred and irregular edges. To address these issues, this paper proposes an automatic method to extract burn scar based on Level Set Method (LSM). This method utilizes the advantages of the different features in remote sensing images, as well as considers the practical needs of extracting the burn scar rapidly and automatically. This approach integrates Change Vector Analysis (CVA), Normalized Difference Vegetation Index (NDVI) and the Normalized Burn Ratio (NBR) to obtain difference image and modifies conventional Level Set Method Chan-Vese (C-V) model with a new initial curve which results from a binary image applying K-means method on fitting errors of two near-infrared band images. Landsat 5 TM and Landsat 8 OLI data sets are used to validate the proposed method. Comparison with conventional C-V model, OSTU algorithm, Fuzzy C-mean (FCM) algorithm are made to show that the proposed approach can extract the outline curve of fire burn scar effectively and exactly. The method has higher extraction accuracy and less algorithm complexity than that of the conventional C-V model. PMID:24503563

Classifying human operator functional state based on electrophysiological and performance measures and fuzzy clustering method.

PubMed

Zhang, Jian-Hua; Peng, Xiao-Di; Liu, Hua; Raisch, Jörg; Wang, Ru-Bin

2013-12-01

The human operator's ability to perform their tasks can fluctuate over time. Because the cognitive demands of the task can also vary it is possible that the capabilities of the operator are not sufficient to satisfy the job demands. This can lead to serious errors when the operator is overwhelmed by the task demands. Psychophysiological measures, such as heart rate and brain activity, can be used to monitor operator cognitive workload. In this paper, the most influential psychophysiological measures are extracted to characterize Operator Functional State (OFS) in automated tasks under a complex form of human-automation interaction. The fuzzy c-mean (FCM) algorithm is used and tested for its OFS classification performance. The results obtained have shown the feasibility and effectiveness of the FCM algorithm as well as the utility of the selected input features for OFS classification. Besides being able to cope with nonlinearity and fuzzy uncertainty in the psychophysiological data it can provide information about the relative importance of the input features as well as the confidence estimate of the classification results. The OFS pattern classification method developed can be incorporated into an adaptive aiding system in order to enhance the overall performance of a large class of safety-critical human-machine cooperative systems.

Load forecast method of electric vehicle charging station using SVR based on GA-PSO

NASA Astrophysics Data System (ADS)

Lu, Kuan; Sun, Wenxue; Ma, Changhui; Yang, Shenquan; Zhu, Zijian; Zhao, Pengfei; Zhao, Xin; Xu, Nan

2017-06-01

This paper presents a Support Vector Regression (SVR) method for electric vehicle (EV) charging station load forecast based on genetic algorithm (GA) and particle swarm optimization (PSO). Fuzzy C-Means (FCM) clustering is used to establish similar day samples. GA is used for global parameter searching and PSO is used for a more accurately local searching. Load forecast is then regressed using SVR. The practical load data of an EV charging station were taken to illustrate the proposed method. The result indicates an obvious improvement in the forecasting accuracy compared with SVRs based on PSO and GA exclusively.

Application of affinity propagation algorithm based on manifold distance for transformer PD pattern recognition

NASA Astrophysics Data System (ADS)

Wei, B. G.; Huo, K. X.; Yao, Z. F.; Lou, J.; Li, X. Y.

2018-03-01

It is one of the difficult problems encountered in the research of condition maintenance technology of transformers to recognize partial discharge (PD) pattern. According to the main physical characteristics of PD, three models of oil-paper insulation defects were set up in laboratory to study the PD of transformers, and phase resolved partial discharge (PRPD) was constructed. By using least square method, the grey-scale images of PRPD were constructed and features of each grey-scale image were 28 box dimensions and 28 information dimensions. Affinity propagation algorithm based on manifold distance (AP-MD) for transformers PD pattern recognition was established, and the data of box dimension and information dimension were clustered based on AP-MD. Study shows that clustering result of AP-MD is better than the results of affinity propagation (AP), k-means and fuzzy c-means algorithm (FCM). By choosing different k values of k-nearest neighbor, we find clustering accuracy of AP-MD falls when k value is larger or smaller, and the optimal k value depends on sample size.

Artificial intelligence techniques coupled with seasonality measures for hydrological regionalization of Q90 under Brazilian conditions

NASA Astrophysics Data System (ADS)

Beskow, Samuel; de Mello, Carlos Rogério; Vargas, Marcelle M.; Corrêa, Leonardo de L.; Caldeira, Tamara L.; Durães, Matheus F.; de Aguiar, Marilton S.

2016-10-01

Information on stream flows is essential for water resources management. The stream flow that is equaled or exceeded 90% of the time (Q90) is one the most used low stream flow indicators in many countries, and its determination is made from the frequency analysis of stream flows considering a historical series. However, stream flow gauging network is generally not spatially sufficient to meet the necessary demands of technicians, thus the most plausible alternative is the use of hydrological regionalization. The objective of this study was to couple the artificial intelligence techniques (AI) K-means, Partitioning Around Medoids (PAM), K-harmonic means (KHM), Fuzzy C-means (FCM) and Genetic K-means (GKA), with measures of low stream flow seasonality, for verification of its potential to delineate hydrologically homogeneous regions for the regionalization of Q90. For the performance analysis of the proposed methodology, location attributes from 108 watersheds situated in southern Brazil, and attributes associated with their seasonality of low stream flows were considered in this study. It was concluded that: (i) AI techniques have the potential to delineate hydrologically homogeneous regions in the context of Q90 in the study region, especially the FCM method based on fuzzy logic, and GKA, based on genetic algorithms; (ii) the attributes related to seasonality of low stream flows added important information that increased the accuracy of the grouping; and (iii) the adjusted mathematical models have excellent performance and can be used to estimate Q90 in locations lacking monitoring.

Advanced soft computing diagnosis method for tumour grading.

PubMed

Papageorgiou, E I; Spyridonos, P P; Stylios, C D; Ravazoula, P; Groumpos, P P; Nikiforidis, G N

2006-01-01

To develop an advanced diagnostic method for urinary bladder tumour grading. A novel soft computing modelling methodology based on the augmentation of fuzzy cognitive maps (FCMs) with the unsupervised active Hebbian learning (AHL) algorithm is applied. One hundred and twenty-eight cases of urinary bladder cancer were retrieved from the archives of the Department of Histopathology, University Hospital of Patras, Greece. All tumours had been characterized according to the classical World Health Organization (WHO) grading system. To design the FCM model for tumour grading, three experts histopathologists defined the main histopathological features (concepts) and their impact on grade characterization. The resulted FCM model consisted of nine concepts. Eight concepts represented the main histopathological features for tumour grading. The ninth concept represented the tumour grade. To increase the classification ability of the FCM model, the AHL algorithm was applied to adjust the weights of the FCM. The proposed FCM grading model achieved a classification accuracy of 72.5%, 74.42% and 95.55% for tumours of grades I, II and III, respectively. An advanced computerized method to support tumour grade diagnosis decision was proposed and developed. The novelty of the method is based on employing the soft computing method of FCMs to represent specialized knowledge on histopathology and on augmenting FCMs ability using an unsupervised learning algorithm, the AHL. The proposed method performs with reasonably high accuracy compared to other existing methods and at the same time meets the physicians' requirements for transparency and explicability.

Change Detection of Remote Sensing Images by Dt-Cwt and Mrf

NASA Astrophysics Data System (ADS)

Ouyang, S.; Fan, K.; Wang, H.; Wang, Z.

2017-05-01

Aiming at the significant loss of high frequency information during reducing noise and the pixel independence in change detection of multi-scale remote sensing image, an unsupervised algorithm is proposed based on the combination between Dual-tree Complex Wavelet Transform (DT-CWT) and Markov random Field (MRF) model. This method first performs multi-scale decomposition for the difference image by the DT-CWT and extracts the change characteristics in high-frequency regions by using a MRF-based segmentation algorithm. Then our method estimates the final maximum a posterior (MAP) according to the segmentation algorithm of iterative condition model (ICM) based on fuzzy c-means(FCM) after reconstructing the high-frequency and low-frequency sub-bands of each layer respectively. Finally, the method fuses the above segmentation results of each layer by using the fusion rule proposed to obtain the mask of the final change detection result. The results of experiment prove that the method proposed is of a higher precision and of predominant robustness properties.

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.

Computer-aided detection of breast lesions in DCE-MRI using region growing based on fuzzy C-means clustering and vesselness filter

NASA Astrophysics Data System (ADS)

B. Shokouhi, Shahriar; Fooladivanda, Aida; Ahmadinejad, Nasrin

2017-12-01

A computer-aided detection (CAD) system is introduced in this paper for detection of breast lesions in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). The proposed CAD system firstly compensates motion artifacts and segments the breast region. Then, the potential lesion voxels are detected and used as the initial seed points for the seeded region-growing algorithm. A new and robust region-growing algorithm incorporating with Fuzzy C-means (FCM) clustering and vesselness filter is proposed to segment any potential lesion regions. Subsequently, the false positive detections are reduced by applying a discrimination step. This is based on 3D morphological characteristics of the potential lesion regions and kinetic features which are fed to the support vector machine (SVM) classifier. The performance of the proposed CAD system is evaluated using the free-response operating characteristic (FROC) curve. We introduce our collected dataset that includes 76 DCE-MRI studies, 63 malignant and 107 benign lesions. The prepared dataset has been used to verify the accuracy of the proposed CAD system. At 5.29 false positives per case, the CAD system accurately detects 94% of the breast lesions.

A Computer-Aided Type-II Fuzzy Image Processing for Diagnosis of Meniscus Tear.

PubMed

Zarandi, M H Fazel; Khadangi, A; Karimi, F; Turksen, I B

2016-12-01

Meniscal tear is one of the prevalent knee disorders among young athletes and the aging population, and requires correct diagnosis and surgical intervention, if necessary. Not only the errors followed by human intervention but also the obstacles of manual meniscal tear detection highlight the need for automatic detection techniques. This paper presents a type-2 fuzzy expert system for meniscal tear diagnosis using PD magnetic resonance images (MRI). The scheme of the proposed type-2 fuzzy image processing model is composed of three distinct modules: Pre-processing, Segmentation, and Classification. λ-nhancement algorithm is used to perform the pre-processing step. For the segmentation step, first, Interval Type-2 Fuzzy C-Means (IT2FCM) is applied to the images, outputs of which are then employed by Interval Type-2 Possibilistic C-Means (IT2PCM) to perform post-processes. Second stage concludes with re-estimation of "η" value to enhance IT2PCM. Finally, a Perceptron neural network with two hidden layers is used for Classification stage. The results of the proposed type-2 expert system have been compared with a well-known segmentation algorithm, approving the superiority of the proposed system in meniscal tear recognition.

Design of hybrid radial basis function neural networks (HRBFNNs) realized with the aid of hybridization of fuzzy clustering method (FCM) and polynomial neural networks (PNNs).

PubMed

Huang, Wei; Oh, Sung-Kwun; Pedrycz, Witold

2014-12-01

In this study, we propose Hybrid Radial Basis Function Neural Networks (HRBFNNs) realized with the aid of fuzzy clustering method (Fuzzy C-Means, FCM) and polynomial neural networks. Fuzzy clustering used to form information granulation is employed to overcome a possible curse of dimensionality, while the polynomial neural network is utilized to build local models. Furthermore, genetic algorithm (GA) is exploited here to optimize the essential design parameters of the model (including fuzzification coefficient, the number of input polynomial fuzzy neurons (PFNs), and a collection of the specific subset of input PFNs) of the network. To reduce dimensionality of the input space, principal component analysis (PCA) is considered as a sound preprocessing vehicle. The performance of the HRBFNNs is quantified through a series of experiments, in which we use several modeling benchmarks of different levels of complexity (different number of input variables and the number of available data). A comparative analysis reveals that the proposed HRBFNNs exhibit higher accuracy in comparison to the accuracy produced by some models reported previously in the literature. Copyright © 2014 Elsevier Ltd. All rights reserved.

A geomorphology-based ANFIS model for multi-station modeling of rainfall-runoff process

NASA Astrophysics Data System (ADS)

Nourani, Vahid; Komasi, Mehdi

2013-05-01

This paper demonstrates the potential use of Artificial Intelligence (AI) techniques for predicting daily runoff at multiple gauging stations. Uncertainty and complexity of the rainfall-runoff process due to its variability in space and time in one hand and lack of historical data on the other hand, cause difficulties in the spatiotemporal modeling of the process. In this paper, an Integrated Geomorphological Adaptive Neuro-Fuzzy Inference System (IGANFIS) model conjugated with C-means clustering algorithm was used for rainfall-runoff modeling at multiple stations of the Eel River watershed, California. The proposed model could be used for predicting runoff in the stations with lack of data or any sub-basin within the watershed because of employing the spatial and temporal variables of the sub-basins as the model inputs. This ability of the integrated model for spatiotemporal modeling of the process was examined through the cross validation technique for a station. In this way, different ANFIS structures were trained using Sugeno algorithm in order to estimate daily discharge values at different stations. In order to improve the model efficiency, the input data were then classified into some clusters by the means of fuzzy C-means (FCMs) method. The goodness-of-fit measures support the gainful use of the IGANFIS and FCM methods in spatiotemporal modeling of hydrological processes.

Multivariate Spatial Condition Mapping Using Subtractive Fuzzy Cluster Means

PubMed Central

Sabit, Hakilo; Al-Anbuky, Adnan

2014-01-01

Wireless sensor networks are usually deployed for monitoring given physical phenomena taking place in a specific space and over a specific duration of time. The spatio-temporal distribution of these phenomena often correlates to certain physical events. To appropriately characterise these events-phenomena relationships over a given space for a given time frame, we require continuous monitoring of the conditions. WSNs are perfectly suited for these tasks, due to their inherent robustness. This paper presents a subtractive fuzzy cluster means algorithm and its application in data stream mining for wireless sensor systems over a cloud-computing-like architecture, which we call sensor cloud data stream mining. Benchmarking on standard mining algorithms, the k-means and the FCM algorithms, we have demonstrated that the subtractive fuzzy cluster means model can perform high quality distributed data stream mining tasks comparable to centralised data stream mining. PMID:25313495

Investigation of the accuracy of breast tissue segmentation methods for the purpose of developing breast deformation models for use in adaptive radiotherapy

NASA Astrophysics Data System (ADS)

Juneja, P.; Harris, E. J.; Evans, P. M.

2014-03-01

Realistic modelling of breast deformation requires the breast tissue to be segmented into fibroglandular and fatty tissue and assigned suitable material properties. There are a number of breast tissue segmentation methods proposed and used in the literature. The purpose of this study was to validate and compare the accuracy of various segmentation methods and to investigate the effect of the tissue distribution on the segmentation accuracy. Computed tomography (CT) data for 24 patients, both in supine and prone positions were segmented into fibroglandular and fatty tissue. The segmentation methods explored were: physical density thresholding; interactive thresholding; fuzzy c-means clustering (FCM) with three classes (FCM3) and four classes (FCM4); and k-means clustering. Validation was done in two-stages: firstly, a new approach, supine-prone validation based on the assumption that the breast composition should appear the same in the supine and prone scans was used. Secondly, outlines from three experts were used for validation. This study found that FCM3 gave the most accurate segmentation of breast tissue from CT data and that the segmentation accuracy is adversely affected by the sparseness of the fibroglandular tissue distribution.

Landslide susceptibility analysis with logistic regression model based on FCM sampling strategy

NASA Astrophysics Data System (ADS)

Wang, Liang-Jie; Sawada, Kazuhide; Moriguchi, Shuji

2013-08-01

Several mathematical models are used to predict the spatial distribution characteristics of landslides to mitigate damage caused by landslide disasters. Although some studies have achieved excellent results around the world, few studies take the inter-relationship of the selected points (training points) into account. In this paper, we present the Fuzzy c-means (FCM) algorithm as an optimal method for choosing the appropriate input landslide points as training data. Based on different combinations of the Fuzzy exponent (m) and the number of clusters (c), five groups of sampling points were derived from formal seed cells points and applied to analyze the landslide susceptibility in Mizunami City, Gifu Prefecture, Japan. A logistic regression model is applied to create the models of the relationships between landslide-conditioning factors and landslide occurrence. The pre-existing landslide bodies and the area under the relative operative characteristic (ROC) curve were used to evaluate the performance of all the models with different m and c. The results revealed that Model no. 4 (m=1.9, c=4) and Model no. 5 (m=1.9, c=5) have significantly high classification accuracies, i.e., 90.0%. Moreover, over 30% of the landslide bodies were grouped under the very high susceptibility zone. Otherwise, Model no. 4 and Model no. 5 had higher area under the ROC curve (AUC) values, which were 0.78 and 0.79, respectively. Therefore, Model no. 4 and Model no. 5 offer better model results for landslide susceptibility mapping. Maps derived from Model no. 4 and Model no. 5 would offer the local authorities crucial information for city planning and development.

Classification of arrhythmia using hybrid networks.

PubMed

Haseena, Hassan H; Joseph, Paul K; Mathew, Abraham T

2011-12-01

Reliable detection of arrhythmias based on digital processing of Electrocardiogram (ECG) signals is vital in providing suitable and timely treatment to a cardiac patient. Due to corruption of ECG signals with multiple frequency noise and presence of multiple arrhythmic events in a cardiac rhythm, computerized interpretation of abnormal ECG rhythms is a challenging task. This paper focuses a Fuzzy C- Mean (FCM) clustered Probabilistic Neural Network (PNN) and Multi Layered Feed Forward Network (MLFFN) for the discrimination of eight types of ECG beats. Parameters such as fourth order Auto Regressive (AR) coefficients along with Spectral Entropy (SE) are extracted from each ECG beat and feature reduction has been carried out using FCM clustering. The cluster centers form the input of neural network classifiers. The extensive analysis of Massachusetts Institute of Technology- Beth Israel Hospital (MIT-BIH) arrhythmia database shows that FCM clustered PNNs is superior in cardiac arrhythmia classification than FCM clustered MLFFN with an overall accuracy of 99.05%, 97.14%, respectively.

Interlaboratory assessment of mitotic index by flow cytometry confirms superior reproducibility relative to microscopic scoring.

PubMed

Roberts, D J; Spellman, R A; Sanok, K; Chen, H; Chan, M; Yurt, P; Thakur, A K; DeVito, G L; Murli, H; Stankowski, L F

2012-05-01

A flow cytometric procedure for determining mitotic index (MI) as part of the metaphase chromosome aberrations assay, developed and utilized routinely at Pfizer as part of their standard assay design, has been adopted successfully by Covance laboratories. This method, using antibodies against phosphorylated histone tails (H3PS10) and nucleic acid stain, has been evaluated by the two independent test sites and compared to manual scoring. Primary human lymphocytes were treated with cyclophosphamide, mitomycin C, benzo(a)pyrene, and etoposide at concentrations inducing dose-dependent cytotoxicity. Deming regression analysis indicates that the results generated via flow cytometry (FCM) were more consistent between sites than those generated via microscopy. Further analysis using the Bland-Altman modification of the Tukey mean difference method supports this finding, as the standard deviations (SDs) of differences in MI generated by FCM were less than half of those generated manually. Decreases in scoring variability owing to the objective nature of FCM, and the greater number of cells analyzed, make FCM a superior method for MI determination. In addition, the FCM method has proven to be transferable and easily integrated into standard genetic toxicology laboratory operations. Copyright © 2012 Wiley Periodicals, Inc.

A multiple-feature and multiple-kernel scene segmentation algorithm for humanoid robot.

PubMed

Liu, Zhi; Xu, Shuqiong; Zhang, Yun; Chen, Chun Lung Philip

2014-11-01

This technical correspondence presents a multiple-feature and multiple-kernel support vector machine (MFMK-SVM) methodology to achieve a more reliable and robust segmentation performance for humanoid robot. The pixel wise intensity, gradient, and C1 SMF features are extracted via the local homogeneity model and Gabor filter, which would be used as inputs of MFMK-SVM model. It may provide multiple features of the samples for easier implementation and efficient computation of MFMK-SVM model. A new clustering method, which is called feature validity-interval type-2 fuzzy C-means (FV-IT2FCM) clustering algorithm, is proposed by integrating a type-2 fuzzy criterion in the clustering optimization process to improve the robustness and reliability of clustering results by the iterative optimization. Furthermore, the clustering validity is employed to select the training samples for the learning of the MFMK-SVM model. The MFMK-SVM scene segmentation method is able to fully take advantage of the multiple features of scene image and the ability of multiple kernels. Experiments on the BSDS dataset and real natural scene images demonstrate the superior performance of our proposed method.

Categorizing document by fuzzy C-Means and K-nearest neighbors approach

NASA Astrophysics Data System (ADS)

Priandini, Novita; Zaman, Badrus; Purwanti, Endah

2017-08-01

Increasing of technology had made categorizing documents become important. It caused by increasing of number of documents itself. Managing some documents by categorizing is one of Information Retrieval application, because it involve text mining on its process. Whereas, categorization technique could be done both Fuzzy C-Means (FCM) and K-Nearest Neighbors (KNN) method. This experiment would consolidate both methods. The aim of the experiment is increasing performance of document categorize. First, FCM is in order to clustering training documents. Second, KNN is in order to categorize testing document until the output of categorization is shown. Result of the experiment is 14 testing documents retrieve relevantly to its category. Meanwhile 6 of 20 testing documents retrieve irrelevant to its category. Result of system evaluation shows that both precision and recall are 0,7.

Image segmentation using fuzzy LVQ clustering networks

NASA Technical Reports Server (NTRS)

Tsao, Eric Chen-Kuo; Bezdek, James C.; Pal, Nikhil R.

1992-01-01

In this note we formulate image segmentation as a clustering problem. Feature vectors extracted from a raw image are clustered into subregions, thereby segmenting the image. A fuzzy generalization of a Kohonen learning vector quantization (LVQ) which integrates the Fuzzy c-Means (FCM) model with the learning rate and updating strategies of the LVQ is used for this task. This network, which segments images in an unsupervised manner, is thus related to the FCM optimization problem. Numerical examples on photographic and magnetic resonance images are given to illustrate this approach to image segmentation.

Characterization and prediction of the backscattered form function of an immersed cylindrical shell using hybrid fuzzy clustering and bio-inspired algorithms.

PubMed

Agounad, Said; Aassif, El Houcein; Khandouch, Younes; Maze, Gérard; Décultot, Dominique

2018-02-01

The acoustic scattering of a plane wave by an elastic cylindrical shell is studied. A new approach is developed to predict the form function of an immersed cylindrical shell of the radius ratio b/a ('b' is the inner radius and 'a' is the outer radius). The prediction of the backscattered form function is investigated by a combined approach between fuzzy clustering algorithms and bio-inspired algorithms. Four famous fuzzy clustering algorithms: the fuzzy c-means (FCM), the Gustafson-Kessel algorithm (GK), the fuzzy c-regression model (FCRM) and the Gath-Geva algorithm (GG) are combined with particle swarm optimization and genetic algorithm. The symmetric and antisymmetric circumferential waves A, S 0 , A 1 , S 1 and S 2 are investigated in a reduced frequency (k 1 a) range extends over 0.1

Optimized face recognition algorithm using radial basis function neural networks and its practical applications.

PubMed

Yoo, Sung-Hoon; Oh, Sung-Kwun; Pedrycz, Witold

2015-09-01

In this study, we propose a hybrid method of face recognition by using face region information extracted from the detected face region. In the preprocessing part, we develop a hybrid approach based on the Active Shape Model (ASM) and the Principal Component Analysis (PCA) algorithm. At this step, we use a CCD (Charge Coupled Device) camera to acquire a facial image by using AdaBoost and then Histogram Equalization (HE) is employed to improve the quality of the image. ASM extracts the face contour and image shape to produce a personal profile. Then we use a PCA method to reduce dimensionality of face images. In the recognition part, we consider the improved Radial Basis Function Neural Networks (RBF NNs) to identify a unique pattern associated with each person. The proposed RBF NN architecture consists of three functional modules realizing the condition phase, the conclusion phase, and the inference phase completed with the help of fuzzy rules coming in the standard 'if-then' format. In the formation of the condition part of the fuzzy rules, the input space is partitioned with the use of Fuzzy C-Means (FCM) clustering. In the conclusion part of the fuzzy rules, the connections (weights) of the RBF NNs are represented by four kinds of polynomials such as constant, linear, quadratic, and reduced quadratic. The values of the coefficients are determined by running a gradient descent method. The output of the RBF NNs model is obtained by running a fuzzy inference method. The essential design parameters of the network (including learning rate, momentum coefficient and fuzzification coefficient used by the FCM) are optimized by means of Differential Evolution (DE). The proposed P-RBF NNs (Polynomial based RBF NNs) are applied to facial recognition and its performance is quantified from the viewpoint of the output performance and recognition rate. Copyright © 2015 Elsevier Ltd. All rights reserved.

Cytochemistry and C-values: The Less-well-known World of Nuclear DNA Amounts

PubMed Central

Greilhuber, J.

2008-01-01

Background In the plant sciences there are two widely applied technologies for measuring nuclear DNA content: Feulgen absorbance cytophotometry and flow cytometry (FCM). While FCM is, with good reasons, increasingly popular among plant scientists, absorbance-cytophotometric techniques lose ground. This results in a narrowing of the methodological repertoire, which is neither desirable nor beneficial. Both approaches have their advantages, but static cytophotometry seems to pose more instrumental difficulties and material-based problems than FCM, so that Feulgen-based data in the literature are often less reliable than one would expect. Scope The purpose of this article is to present a selective overview of the field of nuclear DNA content measurement, and C-values in particular, with a focus on the technical difficulties imposed by the characteristics of the biological material and with some comments on the photometrical aspects of the work. For over 20 years it has been known that plant polyphenols cause problems in Feulgen DNA cytophotometry, since they act as major staining inhibitors leading to unreliable results. However, little information is available about the chemical classes of plant metabolites capable of DNA staining interference and the mechanisms of their inhibition. Plant slimes are another source of concern. Conclusions In FCM research to uncover the effects of secondary metabolites on measurement results has begun only recently. In particular, the analysis of intraspecific genome size variation demands a stringent methodology which accounts for inhibitors. FCM tests for inhibitory effects of endogenous metabolites should become obligatory. The use of dry seeds for harvesting embryo and endosperm nuclei for FCM and Feulgen densitometry may often provide a means of circumventing staining inhibitors. The importance of internal standardization is highlighted. Our goal is a better understanding of phytochemical/cytochemical interactions in plant DNA photometry for the benefit of an ever-growing list of plant genome sizes. PMID:17951594

Abdominal adipose tissue quantification on water-suppressed and non-water-suppressed MRI at 3T using semi-automated FCM clustering algorithm

NASA Astrophysics Data System (ADS)

Valaparla, Sunil K.; Peng, Qi; Gao, Feng; Clarke, Geoffrey D.

2014-03-01

Accurate measurements of human body fat distribution are desirable because excessive body fat is associated with impaired insulin sensitivity, type 2 diabetes mellitus (T2DM) and cardiovascular disease. In this study, we hypothesized that the performance of water suppressed (WS) MRI is superior to non-water suppressed (NWS) MRI for volumetric assessment of abdominal subcutaneous (SAT), intramuscular (IMAT), visceral (VAT), and total (TAT) adipose tissues. We acquired T1-weighted images on a 3T MRI system (TIM Trio, Siemens), which was analyzed using semi-automated segmentation software that employs a fuzzy c-means (FCM) clustering algorithm. Sixteen contiguous axial slices, centered at the L4-L5 level of the abdomen, were acquired in eight T2DM subjects with water suppression (WS) and without (NWS). Histograms from WS images show improved separation of non-fatty tissue pixels from fatty tissue pixels, compared to NWS images. Paired t-tests of WS versus NWS showed a statistically significant lower volume of lipid in the WS images for VAT (145.3 cc less, p=0.006) and IMAT (305 cc less, p<0.001), but not SAT (14.1 cc more, NS). WS measurements of TAT also resulted in lower fat volumes (436.1 cc less, p=0.002). There is strong correlation between WS and NWS quantification methods for SAT measurements (r=0.999), but poorer correlation for VAT studies (r=0.845). These results suggest that NWS pulse sequences may overestimate adipose tissue volumes and that WS pulse sequences are more desirable due to the higher contrast generated between fatty and non-fatty tissues.

Integrating dynamic fuzzy C-means, data envelopment analysis and artificial neural network to online prediction performance of companies in stock exchange

NASA Astrophysics Data System (ADS)

Jahangoshai Rezaee, Mustafa; Jozmaleki, Mehrdad; Valipour, Mahsa

2018-01-01

One of the main features to invest in stock exchange companies is their financial performance. On the other hand, conventional evaluation methods such as data envelopment analysis are not only a retrospective process, but are also a process, which are incomplete and ineffective approaches to evaluate the companies in the future. To remove this problem, it is required to plan an expert system for evaluating organizations when the online data are received from stock exchange market. This paper deals with an approach for predicting the online financial performance of companies when data are received in different time's intervals. The proposed approach is based on integrating fuzzy C-means (FCM), data envelopment analysis (DEA) and artificial neural network (ANN). The classical FCM method is unable to update the number of clusters and their members when the data are changed or the new data are received. Hence, this method is developed in order to make dynamic features for the number of clusters and clusters members in classical FCM. Then, DEA is used to evaluate DMUs by using financial ratios to provide targets in neural network. Finally, the designed network is trained and prepared for predicting companies' future performance. The data on Tehran Stock Market companies for six consecutive years (2007-2012) are used to show the abilities of the proposed approach.

Rapid Estimation of Astaxanthin and the Carotenoid-to-Chlorophyll Ratio in the Green Microalga Chromochloris zofingiensis Using Flow Cytometry.

PubMed

Chen, Junhui; Wei, Dong; Pohnert, Georg

2017-07-19

The green microalga Chromochloris zofingiensis can accumulate significant amounts of valuable carotenoids, mainly natural astaxanthin, a product with applications in functional food, cosmetics, nutraceuticals, and with potential therapeutic value in cardiovascular and neurological diseases. To optimize the production of astaxanthin, it is essential to monitor the content of astaxanthin in algal cells during cultivation. The widely used HPLC (high-performance liquid chromatography) method for quantitative astaxanthin determination is time-consuming and laborious. In the present work, we present a method using flow cytometry (FCM) for in vivo determination of the astaxanthin content and the carotenoid-to-chlorophyll ratio (Car/Chl) in mixotrophic C. zofingiensis . The method is based on the assessment of fluorescent characteristics of cellular pigments. The mean fluorescence intensity (MFI) of living cells was determined by FCM to monitor pigment formation based on the correlation between MFI detected in particular channels (FL1: 533 ± 15 nm; FL2: 585 ± 20 nm; FL3: >670 nm) and pigment content in algal cells. Through correlation and regression analysis, a linear relationship was observed between MFI in FL2 (band-pass filter, emission at 585 nm in FCM) and astaxanthin content (in HPLC) and applied for predicting astaxanthin content. With similar procedures, the relationships between MFI in different channels and Car/Chl ratio in mixotrophic C. zofingiensis were also determined. Car/Chl ratios could be estimated by the ratios of MFI (FL1/FL3, FL2/FL3). FCM is thus a highly efficient and feasible method for rapid estimation of astaxanthin content in the green microalga C. zofingiensis . The rapid FCM method is complementary to the current HPLC method, especially for rapid evaluation and prediction of astaxanthin formation as it is required during the high-throughput culture in the laboratory and mass cultivation in industry.

Rapid Estimation of Astaxanthin and the Carotenoid-to-Chlorophyll Ratio in the Green Microalga Chromochloris zofingiensis Using Flow Cytometry

PubMed Central

Chen, Junhui; Pohnert, Georg

2017-01-01

The green microalga Chromochloris zofingiensis can accumulate significant amounts of valuable carotenoids, mainly natural astaxanthin, a product with applications in functional food, cosmetics, nutraceuticals, and with potential therapeutic value in cardiovascular and neurological diseases. To optimize the production of astaxanthin, it is essential to monitor the content of astaxanthin in algal cells during cultivation. The widely used HPLC (high-performance liquid chromatography) method for quantitative astaxanthin determination is time-consuming and laborious. In the present work, we present a method using flow cytometry (FCM) for in vivo determination of the astaxanthin content and the carotenoid-to-chlorophyll ratio (Car/Chl) in mixotrophic C. zofingiensis. The method is based on the assessment of fluorescent characteristics of cellular pigments. The mean fluorescence intensity (MFI) of living cells was determined by FCM to monitor pigment formation based on the correlation between MFI detected in particular channels (FL1: 533 ± 15 nm; FL2: 585 ± 20 nm; FL3: >670 nm) and pigment content in algal cells. Through correlation and regression analysis, a linear relationship was observed between MFI in FL2 (band-pass filter, emission at 585 nm in FCM) and astaxanthin content (in HPLC) and applied for predicting astaxanthin content. With similar procedures, the relationships between MFI in different channels and Car/Chl ratio in mixotrophic C. zofingiensis were also determined. Car/Chl ratios could be estimated by the ratios of MFI (FL1/FL3, FL2/FL3). FCM is thus a highly efficient and feasible method for rapid estimation of astaxanthin content in the green microalga C. zofingiensis. The rapid FCM method is complementary to the current HPLC method, especially for rapid evaluation and prediction of astaxanthin formation as it is required during the high-throughput culture in the laboratory and mass cultivation in industry. PMID:28753934

Cupping artifact correction and automated classification for high-resolution dedicated breast CT images.

PubMed

Yang, Xiaofeng; Wu, Shengyong; Sechopoulos, Ioannis; Fei, Baowei

2012-10-01

To develop and test an automated algorithm to classify the different tissues present in dedicated breast CT images. The original CT images are first corrected to overcome cupping artifacts, and then a multiscale bilateral filter is used to reduce noise while keeping edge information on the images. As skin and glandular tissues have similar CT values on breast CT images, morphologic processing is used to identify the skin mask based on its position information. A modified fuzzy C-means (FCM) classification method is then used to classify breast tissue as fat and glandular tissue. By combining the results of the skin mask with the FCM, the breast tissue is classified as skin, fat, and glandular tissue. To evaluate the authors' classification method, the authors use Dice overlap ratios to compare the results of the automated classification to those obtained by manual segmentation on eight patient images. The correction method was able to correct the cupping artifacts and improve the quality of the breast CT images. For glandular tissue, the overlap ratios between the authors' automatic classification and manual segmentation were 91.6% ± 2.0%. A cupping artifact correction method and an automatic classification method were applied and evaluated for high-resolution dedicated breast CT images. Breast tissue classification can provide quantitative measurements regarding breast composition, density, and tissue distribution.

Cupping artifact correction and automated classification for high-resolution dedicated breast CT images

PubMed Central

Yang, Xiaofeng; Wu, Shengyong; Sechopoulos, Ioannis; Fei, Baowei

2012-01-01

Purpose: To develop and test an automated algorithm to classify the different tissues present in dedicated breast CT images. Methods: The original CT images are first corrected to overcome cupping artifacts, and then a multiscale bilateral filter is used to reduce noise while keeping edge information on the images. As skin and glandular tissues have similar CT values on breast CT images, morphologic processing is used to identify the skin mask based on its position information. A modified fuzzy C-means (FCM) classification method is then used to classify breast tissue as fat and glandular tissue. By combining the results of the skin mask with the FCM, the breast tissue is classified as skin, fat, and glandular tissue. To evaluate the authors’ classification method, the authors use Dice overlap ratios to compare the results of the automated classification to those obtained by manual segmentation on eight patient images. Results: The correction method was able to correct the cupping artifacts and improve the quality of the breast CT images. For glandular tissue, the overlap ratios between the authors’ automatic classification and manual segmentation were 91.6% ± 2.0%. Conclusions: A cupping artifact correction method and an automatic classification method were applied and evaluated for high-resolution dedicated breast CT images. Breast tissue classification can provide quantitative measurements regarding breast composition, density, and tissue distribution. PMID:23039675

Classification of posture maintenance data with fuzzy clustering algorithms

NASA Technical Reports Server (NTRS)

Bezdek, James C.

1992-01-01

Sensory inputs from the visual, vestibular, and proprioreceptive systems are integrated by the central nervous system to maintain postural equilibrium. Sustained exposure to microgravity causes neurosensory adaptation during spaceflight, which results in decreased postural stability until readaptation occurs upon return to the terrestrial environment. Data which simulate sensory inputs under various sensory organization test (SOT) conditions were collected in conjunction with Johnson Space Center postural control studies using a tilt-translation device (TTD). The University of West Florida applied the fuzzy c-meams (FCM) clustering algorithms to this data with a view towards identifying various states and stages of subjects experiencing such changes. Feature analysis, time step analysis, pooling data, response of the subjects, and the algorithms used are discussed.

A multicolour flow cytometric assay for c-MYC protein in B-cell lymphoma.

PubMed

Alayed, Khaled; Schweitzer, Karen; Awadallah, Amad; Shetty, Shashirekha; Turakhia, Samir; Meyerson, Howard

2018-05-16

Develop an objective assay to detect c-MYC protein expression using multiparametric flow cytometry (FCM) as an alternative to immunohistochemistry (IHC). 57 patient samples and 11 cell line samples were evaluated. Cell suspensions were obtained and c-MYC staining was performed in combination with CD45 and CD19 and, in some samples, CD10. The percentage of c-MYC+ cells by FCM was correlated with the percentage determined by IHC. The relationship between c-MYC protein expression and the presence of a c-MYC gene rearrangement in aggressive and high-grade lymphomas was also assessed. c-MYC expression by FCM and IHC demonstrated a high degree of correlation in a training set of 33 patient cases, r=0.92, 11 cell line samples, r=0.81 and in a validation set of 24 aggressive and high-grade B-cell lymphomas, r=0.85. c-MYC gene was rearranged by fluorescence in situ hybridisation in 6/9 samples with high c-MYC expression (>40%) by FCM and 6/14 by IHC. We have developed a reliable multicolour FCM assay to detect c-MYC expression suitable for clinical laboratories that should be helpful to accurately quantify c-MYC expression in B-cell lymphomas. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Comparison of BALB/c and CBA/J mice for the local lymph node assay using bromodeoxyuridine with flow cytometry (LLNA: BrdU-FCM).

PubMed

Lee, Yong Sun; Yi, Jung-Sun; Seo, Souk Jin; Kim, Joo Hwan; Jung, Mi-Sook; Seo, Im-Kwon; Ahn, Ilyoung; Ko, Kyungyuk; Kim, Tae Sung; Lim, Kyung Min; Sohn, Soojung

2017-02-01

The local lymph node assay using 5-bromo-2-deoxyuridine (BrdU) with flow cytometry (LLNA: BrdU-FCM) is a modified LLNA that is used to identify skin sensitizers by counting BrdU-incorporated lymph node cells (LNCs) with flow cytometry. Unlike other LLNA methods (OECD TG 429, 442A and 442B) in which the CBA/J mouse strain is used, LLNA: BrdU-FCM was originally designed to be compatible with BALB/c, a mouse strain that is more widely used in many countries. To justify the substitution of CBA/J for BALB/c, the equivalence of the test results between two strains shall be established prior to the official implementation of LLNA: BrdU-FCM. This study aims to compare the test results of LLNA: BrdU-FCM produced in BALB/c mice with those in CBA/J mice for 18 reference substances, including 13 sensitizers and 5 non-sensitizers, listed in OECD Test Guideline 429. Based on the LLNA: BrdU-FCM test procedure, we selected an appropriate solvent and then performed preliminary tests to determine the non-irritating dose ranges for the main study, which revealed the difference in the irritation responses to 8 of the 18 chemicals between the two strains. In the main study, we measured the changes in the number of total LNCs, which indicated differences in the responses to test chemicals between the two strains. However, the stimulation index obtained with the counts of BrdU-incorporated LNCs with 7-AAD using flow cytometry yielded comparable results and 100% concordance between the BALB/c and CBA/J mouse strains was achieved, suggesting that the performance of LLNA: BrdU-FCM using BALB/c mice was equivalent to that with CBA/J mice. Copyright © 2016 Elsevier Inc. All rights reserved.

The evaluation of correction algorithms of intensity nonuniformity in breast MRI images: a phantom study

NASA Astrophysics Data System (ADS)

Borys, Damian; Serafin, Wojciech; Gorczewski, Kamil; Kijonka, Marek; Frackiewicz, Mariusz; Palus, Henryk

2018-04-01

The aim of this work was to test the most popular and essential algorithms of the intensity nonuniformity correction of the breast MRI imaging. In this type of MRI imaging, especially in the proximity of the coil, the signal is strong but also can produce some inhomogeneities. Evaluated methods of signal correction were: N3, N3FCM, N4, Nonparametric, and SPM. For testing purposes, a uniform phantom object was used to obtain test images using breast imaging MRI coil. To quantify the results, two measures were used: integral uniformity and standard deviation. For each algorithm minimum, average and maximum values of both evaluation factors have been calculated using the binary mask created for the phantom. In the result, two methods obtained the lowest values in these measures: N3FCM and N4, however, for the second method visually phantom was the most uniform after correction.

Research on a pulmonary nodule segmentation method combining fast self-adaptive FCM and classification.

PubMed

Liu, Hui; Zhang, Cai-Ming; Su, Zhi-Yuan; Wang, Kai; Deng, Kai

2015-01-01

The key problem of computer-aided diagnosis (CAD) of lung cancer is to segment pathologically changed tissues fast and accurately. As pulmonary nodules are potential manifestation of lung cancer, we propose a fast and self-adaptive pulmonary nodules segmentation method based on a combination of FCM clustering and classification learning. The enhanced spatial function considers contributions to fuzzy membership from both the grayscale similarity between central pixels and single neighboring pixels and the spatial similarity between central pixels and neighborhood and improves effectively the convergence rate and self-adaptivity of the algorithm. Experimental results show that the proposed method can achieve more accurate segmentation of vascular adhesion, pleural adhesion, and ground glass opacity (GGO) pulmonary nodules than other typical algorithms.

A dynamic multi-scale Markov model based methodology for remaining life prediction

NASA Astrophysics Data System (ADS)

Yan, Jihong; Guo, Chaozhong; Wang, Xing

2011-05-01

The ability to accurately predict the remaining life of partially degraded components is crucial in prognostics. In this paper, a performance degradation index is designed using multi-feature fusion techniques to represent deterioration severities of facilities. Based on this indicator, an improved Markov model is proposed for remaining life prediction. Fuzzy C-Means (FCM) algorithm is employed to perform state division for Markov model in order to avoid the uncertainty of state division caused by the hard division approach. Considering the influence of both historical and real time data, a dynamic prediction method is introduced into Markov model by a weighted coefficient. Multi-scale theory is employed to solve the state division problem of multi-sample prediction. Consequently, a dynamic multi-scale Markov model is constructed. An experiment is designed based on a Bently-RK4 rotor testbed to validate the dynamic multi-scale Markov model, experimental results illustrate the effectiveness of the methodology.

Effect of Ferric Carboxymaltose on Exercise Capacity in Patients With Chronic Heart Failure and Iron Deficiency.

PubMed

van Veldhuisen, Dirk J; Ponikowski, Piotr; van der Meer, Peter; Metra, Marco; Böhm, Michael; Doletsky, Artem; Voors, Adriaan A; Macdougall, Iain C; Anker, Stefan D; Roubert, Bernard; Zakin, Lorraine; Cohen-Solal, Alain

2017-10-10

Iron deficiency is common in patients with heart failure (HF) and is associated with reduced exercise capacity and poor outcomes. Whether correction of iron deficiency with (intravenous) ferric carboxymaltose (FCM) affects peak oxygen consumption [peak VO 2 ], an objective measure of exercise intolerance in HF, has not been examined. We studied patients with systolic HF (left ventricular ejection fraction ≤45%) and mild to moderate symptoms despite optimal HF medication. Patients were randomized 1:1 to treatment with FCM for 24 weeks or standard of care. The primary end point was the change in peak VO 2 from baseline to 24 weeks. Secondary end points included the effect on hematinic and cardiac biomarkers, quality of life, and safety. For the primary analysis, patients who died had a value of 0 imputed for 24-week peak VO 2 . Additional sensitivity analyses were performed to determine the impact of imputation of missing peak VO 2 data. A total of 172 patients with HF were studied and received FCM (n=86) or standard of care (control group, n=86). At baseline, the groups were well matched; mean age was 64 years, 75% were male, mean left ventricular ejection fraction was 32%, and peak VO 2 was 13.5 mL/min/kg. FCM significantly increased serum ferritin and transferrin saturation. At 24 weeks, peak VO 2 had decreased in the control group (least square means -1.19±0.389 mL/min/kg) but was maintained on FCM (-0.16±0.387 mL/min/kg; P =0.020 between groups). In a sensitivity analysis, in which missing data were not imputed, peak VO 2 at 24 weeks decreased by -0.63±0.375 mL/min/kg in the control group and by -0.16±0.373 mL/min/kg in the FCM group; P =0.23 between groups). Patients' global assessment and functional class as assessed by the New York Heart Association improved on FCM versus standard of care. Treatment with intravenous FCM in patients with HF and iron deficiency improves iron stores. Although a favorable effect on peak VO 2 was observed on FCM, compared with standard of care in the primary analysis, this effect was highly sensitive to the imputation strategy for peak VO 2 among patients who died. Whether FCM is associated with an improved outcome in these high-risk patients needs further study. URL: http://www.clinicaltrials.gov. Unique identifier: NCT01394562. © 2017 The Authors.

Effect of Ferric Carboxymaltose on Exercise Capacity in Patients With Chronic Heart Failure and Iron Deficiency

PubMed Central

Ponikowski, Piotr; van der Meer, Peter; Metra, Marco; Böhm, Michael; Doletsky, Artem; Voors, Adriaan A.; Macdougall, Iain C.; Anker, Stefan D.; Roubert, Bernard; Zakin, Lorraine; Cohen-Solal, Alain

2017-01-01

Background: Iron deficiency is common in patients with heart failure (HF) and is associated with reduced exercise capacity and poor outcomes. Whether correction of iron deficiency with (intravenous) ferric carboxymaltose (FCM) affects peak oxygen consumption [peak VO2], an objective measure of exercise intolerance in HF, has not been examined. Methods: We studied patients with systolic HF (left ventricular ejection fraction ≤45%) and mild to moderate symptoms despite optimal HF medication. Patients were randomized 1:1 to treatment with FCM for 24 weeks or standard of care. The primary end point was the change in peak VO2 from baseline to 24 weeks. Secondary end points included the effect on hematinic and cardiac biomarkers, quality of life, and safety. For the primary analysis, patients who died had a value of 0 imputed for 24-week peak VO2. Additional sensitivity analyses were performed to determine the impact of imputation of missing peak VO2 data. Results: A total of 172 patients with HF were studied and received FCM (n=86) or standard of care (control group, n=86). At baseline, the groups were well matched; mean age was 64 years, 75% were male, mean left ventricular ejection fraction was 32%, and peak VO2 was 13.5 mL/min/kg. FCM significantly increased serum ferritin and transferrin saturation. At 24 weeks, peak VO2 had decreased in the control group (least square means −1.19±0.389 mL/min/kg) but was maintained on FCM (−0.16±0.387 mL/min/kg; P=0.020 between groups). In a sensitivity analysis, in which missing data were not imputed, peak VO2 at 24 weeks decreased by −0.63±0.375 mL/min/kg in the control group and by −0.16±0.373 mL/min/kg in the FCM group; P=0.23 between groups). Patients’ global assessment and functional class as assessed by the New York Heart Association improved on FCM versus standard of care. Conclusions: Treatment with intravenous FCM in patients with HF and iron deficiency improves iron stores. Although a favorable effect on peak VO2 was observed on FCM, compared with standard of care in the primary analysis, this effect was highly sensitive to the imputation strategy for peak VO2 among patients who died. Whether FCM is associated with an improved outcome in these high-risk patients needs further study. Clinical Trial Registration: URL: http://www.clinicaltrials.gov. Unique identifier: NCT01394562. PMID:28701470

Appearance Constrained Semi-Automatic Segmentation from DCE-MRI is Reproducible and Feasible for Breast Cancer Radiomics: A Feasibility Study.

PubMed

Veeraraghavan, Harini; Dashevsky, Brittany Z; Onishi, Natsuko; Sadinski, Meredith; Morris, Elizabeth; Deasy, Joseph O; Sutton, Elizabeth J

2018-03-19

We present a segmentation approach that combines GrowCut (GC) with cancer-specific multi-parametric Gaussian Mixture Model (GCGMM) to produce accurate and reproducible segmentations. We evaluated GCGMM using a retrospectively collected 75 invasive ductal carcinoma with ERPR+ HER2- (n = 15), triple negative (TN) (n = 9), and ER-HER2+ (n = 57) cancers with variable presentation (mass and non-mass enhancement) and background parenchymal enhancement (mild and marked). Expert delineated manual contours were used to assess the segmentation performance using Dice coefficient (DSC), mean surface distance (mSD), Hausdorff distance, and volume ratio (VR). GCGMM segmentations were significantly more accurate than GrowCut (GC) and fuzzy c-means clustering (FCM). GCGMM's segmentations and the texture features computed from those segmentations were the most reproducible compared with manual delineations and other analyzed segmentation methods. Finally, random forest (RF) classifier trained with leave-one-out cross-validation using features extracted from GCGMM segmentation resulted in the best accuracy for ER-HER2+ vs. ERPR+/TN (GCGMM 0.95, expert 0.95, GC 0.90, FCM 0.92) and for ERPR + HER2- vs. TN (GCGMM 0.92, expert 0.91, GC 0.77, FCM 0.83).

Research on a Pulmonary Nodule Segmentation Method Combining Fast Self-Adaptive FCM and Classification

PubMed Central

Liu, Hui; Zhang, Cai-Ming; Su, Zhi-Yuan; Wang, Kai; Deng, Kai

2015-01-01

The key problem of computer-aided diagnosis (CAD) of lung cancer is to segment pathologically changed tissues fast and accurately. As pulmonary nodules are potential manifestation of lung cancer, we propose a fast and self-adaptive pulmonary nodules segmentation method based on a combination of FCM clustering and classification learning. The enhanced spatial function considers contributions to fuzzy membership from both the grayscale similarity between central pixels and single neighboring pixels and the spatial similarity between central pixels and neighborhood and improves effectively the convergence rate and self-adaptivity of the algorithm. Experimental results show that the proposed method can achieve more accurate segmentation of vascular adhesion, pleural adhesion, and ground glass opacity (GGO) pulmonary nodules than other typical algorithms. PMID:25945120

Detecting brain tumor in computed tomography images using Markov random fields and fuzzy C-means clustering techniques

NASA Astrophysics Data System (ADS)

Abdulbaqi, Hayder Saad; Jafri, Mohd Zubir Mat; Omar, Ahmad Fairuz; Mustafa, Iskandar Shahrim Bin; Abood, Loay Kadom

2015-04-01

Brain tumors, are an abnormal growth of tissues in the brain. They may arise in people of any age. They must be detected early, diagnosed accurately, monitored carefully, and treated effectively in order to optimize patient outcomes regarding both survival and quality of life. Manual segmentation of brain tumors from CT scan images is a challenging and time consuming task. Size and location accurate detection of brain tumor plays a vital role in the successful diagnosis and treatment of tumors. Brain tumor detection is considered a challenging mission in medical image processing. The aim of this paper is to introduce a scheme for tumor detection in CT scan images using two different techniques Hidden Markov Random Fields (HMRF) and Fuzzy C-means (FCM). The proposed method has been developed in this research in order to construct hybrid method between (HMRF) and threshold. These methods have been applied on 4 different patient data sets. The result of comparison among these methods shows that the proposed method gives good results for brain tissue detection, and is more robust and effective compared with (FCM) techniques.

Development of a flow cytometric method to analyze subpopulations of bacteria in probiotic products and dairy starters.

PubMed

Bunthof, Christine J; Abee, Tjakko

2002-06-01

Flow cytometry (FCM) is a rapid and sensitive technique that can determine cell numbers and measure various physiological characteristics of individual cells by using appropriate fluorescent probes. Previously, we developed an FCM assay with the viability probes carboxyfluorescein diacetate (cFDA) and TOTO-1 [1'-(4,4,7,7-tetramethyl-4,7-diazaundecamethylene)-bis-4-[3-methyl-2,3dihydro(benzo-1,3-oxazole)-2-methylidene]-1-(3'-trimethylammoniumpropyl)-pyridinium tetraiodide] for (stressed) lactic acid bacteria (C. J. Bunthof, K. Bloemen, P. Breeuwer, F. M. Rombouts, and T. Abee, Appl. Environ. Microbiol. 67:2326-2335, 2001). cFDA stains intact cells with enzymatic activity, and TOTO-1 stains membrane-permeabilized cells. Here we used this assay to study the viability of bacterial suspensions in milk, dairy fermentation starters, and probiotic products. To facilitate FCM analysis of bacteria in milk, a commercially available milk-clearing solution was used. The procedure was optimized to increase the signal-to-noise ratio. FCM enumerations were accurate down to a concentration of 10(5) cells ml(-1). The level of retrieval of Lactobacillus plantarum WCFS 1 suspended in milk was high, and viability was not affected by the procedure. The plate counts for cleared samples of untreated cell suspensions were nearly as high as the total FCM counts, and the correlation was strong (r > 0.99). In dairy fermentation starters and in probiotic products the FCM total cell counts were substantially higher than the numbers of CFU. Three functional populations could be distinguished: culturable cells, cells that are intact and metabolically active but not culturable, and permeabilized cells. The proportions of the populations differed in the products tested. This FCM method provides tools to assess the functionality of different populations in fermentation starters and probiotic products.

Development of a Flow Cytometric Method To Analyze Subpopulations of Bacteria in Probiotic Products and Dairy Starters

PubMed Central

Bunthof, Christine J.; Abee, Tjakko

2002-01-01

Flow cytometry (FCM) is a rapid and sensitive technique that can determine cell numbers and measure various physiological characteristics of individual cells by using appropriate fluorescent probes. Previously, we developed an FCM assay with the viability probes carboxyfluorescein diacetate (cFDA) and TOTO-1 {1′-(4,4,7,7-tetramethyl-4,7-diazaundecamethylene)-bis-4-[3-methyl-2,3dihydro(benzo-1,3-oxazole)-2-methylidene]-1-(3′-trimethylammoniumpropyl)-pyridinium tetraiodide} for (stressed) lactic acid bacteria (C. J. Bunthof, K. Bloemen, P. Breeuwer, F. M. Rombouts, and T. Abee, Appl. Environ. Microbiol. 67:2326-2335, 2001). cFDA stains intact cells with enzymatic activity, and TOTO-1 stains membrane-permeabilized cells. Here we used this assay to study the viability of bacterial suspensions in milk, dairy fermentation starters, and probiotic products. To facilitate FCM analysis of bacteria in milk, a commercially available milk-clearing solution was used. The procedure was optimized to increase the signal-to-noise ratio. FCM enumerations were accurate down to a concentration of 105 cells ml−1. The level of retrieval of Lactobacillus plantarum WCFS 1 suspended in milk was high, and viability was not affected by the procedure. The plate counts for cleared samples of untreated cell suspensions were nearly as high as the total FCM counts, and the correlation was strong (r > 0.99). In dairy fermentation starters and in probiotic products the FCM total cell counts were substantially higher than the numbers of CFU. Three functional populations could be distinguished: culturable cells, cells that are intact and metabolically active but not culturable, and permeabilized cells. The proportions of the populations differed in the products tested. This FCM method provides tools to assess the functionality of different populations in fermentation starters and probiotic products. PMID:12039752

Estimation of breast percent density in raw and processed full field digital mammography images via adaptive fuzzy c-means clustering and support vector machine segmentation

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

Keller, Brad M.; Nathan, Diane L.; Wang Yan

Purpose: The amount of fibroglandular tissue content in the breast as estimated mammographically, commonly referred to as breast percent density (PD%), is one of the most significant risk factors for developing breast cancer. Approaches to quantify breast density commonly focus on either semiautomated methods or visual assessment, both of which are highly subjective. Furthermore, most studies published to date investigating computer-aided assessment of breast PD% have been performed using digitized screen-film mammograms, while digital mammography is increasingly replacing screen-film mammography in breast cancer screening protocols. Digital mammography imaging generates two types of images for analysis, raw (i.e., 'FOR PROCESSING') andmore » vendor postprocessed (i.e., 'FOR PRESENTATION'), of which postprocessed images are commonly used in clinical practice. Development of an algorithm which effectively estimates breast PD% in both raw and postprocessed digital mammography images would be beneficial in terms of direct clinical application and retrospective analysis. Methods: This work proposes a new algorithm for fully automated quantification of breast PD% based on adaptive multiclass fuzzy c-means (FCM) clustering and support vector machine (SVM) classification, optimized for the imaging characteristics of both raw and processed digital mammography images as well as for individual patient and image characteristics. Our algorithm first delineates the breast region within the mammogram via an automated thresholding scheme to identify background air followed by a straight line Hough transform to extract the pectoral muscle region. The algorithm then applies adaptive FCM clustering based on an optimal number of clusters derived from image properties of the specific mammogram to subdivide the breast into regions of similar gray-level intensity. Finally, a SVM classifier is trained to identify which clusters within the breast tissue are likely fibroglandular, which are then aggregated into a final dense tissue segmentation that is used to compute breast PD%. Our method is validated on a group of 81 women for whom bilateral, mediolateral oblique, raw and processed screening digital mammograms were available, and agreement is assessed with both continuous and categorical density estimates made by a trained breast-imaging radiologist. Results: Strong association between algorithm-estimated and radiologist-provided breast PD% was detected for both raw (r= 0.82, p < 0.001) and processed (r= 0.85, p < 0.001) digital mammograms on a per-breast basis. Stronger agreement was found when overall breast density was assessed on a per-woman basis for both raw (r= 0.85, p < 0.001) and processed (0.89, p < 0.001) mammograms. Strong agreement between categorical density estimates was also seen (weighted Cohen's {kappa}{>=} 0.79). Repeated measures analysis of variance demonstrated no statistically significant differences between the PD% estimates (p > 0.1) due to either presentation of the image (raw vs processed) or method of PD% assessment (radiologist vs algorithm). Conclusions: The proposed fully automated algorithm was successful in estimating breast percent density from both raw and processed digital mammographic images. Accurate assessment of a woman's breast density is critical in order for the estimate to be incorporated into risk assessment models. These results show promise for the clinical application of the algorithm in quantifying breast density in a repeatable manner, both at time of imaging as well as in retrospective studies.« less

Estimation of breast percent density in raw and processed full field digital mammography images via adaptive fuzzy c-means clustering and support vector machine segmentation

PubMed Central

Keller, Brad M.; Nathan, Diane L.; Wang, Yan; Zheng, Yuanjie; Gee, James C.; Conant, Emily F.; Kontos, Despina

2012-01-01

Purpose: The amount of fibroglandular tissue content in the breast as estimated mammographically, commonly referred to as breast percent density (PD%), is one of the most significant risk factors for developing breast cancer. Approaches to quantify breast density commonly focus on either semiautomated methods or visual assessment, both of which are highly subjective. Furthermore, most studies published to date investigating computer-aided assessment of breast PD% have been performed using digitized screen-film mammograms, while digital mammography is increasingly replacing screen-film mammography in breast cancer screening protocols. Digital mammography imaging generates two types of images for analysis, raw (i.e., “FOR PROCESSING”) and vendor postprocessed (i.e., “FOR PRESENTATION”), of which postprocessed images are commonly used in clinical practice. Development of an algorithm which effectively estimates breast PD% in both raw and postprocessed digital mammography images would be beneficial in terms of direct clinical application and retrospective analysis. Methods: This work proposes a new algorithm for fully automated quantification of breast PD% based on adaptive multiclass fuzzy c-means (FCM) clustering and support vector machine (SVM) classification, optimized for the imaging characteristics of both raw and processed digital mammography images as well as for individual patient and image characteristics. Our algorithm first delineates the breast region within the mammogram via an automated thresholding scheme to identify background air followed by a straight line Hough transform to extract the pectoral muscle region. The algorithm then applies adaptive FCM clustering based on an optimal number of clusters derived from image properties of the specific mammogram to subdivide the breast into regions of similar gray-level intensity. Finally, a SVM classifier is trained to identify which clusters within the breast tissue are likely fibroglandular, which are then aggregated into a final dense tissue segmentation that is used to compute breast PD%. Our method is validated on a group of 81 women for whom bilateral, mediolateral oblique, raw and processed screening digital mammograms were available, and agreement is assessed with both continuous and categorical density estimates made by a trained breast-imaging radiologist. Results: Strong association between algorithm-estimated and radiologist-provided breast PD% was detected for both raw (r = 0.82, p < 0.001) and processed (r = 0.85, p < 0.001) digital mammograms on a per-breast basis. Stronger agreement was found when overall breast density was assessed on a per-woman basis for both raw (r = 0.85, p < 0.001) and processed (0.89, p < 0.001) mammograms. Strong agreement between categorical density estimates was also seen (weighted Cohen's κ ≥ 0.79). Repeated measures analysis of variance demonstrated no statistically significant differences between the PD% estimates (p > 0.1) due to either presentation of the image (raw vs processed) or method of PD% assessment (radiologist vs algorithm). Conclusions: The proposed fully automated algorithm was successful in estimating breast percent density from both raw and processed digital mammographic images. Accurate assessment of a woman's breast density is critical in order for the estimate to be incorporated into risk assessment models. These results show promise for the clinical application of the algorithm in quantifying breast density in a repeatable manner, both at time of imaging as well as in retrospective studies. PMID:22894417

Estimation of breast percent density in raw and processed full field digital mammography images via adaptive fuzzy c-means clustering and support vector machine segmentation.

PubMed

Keller, Brad M; Nathan, Diane L; Wang, Yan; Zheng, Yuanjie; Gee, James C; Conant, Emily F; Kontos, Despina

2012-08-01

The amount of fibroglandular tissue content in the breast as estimated mammographically, commonly referred to as breast percent density (PD%), is one of the most significant risk factors for developing breast cancer. Approaches to quantify breast density commonly focus on either semiautomated methods or visual assessment, both of which are highly subjective. Furthermore, most studies published to date investigating computer-aided assessment of breast PD% have been performed using digitized screen-film mammograms, while digital mammography is increasingly replacing screen-film mammography in breast cancer screening protocols. Digital mammography imaging generates two types of images for analysis, raw (i.e., "FOR PROCESSING") and vendor postprocessed (i.e., "FOR PRESENTATION"), of which postprocessed images are commonly used in clinical practice. Development of an algorithm which effectively estimates breast PD% in both raw and postprocessed digital mammography images would be beneficial in terms of direct clinical application and retrospective analysis. This work proposes a new algorithm for fully automated quantification of breast PD% based on adaptive multiclass fuzzy c-means (FCM) clustering and support vector machine (SVM) classification, optimized for the imaging characteristics of both raw and processed digital mammography images as well as for individual patient and image characteristics. Our algorithm first delineates the breast region within the mammogram via an automated thresholding scheme to identify background air followed by a straight line Hough transform to extract the pectoral muscle region. The algorithm then applies adaptive FCM clustering based on an optimal number of clusters derived from image properties of the specific mammogram to subdivide the breast into regions of similar gray-level intensity. Finally, a SVM classifier is trained to identify which clusters within the breast tissue are likely fibroglandular, which are then aggregated into a final dense tissue segmentation that is used to compute breast PD%. Our method is validated on a group of 81 women for whom bilateral, mediolateral oblique, raw and processed screening digital mammograms were available, and agreement is assessed with both continuous and categorical density estimates made by a trained breast-imaging radiologist. Strong association between algorithm-estimated and radiologist-provided breast PD% was detected for both raw (r = 0.82, p < 0.001) and processed (r = 0.85, p < 0.001) digital mammograms on a per-breast basis. Stronger agreement was found when overall breast density was assessed on a per-woman basis for both raw (r = 0.85, p < 0.001) and processed (0.89, p < 0.001) mammograms. Strong agreement between categorical density estimates was also seen (weighted Cohen's κ ≥ 0.79). Repeated measures analysis of variance demonstrated no statistically significant differences between the PD% estimates (p > 0.1) due to either presentation of the image (raw vs processed) or method of PD% assessment (radiologist vs algorithm). The proposed fully automated algorithm was successful in estimating breast percent density from both raw and processed digital mammographic images. Accurate assessment of a woman's breast density is critical in order for the estimate to be incorporated into risk assessment models. These results show promise for the clinical application of the algorithm in quantifying breast density in a repeatable manner, both at time of imaging as well as in retrospective studies.

Ferric carboxymaltose-induced hypophosphataemia after kidney transplantation.

PubMed

Sari, V; Atiqi, R; Hoorn, E J; Heijboer, A C; van Gelder, T; Hesselink, D A

2017-03-01

Ferric carboxymaltose (FCM) can induce hypophosphataemia in the general population and patients with chronic kidney disease (CKD). Less is known about the effect of FCM in the kidney transplant population. It has been suggested that fibroblast growth factor 23 (FGF-23)-mediated renal phosphate wasting may be the most likely cause of this phenomenon. In the current study, the effects of FCM on phosphate metabolism were studied in a cohort of kidney transplant recipients. Two index patients receiving FCM are described. Additionally, data of 23 kidney transplant recipients who received a single dose of FCM intravenously between 1 January 2014 and 1 July 2015 were collected. Changes in the serum phosphate concentration were analysed in all subjects. Change in plasma FGF-23 concentrations was analysed in the index patients. In the two index patients an increase in FGF-23 and a decrease in phosphate concentrations were observed after FCM administration. In the 23 kidney transplant patients, median estimated glomerular filtration rate was 42 ml/min/1.73 m2 ( range 10-90 ml/ min/1.73 m2). Mean phosphate concentration before and after FCM administration was 1.05 ±; 0.35 mmol/l and 0.78 ±; 0.41 mmol/l, respectively (average decrease of 0.27 mmol/l; p = 0.003). In the total population, 13 (56.5%) patients showed a transient decline in phosphate concentration after FCM administration. Hypophosphataemia following FCM administration was severe (i.e. < 0.5 mmol/l) in 8 (34.8%) patients. Administration of a single dose of FCM may induce transient and mostly asymptomatic renal phosphate wasting and hypophosphataemia in kidney transplant recipients. This appears to be explained by an increase in FGF-23 concentration.

Comparison of quantitative flow cytometric data provided by panels with lower and increased color number

NASA Astrophysics Data System (ADS)

Bocsi, József; Mittag, Anja; Pierzchalski, Arkadiusz; Baumgartner, Adolf; Dähnert, Ingo; Tárnok, Attila

2012-03-01

To date the flow cytometry (FCM) industry is booming with new generations of commercial clinical instruments. Long-term clinical studies have the dilemma that moving to new instruments being capable of more complex cell-analysis makes it difficult to compare new data with those obtained on older instruments with less complex analysis panels. Since 15 years we conduct follow-up studies on children with congenital heart diseases. In this period we moved from 2- to 3- and now to 10-color FCM immunophenotyping panels. Questions arise how to compare and transfer data from lower to higher level of complexity. Two comparable antibody panels for leukocyte immunophenotyping (12-tube 2-colors, and 9-tube 4-colors) were measured on a BD FACScalibur FCM (calibration: Spherotech beads) in 19 blood samples from children with congenital heart disease. This increase of colors was accompanied by moving antibodies that were in the 2-color panel either FITC or PE labeled to red dyes such as PerCP or APC. Algorithms were developed for bridging data for quantitative characterization of antigen expression (mean fluorescence intensity) and frequency of different cell subpopulations in combination with rainbow bead standard data. This approach worked for the most relevant antibodies (CD3, CD4, CD8 etc.) well, but rendered substantial uncertainty for activation markers (CD69 etc.). Our techniques are particularly well suited to the analysis in long-term studies and have the potential to compare older and recent results in a standardized way.

Faecal cortisol metabolites in Bengal (Panthera tigris tigris) and Sumatran tigers (Panthera tigris sumatrae).

PubMed

Narayan, Edward J; Parnell, Tempe; Clark, Giles; Martin-Vegue, Patrick; Mucci, Al; Hero, Jean-Marc

2013-12-01

The tiger (Panthera tigris) faces a great risk of extinction as its wild numbers have plummeted due to poaching and habitat destruction so ex-situ conservation programs are becoming ever more necessary. Reliable non-invasive biomarkers of the stress hormone (cortisol) are necessary for assessing the health and welfare of tigers in captivity. To our knowledge, non-invasive stress endocrinology methods have not been tested as widely in tigers. The first aim of this study was to describe and validate a faecal cortisol metabolite enzyme-immmunoassay (FCM EIA) for two tiger sub-species, the Bengal tiger (Panthera tigris tigris) and the Sumatran tiger (Panthera tigris sumatrae). Individual tigers (n=22) were studied in two large Zoos in Queensland, Australia (Dreamworld Theme Park and Australia Zoo). Fresh faecal samples (<12 h old) were collected each morning from both Zoos over a study period of 21 days. Biological validation was conducted separately by collecting feces 5 days before and 5 days after blood was taken from four male and five female tigers. Results showed that mean FCM levels increased by 138% and 285% in the male and female tigers within 1 day after bloods were taken, returning to baseline in 5 days. Laboratory validations of the FCM EIA were done using an extraction efficiency test and parallelism. Results showed >89% recovery of the cortisol standard that was added to tiger faecal extract. We also obtained parallel displacement of the serially diluted cortisol standard against serially diluted tiger faecal extract. Our second aim was to determine whether the FCM levels were significantly different between tiger sub-species and sex. Results showed no significant difference in mean FCM levels between the Bengal and Sumatran tiger sub-species. Mean levels of FCMs were significantly higher in females than in male tigers. Those male and female tigers with reported health issues during the study period expressed higher FCM levels than the reportedly healthy tigers. Interestingly, those tigers that took part in some activity (such as walks, photos, presentations and guest feeds) expressed moderately higher FCM levels at Dreamworld and lower FCM levels at Australia Zoo in comparison to those tigers that did not take part in such activities. These results indicate potential habituation in some tigers for routine activity through specialized training and pre-conditioning. In conclusion, the FCM EIA described in this study provides a reliable non-invasive method for evaluating the stress status of tigers in Zoos. Copyright © 2013 Elsevier Inc. All rights reserved.

Impact of pixel-based machine-learning techniques on automated frameworks for delineation of gross tumor volume regions for stereotactic body radiation therapy.

PubMed

Kawata, Yasuo; Arimura, Hidetaka; Ikushima, Koujirou; Jin, Ze; Morita, Kento; Tokunaga, Chiaki; Yabu-Uchi, Hidetake; Shioyama, Yoshiyuki; Sasaki, Tomonari; Honda, Hiroshi; Sasaki, Masayuki

2017-10-01

The aim of this study was to investigate the impact of pixel-based machine learning (ML) techniques, i.e., fuzzy-c-means clustering method (FCM), and the artificial neural network (ANN) and support vector machine (SVM), on an automated framework for delineation of gross tumor volume (GTV) regions of lung cancer for stereotactic body radiation therapy. The morphological and metabolic features for GTV regions, which were determined based on the knowledge of radiation oncologists, were fed on a pixel-by-pixel basis into the respective FCM, ANN, and SVM ML techniques. Then, the ML techniques were incorporated into the automated delineation framework of GTVs followed by an optimum contour selection (OCS) method, which we proposed in a previous study. The three-ML-based frameworks were evaluated for 16 lung cancer cases (six solid, four ground glass opacity (GGO), six part-solid GGO) with the datasets of planning computed tomography (CT) and 18 F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/CT images using the three-dimensional Dice similarity coefficient (DSC). DSC denotes the degree of region similarity between the GTVs contoured by radiation oncologists and those estimated using the automated framework. The FCM-based framework achieved the highest DSCs of 0.79±0.06, whereas DSCs of the ANN-based and SVM-based frameworks were 0.76±0.14 and 0.73±0.14, respectively. The FCM-based framework provided the highest segmentation accuracy and precision without a learning process (lowest calculation cost). Therefore, the FCM-based framework can be useful for delineation of tumor regions in practical treatment planning. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Generation of brain pseudo-CTs using an undersampled, single-acquisition UTE-mDixon pulse sequence and unsupervised clustering

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

Su, Kuan-Hao; Hu, Lingzhi; Traughber, Melanie

Purpose: MR-based pseudo-CT has an important role in MR-based radiation therapy planning and PET attenuation correction. The purpose of this study is to establish a clinically feasible approach, including image acquisition, correction, and CT formation, for pseudo-CT generation of the brain using a single-acquisition, undersampled ultrashort echo time (UTE)-mDixon pulse sequence. Methods: Nine patients were recruited for this study. For each patient, a 190-s, undersampled, single acquisition UTE-mDixon sequence of the brain was acquired (TE = 0.1, 1.5, and 2.8 ms). A novel method of retrospective trajectory correction of the free induction decay (FID) signal was performed based on point-spreadmore » functions of three external MR markers. Two-point Dixon images were reconstructed using the first and second echo data (TE = 1.5 and 2.8 ms). R2{sup ∗} images (1/T2{sup ∗}) were then estimated and were used to provide bone information. Three image features, i.e., Dixon-fat, Dixon-water, and R2{sup ∗}, were used for unsupervised clustering. Five tissue clusters, i.e., air, brain, fat, fluid, and bone, were estimated using the fuzzy c-means (FCM) algorithm. A two-step, automatic tissue-assignment approach was proposed and designed according to the prior information of the given feature space. Pseudo-CTs were generated by a voxelwise linear combination of the membership functions of the FCM. A low-dose CT was acquired for each patient and was used as the gold standard for comparison. Results: The contrast and sharpness of the FID images were improved after trajectory correction was applied. The mean of the estimated trajectory delay was 0.774 μs (max: 1.350 μs; min: 0.180 μs). The FCM-estimated centroids of different tissue types showed a distinguishable pattern for different tissues, and significant differences were found between the centroid locations of different tissue types. Pseudo-CT can provide additional skull detail and has low bias and absolute error of estimated CT numbers of voxels (−22 ± 29 HU and 130 ± 16 HU) when compared to low-dose CT. Conclusions: The MR features generated by the proposed acquisition, correction, and processing methods may provide representative clustering information and could thus be used for clinical pseudo-CT generation.« less

Detecting brain tumor in computed tomography images using Markov random fields and fuzzy C-means clustering techniques

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

Abdulbaqi, Hayder Saad; Department of Physics, College of Education, University of Al-Qadisiya, Al-Qadisiya; Jafri, Mohd Zubir Mat

Brain tumors, are an abnormal growth of tissues in the brain. They may arise in people of any age. They must be detected early, diagnosed accurately, monitored carefully, and treated effectively in order to optimize patient outcomes regarding both survival and quality of life. Manual segmentation of brain tumors from CT scan images is a challenging and time consuming task. Size and location accurate detection of brain tumor plays a vital role in the successful diagnosis and treatment of tumors. Brain tumor detection is considered a challenging mission in medical image processing. The aim of this paper is to introducemore » a scheme for tumor detection in CT scan images using two different techniques Hidden Markov Random Fields (HMRF) and Fuzzy C-means (FCM). The proposed method has been developed in this research in order to construct hybrid method between (HMRF) and threshold. These methods have been applied on 4 different patient data sets. The result of comparison among these methods shows that the proposed method gives good results for brain tissue detection, and is more robust and effective compared with (FCM) techniques.« less

A new approach for automatic matching of ground control points in urban areas from heterogeneous images

NASA Astrophysics Data System (ADS)

Cong, Chao; Liu, Dingsheng; Zhao, Lingjun

2008-12-01

This paper discusses a new method for the automatic matching of ground control points (GCPs) between satellite remote sensing Image and digital raster graphic (DRG) in urban areas. The key of this method is to automatically extract tie point pairs according to geographic characters from such heterogeneous images. Since there are big differences between such heterogeneous images respect to texture and corner features, more detail analyzations are performed to find similarities and differences between high resolution remote sensing Image and (DRG). Furthermore a new algorithms based on the fuzzy-c means (FCM) method is proposed to extract linear feature in remote sensing Image. Based on linear feature, crossings and corners extracted from these features are chosen as GCPs. On the other hand, similar method was used to find same features from DRGs. Finally, Hausdorff Distance was adopted to pick matching GCPs from above two GCP groups. Experiences shown the method can extract GCPs from such images with a reasonable RMS error.

Sensitivity and specificity of univariate MRI analysis of experimentally degraded cartilage

PubMed Central

Lin, Ping-Chang; Reiter, David A.; Spencer, Richard G.

2010-01-01

MRI is increasingly used to evaluate cartilage in tissue constructs, explants, and animal and patient studies. However, while mean values of MR parameters, including T1, T2, magnetization transfer rate km, apparent diffusion coefficient ADC, and the dGEMRIC-derived fixed charge density, correlate with tissue status, the ability to classify tissue according to these parameters has not been explored. Therefore, the sensitivity and specificity with which each of these parameters was able to distinguish between normal and trypsin- degraded, and between normal and collagenase-degraded, cartilage explants were determined. Initial analysis was performed using a training set to determine simple group means to which parameters obtained from a validation set were compared. T1 and ADC showed the greatest ability to discriminate between normal and degraded cartilage. Further analysis with k-means clustering, which eliminates the need for a priori identification of sample status, generally performed comparably. Use of fuzzy c-means (FCM) clustering to define centroids likewise did not result in improvement in discrimination. Finally, a FCM clustering approach in which validation samples were assigned in a probabilistic fashion to control and degraded groups was implemented, reflecting the range of tissue characteristics seen with cartilage degradation. PMID:19705467

Dorsal shaving affects concentrations of faecal cortisol metabolites in lactating golden hamsters

NASA Astrophysics Data System (ADS)

Ohrnberger, Sarah A.; Brinkmann, Katharina; Palme, Rupert; Valencak, Teresa G.

2018-02-01

Breeding of golden hamsters is classically performed at thermal conditions ranging from 20 to 24 °C. However, growing evidence suggests that lactating females suffer from heat stress. We hypothesised that shaving females dorsally to maximise heat dissipation may reduce stress during reproduction. We thus compared faecal cortisol metabolites (FCM) from shaved golden hamster mothers with those from unshaved controls. We observed significantly lower FCM levels in the shaved mothers ( F 1,22 = 8.69, p = 0.0075) pointing to lower stress due to ameliorated heat dissipation over the body surface. In addition, we observed 0.4 °C lower mean subcutaneous body temperatures in the shaved females, although this effect did not reach significance ( F 1,22 = 1.86, p = 0.18). Our results suggest that golden hamsters having body masses being more than four times that of laboratory mice provide a very interesting model to study aspects of lactation and heat production at the same time.

Dorsal shaving affects concentrations of faecal cortisol metabolites in lactating golden hamsters.

PubMed

Ohrnberger, Sarah A; Brinkmann, Katharina; Palme, Rupert; Valencak, Teresa G

2018-01-15

Breeding of golden hamsters is classically performed at thermal conditions ranging from 20 to 24 °C. However, growing evidence suggests that lactating females suffer from heat stress. We hypothesised that shaving females dorsally to maximise heat dissipation may reduce stress during reproduction. We thus compared faecal cortisol metabolites (FCM) from shaved golden hamster mothers with those from unshaved controls. We observed significantly lower FCM levels in the shaved mothers (F 1,22  = 8.69, p = 0.0075) pointing to lower stress due to ameliorated heat dissipation over the body surface. In addition, we observed 0.4 °C lower mean subcutaneous body temperatures in the shaved females, although this effect did not reach significance (F 1,22  = 1.86, p = 0.18). Our results suggest that golden hamsters having body masses being more than four times that of laboratory mice provide a very interesting model to study aspects of lactation and heat production at the same time.

Renal function in patients with non-dialysis chronic kidney disease receiving intravenous ferric carboxymaltose: an analysis of the randomized FIND-CKD trial.

PubMed

Macdougall, Iain C; Bock, Andreas H; Carrera, Fernando; Eckardt, Kai-Uwe; Gaillard, Carlo; Van Wyck, David; Meier, Yvonne; Larroque, Sylvain; Roger, Simon D

2017-01-17

Preclinical studies demonstrate renal proximal tubular injury after administration of some intravenous iron preparations but clinical data on renal effects of intravenous iron are sparse. FIND-CKD was a 56-week, randomized, open-label, multicenter study in which patients with non-dialysis dependent chronic kidney disease (ND-CKD), anemia and iron deficiency without erythropoiesis-stimulating agent therapy received intravenous ferric carboxymaltose (FCM), targeting either higher (400-600 μg/L) or lower (100-200 μg/L) ferritin values, or oral iron. Mean (SD) eGFR at baseline was 34.9 (11.3), 32.8 (10.8) and 34.2 (12.3) mL/min/1.73 m 2 in the high ferritin FCM (n = 97), low ferritin FCM (n = 89) and oral iron (n = 167) groups, respectively. Corresponding values at month 12 were 35.6 (13.8), 32.1 (12.7) and 33.4 (14.5) mL/min/1.73 m 2 . The pre-specified endpoint of mean (SE) change in eGFR from baseline to month 12 was +0.7 (0.9) mL/min/1.73 m 2 with high ferritin FCM (p = 0.15 versus oral iron), -0.9 (0.9) mL/min/1.73 m 2 with low ferritin FCM (p = 0.99 versus oral iron) and -0.9 (0.7) mL/min/1.73 m 2 with oral iron. No significant association was detected between quartiles of FCM dose, change in ferritin or change in TSAT versus change in eGFR. Dialysis initiation was similar between groups. Renal adverse events were rare, with no indication of between-group differences. Intravenous FCM at doses that maintained ferritin levels of 100-200 μg/L or 400-600 μg/L did not negatively impact renal function (eGFR) in patients with ND-CKD over 12 months versus oral iron, and eGFR remained stable. These findings show no evidence of renal toxicity following intravenous FCM over a 1-year period. ClinicalTrials.gov NCT00994318 (first registration 12 October 2009).

Fluorescence Confocal Microscopy for Ex Vivo Diagnosis of Conjunctival Tumors: A Pilot Study.

PubMed

Iovieno, Alfonso; Longo, Caterina; De Luca, Mariacarla; Piana, Simonetta; Fontana, Luigi; Ragazzi, Moira

2016-08-01

To evaluate the potential use of fluorescence confocal microscopy (FCM) for ex vivo diagnosis and excision margin assessment of conjunctival neoplasms. Validity study. setting: Single institution. Consecutive patients with clinically suspicious conjunctival lesions. Conjunctival lesions were excised in toto using a standard "no-touch technique" by a single surgeon (A.I.). Collected specimens were examined with a commercially available laser scanning fluorescence confocal microscope after immersion in a 0.6 mM solution of acridine orange dye for 10-20 seconds. Specimens were subsequently processed with standard histologic analysis. FCM diagnosis of the nature and extension of conjunctival lesions. Sixteen consecutive patients were included in the study (11 male, 5 female; mean age 58.1 ± 26.1 years, range 10-90 years). The median time needed to process and analyze a sample with FCM was 15 minutes. Eleven of 16 lesions were identified by FCM as squamous (2 benign papillomas, 2 grade 2 conjunctival intraepithelial neoplasias, 7 in situ squamous carcinomas) and 5 as nonsquamous (1 pingueculum, 1 dermolipoma, 2 melanocytic nevi, 1 melanoma). In all cases FCM was able to detect horizontal and vertical extension of the lesion. All FCM findings were confirmed by corresponding subsequent histologic examination. FCM provides a fast ex vivo preliminary diagnosis of suspicious conjunctival lesions with good histologic details and margin assessment, and may represent a novel tool for intraoperative and postsurgical management of conjunctival tumors. This is the first study to investigate ex vivo FCM application in ophthalmology. Copyright © 2016 Elsevier Inc. All rights reserved.

The finite cell method for polygonal meshes: poly-FCM

NASA Astrophysics Data System (ADS)

Duczek, Sascha; Gabbert, Ulrich

2016-10-01

In the current article, we extend the two-dimensional version of the finite cell method (FCM), which has so far only been used for structured quadrilateral meshes, to unstructured polygonal discretizations. Therefore, the adaptive quadtree-based numerical integration technique is reformulated and the notion of generalized barycentric coordinates is introduced. We show that the resulting polygonal (poly-)FCM approach retains the optimal rates of convergence if and only if the geometry of the structure is adequately resolved. The main advantage of the proposed method is that it inherits the ability of polygonal finite elements for local mesh refinement and for the construction of transition elements (e.g. conforming quadtree meshes without hanging nodes). These properties along with the performance of the poly-FCM are illustrated by means of several benchmark problems for both static and dynamic cases.

Cost-minimization analysis favours intravenous ferric carboxymaltose over ferric sucrose or oral iron as preoperative treatment in patients with colon cancer and iron deficiency anaemia.

PubMed

Calvet, Xavier; Gené, Emili; ÀngelRuíz, Miquel; Figuerola, Ariadna; Villoria, Albert; Cucala, Mercedes; Mearin, Fermín; Delgado, Salvadora; Calleja, Jose Luis

2016-01-01

Ferric Carboxymaltose (FCM), Iron Sucrose (IS) and Oral Iron (OI) are alternative treatments for preoperative anaemia. To compare the cost implications, using a cost-minimization analysis, of three alternatives: FCM vs. IS vs. OI for treating iron-deficient anaemia before surgery in patients with colon cancer. Data from 282 patients with colorectal cancer and anaemia were obtained from a previous study. One hundred and eleven received FCS, 16 IS and 155 OI. Costs of intravenous iron drugs were obtained from the Spanish Regulatory Agency. Direct and indirect costs were obtained from the analytical accounting unit of the Hospital. In the base case mean costs per patient were calculated. Sensitivity analysis and probabilistic Monte Carlo simulation were performed. Total costs per patient were 1827® in the FCM group, 2312® in the IS group and 2101® in the OI group. Cost savings per patient for FCM treatment were 485® compared to IS and 274® compared to OI. A Monte Carlo simulation favoured the use of FCM in 84.7% and 84.4% of simulations when compared to IS and OI, respectively. FCM infusion before surgery reduced costs in patients with colon cancer and iron-deficiency anaemia when compared with OI and IS.

Comparative safety of intravenous ferumoxytol versus ferric carboxymaltose in iron deficiency anemia: A randomized trial.

PubMed

Adkinson, N Franklin; Strauss, William E; Macdougall, Iain C; Bernard, Kristine E; Auerbach, Michael; Kaper, Robert F; Chertow, Glenn M; Krop, Julie S

2018-05-01

Few trials have examined rates of hypersensitivity reactions (HSRs) with intravenous iron formulations used to treat iron deficiency anemia (IDA). This randomized, multicenter, double-blind clinical trial compared the safety, and efficacy of ferumoxytol versus ferric carboxymaltose (FCM), focusing on rates of HSRs and hypotension as the primary end point. Patients with IDA of any etiology in whom oral iron was unsatisfactory or intolerable received ferumoxytol (n = 997) or FCM (n = 1000) intravenously over ≥15 minutes on days 1 and 8 or 9 for total respective doses of 1.02 g and 1.50 g. Composite incidences of moderate-to-severe HSRs, including anaphylaxis, or moderate-to-severe hypotension from baseline to week 5 (primary safety end point) were 0.6% and 0.7% in the ferumoxytol and FCM groups, respectively, with ferumoxytol noninferior to FCM. No anaphylaxis was reported in either group. The secondary safety end point of incidences of moderate-to-severe HSRs, including anaphylaxis, serious cardiovascular events, and death from baseline to week 5 were 1.3% and 2.0% in the ferumoxytol and FCM groups, respectively (noninferiority test P < .0001). Least-squares mean changes in hemoglobin at week 5 were 1.4 g/dL and 1.6 g/dL in the ferumoxytol and FCM groups, respectively (noninferiority test P < .0001). Incidence of hypophosphatemia was 0.4% for ferumoxytol and 38.7% for FCM. © 2018 The Authors American Journal of Hematology Published by Wiley Periodicals, Inc.

Long Term Uncertainty Investigations of 1 MN Force Calibration Machine at NPL, India (NPLI)

NASA Astrophysics Data System (ADS)

Kumar, Rajesh; Kumar, Harish; Kumar, Anil; Vikram

2012-01-01

The present paper is an attempt to study the long term uncertainty of 1 MN hydraulic multiplication system (HMS) force calibration machine (FCM) at the National Physical Laboratory, India (NPLI), which is used for calibration of the force measuring instruments in the range of 100 kN - 1 MN. The 1 MN HMS FCM was installed at NPLI in 1993 and was built on the principle of hydraulic amplifications of dead weights. The best measurement capability (BMC) of the machine is ± 0.025% (k = 2) and it is traceable to national standards by means of precision force transfer standards (FTS). The present study discusses the uncertainty variations of the 1 MN HMS FCM over the years and describes the other parameters in detail, too. The 1 MN HMS FCM was calibrated in the years 2004, 2006, 2007, 2008, 2009 and 2010 and the results have been reported.

Identification of homogeneous regions for regionalization of watersheds by two-level self-organizing feature maps

NASA Astrophysics Data System (ADS)

Farsadnia, F.; Rostami Kamrood, M.; Moghaddam Nia, A.; Modarres, R.; Bray, M. T.; Han, D.; Sadatinejad, J.

2014-02-01

One of the several methods in estimating flood quantiles in ungauged or data-scarce watersheds is regional frequency analysis. Amongst the approaches to regional frequency analysis, different clustering techniques have been proposed to determine hydrologically homogeneous regions in the literature. Recently, Self-Organization feature Map (SOM), a modern hydroinformatic tool, has been applied in several studies for clustering watersheds. However, further studies are still needed with SOM on the interpretation of SOM output map for identifying hydrologically homogeneous regions. In this study, two-level SOM and three clustering methods (fuzzy c-mean, K-mean, and Ward's Agglomerative hierarchical clustering) are applied in an effort to identify hydrologically homogeneous regions in Mazandaran province watersheds in the north of Iran, and their results are compared with each other. Firstly the SOM is used to form a two-dimensional feature map. Next, the output nodes of the SOM are clustered by using unified distance matrix algorithm and three clustering methods to form regions for flood frequency analysis. The heterogeneity test indicates the four regions achieved by the two-level SOM and Ward approach after adjustments are sufficiently homogeneous. The results suggest that the combination of SOM and Ward is much better than the combination of either SOM and FCM or SOM and K-mean.

Development of a Calibration Strip for Immunochromatographic Assay Detection Systems.

PubMed

Gao, Yue-Ming; Wei, Jian-Chong; Mak, Peng-Un; Vai, Mang-I; Du, Min; Pun, Sio-Hang

2016-06-29

With many benefits and applications, immunochromatographic (ICG) assay detection systems have been reported on a great deal. However, the existing research mainly focuses on increasing the dynamic detection range or application fields. Calibration of the detection system, which has a great influence on the detection accuracy, has not been addressed properly. In this context, this work develops a calibration strip for ICG assay photoelectric detection systems. An image of the test strip is captured by an image acquisition device, followed by performing a fuzzy c-means (FCM) clustering algorithm and maximin-distance algorithm for image segmentation. Additionally, experiments are conducted to find the best characteristic quantity. By analyzing the linear coefficient, an average value of hue (H) at 14 min is chosen as the characteristic quantity and the empirical formula between H and optical density (OD) value is established. Therefore, H, saturation (S), and value (V) are calculated by a number of selected OD values. Then, H, S, and V values are transferred to the RGB color space and a high-resolution printer is used to print the strip images on cellulose nitrate membranes. Finally, verification of the printed calibration strips is conducted by analyzing the linear correlation between OD and the spectral reflectance, which shows a good linear correlation (R² = 98.78%).

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

Kuo, J; Su, K; Department of Radiology, University Hospitals Case Medical Center, Case Western Reserve University, Cleveland, Ohio

Purpose: Accurate and robust photon attenuation derived from MR is essential for PET/MR and MR-based radiation treatment planning applications. Although the fuzzy C-means (FCM) algorithm has been applied for pseudo-CT generation, the input feature combination and the number of clusters have not been optimized. This study aims to optimize both for clinically practical pseudo-CT generation. Methods: Nine volunteers were recruited. A 190-second, single-acquisition UTE-mDixon with 25% (angular) sampling and 3D radial readout was performed to acquire three primitive MR features at TEs of 0.1, 1.5, and 2.8 ms: the free-induction-decay (FID), the first and the second echo images. Three derivedmore » images, Dixon-fat and Dixon-water generated by two-point Dixon water/fat separation, and R2* (1/T2*) map, were also created. To identify informative inputs for generating a pseudo-CT image volume, all 63 combinations, choosing one to six of the feature images, were used as inputs to FCM for pseudo-CT generation. Further, the number of clusters was varied from four to seven to find the optimal approach. Mean prediction deviation (MPD), mean absolute prediction deviation (MAPD), and correlation coefficient (R) of different combinations were compared for feature selection. Results: Among the 63 feature combinations, the four that resulted in the best MAPD and R were further compared along with the set containing all six features. The results suggested that R2* and Dixon-water are the most informative features. Further, including FID also improved the performance of pseudo-CT generation. Consequently, the set containing FID, Dixon-water, and R2* resulted in the most accurate, robust pseudo-CT when the number of cluster equals to five (5C). The clusters were interpreted as air, fat, bone, brain, and fluid. The six-cluster Result additionally included bone marrow. Conclusion: The results suggested that FID, Dixon-water, R2* are the most important features. The findings can be used to facilitate pseudo-CT generation for unsupervised clustering. Please note that the project was completed with partial funding from the Ohio Department of Development grant TECH 11-063 and a sponsored research agreement with Philips Healthcare that is managed by Case Western Reserve University. As noted in the affiliations, some of the authors are Philips employees.« less

UN TRISO Compaction in SiC for FCM Fuel Irradiations

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

Terrani, Kurt A.; Trammell, Michael P.; Kiggans, James O.

2016-11-01

The U.S. Department of Energy Office of Nuclear Energy (DOE-NE) Advanced Fuels Campaign (AFC) is conducting research and development to elevate the technology readiness level of Fully Ceramic Microencapsulated (FCM) fuels, a candidate nuclear fuel with potentially enhanced accident tolerance due to very high fission product retention. One of the early activities in FY17 was to demonstrate production of FCM pellets with uranium nitride TRISO particles. This was carried out in preparation of the larger pellet production campaign in support of the upcoming irradiation testing of this fuel form at INL’s Advanced Test Reactor.

Production of LEU Fully Ceramic Microencapsulated Fuel for Irradiation Testing

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

Terrani, Kurt A; Kiggans Jr, James O; McMurray, Jake W

2016-01-01

Fully Ceramic Microencapsulated (FCM) fuel consists of tristructural isotropic (TRISO) fuel particles embedded inside a SiC matrix. This fuel inherently possesses multiple barriers to fission product release, namely the various coating layers in the TRISO fuel particle as well as the dense SiC matrix that hosts these particles. This coupled with the excellent oxidation resistance of the SiC matrix and the SiC coating layer in the TRISO particle designate this concept as an accident tolerant fuel (ATF). The FCM fuel takes advantage of uranium nitride kernels instead of oxide or oxide-carbide kernels used in high temperature gas reactors to enhancemore » heavy metal loading in the highly moderated LWRs. Production of these kernels with appropriate density, coating layer development to produce UN TRISO particles, and consolidation of these particles inside a SiC matrix have been codified thanks to significant R&D supported by US DOE Fuel Cycle R&D program. Also, surrogate FCM pellets (pellets with zirconia instead of uranium-bearing kernels) have been neutron irradiated and the stability of the matrix and coating layer under LWR irradiation conditions have been established. Currently the focus is on production of LEU (7.3% U-235 enrichment) FCM pellets to be utilized for irradiation testing. The irradiation is planned at INL s Advanced Test Reactor (ATR). This is a critical step in development of this fuel concept to establish the ability of this fuel to retain fission products under prototypical irradiation conditions.« less

Evaluating ex vivo fluorescence confocal microscopy images of basal cell carcinomas in Mohs excised tissue.

PubMed

Longo, C; Rajadhyaksha, M; Ragazzi, M; Nehal, K; Gardini, S; Moscarella, E; Lallas, A; Zalaudek, I; Piana, S; Argenziano, G; Pellacani, G

2014-09-01

Fluorescence confocal microscopy (FCM) is an emerging technology for rapid imaging of excised tissue, without the need for frozen- or fixed-section processing. Basal cell carcinomas (BCCs) can be detected in Mohs excisions although few studies have described the major BCC findings as seen on FCM. To describe the major BCC findings of excised tissue during Mohs surgery and to correlate them with histopathology. Freshly excised tumours and frozen-thawed discarded tissue of BCC during Mohs surgery were analysed by means of FCM. A side-by-side correlation between FCM images and histological sections was performed. The FCM features of overlying skin and adnexal structures were also described. Sixty-four BCC cases were analysed. Distinct BCC types appeared unique in terms of shape and size of tumour islands [bigger in nodular (18/25), smaller and rounded in micronodular (7/7) and tiny cords for infiltrative ones (24/30)] and for the presence of clefting, palisading and increased nucleus/cytoplasm ratio. An excellent correlation was found between FCM and histological findings (Cohen's κ statistics = 0·9). In six cases, the presence of sebaceous glands and intense stroma reaction represented possible confounders. Fluorescence confocal microscopy is a fast and new imaging technique that allows an excellent visualization of skin structures and BCC findings during Mohs surgery. © 2014 British Association of Dermatologists.

Evaluating physiological stress in Sumatran tigers (Panthera tigris ssp. sumatrae) managed in Australian zoos.

PubMed

Parnell, Tempe; Narayan, Edward J; Magrath, Michael J L; Roe, Sheila; Clark, Giles; Nicolson, Vere; Martin-Vegue, Patrick; Mucci, Al; Hero, Jean-Marc

2014-01-01

Glucocorticoid quantification using non-invasive methods provides a powerful tool for assessing the health and welfare of wildlife in zoo-based programmes. In this study, we provide baseline data on faecal-based glucocorticoid (cortisol) monitoring of Sumatran tigers (Panthera tigris ssp. sumatrae) managed at the Melbourne Zoo in Victoria, Australia. We sampled five tigers daily for 60 days. Faecal cortisol metabolites (FCMs) in tiger faecal extracts were quantified using enzyme immunoassays that were successfully validated using parallelism and accuracy recovery checks. Two female tigers had significantly higher mean FCM levels than the two males and another female, suggesting that females may have higher FCM levels. A significant elevation was noted in the FCM levels for one female 2 days after she was darted and anaesthetized; however, the FCM levels returned to baseline levels within 3 days after the event. Comparative analysis of FCM levels of tigers sampled at Melbourne Zoo with tigers sampled earlier at two other Australian Zoos (Dreamworld Themepark and Australia Zoo) showed that FCM levels varied between zoos. Differences in the enclosure characteristics, timing of sampling, size and composition of groupings and training procedures could all contribute to this variation. Overall, we recommend the use of non-invasive sampling for the assessment of adrenocortical activity of felids managed in zoos in Australia and internationally in order to improve the welfare of these charismatic big cats.

Evaluating physiological stress in Sumatran tigers (Panthera tigris ssp. sumatrae) managed in Australian zoos

PubMed Central

Parnell, Tempe; Narayan, Edward J.; Magrath, Michael J. L.; Roe, Sheila; Clark, Giles; Nicolson, Vere; Martin-Vegue, Patrick; Mucci, Al; Hero, Jean-Marc

2014-01-01

Glucocorticoid quantification using non-invasive methods provides a powerful tool for assessing the health and welfare of wildlife in zoo-based programmes. In this study, we provide baseline data on faecal-based glucocorticoid (cortisol) monitoring of Sumatran tigers (Panthera tigris ssp. sumatrae) managed at the Melbourne Zoo in Victoria, Australia. We sampled five tigers daily for 60 days. Faecal cortisol metabolites (FCMs) in tiger faecal extracts were quantified using enzyme immunoassays that were successfully validated using parallelism and accuracy recovery checks. Two female tigers had significantly higher mean FCM levels than the two males and another female, suggesting that females may have higher FCM levels. A significant elevation was noted in the FCM levels for one female 2 days after she was darted and anaesthetized; however, the FCM levels returned to baseline levels within 3 days after the event. Comparative analysis of FCM levels of tigers sampled at Melbourne Zoo with tigers sampled earlier at two other Australian Zoos (Dreamworld Themepark and Australia Zoo) showed that FCM levels varied between zoos. Differences in the enclosure characteristics, timing of sampling, size and composition of groupings and training procedures could all contribute to this variation. Overall, we recommend the use of non-invasive sampling for the assessment of adrenocortical activity of felids managed in zoos in Australia and internationally in order to improve the welfare of these charismatic big cats. PMID:27293659

Spectral embedding based active contour (SEAC) for lesion segmentation on breast dynamic contrast enhanced magnetic resonance imaging.

PubMed

Agner, Shannon C; Xu, Jun; Madabhushi, Anant

2013-03-01

Segmentation of breast lesions on dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) is the first step in lesion diagnosis in a computer-aided diagnosis framework. Because manual segmentation of such lesions is both time consuming and highly susceptible to human error and issues of reproducibility, an automated lesion segmentation method is highly desirable. Traditional automated image segmentation methods such as boundary-based active contour (AC) models require a strong gradient at the lesion boundary. Even when region-based terms are introduced to an AC model, grayscale image intensities often do not allow for clear definition of foreground and background region statistics. Thus, there is a need to find alternative image representations that might provide (1) strong gradients at the margin of the object of interest (OOI); and (2) larger separation between intensity distributions and region statistics for the foreground and background, which are necessary to halt evolution of the AC model upon reaching the border of the OOI. In this paper, the authors introduce a spectral embedding (SE) based AC (SEAC) for lesion segmentation on breast DCE-MRI. SE, a nonlinear dimensionality reduction scheme, is applied to the DCE time series in a voxelwise fashion to reduce several time point images to a single parametric image where every voxel is characterized by the three dominant eigenvectors. This parametric eigenvector image (PrEIm) representation allows for better capture of image region statistics and stronger gradients for use with a hybrid AC model, which is driven by both boundary and region information. They compare SEAC to ACs that employ fuzzy c-means (FCM) and principal component analysis (PCA) as alternative image representations. Segmentation performance was evaluated by boundary and region metrics as well as comparing lesion classification using morphological features from SEAC, PCA+AC, and FCM+AC. On a cohort of 50 breast DCE-MRI studies, PrEIm yielded overall better region and boundary-based statistics compared to the original DCE-MR image, FCM, and PCA based image representations. Additionally, SEAC outperformed a hybrid AC applied to both PCA and FCM image representations. Mean dice similarity coefficient (DSC) for SEAC was significantly better (DSC = 0.74 ± 0.21) than FCM+AC (DSC = 0.50 ± 0.32) and similar to PCA+AC (DSC = 0.73 ± 0.22). Boundary-based metrics of mean absolute difference and Hausdorff distance followed the same trends. Of the automated segmentation methods, breast lesion classification based on morphologic features derived from SEAC segmentation using a support vector machine classifier also performed better (AUC = 0.67 ± 0.05; p < 0.05) than FCM+AC (AUC = 0.50 ± 0.07), and PCA+AC (AUC = 0.49 ± 0.07). In this work, we presented SEAC, an accurate, general purpose AC segmentation tool that could be applied to any imaging domain that employs time series data. SE allows for projection of time series data into a PrEIm representation so that every voxel is characterized by the dominant eigenvectors, capturing the global and local time-intensity curve similarities in the data. This PrEIm allows for the calculation of strong tensor gradients and better region statistics than the original image intensities or alternative image representations such as PCA and FCM. The PrEIm also allows for building a more accurate hybrid AC scheme.

Remote sensing imagery classification using multi-objective gravitational search algorithm

NASA Astrophysics Data System (ADS)

Zhang, Aizhu; Sun, Genyun; Wang, Zhenjie

2016-10-01

Simultaneous optimization of different validity measures can capture different data characteristics of remote sensing imagery (RSI) and thereby achieving high quality classification results. In this paper, two conflicting cluster validity indices, the Xie-Beni (XB) index and the fuzzy C-means (FCM) (Jm) measure, are integrated with a diversity-enhanced and memory-based multi-objective gravitational search algorithm (DMMOGSA) to present a novel multi-objective optimization based RSI classification method. In this method, the Gabor filter method is firstly implemented to extract texture features of RSI. Then, the texture features are syncretized with the spectral features to construct the spatial-spectral feature space/set of the RSI. Afterwards, cluster of the spectral-spatial feature set is carried out on the basis of the proposed method. To be specific, cluster centers are randomly generated initially. After that, the cluster centers are updated and optimized adaptively by employing the DMMOGSA. Accordingly, a set of non-dominated cluster centers are obtained. Therefore, numbers of image classification results of RSI are produced and users can pick up the most promising one according to their problem requirements. To quantitatively and qualitatively validate the effectiveness of the proposed method, the proposed classification method was applied to classifier two aerial high-resolution remote sensing imageries. The obtained classification results are compared with that produced by two single cluster validity index based and two state-of-the-art multi-objective optimization algorithms based classification results. Comparison results show that the proposed method can achieve more accurate RSI classification.

Elucidation of Seventeen Human Peripheral Blood B cell Subsets and Quantification of the Tetanus Response Using a Density-Based Method for the Automated Identification of Cell Populations in Multidimensional Flow Cytometry Data

PubMed Central

Qian, Yu; Wei, Chungwen; Lee, F. Eun-Hyung; Campbell, John; Halliley, Jessica; Lee, Jamie A.; Cai, Jennifer; Kong, Megan; Sadat, Eva; Thomson, Elizabeth; Dunn, Patrick; Seegmiller, Adam C.; Karandikar, Nitin J.; Tipton, Chris; Mosmann, Tim; Sanz, Iñaki; Scheuermann, Richard H.

2011-01-01

Background Advances in multi-parameter flow cytometry (FCM) now allow for the independent detection of larger numbers of fluorochromes on individual cells, generating data with increasingly higher dimensionality. The increased complexity of these data has made it difficult to identify cell populations from high-dimensional FCM data using traditional manual gating strategies based on single-color or two-color displays. Methods To address this challenge, we developed a novel program, FLOCK (FLOw Clustering without K), that uses a density-based clustering approach to algorithmically identify biologically relevant cell populations from multiple samples in an unbiased fashion, thereby eliminating operator-dependent variability. Results FLOCK was used to objectively identify seventeen distinct B cell subsets in a human peripheral blood sample and to identify and quantify novel plasmablast subsets responding transiently to tetanus and other vaccinations in peripheral blood. FLOCK has been implemented in the publically available Immunology Database and Analysis Portal – ImmPort (http://www.immport.org) for open use by the immunology research community. Conclusions FLOCK is able to identify cell subsets in experiments that use multi-parameter flow cytometry through an objective, automated computational approach. The use of algorithms like FLOCK for FCM data analysis obviates the need for subjective and labor intensive manual gating to identify and quantify cell subsets. Novel populations identified by these computational approaches can serve as hypotheses for further experimental study. PMID:20839340

A budget impact analysis of parenteral iron treatments for iron deficiency anemia in the UK: reduced resource utilization with iron isomaltoside 1000.

PubMed

Pollock, Richard F; Muduma, Gorden

2017-01-01

The reported prevalence of iron deficiency anemia (IDA) varies widely but estimates suggest that 3% of men and 8% of women have IDA in the UK. Parenteral iron is indicated for patients intolerant or unresponsive to oral iron or requiring rapid iron replenishment. This study evaluated differences in the cost of treating these patients with iron isomaltoside (Monofer ® , IIM) relative to other intravenous iron formulations. A budget impact model was developed to evaluate the cost of using IIM relative to ferric carboxymaltose (Ferinject ® , FCM), low molecular weight iron dextran (Cosmofer ® , LMWID), and iron sucrose (Venofer ® , IS) in patients with IDA. To establish iron need, iron deficits were modeled using a simplified dosing table. The base case analysis was conducted over 1 year in patients with IDA with mean bodyweight of 82.4 kg (SD 22.5 kg) and hemoglobin levels of 9.99 g/dL (SD 1.03 g/dL) based on an analysis of patient characteristics in IDA trials. Costs were modeled using UK health care resource groups. Using IIM required 1.3 infusions to correct the mean iron deficit, compared with 1.3, 1.8, and 7.7 with LMWID, FCM, and IS, respectively. Patients using IIM required multiple infusions in 35% of cases, compared with 35%, 77%, and 100% of patients with LMWID, FCM, and IS, respectively. Total costs were estimated to be GBP 451 per patient with IIM or LMWID, relative to GBP 594 with FCM (a GBP 143 or 24% saving with IIM) or GBP 2,600 with IS (a GBP 2,149 or 83% saving with IIM). Using IIM or LMWID in place of FCM or IS resulted in a marked reduction in the number of infusions required to correct iron deficits in patients with IDA. The reduction in infusions was accompanied by substantial reductions in cost relative to FCM and IS over 1 year.

Clustering for unsupervised fault diagnosis in nuclear turbine shut-down transients

NASA Astrophysics Data System (ADS)

Baraldi, Piero; Di Maio, Francesco; Rigamonti, Marco; Zio, Enrico; Seraoui, Redouane

2015-06-01

Empirical methods for fault diagnosis usually entail a process of supervised training based on a set of examples of signal evolutions "labeled" with the corresponding, known classes of fault. However, in practice, the signals collected during plant operation may be, very often, "unlabeled", i.e., the information on the corresponding type of occurred fault is not available. To cope with this practical situation, in this paper we develop a methodology for the identification of transient signals showing similar characteristics, under the conjecture that operational/faulty transient conditions of the same type lead to similar behavior in the measured signals evolution. The methodology is founded on a feature extraction procedure, which feeds a spectral clustering technique, embedding the unsupervised fuzzy C-means (FCM) algorithm, which evaluates the functional similarity among the different operational/faulty transients. A procedure for validating the plausibility of the obtained clusters is also propounded based on physical considerations. The methodology is applied to a real industrial case, on the basis of 148 shut-down transients of a Nuclear Power Plant (NPP) steam turbine.

An interactive method based on the live wire for segmentation of the breast in mammography images.

PubMed

Zewei, Zhang; Tianyue, Wang; Li, Guo; Tingting, Wang; Lu, Xu

2014-01-01

In order to improve accuracy of computer-aided diagnosis of breast lumps, the authors introduce an improved interactive segmentation method based on Live Wire. This paper presents the Gabor filters and FCM clustering algorithm is introduced to the Live Wire cost function definition. According to the image FCM analysis for image edge enhancement, we eliminate the interference of weak edge and access external features clear segmentation results of breast lumps through improving Live Wire on two cases of breast segmentation data. Compared with the traditional method of image segmentation, experimental results show that the method achieves more accurate segmentation of breast lumps and provides more accurate objective basis on quantitative and qualitative analysis of breast lumps.

Properties of human blood monocytes. I. CD91 expression and log orthogonal light scatter provide a robust method to identify monocytes that is more accurate than CD14 expression.

PubMed

Hudig, Dorothy; Hunter, Kenneth W; Diamond, W John; Redelman, Doug

2014-03-01

This study was designed to improve identification of human blood monocytes by using antibodies to molecules that occur consistently on all stages of monocyte development and differentiation. We examined blood samples from 200 healthy adults without clinically diagnosed immunological abnormalities by flow cytometry (FCM) with multiple combinations of antibodies and with a hematology analyzer (Beckman LH750). CD91 (α2 -macroglobulin receptor) was expressed only by monocytes and to a consistent level among subjects [mean median fluorescence intensity (MFI) = 16.2 ± 3.2]. Notably, only 85.7 ± 5.82% of the CD91(+) monocytes expressed high levels of the classical monocyte marker CD14, with some CD91(+) CD16(+) cells having negligible CD14, indicating that substantial FCM under-counts will occur when monocytes are identified by high CD14. CD33 (receptor for sialyl conjugates) was co-expressed with CD91 on monocytes but CD33 expression varied by nearly ten-fold among subjects (mean MFI = 17.4 ± 7.7). In comparison to FCM analyses, the hematology analyzer systematically over-counted monocytes and eosinophils while lymphocyte and neutrophil differential values generally agreed with FCM methods. CD91 is a better marker to identify monocytes than CD14 or CD33. Furthermore, FCM (with anti-CD91) identifies monocytes better than a currently used clinical CBC instrument. Use of anti-CD91 together with anti-CD14 and anti-CD16 supports the identification of the diagnostically significant monocyte populations with variable expression of CD14 and CD16. Copyright © 2013 Clinical Cytometry Society.

Studies on processing, consumer survey and storage stability of a ready-to-reconstitute fish cutlet mix.

PubMed

Shaviklo, G Reza; Thorkelsson, Gudjon; Sveinsdottir, Kolbrun; Pourreza, Fatemeh

2013-10-01

A convenience ready-to-reconstitute cutlet mix containing 30% fish protein powder was developed to improve the nutritional quality of the product. Consumer survey was based on the home use test (HUT) method. The acceptance of the fish cutlet mix (FCM) was studied using a 9-point hedonic scale ranging from 1 (extremely dislike) to 9 (extremely like). Product's characteristics and stability were studied during 6 months of storage at 27 ± 2 °C. The FCM packed in a polyethylene bag and cardboard box was stable during the storage period. There were no changes in colour, moisture gain and water activity, and TBARS values remained low. The FCM was accepted by the consumers in the study (n = 85). The average liking was high (7.5 ± 1.3) and it was influenced by frequency of fish and chicken consumption, educational level and household size. People who ate fish once a week liked the product more than other consumers. Also those with higher educational level and bigger household size. The results in this paper are important information for companies planning to develop ready-to-eat products fortified with fish proteins. The products could be means of increasing fish consumption in countries/areas where there is no tradition of consuming fresh or frozen fish.

Modeling Uncertainties in EEG Microstates: Analysis of Real and Imagined Motor Movements Using Probabilistic Clustering-Driven Training of Probabilistic Neural Networks.

PubMed

Dinov, Martin; Leech, Robert

2017-01-01

Part of the process of EEG microstate estimation involves clustering EEG channel data at the global field power (GFP) maxima, very commonly using a modified K-means approach. Clustering has also been done deterministically, despite there being uncertainties in multiple stages of the microstate analysis, including the GFP peak definition, the clustering itself and in the post-clustering assignment of microstates back onto the EEG timecourse of interest. We perform a fully probabilistic microstate clustering and labeling, to account for these sources of uncertainty using the closest probabilistic analog to KM called Fuzzy C-means (FCM). We train softmax multi-layer perceptrons (MLPs) using the KM and FCM-inferred cluster assignments as target labels, to then allow for probabilistic labeling of the full EEG data instead of the usual correlation-based deterministic microstate label assignment typically used. We assess the merits of the probabilistic analysis vs. the deterministic approaches in EEG data recorded while participants perform real or imagined motor movements from a publicly available data set of 109 subjects. Though FCM group template maps that are almost topographically identical to KM were found, there is considerable uncertainty in the subsequent assignment of microstate labels. In general, imagined motor movements are less predictable on a time point-by-time point basis, possibly reflecting the more exploratory nature of the brain state during imagined, compared to during real motor movements. We find that some relationships may be more evident using FCM than using KM and propose that future microstate analysis should preferably be performed probabilistically rather than deterministically, especially in situations such as with brain computer interfaces, where both training and applying models of microstates need to account for uncertainty. Probabilistic neural network-driven microstate assignment has a number of advantages that we have discussed, which are likely to be further developed and exploited in future studies. In conclusion, probabilistic clustering and a probabilistic neural network-driven approach to microstate analysis is likely to better model and reveal details and the variability hidden in current deterministic and binarized microstate assignment and analyses.

Modeling Uncertainties in EEG Microstates: Analysis of Real and Imagined Motor Movements Using Probabilistic Clustering-Driven Training of Probabilistic Neural Networks

PubMed Central

Dinov, Martin; Leech, Robert

2017-01-01

Part of the process of EEG microstate estimation involves clustering EEG channel data at the global field power (GFP) maxima, very commonly using a modified K-means approach. Clustering has also been done deterministically, despite there being uncertainties in multiple stages of the microstate analysis, including the GFP peak definition, the clustering itself and in the post-clustering assignment of microstates back onto the EEG timecourse of interest. We perform a fully probabilistic microstate clustering and labeling, to account for these sources of uncertainty using the closest probabilistic analog to KM called Fuzzy C-means (FCM). We train softmax multi-layer perceptrons (MLPs) using the KM and FCM-inferred cluster assignments as target labels, to then allow for probabilistic labeling of the full EEG data instead of the usual correlation-based deterministic microstate label assignment typically used. We assess the merits of the probabilistic analysis vs. the deterministic approaches in EEG data recorded while participants perform real or imagined motor movements from a publicly available data set of 109 subjects. Though FCM group template maps that are almost topographically identical to KM were found, there is considerable uncertainty in the subsequent assignment of microstate labels. In general, imagined motor movements are less predictable on a time point-by-time point basis, possibly reflecting the more exploratory nature of the brain state during imagined, compared to during real motor movements. We find that some relationships may be more evident using FCM than using KM and propose that future microstate analysis should preferably be performed probabilistically rather than deterministically, especially in situations such as with brain computer interfaces, where both training and applying models of microstates need to account for uncertainty. Probabilistic neural network-driven microstate assignment has a number of advantages that we have discussed, which are likely to be further developed and exploited in future studies. In conclusion, probabilistic clustering and a probabilistic neural network-driven approach to microstate analysis is likely to better model and reveal details and the variability hidden in current deterministic and binarized microstate assignment and analyses. PMID:29163110

Biomechanical Model for Computing Deformations for Whole-Body Image Registration: A Meshless Approach

PubMed Central

Li, Mao; Miller, Karol; Joldes, Grand Roman; Kikinis, Ron; Wittek, Adam

2016-01-01

Patient-specific biomechanical models have been advocated as a tool for predicting deformations of soft body organs/tissue for medical image registration (aligning two sets of images) when differences between the images are large. However, complex and irregular geometry of the body organs makes generation of patient-specific biomechanical models very time consuming. Meshless discretisation has been proposed to solve this challenge. However, applications so far have been limited to 2-D models and computing single organ deformations. In this study, 3-D comprehensive patient-specific non-linear biomechanical models implemented using Meshless Total Lagrangian Explicit Dynamics (MTLED) algorithms are applied to predict a 3-D deformation field for whole-body image registration. Unlike a conventional approach which requires dividing (segmenting) the image into non-overlapping constituents representing different organs/tissues, the mechanical properties are assigned using the Fuzzy C-Means (FCM) algorithm without the image segmentation. Verification indicates that the deformations predicted using the proposed meshless approach are for practical purposes the same as those obtained using the previously validated finite element models. To quantitatively evaluate the accuracy of the predicted deformations, we determined the spatial misalignment between the registered (i.e. source images warped using the predicted deformations) and target images by computing the edge-based Hausdorff distance. The Hausdorff distance-based evaluation determines that our meshless models led to successful registration of the vast majority of the image features. PMID:26791945

Intravenous iron treatments for iron deficiency anemia in inflammatory bowel disease: a budget impact analysis of iron isomaltoside 1000 (Monofer) in the UK.

PubMed

Pollock, R F; Muduma, G

2017-12-01

Iron deficiency is the leading cause of anemia in patients with inflammatory bowel disease (IBD). Intravenous iron is the first-line treatment for clinically active IBD or previous oral iron intolerance. The aim of the present study was to develop a comparative model of iron deficiency and delivery for iron isomaltoside (IIM), ferric carboxymaltose (FCM), low molecular weight iron dextran (LMWID), and iron sucrose (IS) in the treatment of iron deficiency anemia associated with IBD. Areas covered: A model was developed to evaluate iron delivery characteristics, resource use and costs associated with IIM, FCM, LMWID and IS. Iron deficiency was modeled using dosing tables and retreatments were modeled based on a pooled retrospective analysis. The analyses were conducted over 5 years in patients with IBD with mean bodyweight of 75.4 kg and hemoglobin levels of 10.77 g/dL based on observational data. Expert opinion: The modeling analysis showed that using IIM required 1.2 infusions (per treatment) to correct the mean iron deficit, compared with 1.6, 1.2, and 7.1 with FCM, LMWID and IS, respectively. Costs were estimated to be 2,518 pounds sterling (GBP) per patient with IIM or LMWID, relative to GBP 3,309 with FCM or GBP 14,382 with IS.

Genetic Algorithm-Based Optimization to Match Asteroid Energy Deposition Curves

NASA Technical Reports Server (NTRS)

Tarano, Ana; Mathias, Donovan; Wheeler, Lorien; Close, Sigrid

2018-01-01

An asteroid entering Earth's atmosphere deposits energy along its path due to thermal ablation and dissipative forces that can be measured by ground-based and spaceborne instruments. Inference of pre-entry asteroid properties and characterization of the atmospheric breakup is facilitated by using an analytic fragment-cloud model (FCM) in conjunction with a Genetic Algorithm (GA). This optimization technique is used to inversely solve for the asteroid's entry properties, such as diameter, density, strength, velocity, entry angle, and strength scaling, from simulations using FCM. The previous parameters' fitness evaluation involves minimizing error to ascertain the best match between the physics-based calculated energy deposition and the observed meteors. This steady-state GA provided sets of solutions agreeing with literature, such as the meteor from Chelyabinsk, Russia in 2013 and Tagish Lake, Canada in 2000, which were used as case studies in order to validate the optimization routine. The assisted exploration and exploitation of this multi-dimensional search space enables inference and uncertainty analysis that can inform studies of near-Earth asteroids and consequently improve risk assessment.

Novel full-spectral flow cytometry with multiple spectrally-adjacent fluorescent proteins and fluorochromes and visualization of in vivo cellular movement.

PubMed

Futamura, Koji; Sekino, Masashi; Hata, Akihiro; Ikebuchi, Ryoyo; Nakanishi, Yasutaka; Egawa, Gyohei; Kabashima, Kenji; Watanabe, Takeshi; Furuki, Motohiro; Tomura, Michio

2015-09-01

Flow cytometric analysis with multicolor fluoroprobes is an essential method for detecting biological signatures of cells. Here, we present a new full-spectral flow cytometer (spectral-FCM). Unlike conventional flow cytometer, this spectral-FCM acquires the emitted fluorescence for all probes across the full-spectrum from each cell with 32 channels sequential PMT unit after dispersion with prism, and extracts the signals of each fluoroprobe based on the spectral shape of each fluoroprobe using unique algorithm in high speed, high sensitive, accurate, automatic and real-time. The spectral-FCM detects the continuous changes in emission spectra from green to red of the photoconvertible protein, KikGR with high-spectral resolution and separates spectrally-adjacent fluoroprobes, such as FITC (Emission peak (Em) 519 nm) and EGFP (Em 507 nm). Moreover, the spectral-FCM can measure and subtract autofluorescence of each cell providing increased signal-to-noise ratios and improved resolution of dim samples, which leads to a transformative technology for investigation of single cell state and function. These advances make it possible to perform 11-color fluorescence analysis to visualize movement of multilinage immune cells by using KikGR-expressing mice. Thus, the novel spectral flow cytometry improves the combinational use of spectrally-adjacent various FPs and multicolor fluorochromes in metabolically active cell for the investigation of not only the immune system but also other research and clinical fields of use. © 2015 International Society for Advancement of Cytometry.

A budget impact analysis of parenteral iron treatments for iron deficiency anemia in the UK: reduced resource utilization with iron isomaltoside 1000

PubMed Central

Pollock, Richard F; Muduma, Gorden

2017-01-01

Background and aims The reported prevalence of iron deficiency anemia (IDA) varies widely but estimates suggest that 3% of men and 8% of women have IDA in the UK. Parenteral iron is indicated for patients intolerant or unresponsive to oral iron or requiring rapid iron replenishment. This study evaluated differences in the cost of treating these patients with iron isomaltoside (Monofer®, IIM) relative to other intravenous iron formulations. Methods A budget impact model was developed to evaluate the cost of using IIM relative to ferric carboxymaltose (Ferinject®, FCM), low molecular weight iron dextran (Cosmofer®, LMWID), and iron sucrose (Venofer®, IS) in patients with IDA. To establish iron need, iron deficits were modeled using a simplified dosing table. The base case analysis was conducted over 1 year in patients with IDA with mean bodyweight of 82.4 kg (SD 22.5 kg) and hemoglobin levels of 9.99 g/dL (SD 1.03 g/dL) based on an analysis of patient characteristics in IDA trials. Costs were modeled using UK health care resource groups. Results Using IIM required 1.3 infusions to correct the mean iron deficit, compared with 1.3, 1.8, and 7.7 with LMWID, FCM, and IS, respectively. Patients using IIM required multiple infusions in 35% of cases, compared with 35%, 77%, and 100% of patients with LMWID, FCM, and IS, respectively. Total costs were estimated to be GBP 451 per patient with IIM or LMWID, relative to GBP 594 with FCM (a GBP 143 or 24% saving with IIM) or GBP 2,600 with IS (a GBP 2,149 or 83% saving with IIM). Conclusion Using IIM or LMWID in place of FCM or IS resulted in a marked reduction in the number of infusions required to correct iron deficits in patients with IDA. The reduction in infusions was accompanied by substantial reductions in cost relative to FCM and IS over 1 year. PMID:28848355

BP network identification technology of infrared polarization based on fuzzy c-means clustering

NASA Astrophysics Data System (ADS)

Zeng, Haifang; Gu, Guohua; He, Weiji; Chen, Qian; Yang, Wei

2011-08-01

Infrared detection system is frequently employed on surveillance operations and reconnaissance mission to detect particular targets of interest in both civilian and military communities. By incorporating the polarization of light as supplementary information, the target discrimination performance could be enhanced. So this paper proposed an infrared target identification method which is based on fuzzy theory and neural network with polarization properties of targets. The paper utilizes polarization degree and light intensity to advance the unsupervised KFCM (kernel fuzzy C-Means) clustering method. And establish different material pol1arization properties database. In the built network, the system can feedback output corresponding material types of probability distribution toward any input polarized degree such as 10° 15°, 20°, 25°, 30°. KFCM, which has stronger robustness and accuracy than FCM, introduces kernel idea and gives the noise points and invalid value different but intuitively reasonable weights. Because of differences in characterization of material properties, there will be some conflicts in classification results. And D - S evidence theory was used in the combination of the polarization and intensity information. Related results show KFCM clustering precision and operation rate are higher than that of the FCM clustering method. The artificial neural network method realizes material identification, which reasonable solved the problems of complexity in environmental information of infrared polarization, and improperness of background knowledge and inference rule. This method of polarization identification is fast in speed, good in self-adaption and high in resolution.

Novel full‐spectral flow cytometry with multiple spectrally‐adjacent fluorescent proteins and fluorochromes and visualization of in vivo cellular movement

PubMed Central

Futamura, Koji; Sekino, Masashi; Hata, Akihiro; Ikebuchi, Ryoyo; Nakanishi, Yasutaka; Egawa, Gyohei; Kabashima, Kenji; Watanabe, Takeshi; Furuki, Motohiro

2015-01-01

Abstract Flow cytometric analysis with multicolor fluoroprobes is an essential method for detecting biological signatures of cells. Here, we present a new full‐spectral flow cytometer (spectral‐FCM). Unlike conventional flow cytometer, this spectral‐FCM acquires the emitted fluorescence for all probes across the full‐spectrum from each cell with 32 channels sequential PMT unit after dispersion with prism, and extracts the signals of each fluoroprobe based on the spectral shape of each fluoroprobe using unique algorithm in high speed, high sensitive, accurate, automatic and real‐time. The spectral‐FCM detects the continuous changes in emission spectra from green to red of the photoconvertible protein, KikGR with high‐spectral resolution and separates spectrally‐adjacent fluoroprobes, such as FITC (Emission peak (Em) 519 nm) and EGFP (Em 507 nm). Moreover, the spectral‐FCM can measure and subtract autofluorescence of each cell providing increased signal‐to‐noise ratios and improved resolution of dim samples, which leads to a transformative technology for investigation of single cell state and function. These advances make it possible to perform 11‐color fluorescence analysis to visualize movement of multilinage immune cells by using KikGR‐expressing mice. Thus, the novel spectral flow cytometry improves the combinational use of spectrally‐adjacent various FPs and multicolor fluorochromes in metabolically active cell for the investigation of not only the immune system but also other research and clinical fields of use. © 2015 The Authors. Cytometry Part A Published by Wiley Periodicals, Inc. on behalf of ISAC PMID:26217952

flowAI: automatic and interactive anomaly discerning tools for flow cytometry data.

PubMed

Monaco, Gianni; Chen, Hao; Poidinger, Michael; Chen, Jinmiao; de Magalhães, João Pedro; Larbi, Anis

2016-08-15

Flow cytometry (FCM) is widely used in both clinical and basic research to characterize cell phenotypes and functions. The latest FCM instruments analyze up to 20 markers of individual cells, producing high-dimensional data. This requires the use of the latest clustering and dimensionality reduction techniques to automatically segregate cell sub-populations in an unbiased manner. However, automated analyses may lead to false discoveries due to inter-sample differences in quality and properties. We present an R package, flowAI, containing two methods to clean FCM files from unwanted events: (i) an automatic method that adopts algorithms for the detection of anomalies and (ii) an interactive method with a graphical user interface implemented into an R shiny application. The general approach behind the two methods consists of three key steps to check and remove suspected anomalies that derive from (i) abrupt changes in the flow rate, (ii) instability of signal acquisition and (iii) outliers in the lower limit and margin events in the upper limit of the dynamic range. For each file analyzed our software generates a summary of the quality assessment from the aforementioned steps. The software presented is an intuitive solution seeking to improve the results not only of manual but also and in particular of automatic analysis on FCM data. R source code available through Bioconductor: http://bioconductor.org/packages/flowAI/ CONTACTS: mongianni1@gmail.com or Anis_Larbi@immunol.a-star.edu.sg Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

SVM Pixel Classification on Colour Image Segmentation

NASA Astrophysics Data System (ADS)

Barui, Subhrajit; Latha, S.; Samiappan, Dhanalakshmi; Muthu, P.

2018-04-01

The aim of image segmentation is to simplify the representation of an image with the help of cluster pixels into something meaningful to analyze. Segmentation is typically used to locate boundaries and curves in an image, precisely to label every pixel in an image to give each pixel an independent identity. SVM pixel classification on colour image segmentation is the topic highlighted in this paper. It holds useful application in the field of concept based image retrieval, machine vision, medical imaging and object detection. The process is accomplished step by step. At first we need to recognize the type of colour and the texture used as an input to the SVM classifier. These inputs are extracted via local spatial similarity measure model and Steerable filter also known as Gabon Filter. It is then trained by using FCM (Fuzzy C-Means). Both the pixel level information of the image and the ability of the SVM Classifier undergoes some sophisticated algorithm to form the final image. The method has a well developed segmented image and efficiency with respect to increased quality and faster processing of the segmented image compared with the other segmentation methods proposed earlier. One of the latest application result is the Light L16 camera.

Single‐dose intravenous iron in Southeast Asian heart failure patients: A pilot randomized placebo‐controlled study (PRACTICE‐ASIA‐HF)

PubMed Central

Yeo, Poh Shuan Daniel; Hadi, Farid Abdul; Cushway, Timothy; Lee, Kim Yee; Yin, Fang Fang; Ching, Anne; Li, Ruili; Loh, Seet Yoong; Lim, Shir Lynn; Wong, Raymond Ching‐Chiew; Tai, Bee Choo; Richards, Arthur Mark; Lam, Carolyn S.P.

2018-01-01

Abstract Aims Iron deficiency is highly prevalent in Southeast Asians with heart failure (HF) and associated with worse outcomes. This trial aimed to assess the effect of intravenous iron in Southeast Asians hospitalized with decompensated HF. Methods and results Fifty patients hospitalized for acute decompensated HF, regardless of ejection fraction, with iron deficiency (defined as serum ferritin <300 ng/mL if transferrin saturation is <20%) were randomized to receive either one dose of intravenous ferric carboxymaltose (FCM) 1000 mg or placebo (0.9% saline) following HF stabilization and before discharge in two Singapore tertiary centres. The primary endpoint was difference in 6‐min walk test (6MWT) distance over 12 weeks, while secondary endpoints were quality of life assessed using validated Kansas City Cardiomyopathy Questionnaire (KCCQ) and Visual Analogue Scale (VAS). Improvement in 6MWT distance at Week 12 was observed in both FCM and placebo groups (from 252 ± 123 to 334 ± 128 m and from 243 ± 67 to 301 ± 83 m, respectively). Unadjusted analysis showed 6MWT distance for FCM exceeded that for placebo, but adjustment for baseline covariates and time attenuated this effect {adjusted mean difference between groups: 0.88 m [95% confidence interval (CI) −30.2 to 32.0, P = 0.956]}. KCCQ overall summary and VAS were similar in both groups [adjusted mean difference: KCCQ −1.48 (95% CI −8.27 to 5.31, P = 0.670) and VAS 0.26 (95% CI −0.33 to 0.86, P = 0.386)]. FCM was well tolerated with no serious treatment‐related adverse events. Conclusions Intravenous FCM administered pre‐discharge in Southeast Asians hospitalized with decompensated HF is clinically feasible. Changes in 6MWT distance should be measured beyond Week 12 to account for background therapy effects. PMID:29345426

Cell-production rates estimated by the use of vincristine sulphate and flow cytometry. I. An in vitro study using murine tumour cell lines.

PubMed

Barfod, I H; Barfod, N M

1980-01-01

A method for the evaluation of cell-production rates is described which combines flow cytometry (FCM) and the stathmokinetic method. By means of FCM it is possible to estimate the distribution of cells with G1, S and (G2 + M) DNA content in a population. As this method gives the relative (G2 + M) DNA content of cells within the cell cycle, it may be possible to evaluate cell-production rates by this technique. In the present study it was found that administration of a metaphase-arresting (stathmokinetic) agent, vincristine sulphate (VS), to asynchronous cell populations of three different murine tumour cell lines in vitro increased the peak representing cells with (G2 + M) DNA content as the number of mitotic (M) cells increased during the period of treatment. The accumulation of mitotic cells was determined by cell counts on smears under the microscope and compared with increase in the (G2 + M) DNA peak measured by FCM as a function of time after the administration of VS. Good agreement was obtained between the cell-production rates as estimated by FCM and by mitotic counts in all three cell lines investigated.

A modified approach combining FNEA and watershed algorithms for segmenting remotely-sensed optical images

NASA Astrophysics Data System (ADS)

Liu, Likun

2018-01-01

In the field of remote sensing image processing, remote sensing image segmentation is a preliminary step for later analysis of remote sensing image processing and semi-auto human interpretation, fully-automatic machine recognition and learning. Since 2000, a technique of object-oriented remote sensing image processing method and its basic thought prevails. The core of the approach is Fractal Net Evolution Approach (FNEA) multi-scale segmentation algorithm. The paper is intent on the research and improvement of the algorithm, which analyzes present segmentation algorithms and selects optimum watershed algorithm as an initialization. Meanwhile, the algorithm is modified by modifying an area parameter, and then combining area parameter with a heterogeneous parameter further. After that, several experiments is carried on to prove the modified FNEA algorithm, compared with traditional pixel-based method (FCM algorithm based on neighborhood information) and combination of FNEA and watershed, has a better segmentation result.

Signal-Noise Identification of Magnetotelluric Signals Using Fractal-Entropy and Clustering Algorithm for Targeted De-Noising

NASA Astrophysics Data System (ADS)

Li, Jin; Zhang, Xian; Gong, Jinzhe; Tang, Jingtian; Ren, Zhengyong; Li, Guang; Deng, Yanli; Cai, Jin

A new technique is proposed for signal-noise identification and targeted de-noising of Magnetotelluric (MT) signals. This method is based on fractal-entropy and clustering algorithm, which automatically identifies signal sections corrupted by common interference (square, triangle and pulse waves), enabling targeted de-noising and preventing the loss of useful information in filtering. To implement the technique, four characteristic parameters — fractal box dimension (FBD), higuchi fractal dimension (HFD), fuzzy entropy (FuEn) and approximate entropy (ApEn) — are extracted from MT time-series. The fuzzy c-means (FCM) clustering technique is used to analyze the characteristic parameters and automatically distinguish signals with strong interference from the rest. The wavelet threshold (WT) de-noising method is used only to suppress the identified strong interference in selected signal sections. The technique is validated through signal samples with known interference, before being applied to a set of field measured MT/Audio Magnetotelluric (AMT) data. Compared with the conventional de-noising strategy that blindly applies the filter to the overall dataset, the proposed method can automatically identify and purposefully suppress the intermittent interference in the MT/AMT signal. The resulted apparent resistivity-phase curve is more continuous and smooth, and the slow-change trend in the low-frequency range is more precisely reserved. Moreover, the characteristic of the target-filtered MT/AMT signal is close to the essential characteristic of the natural field, and the result more accurately reflects the inherent electrical structure information of the measured site.

Towards semi-automatic rock mass discontinuity orientation and set analysis from 3D point clouds

NASA Astrophysics Data System (ADS)

Guo, Jiateng; Liu, Shanjun; Zhang, Peina; Wu, Lixin; Zhou, Wenhui; Yu, Yinan

2017-06-01

Obtaining accurate information on rock mass discontinuities for deformation analysis and the evaluation of rock mass stability is important. Obtaining measurements for high and steep zones with the traditional compass method is difficult. Photogrammetry, three-dimensional (3D) laser scanning and other remote sensing methods have gradually become mainstream methods. In this study, a method that is based on a 3D point cloud is proposed to semi-automatically extract rock mass structural plane information. The original data are pre-treated prior to segmentation by removing outlier points. The next step is to segment the point cloud into different point subsets. Various parameters, such as the normal, dip/direction and dip, can be calculated for each point subset after obtaining the equation of the best fit plane for the relevant point subset. A cluster analysis (a point subset that satisfies some conditions and thus forms a cluster) is performed based on the normal vectors by introducing the firefly algorithm (FA) and the fuzzy c-means (FCM) algorithm. Finally, clusters that belong to the same discontinuity sets are merged and coloured for visualization purposes. A prototype system is developed based on this method to extract the points of the rock discontinuity from a 3D point cloud. A comparison with existing software shows that this method is feasible. This method can provide a reference for rock mechanics, 3D geological modelling and other related fields.

Fuzzy Cognitive Maps for Glacier Hazards Assessment: Application to Predicting the Potential for Glacier Lake Outbursts

NASA Astrophysics Data System (ADS)

Furfaro, R.; Kargel, J. S.; Fink, W.; Bishop, M. P.

2010-12-01

Glaciers and ice sheets are among the largest unstable parts of the solid Earth. Generally, glaciers are devoid of resources (other than water), are dangerous, are unstable and no infrastructure is normally built directly on their surfaces. Areas down valley from large alpine glaciers are also commonly unstable due to landslide potential of moraines, debris flows, snow avalanches, outburst floods from glacier lakes, and other dynamical alpine processes; yet there exists much development and human occupation of some disaster-prone areas. Satellite remote sensing can be extremely effective in providing cost-effective and time- critical information. Space-based imagery can be used to monitor glacier outlines and their lakes, including processes such as iceberg calving and debris accumulation, as well as changing thicknesses and flow speeds. Such images can also be used to make preliminary identifications of specific hazardous spots and allows preliminary assessment of possible modes of future disaster occurrence. Autonomous assessment of glacier conditions and their potential for hazards would present a major advance and permit systematized analysis of more data than humans can assess. This technical leap will require the design and implementation of Artificial Intelligence (AI) algorithms specifically designed to mimic glacier experts’ reasoning. Here, we introduce the theory of Fuzzy Cognitive Maps (FCM) as an AI tool for predicting and assessing natural hazards in alpine glacier environments. FCM techniques are employed to represent expert knowledge of glaciers physical processes. A cognitive model embedded in a fuzzy logic framework is constructed via the synergistic interaction between glaciologists and AI experts. To verify the effectiveness of the proposed AI methodology as applied to predicting hazards in glacier environments, we designed and implemented a FCM that addresses the challenging problem of autonomously assessing the Glacier Lake Outburst Flow Potential and Impound Water Upstream Flow Potential. The FCM is constructed using what is currently our understanding of how glacier lake outbursts occur, whereas the causal connection between concepts is defined to capture the expertise of glacier scientists. The proposed graph contains 27 nodes and a network of connections that represent the causal link between concepts. To test the developed FCM, we defined three scenarios representing glacier lake environmental conditions that either occurred or that are likely to occur in such highly dynamic environments. For each case, the FCM has been initialized using observables extracted from hypothesized remote sensing imagery. The map, which converges to a fixed point for all of the test scenarios within 15 iterations, shows reasoning consistent with that of glacier experts. The FCM-based cognitive approach has the potential to be the AI core of real-time operational hazards assessment and detection systems.

Fluorescent microspheres as surrogates in evaluating the efficacy of riverbank filtration for removing Cryptosporidium parvum oocysts and other pathogens

USGS Publications Warehouse

Harvey, Ronald W.; Metge, David W.; Sheets, Rodney A.; Jasperse, Jay

2011-01-01

A major benefit of riverbank filtration (RBF) is that it provides a relatively effective means for pathogen removal. There is a need to conduct more injection-and-recovery transport studies at operating RBF sites in order to properly assess the combined effects of the site heterogeneities and ambient physicochemical conditions, which are difficult to replicate in the lab. For field transport studies involving pathogens, there is considerable interest in using fluorescent carboxylated microspheres (FCM) as surrogates, because they are chemically inert, negatively charged, easy to detect, available in a wide variety of sizes, and have been found to be nonhazardous in tracer applications. Although there have been a number of in-situ studies comparing the subsurface transport behaviors of FCM to those of bacteria and viruses, much less is known about their suitability for investigations of protozoa. Oocysts of the intestinal protozoan pathogen Cryptosporidium spp are of particular concern for many RBF operations because of their ubiquity and persistence in rivers and high resistance to chlorine disinfection. Although microspheres often have proven to be less-than-ideal analogs for capturing the abiotic transport behavior of viruses and bacteria, there is encouraging recent evidence regarding use of FCM as surrogates for C. parvum oocysts. This chapter discusses the potential of fluorescent microspheres as safe and easy-to-detect surrogates for evaluating the efficacy of RBF operations for removing pathogens, particularly Cryptosporidium, from source waters at different points along the flow path.

Intravenous Iron Administration and Hypophosphatemia in Clinical Practice

PubMed Central

Hardy, S.; Vandemergel, X.

2015-01-01

Introduction. Parenteral iron formulations are frequently used to correct iron deficiency anemia (IDA) and iron deficiency (ID). Intravenous formulation efficacy on ferritin and hemoglobin level improvement is greater than that of oral formulations while they are associated with lower gastrointestinal side effects. Ferric carboxymaltose- (FCM-) related hypophosphatemia is frequent and appears without clinical significance. The aim of this study was to assess the prevalence, duration, and potential consequences of hypophosphatemia after iron injection. Patients and Methods. The medical records of all patients who underwent parenteral iron injection between 2012 and 2014 were retrospectively reviewed. Pre- and postinjection hemoglobin, ferritin, plasma phosphate, creatinine, and vitamin D levels were assessed. Patients who developed moderate (range: 0.32–0.80 mmol/L) or severe (<0.32 mmol/L) hypophosphatemia were questioned for symptoms. Results. During the study period, 234 patients received iron preparations but 104 were excluded because of missing data. Among the 130 patients included, 52 received iron sucrose (FS) and 78 FCM formulations. Among FS-treated patients, 22% developed hypophosphatemia versus 51% of FCM-treated patients, including 13% who developed profound hypophosphatemia. Hypophosphatemia severity correlated with the dose of FCM (p = 0.04) but not with the initial ferritin, hemoglobin, or vitamin D level. Mean hypophosphatemia duration was 6 months. No immediate clinical consequence was found except for persistent fatigue despite anemia correction in some patients. Conclusions. Hypophosphatemia is frequent after parenteral FCM injection and may have clinical consequences, including persistent fatigue. Further studies of chronic hypophosphatemia long-term consequences, especially bone assessments, are needed. PMID:26000018

Full color emitting fluorescent carbon material as reversible pH sensor with multicolor live cell imaging.

PubMed

Sharma, Vinay; Kaur, Navpreet; Tiwari, Pranav; Mobin, Shaikh M

2018-05-01

Carbon-based nano materials are developed as a cytocompatible alternative to semiconducting quantum dots for bioimaging and fluorescence-based sensing. The green alternatives for the synthesis of carbon materials are imminent. The present study demonstrates microwave based one step quick synthesis of fluorescent carbon material (FCM) having three variants: (i) un-doped fluorescent carbon material (UFCM) (ii) nitrogen doped FCM (N@FCM), and (iii) nitrogen & phosphorus co-doped FCM (N-P@FCM) using sugarcane extract as a carbon source. The N doping was performed using ethylenediamine and phosphoric acid was used for P doping. The heteroatom doped FCM were synthesized due to insolubility of UFCM in water. Unlike, UFCM, the N@FCM and N-P@FCM were found to be highly soluble in water. The N-P@FCM shows highest quantum yield among the three. The N-P@FCM was explored for alkaline pH sensing and it shows a quenching of fluorescence in the pH range 09-14. The sensing behaviour shows reversibility and high selectivity. Further, the sensor was also investigated for their biocompatibility and hence employed as a promising multicolour probe for cancer cell imaging. The generality in cell imaging was investigated by flow cytometry. The hetero-atom doped green carbon-dots may open new avenues for sensing and selective cellular targeting. Copyright © 2018 Elsevier B.V. All rights reserved.

A novel segmentation approach for implementation of MRAC in head PET/MRI employing Short-TE MRI and 2-point Dixon method in a fuzzy C-means framework

NASA Astrophysics Data System (ADS)

Khateri, Parisa; Rad, Hamidreza Saligheh; Jafari, Amir Homayoun; Ay, Mohammad Reza

2014-01-01

Quantitative PET image reconstruction requires an accurate map of attenuation coefficients of the tissue under investigation at 511 keV (μ-map), and in order to correct the emission data for attenuation. The use of MRI-based attenuation correction (MRAC) has recently received lots of attention in the scientific literature. One of the major difficulties facing MRAC has been observed in the areas where bone and air collide, e.g. ethmoidal sinuses in the head area. Bone is intrinsically not detectable by conventional MRI, making it difficult to distinguish air from bone. Therefore, development of more versatile MR sequences to label the bone structure, e.g. ultra-short echo-time (UTE) sequences, certainly plays a significant role in novel methodological developments. However, long acquisition time and complexity of UTE sequences limit its clinical applications. To overcome this problem, we developed a novel combination of Short-TE (ShTE) pulse sequence to detect bone signal with a 2-point Dixon technique for water-fat discrimination, along with a robust image segmentation method based on fuzzy clustering C-means (FCM) to segment the head area into four classes of air, bone, soft tissue and adipose tissue. The imaging protocol was set on a clinical 3 T Tim Trio and also 1.5 T Avanto (Siemens Medical Solution, Erlangen, Germany) employing a triple echo time pulse sequence in the head area. The acquisition parameters were as follows: TE1/TE2/TE3=0.98/4.925/6.155 ms, TR=8 ms, FA=25 on the 3 T system, and TE1/TE2/TE3=1.1/2.38/4.76 ms, TR=16 ms, FA=18 for the 1.5 T system. The second and third echo-times belonged to the Dixon decomposition to distinguish soft and adipose tissues. To quantify accuracy, sensitivity and specificity of the bone segmentation algorithm, resulting classes of MR-based segmented bone were compared with the manual segmented one by our expert neuro-radiologist. Results for both 3 T and 1.5 T systems show that bone segmentation applied in several slices yields average accuracy, sensitivity and specificity higher than 90%. Results indicate that FCM is an appropriate technique for tissue classification in the sinusoidal area where there is air-bone interface. Furthermore, using Dixon method, fat and brain tissues were successfully separated.

Host stress physiology and Trypanosoma haemoparasite infection influence innate immunity in the woylie (Bettongia penicillata).

PubMed

Hing, Stephanie; Currie, Andrew; Broomfield, Steven; Keatley, Sarah; Jones, Krista; Thompson, R C Andrew; Narayan, Edward; Godfrey, Stephanie S

2016-06-01

Understanding immune function is critical to conserving wildlife in view of infectious disease threats, particularly in threatened species vulnerable to stress, immunocompromise and infection. However, few studies examine stress, immune function and infection in wildlife. We used a flow cytometry protocol developed for human infants to assess phagocytosis, a key component of innate immunity, in a critically endangered marsupial, the woylie (Bettongia penicillata). The effects of stress physiology and Trypanosoma infection on phagocytosis were investigated. Blood and faecal samples were collected from woylies in a captive facility over three months. Trypanosoma status was determined using PCR. Faecal cortisol metabolites (FCM) were quantified by enzyme-immunoassay. Mean phagocytosis measured was >90%. An interaction between sex and FCM influenced the percentage of phagocytosing leukocytes, possibly reflecting the influence of sex hormones and glucocorticoids. An interaction between Trypanosoma status and FCM influenced phagocytosis index, suggesting that stress physiology and infection status influence innate immunity. Copyright © 2016 Elsevier Ltd. All rights reserved.

TEM characterization of irradiated U-7Mo/Mg dispersion fuel

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

Gan, J.; Keiser, D. D.; Miller, B. D.

This paper presents the results of transmission electron microscopy (TEM) characterization on neutron-irradiated samples taken from the low-flux and high-flux sides of the same fuel plate with U-7Mo fuel particles dispersed in Mg matrix with aluminum alloy Al6061 as cladding material that was irradiated edge-on to the core in the Advanced Test Reactor. The corresponding local fission density and fission rate of the fuel particles and the average fuel-plate centerline temperature for the low-flux and high-flux samples are estimated to be 3.7 × 10 21 f/cm 3, 7.4 × 10 14 f/cm 3/s and 123 °C, and 5.5 × 10more » 21 f/cm3, 11.0 × 10 14 f/cm 3/s and 158 °C, respectively. Complex interaction layers developed at the Al-Mg interface, consisting of Al 3Mg 2 and Al 12Mg 17 along with precipitates of MgO, Mg 2Si and FeAl 5.3. No interaction between Mg matrix and U-Mo fuel particle was identified. For the U-Mo fuel particles, at low fission density, small elongated bubbles wrapped around the clean areas with a fission gas bubble superlattice, which suggests that bubble coalescence is an important mechanism for converting the fission gas bubble superlattice to large bubbles. At high fission density, no bubbles or porosity were observed in the Mg matrix, and pockets of residual fission gas bubble superlattice were observed in the U-Mo fuel particle interior.« less

TEM characterization of irradiated U-7Mo/Mg dispersion fuel

DOE PAGES

Gan, J.; Keiser, D. D.; Miller, B. D.; ...

2017-07-15

This paper presents the results of transmission electron microscopy (TEM) characterization on neutron-irradiated samples taken from the low-flux and high-flux sides of the same fuel plate with U-7Mo fuel particles dispersed in Mg matrix with aluminum alloy Al6061 as cladding material that was irradiated edge-on to the core in the Advanced Test Reactor. The corresponding local fission density and fission rate of the fuel particles and the average fuel-plate centerline temperature for the low-flux and high-flux samples are estimated to be 3.7 × 10 21 f/cm 3, 7.4 × 10 14 f/cm 3/s and 123 °C, and 5.5 × 10more » 21 f/cm3, 11.0 × 10 14 f/cm 3/s and 158 °C, respectively. Complex interaction layers developed at the Al-Mg interface, consisting of Al 3Mg 2 and Al 12Mg 17 along with precipitates of MgO, Mg 2Si and FeAl 5.3. No interaction between Mg matrix and U-Mo fuel particle was identified. For the U-Mo fuel particles, at low fission density, small elongated bubbles wrapped around the clean areas with a fission gas bubble superlattice, which suggests that bubble coalescence is an important mechanism for converting the fission gas bubble superlattice to large bubbles. At high fission density, no bubbles or porosity were observed in the Mg matrix, and pockets of residual fission gas bubble superlattice were observed in the U-Mo fuel particle interior.« less

Performance of Transuranic-Loaded Fully Ceramic Micro-Encapsulated Fuel in LWRs Final Report, Including Void Reactivity Evaluation

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

Michael A. Pope; R. Sonat Sen; Brian Boer

2011-09-01

The current focus of the Deep Burn Project is on once-through burning of transuranics (TRU) in light-water reactors (LWRs). The fuel form is called Fully-Ceramic Micro-encapsulated (FCM) fuel, a concept that borrows the tri-isotropic (TRISO) fuel particle design from high-temperature reactor technology. In the Deep Burn LWR (DB-LWR) concept, these fuel particles are pressed into compacts using SiC matrix material and loaded into fuel pins for use in conventional LWRs. The TRU loading comes from the spent fuel of a conventional LWR after 5 years of cooling. Unit cell and assembly calculations have been performed using the DRAGON-4 code tomore » assess the physics attributes of TRU-only FCM fuel in an LWR lattice. Depletion calculations assuming an infinite lattice condition were performed with calculations of various reactivity coefficients performed at each step. Unit cells and assemblies containing typical UO2 and mixed oxide (MOX) fuel were analyzed in the same way to provide a baseline against which to compare the TRU-only FCM fuel. Then, assembly calculations were performed evaluating the performance of heterogeneous arrangements of TRU-only FCM fuel pins along with UO2 pins.« less

Identification of food spoilage in the smart home based on neural and fuzzy processing of odour sensor responses.

PubMed

Green, Geoffrey C; Chan, Adrian D C; Goubran, Rafik A

2009-01-01

Adopting the use of real-time odour monitoring in the smart home has the potential to alert the occupant of unsafe or unsanitary conditions. In this paper, we measured (with a commercial metal-oxide sensor-based electronic nose) the odours of five household foods that had been left out at room temperature for a week to spoil. A multilayer perceptron (MLP) neural network was trained to recognize the age of the samples (a quantity related to the degree of spoilage). For four of these foods, median correlation coefficients (between target values and MLP outputs) of R > 0.97 were observed. Fuzzy C-means clustering (FCM) was applied to the evolving odour patterns of spoiling milk, which had been sampled more frequently (4h intervals for 7 days). The FCM results showed that both the freshest and oldest milk samples had a high degree of membership in "fresh" and "spoiled" clusters, respectively. In the future, as advancements in electronic nose development remove the present barriers to acceptance, signal processing methods like those explored in this paper can be incorporated into odour monitoring systems used in the smart home.

Characterization of particulate products for aging of ethylbenzene secondary organic aerosol in the presence of ammonium sulfate seed aerosol.

PubMed

Huang, Mingqiang; Zhang, Jiahui; Cai, Shunyou; Liao, Yingmin; Zhao, Weixiong; Hu, Changjin; Gu, Xuejun; Fang, Li; Zhang, Weijun

2016-09-01

Aging of secondary organic aerosol (SOA) particles formed from OH- initiated oxidation of ethylbenzene in the presence of high mass (100-300μg/m(3)) concentrations of (NH4)2SO4 seed aerosol was investigated in a home-made smog chamber in this study. The chemical composition of aged ethylbenzene SOA particles was measured using an aerosol laser time-of-flight mass spectrometer (ALTOFMS) coupled with a Fuzzy C-Means (FCM) clustering algorithm. Experimental results showed that nitrophenol, ethyl-nitrophenol, 2,4-dinitrophenol, methyl glyoxylic acid, 5-ethyl-6-oxo-2,4-hexadienoic acid, 2-ethyl-2,4-hexadiendioic acid, 2,3-dihydroxy-5-ethyl-6-oxo-4-hexenoic acid, 1H-imidazole, hydrated N-glyoxal substituted 1H-imidazole, hydrated glyoxal dimer substituted imidazole, 1H-imidazole-2-carbaldehyde, N-glyoxal substituted hydrated 1H-imidazole-2-carbaldehyde and high-molecular-weight (HMW) components were the predominant products in the aged particles. Compared to the previous aromatic SOA aging studies, imidazole compounds, which can absorb solar radiation effectively, were newly detected in aged ethylbenzene SOA in the presence of high concentrations of (NH4)2SO4 seed aerosol. These findings provide new information for discussing aromatic SOA aging mechanisms. Copyright © 2016. Published by Elsevier B.V.

Distributed k-Means Algorithm and Fuzzy c-Means Algorithm for Sensor Networks Based on Multiagent Consensus Theory.

PubMed

Qin, Jiahu; Fu, Weiming; Gao, Huijun; Zheng, Wei Xing

2016-03-03

This paper is concerned with developing a distributed k-means algorithm and a distributed fuzzy c-means algorithm for wireless sensor networks (WSNs) where each node is equipped with sensors. The underlying topology of the WSN is supposed to be strongly connected. The consensus algorithm in multiagent consensus theory is utilized to exchange the measurement information of the sensors in WSN. To obtain a faster convergence speed as well as a higher possibility of having the global optimum, a distributed k-means++ algorithm is first proposed to find the initial centroids before executing the distributed k-means algorithm and the distributed fuzzy c-means algorithm. The proposed distributed k-means algorithm is capable of partitioning the data observed by the nodes into measure-dependent groups which have small in-group and large out-group distances, while the proposed distributed fuzzy c-means algorithm is capable of partitioning the data observed by the nodes into different measure-dependent groups with degrees of membership values ranging from 0 to 1. Simulation results show that the proposed distributed algorithms can achieve almost the same results as that given by the centralized clustering algorithms.

Design, fabrication, and evaluation of on-chip micro-supercapacitors

NASA Astrophysics Data System (ADS)

Beidaghi, Majid

Due to the increasing demand for high power and reliable miniaturized energy storage devices, the development of micro-supercapacitors or electrochemical micro-capacitors have attracted much attention in recent years. This dissertation investigates several strategies to develop on-chip micro-supercapacitors with high power and energy density. Micro-supercapacitors based on interdigitated carbon micro-electrode arrays are fabricated through carbon microelectromechanical systems (C-MEMS) technique which is based on carbonization of patterned photoresist. To improve the capacitive behavior, electrochemical activation is performed on carbon micro-electrode arrays. The developed micro-supercapacitors show specific capacitances as high as 75 mFcm-2 at a scan rate of 5 mVs -1 after electrochemical activation for 30 minutes. The capacitance loss is less than 13% after 1000 cyclic voltammetry (CV) cycles. These results indicate that electrochemically activated C-MEMS micro-electrode arrays are promising candidates for on-chip electrochemical micro-capacitor applications. The energy density of micro-supercapacitors was further improved by conformal coating of polypyrrole (PPy) on C-MEMS structures. In these types of micro-devices the three dimensional (3D) carbon microstructures serve as current collectors for high energy density PPy electrodes. The electrochemical characterizations of these micro-supercapacitors show that they can deliver a specific capacitance of about 162.07 mFcm-2 and a specific power of 1.62mWcm -2 at a 20 mVs-1 scan rate. Addressing the need for high power micro-supercapacitors, the application of graphene as electrode materials for micro-supercapacitor was also investigated. The present study suggests a novel method to fabricate graphene-based micro-supercapacitors with thin film or in-plane interdigital electrodes. The fabricated micro-supercapacitors show exceptional frequency response and power handling performance and could effectively charge and discharge at rates as high as 50 Vs-1. CV measurements show that the specific capacitance of the micro-supercapacitor based on reduced graphene oxide and carbon nanotube composites is 6.1 mFcm -2 at scan rate of 0.01Vs-1. At a very high scan rate of 50 Vs-1, a specific capacitance of 2.8 mFcm-2 (stack capacitance of 3.1 Fcm-3) is recorded. This unprecedented performance can potentially broaden the future applications of micro-supercapacitors.

Application of fuzzy c-means clustering to PRTR chemicals uncovering their release and toxicity characteristics.

PubMed

Xue, Mianqiang; Zhou, Liang; Kojima, Naoya; Dos Muchangos, Leticia Sarmento; Machimura, Takashi; Tokai, Akihiro

2018-05-01

Increasing manufacture and usage of chemicals have not been matched by the increase in our understanding of their risks. Pollutant release and transfer register (PRTR) is becoming a popular measure for collecting chemical data and enhancing the public right to know. However, these data are usually in high dimensionality which restricts their wider use. The present study partitions Japanese PRTR chemicals into five fuzzy clusters by fuzzy c-mean clustering (FCM) to explore the implicit information. Each chemical with membership degrees belongs to each cluster. Cluster I features high releases from non-listed industries and the household sector and high environmental toxicity. Cluster II is characterized by high reported releases and transfers from 24 listed industries above the threshold, mutagenicity, and high environmental toxicity. Chemicals in cluster III have characteristics of high releases from non-listed industries and low toxicity. Cluster IV is characterized by high reported releases and transfers from 24 listed industries above the threshold and extremely high environmental toxicity. Cluster V is characterized by low releases yet mutagenicity and high carcinogenicity. Chemicals with the highest membership degree were identified as representatives for each cluster. For the highest membership degree, half of the chemicals have a value higher than 0.74. If we look at both the highest and the second highest membership degrees simultaneously, about 94% of the chemicals have a value higher than 0.5. FCM can serve as an approach to uncover the implicit information of highly complex chemical dataset, which subsequently supports the strategy development for efficient and effective chemical management. Copyright © 2017 Elsevier B.V. All rights reserved.

Microbial-sized, carboxylate-modified microspheres as surrogate tracers in a variety of subsurface environments: An overview

USGS Publications Warehouse

Harvey, Ronald W.; Metge, David W.; LeBlanc, Denis R.

2017-01-01

Since 1986, fluorescent carboxylate-modified polystyrene/latex microspheres (FCM) have been co-injected into aquifers along with conservative tracers and viruses, bacteria, and (or) protozoa. Use of FCM has resulted in new information about subsurface transport behaviors of microorganisms in fractured crystalline rock, karst limestone, soils, and granular aquifers. FCM have been used as surrogates for oocysts of the pathogenic protist Cryptosporidium parvum in karst limestone and granular drinking-water aquifers. The advantages of FCM in subsurface transport studies are that they are safe in tracer applications, negatively charged, easy to detect, chemically inert, and available in wide range of sizes. The limitations of FCM are that the quantities needed for some field transport studies can be prohibitively expensive and that their surface characteristics may not match the microorganisms of interest. These limitations may be ameliorated, in part by using chemically modified FCM so that their surface characteristics are a better match to that of the organisms. Also, more sensitive methods of detection may allow using smaller quantities of FCM. To assess how the transport behaviors of FCM and pathogens might compare at the field scale, it is helpful to conduct side-by-side comparisons of their transport behaviors using the geologic media and site-specific conditions that characterize the field site.

Data Standards for Flow Cytometry

PubMed Central

SPIDLEN, JOSEF; GENTLEMAN, ROBERT C.; HAALAND, PERRY D.; LANGILLE, MORGAN; MEUR, NOLWENN LE; OCHS, MICHAEL F.; SCHMITT, CHARLES; SMITH, CLAYTON A.; TREISTER, ADAM S.; BRINKMAN, RYAN R.

2009-01-01

Flow cytometry (FCM) is an analytical tool widely used for cancer and HIV/AIDS research, and treatment, stem cell manipulation and detecting microorganisms in environmental samples. Current data standards do not capture the full scope of FCM experiments and there is a demand for software tools that can assist in the exploration and analysis of large FCM datasets. We are implementing a standardized approach to capturing, analyzing, and disseminating FCM data that will facilitate both more complex analyses and analysis of datasets that could not previously be efficiently studied. Initial work has focused on developing a community-based guideline for recording and reporting the details of FCM experiments. Open source software tools that implement this standard are being created, with an emphasis on facilitating reproducible and extensible data analyses. As well, tools for electronic collaboration will assist the integrated access and comprehension of experiments to empower users to collaborate on FCM analyses. This coordinated, joint development of bioinformatics standards and software tools for FCM data analysis has the potential to greatly facilitate both basic and clinical research—impacting a notably diverse range of medical and environmental research areas. PMID:16901228

Methods for microbiological quality assessment in drinking water: a comparative study.

PubMed

Helmi, K; Barthod, F; Méheut, G; Henry, A; Poty, F; Laurent, F; Charni-Ben-Tabassi, N

2015-03-01

The present study aimed to compare several methods for quantifying and discriminating between the different physiological states of a bacterial population present in drinking water. Flow cytometry (FCM), solid-phase cytometry (SPC), epifluorescence microscopy (MSP) and culture method performances were assessed by comparing the results obtained for different water samples. These samples, including chlorinated and non-chlorinated water, were collected in a drinking water treatment plant. Total bacteria were quantified by using SYBR Green II (for FCM) and 4',6'-diamino-2-phenylindole (DAPI) (for MSP), viable and non-viable bacteria were distinguished by using SYBR Green II and propidium iodide dual staining (for FCM), and active cells were distinguished by using CTC (for MSP) and Chemchrome V6 (for FCM and SPC). In our conditions, counts using microscopy and FCM were significantly correlated regarding total bacteria and active cells. Conversely, counts were not significantly similar using solid-phase and FCM for active bacteria. Moreover, the R2A medium showed that bacterial culturability could be recovered after chlorination. This study highlights that FCM appears to be a useful and powerful technique for drinking water production monitoring.

Introduction of a New Diagnostic Method for Breast Cancer Based on Fine Needle Aspiration (FNA) Test Data and Combining Intelligent Systems.

PubMed

Fiuzy, Mohammad; Haddadnia, Javad; Mollania, Nasrin; Hashemian, Maryam; Hassanpour, Kazem

2012-01-01

Accurate Diagnosis of Breast Cancer is of prime importance. Fine Needle Aspiration test or "FNA", which has been used for several years in Europe, is a simple, inexpensive, noninvasive and accurate technique for detecting breast cancer. Expending the suitable features of the Fine Needle Aspiration results is the most important diagnostic problem in early stages of breast cancer. In this study, we introduced a new algorithm that can detect breast cancer based on combining artificial intelligent system and Fine Needle Aspiration (FNA). We studied the Features of Wisconsin Data Base Cancer which contained about 569 FNA test samples (212 patient samples (malignant) and 357 healthy samples (benign)). In this research, we combined Artificial Intelligence Approaches, such as Evolutionary Algorithm (EA) with Genetic Algorithm (GA), and also used Exact Classifier Systems (here by Fuzzy C-Means (FCM)) to separate malignant from benign samples. Furthermore, we examined artificial Neural Networks (NN) to identify the model and structure. This research proposed a new algorithm for an accurate diagnosis of breast cancer. According to Wisconsin Data Base Cancer (WDBC) data base, 62.75% of samples were benign, and 37.25% were malignant. After applying the proposed algorithm, we achieved high detection accuracy of about "96.579%" on 205 patients who were diagnosed as having breast cancer. It was found that the method had 93% sensitivity, 73% specialty, 65% positive predictive value, and 95% negative predictive value, respectively. If done by experts, Fine Needle Aspiration (FNA) can be a reliable replacement for open biopsy in palpable breast masses. Evaluation of FNA samples during aspiration can decrease insufficient samples. FNA can be the first line of diagnosis in women with breast masses, at least in deprived regions, and may increase health standards and clinical supervision of patients. Such a smart, economical, non-invasive, rapid and accurate system can be introduced as a useful diagnostic system for comprehensive treatment of breast cancer. Another advantage of this method is the possibility of diagnosing breast abnormalities. If done by experts, FNA can be a reliable replacement for open biopsy in palpable breast masses. Evaluation of FNA samples during aspiration can decrease insufficient samples.

Monitoring microbiological changes in drinking water systems using a fast and reproducible flow cytometric method.

PubMed

Prest, E I; Hammes, F; Kötzsch, S; van Loosdrecht, M C M; Vrouwenvelder, J S

2013-12-01

Flow cytometry (FCM) is a rapid, cultivation-independent tool to assess and evaluate bacteriological quality and biological stability of water. Here we demonstrate that a stringent, reproducible staining protocol combined with fixed FCM operational and gating settings is essential for reliable quantification of bacteria and detection of changes in aquatic bacterial communities. Triplicate measurements of diverse water samples with this protocol typically showed relative standard deviation values and 95% confidence interval values below 2.5% on all the main FCM parameters. We propose a straightforward and instrument-independent method for the characterization of water samples based on the combination of bacterial cell concentration and fluorescence distribution. Analysis of the fluorescence distribution (or so-called fluorescence fingerprint) was accomplished firstly through a direct comparison of the raw FCM data and subsequently simplified by quantifying the percentage of large and brightly fluorescent high nucleic acid (HNA) content bacteria in each sample. Our approach enables fast differentiation of dissimilar bacterial communities (less than 15 min from sampling to final result), and allows accurate detection of even small changes in aquatic environments (detection above 3% change). Demonstrative studies on (a) indigenous bacterial growth in water, (b) contamination of drinking water with wastewater, (c) household drinking water stagnation and (d) mixing of two drinking water types, univocally showed that this FCM approach enables detection and quantification of relevant bacterial water quality changes with high sensitivity. This approach has the potential to be used as a new tool for application in the drinking water field, e.g. for rapid screening of the microbial water quality and stability during water treatment and distribution in networks and premise plumbing. Copyright © 2013 Elsevier Ltd. All rights reserved.

Automatic segmentation of meningioma from non-contrasted brain MRI integrating fuzzy clustering and region growing.

PubMed

Hsieh, Thomas M; Liu, Yi-Min; Liao, Chun-Chih; Xiao, Furen; Chiang, I-Jen; Wong, Jau-Min

2011-08-26

In recent years, magnetic resonance imaging (MRI) has become important in brain tumor diagnosis. Using this modality, physicians can locate specific pathologies by analyzing differences in tissue character presented in different types of MR images.This paper uses an algorithm integrating fuzzy-c-mean (FCM) and region growing techniques for automated tumor image segmentation from patients with menigioma. Only non-contrasted T1 and T2 -weighted MR images are included in the analysis. The study's aims are to correctly locate tumors in the images, and to detect those situated in the midline position of the brain. The study used non-contrasted T1- and T2-weighted MR images from 29 patients with menigioma. After FCM clustering, 32 groups of images from each patient group were put through the region-growing procedure for pixels aggregation. Later, using knowledge-based information, the system selected tumor-containing images from these groups and merged them into one tumor image. An alternative semi-supervised method was added at this stage for comparison with the automatic method. Finally, the tumor image was optimized by a morphology operator. Results from automatic segmentation were compared to the "ground truth" (GT) on a pixel level. Overall data were then evaluated using a quantified system. The quantified parameters, including the "percent match" (PM) and "correlation ratio" (CR), suggested a high match between GT and the present study's system, as well as a fair level of correspondence. The results were compatible with those from other related studies. The system successfully detected all of the tumors situated at the midline of brain.Six cases failed in the automatic group. One also failed in the semi-supervised alternative. The remaining five cases presented noticeable edema inside the brain. In the 23 successful cases, the PM and CR values in the two groups were highly related. Results indicated that, even when using only two sets of non-contrasted MR images, the system is a reliable and efficient method of brain-tumor detection. With further development the system demonstrates high potential for practical clinical use.

WE-G-204-07: Automated Characterization of Perceptual Quality of Clinical Chest Radiographs: Improvements in Lung, Spine, and Hardware Detection

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

Wells, J; Zhang, L; Samei, E

Purpose: To develop and validate more robust methods for automated lung, spine, and hardware detection in AP/PA chest images. This work is part of a continuing effort to automatically characterize the perceptual image quality of clinical radiographs. [Y. Lin et al. Med. Phys. 39, 7019–7031 (2012)] Methods: Our previous implementation of lung/spine identification was applicable to only one vendor. A more generalized routine was devised based on three primary components: lung boundary detection, fuzzy c-means (FCM) clustering, and a clinically-derived lung pixel probability map. Boundary detection was used to constrain the lung segmentations. FCM clustering produced grayscale- and neighborhood-based pixelmore » classification probabilities which are weighted by the clinically-derived probability maps to generate a final lung segmentation. Lung centerlines were set along the left-right lung midpoints. Spine centerlines were estimated as a weighted average of body contour, lateral lung contour, and intensity-based centerline estimates. Centerline estimation was tested on 900 clinical AP/PA chest radiographs which included inpatient/outpatient, upright/bedside, men/women, and adult/pediatric images from multiple imaging systems. Our previous implementation further did not account for the presence of medical hardware (pacemakers, wires, implants, staples, stents, etc.) potentially biasing image quality analysis. A hardware detection algorithm was developed using a gradient-based thresholding method. The training and testing paradigm used a set of 48 images from which 1920 51×51 pixel{sup 2} ROIs with and 1920 ROIs without hardware were manually selected. Results: Acceptable lung centerlines were generated in 98.7% of radiographs while spine centerlines were acceptable in 99.1% of radiographs. Following threshold optimization, the hardware detection software yielded average true positive and true negative rates of 92.7% and 96.9%, respectively. Conclusion: Updated segmentation and centerline estimation methods in addition to new gradient-based hardware detection software provide improved data integrity control and error-checking for automated clinical chest image quality characterization across multiple radiography systems.« less

Utilization of flow cytometry for diagnosis of hematologic malignancies in Thailand: increasing trends and diagnostic yields in 7,982 samples.

PubMed

Promsuwicha, Orathai; Kankhao, Supattra; Songmuang, Wayuree; Auewarakul, Chirayu U

2014-12-01

Diagnosis of hematologic malignancies requires a multidisciplinary approach. Flow cytometry (FCM) has become an essential tool for immunophenotypic studies of malignant hematopoietic cells. To evaluate the utilization trend of FCM and its diagnostic yields for hematologic malignancy at a major teaching hospital in Thailand. FCM results of bone marrow (BM) and peripheral blood (PB) specimens during 2000-2013 were analyzed and compared to clinical diagnosis. Overall, 7,982 specimens were submitted for diagnostic FCM including 6,561 BM and 1,421 PB. The number of specimens analyzedwas 121, 142, 164, 299, 491, 431, 690, 611, 719, 744, 725, 863, 955 and 1,027, respectively, from 2000 to 2013. The most common clinical diagnoses requested for FCM were acute leukemia (5,911 cases, 74%) followed by lymphoma (1,419 cases, 17.8%), and chronic lymphocytic leukemia (CLL) (634 cases, 7.94%). The highest diagnostic yield of FCM was found in acute leukemia cases (69.71%) followed by CLL (35.33%). Only 15.43% of clinically suspected lymphoma cases were positive by FCM. Overutilization of PB (35.6% of cases) instead of BM for lymphoma staging significantly contributed to low diagnostic yields of lymphoma by FCM as circulating tumor cells may not be present in such cases. FCM has an increasing role in the diagnosis of hematologic malignancies in Thai patients over the past 14 years with the highest diagnostic yield in acute leukemia. Appropriate specimen types and study indications are required in order to reduce futility of costly diagnostic tests and improve diagnostic yields.

Drug‐specific hypophosphatemia and hypersensitivity reactions following different intravenous iron infusions

PubMed Central

Hvas, Christian L.; Dahlerup, Jens F.

2017-01-01

Aims Intravenous (IV) iron infusions have been associated with hypophosphataemia (HP) and hypersensitivity reactions (HSRs). No studies have compared the side effects of ferric carboxymaltose (FCM) with those of isomaltoside 1000 (ISM). This study aimed to describe the occurrence of HP and HSRs following the administration of either FCM or ISM. Methods Data on 231 outpatients treated with IV iron infusions, between November 2011 and April 2014, were collected. During that period, the department made a switch from FCM to ISM and then back to FCM. Of the 231 patients, 39 received both FCM and ISM during the period. The prevalences of HP and HSRs were compared between the two drugs. Results We found more HP events when FCM was given (64 vs. 9; P < 0.01). In contrast, more patients had mild HSRs when ISM was given (2.5% vs. 10.7%; P < 0.01). A comparison of the two drugs in the subpopulation who received both drug types (n = 39) revealed a difference in phosphate decrease (P < 0.01), with the most marked decrease occurring with FCM. Nine patients who had HSRs were exposed to both drugs. No potential HSR crossover between the two drugs was found. Conclusion We found a higher risk of HP with FCM administration when compared to ISM administration. Conversely, we found a higher risk of mild HSRs with ISM administration when compared to FCM administration. The impacts of the two types of side effects should be considered when choosing an IV iron drug. PMID:27859495

Drug-specific hypophosphatemia and hypersensitivity reactions following different intravenous iron infusions.

PubMed

Bager, Palle; Hvas, Christian L; Dahlerup, Jens F

2017-05-01

Intravenous (IV) iron infusions have been associated with hypophosphataemia (HP) and hypersensitivity reactions (HSRs). No studies have compared the side effects of ferric carboxymaltose (FCM) with those of isomaltoside 1000 (ISM). This study aimed to describe the occurrence of HP and HSRs following the administration of either FCM or ISM. Data on 231 outpatients treated with IV iron infusions, between November 2011 and April 2014, were collected. During that period, the department made a switch from FCM to ISM and then back to FCM. Of the 231 patients, 39 received both FCM and ISM during the period. The prevalences of HP and HSRs were compared between the two drugs. We found more HP events when FCM was given (64 vs. 9; P < 0.01). In contrast, more patients had mild HSRs when ISM was given (2.5% vs. 10.7%; P < 0.01). A comparison of the two drugs in the subpopulation who received both drug types (n = 39) revealed a difference in phosphate decrease (P < 0.01), with the most marked decrease occurring with FCM. Nine patients who had HSRs were exposed to both drugs. No potential HSR crossover between the two drugs was found. We found a higher risk of HP with FCM administration when compared to ISM administration. Conversely, we found a higher risk of mild HSRs with ISM administration when compared to FCM administration. The impacts of the two types of side effects should be considered when choosing an IV iron drug. © 2016 The British Pharmacological Society.

Modifications of haematology analyzers to improve cell counting and leukocyte differentiating in cerebrospinal fluid controls of the Joint German Society for Clinical Chemistry and Laboratory Medicine.

PubMed

Kleine, Tilmann O; Nebe, C Thomas; Löwer, Christa; Lehmitz, Reinhard; Kruse, Rolf; Geilenkeuser, Wolf-Jochen; Dorn-Beineke, Alexandra

2009-08-01

Flow cytometry (FCM) is used with haematology analyzers (HAs) to count cells and differentiate leukocytes in cerebrospinal fluid (CSF). To evaluate the FCM techniques of HAs, 10 external DGKL trials with CSF controls were carried out in 2004 to 2008. Eight single platform HAs with and without CSF equipment were evaluated with living blood leukocytes and erythrocytes in CSF like DGKL controls: Coulter (LH750,755), Abbott CD3200, CD3500, CD3700, CD4000, Sapphire, ADVIA 120(R) CSF assay, and Sysmex XE-2100(R). Results were compared with visual counting of native cells in Fuchs-Rosenthal chamber, unstained, and absolute values of leukocyte differentiation, assayed by dual platform analysis with immune-FCM (FACSCalibur, CD45, CD14) and the chamber counts. Reference values X were compared with HA values Y by statistical evaluation with Passing/Bablock (P/B) linear regression analysis to reveal conformity of both methods. The HAs, studied, produced no valid results with DGKL CSF controls, because P/B regression revealed no conformity with the reference values due to:-blank problems with impedance analysis,-leukocyte loss with preanalytical erythrocyte lysis procedures, especially of monocytes,-inaccurate results with ADVIA cell sphering and cell differentiation with algorithms and enzyme activities (e.g., peroxidase). HA techniques have to be improved, e.g., using no erythrocyte lysis and CSF adequate techniques, to examine CSF samples precise and accurate. Copyright 2009 International Society for Advancement of Cytometry.

Hepcidin Response to Iron Therapy in Patients with Non-Dialysis Dependent CKD: An Analysis of the FIND-CKD Trial.

PubMed

Gaillard, Carlo A; Bock, Andreas H; Carrera, Fernando; Eckardt, Kai-Uwe; Van Wyck, David B; Bansal, Sukhvinder S; Cronin, Maureen; Meier, Yvonne; Larroque, Sylvain; Roger, Simon D; Macdougall, Iain C

2016-01-01

Hepcidin is the key regulator of iron homeostasis but data are limited regarding its temporal response to iron therapy, and response to intravenous versus oral iron. In the 56-week, open-label, multicenter, prospective, randomized FIND-CKD study, 626 anemic patients with non-dialysis dependent chronic kidney disease (ND-CKD) and iron deficiency not receiving an erythropoiesis stimulating agent were randomized (1:1:2) to intravenous ferric carboxymaltose (FCM), targeting higher (400-600μg/L) or lower (100-200μg/L) ferritin, or to oral iron. Serum hepcidin levels were measured centrally in a subset of 61 patients. Mean (SD) baseline hepcidin level was 4.0(3.5), 7.3(6.4) and 6.5(5.6) ng/mL in the high ferritin FCM (n = 17), low ferritin FCM (n = 16) and oral iron group (n = 28). The mean (SD) endpoint value (i.e. the last post-baseline value) was 26.0(9.1),15.7(7.7) and 16.3(11.0) ng/mL, respectively. The increase in hepcidin from baseline was significantly smaller with low ferritin FCM or oral iron vs high ferritin FCM at all time points up to week 52. Significant correlations were found between absolute hepcidin and ferritin values (r = 0.65, p<0.001) and between final post-baseline increases in both parameters (r = 0.70, p<0.001). The increase in hepcidin levels over the 12-month study generally mirrored the cumulative iron dose in each group. Hepcidin and transferrin saturation (TSAT) absolute values showed no correlation, although there was an association between final post-baseline increases (r = 0.42, p<0.001). Absolute values (r = 0.36, p = 0.004) and final post-baseline increases of hepcidin and hemoglobin (p = 0.30, p = 0.030) correlated weakly. Baseline hepcidin levels were not predictive of a hematopoietic response to iron therapy. In conclusion, hepcidin levels rose in response to either intravenous or oral iron therapy, but the speed and extent of the rise was greatest with intravenous iron targeting a higher ferritin level. However neither the baseline level nor the change in hepcidin was able to predict response to therapy in this cohort.

Applications of Flow Cytometry to Clinical Microbiology†

PubMed Central

Álvarez-Barrientos, Alberto; Arroyo, Javier; Cantón, Rafael; Nombela, César; Sánchez-Pérez, Miguel

2000-01-01

Classical microbiology techniques are relatively slow in comparison to other analytical techniques, in many cases due to the need to culture the microorganisms. Furthermore, classical approaches are difficult with unculturable microorganisms. More recently, the emergence of molecular biology techniques, particularly those on antibodies and nucleic acid probes combined with amplification techniques, has provided speediness and specificity to microbiological diagnosis. Flow cytometry (FCM) allows single- or multiple-microbe detection in clinical samples in an easy, reliable, and fast way. Microbes can be identified on the basis of their peculiar cytometric parameters or by means of certain fluorochromes that can be used either independently or bound to specific antibodies or oligonucleotides. FCM has permitted the development of quantitative procedures to assess antimicrobial susceptibility and drug cytotoxicity in a rapid, accurate, and highly reproducible way. Furthermore, this technique allows the monitoring of in vitro antimicrobial activity and of antimicrobial treatments ex vivo. The most outstanding contribution of FCM is the possibility of detecting the presence of heterogeneous populations with different responses to antimicrobial treatments. Despite these advantages, the application of FCM in clinical microbiology is not yet widespread, probably due to the lack of access to flow cytometers or the lack of knowledge about the potential of this technique. One of the goals of this review is to attempt to mitigate this latter circumstance. We are convinced that in the near future, the availability of commercial kits should increase the use of this technique in the clinical microbiology laboratory. PMID:10755996

Practical way to develop 10-color flow cytometry protocols for the clinical laboratory

NASA Astrophysics Data System (ADS)

Tárnok, Attila; Bocsi, Jozsef

2010-02-01

The latest development of commercial routine flow cytometers (FCM) is that they are equipped with three (blue, red, violet) or more lasers and many PMT detectors. Nowadays routine clinical instruments are capable of detecting 10 or more fluorescence colors simultaneously. Thereby, presenting opportunities for getting detailed information on the single cell level for cytomics and systems biology for improve diagnostics and monitoring of patients. The University Leipzig, Germany) recently started a cluster of excellence to study the molecular background of life style and environment associated diseases, enrolling 25000 individuals (LIFE). To this end the most comprehensive FCM protocol has to be developed for this study. We aimed to optimize fluorochrome and antibody combinations to the characteristics of the instrument for successful 10-color FCM. Systematic review of issues related to sampling, preparation, instrument settings, spillover and compensation matrix, reagent performance, and general principles of panel construction was performed. 10-color FCM enables for increased accuracy in cell subpopulation identification, the ability to obtain detailed information from blood specimens, improved laboratory efficiency, and the means to consistently detect major and rare cell populations. Careful attention to details of instrument and reagent performance allows for the development of panels suitable for screening of samples from healthy and diseased donors. The characteristics of this technique are particularly well suited for the analysis of broad human population cohorts and have the potential to reach the everyday practice in a standardized way for the clinical laboratory.

Local delivery of fluorescent dye for fiber-optics confocal microscopy of the living heart.

PubMed

Huang, Chao; Kaza, Aditya K; Hitchcock, Robert W; Sachse, Frank B

2014-01-01

Fiber-optics confocal microscopy (FCM) is an emerging imaging technology with various applications in basic research and clinical diagnosis. FCM allows for real-time in situ microscopy of tissue at sub-cellular scale. Recently FCM has been investigated for cardiac imaging, in particular, for discrimination of cardiac tissue during pediatric open-heart surgery. FCM relies on fluorescent dyes. The current clinical approach of dye delivery is based on systemic injection, which is associated with high dye consumption, and adverse clinical events. In this study, we investigated approaches for local dye delivery during FCM imaging based on dye carriers attached to the imaging probe. Using three-dimensional confocal microscopy, automated bench tests, and FCM imaging we quantitatively characterized dye release of carriers composed of open-pore foam only and foam loaded with agarose hydrogel. In addition, we compared local dye delivery with a model of systemic dye delivery in the isolated perfused rodent heart. We measured the signal-to-noise ratio (SNR) of images acquired in various regions of the heart. Our evaluations showed that foam-agarose dye carriers exhibited a prolonged dye release vs. foam-only carriers. Foam-agarose dye carriers allowed reliable imaging of 5-9 lines, which is comparable to 4-8 min of continuous dye release. Our study in the living heart revealed that the SNR of FCM images using local and systemic dye delivery is not different. However, we observed differences in the imaged tissue microstructure with the two approaches. Structural features characteristic of microvasculature were solely observed for systemic dye delivery. Our findings suggest that local dye delivery approach for FCM imaging constitutes an important alternative to systemic dye delivery. We suggest that the approach for local dye delivery will facilitate clinical translation of FCM, for instance, for FCM imaging during pediatric heart surgery.

Genome-wide association study of the four-constitution medicine.

PubMed

Yin, Chang Shik; Park, Hi Joon; Chung, Joo-Ho; Lee, Hye-Jung; Lee, Byung-Cheol

2009-12-01

Four-constitution medicine (FCM), also known as Sasang constitutional medicine, and the heritage of the long history of individualized acupuncture medicine tradition, is one of the holistic and traditional systems of constitution to appraise and categorize individual differences into four major types. This study first reports a genome-wide association study on FCM, to explore the genetic basis of FCM and facilitate the integration of FCM with conventional individual differences research. Healthy individuals of the Korean population were classified into the four constitutional types (FCTs). A total of 353,202 single nucleotide polymorphisms (SNPs) were typed using whole genome amplified samples, and six-way comparison of FCM types provided lists of significantly differential SNPs. In one-to-one FCT comparisons, 15,944 SNPs were significantly differential, and 5 SNPs were commonly significant in all of the three comparisons. In one-to-two FCT comparisons, 22,616 SNPs were significantly differential, and 20 SNPs were commonly significant in all of the three comparison groups. This study presents the association between genome-wide SNP profiles and the categorization of the FCM, and it could further provide a starting point of genome-based identification and research of the constitutions of FCM.

Modeling and Analysis of FCM UN TRISO Fuel Using the PARFUME Code

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

Blaise Collin

2013-09-01

The PARFUME (PARticle Fuel ModEl) modeling code was used to assess the overall fuel performance of uranium nitride (UN) tri-structural isotropic (TRISO) ceramic fuel in the frame of the design and development of Fully Ceramic Matrix (FCM) fuel. A specific modeling of a TRISO particle with UN kernel was developed with PARFUME, and its behavior was assessed in irradiation conditions typical of a Light Water Reactor (LWR). The calculations were used to access the dimensional changes of the fuel particle layers and kernel, including the formation of an internal gap. The survivability of the UN TRISO particle was estimated dependingmore » on the strain behavior of the constituent materials at high fast fluence and burn-up. For nominal cases, internal gas pressure and representative thermal profiles across the kernel and layers were determined along with stress levels in the pyrolytic carbon (PyC) and silicon carbide (SiC) layers. These parameters were then used to evaluate fuel particle failure probabilities. Results of the study show that the survivability of UN TRISO fuel under LWR irradiation conditions might only be guaranteed if the kernel and PyC swelling rates are limited at high fast fluence and burn-up. These material properties are unknown at the irradiation levels expected to be reached by UN TRISO fuel in LWRs. Therefore, more effort is needed to determine them and positively conclude on the applicability of FCM fuel to LWRs.« less

Intracellular flow cytometry may be combined with good quality and high sensitivity RT-qPCR analysis.

PubMed

Sandstedt, Mikael; Jonsson, Marianne; Asp, Julia; Dellgren, Göran; Lindahl, Anders; Jeppsson, Anders; Sandstedt, Joakim

2015-12-01

Flow cytometry (FCM) has become a well-established method for analysis of both intracellular and cell-surface proteins, while quantitative RT-PCR (RT-qPCR) is used to determine gene expression with high sensitivity and specificity. Combining these two methods would be of great value. The effects of intracellular staining on RNA integrity and RT-qPCR sensitivity and quality have not, however, been fully examined. We, therefore, intended to assess these effects further. Cells from the human lung cancer cell line A549 were fixed, permeabilized and sorted by FCM. Sorted cells were analyzed using RT-qPCR. RNA integrity was determined by RNA quality indicator analysis. A549 cells were then mixed with cells of the mouse cardiomyocyte cell line HL-1. A549 cells were identified by the cell surface marker ABCG2, while HL-1 cells were identified by intracellular cTnT. Cells were sorted and analyzed by RT-qPCR. Finally, cell cultures from human atrial biopsies were used to evaluate the effects of fixation and permeabilization on RT-qPCR analysis of nonimmortalized cells stored prior to analysis by FCM. A large amount of RNA could be extracted even when cells had been fixed and permeabilized. Permeabilization resulted in increased RNA degradation and a moderate decrease in RT-qPCR sensitivity. Gene expression levels were also affected to a moderate extent. Sorted populations from the mixed A549 and HL-1 cell samples showed gene expression patterns that corresponded to FCM data. When samples were stored before FCM sorting, the RT-qPCR analysis could still be performed with high sensitivity and quality. In summary, our results show that intracellular FCM may be performed with only minor impairment of the RT-qPCR sensitivity and quality when analyzing sorted cells; however, these effects should be considered when comparing RT-qPCR data of not fixed samples with those of fixed and permeabilized samples. © 2015 International Society for Advancement of Cytometry.

GEM-loaded magnetic albumin nanospheres modified with cetuximab for simultaneous targeting, magnetic resonance imaging, and double-targeted thermochemotherapy of pancreatic cancer cells.

PubMed

Wang, Ling; An, Yanli; Yuan, Chenyan; Zhang, Hao; Liang, Chen; Ding, Fengan; Gao, Qi; Zhang, Dongsheng

2015-01-01

Targeted delivery is a promising strategy to improve the diagnostic imaging and therapeutic effect of cancers. In this paper, novel cetuximab (C225)-conjugated, gemcitabine (GEM)-containing magnetic albumin nanospheres (C225-GEM/MANs) were fabricated and applied as a theranostic nanocarrier to conduct simultaneous targeting, magnetic resonance imaging (MRI), and double-targeted thermochemotherapy against pancreatic cancer cells. Fe3O4 nanoparticles (NPs) and GEM co-loaded albumin nanospheres (GEM/MANs) were prepared, and then C225 was further conjugated to synthesize C225-GEM/MANs. Their morphology, mean particle size, GEM encapsulation ratio, specific cell-binding ability, and thermal dynamic profiles were characterized. The effects of discriminating different EGFR-expressing pancreatic cancer cells (AsPC-1 and MIA PaCa-2) and monitoring cellular targeting effects were assessed by targeted MRI. Lastly, the antitumor efficiency of double/C225/magnetic-targeted and nontargeted thermochemotherapy was compared with chemotherapy alone using 3-(4, 5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) and flow cytometry (FCM) assay. When treated with targeted nanospheres, AsPC-1 cells showed a significantly less intense MRI T2 signal than MIA PaCa-2 cells, while both cells had similar signal strength when incubated with nontargeted nanospheres. T2 signal intensity was significantly lower when magnetic and C225 targeting were combined, rather than used alone. The inhibitory and apoptotic rates of each thermochemotherapy group were significantly higher than those of the chemotherapy-alone groups. Additionally, both MTT and FCM analysis verified that double-targeted thermochemotherapy had the highest targeted killing efficiency among all groups. The C225-GEM/MANs can distinguish various EGFR-expressing live pancreatic cancer cells, monitor diverse cellular targeting effects using targeted MRI imaging, and efficiently mediate double-targeted thermochemotherapy against pancreatic cancer cells.

Financial impact of intravenous iron treatments on the management of anaemia inpatients: a 1 year observational study.

PubMed

Delpeuch, Amina; Ruivard, Marc; Abergel, Armand; Aumaitre, Olivier; Boisgard, Stéphane; Bagel, Sandrine; Sautou, Valérie

2018-03-08

Background Intravenous (IV) iron preparations bypass the difficulties (malabsorption and side effects) associated with oral iron for the treatment of iron deficiency anaemia (IDA). Ferric carboxymaltose (FCM) can be administered as a single infusion over short periods of time but is more expensive than iron sucrose (IS) when the patients are hospitalized. Objectives To evaluate the appropriateness of FCM prescriptions and to establish the economic impact of this management (including disease coding) compared to the use of IV IS. Setting This study was conducted for inpatients in all departments (orthopaedic department, gastroenterology department and two units of the internal medicine department) where FCM was widely prescribed. Method We retrospectively identified 224 patients, diagnosed with IDA using laboratory parameters and/or disease coding, who received FCM between January and December 2014. Main outcome measure The primary outcome was the rate of appropriateness of FCM prescriptions and the financial impact compared to IV IS. Results 89 Patients were included. The total additional cost for an inappropriate prescription of IV FCM (68% of cases) was of 6053 €. The total incremental cost of unsuitable disease coding was estimated at 31,688 €. Indications for IV FCM were categorized: intestinal bleeding (31%), malabsorption (17%), intolerance (9%) and refractory to oral iron (7%). The majority of patients (62%) received 1000 mg of FCM per week. The average length of hospital stay was of 10 days. Conclusion The prescription of IV iron was appropriate in most cases but did not necessarily require FCM. The use of IV IS, in many cases, could present a cost-saving option for inpatients with IDA. The lack of an IDA coding generated incremental costs.

Clinical experience with ferric carboxymaltose in the treatment of cancer- and chemotherapy-associated anaemia

PubMed Central

Steinmetz, T.; Tschechne, B.; Harlin, O.; Klement, B.; Franzem, M.; Wamhoff, J.; Tesch, H.; Rohrberg, R.; Marschner, N.

2013-01-01

Background Intravenous (i.v.) iron can improve anaemia of chronic disease and response to erythropoiesis-stimulating agents (ESAs), but data on its use in practice and without ESAs are limited. This study evaluated effectiveness and tolerability of ferric carboxymaltose (FCM) in routine treatment of anaemic cancer patients. Patients and methods Of 639 patients enrolled in 68 haematology/oncology practices in Germany, 619 received FCM at the oncologist's discretion, 420 had eligible baseline haemoglobin (Hb) measurements, and 364 at least one follow-up Hb measurement. Data of transfused patients were censored from analysis before transfusion. Results The median total iron dose was 1000 mg per patient (interquartile range 600–1500 mg). The median Hb increase was comparable in patients receiving FCM alone (1.4 g/dl [0.2–2.3 g/dl; N = 233]) or FCM + ESA (1.6 g/dl [0.7–2.4 g/dl; N = 46]). Patients with baseline Hb up to 11.0 g/dl and serum ferritin up to 500 ng/ml benefited from FCM treatment (stable Hb ≥11.0 g/dl). Also patients with ferritin >500 ng/ml but low transferrin saturation benefited from FCM treatment. FCM was well tolerated, 2.3% of patients reported putative drug-related adverse events. Conclusions The substantial Hb increase and stabilisation at 11–12 g/dl in FCM-treated patients suggest a role for i.v. iron alone in anaemia correction in cancer patients. PMID:23071262

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.

Alzheimer disease detection from structural MR images using FCM based weighted probabilistic neural network.

PubMed

Duraisamy, Baskar; Shanmugam, Jayanthi Venkatraman; Annamalai, Jayanthi

2018-02-19

An early intervention of Alzheimer's disease (AD) is highly essential due to the fact that this neuro degenerative disease generates major life-threatening issues, especially memory loss among patients in society. Moreover, categorizing NC (Normal Control), MCI (Mild Cognitive Impairment) and AD early in course allows the patients to experience benefits from new treatments. Therefore, it is important to construct a reliable classification technique to discriminate the patients with or without AD from the bio medical imaging modality. Hence, we developed a novel FCM based Weighted Probabilistic Neural Network (FWPNN) classification algorithm and analyzed the brain images related to structural MRI modality for better discrimination of class labels. Initially our proposed framework begins with brain image normalization stage. In this stage, ROI regions related to Hippo-Campus (HC) and Posterior Cingulate Cortex (PCC) from the brain images are extracted using Automated Anatomical Labeling (AAL) method. Subsequently, nineteen highly relevant AD related features are selected through Multiple-criterion feature selection method. At last, our novel FWPNN classification algorithm is imposed to remove suspicious samples from the training data with an end goal to enhance the classification performance. This newly developed classification algorithm combines both the goodness of supervised and unsupervised learning techniques. The experimental validation is carried out with the ADNI subset and then to the Bordex-3 city dataset. Our proposed classification approach achieves an accuracy of about 98.63%, 95.4%, 96.4% in terms of classification with AD vs NC, MCI vs NC and AD vs MCI. The experimental results suggest that the removal of noisy samples from the training data can enhance the decision generation process of the expert systems.

Saliency-Guided Change Detection of Remotely Sensed Images Using Random Forest

NASA Astrophysics Data System (ADS)

Feng, W.; Sui, H.; Chen, X.

2018-04-01

Studies based on object-based image analysis (OBIA) representing the paradigm shift in change detection (CD) have achieved remarkable progress in the last decade. Their aim has been developing more intelligent interpretation analysis methods in the future. The prediction effect and performance stability of random forest (RF), as a new kind of machine learning algorithm, are better than many single predictors and integrated forecasting method. In this paper, we present a novel CD approach for high-resolution remote sensing images, which incorporates visual saliency and RF. First, highly homogeneous and compact image super-pixels are generated using super-pixel segmentation, and the optimal segmentation result is obtained through image superimposition and principal component analysis (PCA). Second, saliency detection is used to guide the search of interest regions in the initial difference image obtained via the improved robust change vector analysis (RCVA) algorithm. The salient regions within the difference image that correspond to the binarized saliency map are extracted, and the regions are subject to the fuzzy c-means (FCM) clustering to obtain the pixel-level pre-classification result, which can be used as a prerequisite for superpixel-based analysis. Third, on the basis of the optimal segmentation and pixel-level pre-classification results, different super-pixel change possibilities are calculated. Furthermore, the changed and unchanged super-pixels that serve as the training samples are automatically selected. The spectral features and Gabor features of each super-pixel are extracted. Finally, superpixel-based CD is implemented by applying RF based on these samples. Experimental results on Ziyuan 3 (ZY3) multi-spectral images show that the proposed method outperforms the compared methods in the accuracy of CD, and also confirm the feasibility and effectiveness of the proposed approach.

An analysis of the health service efficiency and patient experience with two different intravenous iron preparations in a UK anaemia clinic.

PubMed

Wilson, Paul D; Hutchings, Adam; Jeans, Aruna; Macdougall, Iain C

2013-01-01

Historically, the Renal Unit at King's College Hospital used intravenous (IV) iron sucrose (IS) to treat iron deficiency anaemia in patients with chronic kidney disease who were not on dialysis (CKD-ND). As part of a service initiative to improve patient experience, new products were considered as alternatives. This study investigated the potential impact on patient experience and service costs by switching from IS to ferric carboxymaltose (FCM). A decision analytical model was used to calculate the impact of switching from IS to FCM for a cohort of CKD-ND patients. Service provision data were collected for 365 patients who received 600 mg IS within a 12 month period, creating the IS data set. The service provision data, along with a clinically relevant FCM administration protocol (stipulating total doses of 500 mg FCM), were used to calculate a corresponding theoretical data set for FCM for the same cohort of patients. The FCM protocol saved each patient two hospital visits and 2.66 hours of time (equating to approximately a saving of £36.21 in loss of earnings) and £19 in travel costs. Direct attributable costs for iron administration (which included drug, disposables, nursing staff, and hospital-provided patient transport costs) were £58,646 for IS vs £46,473 for FCM. Direct overhead costs (which included nursing preparation time, administration staff, clinic space, and consultant time costs) were £40,172 for the IS service vs £15,174 for the FCM service. Based on clinical experience with the products, this analysis assumes that 500 mg FCM is therapeutically equivalent to 600 mg IS. Consultant time costs are assumed to be the same between the two treatment groups. IV iron administration protocols and data are specific to King's College Hospital. The design is retrospective and changes to the management of the clinic, including service delivery optimization, may also affect real costs. FCM was associated with fewer hospital visits and reduced transport costs for CKD-ND patients receiving IV iron and has the potential to save 19-37% in service costs. Owing to increased administration efficiency, FCM can improve the overall patient experience while reducing the total cost of the King's College Hospital IV iron service for CKD-ND patients, compared with treatment with IS.

Multi-Patches IRIS Based Person Authentication System Using Particle Swarm Optimization and Fuzzy C-Means Clustering

NASA Astrophysics Data System (ADS)

Shekar, B. H.; Bhat, S. S.

2017-05-01

Locating the boundary parameters of pupil and iris and segmenting the noise free iris portion are the most challenging phases of an automated iris recognition system. In this paper, we have presented person authentication frame work which uses particle swarm optimization (PSO) to locate iris region and circular hough transform (CHT) to device the boundary parameters. To undermine the effect of the noise presented in the segmented iris region we have divided the candidate region into N patches and used Fuzzy c-means clustering (FCM) to classify the patches into best iris region and not so best iris region (noisy region) based on the probability density function of each patch. Weighted mean Hammimng distance is adopted to find the dissimilarity score between the two candidate irises. We have used Log-Gabor, Riesz and Taylor's series expansion (TSE) filters and combinations of these three for iris feature extraction. To justify the feasibility of the proposed method, we experimented on the three publicly available data sets IITD, MMU v-2 and CASIA v-4 distance.

A new method based on Dempster-Shafer theory and fuzzy c-means for brain MRI segmentation

NASA Astrophysics Data System (ADS)

Liu, Jie; Lu, Xi; Li, Yunpeng; Chen, Xiaowu; Deng, Yong

2015-10-01

In this paper, a new method is proposed to decrease sensitiveness to motion noise and uncertainty in magnetic resonance imaging (MRI) segmentation especially when only one brain image is available. The method is approached with considering spatial neighborhood information by fusing the information of pixels with their neighbors with Dempster-Shafer (DS) theory. The basic probability assignment (BPA) of each single hypothesis is obtained from the membership function of applying fuzzy c-means (FCM) clustering to the gray levels of the MRI. Then multiple hypotheses are generated according to the single hypothesis. Then we update the objective pixel’s BPA by fusing the BPA of the objective pixel and those of its neighbors to get the final result. Some examples in MRI segmentation are demonstrated at the end of the paper, in which our method is compared with some previous methods. The results show that the proposed method is more effective than other methods in motion-blurred MRI segmentation.

Choice of High-Dose Intravenous Iron Preparation Determines Hypophosphatemia Risk

PubMed Central

Schaefer, Benedikt; Würtinger, Philipp; Finkenstedt, Armin; Braithwaite, Vickie; Viveiros, André; Effenberger, Maria; Sulzbacher, Irene; Moschen, Alexander; Griesmacher, Andrea; Tilg, Herbert; Vogel, Wolfgang; Zoller, Heinz

2016-01-01

Background Ferric carboxymaltose (FCM) and iron isomaltoside 1000 (IIM) are increasingly used because they allow correction of severe iron deficiency in a single infusion. A transient decrease in serum phosphate concentrations is a frequent side effect of FCM. Aim To characterize this adverse event and search for its predictors in a gastroenterology clinic patient cohort. Methods Electronic medical records of patients attending the University Hospital of Innsbruck were searched for the keywords ferric carboxymaltose or iron isomaltoside. Eighty-one patients with documented administration of FCM or IIM with plasma phosphate concentrations before and after treatment were included. Results The prevalence of hypophosphatemia (<0.8 mmol/L) increased from 11% to 32.1% after treatment with i.v. iron. The hypophosphatemia risk was greater after FCM (45.5%) compared with IIM (4%). Severe hypophosphatemia (<0.6 mmol/L) occurred exclusively after FCM (32.7%). The odds for hypophosphatemia after i.v. iron treatment were independently determined by baseline phosphate and the choice of i.v. iron preparation (FCM vs. IIM—OR = 20.8; 95% CI, 2.6–166; p = 0.004). The median time with hypophosphatemia was 41 days, but prolonged hypophosphatemia of ≥ 2 months was documented in 13 of 17 patients in whom follow-up was available. A significant increase in the phosphaturic hormone intact FGF-23 in hypophosphatemic patients shows that this adverse event is caused by FCM-induced hormone dysregulation. Conclusion Treatment with FCM is associated with a high risk of developing severe and prolonged hypophosphatemia and should therefore be monitored. Hypophosphatemia risk appears to be substantially lower with IIM. PMID:27907058

Choice of High-Dose Intravenous Iron Preparation Determines Hypophosphatemia Risk.

PubMed

Schaefer, Benedikt; Würtinger, Philipp; Finkenstedt, Armin; Braithwaite, Vickie; Viveiros, André; Effenberger, Maria; Sulzbacher, Irene; Moschen, Alexander; Griesmacher, Andrea; Tilg, Herbert; Vogel, Wolfgang; Zoller, Heinz

2016-01-01

Ferric carboxymaltose (FCM) and iron isomaltoside 1000 (IIM) are increasingly used because they allow correction of severe iron deficiency in a single infusion. A transient decrease in serum phosphate concentrations is a frequent side effect of FCM. To characterize this adverse event and search for its predictors in a gastroenterology clinic patient cohort. Electronic medical records of patients attending the University Hospital of Innsbruck were searched for the keywords ferric carboxymaltose or iron isomaltoside. Eighty-one patients with documented administration of FCM or IIM with plasma phosphate concentrations before and after treatment were included. The prevalence of hypophosphatemia (<0.8 mmol/L) increased from 11% to 32.1% after treatment with i.v. iron. The hypophosphatemia risk was greater after FCM (45.5%) compared with IIM (4%). Severe hypophosphatemia (<0.6 mmol/L) occurred exclusively after FCM (32.7%). The odds for hypophosphatemia after i.v. iron treatment were independently determined by baseline phosphate and the choice of i.v. iron preparation (FCM vs. IIM-OR = 20.8; 95% CI, 2.6-166; p = 0.004). The median time with hypophosphatemia was 41 days, but prolonged hypophosphatemia of ≥ 2 months was documented in 13 of 17 patients in whom follow-up was available. A significant increase in the phosphaturic hormone intact FGF-23 in hypophosphatemic patients shows that this adverse event is caused by FCM-induced hormone dysregulation. Treatment with FCM is associated with a high risk of developing severe and prolonged hypophosphatemia and should therefore be monitored. Hypophosphatemia risk appears to be substantially lower with IIM.

Isolation and purification of oligopeptides from Ruditapes philippinarum and its inhibition on the growth of DU‑145 cells in vitro.

PubMed

Yang, Zuisu; Zhao, Yuqin; Yan, Haiqiang; Xu, Lv; Ding, Guofang; Yu, Di; Sun, Yu

2015-02-01

Ruditapes philippinarum is a member of the Veneridae family of marine bivalve molluscs. RPOI‑1 (Ruditapes philippinarum oligopeptide) is a tetrapeptide that can be extracted from Ruditapes philippinarum by means of enzymolysis. This study showed that RPOI‑1 strongly inhibits proliferation and induces apoptosis in DU‑145 human prostate cancer cells. When cells were treated with varying concentrations of RPOI‑1, significant inhibition of proliferation was detected by an MTT assay, and sub‑G1 and G2/M phase cell cycle arrest was observed using flow cytometric (FCM) analysis. Furthermore, morphological changes characteristic of apoptosis and an increase in the proportion of apoptotic cells were observed using double sequential acridine orange/ethidium bromide staining, FCM analysis and transmission election microscopy. FCM studies showed that exposing DU‑145 cells to 10, 20 and 30 mg/ml RPOI‑1 for 24 h increased the percentage of cells in the early‑stages of apoptotis in a dose‑dependent manner, with the numbers rising from 3.01% in the control group to 13.40% in the group treated with the highest dose.

Application of flow cytometry to wine microorganisms.

PubMed

Longin, Cédric; Petitgonnet, Clément; Guilloux-Benatier, Michèle; Rousseaux, Sandrine; Alexandre, Hervé

2017-04-01

Flow cytometry (FCM) is a powerful technique allowing detection and enumeration of microbial populations in food and during food process. Thanks to the fluorescent dyes used and specific probes, FCM provides information about cell physiological state and allows enumeration of a microorganism in a mixed culture. Thus, this technique is increasingly used to quantify pathogen, spoilage microorganisms and microorganisms of interest. Since one decade, FCM applications to the wine field increase greatly to determine population and physiological state of microorganisms performing alcoholic and malolactic fermentations. Wine spoilage microorganisms were also studied. In this review we briefly describe FCM principles. Next, a deep revision concerning enumeration of wine microorganisms by FCM is presented including the fluorescent dyes used and techniques allowing a yeast and bacteria species specific enumeration. Then, the last chapter is dedicated to fluorescent dyes which are used to date in fluorescent microscopy but applicable in FCM. This chapter also describes other interesting "future" techniques which could be applied to study the wine microorganisms. Thus, this review seeks to highlight the main advantages of the flow cytometry applied to wine microbiology. Copyright © 2016 Elsevier Ltd. All rights reserved.

Constructing Ultrahigh-Capacity Zinc-Nickel-Cobalt Oxide@Ni(OH)2 Core-Shell Nanowire Arrays for High-Performance Coaxial Fiber-Shaped Asymmetric Supercapacitors.

PubMed

Zhang, Qichong; Xu, Weiwei; Sun, Juan; Pan, Zhenghui; Zhao, Jingxin; Wang, Xiaona; Zhang, Jun; Man, Ping; Guo, Jiabin; Zhou, Zhenyu; He, Bing; Zhang, Zengxing; Li, Qingwen; Zhang, Yuegang; Xu, Lai; Yao, Yagang

2017-12-13

Increased efforts have recently been devoted to developing high-energy-density flexible supercapacitors for their practical applications in portable and wearable electronics. Although high operating voltages have been achieved in fiber-shaped asymmetric supercapacitors (FASCs), low specific capacitance still restricts the further enhancement of their energy density. This article specifies a facile and cost-effective method to directly grow three-dimensionally well-aligned zinc-nickel-cobalt oxide (ZNCO)@Ni(OH) 2 nanowire arrays (NWAs) on a carbon nanotube fiber (CNTF) with an ultrahigh specific capacitance of 2847.5 F/cm 3 (10.678 F/cm 2 ) at a current density of 1 mA/cm 2 , These levels are approximately five times higher than those of ZNCO NWAs/CNTF electrodes (2.10 F/cm 2 ) and four times higher than Ni(OH) 2 /CNTF electrodes (2.55 F/cm 2 ). Benefiting from their unique features, we successfully fabricated a prototype coaxial FASC (CFASC) with a maximum operating voltage of 1.6 V, which was assembled by adopting ZNCO@Ni(OH) 2 NWAs/CNTF as the core electrode and a thin layer of carbon coated vanadium nitride (VN@C) NWAs on a carbon nanotube strip (CNTS) as the outer electrode with KOH poly(vinyl alcohol) (PVA) as the gel electrolyte. A high specific capacitance of 94.67 F/cm 3 (573.75 mF/cm 2 ) and an exceptional energy density of 33.66 mWh/cm 3 (204.02 μWh/cm 2 ) were achieved for our CFASC device, which represent the highest levels of fiber-shaped supercapacitors to date. More importantly, the fiber-shaped ZnO-based photodetector is powered by the integrated CFASC, and it demonstrates excellent sensitivity in detecting UV light. Thus, this work paves the way to the construction of ultrahigh-capacity electrode materials for next-generation wearable energy-storage devices.

[Important differences between faculties of medicine. Implications for family and community medicine].

PubMed

González Lopez-Valcarcel, Beatriz; Ortún, Vicente; Barber, Patricia; Harris, Jeffrey E

2014-03-01

To determine if there are significant differences between universities in the proclivity to choose Family and Community Medicine (FCM), given the constraints imposed by the number of choice. To test the hypothesis that the Schools of Medicine that have the FCM as a compulsory subject in the degree (3 of 27) had the highest preference for this specialty. Observational study on the data file of all the individuals taking the MIR examination between 2003 and 2011. Spain. All those who sat the examinations called by MIR 2003-2011. Position in the ranking of each candidate, elected position (specialty and center), post code of residence, sex, nationality and university in which they studied, and post code location for the residence chosen. The percentage electing FCM is highly correlated with the position in the ranking: 8% of graduates for the 'best' college, 46% for the worst. Very noticeable and consistent differences in the preparation for the MIR among the 27 medical schools. Ranking in the exam, female and foreigner, help predict the choice of FCM. The FCM compulsory curriculum from three universities does not seem to exert any influence. The convenient yardstick competition between the schools of medicine, FCM in their curriculum and the emphasis on the most attractive attributes of the specialty can contribute to the necessary renewal of FCM. Copyright © 2013 Elsevier España, S.L. All rights reserved.

Flow cytometric bacterial cell counts challenge conventional heterotrophic plate counts for routine microbiological drinking water monitoring.

PubMed

Van Nevel, S; Koetzsch, S; Proctor, C R; Besmer, M D; Prest, E I; Vrouwenvelder, J S; Knezev, A; Boon, N; Hammes, F

2017-04-15

Drinking water utilities and researchers continue to rely on the century-old heterotrophic plate counts (HPC) method for routine assessment of general microbiological water quality. Bacterial cell counting with flow cytometry (FCM) is one of a number of alternative methods that challenge this status quo and provide an opportunity for improved water quality monitoring. After more than a decade of application in drinking water research, FCM methodology is optimised and established for routine application, supported by a considerable amount of data from multiple full-scale studies. Bacterial cell concentrations obtained by FCM enable quantification of the entire bacterial community instead of the minute fraction of cultivable bacteria detected with HPC (typically < 1% of all bacteria). FCM measurements are reproducible with relative standard deviations below 3% and can be available within 15 min of samples arriving in the laboratory. High throughput sample processing and complete automation are feasible and FCM analysis is arguably less expensive than HPC when measuring more than 15 water samples per day, depending on the laboratory and selected staining procedure(s). Moreover, many studies have shown FCM total (TCC) and intact (ICC) cell concentrations to be reliable and robust process variables, responsive to changes in the bacterial abundance and relevant for characterising and monitoring drinking water treatment and distribution systems. The purpose of this critical review is to initiate a constructive discussion on whether FCM could replace HPC in routine water quality monitoring. We argue that FCM provides a faster, more descriptive and more representative quantification of bacterial abundance in drinking water. Copyright © 2017 Elsevier Ltd. All rights reserved.

IP-FCM measures physiologic protein-protein interactions modulated by signal transduction and small-molecule drug inhibition.

PubMed

Smith, Stephen E P; Bida, Anya T; Davis, Tessa R; Sicotte, Hugues; Patterson, Steven E; Gil, Diana; Schrum, Adam G

2012-01-01

Protein-protein interactions (PPI) mediate the formation of intermolecular networks that control biological signaling. For this reason, PPIs are of outstanding interest in pharmacology, as they display high specificity and may represent a vast pool of potentially druggable targets. However, the study of physiologic PPIs can be limited by conventional assays that often have large sample requirements and relatively low sensitivity. Here, we build on a novel method, immunoprecipitation detected by flow cytometry (IP-FCM), to assess PPI modulation during either signal transduction or pharmacologic inhibition by two different classes of small-molecule compounds. First, we showed that IP-FCM can detect statistically significant differences in samples possessing a defined PPI change as low as 10%. This sensitivity allowed IP-FCM to detect a PPI that increases transiently during T cell signaling, the antigen-inducible interaction between ZAP70 and the T cell antigen receptor (TCR)/CD3 complex. In contrast, IP-FCM detected no ZAP70 recruitment when T cells were stimulated with antigen in the presence of the src-family kinase inhibitor, PP2. Further, we tested whether IP-FCM possessed sufficient sensitivity to detect the effect of a second, rare class of compounds called SMIPPI (small-molecule inhibitor of PPI). We found that the first-generation non-optimized SMIPPI, Ro-26-4550, inhibited the IL-2:CD25 interaction detected by IP-FCM. This inhibition was detectable using either a recombinant CD25-Fc chimera or physiologic full-length CD25 captured from T cell lysates. Thus, we demonstrate that IP-FCM is a sensitive tool for measuring physiologic PPIs that are modulated by signal transduction and pharmacologic inhibition.

Finite cover method with mortar elements for elastoplasticity problems

NASA Astrophysics Data System (ADS)

Kurumatani, M.; Terada, K.

2005-06-01

Finite cover method (FCM) is extended to elastoplasticity problems. The FCM, which was originally developed under the name of manifold method, has recently been recognized as one of the generalized versions of finite element methods (FEM). Since the mesh for the FCM can be regular and squared regardless of the geometry of structures to be analyzed, structural analysts are released from a burdensome task of generating meshes conforming to physical boundaries. Numerical experiments are carried out to assess the performance of the FCM with such discretization in elastoplasticity problems. Particularly to achieve this accurately, the so-called mortar elements are introduced to impose displacement boundary conditions on the essential boundaries, and displacement compatibility conditions on material interfaces of two-phase materials or on joint surfaces between mutually incompatible meshes. The validity of the mortar approximation is also demonstrated in the elastic-plastic FCM.

High porous bio-nanocarbons prepared by carbonization and NaOH activation of polysaccharides for electrode material of EDLC

NASA Astrophysics Data System (ADS)

Takeuchi, Kenji; Fujishige, Masatsugu; Ishida, Nobuaki; Kunieda, Yoshihiro; Kato, Yosuke; Tanaka, Yusuke; Ochi, Toshiyuki; Shirotori, Hisashi; Uzuhashi, Yuji; Ito, Suguru; Oshida, Kyo-ichi; Endo, Morinobu

2018-07-01

Carbonization and post-activation of polysaccharides (utilized as food residue) created new bio-nanocarbons for the electrode of electric double layer capacitors (EDLC). Large specific capacitance (46.1 F/g, 26.4 F/cm3) and high rate performance was confirmed under optimized conditions of carbonization temperature (600 °C) and supplied amount of sodium hydroxide in NaOH-activation process (250 wt %). The capacitance and rate performance were larger than the reported values, 42.9 F/g, 19.7 F/cm3 of currently used activated carbon MSP-20. The feature that NaOH is usable as the activation agent, instead of KOH, is advantageous for reducing the cost of EDLC.

Application of fuzzy C-Means Algorithm for Determining Field of Interest in Information System Study STTH Medan

NASA Astrophysics Data System (ADS)

Rahman Syahputra, Edy; Agustina Dalimunthe, Yulia; Irvan

2017-12-01

Many students are confused in choosing their own field of specialization, ultimately choosing areas of specialization that are incompatible with a variety of reasons such as just following a friend or because of the area of interest of many choices without knowing whether they have Competencies in the chosen field of interest. This research aims to apply Clustering method with Fuzzy C-means algorithm to classify students in the chosen interest field. The Fuzzy C-Means algorithm is one of the easiest and often used algorithms in data grouping techniques because it makes efficient estimates and does not require many parameters. Several studies have led to the conclusion that the Fuzzy C-Means algorithm can be used to group data based on certain attributes. In this research will be used Fuzzy C-Means algorithm to classify student data based on the value of core subjects in the selection of specialization field. This study also tested the accuracy of the Fuzzy C-Means algorithm in the determination of interest area. The study was conducted on the STT-Harapan Medan Information System Study program, and the object of research is the value of all students of STT-Harapan Medan Information System Study Program 2012. From this research, it is expected to get the specialization field, according to the students' ability based on the prerequisite principal value.

The feasibility of automated online flow cytometry for in-situ monitoring of microbial dynamics in aquatic ecosystems

PubMed Central

Besmer, Michael D.; Weissbrodt, David G.; Kratochvil, Bradley E.; Sigrist, Jürg A.; Weyland, Mathias S.; Hammes, Frederik

2014-01-01

Fluorescent staining coupled with flow cytometry (FCM) is often used for the monitoring, quantification and characterization of bacteria in engineered and environmental aquatic ecosystems including seawater, freshwater, drinking water, wastewater, and industrial bioreactors. However, infrequent grab sampling hampers accurate characterization and subsequent understanding of microbial dynamics in all of these ecosystems. A logic technological progression is high throughput and full automation of the sampling, staining, measurement, and data analysis steps. Here we assess the feasibility and applicability of automated FCM by means of actual data sets produced with prototype instrumentation. As proof-of-concept we demonstrate examples of microbial dynamics in (i) flowing tap water from a municipal drinking water supply network and (ii) river water from a small creek subject to two rainfall events. In both cases, automated measurements were done at 15-min intervals during 12–14 consecutive days, yielding more than 1000 individual data points for each ecosystem. The extensive data sets derived from the automated measurements allowed for the establishment of baseline data for each ecosystem, as well as for the recognition of daily variations and specific events that would most likely be missed (or miss-characterized) by infrequent sampling. In addition, the online FCM data from the river water was combined and correlated with online measurements of abiotic parameters, showing considerable potential for a better understanding of cause-and-effect relationships in aquatic ecosystems. Although several challenges remain, the successful operation of an automated online FCM system and the basic interpretation of the resulting data sets represent a breakthrough toward the eventual establishment of fully automated online microbiological monitoring technologies. PMID:24917858

Bleaching response of Symbiodinium (zooxanthellae): determination by flow cytometry.

PubMed

Lee, Co Sin; Yeo, Yin Sheng Wilson; Sin, Tsai Min

2012-10-01

Coral bleaching is of increasing concern to reef management and stakeholders. Thus far, quantification of coral bleaching tends to be heavily reliant on the enumeration of zooxanthellae, with less emphasis on assessment of photosynthetic or physiological condition, these being often assessed separately by techniques such as liquid chromatography. Traditional methods of enumeration using microscopy are time consuming, subjected to low precision and great observer error. In this study, we presented a method for the distinction of physoiological condition and rapid enumeration of zooxanthellae using flow cytometry (FCM). Microscopy verified that healthy looking/live versus damaged/dead zooxanthellae could be reliably and objectively distinguished and counted by FCM on the basis of red and green fluorescence and light scatter. Excellent correlations were also determined between FCM and microscopy estimates of cell concentrations of fresh zooxanthellae isolates from Pocillopora damicornis. The relative intensities of chlorophyll and β-carotene fluorescences were shown to be important in understanding the results of increased cell counts in freshly isolated zooxanthellae experimentally exposed to high temperatures (34, 36, and 38°C) over 24 h, with ambient temperature (29°C) used as controls. The ability to simultaneously identify and enumerate subpopulations of different physiological states in the same sample provides an enormous advantage in not just determining bleaching responses, but elucidating adaptive response and mechanisms for tolerance. Therefore, this approach might provide a rapid, convenient, and reproducible methodology for climate change studies and reef management programs. Copyright © 2012 International Society for Advancement of Cytometry.

Introduction of a New Diagnostic Method for Breast Cancer Based on Fine Needle Aspiration (FNA) Test Data and Combining Intelligent Systems

PubMed Central

Fiuzy, Mohammad; Haddadnia, Javad; Mollania, Nasrin; Hashemian, Maryam; Hassanpour, Kazem

2012-01-01

Background Accurate Diagnosis of Breast Cancer is of prime importance. Fine Needle Aspiration test or "FNA”, which has been used for several years in Europe, is a simple, inexpensive, noninvasive and accurate technique for detecting breast cancer. Expending the suitable features of the Fine Needle Aspiration results is the most important diagnostic problem in early stages of breast cancer. In this study, we introduced a new algorithm that can detect breast cancer based on combining artificial intelligent system and Fine Needle Aspiration (FNA). Methods We studied the Features of Wisconsin Data Base Cancer which contained about 569 FNA test samples (212 patient samples (malignant) and 357 healthy samples (benign)). In this research, we combined Artificial Intelligence Approaches, such as Evolutionary Algorithm (EA) with Genetic Algorithm (GA), and also used Exact Classifier Systems (here by Fuzzy C-Means (FCM)) to separate malignant from benign samples. Furthermore, we examined artificial Neural Networks (NN) to identify the model and structure. This research proposed a new algorithm for an accurate diagnosis of breast cancer. Results According to Wisconsin Data Base Cancer (WDBC) data base, 62.75% of samples were benign, and 37.25% were malignant. After applying the proposed algorithm, we achieved high detection accuracy of about "96.579%” on 205 patients who were diagnosed as having breast cancer. It was found that the method had 93% sensitivity, 73% specialty, 65% positive predictive value, and 95% negative predictive value, respectively. If done by experts, Fine Needle Aspiration (FNA) can be a reliable replacement for open biopsy in palpable breast masses. Evaluation of FNA samples during aspiration can decrease insufficient samples. FNA can be the first line of diagnosis in women with breast masses, at least in deprived regions, and may increase health standards and clinical supervision of patients. Conclusion Such a smart, economical, non-invasive, rapid and accurate system can be introduced as a useful diagnostic system for comprehensive treatment of breast cancer. Another advantage of this method is the possibility of diagnosing breast abnormalities. If done by experts, FNA can be a reliable replacement for open biopsy in palpable breast masses. Evaluation of FNA samples during aspiration can decrease insufficient samples. PMID:25352966

Synthetic CT for MRI-based liver stereotactic body radiotherapy treatment planning

NASA Astrophysics Data System (ADS)

Bredfeldt, Jeremy S.; Liu, Lianli; Feng, Mary; Cao, Yue; Balter, James M.

2017-04-01

A technique for generating MRI-derived synthetic CT volumes (MRCTs) is demonstrated in support of adaptive liver stereotactic body radiation therapy (SBRT). Under IRB approval, 16 subjects with hepatocellular carcinoma were scanned using a single MR pulse sequence (T1 Dixon). Air-containing voxels were identified by intensity thresholding on T1-weighted, water and fat images. The envelope of the anterior vertebral bodies was segmented from the fat image and fuzzy-C-means (FCM) was used to classify each non-air voxel as mid-density, lower-density, bone, or marrow in the abdomen, with only bone and marrow classified within the vertebral body envelope. MRCT volumes were created by integrating the product of the FCM class probability with its assigned class density for each voxel. MRCTs were deformably aligned with corresponding planning CTs and 2-ARC-SBRT-VMAT plans were optimized on MRCTs. Fluence was copied onto the CT density grids, dose recalculated, and compared. The liver, vertebral bodies, kidneys, spleen and cord had median Hounsfield unit differences of less than 60. Median target dose metrics were all within 0.1 Gy with maximum differences less than 0.5 Gy. OAR dose differences were similarly small (median: 0.03 Gy, std:0.26 Gy). Results demonstrate that MRCTs derived from a single abdominal imaging sequence are promising for use in SBRT dose calculation.

Genome size of Alexandrium catenella and Gracilariopsis lemaneiformis estimated by flow cytometry

NASA Astrophysics Data System (ADS)

Du, Qingwei; Sui, Zhenghong; Chang, Lianpeng; Wei, Huihui; Liu, Yuan; Mi, Ping; Shang, Erlei; Zeeshan, Niaz; Que, Zhou

2016-08-01

Flow cytometry (FCM) technique has been widely applied to estimating the genome size of various higher plants. However, there is few report about its application in algae. In this study, an optimized procedure of FCM was exploited to estimate the genome size of two eukaryotic algae. For analyzing Alexandrium catenella, an important red tide species, the whole cell instead of isolated nucleus was studied, and chicken erythrocytes were used as an internal reference. The genome size of A. catenella was estimated to be 56.48 ± 4.14 Gb (1C), approximately nineteen times larger than that of human genome. For analyzing Gracilariopsis lemaneiformis, an important economical red alga, the purified nucleus was employed, and Arabidopsis thaliana and Chondrus crispus were used as internal references, respectively. The genome size of Gp. lemaneiformis was 97.35 ± 2.58 Mb (1C) and 112.73 ± 14.00 Mb (1C), respectively, depending on the different internal references. The results of this research will promote the related studies on the genomics and evolution of these two species.

Three-dimensional DNA image cytometry by optical projection tomographic microscopy for early cancer diagnosis.

PubMed

Agarwal, Nitin; Biancardi, Alberto M; Patten, Florence W; Reeves, Anthony P; Seibel, Eric J

2014-04-01

Aneuploidy is typically assessed by flow cytometry (FCM) and image cytometry (ICM). We used optical projection tomographic microscopy (OPTM) for assessing cellular DNA content using absorption and fluorescence stains. OPTM combines some of the attributes of both FCM and ICM and generates isometric high-resolution three-dimensional (3-D) images of single cells. Although the depth of field of the microscope objective was in the submicron range, it was extended by scanning the objective's focal plane. The extended depth of field image is similar to a projection in a conventional x-ray computed tomography. These projections were later reconstructed using computed tomography methods to form a 3-D image. We also present an automated method for 3-D nuclear segmentation. Nuclei of chicken, trout, and triploid trout erythrocyte were used to calibrate OPTM. Ratios of integrated optical densities extracted from 50 images of each standard were compared to ratios of DNA indices from FCM. A comparison of mean square errors with thionin, hematoxylin, Feulgen, and SYTOX green was done. Feulgen technique was preferred as it showed highest stoichiometry, least variance, and preserved nuclear morphology in 3-D. The addition of this quantitative biomarker could further strengthen existing classifiers and improve early diagnosis of cancer using 3-D microscopy.

The relative value of cytometry and cytology in the management of bladder cancer: the Memorial Sloan-Kettering Cancer Center experience.

PubMed

Badalament, R A; Fair, W R; Whitmore, W F; Melamed, M R

1988-02-01

The flow cytometric studies presented herein are based almost entirely on DNA measurements and represent an early application of this diagnostic test. Nevertheless, the MSKCC experience with FCM has demonstrated that it is technically feasible and clinically useful. The sensitivity of FCM is in the range of 80% to 85% overall, and is superior to that of conventional voided or bladder wash cytology. In the absence of inflammation secondary to infection, calculi, or intravesical agents such as BCG, the specificity is greater than 90%. In the presence of inflammation, FCM appears to be less specific than conventional cytology. A potential advantage of FCM over cytology is the quantitative nature of the examination permitting comparisons of sequential examinations. Also, there are refinements in technique that hold promise of increasing the accuracy or clinical usefulness of FCM, eg, the joint measurements of DNA and differentiation antigens defined by monoclonal antibodies. Yet, despite the current and potential advantages of FCM, voided urinary cytology continues to be the procedure of choice for detection and monitoring urothelial carcinoma, not only because of our long experience and better understanding of this test, but because of its proven high specificity, because it is noninvasive, widely available, and may help to detect upper tract or urethral tumors.

Use of bioassays to assess hazard of food contact material extracts: State of the art.

PubMed

Severin, Isabelle; Souton, Emilie; Dahbi, Laurence; Chagnon, Marie Christine

2017-07-01

This review focuses on the use of in vitro bioassays for the hazard assessment of food contact materials (FCM) as a relevant strategy, in complement to analytical methods. FCM may transfer constituents to foods, not always detected by analytical chemistry, resulting in low but measurable human exposures. Testing FCM extracts with bioassays represents the biological response of a combination of substances, able to be released from the finished materials. Furthermore, this approach is particularly useful regarding the current risk assessment challenges with unpredicted/unidentified non-intentionally added substances (NIAS) that can be leached from the FCM in the food. Bioassays applied to assess hazard of different FCM types are described for, to date, the toxicological endpoints able to be expressed at low levels; cytotoxicity, genotoxicity and endocrine disruption potential. The bioassay strengths and relative key points needed to correctly use and improve the performance of bioassays for an additional FCM risk assessment is developed. This review compiles studies showing that combining both chemical and toxicological analyses presents a very promising and pragmatic tool for identifying new undesirable NIAS (not predicted) which can represent a great part of the migrating substances and/or "cocktail effect". Copyright © 2017 Elsevier Ltd. All rights reserved.

In vivo fluorescence confocal microscopy: indocyanine green enhances the contrast of epidermal and dermal structures

NASA Astrophysics Data System (ADS)

Skvara, Hans; Kittler, Harald; Schmid, Johannes A.; Plut, Ulrike; Jonak, Constanze

2011-09-01

In recent years, in vivo skin imaging devices have been successfully implemented in skin research as well as in clinical routine. Of particular importance is the use of reflectance confocal microscopy (RCM) and fluorescence confocal microscopy (FCM) that enable visualization of the tissue with a resolution comparable to histology. A newly developed commercially available multi-laser device in which both technologies are integrated now offers the possibility to directly compare RCM with FCM. The fluorophore indocyanine green (ICG) was intradermally injected into healthy forearm skin of 10 volunteers followed by in vivo imaging at various time points. In the epidermis, accurate assessment of cell morphology with FCM was supplemented by identification of pigmented cells and structures with RCM. In dermal layers, only with FCM connective tissue fibers were clearly contoured down to a depth of more than 100 μm. The fluorescent signal still provided a favorable image contrast 24 and 48 hours after injection. Subsequently, ICG was applied to different types of skin diseases (basal cell carcinoma, actinic keratosis, seborrhoeic keratosis, and psoriasis) in order to demonstrate the diagnostic benefit of FCM when directly compared with RCM. Our data suggest a great impact of FCM in combination with ICG on clinical and experimental dermatology in the future.

Adrenal activity in maned wolves is higher on farmlands and park boundaries than within protected areas.

PubMed

Spercoski, Katherinne M; Morais, Rosana N; Morato, Ronaldo G; de Paula, Rogério C; Azevedo, Fernanda C; May-Júnior, Joares A; Santos, Jean P; Reghelin, Angela L; Wildt, David E; Songsasen, Nucharin

2012-11-01

In this study we measured excreted fecal corticoid metabolites (FCM) in maned wolves (Chrysocyon brachyurus) living within a protected reserve, on farmlands or in a boundary zone between the two habitats, and determined the impacts of season and reproductive status on adrenal activity. Feces were collected within a national park (n=191 samples), a park boundary zone (n=39) and on nearby farmlands (n=27), processed and analyzed by enzyme immunoassay. FCM amounts from samples collected on farmlands were higher (P<0.05) than in those collected inside the reserve and from the boundary zone. In relation to seasonality, FCM were elevated (P<0.05) in spring (September-November) when wolf pairs were raising young. We then divided the samples collected during breeding season (March-August) into cycling females and male/non-cycling females based on fecal progesterone: fecal testosterone ratio. FCM concentrations of the former collected inside the park were higher than (P<0.05) than the latter group. However, there were no differences in FCM levels between the two groups for samples collected in the boundary zone and on farmlands. Furthermore, FCM concentrations of male/non-cycling females samples collected on farmlands were 2- to 5-fold higher (P<0.05) than in counterparts collected inside the park. The consistently high FCM concentrations in samples collected on farmlands indicate that, in addition to seasonality, gender and reproductive status, anthropogenic pressures also contribute to elevating adrenal steroid for individuals living in altered habitat. Copyright © 2012 Elsevier Inc. All rights reserved.

Accurate live and dead bacterial cell enumeration using flow cytometry (Conference Presentation)

NASA Astrophysics Data System (ADS)

Ou, Fang; McGoverin, Cushla; Swift, Simon; Vanholsbeeck, Frédérique

2017-03-01

Flow cytometry (FCM) is based on the detection of scattered light and fluorescence to identify cells with particular characteristics of interest. However most FCM cannot precisely control the flow through its interrogation point and hence the volume and concentration of the sample cannot be immediately obtained. The easiest, most reliable and inexpensive way of obtaining absolute counts with FCM is by using reference beads. We investigated a method of using FCM with reference beads to measure live and dead bacterial concentration over the range of 106 to 108 cells/mL and ratio varying from 0 to 100%. We believe we are the first to use this method for such a large cell concentration range while also establishing the effect of varying the live/dead bacteria ratios. Escherichia coli solutions with differing ratios of live:dead cells were stained with fluorescent dyes SYTO 9 and propidium iodide (PI), which label live and dead cells, respectively. Samples were measured using a LSR II Flow Cytometer (BD Biosciences); using 488 nm excitation with 20 mW power. Both SYTO 9 and PI fluorescence were collected and threshold was set to side scatter. Traditional culture-based plate count was done in parallel to the FCM analysis. The concentration of live bacteria from FCM was compared to that obtained by plate counts. Preliminary results show that the concentration of live bacteria obtained by FCM and plate counts correlate well with each other and indicates this may be extended to a wider concentration range or for studying other cell characteristics.

Combining flow cytometry and 16S rRNA gene pyrosequencing: a promising approach for drinking water monitoring and characterization.

PubMed

Prest, E I; El-Chakhtoura, J; Hammes, F; Saikaly, P E; van Loosdrecht, M C M; Vrouwenvelder, J S

2014-10-15

The combination of flow cytometry (FCM) and 16S rRNA gene pyrosequencing data was investigated for the purpose of monitoring and characterizing microbial changes in drinking water distribution systems. High frequency sampling (5 min intervals for 1 h) was performed at the outlet of a treatment plant and at one location in the full-scale distribution network. In total, 52 bulk water samples were analysed with FCM, pyrosequencing and conventional methods (adenosine-triphosphate, ATP; heterotrophic plate count, HPC). FCM and pyrosequencing results individually showed that changes in the microbial community occurred in the water distribution system, which was not detected with conventional monitoring. FCM data showed an increase in the total bacterial cell concentrations (from 345 ± 15 × 10(3) to 425 ± 35 × 10(3) cells mL(-1)) and in the percentage of intact bacterial cells (from 39 ± 3.5% to 53 ± 4.4%) during water distribution. This shift was also observed in the FCM fluorescence fingerprints, which are characteristic of each water sample. A similar shift was detected in the microbial community composition as characterized with pyrosequencing, showing that FCM and genetic fingerprints are congruent. FCM and pyrosequencing data were subsequently combined for the calculation of cell concentration changes for each bacterial phylum. The results revealed an increase in cell concentrations of specific bacterial phyla (e.g., Proteobacteria), along with a decrease in other phyla (e.g., Actinobacteria), which could not be concluded from the two methods individually. The combination of FCM and pyrosequencing methods is a promising approach for future drinking water quality monitoring and for advanced studies on drinking water distribution pipeline ecology. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

Berndt, Alexander, E-mail: alexander.berndt@med.uni-jena.de; Büttner, Robert, E-mail: Robert-Buettner@gmx.net; Gühne, Stefanie, E-mail: stefanie_guehne@gmx.net

Crosstalk between carcinoma associated fibroblasts (CAFs) and oral squamous cell carcinoma (OSCC) cells is suggested to mediate phenotype transition of cancer cells as a prerequisite for tumour progression, to predict patients’ outcome, and to influence the efficacy of EGFR inhibitor therapies. Here we investigate the influence of activated fibroblasts as a model for CAFs on phenotype and EGFR signalling in OSCC cells in vitro. For this, immortalised hTERT-BJ1 fibroblasts were activated with TGFβ1 and PDGFAB to generate a myofibroblast or proliferative phenotype, respectively. Conditioned media (FCM{sub TGF}, FCM{sub PDGF}) were used to stimulate PE/CA-PJ15 OSCC cells. Results were compared tomore » the effect of conditioned media of non-stimulated fibroblasts (FCM{sub B}). FCM{sub TGF} stimulation leads to an up-regulation of vimentin in the OSCC cells and an enhancement of invasive behaviour, indicating EMT-like effects. Similarly, FCM{sub TGF}≫FCM{sub PDGF} induced up-regulation of EGFR, but not of ErbB2/ErbB3. In addition, we detected an increase in basal activities of ERK, PI3K/Akt and Stat3 (FCM{sub TGF}>FCM{sub PDGF}) accompanied by protein interaction of vimentin with pERK. These effects are correlated with an increased proliferation. In summary, our results suggest that the activated myofibroblast phenotype provides soluble factors which are able to induce EMT-like phenomena and to increase EGFR signalling as well as cell proliferation in OSCC cells. Our results indicate a possible influence of activated myofibroblasts on EGFR-inhibitor therapy. Therefore, CAFs may serve as promising novel targets for combined therapy strategies. - Highlights: • A cell culture model for cancer associated fibroblasts is described. • The mutual interaction with OSCC cells leads to up-regulation of EGFR in tumour cells. • mCAF induces EGFR downstream signalling with increased proliferation in OSCC. • Erk activation is associated with protein interaction with vimentin as sign of EMT. • Results qualify CAF as promising new therapeutic targets in OSCC.« less

Flow cytometry for immediate follow-up of drinking water networks after maintenance.

PubMed

Van Nevel, Sam; Buysschaert, Benjamin; De Roy, Karen; De Gusseme, Bart; Clement, Lieven; Boon, Nico

2017-03-15

Drinking water networks need maintenance every once in a while, either planned interventions or emergency repairs. When this involves opening of the water pipes, precautionary measures need to be taken to avoid contamination of the drinking water at all time. Drinking water suppliers routinely apply plating for faecal indicator organisms as quality control in such a situation. However, this takes at least 21 h of waiting time, which can be crucial when dealing with major supply pipes. A combination of flow cytometric (FCM) bacterial cell counts with FCM fingerprinting techniques is proposed in this study as a fast and sensitive additional technique. In three full scale situations, major supply pipes with 400-1050 mm diameter were emptied for maintenance, shock-chlorinated and flushed with large amounts of clean drinking water before taking back in operation. FCM measurements of the discharged flushing water revealed fast lowering and stabilizing bacterial concentrations once flushing is initiated. Immediate comparison with clean reference drinking water used for flushing was done, and the moment when both waters had similar bacterial concentrations was considered as the endpoint of the necessary flushing works. This was usually after 2-4 h of flushing. FCM fingerprinting, based on both bacteria and FCM background, was used as additional method to verify how similar flushing and reference samples were and yielded similar results. The FCM approved samples were several hours later approved as well by the drinking water supplier after plating and incubation for total Coliforms and Enterococci. These were used as decisive control to set the pipes back in operation. FCM proved to be a more conservative test than plating, yet it yielded immediate results. Application of these FCM methods can therefore avoid long unnecessary waiting times and large drinking water losses. Copyright © 2016 Elsevier Ltd. All rights reserved.

Assessment of Possible Cycle Lengths for Fully-Ceramic Micro-Encapsulated Fuel-Based Light Water Reactor Concepts

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

R. Sonat Sen; Michael A. Pope; Abderrafi M. Ougouag

2012-04-01

The tri-isotropic (TRISO) fuel developed for High Temperature reactors is known for its extraordinary fission product retention capabilities [1]. Recently, the possibility of extending the use of TRISO particle fuel to Light Water Reactor (LWR) technology, and perhaps other reactor concepts, has received significant attention [2]. The Deep Burn project [3] currently focuses on once-through burning of transuranic fissile and fissionable isotopes (TRU) in LWRs. The fuel form for this purpose is called Fully-Ceramic Micro-encapsulated (FCM) fuel, a concept that borrows the TRISO fuel particle design from high temperature reactor technology, but uses SiC as a matrix material rather thanmore » graphite. In addition, FCM fuel may also use a cladding made of a variety of possible material, again including SiC as an admissible choice. The FCM fuel used in the Deep Burn (DB) project showed promising results in terms of fission product retention at high burnup values and during high-temperature transients. In the case of DB applications, the fuel loading within a TRISO particle is constituted entirely of fissile or fissionable isotopes. Consequently, the fuel was shown to be capable of achieving reasonable burnup levels and cycle lengths, especially in the case of mixed cores (with coexisting DB and regular LWR UO2 fuels). In contrast, as shown below, the use of UO2-only FCM fuel in a LWR results in considerably shorter cycle length when compared to current-generation ordinary LWR designs. Indeed, the constraint of limited space availability for heavy metal loading within the TRISO particles of FCM fuel and the constraint of low (i.e., below 20 w/0) 235U enrichment combine to result in shorter cycle lengths compared to ordinary LWRs if typical LWR power densities are also assumed and if typical TRISO particle dimensions and UO2 kernels are specified. The primary focus of this summary is on using TRISO particles with up to 20 w/0 enriched uranium kernels loaded in Pressurized Water Reactor (PWR) assemblies. In addition to consideration of this 'naive' use of TRISO fuel in LWRs, several refined options are briefly examined and others are identified for further consideration including the use of advanced, high density fuel forms and larger kernel diameters and TRISO packing fractions. The combination of 800 {micro}m diameter kernels of 20% enriched UN and 50% TRISO packing fraction yielded reactivity sufficient to achieve comparable burnup to present-day PWR fuel.« less

Fuzzy-C-Means Clustering Based Segmentation and CNN-Classification for Accurate Segmentation of Lung Nodules

PubMed

K, Jalal Deen; R, Ganesan; A, Merline

2017-07-27

Objective: Accurate segmentation of abnormal and healthy lungs is very crucial for a steadfast computer-aided disease diagnostics. Methods: For this purpose a stack of chest CT scans are processed. In this paper, novel methods are proposed for segmentation of the multimodal grayscale lung CT scan. In the conventional methods using Markov–Gibbs Random Field (MGRF) model the required regions of interest (ROI) are identified. Result: The results of proposed FCM and CNN based process are compared with the results obtained from the conventional method using MGRF model. The results illustrate that the proposed method can able to segment the various kinds of complex multimodal medical images precisely. Conclusion: However, in this paper, to obtain an exact boundary of the regions, every empirical dispersion of the image is computed by Fuzzy C-Means Clustering segmentation. A classification process based on the Convolutional Neural Network (CNN) classifier is accomplished to distinguish the normal tissue and the abnormal tissue. The experimental evaluation is done using the Interstitial Lung Disease (ILD) database. Creative Commons Attribution License

Fuzzy-C-Means Clustering Based Segmentation and CNN-Classification for Accurate Segmentation of Lung Nodules

PubMed Central

K, Jalal Deen; R, Ganesan; A, Merline

2017-01-01

Objective: Accurate segmentation of abnormal and healthy lungs is very crucial for a steadfast computer-aided disease diagnostics. Methods: For this purpose a stack of chest CT scans are processed. In this paper, novel methods are proposed for segmentation of the multimodal grayscale lung CT scan. In the conventional methods using Markov–Gibbs Random Field (MGRF) model the required regions of interest (ROI) are identified. Result: The results of proposed FCM and CNN based process are compared with the results obtained from the conventional method using MGRF model. The results illustrate that the proposed method can able to segment the various kinds of complex multimodal medical images precisely. Conclusion: However, in this paper, to obtain an exact boundary of the regions, every empirical dispersion of the image is computed by Fuzzy C-Means Clustering segmentation. A classification process based on the Convolutional Neural Network (CNN) classifier is accomplished to distinguish the normal tissue and the abnormal tissue. The experimental evaluation is done using the Interstitial Lung Disease (ILD) database. PMID:28749127

A graph-based watershed merging using fuzzy C-means and simulated annealing for image segmentation

NASA Astrophysics Data System (ADS)

Vadiveloo, Mogana; Abdullah, Rosni; Rajeswari, Mandava

2015-12-01

In this paper, we have addressed the issue of over-segmented regions produced in watershed by merging the regions using global feature. The global feature information is obtained from clustering the image in its feature space using Fuzzy C-Means (FCM) clustering. The over-segmented regions produced by performing watershed on the gradient of the image are then mapped to this global information in the feature space. Further to this, the global feature information is optimized using Simulated Annealing (SA). The optimal global feature information is used to derive the similarity criterion to merge the over-segmented watershed regions which are represented by the region adjacency graph (RAG). The proposed method has been tested on digital brain phantom simulated dataset to segment white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF) soft tissues regions. The experiments showed that the proposed method performs statistically better, with average of 95.242% regions are merged, than the immersion watershed and average accuracy improvement of 8.850% in comparison with RAG-based immersion watershed merging using global and local features.

Reactor physics behavior of transuranic-bearing TRISO-particle fuel in a pressurized water reactor

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

Pope, M. A.; Sen, R. S.; Ougouag, A. M.

2012-07-01

Calculations have been performed to assess the neutronic behavior of pins of Fully-Ceramic Micro-encapsulated (FCM) fuel in otherwise-conventional Pressurized Water Reactor (PWR) fuel pins. The FCM fuel contains transuranic (TRU) - only oxide fuel in tri-isotropic (TRISO) particles with the TRU loading coming from the spent fuel of a conventional LWR after 5 years of cooling. Use of the TRISO particle fuel would provide an additional barrier to fission product release in the event of cladding failure. Depletion calculations were performed to evaluate reactivity-limited burnup of the TRU-only FCM fuel. These calculations showed that due to relatively little space availablemore » for fuel, the achievable burnup with these pins alone is quite small. Various reactivity parameters were also evaluated at each burnup step including moderator temperature coefficient (MTC), Doppler, and soluble boron worth. These were compared to reference UO{sub 2} and MOX unit cells. The TRU-only FCM fuel exhibits degraded MTC and Doppler coefficients relative to UO{sub 2} and MOX. Also, the reactivity effects of coolant voiding suggest that the behavior of this fuel would be similar to a MOX fuel of very high plutonium fraction, which are known to have positive void reactivity. In general, loading of TRU-only FCM fuel into an assembly without significant quantities of uranium presents challenges to the reactor design. However, if such FCM fuel pins are included in a heterogeneous assembly alongside LEU fuel pins, the overall reactivity behavior would be dominated by the uranium pins while attractive TRU destruction performance levels in the TRU-only FCM fuel pins is retained. From this work, it is concluded that use of heterogeneous assemblies such as these appears feasible from a preliminary reactor physics standpoint. (authors)« less

Reactor Physics Behavior of Transuranic-Bearing TRISO-Particle Fuel in a Pressurized Water Reactor

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

Michael A. Pope; R. Sonat Sen; Abderrafi M. Ougouag

2012-04-01

Calculations have been performed to assess the neutronic behavior of pins of Fully-Ceramic Micro-encapsulated (FCM) fuel in otherwise-conventional Pressurized Water Reactor (PWR) fuel pins. The FCM fuel contains transuranic (TRU)-only oxide fuel in tri-isotropic (TRISO) particles with the TRU loading coming from the spent fuel of a conventional LWR after 5 years of cooling. Use of the TRISO particle fuel would provide an additional barrier to fission product release in the event of cladding failure. Depletion calculations were performed to evaluate reactivity-limited burnup of the TRU-only FCM fuel. These calculations showed that due to relatively little space available for fuel,more » the achievable burnup with these pins alone is quite small. Various reactivity parameters were also evaluated at each burnup step including moderator temperature coefficient (MTC), Doppler, and soluble boron worth. These were compared to reference UO{sub 2} and MOX unit cells. The TRU-only FCM fuel exhibits degraded MTC and Doppler coefficients relative to UO{sub 2} and MOX. Also, the reactivity effects of coolant voiding suggest that the behavior of this fuel would be similar to a MOX fuel of very high plutonium fraction, which are known to have positive void reactivity. In general, loading of TRU-only FCM fuel into an assembly without significant quantities of uranium presents challenges to the reactor design. However, if such FCM fuel pins are included in a heterogeneous assembly alongside LEU fuel pins, the overall reactivity behavior would be dominated by the uranium pins while attractive TRU destruction performance levels in the TRU-only FCM fuel pins is. From this work, it is concluded that use of heterogeneous assemblies such as these appears feasible from a preliminary reactor physics standpoint.« less

Self-assessment of competencies in dental education in Germany - a multicentred survey.

PubMed

Bitter, K; Rüttermann, S; Lippmann, M; Hahn, P; Giesler, M

2016-11-01

The aim was to assess the competencies of undergraduate dental students in Germany in the domains team competence, communicative competence, learning competence and scholarship. The survey was conducted at 11 dental schools that are equally distributed all over Germany. Competencies were assessed with the Freiburg Questionnaire to Assess Competencies in Medicine (FCM). A short version of the FCM was used in this study. This short form included the four domains: team competence (three items), communicative competence (eight items), learning competence (five items) and scholarship (four items). Students had to rate each item twice: first with regard to the respondent's current level of competence and second with regard to the level of competence that respondents think is required by their job. All items were rated on a five-point Likert scale (1 'very much' and 5 'not at all'). Responsible lecturers from all selected dental schools received another questionnaire to answer the questions whether the FCM domain corresponding learning objectives were taught at the respective dental school. A total of 317 undergraduate students from 11 dental schools in their last clinical year participated. The response rate varied between 48% and 92%. Cronbach's α for the FCM scales addressing the current level of competencies ranged from 0.70 to 0.89 and for the scales measuring the presumed level of competencies demanded by their job ranged from 0.72 to 0.82. The mean values of the scales for the assessment of the presumed level of competencies demanded by the job were significantly lower compared to the mean values of the scales for the current level of competencies (P < 0.001 in all analyses). We found large differences between the two levels - in terms of 'standardised response means' (SRM) - in the domains team competence (SRM 1.34), learning competence (SRM 1.27) and communicative competence (SRM 1.18). Overall, the learning objectives that correspond to the assessed domains of competencies were taught to 19.6% completely, to 55.4% partially and to 25% not at all at the participating dental schools. The results of the present survey revealed that the participating students perceived deficiencies in all domains of competencies. These results indicate that the assessed domains are still barely integrated into dental medicine curricula in Germany and that further research in this field is needed. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Results of the randomized phase IIB ARCTIC trial of low-dose rituximab in previously untreated CLL.

PubMed

Howard, D R; Munir, T; McParland, L; Rawstron, A C; Milligan, D; Schuh, A; Hockaday, A; Allsup, D J; Marshall, S; Duncombe, A S; O'Dwyer, J L; Smith, A F; Longo, R; Varghese, A; Hillmen, P

2017-11-01

ARCTIC was a multicenter, randomized-controlled, open, phase IIB non-inferiority trial in previously untreated chronic lymphocytic leukemia (CLL). Conventional frontline therapy in fit patients is fludarabine, cyclophosphamide and rituximab (FCR). The trial hypothesized that including mitoxantrone with low-dose rituximab (FCM-miniR) would be non-inferior to FCR. A total of 200 patients were recruited to assess the primary end point of complete remission (CR) rates according to IWCLL criteria. Secondary end points were progression-free survival (PFS), overall survival (OS), overall response rate, minimal residual disease (MRD) negativity, safety and cost-effectiveness. The trial closed following a pre-planned interim analysis. At final analysis, CR rates were 76 FCR vs 55% FCM-miniR (adjusted odds ratio: 0.37; 95% confidence interval: 0.19-0.73). MRD-negativity rates were 54 FCR vs 44% FCM-miniR. More participants experienced serious adverse reactions with FCM-miniR (49%) compared to FCR (41%). There are no significant differences between the treatment groups for PFS and OS. FCM-miniR is not expected to be cost-effective over a lifetime horizon. In summary, FCM-miniR is less well tolerated than FCR with an inferior response and MRD-negativity rate and increased toxicity, and will not be taken forward into a confirmatory trial. The trial demonstrated that oral FCR yields high response rates compared to historical series with intravenous chemotherapy.

Enumeration of residual white blood cells in leukoreduced blood products: Comparing flow cytometry with a portable microscopic cell counter.

PubMed

Castegnaro, Silvia; Dragone, Patrizia; Chieregato, Katia; Alghisi, Alberta; Rodeghiero, Francesco; Astori, Giuseppe

2016-04-01

Transfusion of blood components is potentially associated to the risk of cell-mediated adverse events and current guidelines require a reduction of residual white blood cells (rWBC) below 1 × 10(6) WBC/unit. The reference method to enumerate rare events is the flow cytometry (FCM). The ADAM-rWBC microscopic cell counter has been proposed as an alternative: it measures leukocytes after their staining with propidium iodide. We have tested the Adam-rWBC for the ability to enumerate rWBC in red blood cells and concentrates. We have validated the flow cytometry (FCM) for linearity, precision accuracy and robustness and then the ADAM-rWBC results have been compared with the FCM. Our data confirm the linearity, accuracy, precision and robustness of the FCM. The ADAM-rWBC has revealed an adequate precision and accuracy. Even if the Bland-Altman analysis of the paired data has indicated that the two systems are comparable, it should be noted that the rWBC values obtained by the ADAM-rWBC were significantly higher compared to FCM. In conclusion, the Adam-rWBC cell counter could represent an alternative where FCM technology expertise is not available, even if the risk that borderline products could be misclassified exists. Copyright © 2015 Elsevier Ltd. All rights reserved.

Developing the fuzzy c-means clustering algorithm based on maximum entropy for multitarget tracking in a cluttered environment

NASA Astrophysics Data System (ADS)

Chen, Xiao; Li, Yaan; Yu, Jing; Li, Yuxing

2018-01-01

For fast and more effective implementation of tracking multiple targets in a cluttered environment, we propose a multiple targets tracking (MTT) algorithm called maximum entropy fuzzy c-means clustering joint probabilistic data association that combines fuzzy c-means clustering and the joint probabilistic data association (PDA) algorithm. The algorithm uses the membership value to express the probability of the target originating from measurement. The membership value is obtained through fuzzy c-means clustering objective function optimized by the maximum entropy principle. When considering the effect of the public measurement, we use a correction factor to adjust the association probability matrix to estimate the state of the target. As this algorithm avoids confirmation matrix splitting, it can solve the high computational load problem of the joint PDA algorithm. The results of simulations and analysis conducted for tracking neighbor parallel targets and cross targets in a different density cluttered environment show that the proposed algorithm can realize MTT quickly and efficiently in a cluttered environment. Further, the performance of the proposed algorithm remains constant with increasing process noise variance. The proposed algorithm has the advantages of efficiency and low computational load, which can ensure optimum performance when tracking multiple targets in a dense cluttered environment.

76 FR 51257 - First-Class Package Service

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-18

... Ground, and Bound Printed Matter prices. * * * * * * * * 2.0 Additional Physical Standards by Class of... ``PRSRT'') First-Class Package'' (or ``PKG'') must be printed as part of; directly below; or to the left... follows:] b. * * * labeling: * * * * * 2. Line 2: ``FC PARCELS 3D.'' [Revise item 4.4c2 by changing ``FCM...

Relationship between DNA ploidy and proliferative cell nuclear antigen index in canine hemangiopericytoma.

PubMed

Kang, Seong-Kwi; Park, Nam-Yong; Cho, Ho-Sung; Shin, Sung-Shik; Kang, Mun-Il; Kim, Sang-Ki; Hyun, Changbaig; Park, In-Chul; Kim, Jong-Tack; Jeong, Cheol; Park, Sung-Hee; Park, Su-Jin; Jeong, Jae-Ho; Kim, You-Jung; Ochiai, Kenji; Umemura, Takashi; Cho, Kyoung-Oh

2006-03-01

The mitotic index is reported to be correlated with recurrence, mean patient survival, and metastasis of canine hemangiopericytoma (CHP). However, to the authors' knowledge, studies investigating the parameters that can predict recurrence or metastasis of CHP with low mitotic index have not been done. To evaluate growth kinetics of CHP with low mitotic index, a retrospective analysis of the proliferative activity by antiproliferative cell nuclear antigen monoclonal antibody and DNA contents by flow cytometry (FCM) was performed with 21 formalin-fixed and paraffin-embedded CHP samples. Of the 21 tumors evaluated by FCM, 6 (26.6%) were aneuploid tumors, and 15 (71.4%) were diploid tumors. There was significant correlation between the PCNA index and ploidy pattern. The diploid group had 39.1 +/- 9.2 PCNA index, whereas the aneuploid group's proliferative cell nuclear antigen (PCNA) index was 63.1 +/- 8.2. The diploid group had mean mitotic index value of 1.140 +/- 0.855, and the aneuploid group had a mean value of 1.067 +/- 0.767. From these results, the CHP samples with low mitotic index were classified into either the aneuploid group with higher PCNA index or the diploid group with lower PCNA index, suggesting that DNA ploidy and proliferative activity may give an indication about malignancy of CHPs with a low mitotic index.

The new generation of intravenous iron: chemistry, pharmacology, and toxicology of ferric carboxymaltose.

PubMed

Funk, Felix; Ryle, Peter; Canclini, Camillo; Neiser, Susann; Geisser, Peter

2010-01-01

An ideal preparation for intravenous iron replacement therapy should balance effectiveness and safety. Compounds that release iron rapidly tend to cause toxicity, while large molecules can induce antibody formation and cause anaphylactic reactions. There is therefore a need for an intravenous iron preparation that delivers appropriate amounts of iron in a readily available form but with minimal side effects and thus with an excellent safety profile. In this paper, a review is given on the chemistry, pharmacology, and toxicology of ferric carboxymaltose (FCM, Ferinject), a stable and robust complex formulated as a colloidal solution with a physiological pH. The complex is gradually taken up mainly from the hepatic reticulo-endothelial system (RES), followed by effective delivery of iron to the endogeneous transport system for the haem synthesis in new erythrocytes, as shown in studies on the pharmacodynamics and pharmacokinetics with radio-labelled FCM. Studies with radio-labelled FCM also demonstrated a barrier function of the placenta and a low transfer of iron into the milk of lactating rats. Safety pharmacology studies indicated a favourable profile with regard to cardiovascular, central nervous, respiratory, and renal toxicity. A high maximum non-lethal dose was demonstrated in the single-dose toxicity studies. Furthermore, based on the No-Observed-Adverse-Effect-Levels (NOAELs) found in repeated-dose toxicity studies and on the cumulative doses administered, FCM has good safety margins. Reproductive and developmental toxicity studies did not reveal any direct or indirect harmful effects. No genotoxic potential was found in in vitro or in vivo studies. Moreover, antigenicity studies showed no cross-reactivity of FMC with anti-dextran antibodies and also suggested that FCM does not possess sensitizing potential. Lastly, no evidence of irritation was found in local tolerance studies with FCM. This excellent toxicity profile and the high effectiveness of FCM allow the administration of high doses as a single infusion or bolus injection, which will enhance the cost-effectiveness and convenience of iron replacement therapy. In conclusion, FCM has many of the characteristics of an ideal intravenous iron preparation.

Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model

NASA Astrophysics Data System (ADS)

Yaseen, Zaher Mundher; Ebtehaj, Isa; Bonakdari, Hossein; Deo, Ravinesh C.; Danandeh Mehr, Ali; Mohtar, Wan Hanna Melini Wan; Diop, Lamine; El-shafie, Ahmed; Singh, Vijay P.

2017-11-01

The present study proposes a new hybrid evolutionary Adaptive Neuro-Fuzzy Inference Systems (ANFIS) approach for monthly streamflow forecasting. The proposed method is a novel combination of the ANFIS model with the firefly algorithm as an optimizer tool to construct a hybrid ANFIS-FFA model. The results of the ANFIS-FFA model is compared with the classical ANFIS model, which utilizes the fuzzy c-means (FCM) clustering method in the Fuzzy Inference Systems (FIS) generation. The historical monthly streamflow data for Pahang River, which is a major river system in Malaysia that characterized by highly stochastic hydrological patterns, is used in the study. Sixteen different input combinations with one to five time-lagged input variables are incorporated into the ANFIS-FFA and ANFIS models to consider the antecedent seasonal variations in historical streamflow data. The mean absolute error (MAE), root mean square error (RMSE) and correlation coefficient (r) are used to evaluate the forecasting performance of ANFIS-FFA model. In conjunction with these metrics, the refined Willmott's Index (Drefined), Nash-Sutcliffe coefficient (ENS) and Legates and McCabes Index (ELM) are also utilized as the normalized goodness-of-fit metrics. Comparison of the results reveals that the FFA is able to improve the forecasting accuracy of the hybrid ANFIS-FFA model (r = 1; RMSE = 0.984; MAE = 0.364; ENS = 1; ELM = 0.988; Drefined = 0.994) applied for the monthly streamflow forecasting in comparison with the traditional ANFIS model (r = 0.998; RMSE = 3.276; MAE = 1.553; ENS = 0.995; ELM = 0.950; Drefined = 0.975). The results also show that the ANFIS-FFA is not only superior to the ANFIS model but also exhibits a parsimonious modelling framework for streamflow forecasting by incorporating a smaller number of input variables required to yield the comparatively better performance. It is construed that the FFA optimizer can thus surpass the accuracy of the traditional ANFIS model in general, and is able to remove the false (inaccurately) forecasted data in the ANFIS model for extremely low flows. The present results have wider implications not only for streamflow forecasting purposes, but also for other hydro-meteorological forecasting variables requiring only the historical data input data, and attaining a greater level of predictive accuracy with the incorporation of the FFA algorithm as an optimization tool in an ANFIS model.

A Ranking Analysis/An Interlinking Approach of New Triangular Fuzzy Cognitive Maps and Combined Effective Time Dependent Matrix

NASA Astrophysics Data System (ADS)

Adiga, Shreemathi; Saraswathi, A.; Praveen Prakash, A.

2018-04-01

This paper aims an interlinking approach of new Triangular Fuzzy Cognitive Maps (TrFCM) and Combined Effective Time Dependent (CETD) matrix to find the ranking of the problems of Transgenders. Section one begins with an introduction that briefly describes the scope of Triangular Fuzzy Cognitive Maps (TrFCM) and CETD Matrix. Section two provides the process of causes of problems faced by Transgenders using Fuzzy Triangular Fuzzy Cognitive Maps (TrFCM) method and performs the calculations using the collected data among the Transgender. In Section 3, the reasons for the main causes for the problems of the Transgenders. Section 4 describes the Charles Spearmans coefficients of rank correlation method by interlinking of Triangular Fuzzy Cognitive Maps (TrFCM) Method and CETD Matrix. Section 5 shows the results based on our study.

A Survey of Flow Cytometry Data Analysis Methods

PubMed Central

Bashashati, Ali; Brinkman, Ryan R.

2009-01-01

Flow cytometry (FCM) is widely used in health research and in treatment for a variety of tasks, such as in the diagnosis and monitoring of leukemia and lymphoma patients, providing the counts of helper-T lymphocytes needed to monitor the course and treatment of HIV infection, the evaluation of peripheral blood hematopoietic stem cell grafts, and many other diseases. In practice, FCM data analysis is performed manually, a process that requires an inordinate amount of time and is error-prone, nonreproducible, nonstandardized, and not open for re-evaluation, making it the most limiting aspect of this technology. This paper reviews state-of-the-art FCM data analysis approaches using a framework introduced to report each of the components in a data analysis pipeline. Current challenges and possible future directions in developing fully automated FCM data analysis tools are also outlined. PMID:20049163

Force Measurement Services at Kebs: AN Overview of Equipment, Procedures and Uncertainty

NASA Astrophysics Data System (ADS)

Bangi, J. O.; Maranga, S. M.; Nganga, S. P.; Mutuli, S. M.

This paper describes the facilities, instrumentation and procedures currently used in the force laboratory at the Kenya Bureau of Standards (KEBS) for force measurement services. The laboratory uses the Force Calibration Machine (FCM) to calibrate force-measuring instruments. The FCM derives its traceability via comparisons using reference transfer force transducers calibrated by the Force Standard Machines (FSM) of a National Metrology Institute (NMI). The force laboratory is accredited to ISO/IEC 17025 by the Germany Accreditation Body (DAkkS). The accredited measurement scope of the laboratory is 1 MN to calibrate force transducers in both compression and tension modes. ISO 376 procedures are used while calibrating force transducers. The KEBS reference transfer standards have capacities of 10, 50, 300 and 1000 kN to cover the full range of the FCM. The uncertainty in the forces measured by the FCM were reviewed and determined in accordance to the new EURAMET calibration guide. The relative expanded uncertainty of force W realized by FCM was evaluated in a range from 10 kN-1 MN, and was found to be 5.0 × 10-4 with the coverage factor k being equal to 2. The overall normalized error (En) of the comparison results was also found to be less than 1. The accredited Calibration and Measurement Capability (CMC) of the KEBS force laboratory was based on the results of those intercomparisons. The FCM enables KEBS to provide traceability for the calibration of class ‘1’ force instruments as per the ISO 376.

Analysis of subcellular sized particles. Capillary electrophoresis with post-column laser-induced fluorescence detection versus flow cytometry.

PubMed

Poe, Bobby G; Navratil, Marian; Arriaga, Edgar A

2006-12-29

Flow cytometry (FCM) and more recently capillary electrophoresis with post-column laser-induced fluorescence detection (CE-LIF) have both been used for subcellular particle analysis but their analytical performance has not been compared. In this work, we compare a commercial FCM with an in-house built CE-LIF instrument using fluorescently labeled microspheres and isolated mitochondria. As evidenced by the relative standard deviation (RSD) of the individual fluorescence intensities, FCM is two-fold better than CE-LIF for microspheres with > or =1.5 x 10(6) molecules of equivalent soluble fluorescein (MESF). However, FCM has a comparatively low signal-to-noise ratio (S/N) and high RSD for microspheres with <1.5 x 10(6) MESF. CE-LIF, on the other hand, produces S/N ratios that are >25 times higher than FCM for all the microspheres tested and a lower RSD for microspheres with <1.5 x 10(6) MESF. When 10-N-nonyl acridine orange (NAO)-labeled mitochondria are analyzed, the S/N ratios of both techniques are similar. This appears to result from photobleaching of NAO-labeled mitochondria as they are detected by the LIF detector of the CE-LIF instrument. Both techniques have a niche in subcellular analysis; FCM has the advantage of collecting data for thousands of particles quickly, whereas CE-LIF consumes less than a nanoliter of sample and provides the electrophoretic mobility for individual particles.

Faecal corticosterone metabolite concentrations are not a good predictor of habitat suitability for common gartersnakes.

PubMed

Halliday, William D; Gilmour, Kathleen M; Blouin-Demers, Gabriel

2015-01-01

Measuring habitat suitability is important in conservation and in wildlife management. Measuring the abundance or presence-absence of a species in various habitats is not sufficient to measure habitat suitability because these metrics can be poor predictors of population success. Therefore, having some measure of population success is essential in assessing habitat suitability, but estimating population success is difficult. Identifying suitable proxies for population success could thus be beneficial. We examined whether faecal corticosterone metabolite (fCM) concentrations could be used as a proxy for habitat suitability in common gartersnakes (Thamnophis sirtalis). We conducted a validation study and confirmed that fCM concentrations indeed reflect circulating corticosterone concentrations. We estimated abundance, reproductive output and growth rate of gartersnakes in field and in forest habitat and we also measured fCM concentrations of gartersnakes from these same habitats. Common gartersnakes were more abundant and had higher reproductive outputs and higher growth rates in field habitat than in forest habitat, but fCM concentrations did not differ between the same two habitats. Our results suggest either that fCM concentrations are not a useful metric of habitat suitability in common gartersnakes or that the difference in suitability between the two habitats was too small to induce changes in fCM concentrations. Incorporating fitness metrics in estimates of habitat suitability is important, but these metrics of fitness have to be sensitive enough to vary between habitats.

Use of infrared thermography to assess the influence of high environmental temperature on rabbits.

PubMed

de Lima, V; Piles, M; Rafel, O; López-Béjar, M; Ramón, J; Velarde, A; Dalmau, A

2013-10-01

The aim of this work was to ascertain if infrared thermography (IRT) can be used on rabbits to assess differences in surface body temperature when they are subjected to two different environmental temperatures outside the comfort zone. Rabbits housed in room A were maintained at a temperature of below 30°C and rabbits in room B at a temperature of above 32°C for a year. Faeces were collected six times during the year to assess stress by means of faecal cortisol metabolites (FCM). The assessment of IRT was carried out to assess maximum and minimum temperatures on the eyes, nose and ears. FCM concentration was higher in room B than A, to confirm that stress conditions were higher in room B. Significant differences in IRT were found between the animals housed in both rooms. It was observed that it was more difficult for animals from room B to maintain a regular heat loss. Although all the body zones used to assess temperature with IRT gave statistical differences, the correlations found between the eyes, nose and ears were moderate, suggesting that they were giving different information. In addition, differences up to 3.36°C were found in the eye temperature of rabbits housed in the same room, with a clear effect of their position in relation to extractors and heating equipments. Therefore, IRT could be a good tool to assess heat stress in animals housed on typical rabbit farm buildings, giving a measure of how the animal is perceiving a combination of humidity, temperature and ventilation. Some face areas were better for analysing images. Minimum temperature on eyes and temperatures on nose are suggested to assess heat losses and critical areas of the farm for heat stress in rabbits. Copyright © 2013 Elsevier Ltd. All rights reserved.

A Genetic Algorithm That Exchanges Neighboring Centers for Fuzzy c-Means Clustering

ERIC Educational Resources Information Center

Chahine, Firas Safwan

2012-01-01

Clustering algorithms are widely used in pattern recognition and data mining applications. Due to their computational efficiency, partitional clustering algorithms are better suited for applications with large datasets than hierarchical clustering algorithms. K-means is among the most popular partitional clustering algorithm, but has a major…

Effect of serotonin on the expression of antigens and DNA levels in Yersinia pestis cells with different plasmid content

NASA Astrophysics Data System (ADS)

Klueva, Svetlana N.; Korsukov, Vladimir N.; Schukovskaya, Tatyana N.; Kravtsov, Alexander L.

2004-08-01

Using flow cytometry (FCM) the influence of exogenous serotonin on culture growth, DNA content and fluorescence intensity of cells binding FITC-labelled plague polyclonal immunoglobulins was studied in Yersinia pestis EV (pFra+, pCad+, pPst+), Yersinia pestis KM218 (pFra-, pCad-, pPst-), Yersinia pestis KM 216 (pFra-, pCad-, pPst+). The results have been obtained by FCM showed serotonin accelerated Yersinia pestis EV (pFra+, pCad+, pPst+), Yersinia pestis KM218 (pFra-, pCad-, pPst-) culture growth during cultivation in Hottinger broth pH 7.2 at 28°C at concentration of 10-5 M. The presence of 10-5 M serotonin in nutrient broth could modulate DNA content in 37°C growing population of plague microbe independently of their plasmid content. Serotonin have been an impact on the distribution pattern of the cells according to their phenotypical characteristics, which was reflected in the levels of population heterogeneity in the intensity of specific immunofluorescence determined by FMC.

A curvature-based weighted fuzzy c-means algorithm for point clouds de-noising

NASA Astrophysics Data System (ADS)

Cui, Xin; Li, Shipeng; Yan, Xiutian; He, Xinhua

2018-04-01

In order to remove the noise of three-dimensional scattered point cloud and smooth the data without damnify the sharp geometric feature simultaneity, a novel algorithm is proposed in this paper. The feature-preserving weight is added to fuzzy c-means algorithm which invented a curvature weighted fuzzy c-means clustering algorithm. Firstly, the large-scale outliers are removed by the statistics of r radius neighboring points. Then, the algorithm estimates the curvature of the point cloud data by using conicoid parabolic fitting method and calculates the curvature feature value. Finally, the proposed clustering algorithm is adapted to calculate the weighted cluster centers. The cluster centers are regarded as the new points. The experimental results show that this approach is efficient to different scale and intensities of noise in point cloud with a high precision, and perform a feature-preserving nature at the same time. Also it is robust enough to different noise model.

FIND-CKD: a randomized trial of intravenous ferric carboxymaltose versus oral iron in patients with chronic kidney disease and iron deficiency anaemia.

PubMed

Macdougall, Iain C; Bock, Andreas H; Carrera, Fernando; Eckardt, Kai-Uwe; Gaillard, Carlo; Van Wyck, David; Roubert, Bernard; Nolen, Jacqueline G; Roger, Simon D

2014-11-01

The optimal iron therapy regimen in patients with non-dialysis-dependent chronic kidney disease (CKD) is unknown. Ferinject® assessment in patients with Iron deficiency anaemia and Non-Dialysis-dependent Chronic Kidney Disease (FIND-CKD) was a 56-week, open-label, multicentre, prospective and randomized study of 626 patients with non-dialysis-dependent CKD, anaemia and iron deficiency not receiving erythropoiesis-stimulating agents (ESAs). Patients were randomized (1:1:2) to intravenous (IV) ferric carboxymaltose (FCM), targeting a higher (400-600 µg/L) or lower (100-200 µg/L) ferritin or oral iron therapy. The primary end point was time to initiation of other anaemia management (ESA, other iron therapy or blood transfusion) or haemoglobin (Hb) trigger of two consecutive values <10 g/dL during Weeks 8-52. The primary end point occurred in 36 patients (23.5%), 49 patients (32.2%) and 98 patients (31.8%) in the high-ferritin FCM, low-ferritin FCM and oral iron groups, respectively [hazard ratio (HR): 0.65; 95% confidence interval (CI): 0.44-0.95; P = 0.026 for high-ferritin FCM versus oral iron]. The increase in Hb was greater with high-ferritin FCM versus oral iron (P = 0.014) and a greater proportion of patients achieved an Hb increase ≥1 g/dL with high-ferritin FCM versus oral iron (HR: 2.04; 95% CI: 1.52-2.72; P < 0.001). Rates of adverse events and serious adverse events were similar in all groups. Compared with oral iron, IV FCM targeting a ferritin of 400-600 µg/L quickly reached and maintained Hb level, and delayed and/or reduced the need for other anaemia management including ESAs. Within the limitations of this trial, no renal toxicity was observed, with no difference in cardiovascular or infectious events. NCT00994318. © The Author 2014. Published by Oxford University Press on behalf of ERA-EDTA.

Impact of pre-transplantation minimal residual disease determined by multiparameter flow cytometry on the outcome of AML patients with FLT3-ITD after allogeneic stem cell transplantation.

PubMed

Zhao, Xiaosu; Wang, Zhidong; Ruan, Guorui; Liu, Yanrong; Wang, Yu; Zhang, Xiaohui; Xu, Lanping; Huang, Xiaojun; Chang, Yingjun

2018-06-01

In this study, using multiparameter flow cytometry (FCM), we investigate the impact of minimal residual disease prior to transplantation (pre-MRD) on the transplant outcomes of AML patients with fms-related tyrosine kinase 3 (FLT3)-internal tandem duplication (ITD) mutation. A total of 20 patients who received HLA-matched sibling donor transplantation (MSDT) and 63 patients who received unmanipulated haploidentical hematopoietic stem cell transplantation (haplo-HSCT) were enrolled. Patients were classified into four groups based on the status of pre-FCM: group 1 with positive pre-FCM before MSDT, group 2 with negative pre-FCM before MSDT, group 3 with positive pre-FCM before haplo-HSCT, and group 4 with positive pre-FCM before haplo-HSCT. The results showed that patients in group 1 had the highest cumulative incidence of relapse (2-year CIR, 75.0%), the lowest leukemia-free survival (2-year LFS, 33.3%), and the overall survival (2-year OS, 25.0%) among all four groups. The other three groups of patients had comparable CIR (2-year CIR: group 2 vs. 3 vs. 4, 12.5% vs. 31.3% vs. 22.2%, P > 0.05) and LFS (2-year LFS: group 2 vs. 3 vs. 4, 87.5% vs. 62.5% vs. 66.5%, P > 0.05). Multivariate analysis indicated that disease status (> CR) and pre-MRD were associated with a higher CIR and a lower LFS when patients were classified by pre-MRD and transplant type. Our results suggested that AML patients with FLT3-ITD were able to be separated into high-risk and low-risk relapse groups based on pre-MRD, as determined by multiparameter FCM. Haplo-HSCT might overcome the negative impact of pre-MRD on patient outcomes compared to MSDT. These results require further investigation in prospective study with large numbers of cases.

Plastic fiber optics for micro-imaging of fluorescence signals in living cells

NASA Astrophysics Data System (ADS)

Sakurai, Takashi; Natsume, Mitsuo; Koida, Kowa

2015-03-01

The fiber-coupled microscope (FCM) enables in vivo imaging at deep sites in the tissues or organs that other optical techniques are unable to reach. To develop FCM-based intravital imaging, we employed a plastic optical fiber (POF) bundle that included more than 10,000-units of polystyrene core and polymethyl methacrylate cladding. Each POF had a diameter of less than 5 μm the tip of the bundle was less than 0.5 mm wide, and the flexible wire had a length of 1,000 mm. The optical performance of the plastic FCM was sufficient for detection of significant signal changes in an acinus of rat pancreas labeled with a calcium ion-sensitive fluorescent dye. In the future, the potential power of plastic FCM is expected to increase, enabling analysis of structure and organization of specific functions in live cells within vulnerable organs.

Cr(VI) induces DNA damage, cell cycle arrest and polyploidization: a flow cytometric and comet assay study in Pisum sativum.

PubMed

Rodriguez, Eleazar; Azevedo, Raquel; Fernandes, Pedro; Santos, Conceição

2011-07-18

Chromium(VI) is recognized as the most toxic valency of Cr, but its genotoxicity and cytostaticity in plants is still poorly studied. In order to analyze Cr(VI) cyto- and gentotoxicity, Pisum sativum L. plants were grown in soil and watered with solutions with different concentrations of Cr up to 2000 mg/L. After 28 days of exposure, leaves showed no significant variations in either cell cycle dynamics or ploidy level. As for DNA damage, flow cytometric (FCM) histograms showed significant differences in full peak coefficient of variation (FPCV) values, suggesting clastogenicity. This is paralleled by the Comet assay results, showing an increase in DNA damage for 1000 and 2000 mg/L. In roots, exposure to 2000 mg/L resulted in cell cycle arrest at the G(2)/M checkpoint. It was also verified that under the same conditions 40% of the individuals analyzed suffered polyploidization having both 2C and 4C levels. DNA damage analysis by the Comet assay and FCM revealed dose-dependent increases in DNA damage and FPCV. Through this, we have unequivocally demonstrated for the first time in plants that Cr exposure can result in DNA damage, cell cycle arrest, and polyploidization. Moreover, we critically compare the validity of the Comet assay and FCM in evaluating cytogenetic toxicity tests in plants and demonstrate that the data provided by both techniques complement each other and present high correlation levels. In conclusion, the data presented provides new insight on Cr effects in plants in general and supports the use of the parameters tested in this study as reliable endpoints for this metal toxicity in plants. © 2011 American Chemical Society

Utilization of physicochemical variables developed from changes in sensory attributes and consumer acceptability to predict the shelf life of fresh-cut mango fruit.

PubMed

Salinas-Hernández, Rosa María; González-Aguilar, Gustavo A; Tiznado-Hernández, Martín Ernesto

2015-01-01

Sensory evaluation is the ideal tool for shelf-life determination. With the objective to develop an easy shelf-life indicator, color (L*, a*, b*, chroma and hue angle), total soluble solids (TSS), firmness (F), pH, acidity, and the sensory attributes of appearance, brightness, browning, odor, flavor, texture, color, acidity and sweetness were evaluated in fresh cut mangoes (FCM) stored at 5, 10, 15 and 20 °C. Overall acceptability was evaluated by consumers. Correlation analysis between sensory attributes and physicochemical variables was carried out. Physicochemical cut-off points based on sensory attributes and consumer acceptability was obtained by regression analysis and utilized to estimate FCM shelf-life by kinetic models fitted to each variable. The validation of the model was done by comparing the shelf life estimated by kinetic models and consumers. It was recorded large correlations between appearance, brightness, and color with L*; appearance and color with chroma and hue angle; sweetness and flavor with TSS, and between F and texture. The shelf life estimated based on consumer using a 9 point hedonic scale was in the range of 10-12, 2.3-2.6, 1.3-1.5 and 1.0-1.1 days for 5, 10, 15 and 20 °C. It was recorded large correlation coefficients between the shelf life estimated by consumer acceptability scores and physicochemical variables. Kinetic models based on physicochemical variables showed a tendency to overestimate the shelf life as compared with the models bases on the sensory attributes. It was concluded that physicochemical variables can be used as a tool to estimate the FCM shelf life.

Qualitative and quantitative analysis of monomers in polyesters for food contact materials.

PubMed

Brenz, Fabrian; Linke, Susanne; Simat, Thomas

2017-02-01

Polyesters (PESs) are gaining more importance on the food contact material (FCM) market and the variety of properties and applications is expected to be wide. In order to acquire the desired properties manufacturers can combine several FCM-approved polyvalent carboxylic acids (PCAs) and polyols as monomers. However, information about the qualitative and quantitative composition of FCM articles is often limited. The method presented here describes the analysis of PESs with the identification and quantification of 25 PES monomers (10 PCA, 15 polyols) by HPLC with diode array detection (HPLC-DAD) and GC-MS after alkaline hydrolysis. Accurate identification and quantification were demonstrated by the analysis of seven different FCM articles made of PESs. The results explained between 97.2% and 103.4% w/w of the polymer composition whilst showing equal molar amounts of PCA and polyols. Quantification proved to be precise and sensitive with coefficients of variation (CVs) below 6.0% for PES samples with monomer concentrations typically ranging from 0.02% to 75% w/w. The analysis of 15 PES samples for the FCM market revealed the presence of five different PCAs and 11 different polyols (main monomers, co-monomers, non-intentionally added substances (NIAS)) showing the wide variety of monomers in modern PESs. The presented method provides a useful tool for commercial, state and research laboratories as well as for producers and distributors facing the task of FCM risk assessment. It can be applied for the identification and quantification of migrating monomers and the prediction of oligomer compositions from the identified monomers, respectively.

Blood Vessel Extraction in Color Retinal Fundus Images with Enhancement Filtering and Unsupervised Classification

PubMed Central

2017-01-01

Retinal blood vessels have a significant role in the diagnosis and treatment of various retinal diseases such as diabetic retinopathy, glaucoma, arteriosclerosis, and hypertension. For this reason, retinal vasculature extraction is important in order to help specialists for the diagnosis and treatment of systematic diseases. In this paper, a novel approach is developed to extract retinal blood vessel network. Our method comprises four stages: (1) preprocessing stage in order to prepare dataset for segmentation; (2) an enhancement procedure including Gabor, Frangi, and Gauss filters obtained separately before a top-hat transform; (3) a hard and soft clustering stage which includes K-means and Fuzzy C-means (FCM) in order to get binary vessel map; and (4) a postprocessing step which removes falsely segmented isolated regions. The method is tested on color retinal images obtained from STARE and DRIVE databases which are available online. As a result, Gabor filter followed by K-means clustering method achieves 95.94% and 95.71% of accuracy for STARE and DRIVE databases, respectively, which are acceptable for diagnosis systems. PMID:29065611

Electrical Load Profile Analysis Using Clustering Techniques

NASA Astrophysics Data System (ADS)

Damayanti, R.; Abdullah, A. G.; Purnama, W.; Nandiyanto, A. B. D.

2017-03-01

Data mining is one of the data processing techniques to collect information from a set of stored data. Every day the consumption of electricity load is recorded by Electrical Company, usually at intervals of 15 or 30 minutes. This paper uses a clustering technique, which is one of data mining techniques to analyse the electrical load profiles during 2014. The three methods of clustering techniques were compared, namely K-Means (KM), Fuzzy C-Means (FCM), and K-Means Harmonics (KHM). The result shows that KHM is the most appropriate method to classify the electrical load profile. The optimum number of clusters is determined using the Davies-Bouldin Index. By grouping the load profile, the demand of variation analysis and estimation of energy loss from the group of load profile with similar pattern can be done. From the group of electric load profile, it can be known cluster load factor and a range of cluster loss factor that can help to find the range of values of coefficients for the estimated loss of energy without performing load flow studies.

MRI brain tumor segmentation based on improved fuzzy c-means method

NASA Astrophysics Data System (ADS)

Deng, Wankai; Xiao, Wei; Pan, Chao; Liu, Jianguo

2009-10-01

This paper focuses on the image segmentation, which is one of the key problems in medical image processing. A new medical image segmentation method is proposed based on fuzzy c- means algorithm and spatial information. Firstly, we classify the image into the region of interest and background using fuzzy c means algorithm. Then we use the information of the tissues' gradient and the intensity inhomogeneities of regions to improve the quality of segmentation. The sum of the mean variance in the region and the reciprocal of the mean gradient along the edge of the region are chosen as an objective function. The minimum of the sum is optimum result. The result shows that the clustering segmentation algorithm is effective.

Printed paper and board food contact materials as a potential source of food contamination.

PubMed

Van Bossuyt, Melissa; Van Hoeck, Els; Vanhaecke, Tamara; Rogiers, Vera; Mertens, Birgit

2016-11-01

Food contact materials (FCM) are estimated to be the largest source of food contamination. Apart from plastics, the most commonly used FCM are made of printed paper and board. Unlike their plastic counterparts, these are not covered by a specific European regulation. Several contamination issues have raised concerns towards potential adverse health effects caused by exposure to substances migrating from printed paper and board FCM. In the current study, an inventory combining the substances which may be used in printed paper and board FCM, was created. More than 6000 unique compounds were identified, the majority (77%) considered non-evaluated in terms of potential toxicity. Based on a preliminary study of their physicochemical properties, it is estimated that most of the non-evaluated single substances have the potential to migrate into the food and become bioavailable after oral intake. Almost all are included in the FACET tool, indicating that their use in primary food packaging has been confirmed by industry. Importantly, 19 substances are also present in one of the lists with substances of concern compiled by the European Chemicals Agency (ECHA). To ensure consumer safety, the actual use of these substances in printed paper and board FCM should be investigated urgently. Copyright © 2016 Elsevier Inc. All rights reserved.

First identification of the herpes simplex virus by skin-dedicated ex vivo fluorescence confocal microscopy during herpetic skin infections.

PubMed

Cinotti, E; Perrot, J L; Labeille, B; Campolmi, N; Thuret, G; Naigeon, N; Bourlet, T; Pillet, S; Cambazard, F

2015-06-01

Skin-dedicated ex vivo fluorescence confocal microscopy (FCM) has so far been used to identify cutaneous tumours on freshly excised samples using acridine orange as fluorochrome. To use FCM for a new indication, namely, the identification of the herpes simplex virus (HSV) in skin lesions, using fluorescent antibodies. Six roof samples from skin vesicles suspicious for HSV lesions were incubated with anti-HSV-1 and anti-HSV-2 antibodies coupled with fluorescein isothiocyanate, and examined under skin-dedicated ex vivo FCM. The positive controls were swabs taken from the floor of each vesicle and observed under conventional direct fluorescence assay (DFA) and by viral cultures. Roof samples from three bullae of bullous pemphigoid were the negative controls. Using ex vivo FCM, the samples from the lesions clinically suspicious for HSV infection were seen to be fluorescent after incubation with anti-HSV-1, and were negative after incubation with anti-HSV-2 antibodies. Conventional DFA with an optical microscope and cultures confirmed the presence of HSV-1 infection. By using fluorescent antibodies to identify precise structures, ex vivo FCM can be used for indications other than tumour identification. More specifically, it can be an additional diagnostic tool for HSV infection. © 2014 British Association of Dermatologists.

Evaluating Stress Physiology and Parasite Infection Parameters in the Translocation of Critically Endangered Woylies (Bettongia penicillata).

PubMed

Hing, Stephanie; Northover, Amy S; Narayan, Edward J; Wayne, Adrian F; Jones, Krista L; Keatley, Sarah; Thompson, R C Andrew; Godfrey, Stephanie S

2017-03-01

Translocation can be stressful for wildlife. Stress may be important in fauna translocation because it has been suggested that it can exacerbate the impact of infectious disease on translocated wildlife. However, few studies explore this hypothesis by measuring stress physiology and infection indices in parallel during wildlife translocations. We analysed faecal cortisol metabolite (FCM) concentration and endoparasite parameters (nematodes, coccidians and haemoparasites) in a critically endangered marsupial, the woylie (Bettongia penicillata), 1-3 months prior to translocation, at translocation, and 6 months later. FCM for both translocated and resident woylies was significantly higher after translocation compared to before or at translocation. In addition, body condition decreased with increasing FCM after translocation. These patterns in host condition and physiology may be indicative of translocation stress or stress associated with factors independent of the translocation. Parasite factors also influenced FCM in translocated woylies. When haemoparasites were detected, there was a significant negative relationship between strongyle egg count and FCM. This may reflect the influence of glucocorticoids on the immune response to micro- and macro-parasites. Our results indicate that host physiology and infection patterns can change significantly during translocation, but further investigation is required to determine how these patterns influence translocation success.

[Intravenous ferric carboxymaltose-associated hypophosphatemia in patients with iron deficiency anemia. A common side effect].

PubMed

Sánchez González, Rebeca; Ternavasio-de la Vega, Hugo Guillermo; Moralejo Alonso, Leticia; Inés Revuelta, Sandra; Fuertes Martín, Aurelio

2015-08-07

To determine the frequency, severity, time of onset and factors associated with the development of hypophosphatemia (HF) in patients with iron deficiency anemia treated with intravenous ferric carboxymatose (ivFCM). Retrospective cohort study in patients iron deficiency anemia who received ivFCM and had an a prior and subsequent determination of serum phosphate. We carried out a comparative analysis between baseline and post-ivFCM levels of serum phosphate. In order to identify variables independently associated with HF a logistic regression analysis was also performed. One hundred twenty-five patients were included. HF frequency was 58%. The median time to onset of HF was 18 days. Age, baseline ferritin levels and baseline phosphate levels were independently associated with the development of HF. The risk of HF in patients with baseline phosphate levels ≤ 3.1mg/dl was 67% higher than patients with ≥ 3.7 mg/dl. ivFCM-associated HF is a frequent, early and, sometimes, prolonged effect in patients with iron deficiency anemia. Serum phosphate levels should be monitored after ivFCM administration, especially in older patients and in those with lower baseline phosphate or ferritin levels. Copyright © 2014 Elsevier España, S.L.U. All rights reserved.

31 CFR 103.17 - Reports by futures commission merchants and introducing brokers in commodities of suspicious...

Code of Federal Regulations, 2010 CFR

2010-07-01

... immediate attention, such as terrorist financing or ongoing money laundering schemes, the FCM or IB-C shall... 31 Money and Finance: Treasury 1 2010-07-01 2010-07-01 false Reports by futures commission merchants and introducing brokers in commodities of suspicious transactions. 103.17 Section 103.17 Money and...

Fuzzy C-Means Algorithm for Segmentation of Aerial Photography Data Obtained Using Unmanned Aerial Vehicle

NASA Astrophysics Data System (ADS)

Akinin, M. V.; Akinina, N. V.; Klochkov, A. Y.; Nikiforov, M. B.; Sokolova, A. V.

2015-05-01

The report reviewed the algorithm fuzzy c-means, performs image segmentation, give an estimate of the quality of his work on the criterion of Xie-Beni, contain the results of experimental studies of the algorithm in the context of solving the problem of drawing up detailed two-dimensional maps with the use of unmanned aerial vehicles. According to the results of the experiment concluded that the possibility of applying the algorithm in problems of decoding images obtained as a result of aerial photography. The considered algorithm can significantly break the original image into a plurality of segments (clusters) in a relatively short period of time, which is achieved by modification of the original k-means algorithm to work in a fuzzy task.

B cell increases and ex vivo IL-2 production as secondary endpoints for the detection of sensitizers in non-radioisotopic local lymph node assay using flow cytometry.

PubMed

Jung, Kyoung-Mi; Jang, Won-Hee; Lee, Yong-Kyoung; Yum, Young Na; Sohn, Soojung; Kim, Bae-Hwan; Chung, Jin-Ho; Park, Young-Ho; Lim, Kyung-Min

2012-03-25

Non-radioisotopic local lymph node assay (LLNA) using 5-bromo-2'-deoxyuridine (BrdU) with flow cytometry (FCM) is gaining attention since it is free from the regulatory issues in traditional LLNA (tLLNA) accompanying in vivo uses of radioisotope, (3)H-thymidine. However, there is also concern over compromised performance of non-radioisotopic LLNA, raising needs for additional endpoints to improve the accuracy. With the full 22 reference substances enlisted in OECD Test Guideline No. 429, we evaluated the performance of LLNA:BrdU-FCM along with the concomitant measurements of B/T cell ratio and ex vivo cytokine production from isolated lymph node cells (LNCs) to examine the utility of these markers as secondary endpoints. Mice (Balb/c, female) were topically treated with substances on both ears for 3 days and then, BrdU was intraperitoneally injected on day 5. After a day, lymph nodes were isolated and undergone FCM to determine BrdU incorporation and B/T cell sub-typing with B220+ and CD3e+. Ex vivo cytokine production by LNCs was measured such as IL-2, IL-4, IL-6, IL-12, IFN-γ, MCP-1, GM-CSF and TNFα. Mice treated with sensitizers showed preferential increases in B cell population and the selective production of IL-2, which matched well with the increases in BrdU incorporation. When compared with guinea pig or human data, BrdU incorporation, B cell increase and IL-2 production ex vivo could successfully identify sensitizers with the accuracy comparable to tLLNA, suggesting that these markers may be useful for improving the accuracy of LLNA:BrdU-FCM or as stand-alone non-radioisotopic endpoints. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

An advanced method for classifying atmospheric circulation types based on prototypes connectivity graph

NASA Astrophysics Data System (ADS)

Zagouras, Athanassios; Argiriou, Athanassios A.; Flocas, Helena A.; Economou, George; Fotopoulos, Spiros

2012-11-01

Classification of weather maps at various isobaric levels as a methodological tool is used in several problems related to meteorology, climatology, atmospheric pollution and to other fields for many years. Initially the classification was performed manually. The criteria used by the person performing the classification are features of isobars or isopleths of geopotential height, depending on the type of maps to be classified. Although manual classifications integrate the perceptual experience and other unquantifiable qualities of the meteorology specialists involved, these are typically subjective and time consuming. Furthermore, during the last years different approaches of automated methods for atmospheric circulation classification have been proposed, which present automated and so-called objective classifications. In this paper a new method of atmospheric circulation classification of isobaric maps is presented. The method is based on graph theory. It starts with an intelligent prototype selection using an over-partitioning mode of fuzzy c-means (FCM) algorithm, proceeds to a graph formulation for the entire dataset and produces the clusters based on the contemporary dominant sets clustering method. Graph theory is a novel mathematical approach, allowing a more efficient representation of spatially correlated data, compared to the classical Euclidian space representation approaches, used in conventional classification methods. The method has been applied to the classification of 850 hPa atmospheric circulation over the Eastern Mediterranean. The evaluation of the automated methods is performed by statistical indexes; results indicate that the classification is adequately comparable with other state-of-the-art automated map classification methods, for a variable number of clusters.

Hyperspectral image segmentation using a cooperative nonparametric approach

NASA Astrophysics Data System (ADS)

Taher, Akar; Chehdi, Kacem; Cariou, Claude

2013-10-01

In this paper a new unsupervised nonparametric cooperative and adaptive hyperspectral image segmentation approach is presented. The hyperspectral images are partitioned band by band in parallel and intermediate classification results are evaluated and fused, to get the final segmentation result. Two unsupervised nonparametric segmentation methods are used in parallel cooperation, namely the Fuzzy C-means (FCM) method, and the Linde-Buzo-Gray (LBG) algorithm, to segment each band of the image. The originality of the approach relies firstly on its local adaptation to the type of regions in an image (textured, non-textured), and secondly on the introduction of several levels of evaluation and validation of intermediate segmentation results before obtaining the final partitioning of the image. For the management of similar or conflicting results issued from the two classification methods, we gradually introduced various assessment steps that exploit the information of each spectral band and its adjacent bands, and finally the information of all the spectral bands. In our approach, the detected textured and non-textured regions are treated separately from feature extraction step, up to the final classification results. This approach was first evaluated on a large number of monocomponent images constructed from the Brodatz album. Then it was evaluated on two real applications using a respectively multispectral image for Cedar trees detection in the region of Baabdat (Lebanon) and a hyperspectral image for identification of invasive and non invasive vegetation in the region of Cieza (Spain). A correct classification rate (CCR) for the first application is over 97% and for the second application the average correct classification rate (ACCR) is over 99%.

Relation between the ion size and pore size for an electric double-layer capacitor.

PubMed

Largeot, Celine; Portet, Cristelle; Chmiola, John; Taberna, Pierre-Louis; Gogotsi, Yury; Simon, Patrice

2008-03-05

The research on electrochemical double layer capacitors (EDLC), also known as supercapacitors or ultracapacitors, is quickly expanding because their power delivery performance fills the gap between dielectric capacitors and traditional batteries. However, many fundamental questions, such as the relations between the pore size of carbon electrodes, ion size of the electrolyte, and the capacitance have not yet been fully answered. We show that the pore size leading to the maximum double-layer capacitance of a TiC-derived carbon electrode in a solvent-free ethyl-methylimmidazolium-bis(trifluoro-methane-sulfonyl)imide (EMI-TFSI) ionic liquid is roughly equal to the ion size (approximately 0.7 nm). The capacitance values of TiC-CDC produced at 500 degrees C are more than 160 F/g and 85 F/cm(3) at 60 degrees C, while standard activated carbons with larger pores and a broader pore size distribution present capacitance values lower than 100 F/g and 50 F/cm(3) in ionic liquids. A significant drop in capacitance has been observed in pores that were larger or smaller than the ion size by just an angstrom, suggesting that the pore size must be tuned with sub-angstrom accuracy when selecting a carbon/ion couple. This work suggests a general approach to EDLC design leading to the maximum energy density, which has been now proved for both solvated organic salts and solvent-free liquid electrolytes.

Older mothers follow conservative strategies under predator pressure: the adaptive role of maternal glucocorticoids in yellow-bellied marmots.

PubMed

Monclús, Raquel; Tiulim, Justin; Blumstein, Daniel T

2011-11-01

When the maternal environment is a good predictor of the offspring environment, maternal glucocorticoid (GC) levels might serve to pre-program offspring to express certain phenotypes or life-history characteristics that will increase their fitness. We conducted a field study to assess the effects of naturally occurring maternal GC levels on their offspring in yellow-bellied marmots (Marmota flaviventris) subjected to different predator pressures. Maternal fecal corticosteroid metabolites (FCM) were positively correlated with predator pressure. Predators had both direct and indirect effects on pups. We found that older mothers with higher FCM levels had smaller and female-biased litters. Moreover, sons from older mothers with high FCM levels dispersed significantly more than those from older mothers with low FCM levels, whereas the opposite pattern was found in pups from younger mothers. These age-related effects may permit females to make adaptive decisions that increase their pups' fitness according to their current situation. Copyright © 2011 Elsevier Inc. All rights reserved.

Correlative cryogenic tomography of cells using light and soft x-rays

PubMed Central

Smith, Elizabeth A.; Cinquin, Bertrand P.; Do, Myan; McDermott, Gerry; Le Gros, Mark A.; Larabell, Carolyn A.

2013-01-01

Correlated imaging is the process of imaging a specimen with two complementary modalities, and then combining the two data sets to create a highly informative, composite view. A recent implementation of this concept has been the combination of soft x-ray tomography (SXT) with fluorescence cryogenic microscopy (FCM). SXT-FCM is used to visualize cells that are held in a near-native, cryo-preserved state. The resultant images are, therefore, highly representative of both the cellular architecture and molecular organization in vivo. SXT quantitatively visualizes the cell and sub-cellular structures; FCM images the spatial distribution of fluorescently labeled molecules. Here, we review the characteristics of SXT-FCM, and briefly discuss how this method compares with existing correlative imaging techniques. We also describe how the incorporation of a cryo-rotation stage into a cryogenic fluorescence microscope allows acquisition of fluorescence cryogenic tomography (FCT) data. FCT is optimally suited to correlation with SXT, since both techniques image the specimen in 3-D, potentially with similar, isotropic spatial resolution. PMID:24355261

Impact of ferric carboxymaltose on the evolution of hemoglobin and ECOG performance status in iron-deficient patients with solid tumors: a 3-month follow-up retrospective study.

PubMed

Coussirou, J; Debourdeau, A; Stancu, A; Jean, C; Azouza, W; Chanet, B; De Crozals, F; Boustany, R; Debourdeau, P

2018-05-24

Anemia is often associated with a lower quality of life and less tolerance to treatments in cancer patients. The aims of this retrospective study were to assess the biological (hemoglobin, Hb) and clinical (ECOG index) impact of ferric carboxymaltose (FCM) and to identify predictive factors of response in cancer patients with iron deficiency. We included 133 patients with solid tumors who received at least one dose of FCM in 2015. At baseline, most patients had metastatic cancer (70%), were undergoing chemotherapy (82%), suffered from anemia (90%), and 72% had an ECOG 0-1 index. Mean Hb level was statistically higher at M1 (108.3 g/L ± 13.9), M2 (110.3 g/L ± 16.1), and M3 (111.7 g/L ± 12.6) than M0 (99.2 g/L ± 13.9). Mean ECOG score increased significantly at M1 (1.31 ± 0.80) and M2 (1.31 ± 0.87) compared to M0 (1.13 ± 0.80). Variations of ECOG index between M0 and M1 were independent of levels of Hb and ferritin at inclusion and pretreatment use of transfusion and ESAs. Increase of Hb level was higher in patients with Hb < 100 g/L, ferritinemia < 800 ng/ml, or transfused before inclusion. In multivariate analysis, an ECOG index of 0 was the only predictive factor of an increase of ECOG index and Hb level < 100 g/L and ferritinemia < 800 ng/ml were predictive of an increase in Hb. Even though there was no improvement in ECOG index, this study did identify an increase of Hb for patients receiving FCM, indicating its potential benefit in iron-deficient cancer patients.

Bearing performance degradation assessment based on a combination of empirical mode decomposition and k-medoids clustering

NASA Astrophysics Data System (ADS)

Rai, Akhand; Upadhyay, S. H.

2017-09-01

Bearing is the most critical component in rotating machinery since it is more susceptible to failure. The monitoring of degradation in bearings becomes of great concern for averting the sudden machinery breakdown. In this study, a novel method for bearing performance degradation assessment (PDA) based on an amalgamation of empirical mode decomposition (EMD) and k-medoids clustering is encouraged. The fault features are extracted from the bearing signals using the EMD process. The extracted features are then subjected to k-medoids based clustering for obtaining the normal state and failure state cluster centres. A confidence value (CV) curve based on dissimilarity of the test data object to the normal state is obtained and employed as the degradation indicator for assessing the health of bearings. The proposed outlook is applied on the vibration signals collected in run-to-failure tests of bearings to assess its effectiveness in bearing PDA. To validate the superiority of the suggested approach, it is compared with commonly used time-domain features RMS and kurtosis, well-known fault diagnosis method envelope analysis (EA) and existing PDA classifiers i.e. self-organizing maps (SOM) and Fuzzy c-means (FCM). The results demonstrate that the recommended method outperforms the time-domain features, SOM and FCM based PDA in detecting the early stage degradation more precisely. Moreover, EA can be used as an accompanying method to confirm the early stage defect detected by the proposed bearing PDA approach. The study shows the potential application of k-medoids clustering as an effective tool for PDA of bearings.

Non-invasive evaluation of physiological stress in an iconic Australian marsupial: the Koala (Phascolarctos cinereus).

PubMed

Narayan, Edward J; Webster, Koa; Nicolson, Vere; Mucci, Al; Hero, Jean-Marc

2013-06-15

Koalas (Phascolarctos cinereus) are the only extant representatives of Australia's unique marsupial family Phascolarctidae and were listed as nationally Vulnerable in 2012. Causes of mortality are diverse, although the disease chlamydiosis, dog attacks, collisions with cars, and loss of habitat represent the principal reasons for the continued species decline. Koala breeding facilities in Queensland and New South Wales, Australia have been established for conservation and tourism. Non-invasive monitoring of physiological stress is important for determining the sub-lethal effects of environmental stressors on the well-being, reproduction and survival of Koalas in Zoos and also in the wild. In this study, we developed a faecal cortisol metabolite (FCM) enzyme-immunoassay (EIA) for monitoring physiological stress in Koalas from two established Zoos in Australia and also within a free-living sub-population from Queensland. Biological validation of the FCM EIA was done using an adrenocorticotropic hormone (ACTH) challenge. We discovered excretory lag-times of FCM of 24 h in females (n=2) and 48 h in male (n=2) Koalas in response to the ACTH challenge. FCM levels showed an episodic and delayed peak response lasting up to 9 days post ACTH challenge. This finding should be taken into consideration when designing future experiments to study the impacts of short-term (acute) and chronic stressors on the Koalas. Laboratory validations were done using parallelism and recovery checks (extraction efficiency) of the cortisol standard against pooled Koala faecal extracts. Greater than 99% recovery of the cortisol standard was obtained as well as a parallel displacement curve against Koala faecal extracts. FCM levels of the captive Koalas (n=10 males and 13 females) significantly differed by sex, reproductive condition (lactating versus non-lactating Koalas) and the handling groups. Handled male Koalas had 200% higher FCM levels than their non-handled counterparts, while females were not affected by handling as long they were not undergoing lactation. There was no significant difference in FCM levels between the captive and wild Koalas (n=9 males and 7 females). Overall, these results provide foundation knowledge on non-invasive FCM analysis in this iconic Australian marsupial. Non-invasive stress endocrinology opens up opportunities for evaluating the sub-lethal physiological effects of management activities (including caging, translocation) on the nutritional status, reproductive behaviors and disease status of captive and managed in situ Koala populations. Copyright © 2013 Elsevier Inc. All rights reserved.

Detection of activated basophils using flow cytometry for diagnosis in atopic patients.

PubMed

Cozon, G; Ferrándiz, J; Peyramond, D; Brunet, J

1999-01-01

human basophils release mediators of allergy after cross-linking of IgE receptors by allergens. Specific activation of basophils is detectable through flow cytometry (FCM) using an anti-CD63 fluorescein-conjugated monoclonal antibody. this study evaluate the detection of activated basophils by FCM in routine diagnosis of atopic diseases as regard to skin prick tests and specific immunoglobulin E antibodies. whole blood from twenty patients suspected of atopy was preincubated with interleukin-3 (IL-3), then incubated with specific allergens. After staining using anti-CD63 antibodies, activated basophils were detected through FCM. IL-3-preincubation increases the spontaneous expression of CD63 even at low concentrations (0.1 ng/ml) on the basophils of 2 patients out of 20. The sensitivity and specificity of FCM were respectively 0.56 +/- 0.17 (m +/- SD) and 1.0 +/- 0.0 for the detection of dust mite-activated basophils without IL-3 preincubation, and 0.73 +/- 0.13 and 1.0 +/- 0.0 for the detention of grass pollen-activated basophils. IL-3-preincubation increased the sensitivity in a dose-dependent manner but decreased the specificity fo FCM for detecting dust mite hypersensitivity. this method allow for rapid and easy detection of activated basophils from whole blood, and could be of interest for detecting allergies to non-conventional allergens such as pharmaceutical drugs.

TU-AB-BRA-01: Abdominal Synthetic CT Generation in Support of Liver SBRT Dose Calculation

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

Bredfeldt, JS; Liu, L; Feng, M

2016-06-15

Purpose: To demonstrate and validate a technique for generating MRI-derived synthetic CT volumes (MRCTs) in support of adaptive liver SBRT. Methods: Under IRB approval, ten hepatocellular carcinoma patients were scanned using a single MR sequence (T1 Dixon-VIBE), yielding inherently-registered water, fat, and T1-weighted images. Air-containing voxels were identified by intensity thresholding. The envelope of the anterior vertebral bodies was segmented from the fat image by fitting a shape model to vertebral body candidate voxels, then using level sets to expand the contour outward. Fuzzy-C-Means (FCM) was then used to classify each non-air voxel in the image as fat, water, bone,more » or marrow. Bone and marrow only were classified within the vertebral body envelope. The MRCT was created by integrating the product of the FCM class probability with the assigned class density for each voxel. The resulting MRCTs were deformably aligned with planning CTs and 2-ARC SBRT VMAT plans were optimized on the MRCT density maps. Fluence was copied onto the CT density grids and dose recalculated. Results: The MRCTs faithfully reproduced most of the features visible in the corresponding CT image volumes, with exceptions of ribs and posterior spinous processes. The liver, vertebral bodies, kidneys, spleen and cord all had median HU differences of less than 75 between MRCT and CT images. PTV D99% values had an average 0.2% difference (standard deviation: 0.46%) between calculations on MRCT and CT density grids. The maximum difference in dose to 0.1cc of the PTV was 0.25% (std:0.49%). OAR dose differences were similarly small (mean:0.03Gy, std:0.26Gy). The largest normal tissue complication percentage (NTCP) difference was 1.48% (mean:0.06%, std:0.54%). Conclusions: MRCTs from a single abdominal imaging sequence are promising for use in SBRT dose calculation. Future work will focus on extending models to better define bones in the upper abdomen. Supported by NIHR01EB016079 and NIH1L30CA199594-01.« less

Inserting ex vivo fluorescence confocal microscopy perioperatively in Mohs micrographic surgery expedites bedside assessment of excision margins in recurrent basal cell carcinoma.

PubMed

Longo, Caterina; Ragazzi, Moira; Castagnetti, Fabio; Gardini, Stefano; Palmieri, Tamara; Lallas, Aimilios; Moscarella, Elvira; Piana, Simonetta; Pellacani, Giovanni; Zalaudek, Iris; Argenziano, Giuseppe

2013-01-01

Mohs micrographic surgery can be employed in recurrent basal cell carcinoma, although it is a time-consuming technique. Recently, ex vivo fluorescence confocal microscopy (FCM) has been employed to obtain a fast assessment of tumor margins at the bedside. In our case we successfully employed ex vivo FCM to assess the tumor margins and we treated the persistent tumor with intensity-modulated radiation therapy. Our case demonstrates that a multidisciplinary approach is very efficient in managing complex and recurrent tumors and highlights the benefits of FCM as a new technique that can be used in the surgical theater to speed up the entire procedure.

Understanding the link between meteorology and speciated abundance of bioaerosols in an urban environment using colocated flow cytometry and real-time autofluorescence measurements

NASA Astrophysics Data System (ADS)

Negron Marty, Arnaldo; DeLeon-Rodriguez, Natasha; Waters, Samantha; Ziemba, Luke; Anderson, Bruce; Bergin, Michael; Konstantinidis, Kostas; Nenes, Athanasios

2017-04-01

The abundance and speciation of primary biological atmospheric particles (PBAP) has been of great interest due to their potential impact on human health, cloud formation and contribution to atmospheric nutrient deposition [1, 2]. During this study state-of-the-art sampling techniques and protocols have been developed and combined with the speciation of PBAP by flow cytometry (FCM). An effective FCM protocol has been developed to identify and quantify speciated bioaerosols populations. In addition, a Wideband Integrated Bioaerosol Sensor (WIBS) has been used to understand the temporal variability of the PBAP, by measuring the autofluorescence of the atmospheric particles [3]. The techniques developed here have been applied to understand the PBAP variability and abundance in downtown Atlanta under different meteorological conditions. FCM results show the presence of a low nucleic acid (LNA) and a high nucleic acid (HNA) content subpopulation. The contribution of each subpopulation to the total biological atmospheric particles (TBAP) varies depending on the predominant meteorological conditions. Results suggest the HNA subpopulation, named fungal spores, dominates the composition of the TBAP during humid and warm days after rain events. However, during dry episodes the HNA subpopulation is diminished and the LNA subpopulation dominates the composition of the TBAP in downtown Atlanta. WIBS size distribution shifts between dry periods and humid and warm periods agreed well with the LNA and HNA subpopulations behavior. Our finding suggests Atlanta average PBAP concentration is around 1-8 x 104 part. /m3during Spring, where WIBS represents the lower bound and FCM the upper bound of the quantification. Additional experiments performed with different types of pollen, fungi and bacteria were used to better understand the scattering and fluorescence properties of them under different growing phases. References: [1] Morris, C. E., F. Conen, J. Alex Huffman, V. Phillips, U. Poschl and D. C. Sands (2014). Bioprecipitation: a feedback cycle linking earth history, ecosystem dynamics and land use through biological ice nucleators in the atmosphere. Glob Chang Biol 20(2): 341-351. [2] Després, V. R., J. Alex Huffman, S. M. Burrows, C. Hoose, A. S. Safatov, G. Buryak, J., Fröhlich-Nowoisky, W. Elbert, M. O. Andreae, U. Pöschl and R. Jaenicke (2012). Primary biological aerosol particles in the atmosphere: a review. Tellus B 64(0). [3] Gabey, A. M., M. W. Gallagher, J. Whitehead, J. R. Dorsey, P. H. Kaye and W. R. Stanley (2010). Measurements and comparison of primary biological aerosol above and below a tropical forest canopy using a dual channel fluorescence spectrometer. Atmospheric Chemistry and Physics 10(10): 4453-4466.

Correlative cryogenic tomography of cells using light and soft x-rays.

PubMed

Smith, Elizabeth A; Cinquin, Bertrand P; Do, Myan; McDermott, Gerry; Le Gros, Mark A; Larabell, Carolyn A

2014-08-01

Correlated imaging is the process of imaging a specimen with two complementary modalities, and then combining the two data sets to create a highly informative, composite view. A recent implementation of this concept has been the combination of soft x-ray tomography (SXT) with fluorescence cryogenic microscopy (FCM). SXT-FCM is used to visualize cells that are held in a near-native, cryopreserved. The resultant images are, therefore, highly representative of both the cellular architecture and molecular organization in vivo. SXT quantitatively visualizes the cell and sub-cellular structures; FCM images the spatial distribution of fluorescently labeled molecules. Here, we review the characteristics of SXT-FCM, and briefly discuss how this method compares with existing correlative imaging techniques. We also describe how the incorporation of a cryo-rotation stage into a cryogenic fluorescence microscope allows acquisition of fluorescence cryogenic tomography (FCT) data. FCT is optimally suited for correlation with SXT, since both techniques image the specimen in 3-D, potentially with similar, isotropic spatial resolution. © 2013 Elsevier B.V. All rights reserved.

Lack of anodic capacitance causes power overshoot in microbial fuel cells.

PubMed

Peng, Xinhong; Yu, Han; Yu, Hongbing; Wang, Xin

2013-06-01

Power overshoot commonly makes the performance evaluation of microbial fuel cells (MFCs) inaccurate. Here, three types of carbon with different capacitance (ultracapacitor activated carbon (UAC), plain activated carbon (PAC) and carbon black (CB)) rolled on stainless steel mesh (SSM) as anodes to investigate the relationship between overshoot and anodic capacitance. It was not observed in all cycles of UAC-MFCs (from Cycle 2 to 4) due to the largest abiotic capacitance (Cm(abiotic)) of 2.1F/cm(2), while this phenomenon was eliminated in PAC-MFCs (Cm(abiotic)=1.6 F/cm(2)) from Cycle 3 and in CB-MFCs (Cm(abiotic)=0.5F/cm(2)) from Cycle 4, indicated that the Cm(abiotic) of the anode stored charges and functioned as electron shuttle to overcome the power overshoot. With bacterial colonization, the transient charge storage in biofilm resulted in a 0.1-0.4F/cm(2) increase in total capacitance for anodes, which was the possible reason for the elimination of power overshoot in PAC/CB-MFCs after multi cycle acclimation. Copyright © 2013 Elsevier Ltd. All rights reserved.

Cytometric methods for measuring bacteria in water: advantages, pitfalls and applications.

PubMed

Hammes, Frederik; Egli, Thomas

2010-06-01

Rapid detection of microbial cells is a challenge in microbiology, particularly when complex indigenous communities or subpopulations varying in viability, activity and physiological state are investigated. Flow cytometry (FCM) has developed during the last 30 years into a multidisciplinary technique for analysing bacteria. When used correctly, FCM can provide a broad range of information at the single-cell level, including (but not limited to) total counts, size measurements, nucleic acid content, cell viability and activity, and detection of specific bacterial groups or species. The main advantage of FCM is that it is fast and easy to perform. It is a robust technique, which is adaptable to different types of samples and methods, and has much potential for automation. Hence, numerous FCM applications have emerged in industrial biotechnology, food and pharmaceutical quality control, routine monitoring of drinking water and wastewater systems, and microbial ecological research in soils and natural aquatic habitats. This review focuses on the information that can be gained from the analysis of bacteria in water, highlighting some of the main advantages, pitfalls and applications.

Automatic Fatigue Detection of Drivers through Yawning Analysis

NASA Astrophysics Data System (ADS)

Azim, Tayyaba; Jaffar, M. Arfan; Ramzan, M.; Mirza, Anwar M.

This paper presents a non-intrusive fatigue detection system based on the video analysis of drivers. The focus of the paper is on how to detect yawning which is an important cue for determining driver's fatigue. Initially, the face is located through Viola-Jones face detection method in a video frame. Then, a mouth window is extracted from the face region, in which lips are searched through spatial fuzzy c-means (s-FCM) clustering. The degree of mouth openness is extracted on the basis of mouth features, to determine driver's yawning state. If the yawning state of the driver persists for several consecutive frames, the system concludes that the driver is non-vigilant due to fatigue and is thus warned through an alarm. The system reinitializes when occlusion or misdetection occurs. Experiments were carried out using real data, recorded in day and night lighting conditions, and with users belonging to different race and gender.

Safety of intravenous ferric carboxymaltose versus oral iron in patients with nondialysis-dependent CKD: an analysis of the 1-year FIND-CKD trial.

PubMed

Roger, Simon D; Gaillard, Carlo A; Bock, Andreas H; Carrera, Fernando; Eckardt, Kai-Uwe; Van Wyck, David B; Cronin, Maureen; Meier, Yvonne; Larroque, Sylvain; Macdougall, Iain C

2017-09-01

The evidence base regarding the safety of intravenous (IV) iron therapy in patients with chronic kidney disease (CKD) is incomplete and largely based on small studies of relatively short duration. FIND-CKD (ClinicalTrials.gov number NCT00994318) was a 1-year, open-label, multicenter, prospective study of patients with nondialysis-dependent CKD, anemia and iron deficiency randomized (1:1:2) to IV ferric carboxymaltose (FCM), targeting higher (400-600 µg/L) or lower (100-200 µg/L) ferritin, or oral iron. A post hoc analysis of adverse event rates per 100 patient-years was performed to assess the safety of FCM versus oral iron over an extended period. The safety population included 616 patients. The incidence of one or more adverse events was 91.0, 100.0 and 105.0 per 100 patient-years in the high ferritin FCM, low ferritin FCM and oral iron groups, respectively. The incidence of adverse events with a suspected relation to study drug was 15.9, 17.8 and 36.7 per 100 patient-years in the three groups; for serious adverse events, the incidence was 28.2, 27.9 and 24.3 per 100 patient-years. The incidence of cardiac disorders and infections was similar between groups. At least one ferritin level ≥800 µg/L occurred in 26.6% of high ferritin FCM patients, with no associated increase in adverse events. No patient with ferritin ≥800 µg/L discontinued the study drug due to adverse events. Estimated glomerular filtration rate remained the stable in all groups. These results further support the conclusion that correction of iron deficiency anemia with IV FCM is safe in patients with nondialysis-dependent CKD. © The Author 2017. Published by Oxford University Press on behalf of ERA-EDTA.

Mapping cell populations in flow cytometry data for cross‐sample comparison using the Friedman–Rafsky test statistic as a distance measure

PubMed Central

Hsiao, Chiaowen; Liu, Mengya; Stanton, Rick; McGee, Monnie; Qian, Yu

2015-01-01

Abstract Flow cytometry (FCM) is a fluorescence‐based single‐cell experimental technology that is routinely applied in biomedical research for identifying cellular biomarkers of normal physiological responses and abnormal disease states. While many computational methods have been developed that focus on identifying cell populations in individual FCM samples, very few have addressed how the identified cell populations can be matched across samples for comparative analysis. This article presents FlowMap‐FR, a novel method for cell population mapping across FCM samples. FlowMap‐FR is based on the Friedman–Rafsky nonparametric test statistic (FR statistic), which quantifies the equivalence of multivariate distributions. As applied to FCM data by FlowMap‐FR, the FR statistic objectively quantifies the similarity between cell populations based on the shapes, sizes, and positions of fluorescence data distributions in the multidimensional feature space. To test and evaluate the performance of FlowMap‐FR, we simulated the kinds of biological and technical sample variations that are commonly observed in FCM data. The results show that FlowMap‐FR is able to effectively identify equivalent cell populations between samples under scenarios of proportion differences and modest position shifts. As a statistical test, FlowMap‐FR can be used to determine whether the expression of a cellular marker is statistically different between two cell populations, suggesting candidates for new cellular phenotypes by providing an objective statistical measure. In addition, FlowMap‐FR can indicate situations in which inappropriate splitting or merging of cell populations has occurred during gating procedures. We compared the FR statistic with the symmetric version of Kullback–Leibler divergence measure used in a previous population matching method with both simulated and real data. The FR statistic outperforms the symmetric version of KL‐distance in distinguishing equivalent from nonequivalent cell populations. FlowMap‐FR was also employed as a distance metric to match cell populations delineated by manual gating across 30 FCM samples from a benchmark FlowCAP data set. An F‐measure of 0.88 was obtained, indicating high precision and recall of the FR‐based population matching results. FlowMap‐FR has been implemented as a standalone R/Bioconductor package so that it can be easily incorporated into current FCM data analytical workflows. © 2015 International Society for Advancement of Cytometry PMID:26274018

Mapping cell populations in flow cytometry data for cross-sample comparison using the Friedman-Rafsky test statistic as a distance measure.

PubMed

Hsiao, Chiaowen; Liu, Mengya; Stanton, Rick; McGee, Monnie; Qian, Yu; Scheuermann, Richard H

2016-01-01

Flow cytometry (FCM) is a fluorescence-based single-cell experimental technology that is routinely applied in biomedical research for identifying cellular biomarkers of normal physiological responses and abnormal disease states. While many computational methods have been developed that focus on identifying cell populations in individual FCM samples, very few have addressed how the identified cell populations can be matched across samples for comparative analysis. This article presents FlowMap-FR, a novel method for cell population mapping across FCM samples. FlowMap-FR is based on the Friedman-Rafsky nonparametric test statistic (FR statistic), which quantifies the equivalence of multivariate distributions. As applied to FCM data by FlowMap-FR, the FR statistic objectively quantifies the similarity between cell populations based on the shapes, sizes, and positions of fluorescence data distributions in the multidimensional feature space. To test and evaluate the performance of FlowMap-FR, we simulated the kinds of biological and technical sample variations that are commonly observed in FCM data. The results show that FlowMap-FR is able to effectively identify equivalent cell populations between samples under scenarios of proportion differences and modest position shifts. As a statistical test, FlowMap-FR can be used to determine whether the expression of a cellular marker is statistically different between two cell populations, suggesting candidates for new cellular phenotypes by providing an objective statistical measure. In addition, FlowMap-FR can indicate situations in which inappropriate splitting or merging of cell populations has occurred during gating procedures. We compared the FR statistic with the symmetric version of Kullback-Leibler divergence measure used in a previous population matching method with both simulated and real data. The FR statistic outperforms the symmetric version of KL-distance in distinguishing equivalent from nonequivalent cell populations. FlowMap-FR was also employed as a distance metric to match cell populations delineated by manual gating across 30 FCM samples from a benchmark FlowCAP data set. An F-measure of 0.88 was obtained, indicating high precision and recall of the FR-based population matching results. FlowMap-FR has been implemented as a standalone R/Bioconductor package so that it can be easily incorporated into current FCM data analytical workflows. © The Authors. Published by Wiley Periodicals, Inc. on behalf of ISAC.

Identification of cryovolcanism on Titan using fuzzy cognitive maps

NASA Astrophysics Data System (ADS)

Furfaro, Roberto; Kargel, Jeffrey S.; Lunine, Jonathan I.; Fink, Wolfgang; Bishop, Michael P.

2010-04-01

Future planetary exploration of Titan will require higher degrees of on-board automation, including autonomous determination of sites where the probability of significant scientific findings is the highest. In this paper, a novel Artificial Intelligence (AI) method for the identification and interpretation of sites that yield the highest potential of cryovolcanic activity is presented. We introduce the theory of fuzzy cognitive maps (FCM) as a tool for the analysis of remotely collected data in planetary exploration. A cognitive model embedded in a fuzzy logic framework is constructed via the synergistic interaction of planetary scientists and AI experts. As an application example, we show how FCM can be employed to solve the challenging problem of recognizing cryovolcanism from Synthetic Aperture Radar (SAR) Cassini data. The fuzzy cognitive map is constructed using what is currently known about cryovolcanism on Titan and relies on geological mapping performed by planetary scientists to interpret different locales as cryovolcanic in nature. The system is not conceived to replace the human scientific interpretation, but to enhance the scientists' ability to deal with large amounts of data, and it is a first step in designing AI systems that will be able, in the future, to autonomously make decisions in situations where human analysis and interpretation is not readily available or could not be sufficiently timely. The proposed FCM is tested on Cassini radar data to show the effectiveness of the system in reaching conclusions put forward by human experts and published in the literature. Four tests are performed using the Ta SAR image (October 2004 fly-by). Two regions (i.e. Ganesa Macula and the lobate high backscattering region East of Ganesa) are interpreted by the designed FCM as exhibiting cryovolcanism in agreement with the initial interpretation of the regions by Stofan et al. (2006). Importantly, the proposed FCM is shown to be flexible and adaptive as new data and knowledge are acquired during the course of exploration. Subsequently, the FCM has been modified to include topographic information derived from SAR stereo data. With this additional information, the map concludes that Ganesa Macula is not a cryovolcanic region. In conclusion, the FCM methodology is shown to be a critical and powerful component of future autonomous robotic spacecraft (e.g., orbiter(s), balloon(s), surface/lake lander(s), rover(s)) that will be deployed for the exploration of Titan.

Design of double fuzzy clustering-driven context neural networks.

PubMed

Kim, Eun-Hu; Oh, Sung-Kwun; Pedrycz, Witold

2018-08-01

In this study, we introduce a novel category of double fuzzy clustering-driven context neural networks (DFCCNNs). The study is focused on the development of advanced design methodologies for redesigning the structure of conventional fuzzy clustering-based neural networks. The conventional fuzzy clustering-based neural networks typically focus on dividing the input space into several local spaces (implied by clusters). In contrast, the proposed DFCCNNs take into account two distinct local spaces called context and cluster spaces, respectively. Cluster space refers to the local space positioned in the input space whereas context space concerns a local space formed in the output space. Through partitioning the output space into several local spaces, each context space is used as the desired (target) local output to construct local models. To complete this, the proposed network includes a new context layer for reasoning about context space in the output space. In this sense, Fuzzy C-Means (FCM) clustering is useful to form local spaces in both input and output spaces. The first one is used in order to form clusters and train weights positioned between the input and hidden layer, whereas the other one is applied to the output space to form context spaces. The key features of the proposed DFCCNNs can be enumerated as follows: (i) the parameters between the input layer and hidden layer are built through FCM clustering. The connections (weights) are specified as constant terms being in fact the centers of the clusters. The membership functions (represented through the partition matrix) produced by the FCM are used as activation functions located at the hidden layer of the "conventional" neural networks. (ii) Following the hidden layer, a context layer is formed to approximate the context space of the output variable and each node in context layer means individual local model. The outputs of the context layer are specified as a combination of both weights formed as linear function and the outputs of the hidden layer. The weights are updated using the least square estimation (LSE)-based method. (iii) At the output layer, the outputs of context layer are decoded to produce the corresponding numeric output. At this time, the weighted average is used and the weights are also adjusted with the use of the LSE scheme. From the viewpoint of performance improvement, the proposed design methodologies are discussed and experimented with the aid of benchmark machine learning datasets. Through the experiments, it is shown that the generalization abilities of the proposed DFCCNNs are better than those of the conventional FCNNs reported in the literature. Copyright © 2018 Elsevier Ltd. All rights reserved.

In the elderly, meat protein assimilation from rare meat is lower than that from meat that is well done.

PubMed

Buffière, Caroline; Gaudichon, Claire; Hafnaoui, Noureddine; Migné, Carole; Scislowsky, Valérie; Khodorova, Nadezda; Mosoni, Laurent; Blot, Adeline; Boirie, Yves; Dardevet, Dominique; Santé-Lhoutellier, Véronique; Rémond, Didier

2017-11-01

Background: Meat cooking conditions in in vitro and in vivo models have been shown to influence the rate of protein digestion, which is known to affect postprandial protein metabolism in the elderly. Objective: The present study was conducted to demonstrate the effect of cooking conditions on meat protein assimilation in the elderly. We used a single-meal protocol to assess the meat protein absorption rate and estimate postprandial meat protein utilization in elderly subjects. Design: The study recruited 10 elderly volunteers aged 70-82 y. Each received, on 2 separate occasions, a test meal exclusively composed of intrinsically 15 N-labeled bovine meat (30 g protein), cooked at 55°C for 5 min [rare meat (RM)] or at 90°C for 30 min [fully cooked meat (FCM)], and minced. Whole-body fluxes of leucine, before and after the meal, were determined with the use of a [1- 13 C]leucine intravenous infusion. Meat protein absorption was recorded with the use of 15 N enrichment of amino acids. Results: Postprandial time course observations showed a lower concentration in the plasma of indispensable amino acids ( P < 0.01), a lower entry rate of meat leucine in the plasma ( P < 0.01), and a lower contribution of meat nitrogen to plasma amino acid nitrogen ( P < 0.001), evidencing lower peripheral bioavailability of meat amino acids with RM than with FCM. This was associated with decreased postprandial whole-body protein synthesis with RM than with FCM (40% compared with 56% of leucine intake, respectively; P < 0.01). Conclusions: Whereas meat cooking conditions have little effect on postprandial protein utilization in young adults, the present work showed that the bioavailability and assimilation of meat amino acids in the elderly is lower when meat is poorly cooked. In view to preventing sarcopenia, elderly subjects should be advised to favor the consumption of well-cooked meat. This trial was registered at clinicaltrials.gov as NCT02157805. © 2017 American Society for Nutrition.

[Isolation and purification of primary Kupffer cells from mouse liver].

PubMed

Sun, Chao; Luo, Qingbo; Lu, Xiuxian; Zheng, Daofeng; He, Diao; Wu, Zhongjun

2016-08-01

Objective To isolate and purify Kupffer cells (KCs) from BALB/c mice by an efficient method of low-speed centrifugation and rapid adherence. Methods The mouse liver tissue was perfused in situ and digested with 0.5 g/L collagenase type IV in vitro by water bath. Then, through the low-speed centrifugation, KCs were separated from the mixed hepatocytes, and purified by rapid adherent characteristics. Finally, the production and activity of KCs obtained by this modified method were compared with those isolated by Percoll density gradient centrifugation. We used F4/80 antibody immunofluorescence technique to observe morphological features of KCs, flow cytometry (FCM) to detect the expression of F4/80 antibody and the ink uptake test to observe the phagocytic activity. Moreover, using FCM, we evaluated the expressions of molecules associated with antigen presentation, including major histocompatibility complex class II (MHC II), CD40, CD86 and CD68 on the surface of KCs subjected to hypoxia/reoxygenation (H/R) modeling. And, ELISA was conducted to measure tumor necrosis factor-α (TNF-α) production of the cultured KCs following H/R. Results The yield of KCs was (5.83±0.54)×10(6) per mouse liver and the survival rate of KCs was up to 92% by low-speed centrifugation and rapid adherent method. Compared with Percoll density gradient centrifugation [the yield of KCs was (2.19±0.43)×10(6) per liver], this new method significantly improved the yield of KCs. F4/80 immunofluorescence showed typical morphologic features of KCs such as spindle or polygon shapes and FCM identified nearly 90% F4/80 positive cells. The phagocytic assay showed that lots of ink particles were phagocytosed into the isolated cells. KC H/R models expressed more MHC II, CD40 and CD86 and produced more TNF-α participating in inflammation. Conclusion The efficient method to isolate and purify KCs from BALB /c mice has been successfully established.

Investigating the Potential of the Flipped Classroom Model in K-12 Mathematics Teaching and Learning

ERIC Educational Resources Information Center

Katsa, Maria; Sergis, Stylianos; Sampson, Demetrios G.

2016-01-01

The Flipped Classroom model (FCM) is a promising blended educational innovation aiming to improve the teaching and learning practice in various subject domains and educational levels. However, despite this encouraging evidence, research on the explicit benefits of the FCM on K-12 Mathematics education is still scarce and, in some cases, even…

Application of cluster analysis to geochemical compositional data for identifying ore-related geochemical anomalies

NASA Astrophysics Data System (ADS)

Zhou, Shuguang; Zhou, Kefa; Wang, Jinlin; Yang, Genfang; Wang, Shanshan

2017-12-01

Cluster analysis is a well-known technique that is used to analyze various types of data. In this study, cluster analysis is applied to geochemical data that describe 1444 stream sediment samples collected in northwestern Xinjiang with a sample spacing of approximately 2 km. Three algorithms (the hierarchical, k-means, and fuzzy c-means algorithms) and six data transformation methods (the z-score standardization, ZST; the logarithmic transformation, LT; the additive log-ratio transformation, ALT; the centered log-ratio transformation, CLT; the isometric log-ratio transformation, ILT; and no transformation, NT) are compared in terms of their effects on the cluster analysis of the geochemical compositional data. The study shows that, on the one hand, the ZST does not affect the results of column- or variable-based (R-type) cluster analysis, whereas the other methods, including the LT, the ALT, and the CLT, have substantial effects on the results. On the other hand, the results of the row- or observation-based (Q-type) cluster analysis obtained from the geochemical data after applying NT and the ZST are relatively poor. However, we derive some improved results from the geochemical data after applying the CLT, the ILT, the LT, and the ALT. Moreover, the k-means and fuzzy c-means clustering algorithms are more reliable than the hierarchical algorithm when they are used to cluster the geochemical data. We apply cluster analysis to the geochemical data to explore for Au deposits within the study area, and we obtain a good correlation between the results retrieved by combining the CLT or the ILT with the k-means or fuzzy c-means algorithms and the potential zones of Au mineralization. Therefore, we suggest that the combination of the CLT or the ILT with the k-means or fuzzy c-means algorithms is an effective tool to identify potential zones of mineralization from geochemical data.

Implementation of spectral clustering on microarray data of carcinoma using k-means algorithm

NASA Astrophysics Data System (ADS)

Frisca, Bustamam, Alhadi; Siswantining, Titin

2017-03-01

Clustering is one of data analysis methods that aims to classify data which have similar characteristics in the same group. Spectral clustering is one of the most popular modern clustering algorithms. As an effective clustering technique, spectral clustering method emerged from the concepts of spectral graph theory. Spectral clustering method needs partitioning algorithm. There are some partitioning methods including PAM, SOM, Fuzzy c-means, and k-means. Based on the research that has been done by Capital and Choudhury in 2013, when using Euclidian distance k-means algorithm provide better accuracy than PAM algorithm. So in this paper we use k-means as our partition algorithm. The major advantage of spectral clustering is in reducing data dimension, especially in this case to reduce the dimension of large microarray dataset. Microarray data is a small-sized chip made of a glass plate containing thousands and even tens of thousands kinds of genes in the DNA fragments derived from doubling cDNA. Application of microarray data is widely used to detect cancer, for the example is carcinoma, in which cancer cells express the abnormalities in his genes. The purpose of this research is to classify the data that have high similarity in the same group and the data that have low similarity in the others. In this research, Carcinoma microarray data using 7457 genes. The result of partitioning using k-means algorithm is two clusters.

Detection of infarct lesions from single MRI modality using inconsistency between voxel intensity and spatial location--a 3-D automatic approach.

PubMed

Shen, Shan; Szameitat, André J; Sterr, Annette

2008-07-01

Detection of infarct lesions using traditional segmentation methods is always problematic due to intensity similarity between lesions and normal tissues, so that multispectral MRI modalities were often employed for this purpose. However, the high costs of MRI scan and the severity of patient conditions restrict the collection of multiple images. Therefore, in this paper, a new 3-D automatic lesion detection approach was proposed, which required only a single type of anatomical MRI scan. It was developed on a theory that, when lesions were present, the voxel-intensity-based segmentation and the spatial-location-based tissue distribution should be inconsistent in the regions of lesions. The degree of this inconsistency was calculated, which indicated the likelihood of tissue abnormality. Lesions were identified when the inconsistency exceeded a defined threshold. In this approach, the intensity-based segmentation was implemented by the conventional fuzzy c-mean (FCM) algorithm, while the spatial location of tissues was provided by prior tissue probability maps. The use of simulated MRI lesions allowed us to quantitatively evaluate the performance of the proposed method, as the size and location of lesions were prespecified. The results showed that our method effectively detected lesions with 40-80% signal reduction compared to normal tissues (similarity index > 0.7). The capability of the proposed method in practice was also demonstrated on real infarct lesions from 15 stroke patients, where the lesions detected were in broad agreement with true lesions. Furthermore, a comparison to a statistical segmentation approach presented in the literature suggested that our 3-D lesion detection approach was more reliable. Future work will focus on adapting the current method to multiple sclerosis lesion detection.

Mapping of rock types using a joint approach by combining the multivariate statistics, self-organizing map and Bayesian neural networks: an example from IODP 323 site

NASA Astrophysics Data System (ADS)

Karmakar, Mampi; Maiti, Saumen; Singh, Amrita; Ojha, Maheswar; Maity, Bhabani Sankar

2017-07-01

Modeling and classification of the subsurface lithology is very important to understand the evolution of the earth system. However, precise classification and mapping of lithology using a single framework are difficult due to the complexity and the nonlinearity of the problem driven by limited core sample information. Here, we implement a joint approach by combining the unsupervised and the supervised methods in a single framework for better classification and mapping of rock types. In the unsupervised method, we use the principal component analysis (PCA), K-means cluster analysis (K-means), dendrogram analysis, Fuzzy C-means (FCM) cluster analysis and self-organizing map (SOM). In the supervised method, we use the Bayesian neural networks (BNN) optimized by the Hybrid Monte Carlo (HMC) (BNN-HMC) and the scaled conjugate gradient (SCG) (BNN-SCG) techniques. We use P-wave velocity, density, neutron porosity, resistivity and gamma ray logs of the well U1343E of the Integrated Ocean Drilling Program (IODP) Expedition 323 in the Bering Sea slope region. While the SOM algorithm allows us to visualize the clustering results in spatial domain, the combined classification schemes (supervised and unsupervised) uncover the different patterns of lithology such of as clayey-silt, diatom-silt and silty-clay from an un-cored section of the drilled hole. In addition, the BNN approach is capable of estimating uncertainty in the predictive modeling of three types of rocks over the entire lithology section at site U1343. Alternate succession of clayey-silt, diatom-silt and silty-clay may be representative of crustal inhomogeneity in general and thus could be a basis for detail study related to the productivity of methane gas in the oceans worldwide. Moreover, at the 530 m depth down below seafloor (DSF), the transition from Pliocene to Pleistocene could be linked to lithological alternation between the clayey-silt and the diatom-silt. The present results could provide the basis for the detailed study to get deeper insight into the Bering Sea' sediment deposition and sequence.

Responses of Escherichia coli, Listeria monocytogenes, and Staphylococcus aureus to Simulated Food Processing Treatments, Determined Using Fluorescence-Activated Cell Sorting and Plate Counting▿

PubMed Central

Kennedy, Deirdre; Cronin, Ultan P.; Wilkinson, Martin G.

2011-01-01

Three common food pathogenic microorganisms were exposed to treatments simulating those used in food processing. Treated cell suspensions were then analyzed for reduction in growth by plate counting. Flow cytometry (FCM) and fluorescence-activated cell sorting (FACS) were carried out on treated cells stained for membrane integrity (Syto 9/propidium iodide) or the presence of membrane potential [DiOC2(3)]. For each microbial species, representative cells from various subpopulations detected by FCM were sorted onto selective and nonselective agar and evaluated for growth and recovery rates. In general, treatments giving rise to the highest reductions in counts also had the greatest effects on cell membrane integrity and membrane potential. Overall, treatments that impacted cell membrane permeability did not necessarily have a comparable effect on membrane potential. In addition, some bacterial species with extensively damaged membranes, as detected by FCM, appeared to be able to replicate and grow after sorting. Growth of sorted cells from various subpopulations was not always reflected in plate counts, and in some cases the staining protocol may have rendered cells unculturable. Optimized FCM protocols generated a greater insight into the extent of the heterogeneous bacterial population responses to food control measures than did plate counts. This study underlined the requirement to use FACS to relate various cytometric profiles generated by various staining protocols with the ability of cells to grow on microbial agar plates. Such information is a prerequisite for more-widespread adoption of FCM as a routine microbiological analytical technique. PMID:21602370

Monitoring stress in captive and free-ranging African wild dogs (Lycaon pictus) using faecal glucocorticoid metabolites.

PubMed

Van der Weyde, L K; Martin, G B; Paris, M C J

2016-01-15

An understanding of stress physiology is important for species management because high levels of stress can hamper reproduction and affect an individual's ability to cope with threats to their survival, such as disease and human-wildlife conflict. A commonly used indicator of stress, faecal concentrations of cortisol metabolites (FCM), can be used to assess the impact of social, biological and environmental factors. Measurements of FCM are particularly valuable for endangered species that are logistically challenging to study and where non-invasive techniques are preferred. As the second most endangered canid in Africa, the African wild dog (Lycaon pictus) has been the focus of considerable conservation research, yet there is still little understanding of factors associated with stress, in either captive or free-ranging populations. The present study therefore aimed to determine whether stress levels differ between captive and free-ranging populations, and to detect social, biological and environmental factors that are stressful in these populations. Faecal samples were collected from 20 captive and 62 free-ranging animals. Within free-ranging populations, the sexes differed significantly, but there was no effect of social status, age or breeding period for either sex. Captive females had higher FCM concentrations than free-ranging females. In captive populations, FCM concentrations differed among zoos and with reproductive status in females, but were not related to age class or group-housing structure. In conclusion, FCM is a useful indicator of stress and should be considered an integrative aspect of management, for both in situ and ex situ African wild dog populations. Copyright © 2015 Elsevier Inc. All rights reserved.

Ex vivo fluorescence confocal microscopy for fast evaluation of tumour margins during Mohs surgery.

PubMed

Bennàssar, A; Vilata, A; Puig, S; Malvehy, J

2014-02-01

Ex vivo fluorescence confocal microscopy (FCM) enables real-time imaging of skin morphology directly in freshly excised tissue. FCM displays wide field-of-view mosaics with cellular resolution, thus enabling a rapid bedside pathology. An application of interest is rapid detection of residual basal cell carcinoma (BCC) in skin excisions during Mohs surgery. We sought to evaluate the sensitivity and specificity of ex vivo imaging with FCM for the detection of residual BCC in Mohs tissue excisions, and to calculate the time invested up to the diagnosis for both FCM and frozen sections. Eighty consecutive BCCs were prospectively collected and the margins scanned with ex vivo FCM, including excisions with and without residual BCC of all major subtypes. Each mosaic was divided into two or four, resulting in 480 submosaics for study. Every confocal submosaic was assessed for the presence or absence of BCC and compared with standard frozen sections as the gold standard. Furthermore, the time spent for each technique was calculated and compared. The overall sensitivity and specificity of detecting residual BCC were 88% and 99%, respectively. Moreover, the new technique reduced by almost two-thirds the time invested when compared with the processing of a frozen section (P < 0·001). The results demonstrate the feasibility of confocal mosaicing microscopy in fresh tissue for rapid surgical pathology, potentially to expedite and guide Mohs surgery with high accuracy. This observation is an important step towards the goal of using real-time surgical pathology for skin tumours. © 2013 British Association of Dermatologists.

Integrating bioassays and analytical chemistry as an improved approach to support safety assessment of food contact materials.

PubMed

Veyrand, Julien; Marin-Kuan, Maricel; Bezencon, Claudine; Frank, Nancy; Guérin, Violaine; Koster, Sander; Latado, Hélia; Mollergues, Julie; Patin, Amaury; Piguet, Dominique; Serrant, Patrick; Varela, Jesus; Schilter, Benoît

2017-10-01

Food contact materials (FCM) contain chemicals which can migrate into food and result in human exposure. Although it is mandatory to ensure that migration does not endanger human health, there is still no consensus on how to pragmatically assess the safety of FCM since traditional approaches would require extensive toxicological and analytical testing which are expensive and time consuming. Recently, the combination of bioassays, analytical chemistry and risk assessment has been promoted as a new paradigm to identify toxicologically relevant molecules and address safety issues. However, there has been debate on the actual value of bioassays in that framework. In the present work, a FCM anticipated to release the endocrine active chemical 4-nonyphenol (4NP) was used as a model. In a migration study, the leaching of 4NP was confirmed by LC-MS/MS and GC-MS. This was correlated with an increase in both estrogenic and anti-androgenic activities as measured with bioassays. A standard risk assessment indicated that according to the food intake scenario applied, the level of 4NP measured was lower, close or slightly above the acceptable daily intake. Altogether these results show that bioassays could reveal the presence of an endocrine active chemical in a real-case FCM migration study. The levels reported were relevant for safety assessment. In addition, this work also highlighted that bioactivity measured in migrate does not necessarily represent a safety issue. In conclusion, together with analytics, bioassays contribute to identify toxicologically relevant molecules leaching from FCM and enable improved safety assessment.

Physiological response to etho-ecological stressors in male Alpine chamois: timescale matters!

PubMed

Corlatti, Luca; Palme, Rupert; Lovari, Sandro

2014-07-01

From a life history perspective, glucocorticoids secreted by the neuroendocrine system, integrating different sources of stress through an adaptive feedback mechanism, may have important consequences on individual fitness. Although stress responses have been the object of several investigations, few studies have explored the role of proximate mechanisms responsible for the potential trade-offs between physiological stress and life history traits integrating social and environmental stressors. In 2011 and 2012, we collected data on faecal cortisol metabolites (FCM) in a marked male population of Alpine chamois, within the Gran Paradiso National Park (Italy). Using a model selection approach we analysed the effect of potential etho-ecological stressors such as age, social status (territorial vs. non-territorial males), minimum temperature, snow depth and precipitation on FCM variation. To correctly interpret environmentally and socially induced stress responses, we conducted model selections over multiple temporal scales defined a priori: year, cold months, spring, warm months, mating season. Over the year, FCM levels showed a negative relationship with minimum temperature, but altogether, climatic stressors had negligible effects on glucocorticoid secretion, possibly owing to good adaptations of chamois to severe weather conditions. Age was negatively related to FCM during the rut, possibly due to greater experience of older males in agonistic contests. Social status was an important determinant of FCM excretion: while both the 'stress of subordination' and the 'stress of domination' hypotheses received some support in spring and during the mating season, respectively, previous data suggest that only the latter may have detrimental fitness consequences on male chamois.

Phthalates and food-contact materials: enforcing the 2008 European Union plastics legislation.

PubMed

Petersen, J H; Jensen, L K

2010-11-01

The migration of phthalates into foodstuffs from food-contact materials (FCM) is a well-known source of food contamination. In 2005, the European Food Safety Authority finalized its risk assessment for several of the classical phthalate plasticizers. In their risk management procedure the European Commission transformed the tolerable daily intakes established by the Authority into legislative limits for phthalates in both plastic and food simulants, while taking exposure from other sources into consideration. These limits have been into force since 1 July 2008. A detailed interpretation of the regulation of these substances was agreed upon in the European network of FCM reference laboratories. This paper reports results from a Danish control campaign of samples collected by official food inspectors and analysed by a newly validated analytical method run under accreditation. Samples were from FCM producers, FCM importers and importers of packed foodstuffs from third-party countries. Products containing phthalates above the current limits were found in several categories of FCM: conveyor belts (six of six), lids from packed foodstuffs in glasses (eight of 28), tubes for liquid foodstuffs (four of five) and gloves (five of 14). More than 20% of the samples analysed contained dibutylphthalate (DBP) or di-(2-ethylhexyl)phthalate (DEHP) above the compositional limits of 0.05% and 0.1%, respectively. Analysis of residual phthalates in metal lid gaskets instead of analysis of phthalates in the food when controlling foodstuffs packed outside the European Union proved to be an efficient and simple control method. All findings of phthalates were associated with the use of plasticized polyvinylchloride (PVC).

Physiological response to etho-ecological stressors in male Alpine chamois: timescale matters!

NASA Astrophysics Data System (ADS)

Corlatti, Luca; Palme, Rupert; Lovari, Sandro

2014-07-01

From a life history perspective, glucocorticoids secreted by the neuroendocrine system, integrating different sources of stress through an adaptive feedback mechanism, may have important consequences on individual fitness. Although stress responses have been the object of several investigations, few studies have explored the role of proximate mechanisms responsible for the potential trade-offs between physiological stress and life history traits integrating social and environmental stressors. In 2011 and 2012, we collected data on faecal cortisol metabolites (FCM) in a marked male population of Alpine chamois, within the Gran Paradiso National Park (Italy). Using a model selection approach we analysed the effect of potential etho-ecological stressors such as age, social status (territorial vs. non-territorial males), minimum temperature, snow depth and precipitation on FCM variation. To correctly interpret environmentally and socially induced stress responses, we conducted model selections over multiple temporal scales defined a priori: year, cold months, spring, warm months, mating season. Over the year, FCM levels showed a negative relationship with minimum temperature, but altogether, climatic stressors had negligible effects on glucocorticoid secretion, possibly owing to good adaptations of chamois to severe weather conditions. Age was negatively related to FCM during the rut, possibly due to greater experience of older males in agonistic contests. Social status was an important determinant of FCM excretion: while both the `stress of subordination' and the `stress of domination' hypotheses received some support in spring and during the mating season, respectively, previous data suggest that only the latter may have detrimental fitness consequences on male chamois.

Cumulative asbestos exposure for US automobile mechanics involved in brake repair (circa 1950s-2000).

PubMed

Finley, Brent L; Richter, Richard O; Mowat, Fionna S; Mlynarek, Steve; Paustenbach, Dennis J; Warmerdam, John M; Sheehan, Patrick J

2007-11-01

We analyzed cumulative lifetime exposure to chrysotile asbestos experienced by brake mechanics in the US during the period 1950-2000. Using Monte Carlo methods, cumulative exposures were calculated using the distribution of 8-h time-weighted average exposure concentrations for brake mechanics and the distribution of job tenure data for automobile mechanics. The median estimated cumulative exposures for these mechanics, as predicted by three probabilistic models, ranged from 0.16 to 0.41 fibers per cubic centimeter (f/cm(3)) year for facilities with no dust-control procedures (1970s), and from 0.010 to 0.012 f/cm(3) year for those employing engineering controls (1980s). Upper-bound (95%) estimates for the 1970s and 1980s were 1.96 to 2.79 and 0.07-0.10 f/cm(3) year, respectively. These estimates for US brake mechanics are consistent with, but generally slightly lower than, those reported for European mechanics. The values are all substantially lower than the cumulative exposure of 4.5 f/cm(3) year associated with occupational exposure to 0.1 f/cm(3) of asbestos for 45 years that is currently permitted under the current occupational exposure limits in the US. Cumulative exposures were usually about 100- to 1,000-fold less than those of other occupational groups with asbestos exposure for similar time periods. The cumulative lifetime exposure estimates presented here, combined with the negative epidemiology data for brake mechanics, could be used to refine the risk assessments for chrysotile-exposed populations.

Endoreduplication intensity as a marker of seed developmental stage in the Fabaceae.

PubMed

Rewers, Monika; Sliwinska, Elwira

2012-12-01

Flow cytometry (FCM) can be used to study cell cycle activity in developing, mature and germinating seeds. It provides information about a seed's physiological state and therefore can be used by seed growers for assessing optimal harvest times and presowing treatments. Because an augmented proportion of 4C nuclei usually is indicative of high mitotic activity, the 4C/2C ratio is commonly used to follow the progress of seed development and germination. However, its usefulness for polysomatic (i.e., containing cells with different DNA content) seeds is questioned. Changes in cell cycle/endoreduplication activity in developing seeds of five members of the Fabaceae were studied to determine a more suitable marker of seed developmental stages for polysomatic species based on FCM measurements. Seeds of Phaseolus vulgaris, Medicago sativa, Pisum sativum, Vicia sativa, and Vicia faba var. minor were collected 20, 30, 40, 50, and 60 days after flowering (DAF), embryos were isolated and the proportion of nuclei with different DNA contents in the embryo axis and cotyledon was established. The ratios 4C/2C and (Σ>2C)/2C were calculated. Dried seeds were subjected to laboratory germination tests following international seed testing association (ISTA) rules. Additionally, the absolute nuclear DNA content was estimated in the leaves of the studied species. During seed development nuclei with DNA contents from 2C to 128C were detected; the endopolyploidy pattern depended on the species, seed organ and developmental stage. The cell cycle/endoreduplication parameters correlated negatively with genome size. The (Σ>2C)/2C ratio in the cotyledons reflected the seed developmental stage and corresponded with seed germinability. Therefore, this ratio is recommended as a marker in polysomatic seed research and production instead of the 4C/2C ratio, which does not consider the occurrence of endopolyploid cells. Copyright © 2012 International Society for Advancement of Cytometry.

Neutronics Studies of Uranium-bearing Fully Ceramic Micro-encapsulated Fuel for PWRs

DOE PAGES

George, Nathan M.; Maldonado, G. Ivan; Terrani, Kurt A.; ...

2014-12-01

Our study evaluated the neutronics and some of the fuel cycle characteristics of using uranium-based fully ceramic microencapsulated (FCM) fuel in a pressurized water reactor (PWR). Specific PWR lattice designs with FCM fuel have been developed that are expected to achieve higher specific burnup levels in the fuel while also increasing the tolerance to reactor accidents. The SCALE software system was the primary analysis tool used to model the lattice designs. A parametric study was performed by varying tristructural isotropic particle design features (e.g., kernel diameter, coating layer thicknesses, and packing fraction) to understand the impact on reactivity and resultingmore » operating cycle length. Moreover, to match the lifetime of an 18-month PWR cycle, the FCM particle fuel design required roughly 10% additional fissile material at beginning of life compared with that of a standard uranium dioxide (UO 2) rod. Uranium mononitride proved to be a favorable fuel for the fuel kernel due to its higher heavy metal loading density compared with UO 2. The FCM fuel designs evaluated maintain acceptable neutronics design features for fuel lifetime, lattice peaking factors, and nonproliferation figure of merit.« less

Comparison between Flow Cytometry and Traditional Culture Methods for Efficacy Assessment of Six Disinfectant Agents against Nosocomial Bacterial Species

PubMed Central

Massicotte, Richard; Mafu, Akier A.; Ahmad, Darakhshan; Deshaies, Francis; Pichette, Gilbert; Belhumeur, Pierre

2017-01-01

The present study was undertaken to compare the use of flow cytometry (FCM) and traditional culture methods for efficacy assessment of six disinfectants used in Quebec hospitals including: two quaternary ammonium-based, two activated hydrogen peroxide-based, one phenol-based, and one sodium hypochlorite-based. Four nosocomial bacterial species, Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, and Vancomycin-resistant Enterococci faecalis, were exposed to minimum lethal concentrations (MLCs) and sublethal concentrations (1/2 MLCs) of disinfectants under study. The results showed a strong correlation between the two techniques for the presence of dead and live cell populations, as well as, evidence of injured populations with the FCM. The only exception was observed with sodium hypochlorite at higher concentrations where fluorescence was diminished and underestimating dead cell population. The results also showed that FCM can replace traditional microbiological methods to study disinfectant efficacy on bacteria. Furthermore, FCM profiles for E. coli and E. faecalis cells exposed to sublethal concentrations exhibited distinct populations of injured cells, opening a new aspect for future research and investigation to elucidate the role of injured, cultural/noncuturable/resuscitable cell populations in infection control. PMID:28217115

Effects of Feed Supplementation in Friesien Holstein Crossbreed Cows at the First Quarter on the Production and Quality of Milk

NASA Astrophysics Data System (ADS)

Suharyono; Hardani, S. N. W.; Sitoresmi, P. D.; Adiarto

2018-02-01

Nine heads of dairy cows were used in the study. The dairy cows were in 7-8 months pregnant condition, lactation II and were expected calving soon.The purpose of this study was to determine the effect of feed supplementation to increase the production and quality of milk. The feeding treatment was divided into 3 groups, G1 (control) given the usual feed given by livestock owners, G11 was given GI+500 g UMMB/h/d and G111 was given GI + 500 g MFS/h/d. Variables observed were feed and nutritional consumption, average milk production, milk quality, cumulative milk production, average 4% fat corrected milk (FCM) production, peak milk production. The experimental design used a completely randomized design of direct pattern, continued by Duncan’s new multiple range test (DMRT) if there were a significant difference of variable values between treatments. The results showed that the addition of dietary supplement significantly affected the mean consumption of crude protein between GIII and G1 and G11, respectively 1.22 kg/d versus 0.99 and 0.33 kg/d. The average milk production was also influenced by the addition of dietary supplement that was between G1; G11 and G111, respectively 9.55; 10.69 and 11.85 l/d. Cumulative milk and 4% FCM production were also significantly different at P <0.05, with value of each G1; G11 and G111 was 954.98; 1068.70 and 1184.57 l; 10.72; 12.06 and 13.70 kg/d respectively. The conclusion was MFS to be able to increase cumulative and 4% FCM milk production.

Phase-sensitive flow cytometer

DOEpatents

Steinkamp, John A.

1993-01-01

A phase-sensitive flow cytometer (FCM) provides additional FCM capability to use the fluorescence lifetime of one or more fluorochromes bound to single cells to provide additional information regarding the cells. The resulting fluorescence emission can be resolved into individual fluorescence signals if two fluorochromes are present or can be converted directly to a decay lifetime from a single fluorochrome. The excitation light for the fluorochromes is modulated to produce an amplitude modulated fluorescence pulse as the fluorochrome is excited in the FCM. The modulation signal also forms a reference signal that is phase-shifted a selected amount for subsequent mixing with the output modulated fluorescence intensity signal in phase-sensitive detection circuitry. The output from the phase-sensitive circuitry is then an individual resolved fluorochrome signal or a single fluorochrome decay lifetime, depending on the applied phase shifts.

'Outbreak Gold Standard' selection to provide optimized threshold for infectious diseases early-alert based on China Infectious Disease Automated-alert and Response System.

PubMed

Wang, Rui-Ping; Jiang, Yong-Gen; Zhao, Gen-Ming; Guo, Xiao-Qin; Michael, Engelgau

2017-12-01

The China Infectious Disease Automated-alert and Response System (CIDARS) was successfully implemented and became operational nationwide in 2008. The CIDARS plays an important role in and has been integrated into the routine outbreak monitoring efforts of the Center for Disease Control (CDC) at all levels in China. In the CIDARS, thresholds are determined using the "Mean+2SD‟ in the early stage which have limitations. This study compared the performance of optimized thresholds defined using the "Mean +2SD‟ method to the performance of 5 novel algorithms to select optimal "Outbreak Gold Standard (OGS)‟ and corresponding thresholds for outbreak detection. Data for infectious disease were organized by calendar week and year. The "Mean+2SD‟, C1, C2, moving average (MA), seasonal model (SM), and cumulative sum (CUSUM) algorithms were applied. Outbreak signals for the predicted value (Px) were calculated using a percentile-based moving window. When the outbreak signals generated by an algorithm were in line with a Px generated outbreak signal for each week, this Px was then defined as the optimized threshold for that algorithm. In this study, six infectious diseases were selected and classified into TYPE A (chickenpox and mumps), TYPE B (influenza and rubella) and TYPE C [hand foot and mouth disease (HFMD) and scarlet fever]. Optimized thresholds for chickenpox (P 55 ), mumps (P 50 ), influenza (P 40 , P 55 , and P 75 ), rubella (P 45 and P 75 ), HFMD (P 65 and P 70 ), and scarlet fever (P 75 and P 80 ) were identified. The C1, C2, CUSUM, SM, and MA algorithms were appropriate for TYPE A. All 6 algorithms were appropriate for TYPE B. C1 and CUSUM algorithms were appropriate for TYPE C. It is critical to incorporate more flexible algorithms as OGS into the CIDRAS and to identify the proper OGS and corresponding recommended optimized threshold by different infectious disease types.

Comparative safety of intravenous Ferumoxytol versus Ferric Carboxymaltose for the Treatment of Iron Deficiency Anemia: rationale and study design of a randomized double-blind study with a focus on acute hypersensitivity reactions.

PubMed

Adkinson, N Franklin; Strauss, William E; Bernard, Kristine; Kaper, Robert F; Macdougall, Iain C; Krop, Julie S

2017-01-01

Intravenous (IV) iron is often used to treat iron deficiency anemia in patients who are unable to tolerate or are inadequately managed with oral iron. However, IV iron treatment has been associated with acute hypersensitivity reactions. The comparative risk of adverse events (AEs) with IV iron preparations has been assessed by a few randomized controlled trials, which are most often limited by small patient numbers, which lack statistical power to identify differences in low-frequency AE such as hypersensitivity reactions. Ferumoxytol versus Ferric Carboxymaltose for the Treatment of Iron Deficiency Anemia (FIRM) is a randomized, double-blind, international, multicenter, Phase III study designed to compare the safety of ferumoxytol and ferric carboxymaltose (FCM). The study includes adults with hemoglobin <12.0 g/dL (females) or <14.0 g/dL (males), transferrin saturation ≤20% or ferritin ≤100 ng/mL within 60 days of dosing, and a history of unsatisfactory or nontolerated oral iron therapy or in whom oral iron therapy is inappropriate. Patients are randomized (1:1) to ferumoxytol 510 mg or FCM 750 mg, each given intravenously on days 1 and 8. Primary end points are the incidence of moderate-to-severe hypersensitivity reactions, including anaphylaxis, and moderate-to-severe hypotension. All potential hypersensitivity and hypotensive reactions will be adjudicated by a blinded, independent Clinical Events Committee. A secondary safety end point is the composite frequency of moderate-to-severe hypersensitivity reactions, including anaphylaxis, serious cardiovascular events, and death. Secondary efficacy end points include mean change in hemoglobin and mean change in hemoglobin per milligram of iron administered from baseline to week 5. Urinary excretion of phosphorus and the occurrence of hypophosphatemia after IV iron administration will be examined as well as the mechanisms of such hypophosphatemia in a substudy. FIRM will provide data on the comparative safety of ferumoxytol and FCM, two IV iron preparations with similar dosing schedules, focusing on moderate-to-severe hypersensitivity reactions, including anaphylaxis, and moderate-to-severe hypotension. The study plans to enroll 2000 patients and is expected to complete in 2017.

Evaluation of slide based cytometry (SBC) for concentration measurements of fluorescent dyes in solution

NASA Astrophysics Data System (ADS)

Pierzchalski, Arkadiusz; Marecka, Monika; Müller, Hans-Willy; Bocsi, József; Tárnok, Attila

2009-02-01

Flow cytometers (FCM) are built for particle measurements. In principle, concentration measurement of a homogeneous solution is not possible with FCM due to the lack of a trigger signal. In contrast to FCM slide based cytometry systems could act as tools for the measurement of concentrations using volume defined cell counting chambers. These chambers enable to analyze a well defined volume. Sensovation AG (Stockach, Germany) introduced an automated imaging system that combines imaging with cytometric features analysis. Aim of this study was to apply this imaging system to quantify the fluorescent molecule concentrations. The Lumisens (Sensovation AG) slide-based technology based on fluorescence digital imaging microscopy was used. The instrument is equipped with an inverted microscope, blue and red LEDs, double band-pass filters and a high-resolution cooled 16-bit digital camera. The instrument was focussed on the bottom of 400μm deep 6 chamber slides (IBIDI GmbH, Martinsried, Germany) or flat bottom 96 well plates (Greiner Bio One GmbH, Frickenhausen, Germany). Fluorescent solutions were imaged under 90% pixel saturation in a broad concentration range (FITC: 0.0002-250 μg/ml, methylene blue (MethB): 0.0002-250 μg/ml). Exposition times were recorded. Images were analysed by the iCys (CompuCyte Corp., Cambridge, MA, USA) image analysis software with the phantom contour function. Relative fluorescence intensities were calculated from mean fluorescence intensities per phantom contours divided by the exposition time. Solution concentrations could be distinguished over a broad dynamic range of 3.5 to 5.5 decades log (range FITC: 0.0002-31.25μg/ml, MethB: 0.0076-31.25μg/ml) with a good linear relationship between dye concentration and relative fluorescence intensity. The minimal number of fluorescent molecules per pixel as determined by the mean fluorescence intensity and the molecular weight of the fluorochrome were about 800 molecules FITC and ~2.000 MethB. The novel slide-based imaging system is suitable for detection of fluorescence differences over a broad range of concentrations. This approach may lead to novel assays for measuring concentration differences in cell free solutions and cell cultures e.g. in secretion assays.

Numerical modeling of flow and transport in the far-field of a generic nuclear waste repository in fractured crystalline rock using updated fracture continuum model

NASA Astrophysics Data System (ADS)

Hadgu, T.; Kalinina, E.; Klise, K. A.; Wang, Y.

2016-12-01

Disposal of high-level radioactive waste in a deep geological repository in crystalline host rock is one of the potential options for long term isolation. Characterization of the natural barrier system is an important component of the disposal option. In this study we present numerical modeling of flow and transport in fractured crystalline rock using an updated fracture continuum model (FCM). The FCM is a stochastic method that maps the permeability of discrete fractures onto a regular grid. The original method by McKenna and Reeves (2005) has been updated to provide capabilities that enhance representation of fractured rock. As reported in Hadgu et al. (2015) the method was first modified to include fully three-dimensional representations of anisotropic permeability, multiple independent fracture sets, and arbitrary fracture dips and orientations, and spatial correlation. More recently the FCM has been extended to include three different methods. (1) The Sequential Gaussian Simulation (SGSIM) method uses spatial correlation to generate fractures and define their properties for FCM (2) The ELLIPSIM method randomly generates a specified number of ellipses with properties defined by probability distributions. Each ellipse represents a single fracture. (3) Direct conversion of discrete fracture network (DFN) output. Test simulations were conducted to simulate flow and transport using ELLIPSIM and direct conversion of DFN methods. The simulations used a 1 km x 1km x 1km model domain and a structured with grid block of size of 10 m x 10m x 10m, resulting in a total of 106 grid blocks. Distributions of fracture parameters were used to generate a selected number of realizations. For each realization, the different methods were applied to generate representative permeability fields. The PFLOTRAN (Hammond et al., 2014) code was used to simulate flow and transport in the domain. Simulation results and analysis are presented. The results indicate that the FCM approach is a viable method to model fractured crystalline rocks. The FCM is a computationally efficient way to generate realistic representation of complex fracture systems. This approach is of interest for nuclear waste disposal models applied over large domains. SAND2016-7509 A

Nutrient digestibility and milk production responses to increasing levels of palmitic acid supplementation vary in cows receiving diets with or without whole cottonseed.

PubMed

Rico, J E; de Souza, J; Allen, M S; Lock, A L

2017-01-01

Our study evaluated the dose-dependent effects of a palmitic acid-enriched supplement in basal diets with or without the inclusion of whole cottonseed on nutrient digestibility and production responses of dairy cows. Sixteen Holstein cows (149 ± 56 days in milk) were used in a split plot Latin square design experiment. Cows were blocked by 3.5% fat-corrected milk (FCM) and allocated to a main plot receiving either a basal diet with soyhulls (SH, = 8) or a basal diet with whole cottonseed (CS, = 8) that was fed throughout the experiment. A palmitic acid-enriched supplement (PA 88.5% C16:0) was fed at 0, 0.75, 1.50, or 2.25% of ration DM in a replicated 4 × 4 Latin Square design within each basal diet group. Periods were 14 d with the final 4 d used for data collection. PA dose increased milk fat content linearly, and cubically affected yields of milk fat and 3.5% FCM. The PA dose did not affect milk protein and lactose contents, BW, and BCS, but tended to increase yields of milk, milk protein, and milk lactose. Also, PA dose reduced DMI and 16-carbon fatty acid digestibility quadratically, and increased 18-carbon fatty acid digestibility quadratically. There were no effects of basal diet on the yield of milk or milk components, but DMI tended to decrease in CS compared with SH, increasing feed efficiency (3.5% FCM/DMI). Compared with SH, CS diets increased yield of preformed milk fatty acids and 16-carbon fatty acid digestibility, and tended to decrease 18-carbon fatty acid digestibility. We observed basal diet × PA dose interactions for yields of milk and milk protein and for 16-carbon and total fatty acid digestibility, as well as tendency for yields of milk fat and 3.5% FCM. Also, there was a tendency for an interaction between basal diet and PA dose for NDF digestibility, which increased more for CS with increasing PA than for SH. PA dose linearly decreased digestibility of total fatty acids in SH diets but did not affect it in CS diets Results demonstrate that responses to PA dose are affected by the dietary basal diet. Additionally, the decrease in fatty acid digestibility only in the SH diets suggests that digestibility is impacted mainly by the profile of 16- and 18-carbon fatty acids reaching the duodenum. Under the dietary conditions evaluated, the yield of 3.5% FCM and milk fat were optimal when PA was fed at 1.5% of ration DM.

Aneuploidy in benign tumors and nonneoplastic lesions of musculoskeletal tissues.

PubMed

Alho, A; Skjeldal, S; Pettersen, E O; Melvik, J E; Larsen, T E

1994-02-15

Aneuploidy in DNA flow cytometry (FCM) of musculoskeletal tumors is generally considered to be a sign of malignancy. Previously, giant cell tumor of the bone has been reported to contain aneuploid (near-diploid) DNA stemlines. Otherwise, only spordic cases have been reported. The authors wanted to study the relationships among DNA FCM, histology, and clinical course of nonmalignant musculoskeletal lesions. Twenty-eight histologically benign tumors and seven nonneoplastic lesions were subjected to DNA FCM: After tissue preparation mechanically and with ribonuclease and trypsin, the isolated nuclei were stained with propidium iodine using chicken and rainbow trout erythrocytes as controls. In the DNA FCM histograms, ploidy and cell cycle fractions were determined using a computerized mathematical model. The histologic diagnoses were made without knowledge of the DNA FCM results. Aneuploidy was found in eight lesions. A shoulder in the diploid peak, suggesting a diploid and a near-diploid population, was found in DNA histograms of a condensing osteitis of the clavicle (a benign inflammatory process) and of a giant cell tumor of bone. The latter lesion also had a tetraploid population. Six benign tumors--two enchondromas, one osteochondroma, one subcutaneous and one intramuscular lipoma, and a calcifying aponeurotic fibroma--showed clear aneuploidy with separate peaks. The S-phase fraction was less than 10% in all cases. The highest aneuploid population, DNA index = 1.70, in a subcutaneous lipoma, was small, with an undetectable S phase. Despite nonradical operations in seven lesions, no recurrences were observed during a median follow-up of 49 months (range, 28-73 months). Small aneuploid populations with low DNA synthetic activity may be compatible with a benign histologic picture and uneventful clinical course of the musculoskeletal lesion.

Atmospheric Energy Deposition Modeling and Inference for Varied Meteoroid Structures

NASA Technical Reports Server (NTRS)

Wheeler, Lorien; Mathias, Donovan; Stokan, Edward; Brown, Peter

2018-01-01

Asteroids populations are highly diverse, ranging from coherent monoliths to loosely-bound rubble piles with a broad range of material and compositional properties. These different structures and properties could significantly affect how an asteroid breaks up and deposits energy in the atmosphere, and how much ground damage may occur from resulting blast waves. We have previously developed a fragment-cloud model (FCM) for assessing the atmospheric breakup and energy deposition of asteroids striking Earth. The approach represents ranges of breakup characteristics by combining progressive fragmentation with releases of variable fractions of debris and larger discrete fragments. In this work, we have extended the FCM to also represent asteroids with varied initial structures, such as rubble piles or fractured bodies. We have used the extended FCM to model the Chelyabinsk, Benesov, Kosice, and Tagish Lake meteors, and have obtained excellent matches to energy deposition profiles derived from their light curves. These matches provide validation for the FCM approach, help guide further model refinements, and enable inferences about pre-entry structure and breakup behavior. Results highlight differences in the amount of small debris vs. discrete fragments in matching the various flare characteristics of each meteor. The Chelyabinsk flares were best represented using relatively high debris fractions, while Kosice and Benesov cases were more notably driven by their discrete fragmentation characteristics, perhaps indicating more cohesive initial structures. Tagish Lake exhibited a combination of these characteristics, with lower-debris fragmentation at high altitudes followed by sudden disintegration into small debris in the lower flares. Results from all cases also suggest that lower ablation coefficients and debris spread rates may be more appropriate for the way in which debris clouds are represented in FCM, offering an avenue for future model refinement.

Computational methods for evaluation of cell-based data assessment--Bioconductor.

PubMed

Le Meur, Nolwenn

2013-02-01

Recent advances in miniaturization and automation of technologies have enabled cell-based assay high-throughput screening, bringing along new challenges in data analysis. Automation, standardization, reproducibility have become requirements for qualitative research. The Bioconductor community has worked in that direction proposing several R packages to handle high-throughput data including flow cytometry (FCM) experiment. Altogether, these packages cover the main steps of a FCM analysis workflow, that is, data management, quality assessment, normalization, outlier detection, automated gating, cluster labeling, and feature extraction. Additionally, the open-source philosophy of R and Bioconductor, which offers room for new development, continuously drives research and improvement of theses analysis methods, especially in the field of clustering and data mining. This review presents the principal FCM packages currently available in R and Bioconductor, their advantages and their limits. Copyright © 2012 Elsevier Ltd. All rights reserved.

Diagnostic Flow Cytometry and the AIDS Pandemic.

PubMed

Clift, Ian C

2015-01-01

The onset of the AIDS pandemic in the early 1980s coincided with the convergence of technologies now collectively known as flow cytometry (FCM). Major advances in FCM led significantly toward our understanding of the pathogenicity of the disease, which in turn led to wider adoption of the technology, including using it effectively in a variety of diagnostics. CD4+ T lymphocyte population counts, along with human immunodeficiency virus (HIV) viral load, remain the gold standard in diagnosis and continue to play a major role in the monitoring of advanced retroviral therapies. Arguably, the spread of AIDS (acquired immunodeficiency syndrome), the HIV virus, and the toll of the virus on humanity have been considerably altered by the concurrent development of FCM, the details of which are presented herein. Copyright© by the American Society for Clinical Pathology (ASCP).

Rapid flow cytometry analysis of antimicrobial properties of nettle powder and cranberry powder

NASA Astrophysics Data System (ADS)

Hattuniemi, Maarit; Korhonen, Johanna; Jaakkola, Mari; Räty, Jarkko; Virtanen, Vesa

2010-11-01

Both nettle (Urtica dioica) and cranberry (Vaccinium oxycoccus) are widely known to have good influence on health. The aim of this study was to investigate antimicrobial properties of nettle powder and cranberry powder against Escherichia coli (E. coli) and monitor the growth of the bacteria by a rapid flow cytometry (FCM) method. For FCM measurements samples were stained with fluorescent dyes. The inhibitory effects of plant material on growth of E. coli were estimated by comparing the results of control sample (E. coli) to E. coli samples with plant material. FCM offers both a brilliant tool to investigate the kinetics of the growth of bacterium, since subsamples can be taken from the same liquid medium during the growing period and with fluorescent dyes a rapid method to investigate viability of the bacterium.

Phase-sensitive flow cytometer

DOEpatents

Steinkamp, J.A.

1993-12-14

A phase-sensitive flow cytometer (FCM) provides additional FCM capability to use the fluorescence lifetime of one or more fluorochromes bound to single cells to provide additional information regarding the cells. The resulting fluorescence emission can be resolved into individual fluorescence signals if two fluorochromes are present or can be converted directly to a decay lifetime from a single fluorochrome. The excitation light for the fluorochromes is modulated to produce an amplitude modulated fluorescence pulse as the fluorochrome is excited in the FCM. The modulation signal also forms a reference signal that is phase-shifted a selected amount for subsequent mixing with the output modulated fluorescence intensity signal in phase-sensitive detection circuitry. The output from the phase-sensitive circuitry is then an individual resolved fluorochrome signal or a single fluorochrome decay lifetime, depending on the applied phase shifts. 15 figures.

Testing mapping algorithms of the cancer-specific EORTC QLQ-C30 onto EQ-5D in malignant mesothelioma.

PubMed

Arnold, David T; Rowen, Donna; Versteegh, Matthijs M; Morley, Anna; Hooper, Clare E; Maskell, Nicholas A

2015-01-23

In order to estimate utilities for cancer studies where the EQ-5D was not used, the EORTC QLQ-C30 can be used to estimate EQ-5D using existing mapping algorithms. Several mapping algorithms exist for this transformation, however, algorithms tend to lose accuracy in patients in poor health states. The aim of this study was to test all existing mapping algorithms of QLQ-C30 onto EQ-5D, in a dataset of patients with malignant pleural mesothelioma, an invariably fatal malignancy where no previous mapping estimation has been published. Health related quality of life (HRQoL) data where both the EQ-5D and QLQ-C30 were used simultaneously was obtained from the UK-based prospective observational SWAMP (South West Area Mesothelioma and Pemetrexed) trial. In the original trial 73 patients with pleural mesothelioma were offered palliative chemotherapy and their HRQoL was assessed across five time points. This data was used to test the nine available mapping algorithms found in the literature, comparing predicted against observed EQ-5D values. The ability of algorithms to predict the mean, minimise error and detect clinically significant differences was assessed. The dataset had a total of 250 observations across 5 timepoints. The linear regression mapping algorithms tested generally performed poorly, over-estimating the predicted compared to observed EQ-5D values, especially when observed EQ-5D was below 0.5. The best performing algorithm used a response mapping method and predicted the mean EQ-5D with accuracy with an average root mean squared error of 0.17 (Standard Deviation; 0.22). This algorithm reliably discriminated between clinically distinct subgroups seen in the primary dataset. This study tested mapping algorithms in a population with poor health states, where they have been previously shown to perform poorly. Further research into EQ-5D estimation should be directed at response mapping methods given its superior performance in this study.

Immuno-analysis of microparticles: probing at the limits of detection

PubMed Central

Latham, Sharissa L.; Tiberti, Natalia; Gokoolparsadh, Naveena; Holdaway, Karen; Olivier Couraud, Pierre; Grau, Georges E. R.; Combes, Valery

2015-01-01

Microparticle (MP) research is clouded by debate regarding the accuracy and validity of flow cytometry (FCM) as an analytical methodology, as it is influenced by many variables including the pre-analytical conditions, instruments physical capabilities and detection parameters. This study utilises a simplistic in vitro system for generating MP, and through comparative analysis with immuno-electron microscopy (Immuno-EM) assesses the strengths and limitations of probe selection and high-sensitivity FCM. Of the markers examined, MP were most specifically labelled with phosphatidylserine ligands, annexin V and lactadherin, although only ~60% MP are PS positive. Whilst these two ligands detect comparable absolute MP numbers, they interact with the same population in distinct manners; annexin V binding is enhanced on TNF induced MP. CD105 and CD54 expression were, as expected, consistent and enhanced following TNF activation respectively. Their labelling however accounted for as few as 30–40% of MP. The greatest discrepancies between FCM and I-EM were observed in the population solely labelled for the surface antigen. These findings demonstrate that despite significant improvements in resolution, high-sensitivity FCM remains limited in detecting small-size MP expressing low antigen levels. This study highlights factors to consider when selecting endothelial MP probes, as well as interpreting and representing data. PMID:26553743

New proposal of mechanical reinforcement structures to annular REBaCuO bulk magnet for compact and cryogen-free NMR spectrometer

NASA Astrophysics Data System (ADS)

Fujishiro, H.; Takahashi, K.; Naito, T.; Yanagi, Y.; Itoh, Y.; Nakamura, T.

2018-07-01

We have proposed new reinforcement structures using an aluminum alloy ring to the annular REBaCuO bulks applicable to compact and cryogen-free 400 MHz (9.4 T) nuclear magnetic resonance (NMR) spectrometer using a numerical simulation of mechanical stress. The thermal compressive stress, σθcool, which was applied to the annular bulks during cooling due to the difference of thermal expansion coefficient between bulk and aluminum alloy, became fairly enhanced at the surface of the uppermost bulk for the new reinforcement structures, compared to the conventional reinforcement with the same height as the annular bulk, in which the compressive σθcool value was reduced. During field-cooled magnetization (FCM), the electromagnetic hoop stress, σθFCM, became the maximum at the innermost edge of the uppermost ring bulk at intermediate time step. The actual total hoop stress, σθ (= σθcool + σθFCM), due to both cooling and FCM processes was also analyzed and the new ring structures are fairly effective to reduce the σθ value and became lower than the fracture strength of the bulk. The new reinforcement structures have a possibility to avoid the fracture of the bulks and to realize a 400 MHz NMR spectrometer.

Metastatic pattern and DNA ploidy in stage IV breast cancer at initial diagnosis. Relation to response and survival.

PubMed

De Lena, M; Romero, A; Rabinovich, M; Leone, B; Vallejo, C; Machiavelli, M; Cuevas, M; Rodriguez, R; Lacava, J; Perez, J

1993-06-01

Sixty-nine patients with metastatic breast cancer (MBC) at initial diagnosis were analyzed to verify if metastatic pattern and clinical outcome are related to DNA ploidy determined by flow cytometry (FCM). Characteristics of 55 fully evaluable patients were as follows: median age: 61 years; postmenopausal: 75%; bone-only metastases (BM): 60%; extraosseous-only metastases (EM): 40%. Overall response rates (CR + PR) obtained with different chemotherapies and/or hormonal therapies were 58% and 68% for patients with BM and EM, respectively. Sixty percent of specimens resulted aneuploid, and the mean coefficient of variation of the complete series was 5.1%. In the whole group of patients DNA ploidy of primary tumor did not predict the metastatic pattern and had no influence upon response to treatment, duration of response, time to progression, and overall survival. When analyses were carried out according to metastatic pattern, those patients with BM showed similar results. However, within the group with EM, those with diploid tumors presented a significantly better survival (median 18 vs 13 months, p = .04). FCM-DNA analysis seems to identify a subgroup of patients with poor prognosis constituted by those who had aneuploid primary tumors and metastases to extraosseous sites.

Application of cryopreservation to genetic analyses of a photosynthetic picoeukaryote community.

PubMed

Kawachi, Masanobu; Kataoka, Takafumi; Sato, Mayumi; Noël, Mary-Hélène; Kuwata, Akira; Demura, Mikihide; Yamaguchi, Haruyo

2016-02-01

Cryopreservation is useful for long-term maintenance of living strains in microbial culture collections. We applied this technique to environmental specimens from two monitoring sites at Sendai Bay, Japan and compared the microbial diversity of photosynthetic picoeukaryotes in samples before and after cryopreservation. Flow cytometry (FCM) showed no considerable differences between specimens. We used 2500 cells sorted with FCM for next-generation sequencing of 18S rRNA gene amplicons and after removing low-quality sequences obtained 10,088-37,454 reads. Cluster analysis and comparative correlation analysis of observed high-level operational taxonomic units indicated similarity between specimens before and after cryopreservation. The effects of cryopreservation on cells were assessed with representative culture strains, including fragile cryptophyte cells. We confirmed the usefulness of cryopreservation for genetic studies on environmental specimens, and found that small changes in FCM cytograms after cryopreservation may affect biodiversity estimation. Copyright © 2015 Elsevier B.V. All rights reserved.

Prospective iterative trial of proteasome inhibitor-based desensitization.

PubMed

Woodle, E S; Shields, A R; Ejaz, N S; Sadaka, B; Girnita, A; Walsh, R C; Alloway, R R; Brailey, P; Cardi, M A; Abu Jawdeh, B G; Roy-Chaudhury, P; Govil, A; Mogilishetty, G

2015-01-01

A prospective iterative trial of proteasome inhibitor (PI)-based therapy for reducing HLA antibody (Ab) levels was conducted in five phases differing in bortezomib dosing density and plasmapheresis timing. Phases included 1 or 2 bortezomib cycles (1.3 mg/m(2) × 6-8 doses), one rituximab dose and plasmapheresis. HLA Abs were measured by solid phase and flow cytometry (FCM) assays. Immunodominant Ab (iAb) was defined as highest HLA Ab level. Forty-four patients received 52 desensitization courses (7 patients enrolled in multiple phases): Phase 1 (n = 20), Phase 2 (n = 12), Phase 3 (n = 10), Phase 4 (n = 5), Phase 5 (n = 5). iAb reductions were observed in 38 of 44 (86%) patients and persisted up to 10 months. In Phase 1, a 51.5% iAb reduction was observed at 28 days with bortezomib alone. iAb reductions increased with higher bortezomib dosing densities and included class I, II, and public antigens (HLA DRβ3, HLA DRβ4 and HLA DRβ5). FCM median channel shifts decreased in 11/11 (100%) patients by a mean of 103 ± 54 mean channel shifts (log scale). Nineteen out of 44 patients (43.2%) were transplanted with low acute rejection rates (18.8%) and de novo DSA formation (12.5%). In conclusion, PI-based desensitization consistently and durably reduces HLA Ab levels providing an alternative to intravenous immune globulin-based desensitization. © Copyright 2014 The American Society of Transplantation and the American Society of Transplant Surgeons.

Effect of Fluorocarbon and Hydrocarbon Chain Lengths in Hybrid Surfactants for Supercritical CO2.

PubMed

Sagisaka, Masanobu; Ono, Shinji; James, Craig; Yoshizawa, Atsushi; Mohamed, Azmi; Guittard, Frédéric; Rogers, Sarah E; Heenan, Richard K; Yan, Ci; Eastoe, Julian

2015-07-14

Hybrid surfactants containing both fluorocarbon (FC) and hydrocarbon (HC) chains have recently been shown to solubilize water and form elongated reversed micelles in supercritical CO2. To clarify the most effective FC and HC chain lengths, the aggregation behavior and interfacial properties of hybrid surfactants FCm-HCn (FC length m/HC length n = 4/2, 4/4, 6/2, 6/4, 6/5, 6/6, and 6/8) were examined in W/CO2 mixtures as functions of pressure, temperature, and water-to-surfactant molar ratio (W0). The solubilizing power of hybrid surfactants for W/CO2 microemulsions was strongly affected by not only the FC length but also by that of the HC. Although the surfactants having short FC and/or HC tails (namely, m/n = 4/2, 4/4, and 6/2) did not dissolve in supercritical CO2 (even at ∼17 mM, ≤400 bar, temperature ≤ 75 °C, and W0 = 0-40), the other hybrid surfactants were able to yield transparent single-phase W/CO2 mixtures identified as microemulsions. The solubilizing power of FC6-HCm surfactants reached a maximum (W0 ∼ 80 at 45 °C and 350 bar) with a hydrocarbon length, m, of 4. The W0 value of 80 is the highest for a HC-FC hybrid surfactant, matching the highest value reported for a FC surfactant which contained more FC groups. High-pressure small-angle neutron scattering measurements from FCm-HCn/D2O/CO2 microemulsions were consistent with growth of the microemulsion droplets with increasing W0. In addition, not only spherical reversed micelles but also nonspherical assemblies (rodlike or ellipsoidal) were found for the systems with FC6-HCn (n = 4-6). At fixed surfactant concentration and W0 (17 mM and W0 = 20), the longest reversed micelles were obtained for FC6-HC6 where a mean aspect ratio of 6.3 was calculated for the aqueous cores.

Spectral staining of tumor tissue by fiber optic FTIR spectroscopy

NASA Astrophysics Data System (ADS)

Salzer, Reiner; Steiner, Gerald; Kano, Angelique; Richter, Tom; Bergmann, Ralf; Rodig, Heike; Johannsen, Bernd; Kobelke, Jens

2003-07-01

Infrared (IR) optical fiber have aroused great interest in recent years because of their potential in in-vivo spectroscopy. This potential includes the ability to be flexible, small and to guide IR light in a very large range of wavelengths. Two types - silver halide and chalcogenide - infrared transmitting fibers are investigated in the detection of a malignant tumor. As a test sample for all types of fibers we used a thin section of an entire rat brain with glioblastoma. The fibers were connected with a common infrared microscope. Maps across the whole tissue section with more than 200 spectra were recorded by moving the sample with an XY stage. Data evaluation was performed using fuzzy c-means cluster analysis (FCM). The silver halide fibers provided excellent results. The tumor was clearly discernible from healthy tissue. Chalcogenide fibers are not suitable to distinguish tumor from normal tissue because the fiber has a very low transmittance in the important fingerprint region.

Quantification of green fluorescent protein by in vivo imaging, PCR, and flow cytometry: comparison of transgenic strains and relevance for fetal cell microchimerism.

PubMed

Fujiki, Yutaka; Tao, Kai; Bianchi, Diana W; Giel-Moloney, Maryann; Leiter, Andrew B; Johnson, Kirby L

2008-02-01

Animal models are increasingly being used for the assessment of fetal cell microchimerism in maternal tissue. We wished to determine the optimal transgenic mouse strain and analytic technique to facilitate the detection of rare transgenic microchimeric fetal cells amongst a large number of maternal wild-type cells. We evaluated two strains of mice transgenic for the enhanced green fluorescent protein (EGFP): a commercially available, commonly used strain (C57BL/6-Tg(ACTB-EGFP)10sb/J) (CAG) and a newly created strain (ROSA26-EGFP) using three different techniques: in vivo and ex vivo fluorescent imaging (for whole body and dissected organs, respectively), PCR amplification of gfp, and flow cytometry (FCM). By fluorescent imaging, organs from CAG mice were 10-fold brighter than organs from ROSA26-EGFP mice (P < 0.0001). By PCR, more transgene from CAG mice was detected compared to ROSA26-EGFP mice (P = 0.04). By FCM, ROSA26-EGFP cell fluorescence was more uniform than CAG cells. A greater proportion of cells from ROSA26-EGFP organs were positive for EGFP than cells from CAG organs, but CAG mice had a greater proportion of cells with the brightest fluorescent intensity. Each transgenic strain possesses characteristics that make it useful under specific experimental circumstances. The CAG mouse model is preferable when experiments require brighter cells, whereas ROSA26-EGFP is more appropriate when uniform or ubiquitous expression is more important than brightness. Investigators must carefully select the transgenic strain most suited to the experimental design to obtain the most consistent and reproducible data. In vivo imaging allows for phenotypic evaluation of whole animals and intact organs; however, we did not evaluate its utility for the detection of rare, fetal microchimeric cells in the maternal organs. Finally, while PCR amplification of a paternally inherited transgene does allow for the quantitative determination of rare microchimeric cells, FCM allows for both quantitative and qualitative evaluations of fetal cells at very high sensitivity in a plethora of maternal organs. (c) 2008 International Society for Analytical Cytology

Modified fuzzy c-means applied to a Bragg grating-based spectral imager for material clustering

NASA Astrophysics Data System (ADS)

Rodríguez, Aida; Nieves, Juan Luis; Valero, Eva; Garrote, Estíbaliz; Hernández-Andrés, Javier; Romero, Javier

2012-01-01

We have modified the Fuzzy C-Means algorithm for an application related to segmentation of hyperspectral images. Classical fuzzy c-means algorithm uses Euclidean distance for computing sample membership to each cluster. We have introduced a different distance metric, Spectral Similarity Value (SSV), in order to have a more convenient similarity measure for reflectance information. SSV distance metric considers both magnitude difference (by the use of Euclidean distance) and spectral shape (by the use of Pearson correlation). Experiments confirmed that the introduction of this metric improves the quality of hyperspectral image segmentation, creating spectrally more dense clusters and increasing the number of correctly classified pixels.

Fuzzy Document Clustering Approach using WordNet Lexical Categories

NASA Astrophysics Data System (ADS)

Gharib, Tarek F.; Fouad, Mohammed M.; Aref, Mostafa M.

Text mining refers generally to the process of extracting interesting information and knowledge from unstructured text. This area is growing rapidly mainly because of the strong need for analysing the huge and large amount of textual data that reside on internal file systems and the Web. Text document clustering provides an effective navigation mechanism to organize this large amount of data by grouping their documents into a small number of meaningful classes. In this paper we proposed a fuzzy text document clustering approach using WordNet lexical categories and Fuzzy c-Means algorithm. Some experiments are performed to compare efficiency of the proposed approach with the recently reported approaches. Experimental results show that Fuzzy clustering leads to great performance results. Fuzzy c-means algorithm overcomes other classical clustering algorithms like k-means and bisecting k-means in both clustering quality and running time efficiency.

Application of least mean square algorithm to suppression of maglev track-induced self-excited vibration

NASA Astrophysics Data System (ADS)

Zhou, D. F.; Li, J.; Hansen, C. H.

2011-11-01

Track-induced self-excited vibration is commonly encountered in EMS (electromagnetic suspension) maglev systems, and a solution to this problem is important in enabling the commercial widespread implementation of maglev systems. Here, the coupled model of the steel track and the magnetic levitation system is developed, and its stability is investigated using the Nyquist criterion. The harmonic balance method is employed to investigate the stability and amplitude of the self-excited vibration, which provides an explanation of the phenomenon that track-induced self-excited vibration generally occurs at a specified amplitude and frequency. To eliminate the self-excited vibration, an improved LMS (Least Mean Square) cancellation algorithm with phase correction (C-LMS) is employed. The harmonic balance analysis shows that the C-LMS cancellation algorithm can completely suppress the self-excited vibration. To achieve adaptive cancellation, a frequency estimator similar to the tuner of a TV receiver is employed to provide the C-LMS algorithm with a roughly estimated reference frequency. Numerical simulation and experiments undertaken on the CMS-04 vehicle show that the proposed adaptive C-LMS algorithm can effectively eliminate the self-excited vibration over a wide frequency range, and that the robustness of the algorithm suggests excellent potential for application to EMS maglev systems.

Performance standard-based validation study for local lymph node assay: 5-bromo-2-deoxyuridine-flow cytometry method.

PubMed

Ahn, Ilyoung; Kim, Tae-Sung; Jung, Eun-Sun; Yi, Jung-Sun; Jang, Won-Hee; Jung, Kyoung-Mi; Park, Miyoung; Jung, Mi-Sook; Jeon, Eun-Young; Yeo, Kyeong-Uk; Jo, Ji-Hoon; Park, Jung-Eun; Kim, Chang-Yul; Park, Yeong-Chul; Seong, Won-Keun; Lee, Ai-Young; Chun, Young Jin; Jeong, Tae Cheon; Jeung, Eui Bae; Lim, Kyung-Min; Bae, SeungJin; Sohn, Soojung; Heo, Yong

2016-10-01

Local lymph node assay: 5-bromo-2-deoxyuridine-flow cytometry method (LLNA: BrdU-FCM) is a modified non-radioisotopic technique with the additional advantages of accommodating multiple endpoints with the introduction of FCM, and refinement and reduction of animal use by using a sophisticated prescreening scheme. Reliability and accuracy of the LLNA: BrdU-FCM was determined according to OECD Test Guideline (TG) No. 429 (Skin Sensitization: Local Lymph Node Assay) performance standards (PS), with the participation of four laboratories. Transferability was demonstrated through successfully producing stimulation index (SI) values for 25% hexyl cinnamic aldehyde (HCA) consistently greater than 3, a predetermined threshold, by all participating laboratories. Within- and between-laboratory reproducibility was shown using HCA and 2,4-dinitrochlorobenzene, in which EC2.7 values (the estimated concentrations eliciting an SI of 2.7, the threshold for LLNA: BrdU-FCM) fell consistently within the acceptance ranges, 0.025-0.1% and 5-20%, respectively. Predictive capacity was tested using the final protocol version 1.3 for the 18 reference chemicals listed in OECD TG 429, of which results showed 84.6% sensitivity, 100% specificity, and 88.9% accuracy compared with the original LLNA. The data presented are considered to meet the performance criteria for the PS, and its predictive capacity was also sufficiently validated. Copyright © 2016 Elsevier Inc. All rights reserved.

Fast evaluation of 69 basal cell carcinomas with ex vivo fluorescence confocal microscopy: criteria description, histopathological correlation, and interobserver agreement.

PubMed

Bennàssar, Antoni; Carrera, Cristina; Puig, Susana; Vilalta, Antoni; Malvehy, Josep

2013-07-01

Fluorescence confocal microscopy (FCM) represents a first step toward a rapid "bedside pathology" in the Mohs surgery setting and in other fields of general pathology. To describe and validate FCM criteria for the main basal cell carcinoma (BCC) subtypes and to demonstrate the overall agreement with classic pathologic analysis of hematoxylin-eosin-stained samples. DESIGN A total of 69 BCCs from 66 patients were prospectively imaged using ex vivo FCM. Confocal mosaics were evaluated in real time and compared with classic pathologic analysis. Department of Dermatology, Hospital Clínic of Barcelona, Barcelona, Spain, between November 2010 and July 2011. Patients with BCC attending the Mohs Surgery Unit. Presence or absence of BCC and histological subtype (superficial, nodular, and infiltrating) in the confocal mosaics. Eight criteria for BCC were described, evaluated, and validated. Although there were minor differences among BCC subtypes, the most BCC-defining criteria were peripheral palisading, clefting, nuclear pleomorphism, and presence of stroma. These criteria were validated with independent observers (κ values >0.7 [corrected] for most criteria). We herein propose, describe, and validate FCM criteria for BCC diagnosis. Fluorescence confocal microscopy is an attractive alternative to histopathologic analysis of frozen sections during Mohs surgery because large areas of freshly excised tissue can be assessed in real time without the need for tissue processing while minimizing labor and costs.

Long-term safety and outcome of fludarabine, cyclophosphamide and mitoxantrone (FCM) regimen in previously untreated patients with advanced follicular lymphoma: 12 years follow-up of a phase 2 trial.

PubMed

Magnano, Laura; Montoto, Silvia; González-Barca, Eva; Briones, Javier; Sancho, Juan Manuel; Muntañola, Ana; Salar, Antonio; Besalduch, Joan; Escoda, Lourdes; Moreno, Carol; Domingo-Domenech, Eva; Estany, Cristina; Oriol, Albert; Altés, Albert; Pedro, Carmen; Gardella, Santiago; Asensio, Antoni; Vivancos, Pilar; Fernández de Sevilla, Alberto; Ribera, Josep María; Colomer, Dolors; Campo, Elias; López-Guillermo, Armando

2017-04-01

Fludarabine combinations are very affective in follicular lymphoma (FL) with high rates of complete response and prolonged survival. However, late toxicities could be a concern. The aim of the present study was to analyze the long-term impact on survival, relapse and late toxicities of a trial of treatment with fludarabine, mitoxantrone and cyclophosphamide (FCM regimen) for untreated patients with advanced stage FL. One hundred and twenty patients enrolled in a phase 2 trial of treatment with FCM regimen between 2000 and 2003 were evaluated. After a median follow-up of 12 years, 52 patients eventually relapsed/progressed with 10 year progression-free survival (PFS) of 46 %. Ten patients showed histological transformation to aggressive lymphoma with a risk of transformation of 2 and 9 % at 5 and 10 years, respectively. Three patients developed therapy-related myelodysplastic syndrome/acute myeloid leukaemia (MDS/AML) and seven solid neoplasms with an overall risk of 3 and 8 % at 5 and 10 years, respectively. Twenty-six patients eventually died during the follow-up. Overall survival at 10 years was 83 %. In conclusion, FCM regimen allows excellent long-lasting response in previously untreated patients with FL. The incidence of late events including histological transformation and secondary neoplasia is low but not negligible.

Immunophenotyping by slide-based cytometry and by flow cytometry are comparable

NASA Astrophysics Data System (ADS)

Gerstner, Andreas O.; Laffers, Wiebke; Mittag, Anja; Daehnert, Ingo; Lenz, Domnik; Bootz, Friedrich; Bocsi, Jozsef; Tarnok, Attila

2005-03-01

Immunophenotyping of peripheral blood leukocytes (PBLs) is performed by flow cytometry (FCM) as the golden standard. Slide based cytometry systems for example laser scanning cytometer (LSC) can give additional information (repeated staining and scanning, morphology). In order to adequately judge on the clinical usefulness of immunophenotyping by LSC it is obligatory to compare it with the long established FCM assays. We performed this study to systematically compare the two methods, FCM and LSC for immunophenotyping and to test the correlation of the results. Leucocytes were stained with directly labeled monoclonal antibodies with whole blood staining method. Aliquots of the same paraformaldehyde fixed specimens were analyzed in a FACScan (BD-Biosciences) using standard protocols and parallel with LSC (CompuCyte) after placing to glass slide, drying and fixation by aceton and 7-AAD staining. Calculating the percentage distribution of PBLs obtained by LSC and by FCM shows very good correlation with regression coefficients close to 1.0 for the major populations (neutrophils, lymphocytes, and monocytes), as well as for the lymphocyte sub-populations (T-helper-, T-cytotoxic-, B-, NK-cells). LSC can be recommended for immunophenotyping of PBLs especially in cases where only very limited sample volumes are available or where additional analysis of the cells" morphology is important. There are limitations in the detection of rare leucocytes or weak antigens where appropriate amplification steps for immunofluorescence should be engaged.

Prevalence and determinants of stereotypic behaviours and physiological stress among tigers and leopards in Indian zoos

PubMed Central

Vaz, Janice; Narayan, Edward J.; Dileep Kumar, R.; Thenmozhi, K.; Thiyagesan, Krishnamoorthy

2017-01-01

India’s charismatic wildlife species are facing immense pressure from anthropogenic-induced environmental perturbations. Zoos play a major role in the conservation of threatened species, but their adaptation in captivity is posing a major challenge globally. Stress from inadequate adaptation could lead to suppression of cognitive functioning and increased display of stereotypic behaviour. It is thus necessary to measure biological traits like behaviour, stress physiology, and contextual factors driving the animals maintained at zoos. In this study, we assessed stereotypic behaviour and stress physiology employing standard behaviour scoring, non-invasive stress monitoring, and their contextual drivers in a sub-population of two large felid species managed in six Indian zoos. The prevalence and intensity of stereotypic behaviours and levels of faecal corticosterone metabolites (FCM) were ascertained among 41 Royal Bengal tigers Panthera tigris tigris and 21 Indian leopards Panthera pardus fusca between April 2014 and March 2015. Behavioural observations showed that tigers spent more time stereotyping (12%) than leopards (7%) during daylight hours. Stress levels assessed using FCM revealed that tigers (23.6 ± 1.62 ng/g) had marginally lower level of corticosterone metabolites than leopards (27.2 ±1.36 ng/g). Stereotypic behaviour increased significantly with FCM level when the effect of heath status was controlled in tigers, and the effects tree cover, stone, den and keeper attitude controlled in leopards. Comparison of stereotypes of tigers with various biological and environmental factors using binary logistic regression revealed that stereotypic prevalence decreased with increased enclosure size, and enclosure enrichments like presence of pools and stones, when managed socially with conspecifics, and with positive keeper attitude, these factors accounting for 43% of variations in stereotypic prevalence among tigers. Stereotype among leopards was significantly absent when associated with increased tree cover and presence of pool, and den in the enclosure, age and among zoo-born than wild-born ones. These factors explain 81% of variations in stereotypic prevalence in them. A comparison of FCM levels with context-dependent factors revealed that stress levels among tigers decreased significantly with enclosure size and with individuals from nil to low, and severity of health issues. These factors explain 64% of variations in FCM levels. In leopards, the presence of stones in the enclosure and keepers with positive attitude resulted in significant decrease in FCM levels, these factors together accounting for 94% of variations. Multiple regressions on selected variables based on Factor Analysis of Mixed Data showed that in tigers the intensity of stereotype decreased significantly with enclosure size, sociality and positive keeper attitude and FCM level with health problems. Similarly, analyses in leopards revealed that intensity of stereotype decreased significantly with tree cover, age and FCM level with positive keeper attitude. Overall, our study suggests that to reduce stereotypes and stress level, tigers in captivity should be managed in larger enclosures enriched with pool, and stones, and in appropriate social conditions with adequate veterinary care. Leopards should be managed in enclosures with dense tree cover, pool, stones and den. Positive keeper attitude plays a crucial role in the welfare of both the species in captivity. Our study is promising and is comparable with their natural behaviour in the wild; for example, tigers require larger natural habitats, while leopards can manage even with smaller isolated patches but with dense vegetation cover. PMID:28414723

Prevalence and determinants of stereotypic behaviours and physiological stress among tigers and leopards in Indian zoos.

PubMed

Vaz, Janice; Narayan, Edward J; Dileep Kumar, R; Thenmozhi, K; Thiyagesan, Krishnamoorthy; Baskaran, Nagarajan

2017-01-01

India's charismatic wildlife species are facing immense pressure from anthropogenic-induced environmental perturbations. Zoos play a major role in the conservation of threatened species, but their adaptation in captivity is posing a major challenge globally. Stress from inadequate adaptation could lead to suppression of cognitive functioning and increased display of stereotypic behaviour. It is thus necessary to measure biological traits like behaviour, stress physiology, and contextual factors driving the animals maintained at zoos. In this study, we assessed stereotypic behaviour and stress physiology employing standard behaviour scoring, non-invasive stress monitoring, and their contextual drivers in a sub-population of two large felid species managed in six Indian zoos. The prevalence and intensity of stereotypic behaviours and levels of faecal corticosterone metabolites (FCM) were ascertained among 41 Royal Bengal tigers Panthera tigris tigris and 21 Indian leopards Panthera pardus fusca between April 2014 and March 2015. Behavioural observations showed that tigers spent more time stereotyping (12%) than leopards (7%) during daylight hours. Stress levels assessed using FCM revealed that tigers (23.6 ± 1.62 ng/g) had marginally lower level of corticosterone metabolites than leopards (27.2 ±1.36 ng/g). Stereotypic behaviour increased significantly with FCM level when the effect of heath status was controlled in tigers, and the effects tree cover, stone, den and keeper attitude controlled in leopards. Comparison of stereotypes of tigers with various biological and environmental factors using binary logistic regression revealed that stereotypic prevalence decreased with increased enclosure size, and enclosure enrichments like presence of pools and stones, when managed socially with conspecifics, and with positive keeper attitude, these factors accounting for 43% of variations in stereotypic prevalence among tigers. Stereotype among leopards was significantly absent when associated with increased tree cover and presence of pool, and den in the enclosure, age and among zoo-born than wild-born ones. These factors explain 81% of variations in stereotypic prevalence in them. A comparison of FCM levels with context-dependent factors revealed that stress levels among tigers decreased significantly with enclosure size and with individuals from nil to low, and severity of health issues. These factors explain 64% of variations in FCM levels. In leopards, the presence of stones in the enclosure and keepers with positive attitude resulted in significant decrease in FCM levels, these factors together accounting for 94% of variations. Multiple regressions on selected variables based on Factor Analysis of Mixed Data showed that in tigers the intensity of stereotype decreased significantly with enclosure size, sociality and positive keeper attitude and FCM level with health problems. Similarly, analyses in leopards revealed that intensity of stereotype decreased significantly with tree cover, age and FCM level with positive keeper attitude. Overall, our study suggests that to reduce stereotypes and stress level, tigers in captivity should be managed in larger enclosures enriched with pool, and stones, and in appropriate social conditions with adequate veterinary care. Leopards should be managed in enclosures with dense tree cover, pool, stones and den. Positive keeper attitude plays a crucial role in the welfare of both the species in captivity. Our study is promising and is comparable with their natural behaviour in the wild; for example, tigers require larger natural habitats, while leopards can manage even with smaller isolated patches but with dense vegetation cover.

Migration of nanosized layered double hydroxide platelets from polylactide nanocomposite films.

PubMed

Schmidt, B; Katiyar, V; Plackett, D; Larsen, E H; Gerds, N; Koch, C Bender; Petersen, J H

2011-01-01

Melt-extruded L-polylactide (PLA) nanocomposite films were prepared from commercially available PLA and laurate-modified Mg-Al layered double hydroxide (LDH-C12). Three films were tested for total migration as well as specific migration of LDH, tin, laurate and low molecular weight PLA oligomers (OLLA). This is the first reported investigation on the migration properties of PLA-LDH nanocomposite films. The tests were carried out as part of an overall assessment of the suitability of such films for use as food contact materials (FCM). Total migration was determined according to a European standard method. All three films showed migration of nanosized LDH, which was quantified using acid digestion followed by inductively coupled plasma mass spectrometric (ICP-MS) detection of (26)Mg. Migration of LDH from the films was also confirmed by examining migrates using transmission electron microscopy (TEM) and was attributed indirectly to the significant PLA molecular weight reduction observed in extruded PLA-LDH-C12 films. Migration of tin was detected in two of the film samples prepared by dispersion of LDH-C12 using a masterbatch technique and migration of the laurate organomodifier took place from all three film types. The results indicate that the material properties are in compliance with the migration limits for total migration and specific lauric acid migration as set down by the EU legislation for FCM, at least if a reduction factor for fresh meat is taken into consideration. The tin detected arises from the use of organotin catalysts in the manufacture of PLA.

Use of the Fracture Continuum Model for Numerical Modeling of Flow and Transport of Deep Geologic Disposal of Nuclear Waste in Crystalline Rock

NASA Astrophysics Data System (ADS)

Hadgu, T.; Kalinina, E.; Klise, K. A.; Wang, Y.

2015-12-01

Numerical modeling of disposal of nuclear waste in a deep geologic repository in fractured crystalline rock requires robust characterization of fractures. Various methods for fracture representation in granitic rocks exist. In this study we used the fracture continuum model (FCM) to characterize fractured rock for use in the simulation of flow and transport in the far field of a generic nuclear waste repository located at 500 m depth. The FCM approach is a stochastic method that maps the permeability of discrete fractures onto a regular grid. The method generates permeability fields using field observations of fracture sets. The original method described in McKenna and Reeves (2005) was designed for vertical fractures. The method has since then been extended to incorporate fully three-dimensional representations of anisotropic permeability, multiple independent fracture sets, and arbitrary fracture dips and orientations, and spatial correlation (Kalinina et al. 20012, 2014). For this study the numerical code PFLOTRAN (Lichtner et al., 2015) has been used to model flow and transport. PFLOTRAN solves a system of generally nonlinear partial differential equations describing multiphase, multicomponent and multiscale reactive flow and transport in porous materials. The code is designed to run on massively parallel computing architectures as well as workstations and laptops (e.g. Hammond et al., 2011). Benchmark tests were conducted to simulate flow and transport in a specified model domain. Distributions of fracture parameters were used to generate a selected number of realizations. For each realization, the FCM method was used to generate a permeability field of the fractured rock. The PFLOTRAN code was then used to simulate flow and transport in the domain. Simulation results and analysis are presented. The results indicate that the FCM approach is a viable method to model fractured crystalline rocks. The FCM is a computationally efficient way to generate realistic representation of complex fracture systems. This approach is of interest for nuclear waste disposal models applied over large domains.

Participatory Development and Analysis of a Fuzzy Cognitive Map of the Establishment of a Bio-Based Economy in the Humber Region

PubMed Central

Penn, Alexandra S.; Knight, Christopher J. K.; Lloyd, David J. B.; Avitabile, Daniele; Kok, Kasper; Schiller, Frank; Woodward, Amy; Druckman, Angela; Basson, Lauren

2013-01-01

Fuzzy Cognitive Mapping (FCM) is a widely used participatory modelling methodology in which stakeholders collaboratively develop a ‘cognitive map’ (a weighted, directed graph), representing the perceived causal structure of their system. This can be directly transformed by a workshop facilitator into simple mathematical models to be interrogated by participants by the end of the session. Such simple models provide thinking tools which can be used for discussion and exploration of complex issues, as well as sense checking the implications of suggested causal links. They increase stakeholder motivation and understanding of whole systems approaches, but cannot be separated from an intersubjective participatory context. Standard FCM methodologies make simplifying assumptions, which may strongly influence results, presenting particular challenges and opportunities. We report on a participatory process, involving local companies and organisations, focussing on the development of a bio-based economy in the Humber region. The initial cognitive map generated consisted of factors considered key for the development of the regional bio-based economy and their directional, weighted, causal interconnections. A verification and scenario generation procedure, to check the structure of the map and suggest modifications, was carried out with a second session. Participants agreed on updates to the original map and described two alternate potential causal structures. In a novel analysis all map structures were tested using two standard methodologies usually used independently: linear and sigmoidal FCMs, demonstrating some significantly different results alongside some broad similarities. We suggest a development of FCM methodology involving a sensitivity analysis with different mappings and discuss the use of this technique in the context of our case study. Using the results and analysis of our process, we discuss the limitations and benefits of the FCM methodology in this case and in general. We conclude by proposing an extended FCM methodology, including multiple functional mappings within one participant-constructed graph. PMID:24244303

Normed kernel function-based fuzzy possibilistic C-means (NKFPCM) algorithm for high-dimensional breast cancer database classification with feature selection is based on Laplacian Score

NASA Astrophysics Data System (ADS)

Lestari, A. W.; Rustam, Z.

2017-07-01

In the last decade, breast cancer has become the focus of world attention as this disease is one of the primary leading cause of death for women. Therefore, it is necessary to have the correct precautions and treatment. In previous studies, Fuzzy Kennel K-Medoid algorithm has been used for multi-class data. This paper proposes an algorithm to classify the high dimensional data of breast cancer using Fuzzy Possibilistic C-means (FPCM) and a new method based on clustering analysis using Normed Kernel Function-Based Fuzzy Possibilistic C-Means (NKFPCM). The objective of this paper is to obtain the best accuracy in classification of breast cancer data. In order to improve the accuracy of the two methods, the features candidates are evaluated using feature selection, where Laplacian Score is used. The results show the comparison accuracy and running time of FPCM and NKFPCM with and without feature selection.

Development of a novel flow cytometric approach to evaluate fish sperm chromatin using fixed samples

USGS Publications Warehouse

Jenkins, Jill A.

2013-01-01

The integrity of the paternal DNA is essential for the accurate transmission of genetic information, yet fertilization is not inhibited by chromatin breakage. Some methods are available for the sensitive detection of DNA damage and can be applied in studies of environmental toxicology, carcinogenesis, aging, and assisted reproduction techniques in both clinical and experimental settings. Because semen samples obtained from remote locations undergo chromatin damage prior to laboratory assessment, the present study was undertaken to evaluate treatments for effective chromatin staining in the development of a DNA fragmentation assay using fixed milt from yellow perch (Perca flavescens). Similar to the sperm chromatin structure assay (SCSA), susceptibility of nuclear DNA to acid-induced denaturation was measured by flow cytometry (FCM). Use of 10% buffered formalin for milt fixation allowed easier peak discrimination than 4% paraformaldehyde. The effects of time and temperature of incubation in 0.08 N HCl were evaluated in order to determine the ideal conditions for promoting DNA decondensation and making strand breaks more available for staining and detection by FCM. The best results were obtained with incubation at 37°C for 1 minute, followed by cold propidium iodide staining for 30 minutes.

Computer-aided diagnostic approach of dermoscopy images acquiring relevant features

NASA Astrophysics Data System (ADS)

Castillejos-Fernández, H.; Franco-Arcega, A.; López-Ortega, O.

2016-09-01

In skin cancer detection, automated analysis of borders, colors, and structures of a lesion relies upon an accurate segmentation process and it is an important first step in any Computer-Aided Diagnosis (CAD) system. However, irregular and disperse lesion borders, low contrast, artifacts in images and variety of colors within the interest region make the problem difficult. In this paper, we propose an efficient approach of automatic classification which considers specific lesion features. First, for the selection of lesion skin we employ the segmentation algorithm W-FCM.1 Then, in the feature extraction stage we consider several aspects: the area of the lesion, which is calculated by correlating axes and we calculate the specific the value of asymmetry in both axes. For color analysis we employ an ensemble of clusterers including K-Means, Fuzzy K-Means and Kohonep maps, all of which estimate the presence of one or more colors defined in ABCD rule and the values for each of the segmented colors. Another aspect to consider is the type of structures that appear in the lesion Those are defined by using the ell-known GLCM method. During the classification stage we compare several methods in order to define if the lesion is benign or malignant. An important contribution of the current approach in segmentation-classification problem resides in the use of information from all color channels together, as well as the measure of each color in the lesion and the axes correlation. The segmentation and classification measures have been performed using sensibility, specificity, accuracy and AUC metric over a set of dermoscopy images from ISDIS data set

Algorithm optimization for multitined radiofrequency ablation: comparative study in ex vivo and in vivo bovine liver.

PubMed

Appelbaum, Liat; Sosna, Jacob; Pearson, Robert; Perez, Sarah; Nissenbaum, Yizhak; Mertyna, Pawel; Libson, Eugene; Goldberg, S Nahum

2010-02-01

To prospectively optimize multistep algorithms for largest available multitined radiofrequency (RF) electrode system in ex vivo and in vivo tissues, to determine best energy parameters to achieve large predictable target sizes of coagulation, and to compare these algorithms with manufacturer's recommended algorithms. Institutional animal care and use committee approval was obtained for the in vivo portion of this study. Ablation (n = 473) was performed in ex vivo bovine liver; final tine extension was 5-7 cm. Variables in stepped-deployment RF algorithm were interrogated and included initial current ramping to 105 degrees C (1 degrees C/0.5-5.0 sec), the number of sequential tine extensions (2-7 cm), and duration of application (4-12 minutes) for final two to three tine extensions. Optimal parameters to achieve 5-7 cm of coagulation were compared with recommended algorithms. Optimal settings for 5- and 6-cm final tine extensions were confirmed in in vivo perfused bovine liver (n = 14). Multivariate analysis of variance and/or paired t tests were used. Mean RF ablation zones of 5.1 cm +/- 0.2 (standard deviation), 6.3 cm +/- 0.4, and 7 cm +/- 0.3 were achieved with 5-, 6-, and 7-cm final tine extensions in a mean of 19.5 min +/- 0.5, 27.9 min +/- 6, and 37.1 min +/- 2.3, respectively, at optimal settings. With these algorithms, size of ablation at 6- and 7-cm tine extension significantly increased from mean of 5.4 cm +/- 0.4 and 6.1 cm +/- 0.6 (manufacturer's algorithms) (P <.05, both comparisons); two recommended tine extensions were eliminated. In vivo confirmation produced mean diameter in specified time: 5.5 cm +/- 0.4 in 18.5 min +/- 0.5 (5-cm extensions) and 5.7 cm +/- 0.2 in 21.2 min +/- 0.6 (6-cm extensions). Large zones of coagulation of 5-7 cm can be created with optimized RF algorithms that help reduce number of tine extensions compared with manufacturer's recommendations. Such algorithms are likely to facilitate the utility of these devices for RF ablation of focal tumors in clinical practice. (c) RSNA, 2010.

New Embedded Denotes Fuzzy C-Mean Application for Breast Cancer Density Segmentation in Digital Mammograms

NASA Astrophysics Data System (ADS)

Othman, Khairulnizam; Ahmad, Afandi

2016-11-01

In this research we explore the application of normalize denoted new techniques in advance fast c-mean in to the problem of finding the segment of different breast tissue regions in mammograms. The goal of the segmentation algorithm is to see if new denotes fuzzy c- mean algorithm could separate different densities for the different breast patterns. The new density segmentation is applied with multi-selection of seeds label to provide the hard constraint, whereas the seeds labels are selected based on user defined. New denotes fuzzy c- mean have been explored on images of various imaging modalities but not on huge format digital mammograms just yet. Therefore, this project is mainly focused on using normalize denoted new techniques employed in fuzzy c-mean to perform segmentation to increase visibility of different breast densities in mammography images. Segmentation of the mammogram into different mammographic densities is useful for risk assessment and quantitative evaluation of density changes. Our proposed methodology for the segmentation of mammograms on the basis of their region into different densities based categories has been tested on MIAS database and Trueta Database.

[The attitudes and behavior of the general primary-care physician towards the neurological patient].

PubMed

Casabella Abril, B; Pérez Sánchez, J

1995-04-15

1) To find the opinion of general practitioners working in primary care (GP in PC) regarding how they deal with neurological patients. 2) To find the effect on this question of intern training in family and community medicine (FCM). A survey filled out by a representative sample of GP in PC working at PC public clinics in 1991 in a health region in Catalonia. 56 GP in PC. A self-administered selection questionnaire (multiple choice and scale of 5 points). MEASUREMENTS, MAIN RESULTS AND CONCLUSIONS: Less confidence handling neurological patients than patients with other common medical conditions. Greater need for recycling in neurology than in other basic areas of medicine. Positive impact of FCM intern training on doctors' approach to the examination of neurological patients and application of basic exploratory techniques (ophthalmoscope, reflex hammer, diapason and phonendoscope). The GP intern-trained in FCM lacks confidence in present out-patient specialised support (the area neuropsychiatrist).

Flow Cytometry Data Preparation Guidelines for Improved Automated Phenotypic Analysis.

PubMed

Jimenez-Carretero, Daniel; Ligos, José M; Martínez-López, María; Sancho, David; Montoya, María C

2018-05-15

Advances in flow cytometry (FCM) increasingly demand adoption of computational analysis tools to tackle the ever-growing data dimensionality. In this study, we tested different data input modes to evaluate how cytometry acquisition configuration and data compensation procedures affect the performance of unsupervised phenotyping tools. An analysis workflow was set up and tested for the detection of changes in reference bead subsets and in a rare subpopulation of murine lymph node CD103 + dendritic cells acquired by conventional or spectral cytometry. Raw spectral data or pseudospectral data acquired with the full set of available detectors by conventional cytometry consistently outperformed datasets acquired and compensated according to FCM standards. Our results thus challenge the paradigm of one-fluorochrome/one-parameter acquisition in FCM for unsupervised cluster-based analysis. Instead, we propose to configure instrument acquisition to use all available fluorescence detectors and to avoid integration and compensation procedures, thereby using raw spectral or pseudospectral data for improved automated phenotypic analysis. Copyright © 2018 by The American Association of Immunologists, Inc.

[Application and usefulness of flowcytometry in the haematology laboratory].

PubMed

Kubota, K; Makino, M

1991-02-01

Recent technological advances, in both hardware and software, and availability of various monoclonal antibodies (MoAb) for membrane antigens of blood cells have expanded the application of flow cytometry (FCM) in medicine. In the haematology laboratory, FCM has been used mainly for assessment of leukemia and lymphoma and for determination of lymphocyte subsets. In acute leukemia, FCM is useful to classify ALL accurately, particularly for bi phenotypic or mixed lineage leukemia. In lymphocyte subset determination, we found that the use of magnetic beads to remove contaminating monocytes and some granulocytes to purify the lymphocyte-population is helpful in clarify the subsets. We present data describing the age dependent variation in lymphocyte subsets in the pediatric population. In early life (up to 2 years old), CD4 (+) 2H4 (+) lymphocyte overwhelmed CD4 (+) 2H4 (-) cells, implying predominance of suppressor-inducer activity. We also presented some cases of markedly increased double negative T cells (gamma/delta TCR) and a rare case of double positive (CD4+, CD8+) T cells.

Intraoperative diagnosis of nonpigmented nail tumours with ex vivo fluorescence confocal microscopy: 10 cases.

PubMed

Debarbieux, S; Gaspar, R; Depaepe, L; Dalle, S; Balme, B; Thomas, L

2015-04-01

Ex vivo fluorescence confocal microscopy (FCM) permits real-time imaging of freshly excised skin tissues. Its usefulness as a time-sparing alternative to frozen sections in Mohs surgery of basal cell carcinoma is well documented. The purpose of this study was to describe the ex vivo FCM features of a series of benign and malignant nonpigmented tumours of the nail unit, and to correlate them with conventional histopathology. Nail apparatus tumours from 10 patients were imaged during surgical exploration using ex vivo FCM after immersion in acridine orange. Confocal mosaics of the freshly performed biopsies were evaluated in real time and retrospectively compared with haematoxylin and eosin sections. Our series included two invasive epithelial tumours (Group 1), four in situ or minimally invasive squamous cell carcinomas (SCC) (Group 2), three benign epithelial tumours (Group 3) and one nodular melanoma (Group 4). The correlation was excellent for malignant epithelial tumours exhibiting marked cytological and architectural atypias (Bowen disease, invasive SCC and onycholemmal carcinoma). Onychomatricomas exhibited a very peculiar aspect with densely cellular papillae. The correlation was less favourable for minimally invasive well-differentiated SCCs with slight cytological atypias. The correlation was poor for our case of amelanotic invasive subungual melanoma. Ex vivo FCM could be a useful tool to shorten management of nonpigmented nail tumours: in the case of a malignant tumour, it could indeed lead to performing wide excision during the same surgical procedure and possibly assessing the surgical margins. © 2014 British Association of Dermatologists.

Quantification of sand fraction from seismic attributes using Neuro-Fuzzy approach

NASA Astrophysics Data System (ADS)

Verma, Akhilesh K.; Chaki, Soumi; Routray, Aurobinda; Mohanty, William K.; Jenamani, Mamata

2014-12-01

In this paper, we illustrate the modeling of a reservoir property (sand fraction) from seismic attributes namely seismic impedance, seismic amplitude, and instantaneous frequency using Neuro-Fuzzy (NF) approach. Input dataset includes 3D post-stacked seismic attributes and six well logs acquired from a hydrocarbon field located in the western coast of India. Presence of thin sand and shale layers in the basin area makes the modeling of reservoir characteristic a challenging task. Though seismic data is helpful in extrapolation of reservoir properties away from boreholes; yet, it could be challenging to delineate thin sand and shale reservoirs using seismic data due to its limited resolvability. Therefore, it is important to develop state-of-art intelligent methods for calibrating a nonlinear mapping between seismic data and target reservoir variables. Neural networks have shown its potential to model such nonlinear mappings; however, uncertainties associated with the model and datasets are still a concern. Hence, introduction of Fuzzy Logic (FL) is beneficial for handling these uncertainties. More specifically, hybrid variants of Artificial Neural Network (ANN) and fuzzy logic, i.e., NF methods, are capable for the modeling reservoir characteristics by integrating the explicit knowledge representation power of FL with the learning ability of neural networks. In this paper, we opt for ANN and three different categories of Adaptive Neuro-Fuzzy Inference System (ANFIS) based on clustering of the available datasets. A comparative analysis of these three different NF models (i.e., Sugeno-type fuzzy inference systems using a grid partition on the data (Model 1), using subtractive clustering (Model 2), and using Fuzzy c-means (FCM) clustering (Model 3)) and ANN suggests that Model 3 has outperformed its counterparts in terms of performance evaluators on the present dataset. Performance of the selected algorithms is evaluated in terms of correlation coefficients (CC), root mean square error (RMSE), absolute error mean (AEM) and scatter index (SI) between target and predicted sand fraction values. The achieved estimation accuracy may diverge minutely depending on geological characteristics of a particular study area. The documented results in this study demonstrate acceptable resemblance between target and predicted variables, and hence, encourage the application of integrated machine learning approaches such as Neuro-Fuzzy in reservoir characterization domain. Furthermore, visualization of the variation of sand probability in the study area would assist in identifying placement of potential wells for future drilling operations.

TGF-β1, released by myofibroblasts, differentially regulates transcription and function of sodium and potassium channels in adult rat ventricular myocytes.

PubMed

Kaur, Kuljeet; Zarzoso, Manuel; Ponce-Balbuena, Daniela; Guerrero-Serna, Guadalupe; Hou, Luqia; Musa, Hassan; Jalife, José

2013-01-01

Cardiac injury promotes fibroblasts activation and differentiation into myofibroblasts, which are hypersecretory of multiple cytokines. It is unknown whether any of such cytokines are involved in the electrophysiological remodeling of adult cardiomyocytes. We cultured adult cardiomyocytes for 3 days in cardiac fibroblast conditioned medium (FCM) from adult rats. In whole-cell voltage-clamp experiments, FCM-treated myocytes had 41% more peak inward sodium current (I(Na)) density at -40 mV than myocytes in control medium (p<0.01). In contrast, peak transient outward current (I(to)) was decreased by ∼55% at 60 mV (p<0.001). Protein analysis of FCM demonstrated that the concentration of TGF-β1 was >3 fold greater in FCM than control, which suggested that FCM effects could be mediated by TGF-β1. This was confirmed by pre-treatment with TGF-β1 neutralizing antibody, which abolished the FCM-induced changes in both I(Na) and I(to). In current-clamp experiments TGF-β1 (10 ng/ml) prolonged the action potential duration at 30, 50, and 90 repolarization (p<0.05); at 50 ng/ml it gave rise to early afterdepolarizations. In voltage-clamp experiments, TGF-β1 increased I(Na) density in a dose-dependent manner without affecting voltage dependence of activation or inactivation. I(Na) density was -36.25±2.8 pA/pF in control, -59.17±6.2 pA/pF at 0.1 ng/ml (p<0.01), and -58.22±6.6 pA/pF at 1 ng/ml (p<0.01). In sharp contrast, I(to) density decreased from 22.2±1.2 pA/pF to 12.7±0.98 pA/pF (p<0.001) at 10 ng/ml. At 1 ng/ml TGF-β1 significantly increased SCN5A (Na(V)1.5) (+73%; p<0.01), while reducing KCNIP2 (Kchip2; -77%; p<0.01) and KCND2 (K(V)4.2; -50% p<0.05) mRNA levels. Further, the TGF-β1-induced increase in I(Na) was mediated through activation of the PI3K-AKT pathway via phosphorylation of FOXO1 (a negative regulator of SCN5A). TGF-β1 released by myofibroblasts differentially regulates transcription and function of the main cardiac sodium channel and of the channel responsible for the transient outward current. The results provide new mechanistic insight into the electrical remodeling associated with myocardial injury.

Deposition, clearance, and shortening of Kevlar para-aramid fibrils in acute, subchronic, and chronic inhalation studies in rats.

PubMed

Kelly, D P; Merriman, E A; Kennedy, G L; Lee, K P

1993-10-01

The deposition and clearance of lung-deposited Kevlar para-aramid fibrils (subfibers) have been investigated as part of a subchronic and chronic inhalation toxicity testing program. Fibrils recovered from lung tissue in para-aramid-exposed Sprague-Dawley rats were microscopically counted and measured after exposures to airborne fibrils which were about 12 microns median length (ML) and < 0.3 micron median diameter. In each of three studies lung-recovered fibrils were progressively shorter with increasing residence time in the lungs. Twenty-eight days after a single 6-hr exposure at 400 respirable fibrils per cubic centimeter (f/cm3) the ML of recovered fibrils decreased to about 5 microns. Twenty-four months after a 3-week exposure to 25 or 400 f/cm3, fibrils reached about 2 microns ML. After 2 years of continuous exposure at 2.5, 25, or 100 f/cm3 or 1 year exposure plus 1 year recovery at 400 f/cm3, fibril ML approached 4 microns. In the 2-year study, the lung-fiber accumulation rate/exposure concentration was similar for the three highest concentrations and was about 3 x greater than that seen at 2.5 f/cm3, indicating that concentrations of about 25 f/cm3 or more may overwhelm clearance mechanisms. Time required for fibrils to be reduced to < 5 microns in the lung was markedly less at lower exposure concentration and shorter exposure time. The primary shortening mechanism is proposed to be long fibril cutting by enzymatic attack at fibril defects. However, length-selective fibril deposition and clearance may contribute to shortening in the first few days after exposure. The enzymatic cutting hypothesis is supported by measured increases in numbers of short fibers following cessation of exposures, continued shortening of the fibril length distribution up to 2 years following exposure, and in vitro fibril shortening after 3 months in a proteolytic enzyme preparation. The conclusion is that para-aramid fibrils are less durable in the lungs of rats than expected from the known chemical resistance of commercial yarn. These data suggest that at the low para-aramid fibril exposures found in the workplace, this fibril-shortening mechanism may limit the residence time of long fibers in the lungs of exposed workers. In addition, associated cascade impactor aerodynamic measurements indicate that due to their ribbon shape and curly nature, para-aramid fibrils behave aerodynamically larger than straight fibers.

Predicting ad libitum dry matter intake and yields of Jersey cows.

PubMed

Holter, J B; West, J W; McGilliard, M L; Pell, A N

1996-05-01

Two data files were used that contained weekly mean values for ad libitum DMI of lactating Jersey cows along with appropriate cow, ration, and environmental traits for predicting DMI. One data file (n = 666) was used to develop prediction equations for DMI because that file represented a number of separate experiments and contained more diversity in potential predictors, especially those related to ration, such as forage type. The other data file (n = 1613) was used primarily to verify these equations. Milk protein yield displaced 4% FCM output as a prediction variable and improved the R2 by several units but was not used in the final equations, however, for the sake of simplicity. All equations contained adjustments for the effects of heat stress, parity (1 vs. > 1), DIM > 15, BW, use of recombinant bST, and other significant independent variables. Equations were developed to predict DMI of cows fed individually or in groups and to predict daily yields of 4% FCM and milk protein; equations accounted for 0.69, 0.74, 0.81, and 0.76 of the variation in the dependent variables with standard deviations of 1.7, 1.6, 2.7, and 0.084 kg/ d, respectively. These equations should be applied to the development of software for computerized dairy ration balancing.

Comparison Spatial Pattern of Land Surface Temperature with Mono Window Algorithm and Split Window Algorithm: A Case Study in South Tangerang, Indonesia

NASA Astrophysics Data System (ADS)

Bunai, Tasya; Rokhmatuloh; Wibowo, Adi

2018-05-01

In this paper, two methods to retrieve the Land Surface Temperature (LST) from thermal infrared data supplied by band 10 and 11 of the Thermal Infrared Sensor (TIRS) onboard the Landsat 8 is compared. The first is mono window algorithm developed by Qin et al. and the second is split window algorithm by Rozenstein et al. The purpose of this study is to perform the spatial distribution of land surface temperature, as well as to determine more accurate algorithm for retrieving land surface temperature by calculated root mean square error (RMSE). Finally, we present comparison the spatial distribution of land surface temperature by both of algorithm, and more accurate algorithm is split window algorithm refers to the root mean square error (RMSE) is 7.69° C.

Water quality assessment with emphasis in parameter optimisation using pattern recognition methods and genetic algorithm.

PubMed

Sotomayor, Gonzalo; Hampel, Henrietta; Vázquez, Raúl F

2018-03-01

A non-supervised (k-means) and a supervised (k-Nearest Neighbour in combination with genetic algorithm optimisation, k-NN/GA) pattern recognition algorithms were applied for evaluating and interpreting a large complex matrix of water quality (WQ) data collected during five years (2008, 2010-2013) in the Paute river basin (southern Ecuador). 21 physical, chemical and microbiological parameters collected at 80 different WQ sampling stations were examined. At first, the k-means algorithm was carried out to identify classes of sampling stations regarding their associated WQ status by considering three internal validation indexes, i.e., Silhouette coefficient, Davies-Bouldin and Caliński-Harabasz. As a result, two WQ classes were identified, representing low (C1) and high (C2) pollution. The k-NN/GA algorithm was applied on the available data to construct a classification model with the two WQ classes, previously defined by the k-means algorithm, as the dependent variables and the 21 physical, chemical and microbiological parameters being the independent ones. This algorithm led to a significant reduction of the multidimensional space of independent variables to only nine, which are likely to explain most of the structure of the two identified WQ classes. These parameters are, namely, electric conductivity, faecal coliforms, dissolved oxygen, chlorides, total hardness, nitrate, total alkalinity, biochemical oxygen demand and turbidity. Further, the land use cover of the study basin revealed a very good agreement with the WQ spatial distribution suggested by the k-means algorithm, confirming the credibility of the main results of the used WQ data mining approach. Copyright © 2017 Elsevier Ltd. All rights reserved.

A new warfarin dosing algorithm including VKORC1 3730 G > A polymorphism: comparison with results obtained by other published algorithms.

PubMed

Cini, Michela; Legnani, Cristina; Cosmi, Benilde; Guazzaloca, Giuliana; Valdrè, Lelia; Frascaro, Mirella; Palareti, Gualtiero

2012-08-01

Warfarin dosing is affected by clinical and genetic variants, but the contribution of the genotype associated with warfarin resistance in pharmacogenetic algorithms has not been well assessed yet. We developed a new dosing algorithm including polymorphisms associated both with warfarin sensitivity and resistance in the Italian population, and its performance was compared with those of eight previously published algorithms. Clinical and genetic data (CYP2C9*2, CYP2C9*3, VKORC1 -1639 G > A, and VKORC1 3730 G > A) were used to elaborate the new algorithm. Derivation and validation groups comprised 55 (58.2% men, mean age 69 years) and 40 (57.5% men, mean age 70 years) patients, respectively, who were on stable anticoagulation therapy for at least 3 months with different oral anticoagulation therapy (OAT) indications. Performance of the new algorithm, evaluated with mean absolute error (MAE) defined as the absolute value of the difference between observed daily maintenance dose and predicted daily dose, correlation with the observed dose and R(2) value, was comparable with or slightly lower than that obtained using the other algorithms. The new algorithm could correctly assign 53.3%, 50.0%, and 57.1% of patients to the low (≤25 mg/week), intermediate (26-44 mg/week) and high (≥ 45 mg/week) dosing range, respectively. Our data showed a significant increase in predictive accuracy among patients requiring high warfarin dose compared with the other algorithms (ranging from 0% to 28.6%). The algorithm including VKORC1 3730 G > A, associated with warfarin resistance, allowed a more accurate identification of resistant patients who require higher warfarin dosage.

Postmortem validation of breast density using dual-energy mammography

PubMed Central

Molloi, Sabee; Ducote, Justin L.; Ding, Huanjun; Feig, Stephen A.

2014-01-01

Purpose: Mammographic density has been shown to be an indicator of breast cancer risk and also reduces the sensitivity of screening mammography. Currently, there is no accepted standard for measuring breast density. Dual energy mammography has been proposed as a technique for accurate measurement of breast density. The purpose of this study is to validate its accuracy in postmortem breasts and compare it with other existing techniques. Methods: Forty postmortem breasts were imaged using a dual energy mammography system. Glandular and adipose equivalent phantoms of uniform thickness were used to calibrate a dual energy basis decomposition algorithm. Dual energy decomposition was applied after scatter correction to calculate breast density. Breast density was also estimated using radiologist reader assessment, standard histogram thresholding and a fuzzy C-mean algorithm. Chemical analysis was used as the reference standard to assess the accuracy of different techniques to measure breast composition. Results: Breast density measurements using radiologist reader assessment, standard histogram thresholding, fuzzy C-mean algorithm, and dual energy were in good agreement with the measured fibroglandular volume fraction using chemical analysis. The standard error estimates using radiologist reader assessment, standard histogram thresholding, fuzzy C-mean, and dual energy were 9.9%, 8.6%, 7.2%, and 4.7%, respectively. Conclusions: The results indicate that dual energy mammography can be used to accurately measure breast density. The variability in breast density estimation using dual energy mammography was lower than reader assessment rankings, standard histogram thresholding, and fuzzy C-mean algorithm. Improved quantification of breast density is expected to further enhance its utility as a risk factor for breast cancer. PMID:25086548

Postmortem validation of breast density using dual-energy mammography

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

Molloi, Sabee, E-mail: symolloi@uci.edu; Ducote, Justin L.; Ding, Huanjun

2014-08-15

Purpose: Mammographic density has been shown to be an indicator of breast cancer risk and also reduces the sensitivity of screening mammography. Currently, there is no accepted standard for measuring breast density. Dual energy mammography has been proposed as a technique for accurate measurement of breast density. The purpose of this study is to validate its accuracy in postmortem breasts and compare it with other existing techniques. Methods: Forty postmortem breasts were imaged using a dual energy mammography system. Glandular and adipose equivalent phantoms of uniform thickness were used to calibrate a dual energy basis decomposition algorithm. Dual energy decompositionmore » was applied after scatter correction to calculate breast density. Breast density was also estimated using radiologist reader assessment, standard histogram thresholding and a fuzzy C-mean algorithm. Chemical analysis was used as the reference standard to assess the accuracy of different techniques to measure breast composition. Results: Breast density measurements using radiologist reader assessment, standard histogram thresholding, fuzzy C-mean algorithm, and dual energy were in good agreement with the measured fibroglandular volume fraction using chemical analysis. The standard error estimates using radiologist reader assessment, standard histogram thresholding, fuzzy C-mean, and dual energy were 9.9%, 8.6%, 7.2%, and 4.7%, respectively. Conclusions: The results indicate that dual energy mammography can be used to accurately measure breast density. The variability in breast density estimation using dual energy mammography was lower than reader assessment rankings, standard histogram thresholding, and fuzzy C-mean algorithm. Improved quantification of breast density is expected to further enhance its utility as a risk factor for breast cancer.« less

Fast detection of vascular plaque in optical coherence tomography images using a reduced feature set

NASA Astrophysics Data System (ADS)

Prakash, Ammu; Ocana Macias, Mariano; Hewko, Mark; Sowa, Michael; Sherif, Sherif

2018-03-01

Optical coherence tomography (OCT) images are capable of detecting vascular plaque by using the full set of 26 Haralick textural features and a standard K-means clustering algorithm. However, the use of the full set of 26 textural features is computationally expensive and may not be feasible for real time implementation. In this work, we identified a reduced set of 3 textural feature which characterizes vascular plaque and used a generalized Fuzzy C-means clustering algorithm. Our work involves three steps: 1) the reduction of a full set 26 textural feature to a reduced set of 3 textural features by using genetic algorithm (GA) optimization method 2) the implementation of an unsupervised generalized clustering algorithm (Fuzzy C-means) on the reduced feature space, and 3) the validation of our results using histology and actual photographic images of vascular plaque. Our results show an excellent match with histology and actual photographic images of vascular tissue. Therefore, our results could provide an efficient pre-clinical tool for the detection of vascular plaque in real time OCT imaging.

Fractal dimension to classify the heart sound recordings with KNN and fuzzy c-mean clustering methods

NASA Astrophysics Data System (ADS)

Juniati, D.; Khotimah, C.; Wardani, D. E. K.; Budayasa, K.

2018-01-01

The heart abnormalities can be detected from heart sound. A heart sound can be heard directly with a stethoscope or indirectly by a phonocardiograph, a machine of the heart sound recording. This paper presents the implementation of fractal dimension theory to make a classification of phonocardiograms into a normal heart sound, a murmur, or an extrasystole. The main algorithm used to calculate the fractal dimension was Higuchi’s Algorithm. There were two steps to make a classification of phonocardiograms, feature extraction, and classification. For feature extraction, we used Discrete Wavelet Transform to decompose the signal of heart sound into several sub-bands depending on the selected level. After the decomposition process, the signal was processed using Fast Fourier Transform (FFT) to determine the spectral frequency. The fractal dimension of the FFT output was calculated using Higuchi Algorithm. The classification of fractal dimension of all phonocardiograms was done with KNN and Fuzzy c-mean clustering methods. Based on the research results, the best accuracy obtained was 86.17%, the feature extraction by DWT decomposition level 3 with the value of kmax 50, using 5-fold cross validation and the number of neighbors was 5 at K-NN algorithm. Meanwhile, for fuzzy c-mean clustering, the accuracy was 78.56%.

Trapped magnetic-field properties of prototype for Gd-Ba-Cu-O/MgB2 hybrid-type superconducting bulk magnet

NASA Astrophysics Data System (ADS)

Naito, Tomoyuki; Mochizuki, Hidehiko; Fujishiro, Hiroyuki; Teshima, Hidekazu

2016-03-01

We have studied experimentally and numerically the trapped magnetic-field properties of a hybrid-type superconducting bulk magnet, which comprised an inner Gd-Ba-Cu-O (GdBCO) disk-bulk and an outer MgB2 ring-bulk, under field-cooled magnetization (FCM) and pulsed-field magnetization (PFM). The trapped field by FCM at the center of the hybrid bulk was 4.5 T at 20 K, which was 0.2 T higher than that of the inner GdBCO disk-bulk without MgB2 ring-bulk. The experimental results by FCM were quantitatively reproduced by the numerical estimations for a model, which makes it possible to understand the trapped field properties of the hybrid bulk. The total magnetic flux by FCM, which was estimated numerically, was enhanced by about 1.7 times from 0.91 mWb of the single GdBCO bulk to 1.53 mWb of the hybrid bulk. We also succeeded in magnetizing the whole hybrid bulk by applying multi-pulsed-fields. The central trapped field of 1.88 T was not enhanced, but the total magnetic flux, which was obtained experimentally, was evidently increased by 2.5 times (0.25 \\to 0.62 mWb) for the hybrid bulk. The obtained results suggest that the hybridization is effective to enhance the total magnetic flux. To confirm the reinforcing effect of the MgB2 ring to the GdBCO disk during the cooling and magnetization processes, we have measured the thermal dilatation, {\\text{}}{dL}({\\text{}}T)/{\\text{}}L(300 K), of the GdBCO, MgB2 and stainless steel. As a result, the thermal dilatation of MgB2 was smaller than that of GdBCO. MgB2 ring-bulk shows no compression effect to resist the hoop stress of the GdBCO disk-bulk during the FCM process. The reinforcing material such as the stainless steel ring must be set outside the GdBCO disk-bulk.

Segmentation of Polarimetric SAR Images Usig Wavelet Transformation and Texture Features

NASA Astrophysics Data System (ADS)

Rezaeian, A.; Homayouni, S.; Safari, A.

2015-12-01

Polarimetric Synthetic Aperture Radar (PolSAR) sensors can collect useful observations from earth's surfaces and phenomena for various remote sensing applications, such as land cover mapping, change and target detection. These data can be acquired without the limitations of weather conditions, sun illumination and dust particles. As result, SAR images, and in particular Polarimetric SAR (PolSAR) are powerful tools for various environmental applications. Unlike the optical images, SAR images suffer from the unavoidable speckle, which causes the segmentation of this data difficult. In this paper, we use the wavelet transformation for segmentation of PolSAR images. Our proposed method is based on the multi-resolution analysis of texture features is based on wavelet transformation. Here, we use the information of gray level value and the information of texture. First, we produce coherency or covariance matrices and then generate span image from them. In the next step of proposed method is texture feature extraction from sub-bands is generated from discrete wavelet transform (DWT). Finally, PolSAR image are segmented using clustering methods as fuzzy c-means (FCM) and k-means clustering. We have applied the proposed methodology to full polarimetric SAR images acquired by the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) L-band system, during July, in 2012 over an agricultural area in Winnipeg, Canada.

Characterization of the Population of the Sulfur-Oxidizing Symbiont of Codakia orbicularis (Bivalvia, Lucinidae) by Single-Cell Analyses▿ †

PubMed Central

Caro, Audrey; Gros, Olivier; Got, Patrice; De Wit, Rutger; Troussellier, Marc

2007-01-01

We investigated the characteristics of the sulfur-oxidizing symbiont hosted in the gills of Codakia orbicularis, a bivalve living in shallow marine tropical environments. Special attention was paid to describing the heterogeneity of the population by using single-cell approaches including flow cytometry (FCM) and different microscopic techniques and by analyzing a cell size fractionation experiment. Up to seven different subpopulations were distinguished by FCM based on nucleic acid content and light side scattering of the cells. The cell size analysis of symbionts showed that the symbiotic population was very heterogeneous in size, i.e., ranging from 0.5 to 5 μm in length, with variable amounts of intracellular sulfur. The side-scatter signal analyzed by FCM, which is often taken as a proxy of cell size, was greatly influenced by the sulfur content of the symbionts. FCM revealed an important heterogeneity in the relative nucleic acid content among the subclasses. The larger cells contained exceptionally high levels of nucleic acids, suggesting that these cells contained multiple copies of their genome, i.e., ranging from one copy for the smaller cells to more than four copies for the larger cells. The proportion of respiring symbionts (5-cyano-2,3-ditolyl-terazolium chloride positive) in the bacteriocytes of Codakia revealed that around 80% of the symbionts hosted by Codakia maintain respiratory activity throughout the year. These data allowed us to gain insight into the functioning of the symbionts within the host and to propose some hypotheses on how the growth of the symbionts is controlled by the host. PMID:17259363

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

Jolly, Brian C.; Helmreich, Grant; Cooley, Kevin M.

In support of fully ceramic microencapsulated (FCM) fuel development, coating development work is ongoing at Oak Ridge National Laboratory (ORNL) to produce tri-structural isotropic (TRISO) coated fuel particles with both UN kernels and surrogate (uranium-free) kernels. The nitride kernels are used to increase fissile density in these SiC-matrix fuel pellets with details described elsewhere. The surrogate TRISO particles are necessary for separate effects testing and for utilization in the consolidation process development. This report focuses on the fabrication and characterization of surrogate TRISO particles which use 800μm in diameter ZrO 2 microspheres as the kernel.

Data transmission and acquisition in NEMO

NASA Astrophysics Data System (ADS)

Bunkheila, G.

2006-11-01

A comprehensive system for data transmission and acquisition has been developed for an "à la NEMO" underwater neutrino telescope based on Čerenkov light detection using photomultipliers (PMTs) as sensors. Signals generated by each sensor are triggered, sampled and tagged by an electronics board, called Front End Module (FEM). Data streams from up to eight FEMs located on one tower floor are collected by a concentration board called Floor Control Module (FCM) and sent to a twin FCM board—located at the onshore station and plugged into an interface machine (FCM Interface, or FCMI) via a PCI bus—through a DWDM-compliant optical fiber and using a self-synchronous serial protocol. All sensor data reach the onshore lab through FCMI where they are made available to subsequent elaboration processes, such as time-wise alignment and muon track event-triggering. To meet requirements of the latter, onshore data unpacking is carried out with respect to their topological origin. The system promised, and keeps on showing, very light charges on power consumption and infrastructure complexity, while having recently proved to behave at high performance levels in its optical part.

NaNet3: The on-shore readout and slow-control board for the KM3NeT-Italia underwater neutrino telescope

NASA Astrophysics Data System (ADS)

Ammendola, R.; Biagioni, A.; Frezza, O.; Lo Cicero, F.; Martinelli, M.; Paolucci, P. S.; Pontisso, L.; Simula, F.; Vicini, P.; Ameli, F.; Nicolau, C. A.; Pastorelli, E.; Simeone, F.; Tosoratto, L.; Lonardo, A.

2016-04-01

The KM3NeT-Italia underwater neutrino detection unit, the tower, consists of 14 floors. Each floor supports 6 Optical Modules containing front-end electronics needed to digitize the PMT signal, format and transmit the data and 2 hydrophones that reconstruct in real-time the position of Optical Modules, for a maximum tower throughput of more than 600 MB/s. All floor data are collected by the Floor Control Module (FCM) board and transmitted by optical bidirectional virtual point-to-point connections to the on-shore laboratory, each FCM needing an on-shore counterpart as communication endpoint. In this contribution we present NaNet3, an on-shore readout board based on Altera Stratix V GX FPGA able to manage multiple FCM data channels with a capability of 800 Mbps each. The design is a NaNet customization for the KM3NeT-Italia experiment, adding support in its I/O interface for a synchronous link protocol with deterministic latency at physical level and for a Time Division Multiplexing protocol at data level.

Quantitative detection of the colloidal gold immunochromatographic strip in HSV color space

NASA Astrophysics Data System (ADS)

Wu, Yuanshu; Gao, Yueming; Du, Min

2014-09-01

In this paper, a fast, reliable and accurate quantitative detection method for the colloidal gold immunochromatographic strip(GICA) is presented. An image acquisition device which is mainly composed of annular LED source, zoom ratio lens, and 10bit CMOS image sensors with 54.5dB SNR is designed for the detection. Firstly, the test line is extracted from the strip window through using the H component peak points of the HSV space as the clustering centers via the Fuzzy C-Means(FCM) clustering method. Then, a two dimensional eigenvalue composed with the hue(H) and saturation(S) of HSV space was proposed to improve the accuracy of the quantitative detection. At last, the experiment of human chorionic gonadotropin(HCG) with the concentration range 0-500mIU/mL is carried out. The results show that the linear correlation coefficient between this method and optical density(OD) values measured by the fiber optical sensor reach 96.74%. Meanwhile, the linearity of fitting curve constructed with concentration was greater than 95.00%.

Orion GN and C Model Based Development: Experience and Lessons Learned

NASA Technical Reports Server (NTRS)

Jackson, Mark C.; Henry, Joel R.

2012-01-01

The Orion Guidance Navigation and Control (GN&C) team is charged with developing GN&C algorithms for the Exploration Flight Test One (EFT-1) vehicle. The GN&C team is a joint team consisting primarily of Prime Contractor (Lockheed Martin) and NASA personnel and contractors. Early in the GN&C development cycle the team selected MATLAB/Simulink as the tool for developing GN&C algorithms and Mathworks autocode tools as the means for converting GN&C algorithms to flight software (FSW). This paper provides an assessment of the successes and problems encountered by the GN&C team from the perspective of Orion GN&C developers, integrators, FSW engineers and management. The Orion GN&C approach to graphical development, including simulation tools, standards development and autocode approaches are scored for the main activities that the team has completed through the development phases of the program.

Nitrogen Starvation Induced Oxidative Stress in an Oil-Producing Green Alga Chlorella sorokiniana C3

PubMed Central

He, Chen-Liu; Wang, Qiang

2013-01-01

Microalgal lipid is one of the most promising feedstocks for biodiesel production. Chlorella appears to be a particularly good option, and nitrogen (N) starvation is an efficient environmental pressure used to increase lipid accumulation in Chlorella cells. The effects of N starvation of an oil-producing wild microalga, Chlorella sorokiniana C3, on lipid accumulation were investigated using thin layer chromatography (TLC), confocal laser scanning microscopy (CLSM) and flow cytometry (FCM). The results showed that N starvation resulted in lipid accumulation in C. sorokiniana C3 cells, oil droplet (OD) formation and significant lipid accumulation in cells were detected after 2 d and 8 d of N starvation, respectively. During OD formation, reduced photosynthetic rate, respiration rate and photochemistry efficiency accompanied by increased damage to PSII were observed, demonstrated by chlorophyll (Chl) fluorescence, 77K fluorescence and oxygen evolution tests. In the mean time the rate of cyclic electron transportation increased correspondingly to produce more ATP for triacylglycerols (TAGs) synthesis. And 0.5 d was found to be the turning point for the early stress response and acclimation of cells to N starvation. Increased level of membrane peroxidation was also observed during OD formation, and superoxide dismutase (SOD), peroxide dismutase (POD) and catalase (CAT) enzyme activity assays suggested impaired reactive oxygen species (ROS) scavenging ability. Significant neutral lipid accumulation was also observed by artificial oxidative stress induced by H2O2 treatment. These results suggested coupled neutral lipid accumulation and oxidative stress during N starvation in C. sorokiniana C3. PMID:23874918

Parallel k-means++

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

A parallelization of the k-means++ seed selection algorithm on three distinct hardware platforms: GPU, multicore CPU, and multithreaded architecture. K-means++ was developed by David Arthur and Sergei Vassilvitskii in 2007 as an extension of the k-means data clustering technique. These algorithms allow people to cluster multidimensional data, by attempting to minimize the mean distance of data points within a cluster. K-means++ improved upon traditional k-means by using a more intelligent approach to selecting the initial seeds for the clustering process. While k-means++ has become a popular alternative to traditional k-means clustering, little work has been done to parallelize this technique.more » We have developed original C++ code for parallelizing the algorithm on three unique hardware architectures: GPU using NVidia's CUDA/Thrust framework, multicore CPU using OpenMP, and the Cray XMT multithreaded architecture. By parallelizing the process for these platforms, we are able to perform k-means++ clustering much more quickly than it could be done before.« less

[Preparation and preliminary evaluation of KGDS-targeted ultrasound contrast agent].

PubMed

Gao, Feng; Ding, Yanfei; Sheng, Xiaoxi; Wang, Wei; Liang, Qi; Luo, Zhuoqiong; Zhou, Ping; Li, Hui

2009-12-01

To prepare a thrombus-targeted ultrasonic contrast agent and to investigate its targeted ability to fresh blood clots. We first synthesized FITC-KGDS-Palm compound, and then prepared thrombus-targeted microbubbles using "ultrasound & high speed shearing method". Fluorescence labeling thrombus-specific peptides and KGDS, directed at the activated glycoprotein(GP)IIb/IIIa receptor of platelets were attached to the surface of lipid microbubbles. The concentration and size of TUCA were measured by Malvern Zeta Sizer Nano-ZS590 and Coulter counter. Immunofluorescence was applied to confirm the conjugation. The conjunct ratio was assessed by flow cytometer (FCM). The KGDS-TUCA was straw yellow turbid liquor, and the concentration was 1.5 x 10(9)/mL, and the average size was 1.5 microm. The targeted microbubbles conjugated with the thrombus-specific peptides showed bright green rings by fluorescence microscope. FCM demonstrated that the wavelength of shell of KGDS-TUCA changed greatly, and the conjunct ratio was 90.04%. In vitro study showed KGDS-TUCA remained stable for 48 h at 4 degree C and target-attached to blood clots and showed good stability. The ultrasound & high speed shearing method to prepare TUCA is easy and in favor of purification. KGDS-TUCA has high specific biological activity. The conjunct ratio and stability of KGDS-TUCA are excellent.

Laser Scanning Cytometry: Principles and Applications—An Update

PubMed Central

Pozarowski, Piotr; Holden, Elena; Darzynkiewicz, Zbigniew

2012-01-01

Laser scanning cytometer (LSC) is the microscope-based cytofluorometer that offers a plethora of unique analytical capabilities, not provided by flow cytometry (FCM). This review describes attributes of LSC and covers its numerous applications derived from plentitude of the parameters that can be measured. Among many LSC applications the following are emphasized: (a) assessment of chromatin condensation to identify mitotic, apoptotic cells, or senescent cells; (b) detection of nuclear or mitochondrial translocation of critical factors such as NF-κB, p53, or Bax; (c) semi-automatic scoring of micronuclei in mutagenicity assays; (d) analysis of fluorescence in situ hybridization (FISH) and use of the FISH analysis attribute to measure other punctuate fluorescence patterns such as γH2AX foci or receptor clustering; (e) enumeration and morphometry of nucleoli and other cell organelles; (f) analysis of progeny of individual cells in clonogenicity assay; (g) cell immunophenotyping; (h) imaging, visual examination, or sequential analysis using different probes of the same cells upon their relocation; (i) in situ enzyme kinetics, drug uptake, and other time-resolved processes; (j) analysis of tissue section architecture using fluorescent and chromogenic probes; (k) application for hypocellular samples (needle aspirate, spinal fluid, etc.); and (l) other clinical applications. Advantages and limitations of LSC are discussed and compared with FCM. PMID:23027005

76 FR 69333 - Derivatives Clearing Organization General Provisions and Core Principles

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-08

...The Commodity Futures Trading Commission (Commission) is adopting final regulations to implement certain provisions of Title VII and Title VIII of the Dodd-Frank Wall Street Reform and Consumer Protection Act (Dodd-Frank Act) governing derivatives clearing organization (DCO) activities. More specifically, the regulations establish the regulatory standards for compliance with DCO Core Principles A (Compliance), B (Financial Resources), C (Participant and Product Eligibility), D (Risk Management), E (Settlement Procedures), F (Treatment of Funds), G (Default Rules and Procedures), H (Rule Enforcement), I (System Safeguards), J (Reporting), K (Recordkeeping), L (Public Information), M (Information Sharing), N (Antitrust Considerations), and R (Legal Risk) set forth in Section 5b of the Commodity Exchange Act (CEA). The Commission also is updating and adding related definitions; adopting implementing rules for DCO chief compliance officers (CCOs); revising procedures for DCO applications including the required use of a new Form DCO; adopting procedural rules applicable to the transfer of a DCO registration; and adding requirements for approval of DCO rules establishing a portfolio margining program for customer accounts carried by a futures commission merchant (FCM) that is also registered as a securities broker-dealer (FCM/BD). In addition, the Commission is adopting certain technical amendments to parts 21 and 39, and is adopting certain delegation provisions under part 140.

Common-mask guided image reconstruction (c-MGIR) for enhanced 4D cone-beam computed tomography

NASA Astrophysics Data System (ADS)

Park, Justin C.; Zhang, Hao; Chen, Yunmei; Fan, Qiyong; Li, Jonathan G.; Liu, Chihray; Lu, Bo

2015-12-01

Compared to 3D cone beam computed tomography (3D CBCT), the image quality of commercially available four-dimensional (4D) CBCT is severely impaired due to the insufficient amount of projection data available for each phase. Since the traditional Feldkamp-Davis-Kress (FDK)-based algorithm is infeasible for reconstructing high quality 4D CBCT images with limited projections, investigators had developed several compress-sensing (CS) based algorithms to improve image quality. The aim of this study is to develop a novel algorithm which can provide better image quality than the FDK and other CS based algorithms with limited projections. We named this algorithm ‘the common mask guided image reconstruction’ (c-MGIR). In c-MGIR, the unknown CBCT volume is mathematically modeled as a combination of phase-specific motion vectors and phase-independent static vectors. The common-mask matrix, which is the key concept behind the c-MGIR algorithm, separates the common static part across all phase images from the possible moving part in each phase image. The moving part and the static part of the volumes were then alternatively updated by solving two sub-minimization problems iteratively. As the novel mathematical transformation allows the static volume and moving volumes to be updated (during each iteration) with global projections and ‘well’ solved static volume respectively, the algorithm was able to reduce the noise and under-sampling artifact (an issue faced by other algorithms) to the maximum extent. To evaluate the performance of our proposed c-MGIR, we utilized imaging data from both numerical phantoms and a lung cancer patient. The qualities of the images reconstructed with c-MGIR were compared with (1) standard FDK algorithm, (2) conventional total variation (CTV) based algorithm, (3) prior image constrained compressed sensing (PICCS) algorithm, and (4) motion-map constrained image reconstruction (MCIR) algorithm, respectively. To improve the efficiency of the algorithm, the code was implemented with a graphic processing unit for parallel processing purposes. Root mean square error (RMSE) between the ground truth and reconstructed volumes of the numerical phantom were in the descending order of FDK, CTV, PICCS, MCIR, and c-MGIR for all phases. Specifically, the means and the standard deviations of the RMSE of FDK, CTV, PICCS, MCIR and c-MGIR for all phases were 42.64  ±  6.5%, 3.63  ±  0.83%, 1.31%  ±  0.09%, 0.86%  ±  0.11% and 0.52 %  ±  0.02%, respectively. The image quality of the patient case also indicated the superiority of c-MGIR compared to other algorithms. The results indicated that clinically viable 4D CBCT images can be reconstructed while requiring no more projection data than a typical clinical 3D CBCT scan. This makes c-MGIR a potential online reconstruction algorithm for 4D CBCT, which can provide much better image quality than other available algorithms, while requiring less dose and potentially less scanning time.

Common-mask guided image reconstruction (c-MGIR) for enhanced 4D cone-beam computed tomography.

PubMed

Park, Justin C; Zhang, Hao; Chen, Yunmei; Fan, Qiyong; Li, Jonathan G; Liu, Chihray; Lu, Bo

2015-12-07

Compared to 3D cone beam computed tomography (3D CBCT), the image quality of commercially available four-dimensional (4D) CBCT is severely impaired due to the insufficient amount of projection data available for each phase. Since the traditional Feldkamp-Davis-Kress (FDK)-based algorithm is infeasible for reconstructing high quality 4D CBCT images with limited projections, investigators had developed several compress-sensing (CS) based algorithms to improve image quality. The aim of this study is to develop a novel algorithm which can provide better image quality than the FDK and other CS based algorithms with limited projections. We named this algorithm 'the common mask guided image reconstruction' (c-MGIR).In c-MGIR, the unknown CBCT volume is mathematically modeled as a combination of phase-specific motion vectors and phase-independent static vectors. The common-mask matrix, which is the key concept behind the c-MGIR algorithm, separates the common static part across all phase images from the possible moving part in each phase image. The moving part and the static part of the volumes were then alternatively updated by solving two sub-minimization problems iteratively. As the novel mathematical transformation allows the static volume and moving volumes to be updated (during each iteration) with global projections and 'well' solved static volume respectively, the algorithm was able to reduce the noise and under-sampling artifact (an issue faced by other algorithms) to the maximum extent. To evaluate the performance of our proposed c-MGIR, we utilized imaging data from both numerical phantoms and a lung cancer patient. The qualities of the images reconstructed with c-MGIR were compared with (1) standard FDK algorithm, (2) conventional total variation (CTV) based algorithm, (3) prior image constrained compressed sensing (PICCS) algorithm, and (4) motion-map constrained image reconstruction (MCIR) algorithm, respectively. To improve the efficiency of the algorithm, the code was implemented with a graphic processing unit for parallel processing purposes.Root mean square error (RMSE) between the ground truth and reconstructed volumes of the numerical phantom were in the descending order of FDK, CTV, PICCS, MCIR, and c-MGIR for all phases. Specifically, the means and the standard deviations of the RMSE of FDK, CTV, PICCS, MCIR and c-MGIR for all phases were 42.64  ±  6.5%, 3.63  ±  0.83%, 1.31%  ±  0.09%, 0.86%  ±  0.11% and 0.52 %  ±  0.02%, respectively. The image quality of the patient case also indicated the superiority of c-MGIR compared to other algorithms.The results indicated that clinically viable 4D CBCT images can be reconstructed while requiring no more projection data than a typical clinical 3D CBCT scan. This makes c-MGIR a potential online reconstruction algorithm for 4D CBCT, which can provide much better image quality than other available algorithms, while requiring less dose and potentially less scanning time.

Lake System Development on the northern Tibetan Plateau during the last 12 ka

NASA Astrophysics Data System (ADS)

Ramisch, A. C.; Lockot, G.; Kasper, T.; Schulte, P.; Zhang, Y.; Daut, G.; Haberzettl, T.; Stauch, G.; Hartmann, K.; Zhu, L.; Lehmkuhl, F.; Maeusbacher, R.; Wuennemann, B.; Diekmann, B.

2013-12-01

Lake systems and their drainage basins provide valuable information of late Quaternary palaeo-environmental conditions on the Tibetan Plateau (TP). This information is often difficult to interpret because of a complex forcing-response mechanism of lake systems and their environment. Here we present an analysis of the endogenic mineral precipitation of Lake Heihai (northern TP) and its environmental constrains expressed by the exogenic mineral input. The mineralogical analysis of carbonate phases by means of X-ray diffraction revealed three distinct stages of carbonate precipitation: Aragonite (late Glacial), Monohydrocalcite (early to mid-Holocene) and Mg bearing Calcite (late Holocene). Each phase precipitates under steady state conditions of exogenic mineral input, as determined by a phase space analysis. This suggests a self-organized precipitation process driven by interactions of different ions. Hence, under steady environmental conditions carbonate precipitation is strongly dependent on the ionic compositions of the lake water and thus controlled by sources of the exogenic mineral input. To analyze the provenance of the exogenic mineral input, a Fuzzy C-Means (FCM) Clustering algorithm was performed on the minerogenic detrital fraction of the total mineral content of 57 surface reference samples. Three major sources can be distinguished: (a) glacially mediated, far distant transport originating from SE catchment (b) precipitation generated, close distant runoff originating from the SW catchment and (c) close distant transport of granite weathering products in the northern parts of the drainage basin. A change from the compositional dominance of (b) over (a) to (a) over (b) in lake sediments suggests a transition from rainfall to glacier dominated runoff production and hence drier climate conditions in the study area during the late Holocene. The environmentally controlled changes in the exogenic mineral input are compared to two different lake systems: Lake Donggi Cona (northern Tibetan Plateau) and Lake Nam Co (southern Tibetan Plateau). Major differences occur during two broad Holocene episodes: Until ~6 ka cal BP the differences reach their maximum with a peak around 9.5 cal ka BP. An intensification of the Indian Summer Monsoon (ISM) led to wetter conditions and an increased minerogenic input into Lake Nam Co. Subsequently, the aridification on the TP led to decreased minerogenic input in all three lakes especially since ~2 ka cal BP. Short term divergences from this trend are caused by dry spells on the northern TP. Their timing is quasi synchronous to Holocene Bond events, suggesting a teleconnection of northern TP climate to the circulation of the North Atlantic Ocean.

Inference from clustering with application to gene-expression microarrays.

PubMed

Dougherty, Edward R; Barrera, Junior; Brun, Marcel; Kim, Seungchan; Cesar, Roberto M; Chen, Yidong; Bittner, Michael; Trent, Jeffrey M

2002-01-01

There are many algorithms to cluster sample data points based on nearness or a similarity measure. Often the implication is that points in different clusters come from different underlying classes, whereas those in the same cluster come from the same class. Stochastically, the underlying classes represent different random processes. The inference is that clusters represent a partition of the sample points according to which process they belong. This paper discusses a model-based clustering toolbox that evaluates cluster accuracy. Each random process is modeled as its mean plus independent noise, sample points are generated, the points are clustered, and the clustering error is the number of points clustered incorrectly according to the generating random processes. Various clustering algorithms are evaluated based on process variance and the key issue of the rate at which algorithmic performance improves with increasing numbers of experimental replications. The model means can be selected by hand to test the separability of expected types of biological expression patterns. Alternatively, the model can be seeded by real data to test the expected precision of that output or the extent of improvement in precision that replication could provide. In the latter case, a clustering algorithm is used to form clusters, and the model is seeded with the means and variances of these clusters. Other algorithms are then tested relative to the seeding algorithm. Results are averaged over various seeds. Output includes error tables and graphs, confusion matrices, principal-component plots, and validation measures. Five algorithms are studied in detail: K-means, fuzzy C-means, self-organizing maps, hierarchical Euclidean-distance-based and correlation-based clustering. The toolbox is applied to gene-expression clustering based on cDNA microarrays using real data. Expression profile graphics are generated and error analysis is displayed within the context of these profile graphics. A large amount of generated output is available over the web.

A review of fuzzy cognitive maps in medicine: Taxonomy, methods, and applications.

PubMed

Amirkhani, Abdollah; Papageorgiou, Elpiniki I; Mohseni, Akram; Mosavi, Mohammad R

2017-04-01

A high percentage of medical errors, committed because of physician's lack of experience, huge volume of data to be analyzed, and inaccessibility to medical records of previous patients, can be reduced using computer-aided techniques. Therefore, designing more efficient medical decision-support systems (MDSSs) to assist physicians in decision-making is crucially important. Through combining the properties of fuzzy logic and neural networks, fuzzy cognitive maps (FCMs) are among the latest, most efficient, and strongest artificial intelligence techniques for modeling complex systems. This review study is conducted to identify different FCM structures used in MDSS designs. The best structure for each medical application can be introduced by studying the properties of FCM structures. This paper surveys the most important decision- making methods and applications of FCMs in the medical field in recent years. To investigate the efficiency and capability of different FCM models in designing MDSSs, medical applications are categorized into four key areas: decision-making, diagnosis, prediction, and classification. Also, various diagnosis and decision support problems addressed by FCMs in recent years are reviewed with the goal of introducing different types of FCMs and determining their contribution to the improvements made in the fields of medical diagnosis and treatment. In this survey, a general trend for future studies in this field is provided by analyzing various FCM structures used for medical purposes, and the results from each category. Due to the unique specifications of FCMs in integrating human knowledge and experience with computer-aided techniques, they are among practical instruments for MDSS design. In the not too distant future, they will have a significant role in medical sciences. Copyright © 2017 Elsevier B.V. All rights reserved.

Environmental and Intrinsic Correlates of Stress in Free-Ranging Wolves

PubMed Central

Molnar, Barbara; Fattebert, Julien; Palme, Rupert; Ciucci, Paolo; Betschart, Bruno; Smith, Douglas W.; Diehl, Peter-Allan

2015-01-01

Background When confronted with a stressor, animals react with several physiological and behavioral responses. Although sustained or repeated stress can result in severe deleterious physiological effects, the causes of stress in free-ranging animals are yet poorly documented. In our study, we aimed at identifying the main factors affecting stress levels in free-ranging wolves (Canis lupus). Methodology/Principal Findings We used fecal cortisol metabolites (FCM) as an index of stress, after validating the method for its application in wolves. We analyzed a total of 450 fecal samples from eleven wolf packs belonging to three protected populations, in Italy (Abruzzo), France (Mercantour), and the United States (Yellowstone). We collected samples during two consecutive winters in each study area. We found no relationship between FCM concentrations and age, sex or social status of individuals. At the group level, our results suggest that breeding pair permanency and the loss of pack members through processes different from dispersal may importantly impact stress levels in wolves. We measured higher FCM levels in comparatively small packs living in sympatry with a population of free-ranging dogs. Lastly, our results indicate that FCM concentrations are associated with endoparasitic infections of individuals. Conclusions/Significance In social mammals sharing strong bonds among group members, the death of one or several members of the group most likely induces important stress in the remainder of the social unit. The potential impact of social and territorial stability on stress levels should be further investigated in free-ranging populations, especially in highly social and in territorial species. As persistent or repeated stressors may facilitate or induce pathologies and physiological alterations that can affect survival and fitness, we advocate considering the potential impact of anthropogenic causes of stress in management and conservation programs regarding wolves and other wildlife. PMID:26398784

Environmental and Intrinsic Correlates of Stress in Free-Ranging Wolves.

PubMed

Molnar, Barbara; Fattebert, Julien; Palme, Rupert; Ciucci, Paolo; Betschart, Bruno; Smith, Douglas W; Diehl, Peter-Allan

2015-01-01

When confronted with a stressor, animals react with several physiological and behavioral responses. Although sustained or repeated stress can result in severe deleterious physiological effects, the causes of stress in free-ranging animals are yet poorly documented. In our study, we aimed at identifying the main factors affecting stress levels in free-ranging wolves (Canis lupus). We used fecal cortisol metabolites (FCM) as an index of stress, after validating the method for its application in wolves. We analyzed a total of 450 fecal samples from eleven wolf packs belonging to three protected populations, in Italy (Abruzzo), France (Mercantour), and the United States (Yellowstone). We collected samples during two consecutive winters in each study area. We found no relationship between FCM concentrations and age, sex or social status of individuals. At the group level, our results suggest that breeding pair permanency and the loss of pack members through processes different from dispersal may importantly impact stress levels in wolves. We measured higher FCM levels in comparatively small packs living in sympatry with a population of free-ranging dogs. Lastly, our results indicate that FCM concentrations are associated with endoparasitic infections of individuals. In social mammals sharing strong bonds among group members, the death of one or several members of the group most likely induces important stress in the remainder of the social unit. The potential impact of social and territorial stability on stress levels should be further investigated in free-ranging populations, especially in highly social and in territorial species. As persistent or repeated stressors may facilitate or induce pathologies and physiological alterations that can affect survival and fitness, we advocate considering the potential impact of anthropogenic causes of stress in management and conservation programs regarding wolves and other wildlife.

Optimized multiparametric flow cytometric analysis of circulating endothelial cells and their subpopulations in peripheral blood of patients with solid tumors: a technical analysis.

PubMed

Zhou, Fangbin; Zhou, Yaying; Yang, Ming; Wen, Jinli; Dong, Jun; Tan, Wenyong

2018-01-01

Circulating endothelial cells (CECs) and their subpopulations could be potential novel biomarkers for various malignancies. However, reliable enumerable methods are warranted to further improve their clinical utility. This study aimed to optimize a flow cytometric method (FCM) assay for CECs and subpopulations in peripheral blood for patients with solid cancers. An FCM assay was used to detect and identify CECs. A panel of 60 blood samples, including 44 metastatic cancer patients and 16 healthy controls, were used in this study. Some key issues of CEC enumeration, including sample material and anticoagulant selection, optimal titration of antibodies, lysis/wash procedures of blood sample preparation, conditions of sample storage, sufficient cell events to enhance the signal, fluorescence-minus-one controls instead of isotype controls to reduce background noise, optimal selection of cell surface markers, and evaluating the reproducibility of our method, were integrated and investigated. Wilcoxon and Mann-Whitney U tests were used to determine statistically significant differences. In this validation study, we refined a five-color FCM method to detect CECs and their subpopulations in peripheral blood of patients with solid tumors. Several key technical issues regarding preanalytical elements, FCM data acquisition, and analysis were addressed. Furthermore, we clinically validated the utility of our method. The baseline levels of mature CECs, endothelial progenitor cells, and activated CECs were higher in cancer patients than healthy subjects ( P <0.01). However, there was no significant difference in resting CEC levels between healthy subjects and cancer patients ( P =0.193). We integrated and comprehensively addressed significant technical issues found in previously published assays and validated the reproducibility and sensitivity of our proposed method. Future work is required to explore the potential of our optimized method in clinical oncologic applications.

Evaluation of radioisotopic and non-radioisotopic versions of local lymph node assays for subcategorization of skin sensitizers compliant to UN GHS rev 4.

PubMed

Ha, Soojin; Ahn, Il Young; Kim, Da-Eun; Lee, Jong Kwon; Sohn, Soojung; Jung, Mi-Sook; Heo, Yong; Omori, Takashi; Bae, SeungJin; Lim, Kyung-Min

2017-04-01

Recently UN GHS has introduced the sub-categorization of skin sensitizers for which ECt (concentration estimated to induce stimulation index above threshold) of the murine local lymph node assay (LLNA) is used as criteria. Non-radioisotopic variants of LLNA, LLNA: DA, LLNA: BrdU-ELISA, LNCC and LLNA: BrdU-FCM were developed yet their utilities for potency sub-categorization are not established. Here we assessed the agreement of LLNA variants with LLNA or human data in potency sub-categorization for 22 reference substances of OECD TG429. Concordance of sub-categorization with LLNA was highest for LLNA: BrdU-FCM(91%, κ = 0.833, weighted kappa) followed by LLNA: BrdU-ELISA (82%, κ = 0.744) and LLNA: DA (73%, κ = 0.656) whereas LNCC only showed a modest association (64%, κ = 0.441). With human data, LLNA agreed best (77%) followed by LLNA: DA and LLNA: BrdU-FCM(73%), LLNA: BrdU-ELISA (68%) and LNCC(55%). Bland-Altman plot revealed that ECt's of LLNA variants largely agreed with LLNA where most values fell within 95% limit of agreement. Correlation between ECt's of LLNA and LLNA variants were high except for LNCC(pair-wise with LLNA, LLNA: DA, r = 0.848, LLNA: BrdU-ELISA, r = 0.744, LLNA: BrdU-FCM, r=0.786, and LNCC, r = 0.561 by Pearson). Collectively, these results demonstrated that LLNA variants exhibit performance comparable to LLNA in the potency sub-categorization although additional substances shall be analyzed in the future. Copyright © 2017 Elsevier Inc. All rights reserved.

Excretion and measurement of corticosterone and testosterone metabolites in bank voles (Myodes glareolus).

PubMed

Sipari, Saana; Ylönen, Hannu; Palme, Rupert

2017-03-01

The bank vole is a commonly used model species in behavioral and ecophysiological studies. Thus, presenting a validated method for noninvasive monitoring of corticosterone and testosterone secretion is of high relevance. Here, we evaluated the effect of time of day and an ACTH challenge test on measured fecal corticosterone (FCM) and testosterone (FTM) metabolites in both sexes. Furthermore, we performed radiometabolism experiments for both steroids and sexes to study metabolism and excretion of 3 H-corticosterone and 3 H-testosterone. FCM and FTM were analysed with a 5α-pregnane-3β,11β,21-triol-20-one enzyme immunoassay (EIA) and a testosterone (measuring 17β-hydroxyandrostanes) EIA, respectively. Males had significantly higher FCM levels than females and their main excretion route was via the feces (∼72%), whereas females excreted nearly equal portions in both feces and urine. For testosterone the main excretion route was via the feces in both sexes (∼80%). The time course of excretion was similar in both sexes, but for the first time a significant difference between injected steroids was found: Corticosterone was excreted faster than testosterone, both in urine (median of peak levels: 4h vs 6h) and feces (6h vs 8h). Several metabolites were present in the feces and the tested EIAs reacted with some of them. Time of day had a significant effect on measured fecal steroid metabolites. As expected, males had significantly higher FTM levels than females. ACTH administration significantly increased FCM values; peaks were observed 4-8h after injection. In conclusion, both tested EIAs proved suited for a noninvasive measurement of glucocorticoids and androgens in bank voles. Copyright © 2016 Elsevier Inc. All rights reserved.

Rapid differentiation of methicillin-resistant and methicillin-susceptible Staphylococcus aureus by flow cytometry after brief antibiotic exposure.

PubMed

Shrestha, Nabin K; Scalera, Nikole M; Wilson, Deborah A; Procop, Gary W

2011-06-01

We noticed that methicillin-resistant Staphylococcus aureus (MRSA) and methicillin-susceptible S. aureus (MSSA) isolates yielded side-scatter (SSC) and fluorescence intensity (FI) differences on flow cytometry (FCM) following incubation in oxacillin broth. The purpose of this study was to determine whether MRSA and MSSA could be reliably differentiated by FCM. S. aureus isolates were incubated in oxacillin-containing Mueller-Hinton broth, stained using the FASTEST total viable organisms kit, and analyzed by FCM in the MicroPRO instrument. SSC versus FI were examined, and gates 1 and 2 were defined to encompass the majority of MSSA and MRSA signal events, respectively. A count ratio (CR) was defined as the ratio of counts in gate 2 to those in gate 1. Initially, 33 isolates were tested after 4 h of incubation for proof-of-concept. Twenty others were then tested after incubation intervals ranging from 30 min to 4 h to determine the earliest possible time for differentiation. Next, 100 separate isolates were tested to determine the best CR cutoff value. Finally, the CR was validated by using an independent cohort of 121 isolates. We noted that MRSA isolates had higher SSC and FI readings than did MSSA isolates after 2 h of incubation. The receiver-operator characteristics curve showed that a CR cutoff of 0.0445 reliably differentiated MRSA from MSSA. In the validation cohort, this cutoff had a sensitivity of 100% and a specificity of 98.7% for identifying MRSA from among S. aureus isolates, following 2 h of incubation. This study demonstrates that MRSA and MSSA can be accurately differentiated by FCM after 2 h of incubation in an oxacillin-containing liquid culture medium.

Rapid Differentiation of Methicillin-Resistant and Methicillin-Susceptible Staphylococcus aureus by Flow Cytometry after Brief Antibiotic Exposure▿

PubMed Central

Shrestha, Nabin K.; Scalera, Nikole M.; Wilson, Deborah A.; Procop, Gary W.

2011-01-01

We noticed that methicillin-resistant Staphylococcus aureus (MRSA) and methicillin-susceptible S. aureus (MSSA) isolates yielded side-scatter (SSC) and fluorescence intensity (FI) differences on flow cytometry (FCM) following incubation in oxacillin broth. The purpose of this study was to determine whether MRSA and MSSA could be reliably differentiated by FCM. S. aureus isolates were incubated in oxacillin-containing Mueller-Hinton broth, stained using the FASTEST total viable organisms kit, and analyzed by FCM in the MicroPRO instrument. SSC versus FI were examined, and gates 1 and 2 were defined to encompass the majority of MSSA and MRSA signal events, respectively. A count ratio (CR) was defined as the ratio of counts in gate 2 to those in gate 1. Initially, 33 isolates were tested after 4 h of incubation for proof-of-concept. Twenty others were then tested after incubation intervals ranging from 30 min to 4 h to determine the earliest possible time for differentiation. Next, 100 separate isolates were tested to determine the best CR cutoff value. Finally, the CR was validated by using an independent cohort of 121 isolates. We noted that MRSA isolates had higher SSC and FI readings than did MSSA isolates after 2 h of incubation. The receiver-operator characteristics curve showed that a CR cutoff of 0.0445 reliably differentiated MRSA from MSSA. In the validation cohort, this cutoff had a sensitivity of 100% and a specificity of 98.7% for identifying MRSA from among S. aureus isolates, following 2 h of incubation. This study demonstrates that MRSA and MSSA can be accurately differentiated by FCM after 2 h of incubation in an oxacillin-containing liquid culture medium. PMID:21471343

The implementation of hybrid clustering using fuzzy c-means and divisive algorithm for analyzing DNA human Papillomavirus cause of cervical cancer

NASA Astrophysics Data System (ADS)

Andryani, Diyah Septi; Bustamam, Alhadi; Lestari, Dian

2017-03-01

Clustering aims to classify the different patterns into groups called clusters. In this clustering method, we use n-mers frequency to calculate the distance matrix which is considered more accurate than using the DNA alignment. The clustering results could be used to discover biologically important sub-sections and groups of genes. Many clustering methods have been developed, while hard clustering methods considered less accurate than fuzzy clustering methods, especially if it is used for outliers data. Among fuzzy clustering methods, fuzzy c-means is one the best known for its accuracy and simplicity. Fuzzy c-means clustering uses membership function variable, which refers to how likely the data could be members into a cluster. Fuzzy c-means clustering works using the principle of minimizing the objective function. Parameters of membership function in fuzzy are used as a weighting factor which is also called the fuzzier. In this study we implement hybrid clustering using fuzzy c-means and divisive algorithm which could improve the accuracy of cluster membership compare to traditional partitional approach only. In this study fuzzy c-means is used in the first step to find partition results. Furthermore divisive algorithms will run on the second step to find sub-clusters and dendogram of phylogenetic tree. To find the best number of clusters is determined using the minimum value of Davies Bouldin Index (DBI) of the cluster results. In this research, the results show that the methods introduced in this paper is better than other partitioning methods. Finally, we found 3 clusters with DBI value of 1.126628 at first step of clustering. Moreover, DBI values after implementing the second step of clustering are always producing smaller IDB values compare to the results of using first step clustering only. This condition indicates that the hybrid approach in this study produce better performance of the cluster results, in term its DBI values.

The Creating an Optimal Warfarin Nomogram (CROWN) Study

PubMed Central

Perlstein, Todd S.; Goldhaber, Samuel Z.; Nelson, Kerrie; Joshi, Victoria; Morgan, T. Vance; Lesko, Lawrence J.; Lee, Joo-Yeon; Gobburu, Jogarao; Schoenfeld, David; Kucherlapati, Raju; Freeman, Mason W.; Creager, Mark A.

2014-01-01

A significant proportion of warfarin dose variability is explained by variation in the genotypes of the cytochrome P450 CYP2C9 and the vitamin K epoxide reductase complex, VKORC1, enzymes that influence warfarin metabolism and sensitivity, respectively. We sought to develop an optimal pharmacogenetic warfarin dosing algorithm that incorporated clinical and genetic information. We enroled patients initiating warfarin therapy. Genotyping was performed of the VKORC1, –1639G>A, the CYP2C9*2, 430C>T, and the CYP2C9*3, 1075C>A genotypes. The initial warfarin dosing algorithm (Algorithm A) was based upon established clinical practice and published warfarin pharmacogenetic information. Subsequent dosing algorithms (Algorithms B and Algorithm C) were derived from pharmacokinetic / pharmacodynamic (PK/PD) modelling of warfarin dose, international normalised ratio (INR), clinical and genetic factors from patients treated by the preceding algorithm(s). The primary outcome was the time in the therapeutic range, considered an INR of 1.8 to 3.2. A total of 344 subjects are included in the study analyses. The mean percentage time within the therapeutic range for each subject increased progressively from Algorithm A to Algorithm C from 58.9 (22.0), to 59.7 (23.0), to 65.8 (16.9) percent (p = 0.04). Improvement also occurred in most secondary endpoints, which included the per-patient percentage of INRs outside of the therapeutic range (p = 0.004), the time to the first therapeutic INR (p = 0.07), and the time to achieve stable therapeutic anticoagulation (p < 0.001). In conclusion, warfarin pharmacogenetic dosing can be optimised in real time utilising observed PK/PD information in an adaptive fashion. Clinical Trial Registration ClinicalTrials.gov (NCT00401414) PMID:22116191

Direct quantification of bacterial biomass in influent, effluent and activated sludge of wastewater treatment plants by using flow cytometry.

PubMed

Foladori, P; Bruni, L; Tamburini, S; Ziglio, G

2010-07-01

A rapid multi-step procedure, potentially amenable to automation, was proposed for quantifying viable and active bacterial cells, estimating their biovolume using flow cytometry (FCM) and to calculate their biomass within the main stages of a wastewater treatment plant: raw wastewater, settled wastewater, activated sludge and effluent. Fluorescent staining of bacteria using SYBR-Green I + Propidium Iodide (to discriminate cell integrity or permeabilisation) and BCECF-AM (to identify enzymatic activity) was applied to count bacterial cells by FCM. A recently developed specific procedure was applied to convert Forward Angle Light Scatter measured by FCM into the corresponding bacterial biovolume. This conversion permits the calculation of the viable and active bacterial biomass in wastewater, activated sludge and effluent, expressed as Volatile Suspended Solids (VSS) or particulate Chemical Oxygen Demand (COD). Viable bacterial biomass represented only a small part of particulate COD in raw wastewater (4.8 +/- 2.4%), settled wastewater (10.7 +/- 3.1%), activated sludge (11.1 +/- 2.1%) and effluent (3.2 +/- 2.2%). Active bacterial biomass counted for a percentage of 30-47% of the viable bacterial biomass within the stages of the wastewater treatment plant. Copyright 2010 Elsevier Ltd. All rights reserved.

Exposure to airborne asbestos in thermal power plants in Mongolia

PubMed Central

Damiran, Naransukh; Silbergeld, Ellen K; Frank, Arthur L; Lkhasuren, Oyuntogos; Ochir, Chimedsuren; Breysse, Patrick N

2015-01-01

Background: Coal-fired thermal power plants (TPPs) in Mongolia use various types of asbestos-containing materials (ACMs) in thermal insulation of piping systems, furnaces, and other products. Objective: To investigate the occupational exposure of insulation workers to airborne asbestos in Mongolian power plants. Methods: Forty-seven air samples were collected from four power plants in Mongolia during the progress of insulation work. The samples were analyzed by phase contrast microscopy (PCM) and transmission electron microscopy (TEM). Results: The average phase contrast microscopy equivalent (PCME) asbestos fiber concentration was 0.93 f/cm3. Sixteen of the 41 personal and one of the area samples exceeded the United States Occupational Safety and Health Administration (US OSHA) short-term exposure limit of 1.0 f/cm3. If it is assumed that the short-term samples collected are representative of full-shift exposure, then the exposures are approximately 10 times higher than the US OSHA 8-hour permissible exposure limit of 0.1 f/cm3. Conclusion: Power plant insulation workers are exposed to airborne asbestos at concentrations that exceed the US OSHA Permissible Exposure Limit. Action to mitigate the risks should be taken in Mongolia. PMID:25730489

Exposure to airborne asbestos in thermal power plants in Mongolia.

PubMed

Damiran, Naransukh; Silbergeld, Ellen K; Frank, Arthur L; Lkhasuren, Oyuntogos; Ochir, Chimedsuren; Breysse, Patrick N

2015-01-01

Coal-fired thermal power plants (TPPs) in Mongolia use various types of asbestos-containing materials (ACMs) in thermal insulation of piping systems, furnaces, and other products. To investigate the occupational exposure of insulation workers to airborne asbestos in Mongolian power plants. Forty-seven air samples were collected from four power plants in Mongolia during the progress of insulation work. The samples were analyzed by phase contrast microscopy (PCM) and transmission electron microscopy (TEM). The average phase contrast microscopy equivalent (PCME) asbestos fiber concentration was 0·93 f/cm(3). Sixteen of the 41 personal and one of the area samples exceeded the United States Occupational Safety and Health Administration (US OSHA) short-term exposure limit of 1·0 f/cm(3). If it is assumed that the short-term samples collected are representative of full-shift exposure, then the exposures are approximately 10 times higher than the US OSHA 8-hour permissible exposure limit of 0·1 f/cm(3). Power plant insulation workers are exposed to airborne asbestos at concentrations that exceed the US OSHA Permissible Exposure Limit. Action to mitigate the risks should be taken in Mongolia.

Assessing framing assumptions in quantitative health impact assessments: a housing intervention example.

PubMed

Mesa-Frias, Marco; Chalabi, Zaid; Foss, Anna M

2013-09-01

Health impact assessment (HIA) is often used to determine ex ante the health impact of an environmental policy or an environmental intervention. Underpinning any HIA is the framing assumption, which defines the causal pathways mapping environmental exposures to health outcomes. The sensitivity of the HIA to the framing assumptions is often ignored. A novel method based on fuzzy cognitive map (FCM) is developed to quantify the framing assumptions in the assessment stage of a HIA, and is then applied to a housing intervention (tightening insulation) as a case-study. Framing assumptions of the case-study were identified through a literature search of Ovid Medline (1948-2011). The FCM approach was used to identify the key variables that have the most influence in a HIA. Changes in air-tightness, ventilation, indoor air quality and mould/humidity have been identified as having the most influence on health. The FCM approach is widely applicable and can be used to inform the formulation of the framing assumptions in any quantitative HIA of environmental interventions. We argue that it is necessary to explore and quantify framing assumptions prior to conducting a detailed quantitative HIA during the assessment stage. Copyright © 2013 Elsevier Ltd. All rights reserved.

Metabolic and endocrine profiles and reproductive parameters in dairy cows under grazing conditions: effect of polymorphisms in somatotropic axis genes

PubMed Central

2011-01-01

Background The present study hypothesized that GH-AluI and IGF-I-SnabI polymorphisms do change the metabolic/endocrine profiles in Holstein cows during the transition period, which in turn are associated with productive and reproductive parameters. Methods Holstein cows (Farm 1, primiparous cows, n = 110, and Farm 2, multiparous cows, n = 76) under grazing conditions were selected and GH and IGF-I genotypes were determined. Blood samples for metabolic/endocrine determinations were taken during the transition period and early lactation in both farms. Data was analyzed by farm using a repeated measures analyses including GH and IGF-I genotypes, days and interactions as fixed effects, sire and cow as random effects and calving date as covariate. Results and Discussion Frequencies of GH and IGF-I alleles were L:0.84, V:0.16 and A:0.60, B:0.40, respectively. The GH genotype was not associated with productive or reproductive variables, but interaction with days affected FCM yield in multiparous (farm 2) cows (LL yielded more than LV cows) in early lactation. The GH genotype affected NEFA and IGF-I concentrations in farm 1 (LV had higher NEFA and lower IGF-I than LL cows) suggesting a better energy status of LL cows. There was no effect of IGF-I genotype on productive variables, but a trend was found for FCM in farm 2 (AB cows yielded more than AA cows). IGF-I genotype affected calving first service interval in farm 1, and the interaction with days tended to affect FCM yield (AB cows had a shorter interval and yielded more FCM than BB cows). IGF-I genotype affected BHB, NEFA, and insulin concentrations in farm 1: primiparous BB cows had lower NEFA and BHB and higher insulin concentrations. In farm 2, there was no effect of IGF-I genotype, but there was an interaction with days on IGF-I concentration, suggesting a greater uncoupling somatropic axis in AB and BB than AA cows, being in accordance with greater FCM yield in AB cows. Conclusion The GH and IGF-I genotypes had no substantial effect on productive parameters, although IGF-I genotype affected calving-first service interval in primiparous cows. Besides, these genotypes may modify the endocrine/metabolic profiles of the transition dairy cow under grazing conditions. PMID:21635772

Analyzing the impact of social factors on homelessness: a Fuzzy Cognitive Map approach

PubMed Central

2013-01-01

Background The forces which affect homelessness are complex and often interactive in nature. Social forces such as addictions, family breakdown, and mental illness are compounded by structural forces such as lack of available low-cost housing, poor economic conditions, and insufficient mental health services. Together these factors impact levels of homelessness through their dynamic relations. Historic models, which are static in nature, have only been marginally successful in capturing these relationships. Methods Fuzzy Logic (FL) and fuzzy cognitive maps (FCMs) are particularly suited to the modeling of complex social problems, such as homelessness, due to their inherent ability to model intricate, interactive systems often described in vague conceptual terms and then organize them into a specific, concrete form (i.e., the FCM) which can be readily understood by social scientists and others. Using FL we converted information, taken from recently published, peer reviewed articles, for a select group of factors related to homelessness and then calculated the strength of influence (weights) for pairs of factors. We then used these weighted relationships in a FCM to test the effects of increasing or decreasing individual or groups of factors. Results of these trials were explainable according to current empirical knowledge related to homelessness. Results Prior graphic maps of homelessness have been of limited use due to the dynamic nature of the concepts related to homelessness. The FCM technique captures greater degrees of dynamism and complexity than static models, allowing relevant concepts to be manipulated and interacted. This, in turn, allows for a much more realistic picture of homelessness. Through network analysis of the FCM we determined that Education exerts the greatest force in the model and hence impacts the dynamism and complexity of a social problem such as homelessness. Conclusions The FCM built to model the complex social system of homelessness reasonably represented reality for the sample scenarios created. This confirmed that the model worked and that a search of peer reviewed, academic literature is a reasonable foundation upon which to build the model. Further, it was determined that the direction and strengths of relationships between concepts included in this map are a reasonable approximation of their action in reality. However, dynamic models are not without their limitations and must be acknowledged as inherently exploratory. PMID:23971944

A Scalable Framework For Segmenting Magnetic Resonance Images

PubMed Central

Hore, Prodip; Goldgof, Dmitry B.; Gu, Yuhua; Maudsley, Andrew A.; Darkazanli, Ammar

2009-01-01

A fast, accurate and fully automatic method of segmenting magnetic resonance images of the human brain is introduced. The approach scales well allowing fast segmentations of fine resolution images. The approach is based on modifications of the soft clustering algorithm, fuzzy c-means, that enable it to scale to large data sets. Two types of modifications to create incremental versions of fuzzy c-means are discussed. They are much faster when compared to fuzzy c-means for medium to extremely large data sets because they work on successive subsets of the data. They are comparable in quality to application of fuzzy c-means to all of the data. The clustering algorithms coupled with inhomogeneity correction and smoothing are used to create a framework for automatically segmenting magnetic resonance images of the human brain. The framework is applied to a set of normal human brain volumes acquired from different magnetic resonance scanners using different head coils, acquisition parameters and field strengths. Results are compared to those from two widely used magnetic resonance image segmentation programs, Statistical Parametric Mapping and the FMRIB Software Library (FSL). The results are comparable to FSL while providing significant speed-up and better scalability to larger volumes of data. PMID:20046893

Fuzzy cognitive map in differential diagnosis of alterations in urinary elimination: a nursing approach.

PubMed

Lopes, Maria Helena Baena de Moraes; Ortega, Neli Regina Siqueira; Silveira, Paulo Sérgio Panse; Massad, Eduardo; Higa, Rosângela; Marin, Heimar de Fátima

2013-03-01

To develop a decision support system to discriminate the diagnoses of alterations in urinary elimination, according to the nursing terminology of NANDA International (NANDA-I). A fuzzy cognitive map (FCM) was structured considering six possible diagnoses: stress urinary incontinence, reflex urinary incontinence, urge urinary incontinence, functional urinary incontinence, total urinary incontinence and urinary retention; and 39 signals associated with them. The model was implemented in Microsoft Visual C++(®) Edition 2005 and applied in 195 real cases. Its performance was evaluated through the agreement test, comparing its results with the diagnoses determined by three experts (nurses). The sensitivity and specificity of the model were calculated considering the expert's opinion as a gold standard. In order to compute the Kappa's values we considered two situations, since more than one diagnosis was possible: the overestimation of the accordance in which the case was considered as concordant when at least one diagnoses was equal; and the underestimation of the accordance, in which the case was considered as discordant when at least one diagnosis was different. The overestimation of the accordance showed an excellent agreement (kappa=0.92, p<0.0001); and the underestimation provided a moderate agreement (kappa=0.42, p<0.0001). In general the FCM model showed high sensitivity and specificity, of 0.95 and 0.92, respectively, but provided a low specificity value in determining the diagnosis of urge urinary incontinence (0.43) and a low sensitivity value to total urinary incontinence (0.42). The decision support system developed presented a good performance compared to other types of expert systems for differential diagnosis of alterations in urinary elimination. Since there are few similar studies in the literature, we are convinced of the importance of investing in this kind of modeling, both from the theoretical and from the health applied points of view. In spite of the good results, the FCM should be improved to identify the diagnoses of urge urinary incontinence and total urinary incontinence. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Fuzzy cognitive map in differential diagnosis of alterations in urinary elimination: A nursing approach

PubMed Central

de Moraes Lopes, Maria Helena Baena; Ortega, Neli Regina Siqueira; Silveira, Paulo Sérgio Panse; Massad, Eduardo; Higa, Rosângela; de Fátima Marin, Heimar

2013-01-01

Purpose To develop a decision support system to discriminate the diagnoses of alterations in urinary elimination, according to the nursing terminology of NANDA International (NANDA-I). Methods A fuzzy cognitive map (FCM) was structured considering six possible diagnoses: stress urinary incontinence, reflex urinary incontinence, urge urinary incontinence, functional urinary incontinence, total urinary incontinence and urinary retention; and 39 signals associated with them. The model was implemented in Microsoft Visual C++® Edition 2005 and applied in 195 real cases. Its performance was evaluated through the agreement test, comparing its results with the diagnoses determined by three experts (nurses). The sensitivity and specificity of the model were calculated considering the expert’s opinion as a gold standard. In order to compute the Kappa’s values we considered two situations, since more than one diagnosis was possible: the overestimation of the accordance in which the case was considered as concordant when at least one diagnoses was equal; and the underestimation of the accordance, in which the case was considered as discordant when at least one diagnosis was different. Results The overestimation of the accordance showed an excellent agreement (kappa = 0.92, p < 0.0001); and the underestimation provided a moderate agreement (kappa = 0.42, p < 0.0001). In general the FCM model showed high sensitivity and specificity, of 0.95 and 0.92, respectively, but provided a low specificity value in determining the diagnosis of urge urinary incontinence (0.43) and a low sensitivity value to total urinary incontinence (0.42). Conclusions The decision support system developed presented a good performance compared to other types of expert systems for differential diagnosis of alterations in urinary elimination. Since there are few similar studies in the literature, we are convinced of the importance of investing in this kind of modeling, both from the theoretical and from the health applied points of view. Limitations In spite of the good results, the FCM should be improved to identify the diagnoses of urge urinary incontinence and total urinary incontinence. PMID:22743142

Real-time core body temperature estimation from heart rate for first responders wearing different levels of personal protective equipment.

PubMed

Buller, Mark J; Tharion, William J; Duhamel, Cynthia M; Yokota, Miyo

2015-01-01

First responders often wear personal protective equipment (PPE) for protection from on-the-job hazards. While PPE ensembles offer individuals protection, they limit one's ability to thermoregulate, and can place the wearer in danger of heat exhaustion and higher cardiac stress. Automatically monitoring thermal-work strain is one means to manage these risks, but measuring core body temperature (Tc) has proved problematic. An algorithm that estimates Tc from sequential measures of heart rate (HR) was compared to the observed Tc from 27 US soldiers participating in three different chemical/biological training events (45-90 min duration) while wearing PPE. Hotter participants (higher Tc) averaged (HRs) of 140 bpm and reached Tc around 39 °C. Overall the algorithm had a small bias (0.02 °C) and root mean square error (0.21 °C). Limits of agreement (LoA ± 0.48 °C) were similar to comparisons of Tc measured by oesophageal and rectal probes. The algorithm shows promise for use in real-time monitoring of encapsulated first responders. An algorithm to estimate core temperature (Tc) from non-invasive measures of HR was validated. Three independent studies (n = 27) compared the estimated Tc to the observed Tc in humans participating in chemical/ biological hazard training. The algorithm’s bias and variance to observed data were similar to that found from comparisons of oesophageal and rectal measurements.

High-purity flow sorting of early meiocytes based on DNA analysis of guinea pig spermatogenic cells.

PubMed

Rodríguez-Casuriaga, Rosana; Geisinger, Adriana; Santiñaque, Federico F; López-Carro, Beatriz; Folle, Gustavo A

2011-08-01

Mammalian spermatogenesis is still nowadays poorly understood at the molecular level. Testis cellular heterogeneity is a major drawback for spermatogenic gene expression studies, especially when research is focused on stages that are usually very short and poorly represented at the cellular level such as initial meiotic prophase I (i.e., leptotene [L] and zygotene [Z]). Presumably, genes whose products are involved in critical meiotic events such as alignment, pairing and recombination of homologous chromosomes are expressed during the short stages of early meiotic prophase. Aiming to characterize mammalian early meiotic gene expression, we have found the guinea pig (Cavia porcellus) as an especially attractive model. A detailed analysis of its first spermatogenic wave by flow cytometry (FCM) and optical microscopy showed that guinea pig testes exhibit a higher representation of early meiotic stages compared to other studied rodents, partly because of their longer span, and also as a result of the increased number of cells entering meiosis. Moreover, we have found that adult guinea pig testes exhibit a peculiar 4C DNA content profile, with a bimodal peak for L/Z and P spermatocytes that is absent in other rodents. Besides, we show that this unusual 4C peak allows the separation by FCM of highly pure L/Z spermatocyte populations aside from pachytene ones, even from adult individuals. To our knowledge, this is the first report on an accurate and suitable method for highly pure early meiotic prophase cell isolation from adult mammals, and thus sets an interesting approach for gene expression studies aiming at a deeper understanding of the molecular groundwork underlying male gamete production. Copyright © 2011 International Society for Advancement of Cytometry.

In vivo integrated photoacoustic and confocal microscopy of hemoglobin oxygen saturation and oxygen partial pressure.

PubMed

Wang, Yu; Hu, Song; Maslov, Konstantin; Zhang, Yu; Xia, Younan; Wang, Lihong V

2011-04-01

We developed dual-modality microscope integrating photoacoustic microscopy (PAM) and fluorescence confocal microscopy (FCM) to noninvasively image hemoglobin oxygen saturation (sO₂) and oxygen partial pressure (pO₂) in vivo in single blood vessels with high spatial resolution. While PAM measures sO₂ by imaging hemoglobin optical absorption at two wavelengths, FCM quantifies pO₂ using phosphorescence quenching. The variations of sO₂ and pO₂ values in multiple orders of vessel branches under hyperoxic (100% oxygen) and normoxic (21% oxygen) conditions correlate well with the oxygen-hemoglobin dissociation curve. In addition, the total concentration of hemoglobin is imaged by PAM at an isosbestic wavelength.

Mapping the EORTC QLQ-C30 onto the EQ-5D-3L: assessing the external validity of existing mapping algorithms.

PubMed

Doble, Brett; Lorgelly, Paula

2016-04-01

To determine the external validity of existing mapping algorithms for predicting EQ-5D-3L utility values from EORTC QLQ-C30 responses and to establish their generalizability in different types of cancer. A main analysis (pooled) sample of 3560 observations (1727 patients) and two disease severity patient samples (496 and 93 patients) with repeated observations over time from Cancer 2015 were used to validate the existing algorithms. Errors were calculated between observed and predicted EQ-5D-3L utility values using a single pooled sample and ten pooled tumour type-specific samples. Predictive accuracy was assessed using mean absolute error (MAE) and standardized root-mean-squared error (RMSE). The association between observed and predicted EQ-5D utility values and other covariates across the distribution was tested using quantile regression. Quality-adjusted life years (QALYs) were calculated using observed and predicted values to test responsiveness. Ten 'preferred' mapping algorithms were identified. Two algorithms estimated via response mapping and ordinary least-squares regression using dummy variables performed well on number of validation criteria, including accurate prediction of the best and worst QLQ-C30 health states, predicted values within the EQ-5D tariff range, relatively small MAEs and RMSEs, and minimal differences between estimated QALYs. Comparison of predictive accuracy across ten tumour type-specific samples highlighted that algorithms are relatively insensitive to grouping by tumour type and affected more by differences in disease severity. Two of the 'preferred' mapping algorithms suggest more accurate predictions, but limitations exist. We recommend extensive scenario analyses if mapped utilities are used in cost-utility analyses.

Modeling of nanotherapeutics delivery based on tumor perfusion

PubMed Central

van de Ven, Anne L.; Abdollahi, Behnaz; Martinez, Carlos J.; Burey, Lacey A.; Landis, Melissa D.; Chang, Jenny C.; Ferrari, Mauro; Frieboes, Hermann B.

2013-01-01

Heterogeneities in the perfusion of solid tumors prevent optimal delivery of nanotherapeutics. Clinical imaging protocols to obtain patient-specific data have proven difficult to implement. It is challenging to determine which perfusion features hold greater prognostic value and to relate measurements to vessel structure and function. With the advent of systemically administered nanotherapeutics, whose delivery is dependent on overcoming diffusive and convective barriers to transport, such knowledge is increasingly important. We describe a framework for the automated evaluation of vascular perfusion curves measured at the single vessel level. Primary tumor fragments, collected from triple-negative breast cancer patients and grown as xenografts in mice, were injected with fluorescence contrast and monitored using intravital microscopy. The time to arterial peak and venous delay, two features whose probability distributions were measured directly from time-series curves, were analyzed using a Fuzzy C-mean (FCM) supervised classifier in order to rank individual tumors according to their perfusion characteristics. The resulting rankings correlated inversely with experimental nanoparticle accumulation measurements, enabling modeling of nanotherapeutics delivery without requiring any underlying assumptions about tissue structure or function, or heterogeneities contained within. With additional calibration, these methodologies may enable the study of nanotherapeutics delivery strategies in a variety of tumor models. PMID:24039540

Nitrogen-Doped Carbon Nanoparticles for Oxygen Reduction Prepared via a Crushing Method Involving a High Shear Mixer.

PubMed

Shi, Lei; Wu, Tao; Wang, Yiqing; Zhang, Jie; Wang, Gang; Zhang, Jinli; Dai, Bin; Yu, Feng

2017-09-04

The disposal of agricultural wastes such as fresh banana peels (BPs) is an environmental issue. In this work, fresh BPs were successfully transformed into nitrogen-doped carbon nanoparticles (N-CNPs) by using a high shear mixer facilitated crushing method (HSM-FCM) followed by carbonization under Ar atmosphere. Ammonia-activated N-CNPs (N-CNPs-NH₃) were prepared via subsequent ammonia activation treatments at a high temperature. The as-prepared N-CNPs and N-CNPs-NH₃ materials both exhibited high surface areas (above 700 m²/g) and mean particle size of 50 nm. N-CNPs-NH 3 showed a relatively higher content of pyridinic and graphitic N compared to N-CNPs. In alkaline media, N-CNPs-NH₃ showed superior performances as an oxygen reduction reaction (ORR) catalyst (E₀ = -0.033 V, J = 2.4 mA/cm²) compared to N-CNPs (E₀ = 0.07 V, J = 1.8 mA/cm²). In addition, N-CNPs-NH₃ showed greater oxygen reduction stability and superior methanol crossover avoidance than a conventional Pt/C catalyst. This study provides a novel, simple, and scalable approach to valorize biomass wastes by synthesizing highly efficient electrochemical ORR catalysts.

R-HPDC Process with Forced Convection Mixing Device for Automotive Part of A380 Aluminum Alloy

PubMed Central

Zhou, Bing; Kang, Yonglin; Qi, Mingfan; Zhang, Huanhuan; Zhu, Guoming

2014-01-01

The continuing quest for cost-effective and complex shaped aluminum castings with fewer defects for applications in the automotive industries has aroused the interest in rheological high pressure die casting (R-HPDC). A new machine, forced convection mixing (FCM) device, based on the mechanical stirring and convection mixing theory for the preparation of semisolid slurry in convenience and functionality was proposed to produce the automotive shock absorber part by R-HPDC process. The effect of barrel temperature and rotational speed of the device on the grain size and morphology of semi-solid slurry were extensively studied. In addition, flow behavior and temperature field of the melt in the FCM process was investigated combining computational fluid dynamics simulation. The results indicate that the microstructure and pore defects at different locations of R-HPDC casting have been greatly improved. The vigorous fluid convection in FCM process has changed the temperature field and composition distribution of conventional solidification. Appropriately increasing the rotational speed can lead to a uniform temperature filed sooner. The lower barrel temperature leads to a larger uniform degree of supercooling of the melt that benefits the promotion of nucleation rate. Both of them contribute to the decrease of the grain size and the roundness of grain morphology. PMID:28788608

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

Hu, Nantao; Zhang, Liling; Yang, Chao

Thin, robust, lightweight, and flexible supercapacitors (SCs) have aroused growing attentions nowadays due to the rapid development of flexible electronics. Graphene-polyaniline (PANI) hybrids are attractive candidates for high performance SCs. In order to utilize them in real devices, it is necessary to improve the capacitance and the structure stability of PANI. Here we report a hierarchical three-dimensional structure, in which all of PANI nanofibers (NFs) are tightly wrapped inside reduced graphene oxide (rGO) nanosheet skeletons, for high-performance flexible SCs. The as-fabricated film electrodes with this unique structure showed a highest gravimetric specific capacitance of 921 F/g and volumetric capacitance ofmore » 391 F/cm 3. The assembled solid-state SCs gave a high specific capacitance of 211 F/g (1 A/g), a high area capacitance of 0.9 F/cm 2, and a competitive volumetric capacitance of 25.6 F/cm 3. The SCs also exhibited outstanding rate capability (~75% retention at 20 A/g) as well as excellent cycling stability (100% retention at 10 A/g for 2000 cycles). Additionally, no structural failure and loss of performance were observed under the bending state. Lastly, this structure design paves a new avenue for engineering rGO/PANI or other similar hybrids for high performance flexible energy storage devices.« less

Generation of Monoclonal Antibodies against Immunoglobulin Proteins of the Domestic Ferret (Mustela putorius furo)

PubMed Central

2017-01-01

The domestic ferret (Mustela putorius furo) serves as an animal model for the study of several viruses that cause human disease, most notably influenza. Despite the importance of this animal model, characterization of the immune response by flow cytometry (FCM) is severely hampered due to the limited number of commercially available reagents. To begin to address this unmet need and to facilitate more in-depth study of ferret B cells including the identification of antibody-secreting cells, eight unique murine monoclonal antibodies (mAb) with specificity for ferret immunoglobulin (Ig) were generated using conventional B cell hybridoma technology. These mAb were screened for reactivity against ferret peripheral blood mononuclear cells by FCM and demonstrate specificity for CD79β+ B cells. Several of these mAb are specific for the light chain of surface B cell receptor (BCR) and enable segregation of kappa and lambda B cells. Additionally, a mAb that yielded surface staining of nearly all surface BCR positive cells (i.e., pan ferret Ig) was generated. Collectively, these MαF-Ig mAb offer advancement compared to the existing portfolio of polyclonal anti-ferret Ig detection reagents and should be applicable to a wide array of immunologic assays including the identification of antibody-secreting cells by FCM. PMID:28286781

Interphase cytogenetics of prostatic carcinoma in fine needle aspirate smears of radical prostatectomy specimens: A practical screening tool?

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

Wang, R.Y.; Troncoso, P.; El-Naggar, A.K.

1994-09-01

Identification of chromosomal aberrations that may be used for diagnostic or prognostic evaluation of prostatic adenocarcinoma has been the subject of great interest. In a previous study, we applied the fluorescence in situ hybridization (FISH) method on paraffin-embedded material to show that trisomy 7 was associated with the progression of human prostate cancer. In this study, we attempted to assess the utility of the FISH technique in detecting aneuploidy in fine needle aspirate (FNA) smears of prostatic tissues and to compare FISH results with that of DNA flow cytometry (FCM). Paired samples of normal and tumor FNA smears were obtainedmore » from 10 radical prostatectomy specimens. Dual-color chromosomes 7 and 9-specific centromeric DNA probes were used for FISH. FISH analysis demonstrated increased frequencies of trisomy 7 cells in all 10 tumors studied when compared with the paired normals. In contrast, 6 of 10 tumors were determined to be diploid by FCM. Our results show that FNA of radical prostatectomy specimens is a practical method for obtaining suitable material for both FISH and FCM analyses of prostate carcinoma. Thus, interphase FISH may be a practical screening tool to determine aneuploidy in FNA smears of prostatic carcinoma.« less

Three dimensional two-photon brain imaging in freely moving mice using a miniature fiber coupled microscope with active axial-scanning.

PubMed

Ozbay, Baris N; Futia, Gregory L; Ma, Ming; Bright, Victor M; Gopinath, Juliet T; Hughes, Ethan G; Restrepo, Diego; Gibson, Emily A

2018-05-25

We present a miniature head mounted two-photon fiber-coupled microscope (2P-FCM) for neuronal imaging with active axial focusing enabled using a miniature electrowetting lens. We show three-dimensional two-photon imaging of neuronal structure and record neuronal activity from GCaMP6s fluorescence from multiple focal planes in a freely-moving mouse. Two-color simultaneous imaging of GFP and tdTomato fluorescence is also demonstrated. Additionally, dynamic control of the axial scanning of the electrowetting lens allows tilting of the focal plane enabling neurons in multiple depths to be imaged in a single plane. Two-photon imaging allows increased penetration depth in tissue yielding a working distance of 450 μm with an additional 180 μm of active axial focusing. The objective NA is 0.45 with a lateral resolution of 1.8 μm, an axial resolution of 10 μm, and a field-of-view of 240 μm diameter. The 2P-FCM has a weight of only ~2.5 g and is capable of repeatable and stable head-attachment. The 2P-FCM with dynamic axial scanning provides a new capability to record from functionally distinct neuronal layers, opening new opportunities in neuroscience research.

Economic evaluation of the one-hour rule-out and rule-in algorithm for acute myocardial infarction using the high-sensitivity cardiac troponin T assay in the emergency department.

PubMed

Ambavane, Apoorva; Lindahl, Bertil; Giannitsis, Evangelos; Roiz, Julie; Mendivil, Joan; Frankenstein, Lutz; Body, Richard; Christ, Michael; Bingisser, Roland; Alquezar, Aitor; Mueller, Christian

2017-01-01

The 1-hour (h) algorithm triages patients presenting with suspected acute myocardial infarction (AMI) to the emergency department (ED) towards "rule-out," "rule-in," or "observation," depending on baseline and 1-h levels of high-sensitivity cardiac troponin (hs-cTn). The economic consequences of applying the accelerated 1-h algorithm are unknown. We performed a post-hoc economic analysis in a large, diagnostic, multicenter study of hs-cTnT using central adjudication of the final diagnosis by two independent cardiologists. Length of stay (LoS), resource utilization (RU), and predicted diagnostic accuracy of the 1-h algorithm compared to standard of care (SoC) in the ED were estimated. The ED LoS, RU, and accuracy of the 1-h algorithm was compared to that achieved by the SoC at ED discharge. Expert opinion was sought to characterize clinical implementation of the 1-h algorithm, which required blood draws at ED presentation and 1h, after which "rule-in" patients were transferred for coronary angiography, "rule-out" patients underwent outpatient stress testing, and "observation" patients received SoC. Unit costs were for the United Kingdom, Switzerland, and Germany. The sensitivity and specificity for the 1-h algorithm were 87% and 96%, respectively, compared to 69% and 98% for SoC. The mean ED LoS for the 1-h algorithm was 4.3h-it was 6.5h for SoC, which is a reduction of 33%. The 1-h algorithm was associated with reductions in RU, driven largely by the shorter LoS in the ED for patients with a diagnosis other than AMI. The estimated total costs per patient were £2,480 for the 1-h algorithm compared to £4,561 for SoC, a reduction of up to 46%. The analysis shows that the use of 1-h algorithm is associated with reduction in overall AMI diagnostic costs, provided it is carefully implemented in clinical practice. These results need to be prospectively validated in the future.

Isolation and identification of entomopathogenic nematodes from citrus orchards in South Africa and their biocontrol potential against false codling moth.

PubMed

Malan, Antoinette P; Knoetze, Rinus; Moore, Sean D

2011-10-01

A survey was conducted to determine the diversity and frequency of endemic entomopathogenic nematodes (EPN) in citrus orchards in the Western Cape, Eastern Cape and Mpumalanga provinces of South Africa. The main aim of the survey was to obtain nematodes as biological control agents against false codling moth (FCM), Thaumatotibia leucotreta, a key pest of citrus in South Africa. From a total of 202 samples, 35 (17%) tested positive for the presence of EPN. Of these, four isolates (11%) were found to be steinernematids, while 31 (89%) were heterorhabditids. Sequencing and characterisation of the internal transcribed spacer (ITS) region was used to identify all nematode isolates to species level. Morphometrics, morphology and biology of the infective juvenile (IJ) and the first-generation male were used to support molecular identification and characterisation. The Steinernema spp. identified were Steinernema khoisanae, Steinernema yirgalemense and Steinernema citrae. This is the first report of S. yirgalemense in South Africa, while for S. citrae it is the second new steinernematid to be identified from South Africa. Heterorhabditis species identified include Heterorhabditis bacteriophora, Heterorhabditis zealandica and an unknown species of Heterorhabditis. Laboratory bioassays, using 24-well bioassay disks, have shown isolates of all six species found during the survey, to be highly virulent against the last instar of FCM larvae. S. yirgalemense, at a concentration of 50IJs/FCM larva caused 100% mortality and 74% at a concentration of 200IJs/pupa. Using a sand bioassay, S. yirgalemense gave 93% control of cocooned pupae and emerging moths at a concentration of 20IJs/cm(2). This is the first report on the potential use of EPN to control the soil-borne life stages of FCM, which includes larvae, pupae and emerging moths. It was shown that emerging moths were infected with nematodes, which may aid in control and dispersal. Copyright © 2011 Elsevier Inc. All rights reserved.

Nutrient demand interacts with grass maturity to affect milk fat concentration and digestion responses in dairy cows.

PubMed

Kammes, K L; Allen, M S

2012-09-01

Effects of grass maturity on dry matter intake (DMI), milk production, ruminal fermentation and pool sizes, digestion and passage kinetics, and chewing activity and the relationship of these effects with preliminary DMI (pDMI) were evaluated using 13 ruminally and duodenally cannulated Holstein cows in a crossover design with a 14-d preliminary period and two 18-d treatment periods. During the preliminary period, pDMI of individual cows ranged from 23.5 to 28.2 kg/d (mean=26.1 kg/d) and 3.5% fat-corrected milk (FCM) yield ranged from 30.8 to 57.2 kg/d (mean=43.7 kg/d). Experimental treatments were diets containing orchardgrass silage harvested either (1) early-cut, less mature (EC) or (2) late-cut, more mature (LC) as the sole forage. Early- and late-cut orchardgrass contained 44.9 and 54.4% neutral detergent fiber (NDF) and 20.1 and 15.3% crude protein, respectively. Forage:concentrate ratio was 58:42 and 46:54 for EC and LC, respectively; both diets contained approximately 25% forage NDF and 30% total NDF. Preliminary DMI, an index of nutrient demand, was determined during the last 4d of the preliminary period when cows were fed a common diet and used as a covariate. Main effects of grass maturity and their interaction with pDMI were tested by ANOVA. The EC diet decreased milk yield and increased milk fat concentration compared with the LC diet. Grass maturity and its interaction with pDMI did not affect FCM yield, DMI, rumen pH, or microbial efficiency. The EC diet increased rates of ruminal digestion of potentially digestible NDF and passage of indigestible NDF (iNDF) compared with the LC diet. The lower concentration and faster passage rate of iNDF for EC resulted in lower rumen pools of iNDF, total NDF, organic matter, and dry matter for EC than LC. Ruminal passage rates of potentially digestible NDF and starch were related to level of intake (quadratic and linear interactions, respectively) and subsequently affected ruminal digestibility of these nutrients. The EC diet decreased eating, ruminating, and total chewing time per unit of forage NDF intake compared with the LC diet. When grass silage was the only source of forage in the diet, cows supplemented with additional concentrate to account for decreasing protein and increasing fiber concentrations associated with more mature grass had similar feed intake and produced similar FCM yields as cows fed less mature grass. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Towards the harmonization between National Forest Inventory and Forest Condition Monitoring. Consistency of plot allocation and effect of tree selection methods on sample statistics in Italy.

PubMed

Gasparini, Patrizia; Di Cosmo, Lucio; Cenni, Enrico; Pompei, Enrico; Ferretti, Marco

2013-07-01

In the frame of a process aiming at harmonizing National Forest Inventory (NFI) and ICP Forests Level I Forest Condition Monitoring (FCM) in Italy, we investigated (a) the long-term consistency between FCM sample points (a subsample of the first NFI, 1985, NFI_1) and recent forest area estimates (after the second NFI, 2005, NFI_2) and (b) the effect of tree selection method (tree-based or plot-based) on sample composition and defoliation statistics. The two investigations were carried out on 261 and 252 FCM sites, respectively. Results show that some individual forest categories (larch and stone pine, Norway spruce, other coniferous, beech, temperate oaks and cork oak forests) are over-represented and others (hornbeam and hophornbeam, other deciduous broadleaved and holm oak forests) are under-represented in the FCM sample. This is probably due to a change in forest cover, which has increased by 1,559,200 ha from 1985 to 2005. In case of shift from a tree-based to a plot-based selection method, 3,130 (46.7%) of the original 6,703 sample trees will be abandoned, and 1,473 new trees will be selected. The balance between exclusion of former sample trees and inclusion of new ones will be particularly unfavourable for conifers (with only 16.4% of excluded trees replaced by new ones) and less for deciduous broadleaves (with 63.5% of excluded trees replaced). The total number of tree species surveyed will not be impacted, while the number of trees per species will, and the resulting (plot-based) sample composition will have a much larger frequency of deciduous broadleaved trees. The newly selected trees have-in general-smaller diameter at breast height (DBH) and defoliation scores. Given the larger rate of turnover, the deciduous broadleaved part of the sample will be more impacted. Our results suggest that both a revision of FCM network to account for forest area change and a plot-based approach to permit statistical inference and avoid bias in the tree sample composition in terms of DBH (and likely age and structure) are desirable in Italy. As the adoption of a plot-based approach will keep a large share of the trees formerly selected, direct tree-by-tree comparison will remain possible, thus limiting the impact on the time series comparability. In addition, the plot-based design will favour the integration with NFI_2.

Determining the Number of Clusters in a Data Set Without Graphical Interpretation

NASA Technical Reports Server (NTRS)

Aguirre, Nathan S.; Davies, Misty D.

2011-01-01

Cluster analysis is a data mining technique that is meant ot simplify the process of classifying data points. The basic clustering process requires an input of data points and the number of clusters wanted. The clustering algorithm will then pick starting C points for the clusters, which can be either random spatial points or random data points. It then assigns each data point to the nearest C point where "nearest usually means Euclidean distance, but some algorithms use another criterion. The next step is determining whether the clustering arrangement this found is within a certain tolerance. If it falls within this tolerance, the process ends. Otherwise the C points are adjusted based on how many data points are in each cluster, and the steps repeat until the algorithm converges,

Synthesis and electrochemical performance of Ti3C2Tx with hydrothermal process

NASA Astrophysics Data System (ADS)

Wang, Libo; Zhang, Heng; Wang, Bo; Shen, Changjie; Zhang, Chuanxiang; Hu, Qianku; Zhou, Aiguo; Liu, Baozhong

2016-09-01

In this study, a simple hydrothermal method has been developed to prepare Ti3C2Tx from Ti3AlC2 as a high-performance electrode material for supercapacitors. This method is environmentally friendly and has a low level of danger. The morphology and structure of the Ti3C2Tx can be controlled by hydrothermal reaction time, temperature and NH4F amounts. The prepared Ti3C2Tx was characterized by X-ray diffraction, field emission scanning electron microscopy, Raman spectroscopy, X-ray photoelectron spectroscopy and Brunauer-Emmet-Teller. The results show that the prepared Ti3C2Tx is terminated by O, OH, and F groups. The electrochemical properties of the Ti3C2Tx sample exhibit specific capacitance up to 141 Fcm-3 in 3 M KOH aqueous electrolyte, and even after 1000 cycles, no significant degradation of the volumetric capacitance was observed. These results indicate that the Ti3C2Tx material prepared by this hydrothermal method can be used in high performance supercapacitors.

Generalized Split-Window Algorithm for Estimate of Land Surface Temperature from Chinese Geostationary FengYun Meteorological Satellite (FY-2C) Data

PubMed Central

Tang, Bohui; Bi, Yuyun; Li, Zhao-Liang; Xia, Jun

2008-01-01

On the basis of the radiative transfer theory, this paper addressed the estimate of Land Surface Temperature (LST) from the Chinese first operational geostationary meteorological satellite-FengYun-2C (FY-2C) data in two thermal infrared channels (IR1, 10.3-11.3 μm and IR2, 11.5-12.5 μm), using the Generalized Split-Window (GSW) algorithm proposed by Wan and Dozier (1996). The coefficients in the GSW algorithm corresponding to a series of overlapping ranging of the mean emissivity, the atmospheric Water Vapor Content (WVC), and the LST were derived using a statistical regression method from the numerical values simulated with an accurate atmospheric radiative transfer model MODTRAN 4 over a wide range of atmospheric and surface conditions. The simulation analysis showed that the LST could be estimated by the GSW algorithm with the Root Mean Square Error (RMSE) less than 1 K for the sub-ranges with the Viewing Zenith Angle (VZA) less than 30° or for the sub-rangs with VZA less than 60° and the atmospheric WVC less than 3.5 g/cm2 provided that the Land Surface Emissivities (LSEs) are known. In order to determine the range for the optimum coefficients of the GSW algorithm, the LSEs could be derived from the data in MODIS channels 31 and 32 provided by MODIS/Terra LST product MOD11B1, or be estimated either according to the land surface classification or using the method proposed by Jiang et al. (2006); and the WVC could be obtained from MODIS total precipitable water product MOD05, or be retrieved using Li et al.' method (2003). The sensitivity and error analyses in term of the uncertainty of the LSE and WVC as well as the instrumental noise were performed. In addition, in order to compare the different formulations of the split-window algorithms, several recently proposed split-window algorithms were used to estimate the LST with the same simulated FY-2C data. The result of the intercomparsion showed that most of the algorithms give comparable results. PMID:27879744

Study of Early Transition Metal Carbides for Energy Storage Applications

NASA Astrophysics Data System (ADS)

Dall'Agnese, Yohan

An increase in energy and power density is needed to match the growing energy storage demands linked with the development of renewable energy production, and portable electronics. Several energy storage technologies exist including lithium-ion batteries, sodium-ion batteries, fuel cells and supercapacitors. These systems are mutually complementary. For example, supercapacitors can deliver high power densities whereas batteries can be used for high energy density applications. The first objective of this work was to investigate the electrochemical performances of a new family of 2-D materials called MXenes by cyclic voltammetry and galvanostatic charge-discharge measurements and to propose new solutions to tackle the energy storage concern. To achieve this goal, several directions have been explored. The first part of the research focused on Ti3C 2-based MXenes behavior as electrode materials for supercapacitors in aqueous electrolytes. The charge storage mechanisms in basic and neutral aqueous electrolytes, investigated by X-ray diffraction, were demonstrated to be attributed to cations intercalation between Ti3C2 layers. X-ray photoelectron spectroscopy highlighted the contribution of oxygenated functional groups on surface redox reactions in sulfuric acid. High capacitances were achieved, up to 520 F/cm3 and 325 F/g. Then the electrochemical behaviors of MXenes in sodium-based organic electrolytes were explored. A new hybrid system of sodium-ion capacitor was proposed. It was demonstrated that V2C-based MXene electrodes were suitable to be used as positive electrodes with an operating potential from 1 V to 3.5 V vs. Na+/Na. Continuous intercalation and de-intercalation of sodium ions between the V2C layers during sodiation and desodiation were showed by X-ray diffraction. An asymmetric sodium-ion capacitor full cell was assembled using hard carbon as negative electrode and showed promising results, with a capacity of 50 mAh/g. The last part was focused on the study of MXene electrodes for supercapacitors in an organic electrolyte; 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (EMITFSI) in acetonitrile. High volumetric capacitances, up to 245 F/cm 3, were achieved by using carbon nanotubes as an additive to improve ion accessibility to Ti3C2 layers. The redox intercalation of large EMI+ cations between Ti3C2 layers at -0.4 V vs. Ag was observed by X-ray diffraction.

Visual selection and maintenance of the cell lines with high plant regeneration ability and low ploidy level in Dianthus acicularis by monitoring with flow cytometry analysis.

PubMed

Shiba, Tomonori; Mii, Masahiro

2005-12-01

Efficient plant regeneration system from cell suspension cultures was established in D. acicularis (2n=90) by monitoring ploidy level and visual selection of the cultures. The ploidy level of the cell cultures closely related to the shoot regeneration ability. The cell lines comprising original ploidy levels (2C+4C cells corresponding to DNA contents of G1 and G2 cells of diploid plant, respectively) showed high regeneration ability, whereas those containing the cells with 8C or higher DNA C-values showed low or no regeneration ability. The highly regenerable cell lines thus selected consisted of compact cell clumps with yellowish color and relatively moderate growth, suggesting that it is possible to select visually the highly regenerable cell lines with the original ploidy level. All the regenerated plantlets from the highly regenerable cell cultures exhibited normal phenotypes and no variations in ploidy level were observed by flow cytometry (FCM) analysis.

Design and Synthesis of 3D Potassium-Ion Pre-Intercalated Graphene for Supercapacitors

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

Chang, Liang; Stacchiola, Dario J.; Hu, Yun Hang

Here in this paper, a novel material—3D potassium-ion preintercalated graphene—was designed and synthesized via one step using a new reaction between K and CO. Furthermore, this material exhibited excellent performance as electrodes for aqueous symmetrical supercapacitors. When the electrode was scaled up from 3.0 to 8.0 mg/cm 2, negligible capacitance degradation was observed, leading to a very high areal capacitance of 1.50 F/cm 2 at 1 A/g. Furthermore, even if a large operating temperature of -15 or 55 °C was employed, its excellent electrochemical performance remained with specific capacitances of 208 F/g at 55 °C, 184 F/g at 25 °C,more » and 98 F/g at -15 °C. This could be attributed to 3D structure and K+ preintercalation of the material, which provides rich active sites for electric double-layer formation, lower ion transport resistance, and shorter diffusion distance.« less

Design and Synthesis of 3D Potassium-Ion Pre-Intercalated Graphene for Supercapacitors

DOE PAGES

Chang, Liang; Stacchiola, Dario J.; Hu, Yun Hang

2018-02-22

Here in this paper, a novel material—3D potassium-ion preintercalated graphene—was designed and synthesized via one step using a new reaction between K and CO. Furthermore, this material exhibited excellent performance as electrodes for aqueous symmetrical supercapacitors. When the electrode was scaled up from 3.0 to 8.0 mg/cm 2, negligible capacitance degradation was observed, leading to a very high areal capacitance of 1.50 F/cm 2 at 1 A/g. Furthermore, even if a large operating temperature of -15 or 55 °C was employed, its excellent electrochemical performance remained with specific capacitances of 208 F/g at 55 °C, 184 F/g at 25 °C,more » and 98 F/g at -15 °C. This could be attributed to 3D structure and K+ preintercalation of the material, which provides rich active sites for electric double-layer formation, lower ion transport resistance, and shorter diffusion distance.« less

Three-dimensional skeleton networks of graphene wrapped polyaniline nanofibers: an excellent structure for high-performance flexible solid-state supercapacitors

PubMed Central

Hu, Nantao; Zhang, Liling; Yang, Chao; Zhao, Jian; Yang, Zhi; Wei, Hao; Liao, Hanbin; Feng, Zhenxing; Fisher, Adrian; Zhang, Yafei; Xu, Zhichuan J.

2016-01-01

Thin, robust, lightweight, and flexible supercapacitors (SCs) have aroused growing attentions nowadays due to the rapid development of flexible electronics. Graphene-polyaniline (PANI) hybrids are attractive candidates for high performance SCs. In order to utilize them in real devices, it is necessary to improve the capacitance and the structure stability of PANI. Here we report a hierarchical three-dimensional structure, in which all of PANI nanofibers (NFs) are tightly wrapped inside reduced graphene oxide (rGO) nanosheet skeletons, for high-performance flexible SCs. The as-fabricated film electrodes with this unique structure showed a highest gravimetric specific capacitance of 921 F/g and volumetric capacitance of 391 F/cm3. The assembled solid-state SCs gave a high specific capacitance of 211 F/g (1 A/g), a high area capacitance of 0.9 F/cm2, and a competitive volumetric capacitance of 25.6 F/cm3. The SCs also exhibited outstanding rate capability (~75% retention at 20 A/g) as well as excellent cycling stability (100% retention at 10 A/g for 2000 cycles). Additionally, no structural failure and loss of performance were observed under the bending state. This structure design paves a new avenue for engineering rGO/PANI or other similar hybrids for high performance flexible energy storage devices. PMID:26795067

Screening of carcinoma metastasis by flow cytometry: A study of 238 cases.

PubMed

Acosta, Maria; Pereira, José; Arroz, Maria

2016-05-01

Malignant epithelial cells may be detected in different specimens, by immunophenotyping using flow cytometry (FCM). CD326 (epithelial-specific antigen, clone Ber-Ep4) was used to identify epithelial cells, CD45 to discriminate between leucocytes (positive for this antigen) and non-hematological cells (negative for this antigen), and CD33 to identify monocytes/macrophages. This combination is particularly useful in effusions to characterize large cells and distinguish between monocyte/macrophages (CD45+ CD33+ CD326-), mesothelial cells (CD45 ± (dim) CD33 - CD326-) and epithelial cells (CD45 - CD33 - CD326 +). We evaluated the efficiency of flow cytometry to detect malignant epithelial cells in 238 fresh samples, including effusions, lymph node biopsies, fine needle aspirates, bone marrow aspirates, cerebrospinal fluid, among others. These are specimens expected to lack epithelial cells. FCM results were then compared to the results of smear and cell block morphology, as well as immunocytochemistry on paraffin wax embedded cell blocks, when available. Final diagnosis was the gold standard and a very good sensitivity (96.7%) and specificity (99.3%) were obtained. We concluded that the detection of CD326 positive cells using FCM is strongly indicative of the presence of carcinoma cells. © 2015 International Clinical Cytometry Society. © 2015 International Clinical Cytometry Society.

Multi-parameter flow cytometry as a process analytical technology (PAT) approach for the assessment of bacterial ghost production.

PubMed

Langemann, Timo; Mayr, Ulrike Beate; Meitz, Andrea; Lubitz, Werner; Herwig, Christoph

2016-01-01

Flow cytometry (FCM) is a tool for the analysis of single-cell properties in a cell suspension. In this contribution, we present an improved FCM method for the assessment of E-lysis in Enterobacteriaceae. The result of the E-lysis process is empty bacterial envelopes-called bacterial ghosts (BGs)-that constitute potential products in the pharmaceutical field. BGs have reduced light scattering properties when compared with intact cells. In combination with viability information obtained from staining samples with the membrane potential-sensitive fluorescent dye bis-(1,3-dibutylarbituric acid) trimethine oxonol (DiBAC4(3)), the presented method allows to differentiate between populations of viable cells, dead cells, and BGs. Using a second fluorescent dye RH414 as a membrane marker, non-cellular background was excluded from the data which greatly improved the quality of the results. Using true volumetric absolute counting, the FCM data correlated well with cell count data obtained from colony-forming units (CFU) for viable populations. Applicability of the method to several Enterobacteriaceae (different Escherichia coli strains, Salmonella typhimurium, Shigella flexneri 2a) could be shown. The method was validated as a resilient process analytical technology (PAT) tool for the assessment of E-lysis and for particle counting during 20-l batch processes for the production of Escherichia coli Nissle 1917 BGs.

Three-dimensional skeleton networks of graphene wrapped polyaniline nanofibers: An excellent structure for high-performance flexible solid-state supercapacitors

DOE PAGES

Hu, Nantao; Zhang, Liling; Yang, Chao; ...

2016-01-22

Thin, robust, lightweight, and flexible supercapacitors (SCs) have aroused growing attentions nowadays due to the rapid development of flexible electronics. Graphene-polyaniline (PANI) hybrids are attractive candidates for high performance SCs. In order to utilize them in real devices, it is necessary to improve the capacitance and the structure stability of PANI. Here we report a hierarchical three-dimensional structure, in which all of PANI nanofibers (NFs) are tightly wrapped inside reduced graphene oxide (rGO) nanosheet skeletons, for high-performance flexible SCs. The as-fabricated film electrodes with this unique structure showed a highest gravimetric specific capacitance of 921 F/g and volumetric capacitance ofmore » 391 F/cm 3. The assembled solid-state SCs gave a high specific capacitance of 211 F/g (1 A/g), a high area capacitance of 0.9 F/cm 2, and a competitive volumetric capacitance of 25.6 F/cm 3. The SCs also exhibited outstanding rate capability (~75% retention at 20 A/g) as well as excellent cycling stability (100% retention at 10 A/g for 2000 cycles). Additionally, no structural failure and loss of performance were observed under the bending state. Lastly, this structure design paves a new avenue for engineering rGO/PANI or other similar hybrids for high performance flexible energy storage devices.« less

A diabetic retinopathy detection method using an improved pillar K-means algorithm.

PubMed

Gogula, Susmitha Valli; Divakar, Ch; Satyanarayana, Ch; Rao, Allam Appa

2014-01-01

The paper presents a new approach for medical image segmentation. Exudates are a visible sign of diabetic retinopathy that is the major reason of vision loss in patients with diabetes. If the exudates extend into the macular area, blindness may occur. Automated detection of exudates will assist ophthalmologists in early diagnosis. This segmentation process includes a new mechanism for clustering the elements of high-resolution images in order to improve precision and reduce computation time. The system applies K-means clustering to the image segmentation after getting optimized by Pillar algorithm; pillars are constructed in such a way that they can withstand the pressure. Improved pillar algorithm can optimize the K-means clustering for image segmentation in aspects of precision and computation time. This evaluates the proposed approach for image segmentation by comparing with Kmeans and Fuzzy C-means in a medical image. Using this method, identification of dark spot in the retina becomes easier and the proposed algorithm is applied on diabetic retinal images of all stages to identify hard and soft exudates, where the existing pillar K-means is more appropriate for brain MRI images. This proposed system help the doctors to identify the problem in the early stage and can suggest a better drug for preventing further retinal damage.

Effects of siRNA-mediated knockdown of jumonji domain containing 2A on proliferation, migration and invasion of the human breast cancer cell line MCF-7

PubMed Central

LI, BEI-XU; LUO, CHENG-LIANG; LI, HUI; YANG, PENG; ZHANG, MING-CHANG; XU, HONG-MEI; XU, HONG-FEI; SHEN, YI-WEN; XUE, AI-MIN; ZHAO, ZI-QIN

2012-01-01

Jumonji domain containing 2A (JMJD2A) is a potential cancer-associated gene that may be involved in human breast cancer. The present study aimed to investigate suppressive effects on the MCF-7 human breast cancer cell line by transfection with JMJD2A-specific siRNA. Quantitative real-time PCR and western blot analysis were used to detect the expression levels of JMJD2A. Flow cytometric (FCM) analysis and WST-8 assay were used to evaluate cell proliferation. Boyden chambers were used in cell migration and invasion assays to evaluate the cell exercise capacity. Expression levels of JMJD2A mRNA and protein in the siRNA group were both downregulated successfully by transfection. FCM results showed that the percentage of cells in the G0/G1 phase in the siRNA group was significantly greater than that in the blank (P<0.05) and negative control groups (P<0.05). Additionally, the mean absorbance in the siRNA group was significantly lower (P<0.05), as observed by WST-8 assay. Moreover, a decreased number of migrated cells in the siRNA group was observed (P<0.05) using a cell migration and invasion assay. These data indicated that knockdown of JMJD2A may cause inhibition of proliferation, migration and invasion of MCF-7 cells. This study provides a new perspective in understanding the molecular mechanisms underlying the progression of breast cancer and offers a potential therapeutic target for breast cancer. PMID:23170139

Vaccination against GnRH may suppress aggressive behaviour and musth in African elephant (Loxodonta africana) bulls--a pilot study.

PubMed

De Nys, H M; Bertschinger, H J; Turkstra, J A; Colenbrander, B; Palme, R; Human, A M

2010-03-01

Aggressive behaviour and musth are constant problems in captive and sometimes in free-ranging African elephant bulls. Aggressive bulls are difficult and musth bulls almost impossible to manage without severely restricting their movement either by leg-chaining or using tranquillisers. This study investigated the relationship between faecal androgen metabolites (FAM) and faecal cortisol metabolites (FCM) concentrations and aggressive behaviour and tested a GnRH vaccine as a means of down-regulating aggressive behaviour and musth in 1 free-ranging and 5 captive elephant bulls. The bulls were non-aggressive (n=3), aggressive (n=2) or in musth (n=1) at the onset of the study. The bulls were injected with a GnRH vaccine-adjuvant combination 3 or 4 times at 3- to 7-week intervals. Behaviour, FAM and FCM concentrations were measured during every week prior to vaccination until 4 months after the last vaccination. FAM concentrations were positively correlated with aggressive behaviour before the 1st vaccination. Androgen production, as reflected by FAM concentrations, was down-regulated in 3 of the 6 immunised bulls. At least 2 bulls and possibly a 3rd showed behavioural improvement following GnRH vaccination and in all 3 temporal gland secretion ceased. No further aggressive behaviour was observed until the end of the study in any of the bulls. The results of this 1st GnRH immunisation study suggest that it could be a useful method to control aggressive behaviour and musth in African elephant bulls.

Chromosomal aberrations and aneuploidy in oral potentially malignant lesions: distinctive features for tongue

PubMed Central

2011-01-01

Background The mucosae of the oral cavity are different at the histological level but appear all equally exposed to common genotoxic agents. As a result of this exposure, changes in the mucosal epithelia may develop giving rise to Oral Potentially Malignant Lesions (OPMLs), which with time may in turn progress to Oral Squamous Cell Carcinomas (OSCCs). Therefore, much effort should be devoted to identify features able to predict the likeliness of progression associated with an OPML. Such features may be helpful in assisting the clinician to establish both appropriate therapies and follow-up schedules. Here, we report a pilot study that compared the occurrence of DNA aneuploidy and chromosomal copy number aberrations (CNAs) in the OPMLs from different oral anatomical subsites. Methods Samples from histologically diagnosed OPMLs were processed for high resolution DNA flow cytometry (hr DNA-FCM) in order to determine the relative DNA content expressed by the DNA index (DI). Additionally, array-Comparative Genomic Hybridization (a-CGH) analysis was performed on DNA obtained from diploid nuclei suspensions directly. When aneuploid nuclei were detected, these were physically separated from diploid nuclei on the base of their DI values by means of a DNA-FCM-Sorter in order to improve the a-CGH analysis. Results Tongue OPMLs were more frequently associated with DNA aneuploidy and CNAs than OPMLs arising from all the other mucosal subsites. Conclusions We suggest that the follow-up and the management of the patients with tongue OPMLs should receive a distinctive special attention. Clearly, this hypothesis should be validated in a prospective clinical study. PMID:21995418

The global Minmax k-means algorithm.

PubMed

Wang, Xiaoyan; Bai, Yanping

2016-01-01

The global k -means algorithm is an incremental approach to clustering that dynamically adds one cluster center at a time through a deterministic global search procedure from suitable initial positions, and employs k -means to minimize the sum of the intra-cluster variances. However the global k -means algorithm sometimes results singleton clusters and the initial positions sometimes are bad, after a bad initialization, poor local optimal can be easily obtained by k -means algorithm. In this paper, we modified the global k -means algorithm to eliminate the singleton clusters at first, and then we apply MinMax k -means clustering error method to global k -means algorithm to overcome the effect of bad initialization, proposed the global Minmax k -means algorithm. The proposed clustering method is tested on some popular data sets and compared to the k -means algorithm, the global k -means algorithm and the MinMax k -means algorithm. The experiment results show our proposed algorithm outperforms other algorithms mentioned in the paper.

A model of large volumetric capacitance in graphene supercapacitors based on ion clustering

NASA Astrophysics Data System (ADS)

Skinner, Brian; Fogler, Michael; Shklovskii, Boris

2012-02-01

Electric double layer supercapacitors are promising devices for high-power energy storage based on the reversible absorption of ions into porous, conducting electrodes. Graphene is a particularly good candidate for the electrode material in supercapacitors due to its high conductivity and large surface area. In this paper we consider supercapacitor electrodes made from a stack of graphene sheets with randomly-inserted ``spacer" molecules. We show that the large volumetric capacitances C > 100 F/cm^3 observed experimentally can be understood as a result of collective intercalation of ions into the graphene stack and the accompanying nonlinear screening by graphene electrons that renormalizes the charge of the ion clusters.

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

Jolly, Brian C.; Lindemer, Terrence; Terrani, Kurt A.

In support of fully ceramic matrix (FCM) fuel development, coating development work has begun at the Oak Ridge National Laboratory (ORNL) to produce tri-isotropic (TRISO) coated fuel particles with UN kernels. The nitride kernels are used to increase heavy metal density in these SiC-matrix fuel pellets with details described elsewhere. The advanced gas reactor (AGR) program at ORNL used fluidized bed chemical vapor deposition (FBCVD) techniques for TRISO coating of UCO (two phase mixture of UO 2 and UC x) kernels. Similar techniques were employed for coating of the UN kernels, however significant changes in processing conditions were required tomore » maintain acceptable coating properties due to physical property and dimensional differences between the UCO and UN kernels.« less

Computer program documentation: ISOCLS iterative self-organizing clustering program, program C094

NASA Technical Reports Server (NTRS)

Minter, R. T. (Principal Investigator)

1972-01-01

The author has identified the following significant results. This program implements an algorithm which, ideally, sorts a given set of multivariate data points into similar groups or clusters. The program is intended for use in the evaluation of multispectral scanner data; however, the algorithm could be used for other data types as well. The user may specify a set of initial estimated cluster means to begin the procedure, or he may begin with the assumption that all the data belongs to one cluster. The procedure is initiatized by assigning each data point to the nearest (in absolute distance) cluster mean. If no initial cluster means were input, all of the data is assigned to cluster 1. The means and standard deviations are calculated for each cluster.

Deconvoluting simulated metagenomes: the performance of hard- and soft- clustering algorithms applied to metagenomic chromosome conformation capture (3C)

PubMed Central

DeMaere, Matthew Z.

2016-01-01

Background Chromosome conformation capture, coupled with high throughput DNA sequencing in protocols like Hi-C and 3C-seq, has been proposed as a viable means of generating data to resolve the genomes of microorganisms living in naturally occuring environments. Metagenomic Hi-C and 3C-seq datasets have begun to emerge, but the feasibility of resolving genomes when closely related organisms (strain-level diversity) are present in the sample has not yet been systematically characterised. Methods We developed a computational simulation pipeline for metagenomic 3C and Hi-C sequencing to evaluate the accuracy of genomic reconstructions at, above, and below an operationally defined species boundary. We simulated datasets and measured accuracy over a wide range of parameters. Five clustering algorithms were evaluated (2 hard, 3 soft) using an adaptation of the extended B-cubed validation measure. Results When all genomes in a sample are below 95% sequence identity, all of the tested clustering algorithms performed well. When sequence data contains genomes above 95% identity (our operational definition of strain-level diversity), a naive soft-clustering extension of the Louvain method achieves the highest performance. Discussion Previously, only hard-clustering algorithms have been applied to metagenomic 3C and Hi-C data, yet none of these perform well when strain-level diversity exists in a metagenomic sample. Our simple extension of the Louvain method performed the best in these scenarios, however, accuracy remained well below the levels observed for samples without strain-level diversity. Strain resolution is also highly dependent on the amount of available 3C sequence data, suggesting that depth of sequencing must be carefully considered during experimental design. Finally, there appears to be great scope to improve the accuracy of strain resolution through further algorithm development. PMID:27843713

Self-assembled Ti3C2Tx/SCNT composite electrode with improved electrochemical performance for supercapacitor.

PubMed

Fu, Qishan; Wang, Xinyu; Zhang, Na; Wen, Jing; Li, Lu; Gao, Hong; Zhang, Xitian

2018-02-01

Two-dimensional titanium carbide has gained considerable attention in recent years as an electrode material for supercapacitors due to its high melting point, good electrical conductivity, hydrophilicity and large electrochemically active surfaces. However, the irreversible restacking during synthesis restricts its development and practical applications. Here, Ti 3 C 2 T x /SCNT self-assembled composite electrodes were rationally designed and successfully synthesized by introducing single-walled carbon nanotubes (SCNTs) as interlayer spacers to decrease the restacking of the Ti 3 C 2 T x sheets during the synthesis process. SCNTs can not only increase the specific surface area as well as the interlayer space of the Ti 3 C 2 T x electrode, but also increase the accessible capability of electrolyte ions, and thus it improved the electrochemical performance of the electrode. The as-prepared Ti 3 C 2 T x /SCNT self-assembled composite electrode achieved a high areal capacitance of 220mF/cm 2 (314F/cm 3 ) and a remarkable capacitance retention of 95% after 10,000cycles. Copyright © 2017 Elsevier Inc. All rights reserved.

CURE-SMOTE algorithm and hybrid algorithm for feature selection and parameter optimization based on random forests.

PubMed

Ma, Li; Fan, Suohai

2017-03-14

The random forests algorithm is a type of classifier with prominent universality, a wide application range, and robustness for avoiding overfitting. But there are still some drawbacks to random forests. Therefore, to improve the performance of random forests, this paper seeks to improve imbalanced data processing, feature selection and parameter optimization. We propose the CURE-SMOTE algorithm for the imbalanced data classification problem. Experiments on imbalanced UCI data reveal that the combination of Clustering Using Representatives (CURE) enhances the original synthetic minority oversampling technique (SMOTE) algorithms effectively compared with the classification results on the original data using random sampling, Borderline-SMOTE1, safe-level SMOTE, C-SMOTE, and k-means-SMOTE. Additionally, the hybrid RF (random forests) algorithm has been proposed for feature selection and parameter optimization, which uses the minimum out of bag (OOB) data error as its objective function. Simulation results on binary and higher-dimensional data indicate that the proposed hybrid RF algorithms, hybrid genetic-random forests algorithm, hybrid particle swarm-random forests algorithm and hybrid fish swarm-random forests algorithm can achieve the minimum OOB error and show the best generalization ability. The training set produced from the proposed CURE-SMOTE algorithm is closer to the original data distribution because it contains minimal noise. Thus, better classification results are produced from this feasible and effective algorithm. Moreover, the hybrid algorithm's F-value, G-mean, AUC and OOB scores demonstrate that they surpass the performance of the original RF algorithm. Hence, this hybrid algorithm provides a new way to perform feature selection and parameter optimization.

Comparison among Reconstruction Algorithms for Quantitative Analysis of 11C-Acetate Cardiac PET Imaging.

PubMed

Shi, Ximin; Li, Nan; Ding, Haiyan; Dang, Yonghong; Hu, Guilan; Liu, Shuai; Cui, Jie; Zhang, Yue; Li, Fang; Zhang, Hui; Huo, Li

2018-01-01

Kinetic modeling of dynamic 11 C-acetate PET imaging provides quantitative information for myocardium assessment. The quality and quantitation of PET images are known to be dependent on PET reconstruction methods. This study aims to investigate the impacts of reconstruction algorithms on the quantitative analysis of dynamic 11 C-acetate cardiac PET imaging. Suspected alcoholic cardiomyopathy patients ( N = 24) underwent 11 C-acetate dynamic PET imaging after low dose CT scan. PET images were reconstructed using four algorithms: filtered backprojection (FBP), ordered subsets expectation maximization (OSEM), OSEM with time-of-flight (TOF), and OSEM with both time-of-flight and point-spread-function (TPSF). Standardized uptake values (SUVs) at different time points were compared among images reconstructed using the four algorithms. Time-activity curves (TACs) in myocardium and blood pools of ventricles were generated from the dynamic image series. Kinetic parameters K 1 and k 2 were derived using a 1-tissue-compartment model for kinetic modeling of cardiac flow from 11 C-acetate PET images. Significant image quality improvement was found in the images reconstructed using iterative OSEM-type algorithms (OSME, TOF, and TPSF) compared with FBP. However, no statistical differences in SUVs were observed among the four reconstruction methods at the selected time points. Kinetic parameters K 1 and k 2 also exhibited no statistical difference among the four reconstruction algorithms in terms of mean value and standard deviation. However, for the correlation analysis, OSEM reconstruction presented relatively higher residual in correlation with FBP reconstruction compared with TOF and TPSF reconstruction, and TOF and TPSF reconstruction were highly correlated with each other. All the tested reconstruction algorithms performed similarly for quantitative analysis of 11 C-acetate cardiac PET imaging. TOF and TPSF yielded highly consistent kinetic parameter results with superior image quality compared with FBP. OSEM was relatively less reliable. Both TOF and TPSF were recommended for cardiac 11 C-acetate kinetic analysis.

Adenovirus expressing IFN-λ (Ad/hIFN-λ) produced anti-tumor effects through inducing apoptosis in human tongue squamous cell carcinoma cell.

PubMed

Song, Bing; Yang, Yong; Wang, Yan-Li; Fan, Xiao-Hui; Huang, Yu-Mei; Ci, Hao-Su; Zuo, Jin-Hua

2015-01-01

To investigate the potential therapeutic effects of adenovirus expressing IFN-λ1 and IFN-λ2 (Ad/hIFN-λ) in treating squamous cell carcinoma of the oral tongue (SCCOT) and to explore the underlying mechanisms. Two SCCOT cell lines HSC-3 and Tca8113 were adopted as study objects. Cell Counting Kit-8 (CCK-8) cell proliferation and viability assay was performed to evaluate the antiproliferative effects of Ad/hIFN-λ and IFN-λ treatments at different dosages. Flow cytometry (FCM) was performed to investigate the apoptosis rate induced by Ad/hIFN-λ. In vivo study was performed through evaluating tumorigenicity and tumor volume on BALB/c nu/nu mice inoculated with HSC-3 cells with or without infection of Ad/hIFN-λ. qPCR was used to screen important apoptosis related genes expression and western blot (WB) was performed to verify the results. WB was also used to test the phosphorylation of STATs protein in the JAK/STAT signaling pathways. Our results indicated an obvious antiproliferative effect of Ad/hIFN-λ in vitro on infected HSC-3 and Tca8113 cells. The antiproliferative effects started to appear at 48 h (day 2) after infection. IFN-λs alone treating HSC-3 and Tca8113 cells also showed a dose-dependent inhibitory manner. Though the antiproliferative effects did not show on 24 h (day 1), early apoptosis rate already increased significantly in cells infected with Ad/hIFN-λ (P<0.05) detected by FCM. The underlying mechanisms of antiproliferative activity rely on the IFN-λ signaling by phosphorylation of STATs protein. Expression of Bax, Bcl-2 and Caspase-3 were promoted by Ad/hIFN-λ leading to higher apoptosis rate. Upper stream of p21 and Rb dephosphorylation explained the Caspase-3 activation. Animal study showed that HSC-3 cells infected with Ad/hIFN-λ significantly promoted the survival rate and decreased mean tumor volume comparing to HSC-3 cells group. Ad/hIFN-λ injection had obvious antiproliferative effects on HSC-3 and Tca8113 cells. Ad/hIFN-λ induced apoptosis in SCCOT cells through increasing Bcl-2, Bax and Caspase-3 expression. Ad/hIFN-λ is a potential therapeutic strategy in treating oral tongue carcinoma.

Optical Coherence Tomography (OCT) Device Independent Intraretinal Layer Segmentation

PubMed Central

Ehnes, Alexander; Wenner, Yaroslava; Friedburg, Christoph; Preising, Markus N.; Bowl, Wadim; Sekundo, Walter; zu Bexten, Erdmuthe Meyer; Stieger, Knut; Lorenz, Birgit

2014-01-01

Purpose To develop and test an algorithm to segment intraretinal layers irrespectively of the actual Optical Coherence Tomography (OCT) device used. Methods The developed algorithm is based on the graph theory optimization. The algorithm's performance was evaluated against that of three expert graders for unsigned boundary position difference and thickness measurement of a retinal layer group in 50 and 41 B-scans, respectively. Reproducibility of the algorithm was tested in 30 C-scans of 10 healthy subjects each with the Spectralis and the Stratus OCT. Comparability between different devices was evaluated in 84 C-scans (volume or radial scans) obtained from 21 healthy subjects, two scans per subject with the Spectralis OCT, and one scan per subject each with the Stratus OCT and the RTVue-100 OCT. Each C-scan was segmented and the mean thickness for each retinal layer in sections of the early treatment of diabetic retinopathy study (ETDRS) grid was measured. Results The algorithm was able to segment up to 11 intraretinal layers. Measurements with the algorithm were within the 95% confidence interval of a single grader and the difference was smaller than the interindividual difference between the expert graders themselves. The cross-device examination of ETDRS-grid related layer thicknesses highly agreed between the three OCT devices. The algorithm correctly segmented a C-scan of a patient with X-linked retinitis pigmentosa. Conclusions The segmentation software provides device-independent, reliable, and reproducible analysis of intraretinal layers, similar to what is obtained from expert graders. Translational Relevance Potential application of the software includes routine clinical practice and multicenter clinical trials. PMID:24820053

An improved K-means clustering method for cDNA microarray image segmentation.

PubMed

Wang, T N; Li, T J; Shao, G F; Wu, S X

2015-07-14

Microarray technology is a powerful tool for human genetic research and other biomedical applications. Numerous improvements to the standard K-means algorithm have been carried out to complete the image segmentation step. However, most of the previous studies classify the image into two clusters. In this paper, we propose a novel K-means algorithm, which first classifies the image into three clusters, and then one of the three clusters is divided as the background region and the other two clusters, as the foreground region. The proposed method was evaluated on six different data sets. The analyses of accuracy, efficiency, expression values, special gene spots, and noise images demonstrate the effectiveness of our method in improving the segmentation quality.

Creating Very True Quantum Algorithms for Quantum Energy Based Computing

NASA Astrophysics Data System (ADS)

Nagata, Koji; Nakamura, Tadao; Geurdes, Han; Batle, Josep; Abdalla, Soliman; Farouk, Ahmed; Diep, Do Ngoc

2018-04-01

An interpretation of quantum mechanics is discussed. It is assumed that quantum is energy. An algorithm by means of the energy interpretation is discussed. An algorithm, based on the energy interpretation, for fast determining a homogeneous linear function f( x) := s. x = s 1 x 1 + s 2 x 2 + ⋯ + s N x N is proposed. Here x = ( x 1, … , x N ), x j ∈ R and the coefficients s = ( s 1, … , s N ), s j ∈ N. Given the interpolation values (f(1), f(2),...,f(N))=ěc {y}, the unknown coefficients s = (s1(ěc {y}),\\dots , sN(ěc {y})) of the linear function shall be determined, simultaneously. The speed of determining the values is shown to outperform the classical case by a factor of N. Our method is based on the generalized Bernstein-Vazirani algorithm to qudit systems. Next, by using M parallel quantum systems, M homogeneous linear functions are determined, simultaneously. The speed of obtaining the set of M homogeneous linear functions is shown to outperform the classical case by a factor of N × M.

Creating Very True Quantum Algorithms for Quantum Energy Based Computing

NASA Astrophysics Data System (ADS)

Nagata, Koji; Nakamura, Tadao; Geurdes, Han; Batle, Josep; Abdalla, Soliman; Farouk, Ahmed; Diep, Do Ngoc

2017-12-01

An interpretation of quantum mechanics is discussed. It is assumed that quantum is energy. An algorithm by means of the energy interpretation is discussed. An algorithm, based on the energy interpretation, for fast determining a homogeneous linear function f(x) := s.x = s 1 x 1 + s 2 x 2 + ⋯ + s N x N is proposed. Here x = (x 1, … , x N ), x j ∈ R and the coefficients s = (s 1, … , s N ), s j ∈ N. Given the interpolation values (f(1), f(2),...,f(N))=ěc {y}, the unknown coefficients s = (s1(ěc {y}),\\dots , sN(ěc {y})) of the linear function shall be determined, simultaneously. The speed of determining the values is shown to outperform the classical case by a factor of N. Our method is based on the generalized Bernstein-Vazirani algorithm to qudit systems. Next, by using M parallel quantum systems, M homogeneous linear functions are determined, simultaneously. The speed of obtaining the set of M homogeneous linear functions is shown to outperform the classical case by a factor of N × M.

Burn Injuries and Their Impact on Cognitive-Communication Skills in the Inpatient Rehabilitation Setting.

PubMed

Hendricks, Carla Tierney; Camara, Kristin; Violick Boole, Kathryn; Napoli, Maureen F; Goldstein, Richard; Ryan, Colleen M; Schneider, Jeffrey C

The prevalence and extent of cognitive-communication disorders and factors that have impact on outcomes are examined in the burn population within an inpatient rehabilitation facility. A retrospective data analysis was conducted on adults diagnosed with burn injury (n = 144). Descriptive statistics were used to identify the prevalence of cognitive-communication deficits on admission and discharge. The main outcomes were cognitive-communication ratings on discharge from inpatient rehabilitation as measured by the memory and problem-solving domains of the Functional Independence Measure (FIM) and composite score of the Functional Communication Measure (FCM). Medical, demographic and rehabilitation predictors of the main outcomes were assessed using regression analyses. On admission to inpatient rehabilitation, 79% of the total population presented with cognitive-communication impairments, and of them, 27% presented with persistent deficits on discharge. Admission FIM memory score, marital status, and age were significant predictors of discharge FIM memory score. Admission FIM problem-solving score, age, marital status, and prehospital living-with were significant predictors of discharge FIM problem-solving score. Admission FCM score and age were significant predictors of discharge FCM cognitive score. Persons with burn injuries are at risk for cognitive-communication impairments, which may persist after inpatient rehabilitation. FIM data obtained on admission can be used as a screening tool to identify these at-risk patients. Future work is needed to assess the efficacy of speech-language pathologist intervention for cognitive-communication deficits within the burn injury population.

A risk management model for familial breast cancer: A new application using Fuzzy Cognitive Map method.

PubMed

Papageorgiou, Elpiniki I; Jayashree Subramanian; Karmegam, Akila; Papandrianos, Nikolaos

2015-11-01

Breast cancer is the most deadly disease affecting women and thus it is natural for women aged 40-49 years (who have a family history of breast cancer or other related cancers) to assess their personal risk for developing familial breast cancer (FBC). Besides, as each individual woman possesses different levels of risk of developing breast cancer depending on their family history, genetic predispositions and personal medical history, individualized care setting mechanism needs to be identified so that appropriate risk assessment, counseling, screening, and prevention options can be determined by the health care professionals. The presented work aims at developing a soft computing based medical decision support system using Fuzzy Cognitive Map (FCM) that assists health care professionals in deciding the individualized care setting mechanisms based on the FBC risk level of the given women. The FCM based FBC risk management system uses NHL to learn causal weights from 40 patient records and achieves a 95% diagnostic accuracy. The results obtained from the proposed model are in concurrence with the comprehensive risk evaluation tool based on Tyrer-Cuzick model for 38/40 patient cases (95%). Besides, the proposed model identifies high risk women by calculating higher accuracy of prediction than the standard Gail and NSAPB models. The testing accuracy of the proposed model using 10-fold cross validation technique outperforms other standard machine learning based inference engines as well as previous FCM-based risk prediction methods for BC. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Absolute counting of neutrophils in whole blood using flow cytometry.

PubMed

Brunck, Marion E G; Andersen, Stacey B; Timmins, Nicholas E; Osborne, Geoffrey W; Nielsen, Lars K

2014-12-01

Absolute neutrophil count (ANC) is used clinically to monitor physiological dysfunctions such as myelosuppression or infection. In the research laboratory, ANC is a valuable measure to monitor the evolution of a wide range of disease states in disease models. Flow cytometry (FCM) is a fast, widely used approach to confidently identify thousands of cells within minutes. FCM can be optimised for absolute counting using spiked-in beads or by measuring the sample volume analysed. Here we combine the 1A8 antibody, specific for the mouse granulocyte protein Ly6G, with flow cytometric counting in straightforward FCM assays for mouse ANC, easily implementable in the research laboratory. Volumetric and Trucount™ bead assays were optimized for mouse neutrophils, and ANC values obtained with these protocols were compared to ANC measured by a dual-platform assay using the Orphee Mythic 18 veterinary haematology analyser. The single platform assays were more precise with decreased intra-assay variability compared with ANC obtained using the dual protocol. Defining ANC based on Ly6G expression produces a 15% higher estimate than the dual protocol. Allowing for this difference in ANC definition, the flow cytometry counting assays using Ly6G can be used reliably in the research laboratory to quantify mouse ANC from a small volume of blood. We demonstrate the utility of the volumetric protocol in a time-course study of chemotherapy induced neutropenia using four drug regimens. © 2014 International Society for Advancement of Cytometry.

Does hierarchy stability influence testosterone and cortisol levels of bearded capuchin monkeys (Sapajus libidinosus) adult males? A comparison between two wild groups.

PubMed

Mendonça-Furtado, Olívia; Edaes, Mariana; Palme, Rupert; Rodrigues, Agatha; Siqueira, José; Izar, Patrícia

2014-11-01

Testosterone and cortisol are hormones expected to play a major role in competitive behaviours (i.e. aggression), and are related to rank and hierarchical stability. Through a non-invasive technique, we analyzed faecal testosterone (FTM(1)) and cortisol (FCM(2)) metabolites of dominant and subordinate males from two wild groups of bearded capuchin monkeys. One group had a stable dominance hierarchy while the other had an unstable hierarchy, with a marked conflict period related to a male take-over. In the unstable hierarchy group (1) the dominant male had higher FTM peaks than subordinates, and (2) basal FTM levels were higher than in the stable group. These findings are in accordance with the Challenge Hypothesis and rank-based predictions, and confirm that in Sapajus libidinosus hierarchy stability, social status, aggression rates and testosterone are closely related. Dominants of both groups had higher basal and peak FCM levels, suggesting that in S. libidinosus the dominant male has a higher allostatic load than subordinates, related to his role in protection against predators, intragroup appeasement, and control of food sources. Finally, we suggest that males of S. libidinosus are resistant to testosterone suppression by cortisol, because in the unstable group in spite of an increase in FCM there was also an increase in FTM during the conflict period. This article is part of a Special Issue entitled: Neotropical Behaviour. Copyright © 2014 Elsevier B.V. All rights reserved.

Soft- to network hard-material for constructing both ion- and electron-conductive hierarchical porous structure to significantly boost energy density of a supercapacitor.

PubMed

Yang, Pingping; Xie, Jiale; Guo, Chunxian; Li, Chang Ming

2017-01-01

Soft-material PEDOT is used to network hard Co 3 O 4 nanowires for constructing both ion- and electron-conductive hierarchical porous structure Co 3 O 4 /PEDOT to greatly boost the capacitor energy density than sum of that of plain Co 3 O 4 nanowires and PEDOT film. Specifically, the networked hierarchical porous structure of Co 3 O 4 /PEDOT is synthesized and tailored through hydrothermal method and post-electrochemical polymerization method for the PEDOT coating onto Co 3 O 4 nanowires. Typically, Co 3 O 4 /PEDOT supercapacitor gets a highest areal capacitance of 160mFcm -2 at a current density of 0.2mAcm -2 , which is about 2.2 times larger than the sum of that of plain Co 3 O 4 NWs (0.92mFcm -2 ) and PEDOT film (69.88mFcm -2 ). Besides, if only PEDOT as active mass is counted, Co 3 O 4 /PEDOT cell can achieve a highest capacitance of 567.21Fg -1 , this is the highest capacitance value obtained by PEDOT-based supercapacitors. Furthermore, this soft-hard network porous structure also achieves a high cycling stability of 93% capacitance retention after the 20,000th cycle. This work demonstrates a new approach to constructing both ion and electron conductive hierarchical porous structure to significantly boost energy density of a supercapacitor. Copyright © 2016 Elsevier Inc. All rights reserved.

Antifouling Coatings Influence both Abundance and Community Structure of Colonizing Biofilms: a Case Study in the Northwestern Mediterranean Sea

PubMed Central

Camps, Mercedes; Barani, Aude; Gregori, Gérald; Bouchez, Agnès; Le Berre, Brigitte; Bressy, Christine; Blache, Yves

2014-01-01

When immersed in seawater, substrates are rapidly colonized by both micro- and macroorganisms. This process is responsible for important economic and ecological prejudices, particularly when related to ship hulls or aquaculture nets. Commercial antifouling coatings are supposed to reduce biofouling, i.e., micro- and macrofoulers. In this study, biofilms that primarily settled on seven different coatings (polyvinyl chloride [PVC], a fouling release coating [FRC], and five self-polishing copolymer coatings [SPC], including four commercial ones) were quantitatively studied, after 1 month of immersion in summer in the Toulon Bay (Northwestern Mediterranean Sea, France), by using flow cytometry (FCM), microscopy, and denaturing gradient gel electrophoresis. FCM was used after a pretreatment to separate cells from the biofilm matrix, in order to determine densities of heterotrophic bacteria, picocyanobacteria, and pico- and nanoeukaryotes on these coatings. Among diatoms, the only microphytobenthic class identified by microscopy, Licmophora, Navicula, and Nitzschia were determined to be the dominant taxa. Overall, biocide-free coatings showed higher densities than all other coatings, except for one biocidal coating, whatever the group of microorganisms. Heterotrophic bacteria always showed the highest densities, and diatoms showed the lowest, but the relative abundances of these groups varied depending on the coating. In particular, the copper-free SPC failed to prevent diatom settlement, whereas the pyrithione-free SPC exhibited high picocyanobacterial density. These results highlight the interest in FCM for antifouling coating assessment as well as specific selection among microbial communities by antifouling coatings. PMID:24907329

Microparticle Analysis in Disorders of Hemostasis and Thrombosis

PubMed Central

Mooberry, Micah J.; Key, Nigel S.

2015-01-01

Microparticles (MPs) are submicron vesicles released from the plasma membrane of eukaryotic cells in response to activation or apoptosis. MPs are known to be involved in numerous biologic processes, including inflammation, the immune response, cancer metastasis, and angiogenesis. Their earliest recognized and most widely accepted role, however, is the ability to promote and support the process of blood coagulation. Consequently, there is ongoing interest in studying MPs in disorders of hemostasis and thrombosis. Both phosphatidylserine (PS) exposure and the presence of tissue factor (TF) in the MP membrane may account for their procoagulant properties, and elevated numbers of MPs in plasma have been reported in numerous prothrombotic conditions. To date, however, there are few data on true causality linking MPs to the genesis of thrombosis. A variety of methodologies have been employed to characterize and quantify MPs, although detection is challenging due to their submicron size. Flow cytometry (FCM) remains the most frequently utilized strategy for MP detection; however, it is associated with significant technological limitations. Additionally, pre-analytical and analytical variables can influence the detection of MPs by FCM, rendering data interpretation difficult. Lack of methodologic standardization in MP analysis by FCM confounds the issue further, although efforts are currently underway to address this limitation. Moving forward, it will be important to address these technical challenges as a scientific community if we are to better understand the role that MPs play in disorders of hemostasis and thrombosis. PMID:25704723

MnFe2O4: Synthesis, morphology and electrochemical properties

NASA Astrophysics Data System (ADS)

Kulkarni, Shrikant; Thombare, Balu; Patil, Shankar

2017-05-01

MnFe2O4 has been synthesized by simple ammonia assisted co-precipitation method to obtain nanocrystalline powder. X-ray diffraction studies confirmed its crystallinity and phase purity. The MnFe2O4 calcined at 1000°C for 4 h has spinel crystal structure with Fd3m space group and lattice constant 8.511 Å. The electrode was prepared by dip coating method on stainless steel substrate and fired at 600°C for 2 h. Random shape grains of 0.2 to 1.5 micron with pores of 1-2 micron dimensions were observed in SEM images. The electrochemical studies of MnFe2O4 were carried out with 1 mole Na2SO4 electrolyte. The MnFe2O4 electrode shows highest specific capacitance of 27.53 F.g-1 and interfacial capacitance of 0.83 F.cm-2.

Mental maps and travel behaviour: meanings and models

NASA Astrophysics Data System (ADS)

Hannes, Els; Kusumastuti, Diana; Espinosa, Maikel León; Janssens, Davy; Vanhoof, Koen; Wets, Geert

2012-04-01

In this paper, the " mental map" concept is positioned with regard to individual travel behaviour to start with. Based on Ogden and Richards' triangle of meaning (The meaning of meaning: a study of the influence of language upon thought and of the science of symbolism. International library of psychology, philosophy and scientific method. Routledge and Kegan Paul, London, 1966) distinct thoughts, referents and symbols originating from different scientific disciplines are identified and explained in order to clear up the notion's fuzziness. Next, the use of this concept in two major areas of research relevant to travel demand modelling is indicated and discussed in detail: spatial cognition and decision-making. The relevance of these constructs to understand and model individual travel behaviour is explained and current research efforts to implement these concepts in travel demand models are addressed. Furthermore, these mental map notions are specified in two types of computational models, i.e. a Bayesian Inference Network (BIN) and a Fuzzy Cognitive Map (FCM). Both models are explained, and a numerical and a real-life example are provided. Both approaches yield a detailed quantitative representation of the mental map of decision-making problems in travel behaviour.

Bone marrow-derived cultured mast cells and peritoneal mast cells as targets of a growth activity secreted by BALB/3T3 fibroblasts

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

Jozaki, K.; Kuriu, A.; Hirota, S.

1991-03-01

When fibroblast cell lines were cultured in contact with bone marrow-derived cultured mast cells (CMC), both NIH/3T3 and BALB/3T3 cell lines supported the proliferation of CMC. In contrast, when contact between fibroblasts and CMC was prohibited by Biopore membranes or soft agar, only BALB/3T3 fibroblasts supported CMC proliferation, suggesting that BALB/3T3 but not NIH/3T3 cells secreted a significant amount of a mast cell growth activity. Moreover, the BALB/3T3-derived growth activity induced the incorporation of (3H)thymidine by CMC and the clonal growth of peritoneal mast cells in methylcellulose. The mast cell growth activity appeared to be different from interleukin 3 (IL-3)more » and interleukin 4 (IL-4), because mRNAs for these interleukins were not detectable in BALB/3T3 fibroblasts. Although mast cells are genetically deficient in tissues of W/Wv mice, CMC did develop when bone marrow cells of W/Wv mice were cultured with pokeweed mitogen-stimulated spleen cell-conditioned medium. Because BALB/3T3 fibroblast-conditioned medium (BALB-FCM) did not induce the incorporation of (3H)thymidine by W/Wv CMC, the growth activity in BALB-FCM appeared to be a ligand for the receptor encoded by the W (c-kit) locus. Because CMC and peritoneal mast cells are obtained as homogeneous suspensions rather easily, these cells may be potentially useful as targets for the fibroblast-derived mast cell growth activity.« less

Supplementation with Ca salts of soybean oil interacts with concentrate level in grazing dairy cows: milk production and milk composition.

PubMed

Macedo, Fernanda Lopes; de Souza, Jonas; Batistel, Fernanda; Chagas, Lucas Jado; Santos, Flávio Augusto Portela

2016-12-01

In this study, we investigated the associative effects of concentrate levels and Ca salts of soybean oil (CSSO) supplementation on milk production, milk composition, and milk fatty acids of mid-lactation dairy cows grazing on tropical pasture. Twenty-four Jersey × Holstein cows were used in a randomized block design and assigned to four treatments arranged in a 2 × 2 factorial design. Factors evaluated were concentrate levels (low, 3 kg/day vs. high, 7 kg/day of concentrate) and CSSO supplementation (without CSSO vs. with 250 g CSSO cow/day). All cows grazed on elephant grass (Pennisetum purpureum cv. Cameroon) and received the supplemental treatments for a 90-day period. Interactions between concentrate level and CSSO were detected for milk yield, milk yield components, energy-corrected milk (ECM) and 3.5 % fat-corrected milk (FCM). Milk yield increased when CSSO was fed in a low concentrate level, while it decreased milk production in a high concentrate level. Yields of fat, protein, lactose, 3.5 % FCM, and ECM were not affected with CSSO in the low concentrate, but reduced in the high concentrate level. CSSO increased proportions of monounsaturated milk FA, C18:2 trans-10 cis-12, and polyunsaturated FA, and reduced proportions of saturated milk FA in milk. In conclusion, feeding the high level of concentrate was an effective strategy to improve milk yield and solid production. CSSO supplementation increased milk production when fed at low concentrate level but did not affect yield of solids.

Recombinant scFv antibodies against infectious pancreatic necrosis virus isolated by flow cytometry.

PubMed

Xu, Li-Ming; Zhao, Jing-Zhuang; Liu, Miao; Cao, Yong-Sheng; Yin, Jia-Sheng; Liu, Hong-Bai; Lu, Tongyan

2016-11-01

Infectious pancreatic necrosis is a significant disease of farmed salmonids in China. In this study, a single chain variable fragment (scFv) antibody library derived from rainbow trout (Oncorhynchus mykiss) and viral protein VP2 of a Chinese infectious pancreatic necrosis virus (IPNV) isolate ChRtm213 were co-expressed by a bacterial display technology. The library was subjected to three rounds of screening by flow cytometry (FCM) to select IPNV specific antibodies. Six antibody clones with different mean fluorescence intensities (MFI) were obtained by picking colonies at random. The antibody clones were expressed and purified. The purified IPNV-specific scFv antibodies were used successfully in Western blotting, enzyme linked immunosorbent assay (ELISA) and an immunofluorescence antibody test (IFAT). This method provides a high throughput means to screen an antibody library by flow cytometry, and isolate a panel of antibody that can be used as potential reagents for the detection and study of IPNV that are prevalent in China. Copyright © 2016 Elsevier B.V. All rights reserved.

[Determination of acidity and vitamin C in apples using portable NIR analyzer].

PubMed

Yang, Fan; Li, Ya-Ting; Gu, Xuan; Ma, Jiang; Fan, Xing; Wang, Xiao-Xuan; Zhang, Zhuo-Yong

2011-09-01

Near infrared (NIR) spectroscopy technology based on a portable NIR analyzer, combined with kernel Isomap algorithm and generalized regression neural network (GRNN) has been applied to establishing quantitative models for prediction of acidity and vitamin C in six kinds of apple samples. The obtained results demonstrated that the fitting and the predictive accuracy of the models with kernel Isomap algorithm were satisfactory. The correlation between actual and predicted values of calibration samples (R(c)) obtained by the acidity model was 0.999 4, and for prediction samples (R(p)) was 0.979 9. The root mean square error of prediction set (RMSEP) was 0.055 8. For the vitamin C model, R(c) was 0.989 1, R(p) was 0.927 2, and RMSEP was 4.043 1. Results proved that the portable NIR analyzer can be a feasible tool for the determination of acidity and vitamin C in apples.

A comparison of neural network and fuzzy clustering techniques in segmenting magnetic resonance images of the brain.

PubMed

Hall, L O; Bensaid, A M; Clarke, L P; Velthuizen, R P; Silbiger, M S; Bezdek, J C

1992-01-01

Magnetic resonance (MR) brain section images are segmented and then synthetically colored to give visual representations of the original data with three approaches: the literal and approximate fuzzy c-means unsupervised clustering algorithms, and a supervised computational neural network. Initial clinical results are presented on normal volunteers and selected patients with brain tumors surrounded by edema. Supervised and unsupervised segmentation techniques provide broadly similar results. Unsupervised fuzzy algorithms were visually observed to show better segmentation when compared with raw image data for volunteer studies. For a more complex segmentation problem with tumor/edema or cerebrospinal fluid boundary, where the tissues have similar MR relaxation behavior, inconsistency in rating among experts was observed, with fuzz-c-means approaches being slightly preferred over feedforward cascade correlation results. Various facets of both approaches, such as supervised versus unsupervised learning, time complexity, and utility for the diagnostic process, are compared.

SU-C-BRE-02: BED Vs. Local Control: Radiobiological Effect of Tumor Volume in Monte Carlo (MC) Lung SBRT Planning

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

Pokhrel, D; Badkul, R; Jiang, H

2014-06-15

Purpose: SBRT with hypofractionated dose schemata has emerged a compelling treatment modality for medically inoperable early stage lung cancer patients. It requires more accurate dose calculation and treatment delivery technique. This report presents the relationship between tumor control probability(TCP) and size-adjusted biological effective dose(sBED) of tumor volume for MC lung SBRT patients. Methods: Fifteen patients who were treated with MC-based lung SBRT to 50Gy in 5 fractions to PTVV100%=95% were studied. ITVs were delineated on MIP images of 4DCT-scans. PTVs diameter(ITV+5mm margins) ranged from 2.7–4.9cm (mean 3.7cm). Plans were generated using non-coplanar conformal arcs/beams using iPlan XVMC algorithm (BrainLABiPlan ver.4.1.2)more » for Novalis-TX with HD-MLCs and 6MVSRS(1000MU/min) mode, following RTOG-0813 dosimetric guidelines. To understand the known uncertainties of conventional heterogeneities-corrected/uncorrected pencil beam (PBhete/ PB-homo) algorithms, dose distributions were re-calculated with PBhete/ PB-homo using same beam configurations, MLCs and monitor units. Biologically effective dose(BED10) was computed using LQ-model with α/β=10Gy for meanPTV and meanITV. BED10-c*L, gave size-adjusted BED(sBED), where c=10Gy/cm and L=PTV diameter in centimeter. The TCP model was adopted from Ohri et al.(IJROBP, 2012): TCP = exp[sBEDTCD50]/ k /(1.0 + exp[sBED-TCD50]/k), where k=31Gy corresponding to TCD50=0Gy; and more realistic MC-based TCP was computed for PTV(V99%). Results: Mean PTV PB-hete TCP value was 6% higher, but, mean PTV PB-homo TCP value was 4% lower compared to mean PTV MC TCP. Mean ITV PB-hete/PB-homo TCP values were comparable (within ±3.0%) to mean ITV MC TCP. The mean PTV(V99%)had BED10=90.9±3.7%(median=92.2%),sBED=54.1±8.2%(median=53.5%) corresponding to mean MC TCP value of 84.8±3.3%(median=84.9%) at 2- year local control. Conclusion: The TCP model which incorporates BED10 and tumor diameter indicates that radiobiological effect of target volume and dose calculation algorithm significantly affects TCP for lung SBRT patients. Dose calculation using MC-based algorithm is more realistic with tissue heterogeneities and is routinely performed in our clinic. Patients will be followed up to determine whether TCP prediction correlate clinical outcomes.« less

Generic Algorithms for Estimating Foliar Pigment Content

NASA Astrophysics Data System (ADS)

Gitelson, Anatoly; Solovchenko, Alexei

2017-09-01

Foliar pigment contents and composition are main factors governing absorbed photosynthetically active radiation, photosynthetic activity, and physiological status of vegetation. In this study the performance of nondestructive techniques based on leaf reflectance were tested for estimating chlorophyll (Chl) and anthocyanin (AnC) contents in species with widely variable leaf structure, pigment content, and composition. Only three spectral bands (green, red edge, and near-infrared) are required for nondestructive Chl and AnC estimation with normalized root-mean-square error (NRMSE) below 4.5% and 6.1%, respectively. The algorithms developed are generic, not requiring reparameterization for each species allowing for accurate nondestructive Chl and AnC estimation using simple handheld field/lab instrumentation. They also have potential in interpretation of airborne and satellite data.

A Fresh Cadaver Model for the Instruction of Ultrasound-Guided Fine-Needle Aspiration of Thyroid Nodules.

PubMed

McCrary, Hilary C; Faucett, Erynne A; Hurbon, Audriana N; Milinic, Tijana; Cervantes, Jose A; Kent, Sean L; Adamas-Rappaport, William J

2017-07-01

Objective The aim of our study is to determine if a fresh cadaver model (FCM) for the instruction of ultrasound (US)-guided fine-needle aspiration (FNA) of thyroid nodules is a practical method for instruction. Study Design Pre- and postinstruction assessment of medical students' ability to perform US-guided FNA of artificially created thyroid nodules placed adjacent to the thyroid gland of a fresh cadaver. Setting University-based fresh cadaver laboratory. Subjects and Methods Study participants included a total of 17 first- and second-year medical students with minimal US training. Technical skills were assessed using a 10-item checklist. In addition, a cognitive assessment regarding the indications, contraindications, and complications of the procedure was completed. A postinstruction assessment was provided for participants 5 weeks after their initial assessment. Differences between pre- and postinstruction assessment scores of technical skills were analyzed using McNemar's test. The mean cognitive knowledge gain was analyzed using a paired 2-sample t test. Results Eight of 10 items on the skills checklist were statistically significant between pre- and postinstruction skills assessment ( P < .05). There was a statistically significant change in cognitive knowledge gain regarding the contraindications of the procedure ( P = .001), but not for indications or complications ( P = .104 and P = .111, respectively). Conclusion US-guided FNA continues to be an important diagnostic procedure in the workup of thyroid nodules, making it an essential skill to integrate into surgical skills lab. Our FCM for the instruction of US-guided FNA is the first of its kind, and this pilot study shows this is a viable method for instruction.

Sensitivity enhanced strain and temperature measurements based on FBG and frequency chirp magnification.

PubMed

Du, Jiangbing; He, Zuyuan

2013-11-04

In this work, highly sensitive measurements of strain and temperature have been demonstrated using a fiber Bragg grating (FBG) sensor with significantly enhance sensitivity by all-optical signal processing. The sensitivity enhancement is achieved by degenerated Four Wave Mixing (FWM) for frequency chirp magnification (FCM), which can be used for magnifying the wavelength drift of the FBG sensor induced by strain and temperature change. Highly sensitive measurements of static strain and temperature have been experimentally demonstrated with strain sensitivity of 5.36 pm/με and temperature sensitivity of 54.09 pm/°C. The sensitivity has been enhanced by a factor of five based on a 4-order FWM in a highly nonlinear fiber (HNLF).

"Symptom-based insulin adjustment for glucose normalization" (SIGN) algorithm: a pilot study.

PubMed

Lee, Joyce Yu-Chia; Tsou, Keith; Lim, Jiahui; Koh, Feaizen; Ong, Sooim; Wong, Sabrina

2012-12-01

Lack of self-monitoring of blood glucose (SMBG) records in actual practice settings continues to create therapeutic challenges for clinicians, especially in adjusting insulin therapy. In order to overcome this clinical obstacle, a "Symptom-based Insulin adjustment for Glucose Normalization" (SIGN) algorithm was developed to guide clinicians in caring for patients with uncontrolled type 2 diabetes who have few to no SMBG records. This study examined the clinical outcome and safety of the SIGN algorithm. Glycated hemoglobin (HbA1c), insulin usage, and insulin-related adverse effects of a total of 114 patients with uncontrolled type 2 diabetes who refused to use SMBG or performed SMBG once a day for less than three times per week were studied 3 months prior to the implementation of the algorithm and prospectively at every 3-month interval for a total of 6 months after the algorithm implementation. Patients with type 1 diabetes, nonadherence to diabetes medications, or who were not on insulin therapy at any time during the study period were excluded from this study. Mean HbA1c improved by 0.29% at 3 months (P = 0.015) and 0.41% at 6 months (P = 0.006) after algorithm implementation. A slight increase in HbA1c was observed when the algorithm was not implemented. There were no major hypoglycemic episodes. The number of minor hypoglycemic episodes was minimal with the majority of the cases due to irregular meal habits. The SIGN algorithm appeared to offer a viable and safe approach when managing uncontrolled patients with type 2 diabetes who have few to no SMBG records.

Efficient lossy compression implementations of hyperspectral images: tools, hardware platforms, and comparisons

NASA Astrophysics Data System (ADS)

García, Aday; Santos, Lucana; López, Sebastián.; Callicó, Gustavo M.; Lopez, Jose F.; Sarmiento, Roberto

2014-05-01

Efficient onboard satellite hyperspectral image compression represents a necessity and a challenge for current and future space missions. Therefore, it is mandatory to provide hardware implementations for this type of algorithms in order to achieve the constraints required for onboard compression. In this work, we implement the Lossy Compression for Exomars (LCE) algorithm on an FPGA by means of high-level synthesis (HSL) in order to shorten the design cycle. Specifically, we use CatapultC HLS tool to obtain a VHDL description of the LCE algorithm from C-language specifications. Two different approaches are followed for HLS: on one hand, introducing the whole C-language description in CatapultC and on the other hand, splitting the C-language description in functional modules to be implemented independently with CatapultC, connecting and controlling them by an RTL description code without HLS. In both cases the goal is to obtain an FPGA implementation. We explain the several changes applied to the original Clanguage source code in order to optimize the results obtained by CatapultC for both approaches. Experimental results show low area occupancy of less than 15% for a SRAM-based Virtex-5 FPGA and a maximum frequency above 80 MHz. Additionally, the LCE compressor was implemented into an RTAX2000S antifuse-based FPGA, showing an area occupancy of 75% and a frequency around 53 MHz. All these serve to demonstrate that the LCE algorithm can be efficiently executed on an FPGA onboard a satellite. A comparison between both implementation approaches is also provided. The performance of the algorithm is finally compared with implementations on other technologies, specifically a graphics processing unit (GPU) and a single-threaded CPU.

Sim3C: simulation of Hi-C and Meta3C proximity ligation sequencing technologies.

PubMed

DeMaere, Matthew Z; Darling, Aaron E

2018-02-01

Chromosome conformation capture (3C) and Hi-C DNA sequencing methods have rapidly advanced our understanding of the spatial organization of genomes and metagenomes. Many variants of these protocols have been developed, each with their own strengths. Currently there is no systematic means for simulating sequence data from this family of sequencing protocols, potentially hindering the advancement of algorithms to exploit this new datatype. We describe a computational simulator that, given simple parameters and reference genome sequences, will simulate Hi-C sequencing on those sequences. The simulator models the basic spatial structure in genomes that is commonly observed in Hi-C and 3C datasets, including the distance-decay relationship in proximity ligation, differences in the frequency of interaction within and across chromosomes, and the structure imposed by cells. A means to model the 3D structure of randomly generated topologically associating domains is provided. The simulator considers several sources of error common to 3C and Hi-C library preparation and sequencing methods, including spurious proximity ligation events and sequencing error. We have introduced the first comprehensive simulator for 3C and Hi-C sequencing protocols. We expect the simulator to have use in testing of Hi-C data analysis algorithms, as well as more general value for experimental design, where questions such as the required depth of sequencing, enzyme choice, and other decisions can be made in advance in order to ensure adequate statistical power with respect to experimental hypothesis testing.

Cell-production rates estimated by the use of vincristine sulphate and flow cytometry. II. Correlation between the cell-production rates of ageing ascites tumours and the number of S phase tumour cells.

PubMed

Barfod, I H; Barfod, N M

1980-01-01

A new method for the evaluation of cell production rates combining flow cytometry (FCM) and the stathmokinetic method using vincristine sulphate (VS) has been used for the analysis of three aneuploid ascites tumours at different stages of growth. Using this technique it was possible to estimate the well-known decrease in cell production rates of ageing ascites tumours. The percentage of normal host cells in the aneuploid tumours studied was easily determined by FCM prior to the calculation of the tumour cell-production rates. A correlation was found between the percentage of tumour cells in the S phase and the tumour cell-production rate. This correlation is probably explained by the gradual transfer of proliferating cells in S phase to resting G1 and G2 phases with increasing tumour age.

[Companion diagnostics "POTELIGEO TEST IHC/FCM" used with "POTELIGEO" (mogamulizumab) for adult T-cell leukemia-lymphoma (ATL) treatment].

PubMed

Goami, Takeshi

2014-05-01

Personalized medicine offers the best treatment for individual patients, it is important for an IVD manufacturer to develop companion diagnostics in parallel with the development of new drugs through close cooperation with drug companies, and supply diagnostics companies with new drugs for physicians and patients. We received approval for a premarket approval application (PMA) for two in vitro diagnostic ("IVD") reagents, POTELIGEO TEST IHC and POTELIGEO TEST FCM ("POTELIGEO TEST"), in March 2012, and subsequently launched POTELIGEO TEST in May 2012. POTELIGEO TEST is a companion diagnostic used with POTELIGEO for which Kyowa Hakko Kirin has a new drug application (NDA) that was approved in March 2012, and is designed to help physicians identify appropriate subpopulations of adult T-cell leukemia-lymphoma(ATL) patients who are most likely to respond to POTELIGEO 20 mg (mogamulizumab) Injection ("POTELIGEO").

A spectrally tunable LED sphere source enables accurate calibration of tristimulus colorimeters

NASA Astrophysics Data System (ADS)

Fryc, I.; Brown, S. W.; Ohno, Y.

2006-02-01

The Four-Color Matrix method (FCM) was developed to improve the accuracy of chromaticity measurements of various display colors. The method is valid for each type of display having similar spectra. To develop the Four-Color correction matrix, spectral measurements of primary red, green, blue, and white colors of a display are needed. Consequently, a calibration facility should be equipped with a number of different displays. This is very inconvenient and expensive. A spectrally tunable light source (STS) that can mimic different display spectral distributions would eliminate the need for maintaining a wide variety of displays and would enable a colorimeter to be calibrated for a number of different displays using the same setup. Simulations show that an STS that can create red, green, blue and white distributions that are close to the real spectral power distribution (SPD) of a display works well with the FCM for the calibration of colorimeters.

Flow Cytometry Method Analysis of Apoptosis: No Significant Difference Between EDTA and EDTA-free Trypsin Treatment Procedure.

PubMed

Xu, Xiao-yan; Nie, Xiao-cui; Ma, Hai-ying; Song, Guo-qing; Zhang, Xiao-tong; Jin, Yu-nan; Yu, Yan-qiu

2015-04-01

Flow cytometry method (FCM) is a generally accepted tool to analyze apoptosis. Although apoptosis assay kit was applied by many companies, the manufacturers were not consistent with whether using Trypsin with EDTA to collect the adherent cells. In another words, the influence of EDTA on apoptotic ratio is not clear. In this work, we compared the proportion of apoptotic cells with EDTA or EDTA-free Trypsin treatment by FCM. We concluded that Trypsin with or without EDTA has little influence on the proportion of apoptotic cells. In addition, we found that the ratio of necrosis and apoptosis was different in cells collected by scraping. WAVE2 protein was analyzed as a typical example for movement related protein. WAVE2 expression is elevated in the EDTA Trypsin treated group, compared with EDTA-free Trypsin treatment and scrapping group. © The Author(s) 2014.

Comparing MODIS C6 'Deep Blue' and 'Dark Target' Aerosol Data

NASA Technical Reports Server (NTRS)

Hsu, N. C.; Sayer, A. M.; Bettenhausen, C.; Lee, J.; Levy, R. C.; Mattoo, S.; Munchak, L. A.; Kleidman, R.

2014-01-01

The MODIS Collection 6 Atmospheres product suite includes refined versions of both 'Deep Blue' (DB) and 'Dark Target' (DT) aerosol algorithms, with the DB dataset now expanded to include coverage over vegetated land surfaces. This means that, over much of the global land surface, users will have both DB and DT data to choose from. A 'merged' dataset is also provided, primarily for visualization purposes, which takes retrievals from either or both algorithms based on regional and seasonal climatologies of normalized difference vegetation index (NDVI). This poster present some comparisons of these two C6 aerosol algorithms, focusing on AOD at 550 nm derived from MODIS Aqua measurements, with each other and with Aerosol Robotic Network (AERONET) data, with the intent to facilitate user decisions about the suitability of the two datasets for their desired applications.

Chance of Vulnerability Reduction in Application-Specific NoC through Distance Aware Mapping Algorithm

NASA Astrophysics Data System (ADS)

Janidarmian, Majid; Fekr, Atena Roshan; Bokharaei, Vahhab Samadi

2011-08-01

Mapping algorithm which means which core should be linked to which router is one of the key issues in the design flow of network-on-chip. To achieve an application-specific NoC design procedure that minimizes the communication cost and improves the fault tolerant property, first a heuristic mapping algorithm that produces a set of different mappings in a reasonable time is presented. This algorithm allows the designers to identify the set of most promising solutions in a large design space, which has low communication costs while yielding optimum communication costs in some cases. Another evaluated parameter, vulnerability index, is then considered as a principle of estimating the fault-tolerance property in all produced mappings. Finally, in order to yield a mapping which considers trade-offs between these two parameters, a linear function is defined and introduced. It is also observed that more flexibility to prioritize solutions within the design space is possible by adjusting a set of if-then rules in fuzzy logic.

Rapid detection of total and viable Legionella pneumophila in tap water by immunomagnetic separation, double fluorescent staining and flow cytometry.

PubMed

Keserue, Hans-Anton; Baumgartner, Andreas; Felleisen, Richard; Egli, Thomas

2012-11-01

We developed a rapid detection method for Legionella pneumophila (Lp) by filtration, immunomagnetic separation, double fluorescent staining, and flow cytometry (IMS-FCM method). The method requires 120 min and can discriminate 'viable' and 'membrane-damaged' cells. The recovery is over 85% of spiked Lp SG 1 cells in 1 l of tap water and detection limits are around 50 and 15 cells per litre for total and viable Lp, respectively. The method was compared using water samples from house installations in a blind study with three environmental laboratories performing the ISO 11731 plating method. In 53% of the water samples from different taps and showers significantly higher concentrations of Lp were detected by flow cytometry. No correlation to the plate culture method was found. Since also 'viable but not culturable' (VNBC) cells are detected by our method, this result was expected. The IMS-FCM method is limited by the specificity of the used antibodies; in the presented case they target Lp serogroups 1-12. This and the fact that no Lp-containing amoebae are detected may explain why in 21% of all samples higher counts were observed using the plate culture method. Though the IMS-FCM method is not yet fit to completely displace the established plating method (ISO 11731) for routine Lp monitoring, it has major advantages to plating and can quickly provide important insights into the ecology of this pathogen in water distribution systems. © 2012 The Authors. Microbial Biotechnology © 2012 Society for Applied Microbiology and Blackwell Publishing Ltd.

Contrasting stress responses of two co-occurring chipmunk species (Tamias alpinus and T. speciosus).

PubMed

Hammond, Talisin T; Palme, Rupert; Lacey, Eileen A

2015-01-15

Glucocorticoid (GC) hormones are important mediators of responses to environmental conditions. Accordingly, differences in GC physiology may contribute to interspecific variation in response to anthropogenically-induced patterns of climate change. To begin exploring this possibility, we validated the use of fecal cortisol/corticosterone metabolites (FCM) to measure baseline glucocorticoid levels in two species of co-occurring chipmunks that have exhibited markedly different patterns of response to environmental change. In Yosemite National Park, the alpine chipmunk (Tamias alpinus) has undergone a significant upward contraction of its elevational range over the past century; in contrast, the lodgepole chipmunk (Tamiasspeciosus) has experienced no significant change in elevational distribution over this period. To determine if GC levels in these species vary in response to external stimuli and to assess whether these responses differ between species, we compared FCM levels for the same individuals (1) at the time of capture in the field, (2) after a short period of captivity, and (3) after adrenocorticotropic hormone (ACTH), (4) handling, and (5) trapping challenges conducted while these animals were held in captivity. Our analyses indicate that T. alpinus was more responsive to several of these changes in external conditions. Although both species displayed a significant FCM response to ACTH challenge, only T. alpinus showed a significant response to our handling challenge and to captive housing conditions. These findings underscore the importance of species-specific validation studies and support the potential for studies of GC physiology to generate insights into interspecific differences in response to environmental change. Copyright © 2014 Elsevier Inc. All rights reserved.

Low plasma cortisol and fecal cortisol metabolite measures as indicators of compromised welfare in domestic horses (Equus caballus)

PubMed Central

Jego, Patrick; Henry, Séverine; Bruchet, Anaelle; Palme, Rupert; Coste, Caroline; Hausberger, Martine

2017-01-01

The hypothalamic-pituitary-adrenal (HPA) axis response to chronic stress is far from straight forward, particularly with regards to animal welfare. There are reports of no effect as well as both decreases and increases in cortisol after chronic stressors. Therefore, the first aim of the present study was to determine how measures of compromised welfare, such as chronic pain and haematological anomalies, related to cortisol levels in domestic horses (Equus caballus). Domestic horses are an informative model to investigate the impact of chronic stress (due to environment, pain, work, housing conditions…) on the HPA axis. The second aim was to determine whether levels of fecal cortisol metabolites (FCM) may be used as an indicator of welfare measures. The present study used fifty-nine horses (44 geldings and 15 mares), from three riding centres in Brittany, France. The primary findings show that horses whose welfare was clearly compromised (as indicated by an unusual ears backward position, presence of vertebral problems or haematological anomalies, e.g. anaemia) also had lower levels of both FCM and plasma cortisol. This work extends our previous findings showing that withdrawn postures, indicators of depressive-like behavior in horses, are associated with lower plasma cortisol levels. We also found that evening plasma cortisol levels positively correlated with FCM levels in horses. Future research aims to determine the extent to which factors of influence on welfare, such as living conditions (e.g. single stalls versus group housing in pasture or paddocks), early life factors, and human interaction, act as mediators of cortisol levels in horses. PMID:28886020

Correlation between ploidy status using flow cytometry and nucleolar organizer regions in benign and malignant epithelial odontogenic tumors.

PubMed

Mohamed Mahmoud, Sarah Ahmed; El-Rouby, Dalia Hussein; El-Ghani, Safa Fathy Abd; Badawy, Omnia Mohamed

2017-06-01

Differentiation between the aggressive benign odontogenic tumors and their malignant counterparts is controversial and difficult. While flow cytometry (FCM) allowed DNA analysis in neoplasia, argyrophilic organizer regions (AgNORs) number and/or size in a nucleus are correlated with the ribosomal gene activity and therefore with cellular proliferation. The aim of this research was to study the diagnostic accuracy of FCM and AgNORs staining in differentiating between benign and malignant epithelial odontogenic tumors and to correlate between these two interventions. Sixteen benign cases [8 cases of ameloblastoma (AB) and 8 cases of keratocystic odontogenic tumor (KCOT)] and 13 malignant epithelial odontogenic tumors [8 cases of ameloblastic carcinoma (ABC) and 5 cases of clear cell odontogenic carcinoma(CCOC)] were included in the current study. For FCM analysis, a single cell suspension from Formalin fixed paraffin-embedded (FFPE) tumors was prepared according to a modified method described by Hedley (1989) and AgNORs staining were performed in accordance to the Ploton protocol (1986). Analysis of AgNORs was performed using both quantitative and qualitative methods. The work revealed that all the examined tumors were diploid, except for 40% of CCOC cases. The S-phase fraction (SPF) value, AgNORs count and AgNORs area/cell showed statistically significant difference on comparing benign and malignant groups. A weak positive correlation was observed between SPF and AgNORs count. The SPF value was considered to be more sensitive and specific in differentiation between aggressive benign and malignant epithelial odontogenic tumors in comparison to AgNORs counting. Copyright © 2017 Elsevier Ltd. All rights reserved.

Low plasma cortisol and fecal cortisol metabolite measures as indicators of compromised welfare in domestic horses (Equus caballus).

PubMed

Pawluski, Jodi; Jego, Patrick; Henry, Séverine; Bruchet, Anaelle; Palme, Rupert; Coste, Caroline; Hausberger, Martine

2017-01-01

The hypothalamic-pituitary-adrenal (HPA) axis response to chronic stress is far from straight forward, particularly with regards to animal welfare. There are reports of no effect as well as both decreases and increases in cortisol after chronic stressors. Therefore, the first aim of the present study was to determine how measures of compromised welfare, such as chronic pain and haematological anomalies, related to cortisol levels in domestic horses (Equus caballus). Domestic horses are an informative model to investigate the impact of chronic stress (due to environment, pain, work, housing conditions…) on the HPA axis. The second aim was to determine whether levels of fecal cortisol metabolites (FCM) may be used as an indicator of welfare measures. The present study used fifty-nine horses (44 geldings and 15 mares), from three riding centres in Brittany, France. The primary findings show that horses whose welfare was clearly compromised (as indicated by an unusual ears backward position, presence of vertebral problems or haematological anomalies, e.g. anaemia) also had lower levels of both FCM and plasma cortisol. This work extends our previous findings showing that withdrawn postures, indicators of depressive-like behavior in horses, are associated with lower plasma cortisol levels. We also found that evening plasma cortisol levels positively correlated with FCM levels in horses. Future research aims to determine the extent to which factors of influence on welfare, such as living conditions (e.g. single stalls versus group housing in pasture or paddocks), early life factors, and human interaction, act as mediators of cortisol levels in horses.

Usefullness of IGH/TCR PCR studies in lymphoproliferative disorders with inconclusive clonality by flow cytometry.

PubMed

Ribera, Jordi; Zamora, Lurdes; Juncà, Jordi; Rodríguez, Inés; Marcé, Silvia; Cabezón, Marta; Millá, Fuensanta

2013-07-25

In up to 5-15% of studies of lymphoproliferative disorders (LPD) flow cytometry (FCM) or immunomorphologic methods cannot discriminate malignant from reactive processes. The aim of this work was to determine the usefulness of PCR for solving these diagnostic uncertainties. We analyzed IGH and TCRγ genes by PCR in 106 samples with inconclusive FCM results. A clonal result was registered in 36/106 studies, with a LPD being confirmed in 27 (75%) of these cases. Specifically, 9/9 IGH clonal and 16/25 TCRγ clonal results were finally diagnosed with LPD. Additionally, 2 clonal TCRγ samples with suspicion of undefined LPD were finally diagnosed with T LPD. Although polyclonal results were obtained in 47 of the cases studied (38 IGH and 9 TCRγ), hematologic neoplasms were diagnosed in 4/38 IGH polyclonal and in 1/9 TCRγ polyclonal studies. There were also 14 PCR polyclonal results (4 IGH, 10 TCRγ), albeit non-conclusive. Of these, 2/4 were eventually diagnosed with B-cell lymphoma and 3/10 with T-cell LPD. In 8 IGH samples the results of PCR techniques were non-informative but in 3/8 cases a B lymphoma was finally confirmed. We concluded that PCR is a useful technique to identify LPD when FCM is inconclusive. A PCR clonal B result is indicative of malignancy but IGH polyclonal and non-conclusive results do not exclude lymphoid neoplasms. Interpretation of T-cell clonality should be based on all the available clinical and analytical data. © 2013 Clinical Cytometry Society. Copyright © 2013 Clinical Cytometry Society.

Formalization of treatment guidelines using Fuzzy Cognitive Maps and semantic web tools.

PubMed

Papageorgiou, Elpiniki I; Roo, Jos De; Huszka, Csaba; Colaert, Dirk

2012-02-01

Therapy decision making and support in medicine deals with uncertainty and needs to take into account the patient's clinical parameters, the context of illness and the medical knowledge of the physician and guidelines to recommend a treatment therapy. This research study is focused on the formalization of medical knowledge using a cognitive process, called Fuzzy Cognitive Maps (FCMs) and semantic web approach. The FCM technique is capable of dealing with situations including uncertain descriptions using similar procedure such as human reasoning does. Thus, it was selected for the case of modeling and knowledge integration of clinical practice guidelines. The semantic web tools were established to implement the FCM approach. The knowledge base was constructed from the clinical guidelines as the form of if-then fuzzy rules. These fuzzy rules were transferred to FCM modeling technique and, through the semantic web tools, the whole formalization was accomplished. The problem of urinary tract infection (UTI) in adult community was examined for the proposed approach. Forty-seven clinical concepts and eight therapy concepts were identified for the antibiotic treatment therapy problem of UTIs. A preliminary pilot-evaluation study with 55 patient cases showed interesting findings; 91% of the antibiotic treatments proposed by the implemented approach were in fully agreement with the guidelines and physicians' opinions. The results have shown that the suggested approach formalizes medical knowledge efficiently and gives a front-end decision on antibiotics' suggestion for cystitis. Concluding, modeling medical knowledge/therapeutic guidelines using cognitive methods and web semantic tools is both reliable and useful. Copyright © 2011 Elsevier Inc. All rights reserved.

Lane detection based on color probability model and fuzzy clustering

NASA Astrophysics Data System (ADS)

Yu, Yang; Jo, Kang-Hyun

2018-04-01

In the vehicle driver assistance systems, the accuracy and speed of lane line detection are the most important. This paper is based on color probability model and Fuzzy Local Information C-Means (FLICM) clustering algorithm. The Hough transform and the constraints of structural road are used to detect the lane line accurately. The global map of the lane line is drawn by the lane curve fitting equation. The experimental results show that the algorithm has good robustness.

Image and flow cytometric analysis of gold nanoparticle uptake by macrophages

NASA Astrophysics Data System (ADS)

Fixler, Dror; Ankri, Rinat; Weiss, Ronald; Grahnert, Anja; Melzer, Susanne; Tárnok, Attila

2016-03-01

Background/Aim: In atherosclerosis stable and vulnerable atherosclerotic plaque types are distinguished that behave differently concerning rupture, thrombosis and clinical events. The stable are rich in M2 macrophages. The unstable are rich in inflammatory M1 macrophages and are highly susceptible to rupture, setting patients at risk for thrombotic events when they undergo invasive diagnosis such as coronary angiography. Therefore, novel approaches for non-invasive detection and classification of vulnerable plaques in vivo are needed. Whereas classical approaches fail to differentiate between both plaque types, a new biophotonic method (combination of the diffusion reflection (DR) method with flow cytometry (FCM) or image cytometry (IC)) to analyze gold nanoparticle (GNP) loading of plaques could overcome this limitation. Methods: Two types of GNP were used three variants of gold nanorods (GNRI with 40x18 nm, II 65x25 nm and III 52x13 nm in size) and gold nanospheres (GNS with an average diameter of 18.5 nm). The GNS had an absorption peak at 520 nm and the GNR at 630 nm. Monocytes were isolated from human buffy blood samples, differentiated into macrophages and their subtypes and labelled with GNR and GNS for 3 and 24 h. GNS and GNR loading were determined by FCM and/or IC. Macrophages within tissue-like phantoms were analyzed by the DR system. Results: After GNR labelling of macrophages the FCM light scatter values increased up to 3.7 fold and the DR slope changed from an average slope of 0.196 (macrophages only) to an average slope of 0.827 (macrophages labelled with GNR). But, GNRIII did not present much higher DR slopes than the control phantoms, indicating that macrophages take up GNRIII in a lower amount than GNRI or II. IC and microscopy showed that all particle variants were taken up by the cells in a heterogeneous fashion. Conclusion and outlook: The combination of FCM and DR measurements provides a potential novel, highly sensitive and non-invasive method for the identification of atherosclerotic vulnerable plaques, aimed to develop a potential tool for in vivo tracking. Further experiments will show, if different macrophage subtypes (M1 or M2) take up the particles differently and may thereby serve to distinguish stable from vulnerable plaques.

The sensitive hare: sublethal effects of predator stress on reproduction in snowshoe hares.

PubMed

Sheriff, Michael J; Krebs, Charles J; Boonstra, Rudy

2009-11-01

1. Prey responses to high predation risk can be morphological or behavioural and ultimately come at the cost of survival, growth, body condition, or reproduction. These sub-lethal predator effects have been shown to be mediated by physiological stress. We tested the hypothesis that elevated glucocorticoid concentrations directly cause a decline in reproduction in individual free-ranging female snowshoe hares, Lepus americanus. We measured the cortisol concentration from each dam (using a faecal analysis enzyme immunoassay) and her reproductive output (litter size, offspring birth mass, offspring right hind foot (RHF) length) 30 h after birth. 2. In a natural monitoring study, we monitored hares during the first and second litter from the population peak (2006) to the second year of the decline (2008). We found that faecal cortisol metabolite (FCM) concentration in dams decreased 52% from the first to the second litter. From the first to the second litter, litter size increased 122%, offspring body mass increased 130%, and offspring RHF length increased 112%. Dam FCM concentrations were inversely related to litter size (r(2) = 0.19), to offspring birth mass (r(2) = 0.32), and to offspring RHF length (r(2) = 0.64). 3. In an experimental manipulation, we assigned wild-caught, pregnant hares to a control and a stressed group and held them in pens. Hares in the stressed group were exposed to a dog 1-2 min every other day before parturition to simulate high predation risk. At parturition, unsuccessful-stressed dams (those that failed to give birth to live young) and stressed dams had 837% and 214%, respectively, higher FCM concentrations than control dams. Of those females that gave birth, litter size was similar between control and stressed dams. However, offspring from stressed dams were 37% lighter and 16% smaller than offspring from control dams. Increasing FCM concentration in dams caused the decline of offspring body mass (r(2) = 0.57) and RHF (r(2) = 0.52). 4. This is the first study in a free-ranging population of mammals to show that elevated, predator-induced, glucocorticoid concentrations in individual dams caused a decline in their reproductive output measured both by number and quality of offspring. Thus, we provide evidence that any stressor, not just predation, which increases glucocorticoid concentrations will result in a decrease in reproductive output.

Tailored Algorithm for Sensitivity Enhancement of Gas Concentration Sensors Based on Tunable Laser Absorption Spectroscopy.

PubMed

Vargas-Rodriguez, Everardo; Guzman-Chavez, Ana Dinora; Baeza-Serrato, Roberto

2018-06-04

In this work, a novel tailored algorithm to enhance the overall sensitivity of gas concentration sensors based on the Direct Absorption Tunable Laser Absorption Spectroscopy (DA-ATLAS) method is presented. By using this algorithm, the sensor sensitivity can be custom-designed to be quasi constant over a much larger dynamic range compared with that obtained by typical methods based on a single statistics feature of the sensor signal output (peak amplitude, area under the curve, mean or RMS). Additionally, it is shown that with our algorithm, an optimal function can be tailored to get a quasi linear relationship between the concentration and some specific statistics features over a wider dynamic range. In order to test the viability of our algorithm, a basic C 2 H 2 sensor based on DA-ATLAS was implemented, and its experimental measurements support the simulated results provided by our algorithm.

Classifying epileptic EEG signals with delay permutation entropy and Multi-Scale K-means.

PubMed

Zhu, Guohun; Li, Yan; Wen, Peng Paul; Wang, Shuaifang

2015-01-01

Most epileptic EEG classification algorithms are supervised and require large training datasets, that hinder their use in real time applications. This chapter proposes an unsupervised Multi-Scale K-means (MSK-means) MSK-means algorithm to distinguish epileptic EEG signals and identify epileptic zones. The random initialization of the K-means algorithm can lead to wrong clusters. Based on the characteristics of EEGs, the MSK-means MSK-means algorithm initializes the coarse-scale centroid of a cluster with a suitable scale factor. In this chapter, the MSK-means algorithm is proved theoretically superior to the K-means algorithm on efficiency. In addition, three classifiers: the K-means, MSK-means MSK-means and support vector machine (SVM), are used to identify seizure and localize epileptogenic zone using delay permutation entropy features. The experimental results demonstrate that identifying seizure with the MSK-means algorithm and delay permutation entropy achieves 4. 7 % higher accuracy than that of K-means, and 0. 7 % higher accuracy than that of the SVM.

Integrated G and C Implementation within IDOS: A Simulink Based Reusable Launch Vehicle Simulation

NASA Technical Reports Server (NTRS)

Fisher, Joseph E.; Bevacqua, Tim; Lawrence, Douglas A.; Zhu, J. Jim; Mahoney, Michael

2003-01-01

The implementation of multiple Integrated Guidance and Control (IG&C) algorithms per flight phase within a vehicle simulation poses a daunting task to coordinate algorithm interactions with the other G&C components and with vehicle subsystems. Currently being developed by Universal Space Lines LLC (USL) under contract from NASA, the Integrated Development and Operations System (IDOS) contains a high fidelity Simulink vehicle simulation, which provides a means to test cutting edge G&C technologies. Combining the modularity of this vehicle simulation and Simulink s built-in primitive blocks provide a quick way to implement algorithms. To add discrete-event functionality to the unfinished IDOS simulation, Vehicle Event Manager (VEM) and Integrated Vehicle Health Monitoring (IVHM) subsystems were created to provide discrete-event and pseudo-health monitoring processing capabilities. Matlab's Stateflow is used to create the IVHM and Event Manager subsystems and to implement a supervisory logic controller referred to as the Auto-commander as part of the IG&C to coordinate the control system adaptation and reconfiguration and to select the control and guidance algorithms for a given flight phase. Manual creation of the Stateflow charts for all of these subsystems is a tedious and time-consuming process. The Stateflow Auto-builder was developed as a Matlab based software tool for the automatic generation of a Stateflow chart from information contained in a database. This paper describes the IG&C, VEM and IVHM implementations in IDOS. In addition, this paper describes the Stateflow Auto-builder.

Open source clustering software.

PubMed

de Hoon, M J L; Imoto, S; Nolan, J; Miyano, S

2004-06-12

We have implemented k-means clustering, hierarchical clustering and self-organizing maps in a single multipurpose open-source library of C routines, callable from other C and C++ programs. Using this library, we have created an improved version of Michael Eisen's well-known Cluster program for Windows, Mac OS X and Linux/Unix. In addition, we generated a Python and a Perl interface to the C Clustering Library, thereby combining the flexibility of a scripting language with the speed of C. The C Clustering Library and the corresponding Python C extension module Pycluster were released under the Python License, while the Perl module Algorithm::Cluster was released under the Artistic License. The GUI code Cluster 3.0 for Windows, Macintosh and Linux/Unix, as well as the corresponding command-line program, were released under the same license as the original Cluster code. The complete source code is available at http://bonsai.ims.u-tokyo.ac.jp/mdehoon/software/cluster. Alternatively, Algorithm::Cluster can be downloaded from CPAN, while Pycluster is also available as part of the Biopython distribution.

Scene-based nonuniformity correction with reduced ghosting using a gated LMS algorithm.

PubMed

Hardie, Russell C; Baxley, Frank; Brys, Brandon; Hytla, Patrick

2009-08-17

In this paper, we present a scene-based nouniformity correction (NUC) method using a modified adaptive least mean square (LMS) algorithm with a novel gating operation on the updates. The gating is designed to significantly reduce ghosting artifacts produced by many scene-based NUC algorithms by halting updates when temporal variation is lacking. We define the algorithm and present a number of experimental results to demonstrate the efficacy of the proposed method in comparison to several previously published methods including other LMS and constant statistics based methods. The experimental results include simulated imagery and a real infrared image sequence. We show that the proposed method significantly reduces ghosting artifacts, but has a slightly longer convergence time. (c) 2009 Optical Society of America

Glycaemic control and implementation of the ADA/EASD-2006 consensus algorithm in type 2 diabetes mellitus patients in primary care in Spain.

PubMed

Alvarez-Guisasola, F

2014-01-01

In 2006, the American Diabetes Association and the European Association for the Study of Diabetes established a consensus algorithm (ADA/EASD-2006) for the adjustment of drug therapy for type 2 diabetes mellitus (T2DM). To study glycaemic control in T2DM patients and the implementation of the ADA/EASD-2006 recommendations in primary care centres in Spain. Prospective observational study in 1194 patients with T2DM conducted in 250 primary care centres in Spain. Patients were assessed at study inclusion (V0) and at 3 (V1) and 6 months (V2) post baseline. Information was collected at the level of DM control, HbA(1c) < 7% (HbC) and implementation of the ADA/EASD-2006 guidelines. Type 2 diabetes mellitus patients (53% women; mean age 64.9 years) had a mean (SD) HbA(1c) 7.8 (1.4)% and HbC 25.2% at baseline, 95% of them were receiving oral antihyperglycaemic agents (AAs) only. At V1, HbA(1c) was 7.3 (1.1)% and HbC was 38.1%; 65.0% of patients were receiving oral AAs, 5.6% insulin and 27.9% oral AAs plus insulin. At V2, HbA(1c) was 7.1 (0.9)% and HbC was 48.0%; 57.1% of patients were receiving oral AAs, 5.0% insulin and 36.9% oral AAs plus insulin. The ADA/EASD-2006 algorithm was adhered to in 33% patients up to study month 3, vs. 17.2% throughout the entire 6-month period. In patients with T2DM seen in primary care, the HbA1c target was met in 48.0% after adjusting their AAs. However, this is not reflected in greater implementation of the ADA/EASD-2006 guidelines, which are adhered to in only 17%. © 2013 John Wiley & Sons Ltd.

Are judgments a form of data clustering? Reexamining contrast effects with the k-means algorithm.

PubMed

Boillaud, Eric; Molina, Guylaine

2015-04-01

A number of theories have been proposed to explain in precise mathematical terms how statistical parameters and sequential properties of stimulus distributions affect category ratings. Various contextual factors such as the mean, the midrange, and the median of the stimuli; the stimulus range; the percentile rank of each stimulus; and the order of appearance have been assumed to influence judgmental contrast. A data clustering reinterpretation of judgmental relativity is offered wherein the influence of the initial choice of centroids on judgmental contrast involves 2 combined frequency and consistency tendencies. Accounts of the k-means algorithm are provided, showing good agreement with effects observed on multiple distribution shapes and with a variety of interaction effects relating to the number of stimuli, the number of response categories, and the method of skewing. Experiment 1 demonstrates that centroid initialization accounts for contrast effects obtained with stretched distributions. Experiment 2 demonstrates that the iterative convergence inherent to the k-means algorithm accounts for the contrast reduction observed across repeated blocks of trials. The concept of within-cluster variance minimization is discussed, as is the applicability of a backward k-means calculation method for inferring, from empirical data, the values of the centroids that would serve as a representation of the judgmental context. (c) 2015 APA, all rights reserved.

Differences between true mean daily, monthly and annual air temperatures and air temperatures calculated with three equations: a case study from three Croatian stations

NASA Astrophysics Data System (ADS)

Bonacci, Ognjen; Željković, Ivana; Trogrlić, Robert Šakić; Milković, Janja

2013-10-01

Differences between true mean daily, monthly and annual air temperatures T0 [Eq. (1)] and temperatures calculated with three different equations [(2), (3) and (4)] (commonly used in climatological practice) were investigated at three main meteorological Croatian stations from 1 January 1999 to 31 December 2011. The stations are situated in the following three climatically distinct areas: (1) Zagreb-Grič (mild continental climate), (2) Zavižan (cold mountain climate), and (3) Dubrovnik (hot Mediterranean climate). T1 [Eq. (2)] and T3 [Eq. (4)] mean temperatures are defined by the algorithms based on the weighted means of temperatures measured at irregularly spaced, yet fixed hours. T2 [Eq. (3)] is the mean temperature defined as the average of daily maximum and minimum temperature. The equation as well as the time of observations used introduces a bias into mean temperatures. The largest differences occur for mean daily temperatures. The calculated daily difference value from all three equations and all analysed stations varies from -3.73 °C to +3.56 °C, from -1.39 °C to +0.79 °C for monthly differences and from -0.76 °C to +0.30 °C for annual differences.

77 FR 16025 - Combined Notice of Filings #1

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-19

...: Wolverine Power Supply Cooperative, Inc. Description: Amendment to Application of Wolverine Power Supply...: ER12-547-001. Applicants: Auburndale Power Partners, Limited Partnership. Description: Auburndale Power...: ISO New England Inc., New England Power Pool Participants Committee. Description: Revisions to FCM...

Layer Structured Bismuth Selenides of Bi₂Se₃ and Bi₃Se₄ for High Energy and Flexible All-Solid-State Micro-Supercapacitors.

PubMed

Hao, Chunxue; Wang, Lidan; Wen, Fusheng; Xiang, Jianyong; Li, Lei; Hu, Wentao; Liu, Zhongyuan

2017-12-20

Bismuth selenides (Bi2Se3 and Bi3Se4), both of which have the layered rhombohedral crystal structure, and found to be useful as electrode materials for supercapacitor application in this work. Bi2Se3 nanoplates as electrode material exhibit much better performance than that of Bi3Se4 nanoparticles in liquid electrolyte system (6 M KOH), which delivers a higher specific capacitance (272.9 F/g) than that of Bi3Se4 (193.6 F/g) at 5 mV/s. This result would may be attributed to that Bi2Se3 nanoplates possess more active electrochemical surfaces for the reversible surface redox reactions owing to its planar quintuple stacked layers (septuple layers for Bi3Se4). For the demand of electronic skin, we used a novel flexible annular interdigital structure electrode applying for all-solid-state micro-supercapacitors (AMSCs). Bi2Se3 AMSCs device delivers a much more excellent supercapacitor performance, exhibits a large stack capacitance 89.5 F/cm3 (Bi3Se4: 79.1 F/cm3) at 20 mV/s, a high energy density 17.9 mWh/cm3 and high power density 18.9 W/cm3. The bismuth selenides also exhibit good cycle stability, retention 95.5% (90.3%) after 1000 c for Bi2Se3 (Bi3Se4). Obviously, Bi2Se3 nanoplates can be promising electrode materials for flexible annular interdigital all-solid-sate supercapacitor. © 2017 IOP Publishing Ltd.

Enhancement of methane production from co-digestion of chicken manure with agricultural wastes.

PubMed

Abouelenien, Fatma; Namba, Yuzaburo; Kosseva, Maria R; Nishio, Naomichi; Nakashimada, Yutaka

2014-05-01

The potential for methane production from semi-solid chicken manure (CM) and mixture of agricultural wastes (AWS) in a co-digestion process has been experimentally evaluated at thermophilic and mesophilic temperatures. To the best of author(')s knowledge, it is the first time that CM is co-digested with mixture of AWS consisting of coconut waste, cassava waste, and coffee grounds. Two types of anaerobic digestion processes (AD process) were used, process 1 (P1) using fresh CM (FCM) and process 2 (P2) using treated CM (TCM), ammonia stripped CM, were conducted. Methane production in P1 was increased by 93% and 50% compared to control (no AWS added) with maximum methane production of 502 and 506 mL g(-1)VS obtained at 55°C and 35°C, respectively. Additionally, 42% increase in methane production was observed with maximum volume of 695 mL g(-1)VS comparing P2 test with P2 control under 55°C. Ammonia accumulation was reduced by 39% and 32% in P1 and P2 tests. Copyright © 2014 Elsevier Ltd. All rights reserved.

A comparison between simplified and intensive dose-titration algorithms using AIR inhaled insulin for insulin-naive patients with type 2 diabetes in a randomized noninferiority trial.

PubMed

Mathieu, C; Cuddihy, R; Arakaki, R F; Belin, R M; Planquois, J-M; Lyons, J N; Heilmann, C R

2009-09-01

Insulin initiation and optimization is a challenge for patients with type 2 diabetes. Our objective was to determine whether safety and efficacy of AIR inhaled insulin (Eli Lilly and Co., Indianapolis, IN) (AIR is a registered trademark of Alkermes, Inc., Cambridge, MA) using a simplified regimen was noninferior to an intensive regimen. This was an open-label, randomized study in insulin-naive adults not optimally controlled by oral antihyperglycemic medications. Simplified titration included a 6 U per meal AIR insulin starting dose. Individual doses were adjusted at mealtime in 2-U increments from the previous day's four-point self-monitored blood glucose (SMBG) (total < or =6 U). Starting Air insulin doses for intensive titration were based on fasting blood glucose, gender, height, and weight. Patients conducted four-point SMBG daily for the study duration. Insulin doses were titrated based on the previous 3 days' mean SMBG (total < or =8 U). End point hemoglobin A1C (A1C) was 7.07 +/- 0.09% and 6.87 +/- 0.09% for simplified (n = 178) and intensive (n = 180) algorithms, respectively. Noninferiority between algorithms was not established. The fasting blood glucose (least squares mean +/- standard error) values for the simplified (137.27 +/- 3.42 mg/dL) and intensive (133.13 +/- 3.42 mg/dL) algorithms were comparable. Safety profiles were comparable. The hypoglycemic rate at 4, 8, 12, and 24 weeks was higher in patients receiving intensive titration (all P < .0001). The nocturnal hypoglycemic rate for patients receiving intensive titration was higher than for those receiving simplified titration at 8 (P < 0.015) and 12 weeks (P < 0.001). Noninferiority between the algorithms, as measured by A1C, was not demonstrated. This finding re-emphasizes the difficulty of identifying optimal, simplified insulin regimens for patients.

A Parametric k-Means Algorithm

PubMed Central

Tarpey, Thaddeus

2007-01-01

Summary The k points that optimally represent a distribution (usually in terms of a squared error loss) are called the k principal points. This paper presents a computationally intensive method that automatically determines the principal points of a parametric distribution. Cluster means from the k-means algorithm are nonparametric estimators of principal points. A parametric k-means approach is introduced for estimating principal points by running the k-means algorithm on a very large simulated data set from a distribution whose parameters are estimated using maximum likelihood. Theoretical and simulation results are presented comparing the parametric k-means algorithm to the usual k-means algorithm and an example on determining sizes of gas masks is used to illustrate the parametric k-means algorithm. PMID:17917692

Triso coating development progress for uranium nitride kernels

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

Jolly, Brian C.; Lindemer, Terrence; Terrani, Kurt A.

2015-08-01

In support of fully ceramic matrix (FCM) fuel development [1-2], coating development work is ongoing at the Oak Ridge National Laboratory (ORNL) to produce tri-structural isotropic (TRISO) coated fuel particles with UN kernels [3]. The nitride kernels are used to increase fissile density in these SiC-matrix fuel pellets with details described elsewhere [4]. The advanced gas reactor (AGR) program at ORNL used fluidized bed chemical vapor deposition (FBCVD) techniques for TRISO coating of UCO (two phase mixture of UO2 and UCx) kernels [5]. Similar techniques were employed for coating of the UN kernels, however significant changes in processing conditions weremore » required to maintain acceptable coating properties due to physical property and dimensional differences between the UCO and UN kernels (Table 1).« less

Prediction of the compression ratio for municipal solid waste using decision tree.

PubMed

Heshmati R, Ali Akbar; Mokhtari, Maryam; Shakiba Rad, Saeed

2014-01-01

The compression ratio of municipal solid waste (MSW) is an essential parameter for evaluation of waste settlement and landfill design. However, no appropriate model has been proposed to estimate the waste compression ratio so far. In this study, a decision tree method was utilized to predict the waste compression ratio (C'c). The tree was constructed using Quinlan's M5 algorithm. A reliable database retrieved from the literature was used to develop a practical model that relates C'c to waste composition and properties, including dry density, dry weight water content, and percentage of biodegradable organic waste using the decision tree method. The performance of the developed model was examined in terms of different statistical criteria, including correlation coefficient, root mean squared error, mean absolute error and mean bias error, recommended by researchers. The obtained results demonstrate that the suggested model is able to evaluate the compression ratio of MSW effectively.

Generalized Split-Window Algorithm for Estimate of Land Surface Temperature from Chinese Geostationary FengYun Meteorological Satellite (FY-2C) Data.

PubMed

Tang, Bohui; Bi, Yuyun; Li, Zhao-Liang; Xia, Jun

2008-02-14

On the basis of the radiative transfer theory, this paper addressed the estimate ofLand Surface Temperature (LST) from the Chinese first operational geostationarymeteorological satellite-FengYun-2C (FY-2C) data in two thermal infrared channels (IR1,10.3-11.3 μ m and IR2, 11.5-12.5 μ m ), using the Generalized Split-Window (GSW)algorithm proposed by Wan and Dozier (1996). The coefficients in the GSW algorithmcorresponding to a series of overlapping ranging of the mean emissivity, the atmosphericWater Vapor Content (WVC), and the LST were derived using a statistical regressionmethod from the numerical values simulated with an accurate atmospheric radiativetransfer model MODTRAN 4 over a wide range of atmospheric and surface conditions.The simulation analysis showed that the LST could be estimated by the GSW algorithmwith the Root Mean Square Error (RMSE) less than 1 K for the sub-ranges with theViewing Zenith Angle (VZA) less than 30° or for the sub-rangs with VZA less than 60°and the atmospheric WVC less than 3.5 g/cm² provided that the Land Surface Emissivities(LSEs) are known. In order to determine the range for the optimum coefficients of theGSW algorithm, the LSEs could be derived from the data in MODIS channels 31 and 32 provided by MODIS/Terra LST product MOD11B1, or be estimated either according tothe land surface classification or using the method proposed by Jiang et al. (2006); and theWVC could be obtained from MODIS total precipitable water product MOD05, or beretrieved using Li et al.' method (2003). The sensitivity and error analyses in term of theuncertainty of the LSE and WVC as well as the instrumental noise were performed. Inaddition, in order to compare the different formulations of the split-window algorithms,several recently proposed split-window algorithms were used to estimate the LST with thesame simulated FY-2C data. The result of the intercomparsion showed that most of thealgorithms give comparable results.

Comparison of aerosol optical depth from satellite (MODIS), sun photometer and broadband pyrheliometer ground-based observations in Cuba

NASA Astrophysics Data System (ADS)

Antuña-Marrero, Juan Carlos; Cachorro Revilla, Victoria; García Parrado, Frank; de Frutos Baraja, Ángel; Rodríguez Vega, Albeth; Mateos, David; Estevan Arredondo, René; Toledano, Carlos

2018-04-01

In the present study, we report the first comparison between the aerosol optical depth (AOD) and Ångström exponent (AE) of the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the Terra (AODt) and Aqua (AODa) satellites and those measured using a sun photometer (AODSP) at Camagüey, Cuba, for the period 2008 to 2014. The comparison of Terra and Aqua data includes AOD derived with both deep blue (DB) and dark target (DT) algorithms from MODIS Collection 6. Combined Terra and Aqua (AODta) data were also considered. Assuming an interval of ±30 min around the overpass time and an area of 25 km around the sun photometer site, two coincidence criteria were considered: individual pairs of observations and both spatial and temporal mean values, which we call collocated daily means. The usual statistics (root mean square error, RMSE; mean absolute error, MAE; median bias, BIAS), together with linear regression analysis, are used for this comparison. Results show very similar values for both coincidence criteria: the DT algorithm generally displays better statistics and higher homogeneity than the DB algorithm in the behaviour of AODt, AODa, AODta compared to AODSP. For collocated daily means, (a) RMSEs of 0.060 and 0.062 were obtained for Terra and Aqua with the DT algorithm and 0.084 and 0.065 for the DB algorithm, (b) MAE follows the same patterns, (c) BIAS for both Terra and Aqua presents positive and negative values but its absolute values are lower for the DT algorithm; (d) combined AODta data also give lower values of these three statistical indicators for the DT algorithm; (e) both algorithms present good correlations for comparing AODt, AODa, AODta vs. AODSP, with a slight overestimation of satellite data compared to AODSP, (f). The DT algorithm yields better figures with slopes of 0.96 (Terra), 0.96 (Aqua) and 0.96 (Terra + Aqua) compared to the DB algorithm (1.07, 0.90, 0.99), which displays greater variability. Multi-annual monthly means of AODta establish a first climatology that is more comparable to that given by the sun photometer and their statistical evaluation reveals better agreement with AODSP for the DT algorithm. Results of the AE comparison showed similar results to those reported in the literature concerning the two algorithms' capacity for retrieval. A comparison between broadband aerosol optical depth (BAOD), derived from broadband pyrheliometer observations at the Camagüey site and three other meteorological stations in Cuba, and AOD observations from MODIS on board Terra and Aqua show a poor correlation with slopes below 0.4 for both algorithms. Aqua (Terra) showed RMSE values of 0.073 (0.080) and 0.088 (0.087) for the DB and DT algorithms. As expected, RMSE values are higher than those from the MODIS-sun photometer comparison, but within the same order of magnitude. Results from the BAOD derived from solar radiation measurements demonstrate its reliability in describing climatological AOD series estimates.

Latest advances in confocal microscopy of skin cancers toward guiding patient care: a Mohs surgeon's review and perspective (Conference Presentation)

NASA Astrophysics Data System (ADS)

Nehal, Kishwer S.; Rajadhyaksha, Milind

2016-02-01

Latest advances in confocal microscopy of skin cancers toward guiding patient care: a Mohs surgeon's review and perspective About 350 publications worldwide have reported the ability of reflectance confocal microscopy (RCM) imaging to detect melanocytic skin lesions in vivo with specificity of 84-88% and sensitivity of 71-92%, and non-melanocytic skin lesions with specificity of 85-97% and sensitivity 100-92%. Lentigo maligna melanoma can be detected with sensitivity of 93% and specificity 82%. While the sensitivity is comparable to that of dermoscopy, the specificity is 2X superior, especially for lightly- and non-pigmented lesions. Dermoscopy combined with RCM imaging is proving to be both highly sensitive and highly specific. Recent studies have reported that the ratio of equivocal (i.e., would have been biopsied) lesions to detected melanomas dropped by ~2X when guided by dermoscopy and RCM imaging, compared to that with dermoscopy alone. Dermoscopy combined with RCM imaging is now being implemented to guide noninvasive diagnosis (to rule out malignancy and biopsy) and to also guide treatment, with promising initial impact: thus far, about 3,000 patients have been saved from biopsies of benign lesions. These are currently under follow-up monitoring. With fluorescence confocal microscopy (FCM) mosaicing, residual basal cell carcinomas can be detected in Mohs surgically excised fresh tissue ex vivo, with sensitivity of 94-97% and specificity 89-94%. FCM mosaicing is now being implemented for guiding Mohs surgery. To date, about 600 Mohs procedures have been performed, guided with mosaicing, and with pathology being performed in parallel to confirm the final outcome. These latest advances demonstrate the promising ability of RCM and FCM to guide patient care.

Effects of assimilable organic carbon and free chlorine on bacterial growth in drinking water.

PubMed

Liu, Xiaolu; Wang, Jingqi; Liu, Tingting; Kong, Weiwen; He, Xiaoqing; Jin, Yi; Zhang, Bolin

2015-01-01

Assimilable organic carbon (AOC) is one of the most important factors affecting the re-growth of microorganisms in drinking water. High AOC concentrations result in biological instability, but disinfection kills microbes to ensure the safety of drinking water. Free chlorine is an important oxidizing agent used during the disinfection process. Therefore, we explored the combined effects of AOC and free chlorine on bacterial growth in drinking water using flow cytometry (FCM). The initial AOC concentration was 168 μg.L(-1) in all water samples. Without free chlorine, the concentrations of intact bacteria increased but the level of AOC decreased. The addition of sodium hypochlorite caused an increase and fluctuation in AOC due to the oxidation of organic carbon. The concentrations of intact bacteria decreased from 1.1 × 10(5) cells.mL(-1) to 2.6 × 10(4) cells.mL(-1) at an initial free chlorine dose of 0.6 mg.L(-1) to 4.8 × 10(4) cells.mL(-1) at an initial free chlorine dose of 0.3 mg.L(-1) due to free chlorine originating from sodium hypochlorite. Additionally, free chlorine might be more obviously affected AOC concentrations than microbial growth did. These results suggested that AOC and free chlorine might have combined effects on microbial growth. In this study, our results showed concentrations determined by FCM were higher than those by HPC, which indicated that some E. coli detected by FCM might not be detected using HPC in drinking water. The level of free chlorine might restrain the consumption of AOC by inhibiting the growth of E. coli; on the other hand, chlorination might increase the level of AOC, thereby increase the potential for microbial growth in the drinking water network.

Effects of Assimilable Organic Carbon and Free Chlorine on Bacterial Growth in Drinking Water

PubMed Central

Liu, Tingting; Kong, Weiwen; He, Xiaoqing; Jin, Yi; Zhang, Bolin

2015-01-01

Assimilable organic carbon (AOC) is one of the most important factors affecting the re-growth of microorganisms in drinking water. High AOC concentrations result in biological instability, but disinfection kills microbes to ensure the safety of drinking water. Free chlorine is an important oxidizing agent used during the disinfection process. Therefore, we explored the combined effects of AOC and free chlorine on bacterial growth in drinking water using flow cytometry (FCM). The initial AOC concentration was 168 μg.L-1 in all water samples. Without free chlorine, the concentrations of intact bacteria increased but the level of AOC decreased. The addition of sodium hypochlorite caused an increase and fluctuation in AOC due to the oxidation of organic carbon. The concentrations of intact bacteria decreased from 1.1×105 cells.mL-1 to 2.6×104 cells.mL-1 at an initial free chlorine dose of 0.6 mg.L-1 to 4.8×104 cells.mL-1 at an initial free chlorine dose of 0.3 mg.L-1 due to free chlorine originating from sodium hypochlorite. Additionally, free chlorine might be more obviously affected AOC concentrations than microbial growth did. These results suggested that AOC and free chlorine might have combined effects on microbial growth. In this study, our results showed concentrations determined by FCM were higher than those by HPC, which indicated that some E. coli detected by FCM might not be detected using HPC in drinking water. The level of free chlorine might restrain the consumption of AOC by inhibiting the growth of E. coli; on the other hand, chlorination might increase the level of AOC, thereby increase the potential for microbial growth in the drinking water network. PMID:26034988

Long-Term Effects of Residual Chlorine on Pseudomonas aeruginosa in Simulated Drinking Water Fed With Low AOC Medium

PubMed Central

Mao, Guannan; Song, Yuhao; Bartlam, Mark; Wang, Yingying

2018-01-01

Residual chlorine is often required to remain present in public drinking water supplies during distribution to ensure water quality. It is essential to understand how bacteria respond to long-term chlorine exposure, especially with the presence of assimilable organic carbon (AOC). This study aimed to investigate the effects of chlorination on Pseudomonas aeruginosa in low AOC medium by both conventional plating and culture-independent methods including flow cytometry (FCM) and quantitative PCR (qPCR). In a simulated chlorinated system using a bioreactor, membrane damage and DNA damage were measured by FCM fluorescence fingerprint. The results indicated membrane permeability occurred prior to DNA damage in response to chlorination. A regrowth of P. aeruginosa was observed when the free chlorine concentration was below 0.3 mg/L. The bacterial response to long-term exposure to a constant low level of free chlorine (0.3 mg/L) was subsequently studied in detail. Both FCM and qPCR data showed a substantial reduction during initial exposure (0–16 h), followed by a plateau where the cell concentration remained stable (16–76 h), until finally all bacteria were inactivated with subsequent continuous chlorine exposure (76–124 h). The results showed three-stage inactivation kinetics for P. aeruginosa at a low chlorine level with extended exposure time: an initial fast inactivation stage, a relatively stable middle stage, and a final stage with a slower rate than the initial stage. A series of antibiotic resistance tests suggested long-term exposure to low chlorine level led to the selection of antibiotic-resistant P. aeruginosa. The combined results suggest that depletion of residual chlorine in low AOC medium systems could reactivate P. aeruginosa, leading to a possible threat to drinking water safety. PMID:29774019

Chemokine CCL28 induces apoptosis of decidual stromal cells via binding CCR3/CCR10 in human spontaneous abortion.

PubMed

Sun, Chan; Zhang, Yuan-Yuan; Tang, Chuan-Ling; Wang, Song-Cun; Piao, Hai-Lan; Tao, Yu; Zhu, Rui; Du, Mei-Rong; Li, Da-Jin

2013-10-01

Spontaneous abortion is the most common complication of pregnancy. Immune activation and the subsequent inflammation-induced tissue injury are often observed at the maternal-fetal interface as the final pathological assault in recurrent spontaneous abortion. However, the precise mechanisms responsible for spontaneous abortion involving inflammation are not fully understood. Chemokine CCL28 and its receptors CCR3 and CCR10 are important regulators in inflammatory process. Here, we examined the expression of CCL28 and its receptors in decidual stromal cells (DSCs) by immunochemistry and flow cytometry (FCM), and compared their expression level in DSCs from normal pregnancy versus spontaneous abortion, and their relationship to inflammatory cytokines production by DSCs. We further analyzed regulation of the pro-inflammatory cytokines on CCL28 expression in DSCs by real-time polymerase chain reaction, In-cell Western and FCM. The effects of CCL28-CCR3/CCR10 interaction on DSC apoptosis was investigated by Annexin V staining and FCM analysis or DAPI staining and nuclear morphology. Higher levels of the inflammatory cytokines interleukin (IL)-1β, IL-17A and tumor necrosis factor-α, and increased CCR3/CCR10 expression were observed in DSCs from spontaneous abortion compared with normal pregnancy. Treatment with inflammatory cytokines differently affected CCL28 and CCR3/CCR10 expression in DSCs. Human recombinant CCL28 promoted DSC apoptosis, which was eliminated by pretreatment with neutralizing antibodies against CCR3/CCR10 and CCL28. However, CCL28 did not affect DSC growth. These results suggest that the inflammation-promoted up-regulation of CCL28 and its receptors interaction in DSCs is involved in human spontaneous abortion via inducing DSC apoptosis.

[The Enhanceing effect of IL-12 on phagocytosis and killing of Mycobacterium tuberculosis by neutrophils in tuberculosis patients].

PubMed

Jiang, Li-na; Yao, Chun-yan; Jin, Qi-li; He, Wen-xin; Li, Bai-qing

2011-11-01

To explore the effects of IL-12 on phagocytosis and killing of Mycobacterium tuberculosis by neutrophils or polymorphonuclear cells (PMNs) in tuberculosis patients. The fresh peripheral blood samples from TB patients and healthy adults were incubated with M.tb labeled with FITC, and the percentages of phagocytosis of M.tb by PMNs was measured by flow cytometry (FCM). The fresh peripheral blood samples were incubated with DCFH-DA, and with or without M.tb for different times, the percentage of activation and the ROS production of PMNs were measured by FCM. Whole blood samples were pretreated with IL-12, the changes of phagocytosis, activation and ROS production of PMNs were measured by FCM. The percentages of phagocytosis by PMNs, activation and ROS production of PMNs in both TB patients and healthy adults increased dependent on the time of incubation with M.tb. Only the phagocytosis of M.tb by PMNs at 5 min in TB patients of tuberculosis patients (51.82±6.93)% was obviously higher than that in healthy adults (47.20±4.26)%, (P<0.05). Pretreatment of whole blood with IL-12 before incubation with M.tb, the percentages of phagocytosis, activation and ROS production of PMNs in both TB patients and healthy adults increased in dose dependent manner, but no significant difference was found between both groups. The results indicated that the phagocytosis of M.tb and ROS production by PMNs in TB patients were almost the same as that in healthy controls, except for phagocytosis is higher at early stage. Furthermore, IL-12 can enhance the responsiveness to the phagocytosis and ROS production of PMNs.

Welfare indicators in laying hens in relation to nest exclusion.

PubMed

Alm, M; Tauson, R; Holm, L; Wichman, A; Kalliokoski, O; Wall, H

2016-06-01

Consumer concerns about the welfare of laying hens are increasing, leading to increased interest in identifying reliable ways to assess welfare. The present study evaluated invasive and non-invasive welfare indicators in relation to a stressful challenge. The study included 126 Lohmann Selected Leghorn hens housed in furnished cages. Welfare indicators were measured between 61 and 70 wk of age in birds excluded from their nests for 5 consecutive d and control birds that had continuous access to nests. Baseline recordings were carried out in both groups prior to and post exclusion period. The assessed indicators were: corticosterone metabolites in droppings (FCM), corticosterone concentration in yolk, corticosterone concentration in plasma, irregularities of eggshells, heterophil to lymphocyte (H:L) ratio, tonic immobility duration, and feather cover. Behavioral observations showed that the birds had a clear preference for using the secluded nest sites, confirming that they were likely to perceive nest exclusion as an undesirable experience. Further, elevated levels of FCM in droppings, yolk corticosterone concentrations, H:L ratios and irregular eggshells were detected in both nest deprived and control birds during the exclusion. This suggests that these indicators were able to detect an increased stress response arising from nest deprivation, and it is hypothesized that the stress spread to birds in adjacent cages with access to nests. There was a positive and consistent correlation between FCM in droppings and eggshell irregularities, also supporting the use of eggshell irregularities as a potential non-invasive welfare indicator. However, the pattern of the stress response varied between indicators and correlations were generally few and inconsistent, highlighting the complexity of the relationship among welfare indicators. © 2016 Poultry Science Association Inc.

Automated four color CD4/CD8 analysis of leukocytes by scanning fluorescence microscopy using Quantum dots

NASA Astrophysics Data System (ADS)

Bocsi, Jozsef; Mittag, Anja; Varga, Viktor S.; Molnar, Bela; Tulassay, Zsolt; Sack, Ulrich; Lenz, Dominik; Tarnok, Attila

2006-02-01

Scanning Fluorescence Microscope (SFM) is a new technique for automated motorized microscopes to measure multiple fluorochrome labeled cells (Bocsi et al. Cytometry 2004, 61A:1). The ratio of CD4+/CD8+ cells is an important in immune diagnostics in immunodeficiency and HIV. Therefor a four-color staining protocol (DNA, CD3, CD4 and CD8) for automated SFM analysis of lymphocytes was developed. EDTA uncoagulated blood was stained with organic and inorganic (Quantum dots) fluorochromes in different combinations. Aliquots of samples were measured by Flow Cytometry (FCM) and SFM. By SFM specimens were scanned and digitized using four fluorescence filter sets. Automated cell detection (based on Hoechst 33342 fluorescence), CD3, CD4 and CD8 detection were performed, CD4/CD8 ratio was calculated. Fluorescence signals were well separable on SFM and FCM. Passing and Bablok regression of all CD4/CD8 ratios obtained by FCM and SFM (F(X)=0.0577+0.9378x) are in the 95% confidence interval. Cusum test did not show significant deviation from linearity (P>0.10). This comparison indicates that there is no systemic bias between the two different methods. In SFM analyses the inorganic Quantum dot staining was very stable in PBS in contrast to the organic fluorescent dyes, but bleached shortly after mounting with antioxidant and free radical scavenger mounting media. This shows the difficulty of combinations of organic dyes and Quantum dots. Slide based multi-fluorescence labeling system and automated SFM are applicable tools for the CD4/CD8 ratio determination in peripheral blood samples. Quantum Dots are stable inorganic fluorescence labels that may be used as reliable high resolution dyes for cell labeling.

Use of a plastic insulin dosage guide to correct blood glucose levels out of the target range and for carbohydrate counting in subjects with type 1 diabetes.

PubMed

Kaufman, F R; Halvorson, M; Carpenter, S

1999-08-01

To improve glycemic control, a hand-held plastic Insulin Dosage Guide was developed to correct blood glucose levels outside of the target range. Protocol 1: Some 40 children (mean age 10.6+/-4.6 years) were randomly assigned for 3 months to use a written-on-paper algorithm or the Insulin Dosage Guide to correct abnormal blood glucose levels. Mean HbA1c and blood glucose levels and time to teach insulin dosage correction were compared. Protocol 2: The Insulin Dosage Guide was used by 83 subjects (mean age 11.4+/-4.3 years) for 1 year, and mean HbA1c levels, blood glucose levels, and number of consecutive high blood glucose values taken before and after the year were compared. Protocol 3: Some 20 patients (mean age 10.1+/-3.7 years) using rapid-acting insulin and 64 patients (mean age 15.9+/-3.6 years) using an insulin pump and rapid-acting insulin used the Insulin Dosage Guide and had mean blood glucose levels, HbA1c, and percentage of blood glucose levels outside of the target range determined. Protocol 1: There was a significant reduction in mean HbA1c (P = 0.04) and blood glucose levels (P = 0.05) and in the time needed to teach how to correct blood glucose values using the Insulin Dosage Guide compared with the paper algorithm. Protocol 2: There was a decrease in mean HbA1c levels (P = 0.0001) and a decrease in the mean number of consecutive blood glucose levels (P = 0.001) over the 1-year time period. Protocol 3: With rapid-acting insulin, there was a significant increase in the percentage of blood glucose levels within the target range (1 month, P = 0.04; at 3 months, P = 0.03). With the insulin pump, there was a high rate (90%) of blood glucose levels in the target range during pump initiation when the Insulin Dosage Guide was used. This inexpensive hand-held plastic card, which is portable and easy to use, may help patients improve glycemia and successfully manage diabetes.

Efficient fuzzy C-means architecture for image segmentation.

PubMed

Li, Hui-Ya; Hwang, Wen-Jyi; Chang, Chia-Yen

2011-01-01

This paper presents a novel VLSI architecture for image segmentation. The architecture is based on the fuzzy c-means algorithm with spatial constraint for reducing the misclassification rate. In the architecture, the usual iterative operations for updating the membership matrix and cluster centroid are merged into one single updating process to evade the large storage requirement. In addition, an efficient pipelined circuit is used for the updating process for accelerating the computational speed. Experimental results show that the the proposed circuit is an effective alternative for real-time image segmentation with low area cost and low misclassification rate.

Garlic-derived compound S-allylmercaptocysteine (SAMC) is active against anaplastic thyroid cancer cell line 8305C (HPACC).

PubMed

Liu, Yuexin; Yan, Jinyin; Han, Xiaochen; Hu, Wanning

2015-01-01

Epidemiological and experimental carcinogenesis studies provide evidence that components of garlic have anticancer activity. In this study, the apoptotic effects of Garlic-derived compound S-allylmercaptocysteine (SAMC) were investigated in 8305C human anaplastic thyroid carcinoma cells. The cell line 8305C (HPACC) were treated with SAMC and the MTT assay, flow cytometry (FCM), electron microscope method were used to test cell cycle, inhibitory rate and morphologic changes respectively. HPACC-8305C cells were suppressed after exposure to SAMC of 0.02 mg/ml, 0.06 mg/ml, and 0.1 mg/ml for 48 h. Compared with the control, the difference was significant (P< 0.05). SAMC could induce apoptosis of the cells in a dose-dependent and non-linear manner and increase the proportion of cells in the G2/M phase. Compared with the control, the difference was significant in terms of the percentage of cells in the G2/M phase (P< 0.05). After exposure to SAMC at 0.02 mg/ml for 24 hours, HPACC-8305C cells showed typical morphologic change. SAMC inhibits the growth of HPACC-8305C cells by induction of apoptotic cell death and inhibit telomerase activity, which appears to account for its anti-cancer activity.

Combining the genetic algorithm and successive projection algorithm for the selection of feature wavelengths to evaluate exudative characteristics in frozen-thawed fish muscle.

PubMed

Cheng, Jun-Hu; Sun, Da-Wen; Pu, Hongbin

2016-04-15

The potential use of feature wavelengths for predicting drip loss in grass carp fish, as affected by being frozen at -20°C for 24 h and thawed at 4°C for 1, 2, 4, and 6 days, was investigated. Hyperspectral images of frozen-thawed fish were obtained and their corresponding spectra were extracted. Least-squares support vector machine and multiple linear regression (MLR) models were established using five key wavelengths, selected by combining a genetic algorithm and successive projections algorithm, and this showed satisfactory performance in drip loss prediction. The MLR model with a determination coefficient of prediction (R(2)P) of 0.9258, and lower root mean square error estimated by a prediction (RMSEP) of 1.12%, was applied to transfer each pixel of the image and generate the distribution maps of exudation changes. The results confirmed that it is feasible to identify the feature wavelengths using variable selection methods and chemometric analysis for developing on-line multispectral imaging. Copyright © 2015 Elsevier Ltd. All rights reserved.

Point spread functions and deconvolution of ultrasonic images.

PubMed

Dalitz, Christoph; Pohle-Fröhlich, Regina; Michalk, Thorsten

2015-03-01

This article investigates the restoration of ultrasonic pulse-echo C-scan images by means of deconvolution with a point spread function (PSF). The deconvolution concept from linear system theory (LST) is linked to the wave equation formulation of the imaging process, and an analytic formula for the PSF of planar transducers is derived. For this analytic expression, different numerical and analytic approximation schemes for evaluating the PSF are presented. By comparing simulated images with measured C-scan images, we demonstrate that the assumptions of LST in combination with our formula for the PSF are a good model for the pulse-echo imaging process. To reconstruct the object from a C-scan image, we compare different deconvolution schemes: the Wiener filter, the ForWaRD algorithm, and the Richardson-Lucy algorithm. The best results are obtained with the Richardson-Lucy algorithm with total variation regularization. For distances greater or equal twice the near field distance, our experiments show that the numerically computed PSF can be replaced with a simple closed analytic term based on a far field approximation.