Successful Endomyocardial Biopsy Guided by Transthoracic Two-Dimensional Echocardiography

Introduction. Two-dimensional (2-D) echocardiography is an excellent alternative method to perform endomyocardial biopsies (EB) in special situations, mainly when the patient is in a critical state and cannot go to the catheterization laboratory or when there are contraindications to the use of fluoroscopy as in the pregnancy. Objective. This single-center experience analyzed the last 25 years use of an EB technique guided by echocardiography realized at the bedside on critical patients. Methods. From 1985 to 2010, we performed 76 EB guided by 2-D echocardiography on 59 patients, among whom 38 (64.4%) were critically ill with examinations at the bedside; among 10 (16.9%) subjects, the procedure was carried out simultaneously with fluoroscopy for safety`s sake during the learning period. In addition, 8 (13.6%) were unavailable for fluoroscopy, and 3 (5.1%) required a hybrid method due to an intracardiac tumor. Results. The main adverse effects included local pain (n = 4, 5.6%); difficult out successful puncture due to previous biopsies (n = 4, 5.6%); local hematoma without major consequences (n = 3, 4.2%); failed but ultimately successful puncture on the first try due to previous biopsies or (n = 3, 4.2%); obesity and immediate postoperative period with impossibility to pass the bioptome into the right ventricle; however 2 days later the procedure was repeated successfully by echocardiography (n = 1, 1.4%). All myocardial specimens displayed suitable size. There were no undesirable extraction effects on the tricuspid valve tissue. In this series, there was no case of death, hemopericardium, or other major complication as a direct consequence of the biopsy. Conclusion. 2-D echocardiography is a special feature to guide EB is mainly in critically ill patients because it can be performed at the bedside without additional risk or disadvantages of fluoroscopy. The hybrid method associating 2-D echocardiography and fluoroscopy allows the procedure in different situations such as intracardiac tumor cases.

A continuum model for periodic two-dimensional block structures

A continuum model for regular block structures is derived by replacing the difference quotients of the discrete equations by corresponding differential quotients. The homogenization procedure leads to an anisotropic Cosserat Continuum. For elastic block interactions the dispersion relations of the discrete and the continuous models are derived and compared. Yield criteria for block tilting and sliding are formulated. An extension of the theory for large deformation is proposed. (C) 1997 by John Wiley & Sons, Ltd.

Analyzing the connectivity between regions of interest: An approach based on cluster Granger causality for NRI data analysis

The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

Independent component analysis applied to raman spectra for classification of in vitro human coronary arteries

Optical diagnostic methods, such as near-infrared Raman spectroscopy allow quantification and evaluation of human affecting diseases, which could be useful in identifying and diagnosing atherosclerosis in coronary arteries. The goal of the present work is to apply Independent Component Analysis (ICA) for data reduction and feature extraction of Raman spectra and to perform the Mahalanobis distance for group classification according to histopathology, obtaining feasible diagnostic information to detect atheromatous plaque. An 830nm Ti:sapphire laser pumped by an argon laser provides near-infrared excitation. A spectrograph disperses light scattered from arterial tissues over a liquid-nitrogen cooled CCD to detect the Raman spectra. A total of 111 spectra from arterial fragments were utilized.

Detection of Auditory Cortex Activity by fMRI Using a Dependent Component Analysis

Functional MRI (fMRI) data often have low signal-to-noise-ratio (SNR) and are contaminated by strong interference from other physiological sources. A promising tool for extracting signals, even under low SNR conditions, is blind source separation (BSS), or independent component analysis (ICA). BSS is based on the assumption that the detected signals are a mixture of a number of independent source signals that are linearly combined via an unknown mixing matrix. BSS seeks to determine the mixing matrix to recover the source signals based on principles of statistical independence. In most cases, extraction of all sources is unnecessary; instead, a priori information can be applied to extract only the signal of interest. Herein we propose an algorithm based on a variation of ICA, called Dependent Component Analysis (DCA), where the signal of interest is extracted using a time delay obtained from an autocorrelation analysis. We applied such method to inspect functional Magnetic Resonance Imaging (fMRI) data, aiming to find the hemodynamic response that follows neuronal activation from an auditory stimulation, in human subjects. The method localized a significant signal modulation in cortical regions corresponding to the primary auditory cortex. The results obtained by DCA were also compared to those of the General Linear Model (GLM), which is the most widely used method to analyze fMRI datasets.

Two-dimensional radiographic and clinical references of the tooth crown for orthodontic mini-implant insertion: A guide-free technique

Objective. This study evaluated the reliability of tooth-crown radiographic references to aid in orthodontic mini-implant insertion and showed an insertion technique based on these references. Study design. The sample consisted of 213 interradicular septa evaluated in 53 bitewing radiographs. The proximal contour of adjacent tooth crowns was used to define septum width and its midpoint was linked to the interdental contact point to determine septum midline (SML). The distances from SML to mesial and distal teeth were measured and compared to evaluate SML centralization degree in 2 different septum heights. Results. The mesial and distal distances were not statistically different in the midpoint of the septum height, but they were different at the apical septum height. Conclusions. The tooth-crown radiographic references determine a high centralization degree of the SML on which an insertion site could be defined. The greater SML centralization degree was observed at the coronal septum area. (Oral Surg Oral Med Oral Pathol Oral Radiol Endod 2010;110:e8-e16)

Treatment outcome in individuals with chronic pain: is the Pain Stages of Change Questionnaire (PSOCQ) a useful tool? Jenny StrongCorresponding Author Contact Information, E-mail The Corresponding Author, a, Kym Westburya, Glen Smithb, Ian McKenziec and William Ryan

The efficacy of psychological treatments emphasising a self-management approach to chronic pain has been demonstrated by substantial empirical research. Nevertheless, high drop-out and relapse rates and low or unsuccessful engagement in self-management pain rehabilitation programs have prompted the suggestion that people vary in their readiness to adopt a self-management approach to their pain. The Pain Stages of Change Questionnaire (PSOCQ) was developed to assess a patient's readiness to adopt a self-management approach to their chronic pain. Preliminary evidence has supported the PSOCQ's psychometric properties. The current study was designed to further examine the psychometric properties of the PSOCQ, including its reliability, factorial structure and predictive validity. A total of 107 patients with an average age of 36.2 years (SD = 10.63) attending a multi-disciplinary pain management program completed the PSOCQ, the Pain Self-Efficacy Questionnaire (PSEQ) and the West Haven-Yale Multidimensional Pain Inventory (WHYMPI) pre-admission and at discharge from the program. Initial data analysis found inadequate internal consistencies of the precontemplation and action scales of the PSOCQ and a high correlation (r = 0.66, P < 0.01) between the action and maintenance scales. Principal component analysis supported a two-factor structure: 'Contemplation' and 'Engagement'. Subsequent analyses revealed that the PSEQ was a better predictor of treatment outcome than the PSOCQ scales. Discussion centres upon the utility of the PSOCQ in a clinical pain setting in light of the above findings, and a need for further research. (C) 2002 International Association for the Study of Pain. Published by Elsevier Science B.V. All rights reserved.

Adaptive multiscale principal components analysis for online monitoring of wastewater treatment

Fault detection and isolation (FDI) are important steps in the monitoring and supervision of industrial processes. Biological wastewater treatment (WWT) plants are difficult to model, and hence to monitor, because of the complexity of the biological reactions and because plant influent and disturbances are highly variable and/or unmeasured. Multivariate statistical models have been developed for a wide variety of situations over the past few decades, proving successful in many applications. In this paper we develop a new monitoring algorithm based on Principal Components Analysis (PCA). It can be seen equivalently as making Multiscale PCA (MSPCA) adaptive, or as a multiscale decomposition of adaptive PCA. Adaptive Multiscale PCA (AdMSPCA) exploits the changing multivariate relationships between variables at different time-scales. Adaptation of scale PCA models over time permits them to follow the evolution of the process, inputs or disturbances. Performance of AdMSPCA and adaptive PCA on a real WWT data set is compared and contrasted. The most significant difference observed was the ability of AdMSPCA to adapt to a much wider range of changes. This was mainly due to the flexibility afforded by allowing each scale model to adapt whenever it did not signal an abnormal event at that scale. Relative detection speeds were examined only summarily, but seemed to depend on the characteristics of the faults/disturbances. The results of the algorithms were similar for sudden changes, but AdMSPCA appeared more sensitive to slower changes.

Two-dimensional balanced sampling plans excluding contiguous units

A balanced sampling plan excluding contiguous units (or BSEC for short) was first introduced by Hedayat, Rao and Stufken in 1988. These designs can be used for survey sampling when the units are arranged in one-dimensional ordering and the contiguous units in this ordering provide similar information. In this paper, we generalize the concept of a BSEC to the two-dimensional situation and give constructions of two-dimensional BSECs with block size 3. The existence problem is completely solved in the case where lambda = 1.

Repair-replace strategies for two-dimensional warranty policies

For repairable items sold with free replacement warranty, the actions available to the manufacturer to rectify failures under warranty are to (1) repair the failed item or (2) replace it with a new one. A proper repair-replace strategy can reduce the expected cost of servicing the warranty. In this paper, we study repair-replace strategies for items sold with a two-dimensional free replacement warranty. (C) 2003 Elsevier Ltd. All rights reserved.

The application of wave induced forces to a two-dimensional finite element long wave hydrodynamic model

This paper describes the modification of a two-dimensional finite element long wave hydrodynamic model in order to predict the net current and water levels attributable to the influences of waves. Tests examine the effects of the application of wave induced forces, including comparisons to a physical experiment. An example of a real river system is presented with comparisons to measured data, which demonstrate the importance of simulating the combined effects of tides and waves upon hydrodynamic behavior. (C) 2002 Elsevier Science Ltd. All rights reserved.

An SPSS R-Menu for Ordinal Factor Analysis

Exploratory factor analysis is a widely used statistical technique in the social sciences. It attempts to identify underlying factors that explain the pattern of correlations within a set of observed variables. A statistical software package is needed to perform the calcula- tions. However, there are some limitations with popular statistical software packages, like SPSS. The R programming language is a free software package for statistical and graphical computing. It o ers many packages written by contributors from all over the world and programming resources that allow it to overcome the dialog limitations of SPSS. This paper o ers an SPSS dialog written in the R programming language with the help of some packages, so that researchers with little or no knowledge in programming, or those who are accustomed to making their calculations based on statistical dialogs, have more options when applying factor analysis to their data and hence can adopt a better approach when dealing with ordinal, Likert-type data.

Transport properties in microcrystalline silicon solar cells under AM1.5 illumination analysed by two-dimensional numerical simulation

Microcrystalline silicon is a two-phase material. Its composition can be interpreted as a series of grains of crystalline silicon imbedded in an amorphous silicon tissue, with a high concentration of dangling bonds in the transition regions. In this paper, results for the transport properties of a mu c-Si:H p-i-n junction obtained by means of two-dimensional numerical simulation are reported. The role played by the boundary regions between the crystalline grains and the amorphous matrix is taken into account and these regions are treated similar to a heterojunction interface. The device is analysed under AM1.5 illumination and the paper outlines the influence of the local electric field at the grain boundary transition regions on the internal electric configuration of the device and on the transport mechanism within the mu c-Si:H intrinsic layer.