Agua y Suero Fisiológico para Prevenir la Formación de Paracloroanilina

Indexación: Web of Science; Scielo.ABSTRACT: This study determined if p-chloroaniline (PCA) can be minimized by using distilled water and physiological saline solution following sodium hypochlorite but before chlorhexidine. Hypochlorite 5%, 0.5%, 0.05%, 0.005% and 0.0005% dissolved in 0.9% NaCl and in distilled water were mixed with 2% chlorhexidine for the formation of PCA. The PCA was determined using UV-VISIBLE spectrometry, with spectral curve was determined the wavelength of maximum absorption of PCA. Formed PCA absorbance was measured between 0.025%, 0.02%, 0.015%, 0.01%, 0.005% and 0.0025% hypochlorite and 2% chlorhexidine. 2% chlorhexidine and hypochlorite with physiological saline form a white precipitate which prevents the measurement of PCA. Colored PCA is formed with 0.05%, 0.005% hypochlorite aqueous dilutions and 2% chlorhexidine. The lwavelength of maximum absorption obtained was 470 nm and absorbance of PCA showed a linear decrease. 0.005% NaClO produces the least amount of PCA. The best solvent to prevent the formation of PCA during the interaction of sodium hypochlorite with chlorhexidine is distilled water.Este estudio determinó si la p-cloroanilina (PCA) puede ser minimizada mediante el uso de agua destilada y solución salina fisiológica seguido de la aplicación de hipoclorito de sodio, previo a la aplicación de clorhexidina. Hipoclorito al 5%, 0,5%, 0,05%, 0,005% y 0,0005% fue disuelto en 0,9% de NaCl y en agua destilada se mezcló con 2% de clorhexidina para la formación de PCA. El PCA se determinó mediante espectrometría UV-Visible, y con curva espectral se determinó la longitud de onda máxima del PCA. La absorbancia del PCA formado se midió con 0,025%, 0,02%, 0,015%, 0,01%, 0,005% y 0,0025% de hipoclorito y 2% de clorhexidina. La combinación de 2% de clorhexidina e hipoclorito en solución salina fisiológica forman un precipitado blanco que impide la medición del PCA. El PCA coloreado es formado con 0,05%, 0,005% diluciones acuosas de hipoclorito y 2% de clorhexidina. La longitud de onda máxima obtenida fue de 470 nm y la absorbancia del PCA mostró una disminución lineal. NaClO al 0,005% produce menor cantidad de PCA. El mejor disolvente para evitar la formación de PCA durante la interacción de hipoclorito de sodio con clorhexidina es agua destilada.http://ref.scielo.org/2kpw6

N-Dimensional Principal Component Analysis

In this paper, we first briefly introduce the multidimensional Principal Component Analysis (PCA) techniques, and then amend our previous N-dimensional PCA (ND-PCA) scheme by introducing multidirectional decomposition into ND-PCA implementation. For the case of high dimensionality, PCA technique is usually extended to an arbitrary n-dimensional space by the Higher-Order Singular Value Decomposition (HO-SVD) technique. Due to the size of tensor, HO-SVD implementation usually leads to a huge matrix along some direction of tensor, which is always beyond the capacity of an ordinary PC. The novelty of this paper is to amend our previous ND-PCA scheme to deal with this challenge and further prove that the revised ND-PCA scheme can provide a near optimal linear solution under the given error bound. To evaluate the numerical property of the revised ND-PCA scheme, experiments are performed on a set of 3D volume datasets

Upregulated wnt-11 and mir-21 expression trigger epithelial mesenchymal transition in aggressive prostate cancer cells

Prostate cancer (PCa) is the second-leading cause of cancer-related death among men. microRNAs have been identified as having potential roles in tumorigenesis. An oncomir, miR-21, is commonly highly upregulated in many cancers, including PCa, and showed correlation with the Wnt-signaling axis to increase invasion. Wnt-11 is a developmentally regulated gene and has been found to be upregulated in PCa, but its mechanism is unknown. The present study aimed to investigate the roles of miR-21 and Wnt-11 in PCa in vivo and in vitro. First, different Gleason score PCa tissue samples were used; both miR-21 and Wnt-11 expressions correlate with high Gleason scores in PCa patient tissues. This data then was confirmed with formalin-fixed paraffin cell blocks using PCa cell lines LNCaP and PC3. Cell survival and colony formation studies proved that miR-21 involves in cells’ behaviors, as well as the epithelial-mesenchymal transition. Consistent with the previous data, silencing miR-21 led to significant inhibition of cellular invasiveness. Overall, these results suggest that miR-21 plays a significant role related to Wnt-11 in the pathophysiology of PCa

Validation of nonlinear PCA

Linear principal component analysis (PCA) can be extended to a nonlinear PCA by using artificial neural networks. But the benefit of curved components requires a careful control of the model complexity. Moreover, standard techniques for model selection, including cross-validation and more generally the use of an independent test set, fail when applied to nonlinear PCA because of its inherent unsupervised characteristics. This paper presents a new approach for validating the complexity of nonlinear PCA models by using the error in missing data estimation as a criterion for model selection. It is motivated by the idea that only the model of optimal complexity is able to predict missing values with the highest accuracy. While standard test set validation usually favours over-fitted nonlinear PCA models, the proposed model validation approach correctly selects the optimal model complexity.Comment: 12 pages, 5 figure