An image processing application for quantification of protein aggregates in Caenorhabditis elegans

Protein aggregation became a widely accepted marker of many polyQ disorders, including Machado-Joseph disease (MJD), and is often used as readout for disease progression and development of therapeutic strategies. The lack of good platforms to rapidly quantify protein aggregates in a wide range of disease animal models prompted us to generate a novel image processing application that automatically identifies and quantifies the aggregates in a standardized and operator-independent manner. We propose here a novel image processing tool to quantify the protein aggregates in a Caenorhabditis elegans (C. elegans) model of MJD. Confocal mi-croscopy images were obtained from animals of different genetic conditions. The image processing application was developed using MeVisLab as a platform to pro-cess, analyse and visualize the images obtained from those animals. All segmenta-tion algorithms were based on intensity pixel levels.The quantification of area or numbers of aggregates per total body area, as well as the number of aggregates per animal were shown to be reliable and reproducible measures of protein aggrega-tion in C. elegans. The results obtained were consistent with the levels of aggrega-tion observed in the images. In conclusion, this novel imaging processing applica-tion allows the non-biased, reliable and high throughput quantification of protein aggregates in a C. elegans model of MJD, which may contribute to a significant improvement on the prognosis of treatment effectiveness for this group of disor-ders

Determinants of environmental disclosure in the annual reports of large companies operating in Portugal

Similarly to what has happened in other countries, since the early 1990s Portuguese companies have developed corporate environmental reporting practices in response to internal and external factors. This paper is based on empirical research directed to both the study of environmental reporting practices developed by Portuguese companies and the identification of the factors that explain the extent to which these companies disclose environmental information. This study focuses on the environmental disclosures made in the annual reports by a sample of 109 large firms operating in Portugal during the period 2002-04. Using the content analysis technique we have developed an index in order to assess the presence of the environmental disclosures in companies’ annual reports and their breadth. Based on the extant literature, several characteristics relating to firms’ attributes were selected and their influence on the level of environmental disclosure was tested empirically. The selected explanatory variables were firm size, industry membership, profitability, foreign ownership, quotation on the stock market and environmental certification. The results reveal that, in spite of the fact that the level of environmental information disclosed during the period 2002-04 is low, the extent of environmental disclosure has increased as well as the number of Portuguese companies that disclose environmental information. Moreover, the firm size and the fact that a company is listed on the stock market are positively related to the extent of environmental disclosure. This study adds to the international research on environmental disclosure by providing empirical data from a country, Portugal, where empirical evidence is still relatively unknown, extending the scope of the current understanding of the environmental reporting practices.

Application of Gage R&R methodology for improving the training and evaluation of automatic optical inspection machine operators

The current level of demand by customers in the electronics industry requires the production of parts with an extremely high level of reliability and quality to ensure complete confidence on the end customer. Automatic Optical Inspection (AOI) machines have an important role in the monitoring and detection of errors during the manufacturing process for printed circuit boards. These machines present images of products with probable assembly mistakes to an operator and him decide whether the product has a real defect or if in turn this was an automated false detection. Operator training is an important aspect for obtaining a lower rate of evaluation failure by the operator and consequently a lower rate of actual defects that slip through to the following processes. The Gage R&R methodology for attributes is part of a Six Sigma strategy to examine the repeatability and reproducibility of an evaluation system, thus giving important feedback on the suitability of each operator in classifying defects. This methodology was already applied in several industry sectors and services at different processes, with excellent results in the evaluation of subjective parameters. An application for training operators of AOI machines was developed, in order to be able to check their fitness and improve future evaluation performance. This application will provide a better understanding of the specific training needs for each operator, and also to accompany the evolution of the training program for new components which in turn present additional new difficulties for the operator evaluation. The use of this application will contribute to reduce the number of defects misclassified by the operators that are passed on to the following steps in the productive process. This defect reduction will also contribute to the continuous improvement of the operator evaluation performance, which is seen as a quality management goal.