Automatic segmentation and 3D feature extraction of protein aggregates in Caenorhabditis Elegans

In the last years, it has become increasingly clear that neurodegenerative diseases involve protein aggregation, a process often used as disease progression readout and to develop therapeutic strategies. This work presents an image processing tool to automatic segment, classify and quantify these aggregates and the whole 3D body of the nematode Caenorhabditis Elegans. A total of 150 data set images, containing different slices, were captured with a confocal microscope from animals of distinct genetic conditions. Because of the animals’ transparency, most of the slices pixels appeared dark, hampering their body volume direct reconstruction. Therefore, for each data set, all slices were stacked in one single 2D image in order to determine a volume approximation. The gradient of this image was input to an anisotropic diffusion algorithm that uses the Tukey’s biweight as edge-stopping function. The image histogram median of this outcome was used to dynamically determine a thresholding level, which allows the determination of a smoothed exterior contour of the worm and the medial axis of the worm body from thinning its skeleton. Based on this exterior contour diameter and the medial animal axis, random 3D points were then calculated to produce a volume mesh approximation. The protein aggregations were subsequently segmented based on an iso-value and blended with the resulting volume mesh. The results obtained were consistent with qualitative observations in literature, allowing non-biased, reliable and high throughput protein aggregates quantification. This may lead to a significant improvement on neurodegenerative diseases treatment planning and interventions prevention

Integration of Individualized Management Systems (MSs) as an Aggregating Factor of Sustainable Value for Organizations: An Overview Through a Review of the Literature

Nowadays, there exist various standards for individual management systems (MSs), at least, one for each stakeholder. New ones will be published. An integrated management system (IMS) aims to integrate some or all components of the business into one coherent and efficient MS. Maximizing integration is more and more a strategic priority in that it constitutes an opportunity to eliminate and/or reduce potential factors of destruction of value for the organizations and also to be more competitive and consequently promote its sustainable success. A preliminary investigation was conducted on a Portuguese industrial company which, over the years, has been adopting gradually, in whole or in part, individualized management system standards (MSSs). A research, through a questionnaire, was performed with the objective to develop, in a real business environment, an adequate and efficient IMS-QES (quality, environment, and safety) model and to potentiate for the future a generic IMS model to integrate other MSSs. The strategy and research methods have taken into consideration the case study. It was obtained a set of relevant conclusions resulting from the statistical analyses of the responses to the survey. Globally, the investigation results, by themselves, justified and prioritized the conception of a model of development of the IMS-QES and consequent definition and validation of a structure of an IMS-QES model, to be implemented at the small- and medium-sized enterprise (SME) where the investigation was conducted.

Effect of cylindrical filler aggregation on the electrical conductivity of composites

This work reports on the effect of carbon nanotube aggregation on the electrical conductivity and other network properties of polymer/carbon nanotube composites by modeling the carbon nanotubes as hard-core cylinders. It is shown that the conductivity decreases for increasing filler aggregation, and that this effect is more significant for higher cylinder volume fractions. It is also demonstrated, for volume fractions at which the giant component is present, that increasing the fraction of cylinders within clusters leads to a break of the giant component and the formation of a set of finite clusters. The decrease of the giant component with the increase of the fraction of cylinders within the cluster can be related to a decrease of the spanning probability due to a decrease of the number of cylinders between the clusters. Finally, it is demonstrated that the effect of aggregation can be understood by employing the network theory.