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

Success factors of regional airports: the case of Oporto airport

Oporto Airport (OPO) is a success story among European regional airports. This success is expressed, among other ways, in the rapid expansion of routes and the strong growth in demand, as well as in the recognition of the airport’s quality by its users. Over the past decade, the volume of traffic increased by almost 3.4 million passengers, from the 2.6 million recorded in 2002 to over 6 million in 2012. In this paper, we analyse some of the factors that influenced the success of Oporto Airport, namely the expansion of capacity and improvements to infrastructure, the increase in the number of routes and the increased demand in response to the new capacities of this airport-airlines set. Particular emphasis is given to the role of low cost carriers (LCC) in the growth of Oporto Airport and to strategies of attracting more traffic. Some of the main opportunities and challenges that this airport will face in the coming years are also discussed.