Semi-automated and fully automated mammographic density measurement and breast cancer risk prediction

The task of breast density quantification is becoming increasingly relevant due to its association with breast cancer risk. In this work, a semi-automated and a fully automated tools to assess breast density from full-field digitized mammograms are presented. The first tool is based on a supervised interactive thresholding procedure for segmenting dense from fatty tissue and is used with a twofold goal: for assessing mammographic density (MD) in a more objective and accurate way than via visual-based methods and for labeling the mammograms that are later employed to train the fully automated tool. Although most automated methods rely on supervised approaches based on a global labeling of the mammogram, the proposed method relies on pixel-level labeling, allowing better tissue classification and density measurement on a continuous scale. The fully automated method presented combines a classification scheme based on local features and thresholding operations that improve the performance of the classifier. A dataset of 655 mammograms was used to test the concordance of both approaches in measuring MD. Three expert radiologists measured MD in each of the mammograms using the semi-automated tool (DM-Scan). It was then measured by the fully automated system and the correlation between both methods was computed. The relation between MD and breast cancer was then analyzed using a case–control dataset consisting of 230 mammograms. The Intraclass Correlation Coefficient (ICC) was used to compute reliability among raters and between techniques. The results obtained showed an average ICC = 0.922 among raters when using the semi-automated tool, whilst the average correlation between the semi-automated and automated measures was ICC = 0.838. In the case–control study, the results obtained showed Odds Ratios (OR) of 1.38 and 1.50 per 10% increase in MD when using the semi-automated and fully automated approaches respectively. It can therefore be concluded that the automated and semi-automated MD assessments present a good correlation. Both the methods also found an association between MD and breast cancer risk, which warrants the proposed tools for breast cancer risk prediction and clinical decision making. A full version of the DM-Scan is freely available.     

Using “human state aware” robots to enhance physical human–robot interaction in a cooperative scenario

Human motor performance, speed and variability are highly susceptible to emotional states. This paper reviews the impact of the emotions on the motor control performance, and studies the possibility of improving the perceived skill/challenge relation on a multimodal neural rehabilitation scenario, by means of a biocybernetic controller that modulates the assistance provided by a haptic controlled robot in reaction to undesirable physical and mental states. Results from psychophysiological, performance and self assessment data for closed loop experiments in contrast with their open loop counterparts, suggest that the proposed method had a positive impact on the overall challenge/skill relation leading to an enhanced physical human–robot interaction experience.     

Tunnel Ventilation Analysis Using a Probabilistic Approach: Case Study,Fire in Road Tunnels with Longitudinal Ventilation

Fire Technology - Tunnels are nowadays key elements in transport networks worldwide. To achieve a safe and efficient operation, a proper integration and design of Mechanical, Electrical and...     

Production of volatile compounds in the fermentation of chardonnay musts inoculated with two strains of Saccharomyces cerevisiae with different nitrogen demands

This paper studies the behaviour of two strains of Saccharomyces cerevisiae with different nitrogen requirements in the production of esters and higher alcohols during alcoholic fermentation. To carry out the study a chardonnay must with a high content of nitrogen compounds was used. The results showed that the strain with the highest nitrogen demand produced a higher concentration of esters during fermentation and gave rise to a wine with a somewhat lesser content of higher alcohols. The formation of volatile compounds was probably related to the consumption of nitrogen by the strains as the nitrogen nutrients act as precursors in the synthesis of esters and alcohols and regulate their production.     

Thermal spikes in Ag/Fe and Cu/Fe ion beam mixing

Ion beam mixing has been studied since 1980, and since then a lot of experimental and theoretical work has been done and knowledge has been gathered. Nevertheless, there are still many fundamental aspects that need to be clarified and with that aim many experiments need to be performed. Copper and iron are miscible in the liquid state, while silver and iron are not. However, both systems are thermally immiscible in the solid state. In order to have an insight into the importance of mixing within thermal spikes during ion beam irradiation, we deposited Cu/Fe and Ag/Fe bilayers onto Si substrates and irradiated them at room temperature with 2 MeV Cu and 2.5 MeV Au ions. A combination of Rutherford backscattering spectrometry (RBS) and atomic force microscopy (AFM) was used to analyze the atomic transport at the interface and the morphology changes of the samples. From the element profiles at the interface we conclude a mixing efficiency, which is indeed larger than the prediction of the ballistic model in the Cu/Fe system and smaller in the Ag/Fe system. Since ballistic mixing is expected in any case, we argue that demixing and phase separation in the Ag/Fe system occur in the thermal spike phase of the cascade as a consequence of the positive heat of mixing. Further mixing does occur in the thermal spike in the Cu/Fe system and they remain mixed even at the solid state because of the high cooling rate. In addition, ion irradiation induces a large surface roughening of the Ag and Cu top layers as proven by AFM. This effect is important for the correct interpretation of the results. Furthermore, this recrystallization affects also the interface, producing a rough interface, that appears in the RBS spectra as an atomic ‘diffusion’ at the interface.     

Markovian-based traffic modeling for mobile ad hoc networks

Mobile ad hoc networks (MANETs) show very significant difference with respect to other computer networks due to the presence of extremely large packet loss bursts. The development of protocols for mobile ad hoc networks, especially multimedia protocols, require extensive evaluation either through simulation or real-life tests. Such testing consumes a great amount of resources both in terms of time and trace file sizes. Therefore, finding efficient means of reducing the amount of data that is stored and processed is quite important to accelerate the evaluation of different audio/video streaming applications. If, moreover, we are able to model the loss pattern experienced, we can further accelerate the evaluation process.In this work we propose two models based on hidden Markov chains that are able to grasp both packet arrivals and packet loss patterns in MANETs. A simpler two-state model is proposed to model losses when proactive routing protocols are used, while a more complex three-state model is proposed for reactive routing protocols. We also introduce a new set for packet loss pattern measurements that can be of interest for the evaluation of audio/video streaming applications.Experimental results show that the proposed models can adequately reproduce extremely long packet loss patterns, typical of MANET environments, with a high degree of accuracy. Overall, we find that the proposed models are able to significantly reduce both the simulation time and the trace file sizes required.     

MMP1 and MMP11 Expression in Peripheral Blood Mononuclear Cells upon Their Interaction with Breast Cancer Cells and Fibroblasts

Tumor-infiltrating immune cells phenotype is associated with tumor progression. However, little is known about the phenotype of the peripheral blood mononuclear cells (PBMC) from breast cancer patients. We investigated MMP1 and MMP11 expression in PBMC from breast cancer patients and we analyzed gene expression changes upon their interaction with cancer cells and cancer-associated fibroblasts (CAF). We measured the impact of PBMC on proinflammatory gene expression in breast cancer cells, normal fibroblast (NF), and CAF and the impact on proliferation and invasiveness capacity of breast cancer cells. Gene expression of MMP1 and MMP11 in PBMC from breast cancer patients (n = 54) and control (n = 28); expression of IL1A, IL6, IL17, IFNβ, and NFĸB in breast cancer cell lines (MCF-7 and MDA-MB-231); and, additionally, IL10 and MMP11 in CAF and NF were analyzed by qRT-PCR before and after co-culture. Our results show the existence of a subpopulation of breast cancer patients (25.9%) with very high levels of MMP11 gene expression in PBMC. Also, gene expression of MMP1 and MMP11 increases in PBMC after co-culture with breast cancer cell lines, NF or CAF. PBMC from healthy or breast cancer patients induce an increased proliferation rate on MCF-7 and an increased invasiveness capacity of MDA-MB-231. Finally, we show a differential expression profile of inflammatory genes in NF and CAF when co-cultured with control or breast cancer PBMC. We have observed that MMPs’ expression in PBMC is regulated by the microenvironment, while the expression of inflammatory genes in NF or CAF is differentially regulated by PBMC. These findings confirm the importance of the crosstalk between stromal cells and suggest that PBMC would play a role in promoting aggressive tumor behavior.