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.     

The cognitive impact of past behavior: Influences on beliefs, attitudes, and future behavioral decisions.

To study the processes by which past behavior influences future behavior, participants were led to believe that without being aware of it, they had expressed either support for or opposition to the institution of comprehensive exams. Judgment and response time data suggested that participants' perceptions of their past behavior often influenced their decisions to repeat the behavior. This influence was partly the result of cognitive activity that influenced participants' cognitions about specific behavioral consequences and the attitude they based on these cognitions. More generally, however, feedback about past behavior had a direct effect on participants' attitudes and ultimate behavioral decisions that was independent of the outcome-specific cognitions. Results are discussed in terms of their implications for biased scanning of memory, dissonance reduction, self-perception, and the use of behavior as a heuristic. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Antimicrobial peptides and their superior fluorinated analogues: structure-activity relationships as revealed by NMR spectroscopy and MD calculations

The conformations of two synthetic pentapeptides with antimicrobial activity and their 4-fluorophenylalanine (Pff)-containing analogues (ArXArXAr-NH(2); Ar=Phe, Pff; X=Lys, Arg) have been studied. NMR experiments carried out both in aqueous fluoroalcohol solutions and SDS micelles permitted their interactions with membrane-like environments to be explored. WaterLOGSY experiments and Mn(2+)-based paramagnetic probes were also applied to assess their orientations with respect to the SDS micelles. In addition, pulse-field gradient (PFG) diffusion NMR spectroscopy studies were conducted, under different experimental conditions (i.e., concentration, temperature) to characterize the possible changes in the peptides' aggregation states as a putative critical factor for their antimicrobial activity. Finally, molecular dynamics simulations on a variety of conformations showed the intrinsic flexibility of these peptides in both aqueous solutions and membrane-mimetic systems.     

Observations on natural factors influencing resistance of faba bean seeds to storage insect pests

The effect of natural content of tannins and other phenolic compounds in faba bean seeds hull on the infestation by some store pests was investigated. The hull, particularly the content of phenolic compounds, does not influence the infestation and reproduction of Tribolium destructor and Trogoderma granarium. More sensitive to phenols seem to be the species Sitophilus oryzae and Oryzaephilus surinamensis. These results do not markedly confirm the checking effect of phenols on the degree of the infestation of faba beans by stored pests.     

Surface and Groundwater Quality Evolution in the Agrio and Guadiamar Rivers After the Aznalcóllar Mine Spill (SW Spain): Lessons Learned

Mine Water and the Environment - The failure of the tailing dam at the Aznalcóllar mine (SW Spain) in 1998 released ≈ 6 million m3 of pyrite sludge and acidic...     

Pixel selection for near-infrared chemical imaging (NIR-CI) discrimination between fish and terrestrial animal species in animal protein by-product meals

This paper proposes a method based on near-infrared hyperspectral imaging for discriminating between terrestrial and fish species in animal protein by-products used in livestock feed. Four algorithms (Mahalanobis distance, Kennard-Stone, spatial interpolation, and binning) were compared in order to select an appropriate subset of pixels for further partial least squares discriminant analysis (PLS-DA). The method was applied to a set of 50 terrestrial and 40 fish meals analyzed in the 1000-1700 nm range. Models were then tested using an external validation set comprising 45 samples (25 fish and 20 terrestrial). The PLS-DA models obtained using the four subset-selection algorithms yielded a classification accuracy of 99.80%, 99.79%, 99.85%, and 99.61%, respectively. The results represent a first step for the analysis of mixtures of species and suggest that NIR-CI, providing valuable information on the origin of animal components in processed animal proteins, is a promising method that could be used as part of the EU feed control program aimed at eradicating and preventing bovine spongiform encephalopathy (BSE) and related diseases.     

Innovative materials for Gen IV systems and transmutation facilities: The cross-cutting research project GETMAT

Important Generation IV criteria for advanced fuel cycles are both improved efficiency and economical competitiveness. To reach these goals and keep high safety standards a key item is the availability of suitable structural materials. Ferritic/Martensitic (F/M) and Oxide-Dispersion-Strengthened (ODS) steels are indicated as the most promising candidates to withstand temperature, stress and irradiation fields expected in the core and primary system of most of the new generation reactors. In this context, the “Generation IV and Transmutation Materials” (GETMAT) project, sponsored by the EC, will contribute to the characterisation of ODS and F/M steels. The experimental and phenomenological aspects are complemented by the development of physical models aimed at describing and possibly predicting materials performance in operation.     

Grape,apple and pineapple juice characterisation and detection of mixtures

Several multivariate statistical methods (principal component, cluster, stepwise discriminant and multiple linear regression analysis) were applied to analytical data obtained by conventional methods and to analytical data for free amino acids, in an attempt to distinguish between grape, apple and pineapple juice. Analysis for methionine, proline, asparagine, arginine and glutamic acid made it possible to differentiate among the 34 samples of grape, apple and pineapple juices studied. Multiple linear regression analysis of computer-simulated mixtures of grape and apple juices made it possible to detect the proportion of each fruit within the blend.     

Flavouring of imitation cheese with enzyme-modified cheeses (EMCs): Sensory impact and measurement of aroma active short chain fatty acids (SCFAs)

Enzyme-modified cheeses (EMCs) are used to impart flavour to imitation cheese products. Cheeses (pH 6 or 5.5) were formulated with 5% w/w EMC, having low, medium or high levels of lipolysis and were examined by a sensory panel. Free fatty acid analyses were performed using SPME/GC. The flavour profile of the flavoured cheeses was affected by EMC composition and pH of the cheese base. Cheeses at a pH of 6.0, flavoured with low lipolysis EMCs, were described as ‘bland’. Lowering the pH of the cheese matrix to 5.5 appeared to increase the flavour intensity of the cheese flavoured with low lipolysis EMC and panellists ranked this cheese the highest, describing its flavour as ‘well-balanced and ‘cheesy’. This study shows that the flavours of imitation cheeses are influenced by the level of lipolysis of the EMCs used to flavour them and also by the pH of the cheese base.     

The effect of low-temperature blanching on the quality of fresh and frozen/thawed mashed potatoes

The effect of low‐temperature blanching (LTB) prior to cooking on colour, textural, firmness and oscillatory parameters, sensory attributes and overall acceptability of either fresh or frozen/thawed mashed potatoes was studied using response surface methodology (RSM) to establish the optimum temperature and time for blanching in both types of mashed potatoes. A central composite rotatable design was used to study the effects of variation in levels of blanching temperature (57.93–72.07 °C) and time (15.86–44.14 min) on the quality parameters. Stationary points showing maximum thickening had critical temperatures (approximately 67–69 °C) and times (approximately 26–30 min) in the ranges of temperature and time used for each independent variable for both fresh and frozen/thawed mashed potato. Results showed a high correlation between structural reinforcement and overall acceptability under optimum experimental blanching conditions. This demonstrates the potential of this experimental approach in terms of tailoring physical properties to predetermined levels in order to meet consumer preferences in mashed potatoes, and of altering the changes that occur after freezing and thawing.