Abstract
Purpose: Male Breast Cancer (MBC) remains a poor understood disease. Prognostic factors are not well established and specific prognostic subgroups are warranted. Patients/methods: Retrospectively revision of 111 cases treated in the same Cancer Center. Blinded-central pathological revision with immunohistochemical (IHQ) analysis for estrogen (ER), progesterone (PR) and androgen (AR) receptors, HER2, ki67 and p53 was done. Cox regression model was used for uni/multivariate survival analysis. Two classifications of Female Breast Cancer (FBC) subgroups (based in ER, PR, HER2, 2000 classification, and in ER, PR, HER2, ki67, 2013 classification) were used to achieve their prognostic value in MBC patients. Hierarchical clustering was performed to define subgroups based on the six-IHQ panel. Results: According to FBC classifications, the majority of tumors were luminal: A (89.2%; 60.0%) and B (7.2%; 35.8%). Triple negative phenotype was infrequent (2.7%; 3.2%) and HER2 enriched, non-luminal, was rare (=1% in both). In multivariate analysis the poor prognostic factors were: size >2 cm (HR:1.8; 95%CI:1.0-3.4years, p = 0.049), absence of ER (HR:4.9; 95%CI:1.7-14.3years, p = 0.004) and presence of distant metastasis (HR:5.3; 95%CI:2.2-3.1years, p < 0.001). FBC subtypes were independent prognostic factors (p = 0.009, p = 0.046), but when analyzed only luminal groups, prognosis did not differ regardless the classification used (p > 0.20). Clustering defined different subgroups, that have prognostic value in multivariate analysis (p = 0.005), with better survival in ER/PR+, AR-, HER2-and ki67/p53 low group (median: 11.5 years; 95%CI: 6.2-16.8 years) and worst in PR-group (median:4.5 years; 95%CI: 1.6-7.8 years). Conclusion: FBC subtypes do not give the same prognostic information in MBC even in luminal groups. Two subgroups with distinct prognosis were identified in a common six-IHQ panel. Future studies must achieve their real prognostic value in these patients. © 2015 Elsevier Ltd.

Abstract
Background: Tamoxifen remains the standard hormonotherapy for Male breast cancer patients (MBC). Previous studies, in women, tried to evaluate the impact of CYP2D6 polymorphisms in tamoxifen efficacy with conflicting results. Herein we analyze the relation between CYP2D6*4 polymorphism and survival in MBC patients. Patients and methods: Fifty-three patients, proposed to tamoxifen in adjuvant setting, were enrolled. Clinical information was collected from records and histological revision with additional immunochemistry analysis was done to better characterize the tumors. Comprehensive CYP2D6*4 genotyping from blood or tumor tissue was performed and translated into two predicted metabolic activity groups. Results: Patients included in the two CYP2D6*4 groups did not differ concerning to age, histological characteristics, and primary treatments performed. Median age at diagnosis was 63 years-old and patients were submitted at least to mastectomy and adjuvant hormonotherapy. Recurrence was observed in 7 patients (13.2%) and 13 patients (25.5%) died with a 5-year disease-free survival of 86.2%. The poorer metabolizer group had a high risk for recurrence (p = 0.034) and this outcome effect remains in different subgroups: in tumors larger than 2 cm (p < 0.001), nodal status, N0 vs N+ (p = 0.04) and in advanced stage, stage III (p < 0.001). Poorer metabolizer patients had also a worse overall survival when tumors were larger than 2 cm (p = 0.03). Conclusions: In our series, there was an association between CYP2D6*4 polymorphism and a probability of recurrence, with a consistent effect in risk groups defined by classic prognostic factors. Multicentric studies with larger samples are needed to validate these results.

Abstract
Climate change has raised consciousness of the need to use cleaner energy instead of fossil fuels. Meanwhile, a change of consciousness regarding resource use has to be achieved, which can be triggered by energy consumption monitoring studies that also provide useful recommendations for energy saving. Over time, researchers have identified behaviors by monitoring energy consumption in households, but these studies are usually limited to the number of monitored households and/or to the geographical region in which the monitoring takes place. In this research work, a study with a global reach is proposed to mitigate these limitations. Using a hierarchical clustering algorithm, three distinct groups were identified using the collected data, representative of distinct behaviors. The results illustrate several behaviors regarding energy consumption, like cold temperatures, seasonal behaviors, wake up hour, stay-at-home periods, and standby device consumption.

Abstract
High failure and dropout rates are common in higher education institutions with introductory programming courses. Some researchers advocate that sometimes teachers don't use correct methods of assessment and that many students pass in programming without knowing how to program. In this paper authors describe the assessment methodology applied to a first year, first semester, Biomedical Engineering programming course (2015/2016). Students' programming skills were tested by playing a game in the first class, then they were assessed with three tests and a final exam, each with topics the authors considered fundamental for the students to master. A correlation analyses between the different types of tests and exam questions is done, to evaluate the most suitable, for assessing programming knowledge, showing that it is possible to use different question types as a pedagogical strategy, to assess student difficulty levels and programming skills, that help students acquire abstract, reasoning and algorithm thinking in an acceptable level. Also, it is shown that different forms of questions are equivalent to assess equal knowledge and that it is possible to predict the ability of a student to program at an early stage.

Abstract

Abstract