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In Spain, the health crisis caused by the COVID-19 pandemic led to the declaration of a state of alarm in the whole country in 2020; in this context, a nationwide lockdown was implemented, potentially altering the dietary habits of the population. The aims of this study were to describe the diet and its nutritional quality in Spanish households during the first COVID-19 epidemic wave and to compare them with the same period in 2019. Data on monthly foods and beverages household purchases in 2019 and 2020 were obtained from the nationwide Food Consumption Surveys. In April, there was an average increase, compared with 2019, of more than 40% for all food groups, with significant peaks in: alcoholic beverages (75%), appetizers (60%), eggs (59%), sugar and sweets (52%), and vegetables (50%). In March, the greatest peak was for pulses, with a 63% increment. The mean energy value of purchased foods in April was 2801 kcal/person/day, corresponding to an increase of 771 kcal/person/day (+38%), compared to the same month of 2019 (March and May: +520 kcal (+26%), June: +343 kcal (+18%)). Regarding nutrient density, there was a reduction in calcium, iodine, zinc, selenium, riboflavin, vitamins B12, D, A, especially retinol, and an increase in fibre, sodium, folic acid, carotenes and vitamin E. Alcohol content per 1000 kcal increased by more than 20% from April to July. Food purchase patterns in Spanish households changed during lockdown and after it, with no appreciable improvement in the quality of the diet., Sección Dptal. de Nutrición y Ciencia de los Alimentos (Veterinaria), Fac. de Veterinaria, TRUE, pub

Background Whether there are lifetime points of greater sensitivity to the deleterious effects of alcohol intake on the breasts remains inconclusive. Objective To compare the influence of distinctive trajectories of alcohol consumption throughout a woman's life on development of breast cancer (BC). Methods 1278 confirmed invasive BC cases and matched (by age and residence) controls from the Epi-GEICAM study (Spain) were used. The novel group-based trajectory modelling was used to identify different alcohol consumption trajectories throughout women's lifetime. Results Four alcohol trajectories were identified. The first comprised women (45%) with low alcohol consumption (<5 g/day) throughout their life. The second included those (33%) who gradually moved from a low alcohol consumption in adolescence to a moderate in adulthood (5 to <15 g/day), never having a high consumption; and oppositely, women in the third trajectory (16%) moved from moderate consumption in adolescence, to a lower consumption in adulthood. Women in the fourth (6%) moved from a moderate alcohol consumption in adolescence to the highest consumption in adulthood (>= 15 g/day), never having a low alcohol consumption. Comparing with the first trajectory, the fourth doubled BC risk (OR 2.19; 95% CI 1.27, 3.77), followed by the third (OR 1.44; 0.96, 2.16) and ultimately by the second trajectory (OR 1.17; 0.86, 1.58). The magnitude of BC risk was greater in postmenopausal women, especially in those with underweight or normal weight. When alcohol consumption was independently examined at each life stage, >= 15 g/day of alcohol consumption in adolescence was strongly associated with BC risk followed by consumption in adulthood. Conclusions The greater the alcohol consumption accumulated throughout life, the greater the risk of BC, especially in postmenopausal women. Alcohol consumption during adolescence may particularly influence BC risk.

Background: The fight against the current coronavirus disease 2019 (COVID-19) pandemic has created a huge demand of biotechnological, pharmaceutical, research and sanitary materials at unprecedented scales. One of the most urgent demands affects the diagnostic tests. The growing need for rapid and accurate laboratory diagnostic tests requires the development of biotechnological processes aimed at producing reagents able to cope with this demand in a scalable, cost-effective manner, with rapid turnaround times. This is particularly applicable to the antigens employed in serological tests. Recombinant protein expression using plants as biofactories is particularly suitable for mass production of protein antigens useful in serological diagnosis, with a neat advantage in economic terms. Methods: We expressed a large portion of the nucleoprotein (N) derived from SARS-CoV-2 in Nicotiana benthamiana plants. After purification, the recombinant N protein obtained was used to develop an indirect enzyme-linked immunosorbent assay (ELISA) for detection of antibodies to SARS-CoV-2 in human sera. To validate the ELISA, a panel of 416 sera from exposed personnel at essential services in Madrid City Council were tested, and the results compared to those obtained by another ELISA, already validated, used as reference. Furthermore, a subset of samples for which RT-PCR results were available were used to confirm sensitivity and specificity of the test. Results: The performance of the N protein expressed in plants as antigen in serologic test for SARS-CoV-2 antibody detection was shown to be highly satisfactory, with calculated diagnostic sensitivity of 96.41% (95% CI: 93.05–98.44) and diagnostic specificity of 96.37 (95% CI: 93.05–98.44) as compared to the reference ELISA, with a kappa (K) value of 0.928 (95% CI:0.892–0.964). Furthermore, the ELISA developed with plant-derived N antigen detected SARS-CoV-2 antibodies in 84 out of 93 sera from individuals showing RT-PCR positive result

[EN] Background and Objective: Breast cancer is the most frequent cancer in women. The Spanish healthcare network established population-based screening programs in all Autonomous Communities, where mammograms of asymptomatic women are taken with early diagnosis purposes. Breast density assessed from digital mammograms is a biomarker known to be related to a higher risk to develop breast cancer. It is thus crucial to provide a reliable method to measure breast density from mammograms. Furthermore the complete automation of this segmentation process is becoming fundamental as the amount of mammograms increases every day. Important challenges are related with the differences in images from different devices and the lack of an objective gold standard. This paper presents a fully automated framework based on deep learning to estimate the breast density. The framework covers breast detection, pectoral muscle exclusion, and fibroglandular tissue segmentation. Methods: A multi-center study, composed of 1785 women whose "for presentation" mammograms were segmented by two experienced radiologists. A total of 4992 of the 6680 mammograms were used as training corpus and the remaining (1688) formed the test corpus. This paper presents a histogram normalization step that smoothed the difference between acquisition, a regression architecture that learned segmentation parameters as intrinsic image features and a loss function based on the DICE score. Results: The results obtained indicate that the level of concordance (DICE score) reached by the two radiologists (0.77) was also achieved by the automated framework when it was compared to the closest breast segmentation from the radiologists. For the acquired with the highest quality device, the DICE score per acquisition device reached 0.84, while the concordance between radiologists was 0.76. Conclusions: An automatic breast density estimator based on deep learning exhibits similar performance when compared with two experienced ra

Background: Night-shift work, exposure to artificial light-at-night (ALAN) and particularly blue light spectrum, and the consequent circadian disruption may increase the risk of breast and prostate cancer. Colorectal cancer risk may also be increased among night-shift workers. We investigated the association between exposure to ALAN according to light spectrum and colorectal cancer among subjects who had never worked at night in a general population case-control study in Spain. Methods: We examined information on 661 incident histologically verified colorectal cancer cases and 1,322 controls from Barcelona and Madrid, 2007-2013. Outdoor ALAN exposure was based on images from the International Space Station (ISS) including data on remotely sensed upward light intensity. We derived adjusted odds ratio (OR) estimates and confidence intervals (CI) for visual light, blue light, and spectral sensitivities of the five human photopigments assigned to participant's geocoded longest residence. Results: Exposure to blue light spectrum was positively associated with colorectal cancer (OR = 1.6; 95% CI: 1.2-2.2; highest vs. lowest tertile). ORs were similar (OR = 1.7; 95% CI: 1.3-2.3) when further adjusting for area socioeconomic status, diet patterns, smoking, sleep, and family history. We observed no association for outdoor visual light (full spectrum) (OR = 1.0; 95% CI, 0.7-1.2; highest vs. lowest tertile). Analysis of the five photopigments gave similar results with increased risks for shorter wavelengths overlapping with the blue spectrum and no association for longer wavelengths. Conclusions: Outdoor blue light spectrum exposure that is increasingly prevalent in recent years may be associated with colorectal cancer risk. See video abstract: http://links.lww.com/EDE/B708. © 2020 Wolters Kluwer Health. All rights reserved.