The present study aimed to compare Portuguese food and nutrient data retrieved from three distinct sources of dietary data: national food supply, household food availability and individual food consumption. In particular it was intended to validate the use of the dietary data derived from the Portuguese household budget surveys (HBS). The data sources used were food balance sheets (FBS) (1990, 1995 and 2000) generated by the Food and Agriculture Organization (FAO), HBS (1990HBS ( , 1995HBS ( and 2000 collected by the National Statistics Institute (INE) and individual consumption obtained through a food frequency questionnaire (FFQ) applied in the context of the EpiPorto study circa 2000. Thirteen comparable food groups were established for analysis. Total energy, macronutrients and other selected dietary components were considered. The average daily values of different dietary sources were compared in absolute amounts (g/person per day) and in relative energy contribution (%E). To evaluate association and agreement between sources, Spearman's correlation coefficients and distance matrices based on Euclidian distances were computed. The obtained average daily per capita amounts reflect the different points of data collection in the food chain; HBS fall in the expected position, below FBS and closer to FFQ. Agreement between FBS, HBS and FFQ was higher when data were expressed in relative energy contribution than when absolute amounts were considered. In general, the observed discrepancies between the three data sources could be attributed to known differences in the methodological approaches. This study supports the finding that despite their constraints the HBS-derived data are a valid option to evaluate dietary habits in Portugal.

Face shields have been adopted worldwide as personal protective equipment for healthcare professionals during the COVID-19 pandemic. This device provides a transparent facial physical barrier reducing the exposure to aerosol particles. The fused deposition modeling (FDM) is the most applied process of additive manufacturing due to its usability and low-cost. The injection molding (IM) is the fastest process for mass production. This study is the first to perform a qualitative comparison between the use of FDM and IM processes for mass production and rapid distribution of face shields in a pandemic. The design of the face shield and tests were conducted in prototyping cycles based on requirements of medical, Brazilian standards, manufacturing, and production. The FDM face shields manufacturing was carried out by a volunteer network, and the IM manufacturing was carried out by companies. The volunteers produced 35,000 medical face shields through the FDM process with daily delivery to several hospitals. A total of 80,000 face shields was produced by the IM process and delivered to remote Brazilian regions. The mass production of 115,000 face shields protected health professionals from public hospitals in all states of Brazil. In a pandemic, both FDM and IM processes are suitable for mass production of face shields. Once a committed network of volunteers is formed in strategic regions, the FDM process promotes a fast daily production. The IM process is the best option for large scale production of face shields and delivery to remote areas where access to 3D printing is reduced.

Forecasting COVID-19 disease severity is key to supporting clinical decision making and assisting resource allocation, particularly in intensive care units (ICUs). Here, we investigated the utility of time- and frequency-related features of the backscattered signal of serum patient samples to predict COVID-19 disease severity immediately after diagnosis. ICU admission was the primary outcome used to define disease severity. We developed a stacking ensemble machine learning model including the backscattered signal features (optical fingerprint), patient comorbidities, and age (AUROC = 0.80), which significantly outperformed the predictive value of clinical and laboratory variables available at hospital admission (AUROC = 0.71). The information derived from patient optical fingerprints was not strongly correlated with any clinical/laboratory variable, suggesting that optical fingerprinting brings unique information for COVID-19 severity risk assessment. Optical fingerprinting is a label-free, real-time, and low-cost technology that can be easily integrated as a front-line tool to facilitate the triage and clinical management of COVID-19 patients.

A new fabrication method of polymeric optical fiber tweezers with a multi-mode tip is presented. Preliminary results show higher robustness, improved ability for 2D trapping and differentiation of particles based on back-scattering analysis.