Carotenoid pigment content is an important quality trait as it confers a natural bright yellow color to pasta preferred by consumers (whiteness vs. yellowness) and nutrients, such as provitamin A and antioxidants, essential for human diet. The main goal of the present review is to summarize the knowledge about the genetic regulation of the accumulation of pigment content in durum wheat grain and describe the genetic improvements obtained by using breeding approaches in the last two decades. Although carotenoid pigment content is a quantitative character regulated by various genes with additive effects, its high heritability has facilitated the durum breeding progress for this quality trait. Mapping research for yellow index and yellow pigment content has identified quantitative trait loci (QTL) on all wheat chromosomes. The major QTL, accounting for up to 60%, were mapped on 7L homoeologous chromosome arms, and they are explained by allelic variations of the phytoene synthase (PSY) genes. Minor QTL were detected on all chromosomes and associated to significant molecular markers, indicating the complexity of the trait. Despite there being currently a better knowledge of the mechanisms controlling carotenoid content and composition, there are gaps that require further investigation and bridging to better understand the genetic architecture of this important trait. The development and the utilization of molecular markers in marker-assisted selection (MAS) programs for improving grain quality have been reviewed and discussed.

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Isoflavones, which exist in their conjugated or aglycone forms, are well recognized for their potential health benefits. However, isoflavones as aglycone have been regarded as the most bioactive form. In the present study, the profile of isoflavones and their scavenging activity as affected by germination were investigated in several soybean fractions, namely cotyledons, epicotyls, radicles, and hypocotyls. Only aglycones were detected in the radicles from 144 h until 168 h of germination, which makes this component a potential feedstock for studies aiming at isolation, especially of daidzein, which was present in higher concentrations. In terms of total yield and contribution to the total weight of the germinated soybeans, the cotyledons are the best source of aglycones, which was achieved at 144 h of germination. The higher scavenging activity of high-aglycone components from germinated soybeans supports the use of germination to obtain functional foods and/or ingredients with potentially superior bioactivities.

Respiratory insufficiency is a symptom that requires hospitalization. This work investigates whether it is possible to detect this condition by analyzing patient's speech samples; the analysis was performed on data collected during the first wave of the COVID-19 pandemic in 2020, and thus limited to respiratory insufficiency in COVID-19 patients. For that, a dataset was created consisting of speech emissions of both COVID-19 patients affected by respiratory insufficiency and a control group. This dataset was used to build a Convolution Neural Network to detect respiratory insufficiency using speech emission MFCC representations. Methodologically, dealing with background noise was a challenge, so we also collected background noise from COVID-19 wards where patients were located. Due to the difficulty in filtering noise without eliminating crucial information, noise samples were injected in the control group data to prevent bias. Moreover, we investigated (i) two approaches to address the duration variance of audios, and (ii) the ideal number of noise samples to inject in both patients and the control group to prevent bias and overfitting. The techniques developed reached 91.66% accuracy. Thus we validated the project's Leading Hypothesis, namely that it is possible to detect respiratory insufficiency in speech utterances, under real-life environmental conditions; we believe our results justify further enquiries into the use of automated speech analysis to support health professionals in triage procedures.

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