Quality changes and shelf-life prediction of a fresh fruit and vegetables purple smoothie

The sensory, microbial and bioactive quality changes of untreated (CTRL) and mild heat−treated (HT; 90 ºC/45 s) smoothies were studied and modelled throughout storage (5, 15 and 25 ºC). The overall acceptability was better preserved in HT samples being highly correlated (hierarchical clustering) with the flavour. The sensory quality data estimated smoothie shelf−life (CTRL/HT) of 18/55 (at 5 ºC), 4.5/12 (at 15 ºC), 2.4/5.8 (at 25 ºC) days. The yeast and moulds growth rate was lower in HT compared to CTRL while a lag phase for mesophiles/psychrophiles was observed in HT−5/15 ºC. HT and 5 ºC−storage stabilized the phenolics content. FRAP reported the best correlation (R2=0.94) with the studied bioactive compounds, followed by ABTS (R2=0.81) while DPPH was the total antioxidant capacity method with the lowest adjustment (R2=0.49). Conclusively, modelling was used to estimate the shelf−life of a smoothie based on quality retention after a short time−high temperature heat treatment that better preserved microbial and nutritional quality during storage.The financial support of this research was provided by the Ministerio Español de Economía y Competitividad MINECO (Projects AGL2013−48830−C2−1−R and AGL2013−48993−C2−1−R) and by FEDER funds. G.A. González−Tejedor thanks to Panamá Government for the scholarship to carry out his PhD Thesis. A. Garre (BES−2014−070946) is grateful to the MINECO for awarding him a pre−doctoral grant. We are also grateful to E. Esposito and N. Castillejo for their skilful technical assistance

Quality of life in caregivers of patients with schizophrenia: A literature review

<p>Abstract</p> <p>Background</p> <p>A couple of decades ago, hospitals or psychiatric institutions were in charge of caring for patients with schizophrenia; however, nowadays this role is performed by one or more patient's relatives. Evidence shows that informal caregivers experience negative changes in their quality of life (QOL). The aim of this study is to review the main factors associated with the QOL of caregivers of people with schizophrenia.</p> <p>Methods</p> <p>A search through databases from journals published last decade between 1998 and 2008 was performed. In accordance with the inclusion criteria, titles and abstracts of citations obtained from the search were examined independently by two authors and irrelevant articles discarded. The full text of those studies considered relevant by either reviewer were obtained and assessed independently. Where differences of opinion rose they were resolved by discussion. Out of the 258 references, 37 were included in the review.</p> <p>Studies which assessed factors associated with caregivers of people with schizophrenia's quality of life were included and the information summarized.</p> <p>Results</p> <p>Evidence suggest that physical, emotional and economic distress affect negatively caregiver's QOL as a result of a number of unfulfilled needs such as, restoration of patient functioning in family and social roles, economic burden, lack of spare time, among other factors.</p> <p>Conclusion</p> <p>Decreased QOL may be associated with caregivers' burden, lack of social support, course of the disease and family relationships problems. In addition, in developing countries, QOL is affected by caregivers' economic burden. High quality research is needed in order to identify factors associated with QOL over time and testing the efficacy of interventions aiming to improve QOL in caregivers of patients with schizophrenia.</p

A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes(1). Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel(2)) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.A large genome-wide association study of more than 5 million individuals reveals that 12,111 single-nucleotide polymorphisms account for nearly all the heritability of height attributable to common genetic variants

A saturated map of common genetic variants associated with human height.

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis.

BACKGROUND: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. RESULTS: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. CONCLUSIONS: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk