Addressing Food Loss and Waste : A Global Problem with Local Solutions

The report focuses on the role that food loss and waste (FLW) could play in reducing the environmental footprint of food systems while attempting to meet the caloric and nutrient needs of a population expected to increase by 3 billion people in the next 30 years. The performance of the global food system over the last century has been extraordinary. From a global population of 1.6 billion people in 1900 to nearly 8 billion in 2020, the agri-food sector has risen to the challenge of providing global caloric sufficiency, mainly by increasing yields of a few principal staple crops. However, this path is no longer sustainable

Solar flare prediction using advanced feature extraction, machine learning and feature selection

YesNovel machine-learning and feature-selection algorithms have been developed to study: (i) the flare prediction capability of magnetic feature (MF) properties generated by the recently developed Solar Monitor Active Region Tracker (SMART); (ii) SMART's MF properties that are most significantly related to flare occurrence. Spatio-temporal association algorithms are developed to associate MFs with flares from April 1996 to December 2010 in order to differentiate flaring and non-flaring MFs and enable the application of machine learning and feature selection algorithms. A machine-learning algorithm is applied to the associated datasets to determine the flare prediction capability of all 21 SMART MF properties. The prediction performance is assessed using standard forecast verification measures and compared with the prediction measures of one of the industry's standard technologies for flare prediction that is also based on machine learning - Automated Solar Activity Prediction (ASAP). The comparison shows that the combination of SMART MFs with machine learning has the potential to achieve more accurate flare prediction than ASAP. Feature selection algorithms are then applied to determine the MF properties that are most related to flare occurrence. It is found that a reduced set of 6 MF properties can achieve a similar degree of prediction accuracy as the full set of 21 SMART MF properties

Biophysical and electrochemical studies of protein-nucleic acid interactions

This review is devoted to biophysical and electrochemical methods used for studying protein-nucleic acid (NA) interactions. The importance of NA structure and protein-NA recognition for essential cellular processes, such as replication or transcription, is discussed to provide background for description of a range of biophysical chemistry methods that are applied to study a wide scope of protein-DNA and protein-RNA complexes. These techniques employ different detection principles with specific advantages and limitations and are often combined as mutually complementary approaches to provide a complete description of the interactions. Electrochemical methods have proven to be of great utility in such studies because they provide sensitive measurements and can be combined with other approaches that facilitate the protein-NA interactions. Recent applications of electrochemical methods in studies of protein-NA interactions are discussed in detail

Prostate cancer in BRCA2 germline mutation carriers is associated with poorer prognosis

BACKGROUND: The germline BRCA2 mutation is associated with increased prostate cancer (PrCa) risk. We have assessed survival in young PrCa cases with a germline mutation in BRCA2 and investigated loss of heterozygosity at BRCA2 in their tumours. METHODS: Two cohorts were compared: one was a group with young-onset PrCa, tested for germline BRCA2 mutations (6 of 263 cases had a germline BRAC2 mutation), and the second was a validation set consisting of a clinical set from Manchester of known BRCA2 mutuation carriers (15 cases) with PrCa. Survival data were compared with a control series of patients in a single clinic as determined by Kaplan-Meier estimates. Loss of heterozygosity was tested for in the DNA of tumour tissue of the young-onset group by typing four microsatellite markers that flanked the BRCA2 gene, followed by sequencing. RESULTS: Median survival of all PrCa cases with a germline BRCA2 mutation was shorter at 4.8 years than was survival in controls at 8.5 years (P = 0.002). Loss of heterozygosity was found in the majority of tumours of BRCA2 mutation carriers. Multivariate analysis confirmed that the poorer survival of PrCa in BRCA2 mutation carriers is associated with the germline BRCA2 mutation per se. CONCLUSION: BRCA2 germline mutation is an independent prognostic factor for survival in PrCa. Such patients should not be managed with active surveillance as they have more aggressive disease. British Journal of Cancer (2010) 103, 918-924. doi:10.1038/sj.bjc.6605822 www.bjcancer.com Published online 24 August 2010 (C) 2010 Cancer Research U

Genetics of Microenvironmental Sensitivity of Body Weight in Rainbow Trout (Oncorhynchus mykiss) Selected for Improved Growth

Microenvironmental sensitivity of a genotype refers to the ability to buffer against non-specific environmental factors, and it can be quantified by the amount of residual variation in a trait expressed by the genotype’s offspring within a (macro)environment. Due to the high degree of polymorphism in behavioral, growth and life-history traits, both farmed and wild salmonids are highly susceptible to microenvironmental variation, yet the heritable basis of this characteristic remains unknown. We estimated the genetic (co)variance of body weight and its residual variation in 2-year-old rainbow trout (Oncorhynchus mykiss) using a multigenerational data of 45,900 individuals from the Finnish national breeding programme. We also tested whether or not microenvironmental sensitivity has been changed as a correlated genetic response when genetic improvement for growth has been practiced over five generations. The animal model analysis revealed the presence of genetic heterogeneity both in body weight and its residual variation. Heritability of residual variation was remarkably lower (0.02) than that for body weight (0.35). However, genetic coefficient of variation was notable in both body weight (14%) and its residual variation (37%), suggesting a substantial potential for selection responses in both traits. Furthermore, a significant negative genetic correlation (−0.16) was found between body weight and its residual variation, i.e., rapidly growing genotypes are also more tolerant to perturbations in microenvironment. The genetic trends showed that fish growth was successfully increased by selective breeding (an average of 6% per generation), whereas no genetic change occurred in residual variation during the same period. The results imply that genetic improvement for body weight does not cause a concomitant increase in microenvironmental sensitivity. For commercial production, however, there may be high potential to simultaneously improve weight gain and increase its uniformity if both criteria are included in a selection index

Cyanobacterial lipopolysaccharides and human health – a review

Cyanobacterial lipopolysaccharide/s (LPS) are frequently cited in the cyanobacteria literature as toxins responsible for a variety of heath effects in humans, from skin rashes to gastrointestinal, respiratory and allergic reactions. The attribution of toxic properties to cyanobacterial LPS dates from the 1970s, when it was thought that lipid A, the toxic moiety of LPS, was structurally and functionally conserved across all Gram-negative bacteria. However, more recent research has shown that this is not the case, and lipid A structures are now known to be very different, expressing properties ranging from LPS agonists, through weak endotoxicity to LPS antagonists. Although cyanobacterial LPS is widely cited as a putative toxin, most of the small number of formal research reports describe cyanobacterial LPS as weakly toxic compared to LPS from the Enterobacteriaceae. We systematically reviewed the literature on cyanobacterial LPS, and also examined the much lager body of literature relating to heterotrophic bacterial LPS and the atypical lipid A structures of some photosynthetic bacteria. While the literature on the biological activity of heterotrophic bacterial LPS is overwhelmingly large and therefore difficult to review for the purposes of exclusion, we were unable to find a convincing body of evidence to suggest that heterotrophic bacterial LPS, in the absence of other virulence factors, is responsible for acute gastrointestinal, dermatological or allergic reactions via natural exposure routes in humans. There is a danger that initial speculation about cyanobacterial LPS may evolve into orthodoxy without basis in research findings. No cyanobacterial lipid A structures have been described and published to date, so a recommendation is made that cyanobacteriologists should not continue to attribute such a diverse range of clinical symptoms to cyanobacterial LPS without research confirmation

Natural Allelic Variation Defines a Role for ATMYC1: Trichome Cell Fate Determination

The molecular nature of biological variation is not well understood. Indeed, many questions persist regarding the types of molecular changes and the classes of genes that underlie morphological variation within and among species. Here we have taken a candidate gene approach based on previous mapping results to identify the gene and ultimately a polymorphism that underlies a trichome density QTL in Arabidopsis thaliana. Our results show that natural allelic variation in the transcription factor ATMYC1 alters trichome density in A. thaliana; this is the first reported function for ATMYC1. Using site-directed mutagenesis and yeast two-hybrid experiments, we demonstrate that a single amino acid replacement in ATMYC1, discovered in four ecotypes, eliminates known protein–protein interactions in the trichome initiation pathway. Additionally, in a broad screen for molecular variation at ATMYC1, including 72 A. thaliana ecotypes, a high-frequency block of variation was detected that results in >10% amino acid replacement within one of the eight exons of the gene. This sequence variation harbors a strong signal of divergent selection but has no measurable effect on trichome density. Homologs of ATMYC1 are pleiotropic, however, so this block of variation may be the result of natural selection having acted on another trait, while maintaining the trichome density role of the gene. These results show that ATMYC1 is an important source of variation for epidermal traits in A. thaliana and indicate that the transcription factors that make up the TTG1 genetic pathway generally may be important sources of epidermal variation in plants

Genomic Analysis of QTLs and Genes Altering Natural Variation in Stochastic Noise

Quantitative genetic analysis has long been used to study how natural variation of genotype can influence an organism's phenotype. While most studies have focused on genetic determinants of phenotypic average, it is rapidly becoming understood that stochastic noise is genetically determined. However, it is not known how many traits display genetic control of stochastic noise nor how broadly these stochastic loci are distributed within the genome. Understanding these questions is critical to our understanding of quantitative traits and how they relate to the underlying causal loci, especially since stochastic noise may be directly influenced by underlying changes in the wiring of regulatory networks. We identified QTLs controlling natural variation in stochastic noise of glucosinolates, plant defense metabolites, as well as QTLs for stochastic noise of related transcripts. These loci included stochastic noise QTLs unique for either transcript or metabolite variation. Validation of these loci showed that genetic polymorphism within the regulatory network alters stochastic noise independent of effects on corresponding average levels. We examined this phenomenon more globally, using transcriptomic datasets, and found that the Arabidopsis transcriptome exhibits significant, heritable differences in stochastic noise. Further analysis allowed us to identify QTLs that control genomic stochastic noise. Some genomic QTL were in common with those altering average transcript abundance, while others were unique to stochastic noise. Using a single isogenic population, we confirmed that natural variation at ELF3 alters stochastic noise in the circadian clock and metabolism. Since polymorphisms controlling stochastic noise in genomic phenotypes exist within wild germplasm for naturally selected phenotypes, this suggests that analysis of Arabidopsis evolution should account for genetic control of stochastic variance and average phenotypes. It remains to be determined if natural genetic variation controlling stochasticity is equally distributed across the genomes of other multi-cellular eukaryotes