Bayesian networks to explain the effect of label information on product perception

Interdisciplinary approaches in food research require new methods in data analysis that are able to deal with complexity and facilitate the communication among model users. Four parallel full factorial within-subject designs were performed to examine the relative contribution to consumer product evaluation of intrinsic product properties and information given on packaging. Detailed experimental designs and results obtained from analyses of variance were published [1]. The data was analyzed again with the machine learning modelling technique Bayesian networks. The objective of the current paper is to explain basic features of this technique and its advantages over the standard statistical approach regarding handling of complexity and communication of results. With analysis of variance, visualization and interpretation of main effects and interactions effects becomes difficult in complex systems. The Bayesian network model offers the possibility to formally incorporate (domain) experts knowledge. By combining empirical data with the pre-defined network structure, new relationships can be learned, thus generating an update of current knowledge. Probabilistic inference in Bayesian networks allows instant and global use of the model; its graphical representation makes it easy to visualize and communicate the results. Making use of the most of data from one single experiment, as well as combining data of independent experiments makes Bayesian networks for analysing these and similarly complex and rich data set

Evolutionary Mechanisms of Long-Term Genome Diversification Associated With Niche Partitioning in Marine Picocyanobacteria.

Marine picocyanobacteria of the genera Prochlorococcus and Synechococcus are the most abundant photosynthetic organisms on Earth, an ecological success thought to be linked to the differential partitioning of distinct ecotypes into specific ecological niches. However, the underlying processes that governed the diversification of these microorganisms and the appearance of niche-related phenotypic traits are just starting to be elucidated. Here, by comparing 81 genomes, including 34 new Synechococcus, we explored the evolutionary processes that shaped the genomic diversity of picocyanobacteria. Time-calibration of a core-protein tree showed that gene gain/loss occurred at an unexpectedly low rate between the different lineages, with for instance 5.6 genes gained per million years (My) for the major Synechococcus lineage (sub-cluster 5.1), among which only 0.71/My have been fixed in the long term. Gene content comparisons revealed a number of candidates involved in nutrient adaptation, a large proportion of which are located in genomic islands shared between either closely or more distantly related strains, as identified using an original network construction approach. Interestingly, strains representative of the different ecotypes co-occurring in phosphorus-depleted waters (Synechococcus clades III, WPC1, and sub-cluster 5.3) were shown to display different adaptation strategies to this limitation. In contrast, we found few genes potentially involved in adaptation to temperature when comparing cold and warm thermotypes. Indeed, comparison of core protein sequences highlighted variants specific to cold thermotypes, notably involved in carotenoid biosynthesis and the oxidative stress response, revealing that long-term adaptation to thermal niches relies on amino acid substitutions rather than on gene content variation. Altogether, this study not only deciphers the respective roles of gene gains/losses and sequence variation but also uncovers numerous gene candidates likely involved in niche partitioning of two key members of the marine phytoplankton

Assessment of inflammatory resilience in healthy subjects using dietary lipid and glucose challenges

Background Resilience or the ability of our body to cope with daily-life challenges has been proposed as a new definition of health, with restoration of homeostasis as target resultant of various physiological stress responses. Challenge models may thus be a sensitive measure to study the body’s health. The objective of this study was to select a dietary challenge model for the assessment of inflammatory resilience. Meals are a challenge to metabolic homeostasis and are suggested to affect inflammatory pathways, yet data in literature are limited and inconsistent. Method The kinetic responses of three different dietary challenges and a water control challenge were assessed on various metabolic and inflammatory markers in 14 healthy males and females using a full cross-over study design. The dietary challenges included glucose (75 g glucose in 300 ml water), lipids (200 ml whipping cream) and a mix of glucose and lipids (same amounts as above), respectively. Blood samples were collected at baseline and at 0.5, 1, 2, 4, 6, 8 and 10 h after consumption of the treatment products. Inflammation (IFN¿, IL-1ß, IL-6, IL-8, IL-10, IL-12p70, TNF-a CRP, ICAM-1, VCAM-1, SAA, E-selectin, P-selectin, thrombomodulin, leukocytes, neutrophils, lymphocytes) and clinical (e.g. glucose, insulin, triglycerides) markers as well as gene expression in blood cells and plasma oxylipin profiles were measured. Results All three dietary challenges induced changes related to metabolic control such as increases in glucose and insulin after the glucose challenge and increases in triglycerides after the lipid challenge. In addition, differences between the challenges were observed for precursor oxylipins and some downstream metabolites including DiHETrE’s and HODE’s. However, none of the dietary challenges induced an acute inflammatory response, except for a modest increase in circulating leukocyte numbers after the glucose and mix challenges. Furthermore, subtle, yet statistically significant increases in vascular inflammatory markers (sICAM-1 and sVCAM-1) were found after the mix challenge, when compared to the water control challenge. Conclusions This study shows that dietary glucose and lipid challenges did not induce a strong acute inflammatory response in healthy subjects, as quantified by an accurate and broad panel of parameters

Taxonomic distribution and origins of the extended LHC (light-harvesting complex) antenna protein superfamily

<p>Abstract</p> <p>Background</p> <p>The extended light-harvesting complex (LHC) protein superfamily is a centerpiece of eukaryotic photosynthesis, comprising the LHC family and several families involved in photoprotection, like the LHC-like and the photosystem II subunit S (PSBS). The evolution of this complex superfamily has long remained elusive, partially due to previously missing families.</p> <p>Results</p> <p>In this study we present a meticulous search for LHC-like sequences in public genome and expressed sequence tag databases covering twelve representative photosynthetic eukaryotes from the three primary lineages of plants (Plantae): glaucophytes, red algae and green plants (Viridiplantae). By introducing a coherent classification of the different protein families based on both, hidden Markov model analyses and structural predictions, numerous new LHC-like sequences were identified and several new families were described, including the red lineage chlorophyll <it>a/b</it>-binding-like protein (RedCAP) family from red algae and diatoms. The test of alternative topologies of sequences of the highly conserved chlorophyll-binding core structure of LHC and PSBS proteins significantly supports the independent origins of LHC and PSBS families via two unrelated internal gene duplication events. This result was confirmed by the application of cluster likelihood mapping.</p> <p>Conclusions</p> <p>The independent evolution of LHC and PSBS families is supported by strong phylogenetic evidence. In addition, a possible origin of LHC and PSBS families from different homologous members of the stress-enhanced protein subfamily, a diverse and anciently paralogous group of two-helix proteins, seems likely. The new hypothesis for the evolution of the extended LHC protein superfamily proposed here is in agreement with the character evolution analysis that incorporates the distribution of families and subfamilies across taxonomic lineages. Intriguingly, stress-enhanced proteins, which are universally found in the genomes of green plants, red algae, glaucophytes and in diatoms with complex plastids, could represent an important and previously missing link in the evolution of the extended LHC protein superfamily.</p

The Evolution of Mammalian Gene Families

Gene families are groups of homologous genes that are likely to have highly similar functions. Differences in family size due to lineage-specific gene duplication and gene loss may provide clues to the evolutionary forces that have shaped mammalian genomes. Here we analyze the gene families contained within the whole genomes of human, chimpanzee, mouse, rat, and dog. In total we find that more than half of the 9,990 families present in the mammalian common ancestor have either expanded or contracted along at least one lineage. Additionally, we find that a large number of families are completely lost from one or more mammalian genomes, and a similar number of gene families have arisen subsequent to the mammalian common ancestor. Along the lineage leading to modern humans we infer the gain of 689 genes and the loss of 86 genes since the split from chimpanzees, including changes likely driven by adaptive natural selection. Our results imply that humans and chimpanzees differ by at least 6% (1,418 of 22,000 genes) in their complement of genes, which stands in stark contrast to the oft-cited 1.5% difference between orthologous nucleotide sequences. This genomic “revolving door” of gene gain and loss represents a large number of genetic differences separating humans from our closest relatives

Guest Molecule-Responsive Functional Calcium Phosphonate Frameworks for Tuned Proton Conductivity

We report the synthesis, structural characterization, and functionality of an open-framework hybrid that combines Ca2+ ions and the rigid polyfunctional ligand 5-(dihydroxyphosphoryl) isophthalic acid (PiPhtA). Ca-PiPhtA-I is obtained by slow crystallization at ambient conditions from acidic (pH≈3) aqueous solutions. It possesses a high water content (both Ca coordinated and in the lattice), and importantly, it exhibits water-filled 1D channels. At 75 °C, Ca-PiPhtA-I is partially dehydrated and exhibits a crystalline diffraction pattern that can be indexed in a monoclinic cell with parameters close to the pristine phase. Rietveld refinement was carried out for the sample heated at 75 °C, Ca-PiPhtA-II, using synchrotron powder X-ray diffraction data.All connectivity modes of the “parent” Ca-PiPhtA-I framework are retained in Ca-PiPhtA-II. Upon Ca-PiPhtA-I exposure to ammonia vapors (28% aqueous NH3) a new derivative is obtained (Ca-PiPhtA-NH3) containing 7 NH3 and 16 H2O molecules according to elemental and thermal analyses. Ca-PiPhtA-NH3 exhibits a complex X-ray diffraction pattern with peaks at 15.3 and 13.0 Å that suggest partial breaking and transformation of the parent pillared structure. Although detailed structural identification of Ca-PiPhtA-NH3 was not possible, due in part to nonequilibrium adsorption conditions and the lack of crystallinity, FT-IR spectra and DTA-TG analysis indicate profound structural changes compared to the pristine Ca-PiPhtA-I. At 98% RH and T = 24 °C, proton conductivity, σ, for Ca PiPhtA-I is 5.7 ×10−4 S·cm−1. It increases to 1.3 × 10−3 S·cm−1 upon activation by preheating the sample at 40 °C for 2 h followed by water equilibration at room temperature under controlled conditions. Ca-PiPhtA-NH3 exhibits the highest proton conductivity, 6.6 × 10−3 S·cm−1, measured at 98% RH and T = 24 °C. Ea for proton transfer in the above-mentioned frameworks range between 0.23 and 0.4 eV, typical of a Grothuss mechanism of proton conduction.Proyecto nacional MAT2010-1517

The Biodiversity of the Mediterranean Sea: Estimates, Patterns, and Threats

The Mediterranean Sea is a marine biodiversity hot spot. Here we combined an extensive literature analysis with expert opinions to update publicly available estimates of major taxa in this marine ecosystem and to revise and update several species lists. We also assessed overall spatial and temporal patterns of species diversity and identified major changes and threats. Our results listed approximately 17,000 marine species occurring in the Mediterranean Sea. However, our estimates of marine diversity are still incomplete as yet—undescribed species will be added in the future. Diversity for microbes is substantially underestimated, and the deep-sea areas and portions of the southern and eastern region are still poorly known. In addition, the invasion of alien species is a crucial factor that will continue to change the biodiversity of the Mediterranean, mainly in its eastern basin that can spread rapidly northwards and westwards due to the warming of the Mediterranean Sea. Spatial patterns showed a general decrease in biodiversity from northwestern to southeastern regions following a gradient of production, with some exceptions and caution due to gaps in our knowledge of the biota along the southern and eastern rims. Biodiversity was also generally higher in coastal areas and continental shelves, and decreases with depth. Temporal trends indicated that overexploitation and habitat loss have been the main human drivers of historical changes in biodiversity. At present, habitat loss and degradation, followed by fishing impacts, pollution, climate change, eutrophication, and the establishment of alien species are the most important threats and affect the greatest number of taxonomic groups. All these impacts are expected to grow in importance in the future, especially climate change and habitat degradation. The spatial identification of hot spots highlighted the ecological importance of most of the western Mediterranean shelves (and in particular, the Strait of Gibraltar and the adjacent Alboran Sea), western African coast, the Adriatic, and the Aegean Sea, which show high concentrations of endangered, threatened, or vulnerable species. The Levantine Basin, severely impacted by the invasion of species, is endangered as well

Interactive impact of childhood maltreatment, depression, and age on cortical brain structure: Mega-analytic findings from a large multi-site cohort

Background. Childhood maltreatment (CM) plays an important role in the development of major depressive disorder (MDD). The aim of this study was to examine whether CM severity and type are associated with MDD-related brain alterations, and how they interact with sex and age.MethodsWithin the ENIGMA-MDD network, severity and subtypes of CM using the Childhood Trauma Questionnaire were assessed and structural magnetic resonance imaging data from patients with MDD and healthy controls were analyzed in a mega-analysis comprising a total of 3872 participants aged between 13 and 89 years. Cortical thickness and surface area were extracted at each site using FreeSurfer.ResultsCM severity was associated with reduced cortical thickness in the banks of the superior temporal sulcus and supramarginal gyrus as well as with reduced surface area of the middle temporal lobe. Participants reporting both childhood neglect and abuse had a lower cortical thickness in the inferior parietal lobe, middle temporal lobe, and precuneus compared to participants not exposed to CM. In males only, regardless of diagnosis, CM severity was associated with higher cortical thickness of the rostral anterior cingulate cortex. Finally, a significant interaction between CM and age in predicting thickness was seen across several prefrontal, temporal, and temporo-parietal regions.ConclusionsSeverity and type of CM may impact cortical thickness and surface area. Importantly, CM may influence age-dependent brain maturation, particularly in regions related to the default mode network, perception, and theory of mind. © 2019 Cambridge University Press

Bayesian networks for food science: theoretical background and potential applications

Although Bayesian networks have gained popularity in many fields, they have just recently emerged in food-related problems. This technique can be used as a tool for prediction, explanation, exploration or decision making under uncertainty. The chapter mainly gives a theoretical background of Bayesian networks through a food example. It also discusses the advantages and challenges, as well as potential applications of Bayesian networks in the food area

Prediction of notes from vocal time series produced by singing voice

SIGLEAvailable from TIB Hannover: RR 8460(2003,1) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman