Plant cell walls: impact on nutrient bioaccessibility and digestibility

Cell walls are important structural components of plants, affecting both the bioaccessibility and subsequent digestibility of the nutrients that plant-based foods contain. These supramolecular structures are composed of complex heterogeneous networks primarily consisting of cellulose, and hemicellulosic and pectic polysaccharides. The composition and organization of these different polysaccharides vary depending on the type of plant tissue, imparting them with specific physicochemical properties. These properties dictate how the cell walls behave in the human gastrointestinal tract, and how amenable they are to digestion, thereby modulating nutrient release from the plant tissue. This short narrative review presents an overview of our current knowledge on cell walls and how they impact nutrient bioaccessibility and digestibility. Some of the most relevant methods currently used to characterize the food matrix and the cell walls are also described

Designing a mobile augmented memory system for people with traumatic brain injuries

Augmented memory systems help people remember events in their lives. Individuals with Traumatic Brain Injury (TBI) often have memory impairments. We conducted a user study to learn about strategies individuals with TBI use to remember events in their lives. We explored what characteristics individuals with TBI expect of an augmented memory system. We then investigated these aspects in an initial mobile app design, and propose here a concept for a rehearsal application that addresses the issues found in our studies

Erosion patterns in a sediment layer

We report here on a laboratory-scale experiment which reproduces a rich variety of natural patterns with few control parameters. In particular, we focus on intriguing rhomboid structures often found on sandy shores and flats. We show that the standard views based on water surface waves come short to explain the phenomenon and we evidence a new mechanism based on a mud avalanche instability.Comment: 4 pages, 4 figures, to appear as Phys. Rev. E rapid com

Diet of the Common Warthog (Phacochoerus africanus) on Former Cattle Grounds in a Tanzanian Savanna

In otherwise nutrient-poor savannas, fertile vegetation patches are particularly attractive to ungulates because of the higher-quality food they provide. We investigated forage plants and diet of the common warthog (Phacochoerus africanus) on an abandoned cattle ranch in coastal Tanzania. The forage grasses of highest nutritional quality occurred in former paddock enclosures (bomas) where cattle had been herded at night. In the dry season, grass samples from bomas contained approximately 4 times as much nitrogen and phosphorus as those of the surrounding vegetation. δ15N values of soil and plants also were highest in bomas and decreased significantly with distance, and high δ15N values in feces suggest that warthogs preferentially fed in the vicinity of the former bomas. δ13C values of warthog feces indicate that warthogs ingested on average 83% (77-98%) C4 grasses, with this proportion varying regionally but not seasonally. We conclude that, for medium-sized selective grazers such as warthogs, bomas represent attractive feeding grounds. We also hypothesize that by promoting nutrient turnover in these patchily distributed areas, grazing animals help to maintain them as sources of high-quality forag

A quark action for very coarse lattices

We investigate a tree-level O(a^3)-accurate action, D234c, on coarse lattices. For the improvement terms we use tadpole-improved coefficients, with the tadpole contribution measured by the mean link in Landau gauge. We measure the hadron spectrum for quark masses near that of the strange quark. We find that D234c shows much better rotational invariance than the Sheikholeslami-Wohlert action, and that mean-link tadpole improvement leads to smaller finite-lattice-spacing errors than plaquette tadpole improvement. We obtain accurate ratios of lattice spacings using a convenient ``Galilean quarkonium'' method. We explore the effects of possible O(alpha_s) changes to the improvement coefficients, and find that the two leading coefficients can be independently tuned: hadron masses are most sensitive to the clover coefficient, while hadron dispersion relations are most sensitive to the third derivative coefficient C_3. Preliminary non-perturbative tuning of these coefficients yields values that are consistent with the expected size of perturbative corrections.Comment: 22 pages, LaTe

A random set scoring model for prioritization of disease candidate genes using protein complexes and data-mining of GeneRIF, OMIM and PubMed records.

BACKGROUND: Prioritizing genetic variants is a challenge because disease susceptibility loci are often located in genes of unknown function or the relationship with the corresponding phenotype is unclear. A global data-mining exercise on the biomedical literature can establish the phenotypic profile of genes with respect to their connection to disease phenotypes. The importance of protein-protein interaction networks in the genetic heterogeneity of common diseases or complex traits is becoming increasingly recognized. Thus, the development of a network-based approach combined with phenotypic profiling would be useful for disease gene prioritization. RESULTS: We developed a random-set scoring model and implemented it to quantify phenotype relevance in a network-based disease gene-prioritization approach. We validated our approach based on different gene phenotypic profiles, which were generated from PubMed abstracts, OMIM, and GeneRIF records. We also investigated the validity of several vocabulary filters and different likelihood thresholds for predicted protein-protein interactions in terms of their effect on the network-based gene-prioritization approach, which relies on text-mining of the phenotype data. Our method demonstrated good precision and sensitivity compared with those of two alternative complex-based prioritization approaches. We then conducted a global ranking of all human genes according to their relevance to a range of human diseases. The resulting accurate ranking of known causal genes supported the reliability of our approach. Moreover, these data suggest many promising novel candidate genes for human disorders that have a complex mode of inheritance. CONCLUSION: We have implemented and validated a network-based approach to prioritize genes for human diseases based on their phenotypic profile. We have devised a powerful and transparent tool to identify and rank candidate genes. Our global gene prioritization provides a unique resource for the biological interpretation of data from genome-wide association studies, and will help in the understanding of how the associated genetic variants influence disease or quantitative phenotypes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2105-15-315) contains supplementary material, which is available to authorized users

Clinical and medication profiles stratified by household income in patients referred for diabetes care

BACKGROUND: Low income individuals with diabetes are at particularly high risk for poor health outcomes. While specialized diabetes care may help reduce this risk, it is not currently known whether there are significant clinical differences across income groups at the time of referral. The objective of this study is to determine if the clinical profiles and medication use of patients referred for diabetes care differ across income quintiles. METHODS: This cross-sectional study was conducted using a Canadian, urban, Diabetes Education Centre (DEC) database. Clinical information on the 4687 patients referred to the DEC from May 2000 – January 2002 was examined. These data were merged with 2001 Canadian census data on income. Potential differences in continuous clinical parameters across income quintiles were examined using regression models. Differences in medication use were examined using Chi square analyses. RESULTS: Multivariate regression analysis indicated that income was negatively associated with BMI (p < 0.0005) and age (p = 0.023) at time of referral. The highest income quintiles were found to have lower serum triglycerides (p = 0.011) and higher HDL-c (p = 0.008) at time of referral. No significant differences were found in HBA1C, LDL-c or duration of diabetes. The Chi square analysis of medication use revealed that despite no significant differences in HBA1C, the lowest income quintiles used more metformin (p = 0.001) and sulfonylureas (p < 0.0005) than the wealthy. Use of other therapies were similar across income groups, including lipid lowering medications. High income patients were more likely to be treated with diet alone (p < 0.0005). CONCLUSION: Our findings demonstrate that low income patients present to diabetes clinic older, heavier and with a more atherogenic lipid profile than do high income patients. Overall medication use was higher among the lower income group suggesting that differences in clinical profiles are not the result of under-treatment, thus invoking lifestyle factors as potential contributors to these findings

CD4 intragenic SNPs associate with HIV-2 plasma viral load and CD4 count in a community-based study from Guinea-Bissau, West Africa.

OBJECTIVES: The human genetics of HIV-2 infection and disease progression is understudied. Therefore, we studied the effect of variation in 2 genes that encode products critical to HIV pathogenesis and disease progression: CD4 and CD209. DESIGN: This cross-sectional study consisted of 143 HIV-2, 30 HIV-1 + HIV-2 and 29 HIV-1-infected subjects and 194 uninfected controls recruited from rural Guinea-Bissau. METHODS: We genotyped 14 CD4 and 4 CD209 single nucleotide polymorphisms (SNPs) that were tested for association with HIV infection, HIV-2 plasma viral load (high vs. low), and CD4 T-cell count (high vs. low). RESULTS: The most significant association was between a CD4 haplotype rs11575097-rs10849523 and high viral load [odds ratio (OR): = 2.37, 95% confidence interval (CI): 1.35 to 4.19, P = 0.001, corrected for multiple testing], suggesting increased genetic susceptibility to HIV-2 disease progression for individuals carrying the high-risk haplotype. Significant associations were also observed at a CD4 SNP (rs2255301) with HIV-2 infection (OR: = 2.36, 95% CI: 1.19 to 4.65, P = 0.01) and any HIV infection (OR: = 2.50, 95% CI: 1.34 to 4.69, P = 0.004). CONCLUSIONS: Our results support a role of CD4 polymorphisms in HIV-2 infection, in agreement with recent data showing that CD4 gene variants increase risk to HIV-1 in Kenyan female sex workers. These findings indicate at least some commonality in HIV-1 and HIV-2 susceptibility

Effects of intervention upon precompetition state anxiety in elite junior tennis players: The relevance of the matching hypothesis

Reproduced with permission of publisher from: Terry, P., Coakley, L., & Karageorghis, C. Effects of intervention upon precompetition state anxiety in elite junior tennis players: the relevance of the matching hypothesis. Perceptual and Motor Skills, 1995, 81, 287-296. © Perceptual and Motor Skills 1995The matching hypothesis proposes that interventions for anxiety should be matched to the modality in which anxiety is experienced. This study investigated the relevance of the matching hypothesis for anxiety interventions in tennis. Elite junior tennis players (N = 100; Age: M = 13.9 yr., SD = 1.8 yr.) completed the Competitive State Anxiety Inventory-2 before and after one of four randomly assigned intervention strategies approximately one hour prior to competition at a National Junior Championship. A two-factor multivariate analysis of variance (group x time) with repeated measures on the time factor gave no significant main effect by group but indicated significant reductions in somatic anxiety and cognitive anxiety and a significant increase in self-confidence following intervention. A significant group by time interaction emerged for self-confidence. The results question the need to match intervention strategy to the mode of anxiety experienced

Assessment of Ground-Based and Aerial Cloud Seeding Using Trace Chemistry

Targeting seedable clouds with silver iodide in complex terrain adds considerable uncertainty in weather modification studies. This study explores the geographic and temporal distribution of silver iodide associated with an active cloud seeding program in central Idaho snowpack using trace chemistry. Over 4,000 snow samples were analyzed for the presence of a cloud seeding silver iodide (AgI) signature over two winter seasons. The results indicate the following. (1) At sites within 70 km of AgI sources, silver enrichments were detected at 88% of cases involving seeding efforts from ground generators, but none from aircraft seeded cases. (2) Real-time snow collection methods were replicable within 0.41 ppt and confirmed seeding signatures for the entire duration of a seeded storm (n=3). (3) Sites sampled beyond 70 km of AgI sources (n=13) lacked detectable seeding signatures in snow. The results of this study demonstrate some of the strengths and limitations of chemical tracers to evaluate cloud seeding operations and provide observational data that can inform numerical simulations of these processes. The results also indicate that this chemical approach can be used to help constrain the spatiotemporal distribution of silver from cloud seeding efforts