Factors associated with Toxoplasma gondii infection in confined farrow-to-finish pig herds in western France: an exploratory study in 60 herds

Background: Infection by Toxoplasma gondii postnatally can occur after ingestion of contaminated meat or water (tissue cysts/oocysts). In Europe, percentage of meat borne infections is estimated between 30 and 63 %, out of which pork makes the most important source. The aim of this study was to (i) investigate the seroprevalence of T. gondii in intensive pig farms from western France; and (ii) identify the risk factors associated with seropositivity. Methods: Data were collected between November 2006 and February 2008 in 60 intensive farrow-to-finish farms, where sera were taken from 3595 fattening pigs, weaned and suckling piglets. Information about three classes of potential seropositivity risk factors were obtained through a questionnaire concerning: (i) breeding characteristics; (ii) farm management; and (iii) husbandry and hygiene. The modified agglutination test (MAT) was used for detection of specific anti T. gondii antibodies in pig sera, starting from 1/6 dilution. Results: The overall proportion of seropositive animals was 6.9 %, but the proportion of herds with at least one positive pig was 100 %. Multivariate logistic mixed model showed an increased seropositivity risk in weaned compared to suckling piglets, and a decreasing risk for mid-sized and large farms. The presence of a Danish entry facility, that clearly separates clean and dirty areas, had a protective effect on T. gondii seropositivity as well. Conclusions: The observed proportion of herds with at least one T. gondii seropositive animal provides further evidence that even in confined conditions of pig breeding, infection occurs, and is common. The highest risk for acquiring T. gondii is at the end of weaning period. Smaller confined pig farms demonstrate higher T. gondii seropositivity levels. This study also showed that Danish entry on farm buildings provides effective protection against T. gondii

A hepatitis B virus causes chronic infections in equids worldwide

Preclinical testing of novel therapeutics for chronic hepatitis B (CHB) requires suitable animal models. Equids host homologs of hepatitis C virus (HCV). Because coinfections of hepatitis B virus (HBV) and HCV occur in humans, we screened 2,917 specimens from equids from five continents for HBV. We discovered a distinct HBV species (Equid HBV, EqHBV) in 3.2% of donkeys and zebras by PCR and antibodies against EqHBV in 5.4% of donkeys and zebras. Molecular, histopathological, and biochemical analyses revealed that infection patterns of EqHBV resembled those of HBV in humans, including hepatotropism, moderate liver damage, evolutionary stasis, and potential horizontal virus transmission. Naturally infected donkeys showed chronic infections resembling CHB with high viral loads of up to 2.6 × 109 mean copies per milliliter serum for >6 mo and weak antibody responses. Antibodies against Equid HCV were codetected in 26.5% of donkeys seropositive for EqHBV, corroborating susceptibility to both hepatitis viruses. Deltavirus pseudotypes carrying EqHBV surface proteins were unable to infect human cells via the HBV receptor NTCP (Na+/taurocholate cotransporting polypeptide), suggesting alternative viral entry mechanisms. Both HBV and EqHBV deltavirus pseudotypes infected primary horse hepatocytes in vitro, supporting a broad host range for EqHBV among equids and suggesting that horses might be suitable for EqHBV and HBV infections in vivo. Evolutionary analyses suggested that EqHBV originated in Africa several thousand years ago, commensurate with the domestication of donkeys. In sum, EqHBV naturally infects diverse equids and mimics HBV infection patterns. Equids provide a unique opportunity for preclinical testing of novel therapeutics for CHB and to investigate HBV/ HCV interplay upon coinfection

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Maintenance of traditional cultural orientation is associated with lower rates of obesity and sedentary behaviours among African migrant children to Australia

Background: Migrants from developing to developed countries rapidly develop more obesity than the host population. While the effects of socio-economic status on obesity are well established, the influence of cultural factors, including acculturation, is not known.Objective: To examine the association between acculturation and obesity and its risk factors among African migrant children in Australia.Design and participants: A cross-sectional study using a non-probability sample of 3- to 12-year-old sub-Saharan African migrant children. A bidimensional model of strength of affiliation with African and Australian cultures was used to divide the sample into four cultural orientations: traditional (African), assimilated (Australian), integrated (both) and marginalized (neither).Main outcome measures: Body mass index (BMI), leisure-time physical activity (PA) and sedentary behaviours (SBs) and energy density of food.Results: In all, 18.4% (95% confidence interval (CI): 14&ndash;23%) were overweight and 8.6% (95% CI: 6&ndash;12%) were obese. After adjustment for confounders, integrated (&szlig;=1.1; P&lt;0.05) and marginalized &szlig;(=1.4; P&lt;0.01) children had higher BMI than traditional children. However, integrated children had significantly higher time engaged in both PA (&szlig;=46.9, P&lt;0.01) and SBs (&szlig;=43.0, P&lt;0.05) than their traditional counterparts. In comparison with traditional children, assimilated children were more sedentary (&szlig;=57.5, P&lt;0.01) while marginalization was associated with increased consumption of energy-dense foods (&szlig;=42.0, P&lt;0.05).Conclusions: Maintenance of traditional orientation was associated with lower rates of obesity and SBs. Health promotion programs and frameworks need to be rooted in traditional values and habits to maintain and reinforce traditional dietary and PA habits, as well as identify the marginalized clusters and address their needs.<br /

TRY plant trait database - enhanced coverage and open access

This article has 730 authors, of which I have only listed the lead author and myself as a representative of University of HelsinkiPlant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.Peer reviewe

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Metabolomics and Age-Related Macular Degeneration

Age-related macular degeneration (AMD) leads to irreversible visual loss, therefore, early intervention is desirable, but due to its multifactorial nature, diagnosis of early disease might be challenging. Identification of early markers for disease development and progression is key for disease diagnosis. Suitable biomarkers can potentially provide opportunities for clinical intervention at a stage of the disease when irreversible changes are yet to take place. One of the most metabolically active tissues in the human body is the retina, making the use of hypothesis-free techniques, like metabolomics, to measure molecular changes in AMD appealing. Indeed, there is increasing evidence that metabolic dysfunction has an important role in the development and progression of AMD. Therefore, metabolomics appears to be an appropriate platform to investigate disease-associated biomarkers. In this review, we explored what is known about metabolic changes in the retina, in conjunction with the emerging literature in AMD metabolomics research. Methods for metabolic biomarker identification in the eye have also been discussed, including the use of tears, vitreous, and aqueous humor, as well as imaging methods, like fluorescence lifetime imaging, that could be translated into a clinical diagnostic tool with molecular level resolution

Ophthalmology

OBJECTIVE: In the current study we aimed to identify metabolites associated with age-related macular degeneration (AMD) by performing the largest metabolome association analysis in AMD to date. In addition, we aimed to determine the effect of AMD-associated genetic variants on metabolite levels, and aimed to investigate associations between the identified metabolites and activity of the complement system, one of the main AMD-associated disease pathways. DESIGN: Case-control assocation analysis of metabolomics data. SUBJECTS: 2,267 AMD cases and 4,266 controls from five European cohorts. METHODS: Metabolomics was performed using a high-throughput H-NMR metabolomics platform, which allows the quantification of 146 metabolite measurements and 79 derivative values. Metabolome-AMD associations were studied using univariate logistic regression analyses. The effect of 52 AMD-associated genetic variants on the identified metabolites was investigated using linear regression. In addition, associations between the identified metabolites and activity of the complement pathway (defined by the C3d/C3 ratio) were investigated using linear regression. MAIN OUTCOME MEASURES: Metabolites associated with AMD RESULTS: We identified 60 metabolites that were significantly associated with AMD, including increased levels of large and extra-large HDL subclasses and decreased levels of VLDL, amino acids and citrate. Out of 52 AMD-associated genetic variants, seven variants were significantly associated with 34 of the identified metabolites. The strongest associations were identified for genetic variants located in or near genes involved in lipid metabolism (ABCA1, CETP, APOE, LIPC) with metabolites belonging to the large and extra-large HDL subclasses. In addition, 57 out of 60 metabolites were significantly associated with complement activation levels, and these associations were independent of AMD status. Increased large and extra-large HDL levels and decreased VLDL and amino acid levels were associated with increased complement activation. CONCLUSIONS: Lipoprotein levels were associated with AMD-associated genetic variants, while decreased essential amino acids may point to nutritional deficiencies in AMD. We observed strong associations between the vast majority of the AMD-associated metabolites and systemic complement activation levels, independent of AMD status. This may indicate biological interactions between the main AMD disease pathways, and suggests that multiple pathways may need to be targeted simultaneously for successful treatment of AMD