| 1011. |
- O'Dushlaine, Colm, et al.
(author)
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Genes predict village of origin in rural Europe
- 2010
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In: European Journal of Human Genetics. - : Springer Science and Business Media LLC. - 1018-4813 .- 1476-5438. ; 18:11, s. 1269-1270
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Journal article (peer-reviewed)abstract
- The genetic structure of human populations is important in population genetics, forensics and medicine. Using genome-wide scans and individuals with all four grandparents born in the same settlement, we here demonstrate remarkable geographical structure across 8-30 km in three different parts of rural Europe. After excluding close kin and inbreeding, village of origin could still be predicted correctly on the basis of genetic data for 89-100% of individuals.
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| 1012. |
- Pedersen, Marie, et al.
(author)
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Bulky DNA Adducts in Cord Blood, Maternal Fruit-and-Vegetable Consumption, and Birth Weight in a European Mother-Child Study (NewGeneris)
- 2013
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In: Journal of Environmental Health Perspectives. - : Environmental Health Perspectives. - 0091-6765 .- 1552-9924. ; 121:10, s. 1200-1206
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Journal article (peer-reviewed)abstract
- Background: Tobacco-smoke, airborne, and dietary exposures to polycyclic aromatic-hydrocarbons (PAHs) have been associated with reduced prenatal growth. Evidence from -biomarker-based studies of low-exposed populations is limited. Bulky DNA adducts in cord blood reflect the prenatal effective dose to several genotoxic agents including PAHs. Objectives: We estimated the association between bulky DNA adduct levels and birth weight in a multicenter study and examined modification of this association by maternal intake of fruits and vegetables during pregnancy. Methods: Pregnant women from Denmark, England, Greece, Norway, and Spain were recruited in 2006-2010. Adduct levels were measured by the 32P-postlabeling technique in white blood cells from 229 mothers and 612 newborns. Maternal diet was examined through questionnaires. Results: Adduct levels in maternal and cord blood samples were similar and positively correlated (median, 12.1 vs. 11.4 adducts in 108 nucleotides; Spearman rank correlation coefficient = 0.66, p < 0.001). Cord blood adduct levels were negatively associated with birth weight, with an estimated difference in mean birth weight of -129 g (95% CI: -233, -25 g) for infants in the highest versus lowest tertile of adducts. The negative association with birth weight was limited to births in Norway, Denmark, and England, the countries with the lowest adduct levels, and was more pronounced in births to mothers with low intake of fruits and vegetables (-248 g; 95% CI: -405, -92 g) compared with those with high intake (-58 g; 95% CI: -206, 90 g). Conclusions: Maternal exposure to genotoxic agents that induce the formation of bulky DNA adducts may affect intrauterine growth. Maternal fruit and vegetable consumption may be protective.
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| 1013. |
- Perry, John R. B., et al.
(author)
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Stratifying Type 2 Diabetes Cases by BMI Identifies Genetic Risk Variants in LAMA1 and Enrichment for Risk Variants in Lean Compared to Obese Cases
- 2012
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In: PLoS Genetics. - : Public Library of Science (PLoS). - 1553-7404. ; 8:5
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Journal article (peer-reviewed)abstract
- Common diseases such as type 2 diabetes are phenotypically heterogeneous. Obesity is a major risk factor for type 2 diabetes, but patients vary appreciably in body mass index. We hypothesized that the genetic predisposition to the disease may be different in lean (BMI<25 Kg/m(2)) compared to obese cases (BMI >= 30 Kg/m(2)). We performed two case-control genome-wide studies using two accepted cut-offs for defining individuals as overweight or obese. We used 2,112 lean type 2 diabetes cases (BMI<25 kg/m(2)) or 4,123 obese cases (BMI >= 30 kg/m(2)), and 54,412 un-stratified controls. Replication was performed in 2,881 lean cases or 8,702 obese cases, and 18,957 un-stratified controls. To assess the effects of known signals, we tested the individual and combined effects of SNPs representing 36 type 2 diabetes loci. After combining data from discovery and replication datasets, we identified two signals not previously reported in Europeans. A variant (rs8090011) in the LAMA1 gene was associated with type 2 diabetes in lean cases (P = 8.4610 29, OR = 1.13 [95% CI 1.09-1.18]), and this association was stronger than that in obese cases (P = 0.04, OR = 1.03 [95% CI 1.00-1.06]). A variant in HMG20A-previously identified in South Asians but not Europeans-was associated with type 2 diabetes in obese cases (P = 1.3 x 10(-8), OR= 1.11 [95% CI 1.07-1.15]), although this association was not significantly stronger than that in lean cases (P = 0.02, OR = 1.09 [95% CI 1.02-1.17]). For 36 known type 2 diabetes loci, 29 had a larger odds ratio in the lean compared to obese (binomial P = 0.0002). In the lean analysis, we observed a weighted per-risk allele OR = 1.13 [95% CI 1.10-1.17], P = 3.2 x 10(-14). This was larger than the same model fitted in the obese analysis where the OR = 1.06 [95% CI 1.05-1.08], P = 2.2 x 10(-16). This study provides evidence that stratification of type 2 diabetes cases by BMI may help identify additional risk variants and that lean cases may have a stronger genetic predisposition to type 2 diabetes.
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| 1014. |
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| 1015. |
- Prakobphol, A, et al.
(author)
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Salivary agglutinin, which binds Streptococcus mutans and Helicobacter pylori, is the lung scavenger receptor cysteine-rich protein gp-340.
- 2000
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In: The Journal of biological chemistry. - 0021-9258 .- 1083-351X. ; 275:51, s. 39860-6
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Journal article (peer-reviewed)abstract
- Salivary agglutinin is a high molecular mass component of human saliva that binds Streptococcus mutans, an oral bacterium implicated in dental caries. To study its protein sequence, we isolated the agglutinin from human parotid saliva. After trypsin digestion, a portion was analyzed by matrix-assisted laser/desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS), which gave the molecular mass of 14 unique peptides. The remainder of the digest was subjected to high performance liquid chromatography, and the separated peptides were analyzed by MALDI-TOF/post-source decay; the spectra gave the sequences of five peptides. The molecular mass and peptide sequence information showed that salivary agglutinin peptides were identical to sequences in lung (lavage) gp-340, a member of the scavenger receptor cysteine-rich protein family. Immunoblotting with antibodies that specifically recognized either lung gp-340 or the agglutinin confirmed that the salivary agglutinin was gp-340. Immunoblotting with an antibody specific to the sialyl Le(x) carbohydrate epitope detected expression on the salivary but not the lung glycoprotein, possible evidence of different glycoforms. The salivary agglutinin also interacted with Helicobacter pylori, implicated in gastritis and peptic ulcer disease, Streptococcus agalactiae, implicated in neonatal meningitis, and several oral commensal streptococci. These results identify the salivary agglutinin as gp-340 and suggest it binds bacteria that are important determinants of either the oral ecology or systemic diseases.
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| 1016. |
- Randich, S., et al.
(author)
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The Gaia -ESO Survey: Galactic evolution of lithium at high metallicity
- 2020
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In: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 640
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Journal article (peer-reviewed)abstract
- Context. Reconstructing the Galactic evolution of lithium (Li) is the main tool used to constrain the source(s) of Li enrichment in the Galaxy. Recent results have suggested a decline in Li at supersolar metallicities, which may indicate reduced production. Aims. We exploit the unique characteristics of the Gaia-ESO Survey open star cluster sample to further investigate this issue and to better constrain the evolution of Li at high metallicity. Methods. We trace the upper envelope of Li abundance versus metallicity evolution using 18 clusters and considering members that should not have suffered any Li depletion. Results. At variance with previous claims, we do not find any evidence of a Li decrease at high metallicity. The most metal-rich clusters in the sample ([Fe/H] = ∼0.3) actually show the highest Li abundances, with A(Li) > 3.4. Our results clearly show that previous findings, which were based on field stars, were affected by selection effects. The metal-rich population in the solar neighbourhood is composed of relatively old and cool stars that have already undergone some Li depletion; hence, their measured Li does not represent the initial interstellar medium abundance, but a lower limit to it.
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| 1017. |
- Richard-Bollans, A., et al.
(author)
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Machine learning enhances prediction of plants as potential sources of antimalarials
- 2023
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In: Frontiers in Plant Science. - 1664-462X. ; 14
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Journal article (peer-reviewed)abstract
- Plants are a rich source of bioactive compounds and a number of plant-derived antiplasmodial compounds have been developed into pharmaceutical drugs for the prevention and treatment of malaria, a major public health challenge. However, identifying plants with antiplasmodial potential can be time-consuming and costly. One approach for selecting plants to investigate is based on ethnobotanical knowledge which, though having provided some major successes, is restricted to a relatively small group of plant species. Machine learning, incorporating ethnobotanical and plant trait data, provides a promising approach to improve the identification of antiplasmodial plants and accelerate the search for new plant-derived antiplasmodial compounds. In this paper we present a novel dataset on antiplasmodial activity for three flowering plant families - Apocynaceae, Loganiaceae and Rubiaceae (together comprising c. 21,100 species) - and demonstrate the ability of machine learning algorithms to predict the antiplasmodial potential of plant species. We evaluate the predictive capability of a variety of algorithms - Support Vector Machines, Logistic Regression, Gradient Boosted Trees and Bayesian Neural Networks - and compare these to two ethnobotanical selection approaches - based on usage as an antimalarial and general usage as a medicine. We evaluate the approaches using the given data and when the given samples are reweighted to correct for sampling biases. In both evaluation settings each of the machine learning models have a higher precision than the ethnobotanical approaches. In the bias-corrected scenario, the Support Vector classifier performs best - attaining a mean precision of 0.67 compared to the best performing ethnobotanical approach with a mean precision of 0.46. We also use the bias correction method and the Support Vector classifier to estimate the potential of plants to provide novel antiplasmodial compounds. We estimate that 7677 species in Apocynaceae, Loganiaceae and Rubiaceae warrant further investigation and that at least 1300 active antiplasmodial species are highly unlikely to be investigated by conventional approaches. While traditional and Indigenous knowledge remains vital to our understanding of people-plant relationships and an invaluable source of information, these results indicate a vast and relatively untapped source in the search for new plant-derived antiplasmodial compounds.
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| 1018. |
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| 1019. |
- Schmitt, A., et al.
(author)
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Evaluation of non-chemical seed treatment methods for the control of Phoma valerianellae on lamb’s lettuce seeds
- 2009
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In: Journal of Plant Diseases and Protection. - 1861-3829. ; 116:5, s. 200-207
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Journal article (peer-reviewed)abstract
- The aim of the present study was to identify seed treatment methods for eradicating Phoma valerianellae from lamb’s lettuce seeds in organic vegetable production. Using seeds naturally infested with the pathogen, the effect of three physical methods (hot water, aerated steam, electron treatment) and different agents of natural origin (micro-organisms, plant derived products, resistance inducers) was tested on moist filter paper, in seed trays under controlled conditions and in the field. in an initial screening, none of the tested putative resistance inducers prevented infection by P. valerianellae, while two out of seven formulated micro-organism preparations and six out of 16 experimental microbial strains were effective. When selected agents and the three physical seed treatment methods were compared in blotter and seed tray tests, the physical methods were generally the most effective treatments, while the micro-organism treatments were clearly less efficacious. However, in field experiments with the same seed lots and the same treatments, a statistically significant increase in plant stand was not obtained with any of the treatments. Combinations of the three physical treatment methods with selected non-chemical agents did not perform better than the physical treatments alone. The most effective alternative seed treatments identified in the present study, aerated steam, hot water, electron treatment and thyme oil (0.1%), can be recommended for eradication of P. valerianellae from lamb’s lettuce seeds in organic farming. Because their efficacy was generally as high as that of the chemical fungicide Aatiram (active ingredient thiram), they are also potentially suited for use in conventional vegetable production.
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| 1020. |
- Smith, N. G., et al.
(author)
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Global photosynthetic capacity is optimized to the environment
- 2019
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In: Ecology Letters. - : Wiley. - 1461-023X .- 1461-0248. ; 22:3, s. 506-517
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Journal article (peer-reviewed)abstract
- Earth system models (ESMs) use photosynthetic capacity, indexed by the maximum Rubisco carboxylation rate (V-cmax), to simulate carbon assimilation and typically rely on empirical estimates, including an assumed dependence on leaf nitrogen determined from soil fertility. In contrast, new theory, based on biochemical coordination and co-optimization of carboxylation and water costs for photosynthesis, suggests that optimal V-cmax can be predicted from climate alone, irrespective of soil fertility. Here, we develop this theory and find it captures 64% of observed variability in a global, field-measured V-cmax dataset for C-3 plants. Soil fertility indices explained substantially less variation (32%). These results indicate that environmentally regulated biophysical constraints and light availability are the first-order drivers of global photosynthetic capacity. Through acclimation and adaptation, plants efficiently utilize resources at the leaf level, thus maximizing potential resource use for growth and reproduction. Our theory offers a robust strategy for dynamically predicting photosynthetic capacity in ESMs.
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