Can Arbuscular Mycorrhizal Fungi Reduce the Growth of Agricultural Weeds?

BACKGROUND: Arbuscular mycorrhizal fungi (AMF) are known for their beneficial effects on plants. However, there is increasing evidence that some ruderal plants, including several agricultural weeds, respond negatively to AMF colonization. Here, we investigated the effect of AMF on the growth of individual weed species and on weed-crop interactions. METHODOLOGY/PRINCIPAL FINDINGS: First, under controlled glasshouse conditions, we screened growth responses of nine weed species and three crops to a widespread AMF, Glomus intraradices. None of the weeds screened showed a significant positive mycorrhizal growth response and four weed species were significantly reduced by the AMF (growth responses between -22 and -35%). In a subsequent experiment, we selected three of the negatively responding weed species--Echinochloa crus-galli, Setaria viridis and Solanum nigrum--and analyzed their responses to a combination of three AMF (Glomus intraradices, Glomus mosseae and Glomus claroideum). Finally, we tested whether the presence of a crop (maize) enhanced the suppressive effect of AMF on weeds. We found that the growth of the three selected weed species was also reduced by a combination of AMF and that the presence of maize amplified the negative effect of AMF on the growth of E. crus-galli. CONCLUSIONS/SIGNIFICANCE: Our results show that AMF can negatively influence the growth of some weed species indicating that AMF have the potential to act as determinants of weed community structure. Furthermore, mycorrhizal weed growth reductions can be amplified in the presence of a crop. Previous studies have shown that AMF provide a number of beneficial ecosystem services. Taken together with our current results, the maintenance and promotion of AMF activity may thereby contribute to sustainable management of agroecosystems. However, in order to further the practical and ecological relevance of our findings, additional experiments should be performed under field conditions

Lifestyle variables and the risk of myocardial infarction in the General Practice Research Database

<p>Abstract</p> <p>Background</p> <p>The primary objective of this study is to estimate the association between body mass index (BMI) and the risk of first acute myocardial infarction (AMI). As a secondary objective, we considered the association between other lifestyle variables, smoking and heavy alcohol use, and AMI risk.</p> <p>Methods</p> <p>This study was conducted in the general practice research database (GPRD) which is a database based on general practitioner records and is a representative sample of the United Kingdom population. We matched cases of first AMI as identified by diagnostic codes with up to 10 controls between January 1^st, 2001 and December 31^st, 2005 using incidence density sampling. We used multiple imputation to account for missing data.</p> <p>Results</p> <p>We identified 19,353 cases of first AMI which were matched on index date, GPRD practice and age to 192,821 controls. There was a modest amount of missing data in the database, and the patients with missing data had different risks than those with recorded values. We adjusted our analysis for each lifestyle variable jointly and also for age, sex, and number of hospitalizations in the past year. Although a record of underweight (BMI <18.0 kg/m²) did not alter the risk for AMI (adjusted odds ratio (OR): 1.00; 95% confidence interval (CI): 0.87–1.11) when compared with normal BMI (18.0–24.9 kg/m²), obesity (BMI ≥30 kg/m²) predicted an increased risk (adjusted OR: 1.41; 95% CI: 1.35–1.47). A history of smoking also predicted an increased risk of AMI (adjusted OR: 1.81; 95% CI: 1.75–1.87) as did heavy alcohol use (adjusted OR: 1.15; 95% CI: 1.06–1.26).</p> <p>Conclusion</p> <p>This study illustrates that obesity, smoking and heavy alcohol use, as recorded during routine care by a general practitioner, are important predictors of an increased risk of a first AMI. In contrast, low BMI does not increase the risk of a first AMI.</p

Genetics and not shared environment explains familial resemblance in adult metabolomics data

Metabolites are small molecules involved in cellular metabolism where they act as reaction substrates or products. The term 'metabolomics' refers to the comprehensive study of these molecules. The concentrations of metabolites in biological tissues are under genetic control, but this is limited by environmental factors such as diet. In adult mono- and dizygotic twin pairs, we estimated the contribution of genetic and shared environmental influences on metabolite levels by structural equation modeling and tested whether the familial resemblance for metabolite levels is mainly explained by genetic or by environmental factors that are shared by family members. Metabolites were measured across three platforms: two based on proton nuclear magnetic resonance techniques and one employing mass spectrometry. These three platforms comprised 237 single metabolic traits of several chemical classes. For the three platforms, metabolites were assessed in 1407, 1037 and 1116 twin pairs, respectively. We carried out power calculations to establish what percentage of shared environmental variance could be detected given these sample sizes. Our study did not find evidence for a systematic contribution of shared environment, defined as the influence of growing up together in the same household, on metabolites assessed in adulthood. Significant heritability was observed for nearly all 237 metabolites; significant contribution of the shared environment was limited to 6 metabolites. The top quartile of the heritability distribution was populated by 5 of the 11 investigated chemical classes. In this quartile, metabolites of the class lipoprotein were significantly overrepresented, whereas metabolites of classes glycerophospholipids and glycerolipids were significantly underrepresented.Analytical BioScience

Plasma amino acids and neopterin in healthy persons with Down’s syndrome

In persons with Down’s syndrome (DS) immunological abnormalities as well as hypothyroidism and Alzheimer type dementia are frequently observed. In addition, the activity of the enzyme cystathionine beta-synthase (CBS) is over-expressed which results in an altered homocysteine metabolism

The Effects of Arbuscular Mycorrhizal Fungi on Direct and Indirect Defense Metabolites of Plantago lanceolata L.

Arbuscular mycorrhizal fungi can strongly influence the metabolism of their host plant, but their effect on plant defense mechanisms has not yet been thoroughly investigated. We studied how the principal direct defenses (iridoid glycosides) and indirect defenses (volatile organic compounds) of Plantago lanceolata L. are affected by insect herbivory and mechanical wounding. Volatile compounds were collected and quantified from mycorrhizal and non-mycorrhizal P. lanceolata plants that underwent three different treatments: 1) insect herbivory, 2) mechanical wounding, or 3) no damage. The iridoids aucubin and catalpol were extracted and quantified from the same plants. Emission of terpenoid volatiles was significantly higher after insect herbivory than after the other treatments. However, herbivore-damaged mycorrhizal plants emitted lower amounts of sesquiterpenes, but not monoterpenes, than herbivore-damaged non-mycorrhizal plants. In contrast, mycorrhizal infection increased the emission of the green leaf volatile (Z)-3-hexenyl acetate in untreated control plants, making it comparable to emission from mechanically wounded or herbivore-damaged plants whether or not they had mycorrhizal associates. Neither mycorrhization nor treatment had any influence on the levels of iridoid glycosides. Thus, mycorrhizal infection did not have any effect on the levels of direct defense compounds measured in P. lanceolata. However, the large decline in herbivore-induced sesquiterpene emission may have important implications for the indirect defense potential of this species

Combined artificial bee colony algorithm and machine learning techniques for prediction of online consumer repurchase intention

A novel paradigm in the service sector i.e. services through the web is a progressive mechanism for rendering offerings over diverse environments. Internet provides huge opportunities for companies to provide personalized online services to their customers. But prompt novel web services introduction may unfavorably affect the quality and user gratification. Subsequently, prediction of the consumer intention is of supreme importance in selecting the web services for an application. The aim of study is to predict online consumer repurchase intention and to achieve this objective a hybrid approach which a combination of machine learning techniques and Artificial Bee Colony (ABC) algorithm has been used. The study is divided into three phases. Initially, shopping mall and consumer characteristic’s for repurchase intention has been identified through extensive literature review. Secondly, ABC has been used to determine the feature selection of consumers’ characteristics and shopping malls’ attributes (with > 0.1 threshold value) for the prediction model. Finally, validation using K-fold cross has been employed to measure the best classification model robustness. The classification models viz., Decision Trees (C5.0), AdaBoost, Random Forest (RF), Support Vector Machine (SVM) and Neural Network (NN), are utilized for prediction of consumer purchase intention. Performance evaluation of identified models on training-testing partitions (70-30%) of the data set, shows that AdaBoost method outperforms other classification models with sensitivity and accuracy of 0.95 and 97.58% respectively, on testing data set. This study is a revolutionary attempt that considers both, shopping mall and consumer characteristics in examine the consumer purchase intention.N/

Persistent Oxytetracycline Exposure Induces an Inflammatory Process That Improves Regenerative Capacity in Zebrafish Larvae

BACKGROUND: The excessive use of antibiotics in aquaculture can adversely affect not only the environment, but also fish themselves. In this regard, there is evidence that some antibiotics can activate the immune system and reduce their effectiveness. None of those studies consider in detail the adverse inflammatory effect that the antibiotic remaining in the water may cause to the fish. In this work, we use the zebrafish to analyze quantitatively the effects of persistent exposure to oxytetracycline, the most common antibiotic used in fish farming. METHODOLOGY: We developed a quantitative assay in which we exposed zebrafish larvae to oxytetracycline for a period of 24 to 96 hrs. In order to determinate if the exposure causes any inflammation reaction, we evaluated neutrophils infiltration and quantified their total number analyzing the Tg(mpx:GFP)(i114) transgenic line by fluorescence stereoscope, microscope and flow cytometry respectively. On the other hand, we characterized the process at a molecular level by analyzing several immune markers (il-1β, il-10, lysC, mpx, cyp1a) at different time points by qPCR. Finally, we evaluated the influence of the inflammation triggered by oxytetracycline on the regeneration capacity in the lateral line. CONCLUSIONS: Our results suggest that after 48 hours of exposure, the oxytetracycline triggered a widespread inflammation process that persisted until 96 hours of exposure. Interestingly, larvae that developed an inflammation process showed an improved regeneration capacity in the mechanosensory system lateral line