The fluctuation of Meloidogyne population density and the percentage of fungal egg parasitism were determined from July 2011 to July 2013 in two commercial organic vegetable production sites (M10.23 and M10.55) in plastic greenhouses, located in northeastern Spain, in order to know the level of soil suppressiveness. Fungal parasites were identified by molecular methods. In parallel, pot tests characterized the level of soil suppressiveness and the fungal species growing from the eggs. In addition, the egg parasitic ability of 10 fungal isolates per site was also assessed. The genetic profiles of fungal and bacterial populations from M10.23 and M10.55 soils were obtained by Denaturing Gradient Gel Electrophoresis (DGGE), and compared with a non-suppressive soil (M10.33). In M10.23, Meloidogyne population in soil decreased progressively throughout the rotation zucchini, tomato, and radish or spinach. The percentage of egg parasitism was 54.7% in zucchini crop, the only one in which eggs were detected. Pochonia chlamydosporia was the only fungal species isolated. In M10.55, nematode densities peaked at the end of the spring-summer crops (tomato, zucchini, and cucumber), but disease severity was lower than expected (0.2–6.3). The percentage of fungal egg parasitism ranged from 3 to 84.5% in these crops. The results in pot tests confirmed the suppressiveness of the M10.23 and M10.55 soils against Meloidogyne. The number of eggs per plant and the reproduction factor of the population were reduced (P < 0.05) in both non-sterilized soils compared to the sterilized ones after one nematode generation. P. chlamydosporia was the only fungus isolated from Meloidogyne eggs. In in vitro tests, P. chlamydosporia isolates were able to parasitize Meloidogyne eggs from 50 to 97% irrespective of the site. DGGE fingerprints revealed a high diversity in the microbial populations analyzed. Furthermore, both bacterial and fungal genetic patterns differentiated suppressive from non-suppressive soils, but the former showed a higher degree of similarity between both suppressive soils than the later.

Abstract. Managed Aquifer Recharge (MAR) is a technique used worldwide to increase the availability of water resources. We study how MAR modifies microbial ecosystems and its implications for enhancing biodegradation processes to eventually improve groundwater quality. We compare soil and groundwater samples taken from a MAR facility located in NE Spain during recharge (with the facility operating continuously for several months) and after 4 months of no recharge. The study demonstrates a strong correlation between soil and water microbial prints with respect to sampling location along the mapped infiltration path. In particular, managed recharge practices disrupt groundwater ecosystems by modifying diversity indices and the composition of microbial communities, indicating that infiltration favors the growth of certain populations. Analysis of the genetic profiles showed the presence of nine different bacterial phyla in the facility, revealing high biological diversity at the highest taxonomic range. In fact, the microbial population patterns under recharge conditions agree with the intermediate disturbance hypothesis (IDH). Moreover, DNA sequence analysis of excised denaturing gradient gel electrophoresis (DGGE) band patterns revealed the existence of indicator species linked to MAR, most notably Dehalogenimonas sp., Nitrospira sp. and Vogesella sp.. Our real facility multidisciplinary study (hydrological, geochemical and microbial), involving soil and groundwater samples, indicates that MAR is a naturally based, passive and efficient technique with broad implications for the biodegradation of pollutants dissolved in water.

Abstract. Managed Aquifer Recharge (MAR) is a worldwide used technique to increase the availability of water resources.We study how MAR modifies microbial ecosystems, and its implications for enhancing biodegradation processes to eventually improve groundwater quality. We compare soil and groundwater samples taken from a MAR facility located in NE Spain during recharge (with the facility operating continuously for several months) and after four months of no recharge. The study demonstrates a strong correlation between soil and water microbial prints with respect to sampling location along the mapped 5 infiltration path. In particular, managed recharge practices disrupt groundwater ecosystems by modifying diversity indices and the composition of microbial communities, indicating that infiltration favors the growth of certain populations. Analysis of the genetic profiles showed the presence of nine different bacterial phyla in the facility, revealing high biological diversity at the highest taxonomic range. In fact, the microbial population patterns under recharge conditions agree with the Intermediate Disturbance Hypothesis. Moreover, DNA sequence analysis of excised DGGE band patterns revealed the existence of indicator 10 species linked to MAR, most notably Dehalogenimonas sp, Nitrospira sp and Vogesella sp. Our real facility multidisciplinary study (hydrological, geochemical and microbial), involving soil and groundwater samples, support that MAR is a naturallybased, passive, and efficient technique with broad implications for the biodegradation of pollutants dissolved in water.

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years of age, with at least 6 months of enrollment, without personal history of previous CVE or coronary revascularization were included. The PROCAM, Framingham and two modified versions of Framingham risk score were estimated (first: a 75% adjustment; second: Framingham.20, patient receiving statins, BMI. = 25, CKD, triglycerides. = 200mg/dL). Patients with insufficient information were excluded. A multivariate logistic regression model using clinical variables as covariates was used to predict first CVE and was compared with each risk scale. The Delong test and a Boostrap with 1,000 resamples were used to evaluate differences in the AUC-ROC statistic. Results: A sample of 85,798 (66.9%) patients with 2,664 (3.1%) CVE was obtained. The estimated AUC-ROC (95% CI) were: Framighan Score = 0.623 (0.603 -0.643), Framighan Score 75% = 0.641 (0.621 -0.660), Framighan Risk Factors = 0.687 ( 0.668 -0.705), PROCAM Score = 0.599 ( 0.556-0.641), PROCAM score = 0.651 (0.625-0.677), PROCAM risk factors = 0.676 (0.656-0.695), High risk groups = 0.708 ( 0.688-0.727). Establishing the AUC-ROC Framighan Score as a basis, the differences with high-risk groups were significant (Delong test: p ,0.001, Bootstrap test: p ,0.001), Framighan risk factors (Delong test: p ,0.001, Bootstrap test : p ,0.001) and risk factors PROCAM (Delong test: p ,0.001, Bootstrap test: p ,0.001). Conclusions: The high-risk group better predicts CVD. The use of this scale would improve the categorization of cardiovascular risk in this population.