Characterization of Trichoderma species from forest ecosystems by high-throughput phenotypic microarray.

The use of beneficial organisms for the biocontrol of soil-borne pathogens in forestry is still poor explored. In this work, the nutritional demands of 10 previously selected isolates of Trichoderma for the biocontrol of forest soil-borne pathogens have been tested by Phenotype Microarray technology, to investigate about their C-source utilization and exploring the possibility to obtain a microbial consortia (SynCom), an innovative strategy for the biocontrol of plant disease. All Trichoderma isolates tested in this study showed a high spore germination percentage within 3 d and evidenced nutritional preference regardless of the species they belong to, and unrelated to their soil of origin. Results of growth curve analysis and MANOVA test revealed that all isolates assimilate a broad range of substrates, generally preferring complex compounds such as monosaccharides related compounds, nitrogen compounds, carboxylic acids and esters. No evidence of competition for nutritional resources have been observed among isolates of this study. As a result, a combination of different isolates could be proposed to obtain a SynCom useful for the practice of phytopathogen biocontrol in forestry. The addition of i-erythritol, adenosine and turanose to a growth substrate could be suggested as stimulating compounds for the growth of the selected Trichoderma isolates.

Role of plasma phosphorylated neurofilament heavy chain (pNfH) in amyotrophic lateral sclerosis.

The phosphorylated neurofilament heavy chain (pNfH) is a promising biomarker in amyotrophic lateral sclerosis (ALS). We examined plasma pNfH concentrations in order to corroborate its role as a diagnostic and prognostic biomarker in ALS. Incident ALS cases enrolled in a population-based registry were retrospectively selected and matched by sex and age with a cohort of healthy volunteers. Plasma pNfH levels were measured by an ELISA kit and correlated with clinical parameters. Discrimination ability of pNfH was tested using receiving operating characteristic (ROC) curves. Kaplan-Meier (KM) analysis and Cox proportional hazard models were used for survival analysis. Plasma pNfH was significantly higher in patients compared to controls. An optimal cut-off of 39.74 pg/ml discriminated cases from controls with an elevated sensitivity and specificity. Bulbar-onset cases had higher plasma pNfH compared to spinal onset (p = 0.0033). Furthermore, plasma pNfH positively correlated with disease progression rate (r = 0.19, p = 0.031). Baseline plasma pNfH did not influence survival in our cohort. Our findings confirmed the potential utility of plasma pNfH as a diagnostic biomarker in ALS. However, further studies with longitudinal data are needed to corroborate its prognostic value.

The Role of Age on Beta-Amyloid1-42 Plasma Levels in Healthy Subjects.

Beta-amyloid (Aß) plaques have been observed in the brain of healthy elderlies with frequencies strongly influenced by age. The aim of the study is to evaluate the role of age and other biochemical and hematological parameters on Aß1-42 plasma levels in cognitively and neurologically normal individuals. Two-hundred and seventy-five normal subjects stratified by age groups (<35 years, 35-65 years, and >65 years) were included in the study. Aß1-42 plasma levels significantly correlated with age (rs = 0.27; p < 0.0001) in the whole sample, inversely correlated with age in the first age group (rs = -0.25, p = 0.01), positively correlated in the second group (rs = 0.22, p = 0.03), while there was no significant correlation in the older group (rs = 0.02, p = 0.86). Both age (ß-estimate = 0.08; p < 0.001) and cholesterol (ß-estimate = 0.03; p = 0.009) were significantly associated with Aß1-42 plasma level in multivariable analysis. However, only the association with age survived post hoc adjustment for multiple comparisons. The different effects of age on the Aß level across age groups should be explored in further studies to better understand the age-dependent variability. This could better define the value of plasma Aß as a biomarker of the Alzheimer neuropathology.

Bayesian spatiotemporal analysis of zero-inflated biological population density data by a delta-normal spatiotemporal additive model.

We evaluate the spatiotemporal changes in the density of a particular species of crustacean known as deep-water rose shrimp, Parapenaeus longirostris, based on biological sample data collected during trawl surveys carried out from 1995 to 2006 as part of the international project MEDITS (MEDiterranean International Trawl Surveys). As is the case for many biological variables, density data are continuous and characterized by unusually large amounts of zeros, accompanied by a skewed distribution of the remaining values. Here we analyze the normalized density data by a Bayesian delta-normal semiparametric additive model including the effects of covariates, using penalized regression with low-rank thin-plate splines for nonlinear spatial and temporal effects. Modeling the zero and nonzero values by two joint processes, as we propose in this work, allows to obtain great flexibility and easily handling of complex likelihood functions, avoiding inaccurate statistical inferences due to misclassification of the high proportion of exact zeros in the model. Bayesian model estimation is obtained by Markov chain Monte Carlo simulations, suitably specifying the complex likelihood function of the zero-inflated density data. The study highlights relevant nonlinear spatial and temporal effects and the influence of the annual Mediterranean oscillations index and of the sea surface temperature on the distribution of the deep-water rose shrimp density.

Using an automatic resistivity profiler soil sensor on-the-go in precision viticulture.

Spatial information on vineyard soil properties can be useful in precision viticulture. In this paper a combination of high resolution soil spatial information of soil electrical resistivity (ER) and ancillary topographic attributes, such as elevation and slope, were integrated to assess the spatial variability patterns of vegetative growth and yield of a commercial vineyard (Vitis vinifera L. cv. Tempranillo) located in the wine-producing region of La Rioja, Spain. High resolution continuous geoelectrical mapping was accomplished by an Automatic Resistivity Profiler (ARP) on-the-go sensor with an on-board GPS system; rolling electrodes enabled ER to be measured for a depth of investigation approximately up to 0.5, 1 and 2 m. Regression analysis and cluster analysis algorithm were used to jointly process soil resistivity data, landscape attributes and grapevine variables. ER showed a structured variability that matched well with trunk circumference spatial pattern and yield. Based on resistivity and a simple terrain attribute uniform management units were delineated. Once a spatial relationship to target variables is found, the integration of point measurement with continuous soil resistivity mapping is a useful technique to identify within-plots areas of vineyard with similar status.

General health, psychological well-being and distress of youth immigrants in Italy.

In seeking to ease the rehabilitation of refugees there has generally been a failure to take account of the complexity of the refugees' experience of suffering and loss. In this their psychological and emotional well-being as well as the social and economic aspects of the question have frequently been of only peripheral concern, and the response to the psychological impact of violence has been primarily focused on the concept of Post-Traumatic Stress Disorder (PTSD). This approach assumes a pathological response to stress that is both universal across different cultures and centred on the potential of pathologizing coping strategies that might be essential not only for survival but also for psychological well-being.

Spatiotemporal analysis of the PM10 concentration over the Taranto area.

In this paper, an analysis of air quality data is provided for the municipal area of Taranto (southern Italy) characterized by high environmental risks as formally decreed by the Italian government in the 1990s with two administrative measures. This is due to the massive presence of industrial sites with elevated environmental impact activities along the NW boundary of the city conurbation. The aforementioned activities have effects on the environment and on public health, as a number of epidemiological researches concerning this area reconfirm. The present study is focused on particulate matter as measured by PM10 concentrations at 13 monitoring stations, equipped with analogous instruments based on the Beta absorption technology, either reporting hourly, two-hourly, or daily measurements. Daily estimates of the PM10 concentration surfaces are obtained in order to identify areas of higher concentration (hot spots), possibly related to specific anthropic activities. Preliminary analysis involved addressing several data problems: (1) due to the use of two different validation techniques, a calibration procedure was devised to allow for data comparability; (2) imputation techniques were considered to cope with the large number of missing data, due to both different working periods and occasional malfunctions of PM10 sensors; and (3) reliable weather covariates (wind speed and direction, pressure, temperature, etc.) were obtained and considered within the analysis. Spatiotemporal modelling was addressed by a Bayesian kriging-based model proposed by Le and Zidek (2006) characterized by the use of time varying covariates and a semiparametric covariance structure. Advantages and disadvantages of the model are highlighted and assessed in terms of fit and performance. Estimated daily PM10 concentration surfaces are suitable for the interpretation of time trends and for identifying concentration peaks within the urban area.

[Statistical analysis of the incidence of some cancers in the province of Taranto 1999-2001]. / Analisi statistica dell'incidenza di alcune patologie tumorali nella provincia di Taranto 1999-2001.

OBJECTIVE: to estimate the spatial distribution of risk, in order to assess its correlation to environmental pollution exposure around the large production facilities located in the Taranto area, and to identify high risk areas not previously reported. SETTING: Italy, Taranto province (581,508 inhabitants). DESIGN: incidence data in 29 municipalities of the Taranto province were extracted from the Jonico Salentino Cancer Registry (RTJS) for the following cancer sites: lung (ICDX C33-C34); pleura, pleuric mesothelioma (ICDX C45.0); bladder, malignancies only (ICDX C67); brain (ICDX C70-72); non-Hodgkin lymphoma (ICDX C82-85, C96); leukaemia (ICDX C91-5). Age standardized incidence rates for the whole province were computed. High-level risk areas were classified using a Poisson model, computing area-specific p-values associated to the null hypothesis of no increased risk (i.e. relative risk equal to 1). A hierarchical spatial Bayesian model was estimated to strengthen results: specifically two additional variance components, accounting for relative risk spatial autocorrelation and excess heterogeneity respectively, were considered in the model specification. Bayesian mapping of disease incidence allows for the drawing of regularized (smoothed) maps. To adjust for the effect of socio-economic deprivation, a five-variable index was introduced into the model as an ecological covariate. RESULTS: an increased risk of lung, pleura and bladder cancer was observed among male residents in the city of Taranto (respectively: SIR 1.24, p-value < 0.01; SIR: 2.21, p-value < 0.01; SIR 1.28, p-value < 0.01). For non-Hodgkin lymphoma, a significant value was observed in the city of Taranto for males (SIR 1.46, p-value < 0.01), as well as in the neighbouring area of Pulsano for females (SIR 3.88, p-value < 0.01). An unexpected increased risk of brain cancer was found in both sexe risk (especially among males) of lung, pleura and bladder cancer is likely related to the chemical pollutants and asbestos, due to the presence of many industries and shipyards in the city of Taranto.

The relationship between malignant mesothelioma and an asbestos cement plant environmental risk: a spatial case-control study in the city of Bari (Italy).

OBJECTIVES: To estimate the mesothelioma risk and environmental asbestos exposure (EAE) due to an asbestos-cement plant. METHODS: A spatial case-control study including 48 malignant mesothelioma (MM) cases occurred in the period 1993-2003 selected from the regional mesothelioma register (RMR) and 273 controls. The disease risk was estimated by means of a logistic-regression model, in which the probability of disease-occurrence is expressed as a function of the classes of distances. A non-parametric method was applied to estimate the full relative risk surface. RESULTS: Significant MM odds ratio of 5.29 (95 CI: 1.18-23.74) was found for people living within a range up to 500 m centered on the plant. The non-parametric estimation of relative risk surface unveiled a marked peak near the plant not paralleled by the spatial distribution of controls. CONCLUSION: Evidence of an association between mesothelioma risk and EAE is highlighted. The role played by the RMR in increasing the public health local authorities awareness is stressed.

[Assessment of risk of mesothelioma: the case of an asbestos-cement production plant in the city of Bari]. / Valutazione del rischio di mesotelioma: il caso di una fabbrica per la produzione di cemento-amianto nella città di Bari.

OBJECTIVE: In this paper, by means of explorative methods based on geographical analysis, the relationship between the presence of an asbestos-cement factory in the urban area of Bari and malignant mesothelioma cases, occurring between 1980 and 2001 among residents, is analysed. METHODS: The data source of the 64 cases studied is the national register of mesotheliomas (Renam), the Apulia regional operating centre (Cor-Puglia). Data are analysed by the use of the S + SpatialStats software. RESULTS AND DISCUSSION: Both individual data analysis and explorative geographic analysis point out an increased risk of disease among people living near the asbestos-cement factory: within an area centred on the location of plants and having a radius of about 1 Km, the estimated risk is 2.38 times above the normal level. Further analytical studies are required.