A selenium species in cerebrospinal fluid predicts conversion to Alzheimer’s dementia in persons with mild cognitive impairment

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Published on Tuesday, 19 December 2017 10:00

Vinceti M, Chiari A, Eichmüller M, Rothman KJ, Filippini T, Malagoli C, Weuve J, Tondelli M, Zamboni G, Nichelli PF, Michalke B. 

Alzheimers Res Ther. 2017; 9:100. doi: 10.1186/s13195-017-0323-1 

Abstract

The Epidemiology of Selenium and Human Cancer

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Published on Sunday, 15 October 2017 12:00

Vinceti M, Filippini T, Cilloni S, Crespi CM.

Adv Cancer Res. 2017;136:1-48. doi: 10.1016/bs.acr.2017.07.001

Abstract

The relation between selenium and cancer has been one of the most hotly debated topics in human health over the last decades. Early observational studies reported an inverse relation between selenium exposure and cancer risk. Subsequently, randomized controlled trials showed that selenium supplementation does not reduce the risk of cancer and may even increase it for some types, including advanced prostate cancer and skin cancer. An increased risk of diabetes has also been reported. These findings have been consistent in the most methodologically sound trials, suggesting that the early observational studies were misleading. Other studies have investigated selenium compounds as adjuvant therapy for cancer. Though there is currently insufficient evidence regarding the utility and safety of selenium compounds for such treatments, this issue is worthy of further investigation. The study of selenium and cancer is complicated by the existence of a diverse array of organic and inorganic selenium compounds, each with distinct biological properties, and this must be taken into consideration in the interpretation of both observational and experimental human studies.

Pesticide exposure assessed through agricultural crop proximity and risk of amyotrophic lateral sclerosis

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Published on Tuesday, 29 August 2017 12:00

Vinceti M, Filippini T, Violi F, Rothman KJ, Costanzini S, Malagoli C, Wise LA, Odone A, Signorelli C, Iacuzio L, Arcolin E, Mandrioli J, Fini N, Patti F, Lo Fermo S, Pietrini V, Teggi S, Ghermandi G, Scillieri R, Ledda C, Mauceri C, Sciacca S, Fiore M, Ferrante M.

Environ Health. 2017 Aug 29;16(1):91. doi: 10.1186/s12940-017-0297-2

Abstract

BACKGROUND: Epidemiologic studies have raised the possibility that some pesticide compounds induce the neurodegenerative disease amyotrophic lateral sclerosis (ALS), though the available evidence is not entirely consistent.

METHODS: We conducted a population-based case-control study in two Italian populations to assess the extent to which residence in the vicinity of agricultural crops associated with the application of neurotoxic pesticides is a risk factor for ALS, using crop acreage in proximity to the residence as an index of exposure.

RESULTS: Based on 703 cases and 2737 controls, we computed an ALS odds ratio of 0.92 (95% confidence interval 0.78-1.09) for those in proximity to agricultural land. Results were not substantially different when using alternative exposure categories or when analyzing specific crop types, with the exception of a higher risk related to exposure to citrus orchards and olive groves in Southern Italy, though based on few exposed subjects (N = 89 and 8, respectively). There was little evidence of any dose-response relation between crop proximity and ALS risk, and using long-term residence instead of current residence did not substantially change our estimates.

CONCLUSIONS: Though our index of exposure is indirect and subject to considerable misclassification, our results offer little support for the hypothesis that neurotoxic pesticide exposure increases ALS risk.

A GIS-based atmospheric dispersion model for pollutants emitted by complex source areas

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Published on Thursday, 10 August 2017 12:00

Teggi S, CostanziniS, Ghermandi G, Malagoli M, Vinceti M.

Sci Total Environ. 2017 Aug 10;610-611:175-190. doi: 10.1016/j.scitotenv.2017.07.196.

Abstract

Gaussian dispersion models are widely used to simulate the concentrations and deposition fluxes of pollutants emitted by source areas. Very often, the calculation time limits the number of sources and receptors and the geometry of the sources must be simple and without holes. This paper presents CAREA, a new GIS-based Gaussian model for complex source areas. CAREA was coded in the Python language, and is largely based on a simplified formulation of the very popular and recognized AERMOD model. The model allows users to define in a GIS environment thousands of gridded or scattered receptors and thousands of complex sources with hundreds of vertices and holes. CAREA computes ground level, or near ground level, concentrations and dry deposition fluxes of pollutants. The input/output and the runs of the model can be completely managed in GIS environment (e.g. inside a GIS project). The paper presents the CAREA formulation and its applications to very complex test cases. The tests shows that the processing time are satisfactory and that the definition of sources and receptors and the output retrieval are quite easy in a GIS environment. CAREA and AERMOD are compared using simple and reproducible test cases. The comparison shows that CAREA satisfactorily reproduces AERMOD simulations and is considerably faster than AERMOD.

Magnetic fields exposure from high-voltage power lines and risk of amyotrophic lateral sclerosis in two Italian populations

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Published on Thursday, 01 June 2017 12:00

Vinceti M, Malagoli C, Fabbi S, Kheifets L, Violi F, Poli M, Caldara S, Sesti D, Violanti S, Zanichelli P, Notari B, Fava R, Arena A, Calzolari R, Filippini T, Iacuzio L, Arcolin E, Mandrioli J, Fini N, Odone A, Signorelli C, Patti F, Zappia M, Pietrini V, Oleari P, Teggi S, Ghermandi G, Dimartino A, Ledda C, Mauceri C, Sciacca S, Fiore M, Ferrante M.

Amyotroph Lateral Scler Frontotemporal Degener. 2017 Jun 1:1-7. doi: 10.1080/21678421.2017.1332078

Abstract

The aetiology of amyotrophic lateral sclerosis (ALS), a rare and extremely severe neurodegenerative disease, has been associated with magnetic fields exposure. However, evidence for such a relation in the general population is weak, although the previous null results might also be due to exposure misclassification, or a relationship might exist only for selected subgroups. To test such a hypothesis we carried out a population-based case-control study in two Northern and Southern Italy regions, including 703 ALS cases newly diagnosed from 1998 to 2011 and 2737 controls randomly selected from the residents in the study provinces. Overall, we found that a residence near high-voltage power lines, within the corridors yielding a magnetic fields of ≥0.1 μT, was not associated with an excess disease risk, nor did we identify a dose-response relationship after splitting the exposed corridor according to the 0.1, 0.2 and 0.4 μT cut-points of exposure. These results were confirmed taking into account age at onset, period of diagnosis, sex, geographical area, and length of exposure. Overall, despite the residual possibility of unmeasured confounding or small susceptible subgroups not identified in our study, these results appear to confirm that the exposure to magnetic fields from power lines occurring in the general population is not associated with increased ALS risk.