Search

Parkinson's disease (PD) is primarily known as a movement disorder because of typical clinical manifestations associated with the loss of dopaminergic neurons in the substantia nigra. However, it is now widely recognized that PD is a much more complex condition, with multiple and severe nonmotor features implicating additional brain areas and organs in the disease process. Pathologically, typical forms of PD are characterized by the accumulation of α‐synuclein‐rich protein inclusions known as Lewy bodies and Lewy neurites, although other types of protein inclusions are also often present in the brain. Familial forms of PD have provided a wealth of information about molecular pathways leading to neurodegeneration, but only to add to the complexity of the problem and uncover new knowledge gaps. Therefore, modeling PD in the laboratory has become increasingly challenging. Here, we discuss knowledge gaps and challenges in the use of laboratory models for the study of a disease that is clinically heterogeneous and multifactorial. We propose that the combined use of patient‐derived cells and animal models, along with current technological tools, will not only expand our molecular and pathophysiological understanding of PD, but also assist in the identification of therapeutic strategies targeting relevant pathogenic pathways. © 2020 International Parkinson and Movement Disorder Society [ABSTRACT FROM AUTHOR]

The article presents information on the evaluation of the concentrations of heavy metals in soils and mosses of the Sicily Region in Italy. Mosses are good bioindicators and are used for monitoring anthropogenic and natural fall-out on soils. Mosses and the surface soil were sampled at 28 sites. The elements Cd, Cu, Ni, Pb and Zn were analyzed by ICP-MS and Hg by AAS. Statistical analysis was done by PCA and spatial representation by GIS. The sites where the concentrations of heavy metals cause greatest concern, were revealed by the PCA analysis and portrayed using GIS.

An inter-comparison exercise was performed between two laboratories on mineralized moss samples. Ten samples, together with three certified reference materials (CRM 61, CRM 62 and CRM 482) and five blanks were mineralized independently in the two laboratories and then analysed by both with different techniques (AAS, ICP-MS, and INAA). The elements analyzed were: Cd, Cr, Cu, Fe, Ni, and Pb. Accuracy tests showed that, for AAS, the relative standard deviations for five repetitions of the same sample were between 0.2 I for Cd and 2.9 % for Cr and that the concentration values found for reference materials were within one standard deviation from the certified values, with the exception of Cr and Cd for CRM 482. The statistical analysis was performed first with a simple linear regression and a Student t-test taking into account the possible influence of the mineralization procedure and ofthe analytical technique, in order to evaluate their reliability. The results showed that more than 78 % of the regressions had a correlation coefficient higher than 0.750, and that 83 % of the slopes were not different from ogre with a level of significance of 0.01. Afterwards, the precision of the measurements were evaluated using maximum likelihood; the normalized errors showed that 1CP-MS had a better performance on most of the elements analysed (with the exception of Fe) aril that both the mineralization procedures gave satisfactory results. The two laboratories were then found to produce reliable results. [ABSTRACT FROM AUTHOR]