902 research outputs found

    Heavy metals contaminating the environment of a progressive supranuclear palsy cluster induce tau accumulation and cell death in cultured neurons

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    Progressive supranuclear palsy (PSP) is a neurodegenerative disorder characterized by the presence of intracellular aggregates of tau protein and neuronal loss leading to cognitive and motor impairment. Occurrence is mostly sporadic, but rare family clusters have been described. Although the etiopathology of PSP is unknown, mutations in the MAPT/tau gene and exposure to environmental toxins can increase the risk of PSP. Here, we used cell models to investigate the potential neurotoxic effects of heavy metals enriched in a highly industrialized region in France with a cluster of sporadic PSP cases. We found that iPSC-derived iNeurons from a MAPT mutation carrier tend to be more sensitive to cell death induced by chromium (Cr) and nickel (Ni) exposure than an isogenic control line. We hypothesize that genetic variations may predispose to neurodegeneration induced by those heavy metals. Furthermore, using an SH-SY5Y neuroblastoma cell line, we showed that both heavy metals induce cell death by an apoptotic mechanism. Interestingly, Cr and Ni treatments increased total and phosphorylated tau levels in both cell types, implicating Cr and Ni exposure in tau pathology. Overall, this study suggests that chromium and nickel could contribute to the pathophysiology of tauopathies such as PSP by promoting tau accumulation and neuronal cell death

    Predictors of survival in progressive supranuclear palsy and multiple system atrophy: a systematic review and meta-analysis

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    Objective To undertake a systematic review and meta-analysis of studies that investigated prognostic factors and survival in patients with progressive supranuclear palsy (PSP) and multiple system atrophy (MSA). Methods Publications of at least 10 patients with a likely or confirmed diagnosis of PSP or MSA were eligible for inclusion. Methodological quality was rated using a modified version of the Quality in Prognostic Studies tool. For frequently examined prognostic factors, HRs derived by univariate and multivariate analysis were pooled in separate subgroups; other results were synthesised narratively and HRs could not be reported here. Results Thirty-seven studies presenting findings on 6193 patients (1911 PSP, 4282 MSA) fulfilled the inclusion criteria. We identified the following variables as unfavourable predictors of survival. In PSP, PSP-Richardson’s phenotype (univariate HR 2.53; 95% CI 1.69 to 3.78), early dysphagia and early cognitive symptoms. In MSA, severe dysautonomia and early development of combined autonomic and motor features but not MSA phenotype (multivariate HR 1.22; 95% CI 0.83 to 1.80). In PSP and MSA, survival was predicted by early falls (multivariate HR 2.32; 95% CI 1.94 to 2.77), the Neuroprotection and Natural History in Parkinson Plus Syndromes Parkinson Plus Score and the Clinical Global Impression Disease Severity Score but not sex (multivariate HR 0.93; 95% CI 0.67 to 1.28). There was conflicting evidence regarding the prognostic effect of age at onset and stridor. Conclusion Several clinical variables were strongly associated with shorter survival in PSP and MSA. Results on most prognostic factors were consistent across methodologically diverse studies; however, the lack of commonality of prognostic factors investigated is a significant limitation

    Proteome analysis of human substantia nigra in Parkinson's disease

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    Protein expression has been compared in human substantia nigra specimens from Parkinson's disease (PD) patients and from controls, and 44 proteins expressed in this midbrain region were identified by peptide mass fingerprinting. Among them, nine showed changes in their abundance. L and M neurofilament chains are less abundant in PD specimens, whereas peroxiredoxin II, mitochondrial complex III, ATP synthase D chain, complexin I, profilin, L-type calcium channel delta-subunit, and fatty-acid binding protein are significantly more present in PD samples than in controls. Besides the consolidated view of oxidative stress involvement in PD pathogenesis, suggested by overexpression of mitochondrial and reactive oxygen species (ROS)-scavenging proteins, these results indicate a possible potentiation mechanism of afferent signals to substantia nigra following degeneration of dopaminergic neurons

    Mergers and Acquisitions in Latin America: Industrial Productivity and Corporate Governance

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    This paper examines the impact of industrial productivity on transnationals M&As from OECD countries towards Latin American countries in the period 1996 to 2010. It also analyzes the relationship between external mechanism of corporate governance and transnational M&As. For this purpose we use a gravitational model at the industry level. We find that industry productivity and higher standards of corporate governance in the country of origin promote transnational M&As activity. However, it is also found that higher levels of capital and technological productivity decreases transnational M&As activity

    A New Evolutionary Algorithm-Based Home Monitoring Device for Parkinson’s Dyskinesia

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    Parkinson’s disease (PD) is a neurodegenerative movement disorder. Although there is no cure, symptomatic treatments are available and can significantly improve quality of life. The motor, or movement, features of PD are caused by reduced production of the neurotransmitter dopamine. Dopamine deficiency is most often treated using dopamine replacement therapy. However, this therapy can itself lead to further motor abnormalities referred to as dyskinesia. Dyskinesia consists of involuntary jerking movements and muscle spasms, which can often be violent. To minimise dyskinesia, it is necessary to accurately titrate the amount of medication given and monitor a patient’s movements. In this paper, we describe a new home monitoring device that allows dyskinesia to be measured as a patient goes about their daily activities, providing information that can assist clinicians when making changes to medication regimens. The device uses a predictive model of dyskinesia that was trained by an evolutionary algorithm, and achieves AUC>0.9 when discriminating clinically significant dyskinesia
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