The Endoplasmic Reticulum Stress Response in Neuroprogressive Diseases: Emerging Pathophysiological Role and Translational Implications

The endoplasmic reticulum (ER) is the main cellular organelle involved in protein synthesis, assembly and secretion. Accumulating evidence shows that across several neurodegenerative and neuroprogressive diseases, ER stress ensues, which is accompanied by over-activation of the unfolded protein response (UPR). Although the UPR could initially serve adaptive purposes in conditions associated with higher cellular demands and after exposure to a range of pathophysiological insults, over time the UPR may become detrimental, thus contributing to neuroprogression. Herein, we propose that immune-inflammatory, neuro-oxidative, neuro-nitrosative, as well as mitochondrial pathways may reciprocally interact with aberrations in UPR pathways. Furthermore, ER stress may contribute to a deregulation in calcium homoeostasis. The common denominator of these pathways is a decrease in neuronal resilience, synaptic dysfunction and even cell death. This review also discusses how mechanisms related to ER stress could be explored as a source for novel therapeutic targets for neurodegenerative and neuroprogressive diseases. The design of randomised controlled trials testing compounds that target aberrant UPR-related pathways within the emerging framework of precision psychiatry is warranted

A genetic algorithm/mathematical programming approach to solve a two-level soft drink production problem

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)This study applies a genetic algorithm embedded with mathematical programming techniques to solve a synchronized and integrated two-level lot sizing and scheduling problem motivated by a real-world problem that arises in soft drink production. The problem considers a production process compounded by raw material preparation/storage and soft drink bottling. The lot sizing and scheduling decisions should be made simultaneously for raw material preparation/storage in tanks and soft drink bottling in several production lines minimizing inventory, shortage and setup costs. The literature provides mixed-integer programming models for this problem, as well as solution methods based on evolutionary algorithms and relax-and-fix approaches. The method applied by this paper uses a new approach which combines a genetic algorithm (GA) with mathematical programming techniques. The GA deals with sequencing decisions for production lots, so that an exact method can solve a simplified linear programming model, responsible for lot sizing decisions. The computational results show that this evolutionary/mathematical programming approach outperforms the literature methods in terms of production costs and run times when applied to a set of real-world problem instances provided by a soft drink company. (C) 2014 Elsevier Ltd. All rights reserved.484052Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)CNPq [483474/2013-4]FAPESP [2010/10133-0