Locus coeruleus to basolateral amygdala noradrenergic projections promote anxiety-like behavior

Increased tonic activity of locus coeruleus noradrenergic (LC-NE) neurons induces anxiety-like and aversive behavior. While some information is known about the afferent circuitry that endogenously drives this neural activity and behavior, the downstream receptors and anatomical projections that mediate these acute risk aversive behavioral states via the LC-NE system remain unresolved. Here we use a combination of retrograde tracing, fast-scan cyclic voltammetry, electrophysiology, and in vivo optogenetics with localized pharmacology to identify neural substrates downstream of increased tonic LC-NE activity in mice. We demonstrate that photostimulation of LC-NE fibers in the BLA evokes norepinephrine release in the basolateral amygdala (BLA), alters BLA neuronal activity, conditions aversion, and increases anxiety-like behavior. Additionally, we report that β-adrenergic receptors mediate the anxiety-like phenotype of increased NE release in the BLA. These studies begin to illustrate how the complex efferent system of the LC-NE system selectively mediates behavior through distinct receptor and projection-selective mechanisms

Aflatoxin B1 in chilies from the Punjab region, Pakistan

The occurrence of aflatoxin B1 (AFB1) in chilies from Pakistan was determined by using HPLC in work undertaken in Pakistan.Whole (n=22) and powdered (n=22) chilies were analyzed. Sixteen (73.0%) and 19 (86.4%) samples of whole and ground chilies, respectively, were contaminated. The mean concentration in powdered chilies (32.20 μg/kg) was higher statistically than in whole chilies (24.69 μg/kg). Concentrations ranged from 0.00 to 89.56 μg/ kg for powdered chilies, compared with 0.00–96.3 μg/kg for whole chilies. The limits of detection and quantification were 0.05 μg/kg and 0.53 μg/kg, respectively. The concentrations were high in general and greater than the statutory limit set by the European Union. There is considerable scope for improvements in chili production in Pakistan.Higher Education Commission, PakistanFundação para a Ciência e a Tecnologia (FCT

Continuous Process Improvement Implementation Framework Using Multi-Objective Genetic Algorithms and Discrete Event Simulation

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Purpose Continuous process improvement is a hard problem, especially in high variety/low volume environments due to the complex interrelationships between processes. The purpose of this paper is to address the process improvement issues by simultaneously investigating the job sequencing and buffer size optimization problems. Design/methodology/approach This paper proposes a continuous process improvement implementation framework using a modified genetic algorithm (GA) and discrete event simulation to achieve multi-objective optimization. The proposed combinatorial optimization module combines the problem of job sequencing and buffer size optimization under a generic process improvement framework, where lead time and total inventory holding cost are used as two combinatorial optimization objectives. The proposed approach uses the discrete event simulation to mimic the manufacturing environment, the constraints imposed by the real environment and the different levels of variability associated with the resources. Findings Compared to existing evolutionary algorithm-based methods, the proposed framework considers the interrelationship between succeeding and preceding processes and the variability induced by both job sequence and buffer size problems on each other. A computational analysis shows significant improvement by applying the proposed framework. Originality/value Significant body of work exists in the area of continuous process improvement, discrete event simulation and GAs, a little work has been found where GAs and discrete event simulation are used together to implement continuous process improvement as an iterative approach. Also, a modified GA simultaneously addresses the job sequencing and buffer size optimization problems by considering the interrelationships and the effect of variability due to both on each other