Mitochondrial and Autophagic Regulation of Adult Neurogenesis in the Healthy and Diseased Brain

Adult neurogenesis is a highly regulated process during which new neurons are generated from neural stem cells in two discrete regions of the adult brain: the subventricular zone of the lateral ventricle and the subgranular zone of the dentate gyrus in the hippocampus. Defects of adult hippocampal neurogenesis have been linked to cognitive decline and dysfunction during natural aging and in neurodegenerative diseases, as well as psychological stress-induced mood disorders. Understanding the mechanisms and pathways that regulate adult neurogenesis is crucial to improving preventative measures and therapies for these conditions. Accumulating evidence shows that mitochondria directly regulate various steps and phases of adult neurogenesis. This review summarizes recent findings on how mitochondrial metabolism, dynamics, and reactive oxygen species control several aspects of adult neural stem cell function and their differentiation to newborn neurons. It also discusses the importance of autophagy for adult neurogenesis, and how mitochondrial and autophagic dysfunction may contribute to cognitive defects and stress-induced mood disorders by compromising adult neurogenesis. Finally, I suggest possible ways to target mitochondrial function as a strategy for stem cell-based interventions and treatments for cognitive and mood disorders.     

Cognitive and metabolic workload assessment techniques: A review in automotive manufacturing context

Ergonomics assessment in the automotive industry has, to date, focused mainly on physical ergonomics, for example, manual handling and posture. However, workload and, in particular, metabolic and cognitive workload, contributes to worker efficiency but has not received sufficient attention to yield practical guidance for industry. Successful workload assessment requires in-depth understanding of the context in which it will be conducted and of the various assessment techniques which will be applied, with consideration given to factors such as feasibility, resources, and skill of the assessor. These requirements are met with challenges within large and complex organizations and are often dealt with in a piecemeal and isolated matter (i.e., reactive workload assessment). The present paper explores these challenges within the automotive manufacturing industry and aims to develop a decision matrix to guide effective selection of workload assessment techniques focused on metabolic and cognitive demands. It also presents the requirements for time, equipment, and knowledge to implement these techniques as part of a participatory ergonomics approach. Early findings suggest that most assessment techniques reviewed require further development, for example, to establish the acceptance criteria for the specific workload scenario. However, five methods (Garg, Borg RPE, IPAQ, SWAT, and NASA-TLX) are ready to use in certain applications. Ultimately, the findings suggest that it is possible to implement a participatory workload evaluation program within large and complex manufacturing plants.     

Robust optimal operation of continuous catalytic reforming process under feedstock uncertainty

The continuous catalytic regenerative (CCR) reforming process is one of the most significant sources of hydrogen production in the petroleum refining process. However, the fluctuations in feedstock composition and flow rate could significantly affect both product distribution and energy consumption. In this study, a robust deviation criterion based multi-objective optimization approach is proposed to perform the optimal operation of CCR reformer under feedstock uncertainty, with simultaneous maximization of product yields and minimization of energy consumption. Minimax approach is adopted to handle these uncertain objectives, and the Latin hypercube sampling method is then used to calculate these robust deviation criteria. Multi-objective surrogate-based optimization methods are next introduced to effectively solve the robust operational problem with high computational cost. The level diagram method is finally utilized to assist in multi-criteria decision-making. Two robust operational optimization problems with different objectives are solved to demonstrate the effectiveness of the proposed method for robust optimal operation of the CCR reforming process under feedstock uncertainty.     

Modeling unaccounted-for gas among residential natural gas consumers using a comprehensive fuzzy cognitive map

Residential natural gas consumption depends on several factors. Available tools and methods to identify, categorize, and validate effective factors have some limitations, making consumption modeling more complex. Once a comprehensive model of effective consumption factors is developed for residential gas consumers, it can predict consumption. In addition, such a model could be used to verify the accuracy of measuring devices in order to reduce unaccounted for gas (UFG). The key factors affecting residential gas consumption were identified based on previous studies and their mutual effects were analyzed using a fuzzy cognitive mapping (FCM) method. The most significant factors and their effects on natural gas consumption in the residential sector were determined. In this study, for the first time, the expected consumption for each consumer was estimated using a consumption index. Generally, if the estimated consumption is significantly different from the amount recorded by the meter, it could suggest a potential source of UFG. The proposed method was applied to the data collected from the residential gas consumers of a small region in Iran (Dasht-e Arjan region, Fars province), and the results demonstrate the effectiveness of the proposed method.     

Human responses to high levels of carbon dioxide and air temperature

In this study, 30 subjects were exposed to different combinations of air temperature (T_a: 24, 27, and 30°C) and CO₂ level (8000, 10 000, and 12 000 ppm) in a high-humidity (RH: 85%) underground climate chamber. Subjective assessments, physiological responses, and cognitive performance were investigated. The results showed that as compared with exposure to T_a = 24°C, exposure to 30°C at all CO₂ levels caused subjects to feel uncomfortably warm and experience stronger odor intensity, while increased mental effort and greater intensity of acute health symptoms were reported. However, no significant effects of T_a on task performance or physiological responses were found. This indicated that subjects had to exert more effort to maintain their performance in an uncomfortably warm environment. Increasing CO₂ from 8000 to 12 000 ppm at all T_a caused subjects to report higher rates of headache, fatigue, agitation, and feeling depressed, although the results were statistically significant only at 24 and 27°C. The text typing performance and systolic blood pressure (SBP) decreased significantly at this exposure, whereas diastolic blood pressure (DBP) and thermal discomfort increased significantly. These effects suggest higher arousal/stress. No significant interaction effect of T_a and CO₂ concentration on human responses was identified.     

Inhibition of Soluble Epoxide Hydrolase Ameliorates Phenotype and Cognitive Abilities in a Murine Model of Niemann Pick Type C Disease

Niemann–Pick type C (NPC) disease is a rare autosomal recessive inherited childhood neurodegenerative disease characterized by the accumulation of cholesterol and glycosphingolipids, involving the autophagy-lysosome system. Inhibition of soluble epoxide hydrolase (sEH), an enzyme that metabolizes epoxy fatty acids (EpFAs) to 12-diols, exerts beneficial effects in modulating inflammation and autophagy, critical features of the NPC disease. This study aims to evaluate the effects of UB-EV-52, an sEH inhibitor (sEHi), in an NPC mouse model (Npc) by administering it for 4 weeks (5 mg/kg/day). Behavioral and cognitive tests (open-field test (OF)), elevated plus maze (EPM), novel object recognition test (NORT) and object location test (OLT) demonstrated that the treatment produced an improvement in short- and long-term memory as well as in spatial memory. Furthermore, UB-EV-52 treatment increased body weight and lifespan by 25% and reduced gene expression of the inflammatory markers (i.e., Il-1β and Mcp1) and enhanced oxidative stress (OS) markers (iNOS and Hmox1) in the treated Npc mice group. As for autophagic markers, surprisingly, we found significantly reduced levels of LC3B-II/LC3B-I ratio and significantly reduced brain protein levels of lysosomal-associated membrane protein-1 (LAMP-1) in treated Npc mice group compared to untreated ones in hippocampal tissue. Lipid profile analysis showed a significant reduction of lipid storage in the liver and some slight changes in homogenated brain tissue in the treated NPC mice compared to the untreated groups. Therefore, our results suggest that pharmacological inhibition of sEH ameliorates most of the characteristic features of NPC mice, demonstrating that sEH can be considered a potential therapeutic target for this disease.     

Skeletal Muscle Health and Cognitive Function: A Narrative Review

Sarcopenia is the loss of skeletal muscle mass and function with advancing age. It involves both complex genetic and modifiable risk factors, such as lack of exercise, malnutrition and reduced neurological drive. Cognitive decline refers to diminished or impaired mental and/or intellectual functioning. Contracting skeletal muscle is a major source of neurotrophic factors, including brain-derived neurotrophic factor, which regulate synapses in the brain. Furthermore, skeletal muscle activity has important immune and redox effects that modify brain function and reduce muscle catabolism. The identification of common risk factors and underlying mechanisms for sarcopenia and cognition may allow the development of targeted interventions that slow or reverse sarcopenia and also certain forms of cognitive decline. However, the links between cognition and skeletal muscle have not been elucidated fully. This review provides a critical appraisal of the literature on the relationship between skeletal muscle health and cognition. The literature suggests that sarcopenia and cognitive decline share pathophysiological pathways. Ageing plays a role in both skeletal muscle deterioration and cognitive decline. Furthermore, lifestyle risk factors, such as physical inactivity, poor diet and smoking, are common to both disorders, so their potential role in the muscle–brain relationship warrants investigation.     

The Interaction of Diet and Mitochondrial Dysfunction in Aging and Cognition

Aging is inevitable and it is one of the major contributors to cognitive decline. However, the mechanisms underlying age-related cognitive decline are still the object of extensive research. At the biological level, it is unknown how the aging brain is subjected to progressive oxidative stress and neuroinflammation which determine, among others, mitochondrial dysfunction. The link between mitochondrial dysfunction and cognitive impairment is becoming ever more clear by the presence of significant neurological disturbances in human mitochondrial diseases. Possibly, the most important lifestyle factor determining mitochondrial functioning is nutrition. Therefore, with the present work, we review the latest findings disclosing a link between nutrition, mitochondrial functioning and cognition, and pave new ways to counteract cognitive decline in late adulthood through diet.     

Transport Map sampling with PGD model reduction for fast dynamical Bayesian data assimilation

The motivation of this work is to address real-time sequential inference of parameters with a full Bayesian formulation. First, the proper generalized decomposition (PGD) is used to reduce the computational evaluation of the posterior density in the online phase. Second, Transport Map sampling is used to build a deterministic coupling between a reference measure and the posterior measure. The determination of the transport maps involves the solution of a minimization problem. As the PGD model is quasi-analytical and under a variable separation form, the use of gradient and Hessian information speeds up the minimization algorithm. Eventually, uncertainty quantification on outputs of interest of the model can be easily performed due to the global feature of the PGD solution over all coordinate domains. Numerical examples highlight the performance of the method.     

水润滑螺旋阶梯腔艉轴承接触特性分析及结构优化

基于有限元法,考虑艉轴承材料的非线性力学特性以及各结构参数间的交互作用,对该轴承进行接触分析。采用正交试验法分析腔长、腔数、螺旋角、深浅腔比例等主要影响因素对接触应力及变形量的影响规律,采用控制变量法分析螺旋腔腔角、进/出水孔直径、螺旋腔腔深等次要因素对接触应力及变形量的影响规律,分别得到各参数的优化值。同时利用多目标优化方法,对艉轴承的沟槽直径和内衬外径进行优化,以满足低应力及轻量化的设计要求。优化后艉轴承质量降低了29%,接触应力降低了12%,在达到轻量化的目的同时,显著提高了其力学性能。