Chronic Obstructive Pulmonary Disease and Lung Cancer: Underlying Pathophysiology and New Therapeutic Modalities

Chronic obstructive pulmonary disease (COPD) and lung cancer are major lung diseases affecting millions worldwide. Both diseases have links to cigarette smoking and exert a considerable societal burden. People suffering from COPD are at higher risk of developing lung cancer than those without, and are more susceptible to poor outcomes after diagnosis and treatment. Lung cancer and COPD are closely associated, possibly sharing common traits such as an underlying genetic predisposition, epithelial and endothelial cell plasticity, dysfunctional inflammatory mechanisms including the deposition of excessive extracellular matrix, angiogenesis, susceptibility to DNA damage and cellular mutagenesis. In fact, COPD could be the driving factor for lung cancer, providing a conducive environment that propagates its evolution. In the early stages of smoking, body defences provide a combative immune/oxidative response and DNA repair mechanisms are likely to subdue these changes to a certain extent; however, in patients with COPD with lung cancer the consequences could be devastating, potentially contributing to slower postoperative recovery after lung resection and increased resistance to radiotherapy and chemotherapy. Vital to the development of new-targeted therapies is an in-depth understanding of various molecular mechanisms that are associated with both pathologies. In this comprehensive review, we provide a detailed overview of possible underlying factors that link COPD and lung cancer, and current therapeutic advances from both human and preclinical animal models that can effectively mitigate this unholy relationship

A review on assembly sequence planning and assembly line balancing optimisation using soft computing approaches

Assembly optimisation activities occur across development and production stages of manufacturing goods. Assembly Sequence Planning (ASP) and Assembly Line Balancing (ALB) problems are among the assembly optimisation. Both of these activities are classified as NP-hard. Several soft computing approaches using different techniques have been developed to solve ASP and ALB. Although these approaches do not guarantee the optimum solution, they have been successfully applied in many ASP and ALB optimisation works. This paper reported the survey on research in ASP and ALB that use soft computing approaches for the past 10years. To be more specific, only Simple Assembly Line Balancing Problem (SALBP) is considered for ALB. The survey shows that three soft computing algorithms that frequently used to solve ASP and ALB are Genetic Algorithm, Ant Colony Optimisation and Particle Swarm Optimisation. Meanwhile, the research in ASP and ALB is also progressing to the next level by integration of assembly optimisation activities across product development stages

An efficient evolutionary multi-objective framework for MEMS design optimisation: validation, comparison and analysis

The application of multi objective evolutionary algorithms (MOEA) in the design optimisation of microelectromechanical systems (MEMS) is of particular interest in this research. MOEA is a class of soft computing techniques of biologically inspired stochastic algorithms, which have proved to outperform their conventional counterparts in many design optimisation tasks. MEMS designers can utilise a variety of multi-disciplinary design tools that explore a complex design search space, however, still follow the traditional trial and error approaches. The paper proposes a novel framework, which couples both modelling and analysis tools to the most referenced MOEAs (NSGA-II and MOGA-II). The framework is validated and evaluated through a number of case studies of increasing complexity. The research presented in this paper unprecedentedly attempts to compare the performances of the mentioned algorithms in the application domain. The comparative study shows significant insights into the behaviour of both of the algorithms in the design optimisation of MEMS. The paper provides extended discussions and analysis of the results showing, overall, that MOGA-II outperforms NSGA-II, for the selected case studies

Effects of a low carbohydrate weight loss diet on exercise capacity and tolerance in obese subjects

Dietary restriction and increased physical activity are recommended for obesity treatment. Very low carbohydrate diets are used to promote weight loss, but their effects on physical function and exercise tolerance in overweight and obese individuals are largely unknown. The aim of this study was to compare the effects of a very low carbohydrate, high fat (LC) diet with a conventional high carbohydrate, low fat (HC) diet on aerobic capacity, fuel utilization during submaximal exercise, perceived exercise effort (RPE) and muscle strength. Sixty subjects (age: 49.2+/-1.2 years; BMI: 33.6+/-0.5 kg/m2) were randomly assigned to an energy restricted (approximately 6-7 MJ, 30% deficit), planned isocaloric LC or HC for 8 weeks. At baseline and week 8, subjects performed incremental treadmill exercise to exhaustion and handgrip and isometric knee extensor strength were assessed. Weight loss was greater in LC compared with HC (8.4+/-0.4% and 6.7+/-0.5%, respectively; P=0.01 time x diet). Peak oxygen uptake and heart rate were unchanged in both groups (P>0.17). Fat oxidation increased during submaximal exercise in LC but not HC (P0.25). An LC weight loss diet shifted fuel utilization toward greater fat oxidation during exercise, but had no detrimental effect on maximal or submaximal markers of aerobic exercise performance or muscle strength compared with an HC diet. Further studies are required to determine the interaction of LC diets with regular exercise training and the long-term health effects.Grant D. Brinkworth, Manny Noakes, Peter M. Clifton and Jonathan D. Buckle