Air pollution is becoming a major health problem that affects millions of people worldwide. In support of this observation, the World Health Organization estimates that every year, 2.4 million people die because of the effects of air pollution on health. Mitigation strategies such as changes in diesel engine technology could result in fewer premature mortalities, as suggested by the US Environmental Protection Agency. This review: (i) discusses the impact of air pollution on respiratory disease; (ii) provides evidence that reducing air pollution may have a positive impact on the prevention of disease; and (iii) demonstrates the impact concerted polices may have on population health when governments take actions to reduce air pollution.

Background: The Mexico City Metropolitan Area is densely populated, and toxic air pollutants are generated and concentrated at a higher rate because of its geographic characteristics. It is well known that exposure to particulate matter, especially to fine and ultra-fine particles, enhances the risk of cardio-respiratory diseases, especially in populations susceptible to oxidative stress. The aim of this study was to evaluate the effect of fine particles on the respiratory burst of circulating neutrophils from asthmatic patients living in Mexico City.

Currently, research in physiology focuses on molecular mechanisms underlying the functioning of living organisms. Reductionist strategies are used to decompose systems into their components and to measure changes of physiological variables between experimental conditions. However, how these isolated physiological variables translate into the emergence -and collapse- of biological functions of the organism as a whole is often a less tractable question. To generate a useful representation of physiology as a system, known and unknown interactions between heterogeneous physiological components must be taken into account. In this work we use a Complex Inference Networks approach to build physiological networks from biomarkers. We employ two unrelated databases to generate Spearman correlation matrices of 81 and 54 physiological variables, respectively, including endocrine, mechanic, biochemical, anthropometric, physiological, and cellular variables. From these correlation matrices we generated physiological networks by selecting a p-value threshold indicating statistically significant links. We compared the networks from both samples to show which features are robust and representative for physiology in health. We found that although network topology is sensitive to the p-value threshold, an optimal value may be defined by combining criteria of stability of topological features and network connectedness. Unsupervised community detection algorithms allowed to obtain functional clusters that correlate well with current medical knowledge. Finally, we describe the topology of the physiological networks, which lie between random and ordered structural features, and may reflect system robustness and adaptability. Modularity of physiological networks allows to explore functional clusters that are consistent even when considering different physiological variables. Altogether Complex Inference Networks from biomarkers provide an efficient implementation of a systems biology approach that is visually understandable and robust. We hypothesize that physiological networks allow to translate concepts such as homeostasis into quantifiable properties of biological systems useful for determination and quantification of health and disease.

Background: Studies show that diet and exercise are important in the treatment of obesity. The aim of this study was to determine whether additional regular moderate aerobic exercise during a treatment with hypocaloric diet has a beneficial effect on oxidative stress and molecular damage in the obese patient. Methods: Oxidative stress of 16 normal-weight (NW) and 32 obese 1 (O1) subjects (BMI 30–34.9 kg/m²) were established by biomarkers of oxidative stress in plasma. Recombinant human insulin was incubated with blood from NW or O1 subjects, and the molecular damage to the hormone was analyzed. Two groups of treatment, hypocaloric diet (HD) and hypocaloric diet plus regular moderate aerobic exercise (HDMAE), were formed, and their effects in obese subjects were analyzed. Results: The data showed the presence of oxidative stress in O1 subjects. Molecular damage and polymerization of insulin was observed more frequently in the blood from O1 subjects. The treatment of O1 subjects with HD decreased the anthropometric parameters as well as oxidative stress and molecular damage, which was more effectively prevented by the treatment with HDMAE. Conclusion: HD and HDMAE treatments decreased anthropometric parameters, oxidative stress, and molecular damage in O1 subjects.