Sleep is considered an important modulator of the immune response. Thus, a lack of sleep can weaken immunity, increasing organism susceptibility to infection. For instance, shorter sleep durations are associated with a rise in suffering from the common cold. The function of sleep in altering immune responses must be determined to understand how sleep deprivation increases the susceptibility to viral, bacterial, and parasitic infections. There are several explanations for greater susceptibility to infections after reduced sleep, such as impaired mitogenic proliferation of lymphocytes, decreased HLA-DR expression, the upregulation of CD14+, and variations in CD4+ and CD8+ T lymphocytes, which have been observed during partial sleep deprivation. Also, steroid hormones, in addition to regulating sexual behavior, influence sleep. Thus, we hypothesize that sleep and the immune-endocrine system have a bidirectional relationship in governing various physiological processes, including immunity to infections. This review discusses the evidence on the bidirectional effects of the immune response against viral, bacterial, and parasitic infections on sleep patterns and how the lack of sleep affects the immune response against such agents. Because sleep is essential in the maintenance of homeostasis, these situations must be adapted to elicit changes in sleep patterns and other physiological parameters during the immune response to infections to which the organism is continuously exposed.

Most of the current research on parasitic infections that affect humans and domestic animals has been focused on vaccines, diagnostic methods, epidemiology, new drug design, and recently, with the advancement of genomics and proteomics, on the evolutionary origins of parasites. However, the basic biology of many parasites of medical and veterinary importance has not been intensively studied. Some efforts have been made to obtain information on the parasite-host relationship; however, knowledge of the intricate neuroimmunoendocrine interactions of the host-parasite network, the consequences of this interaction on the host and parasite physiology, and its possible applications needs further investigation. We review here the literature, our own studies on the host-parasite neuroimmunoendocrine network, and how this basic knowledge can be used to design new treatments, by way of using hormones, antihormones, and hormone analogues as a possible novel therapy during parasitic diseases, with special emphasis on helminth parasites. Besides the biological interest, these investigations may contribute to the future identification of alternative treatments for several parasitic diseases. This complicated neuroimmunoendocrine network management during parasitic infections, and its physiological and behavioural consequences upon the host, may be operative in other mammalian infections. Such complexity may also help to explain the often conflicting results, observed between infections with respect to the role of the host sex and age, and hints to other avenues of research and strategies for their treatment and control.

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.

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Sleep is considered an important predictor of immunity. A lack of sleep may reduce immunity, which increases susceptibility to any type of infection. Moreover, sleep deprivation in humans produces changes in both, the percent of circulating immune cells (T cells and NK cells) and cytokine levels (IL-1, IFNγ, TNΦ-αα, IL-6 and IL-17). The aim of our study was to investigate whether sleep deprivation produces deregulation on immune variables during the immune response generated against the helminth parasite Trichinella spiralis. Because sleep deprivation is stressful per se, we designed another experiments to compared stress alone (consisting in movement restriction and single housing) with sleep deprivation, in both control (uninfected) and experimental (infected) rats. Our results demonstrate that the sleep deprivation and stress have a differential effect in mesenteric lymph nodes (MLN) and spleen. In uninfected rats sleep deprivation alone produces an increase in natural killer cells (NK+) and B cells (CD45+), accompanied by a decrease in cytotoxic T cells (CD3+CD8+) in spleen; while, in MLN, produces only an increase in natural killer cells (NK+). Both, SD and stress, produce an increased percentage of total T cells (CD3+) in spleen. In the MLN both are also associated to an increase in cytotoxic T cells (CD3+CD8+) and B cells (CD45+). In the spleens of parasitized rats, cell populations did not change. In spleens of both, sleep-deprived and stressed infected rats, we observed an increase in B cells (CD45+). In infected rats, sleep deprivation alone produced an increase in NK cells (NK+). In mesenteric node cell populations of parasitized rats, we observed a decrease in NK cells and an increase in T helper (CD4+) cells in both SD and stressed rats. Rats that were only subjected to stress showed a decrease in B cells (CD45+). These findings suggest that the immune response generated against infection caused by T. spiralis is affected when the sleep pattern is disrupted. These results support the notion that sleep is a fundamental process for an adequate and strong immune response generated against this parasite.