Effects of intensified training and taper on immune function

Although resting immune function is not very different in athletes compared with non-athletes periods of intensified training (overreaching) in already well trained athletes can result in a depression of immunity in the resting state. Illness-prone athletes appear to have an altered cytokine response to antigen stimulation and exercise. Having low levels of salivary IgA secretion also makes athletes more susceptible to upper respiratory tract infections. Overtraining is associated with recurrent infections and immunodepression is common, but immune functions do not seem to be reliable markers of impending overtraining. There are several possible causes of the diminution of immune function associated with periods of heavy training. One mechanism may simply be the cumulative effects of repeated bouts of intense exercise (with or without tissue damage) with the consequent elevation of stress hormones, particularly glucocorticoids such as cortisol, causing temporary inhibition of TH-1 cytokines with a relative dampening of the cell-mediated response. When exercise is repeated frequently there may not be sufficient time for the immune system to recover fully. Tapering has been described as a gradual reduction in the training load which allows the recovery of physiological capacities that were impaired by previous intensive training and permits further training-induced adaptations to occur accompanied by competition performance enhancements. The majority of the studies that have examined the recovery of immunoendocrine responses during 1-3 week tapers in trained athletes have mainly reported enhanced performance, often accompanied by increased anabolic activity, reduced physiological stress and restoration of mucosal immunity and immune function.

Quando se compara a função imune, em repouso, de atletas e não atletas, não se verificam grandes diferenças. Porém, períodos de treinamento intensificado ("overreaching") em atletas bem treinados podem induzir supressão da imunidade no estado de repouso. Os atletas com maior propensão para contrair doenças parecem apresentar uma resposta alterada de citocinas, tanto quando estas são estimuladas por antígenos, quanto em resposta ao exercício propriamente dito. Baixos níveis de secreção de IgA salivar também contribuem para tornar os atletas mais susceptíveis à infecções do trato respiratório superior. A síndrome do "overtraining" é associada a infecções recorrentes e a imunossupressão é comum; no entanto, marcadores da função imune não parecem ser suficientemente sensíveis ao "overtraining" eminente. Existem várias possíveis causas para a diminuição da função imune associadas com períodos de treinamento severo. Um possível mecanismo pode ser simplesmente, o efeito acumulativo de atividades e sessões repetidas de exercício intenso (com ou sem dano tecidual), com a consequente elevação dos hormônios de estresse, particularmente os glicocorticóides como o cortisol, causando assim, uma inibição temporária das citocinas de TH-1, com uma relativa atenuação da resposta imune celular. Quando o exercício é repetido frequentemente, pode não haver tempo suficiente para uma total recuperação do sistema imunológico. O "Tapering" tem sido descrito como uma gradual redução na carga de treinamento a qual permite a recuperação das capacidades fisiológicas, que por sua vez, foram afetadas pelo treinamento intensivo anterior, permitindo assim, que adaptações adicionais decorrentes do treinamento ocorram, acompanhadas pelo incremento do desempenho competitivo. A maioria dos estudos que investigaram a recuperação das respostas imuno-endócrinas em atletas durante uma a três semanas de "taper" tem registrado aumento do desempenho, frequentemente...

Learning ensembles of neural networks by means of a Bayesian artificial immune system.

In this paper, we apply an immune-inspired approach to design ensembles of heterogeneous neural networks for classification problems. Our proposal, called Bayesian artificial immune system, is an estimation of distribution algorithm that replaces the traditional mutation and cloning operators with a probabilistic model, more specifically a Bayesian network, representing the joint distribution of promising solutions. Among the additional attributes provided by the Bayesian framework inserted into an immune-inspired search algorithm are the automatic control of the population size along the search and the inherent ability to promote and preserve diversity among the candidate solutions. Both are attributes generally absent from alternative estimation of distribution algorithms, and both were shown to be useful attributes when implementing the generation and selection of components of the ensemble, thus leading to high-performance classifiers. Several aspects of the design are illustrated in practical applications, including a comparative analysis with other attempts to synthesize ensembles.