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Life history theories analyze and predict variation in vital rates, such as survival and reproduction, based on age. The age-from-stage method to derive age-specific vital rates from stage data was developed because age-specific data are rarely obtained for plants. Age-specific vital rates derived by this method might underestimate effects of age on vital rates, because the models assume that vital rates do not vary within stage classes. Consequently, population models and life history summaries relying on these vital rates could be biased against detecting senescence. Here, we perform a comparative study of methods to estimate age-specific vital rates using monitoring data with known age and stage. We derived age-, stage-, and age-and-stage-specific vital rates with demographic data from a long-lived perennial, Silene spaldingii. Then, we derived three age-specific population matrix models (age, age-from-stage, and age-and-stage). For each model, we derived life history summaries commonly used in ecology: population growth rate, net reproductive value, relative reproductive values, stable age distribution, generation time, and sensitivity and elasticity of population growth rate. Many vital rates depended on both age and stage in S. spaldingii. However, this species does not senesce; in fact, the number of flowers increased with age. As expected, the age-from-stage method was not able to accurately recreate the age dependence in some life history summaries, such as relative reproductive value. The age-from-stage model suggested faster reproductive dynamics in S. spaldingii than the models based on known age, i.e., plants started to reproduce earlier, and fertility remained constant thereafter, which may lead to biased predictions about evolutionary consequences of age-dependent life history traits. However, population growth rate, generation time, and net reproductive rate did not differ significantly among the models. Our study demonstrated that some metrics are robust to imprecision in model structure, while others are more sensitive. In spite of these biases, this case study provides another example of the diversity of aging patterns in plants. Age can be essential information when studying senescence in plants, but demographic metrics that were not about age per se were similar across model structures.

Summary Many perennial plants experience prolonged dormancy, meaning they do not grow above-ground for one or several growing seasons. When plants disappear (fail to sprout) and have not been recorded to re-emerge, they either have died or are alive and dormant. In demographic studies of such species, researchers have been forced to make assumptions about death versus dormancy. Little is known about the consequences of these assumptions for predictions from the population models used in the studies. Here, we define survival of dormancy-prone plants in three distinct ways: Separate, Instant and Slow death. In the Separate death model, plants are assumed to die either in emergent or in dormant stages. Death can also be described as a process of disappearance followed by dying, either in the first year below-ground (Instant death) or with constant mortality rate in any given dormant year (Slow death). Using simulated data with known parameter values, we test whether survival and re-emergence rates are confounded in these life-history models. Using a general model and models for two orchid species (Epipactis atrorubens and Isotria medeoloides), we test how different assumptions about dormancy (Instant and Slow death) affect predictions about population dynamics: population growth rate, generation time, relative reproductive values, life expectancies, and sensitivity and elasticity of population growth rate to stage transitions and vital rates. Our results confirm that survival and re-emergence rates of dormancy-prone plant species are difficult to estimate; parameters were separable only with the assumptions of Instant and Slow death. Both theoretical and empirical analyses show that the predictions of population growth rate and generation time do not depend on the assumptions made about the fate of the plants after their disappearance. Synthesis. Assumptions about dormancy affect some, but not all predictions, about plant population dynamics. In the studies of species with unobservable stages, assumptions about dormancy should be carefully defined and possible consequences of these assumptions for the predictions of the population model should be evaluated. Nonetheless, if we are only interested in overall population viability, ad hoc models of prolonged dormancy are sufficient as a first step.

Background: During the last several decades the prevalence of coeliac disease (CD) has increased worldwide. Aim: To compare the cumulative incidence of CD between Estonian and Finnish children and to identify the risk factors. Materials and methods: Children were recruited as part of the DIABIMMUNE Study. In the birth cohort (BC) 258 children from Estonia and 305 from Finland, and in the young children's cohort (YCC) 1363 and 1384 children were followed up, respectively. The diagnosis of CD was made in accordance with the ESPGHAN guidelines-the presence of IgA-tTG antibodies and small bowel villous atrophy. Results: During the study period 29 children developed CD. The cumulative incidence of CD was significantly higher in Finland (0.77% vs 0.27%; P = 0.01). No difference was seen between the children with CD and the controls in the duration of breastfeeding or the age at cereal introduction. The BC children with CD had had significantly more episodes of infections with fever by the age of 12 months compared to the controls (3.4 vs 1.4; P = 0.04). Conclusion: The 5-year cumulative incidence of childhood CD is significantly higher in Finland than in Estonia. Sequential infections early in life may increase the risk for developing CD. (C) 2016 Published by Elsevier Ltd on behalf of Editrice Gastroenterologica Italiana S.r.l.

Upregulation of IL-17 immunity and detrimental effects of IL-17 on human islets have been implicated in human type 1 diabetes. In animal models, the plasticity of Th1/Th17 cells contributes to the development of autoimmune diabetes. In this study, we demonstrate that the upregulation of the IL-17 pathway and Th1/Th17 plasticity in peripheral blood are markers of advanced β cell autoimmunity and impaired β cell function in human type 1 diabetes. Activated Th17 immunity was observed in the late stage of preclinical diabetes in children with β cell autoimmunity and impaired glucose tolerance, but not in children with early β cell autoimmunity. We found an increased ratio of IFN-γ/IL-17 expression in Th17 cells in children with advanced β cell autoimmunity, which correlated with HbA1c and plasma glucose concentrations in an oral glucose tolerance test, and thus impaired β cell function. Low expression of Helios was seen in Th17 cells, suggesting that Th1/Th17 cells are not converted thymus-derived regulatory T cells. Our results suggest that the development of Th1/Th17 plasticity may serve as a biomarker of disease progression from β cell autoantibody positivity to type 1 diabetes. These data in human type 1 diabetes emphasize the role of Th1/Th17 plasticity as a potential contributor to tissue destruction in autoimmune conditions.