Comparison between the antioxidant status of terrestrial and diving mammals.

Many diving mammals are known for their ability to deal with nitrogen supersaturation and to tolerate apnea for extended periods. They are all characterized by high oxygen-carrying capacity in blood together with high oxygen storage in their muscle mass due to large myoglobin concentrations. The above properties theoretically also imply a high tissue antioxidant defenses (AD) to counteract reactive oxygen species (ROS) generation associated with the rapid transition from apnea to reoxygenation. Different enzymatic (superoxide dismutase, catalase, glutathione reductase, glutathione peroxidase, and glutathione S-transferase), and non-enzymatic (levels of glutathione) AD as well as cellular damage (thiobarbituric acid-reactive substances contents, as a measure of lipoperoxidation) were measured in blood samples obtained from anesthetized animals, and also in blood obtained from recently dead diving mammals, and compared to some terrestrial mammals (n=5 in both groups). The results confirmed that diving mammals have, in general, higher antioxidant status compared to non-diving mammals. Apparently, to avoid exposure of tissues to changing high oxygen levels, and therefore to avoid an oxidative stress condition related to antioxidant consumption and increased ROS generation, diving mammals possess constitutive high levels of antioxidants in tissues. These data are in agreement with short-term AD adaptations related to torpor and to animals that experience large daily changes in oxygen consumption. These data are similar to the long-term adaptations of animals that undergo hibernation, estivation, freezing-thawing and dehydration-rehydration processes. In summary, animals that routinely face high changes in oxygen availability and/or consumption seem to show a general strategy to prevent oxidative damage by having either appropriate high constitutive AD and/or the ability to undergo arrested states, where depressed metabolic rates minimize the oxidative challenge.

The Sardinian IDDM study: 1. Epidemiology and geographical distribution of IDDM in Sardinia during 1989 to 1994.

Analysis of the geographical variation of risk for a disease is a key issue in descriptive epidemiology and may provide useful suggestions for planning further studies to identify the underlying causes. We adopted a Bayesian approach to investigate the geographical distribution of insulin-dependent diabetes mellitus (IDDM) incidence rate across Sardinia. Data on incidence of IDDM in children aged under 15 years (619 IDDM cases) in Sardinia was obtained by the Sardinian Eurodiab ACE register. The overall completeness of ascertainment was: 91.3%. The average yearly standardized incidence rate for the years 1989-1994 was 33.24 per 100000 (95% C.I. 30.60, 35.88), which is the second highest in Europe after Finland. Sex and age-specific risks were higher in males than in females. Considering the variation of IDDM risk according to the age at diagnosis, the risk profile increased up to the 13th year of age for both sexes, being steeper in males. The degree of geographical variation in IDDM risk was small with a slight difference between the highest and the lowest standardized rate across the map. Indeed, even the municipalities at lowest risk in Sardinia showed a risk higher than most European countries. The Sardinian population is genetically atypical, characterized by genetic homogeneity and marked susceptibility to autoimmune diseases. Our finding of a small geographical variation within the island coupled with a marked temporal trend previously observed in data on military conscripts could be interpreted as evidence of a relatively recent environmental aetiological factor that was uniformly distributed across the island and had its effect in a genetically predisposed population.

Bayesian analysis of space-time variation in disease risk.

The analysis of variation of risk for a given disease in space and time is a key issue in descriptive epidemiology. When the data are scarce, maximum likelihood estimates of the area-specific risk and of its linear time-trend can be seriously affected by random variation. In this paper, we propose a Bayesian model in which both area-specific intercept and trend are modelled as random effects and correlation between them is allowed for. This model is an extension of that originally proposed for disease mapping. It is illustrated by the analysis of the cumulative prevalence of insulin dependent diabetes mellitus as observed at the military examination of 18-year-old conscripts born in Sardinia during the period 1936-1971. Data concerning the genetic differentiation of the Sardinian population are used to interpret the results.

[Bayesian analysis of ecological studies]. / Analisi bayesiana di studi ecologici.

Studying the space-time variation of risk for a given disease may give etiological clues and suggestions for planning further studies to investigate the underlying causes. When the observed events are rare, approaches based on maximum likelihood may lead to unstable and largely uninformative estimates of risk and of its time trend due to Poisson sampling variation. In this paper we propose a general Bayesian model for analyzing the variation of risk in space and time. We applied the Bayesian model to the analysis of the geographical variation of breast cancer mortality, to an ecological study on the correlation between lung cancer mortality and degree of urbanization and industrialization and to the analysis of the space-time variation of cumulative prevalence of Insulin Dependent Diabetes Mellitus (IDDM) as observed in military examinations between 1954 and 1989.