Tested combinations of deposition efficiencies and field metabolic factors.

<p>a) Only few combinations of proportionality constants: <i>ω_A</i> ( = <i>A_A</i>×<i>f_A</i>) and <i>ω_Y</i>(<i> = A_Y</i>×<i>f_Y</i>) produced predictions not significantly different from actual data: in older bears (blue), yearlings (yellow) or both groups (green). All tested combinations are coloured grey. b) Combinations of <i>ω_A</i> and <i>ω_Y</i> that produced predictions not significantly different from actual data in both studied groups exhibited a negative relationship.</p

Field Metabolic Rate and PCB Adipose Tissue Deposition Efficiency in East Greenland Polar Bears Derived from Contaminant Monitoring Data

<div><p>Climate change will increasingly affect the natural habitat and diet of polar bears (<i>Ursus maritimus</i>). Understanding the energetic needs of polar bears is therefore important. We developed a theoretical method for estimating polar bear food consumption based on using the highly recalcitrant polychlorinated biphenyl (PCB) congener, 2,2′,4,4′,55-hexaCB (CB153) in bear adipose tissue as an indicator of food intake. By comparing the CB153 tissue concentrations in wild polar bears with estimates from a purposely designed individual-based model, we identified the possible combinations of field metabolic rates (FMR) and CB153 deposition efficiencies in East Greenland polar bears. Our simulations indicate that if 30% of the CB153 consumed by polar bear individuals were deposited into their adipose tissue, the corresponding FMR would be only two times the basal metabolic rate. In contrast, if the modelled CB153 deposition efficiency were 10%, adult polar bears would require six times more energy than that needed to cover basal metabolism. This is considerably higher than what has been assumed for polar bears in previous studies though it is similar to FMRs found in other marine mammals. An implication of this result is that even relatively small reductions in future feeding opportunities could impact the survival of East Greenland polar bears.</p></div

Medians of CB153 concentration of bear sub groups.

<p>Comparison between median observed CB153 concentrations in East Greenland polar bears (solid red lines) and CB153 concentration simulated using the best-fitting parameter combinations (black) or randomly selected parameter combinations (blue). Quartiles are shown as bars for model predictions and as dashed red lines for East Greenland bears.</p

ANCOVA selected parameter combinations.

<p>ANCOVA selected parameter combinations.</p

Time trend in polar bear CB153 concentrations.

<p>Red dots show the CB153 concentrations in individual East Greenland bears across the study period. Red curve shows log – linear trend in the data. Grey and black curves show simulated trends in CB153 concentrations produced using parameter combinations that produced predictions that did not differ from the observed trends in East Greenland for yearlings and older bears, respectively.</p

Prevalence and predictors of adequate treatment of overt hypothyroidism – a population-based study

The aim of this study is to evaluate the adequacy of treatment, and to identify factors influencing treatment of hypothyroidism. Patients newly diagnosed with overt hypothyroidism (n=345) were identified via a register linked to a laboratory database. In selected periods with staff available, 165 patients were invited, and 113 (68.5 %) accepted participating in a comprehensive program including blood tests and completion of questionnaires. We performed a longitudinal follow-up on thyroid function tests 10 years after the diagnosis. Time to reach a serum TSH level of 0.2-10 mU/L (termed as clinically acceptable) and biochemical normalization (TSH: 0.2-5.0 mU/L), respectively, were analyzed using Kaplan Meier survival analysis. Predictors for longer duration to reach the normal TSH range were identified using cox proportional hazards regression. Only 67.7 % of the patients were in the euthyroid range on the long term after diagnosis of overt hypothyroidism (2 years: 59.4 %; 10 years: 67.7 %). Median time to the first normal TSH was 8.9 months (95 % CI: 7.6-10.2 months). The factors associated with longer duration until normalization of TSH after multivariate analysis were age (HR 0.79 per 10 years; 95 % CI: 0.66-0.94; P