Mean redox potential values in surface sediments along the transect D in the Cretan Sea (Table 1)

The seasonal, spatial and bathymetric changes in the distribution of chloroplastic pigments (Chl a, phaeopigments and CPE), TOC, TON, ATP, bottom water nutrient content and the main biochemical classes of organic compounds (lipids, proteins and carbohydrates) were recorded from May 1994 to September 1995 over the continental margin of northern Crete. The concentration of chloroplastic pigment equivalents (CPE) was always low, dropping dramatically along the shelf-slope gradient. Microbial activity (ATP) also dropped sharply beyond the continental shelf following a distribution pattern similar to TOC and TON. Lipid, protein and carbohydrate concentrations, as well as biopolymeric carbon were comparable to those reported for other more productive areas, however, the quality of the organic matter itself was rather poor. Thus, carbohydrates, the dominant biochemical class, were characterised by being highly (80-99%) refractory, as soluble carbohydrates represented (on annual average) only 6% of the total carbohydrate pool. Protein and lipid concentrations strongly decreased with depth, indicating depletion of trophic resources in the bathyal zone. Proteins appeared to be the more degradable compounds and indeed the protein to carbohydrate ratios were found to decrease strongly in the deeper stations. Organic matter content and quality decreased both with increasing distance from the coast and within the sediment. All sedimentary organic compounds were found to vary between sampling periods, with the changes being more pronounced over the continental shelf. The different temporal patterns of the various components suggest a different composition and/or origin of the OM inputs during the different sampling periods. The amount of material reaching the sediments below 540 m is extremely low, suggesting that most of the organic material is decomposed and/or utilised before reaching the sea floor. In conclusion, the continental shelf and bathyal sediments of the Cretan Sea can be considered, from a trophic point of view, as two different subsystems.

(Table 1) Mean annual ground temperatures and description of permafrost boreholes in Russia

The results of the International Permafrost Association's International Polar Year Thermal State of Permafrost (TSP) project are presented based on field measurements from Russia during the IPY years (2007-09) and collected historical data. Most ground temperatures measured in existing and new boreholes show a substantial warming during the last 20 to 30 years. The magnitude of the warming varied with location, but was typically from 0.5°C to 2°C at the depth of zero annual amplitude. Thawing of Little Ice Age permafrost is ongoing at many locations. There are some indications that the late Holocene permafrost has begun to thaw at some undisturbed locations in northeastern Europe and northwest Siberia. Thawing of permafrost is most noticeable within the discontinuous permafrost domain. However, permafrost in Russia is also starting to thaw at some limited locations in the continuous permafrost zone. As a result, a northward displacement of the boundary between continuous and discontinuous permafrost zones was observed. This data set will serve as a baseline against which to measure changes of near-surface permafrost temperatures and permafrost boundaries, to validate climate model scenarios, and for temperature reanalysis.

(Table 1) Annual mean concentrations of atmospheric a- and g-Hexachlorocyclohexane at stations Alert, Canada and Zeppelin, Norway

Twelve year datasets of weekly atmospheric concentrations of alpha- and gamma-HCH were compared between the two Arctic monitoring stations of Alert, Nunavut, Canada, and Zeppelin Mountain, Svalbard, Norway. Time-series analysis was conducted with the use of dynamic harmonic regression (DHR), which provided a very good model fit, to examine both the seasonal behaviour in these isomers and the longer-term, underlying trends. Strong spatial differences were not apparent between the two sites, although subtle differences in seasonal behaviour and composition were identified. For example, the composition of gamma-HCH to total HCH (alpha + gamma) was greater at Zeppelin compared to Alert, probably reflecting this site's proximity to major use regions of lindane. Pronounced seasonality in air concentrations for gamma-HCH was marked by a 'spring maximum event' (SME), confirming earlier studies. For alpha-HCH, the SME was much weaker and only evident at Alert, whereas at Zeppelin, seasonal fluctuations for alpha-HCH were marked by elevated concentrations in summer and lower concentrations during winter, with this pattern most apparent for the years after 2000. We attribute this difference in spatial and temporal patterns to the Arctic oscillation. A similar climatic pattern was not evident at either site in the gamma-HCH data. Seasonally adjusted, long-term trends revealed declining concentrations at both sites for alpha- and gamma-HCH over the entire time-series. Recent legislation affecting lindane use appear to account for this decline in gamma-HCH, with little evidence of a delay or 'lag' between the banning of lindane in Europe (a main source region) or Canada, and a decline in air concentrations observed at both Arctic sites.

Estimation of Sample Size and Power For Quantile Regression

Quantile regression (QR) was first introduced by Roger Koenker and Gilbert Bassett in 1978. It is robust to outliers which affect least squares estimator on a large scale in linear regression. Instead of modeling mean of the response, QR provides an alternative way to model the relationship between quantiles of the response and covariates. Therefore, QR can be widely used to solve problems in econometrics, environmental sciences and health sciences. Sample size is an important factor in the planning stage of experimental design and observational studies. In ordinary linear regression, sample size may be determined based on either precision analysis or power analysis with closed form formulas. There are also methods that calculate sample size based on precision analysis for QR like C.Jennen-Steinmetz and S.Wellek (2005). A method to estimate sample size for QR based on power analysis was proposed by Shao and Wang (2009). In this paper, a new method is proposed to calculate sample size based on power analysis under hypothesis test of covariate effects. Even though error distribution assumption is not necessary for QR analysis itself, researchers have to make assumptions of error distribution and covariate structure in the planning stage of a study to obtain a reasonable estimate of sample size. In this project, both parametric and nonparametric methods are provided to estimate error distribution. Since the method proposed can be implemented in R, user is able to choose either parametric distribution or nonparametric kernel density estimation for error distribution. User also needs to specify the covariate structure and effect size to carry out sample size and power calculation. The performance of the method proposed is further evaluated using numerical simulation. The results suggest that the sample sizes obtained from our method provide empirical powers that are closed to the nominal power level, for example, 80%.

Assessment of the cortisol awakening response: Real-time analysis and curvilinear effects of sample timing inaccuracy

The cortisol awakening response (CAR) is typically measured in the domestic setting. Moderate sample timing inaccuracy has been shown to result in erroneous CAR estimates and such inaccuracy has been shown partially to explain inconsistency in the CAR literature. The need for more reliable measurement of the CAR has recently been highlighted in expert consensus guidelines where it was pointed out that less than 6% of published studies provided electronic-monitoring of saliva sampling time in the post-awakening period. Analyses of a merged data-set of published studies from our laboratory are presented. To qualify for selection, both time of awakening and collection of the first sample must have been verified by electronic-monitoring and sampling commenced within 15 min of awakening. Participants (n = 128) were young (median age of 20 years) and healthy. Cortisol values were determined in the 45 min post-awakening period on 215 sampling days. On 127 days, delay between verified awakening and collection of the first sample was less than 3 min (‘no delay’ group); on 45 days there was a delay of 4–6 min (‘short delay’ group); on 43 days the delay was 7–15 min (‘moderate delay’ group). Cortisol values for verified sampling times accurately mapped on to the typical post-awakening cortisol growth curve, regardless of whether sampling deviated from desired protocol timings. This provides support for incorporating rather than excluding delayed data (up to 15 min) in CAR analyses. For this population the fitted cortisol growth curve equation predicted a mean cortisol awakening level of 6 nmols/l (±1 for 95% CI) and a mean CAR rise of 6 nmols/l (±2 for 95% CI). We also modelled the relationship between real delay and CAR magnitude, when the CAR is calculated erroneously by incorrectly assuming adherence to protocol time. Findings supported a curvilinear hypothesis in relation to effects of sample delay on the CAR. Short delays of 4–6 min between awakening and commencement of saliva sampling resulted an overestimated CAR. Moderate delays of 7–15 min were associated with an underestimated CAR. Findings emphasize the need to employ electronic-monitoring of sampling accuracy when measuring the CAR in the domestic setting.

Attitudes and Knowledge Concerning Corneal Donation in a Population-Based Sample of Urban Chinese Adults.

PURPOSE: To better understand knowledge and attitudes concerning corneal donation among Chinese adults.
METHODS: Randomly selected residents in predetermined age strata 20 to 60+ years completed home-based questionnaires in each of 12 randomly chosen communities in Guangzhou, southern China.
RESULTS: Among 1217 selected persons, 430 (35.3%) completed the questionnaires (mean age 40.4 yrs, 57.9% female). Refusers were older (44.8 yrs, P < 0.001), but sex did not differ (52.2% female, P = 0.07). Among participants, 175 (40.7%) were willing to donate their corneas (WTD). Differences between WTD and not WTD included donation knowledge score (range, 1-12) [WTD (SD) 6.91 ± 2.21, not WTD 5.62 ± 2.43, P < 0.001]; having discussed donation (WTD 26.3%, not WTD 8.63%, P < 0.001); viewing donation as unpopular (WTD 88.0%, not WTD 96.5%, P = 0.001); and feeling donation "damages the body" (WTD 15.4%, not WTD 25.7%, P = 0.013). Associated significantly with WTD in multiple regression models were higher knowledge score [odds ratio (OR) = 1.18, 95% confidence interval (CI), 1.04-1.32, P = 0.008]; not feeling donation "damages the body" (OR = 1.91, 95% CI, 1.07-3.43, P = 0.030); and willingness to discuss donation (OR = 10.6, 95% CI, 3.35-33.9, P < 0.001). WTD did not differ by age (>60 yrs: 22/51, 43.1%; ≤60 yrs: 153/379, 40.4%, P = 0.706). Assuming all those refusing the survey would not donate, 14.4% (175/1217) were WTD for themselves, though only 7.1% (86/1217) would do so on behalf of a family member if they did not know the deceased's preference.
CONCLUSIONS: Interventions to increase knowledge and promote discussions about donation, and policies allowing widespread expression of donation preference, are needed in this setting.

Diagnostic potential of structural neuroimaging for depression from a multi-ethnic community sample

Background At present, we do not have any biological tests which can contribute towards a diagnosis of depression. Neuroimaging measures have shown some potential as biomarkers for diagnosis. However, participants have generally been from the same ethnic background while the applicability of a biomarker would require replication in individuals of diverse ethnicities. Aims We sought to examine the diagnostic potential of the structural neuroanatomy of depression in a sample of a wide ethnic diversity. Method Structural magnetic resonance imaging (MRI) scans were obtained from 23 patients with major depressive disorder in an acute depressive episode (mean age: 39.8 years) and 20 matched healthy volunteers (mean age: 38.8 years). Participants were of Asian, African and Caucasian ethnicity recruited from the general community. Results Structural neuroanatomy combining white and grey matter distinguished patients from controls at the highest accuracy of 81% with the most stable pattern being at around 70%. A widespread network encompassing frontal, parietal, occipital and cerebellar regions contributed towards diagnostic classification. Conclusions These findings provide an important step in the development of potential neuroimaging-based tools for diagnosis as they demonstrate that the identification of depression is feasible within a multi-ethnic group from the community. Declaration of interests C.H.Y.F. has held recent research grants from Eli Lilly and Company and GlaxoSmithKline. L.M. is a former employee and stockholder of Eli Lilly and Company.

Assessment of the quality of sample labelling for clinical research

Objective: To assess the quality of the labels for clinical trial samples through current regulations, and to analyze its potential correlation with the specific characteristics of each sample. Method: A transversal multicenter study where the clinical trial samples from two third level hospitals were analyzed. The eleven items from Directive 2003/94/EC, as well as the name of the clinical trial and the dose on the label cover, were considered variables for labelling quality. The influence of the characteristics of each sample on labelling quality was also analyzed. Outcome: The study included 503 samples from 220 clinical trials. The mean quality of labelling, understood as the proportion of items from Appendix 13, was of 91.9%. Out of these, 6.6% did not include the name of the sample in the outer face of the label, while in 9.7% the dose was missing. The samples with clinical trial-type samples presented a higher quality (p < 0.049), blinding reduced their quality (p = 0.017), and identification by kit number or by patient increased it (p < 0.01). The promoter was the variable which introduced the highest variability into the analysis. Conclusions: The mean quality of labelling is adequate in the majority of clinical trial samples. The lack of essential information in some samples, such as the clinical trial code and the period of validity, is alarming and might be the potential source for dispensing or administration errors.

Mean Platelet Volume (MPV), Platelet Distribution Width (PDW), Platelet Count and Plateletcrit (PCT) as predictors of in-hospital paediatric mortality: a case-control Study.

Background: Thrombocytopenia has been shown to predict mortality. We hypothesize that platelet indices may be more useful prognostic indicators. Our study subjects were children one month to 14 years old admitted to our hospital. Aim: To determine whether platelet count, plateletcrit (PCT), mean platelet volume (MPV) and platelet distribution width (PDW) and their ratios can predict mortality in hospitalised children. Methods: Children who died during hospital stay were the cases. Controls were age matched children admitted contemporaneously. The first blood sample after admission was used for analysis. Receiver operating characteristic (ROC) curve was used to identify the best threshold for measured variables and the ratios studied. Multiple regression analysis was done to identify independent predictors of mortality. Results: Forty cases and forty controls were studied. Platelet count, PCT and the ratios of MPV/Platelet count, MPV/PCT, PDW/Platelet count, PDW/PCT and MPV x PDW/Platelet count x PCT were significantly different among children who survived compared to those who died. On multiple regression analysis the ratio of MPV/PCT, PDW/Platelet count and MPV/ Platelet count were risk factors for mortality with an odds ratio of 4.31(95% CI, 1.69-10.99), 3.86 (95% CI, 1.53-9.75), 3.45 (95% CI, 1.38-8.64) respectively. In 67% of the patients who died MPV/PCT ratio was above 41.8 and PDW/Platelet count was above 3.86. In 65% of patients who died MPV/Platelet count was above 3.45. Conclusion: The MPV/PCT, PDW/Platelet count and MPV/Platelet count, in the first sample after admission in this case control study were predictors of mortality and could predict 65% to 67% of deaths accurately.