Uncovering the genetic history of the present-day greenlandic population

Because of past limitations in samples and genotyping technologies, important questions about the history of the present-day Greenlandic population remain unanswered. In an effort to answer these questions and in general investigate the genetic history of the Greenlandic population, we analyzed ∼200,000 SNPs from more than 10% of the adult Greenlandic population (n = 4,674). We found that recent gene flow from Europe has had a substantial impact on the population: more than 80% of the Greenlanders have some European ancestry (on average ∼25% of their genome). However, we also found that the amount of recent European gene flow varies across Greenland and is far smaller in the more historically isolated areas in the north and east and in the small villages in the south. Furthermore, we found that there is substantial population structure in the Inuit genetic component of the Greenlanders and that individuals from the east, west, and north can be distinguished from each other. Moreover, the genetic differences in the Inuit ancestry are consistent with a single colonization wave of the island from north to west to south to east. Although it has been speculated that there has been historical admixture between the Norse Vikings who lived in Greenland for a limited period ∼600–1,000 years ago and the Inuit, we found no evidence supporting this hypothesis. Similarly, we found no evidence supporting a previously hypothesized admixture event between the Inuit in East Greenland and the Dorset people, who lived in Greenland before the Inuit

Influenza surveillance in Europe: comparing intensity levels calculated using the moving epidemic method.

Although influenza-like illnesses (ILI) and acute respiratory illnesses (ARI) surveillance are well established in Europe, the comparability of intensity among countries and seasons remains an unresolved challenge. The objective is to compare the intensity of ILI and ARI in some European countries. Weekly ILI and ARI incidence rates and proportion of primary care consultations were modeled in 28 countries for the 1996/1997-2013/2014 seasons using the moving epidemic method (MEM). We calculated the epidemic threshold and three intensity thresholds, which delimit five intensity levels: baseline, low, medium, high, and very high. The intensity of 2013/2014 season is described and compared by country. The lowest ILI epidemic thresholds appeared in Sweden and Estonia (below 10 cases per 100 000) and the highest in Belgium, Denmark, Hungary, Poland, Serbia, and Slovakia (above 100 per 100 000). The 2009/2010 season was the most intense, with 35% of the countries showing high or very high intensity levels. The European epidemic period in season 2013/2014 started in January 2014 in Spain, Poland, and Greece. The intensity was between low and medium and only Greece reached the high intensity level, in weeks 7 to 9/2014. Some countries remained at the baseline level throughout the entire surveillance period. Epidemic and intensity thresholds varied by country. Influenza-like illnesses and ARI levels normalized by MEM in 2013/2014 showed that the intensity of the season in Europe was between low and medium in most of the countries. Comparing intensity among seasons or countries is essential for understanding patterns in seasonal epidemics. An automated standardized model for comparison should be implemented at national and international levels.This work has been funded by the National and International Public Institutions and the Regional Health Department of Castilla y León (Spain).S

Clinical use of lithium salts: guide for users and prescribers

Lithium has been used clinically for 70 years, mainly to treat bipolar disorder. Competing treatments and exaggerated impressions about complexity and risks of lithium treatment have led to its declining use in some countries, encouraging this update about its safe clinical use. We conducted a nonsystematic review of recent research reports and developed consensus among international experts on the use of lithium to treat major mood disorders, aiming for a simple but authoritative guide for patients and prescribers

Pain in the lumbar, thoracic or cervical regions: do age and gender matter? A population-based study of 34,902 Danish twins 20–71 years of age

Background. It is unclear to what extent spinal pain varies between genders and in relation to age. It was the purpose of this study to describe the self-reported prevalence of 1) pain ever and pain in the past year in each of the three spinal regions, 2) the duration of such pain over the past year, 3) pain radiating from these areas, and 4) pain in one, two or three areas. In addition, 5) to investigate if spinal pain reporting is affected by gender and 6) to see if it increases gradually with increasing age. Method. A cross-sectional survey was conducted in 2002 on 34,902 twin individuals, aged 20 to 71 years, representative of the general Danish population. Identical questions on pain were asked for the lumbar, thoracic and cervical regions. Results. Low back pain was most common, followed by neck pain with thoracic pain being least common. Pain for at least 30 days in the past year was reported by 12%, 10%, and 4%, respectively. The one-yr prevalence estimates of radiating pain were 22% (leg), 16% (arm), and 5% (chest). Pain in one area only last year was reported by 20%, followed by two (13%) and three areas (8%). Women were always more likely to report pain and they were also more likely to have had pain for longer periods. Lumbar and cervical pain peaked somewhat around the middle years but the curves were flatter for thoracic pain. Similar patterns were noted for radiating pain. Older people did not have pain in a larger number of areas but their pain lasted longer. Conclusion. Pain reported for and from the lumbar and cervical spines was found to be relatively common whereas pain in the thoracic spine and pain radiating into the chest was much less common. Women were, generally, more likely to report pain than men. The prevalence estimates changed surprisingly little over age and were certainly not more common in the oldest groups, although the pain was reported as more long-lasting in the older group

Spatial abundance and clustering of Culicoides (Diptera: Ceratopogonidae) on a local scale

BACKGROUND: Biting midges, Culicoides, of the Obsoletus group and the Pulicaris group have been involved in recent outbreaks of bluetongue virus and the former was also involved in the Schmallenberg virus outbreak in northern Europe. METHODS: For the first time, here we investigate the local abundance pattern of these two species groups in the field by intensive sampling with a grid of light traps on 16 catch nights. Neighboring trap catches can be spatially dependent on each other, hence we developed a conditional autoregressive (CAR) model framework to test a number of spatial and non-spatial covariates expected to affect Culicoides abundance. RESULTS: The distance to sheep penned in the corner of the study field significantly increased the abundance level up to 200 meters away from the sheep. Spatial clustering was found to be significant but could not be explained by any known factors, and cluster locations shifted between catch nights. No significant temporal autocorrelation was detected. CAR models for both species groups identified a significant positive impact of humidity and significant negative impacts of precipitation and wind turbulence. Temperature was also found to be significant with a peak at just below 16 degrees Celcius. Surprisingly, there was a significant positive impact of wind speed. The CAR model for the Pulicaris group also identified a significant attraction to the smaller groups of sheep placed in the field. Furthermore, a large number of spatial covariates which were incorrectly found to be significant in ordinary regression models were not significant in the CAR models. The 95% C.I. on the prediction estimates ranged from 20.4% to 304.8%, underlining the difficulties of predicting the abundance of Culicoides. CONCLUSIONS: We found that significant spatial clusters of Culicoides moved around in a dynamic pattern varying between catch nights. This conforms with the modeling but was not explained by any of the tested covariates. The mean abundance within these clusters was up to 11 times higher for the Obsoletus group and 4 times higher for the Pulicaris group compared to the rest of the field

Quantifying Dispersal of European Culicoides (Diptera: Ceratopogonidae) Vectors between Farms Using a Novel Mark-Release-Recapture Technique

Studying the dispersal of small flying insects such as Culicoides constitutes a great challenge due to huge population sizes and lack of a method to efficiently mark and objectively detect many specimens at a time. We here describe a novel mark-release-recapture method for Culicoides in the field using fluorescein isothiocyanate (FITC) as marking agent without anaesthesia. Using a plate scanner, this detection technique can be used to analyse thousands of individual Culicoides specimens per day at a reasonable cost. We marked and released an estimated 853 specimens of the Pulicaris group and 607 specimens of the Obsoletus group on a cattle farm in Denmark. An estimated 9,090 (8,918-9,260) Obsoletus group specimens and 14,272 (14,194-14,448) Pulicaris group specimens were captured in the surroundings and subsequently analysed. Two (0.3%) Obsoletus group specimens and 28 (4.6%) Pulicaris group specimens were recaptured. The two recaptured Obsoletus group specimens were caught at the release point on the night following release. Eight (29%) of the recaptured Pulicaris group specimens were caught at a pig farm 1,750 m upwind from the release point. Five of these were recaptured on the night following release and the three other were recaptured on the second night after release. This is the first time that movement of Culicoides vectors between farms in Europe has been directly quantified. The findings suggest an extensive and rapid exchange of disease vectors between farms. Rapid movement of vectors between neighboring farms may explain the the high rate of spatial spread of Schmallenberg and bluetongue virus (BTV) in northern Europe