Surveillance of Ixodes ricinus ticks (Acari: Ixodidae) in Iceland

Background: Ixodes ricinus is a three-host tick, a principal vector of Borrelia burgdorferi (s.l.) and one of the main vectors of tick-borne encephalitis (TBE) virus. Iceland is located in the North Atlantic Ocean with subpolar oceanic climate. During the past 3–4 decades, average temperature has increased, supporting more favourable conditions for ticks. Reports of I. ricinus have increased in recent years. If these ticks were able to establish in a changing climate, Iceland may face new threats posed by tick-borne diseases. Methods: Active field surveillance by tick flagging was conducted at 111 sites around Iceland from August 2015 to September 2016. Longworth mammal traps were used to trap Apodemus sylvaticus in southwestern and southern Iceland. Surveillance on tick importation by migratory birds was conducted in southeastern Iceland, using bird nets and a Heligoland trap. Vulpes lagopus carcasses from all regions of the country were inspected for ticks. In addition, existing and new passive surveillance data from two institutes have been merged and are presented. Continental probability of presence models were produced. Boosted Regression Trees spatial modelling methods and its predictions were assessed against reported presence. Results: By field sampling 26 questing I. ricinus ticks (7 males, 3 females and 16 nymphs) were collected from vegetation from three locations in southern and southeastern Iceland. Four ticks were found on migratory birds at their arrival in May 2016. A total of 52 A. sylvaticus were live-trapped but no ticks were found nor on 315 V. lagopus carcasses. Passive surveillance data collected since 1976, reports further 214 I. ricinus ticks from 202 records, with an increase of submissions in recent years. The continental probability of presence model correctly predicts approximately 75% of the recorded presences, but fails to predict a fairly specific category of recorded presence in areas where the records are probably opportunistic and not likely to lead to establishment. Conclusions: To the best of our knowledge, this study represents the first finding of questing I. ricinus ticks in Iceland. The species could possibly be established locally in Iceland in low abundance, although no questing larvae have yet been detected to confirm established populations. Submitted tick records have increased recently, which may reflect an increase in exposure, or in interest in ticks. Furthermore, the amount of records on dogs, cats and humans indicate that ticks were acquired locally, presenting a local biting risk. Tick findings on migratory birds highlight a possible route of importation. Obtaining questing larvae is now a priority to confirm that I. ricinus populations are established in Iceland. Further surveys on wild mammals (e.g. Rangifer tarandus), livestock and migratory birds are recommended to better understand their role as potential hosts for I. ricinus.Work was carried out under VectorNet, a European network for sharing data on the geographic distribution of arthropod vectors, transmitting human and animal disease agents (framework contract OC/EFSA/AHAW/2013/02-FWC1) funded by the European Food Safety Authority (EFSA) and the European Centre for Disease prevention and Control (ECDC). JM is also partly funded by the National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Environmental Change and Health at the London School of Hygiene & Tropical Medicine in partnership with Public Health England (PHE), and in collaboration with the University of Exeter, University College London, and the Met Office; and partly funded by the NIHR HPRU on Emerging Infections and Zoonoses at the University of Liverpool in partnership with PHE and Liverpool School of Tropical Medicine.Peer Reviewe

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe

Dispersal rate of Potamophylax cingulatus and Micropterna sequax (Trichoptera) in Iceland

During the 20th and 21st century, two species of Trichoptera have colonised Iceland. One species is Potamophylax cingulatus and the other is Micropterna sequax. Potamophylax cingulatus was not found in several extensive surveys before 1942, conducted by several entomologists. During a survey in streams in 1974–1978, the species was found to be common in east and north-east Iceland, but the Trichoptera species Apatania zonella was absent, where it was common before 1942. Searching collections of unidentified Trichoptera, a single specimen was found in east Iceland on 30 July 1959. The survey was repeated in 2004–2006 and the species had colonised most streams and rivers in Iceland and A. zonella had disappeared from many of them. Potamophylax cingulatus was first recorded in two light traps in south Iceland in 1997 with two specimens. The catch has increased continuously to 267 in 2022. Micropterna sequax was found in a single light trap at Mógilsá near Reykjavik in 2008. The annual catch has since grown from two specimens to 144. The species was found at Hvanneyri, 40 km north of the original site it was recorded from in 2018 (8 specimens) and, in 2021, it was found in Kjós, 11 km from the original site (one specimen based on a photograph). The dispersal rate for P. cingulatus was about 7–9 km/year, but the dispersal rate for the more recent settler M. sequax was found to be 4 km/year

Mapping the location of grafted PNIPAAM in mesoporous SBA-15 silica using gas adsorption analysis.

The thermoresponsive polymer poly-N-isopropylacrylamide (PNIPAAM) was grafted in mesoporous SBA-15 silica. The grafting process consists of three steps: (i) increasing the amount of surface silanol groups of SBA-15 by hydroxylation, (ii) attachment of an anchor (1-(trichlorosilyl)-2-(m/p-(chloromethylphenyl)ethane) and finally (iii) the polymerization of the monomers (NIPAAM) onto the anchor. After each step, the materials were characterized regarding the porosity, using inert gas (argon, nitrogen) physisorption measurements. Also, the structure was investigated by small-angle X-ray diffraction analysis and thermogravimetric analysis was used for determination of the amount of grafted material. A total of 17% by weight of organic material was introduced in the porous host and the structure was preserved during the grafting process. Physisorption measurements revealed that the anchor is mainly located in the intrawall pores present in SBA-15. Consequently, the polymer is preferentially located in the intrawall pores or in the vicinity thereof. The final mesopore volume is 0.47 cm(3) g(-1) as compared to 0.96 cm(3) g(-1) for the pure SBA-15. The surprisingly large loss of mesopore volume and an almost constant mesopore diameter is consistent with a partial sealing of the mesopore volume in the composite materials. The potential thermocontrol combined with the large mesoporosity and the possible "storage space" provided by the sealed mesopore volume leads to a material with possibilities for various applications

Wind power in forests II : Forest wind

Sweden has good conditions for wind power. However, most of Sweden (ca. 70%) is covered by forest. Forests decrease wind speeds and create turbulence, something which is not favourable for wind power. Several Swedish wind maps have shown that forests in Nordic countries can be well suited for wind power (e.g. Bergström and Söderberg 2011, Byrkjedal and Åkervik 2009). At the same time, there is uncertainty over wind conditions over forests at very high altitudes (ca. 150 m above ground). How good do wind resource assessment models agree with measurements? How much energy is a wind turbine in forest going to produce and which loads will a wind turbine in forest experience? This project has investigated all these issues. Work was concentrated in the following work packages: Wind resource at very high heights Turbulence- and wind measurements at very high heights above forest Analysis of turbulence data from forests Model simulations with wind flow models Model simulations with very-high-resolution weather forecast models Model simulations with Large Eddy Simulation (LES) models Improved specification of so-called “synthetic turbulence” over forest Analysis of airborne laser altimeter measurements over forest Forest’s effects on wind turbine energy production Load simulations for wind turbines over forest WP1 studies how wind speed and direction varies with height over forest (up to ca 150 m above ground and higher up). Several profile relations are studied here.  Frequency distributions of wind shear and veer are presented. WP2 describes turbulence and wind measurements that have been carried out within the project at Hornamossen. Moreover, the measurement campaign that was carried out in a line over the Hornamossen-hill within the New European Wind Atlas project is described. WP3 analyses turbulence data from Hornamossen together with turbulence data from Ryningsnäs. Of special interest is how turbulence intensity decreases with height as well as if the IEC-standard class A, B or C for wind turbines is complied with at different heights. WP4 describes the newly developed linearised wind flow model ORFEUS with a dedicated forest module. WP5 describes model simulations with WRF and the MIUU model, their sensitivity for surface roughness and turbulence parameterisations. Mean wind profiles from the models are compared to Hornamossen. WP6 describes LES simulations with Chalmers LES model and WRF-LES. LES-resultats depend to a large degree on how the turbulent vortices are initialised at the inflow boundaries of the LES model. Several different methods for that are described. WP7 describes a new turbulence model (the Segalini & Arnqvist model) that includes atmospheric stability. This is a further development of the IEC turbulence model (=Mann model) for neutral stability. Coherence of turbulent winds as well as phase profiles are other improvements of the IEC model. WP8 describes a new method to compute leaf/needle/plant area density from laser scans of the Swedish forest and how one estimates surface roughness and zero plane displacement from that. The new method is compared with two other methods. Results are also compared with official forest data (“skoglig grunddata”). The effect on the wind profile is also shown. WP9 describes the new methods for estimating AEP from the Power Curve Working Group and the IEC standard for Power Performance Testing. Effects on estimated AEP are shown. A new simple model for calculating turbulence effects on energy production is developed and compared with data from a wind farm. Within WP10 a new generic open-source wind turbine is developed and used for load simulations with aero-elastic simulations. Results show that the new coherence model for turbulence gives much smaller loads than the turbulence model of the IEC standard. For more information on the different parts of the project the reader is referred to the report’s introduction, the ”Summary and Conclusions” of each chapter as well as the overall summary (”Executive Summary”) at the end of the report.Wind Power in Forest I

Wind power in forests II : Forest wind

Sweden has good conditions for wind power. However, most of Sweden (ca. 70%) is covered by forest. Forests decrease wind speeds and create turbulence, something which is not favourable for wind power. Several Swedish wind maps have shown that forests in Nordic countries can be well suited for wind power (e.g. Bergström and Söderberg 2011, Byrkjedal and Åkervik 2009). At the same time, there is uncertainty over wind conditions over forests at very high altitudes (ca. 150 m above ground). How good do wind resource assessment models agree with measurements? How much energy is a wind turbine in forest going to produce and which loads will a wind turbine in forest experience? This project has investigated all these issues. Work was concentrated in the following work packages: Wind resource at very high heights Turbulence- and wind measurements at very high heights above forest Analysis of turbulence data from forests Model simulations with wind flow models Model simulations with very-high-resolution weather forecast models Model simulations with Large Eddy Simulation (LES) models Improved specification of so-called “synthetic turbulence” over forest Analysis of airborne laser altimeter measurements over forest Forest’s effects on wind turbine energy production Load simulations for wind turbines over forest WP1 studies how wind speed and direction varies with height over forest (up to ca 150 m above ground and higher up). Several profile relations are studied here.  Frequency distributions of wind shear and veer are presented. WP2 describes turbulence and wind measurements that have been carried out within the project at Hornamossen. Moreover, the measurement campaign that was carried out in a line over the Hornamossen-hill within the New European Wind Atlas project is described. WP3 analyses turbulence data from Hornamossen together with turbulence data from Ryningsnäs. Of special interest is how turbulence intensity decreases with height as well as if the IEC-standard class A, B or C for wind turbines is complied with at different heights. WP4 describes the newly developed linearised wind flow model ORFEUS with a dedicated forest module. WP5 describes model simulations with WRF and the MIUU model, their sensitivity for surface roughness and turbulence parameterisations. Mean wind profiles from the models are compared to Hornamossen. WP6 describes LES simulations with Chalmers LES model and WRF-LES. LES-resultats depend to a large degree on how the turbulent vortices are initialised at the inflow boundaries of the LES model. Several different methods for that are described. WP7 describes a new turbulence model (the Segalini & Arnqvist model) that includes atmospheric stability. This is a further development of the IEC turbulence model (=Mann model) for neutral stability. Coherence of turbulent winds as well as phase profiles are other improvements of the IEC model. WP8 describes a new method to compute leaf/needle/plant area density from laser scans of the Swedish forest and how one estimates surface roughness and zero plane displacement from that. The new method is compared with two other methods. Results are also compared with official forest data (“skoglig grunddata”). The effect on the wind profile is also shown. WP9 describes the new methods for estimating AEP from the Power Curve Working Group and the IEC standard for Power Performance Testing. Effects on estimated AEP are shown. A new simple model for calculating turbulence effects on energy production is developed and compared with data from a wind farm. Within WP10 a new generic open-source wind turbine is developed and used for load simulations with aero-elastic simulations. Results show that the new coherence model for turbulence gives much smaller loads than the turbulence model of the IEC standard. For more information on the different parts of the project the reader is referred to the report’s introduction, the ”Summary and Conclusions” of each chapter as well as the overall summary (”Executive Summary”) at the end of the report.Wind Power in Forest I

Wind power in forests : wind and effects on loads

Within the project V-312, Wind power in forests, researchers and a PhD student at Uppsala University, WeatherTech Scandinavia, the Royal Institute of Technology (KTH), DTU Wind Energy in Denmark and Teknikgruppen have been cooperating. Within the project atmospheric turbulence measurements with high vertical resolution have been done, also down between the trees, to make it possible to give better theoretical descriptions of the observed properties. Several mesoscale models have also been used to model the above forest winds. The atmospheric measurements have been complemented by wind tunnel measurements using a wind tunnel floor designed with small cylindrical wooden sticks that should simulate the effect of the trees generating a known momentum sink able to affect the flow. The combined new knowledge about the forest boundary layer wind and turbulence properties have been used as input to a dynamical wind turbine computer model, used to simulate the turbine load response to the turbulent wind field.I projektet V-312, Vindkraft i skog, har forskare och en doktorand vid Uppsala universitet, WeatherTech Scandinavia, Kungliga tekniska högskolan (KTH), DTU Wind Energy i Danmark och Teknikgruppen samarbetat. I projektet har det gjorts mätningar med hög vertikal upplösning av turbulensen i atmosfären, även ned mellan träden, syftande till att möjliggöra en bättre teoretisk beskrivning av de observerade egenskaperna. Dessutom har flera mesoskaliga modeller använts för att modellera vindarna ovanför skogen. Mätningarna i atmosfären har kompletterats med vindtunnelmätningar där bottnen i vindtunneln har bestyckats med små cylindriska träpinnar vilka skulle simulera effekterna av träd och ge upphov till en känd friktionskraft som påverkar strömningen. De kombinerade nya kunskaperna om vind och turbulens i gränsskiktet över en skog har använts för att driva en datormodell som beskriver dynamiken hos vindturbinerna. Detta har sedan använts för att simulera lasterna på turbinerna som uppstår i det turbulenta vindfältet.Vindforsk - vind power in forest