7th Drug hypersensitivity meeting: part two

No abstract availabl

Comparative genomic analysis of European and Middle Eastern community-associated methicillin-resistant Staphylococcus aureus (CC80:ST80-IV) isolates by high-density microarray

AbstractInfections as a result of community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA) are an issue of increasing global healthcare concern. In Europe, this principally involves strains of multi-locus sequence type clonal complex 80 sequence type 80 with methicillin resistance in a staphylococcal chromosomal cassette (SCCmec) type IV arrangement (CC80:ST80-IV). As with other CA-MRSA strains, CC80:ST80-IV isolates tend to appear uniform when analysed by common molecular typing methods (e.g. pulsed field gel electrophoresis, multi-locus sequence type, SCCmec). To explore whether DNA sequence-based differences exist, we compared the genetic composition of six CC80:ST80-IV isolates of diverse chronological and geographic origin (i.e. Denmark and the Middle East) using an Affymetrix high-density microarray that was previously used to analyse CA-MRSA USA300 isolates. The results revealed a high degree of homology despite the diversity in isolation date and origin, with isolate differences primarily in conserved hypothetical open reading frames and intergenic sequences, but also including regions of known function. This included the confirmed loss of SCCmec recombinase genes in two Danish isolates representing potentially new SCCmec types. Microarray analysis grouped the six isolates into three relatedness pairs, also identified by pulsed field gel electrophoresis, which were consistent with both the clinical and molecular data

Methods to quantify avian airspace use in relation to wind energy development

It is likely that there will continue to be a substantial increase in the number of wind turbines as we aim to meet global energy demands through renewable sources. However, these structures can have adverse impacts on airborne wildlife, such as posing a potential collision risk with the turbine structure. A range of methods and technologies have been applied to the collection of bird flight parameters, such as height and speed, to improve the estimation of potential collision compared with traditional visual methods, but these are currently not applied in a consistent and systematic way. To this end, a systematic literature search was conducted to (1) examine the methods and technologies that can be used to provide bird flight data to assess the impact of wind energy developments and (2) provide an updated framework to guide how they might be most usefully applied within the impact assessment process. Four empirical measurement methods were found that improve the estimation of bird flight parameters: radar, telemetry, ornithodolite and LiDAR. These empirical sensor-based tools were typically more often applied in academic peer-reviewed papers than in report-based environmental statements. Where sensor-based tools have been used in the report-based literature, their inconsistent application has resulted in an uncertain regulatory environment for practitioners. Our framework directly incorporates sensor-based methods, together with their limitations and data requirements, from pre-deployment of infrastructure to post-consent monitoring of impacts. This revised approach will help improve the accuracy of estimation of bird flight parameters for ornithological assessment of wind energy. Sensor-based tools may not be the most cost-effective. However, a precedent has been set for wind energy development consent refusal based on ornithological impact assessment, and therefore the cost of collecting accurate and reliable flight data may be balanced favourably against the cost of development consent refusalacceptedVersio

Diurnal timing of nonmigratory movement by birds: the importance of foraging spatial scales

Timing of activity can reveal an organism’s efforts to optimize foraging either by minimizing energy loss through passive movement or by maximizing energetic gain through foraging. Here, we assess whether signals of either of these strategies are detectable in the timing of activity of daily, local movements by birds. We compare the similarities of timing of movement activity among species using six temporal variables: start of activity relative to sunrise, end of activity relative to sunset, relative speed at midday, number of movement bouts, bout duration, and proportion of active daytime hours. We test for the influence of flight mode and foraging habitat on the timing of movement activity across avian guilds. We used 64570 days of GPS movement data collected between 2002 and 2019 for local (non-migratory) movements of 991 birds from 49 species, representing 14 orders. Dissimilarity among daily activity patterns was best explained by flight mode. Terrestrial soaring birds began activity later and stopped activity earlier than pelagic soaring or flapping birds. Broad-scale foraging habitat explained less of the clustering patterns because of divergent timing of active periods of pelagic surface and diving foragers. Among pelagic birds, surface foragers were active throughout the day while diving foragers matched their active hours more closely to daylight hours. Pelagic surface foragers also had the greatest daily foraging distances, which was consistent with their daytime activity patterns. This study demonstrates that flight mode and foraging habitat influence temporal patterns of daily movement activity of birds. Methods Data were compiled from previously collected GPS movement datasets. We include days with 8+ h of data, and exclude migrations > 500 km long. For colonial nesting pelagic birds, we compare only days with known foraging trips. Dataset here includes the six temporal variables used in our study, measured at the hourly and daily scale. Usage Notes Mallon et al. 2020. Diurnal timing of nonmigratory movement by birds: the importance of foraging spatial scales. Journal of Avian Biology The dryad repository contents include the following data: 1. Final dataset used in analysis: mallon2020_trait_data.csv 2. Original hourly data measures of several temporal variables: mallon2020_hr_data.csv 3. Original daily data measures of several temporal variables: mallon2020_day_data.csv 4. Final morphological data used in analysis: mallon2020_morpho_data.csv Data columns of note: active.hr = if individual is active or inactive, based on threshold defined in Mallon et al. 2020 mspeed = mean speed during active hours n.hrs = number of location hours per day dsunrise.min = first activity, relative to sunrise dsunset.max = last activity, relative to sunset midday.speed = hourly speed nearest to solar noon prop.diel = proportion of active hours between sunrise and sunset n.periods.activity = number of movement bouts activity.dur = mean duration of movement bouts r2n = maximum net squared displacement from the beginning of the day (m) mean.r2n = mean net squared displacement from the beginning of the day (m) median.r2n = median net squared displacement from the beginning of the day (m

Ethnic-specific normative reference values for echocardiographic la and LV size, LV mass, and systolic function: The EchoNoRMAL study

Abstract OBJECTIVES: This study sought to derive age-, sex-, and ethnic-appropriate adult reference values for left atrial (LA) and left ventricular (LV) dimensions and volumes, LV mass, fractional shortening, and ejection fraction (EF) derived from geographically diverse population studies. BACKGROUND: The current recommended reference values for measurements from echocardiography may not be suitable to the diverse world population to which they are now applied. METHODS: Population-based datasets of echocardiographic measurements from 22,404 adults without clinical cardiovascular or renal disease, hypertension, or diabetes were combined in an individual person data meta-analysis. Quantile regression was used to derive reference values at the 95th percentile (upper reference value [URV]) and fifth percentile (lower reference value [LRV]) of each measurement against age (treated as linear), separately within sex and ethnic groups. RESULTS: The URVs for left ventricular end-diastolic volume (LVEDV), LV end-systolic volume, and LV stroke volume (SV) were highest in Europeans and lowest in South Asians. Important sex and ethnic differences remained after indexation by body surface area or height for these measurements, as well as for the LRV for SV. LVEDV and SV decreased with increasing age for all groups. Importantly, the LRV for EF differed by ethnicity; there was a clear apparent difference between Europeans and Asians. The URVs for LV end-diastolic diameter and LV end-systolic diameter were higher for Europeans than those for East Asian, South Asian, and African people, particularly among men. Similarly, the URVs for LA diameter and volume were highest for Europeans. CONCLUSIONS: Sex- and/or ethnic-appropriate echocardiographic reference values are indicated for many measurements of LA and LV size, LV mass, and EF. Reference values for LV volumes and mass also differ across the age range