Seabirds of the Chukotka Peninsula, Russia

We conducted seabird surveys along the entire coast of the Chukotka Peninsula (northwestern Siberia, Russia) from 1983 to 1991. We present the first comprehensive descriptions of the distribution and size of Chukotkan seabird colonies. Thirteen species of seabirds were recorded breeding on the peninsula, with an additional 13 migrant or vagrant species. Our estimate that at least 3 300 000 seabirds breed on the Chukotka Peninsula demonstrates the importance of this region to arctic seabird populations. Colony size and species composition may be determined by availability of adequate breeding sites, access to foraging areas, and variable ice conditions.De 1983 à 1991, on a effectué des relevés d'oiseaux marins tout le long du rivage de la péninsule de Tchoukotka (nord-ouest de la Sibérie, en Russie). On présente les premières descriptions exhaustives de la distribution et de la taille des colonies d'oiseaux marins de la Tchoukotka. On a relevé 13 espèces d'oiseaux marins nichant sur la péninsule, et, en plus, 13 espèces d'oiseaux en migration ou errants. Notre estimation d'une population nicheuse d'au moins 3 300 000 oiseaux marins dans la péninsule de Tchoukotka illustre l'importance de la région pour les populations d'oiseaux marins de l'Arctique. La taille des colonies et la composition des espèces pourraient être déterminées par la disponibilité de sites adéquats pour les nids, l'accès à des zones d'alimentation, et la variabilité des conditions de la glace

Basal dynamics of Kronebreen, a fast-flowing tidewater glacier in Svalbard: non-local spatio-temporal response to water input

We evaluate the variability in basal friction for Kronebreen, Svalbard, a fast-flowing tidewater glacier. We invert 3 years (2013–15) of surface velocities at high temporal resolution (generally 11 days), to estimate the changing basal properties of the glacier. Our results suggest that sliding behaviour of Kronebreen within a year is primarily influenced by changes in water input patterns during the meltwater season and basal friction is highly variable from a year to another. At present, models usually employ parameterisations to encompass the complex physics of glacier sliding by mathematically simulate their net effect. For such ice masses with strong seasonal variations of surface melt, the spatio-temporal patterns of basal friction imply that it is neither possible nor appropriate to use a parameterisation for bed friction that is fixed in space and/or time, at least in a timescale of a few years. Basal sliding may not only be governed by local processes such as basal topography or summer melt, but also be mediated by factors that vary over a larger distance and over a longer time period such as subglacial hydrology organisation, ice-thickness changes or calving front geometry

An introduction and overview of the Bering Sea Project : volume IV

© The Author(s), 2016. This is the author's version of the work and is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Deep Sea Research Part II: Topical Studies in Oceanography 134 (2016): 3-12, doi:10.1016/j.dsr2.2016.09.002.The seasonal rhythm of sea-ice advance and retreat in the eastern Bering Sea (EBS) moves ice hundreds of kilometers across the broad continental shelf and exerts a powerful influence on the ecology of these waters. In winter, the combination of latitude, geology, winds, and ocean currents produces ice cover extending far into the southern Bering Sea. In the spring and summer, retreating ice, longer daylight hours, and nutrient-rich ocean water result in exceptionally high marine production, vital to both sea life and people. The intense burst of spring production, together with more episodic summer and early fall production, provides the energy that powers the complex food web and ultimately sustains nearly half of the US annual commercial fish landings, as well as providing food and cultural value to thousands of Bering Sea coastal and island residents.Finally, we acknowledge the National Science Foundation (NSF Award No. 1308087) and the North Pacific Research Board (NPRB) for author support during the concluding phase of the Bering Sea Project, and we thank many colleagues at NSF, NPRB, and NOAA for their management partnership and expertise. Funding for the Bering Sea Project was provided by NSF and NPRB, with in-­‐kind contribution from participants.2018-09-1

Measuring underreporting and under-ascertainment in infectious disease datasets: a comparison of methods

Gibbons CL, Mangen M-JJ, Plaß D, et al. Measuring underreporting and under-ascertainment in infectious disease datasets: a comparison of methods. BMC Public Health. 2014;14(1): 147.Background: Efficient and reliable surveillance and notification systems are vital for monitoring public health and disease outbreaks. However, most surveillance and notification systems are affected by a degree of underestimation (UE) and therefore uncertainty surrounds the 'true' incidence of disease affecting morbidity and mortality rates. Surveillance systems fail to capture cases at two distinct levels of the surveillance pyramid: from the community since not all cases seek healthcare (under-ascertainment), and at the healthcare-level, representing a failure to adequately report symptomatic cases that have sought medical advice (underreporting). There are several methods to estimate the extent of under-ascertainment and underreporting. Methods: Within the context of the ECDC-funded Burden of Communicable Diseases in Europe (BCoDE)-project, an extensive literature review was conducted to identify studies that estimate ascertainment or reporting rates for salmonellosis and campylobacteriosis in European Union Member States (MS) plus European Free Trade Area (EFTA) countries Iceland, Norway and Switzerland and four other OECD countries (USA, Canada, Australia and Japan). Multiplication factors (MFs), a measure of the magnitude of underestimation, were taken directly from the literature or derived (where the proportion of underestimated, under-ascertained, or underreported cases was known) and compared for the two pathogens. Results: MFs varied between and within diseases and countries, representing a need to carefully select the most appropriate MFs and methods for calculating them. The most appropriate MFs are often disease-,country-, age-, and sex-specific. Conclusions: When routine data are used to make decisions on resource allocation or to estimate epidemiological parameters in populations, it becomes important to understand when, where and to what extent these data represent the true picture of disease, and in some instances (such as priority setting) it is necessary to adjust for underestimation. MFs can be used to adjust notification and surveillance data to provide more realistic estimates of incidence

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Summary of effects on three different FRN measures.

<p>The <i>F</i>(1, 45)- and <i>p</i>-values are reported.</p>1<p>Mean amplitude 230–300 ms post-feedback minus average of mean amplitudes preceding and following peaks.</p