Variability, trends and predictability of seasonal sea ice retreat and advance in the Chukchi Sea

As assessed over the period 1979–2014, the date that sea ice retreats to the shelf break (150 m contour) of the Chukchi Sea has a linear trend of −0.7 days per year. The date of seasonal ice advance back to the shelf break has a steeper trend of about +1.5 days per year, together yielding an increase in the open water period of 80 days. Based on detrended time series, we ask how interannual variability in advance and retreat dates relate to various forcing parameters including radiation fluxes, temperature and wind (from numerical reanalyses), and the oceanic heat inflow through the Bering Strait (from in situ moorings). Of all variables considered, the retreat date is most strongly correlated (r ∼ 0.8) with the April through June Bering Strait heat inflow. After testing a suite of statistical linear models using several potential predictors, the best model for predicting the date of retreat includes only the April through June Bering Strait heat inflow, which explains 68% of retreat date variance. The best model predicting the ice advance date includes the July through September inflow and the date of retreat, explaining 67% of advance date variance. We address these relationships by discussing heat balances within the Chukchi Sea, and the hypothesis of oceanic heat transport triggering ocean heat uptake and ice-albedo feedback. Developing an operational prediction scheme for seasonal retreat and advance would require timely acquisition of Bering Strait heat inflow data. Predictability will likely always be limited by the chaotic nature of atmospheric circulation patterns

Record winter winds in 2020/21 drove exceptional Arctic sea ice transport

AbstractThe volume of Arctic sea ice is in decline but exhibits high interannual variability, which is driven primarily by atmospheric circulation. Through analysis of satellite-derived ice products and atmospheric reanalysis data, we show that winter 2020/21 was characterised by anomalously high sea-level pressure over the central Arctic Ocean, which resulted in unprecedented anticyclonic winds over the sea ice. This atmospheric circulation pattern drove older sea ice from the central Arctic Ocean into the lower-latitude Beaufort Sea, where it is more vulnerable to melting in the coming warm season. We suggest that this unusual atmospheric circulation may potentially lead to unusually high summer losses of the Arctic’s remaining store of old ice.</jats:p

Molecular Evolutionary Characterization of a V1R Subfamily Unique to Strepsirrhine Primates

Vomeronasal receptor genes have frequently been invoked as integral to the establishment and maintenance of species boundaries among mammals due to the elaborate one-to-one correspondence between semiochemical signals and neuronal sensory inputs. Here, we report the most extensive sample of vomeronasal receptor class 1 (V1R) sequences ever generated for a diverse yet phylogenetically coherent group of mammals, the tooth-combed primates (suborder Strepsirrhini). Phylogenetic analysis confirms our intensive sampling from a single V1R subfamily, apparently unique to the strepsirrhine primates. We designate this subfamily as V1Rstrep. The subfamily retains extensive repertoires of gene copies that descend from an ancestral gene duplication that appears to have occurred prior to the diversification of all lemuriform primates excluding the basal genusDaubentonia (the aye-aye). We refer to the descendent clades as V1Rstrep-a and V1Rstrep-b. Comparison of the two clades reveals different amino acid compositions corresponding to the predicted ligand-binding site and thus potentially to altered functional profiles between the two. In agreement with previous studies of the mouse lemur (genus, Microcebus), the majority of V1Rstrep gene copies appear to be intact and under strong positive selection, particularly within transmembrane regions. Finally, despite the surprisingly high number of gene copies identified in this study, it is nonetheless probable that V1R diversity remains underestimated in these nonmodel primates and that complete characterization will be limited until high-coverage assembled genomes are available

Two-stage analyses of sequence variants in association with quantitative traits

We propose a two-stage design for the analysis of sequence variants in which a proportion of genes that show some evidence of association are identified initially and then followed up in an independent data set. We compare two different approaches. In both approaches the same summary measure (total number of minor alleles) is used for each gene in the initial analysis. In the first (simple) approach the same summary measure is used in the analysis of the independent data set. In the second (alternative) approach a more specific hypothesis is formed for the second stage; the summary measure used is the count of minor alleles in only those variants that in the initial data showed the same direction of association as was seen overall. We applied the methods to the simulated quantitative traits of Genetic Analysis Workshop 17, blind to the simulation model, and then evaluated their performance once the underlying model was known. Performance was similar for most genes, but the simple strategy considerably out-performed the alternative strategy for one gene, where most of the effect was due to very rare variants; this suggests that the alternative approach would not be advisable when the effect is seen in very rare variants. Further simulations are needed to investigate the potential superior power of the alternative method when some variants within a gene have opposing effects. Overall, the power to detect associations was low; this was also true when using a more powerful joint analysis that combined the two stages of the study

Cirsium species show disparity in patterns of genetic variation at their range-edge, despite similar patterns of reproduction and isolation

Genetic variation was assessed across the UK geographical range of Cirsium acaule and Cirsium heterophyllum. A decline in genetic diversity and increase in population divergence approaching the range edge of these species was predicted based on parallel declines in population density and seed production reported seperately. Patterns were compared with UK populations of the widespread Cirsium arvense.Populations were sampled along a latitudinal transect in the UK and genetic variation assessed using microsatellite markers. Cirsium acaule shows strong isolation by distance, a significant decline in diversity and an increase in divergence among range-edge populations. Geographical structure is also evident in C. arvense, whereas no such patterns are seen in C.heterophyllum. There is a major disparity between patterns of genetic variation in C. acaule and C. heterophyllum despite very similar patterns in seed production and population isolation in these species. This suggests it may be misleading to make assumptions about the geographical structure of genetic variation within species based solely on the present-day reproduction and distribution of populations

Geometric Mixing, Peristalsis, and the Geometric Phase of the Stomach

Mixing fluid in a container at low Reynolds number - in an inertialess environment - is not a trivial task. Reciprocating motions merely lead to cycles of mixing and unmixing, so continuous rotation, as used in many technological applications, would appear to be necessary. However, there is another solution: movement of the walls in a cyclical fashion to introduce a geometric phase. We show using journal-bearing flow as a model that such geometric mixing is a general tool for using deformable boundaries that return to the same position to mix fluid at low Reynolds number. We then simulate a biological example: we show that mixing in the stomach functions because of the "belly phase": peristaltic movement of the walls in a cyclical fashion introduces a geometric phase that avoids unmixing.Comment: Revised, published versio

Risk factors for severe outcomes in patients with systemic vasculitis & COVID‐19: a bi‐national registry‐based cohort study

OBJECTIVE: COVID-19 is a novel infectious disease with a broad spectrum of clinical severity. Patients with systemic vasculitis have an increased risk of serious infections and so may be at risk of severe outcomes following COVID-19. It is important to establish the risk factors for severe COVID-19 outcomes in these patients, including the impact of immunosuppressive therapies. METHODS: A multi-centre cohort was developed through the participation of centres affiliated with national UK and Ireland vasculitis registries. Clinical characteristics and outcomes were described. Logistic regression was used to evaluate associations between potential risk factors and severe COVID-19 outcome, defined as a requirement for advanced oxygen therapy, invasive ventilation, or death. RESULTS: Sixty-five cases of patients with systemic vasculitis who developed COVID-19 were reported (median age 70 years, 49% female) of whom 25 (38%) experienced a severe outcome. Most cases (55/65, 85%) had ANCA-associated vasculitis (AAV). Almost all patients required hospitalization (59/65, 91%), 7 patients (11%) were admitted to intensive care and 18 patients (28%) died. Background glucocorticoid therapy was associated with severe outcome (adjusted odds ratio [aOR] 3.7 (1.1-14.9, p=0.047)) as was comorbid respiratory disease (aOR 7.5 (1.9-38.2, p=0.006)). Vasculitis disease activity and non-glucocorticoid immunosuppression were not associated with severe outcome. CONCLUSION: In patients with systemic vasculitis, glucocorticoid use at presentation and comorbid respiratory disease were associated with severe outcomes in COVID-19. These data can inform clinical decision making relating to risk of severe COVID-19 in this vulnerable patient group

Calibrating the Performance of SNP Arrays for Whole-Genome Association Studies

To facilitate whole-genome association studies (WGAS), several high-density SNP genotyping arrays have been developed. Genetic coverage and statistical power are the primary benchmark metrics in evaluating the performance of SNP arrays. Ideally, such evaluations would be done on a SNP set and a cohort of individuals that are both independently sampled from the original SNPs and individuals used in developing the arrays. Without utilization of an independent test set, previous estimates of genetic coverage and statistical power may be subject to an overfitting bias. Additionally, the SNP arrays' statistical power in WGAS has not been systematically assessed on real traits. One robust setting for doing so is to evaluate statistical power on thousands of traits measured from a single set of individuals. In this study, 359 newly sampled Americans of European descent were genotyped using both Affymetrix 500K (Affx500K) and Illumina 650Y (Ilmn650K) SNP arrays. From these data, we were able to obtain estimates of genetic coverage, which are robust to overfitting, by constructing an independent test set from among these genotypes and individuals. Furthermore, we collected liver tissue RNA from the participants and profiled these samples on a comprehensive gene expression microarray. The RNA levels were used as a large-scale set of quantitative traits to calibrate the relative statistical power of the commercial arrays. Our genetic coverage estimates are lower than previous reports, providing evidence that previous estimates may be inflated due to overfitting. The Ilmn650K platform showed reasonable power (50% or greater) to detect SNPs associated with quantitative traits when the signal-to-noise ratio (SNR) is greater than or equal to 0.5 and the causal SNP's minor allele frequency (MAF) is greater than or equal to 20% (N = 359). In testing each of the more than 40,000 gene expression traits for association to each of the SNPs on the Ilmn650K and Affx500K arrays, we found that the Ilmn650K yielded 15% times more discoveries than the Affx500K at the same false discovery rate (FDR) level

Yellow fever control in Cameroon: Where are we now and where are we going?

<p>Abstract</p> <p>Background</p> <p>Cameroon is one of 12 African countries that bear most of the global burden of yellow fever. In 2002 the country developed a five-year strategic plan for yellow fever control, which included strategies for prevention as well as rapid detection and response to outbreaks when they occur. We have used data collected by the national Expanded Programme on Immunisation to assess the progress made and challenges faced during the first four years of implementing the plan.</p> <p>Methods</p> <p>In January 2003, case-based surveillance of suspected yellow fever cases was instituted in the whole country. A year later, yellow fever immunisation at nine months of age (the same age as routine measles immunisation) was introduced. Supplementary immunisation activities (SIAs), both preventive and in response to outbreaks, also formed an integral part of the yellow fever control plan. Each level of the national health system makes a synthesis of its activities and sends this to the next higher level at defined regular intervals; monthly for routine data and daily for SIAs.</p> <p>Results</p> <p>From 2004 to 2006 the national routine yellow fever vaccination coverage rose from 58.7% to 72.2%. In addition, the country achieved parity between yellow fever and measles vaccination coverage in 2005 and has since maintained this performance level. The number of suspected yellow fever cases in the country increased from 156 in 2003 to 859 in 2006, and the proportion of districts that reported at least one suspected yellow fever case per year increased from 31.4% to 68.2%, respectively. Blood specimens were collected from all suspected cases (within 14 days of onset of symptoms) and tested at a central laboratory for yellow fever IgM antibodies; leading to confirmation of yellow fever outbreaks in the health districts of Bafia, Méri and Ntui in 2003, Ngaoundéré Rural in 2004, Yoko in 2005 and Messamena in 2006. Owing to constraints in rapidly mobilising the necessary resources, reactive SIAs were only conducted in Bafia and Méri several months after confirmation of the outbreak. In both districts, a total of 60,083 people (representing 88.2% of the 68,103 targeted) were vaccinated. Owing to the same constraints, SIAs were not conducted promptly in response to the outbreaks in Ntui, Ngaoundéré Rural, Yoko and Messamena. However, these four and two other health districts at high risk of yellow fever outbreaks (i.e. Maroua Urban and Ngaoundéré Urban) conducted preventive SIAs in November 2006, vaccinating a total of 752,195 people (92.8% of target population). In both the reactive and preventive SIAs, the mean wastage rates for vaccines and injection material were less than 5% and there was no report of a serious adverse event following immunisation.</p> <p>Conclusion</p> <p>Amidst other competing health priorities, over the past four years Cameroon has successfully planned and implemented evidence-based strategies for preventing yellow fever outbreaks and for detecting and responding to the outbreaks when they occur. In order to sustain these initial successes, the country will have to attain and sustain high routine vaccination coverage in each successive birth cohort in every district. This would require fostering and sustaining high-level political commitment, improving the planning and monitoring of immunisation services at all levels, adequate community mobilisation, and efficient coordination of current and future immunisation partners.</p

Two-dimensional NMR lineshape analysis

NMR titration experiments are a rich source of structural, mechanistic, thermodynamic and kinetic information on biomolecular interactions, which can be extracted through the quantitative analysis of resonance lineshapes. However, applications of such analyses are frequently limited by peak overlap inherent to complex biomolecular systems. Moreover, systematic errors may arise due to the analysis of two-dimensional data using theoretical frameworks developed for one-dimensional experiments. Here we introduce a more accurate and convenient method for the analysis of such data, based on the direct quantum mechanical simulation and fitting of entire two-dimensional experiments, which we implement in a new software tool, TITAN (TITration ANalysis). We expect the approach, which we demonstrate for a variety of protein-protein and protein-ligand interactions, to be particularly useful in providing information on multi-step or multi-component interactions