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

Discovery of the Optical Afterglow and Host Galaxy of Short GRB 181123B at z = 1.754: Implications for Delay Time Distributions

We present the discovery of the optical afterglow and host galaxy of the Swift short-duration gamma-ray burst (SGRB) GRB 181123B. Observations with Gemini-North starting ≈9.1 hr after the burst reveal a faint optical afterglow with i ≈ 25.1 mag at an angular offset of 0farcs59 ± 0farcs16 from its host galaxy. Using grizYJHK observations, we measure a photometric redshift of the host galaxy of $z={1.77}_{-0.17}^{+0.30}$. From a combination of Gemini and Keck spectroscopy of the host galaxy spanning 4500–18000 Å, we detect a single emission line at 13390 Å, inferred as Hβ at z = 1.754 ± 0.001 and corroborating the photometric redshift. The host galaxy properties of GRB 181123B are typical of those of other SGRB hosts, with an inferred stellar mass of ≈9.1 × 109 M ⊙, a mass-weighted age of ≈0.9 Gyr, and an optical luminosity of ≈0.9L*. At z = 1.754, GRB 181123B is the most distant secure SGRB with an optical afterglow detection and one of only three at z > 1.5. Motivated by a growing number of high-z SGRBs, we explore the effects of a missing z > 1.5 SGRB population among the current Swift sample on delay time distribution (DTD) models. We find that lognormal models with mean delay times of ≈4–6 Gyr are consistent with the observed distribution but can be ruled out to 95% confidence, with an additional ≈one to five Swift SGRBs recovered at z > 1.5. In contrast, power-law models with ∝t −1 are consistent with the redshift distribution and can accommodate up to ≈30 SGRBs at these redshifts. Under this model, we predict that ≈1/3 of the current Swift population of SGRBs is at z > 1. The future discovery or recovery of existing high-z SGRBs will provide significant discriminating power on their DTDs and thus their formation channels

The Evolution of Compact Binary Star Systems

We review the formation and evolution of compact binary stars consisting of white dwarfs (WDs), neutron stars (NSs), and black holes (BHs). Binary NSs and BHs are thought to be the primary astrophysical sources of gravitational waves (GWs) within the frequency band of ground-based detectors, while compact binaries of WDs are important sources of GWs at lower frequencies to be covered by space interferometers (LISA). Major uncertainties in the current understanding of properties of NSs and BHs most relevant to the GW studies are discussed, including the treatment of the natal kicks which compact stellar remnants acquire during the core collapse of massive stars and the common envelope phase of binary evolution. We discuss the coalescence rates of binary NSs and BHs and prospects for their detections, the formation and evolution of binary WDs and their observational manifestations. Special attention is given to AM CVn-stars -- compact binaries in which the Roche lobe is filled by another WD or a low-mass partially degenerate helium-star, as these stars are thought to be the best LISA verification binary GW sources.Comment: 105 pages, 18 figure

Genome-wide association analysis identifies a meningioma risk locus at 11p15.5.

Background Meningiomas are adult brain tumors originating in the meningeal coverings of the brain and spinal cord, with significant heritable basis. Genome-wide association studies (GWAS) have previously identified only a single risk locus for meningioma, at 10p12.31.Methods To identify a susceptibility locus for meningioma, we conducted a meta-analysis of 2 GWAS, imputed using a merged reference panel from the 1000 Genomes Project and UK10K data, with validation in 2 independent sample series totaling 2138 cases and 12081 controls.Results We identified a new susceptibility locus for meningioma at 11p15.5 (rs2686876, odds ratio = 1.44, P = 9.86 × 10-9). A number of genes localize to the region of linkage disequilibrium encompassing rs2686876, including RIC8A, which plays a central role in the development of neural crest-derived structures, such as the meninges.Conclusions This finding advances our understanding of the genetic basis of meningioma development and provides additional support for a polygenic model of meningioma

Maternal common mental disorders and infant development in Ethiopia : the P-MaMiE Birth Cohort

Background: Chronicity and severity of early exposure to maternal common mental disorders (CMD) has been associated with poorer infant development in high-income countries. In low- and middle-income countries (LAMICs), perinatal CMD is inconsistently associated with infant development, but the impact of severity and persistence has not been examined. Methods: A nested population-based cohort of 258 pregnant women was identified from the Perinatal Maternal Mental Disorder in Ethiopia (P-MaMiE) study, and 194 (75.2%) were successfully followed up until the infants were 12 months of age. Maternal CMD was measured in pregnancy and at two and 12 months postnatal using the WHO Self-Reporting Questionnaire, validated for use in this setting. Infant outcomes were evaluated using the Bayley Scales of Infant Development. Results: Antenatal maternal CMD symptoms were associated with poorer infant motor development ( β ^ -0.20; 95% CI: -0.37 to -0.03), but this became non-significant after adjusting for confounders. Postnatal CMD symptoms were not associated with any domain of infant development. There was evidence of a dose-response relationship between the number of time-points at which the mother had high levels of CMD symptoms (SRQ ≥ 6) and impaired infant motor development ( β ^ = -0.80; 95%CI -2.24, 0.65 for ante- or postnatal CMD only, β ^ = -4.19; 95%CI -8.60, 0.21 for ante- and postnatal CMD, compared to no CMD; test-for-trend χ213.08(1), p < 0.001). Although this association became non-significant in the fully adjusted model, the β ^ coefficients were unchanged indicating that the relationship was not confounded. In multivariable analyses, lower socio-economic status and lower infant weight-for-age were associated with significantly lower scores on both motor and cognitive developmental scales. Maternal experience of physical violence was significantly associated with impaired cognitive development. Conclusions: The study supports the hypothesis that it is the accumulation of risk exposures across time rather than early exposure to maternal CMD per se that is more likely to affect child development. Further investigation of the impact of chronicity of maternal CMD upon child development in LAMICs is indicated. In the Ethiopian setting, poverty, interpersonal violence and infant undernutrition should be targets for interventions to reduce the loss of child developmental potential.Peer Reviewe

Diffusive coupling can discriminate between similar reaction mechanisms in an allosteric enzyme system

<p>Abstract</p> <p>Background</p> <p>A central question for the understanding of biological reaction networks is how a particular dynamic behavior, such as bistability or oscillations, is realized at the molecular level. So far this question has been mainly addressed in well-mixed reaction systems which are conveniently described by ordinary differential equations. However, much less is known about how molecular details of a reaction mechanism can affect the dynamics in diffusively coupled systems because the resulting partial differential equations are much more difficult to analyze.</p> <p>Results</p> <p>Motivated by recent experiments we compare two closely related mechanisms for the product activation of allosteric enzymes with respect to their ability to induce different types of reaction-diffusion waves and stationary Turing patterns. The analysis is facilitated by mapping each model to an associated complex Ginzburg-Landau equation. We show that a sequential activation mechanism, as implemented in the model of Monod, Wyman and Changeux (MWC), can generate inward rotating spiral waves which were recently observed as glycolytic activity waves in yeast extracts. In contrast, in the limiting case of a simple Hill activation, the formation of inward propagating waves is suppressed by a Turing instability. The occurrence of this unusual wave dynamics is not related to the magnitude of the enzyme cooperativity (as it is true for the occurrence of oscillations), but to the sensitivity with respect to changes of the activator concentration. Also, the MWC mechanism generates wave patterns that are more stable against long wave length perturbations.</p> <p>Conclusions</p> <p>This analysis demonstrates that amplitude equations, which describe the spatio-temporal dynamics near an instability, represent a valuable tool to investigate the molecular effects of reaction mechanisms on pattern formation in spatially extended systems. Using this approach we have shown that the occurrence of inward rotating spiral waves in glycolysis can be explained in terms of an MWC, but not with a Hill mechanism for the activation of the allosteric enzyme phosphofructokinase. Our results also highlight the importance of enzyme oligomerization for a possible experimental generation of Turing patterns in biological systems.</p

Hot or not? Discovery and characterization of a thermostable alditol oxidase from Acidothermus cellulolyticus 11B

We describe the discovery, isolation and characterization of a highly thermostable alditol oxidase from Acidothermus cellulolyticus 11B. This protein was identified by searching the genomes of known thermophiles for enzymes homologous to Streptomyces coelicolor A3(2) alditol oxidase (AldO). A gene (sharing 48% protein sequence identity to AldO) was identified, cloned and expressed in Escherichia coli. Following 6xHis tag purification, characterization revealed the protein to be a covalent flavoprotein of 47 kDa with a remarkably similar reactivity and substrate specificity to that of AldO. A steady-state kinetic analysis with a number of different polyol substrates revealed lower catalytic rates but slightly altered substrate specificity when compared to AldO. Thermostability measurements revealed that the novel AldO is a highly thermostable enzyme with an unfolding temperature of 84 °C and an activity half-life at 75 °C of 112 min, prompting the name HotAldO. Inspired by earlier studies, we attempted a straightforward, exploratory approach to improve the thermostability of AldO by replacing residues with high B-factors with corresponding residues from HotAldO. None of these mutations resulted in a more thermostable oxidase; a fact that was corroborated by in silico analysis

Beyond forcing scenarios: predicting climate change through response operators in a coupled general circulation model

Global Climate Models are key tools for predicting the future response of the climate system to a variety of natural and anthropogenic forcings. Here we show how to use statistical mechanics to construct operators able to flexibly predict climate change for a variety of climatic variables of interest. We perform our study on a fully coupled model - MPI-ESM v.1.2 - and for the first time we prove the effectiveness of response theory in predicting future climate response to CO2 increase on a vast range of temporal scales, from inter-annual to centennial, and for very diverse climatic quantities. We investigate within a unified perspective the transient climate response and the equilibrium climate sensitivity and assess the role of fast and slow processes. The prediction of the ocean heat uptake highlights the very slow relaxation to a newly established steady state. The change in the Atlantic Meridional Overturning Circulation (AMOC) and of the Antarctic Circumpolar Current (ACC) is accurately predicted. The AMOC strength is initially reduced and then undergoes a slow and only partial recovery. The ACC strength initially increases as a result of changes in the wind stress, then undergoes a slowdown, followed by a recovery leading to a overshoot with respect to the initial value. Finally, we are able to predict accurately the temperature change in the Northern Atlantic

A Linear Framework for Time-Scale Separation in Nonlinear Biochemical Systems

Cellular physiology is implemented by formidably complex biochemical systems with highly nonlinear dynamics, presenting a challenge for both experiment and theory. Time-scale separation has been one of the few theoretical methods for distilling general principles from such complexity. It has provided essential insights in areas such as enzyme kinetics, allosteric enzymes, G-protein coupled receptors, ion channels, gene regulation and post-translational modification. In each case, internal molecular complexity has been eliminated, leading to rational algebraic expressions among the remaining components. This has yielded familiar formulas such as those of Michaelis-Menten in enzyme kinetics, Monod-Wyman-Changeux in allostery and Ackers-Johnson-Shea in gene regulation. Here we show that these calculations are all instances of a single graph-theoretic framework. Despite the biochemical nonlinearity to which it is applied, this framework is entirely linear, yet requires no approximation. We show that elimination of internal complexity is feasible when the relevant graph is strongly connected. The framework provides a new methodology with the potential to subdue combinatorial explosion at the molecular level