Uppermost mantle (Pn) velocity model for the Afar region, Ethiopia: an insight into rifting processes

The Afar Depression, Ethiopia, offers unique opportunities to study the transition from continental rifting to oceanic spreading because the process is occurring onland. Using traveltime tomography and data from a temporary seismic deployment, we describe the first regional study of uppermost mantle P-wave velocities (VPn). We find two separate low VPn zones (as low as 7.2 km s−1) beneath regions of localized thinned crust in northern Afar, indicating the existence of high temperatures and, potentially, partial melt. The zones are beneath and off-axis from, contemporary crustal magma intrusions in active magmatic segments, the Dabbahu-Manda-Hararo and Erta'Ale segments. This suggests that these intrusions can be fed by off-axis delivery of melt in the uppermost mantle and that discrete areas of mantle upwelling and partial melting, thought to characterize segmentation of the uppermost mantle at seafloor spreading centres, are initiated during the final stages of break-up

Mapping crustal shear wave velocity structure and radial anisotropy beneath West Antarctica using seismic ambient noise

Using 8‐25s period Rayleigh and Love wave phase velocity dispersion data extracted from seismic ambient noise, we (i) model the 3D shear wave velocity structure of the West Antarctic crust and (ii) map variations in crustal radial anisotropy. Enhanced regional resolution is offered by the UK Antarctic Seismic Network. In the West Antarctic Rift System (WARS), a ridge of crust ~26‐30km thick extending south from Marie Byrd Land separates domains of more extended crust (~22km thick) in the Ross and Amundsen Sea Embayments, suggesting along‐strike variability in the Cenozoic evolution of the WARS. The southern margin of the WARS is defined along the southern Transantarctic Mountains (TAM) and Haag Nunataks‐Ellsworth Whitmore Mountains (HEW) block by a sharp crustal thickness gradient. Crust ~35‐40km is modelled beneath the Haag Nunataks‐Ellsworth Mountains, decreasing to ~30‐32km km thick beneath the Whitmore Mountains, reflecting distinct structural domains within the composite HEW block. Our analysis suggests that the lower crust and potentially the mid crust is positively radially anisotropic (VSH > VSV) across West Antarctica. The strongest anisotropic signature is observed in the HEW block, emphasising its unique provenance amongst West Antarctica's crustal units, and conceivably reflects a ~13km thick metasedimentary succession atop Precambrian metamorphic basement. Positive radial anisotropy in the WARS crust is consistent with observations in extensional settings, and likely reflects the lattice‐preferred orientation of minerals such as mica and amphibole by extensional deformation. Our observations support a contention that anisotropy may be ubiquitous in continental crust

Impact of left ventricular ejection fraction on clinical outcomes after left main coronary artery revascularization

Aim: To evaluate the impact of left ventricular ejection fraction (LVEF) on 3-year outcomes in patients with left main coronary artery disease (LMCAD) undergoing percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG) in the EXCEL trial. Methods and results: The EXCEL trial randomized patients with LMCAD to PCI with everolimus-eluting stents (n = 948) or CABG (n = 957). Among 1804 patients with known baseline LVEF, 74 (4.1%) had LVEF <40% [heart failure with reduced ejection fraction (HFrEF)], 152 (8.4%) LVEF 40–49% [heart failure with mid-range ejection fraction (HFmrEF)] and 1578 (87.5%) LVEF ≥50% (heart failure with preserved ejection fraction). Patients with HFrEF vs. HFmrEF vs. preserved LVEF experienced a longer postoperative hospital stay (9.0 vs. 7.0 vs. 6.0 days, P = 0.02) with greater peri-procedural complications after CABG, while hospital stay after PCI was unaffected by LVEF (1.5 vs. 2.0 vs. 1.0 days, P = 0.20). The composite primary endpoint of death, stroke, or myocardial infarction at 3 years was 29.3% (PCI) vs. 27.6% (CABG) in patients with HFrEF, 16.2% vs. 15.0% in patients with HFmrEF, and 14.5% vs. 14.6% in those with preserved LVEF, respectively (Pinteraction = 0.90). Smoothing spline analysis demonstrated that the 3-year risk of all-cause death increased when LVEF decreased, both in patients undergoing CABG and PCI. Conclusion: In the EXCEL trial, the composite rate of death, stroke or myocardial infarction at 3 years was significantly higher in patients with HFrEF compared with HFmrEF or preserved LVEF, driven by an increased rate of all-cause death. No significant differences after PCI vs. CABG were observed among patients with HFrEF, HFmrEF and preserved LVEF. Longer-term follow-up could provide important insights on differences in clinical outcomes that might emerge over time. Clinical Trial Registration: ClinicalTrials.gov ID NCT01205776

Acid sensing by the Drosophila olfactory system.

The odour of acids has a distinct quality that is perceived as sharp, pungent and often irritating. How acidity is sensed and translated into an appropriate behavioural response is poorly understood. Here we describe a functionally segregated population of olfactory sensory neurons in the fruitfly, Drosophila melanogaster, that are highly selective for acidity. These olfactory sensory neurons express IR64a, a member of the recently identified ionotropic receptor (IR) family of putative olfactory receptors. In vivo calcium imaging showed that IR64a+ neurons projecting to the DC4 glomerulus in the antennal lobe are specifically activated by acids. Flies in which the function of IR64a+ neurons or the IR64a gene is disrupted had defects in acid-evoked physiological and behavioural responses, but their responses to non-acidic odorants remained unaffected. Furthermore, artificial stimulation of IR64a+ neurons elicited avoidance responses. Taken together, these results identify cellular and molecular substrates for acid detection in the Drosophila olfactory system and support a labelled-line mode of acidity coding at the periphery

Some general properties of the renormalized stress-energy tensor for static quantum states on (n+1)-dimensional spherically symmetric black holes

We study the renormalized stress-energy tensor (RSET) for static quantum states on (n+1)-dimensional, static, spherically symmetric black holes. By solving the conservation equations, we are able to write the stress-energy tensor in terms of a single unknown function of the radial co-ordinate, plus two arbitrary constants. Conditions for the stress-energy tensor to be regular at event horizons (including the extremal and ``ultra-extremal'' cases) are then derived using generalized Kruskal-like co-ordinates. These results should be useful for future calculations of the RSET for static quantum states on spherically symmetric black hole geometries in any number of space-time dimensions.Comment: 9 pages, no figures, RevTeX4, references added, accepted for publication in General Relativity and Gravitatio

p16INK4A-dependent senescence in the bone marrow niche drives age-related metabolic changes of hematopoietic progenitors

Rapid and effective leukocyte response to infection is a fundamental function of the bone marrow (BM). However, with increasing age, this response becomes impaired, resulting in an increased burden of infectious diseases. Here, we investigate how aging changes the metabolism and function of hematopoietic progenitor cells (HPCs) and the impact of the BM niche on this phenotype. We found that, in response to lipopolysaccharide-induced stress, HPC mitochondrial function is impaired, and there is a failure to upregulate the TCA cycle in progenitor populations in aged animals compared with young animals. Furthermore, aged mesenchymal stromal cells (MSCs) of the BM niche, but not HPCs, exhibit a senescent phenotype, and selective depletion of senescent cells from the BM niche, as well as treatment with the senolytic drug ABT-263, improves mitochondrial function of HPCs when stressed with lipopolysaccharide. In summary, age-related HPC metabolic dysfunction occurs indirectly as a “bystander phenomenon” in the aging BM niche and can be restored by targeting senescent MSCs

Towards Machine Wald

The past century has seen a steady increase in the need of estimating and predicting complex systems and making (possibly critical) decisions with limited information. Although computers have made possible the numerical evaluation of sophisticated statistical models, these models are still designed \emph{by humans} because there is currently no known recipe or algorithm for dividing the design of a statistical model into a sequence of arithmetic operations. Indeed enabling computers to \emph{think} as \emph{humans} have the ability to do when faced with uncertainty is challenging in several major ways: (1) Finding optimal statistical models remains to be formulated as a well posed problem when information on the system of interest is incomplete and comes in the form of a complex combination of sample data, partial knowledge of constitutive relations and a limited description of the distribution of input random variables. (2) The space of admissible scenarios along with the space of relevant information, assumptions, and/or beliefs, tend to be infinite dimensional, whereas calculus on a computer is necessarily discrete and finite. With this purpose, this paper explores the foundations of a rigorous framework for the scientific computation of optimal statistical estimators/models and reviews their connections with Decision Theory, Machine Learning, Bayesian Inference, Stochastic Optimization, Robust Optimization, Optimal Uncertainty Quantification and Information Based Complexity.Comment: 37 page

A review of spatial causal inference methods for environmental and epidemiological applications

The scientific rigor and computational methods of causal inference have had great impacts on many disciplines, but have only recently begun to take hold in spatial applications. Spatial casual inference poses analytic challenges due to complex correlation structures and interference between the treatment at one location and the outcomes at others. In this paper, we review the current literature on spatial causal inference and identify areas of future work. We first discuss methods that exploit spatial structure to account for unmeasured confounding variables. We then discuss causal analysis in the presence of spatial interference including several common assumptions used to reduce the complexity of the interference patterns under consideration. These methods are extended to the spatiotemporal case where we compare and contrast the potential outcomes framework with Granger causality, and to geostatistical analyses involving spatial random fields of treatments and responses. The methods are introduced in the context of observational environmental and epidemiological studies, and are compared using both a simulation study and analysis of the effect of ambient air pollution on COVID-19 mortality rate. Code to implement many of the methods using the popular Bayesian software OpenBUGS is provided