An improved method for measuring muon energy using the truncated mean of dE/dx

The measurement of muon energy is critical for many analyses in large Cherenkov detectors, particularly those that involve separating extraterrestrial neutrinos from the atmospheric neutrino background. Muon energy has traditionally been determined by measuring the specific energy loss (dE/dx) along the muon's path and relating the dE/dx to the muon energy. Because high-energy muons (E_mu > 1 TeV) lose energy randomly, the spread in dE/dx values is quite large, leading to a typical energy resolution of 0.29 in log10(E_mu) for a muon observed over a 1 km path length in the IceCube detector. In this paper, we present an improved method that uses a truncated mean and other techniques to determine the muon energy. The muon track is divided into separate segments with individual dE/dx values. The elimination of segments with the highest dE/dx results in an overall dE/dx that is more closely correlated to the muon energy. This method results in an energy resolution of 0.22 in log10(E_mu), which gives a 26% improvement. This technique is applicable to any large water or ice detector and potentially to large scintillator or liquid argon detectors.Comment: 12 pages, 16 figure

Extent and Causes of Chesapeake Bay Warming

Coastal environments such as the Chesapeake Bay have long been impacted by eutrophication stressors resulting from human activities, and these impacts are now being compounded by global warming trends. However, there are few studies documenting long-term estuarine temperature change and the relative contributions of rivers, the atmosphere, and the ocean. In this study, Chesapeake Bay warming, since 1985, is quantified using a combination of cruise observations and model outputs, and the relative contributions to that warming are estimated via numerical sensitivity experiments with a watershed–estuarine modeling system. Throughout the Bay’s main stem, similar warming rates are found at the surface and bottom between the late 1980s and late 2010s (0.02 +/- 0.02C/year, mean +/- 1 standard error), with elevated summer rates (0.04 +/- 0.01C/year) and lower rates of winter warming (0.01 +/- 0.01C/year). Most (~85%) of this estuarine warming is driven by atmospheric effects. The secondary influence of ocean warming increases with proximity to the Bay mouth, where it accounts for more than half of summer warming in bottom waters. Sea level rise has slightly reduced summer warming, and the influence of riverine warming has been limited to the heads of tidal tributaries. Future rates of warming in Chesapeake Bay will depend not only on global atmospheric trends, but also on regional circulation patterns in mid-Atlantic waters, which are currently warming faster than the atmosphere. Supporting model data available at: https://doi.org/10.25773/c774-a36

Associations of autozygosity with a broad range of human phenotypes

In many species, the offspring of related parents suffer reduced reproductive success, a phenomenon known as inbreeding depression. In humans, the importance of this effect has remained unclear, partly because reproduction between close relatives is both rare and frequently associated with confounding social factors. Here, using genomic inbreeding coefficients (F-ROH) for >1.4 million individuals, we show that F-ROH is significantly associated (p <0.0005) with apparently deleterious changes in 32 out of 100 traits analysed. These changes are associated with runs of homozygosity (ROH), but not with common variant homozygosity, suggesting that genetic variants associated with inbreeding depression are predominantly rare. The effect on fertility is striking: F-ROH equivalent to the offspring of first cousins is associated with a 55% decrease [95% CI 44-66%] in the odds of having children. Finally, the effects of F-ROH are confirmed within full-sibling pairs, where the variation in F-ROH is independent of all environmental confounding.Peer reviewe

New insights into the genetic etiology of Alzheimer's disease and related dementias

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele

Author Correction: Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function

These authors contributed equally: Gail Davies, Max Lam. These authors jointly supervised this work: Todd Lencz, Ian J. Deary

Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting.

OBJECTIVE: To explore genetic and lifestyle risk factors of MRI-defined brain infarcts (BI) in large population-based cohorts. METHODS: We performed meta-analyses of genome-wide association studies (GWAS) and examined associations of vascular risk factors and their genetic risk scores (GRS) with MRI-defined BI and a subset of BI, namely, small subcortical BI (SSBI), in 18 population-based cohorts (n = 20,949) from 5 ethnicities (3,726 with BI, 2,021 with SSBI). Top loci were followed up in 7 population-based cohorts (n = 6,862; 1,483 with BI, 630 with SBBI), and we tested associations with related phenotypes including ischemic stroke and pathologically defined BI. RESULTS: The mean prevalence was 17.7% for BI and 10.5% for SSBI, steeply rising after age 65. Two loci showed genome-wide significant association with BI: FBN2, p = 1.77 × 10-8; and LINC00539/ZDHHC20, p = 5.82 × 10-9. Both have been associated with blood pressure (BP)-related phenotypes, but did not replicate in the smaller follow-up sample or show associations with related phenotypes. Age- and sex-adjusted associations with BI and SSBI were observed for BP traits (p value for BI, p [BI] = 9.38 × 10-25; p [SSBI] = 5.23 × 10-14 for hypertension), smoking (p [BI] = 4.4 × 10-10; p [SSBI] = 1.2 × 10-4), diabetes (p [BI] = 1.7 × 10-8; p [SSBI] = 2.8 × 10-3), previous cardiovascular disease (p [BI] = 1.0 × 10-18; p [SSBI] = 2.3 × 10-7), stroke (p [BI] = 3.9 × 10-69; p [SSBI] = 3.2 × 10-24), and MRI-defined white matter hyperintensity burden (p [BI] = 1.43 × 10-157; p [SSBI] = 3.16 × 10-106), but not with body mass index or cholesterol. GRS of BP traits were associated with BI and SSBI (p ≤ 0.0022), without indication of directional pleiotropy. CONCLUSION: In this multiethnic GWAS meta-analysis, including over 20,000 population-based participants, we identified genetic risk loci for BI requiring validation once additional large datasets become available. High BP, including genetically determined, was the most significant modifiable, causal risk factor for BI