COVID-19 and Cancer: Current Challenges and Perspectives.

Patients with cancer have been disproportionately affected by the COVID-19 pandemic. This effect has included the adverse outcomes in patients with cancer who develop COVID-19, the impact of the COVID-19 pandemic on the delivery of cancer care, and the severe disruption to cancer research. However, patients with cancer are a heterogeneous population, and recent studies have now documented factors that allow risk stratification of patients with cancer in order to optimize care. In this review, we highlight data at the intersection of COVID-19 and cancer, including the biological interplay between the two diseases and practical recommendations for the treatment of patients with cancer during the pandemic. We additionally discuss the potential long-lasting impact of the pandemic on cancer care due to its deleterious effect on cancer research, as well as biological insights from the cancer research community that could help develop novel therapies for all patients with COVID-19

Search for Global Dipole Enhancements in the HiRes-I Monocular Data above 10^{18.5} eV

Several proposed source models for Ultra-High Energy Cosmic Rays (UHECRs) consist of dipole distributions oriented towards major astrophysical landmarks such as the galactic center, M87, or Centaurus A. We use a comparison between real data and simulated data to show that the HiRes-I monocular data for energies above 10^{18.5} eV is, in fact, consistent with an isotropic source model. We then explore methods to quantify our sensitivity to dipole source models oriented towards the Galactic Center, M87, and Centaurus A.Comment: 17 pages, 31 figure

Observation of the Ankle and Evidence for a High-Energy Break in the Cosmic Ray Spectrum

We have measured the cosmic ray spectrum at energies above $10^{17}$ eV using the two air fluorescence detectors of the High Resolution Fly's Eye experiment operating in monocular mode. We describe the detector, PMT and atmospheric calibrations, and the analysis techniques for the two detectors. We fit the spectrum to models describing galactic and extragalactic sources. Our measured spectrum gives an observation of a feature known as the ``ankle'' near $3\times 10^{18}$ eV, and strong evidence for a suppression near $6\times 10^{19}$ eV.Comment: 14 pages, 9 figures. To appear in Physics Letters B. Accepted versio

Utilization of COVID-19 Treatments and Clinical Outcomes among Patients with Cancer: A COVID-19 and Cancer Consortium (CCC19) Cohort Study.

Among 2,186 U.S. adults with invasive cancer and laboratory-confirmed SARS-CoV-2 infection, we examined the association of COVID-19 treatments with 30-day all-cause mortality and factors associated with treatment. Logistic regression with multiple adjustments (e.g., comorbidities, cancer status, baseline COVID-19 severity) was performed. Hydroxychloroquine with any other drug was associated with increased mortality versus treatment with any COVID-19 treatment other than hydroxychloroquine or untreated controls; this association was not present with hydroxychloroquine alone. Remdesivir had numerically reduced mortality versus untreated controls that did not reach statistical significance. Baseline COVID-19 severity was strongly associated with receipt of any treatment. Black patients were approximately half as likely to receive remdesivir as white patients. Although observational studies can be limited by potential unmeasured confounding, our findings add to the emerging understanding of patterns of care for patients with cancer and COVID-19 and support evaluation of emerging treatments through inclusive prospective controlled trials. SIGNIFICANCE: Evaluating the potential role of COVID-19 treatments in patients with cancer in a large observational study, there was no statistically significant 30-day all-cause mortality benefit with hydroxychloroquine or high-dose corticosteroids alone or in combination; remdesivir showed potential benefit. Treatment receipt reflects clinical decision-making and suggests disparities in medication access.This article is highlighted in the In This Issue feature, p. 1426

A Likelihood Method for Measuring the Ultrahigh Energy Cosmic Ray Composition

Air fluorescence detectors traditionally determine the dominant chemical composit ion of the ultrahigh energy cosmic ray flux by comparing the averaged slant depth of the shower maximum, $X_{max}$, as a function of energy to the slant depths expect ed for various hypothesized primaries. In this paper, we present a method to make a direct measurement of the expected mean number of protons and iron by comparing the shap es of the expected $X_{max}$ distributions to the distribution for data. The advantages of this method includes the use of information of the full distribution and its ability to calculate a flux for various cosmic ray compositi ons. The same method can be expanded to marginalize uncertainties due to choice of spectra, hadronic models and atmospheric parameters. We demonstrate the technique with independent simulated data samples from a parent sample of protons and iron. We accurately predict the number of protons and iron in the parent sample and show that the uncertainties are meaningful.Comment: 11 figures, 22 pages, accepted by Astroparticle Physic

Alternative Methods to Finding Patterns in HiRes Stereo Data

In this paper Ultra High Energy Cosmic Rays UHECRs data observed by the HiRes fluorescence detector in stereo mode is analyzed to search for events in the sky with an arrival direction lying on a great circle. Such structure is known as the arc structure. The arc structure is expected when the charged cosmic rays pass through the galactic magnetic field. The arcs searched for could represent a broad or a small scale anisotropy depending on the proposed source model for the UHECRs. The Arcs in this paper are looked for using Hough transform were Hough transform is a technique used to looking for patterns in images. No statistically significant arcs were found in this study

The genetic architecture of the human cerebral cortex

INTRODUCTION The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS We identified 306 nominally genome-wide significant loci (P < 5 × 10−8) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 299 loci for which replication data were available, 241 loci influencing surface area and 14 influencing thickness remained significant after replication, with 199 loci passing multiple testing correction (P < 8.3 × 10−10; 187 influencing surface area and 12 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation (rG = −0.32, SE = 0.05, P = 6.5 × 10−12), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 10 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function