Morphology of Hydrodynamic Winds: A Study of Planetary Winds in Stellar Environments

Bathed in intense ionizing radiation, close-in gaseous planets undergo hydrodynamic atmospheric escape, which ejects the upper extent of their atmospheres into the interplanetary medium. Ultraviolet detections of escaping gas around transiting planets corroborate such a framework. Exposed to the stellar environment, the outflow is shaped by its interaction with the stellar wind and by the planet's orbit. We model these effects using Athena to perform 3-D radiative-hydrodynamic simulations of tidally-locked hydrogen atmospheres receiving large amounts of ionizing extreme-ultraviolet flux in various stellar environments for the low-magnetic-field case. Through a step-by-step exploration of orbital and stellar wind effects on the planetary outflow, we find three structurally distinct stellar wind regimes: weak, intermediate, and strong. We perform synthetic Lyman-$\alpha$ observations and find unique observational signatures for each regime. A weak stellar wind$\textrm{---}$which cannot confine the planetary outflow, leading to a torus of material around the star$\textrm{---}$has a pre-transit, red-shifted dayside arm and a slightly redward-skewed spectrum during transit. The intermediate regime truncates the dayside outflow at large distances from the planet and causes periodic disruptions of the outflow, producing observational signatures that mimic a double transit. The first of these dips is blue-shifted and precedes the optical transit. Finally, strong stellar winds completely confine the outflow into a cometary tail and accelerate the outflow outwards, producing large blue-shifted signals post-transit. Across all three regimes, large signals occur far outside of transit, offering motivation to continue ultraviolet observations outside of direct transit.Comment: 33 pages, 21 figures (7 of which have embedded movies viewable with Adobe Acrobat Pro), Submitted to Ap

Developmental interneuron subtype deficits after targeted loss of Arx

Abstract Background Aristaless-related homeobox (ARX) is a paired-like homeodomain transcription factor that functions primarily as a transcriptional repressor and has been implicated in neocortical interneuron specification and migration. Given the role interneurons appear to play in numerous human conditions including those associated with ARX mutations, it is essential to understand the consequences of mutations in this gene on neocortical interneurons. Previous studies have examined the effect of germline loss of Arx, or targeted mutations in Arx, on interneuron development. We now present the effect of conditional loss of Arx on interneuron development. Results To further elucidate the role of Arx in forebrain development we performed a series of anatomical and developmental studies to determine the effect of conditional loss of Arx specifically from developing interneurons in the neocortex and hippocampus. Analysis and cell counts were performed from mouse brains using immunohistochemical and in situ hybridization assays at 4 times points across development. Our data indicate that early in development, instead of a loss of ventral precursors, there is a shift of these precursors to more ventral locations, a deficit that persists in the adult nervous system. The result of this developmental shift is a reduced number of interneurons (all subtypes) at early postnatal and later time periods. In addition, we find that X inactivation is stochastic, and occurs at the level of the neural progenitors. Conclusion These data provide further support that the role of Arx in interneuron development is to direct appropriate migration of ventral neuronal precursors into the dorsal cortex and that the loss of Arx results in a failure of interneurons to reach the cortex and thus a deficiency in interneurons.http://deepblue.lib.umich.edu/bitstream/2027.42/134595/1/12868_2016_Article_265.pd

Fragment Production and Survival in Irradiated Disks: A Comprehensive Cooling Criterion

Accretion disks that become gravitationally unstable can fragment into stellar or sub-stellar companions. The formation and survival of these fragments depends on the precarious balance between self-gravity, internal pressure, tidal shearing, and rotation. Disk fragmentation depends on two key factors (1) whether the disk can get to the fragmentation boundary of Q=1, and (2) whether fragments can survive for many orbital periods. Previous work suggests that to reach Q=1, and have fragments survive, a disk must cool on an orbital timescale. Here we show that disks heated primarily by external irradiation always satisfy the standard cooling time criterion. Thus even though irradiation heats disks, and makes them more stable in general, once they reach the fragmentation boundary, they fragment more easily. We derive a new cooling criterion that determines fragment survival, and calculate a pressure modified Hill radius, which sets the maximum size of pressure-supported objects in a Keplerian disk. We conclude that fragmentation in protostellar disks might occur at slightly smaller radii than previously thought, and recommend tests for future simulations that will better predict the outcome of fragmentation in real disks.Comment: 14 pages, 4 figures, accepted to Ap

Highly Pathogenic Avian Influenza A(H5N1) Virus Outbreak in New England Seals, United States

We report the spillover of highly pathogenic avian influenza A(H5N1) into marine mammals in the northeastern United States, coincident with H5N1 in sympatric wild birds. Our data indicate monitoring both wild coastal birds and marine mammals will be critical to determine pandemic potential of influenza A viruses

The Runts of the Litter: Why planets formed through gravitational instability can only be failed binary stars

Recent direct imaging discoveries suggest a new class of massive, distant planets around A stars. These widely separated giants have been interpreted as signs of planet formation driven by gravitational instability, but the viability of this mechanism is not clear cut. In this paper, we first discuss the local requirements for fragmentation and the initial fragment mass scales. We then consider whether the fragment's subsequent growth can be terminated within the planetary mass regime. Finally, we place disks in the larger context of star formation and disk evolution models. We find that in order for gravitational instability to produce planets, disks must be atypically cold in order to reduce the initial fragment mass. In addition, fragmentation must occur during a narrow window of disk evolution, after infall has mostly ceased, but while the disk is still sufficiently massive to undergo gravitational instability. Under more typical conditions, disk-born objects will likely grow well above the deuterium burning planetary mass limit. We conclude that if planets are formed by gravitational instability, they must be the low mass tail of the distribution of disk-born companions. To validate this theory, on-going direct imaging surveys must find a greater abundance of brown dwarf and M-star companions to A-stars. Their absence would suggest planet formation by a different mechanism such as core accretion, which is consistent with the debris disks detected in these systems.Comment: 14 pages, 6 figures, accepted to ApJ, some content changes, revised figure

Evidence of a genetic background predisposing to complex regional pain syndrome type 1.

BackgroundComplex regional pain syndrome type 1 (CRPS-1) is a rare, disabling and sometimes chronic disorder usually arising after a trauma. This exploratory study examined whether patients with chronic CRPS-1 have a different genetic profile compared with those who do not have the condition.MethodsExome sequencing was performed to seek altered non-synonymous SNP allele frequencies in a discovery cohort of well-characterised patients with chronic CRPS-1 (n=34) compared with population databases. Identified SNP alleles were confirmed by Sanger sequencing and sought in a replication cohort (n=50). Gene expression of peripheral blood macrophages was assessed.ResultsIn the discovery cohort, the rare allele frequencies of four non-synonymous SNPs were statistically increased. The replication cohort confirmed this finding. In a chronic pain cohort, these alleles were not overexpressed. In total, 25 out of 84 (29.8%) patients with CRPS-1 expressed a rare allele. The SNPs were rs41289586 in ANO10, rs28360457 in P2RX7, rs1126930 in PRKAG1 and rs80308281 in SLC12A9. Males were more likely than females to have a rare SNP allele, 8 out of 14 (57.1%) vs 17 out of 70 (24.3%) (Fisher's p=0.023). ANO10, P2RX7, PRKAG1 and SLC12A9 were all expressed in macrophages from healthy human controls.ConclusionA single SNP in each of the genes ANO10, P2RX7, PRKAG1 and SLC12A9 was associated with developing chronic CRPS-1, with more males than females expressing these rare alleles. Our work suggests the possibility that a permissive genetic background is an important factor in the development of CRPS-1

Expanding the diversity of mycobacteriophages: insights into genome architecture and evolution.

Mycobacteriophages are viruses that infect mycobacterial hosts such as Mycobacterium smegmatis and Mycobacterium tuberculosis. All mycobacteriophages characterized to date are dsDNA tailed phages, and have either siphoviral or myoviral morphotypes. However, their genetic diversity is considerable, and although sixty-two genomes have been sequenced and comparatively analyzed, these likely represent only a small portion of the diversity of the mycobacteriophage population at large. Here we report the isolation, sequencing and comparative genomic analysis of 18 new mycobacteriophages isolated from geographically distinct locations within the United States. Although no clear correlation between location and genome type can be discerned, these genomes expand our knowledge of mycobacteriophage diversity and enhance our understanding of the roles of mobile elements in viral evolution. Expansion of the number of mycobacteriophages grouped within Cluster A provides insights into the basis of immune specificity in these temperate phages, and we also describe a novel example of apparent immunity theft. The isolation and genomic analysis of bacteriophages by freshman college students provides an example of an authentic research experience for novice scientists

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages