AIDS Treatment and Intrahousehold Resource Allocations: Children's Nutrition and Schooling in Kenya

The provision of life-saving antiretroviral (ARV) treatment has emerged as a key component of the global response to HIV/AIDS, but very little is known about the impact of this intervention on the welfare of children in the households of treated persons. We estimate the impact of ARV treatment on children’s schooling and nutrition outcomes using longitudinal household survey data collected in collaboration with a treatment program in western Kenya. We find that children’s weekly hours of school attendance increase by over 20 percent within six months after treatment is initiated for the adult household member. For boys in treatment households, these increases closely follow their reduced market labor supply. Similarly, young children’s short-term nutritional status—as measured by their weight-for-height Z-score—also improves dramatically. We argue that these treatment effects will be considerably larger when compared to the counterfactual scenario of no ARV treatment. The results provide evidence on how intrahousehold resource allocation is altered in response to significant health improvements. Since the improvements in children’s schooling and nutrition at these critical early ages will affect their socio-economic outcomes in adulthood, the widespread provision of ARV treatment is likely to generate significant long-run macroeconomic benefits.

Leveraging U.S. Army Administrative Data for Individual and Team Performance

The Army possesses vast amounts of administrative (archival) data about Soldiers. These data sources include screening tests, personnel action codes, training scores, global assessments, physical fitness scores, and more. However, the Army has yet to integrate these data to create a holistic operating picture. Our research focuses on repurposing Army administrative data to (1) operationalize social constructs of interest to the Army (e.g., Army Values, Warrior Ethos) and (2) model the predictive relationship between these constructs and individual (i.e., Soldier) and team (i.e., unit) performance and readiness. The goal of the project is to provide people analytics models to Army leadership for the purposes of optimizing human capital management decisions. Our talk will describe the theoretical underpinnings of our human performance model, drawing on disciplines such as social and industrial/organizational psychology, as well as our experience gaining access to and working with Army administrative data sources. Access to the archival administrative data is provided through the Army Analytics Group (AAG), Person-event Data Environment (PDE). The PDE is a business intelligence platform that has two central functions: (1) to provide a secure repository for data sources on U.S. military personnel; and (2) to provide a secure collaborative work environment where researchers can access unclassified but sensitive military data

Advancing the Frontier of Peacekeeping Research

The impact of United Nations (UN) peacekeeping on conflict has received a sustained amount of attention in the empirical literature. The advent of new data on UN peacekeeping and new temporal units of analysis have enabled researchers to expand the frontiers of peacekeeping research and undertake a more nuanced examination of peacekeeping effectiveness. In this special section, a series of articles examine how UN peacekeeping affects different types of violence within conflicts and leads to different types of peaceful outcomes. Factors such as the cultural affinity between peacekeepers and local communities, the size of peacekeeping operations and the specific composition of UN forces are shown to be important variables associated with lower levels of casualties and violence and also a higher likelihood of mediation and timely peaceful settlements in civil wars. In the aggregate, these articles suggest that robust peacekeeping is associated with better outcomes in many stages of conflict

Middle East Respiratory Syndrome Coronavirus NS4b Protein Inhibits Host RNase L Activation

ABSTRACT Middle East respiratory syndrome coronavirus (MERS-CoV) is the first highly pathogenic human coronavirus to emerge since severe acute respiratory syndrome coronavirus (SARS-CoV) in 2002. Like many coronaviruses, MERS-CoV carries genes that encode multiple accessory proteins that are not required for replication of the genome but are likely involved in pathogenesis. Evasion of host innate immunity through interferon (IFN) antagonism is a critical component of viral pathogenesis. The IFN-inducible oligoadenylate synthetase (OAS)-RNase L pathway activates upon sensing of viral double-stranded RNA (dsRNA). Activated RNase L cleaves viral and host single-stranded RNA (ssRNA), which leads to translational arrest and subsequent cell death, preventing viral replication and spread. Here we report that MERS-CoV, a lineage C Betacoronavirus , and related bat CoV NS4b accessory proteins have phosphodiesterase (PDE) activity and antagonize OAS-RNase L by enzymatically degrading 2′,5′-oligoadenylate (2-5A), activators of RNase L. This is a novel function for NS4b, which has previously been reported to antagonize IFN signaling. NS4b proteins are distinct from lineage A Betacoronavirus PDEs and rotavirus gene-encoded PDEs, in having an amino-terminal nuclear localization signal (NLS) and are localized mostly to the nucleus. However, the expression level of cytoplasmic MERS-CoV NS4b protein is sufficient to prevent activation of RNase L. Finally, this is the first report of an RNase L antagonist expressed by a human or bat coronavirus and provides a specific mechanism by which this occurs. Our findings provide a potential mechanism for evasion of innate immunity by MERS-CoV while also identifying a potential target for therapeutic intervention. IMPORTANCE Middle East respiratory syndrome coronavirus (MERS-CoV) is the first highly pathogenic human coronavirus to emerge since severe acute respiratory syndrome coronavirus (SARS-CoV). MERS-CoV, like other coronaviruses, carries genes that encode accessory proteins that antagonize the host antiviral response, often the type I interferon response, and contribute to virulence. We found that MERS-CoV NS4b and homologs from related lineage C bat betacoronaviruses BtCoV-SC2013 (SC2013) and BtCoV-HKU5 (HKU5) are members of the 2H-phosphoesterase (2H-PE) enzyme family with phosphodiesterase (PDE) activity. Like murine coronavirus NS2, a previously characterized PDE, MERS NS4b, can antagonize activation of the OAS-RNase L pathway, an interferon-induced potent antiviral activity. Furthermore, MERS-CoV mutants with deletion of genes encoding accessory proteins NS3 to NS5 or NS4b alone or inactivation of the PDE can activate RNase L during infection of Calu-3 cells. Our report may offer a potential target for therapeutic intervention if NS4b proves to be critical to pathogenesis in in vivo models of MERS-CoV infection

DECam-GROWTH Search for the Faint and Distant Binary Neutron Star and Neutron Star-Black Hole Mergers in O3a

Synoptic searches for the optical counterpart to a binary neutron star (BNS) or neutron star-black hole (NSBH) merger can pose significant challenges towards the discovery of kilonovae and performing multi-messenger science. In this work, we describe the advantage of a global multi-telescope network towards this end, with a particular focus on the key and complementary role the Dark Energy Camera (DECam) plays in multi-facility follow-up. We describe the Global Relay of Observatories Watching Transients Happen (GROWTH) Target-of-Opportunity (ToO) Marshal, a common web application we built to ingest events, plan observations, search for transient candidates, and retrieve performance summary statistics for all of the telescopes in our network. Our infrastructure enabled us to conduct observations of two events during O3a, S190426c and S190510g. Furthermore, our analysis of deep DECam observations of S190814bv conducted by the DESGW team, and access to a variety of global follow-up facilities allowed us to place meaningful constraints on the parameters of the kilonova and the merging binary. We emphasize the importance of a global telescope network in conjunction with a power telescope like DECam in performing searches for the counterparts to gravitational-wave sources

A case-control collapsing analysis identifies epilepsy genes implicated in trio sequencing studies focused on de novo mutations

Trio exome sequencing has been successful in identifying genes with de novo mutations (DNMs) causing epileptic encephalopathy (EE) and other neurodevelopmental disorders. Here, we evaluate how well a case-control collapsing analysis recovers genes causing dominant forms of EE originally implicated by DNM analysis. We performed a genome-wide search for an enrichment of "qualifying variants" in protein-coding genes in 488 unrelated cases compared to 12,151 unrelated controls. These "qualifying variants" were selected to be extremely rare variants predicted to functionally impact the protein to enrich for likely pathogenic variants. Despite modest sample size, three known EE genes (KCNT1, SCN2A, and STXBP1) achieved genome-wide significance (p<2.68×10−6). In addition, six of the 10 most significantly associated genes are known EE genes, and the majority of the known EE genes (17 out of 25) originally implicated in trio sequencing are nominally significant (p<0.05), a proportion significantly higher than the expected (Fisher’s exact p = 2.33×10−17). Our results indicate that a case-control collapsing analysis can identify several of the EE genes originally implicated in trio sequencing studies, and clearly show that additional genes would be implicated with larger sample sizes. The case-control analysis not only makes discovery easier and more economical in early onset disorders, particularly when large cohorts are available, but also supports the use of this approach to identify genes in diseases that present later in life when parents are not readily available

GROWTH on S190426c: Real-time Search for a Counterpart to the Probable Neutron Star–Black Hole Merger using an Automated Difference Imaging Pipeline for DECam

The discovery of a transient kilonova following the gravitational-wave (GW) event GW170817 highlighted the critical need for coordinated rapid and wide-field observations, inference, and follow-up across the electromagnetic spectrum. In the southern hemisphere, the Dark Energy Camera (DECam) on the Blanco 4 m telescope is well suited to this task, as it is able to cover wide fields quickly while still achieving the depths required to find kilonovae like the one accompanying GW170817 to ~500 Mpc, the binary neutron star (NS) horizon distance for current generation of LIGO/Virgo collaboration (LVC) interferometers. Here, as part of the multi-facility follow-up by the Global Relay of Observatories Watching Transients Happen collaboration, we describe the observations and automated data movement, data reduction, candidate discovery, and vetting pipeline of our target-of-opportunity DECam observations of S190426c, the first possible NS–black hole merger detected in GWs. Starting 7.5 hr after S190426c, over 11.28 hr of observations, we imaged an area of 525 deg^2 (r band) and 437 deg^2 (z band); this was 16.3% of the total original localization probability, and nearly all of the probability visible from the southern hemisphere. The machine-learning-based pipeline was optimized for fast turnaround, delivering transients for human vetting within 17 minutes, on average, of shutter closure. We reported nine promising counterpart candidates 2.5 hr before the end of our observations. One hour after our data-taking ended (roughly 20 hr after the announcement of S190426c), LVC released a refined skymap that reduced the probability coverage of our observations to 8.0%, demonstrating a critical need for localization updates on shorter (~hour) timescales. Our observations yielded no detection of a bona fide counterpart to m_z = 21.7 and m_r = 22.2 at the 5σ level of significance, consistent with the refined LVC positioning. We view these observations and rapid inferencing as an important real-world test for this novel end-to-end wide-field pipeline