Sensitivity Analysis for the Assessment of Causal Vaccine Effects on Viral Load in HIV Vaccine Trials

Vaccines with limited ability to prevent HIV infection may positively impact the HIV/AIDS pandemic by preventing secondary transmission and disease in vaccine recipients who become infected. To evaluate the impact of vaccination on secondary transmission and disease, efficacy trials assess vaccine effects on HIV viral load and other surrogate endpoints measured after infection. A standard test that compares the distribution of viral load between the infected subgroups of vaccine and placebo recipients does not assess a causal effect of vaccine, because the comparison groups are selected after randomization. To address this problem, we formulate clinically relevant causal estimands using the principal stratification framework developed by Frangakis and Rubin (2002), and propose a class of logistic selection bias models whose members identify the estimands. Given a selection model in the class, procedures are developed for testing and estimation of the causal effect of vaccination on viral load in the principal stratum of subjects who would be infected regardless of randomization assignment. We show how the procedures can be used for a sensitivity analysis that quantifies how the causal effect of vaccination varies with the presumed magnitude of selection bias

Miscarriage and stillbirth following maternal Zika virus infection in nonhuman primates.

Zika virus (ZIKV) infection is associated with congenital defects and pregnancy loss. Here, we found that 26% of nonhuman primates infected with Asian/American ZIKV in early gestation experienced fetal demise later in pregnancy despite showing few clinical signs of infection. Pregnancy loss due to asymptomatic ZIKV infection may therefore be a common but under-recognized adverse outcome related to maternal ZIKV infection

Magnetophoretic bead trapping in a high-flowrate biological detection system.

This report contains the summary of the 'Magnetophoretic Bead Trapping in a High-Flowrate Biological Detection System' LDRD project 74795. The objective of this project is to develop a novel biodetection system for high-throughput sample analysis. The chief application of this system is in detection of very low concentrations of target molecules from a complex liquid solution containing many different constituents--some of which may interfere with identification of the target molecule. The system is also designed to handle air sampling by using an aerosol system (for instance a WESP - Wet Electro-Static Precipitator, or an impact spray system) to get air sample constituents into the liquid volume. The system described herein automatically takes the raw liquid sample, whether air converted or initially liquid matrix, and mixes in magnetic detector beads that capture the targets of interest and then performs the sample cleanup function, allowing increased sensitivity and eliminating most false positives and false negatives at a downstream detector. The surfaces of the beads can be functionalized in a variety of ways in order to maximize the number of targets to be captured and concentrated. Bacteria and viruses are captured using antibodies to surface proteins on bacterial cell walls or viral particle coats. In combination with a cell lysis or PCR (Polymerase Chain Reaction), the beads can be used as a DNA or RNA probe to capture nucleic acid patterns of interest. The sample cleanup capability of this system would allow different raw biological samples, such as blood or saliva to be analyzed for the presence of different infectious agents (e.g. smallpox or SARS). For future studies, we envision functionalizing bead surfaces to bind to chemical weapons agents, radio-isotopes, and explosives. The two main objectives of this project were to explore methods for enhancing the mixing of the capture microspheres in the sample, and to develop a novel high-throughput magnetic microsphere trap. We have developed a novel technique using the magnetic capture microspheres as 'stirrer bars' in a fluid sample to enhance target binding to the microsphere surfaces. We have also made progress in developing a polymer-MEMS electromagnet for trapping magnetic spheres in a high-flowrate fluid format

Planetary Candidates Observed by Kepler, III: Analysis of the First 16 Months of Data

New transiting planet candidates are identified in sixteen months (May 2009 - September 2010) of data from the Kepler spacecraft. Nearly five thousand periodic transit-like signals are vetted against astrophysical and instrumental false positives yielding 1,091 viable new planet candidates, bringing the total count up to over 2,300. Improved vetting metrics are employed, contributing to higher catalog reliability. Most notable is the noise-weighted robust averaging of multi-quarter photo-center offsets derived from difference image analysis which identifies likely background eclipsing binaries. Twenty-two months of photometry are used for the purpose of characterizing each of the new candidates. Ephemerides (transit epoch, T_0, and orbital period, P) are tabulated as well as the products of light curve modeling: reduced radius (Rp/R*), reduced semi-major axis (d/R*), and impact parameter (b). The largest fractional increases are seen for the smallest planet candidates (197% for candidates smaller than 2Re compared to 52% for candidates larger than 2Re) and those at longer orbital periods (123% for candidates outside of 50-day orbits versus 85% for candidates inside of 50-day orbits). The gains are larger than expected from increasing the observing window from thirteen months (Quarter 1-- Quarter 5) to sixteen months (Quarter 1 -- Quarter 6). This demonstrates the benefit of continued development of pipeline analysis software. The fraction of all host stars with multiple candidates has grown from 17% to 20%, and the paucity of short-period giant planets in multiple systems is still evident. The progression toward smaller planets at longer orbital periods with each new catalog release suggests that Earth-size planets in the Habitable Zone are forthcoming if, indeed, such planets are abundant.Comment: Submitted to ApJS. Machine-readable tables are available at http://kepler.nasa.gov, http://archive.stsci.edu/kepler/results.html, and the NASA Exoplanet Archiv

Fetal Demise and Failed Antibody Therapy During Zika Virus Infection of Pregnant Macaques

Zika virus (ZIKV) infection of pregnant women is associated with pathologic complications of fetal development. Here, we infect pregnant rhesus macaques (Macaca mulatta) with a minimally passaged ZIKV isolate from Rio de Janeiro, where a high rate of fetal development complications was observed. The infection of pregnant macaques with this virus results in maternal viremia, virus crossing into the amniotic fluid (AF), and in utero fetal deaths. We also treated three additional ZIKV-infected pregnant macaques with a cocktail of ZIKV-neutralizing human monoclonal antibodies (nmAbs) at peak viremia. While the nmAbs can be effective in clearing the virus from the maternal sera of treated monkeys, it is not sufficient to clear ZIKV from AF. Our report suggests that ZIKV from Brazil causes fetal demise in non-human primates (NHPs) without additional mutations or confounding co-factors. Treatment with a neutralizing anti-ZIKV nmAb cocktail is insufficient to fully stop vertical transmission

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

The state of the Martian climate

60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes