The human kidney is composed of roughly 1.2-million renal tubules that must maintain their tubular structure to function properly. In autosomal dominant polycystic kidney disease (ADPKD) cysts develop from renal tubules and enlarge independently, in a process that ultimately causes renal failure in 50% of affected individuals. Mutations in either PKD1 or PKD2 are associated with ADPKD but the function of these genes is unknown. PKD1 is thought to encode a membrane protein, polycystin-1, involved in cell-cell or cell-matrix interactions, whereas the PKD2 gene product, polycystin-2, is thought to be a channel protein. Here we show that polycystin-1 and -2 interact to produce new calcium-permeable non-selective cation currents. Neither polycystin-1 nor -2 alone is capable of producing currents. Moreover, disease-associated mutant forms of either polycystin protein that are incapable of heterodimerization do not result in new channel activity. We also show that polycystin-2 is localized in the cell in the absence of polycystin-1, but is translocated to the plasma membrane in its presence. Thus, polycystin-1 and -2 co-assemble at the plasma membrane to produce a new channel and to regulate renal tubular morphology and function.

Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, has raised concerns about the reliability of this technology. The MicroArray Quality Control (MAQC) project was initiated to address these concerns, as well as other performance and data analysis issues. Expression data on four titration pools from two distinct reference RNA samples were generated at multiple test sites using a variety of microarray-based and alternative technology platforms. Here we describe the experimental design and probe mapping efforts behind the MAQC project. We show intraplatform consistency across test sites as well as a high level of interplatform concordance in terms of genes identified as differentially expressed. This study provides a resource that represents an important first step toward establishing a framework for the use of microarrays in clinical and regulatory settings.

NY-ESO-1 is a "cancer-testis" antigen frequently expressed in epithelial ovarian cancer (EOC) and is among the most immunogenic tumor antigens defined to date. In an effort to understand in vivo tolerance mechanisms, we assessed the phenotype and function of NY-ESO-1-specific CD8 + T cells derived from peripheral blood lymphocytes (PBLs), tumor-infiltrating lymphocytes (TILs), and tumorassociated lymphocytes (TALs) of EOC patients with NY-ESO-1-expressing tumors, with or without humoral immunity to NY-ESO-1. Whereas NY-ESO-1-specific CD8 + T cells were readily detectable ex vivo with tetramers in TILs and TALs of seropositive patients, they were only detectable in PBLs following in vitro stimulation. Compared with PBLs, tumor-derived NY-ESO-1-specific CD8 + T cells demonstrated impaired effector function, preferential usage of dominant T-cell receptor, and enriched coexpression of inhibitory molecules LAG-3 and PD-1. Expression of LAG-3 and PD-1 on CD8 + T cells was up-regulated by IL-10, IL-6 (cytokines found in tumor ascites), and tumor-derived antigen-presenting cells. Functionally, CD8 + LAG-3 + PD-1 + T cells were more impaired in IFN-γ/TNF-α production compared with LAG-3 + PD-1 − or LAG-3 − PD-1 − subsets. Dual blockade of LAG-3 and PD-1 during T-cell priming efficiently augmented proliferation and cytokine production by NY-ESO-1-specific CD8 + T cells, indicating that antitumor function of NY-ESO-1-specific CD8 + T cells could potentially be improved by therapeutic targeting of these inhibitory receptors.tumor-infiltrating lymphocytes | IL-6 | IL-10 | T cell receptor T he presence of tumor-infiltrating lymphocytes within the tumor microenvironment is considered to be an indication of the host immune response to tumor antigens and is thought to reflect the dynamic process of "cancer immunoediting" (1). In epithelial ovarian cancer (EOC), support for the role of immune surveillance of tumors comes from observations indicating that the presence of intraepithelial CD8 + -infiltrating T lymphocytes in tumors is associated with improved survival of patients with the disease (2). Although several lines of evidence have shown that spontaneous or vaccine-induced tumor-antigen-specific CD8 + T cells can recognize EOC targets (3), prolongation of survival in patients treated with immunization has only rarely been observed. This is probably a reflection of several in vivo immunosuppressive mechanisms in EOC-bearing hosts (4). Therefore, understanding factors that regulate the function(s) of tumor-antigen-specific CD8 + T cells is critical for effective control of tumor recurrence.The NY-ESO-1 tumor antigen is a major target of CD8 + T cell recognition in EOC, eliciting both cellular and humoral immune responses in a proportion of patients with advanced NY-ESO-1-expressing tumors (5). However, similar to infectious disease models, chronic antigenic stimulation may result in exhaustion of antigen-specific CD8 + T cells (6) and loss of ability to produce key cytokines that are critical for the maintenance of CD8 + T ce...

During epidemics, healthcare institutions have a duty to protect HCWs and help them cope with their personal fears and the very stressful work situation. Singapore's experience shows that simple protective measures based on sound epidemiological principles, when implemented in a timely manner, go a long way to reassure HCWs.

With the recent advent of 4G LTE networks, there has been increasing interest to better understand the performance and power characteristics, compared with 3G/WiFi networks. In this paper, we take one of the first steps in this direction.Using a publicly deployed tool we designed for Android called 4GTest attracting more than 3000 users within 2 months and extensive local experiments, we study the network performance of LTE networks and compare with other types of mobile networks. We observe LTE generally has significantly higher downlink and uplink throughput than 3G and even WiFi, with a median value of 13Mbps and 6Mbps, respectively. We develop the first empirically derived comprehensive power model of a commercial LTE network with less than 6% error rate and state transitions matching the specifications. Using a comprehensive data set consisting of 5-month traces of 20 smartphone users, we carefully investigate the energy usage in 3G, LTE, and WiFi networks and evaluate the impact of configuring LTE-related parameters. Despite several new power saving improvements, we find that LTE is as much as 23 times less power efficient compared with WiFi, and even less power efficient than 3G, based on the user traces and the long high power tail is found to be a key contributor. In addition, we perform case studies of several popular applications on Android in LTE and identify that the performance bottleneck for web-based applications lies less in the network, compared to our previous study in 3G [24]. Instead, the device's processing power, despite the significant improvement compared to our analysis two years ago, becomes more of a bottleneck.

West Nile virus (WNV), and related flaviviruses such as tick-borne encephalitis, Japanese encephalitis, yellow fever and dengue viruses, constitute a significant global human health problem1. However, our understanding of the molecular interaction of WNV (and related flaviviruses) with mammalian host cells is limited1. WNV encodes only 10 proteins, implying that the virus may use many cellular proteins for infection1. WNV enters the cytoplasm through pHdependent endocytosis, undergoes cycles of translation and replication, assembles progeny virions in association with endoplasmic reticulum, and exits along the secretory pathway1 -3. RNAinterference (RNAi) presents a powerful forward genetics approach to dissect virus-host cell interactions4 -6. Here we report the identification of 305 host proteins impacting WNV infection,

Autosomal dominant polycystic kidney disease (ADPKD) describes a group of at least three genetically distinct disorders with almost identical clinical features that collectively affects 1:1,000 of the population. Affected individuals typically develop large cystic kidneys and approximately one half develop end-stage renal disease by their seventh decade. It has been suggested that the diseases result from defects in interactive factors involved in a common pathway. The recent discovery of the genes for the two most common forms of ADPKD has provided an opportunity to test this hypothesis. We describe a previously unrecognized coiled-coil domain within the C terminus of the PKD1 gene product, polycystin, and demonstrate that it binds specifically to the C terminus of PKD2. Homotypic interactions involving the C terminus of each are also demonstrated. We show that naturally occurring pathogenic mutations of PKD1 and PKD2 disrupt their associations. We have characterized the structural basis of their heterotypic interactions by deletional and site-specific mutagenesis. Our data suggest that PKD1 and PKD2 associate physically in vivo and may be partners of a common signalling cascade involved in tubular morphogenesis.

We present primary results from the Sequencing Quality Control (SEQC) project, coordinated by the United States Food and Drug Administration. Examining Illumina HiSeq, Life Technologies SOLiD and Roche 454 platforms at multiple laboratory sites using reference RNA samples with built-in controls, we assess RNA sequencing (RNA-seq) performance for junction discovery and differential expression profiling and compare it to microarray and quantitative PCR (qPCR) data using complementary metrics. At all sequencing depths, we discover unannotated exon-exon junctions, with >80% validated by qPCR. We find that measurements of relative expression are accurate and reproducible across sites and platforms if specific filters are used. In contrast, RNA-seq and microarrays do not provide accurate absolute measurements, and gene-specific biases are observed, for these and qPCR. Measurement performance depends on the platform and data analysis pipeline, and variation is large for transcript-level profiling. The complete SEQC data sets, comprising >100 billion reads (10Tb), provide unique resources for evaluating RNA-seq analyses for clinical and regulatory settings.