Macrophages and small extracellular vesicle mediated-intracellular communication in the peritoneal microenvironment: impact on endometriosis development

Endometriosis is an inflammatory disease that is defined as the growth of endometrium-like tissue outside the uterus, commonly on the lining of the pelvic cavity, visceral organs and in the ovaries. It affects around 190 million women of reproductive age worldwide and is associated with chronic pelvic pain and infertility, which greatly impairs health-related life quality. The symptoms of the disease are variable, this combined with a lack of diagnostic biomarkers and necessity of surgical visualisation to confirm disease, the prognosis can take an average timespan of 6–8 years. Accurate non-invasive diagnostic tests and the identification of effective therapeutic targets are essential for disease management. To achieve this, one of the priorities is to define the underlying pathophysiological mechanisms that contribute to endometriosis. Recently, immune dysregulation in the peritoneal cavity has been linked to endometriosis progression. Macrophages account for over 50% of immune cells in the peritoneal fluid and are critical for lesion growth, angiogenesis, innervation and immune regulation. Apart from the secretion of soluble factors like cytokines and chemokines, macrophages can communicate with other cells and prime disease microenvironments, such as the tumour microenvironment, via the secretion of small extracellular vesicles (sEVs). The sEV-mediated intracellular communication pathways between macrophages and other cells within the peritoneal microenvironment in endometriosis remain unclear. Here, we give an overview of peritoneal macrophage (pMΦ) phenotypes in endometriosis and discuss the role of sEVs in the intracellular communication within disease microenvironments and the impact they may have on endometriosis progression

Cross-correlation Weak Lensing of SDSS galaxy Clusters II: Cluster Density Profiles and the Mass--Richness Relation

We interpret and model the statistical weak lensing measurements around 130,000 groups and clusters of galaxies in the Sloan Digital Sky Survey presented by Sheldon et al. 2007 (Paper I). We present non-parametric inversions of the 2D shear profiles to the mean 3D cluster density and mass profiles in bins of both optical richness and cluster i-band luminosity. We correct the inferred 3D profiles for systematic effects, including non-linear shear and the fact that cluster halos are not all precisely centered on their brightest galaxies. We also model the measured cluster shear profile as a sum of contributions from the brightest central galaxy, the cluster dark matter halo, and neighboring halos. We infer the relations between mean cluster virial mass and optical richness and luminosity over two orders of magnitude in cluster mass; the virial mass at fixed richness or luminosity is determined with a precision of 13% including both statistical and systematic errors. We also constrain the halo concentration parameter and halo bias as a function of cluster mass; both are in good agreement with predictions of LCDM models. The methods employed here will be applicable to deeper, wide-area optical surveys that aim to constrain the nature of the dark energy, such as the Dark Energy Survey, the Large Synoptic Survey Telescope and space-based surveys

The problem of scale in the prediction and management of pathogen spillover

Disease emergence events, epidemics and pandemics all underscore the need to predict zoonotic pathogen spillover. Because cross-species transmission is inherently hierarchical, involving processes that occur at varying levels of biological organization, such predictive efforts can be complicated by the many scales and vastness of data potentially required for forecasting. A wide range of approaches are currently used to forecast spillover risk (e.g. macroecology, pathogen discovery, surveillance of human populations, among others), each of which is bound within particular phylogenetic, spatial and temporal scales of prediction. Here, we contextualize these diverse approaches within their forecasting goals and resulting scales of prediction to illustrate critical areas of conceptual and pragmatic overlap. Specifically, we focus on an ecological perspective to envision a research pipeline that connects these different scales of data and predictions from the aims of discovery to intervention. Pathogen discovery and predictions focused at the phylogenetic scale can first provide coarse and pattern-based guidance for which reservoirs, vectors and pathogens are likely to be involved in spillover, thereby narrowing surveillance targets and where such efforts should be conducted. Next, these predictions can be followed with ecologically driven spatio-temporal studies of reservoirs and vectors to quantify spatio-temporal fluctuations in infection and to mechanistically understand how pathogens circulate and are transmitted to humans. This approach can also help identify general regions and periods for which spillover is most likely. We illustrate this point by highlighting several case studies where long-term, ecologically focused studies (e.g. Lyme disease in the northeast USA, Hendra virus in eastern Australia, Plasmodium knowlesi in Southeast Asia) have facilitated predicting spillover in space and time and facilitated the design of possible intervention strategies. Such studies can in turn help narrow human surveillance efforts and help refine and improve future large-scale, phylogenetic predictions. We conclude by discussing how greater integration and exchange between data and predictions generated across these varying scales could ultimately help generate more actionable forecasts and interventions

Tumour Suppressor Genes with Oncogenic Roles in Lung Cancer

Lung cancer is one of the most common cancers and the leading cause of cancer-related deaths worldwide. High-throughput sequencing efforts have uncovered the molecular heterogeneity of this disease, unveiling several genetic and epigenetic disruptions driving its development. Unlike oncogenes, tumour suppressor genes negatively regulate cell cycle control and exhibit loss-of-function alterations in cancer. Although tumour suppressor genes are more frequently disrupted, oncogenes are more likely to be drug-targeted. Many genes are described as presenting both tumour suppressive and oncogenic functions in different tumour types or even within the natural history of the disease in a single tumour. In this chapter, we describe current knowledge of tumour suppressor genes in lung tissues, focusing on tumour suppressor/oncogene duality

Dynamic and integrative approaches to understanding pathogen spillover

No abstract available

Links from mantle to microbe at the Lau Integrated Study Site : insights from a back-arc spreading center

Author Posting. © The Oceanography Society, 2012. This article is posted here by permission of The Oceanography Society for personal use, not for redistribution. The definitive version was published in Oceanography 25, no. 1 (2012): 62–77, doi:10.5670/oceanog.2012.04.The Lau Integrated Study Site (ISS) has provided unique opportunities for study of ridge processes because of its back-arc setting in the southwestern Pacific. Its location allows study of a biogeographical province distinct from those of eastern Pacific and mid-Atlantic ridges, and crustal compositions along the ridge lie outside the range of mid-ocean ridge crustal compositions. The Lau ISS is located above a subduction zone, at an oblique angle. The underlying mantle receives water and other elements derived from the downgoing lithospheric slab, with an increase in slab influence from north to south. Water lowers the mantle melting temperature and leads to greater melt production where the water flux is greater, and to distinctive regional-scale gradients along the ridge. There are deeper faulted axial valleys with basaltic volcanism in the north and inflated axial highs with andesites in the south. Differences in igneous rock composition and release of magmatic volatiles affect compositions of vent fluids and deposits. Differences in vent fluid compositions and small-scale diffuse-flow regimes correlate with regional-scale patterns in microbial and megafaunal distributions. The interdisciplinary research effort at the Lau ISS has successfully identified linkages between subsurface processes and deep-sea biological communities, from mantle to microbe to megafauna.Support was provided by National Science Foundation grants OCE-1038135 to MKT, OCE-0732369 and OCE-0240985 to CRF, OCE-0732369 and OCE-0838107 to PRG, OCE-0242618 to CHL, OCE-0242902 and OCE-0752256 to PJM, OCE-0728391 and OCE-0937404 to A-LR, and a GRFP to RB

Cosmological Constraints from the SDSS maxBCG Cluster Catalog

We use the abundance and weak lensing mass measurements of the SDSS maxBCG cluster catalog to simultaneously constrain cosmology and the richness--mass relation of the clusters. Assuming a flat \LambdaCDM cosmology, we find \sigma_8(\Omega_m/0.25)^{0.41} = 0.832\pm 0.033 after marginalization over all systematics. In common with previous studies, our error budget is dominated by systematic uncertainties, the primary two being the absolute mass scale of the weak lensing masses of the maxBCG clusters, and uncertainty in the scatter of the richness--mass relation. Our constraints are fully consistent with the WMAP five-year data, and in a joint analysis we find \sigma_8=0.807\pm 0.020 and \Omega_m=0.265\pm 0.016, an improvement of nearly a factor of two relative to WMAP5 alone. Our results are also in excellent agreement with and comparable in precision to the latest cosmological constraints from X-ray cluster abundances. The remarkable consistency among these results demonstrates that cluster abundance constraints are not only tight but also robust, and highlight the power of optically-selected cluster samples to produce precision constraints on cosmological parameters.Comment: comments welcom

Precision Measurements of the Cluster Red Sequence using an Error Corrected Gaussian Mixture Model

The red sequence is an important feature of galaxy clusters and plays a crucial role in optical cluster detection. Measurement of the slope and scatter of the red sequence are affected both by selection of red sequence galaxies and measurement errors. In this paper, we describe a new error corrected Gaussian Mixture Model for red sequence galaxy identification. Using this technique, we can remove the effects of measurement error and extract unbiased information about the intrinsic properties of the red sequence. We use this method to select red sequence galaxies in each of the 13,823 clusters in the maxBCG catalog, and measure the red sequence ridgeline location and scatter of each. These measurements provide precise constraints on the variation of the average red galaxy populations in the observed frame with redshift. We find that the scatter of the red sequence ridgeline increases mildly with redshift, and that the slope decreases with redshift. We also observe that the slope does not strongly depend on cluster richness. Using similar methods, we show that this behavior is mirrored in a spectroscopic sample of field galaxies, further emphasizing that ridgeline properties are independent of environment.Comment: 33 pages, 14 Figures; A typo in Eq.A11 is fixed. The C++/Python codes for ECGMM can be downloaded from: https://sites.google.com/site/jiangangecgmm

Development, Calibration and Performance of an HIV Transmission Model Incorporating Natural History and Behavioral Patterns: Application in South Africa

Understanding HIV transmission dynamics is critical to estimating the potential population-wide impact of HIV prevention and treatment interventions. We developed an individual-based simulation model of the heterosexual HIV epidemic in South Africa and linked it to the previously published Cost-Effectiveness of Preventing AIDS Complications (CEPAC) International Model, which simulates the natural history and treatment of HIV. In this new model, the CEPAC Dynamic Model (CDM), the probability of HIV transmission per sexual encounter between short-term, long-term and commercial sex worker partners depends upon the HIV RNA and disease stage of the infected partner, condom use, and the circumcision status of the uninfected male partner. We included behavioral, demographic and biological values in the CDM and calibrated to HIV prevalence in South Africa pre-antiretroviral therapy. Using a multi-step fitting procedure based on Bayesian melding methodology, we performed 264,225 simulations of the HIV epidemic in South Africa and identified 3,750 parameter sets that created an epidemic and had behavioral characteristics representative of a South African population pre-ART. Of these parameter sets, 564 contributed 90% of the likelihood weight to the fit, and closely reproduced the UNAIDS HIV prevalence curve in South Africa from 1990–2002. The calibration was sensitive to changes in the rate of formation of short-duration partnerships and to the partnership acquisition rate among high-risk individuals, both of which impacted concurrency. Runs that closely fit to historical HIV prevalence reflect diverse ranges for individual parameter values and predict a wide range of possible steady-state prevalence in the absence of interventions, illustrating the value of the calibration procedure and utility of the model for evaluating interventions. This model, which includes detailed behavioral patterns and HIV natural history, closely fits HIV prevalence estimates

The Sloan Digital Sky Survey Quasar Lens Search. II. Statistical lens sample from the third data release

We report the first results of our systematic search for strongly lensed quasars using the spectroscopically confirmed quasars in the Sloan Digital Sky Survey (SDSS). Among 46,420 quasars from the SDSS Data Release 3 (~4188 deg^2), we select a subsample of 22,683 quasars that are located at redshifts between 0.6 and 2.2 and are brighter than the Galactic extinction-corrected i-band magnitude of 19.1. We identify 220 lens candidates from the quasar subsample, for which we conduct extensive and systematic follow-up observations in optical and near-infrared wavebands, in order to construct a complete lensed quasar sample at image separations between 1" and 20" and flux ratios of faint to bright lensed images larger than 10^(−0.5). We construct a statistical sample of 11 lensed quasars. Ten of these are galaxy-scale lenses with small image separations (~ 1"-2") and one is a large separation (15") system which is produced by a massive cluster of galaxies, representing the first statistical sample of lensed quasars including both galaxy- and cluster-scale lenses. The Data Release 3 spectroscopic quasars contain an additional 11 lensed quasars outside the statistical sample