Immunization with Dendritic Cells Pulsed ex vivo with Recombinant Chlamydial Protease-Like Activity Factor Induces Protective Immunity Against Genital Chlamydia muridarum Challenge

We have shown that immunization with soluble recombinant chlamydial protease-like activity factor (rCPAF) and a T helper 1 type adjuvant can induce significantly enhanced bacterial clearance and protection against Chlamydia-induced pathological sequelae in the genital tract. In this study, we investigated the use of bone marrow derived dendritic cells (BMDCs) pulsed ex vivo with rCPAF + CpG in an adoptive subcutaneous immunization for the ability to induce protective immunity against genital chlamydial infection. We found that BMDCs pulsed with rCPAF + CpG efficiently up-regulated the expression of activation markers CD86, CD80, CD40, and major histocompatibility complex class II (MHC II), and secreted interleukin-12, but not IL-10 and IL-4. Mice adoptively immunized with rCPAF + CpG-pulsed BMDCs or UV-EB + CpG-pulsed BMDCs produced elevated levels of antigen-specific IFN-γ and enhanced IgG1 and IgG2a antibodies. Moreover, mice immunized with rCPAF + CpG-pulsed BMDCs or UV-EB + CpG-pulsed BMDCs exhibited significantly reduced genital Chlamydia shedding, accelerated resolution of infection, and reduced oviduct pathology when compared to infected mock-immunized animals. These results suggest that adoptive subcutaneous immunization with ex vivo rCPAF-pulsed BMDCs is an effective approach, comparable to that induced by UV-EB–BMDCs, for inducing robust anti-Chlamydia immunity

Gravitational quasinormal modes for Anti-de Sitter black holes

Quasinormal mode spectra for gravitational perturbations of black holes in four dimensional de Sitter and anti-de Sitter space are investigated. The anti-de Sitter case is relevant to the ADS-CFT correspondence in superstring theory. The ADS-CFT correspondence suggests a prefered set of boundary conditions.Comment: 12 pages, 6 figures in ReVTe

Time on androgen deprivation therapy and adaptations to exercise: secondary analysis from a 12-month randomized controlled trial in men with prostate cancer

Objectives To explore if duration of previous exposure to androgen deprivation therapy (ADT) in men with prostate cancer (PCa) undertaking a year-long exercise programme moderates the exercise response with regard to body composition and muscle performance, and also to explore the moderator effects of baseline testosterone, time since ADT, and baseline value of the outcome. Patients and Methods In a multicentre randomized controlled trial, 100 men who had previously undergone either 6 months (short-term) or 18 months (long-term) of ADT in combination with radiotherapy, as part of the TROG 03.04 RADAR trial, were randomized to 6 months supervised exercise, followed by a 6-month home-based maintenance programme, or to printed physical activity educational material for 12 months across 13 university-affiliated exercise clinics in Australia and New Zealand. The participants were long-term survivors of PCa with a mean age of 71.7 ± 6.4 years, and were assessed for lower extremity performance (repeated chair rise), with a subset of men (n = 57) undergoing additional measures for upper and lower body muscle strength and body composition (lean mass, fat mass, appendicular skeletal muscle [ASM]) by dual X-ray absorptiometry. Data were analysed using generalized estimating equations. Results Time on ADT significantly moderated the exercise effects on chair rise (βinteraction = −1.3 s, 95% confidence interval [CI] −2.6 to 0.0), whole-body lean mass (βinteraction = 1194 g, 95% CI 234 to 2153) and ASM mass (βinteraction = 562 g, 95% CI 49 to 1075), and approached significance for fat mass (βinteraction = −1107 g, 95% CI −2346 to 132), with greater benefits for men previously on long-term ADT. At 6 months, the intervention effects on chair rise time −1.5 s (95% CI −2.5 to −0.5), whole-body lean mass 824 g (95% CI 8 to 1640), ASM mass 709 g (95% CI 260 to 1158), and fat mass −1377 g (95% CI −2156 to −598) were significant for men previously on long-term ADT, but not for men on short-term ADT. At 12 months, the intervention effects for men on long-term ADT remained significant for the chair rise, with improved performance (−2.0 s, 95% CI −3.0 to −1.0) and increased ASM (537 g, 95% CI 153 to 921). Time on ADT did not moderate the exercise effects on muscle strength, nor did time since ADT cessation moderate any intervention effects. Similarly, testosterone and baseline values of the outcome had negligible moderator effects. Conclusions Men with PCa previously treated long-term with ADT respond more favourably to exercise in terms of lower body muscle performance and body composition (lean and fat mass, and ASM) than those with short-term ADT exposure. As a result, men who were formerly on long-term androgen suppression regimens should be especially prescribed exercise medicine interventions to alleviate residual treatment-related adverse effects

Mitochondrial metabolism of sexual and asexual blood stages of the malaria parasite Plasmodium falciparum

BACKGROUND: The carbon metabolism of the blood stages of Plasmodium falciparum, comprising rapidly dividing asexual stages and non-dividing gametocytes, is thought to be highly streamlined, with glycolysis providing most of the cellular ATP. However, these parasitic stages express all the enzymes needed for a canonical mitochondrial tricarboxylic acid (TCA) cycle, and it was recently proposed that they may catabolize glutamine via an atypical branched TCA cycle. Whether these stages catabolize glucose in the TCA cycle and what is the functional significance of mitochondrial metabolism remains unresolved. RESULTS: We reassessed the central carbon metabolism of P. falciparum asexual and sexual blood stages, by metabolically labeling each stage with (13)C-glucose and (13)C-glutamine, and analyzing isotopic enrichment in key pathways using mass spectrometry. In contrast to previous findings, we found that carbon skeletons derived from both glucose and glutamine are catabolized in a canonical oxidative TCA cycle in both the asexual and sexual blood stages. Flux of glucose carbon skeletons into the TCA cycle is low in the asexual blood stages, with glutamine providing most of the carbon skeletons, but increases dramatically in the gametocyte stages. Increased glucose catabolism in the gametocyte TCA cycle was associated with increased glucose uptake, suggesting that the energy requirements of this stage are high. Significantly, whereas chemical inhibition of the TCA cycle had little effect on the growth or viability of asexual stages, inhibition of the gametocyte TCA cycle led to arrested development and death. CONCLUSIONS: Our metabolomics approach has allowed us to revise current models of P. falciparum carbon metabolism. In particular, we found that both asexual and sexual blood stages utilize a conventional TCA cycle to catabolize glucose and glutamine. Gametocyte differentiation is associated with a programmed remodeling of central carbon metabolism that may be required for parasite survival either before or after uptake by the mosquito vector. The increased sensitivity of gametocyte stages to TCA-cycle inhibitors provides a potential target for transmission-blocking drugs

Mannose-Containing Oligosaccharides of Non-Specific Human Secretory Immunoglobulin A Mediate Inhibition of Vibrio cholerae Biofilm Formation

The role of antigen-specific secretory IgA (SIgA) has been studied extensively, whereas there is a limited body of evidence regarding the contribution of non-specific SIgA to innate immune defenses against invading pathogens. In this study, we evaluated the effects of non-specific SIgA against infection with Vibrio cholerae O139 strain MO10 and biofilm formation. Seven day old infant mice deficient in IgA (IgA-/- mice) displayed significantly greater intestinal MO10 burden at 24 hr post-challenge when compared to IgA+/+ pups. Importantly, cross-fostering of IgA-/- pups with IgA+/+ nursing dams reversed the greater susceptibility to MO10 infection, suggesting a role for non-specific SIgA in protection against the infection. Since biofilm formation is associated with virulence of MO10, we further examined the role of human non-specific SIgA on this virulence phenotype of the pathogen. Human non-specific SIgA, in a dose-dependent fashion, significantly reduced the biofilm formation by MO10 without affecting the viability of the bacterium. Such an inhibitory effect was not induced by human serum IgA, IgG, or IgM, suggesting a role for the oligosaccharide-rich secretory component (SC) of SIgA. This was supported by the demonstration that SIgA treated with endoglycosidase H, to cleave the high-mannose containing terminal chitobiose residues, did not induce a reduction in biofilm formation by MO10. Furthermore, the addition of free mannose per se, across a wide dose range, induced significant reduction in MO10 biofilm formation. Collectively, these results suggest that mannose containing oligosacchardies within human non-specific secretory IgA can alter important virulence phenotypes of Vibrio cholerae such as biofilm formation, without affecting viability of the microorganism. Such effects may contribute significantly to innate immune defenses against invading pathogens in vivo in the gastrointestinal tract

A Mid-Infrared Census of Star Formation Activity in Bolocam Galactic Plane Survey Sources

We present the results of a search for mid-infrared signs of star formation activity in the 1.1 mm sources in the Bolocam Galactic Plane Survey (BGPS). We have correlated the BGPS catalog with available mid-IR Galactic plane catalogs based on the Spitzer Space Telescope GLIMPSE legacy survey and the Midcourse Space Experiment (MSX) Galactic plane survey. We find that 44% (3,712 of 8,358) of the BGPS sources contain at least one mid-IR source, including 2,457 of 5,067 (49%) within the area where all surveys overlap (10 deg < l < 65 deg). Accounting for chance alignments between the BGPS and mid-IR sources, we conservatively estimate that 20% of the BPGS sources within the area where all surveys overlap show signs of active star formation. We separate the BGPS sources into four groups based on their probability of star formation activity. Extended Green Objects (EGOs) and Red MSX Sources (RMS) make up the highest probability group, while the lowest probability group is comprised of "starless" BGPS sources which were not matched to any mid-IR sources. The mean 1.1 mm flux of each group increases with increasing probability of active star formation. We also find that the "starless" BGPS sources are the most compact, while the sources with the highest probability of star formation activity are on average more extended with large skirts of emission. A subsample of 280 BGPS sources with known distances demonstrates that mass and mean H_2 column density also increase with probability of star formation activity.Comment: 20 pages, 12 figures, 3 tables. Accepted for publication in ApJ. Full Table 2 will be available online through Ap

The Genetic Structure of Pacific Islanders

Human genetic diversity in the Pacific has not been adequately sampled, particularly in Melanesia. As a result, population relationships there have been open to debate. A genome scan of autosomal markers (687 microsatellites and 203 insertions/deletions) on 952 individuals from 41 Pacific populations now provides the basis for understanding the remarkable nature of Melanesian variation, and for a more accurate comparison of these Pacific populations with previously studied groups from other regions. It also shows how textured human population variation can be in particular circumstances. Genetic diversity within individual Pacific populations is shown to be very low, while differentiation among Melanesian groups is high. Melanesian differentiation varies not only between islands, but also by island size and topographical complexity. The greatest distinctions are among the isolated groups in large island interiors, which are also the most internally homogeneous. The pattern loosely tracks language distinctions. Papuan-speaking groups are the most differentiated, and Austronesian or Oceanic-speaking groups, which tend to live along the coastlines, are more intermixed. A small “Austronesian” genetic signature (always <20%) was detected in less than half the Melanesian groups that speak Austronesian languages, and is entirely lacking in Papuan-speaking groups. Although the Polynesians are also distinctive, they tend to cluster with Micronesians, Taiwan Aborigines, and East Asians, and not Melanesians. These findings contribute to a resolution to the debates over Polynesian origins and their past interactions with Melanesians. With regard to genetics, the earlier studies had heavily relied on the evidence from single locus mitochondrial DNA or Y chromosome variation. Neither of these provided an unequivocal signal of phylogenetic relations or population intermixture proportions in the Pacific. Our analysis indicates the ancestors of Polynesians moved through Melanesia relatively rapidly and only intermixed to a very modest degree with the indigenous populations there

Ferromagnetism in laser deposited anatase Ti1−x_{1-x}Cox_{x}O_{2-\delta} films

Pulsed laser deposited films of Co doped anatase TiO2 are examined for Co substitutionality, ferromagnetism, transport, magnetotransport and optical properties. Our results show limited solubility (up to ~ 2 %) of Co in the as-grown films and formation of Co clusters thereafter. For Ti0.93Co0.07O2-d sample, which exhibits a Curie temperature (Tc) over 1180 K, we find the presence of 20-50 nm Co clusters as well as a small concentration of Co incorporated into the remaining matrix. After being subjected to the high temperature anneal during the first magnetization measurement, the very same sample shows a Tc ~ 650 K and almost full matrix incorporation of Co. This Tc is close to that of as-grown Ti0.99Co0.01O2-d sample (~ 700 K). The transport, magnetotransport and optical studies also reveal interesting effects of the matrix incorporation of Co. These results are indicative of an intrinsic Ti1-xCoxO2-d diluted magnetic semiconductor with Tc of about 650-700 K.Comment: 14 pages + 9 figure

Indicators of soil quality - Physical properties (SP1611). Final report to Defra

The condition of soil determines its ability to carry out diverse and essential functions that support human health and wellbeing. These functions (or ecosystem goods and services) include producing food, storing water, carbon and nutrients, protecting our buried cultural heritage and providing a habitat for flora and fauna. Therefore, it is important to know the condition or quality of soil and how this changes over space and time in response to natural factors (such as changing weather patterns) or to land management practices. Meaningful soil quality indicators (SQIs), based on physical, biological or chemical soil properties are needed for the successful implementation of a soil monitoring programme in England and Wales. Soil monitoring can provide decision makers with important data to target, implement and evaluate policies aimed at safeguarding UK soil resources. Indeed, the absence of agreed and well-defined SQIs is likely to be a barrier to the development of soil protection policy and its subsequent implementation. This project assessed whether physical soil properties can be used to indicate the quality of soil in terms of its capacity to deliver ecosystem goods and services. The 22 direct (e.g. bulk density) and 4 indirect (e.g. catchment hydrograph) physical SQIs defined by Loveland and Thompson (2002) and subsequently evaluated by Merrington et al. (2006), were re-visited in the light of new scientific evidence, recent policy drivers and developments in sampling techniques and monitoring methodologies (Work Package 1). The culmination of these efforts resulted in 38 direct and 4 indirect soil physical properties being identified as potential SQIs. Based on the gathered evidence, a ‘logical sieve’ was used to assess the relative strengths, weaknesses and suitability of each potential physical SQI for national scale soil monitoring. Each soil physical property was scored in terms of: soil function – does the candidate SQI reflect all soil function(s)? land use - does the candidate SQI apply to all land uses found nationally? soil degradation - can the candidate SQI express soil degradation processes? does the candidate SQI meet the challenge criteria used by Merrington et al. (2006)?This approach enabled a consistent synthesis of available information and the semi-objective, semi-quantitative and transparent assessment of indicators against a series of scientific and technical criteria (Ritz et al., 2009; Black et al., 2008). The logical sieve was shown to be a flexible decision-support tool to assist a range of stakeholders with different agenda in formulating a prioritised list of potential physical SQIs. This was explored further by members of the soil science and soils policy community at a project workshop. By emphasising the current key policy-related soil functions (i.e. provisioning and regulating), the logical sieve was used to generate scores which were then ranked to identify the most qualified SQIs. The process selected 18 candidate physical SQIs. This list was further filtered to move from the ‘narrative’ to a more ‘numerical’ approach, in order to test the robustness of the candidate SQIs through statistical analysis and modelling (Work Package 2). The remaining 7 physical SQIs were: depth of soil; soil water retention characteristics; packing density; visual soil assessment / evaluation; rate of erosion; sealing; and aggregate stability. For these SQIs to be included in a robust national soil monitoring programme, we investigated the uncertainty in their measurement; the spatial and temporal variability in the indicator as given by observed distributions; and the expected rate of change in the indicator. Whilst a baseline is needed (i.e. the current state of soil), it is the rate of change in soil properties and the implications of that change in terms of soil processes and functioning that are key to effective soil monitoring. Where empirical evidence was available, power analysis was used to understand the variability of indicators as given by the observed distributions. This process determines the ability to detect a particular change in the SQI at a particular confidence level, given the ‘noise’ or variability in the data (i.e. a particular power to detect a change of ‘X’ at a confidence level of ‘Y%’ would require ‘N’ samples). However, the evidence base for analysing the candidate SQIs is poor: data are limited in spatial and temporal extent for England and Wales, in terms of a) the degree (magnitude) of change in the SQI which significantly affects soil processes and functions (i.e. ‘meaningful change’), and b) the change in the SQI that is detectable (i.e. what sample size is needed to detect the meaningful signal from the variability or noise in the signal). This constrains the design and implementation of a scientifically and statistically rigorous and reliable soil monitoring programme. Evidence that is available suggests that what constitutes meaningful change will depend on soil type, current soil state, land use and the soil function under consideration. However, when we tested this by analysing detectable changes in packing density and soil depth (because data were available for these SQIs) over different land covers and soil types, no relationships were found. Schipper and Sparling (2000) identify the challenge: “a standardised methodology may not be appropriate to apply across contrasting soils and land uses. However, it is not practical to optimise sampling and analytical techniques for each soil and land use for extensive sampling on a national scale”. Despite the paucity in data, all seven SQIs have direct relevance to current and likely future soil and environmental policy, because they can be related (qualitatively) to soil processes, soil functions and delivery of ecosystem goods and services. Even so, meaningful and detectable changes in physical SQIs may be out of time with any soil policy change and it is not usually possible to link particular changes in SQIs to particular policy activities. This presents challenges in ascertaining trends that can feed into policy development or be used to gauge the effectiveness of soil protection policies (Work Package 3). Of the seven candidate physical SQIs identified, soil depth and surface sealing are regarded by many as indicators of soil quantity rather than quality. Visual soil evaluation is currently not suited to soil monitoring in the strictest sense, as its semi-qualitative basis cannot be analysed statistically. Also, few data exist on how visual evaluation scores relate to soil functions. However, some studies have begun to investigate how VSE might be moved to a more quantified scale and the method has some potential as a low cost field technique to assess soil condition. Packing density requires data on bulk density and clay content, both of which are highly variable, so compounding the error term associated with this physical SQI. More evidence is needed to show how ‘meaningful’ change in aggregate stability affects soil processes and thus soil functions (for example, using the limited data available, an equivocal relationship was found with water regulation / runoff generation). The analysis of available data has given promising results regarding the prediction of soil water retention characteristics and packing density from relatively easy to measure soil properties (bulk density, texture and organic C) using pedotransfer functions. Expanding the evidence base is possible with the development of rapid, cost-effective techniques such as NIR sensors to measure soil properties. Defra project SP1303 (Brazier et al., 2012) used power analyses to estimate the number of monitoring locations required to detect a statistically significant change in soil erosion rate on cultivated land. However, what constitutes a meaningful change in erosion rates still requires data on the impacts of erosion on soil functions. Priority cannot be given amongst the seven SQIs, because the evidence base for each varies in its robustness and extent. Lack of data (including uncertainty in measurement and variability in observed distributions) applies to individual SQIs; attempts at integrating more than one SQI (including physical, biological and chemical SQIs) to improve associations between soil properties and processes / functions are only likely to propagate errors. Whether existing monitoring programmes can be adapted to incorporate additional measurement of physical SQIs was explored. We considered options where one or more of the candidate physical SQIs might be implemented into soil monitoring programmes (e.g. as a new national monitoring scheme; as part of the Countryside Survey; and as part of the National Soil Inventory). The challenge is to decide whether carrying out soil monitoring that is not statistically robust is still valuable in answering questions regarding current and future soil quality. The relationship between physical (and other) SQIs, soil processes and soil functions is complex, as is how this influences ecosystem services’ delivery. Important gaps remain in even the realisation of a conceptual model for these inter-relationships, let alone their quantification. There is also a question of whether individual quantitative SQIs can be related to ecosystem services, given the number of variables