An extended regression approach to estimating loads and their uncertainties in Great Barrier Reef catchments

There are numerous load estimation methods available, some of which are captured in various online tools. However, most estimators are subject to large biases statistically, and their associated uncertainties are often not reported. This makes interpretation difficult and the estimation of trends or determination of optimal sampling regimes impossible to assess. In this paper, we first propose two indices for measuring the extent of sampling bias, and then provide steps for obtaining reliable load estimates by minimizing the biases and making use of possible predictive variables. The load estimation procedure can be summarized by the following four steps: - (i) output the flow rates at regular time intervals (e.g. 10 minutes) using a time series model that captures all the peak flows; - (ii) output the predicted flow rates as in (i) at the concentration sampling times, if the corresponding flow rates are not collected; - (iii) establish a predictive model for the concentration data, which incorporates all possible predictor variables and output the predicted concentrations at the regular time intervals as in (i), and; - (iv) obtain the sum of all the products of the predicted flow and the predicted concentration over the regular time intervals to represent an estimate of the load. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized regression (rating-curve) approach with additional predictors that capture unique features in the flow data, namely the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and cumulative discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. The model also has the capacity to accommodate autocorrelation in model errors which are the result of intensive sampling during floods. Incorporating this additional information can significantly improve the predictability of concentration, and ultimately the precision with which the pollutant load is estimated. We also provide a measure of the standard error of the load estimate which incorporates model, spatial and/or temporal errors. This method also has the capacity to incorporate measurement error incurred through the sampling of flow. We illustrate this approach using the concentrations of total suspended sediment (TSS) and nitrogen oxide (NOx) and gauged flow data from the Burdekin River, a catchment delivering to the Great Barrier Reef. The sampling biases for NOx concentrations range from 2 to 10 times indicating severe biases. As we expect, the traditional average and extrapolation methods produce much higher estimates than those when bias in sampling is taken into account.

Infection-induced IL-10 and Jak-Stat: A review of the molecular circuitry controlling immune hyperactivity in response to pathogenic microbes

Generation of effective immune responses against pathogenic microbes depends on a fine balance between pro- and anti-inflammatory responses. Interleukin-10 (IL-10) is essential in regulating this balance and has garnered renewed interest recently as a modulator of the response to infection at the JAK-STAT signaling axis of host responses. Here, we examine how IL-10 functions as the “master regulator” of immune responses through JAK-STAT, and provide a perspective from recent insights on bacterial, protozoan, and viral infection model systems. Pattern recognition and subsequent molecular events that drive activation of IL-10-associated JAK-STAT circuitry are reviewed and the implications for microbial pathogenesis are discussed.

Meta-analyses identify 13 loci associated with age at menopause and highlight DNA repair and immune pathways

To newly identify loci for age at natural menopause, we carried out a meta-analysis of 22 genome-wide association studies (GWAS) in 38,968 women of European descent, with replication in up to 14,435 women. In addition to four known loci, we identified 13 loci newly associated with age at natural menopause (at P < 5 x 10(-8)). Candidate genes located at these newly associated loci include genes implicated in DNA repair (EXO1, HELQ, UIMC1, FAM175A, FANCI, TLK1, POLG and PRIM1) and immune function (IL11, NLRP11 and PRRC2A (also known as BAT2)). Gene-set enrichment pathway analyses using the full GWAS data set identified exoDNase, NF-kappaB signaling and mitochondrial dysfunction as biological processes related to timing of menopause.

Quantitative Trait Loci for CD4:CD8 Lymphocyte Ratio Are Associated with Risk of Type 1 Diabetes and HIV-1 Immune Control

Abnormal expansion or depletion of particular lymphocyte subsets is associated with clinical manifestations such as HIV progression to AIDS and autoimmune disease. We sought to identify genetic predictors of lymphocyte levels and reasoned that these may play a role in immune-related diseases. We tested 2.3 million variants for association with five lymphocyte subsets, measured in 2538 individuals from the general population, including CD4+ T cells, CD8+ T cells, CD56+ natural killer (NK) cells, and the derived measure CD4:CD8 ratio. We identified two regions of strong association. The first was located in the major histocompatibility complex (MHC), with multiple SNPs strongly associated with CD4:CD8 ratio (rs2524054, p = 2.1 × 10−28). The second region was centered within a cluster of genes from the Schlafen family and was associated with NK cell levels (rs1838149, p = 6.1 × 10−14). The MHC association with CD4:CD8 replicated convincingly (p = 1.4 × 10−9) in an independent panel of 988 individuals. Conditional analyses indicate that there are two major independent quantitative trait loci (QTL) in the MHC region that regulate CD4:CD8 ratio: one is located in the class I cluster and influences CD8 levels, whereas the second is located in the class II cluster and regulates CD4 levels. Jointly, both QTL explained 8% of the variance in CD4:CD8 ratio. The class I variants are also strongly associated with durable host control of HIV, and class II variants are associated with type-1 diabetes, suggesting that genetic variation at the MHC may predispose one to immune-related diseases partly through disregulation of T cell homeostasis.

Combined effect of double antireflection coating and reversible molecular doping on performance of few-layer graphene/n-silicon Schottky barrier solar cells

Few-layer graphene films were grown by chemical vapor deposition and transferred onto n-type crystalline silicon wafers to fabricate graphene/n-silicon Schottky barrier solar cells. In order to increase the power conversion efficiency of such cells the graphene films were doped with nitric acid vapor and an antireflection treatment was implemented to reduce the sunlight reflection on the top of the device. The doping process increased the work function of the graphene film and had a beneficial effect on its conductivity. The deposition of a double antireflection coating led to an external quantum efficiency up to 90% across the visible and near infrared region, the highest ever reported for this type of devices. The combined effect of graphene doping and antireflection treatment allowed to reach a power conversion efficiency of 8.5% exceeding the pristine (undoped and uncoated) device performance by a factor of 4. The optical properties of the antireflection coating were found to be not affected by the exposure to nitric acid vapor and to remain stable over time.

Ratios of T-cell immune-effectors with tumour associated macrophages and PD-1/PD-L1 axis immune-checkpoint molecules, as prognosticators in diffuse large B cell lymphoma: A population-based study

Background Risk-stratification of diffuse large B-cell lymphoma (DLBCL) requires identification of patients with disease that is not cured despite initial R-CHOP. Although the prognostic importance of the tumour microenvironment (TME) is established, the optimal strategy to quantify it is unknown. Methods The relationship between immune-effector and inhibitory (checkpoint) genes was assessed by NanoString™ in 252 paraffin-embedded DLBCL tissues. A model to quantify net anti-tumoural immunity as an outcome predictor was tested in 158 R-CHOP treated patients, and validated in tissue/blood from two independent R-CHOP treated cohorts of 233 and 140 patients respectively. Findings T and NK-cell immune-effector molecule expression correlated with tumour associated macrophage and PD-1/PD-L1 axis markers consistent with malignant B-cells triggering a dynamic checkpoint response to adapt to and evade immune-surveillance. A tree-based survival model was performed to test if immune-effector to checkpoint ratios were prognostic. The CD4*CD8:(CD163/CD68)*PD-L1 ratio was better able to stratify overall survival than any single or combination of immune markers, distinguishing groups with disparate 4-year survivals (92% versus 47%). The immune ratio was independent of and added to the revised international prognostic index (R-IPI) and cell-of-origin (COO). Tissue findings were validated in 233 DLBCL R-CHOP treated patients. Furthermore, within the blood of 140 R-CHOP treated patients immune-effector:checkpoint ratios were associated with differential interim-PET/CT+ve/-ve expression.

Chlamydial infertility in women: Diagnosis, epidemiology and immune response

This project primarily focused on the development of a novel, non-invasive peptide-based ELISA to diagnose C. trachomatis-related infertility in women. In this study, an in silico approach was applied to identify and design novel peptide antigens that are specific to women with C. trachomatis-related infertility. The serological assay was developed such that it could potentially replace invasive techniques for early infertility investigation. The thesis further investigated the sero-prevalence of chlamydial infertility in women from a low-resource, high prevalence setting. In addition, the thesis also identified immune markers that were associated with the C. trachomatis-related infertility in women.

Dimethyl sulfide and other biogenic volatile organic compound emissions from branching coral and reef seawater: Potential sources of secondary aerosol over the Great Barrier Reef

Volatile organic compounds (VOCs) in the headspace of bubble chambers containing branches of live coral in filtered reef seawater were analysed using gas chromatography with mass spectrometry (GC-MS). When the coral released mucus it was a source of dimethyl sulfide (DMS) and isoprene; however, these VOCs were not emitted to the chamber headspace from mucus-free coral. This finding, which suggests that coral is an intermittent source of DMS and isoprene, was supported by the observation of occasional large pulses of atmospheric DMS (DMSa) over Heron Island reef on the southern Great Barrier Reef (GBR), Australia, in the austral winter. The highest DMSa pulse (320 ppt) was three orders of magnitude less than the DMS mixing ratio (460 ppb) measured in the headspace of a dynamically purged bubble chamber containing a mucus-coated branch of Acropora aspera indicating that coral reefs can be strong point sources of DMSa. Static headspace GC-MS analysis of coral fragments identified mainly DMS and seven other minor reduced sulfur compounds including dimethyl disulfide, methyl mercaptan, and carbon disulfide, while coral reef seawater was an indicated source of methylene chloride, acetone, and methyl ethyl ketone. The VOCs emitted by coral and reef seawater are capable of producing new atmospheric particles < 15 nm diameter as observed at Heron Island reef. DMS and isoprene are known to play a role in low-level cloud formation, so aerosol precursors such as these could influence regional climate through a sea surface temperature regulation mechanism hypothesized to operate over the GBR.

Stimulating immune responses to fight cancer: Basic biology and mechanisms

Chronic inflammation is now recognized as a major cause of malignant disease. In concert with various mechanisms (including DNA instability), hypoxia and activation of inflammatory bioactive lipid pathways and pro-inflammatory cytokines open the doorway to malignant transformation and proliferation, angiogenesis, and metastasis in many cancers. A balance between stimulatory and inhibitory signals regulates the immune response to cancer. These include inhibitory checkpoints that modulate the extent and duration of the immune response and may be activated by tumor cells. This contributes to immune resistance, especially against tumor antigen-specific T-cells. Targeting these checkpoints is an evolving approach to cancer immunotherapy, designed to foster an immune response. The current focus of these trials is on the programmed cell death protein 1 (PD-1) receptor and its ligands (PD-L1, PD-L2) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4). Researchers have developed anti-PD-1 and anti-PDL-1 antibodies that interfere with the ligands and receptor and allow the tumor cell to be recognized and attacked by tumor-infiltrating T-cells. These are currently being studied in lung cancer. Likewise, CTLA-4 inhibitors, which have had success treating advanced melanoma, are being studied in lung cancer with encouraging results.