Malnutrition, gastroenteritis and trypsinogen concentration in hospitalised aboriginal children

Objective: To explore relationships between malnutrition and pancreatic damage in hospitalised aboriginal children. Methods: Immunoreactive trypsinogen (IRT) concentrations were measured in two populations of hospitalised aboriginal children in Australia; 472 children aged 0-3 years, in Alice Springs (Northern Territory); and 187 children aged 0-16 years in Mount Isa (Queensland). Correlation of whole blood IRT with height and weight z-scores, four-site skinfold thickness and upper arm circumference was sought. Results: In Mount Isa, the geometric mean IRT concentration rose with decreasing weight z-score. The IRT concentration was otherwise unrelated to nutritional indices. Sixty percent of the 39 Mount Isa patients with gastroenteritis and 24.5% of the 358 Alice Springs patients with gastroenteritis had an IRT concentration in the upper quartile for their population, compared with 16% for patients with other diagnoses in both populations. Conclusions: A high IRT concentration in patients with low weight z-scores is a confounding effect of gastroenteritis, and may result from subclinical pancreatic disease in gastroenteritis.

Reduced graphene oxide growth on 316L stainless steel for medical applications

We report a new method for the growth of reduced graphene oxide (rGO) on the 316L alloy of stainless steel (SS) and its relevance for biomedical applications. We demonstrate that electrochemical etching increases the concentration of metallic species on the surface and enables the growth of rGO. This result is supported through a combination of Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), atomic force microscopy (AFM), scanning electron microscopy (SEM), density functional theory (DFT) calculations and static water contact angle measurements. Raman spectroscopy identifies the G and D bands for oxidized species of graphene at 1595 cm(-1) and 1350 cm(-1), respectively, and gives an ID/IG ratio of 1.2, indicating a moderate degree of oxidation. XPS shows -OH and -COOH groups in the rGO stoichiometry and static contact angle measurements confirm the wettability of rGO. SEM and AFM measurements were performed on different substrates before and after coronene treatment to confirm rGO growth. Cell viability studies reveal that these rGO coatings do not have toxic effects on mammalian cells, making this material suitable for biomedical and biotechnological applications.

Sediment concentration prediction and statistical evaluation for annual load estimation

We consider the development of statistical models for prediction of constituent concentration of riverine pollutants, which is a key step in load estimation from frequent flow rate data and less frequently collected concentration data. We consider how to capture the impacts of past flow patterns via the average discounted flow (ADF) which discounts the past flux based on the time lapsed - more recent fluxes are given more weight. However, the effectiveness of ADF depends critically on the choice of the discount factor which reflects the unknown environmental cumulating process of the concentration compounds. We propose to choose the discount factor by maximizing the adjusted R-2 values or the Nash-Sutcliffe model efficiency coefficient. The R2 values are also adjusted to take account of the number of parameters in the model fit. The resulting optimal discount factor can be interpreted as a measure of constituent exhaustion rate during flood events. To evaluate the performance of the proposed regression estimators, we examine two different sampling scenarios by resampling fortnightly and opportunistically from two real daily datasets, which come from two United States Geological Survey (USGS) gaging stations located in Des Plaines River and Illinois River basin. The generalized rating-curve approach produces biased estimates of the total sediment loads by -30% to 83%, whereas the new approaches produce relatively much lower biases, ranging from -24% to 35%. This substantial improvement in the estimates of the total load is due to the fact that predictability of concentration is greatly improved by the additional predictors.

Load estimation with uncertainties from opportunistic sampling data: A semiparametric approach

We consider estimating the total load from frequent flow data but less frequent concentration data. 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 that minimizes the biases and makes use of informative predictive variables. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized rating-curve approach with additional predictors that capture unique features in the flow data, such as the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and the discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. Forming 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 for two rivers delivering to the Great Barrier Reef, Queensland, Australia. One is a data set from the Burdekin River, and consists of the total suspended sediment (TSS) and nitrogen oxide (NO(x)) and gauged flow for 1997. The other dataset is from the Tully River, for the period of July 2000 to June 2008. For NO(x) Burdekin, the new estimates are very similar to the ratio estimates even when there is no relationship between the concentration and the flow. However, for the Tully dataset, by incorporating the additional predictive variables namely the discounted flow and flow phases (rising or recessing), we substantially improved the model fit, and thus the certainty with which the load is estimated.

Nonparametric rank regression for analyzing water quality concentration data with multiple detection limits

Environmental data usually include measurements, such as water quality data, which fall below detection limits, because of limitations of the instruments or of certain analytical methods used. The fact that some responses are not detected needs to be properly taken into account in statistical analysis of such data. However, it is well-known that it is challenging to analyze a data set with detection limits, and we often have to rely on the traditional parametric methods or simple imputation methods. Distributional assumptions can lead to biased inference and justification of distributions is often not possible when the data are correlated and there is a large proportion of data below detection limits. The extent of bias is usually unknown. To draw valid conclusions and hence provide useful advice for environmental management authorities, it is essential to develop and apply an appropriate statistical methodology. This paper proposes rank-based procedures for analyzing non-normally distributed data collected at different sites over a period of time in the presence of multiple detection limits. To take account of temporal correlations within each site, we propose an optimal linear combination of estimating functions and apply the induced smoothing method to reduce the computational burden. Finally, we apply the proposed method to the water quality data collected at Susquehanna River Basin in United States of America, which dearly demonstrates the advantages of the rank regression models.

GABAAα1 and GABAAρ1 subunits are expressed in cultured human RPE cells and GABAA receptor agents modify the intracellular calcium concentration.

Purpose: Gamma-aminobutyric acid A (GABAA) receptors (GABAARs), which are ionotropic receptors involving chloride channels, have been identified in various neural (e.g., mouse retinal ganglion cells) and nonneural cells (e.g., mouse lens epithelial cells) regulating the intracellular calcium concentration ([Ca(2+)]i). GABAAR β-subunit protein has been isolated in the cultured human and rat RPE, and GABAAα1 and GABAAρ1 mRNAs and proteins are present in the chick RPE. The purpose of this study was to investigate the expression of GABAAα1 and GABAAρ1, two important subunits in forming functional GABAARs, in the cultured human RPE, and further to explore whether altering receptor activation modifies [Ca(2+)]i. Methods: Human RPE cells were separately cultured from five donor eye cups. Real-time PCR, western blots, and immunofluorescence were used to test for GABAAα1 and GABAAρ1 mRNAs and proteins. The effects of the GABAAR agonist muscimol, antagonist picrotoxin, or the specific GABAAρ antagonist 1,2,5,6-tetrahydropyridin-4-yl) methylphosphinic acid (TPMPA) on [Ca(2+)]i in cultured human RPE were demonstrated using Fluo3-AM. Results: Both GABAAα1 and GABAAρ1 mRNAs and proteins were identified in cultured human RPE cells; antibody staining was mainly localized to the cell membrane and was also present in the cytoplasm but not in the nucleus. Muscimol (100 μM) caused a transient increase of the [Ca(2+)]i in RPE cells regardless of whether Ca(2+) was added to the buffer. Muscimol-induced increases in the [Ca(2+)]i were inhibited by pretreatment with picrotoxin (300 μM) or TPMPA (500 μM). Conclusions: GABAAα1 and GABAAρ1 are expressed in cultured human RPE cells, and GABAA agents can modify [Ca(2+)]i.

Evaluating the risk of mixtures in the indoor air of primary school classrooms

In school environments, children are constantly exposed to mixtures of airborne substances, derived from a variety of sources, both in the classroom and in the school surroundings. It is important to evaluate the hazardous properties of these mixtures, in order to conduct risk assessments of their impact on chil¬dren’s health. Within this context, through the application of a Maximum Cumulative Ratio approach, this study aimed to explore whether health risks due to indoor air mixtures are driven by a single substance or are due to cumulative exposure to various substances. This methodology requires knowledge of the concentration of substances in the air mixture, together with a health related weighting factor (i.e. reference concentration or lowest concentration of interest), which is necessary to calculate the Hazard Index. Maximum cumulative ratio and Hazard Index values were then used to categorise the mixtures into four groups, based on their hazard potential and therefore, appropriate risk management strategies. Air samples were collected from classrooms in 25 primary schools in Brisbane, Australia. Analysis was conducted based on the measured concentration of these substances in about 300 air samples. The results showed that in 92% of the schools, indoor air mixtures belonged to the ‘low concern’ group and therefore, they did not require any further assessment. In the remaining schools, toxicity was mainly governed by a single substance, with a very small number of schools having a multiple substance mix which required a combined risk assessment. The proposed approach enables the identification of such schools and thus, aides in the efficient health risk management of pollution emissions and air quality in the school environment.

Indoor Air Quality in Naturally Ventilated Italian Classrooms

Characterization of indoor air quality in school classrooms is crucial to children’s health and performance. The present study was undertaken to characterize the indoor air quality in six naturally ventilated classrooms of three schools in Cassino (Italy). Indoor particle number, mass, black carbon, CO2 and radon concentrations, as well as outdoor particle number were measured within school hours during the winter and spring season. The study found the concentrations of indoor particle number were influenced by the concentrations in the outdoors; highest BC values were detected in classrooms during peak traffic time. The effect of different seasons’ airing mode on the indoor air quality was also detected. The ratio between indoor and outdoor particles was of 0.85 ± 0.10 in winter, under airing conditions of short opening window periods, and 1.00 ± 0.15 in spring when the windows were opened for longer periods. This was associated to a higher degree of penetration of outdoor particles due to longer period of window opening. Lower CO2 levels were found in classrooms in spring (908 ppm) than in winter (2206 ppm). Additionally, a greater reduction in radon concentrations was found in spring. In addition, high PM10 levels were found in classrooms during break time due to re-suspension of coarse particles. Keywords: classroom; Ni/Nout ratio; airing by opening windows; particle number

Factors influencing the outdoor concentration of carbonaceous aerosols at urban schools in Brisbane, Australia: implications for children’s exposure

This comprehensive study aimed to determine the sources and driving factors of organic carbon (OC) and elemental carbon (EC) concentrations in ambient PM2.5 in urban schools. Sampling was conducted outdoors at 25 schools in the Brisbane Metropolitan Area, Australia. Concentrations of primary and secondary OC were quantified using the EC tracer method, with secondary OC accounting for an average of 60%. Principal component analysis distinguished the contributing sources above the background and identified groups of schools with differing levels of primary and secondary carbonaceous aerosols. Overall, the results showed that vehicle emissions, local weather conditions and secondary organic aerosols (SOA) were the key factors influencing concentrations of carbonaceous component of PM2.5 at these schools. These results provide insights into children’s exposure to vehicle emissions and SOA at such urban schools.

A variant in LIN28B is associated with 2D:4D finger-length ratio, a putative retrospective biomarker of prenatal testosterone exposure

The ratio of the lengths of an individual's second to fourth digit (2D:4D) is commonly used as a noninvasive retrospective biomarker for prenatal androgen exposure. In order to identify the genetic determinants of 2D:4D, we applied a genome-wide association approach to 1507 11-year-old children from the Avon Longitudinal Study of Parents and Children (ALSPAC) in whom 2D:4D ratio had been measured, as well as a sample of 1382 12- to 16-year-olds from the Brisbane Adolescent Twin Study. A meta-analysis of the two scans identified a single variant in the LIN28B gene that was strongly associated with 2D:4D (rs314277: p = 4.1 x 10(-8)) and was subsequently independently replicated in an additional 3659 children from the ALSPAC cohort (p = 1.53 x 10(-6)). The minor allele of the rs314277 variant has previously been linked to increased height and delayed age at menarche, but in our study it was associated with increased 2D:4D in the direction opposite to that of previous reports on the correlation between 2D:4D and age at menarche. Our findings call into question the validity of 2D:4D as a simplistic retrospective biomarker for prenatal testosterone exposure.

Meta-analysis identifies 13 new loci associated with waist-hip ratio and reveals sexual dimorphism in the genetic basis of fat distribution

Waist-hip ratio (WHR) is a measure of body fat distribution and a predictor of metabolic consequences independent of overall adiposity. WHR is heritable, but few genetic variants influencing this trait have been identified. We conducted a meta-analysis of 32 genome-wide association studies for WHR adjusted for body mass index (comprising up to 77,167 participants), following up 16 loci in an additional 29 studies (comprising up to 113,636 subjects). We identified 13 new loci in or near RSPO3, VEGFA, TBX15-WARS2, NFE2L3, GRB14, DNM3-PIGC, ITPR2-SSPN, LY86, HOXC13, ADAMTS9, ZNRF3-KREMEN1, NISCH-STAB1 and CPEB4 (P = 1.9 × 10−9 to P = 1.8 × 10−40) and the known signal at LYPLAL1. Seven of these loci exhibited marked sexual dimorphism, all with a stronger effect on WHR in women than men (P for sex difference = 1.9 × 10−3 to P = 1.2 × 10−13). These findings provide evidence for multiple loci that modulate body fat distribution independent of overall adiposity and reveal strong gene-by-sex interactions.

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.

Structural and thermal properties of inorganic–organic montmorillonite: Implications for their potential environmental applications

Inorganic–organic clays (IOCs), clays intercalated with both organic cations such as cationic surfactants and inorganic cations such as metal hydroxy polycations have the properties of both organic and pillared clays, and thereby the ability to remove both inorganic and organic contaminants from water simultaneously. In this study, IOCs were synthesised using three different methods with different surfactant concentrations. Octadecyltrimethylammonium bromide (ODTMA) and hydroxy aluminium ([Al13O4 (OH)24(H2O)12]7+ or Al13) are used as the organic and inorganic modifiers (intercalation agents). According to the results, the interlayer distance, the surfactant loading amount and the Al/Si ratio of IOCs strictly depend on the intercalation method and the intercalation agent ratio. Interlayers of IOCs synthesised by intercalating ODTMA before Al13 and IOCs synthesised by simultaneous intercalation of ODTMA and Al13 were increased with increasing the ODTMA concentration used in the synthesis procedure and comparatively high loading amounts could be observed in them. In contrast, Al/Si decreased with increasing ODTMA concentration in these two types of IOCs. The results suggest that Al-pillars can be fixed within the interlayers by calcination and any increment in the amount of ODTMA used in the synthesis procedure did not affect the interlayer distance of the IOCs. Overall the study provides valuable insights into the structure and properties of the IOCs and their potential environmental applications.

Simultaneous adsorption of Cd(II) and phosphate on Al13 pillared montmorillonite

Al13 pillared montmorillonites (AlPMts) prepared with different Al/clay ratios were used to remove Cd(II) and phosphate from aqueous solution. The structure of AlPMts was characterized by X-ray diffraction (XRD), Thermogravimetric analysis (TG), and N2 adsorption–desorption. The basal spacing, intercalated amount of Al13 cations, and specific surface area of AlPMts increased with the increase of the Al/clay ratio. In the single adsorption system, with the increase of the Al/clay ratio, the adsorption of phosphate on AlPMts increased but that of Cd(II) decreased. Significantly enhanced adsorptions of Cd(II) and phosphate on AlPMts were observed in a simultaneous system. For both contaminants, the adsorption of one contaminant would increase with the increase of the initial concentration of the other one and increase in the Al/clay ratio. The enhancement of the adsorption of Cd(II) was much higher than that of phosphate on AlPMt. This suggests that the intercalated Al13 cations are the primary co-adsorption sites for phosphate and Cd(II). X-ray photoelectron spectroscopy (XPS) indicated comparable binding energy of P2p but a different binding energy of Cd3d in single and simultaneous systems. The adsorption and XPS results suggested that the formation of P-bridge ternary surface complexes was the possible adsorption mechanism for promoted uptake of Cd(II) and phosphate on AlPMt.

Concentration levels of heavy metals and polycyclic aromatic hydrocarbons in car parks at Queensland University of Technology

This study investigates the level of pollutants (polycyclic aromatic hydrocarbons (PAHs) and heavy metals) in three car parks at QUT, one at Kelvin Grove campus and two at the Gardens Point campus. In addition, comparisons between site designs were assessed to identify the possible sources of heavy metals and PAHs. The main contributing source for heavy metals was identified to be from vehicle debris and emissions, while the source of PAHs was identified to be from petrol and diesel engine vehicle emissions. The highest concentration of pollutants was typically found for the 63 micro meter dust samples, proposed to be due to increased surface areas and thus available adsorption sites.