Physical, chemical, biological and ecotoxicological properties of wastewater discharged from Davis Station, Antarctica

The properties and toxicity of untreatedwastewater at Davis Station, East Antarctica,were investigated to inform decisions regarding the appropriate level of treatment for local discharge purposes and more generally, to better understand the risk associated with dispersal and impact of wastewaters in Antarctica. Suspended solids, nutrients (nitrogen, phosphorus), biological oxygen demand (BOD), metals, organic contaminants, surfactants and microbiological load were measured at various locations throughout the wastewater discharge system. Wastewater quality and properties varied greatly between buildings on station, each ofwhich has separate holding tanks. Nutrients, BOD and settleable solid levelswere higher than standard municipal wastewaters. Microbiological loads were typical of untreated wastewater. Contaminants detected in the wastewater included metals and persistent organic compounds, mainly polybrominated diphenyl ethers (PBDEs). The toxicity of wastewater was also investigated in laboratory bioassays using two local Antarctic marine invertebrates, the amphipod Paramoera walkeri and the microgastropod Skenella paludionoides. Animals were exposed to a range of wastewater concentrations from3% to 68% (test 1) or 63% (test 2) over 21 days with survival monitored daily. Significant mortality occurred in all concentrations of wastewater after 14 to 21 days, and at higher concentrations (50–68% wastewater) mortality occurred after only one day. Results indicate that the local receiving marine environment at Davis Station is at risk from existing wastewater discharges, and that advanced treatment is required both to remove contaminants shown to cause toxicity to biota, as well as to reduce the environmental risks associated with non-native micro-organisms in wastewater.

Functional neuroanatomy of auditory mismatch processing : an event-related fMRI study of duration-deviant oddballs

This study was designed to identify the neural networks underlying automatic auditory deviance detection in 10 healthy subjects using functional magnetic resonance imaging. We measured blood oxygenation level-dependent contrasts derived from the comparison of blocks of stimuli presented as a series of standard tones (50 ms duration) alone versus blocks that contained rare duration-deviant tones (100 ms) that were interspersed among a series of frequent standard tones while subjects were watching a silent movie. Possible effects of scanner noise were assessed by a “no tone” condition. In line with previous positron emission tomography and EEG source modeling studies, we found temporal lobe and prefrontal cortical activation that was associated with auditory duration mismatch processing. Data were also analyzed employing an event-related hemodynamic response model, which confirmed activation in response to duration-deviant tones bilaterally in the superior temporal gyrus and prefrontally in the right inferior and middle frontal gyri. In line with previous electrophysiological reports, mismatch activation of these brain regions was significantly correlated with age. These findings suggest a close relationship of the event-related hemodynamic response pattern with the corresponding electrophysiological activity underlying the event-related “mismatch negativity” potential, a putative measure of auditory sensory memory.

Memory and Epileptogenesis in Complex Biological and Simulated Systems

Oscillations of neural activity may bind widespread cortical areas into a neural representation that encodes disparate aspects of an event. In order to test this theory we have turned to data collected from complex partial epilepsy (CPE) patients with chronically implanted depth electrodes. Data from regions critical to word and face information processing was analyzed using spectral coherence measurements. Similar analyses of intracranial EEG (iEEG) during seizure episodes display HippoCampal Formation (HCF)—NeoCortical (NC) spectral coherence patterns that are characteristic of specific seizure stages (Klopp et al. 1996). We are now building a computational memory model to examine whether spatio-temporal patterns of human iEEG spectral coherence emerge in a computer simulation of HCF cellular distribution, membrane physiology and synaptic connectivity. Once the model is reasonably scaled it will be used as a tool to explore neural parameters that are critical to memory formation and epileptogenesis.

Inducible resistance to maize streak virus

Maize streak virus (MSV), which causes maize streak disease (MSD), is the major viral pathogenic constraint on maize production in Africa. Type member of the Mastrevirus genus in the family Geminiviridae, MSV has a 2.7 kb, single-stranded circular DNA genome encoding a coat protein, movement protein, and the two replication-associated proteins Rep and RepA. While we have previously developed MSV-resistant transgenic maize lines constitutively expressing ‘‘dominant negative mutant’’ versions of the MSV Rep, the only transgenes we could use were those that caused no developmental defects during the regeneration of plants in tissue culture. A better transgene expression system would be an inducible one, where resistance-conferring transgenes are expressed only in MSV-infected cells. However, most known inducible transgene expression systems are hampered by background or ‘‘leaky’’ expression in the absence of the inducer. Here we describe an adaptation of the recently developed INPACT system to express MSV-derived resistance genes in cell culture. Split gene cassette constructs (SGCs) were developed containing three different transgenes in combination with three different promoter sequences. In each SGC, the transgene was split such that it would be translatable only in the presence of an infecting MSV’s replication associated protein. We used a quantitative real-time PCR assay to show that one of these SGCs (pSPLITrepIII-Rb-Ubi) inducibly inhibits MSV replication as efficiently as does a constitutively expressed transgene that has previously proven effective in protecting transgenic maize from MSV. In addition, in our cell-culture based assay pSPLITrepIII-Rb-Ubi inhibited replication of diverse MSV strains, and even, albeit to a lesser extent, of a different mastrevirus species. The application of this new technology to MSV resistance in maize could allow a better, more acceptable product.

Sources and transport pathways of common heavy metals to urban road surfaces

Heavy metals that are built-up on urban impervious surfaces such as roads are transported to urban water resources through stormwater runoff. Therefore, it is essential to understand the predominant pathways of heavy metals to the build-up on roads in order to develop suitable pollution mitigation strategies to protect the receiving water environment. The study presented in this paper investigated the sources and transport pathways of manganese, lead, copper, zinc and chromium, which are heavy metals commonly present in urban road build-up. It was found that manganese and lead are contributed to road build-up primarily by direct deposition due to the re-suspension of roadside soil by wind turbulence, while traffic is the predominant source of copper, zinc and chromium to the atmosphere and road build-up. Atmospheric deposition is also the major transport pathway for copper and zinc, and for chromium, direct deposition by traffic sources is the predominant pathway.

Weak acid extractable metals in Bramble Bay, Queensland, Australia : temporal behaviour, enrichment and source apportionment

Sediment samples were taken from six sampling sites in Bramble Bay, Queensland, Australia between February and November in 2012. They were analysed for a range of heavy metals including Al, Fe, Mn, Ti, Ce, Th, U, V, Cr, Co, Ni, Cu, Zn, As, Cd, Sb, Te, Hg, Tl and Pb. Fraction analysis, enrichment factors and Principal Component Analysis –Absolute Principal Component Scores (PCA-APCS) were carried out in order to assess metal pollution, potential bioavailability and source apportionment. Cr and Ni exceeded the Australian Interim Sediment Quality Guidelines at some sampling sites, while Hg was found to be the most enriched metal. Fraction analysis identified increased weak acid soluble Hg and Cd during the sampling period. Source apportionment via PCA-APCS found four sources of metals pollution, namely, marine sediments, shipping, antifouling coatings and a mixed source. These sources need to be considered in any metal pollution control measure within Bramble Bay.

Assessment and application of clustering techniques to atmospheric particle number size distribution for the purpose of source apportionment

Long-term measurements of particle number size distribution (PNSD) produce a very large number of observations and their analysis requires an efficient approach in order to produce results in the least possible time and with maximum accuracy. Clustering techniques are a family of sophisticated methods which have been recently employed to analyse PNSD data, however, very little information is available comparing the performance of different clustering techniques on PNSD data. This study aims to apply several clustering techniques (i.e. K-means, PAM, CLARA and SOM) to PNSD data, in order to identify and apply the optimum technique to PNSD data measured at 25 sites across Brisbane, Australia. A new method, based on the Generalised Additive Model (GAM) with a basis of penalised B-splines, was proposed to parameterise the PNSD data and the temporal weight of each cluster was also estimated using the GAM. In addition, each cluster was associated with its possible source based on the results of this parameterisation, together with the characteristics of each cluster. The performances of four clustering techniques were compared using the Dunn index and Silhouette width validation values and the K-means technique was found to have the highest performance, with five clusters being the optimum. Therefore, five clusters were found within the data using the K-means technique. The diurnal occurrence of each cluster was used together with other air quality parameters, temporal trends and the physical properties of each cluster, in order to attribute each cluster to its source and origin. The five clusters were attributed to three major sources and origins, including regional background particles, photochemically induced nucleated particles and vehicle generated particles. Overall, clustering was found to be an effective technique for attributing each particle size spectra to its source and the GAM was suitable to parameterise the PNSD data. These two techniques can help researchers immensely in analysing PNSD data for characterisation and source apportionment purposes.

Regional avian species declines estimated from volunteer-collected long-term data using List Length Analysis

Long-term systematic population monitoring data sets are rare but are essential in identifying changes in species abundance. In contrast, community groups and natural history organizations have collected many species lists. These represent a large, untapped source of information on changes in abundance but are generally considered of little value. The major problem with using species lists to detect population changes is that the amount of effort used to obtain the list is often uncontrolled and usually unknown. It has been suggested that using the number of species on the list, the "list length," can be a measure of effort. This paper significantly extends the utility of Franklin's approach using Bayesian logistic regression. We demonstrate the value of List Length Analysis to model changes in species prevalence (i.e., the proportion of lists on which the species occurs) using bird lists collected by a local bird club over 40 years around Brisbane, southeast Queensland, Australia. We estimate the magnitude and certainty of change for 269 bird species and calculate the probabilities that there have been declines and increases of given magnitudes. List Length Analysis confirmed suspected species declines and increases. This method is an important complement to systematically designed intensive monitoring schemes and provides a means of utilizing data that may otherwise be deemed useless. The results of List Length Analysis can be used for targeting species of conservation concern for listing purposes or for more intensive monitoring. While Bayesian methods are not essential for List Length Analysis, they can offer more flexibility in interrogating the data and are able to provide a range of parameters that are easy to interpret and can facilitate conservation listing and prioritization. © 2010 by the Ecological Society of America.

Visualization of complex biological systems: An immune response model using OpenGL

In this paper we present an update on our novel visualization technologies based on cellular immune interaction from both large-scale spatial and temporal perspectives. We do so with a primary motive: to present a visually and behaviourally realistic environment to the community of experimental biologists and physicians such that their knowledge and expertise may be more readily integrated into the model creation and calibration process. Visualization aids understanding as we rely on visual perception to make crucial decisions. For example, with our initial model, we can visualize the dynamics of an idealized lymphatic compartment, with antigen presenting cells (APC) and cytotoxic T lymphocyte (CTL) cells. The visualization technology presented here offers the researcher the ability to start, pause, zoom-in, zoom-out and navigate in 3-dimensions through an idealised lymphatic compartment.

Melanoma cell colony expansion parameters revealed by approximate Bayesian computation

In vitro studies and mathematical models are now being widely used to study the underlying mechanisms driving the expansion of cell colonies. This can improve our understanding of cancer formation and progression. Although much progress has been made in terms of developing and analysing mathematical models, far less progress has been made in terms of understanding how to estimate model parameters using experimental in vitro image-based data. To address this issue, a new approximate Bayesian computation (ABC) algorithm is proposed to estimate key parameters governing the expansion of melanoma cell (MM127) colonies, including cell diffusivity, D, cell proliferation rate, λ, and cell-to-cell adhesion, q, in two experimental scenarios, namely with and without a chemical treatment to suppress cell proliferation. Even when little prior biological knowledge about the parameters is assumed, all parameters are precisely inferred with a small posterior coefficient of variation, approximately 2–12%. The ABC analyses reveal that the posterior distributions of D and q depend on the experimental elapsed time, whereas the posterior distribution of λ does not. The posterior mean values of D and q are in the ranges 226–268 µm2h−1, 311–351 µm2h−1 and 0.23–0.39, 0.32–0.61 for the experimental periods of 0–24 h and 24–48 h, respectively. Furthermore, we found that the posterior distribution of q also depends on the initial cell density, whereas the posterior distributions of D and λ do not. The ABC approach also enables information from the two experiments to be combined, resulting in greater precision for all estimates of D and λ.

Modified MLVA for genotyping Queensland invasive Streptococcus pneumoniae

Background Globally, over 800 000 children under five die each year from infectious diseases caused by Streptococcus pneumoniae. To understand genetic relatedness between isolates, study transmission routes, assess the impact of human interventions e.g. vaccines, and determine infection sources, genotyping methods are required. The ‘gold standard’ genotyping method, Multi-Locus Sequence Typing (MLST), is useful for long-term and global studies. Another genotyping method, Multi-Locus Variable Number of Tandem Repeat Analysis (MLVA), has emerged as a more discriminatory, inexpensive and faster technique; however there is no universally accepted method and it is currently suitable for short-term and localised epidemiology studies. Currently Australia has no national MLST database, nor has it adopted any MLVA method for short-term or localised studies. This study aims to improve S. pneumoniae genotyping methods by modifying the existing MLVA techniques to be more discriminatory, faster, cheaper and technically less demanding than previously published MLVA methods and MLST. Methods Four different MLVA protocols, including a modified method, were applied to 317 isolates of serotyped invasive S. pneumoniae isolated from sterile body sites of Queensland children under 15 years from 2007–2012. MLST was applied to 202 isolates for comparison. Results The modified MLVA4 is significantly more discriminatory than the ‘gold standard’ MLST method. MLVA4 has similar discrimination compared to other MLVA techniques in this study). The failure to amplify particular loci in previous MLVA methods were minimised in MLVA4. Failure to amplify BOX-13 and Spneu19 were found to be serotype specific. Conclusion We have modified a highly discriminatory MLVA technique for genotyping Queensland invasive S. pneumoniae. MLVA4 has the ability to enhance our understanding of the pneumococcal epidemiology and the changing genetics of the pneumococcus in localised and short-term studies.

Tectonometamorphic evolution of the Åreskutan Nappe-Caledonian history revealed by SIMS U–Pb zircon geochronology

Secondary ionization mass spectrometry (SIMS) U–Pb dating of zircons from the Åreskutan Nappe in the central part of the Seve Nappe Complex of western central Jämtland provides new constraints on the timing of granulite–amphibolite-facies metamorphism and tectonic stacking of the nappe during the Caledonian orogeny. Peak-temperature metamorphism in garnet migmatites is constrained to c. 442 ± 4 Ma, very similar to the ages of leucogranites at 442 ± 3 and 441 ± 4 Ma. Within a migmatitic amphibolite, felsic segregations crystallized at 436 ± 2 Ma. Pegmatites, cross-cutting the dominant Caledonian foliation in the Nappe, yield 428 ± 4 and 430 ± 3 Ma ages. The detrital zircon cores in the migmatites and leucogranites provide evidence of Late Palaeoproterozoic, Mesoproterozoic to Early Neoproterozoic source terranes for the metasedimentary rocks. The formation of the ductile and hot Seve migmatites, with their inverted metamorphism and thinning towards the hinterland, can be explained by an extrusion model in which the allochthon stayed ductile for a period of at least 10 million years during cooling from peak-temperature metamorphism early in the Silurian. In our model, Baltica–Laurentia collision occurred in the Late Ordovician–earliest Silurian, with emplacement of the nappes far on to the Baltoscandian platform during the Silurian and early Devonian, Scandian Orogeny lasting until c. 390 Ma.

Validity of the geriatric depression scale and the collateral source version of the geriatric depression scale in nursing homes

Background Depression is a common psychiatric disorder in older people. The study aimed to examine the screening accuracy of the Geriatric Depression Scale (GDS) and the Collateral Source version of the Geriatric Depression Scale (CS-GDS) in the nursing home setting. Methods Eighty-eight residents from 14 nursing homes were assessed for depression using the GDS and the CS-GDS, and validated against clinician diagnosed depression using the Semi-structured Clinical Diagnostic Interview for DSM-IV-TR Axis I Disorders (SCID) for residents without dementia and the Provisional Diagnostic Criteria for Depression in Alzheimer Disease (PDCdAD) for those with dementia. The screening performances of five versions of the GDS (30-, 15-, 10-, 8-, and 4-item) and two versions of the CS-GDS (30- and 15-item) were analyzed using receiver operating characteristic (ROC) curves. Results Among residents without dementia, both the self-rated (AUC = 0.75–0.79) and proxy-rated (AUC = 0.67) GDS variations performed significantly better than chance in screening for depression. However, neither instrument adequately identified depression among residents with dementia (AUC between 0.57 and 0.70). Among the GDS variations, the 4- and 8-item scales had the highest AUC and the optimal cut-offs were >0 and >3, respectively. Conclusions The validity of the GDS in detecting depression requires a certain level of cognitive functioning. While the CS-GDS is designed to remedy this issue by using an informant, it did not have adequate validity in detecting depression among residents with dementia. Further research is needed on informant selection and other factors that can potentially influence the validity of proxy-based measures in the nursing home setting.