Biochemical effects of clomazone herbicide on piava (Leporinus obtusidens)

This study aims to verify the effects of the clomazone concentration used in rice fields on acetylcholinesterase (AChE), thiobarbituric acid reactive substances (TBARS), protein carbonyl and catalase activity in tissues of piava (Leporinus obtusidens). LC(50)-96h was 5.0 mg L(-1) and the fish were exposed to 1/10 of LC(50)-96 h: 0.5 mg L(-1) of clomazone for 96 and 192h. The same parameters were also assayed after a recovery period of 192 h in clean water. AChE activity was reduced only in the brain and heart of fish exposed for 96 h. AChE activity was decreased in the brain, muscle and heart tissues after 192 h of exposure. After 192 h of recovery period, AChE activity remained diminished in brain and muscle and showed a decrease in eye. However, after 192 h of recovery, AChE activity in heart was recovered. Fish showed increased TBARS levels in brain at all experimental periods. TBARS levels decreased in liver and muscle tissues after 192 h of exposure. The increase in muscle TBARS persisted in fish transferred to clean water. Protein carbonyl in the liver was increased in all periods studied including the recovery period. Catalase activity was reduced during all periods. The present study demonstrates the occurrence of disorders in AChE, TBARS, protein carbonyl and catalase activity in piava. The results also show changes in fish after exposure to an environmentally relevant concentration of clomazone. Most effects observed persisted after the recovery period. Thus, these parameters may be used to monitor clomazone toxicity in fish.     

Assisting Australian indigenous resource management and sustainable utilization of species through the use of GIS and environmental modeling techniques

Information on distribution and relative abundance of species is integral to sustainable management, especially if they are to be harvested for subsistence or commerce. In northern Australia, natural landscapes are vast, centers of population few, access is difficult, and Aboriginal resource centers and communities have limited funds and infrastructure. Consequently defining distribution and relative abundance by comprehensive ground survey is difficult and expensive. This highlights the need for simple, cheap, automated methodologies to predict the distribution of species in use, or having potential for use, in commercial enterprise. The technique applied here uses a Geographic Information System (GIS) to make predictions of probability of occurrence using an inductive modeling technique based on Bayes' theorem. The study area is in the Maningrida region, central Arnhem Land, in the Northern Territory, Australia. The species examined, Cycas arnhemica and Brachychiton diversifolius, are currently being 'wild harvested' in commercial trials, involving sale of decorative plants and use as carving wood, respectively. This study involved limited and relatively simple ground surveys requiring approximately 7 days of effort for each species. The overall model performance was evaluated using Cohen's kappa statistics. The predictive ability of the model for C. arnhemica was classified as moderate and for B. diversifolius as fair. The difference in model performance can be attributed to the pattern of distribution of these species. C. arnhemica tends to occur in a clumped distribution due to relatively short distance dispersal of its large seeds and vegetative growth from long-lived rhizomes, while B. diversifolius seeds are smaller and more widely dispersed across the landscape. The output from analysis predicts trends in species distribution that are consistent with independent on-site sampling for each species and therefore should prove useful in gauging the extent of resource availability. However, some caution needs to be applied as the models tend to over predict presence which is a function of distribution patterns and of other variables operating in the landscape such as fire histories which were not included in the model due to limited availability of data.     

Comparison of Outdoor and Classroom Ozone Exposures for School Children in Mexico City

Abstract

To evaluate methods of reducing exposure of school children in southwest Mexico City to ambient ozone, outdoor ozone levels were compared to indoor levels under three distinct classroom conditions: windows/doors open, air cleaner off; windows/doors closed, air cleaner off; windows/ doors closed, air cleaner on. Repeated two-minute average measurements of ozone were made within five minutes of each other inside and outside of six different school classrooms while children were in the room. Outdoor ozone two-minute average levels varied between 64 and 361 ppb; mean outdoor levels were above 160 ppb for each of the three conditions. Adjusting for outdoor relative humidity, for a mean outdoor ozone concentration of 170 ppb, the mean predicted indoor ozone concentrations were 125.3 (±5.7) ppb with windows/doors open; 35.4 (±4.6) ppb with windows/ doors closed, air cleaner off; and 28.9 (±4.3) ppb with windows/ doors closed, air cleaner on. The mean predicted ratios of indoor to outdoor ozone concentrations were 0.71 (±0.03) with windows/doors open; 0.18 (±0.02) ppb with windows/doors closed, air cleaner off; and 0.15 (±0.02) ppb with windows/doors closed, air cleaner on. As outdoor ozone concentrations increased, indoor ozone concentrations increased more rapidly with windows and doors open than with windows and doors closed. Ozone exposure in Mexican schools may be significantly reduced, and can usually be kept below the World Health Organization (WHO) guideline of 80 ppb, by closing windows and doors even when ambient ozone levels reach 30Q ppb or more.     

Systematic Development of an Artificial Neural Network Model for Real-Time Prediction of Ground-Level Ozone in Edmonton,Alberta, Canada

Abstract

Ground-level ozone is a secondary pollutant that has recently gained notoriety for its detrimental effects on human and vegetation health. In this paper, a systematic approach is applied to develop artificial neural network (ANN) models for ground-level ozone (O₃) prediction in Edmonton, Alberta, Canada, using ambient monitoring data for input. The intent of these models is to provide regulatory agencies with a tool for addressing data gaps in ambient monitoring information and predicting O₃ events. The models are used to determine the meteorological conditions and precursors that most affect O₃ concentrations. O₃ time-series effects and the efficacy of the systematic approach are also assessed. The developed models showed good predictive success, with coefficient of multiple determination values ranging from 0.75 to 0.94 for forecasts up to 2 hr in advance. The inputs most important for O₃ prediction were temperature and concentrations of nitric oxide, total hydrocarbons, sulfur dioxide, and nitrogen dioxide.     

Block Copolymers Containing (R)-3-Hydroxybutyrate and Isosorbide Succinate or (S)-Lactic Acid Mers

A new aliphatic block copolyester was synthesized in bulk from transesterification techniques between poly((R)-3-hydroxybutyrate) (PHB) and poly(isosorbide succinate) (PIS). Additionally, other two block copolyesters were synthesized in bulk either from transesterification reactions involving PHB and poly(l-lactide) (PLLA) or from ring-opening copolymerization of l-lactide and hydroxyl-terminated PHB, as result of a previous transesterification reactions with isosorbide. Two-component blends of PHB and PIS or PLLA were also prepared as comparative systems. SEC, MALDI-TOF mass spectrometry (MALDI-TOFMS), ¹H and ¹³C NMR spectroscopy, WAXD, solubility tests, and TG thermal analysis were used for characterization. The block copolymer structures of the products were evidenced by MALDI-TOFMS, ¹³C NMR, and WAXD data. The block copolymers and the corresponding binary blends presented different solubility properties, as revealed by solubility tests. Although the incorporation of PIS sequences into PHB main backbone did not enhance the thermal stability of the product, it reduced its crystallinity, which could be advantageous for faster biodegradation rate. These products, composed of PHB and PIS or PLLA sequences, are an interesting alternative in biomedical applications.     

Biological and chemical assessments of zinc ageing in field soils

As zinc (Zn) is both an essential trace element and potential toxicant, the effects of Zn fixation in soil are of practical significance. Soil samples from four field sites amended with ZnSO₄ were used to investigate ageing of soluble Zn under field conditions over a 2-year period. Lability of Zn measured using ⁶⁵Zn radioisotope dilution showed a significant decrease over time and hence evidence of Zn fixation in three of the four soils. However, 0.01 M CaCl₂ extractions and toxicity measurements using a genetically modified lux-marked bacterial biosensor did not indicate a decrease in soluble/bioavailable Zn over time. This was attributed to the strong regulatory effect of abiotic properties such as pH on these latter measurements. These results also showed that Zn ageing occurred immediately after Zn spiking, emphasising the need to incubate freshly spiked soils before ecotoxicity assessments.     

Aerosol speciation and mass prediction from toluene oxidation under high NOx conditions

A kinetically based gas-particle partitioning box model is used to highlight the importance of parameter representation in the prediction of secondary organic aerosol (SOA) formation following the photo-oxidation of toluene. The model is initialized using experimental data from York University's indoor smog chamber and provides a prediction of the total aerosol yield and speciation. A series of model sensitivity experiments were performed to study the aerosol speciation and mass prediction under high NO_x conditions (VOC/NO_x = 0.2). Sensitivity experiments indicate vapour pressure estimation to be a large area of weakness in predicting aerosol mass, creating an average total error range of 70 μg m^?3 (range of 5–145 μg m^?3), using two different estimation methods. Aerosol speciation proved relatively insensitive to changes in vapour pressure. One species, 3-methyl-6-nitro-catechol, dominated the aerosol phase regardless of the vapour pressure parameterization used and comprised 73–88% of the aerosol by mass. The dominance is associated with the large concentration of 3-methyl-6-nitro-catechol in the gas-phase. The high NO_x initial conditions of this study suggests that the predominance of 3-methyl-6-nitro-catechol likely results from the cresol-forming branch in the Master Chemical Mechanism taking a significant role in secondary organic aerosol formation under high NO_x conditions. Further research into the yields and speciation leading to this reaction product is recommended.     

Development of a real-time immuno-PCR assay for the quantification of 17β-estradiol in water

A competitive real-time (RT) immuno-polymerase chain reaction (iPCR) (RT-iPCR) assay was developed for the sensitive quantification of 17β-estradiol in water. Using a universal iPCR method and polyclonal antibodies, 17β-estradiol was accurately quantified at concentrations ranging from 1 pg mL^?1 to 10 µg mL^?1. The RT-iPCR assay's limit of detection was 0.7 pg mL^?1. The RT-iPCR assay provided an 800-fold increase in sensitivity as well as an expanded working range compared with the corresponding enzyme-linked immunosorbent assay. Assay cross-reactivity to estrone and estriol, two structurally related estrogens, was below 8%. Water samples spiked with 17β-estradiol were analyzed by RT-iPCR to determine the assay's potential as a rapid screen for the monitoring of manure-borne estrogens in the environment. The assay showed recoveries of 82, 102 and 103% for Milli-Q, tap, and irrigation water, respectively, without requiring sample extraction or concentration prior to analysis.     

Work experiences and marital interactions: Elaborating the complexity of work

Previous research suggests that work experiences affect family interactions and family processes but does not adequately specify the job characteristics that influence such family-level outcomes. This study examines relationships between the quality of marital interactions and a range of job characteristics including the level of enrichment provided by the job, job time demands, job pressure, schedule flexibility, and job insecurity. The sample consisted of 523 married full time employees at a major U.S. company. Multiple regression analysis indicated that these job characteristics significantly predict the quality of marital interactions. Some directly influenced the quality of marital interaction while the influence of others was moderated by the presence or absence of stressful household roles. Results suggest that characteristics workers' jobs, and not merely workers' reactions to them, are associated with family interactions and family processes.     

The application of local measures of spatial autocorrelation for describing pattern in north Australian landscapes

This paper tests the use of a spatial analysis technique, based on the calculation of local spatial autocorrelation, as a possible approach for modelling and quantifying structure in northern Australian savanna landscapes. Unlike many landscapes in the world, northern Australian savanna landscapes appear on the surface to be intact. They have not experienced the same large-scale land clearance and intensive land management as other landscapes across Australia. Despite this, natural resource managers are beginning to notice that processes are breaking down and declines in species are becoming more evident. With future declines of species looking more imminent it is particularly important that models are available that can help to assess landscape health, and quantify any structural change that takes place. GIS and landscape ecology provide a useful way of describing landscapes both spatially and temporally and have proved to be particularly useful for understanding vegetation structure or pattern in landscapes across the world. There are many measures that examine spatial structure in the landscape and most of these are now available in a GIS environment (e.g. FRAGSTATS* ARC, r.le, and Patch Analyst). All these methods depend on a landscape described in terms of patches, corridors and matrix. However, since landscapes in northern Australia appear to be relatively intact they tend to exist as surfaces of continuous variation rather than in clearly defined homogeneous units. As a result they cannot be easily described using entity-based models requiring patches and other essentially cartographic approaches. This means that more appropriate methods need to be developed and explored. The approach examined in this paper enables clustering and local pattern in the data to be identified and forms a generic method for conceptualising the landscape structure where patches are not obvious and where boundaries between landscape features are difficult to determine. Two sites are examined using this approach. They have been exposed to different degrees of disturbance by fire and grazing. The results show that savanna landscapes are very complex and that even where there is a high degree of disturbance the landscape is still relatively heterogeneous. This means that treating savanna landscapes as being made up of homogeneous units can limit analysis of pattern, as it can over simplify the structure present, and that methods such as the autocorrelation approach are useful tools for quantifying the variable nature of these landscapes.