Inhibition kinetics of acid and alkaline phosphatases by atrazine and methomyl pesticides

The main objective of this work was to investigate the kinetic characteristics of acid and alkaline phosphatases isolated from different sources and to study the effects of the herbicide atrazine and insecticide methomyl on the activity and kinetic properties of the enzymes. Acid phosphatase (ACP) was isolated from the tomato plant (Solanum lycopersicum L. var. lycopersicum); alkaline phosphatase (ALP) was isolated from two sources, including mature earthworms (Aporrectodea caliginosa) and larvae of the Egyptian cotton leafworm (Spodoptera littoralis). The specific activities of the enzymes were 33.31, 5.56 and 0.72 mmol substrate hydrolyzed per minute per milligram protein for plant ACP, earthworms ALP and cotton leafworm ALP, respectively. The inhibition kinetics indicated that atrazine and methomyl caused competitive–non-competitive inhibition of the enzymes. The relationships between estimates of K_m and V_max calculated from the Michaelis–Menten equation have been explored. The extent of the inhibition was different, as estimated by the values of the inhibition constant K_i that were found to be 3.34 × 10^?3, 1.12 × 10^?2 and 1.07 × 10^?2 mM for plant ACP, earthworms ALP and cotton leafworm ALP, respectively, with methomyl. In the case of atrazine, K_i were found to be 8.99 × 10^?3, 3.55 × 10^?2 and 1.36 × 10^?2 mM for plant ACP, earthworms ALP and cotton leafworm ALP, respectively.     

Delayed neurotoxicity in the wild mallard duckling caused by the organophosphorus insecticides cyanofenphos and leptophos

Abstract

The susceptibility of wild mallard ducklings to the delayed neurotoxic effect of the neurotoxic organophosphorus insecticides cyanofenphos and leptophos was evaluated following a daily dosing regimen. Ducklings were treated daily with either cyanofenphos or with leptophos at different dose levels for 90 days, or until they died, or became paralyzed. A control group of ducklings given corn oil at 1 ml/kg daily for 90 days was used for comparison. All treated birds were observed daily for any clinical signs of neurotoxicity during the course of this study. All of the surviving ducklings that were treated with cyanofenphos at 4 mg/kg/day or leptophos at 10 mg/kg/day developed clinical signs of delayed neurotoxicity after 7 to 11 weeks of intoxication. Symptoms included leg weakness, ataxia, severe ataxia and paralysis. The observed clinical signs were confirmed by histological changes found in the spinal cords of the treated birds. These changes were of the type associated with organophosphorus‐induced delayed neuropathy (OPIDN). These results demonstrate that wild mallard ducklings are susceptible to OPIDN and this avian species can be used in screening organophos‐phorus compounds for such effect.     

Effects of pH, temperature, and water quality on chloride removal with ultra-high lime with aluminum process.

The ultra high-lime with aluminum process (UHLA) has the ability to remove sulfate and chloride in addition to other scale-forming materials from recycled cooling water. Laboratory experiments have demonstrated that the UHLA process can achieve high chloride removal from recycled cooling water, and an equilibrium model was developed to describe chemical behavior during chloride removal. This paper describes the influence of pH, temperature, and initial chloride concentration on chloride removal by UHLA and identifies the precipitated solids formed during treatment. The optimum pH for maximum chloride removal efficiency was found to be 12 +/- 0.2. Chloride removal efficiency was higher at a high initial chloride concentration than at a low initial chloride concentration with the chemical doses used. Solids formed during UHLA treatment were identified by x-ray diffraction as calcium chloroaluminate, tricalcium hydroxyaluminate, and tetracalcium hydroxyaluminate. This supports the assumption of the equilibrium model that these compounds are present and form a solid solution.     

Pinning down vulnerability: from narratives to numbers

Social vulnerability analyses have typically relied upon narratives to capture the nuances of the concept. While narratives have enhanced our understanding of the multiple drivers of vulnerability, they have had limited influence on hazards and climate adaptation policy. This is partially a function of the different needs and goals of the policy and research communities. The former prioritises generalised quantitative information, while the latter is more concerned with capturing complexity. A theoretically driven and empirically tested quantitative vulnerability and capacities index (VCI) for use at the local scale is presented to help connect vulnerability research and policy. There are four versions of the index for use in rural and urban contexts at the household and community levels. There can be an infinite number of drivers of vulnerability, but the VCI draws upon 12 indicators to represent material, institutional and attitudinal aspects of differential vulnerability and capacities.     

Temporal patterns of road network development in the Brazilian Amazon

The Brazilian Amazon is a globally important ecosystem that is undergoing rapid development and land-use change. Roads are a key spatial determinant of land-use conversion and strongly influence the rates and patterns of habitat loss and represent a key component of models that attempt to predict the spatio-temporal patterns of Amazonian land-use change and the consequences of such changes. However, the spatio-temporal patterns of road network development are poorly understood and seldom quantified. Here, we used manually digitised satellite imagery at multiple temporal and spatial scales across the Brazilian Amazon to quantify and model the rate at which road networks are proliferating. We found that the road network grew by almost 17,000 km per year between 2004 and 2007. There was large spatial variation in road network density, with some municipalities having road densities as high as 0.5 km/km², and road network growth rates were highest in municipalities with an intermediate road network density. Simulations indicated that road network development within municipalities follows a logistic growth pattern through time, with most of the development occurring within a 39-year time period. This time period is similar to those of other boom and bust development dynamics observed in the Brazilian Amazon. Understanding the temporal patterns of road development will aid the development of better predictive land-use change models for the Amazon, given the key importance of roads as a predictor of deforestation in many existing models.