Inhibition of pancreatic carboxypeptidase A: A possible mechanism of interaction between penicillic acid and ochratoxin A

Abstract

Penicillic acid and ochratoxin A are environmentally important toxic fungal metabolites (mycotoxins) that are synergistic in combination. The effects of penicillic acid on the pancreatic enzyme, :arboxypeptidase A were investigated in vitro and in vivo. A broad range of inhibition in vitro of the enzyme by PA was demonstrated with a half‐maximal inhibitory concentration equal to 1.1 x 10^‐4M PA. Inhibition of carboxypeptidase A was time and temperature dependent, and resulted in decreased conversion of parent ochratoxin A to the non‐toxic metabolite, ochratoxin alpha. Studies in vivo demonstrated a penicillic acid‐dependent inhibition of pancreatic carboxypeptidase A activity in the mouse and the chicken following multiple oral exposure. It is postulated that the mode of toxic interaction of the two mycotoxins may be due, in part, to impaired detoxification of ochratoxin A through peni‐cillic acid depletion of carboxypeptidase A activity.     

Legislative Prospects

Some of you would have me discuss today the present politics of clean air, some of you would have me discuss in detail the pending amendments to the Clean Air Act, some would have me discuss the failings and failures of the Clean Air Act. I am going to discuss each of these subjects. I want today to put the Clean Air Act and especially it’s 1976 amendments into context. That context is political, it involves the pending amendments and it involves more than 5 years of experience and administrative and judicial interpretation.     

The impact of the board of directors on business climate change management: case of Brazilian companies

Mitigation and Adaptation Strategies for Global Change - The corporate sector is one of the main emitters in the world due to the production process and therefore is identified as a major...     

Analyzing alternative bio-waste feedstocks for potential biodiesel production using time domain (TD)-NMR

Production of biodiesel is currently limited due to lack of economically beneficial feedstocks. Suitability of municipal wastewater sludge and olive mill waste as feedstocks for biodiesel production was evaluated. The various bio-waste sources were analyzed for their oil content and fatty acid composition using conventional analyses complemented with time domain (TD)-NMR analysis. TD-NMR, a rapid non-destructive method newly applied in this field, yielded good correlations with conventional methods. Overall biodiesel yields obtained by TD-NMR analysis were 7.05% and 9.18% (dry wt) for olive mill pomace and liquid wastes, and 11.92%, 7.07%, and 4.65% (dry wt) for primary, secondary, and anaerobically stabilized sludge, respectively. Fatty acid analysis indicated fundamental suitability of these agro-industrial waste resources for biodiesel production. Evaluation of bio-waste materials by TD-NMR revealed the potential of this tool to identify waste-oil sources cost effectively and quickly, supporting expansion of a sustainable biodiesel industry in Israel and other regions.     

ALTERNATIVE FUTURES USING THE WOLLMAN-BONEM MODELS1

Alternative futures are defined to be mutually consistent alternative combinations of assumed sets of future conditions. Alternative futures are employed in conjunction with the Wollman-Bonem model to project future water use. The model solutions under different alternative futures provide an indication of the direction and relative magnitude of changes in water use, both in quantity and quality, that may result from changes in policy-influenced variables, technology, and other data. The Wollman-Bonem model is employed in this paper as a tool to illustrate the alternative futures concept. The model can best be cast as an economic model. The model solutions are not given as a set of formal projections, but as various possible water-use-over-time curves. This should aid in disspelling the erroneous idea that it is possible to make distant projections of water use as a single curve. Multiple curves suggest that water use is really a function of many variables.