The role of xenobiotic metabolizing enzymes in arylamine toxicity and carcinogenesis: Functional and localization studies

In both animal models and humans, the first and obligatory step in the activation of arylamines is N-hydroxylation. This pathway is primarily mediated by the phase-I enzymes CYP1A1, CYP1A2 and CYP4B1. In the presence of flavonoids such as alpha-naphthoflavone and flavone, both CYP3A4 and CYP3A5 have also been shown to play a minor role in the activation of food-derived heterocyclic amines. The further activation of N-hydroxyarylamines by phase-II metabolism can involve both N,O-acetylation and N,O-sulfonation catalyzed by N-acetyltransferases (NAT1 and NAT2) and sulfotransferases, respectively. Using an array of techniques, we have been unable to detect constitutive CYP1A expression in any segments of the human gastrointestinal tract. This is in contrast to the rabbit where CYP1A1 protein was readily detectable on immunoblots in microsomes prepared from the small intestine. In humans, CYP3A3/3A4 expression was detectable in the esophagus and all segments of the small intestine. Northern blot analysis of eleven human colons showed considerable heterogeneity in CYP3A mRNA between individuals, with the presence of two mRNA species in same subjects. Employing the technique of hybridization histochemistry (also known as in situ hybridization), CYP4B1 expression was observed in some human colons but not in the liver or the small intestine. Hybridization histochemistry studies have also demonstrated variable NAT1 and NAT2 expression in the human gastrointestinal tract. NAT1 and NAT2 mRNA expression was detected in the human liver, small intestine, colon, esophagus, bladder, ureter, stomach and lung. Using a general aryl sulfotransferase riboprobe (HAST1), we have demonstrated marked sulfotransferase expression in the human colon, small intestine, lung, stomach and liver. These studies demonstrate that considerable variability exists in the expression of enzymes involved in the activation of aromatic amines in human tissues. The significance of these results in relation to a role for heterocyclic amines in colon cancer is discussed.

Virtual plants - integrating architectural and physiological models

Recent advances in computer technology have made it possible to create virtual plants by simulating the details of structural development of individual plants. Software has been developed that processes plant models expressed in a special purpose mini-language based on the Lindenmayer system formalism. These models can be extended from their architectural basis to capture plant physiology by integrating them with crop models, which estimate biomass production as a consequence of environmental inputs. Through this process, virtual plants will gain the ability to react to broad environmental conditions, while crop models will gain a visualisation component. This integration requires the resolution of the fundamentally different time scales underlying the approaches. Architectural models are usually based on physiological time; each time step encompasses the same amount of development in the plant, without regard to the passage of real time. In contrast, physiological models are based in real time; the amount of development in a time step is dependent on environmental conditions during the period. This paper provides a background on the plant modelling language, then describes how widely-used concepts of thermal time can be implemented to resolve these time scale differences. The process is illustrated using a case study. (C) 1997 Elsevier Science Ltd.

Management of acute psychostimulant toxicity

Psychostimulants produce a broad range of effects. Adverse effects can exist on a spectrum of severity from minor symptoms to life threatening toxicity. Although regular use or use of high doses increases risk of adverse events, many adverse events requiring emergency intervention may occur even in the naïve user.

Standardizing assessment of adverse effects in rheumatology clinical trials. Status of OMERACT Toxicity Working Group March 2000: Towards a common understanding of comparative toxicity/safety profiles for antirheumatic therapies

This paper describes the background and current status of an OMERACT facilitated effort to improve the consistency of adverse event reporting in rheumatology clinical trials, The overall goal is the development of an adverse event assessment tool that would provide a basis for use of common terminology and improve the consistency of reporting severity of side effects within rheumatology clinical trials and during postmarketing surveillance. The resulting Rheumatology Common Toxicity Criteria Index encompassed the following organ systems: allergic/immunologic, cardiac, ENT, gastrointestinal, musculoskeletal, neuropsychiatric, ophthalmologic, pulmonary and skin/integument. Before this tool is widely accepted, its validity, consistency, and feasibility need to be assessed in clinical trials.

Patient based method of assessing adverse events in clinical trials in rheumatology: the revised Stanford Toxicity Index

We describe the progress towards developing a patient rated toxicity index that meets all of the patient-important attributes defined by the OMERACT Drug Safety Working Party, These attributes are frequency, severity. importance to patient, importance to the clinician, impact on economics, impact on activities, and integration of adverse effects with benefits. The Stanford Toxicity Index (STI) has been revised to collect all attributes with the exception of impact on activities. However, since the STI is a part of the Health Assessment Questionnaire (HAQ). impact on activities is collected by the HAQ. In particular, a new question asks patients to rate overall satisfaction, taking into consideration both benefits and adverse effects. The nest step in the development of this tool is to ensure that the STI meets the OMERACT filter of truth, discrimination, and feasibility. Although truth and feasibility have been confirmed by comparisons within the ARAMIS database, discrimination needs to be assessed in clinical trials.

Supervisory control of wastewater treatment plants by combining principal component analysis and fuzzy c-means clustering

In this paper a methodology for integrated multivariate monitoring and control of biological wastewater treatment plants during extreme events is presented. To monitor the process, on-line dynamic principal component analysis (PCA) is performed on the process data to extract the principal components that represent the underlying mechanisms of the process. Fuzzy c-means (FCM) clustering is used to classify the operational state. Performing clustering on scores from PCA solves computational problems as well as increases robustness due to noise attenuation. The class-membership information from FCM is used to derive adequate control set points for the local control loops. The methodology is illustrated by a simulation study of a biological wastewater treatment plant, on which disturbances of various types are imposed. The results show that the methodology can be used to determine and co-ordinate control actions in order to shift the control objective and improve the effluent quality.