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PubMed · 7804647

Processing of samples.

M Gerngross
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Abstract

The Good Laboratory Practice (GLP) Processing Program at Texas A&M University provides a service that encompasses research and pilot scale processing of raw agricultural commodities while conforming to the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA), 40 CFR, Part 160. A general overview of a typical processing study is presented to include preliminary discussions with the study director, sample and protocol receipt, sample processing, fraction shipment, and processing report disposition. Atypical situations are also introduced to stress the need for improved communication and organization within the agrochemical industry. Examples of processed fractions are presented to clarify better the role of the processor in the chemical registration process. To describe the versatility required within this segment of the registration process, a new processing procedure is introduced.

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AgrochemicalsCrops, AgriculturalDustEdible GrainForms and Records ControlGuidelines as TopicLaboratoriesPesticide ResiduesSeedsSpecimen HandlingJournal Article

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M Gerngross. 1994. Processing of samples.. https://pubmed.ncbi.nlm.nih.gov/7804647/

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PubMed1996

Comparative inhibition of enzymes of human erythrocytes and plasma in vitro by agricultural chemicals.

Farm workers generally are exposed to a combination of synthetic agricultural chemicals and natural products while working in the fields. These biologically active compounds control infestation of tobacco by insects, and plant growth. We have investigated, in vitro, the effects of acephate (AP), cadmium (Cd), methamidophos (MAP), maleic hydrazide (MH), and nicotine (NI) on the activities of the erythrocyte enzymes delta-aminolevulinic acid dehydratase (ALAD), superoxide dismutase (SOD), and plasma cholinesterase (CHE). ALAD, SOD, and plasma CHE were assayed, using aminolevulinic acid, pyrogallol, or butyryl thiocholine as substrates, respectively. Different concentrations of the above chemicals were used to obtain minimum and maximum inhibition of the enzymes, and for the development of inhibition dose response curves. These curves were used to determine the concentration of each chemical required to inhibit 50% of enzyme activity (I50). The I50 concentrations of various chemicals for each enzyme were determined in mM for ALAD: AP=95.5, Cd=1.4x10(-3), MH=2.8, MAP=7.1, NI=60.8; for SOD: AP=1.2, Cd=0.8x10(-7), MH=0.04, MAP=0.42, NI=0.81; for CHE: AP=5.6, Cd=18. 8x10(-5), MAP=18.4x10(-4); CHE was not inhibited by MH and NI. Our data indicate that AP inhibited both SOD and CHE to a maximum of 91 and 87%, while MH inhibited both SOD and ALAD to a maximum 78 and 90%. However, SOD was the enzyme that was most sensitive to all the agricultural-chemicals tested in this study. The inhibition of these enzymes will enable the development of a sensitive biomarker and the assessment of long term health risks in farm workers.

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