PubMed · 12073902
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Ken Ortolon. 2002. Bon appétit.. https://pubmed.ncbi.nlm.nih.gov/12073902/
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The objective of this study was to determine the effects of water activity (a(W); 0.900-0.995), temperature (5, 15, 25 and 30 degrees C), time of incubation (7-49 days) and their interactions on mycelial growth and deoxynivalenol (DON) production on irradiated wheat grain by two strains of Fusarium graminearum isolated from wheat ears in Argentina. Optimal a(W) levels for growth were in the range 0.950-0.995 with a temperature optima of 25 degrees C. Maximum growth rates were obtained at the highest a(W) (0.995) and 25 degrees C for both strains. No growth was observed at 5 degrees C regardless of the a(W) levels assayed. Both strains were able to growth at the lowest a(W) assayed (0.900), although the temperature ranges allowing growth at this minimal a(W) was 15-25 degrees C. DON was produced the most rapidly (7 days) when incubated at 25 degrees C and 0.995 a(W). All other conditions required 7-14 days before DON was produced on grain. Maximum amounts of DON for both strains were produced at the highest a(W) treatment (0.995) after 6 weeks at 30 degrees C. The range of DON concentrations varied considerably (5 to 140,000 ng g(-1)) depending on a(W) and temperature interaction treatments. Production of DON occurred over a narrower range of a(W) (0.995-0.95) than that for growth (0.995-0.90). DON was more rapidly produced at 25 degrees C but the maximum amount produced was at 30 degrees C. Two-dimensional profiles of a(W) x temperature were developed from these data to identify areas where conditions indicate a significant risk from DON accumulation.
The Food and Drug Administration (FDA) is classifying the oral rinse to reduce the adhesion of dental plaque device into class II (special controls). The special control that will apply to the device is the guidance document entitled "Class II Special Controls Guidance Document: Oral Rinse to Reduce the Adhesion of Dental Plaque." The agency is classifying the device into class II (special controls) in order to provide a reasonable assurance of safety and effectiveness of the device. Elsewhere in this issue of the Federal Register, FDA is publishing a notice of availability of a guidance document that is the special control for this device.
Product information databases are important prerequisites for providing data to poison centers (PC) to give adequate advice in cases of poisonings and for preparation of statistics as annual reports. For risk assessment measures, they can help for exposure assessments and for priority setting. A product database is a set of information of product and substance names, compositions, and uses of products. Data are provided due to national regulations as well as to national and international agreements between industry, international associations, e.g. the European Association of Poison Centres and Clinical Toxicologists (EAPCCT), and clinical toxicology institutions. They have different contents, i.e. complete formulations, frame formulations, and material safety data sheets. For definite identification of products, the product name should be readily taken from the labels and must be similar to the names provided by electronic media as databases. Products should be classified according to their use. The first system that has been prepared for that purpose is the ATC classification for pharmaceuticals. For chemicals, several systems e.g. the WHO-IPCS classification code, exist; the EU technical guidance document for risk assessment of chemicals is mentioning use categories, and they are used on national levels as well. For risk assessment purposes, statistics of poisonings and other health hazards are important as well as information about exposure. Linking cases of poisonings with product data enables risk assessors to perform statistical evaluations about health effects due to product use categories which can be compared to product compositions. If products are categorized by their use, information about use characteristics, such as frequencies and durations, can be derived. Hence, product categories can be taken to characterize scenarios and thus help for model estimations of exposure and respective doses.