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Models for discrimination of toxic and nontoxic substances as well as models specifying the category of toxicity were built using data from a variety of toxicity studies.
The agency has ranked it in the same category of toxicity as malathion and Anvil, used against mosquitoes, and many over-the-counter pesticides.
The optimal gene number for classification depends on the category of toxicity.
Depending on the substance and category of toxicity, different time points were chosen for classification, as manifestation of toxicity was observed earlier for certain compounds than for others.
Our results indicate that accurate prediction of toxicity (including the category of toxicity) can be achieved using a small set consisting of a few up to some dozens of features (Table 3).
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Categories of toxicity differ not only in optimal feature number but also in prediction accuracy.
For this purpose, a control class and three categories of toxicity were initially defined: cholestasis, steatosis, and direct acting.
New in this study is the modeling of different categories of toxicity in conjunction with numeric measures for the classification confidence.
Since the initial establishment of the tiered, structure-based TTC values developed by Munro et al. (1996), some effort has gone into recognizing finer categories of toxicity, resulting in the publication of additional threshold values for more specific chemical classes (Table 1) (Kroes et al., 2004; Felter et al., 2009).
Baseline mean scores and LSM estimates of changes from baseline for the EQ-5D index-based scores and VAS scores associated with each category of skin toxicity are reported in Table 5a.
The method allows the definition of a hazard footprint of the unwanted product mixture, and of four indices, each characterizing the potential impacts of release scenarios with respect to a specific category of hazards: acute toxicity, chronic toxicity, carcinogenicity and ecotoxicity.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com