PubMed · 15417315
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J F KOK. 1950-05-13. [Anthelmintics].. https://pubmed.ncbi.nlm.nih.gov/15417315/
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Accumulation of o-chlorophenol (CP), 2,4-dichlorophenol (DCP), and atrazine (ATR), as single and mixed contaminants, from hydroponic solutions into roots and shoots of rice seedlings was studied following 48-h exposure of the plant roots. As single contaminants at low levels, the observed bioconcentration factors (BCFs) of CP and DCP with roots approximated the equilibrium values according to the partition-limited model. The BCF of atrazine with roots was about half the partition limit for unknown reasons. The BCFs of CP and ATR with shoots also approximated the partition limits, while the BCF for more lipophilic DCP with shoots was about half the estimated limit, due to insufficient water transport into plants for DCP. As mixed contaminants at low levels, the BCFs with both roots and shoots were comparable with those for the single contaminants; at high levels, the BCFs generally decreased because of the enhanced mixed-contaminant phytotoxicity, as manifested by the greatly reduced plant transpiration rate.
Mebendazole is a common benzimidazole anthelmintic that is water insoluble. It is reported to exist in three different polymorphic forms in the solid state, i.e. polymorph A, B and C. Form C is the pharmaceutically preferred form because of its increased aqueous solubility. This paper deals with the use of variable-temperature X-ray powder analysis (VTXRPD) to study the transformation of Form C. Results showed that Form C was stable and transformed to the more stable polymorph A at high temperature (>180 degrees C). This transformation is a first-order process with activation energy of 238 +/- 16 kJ/mole. Further studies showed that compression did not cause any significant changes in the crystal structure of polymorph C.
Helminth infections are a medical problem in the world nowadays. In this paper a novel atom-level chemical descriptor has been applied to estimate the anthelmintic activity. Total and local linear indices and linear discriminant analysis were used to obtain a quantitative model that discriminates between anthelmintic and non-anthelmintic drug-like compounds. The discriminant model has an accuracy of 90.11% in the training set, with a high Matthews' correlation coefficient (MCC=0.80). To assess the robustness and predictive power of the obtained model, internal (leave-n-out) and external validation process was performed. The QSAR model correctly classified 88.55% of compounds in this external prediction set, yielding a MCC of 0.77. Another LDA model was carried out to outline some conclusions about the possible modes of action of anthelmintic drugs. It has an accuracy of 93.50% in the training set, and 80.00% in the external prediction set. After that, the developed model was used in the virtual--in silico--screening and several compounds from the Merck Index, Negwer's Handbook and Goodman and Gilman were identified by the model as anthelmintic. Finally, the experimental assay of an organic chemical (a furylethylene derivative) by an in vivo test permits us to carry out an assessment of the model. An accuracy of 100% with the theoretical predictions was observed. These results suggest that the proposed method will be a good tool for studying the biological properties of drug candidates during the early state of the drug-development process.