Toxicological effect of N, N, N', N'-tetramethylethylene on rat brain acetylcholinesterase.

N, N, N', N'-tetramethylethylenediamine (TEMED) is extensively used for initiating polymerization of acrylamide and bisacrylamide gel for electrophoresis and for inorganic complex structure formation. The present study evaluates the toxicological effect of TEMED on structures of rat brain acetylcholinesterase (AChE) activity. In vitro study showed that the Ki values for striatum, cortex, cerebellum and hypothalamus were found to be 1.24, 1.4, 1.45 and 1.47 mM. Kinetics studies indicated that TEMED caused mixed type of inhibition that is a combination of competitive and noncompetitive inhibition in striatum, cortex, hypothalamus and cerebellum. The result showed that km increased and V max decreased with increase in TEMED concentration. The IC50 values calculated for striatum, cortex, cerebellum and hypothalamus were found to be as 0.92, 0.92, 1.44 and 1.42 mM. The present study indicates that TEMED is a toxicant for brain via inhibition of AChE. Therefore, proper precaution should be made during its handling.

Toxicological effect of herbicides (diuron and bentazon) on snake venom and electric eel acetylcholinesterase.

The toxicological effects of the active ingredients of the herbicides diuron and bentazon on the activity of acetylcholinesterase (AChE) of krait (Bungarus sindanus) venom and electric eel (Electrophorus electricus) were studied. The diuron and entazon caused non-competitive inhibition of AChE from both species. For the venom AChE, the calculated IC50 for diuron and bentazon were found to be 3.25 and 0.14 µM, while for eel AChE, the respective IC50 values were 3.6 and 0.135 µM. In comparison, bentazon was a more potent inhibitor than diuron of AChE from both species. The insecticide lindane did not have any inhibitory effect on AChE activity in either species, even when tested at high concentrations (200-800 µM).

Complex principal component and correlation structure of 16 yeast genomic variables.

A quickly growing number of characteristics reflecting various aspects of gene function and evolution can be either measured experimentally or computed from DNA and protein sequences. The study of pairwise correlations between such quantitative genomic variables as well as collective analysis of their interrelations by multidimensional methods have delivered crucial insights into the processes of molecular evolution. Here, we present a principal component analysis (PCA) of 16 genomic variables from Saccharomyces cerevisiae, the largest data set analyzed so far. Because many missing values and potential outliers hinder the direct calculation of principal components, we introduce the application of Bayesian PCA. We confirm some of the previously established correlations, such as evolutionary rate versus protein expression, and reveal new correlations such as those between translational efficiency, phosphorylation density, and protein age. Although the first principal component primarily contrasts genomic change and protein expression, the second component separates variables related to gene existence and expressed protein functions. Enrichment analysis on genes affecting variable correlations unveils classes of influential genes. For example, although ribosomal and nuclear transport genes make important contributions to the correlation between protein isoelectric point and molecular weight, protein synthesis and amino acid metabolism genes help cause the lack of significant correlation between propensity for gene loss and protein age. We present the novel Quagmire database (Quantitative Genomics Resource) which allows exploring relationships between more genomic variables in three model organisms-Escherichia coli, S. cerevisiae, and Homo sapiens (http://webclu.bio.wzw.tum.de:18080/quagmire).