Nerve agents interaction sarin

Interaction of CarbE with nerve agents follows a kinetic of first order characterized by inhibition of CarbE at the active site serine residue described by a bimolecular rate constant, ki (Maxwell and Brecht, 2001). For noncharged nerve agents (e.g. sarin and soman) the ki of rat serum CarbE was found to be >10 M min whereas cationic substrates (e.g. VX) are converted with poor reactivity (ki < 10" M min ). This specificity is explained by the electrostatic characteristics of the large active site containing only a few cation-II bonding and anionic residues (Maxwell and Brecht, 2001 Satoh and Hosokawa, 2006). 

For biosensor applications, it is reported that a change in polypyrrole absorbance is induced when the material is exposed to dimethyl-methyl phoshopnate (DMMP) [32], as shown in Fig. 16, where 40% reduction occurred in the UV/Vis absorbance band. DMMP is a chemical precursor to the nerve agent sarin. It is reported that the DMMP interacts electronically with the polypyrrole to increase the amount of free... 

Somani and Husain described the low-dose toxicity of tabun, sarin, soman, and VX under normal as well as stressful conditions. These authors explained the interaction of enviromnental and physical stress on cholinergic as well as noncholinergic effects induced by low-dose exposure to nerve agents and their potential for additive or synergistic neuropathologic sequelae. Under certain conditions, nerve agents may... 

H]L-PIA) to the brain membranes in a dose-dependent manner. Soman was fonnd to be five and nine times more effective than tabun and sarin, respectively, in inhibiting [ H]L-PIA binding. They snggested that nerve agents could interact directly at the A1 adenosine receptors, which could subsequently mediate changes in permeability of the synaptic membrane, with possible effects on Na and/or Ca conductance. 

As stated, a number of PBPK/PD models have been developed for individual nerve agents (sarin, VX, soman, and cyclosarin) in multiple species. Chapter 58 in the current volume discusses tiie development of such models. Standalone PBPK or compartmental models have also been developed that describe the pharmacokinetics of certain countermeasures, such as diazepam (Igari et al., 1983 Gueorguieva et al., 2004) and oximes (Stemler et al., 1990 Sterner et al., 2013). However, to date, few models for specific countermeasures have been harmonized and linked to NA PBPK/PD models to be able to quantitatively describe their pharmacokinetic and pharmacodynamic interactions. This is partly due to the fact that most PBPK/ PD models developed for NAs and other OPs focus on the inhibition of ChEs as the critical endpoint. The lack of a mathematical description of the disruption of other complex biochemical pathways presents a problem for linking these NA models to those of many countermeasures. For example, the conventional NA countermeasures, atropine and diazepam, as well as many novel countermeasures, do not directly impact ChE kinetics because they act at sites distinct from the active site of the esterases, such as muscarinic, GABA, or NMDARs (Figure 69.2). 

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