Discovery of New Classes of Compounds that Reactivate Acetylcholinesterase Inhibited by Organophosphates.

Acetylcholinesterase (AChE) that has been covalently inhibited by organophosphate compounds (OPCs), such as nerve agents and pesticides, has traditionally been reactivated by using nucleophilic oximes. There is, however, a clearly recognized need for new classes of compounds with the ability to reactivate inhibited AChE with improved in vivo efficacy. Here we describe our discovery of new functional groups--Mannich phenols and general bases--that are capable of reactivating OPC--inhibited AChE more efficiently than standard oximes and we describe the cooperative mechanism by which these functionalities are delivered to the active site. These discoveries, supported by preliminary in vivo results and crystallographic data, significantly broaden the available approaches for reactivation of AChE.

Tomographic density imaging using modified DF–DBIM approach

Ultrasonic computed tomography based on back scattering theory is the most powerful and accurate tool in ultrasound based imaging approaches because it is capable of providing quantitative information about the imaged target and detects very small targets. The duple-frequency distorted Born iterative method (DF–DBIM), which uses density information along with sound contrast for imaging, is a promising approach for imaging targets at the level of biological tissues. With two frequencies f₁ (low) and f₂ (high) through Nf₁ and Nf₂ iterations respectively, this method is used to estimate target density along with sound contrast. The implications of duple-frequency fusion for the image reconstruction quality of density information along with sound contrast based ultrasound tomography have been analyzed in this paper. In this paper, we concentrate on the selection of parameters that is supposed to be the best to improve the reconstruction quality of ultrasound tomography. When there are restraints imposed on simulated scenarios to have control of the computational cost, the iteration number Nf₁ is determined resulting in giving the best performance. The DF–DBIM is only effective if there are a moderate number of iterations, transmitters and receivers. In case that the number of transducers is either too large or too small, a result of reconstruction which is better than that of the single frequency approach is not produced by the implementation of DF–DBIM. A fixed sum N(iter) of Nf₁ and Nf₂ was given, the investigation of simulation results shows that the best value of Nf₁ is [N(iter)/2 − 1]. The error, when applying this way of choosing the parameters, will be normalized with the reduction of 56.11%, compared to use single frequency as used in the conventional DBIM method. The target density along with sound contrast is used to image targets in this paper. It is a fact that low-frequency offers fine convergence, and high-frequency offers fine spatial resolution. Wherefore, this technique can effectively expand DBIM's applicability to the problem of biological tissue reconstruction. Thanks to the usage of empirical data, this work will be further developed prior to its application in reality.