Dialysis clearance of buflomedil in hemodialysed patients

Buflomedil (CAS 55837-25-7, Fonzylane) is a peripherally vasoactive drug which improves nutritional blood flow in ischaemic tissue of patients with peripheral vascular disease by the way of an increase of perfusion in the microcirculation. Ten hemodialysed patients with chronic renal failure treated with intravenous infusion of 400 mg of buflomedil during 4 h of dialysis were included in the first study. This study was carried out to determine the dialysis plasma clearance and the amount of drug dialysed during the first intravenous administration of buflomedil. The dialysis clearance calculated from the amount recovered in dialysate was (mean +/- SD) 25.4 +/- 25.6 ml/min. The drug recovery resulting from hemodialysis represented a small fraction of the dose (< or = 5%). A second study was carried out to determine the accumulation of buflomedil in chronic hemodialysed patient. The drug concentration were measured before and at the end (4 h) of the infusion of buflomedil in six other patients maintained on intermittent hemodialysis (3 per week) for 4 weeks. The average Cmin and Cmax were stable during the 12 successive dialyses (mean +/- SD intervals were between 0.36 +/- 0.53 and 0.66 +/- 0.79 microgram/ml for Cmin and between 5.15 +/- 2.19 and 7.37 +/- 1.76 micrograms/ml for Cmax), showing no trend of accumulation of buflomedil. These results agree with the pharmacokinetics of the drug which is mainly metabolised in the liver and has a low renal clearance. Dialysis is unable to modify significantly the plasma concentration of the drug in regularly dialysed patients.     

Mean-field Theory and Synchronization in Random Recurrent Neural Networks

In this paper, we first present a new mathematical approach, based on large deviation techniques, for the study of a large random recurrent neural network with discrete time dynamics. In particular, we state a mean field property and a law of large numbers, in the most general case of random models with sparse connections and several populations. Our results are supported by rigorous proofs. Then, we focus our interest on large size dynamics, in the case of a model with excitatory and inhibitory populations. The study of the mean field system and of the divergence of individual trajectories allows to define different dynamical regimes in the macroscopic parameters space, which include chaos and collective synchronization phenomenons. At last, we look at the behavior of a particular finite-size system submitted to gaussian static inputs. The system adapts its dynamics to the input signal, and spontaneously produces dynamical transitions from asynchronous to synchronous behaviors, which correspond to the crossing of a bifurcation line in the macroscopic parameters space.