Optimal blood glucose regulation of diabetic patients using single network adaptive critics

Diabetes is a long-term disease during which the body's production and use of insulin are impaired, causing glucose concentration level to increase in the bloodstream. Regulating blood glucose levels as close to normal as possible leads to a substantial decrease in long-term complications of diabetes. In this paper, an intelligent online feedback-treatment strategy is presented for the control of blood glucose levels in diabetic patients using single network adaptive critic (SNAC) neural networks (which is based on nonlinear optimal control theory). A recently developed mathematical model of the nonlinear dynamics of glucose and insulin interaction in the blood system has been revised and considered for synthesizing the neural network for feedback control. The idea is to replicate the function of pancreatic insulin, i.e. to have a fairly continuous measurement of blood glucose and a situation-dependent insulin injection to the body using an external device. Detailed studies are carried out to analyze the effectiveness of this adaptive critic-based feedback medication strategy. A comparison study with linear quadratic regulator (LQR) theory shows that the proposed nonlinear approach offers some important advantages such as quicker response, avoidance of hypoglycemia problems, etc. Robustness of the proposed approach is also demonstrated from a large number of simulations considering random initial conditions and parametric uncertainties. Copyright (C) 2009 John Wiley & Sons, Ltd.

Prevalence of multidrug-resistant Staphylococcus aureus in diabetics clinical samples

Antibiotic resistance in 40 Staphylococcus aureus clinical isolates from 110 diabetic patients (36%) was evaluated. Of these, 32 (80%) of the isolates showed multidrug-resistance to more than eight antibiotics and 35% isolates were found to be methicillin resistant S. aureus (MRSA). All 40 S. aureus strains (100%) screened from diabetic clinical specimens were resistant to penicillin, 63% to ampicillin, 55% to streptomycin, 50% to tetracycline and 50% to gentamicin. Where as low resistance rate was observed to ciprofloxacin (20%) and rifampicin (8%). In contrast, all (100%) S. aureus strains recorded susceptibility to teicoplanin, which was followed by vancomycin (95%). Genotypical examination revealed that 80% of the aminoglycoside resistant S. aureus (ARSA) have aminoglycoside modifying enzyme (AME) coding genes; however, 20% of ARSA which showed non-AME mediated (adaptive) aminoglycoside resistance lacked these genes in their genome. In contrast all MRSA isolates possessed mecA, femA genetic determinants in their genome.

Bacteriophage therapy for Staphylococcus aureus bacteremia in streptozotocin-induced diabetic mice

The protective effect of bacteriophage was assessed against experimental Staphylococcus aureus lethal bacteremia in streptozotocin (STZ) induced-diabetic and non-diabetic mice. Intraperitoneal administrations of S. aureus (RCS21) of 2 x 10(8) CFU caused lethal bacteremia in both diabetic and non-diabetic mice. A single administration of a newly isolated lytic phage strain (GRCS) significantly protected diabetic and nondiabetic mice from lethal bacteremia (survival rate 90% and 100% for diabetic and non-diabetic bacteremic groups versus 0% for saline-treated groups). Comparison of phage therapy to oxacillin treatment showed a significant decrease in RCS21 of 5 and 3 log units in diabetic and nondiabetic bacteremic mice, respectively. The same protection efficiency of phage GRCS was attained even when the treatment was delayed up to 4 h in both diabetic and non-diabetic bacteremic mice. Inoculation of mice with a high dose (10(10) PFU) of phage GRCS alone produced no adverse effects attributable to the phage per se. These results suggest that phages could constitute valuable prophylaxis against S. aureus infections, especially in immunocompromised patients. (C) 2010 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.