Hashem A. Abu-Harirah

Background: This study sought to determine whether (1) evidence is available of interactions between anodal tDCS and oscillated tDCS stimulation patterns to increase the power of endogenous brain oscillations and (2) the frequency matching the applied anodal otDCS’s frequency and the brain’s dominant intrinsic frequency influence power shifting during stimulation pattern sessions by both anodal DCS and anodal oscillated DCS. Method: Rats received different anodal tDCS and otDCS stimulation patterns using 8.5 Hz and 13 Hz state-related dominant intrinsic frequencies of anodal otDCS. The rats were divided into groups with specific stimulation patterns: group A: tDCS–otDCS (8.5 Hz)–otDCS (13 Hz); group B: otDCS (8.5 Hz)–tDCS–otDCS (13 Hz); group C: otDCS (13 Hz)–tDCS–otDCS (8.5 Hz). Acute relative power changes (i.e., following 10 min stimulation sessions) in six frequency bands—delta (1.5–4 Hz), theta (4–7 Hz), alpha-1 (7–10 Hz), alpha-2 (10–12 Hz), beta-1 (12–15 Hz) and beta-2 (15–20 Hz)—were compared using three factors and repeated ANOVA measurement. Results: For each stimulation, tDCS increased theta power band and, above bands alpha and beta, a drop in delta power was observed. Anodal otDCS had a mild increasing power effect in both matched intrinsic and delta bands. In group pattern stimulations, increased power of endogenous frequencies matched exogenous otDCS frequencies—8.5 Hz or 13 Hz—with more potent effects in upper bands. The power was markedly more potent with the otDCS–tDCS stimulation pattern than the tDCS–otDCS pattern. Significance: The findings suggest that the otDCS–tDCS pattern stimulation increased the power in matched intrinsic oscillations and, significantly, in the above bands in an ascending order. We provide evidence for the successful corporation between otDCS (as frequency-matched guidance) and tDCS (as a power generator) rather than tDCS alone when stimulating a desired brain intrinsic band (herein, tES specificity).

Globally, multidrug-resistant bacteria affects wound infections, both hospital-acquired infections and community-acquired infections. The main isolates cultured from 607 subjects with wound infections were methicillin-resistant Staphylococcus aureus (MRSA), Escherichia coli, Pseudomonas aeruginosa, and Acinetobacter spp. [multidrug resistant (MDR)]. Gram-negative bacteria caused most of the infections (67%) compared with gram-positive bacteria. Diabetic patients tend to have wound infections with mixed causative agents compared with non-diabetic patients.