Shorter courses of parenteral antibiotic therapy do not appear to influence response rates for children with acute hematogenous osteomyelitis: a systematic review

BACKGROUND: Acute hematogenous osteomyelitis (AHO) occurs primarily in children and is believed to evolve from bacteremia followed by localization of infection to the metaphysis of bones. Currently, there is no consensus on the route and duration of antimicrobial therapy to treat AHO. METHODS: We conducted a systematic review of a short versus long course of treatment for AHO due primarily to Staphylococcus aureus in children aged 3 months to 16 years. We searched Medline, Embase and the Cochrane trials registry for controlled trials. Clinical cure rate at 6 months was the primary outcome variable, and groups receiving less than 7 days of intravenous therapy were compared with groups receiving one week or longer of intravenous antimicrobials. RESULTS: 12 eligible prospective studies, one of which was randomized, were identified. The overall cure rate at 6 months for the short course of intravenous therapy was 95.2% (95% CI = 90.4, 97.7) compared to 98.8% (95% CI = 93.6, 99.8) for the longer course of therapy. There was no significant difference in the duration of oral therapy between the two groups. CONCLUSIONS: Given the potential increased morbidity and cost associated with longer courses of intravenous therapy, this finding should be confirmed through a randomized controlled equivalence trial

Spike-Based Bayesian-Hebbian Learning of Temporal Sequences

Many cognitive and motor functions are enabled by the temporal representation and processing of stimuli, but it remains an open issue how neocortical microcircuits can reliably encode and replay such sequences of information. To better understand this, a modular attractor memory network is proposed in which meta-stable sequential attractor transitions are learned through changes to synaptic weights and intrinsic excitabilities via the spike-based Bayesian Confidence Propagation Neural Network (BCPNN) learning rule. We find that the formation of distributed memories, embodied by increased periods of firing in pools of excitatory neurons, together with asymmetrical associations between these distinct network states, can be acquired through plasticity. The model's feasibility is demonstrated using simulations of adaptive exponential integrate-and-fire model neurons (AdEx). We show that the learning and speed of sequence replay depends on a confluence of biophysically relevant parameters including stimulus duration, level of background noise, ratio of synaptic currents, and strengths of short-term depression and adaptation. Moreover, sequence elements are shown to flexibly participate multiple times in the sequence, suggesting that spiking attractor networks of this type can support an efficient combinatorial code. The model provides a principled approach towards understanding how multiple interacting plasticity mechanisms can coordinate hetero-associative learning in unison