Limb salvage after gas gangrene: a case report and review of the literature

Gas gangrene is a necrotic infection of soft tissue associated with high mortality, often necessitating amputation in order to control the infection. Herein we present a case of gas gangrene of the arm in an intravenous drug user with a history of intramuscular injections with normal saline in the shoulder used to provoke pain for recovery after drug induced coma. The patient was early treated with surgery and antibiotics rendering possible the preservation of the limb and some of its function. Additionally, a review of the literature regarding case reports of limb salvage after gas gangrene is presented

Optimal wind farm sitting using high-resolution digital elevation models and randomized optimization

We investigate the problem of wind farm design in isolated mountainous areas. We first describe a remote sensing approach for the terrain reconstruction of complex terrains. We then employ a well--known evolutionary optimization algorithm to find the optimal wind farm layout. Although the algorithm has been efficiently used for off--shore or smooth on--shore areas, we show that its performance is significantly affected by the complex topography. Moreover, we illustrate how a priori information can be exploited to improve both the computational time and efficiency of the optimization algorithm

Limb salvage after gas gangrene: a case report and review of the literature

Abstract Gas gangrene is a necrotic infection of soft tissue associated with high mortality, often necessitating amputation in order to control the infection. Herein we present a case of gas gangrene of the arm in an intravenous drug user with a history of intramuscular injections with normal saline in the shoulder used to provoke pain for recovery after drug induced coma. The patient was early treated with surgery and antibiotics rendering possible the preservation of the limb and some of its function. Additionally, a review of the literature regarding case reports of limb salvage after gas gangrene is presented.</p

Stochastic dynamics of genetic networks: modelling and parameter identification

Identification of regulatory networks is typically based on deterministic models of gene expression. Increasing experimental evidence suggests that the gene regulation process is intrinsically random. To ensure accurate and thorough processing of the experimental data, stochasticity must be explicitly accounted for both at the modelling stage and in the design of the identification algorithms. Results: We propose a model of gene expression in prokaryotes where transcription is described as a probabilistic event, whereas protein synthesis and degradation are captured by first order deterministic kinetics. Based on this model and assuming that the network of interactions is known, a method for estimating unknown parameters such as synthesis and binding rates from the outcomes of multiple time course experiments is introduced. The method accounts naturally for sparse, irregularly sampled and noisy data and is applicable to gene networks of arbitrary size. The performance of the method is evaluated on a model of nutrient stress response in Escherichia coli