Clinical microbiology study of diabetic foot ulcer in Iran; pathogens and antibacterial susceptibility

The aim of this study was to investigate microbial pathogens and their antibiotic susceptibility profile in infected diabetic foot ulcers in Iranian patients. This was a one-year cross sectional study on diabetic patients with infected diabetic foot ulcer at Shariati Teaching Hospital, Tehran, Iran. Grade of ulcer was determined by Wagner's criteria. Specimens were obtained from the base of ulcer, deep part of the wound or aspiration and were tested with gram staining and antibacterial susceptibility was determined with both disk diffusion and E-Test methods. Total of 546 pathogens were isolated from 165 ulcers of 149 patients. Gram positive aerobes including Enterococcal species and methicillin resistant Staphylococcus aureus (S. aureus) (21.4 and 19.4%, respectively) were identified as the most common pathogens followed by Gram negative isolates including Escherichia coli and Pseudomonas-aeruginosa (12.6 and 5.4%, respectively). The majority of wounds were classified as Wagner grades 2 and 3 (15.7 and 75.7%). Appropriate empiric treatment to cover both these Gram positive and Gram negative pathogens is crucially important

Large scale bioinformatics data mining with parallel genetic programming on graphics processing units

Abstract A suitable single instruction multiple data GP interpreter can achieve high (Giga GPop/second) performance on a SIMD GPU graphics card by simultaneously running multiple diverse members of the genetic programming population. SPMD dataflow parallelisation is achieved because the single interpreter treats the different GP programs as data. On a single 128 node parallel nVidia GeForce 8800 GTX GPU, the interpreter can out run a compiled approach, where data parallelisation comes only by running a single program at a time across multiple inputs. The RapidMind GPGPU Linux C++ system has been demonstrated by predicting ten year+ outcome of breast cancer from a dataset containing a million inputs. NCBI GEO GSE3494 contains hundreds of Affymetrix HG-U133A and HG-U133B GeneChip biopsies. Multiple GP runs each with a population of five million programs winnow useful variables from the chaff at more than 500 million GPops per second. Sources available via FTP.