Scalable FPGA accelerator of the NRM algorithm for efficient stochastic simulation of large-scale biochemical reaction networks

Stochastic simulation of large-scale biochemical reaction networks, with thousands of reactions, is important for systems biology and medicine since it will enable the insilico experimentation with genome-scale reconstructed networks. FPGA based stochastic simulation accelerators can exploit parallelism, but have been limited on the size of biomodels they can handle. We present a high performance scalable System on Chip architecture for implementing Gibson and Bruck's Next Reaction Method efficiently in reconfigurable hardware. Our MPSoC uses aggressive pipelining at the core level and also combines many cores into a Network on Chip to also execute in parallel stochastic repetitions of complex biomodels, each one with up to 4K reactions. The performance of our NRM core depends only on the average outdegree of the biomodel's Dependencies Graph (DG) and not on the number of DG nodes (reactions). By adding cores to the NoC, the system's performance scales linearly and reaches GCycles/sec levels. We show that a medium size FPGA running at ~200 MHz deliver high speedup gains relative to a popular and efficient software simulator running on a very powerful workstation PC

Scalable FPGA accelerator of the NRM algorithm for efficient stochastic simulation of large-scale biochemical reaction networks

Stochastic simulation of large-scale biochemical reaction networks, with thousands of reactions, is important for systems biology and medicine since it will enable the insilico experimentation with genome-scale reconstructed networks. FPGA-based stochastic simulation accelerators can exploit parallelism, but have been limited on the size of biomodels they can handle. We present a high performance scalable System on Chip architecture for implementing Gibson and Bruck’s Next Reaction Method efficiently in reconfigurable hardware. Our MPSoC uses aggressive pipelining at the core level and also combines many cores into a Network on Chip to also execute in parallel stochastic repetitions of complex biomodels, each one with up to 4K reactions. The performance of our NRM core depends only on the average outdegree of the biomodel’s Dependencies Graph (DG) and not on the number of DG nodes (reactions). By adding cores to the NoC, the system’s performance scales linearly and reaches GCycles/sec levels. We show that a medium size FPGA running at similar to 200 MHz deliver high speedup gains relative to a popular and efficient software simulator running on a very powerful workstation PC

Increased bone resorption is implicated in the pathogenesis of bone loss in hemophiliacs: Correlations with hemophilic arthropathy and HIV infection

Osteoporosis has been recently recognized as a severe comorbidity factor in hemophilia. However, its pathogenesis is still obscure. We evaluated the incidence of osteoporosis in 90 hemophilia patients and investigated possible correlations with clinical and laboratory data. Out of the 90 patients, 80 (89%) had severe hemophilia, and 35 (38.9%) were human immunodeficiency virus (HIV)-positive. Hemophilic arthropahty was assessed using World Federation of Hemophilia clinical score and Petterson radiological score. Bone mineral density of the lumbar spine (LS) and femoral neck (FN) were measured using dual-energy X-ray absortiometry. Bone turnover was evaluated by the measurement of: (1) bone resorption markers [N-terminal cross-linking telopeptide of collagen type I (NTX), C-terminal cross-linking telopeptide of collagen type I (CTX), and tartrate-resistant acid phosphatase isoform-5b (TRACP-5b)], (2) bone formation markers [bone-alkaline phosphatase (bALP) and osteocalcin], and (3) osteoclast stimulators (receptor activator of nuclear factor-κB ligand, osteoprotegerin, and tumor necrosis factor-alpha). Osteopenia or osteoporosis was observed in 86% and 65% of the patients in FN and LS, respectively. Osteoporosis was more common among HIV-positive patients in both FN (65.3% vs 41.6%; p = 0.007) and LS (17.86% vs 5.41%, p = 0.004). The severity of osteoporosis in FN correlated with the patients' total clinical and radiological score (p = 0.001). Hemophilia patients showed increased osteoclastic activity (significant increase of TRACP-5b, NTX, and CTX), which was not accompanied by a comparable increased bone formation (reduced osteocalcin and borderline increase of bALP). In multivariate analysis, HIV infection (p=0.05) and total clinical score (p=0.001) were independent risk factors for osteoporosis development. We conclude that there is a high prevalence of osteoporosis among hemophiliacs, which is related to the severity of arthropathy and is enhanced by HIV infection. We report for the first time a high bone resorption that seems not to be balanced by a comparable bone formation. © 2009 Springer-Verlag