Phenol degradation in a three-phase biofilm fluidized sand bed reactor

«Erworben im Rahmen der Schweizer Nationallizenzen (http://www.nationallizenzen.ch)»A previous three phase fluidized sand bed reactor design was improved by adding a draft tube to improve fluidization and submerged effluent tubes for sand separation. The changes had little influence on the oxygen transfer coefficients(KL a), but greatly reduced the aeration rate required for sand suspension. The resulting 12.5 dm3 reactor was operated with 1 h liquid residence time, 10.2dm3/min aeration rate, and 1.7-2.3 kg sand (0.25-0.35 mm diameter) for the degradation of phenol as sole carbon source. The KLa of 0.015 s−1 gave more than adequate oxygen transfer to support rates of 180g phenol/h · m3 and 216 g oxygen/h · m3. The biomass-sand ratios of 20-35 mg volatiles/g gave estimated biomass concentrations of 3-6 g volatiles/dm3. Offline kinetic measurements showed weak inhibition kinetics with constants ofKs=0.2 mg phenol/dm3, Ko2=0.5 mg oxygen/dm3 and KinI= 122.5 mg phenol/dm3. Very small biofilm diffusion effects were observed. Dynamic experiments demonstrated rapid response of dissolved oxygen to phenol changes below the inhibition level. Experimentally simulated continuous stagewise operation required three stages, each with 1 h residence time, for complete degradation of 300 mg phenol/dm3 · h

Acid-sensing ion channel 1 is involved in both axonal injury and demyelination in multiple sclerosis and its animal model.

Although there is growing evidence for a role of excess intracellular cations, particularly calcium ions, in neuronal and glial cell injury in multiple sclerosis, as well as in non-inflammatory neurological conditions, the molecular mechanisms involved are not fully determined. We previously showed that the acid-sensing ion channel 1 which, when activated under the acidotic tissue conditions found in inflammatory lesions opens to allow influx of sodium and calcium ions, contributes to axonal injury in experimental autoimmune encephalomyelitis, an animal model of multiple sclerosis. However, the extent and cellular distribution of acid-sensing ion channel 1 expression in neurons and glia in inflammatory lesions is unknown and, crucially, acid-sensing ion channel 1 expression has not been determined in multiple sclerosis lesions. Here we studied acute and chronic experimental autoimmune encephalomyelitis and multiple sclerosis spinal cord and optic nerve tissues to describe in detail the distribution of acid-sensing ion channel 1 and its relationship with neuronal and glial damage. We also tested the effects of amiloride treatment on tissue damage in the mouse models. We found that acid-sensing ion channel 1 was upregulated in axons and oligodendrocytes within lesions from mice with acute experimental autoimmune encephalomyelitis and from patients with active multiple sclerosis. The expression of acid-sensing ion channel 1 was associated with axonal damage as indicated by co-localization with the axonal injury marker beta amyloid precursor protein. Moreover, blocking acid-sensing ion channel 1 with amiloride protected both myelin and neurons from damage in the acute model, and when given either at disease onset or, more clinically relevant, at first relapse, ameliorated disability in mice with chronic-relapsing experimental autoimmune encephalomyelitis. Together these findings suggest that blockade of acid-sensing ion channel 1 has the potential to provide both neuro- and myelo-protective benefits in multiple sclerosis

T Cell-Mediated Autoimmune Disease Due to Low-Affinity Crossreactivity to Common Microbial Peptides (DOI:10.1016/j.immuni.2009.01.009)

There is a trend towards using accelerators to increase performance and energy efficiency of general-purpose processors. Adoption of accelerators, however, depends on the availability of tools to facilitate programming these devices. In this paper, we present techniques for automatically partitioning programs for execution on accelerators. We call the off-loaded code regions sub-algorithms, which are parts of the program that are loosely connected to the remainder of the program. We present three heuristics for automatically identifying sub-algorithms based on control flow and data flow properties. Analysis of SPECint and MiBench benchmarks shows that on average 12 sub-algorithms are identified (up to 54), covering the full execution time for 27 out of 30 benchmarks. We show that these sub-algorithms are suitable for off-loading them to accelerators by manually implementing sub-algorithms for 2 SPECint benchmarks on the Cell processor