Studies have been made on the formation of bubbles in mercury and in liquid silver by using a single silica nozzle facing upward. Nozzles used in the experiments are of the sizes 0.22-0.82cm in O.D. and 0.10-0.30cm in I.D. The gas-chamber volume V, and the gas-flow rate Vg are varied from 0.15 to 200 cc and from 0.0167 to 70 cc/sec, respectively. The size of bubbles is determined from the frequency of bubble formation and the gasflow rate. The observed bubble size is compared with that calculated from theoretical or experimental equations obtained for wetted nozzles. The experimental values of bubble size do not agree with the values calculated using the inner diameter of the nozzle. On the other hand, when the non-wettability of the nozzle in liquid metals is taken into account and the outer diameters are adopted as the nozzle diameters in the equations, close agreement between the experimental and calculated results is obtained. Thus, it is shown that the quantitative estimation of the size of bubbles formed from a single nozzle in liquid metals is possible.

SynopsisFluid flow and mixing characteristics in a molten metal bath are analyzed for inert gas injection through a nozzle at the center of the vessel bottom. It is postulated that the bath consists of two zones; bubble plume zone where gas-liquid mixtures flow upward and annular zone where liquid flows downward. The analysis is made by setting up a steady-state energy balance for the liquid phase. The liquid velocity in the plume zone, the liquid circulating flow rate and the mixing time are calculated for various injecting conditions and correlated as simple functions of gas flow rate, liquid depth and cross-sectional areas of both the plume zone and the vessel. It is found that the cross-sectional area of the plume zone has a significant influence on the circulating flow. Large cross-sectional area of the plume zone is favorable for mixing in the bath. The calculated results of circulating flow rate and mixing time agree with the experimental results obtained previously. I. IntroductionGas injection into molten steel is widely used in steelmaking processes. Fluid-flow phenomena and mixing in the processes have profound influences on the steelmaking reaction rate. Several experimental and theoretical studies have been made on circulating flow and mixing time in the molten steel bath.l-3~ Nakanishi et al.'> obtained a quantitative correlation between mixing time and stirring power of gas. Szekely et a1.2~ interpreted their experimental measurements for tracer dispersion and dissolution patterns of immersed graphite rods in argon-stirred ladles by using a two equation model of turbulent circulating flow. Recently Hsiao et a1.3~ determined the flow velocity of molten steel in argon-stirred ladles by measuring the drag force exerted on a probe immersed in molten steel.In the chemical engineering field, many models of circulating flow in bubble columns are proposed on the basis of momentum balance4-7) and energy balance.8-10> From the models one can calculate the flow velocity and gas holdup.The present study is concerned with analyzing circulating flow and mixing time in a gas-stirred molten metal bath. The analysis is made by setting up a steady-state energy balance for the liquid phase. The liquid velocity in the bubble plume zone and the mixing time are calculated under various injecting conditions. Effects of various factors influencing the fluid-flow phenomena and the mixing time are investigated.

To promote the functional restoration of the nervous system following injury, it is necessary to provide optimal extracellular signals that can induce neuronal regenerative activities, particularly neurite formation. This study aimed to examine the regulation of neuritogenesis by temperature-controlled repeated thermal stimulation (TRTS) in rat PC12 pheochromocytoma cells, which can be induced by neurotrophic factors to differentiate into neuron-like cells with elongated neurites. A heating plate was used to apply thermal stimulation, and the correlation of culture medium temperature with varying surface temperature of the heating plate was monitored. Plated PC12 cells were exposed to TRTS at two different temperatures via heating plate (preset surface temperature of the heating plate, 39.5°C or 42°C) in growth or differentiating medium for up to 18 h per day. We then measured the extent of growth, neuritogenesis, or acetylcholine esterase (AChE) activity (a neuronal marker). To analyze the mechanisms underlying the effects of TRTS on these cells, we examined changes in intracellular signaling using the following: tropomyosin-related kinase A inhibitor GW441756; p38 mitogen-activated protein kinase (MAPK) inhibitor SB203580; and MAPK/extracellular signal-regulated kinase (ERK) kinase (MEK) inhibitor U0126 with its inactive analog, U0124, as a control. While a TRTS of 39.5°C did not decrease the growth rate of cells in the cell growth assay, it did increase the number of neurite-bearing PC12 cells and AChE activity without the addition of other neuritogenesis inducers. Furthermore, U0126, and SB203580, but not U0124 and GW441756, considerably inhibited TRTS-induced neuritogenesis. These results suggest that TRTS can induce neuritogenesis and that participation of both the ERK1/2 and p38 MAPK signaling pathways is required for TRTS-dependent neuritogenesis in PC12 cells. Thus, TRTS may be an effective technique for regenerative neuromedicine.

Canagliflozin is a recently developed sodium-glucose cotransporter (SGLT) 2 inhibitor that promotes renal glucose excretion and is considered to inhibit renal SGLT2 from the luminal side of proximal tubules. Canagliflozin reportedly inhibits SGLT1 weakly and suppresses postprandial plasma glucose, suggesting that it also inhibits intestinal SGLT1. However, it is difficult to measure the drug concentrations of these assumed sites of action directly. The pharmacokinetic-pharmacodynamic (PK/PD) relationships of canagliflozin remain poorly characterized. Therefore, a physiologically based pharmacokinetic (PBPK) model of canagliflozin was developed based on clinical data from healthy volunteers and it was used to simulate luminal concentrations in intestines and renal tubules. In small intestine simulations, the inhibition ratios for SGLT1 were predicted to be 40%-60% after the oral administration of clinical doses (100-300 mg/day). In contrast, inhibition ratios of canagliflozin for renal SGLT2 and SGLT1 were predicted to be approximately 100% and 0.2%-0.4%, respectively. These analyses suggest that canagliflozin only inhibits SGLT2 in the kidney. Using the simulated proximal tubule luminal concentrations of canagliflozin, the urinary glucose excretion rates in canagliflozin-treated diabetic patients were accurately predicted using the renal glucose reabsorption model as a PD model. Because the simulation of canagliflozin pharmacokinetics was successful, this PBPK methodology was further validated by successfully simulating the pharmacokinetics of dapagliflozin, another SGLT2 inhibitor. The present results suggest the utility of this PBPK/PD model for predicting canagliflozin concentrations at target sites and help to elucidate the pharmacological effects of SGLT1/2 inhibition in humans. Copyright © 2016 John Wiley & Sons, Ltd.