scholarly journals Multidentate Ligand Kinetics. IV. Computer Simulation of the Steady State of the Free Ligands in a Coordination Chain Reaction

1982 ◽  
Vol 55 (8) ◽  
pp. 2541-2546
Author(s):  
Tetsuo Katsuyama ◽  
Toshihiko Kumai
Keyword(s):  
Computer Simulation ◽  
Steady State ◽  
Chain Reaction ◽  
Multidentate Ligand

Dynamic Stability of an Impact System Connected With Rock Drilling

1969 ◽  
Vol 36 (4) ◽  
pp. 743-749 ◽  
Author(s):  
C. C. Fu
Keyword(s):  
Computer Simulation ◽  
Exact Solution ◽  
Steady State ◽  
Asymptotic Stability ◽  
Piecewise Linear ◽  
Steady State Solution ◽  
External Excitation ◽  
Rock Drilling ◽  
Impact System ◽  
Number Of Cycles

This paper deals with asymptotic stability of an analytically derived, synchronous as well as nonsynchronous, steady-state solution of an impact system which exhibits piecewise linear characteristics connected with rock drilling. The exact solution, which assumes one impact for a given number of cycles of the external excitation, is derived, its asymptotic stability is examined, and ranges of parameters are determined for which asymptotic stability is assured. The theoretically predicted stability or instability is verified by a digital computer simulation.

8-Hydroxylation and Glucuronidation of Mirtazapine in Japanese Psychiatric Patients: Significance of the Glucuronidation Pathway of 8-Hydroxy-Mirtazapine

2019 ◽  
Vol 52 (05) ◽  
pp. 237-244
Author(s):  
Masataka Shinozaki ◽  
Jason Pierce ◽  
Yuki Hayashi ◽  
Takashi Watanabe ◽  
Taro Sasaki ◽  
...  
Keyword(s):  
Body Weight ◽  
Steady State ◽  
Plasma Levels ◽  
High Performance ◽  
Psychiatric Patients ◽  
Plasma Concentrations ◽  
Steady State Concentration ◽  
Chain Reaction ◽  
Polymerase Chain ◽  
State Concentration

Abstract Introduction  To investigate the metabolism of mirtazapine (MIR) in Japanese psychiatric patients, we determined the plasma levels of MIR, N-desmethylmirtazapine (DMIR), 8-hydroxy-mirtazapine (8-OH-MIR), mirtazapine glucuronide (MIR-G), and 8-hydroxy-mirtazapine glucuronide (8-OH-MIR-G). Methods  Seventy-nine Japanese psychiatric patients were treated with MIR for 1–8 weeks to achieve a steady-state concentration. Plasma levels of MIR, DMIR, and 8-OH-MIR were determined using high-performance liquid chromatography. Plasma concentrations of MIR-G and 8-OH-MIR-G were determined by total MIR and total 8-OH-MIR (i. e., concentrations after hydrolysis) minus unconjugated MIR and unconjugated 8-OH-MIR, respectively. Polymerase chain reaction was used to determine CYP2D6 genotypes. Results  Plasma levels of 8-OH-MIR were lower than those of MIR and DMIR (median 1.42 nmol/L vs. 92.71 nmol/L and 44.96 nmol/L, respectively). The plasma levels (median) of MIR-G and 8-OH-MIR-G were 75.00 nmol/L and 111.60 nmol/L, giving MIR-G/MIR and 8-OH-MIR-G/8-OH-MIR ratios of 0.92 and 59.50, respectively. Multiple regression analysis revealed that smoking was correlated with the plasma MIR concentration (dose- and body weight–corrected, p=0.040) and that age (years) was significantly correlated with the plasma DMIR concentration (dose- and body weight–corrected, p=0.018). The steady-state plasma concentrations of MIR and its metabolites were unaffected by the number of CYP2D6*5 and CYP2D6*10 alleles. Discussion  The plasma concentration of 8-OH-MIR was as low as 1.42 nmol/L, whereas 8-OH-MIR-G had an approximate 59.50 times higher concentration than 8-OH-MIR, suggesting a significant role for hydroxylation of MIR and its glucuronidation in the Japanese population.

Pancreatic islet discrimination of hexose anomers. I. Steady-state computer simulation

1988 ◽  
Vol 255 (2) ◽  
pp. E189-E200
Author(s):  
M. J. Achs ◽  
D. Garfinkel
Keyword(s):  
Computer Simulation ◽  
Insulin Secretion ◽  
Steady State ◽  
Pancreatic Islets ◽  
Glucose Level ◽  
Pancreatic Islet ◽  
Specific Model ◽  
The Other ◽  
Glycolytic Rate ◽  
Hexose Phosphates

Pancreatic islets detect glucose level by phosphorylating it and converting the glycolytic rate to a signal to secrete insulin. Insulin secretion is greater from the alpha- than from the beta-anomer when the D-glucose level is below 22 mM. D-mannose behaves similarly but at nearly twofold higher concentrations. Two explanations have been proposed: 1) glucokinase, which has the same anomeric preference, is the principal hexose phosphorylating enzyme and limits glycolytic rate. 2) Phosphofructokinase limits glycolysis and hexokinase is the principal enzyme phosphorylating hexose; hexosediphosphate activators of phosphofructokinase are more readily synthesized from alpha-anomers of hexose phosphates. We have simulated both alternatives with a detailed anomerically specific model of the hexose-metabolizing glycolytic enzymes. The pathway preference for alpha-anomer of both hexoses was adequately reproduced with anomerically active limiting glucokinase. The other mechanism did not reproduce the observed pathway preference.

Optimizing the Feedback Gains of the Robust Linear Regulator

1999 ◽  
Vol 121 (3) ◽  
pp. 346-350
Author(s):  
Jie Huang
Keyword(s):  
Computer Simulation ◽  
Steady State ◽  
Transient Response ◽  
Closed Loop ◽  
Feedback Gain ◽  
Frobenius Norm ◽  
Closed Loop System ◽  
Optimal Feedback ◽  
Linear Regulator ◽  
Fixed Set

This paper aims to improve the transient response of a linear regulator system by optimizing the feedback gains associated with a fixed set of desirable eigenvalues of the closed-loop system. The optimal feedback gain is such that the Frobenius norm of the steady state of the compensator is minimized. Computer simulation shows that this scheme is effective in improving the transient response of the regulator system.

COMPUTER SIMULATION FOR THE CROSSING TIME IN A DIPLOID, ASYMMETRIC, SHARPLY-PEAKED LANDSCAPE IN THE INFINITE POPULATION LIMIT

2013 ◽  
Vol 24 (01) ◽  
pp. 1250091 ◽  
Author(s):  
WONPYONG GILL
Keyword(s):  
Computer Simulation ◽  
Steady State ◽  
Selective Advantage ◽  
Sequence Length ◽  
Initial State ◽  
Infinite Population ◽  
Crossing Time ◽  
Increasing Function ◽  
Fitness Parameter ◽  
Extension Parameter

This study calculated the crossing time in the diploid mutation–selection model in an infinite population limit for various dominance parameters, h, and selective advantages, by switching on a diploid, asymmetric, sharply-peaked landscape, from an initial state which is the steady state in a diploid, sharply-peaked landscape. The crossing time for h < 1 was found to diverge at the critical fitness parameter, which increased with increasing selective advantage and decreased with increasing sequence length. When the sequence length was increased with a fixed extension parameter, there was no crossing time for h < 1 when the sequence length was longer than the critical sequence length, which increased with increasing selective advantage. The crossing time for h ≤ 1 was found to be an exponentially increasing function of the sequence length, and the crossing time for h > 1 became saturated at a long sequence length. The crossing time decreased with increasing selective advantage, mainly because the larger selective advantage caused the increase in relative density of the reversal allele to grow exponentially at an earlier time.

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