Cell growth and population activity ofSaccharomyces cerevisiaein two-stage continuous cultivation

1969 ◽  
Vol 11 (5) ◽  
pp. 853-862 ◽  
Author(s):  
K. Beran ◽  
J. Zemanová
Keyword(s):  
Cell Growth ◽  
Continuous Cultivation ◽  
Two Stage ◽  
Population Activity

scholarly journals Gaussian-Process Factor Analysis for Low-Dimensional Single-Trial Analysis of Neural Population Activity

2009 ◽  
Vol 102 (1) ◽  
pp. 614-635 ◽  
Author(s):  
Byron M. Yu ◽  
John P. Cunningham ◽  
Gopal Santhanam ◽  
Stephen I. Ryu ◽  
Krishna V. Shenoy ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Gaussian Process ◽  
Predictive Ability ◽  
Neural Population ◽  
Single Trial ◽  
Two Stage ◽  
Population Activity ◽  
Process Factor ◽  
Low Dimensional ◽  
Neural Population Activity

We consider the problem of extracting smooth, low-dimensional neural trajectories that summarize the activity recorded simultaneously from many neurons on individual experimental trials. Beyond the benefit of visualizing the high-dimensional, noisy spiking activity in a compact form, such trajectories can offer insight into the dynamics of the neural circuitry underlying the recorded activity. Current methods for extracting neural trajectories involve a two-stage process: the spike trains are first smoothed over time, then a static dimensionality-reduction technique is applied. We first describe extensions of the two-stage methods that allow the degree of smoothing to be chosen in a principled way and that account for spiking variability, which may vary both across neurons and across time. We then present a novel method for extracting neural trajectories—Gaussian-process factor analysis (GPFA)—which unifies the smoothing and dimensionality-reduction operations in a common probabilistic framework. We applied these methods to the activity of 61 neurons recorded simultaneously in macaque premotor and motor cortices during reach planning and execution. By adopting a goodness-of-fit metric that measures how well the activity of each neuron can be predicted by all other recorded neurons, we found that the proposed extensions improved the predictive ability of the two-stage methods. The predictive ability was further improved by going to GPFA. From the extracted trajectories, we directly observed a convergence in neural state during motor planning, an effect that was shown indirectly by previous studies. We then show how such methods can be a powerful tool for relating the spiking activity across a neural population to the subject's behavior on a single-trial basis. Finally, to assess how well the proposed methods characterize neural population activity when the underlying time course is known, we performed simulations that revealed that GPFA performed tens of percent better than the best two-stage method.

Modeling of Phytase Production by Cultivation of Pichia pastoris Under the Control of the GAP Promoter

2010 ◽  
Vol 8 (1) ◽  
Author(s):  
Shuiquan Tang ◽  
Gabriel Potvin ◽  
Alison Reiche ◽  
Zisheng Zhang
Keyword(s):  
Cell Growth ◽  
Pichia Pastoris ◽  
Enzyme Production ◽  
Continuous Cultivation ◽  
Fed Batch ◽  
Phytase Production ◽  
Gap Promoter ◽  
Proposed Model ◽  
Simple Kinetic Model ◽  
Recombinant Phytase

Cell growth and recombinant phytase production under the control of the GAP promoter were studied in continuous cultivation experiments of Pichia pastoris. Based on these studies, a simple kinetic model was established to predict biomass and enzyme production. Although parameters were mainly estimated using the results of continuous cultivation, the proposed model was able to successfully predict cell growth and phytase production in three different fed-batch cultivations of P. pastoris using limited glucose feeding.

Increasing CoQ10 Production by Rhodopseudomonas palustris J001 Using a Two-Stage Fermentation Process

2008 ◽  
Vol 63 (11-12) ◽  
pp. 884-888
Author(s):  
Shi-yun Jiang ◽  
Long-jiang Yu
Keyword(s):  
Cell Growth ◽  
Fermentation Process ◽  
Switching Time ◽  
Rhodopseudomonas Palustris ◽  
Food Supplement ◽  
Two Stage ◽  
Successful Approach ◽  
Stage Process ◽  
The One ◽  
Coq10 Production

Abstract CoQ10 is used not only as a medicine but also as a food supplement due to its various physiological activities. The production of CoQ10 by microbes is a successful approach for generating large amounts of this natural product. The effects of dissolved oxygen (DO) contents and the two-stage fermentation process on cell growth and CoQ10 production by Rhodopseudomonas palustris J001 were investigated. The optimal DO contents for cell growth and CoQ10 production were 45% and 15%, respectively. A two-stage fermentation process, which consists of a 1st stage with 45% DO, a 2nd stage with 15% DO and a synchronous feeding of 2.0% NaAc at the switching time (42 h after inoculation), has proven to be the optimum fermentation process for the production of CoQ10. The maximum biomass, CoQ10 production and CoQ10 production rate were 1.31 g l-1, 89.1 mg l-1, and 1.142 mg l-1 h-1, respectively, increased by 28%, 585% and 426% as compared to the one-stage batch production with 45% DO. The DO level was the major factor to increase the CoQ10 production by the two-stage process.

Sign in / Sign up

Export Citation Format

Share Document