Next Issue
Previous Issue

Table of Contents

Processes, Volume 3, Issue 1 (March 2015) , Pages 1-221

  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Readerexternal link to open them.
View options order results:
result details:
Displaying articles 1-14
Export citation of selected articles as:
Open AccessArticle Chromatographic Characterization and Process Performance of Column-Packed Anion Exchange Fibrous Adsorbents for High Throughput and High Capacity Bioseparations
Processes 2015, 3(1), 204-221; https://doi.org/10.3390/pr3010204
Received: 21 January 2015 / Revised: 9 March 2015 / Accepted: 10 March 2015 / Published: 20 March 2015
Cited by 7 | Viewed by 2457 | PDF Full-text (5003 KB) | HTML Full-text | XML Full-text
Abstract
Fibrous materials are prominent among novel chromatographic supports for the separation and purification of biomolecules. In this work, strong anion exchange, quaternary ammonium (Q) functional fibrous adsorbents were evaluated with regards to their physical and functional characteristics. A column packed with Q fibrous [...] Read more.
Fibrous materials are prominent among novel chromatographic supports for the separation and purification of biomolecules. In this work, strong anion exchange, quaternary ammonium (Q) functional fibrous adsorbents were evaluated with regards to their physical and functional characteristics. A column packed with Q fibrous adsorbent illustrated the good column packing efficiency of theoretical plate height (H) values and higher permeability coefficients (>0.9 × 10−7 cm2) than commercial adsorbents. For pulse experiments with acetone and lactoferrin as tracers under nonbinding conditions, the total porosity (for acetone) and the interstitial porosity (for lactoferrin) measured 0.97 and 0.47, respectively. The total ionic capacity of the chemically-functionalized Q fiber was 0.51 mmol/mL. The results indicated that the Q fiber had a static binding capacity of 140 mg/mL and a dynamic binding capacity (DBC) of 76 mg/mL for bovine serum albumin (BSA) and showed a linearly-scalable factor (~110 mL) for a column volume with high capacity and high throughput. Furthermore, this adsorptive material had the ability to bind the high molecular weight protein, thyroglobulin, with a capacity of 6 mg/mL. This work demonstrated the column-packed Q fibrous adsorption system as a potential chromatography support that exhibits high capacity at higher flow rates. Full article
(This article belongs to the Special Issue Advances in Bioseparation Engineering)
Figures

Figure 1

Open AccessArticle Dynamic Modeling of the Human Coagulation Cascade Using Reduced Order Effective Kinetic Models
Processes 2015, 3(1), 178-203; https://doi.org/10.3390/pr3010178
Received: 29 October 2014 / Revised: 3 March 2015 / Accepted: 10 March 2015 / Published: 16 March 2015
Cited by 6 | Viewed by 2926 | PDF Full-text (1102 KB) | HTML Full-text | XML Full-text
Abstract
In this study, we present a novel modeling approach which combines ordinary differential equation (ODE) modeling with logical rules to simulate an archetype biochemical network, the human coagulation cascade. The model consisted of five differential equations augmented with several logical rules describing regulatory [...] Read more.
In this study, we present a novel modeling approach which combines ordinary differential equation (ODE) modeling with logical rules to simulate an archetype biochemical network, the human coagulation cascade. The model consisted of five differential equations augmented with several logical rules describing regulatory connections between model components, and unmodeled interactions in the network. This formulation was more than an order of magnitude smaller than current coagulation models, because many of the mechanistic details of coagulation were encoded as logical rules. We estimated an ensemble of likely model parameters (N = 20) from in vitro extrinsic coagulation data sets, with and without inhibitors, by minimizing the residual between model simulations and experimental measurements using particle swarm optimization (PSO). Each parameter set in our ensemble corresponded to a unique particle in the PSO. We then validated the model ensemble using thrombin data sets that were not used during training. The ensemble predicted thrombin trajectories for conditions not used for model training, including thrombin generation for normal and hemophilic coagulation in the presence of platelets (a significant unmodeled component). We then used flux analysis to understand how the network operated in a variety of conditions, and global sensitivity analysis to identify which parameters controlled the performance of the network. Taken together, the hybrid approach produced a surprisingly predictive model given its small size, suggesting the proposed framework could also be used to dynamically model other biochemical networks, including intracellular metabolic networks, gene expression programs or potentially even cell free metabolic systems. Full article
Open AccessArticle Fast Wavelet-Based Model Predictive Control of Differentially Flat Systems
Processes 2015, 3(1), 161-177; https://doi.org/10.3390/pr3010161
Received: 19 December 2014 / Revised: 18 February 2015 / Accepted: 26 February 2015 / Published: 11 March 2015
Cited by 2 | Viewed by 2500 | PDF Full-text (415 KB) | HTML Full-text | XML Full-text
Abstract
A system is differentially flat if it is Lie–Bäcklund (L-B) equivalent to a free dynamical system that has dimensions equal to that of the input of the original system. Utilizing this equivalence, the problem of nonlinear model predictive control of a flat system [...] Read more.
A system is differentially flat if it is Lie–Bäcklund (L-B) equivalent to a free dynamical system that has dimensions equal to that of the input of the original system. Utilizing this equivalence, the problem of nonlinear model predictive control of a flat system can be reduced to a lower dimensional nonlinear programming problem with respect to the flat outputs. In this work, a novel computational method based on Haar wavelets in the time-domain for solving the resulting nonlinear programming problem is developed to obtain an approximation of the optimal flat output trajectory. The Haar wavelet integral operational matrix is utilized to transform the nonlinear programming problem to a finite dimensional nonlinear optimization problem. The proposed approach makes use of flatness as a structural property of nonlinear systems and the convenient mathematical properties of Haar wavelets to develop an efficient computational algorithm for nonlinear model predictive control of differentially flat systems. Further improvement on computational efficiency is achieved by providing solutions with multiple resolutions (e.g., obtaining high resolution solutions only for the near future, but allowing coarse approximation for the later stage in the prediction horizon). Full article
(This article belongs to the Special Issue Process Control: Current Trends and Future Challenges)
Open AccessArticle Dynamic Modeling of Cell-Free Biochemical Networks Using Effective Kinetic Models
Processes 2015, 3(1), 138-160; https://doi.org/10.3390/pr3010138
Received: 8 September 2014 / Revised: 16 February 2015 / Accepted: 17 February 2015 / Published: 3 March 2015
Cited by 6 | Viewed by 2574 | PDF Full-text (3563 KB) | HTML Full-text | XML Full-text
Abstract
Cell-free systems offer many advantages for the study, manipulation and modeling of metabolism compared to in vivo processes. Many of the challenges confronting genome-scale kinetic modeling can potentially be overcome in a cell-free system. For example, there is no complex transcriptional regulation to [...] Read more.
Cell-free systems offer many advantages for the study, manipulation and modeling of metabolism compared to in vivo processes. Many of the challenges confronting genome-scale kinetic modeling can potentially be overcome in a cell-free system. For example, there is no complex transcriptional regulation to consider, transient metabolic measurements are easier to obtain, and we no longer have to consider cell growth. Thus, cell-free operation holds several significant advantages for model development, identification and validation. Theoretically, genome-scale cell-free kinetic models may be possible for industrially important organisms, such as E. coli, if a simple, tractable framework for integrating allosteric regulation with enzyme kinetics can be formulated. Toward this unmet need, we present an effective biochemical network modeling framework for building dynamic cell-free metabolic models. The key innovation of our approach is the integration of simple effective rules encoding complex allosteric regulation with traditional kinetic pathway modeling. We tested our approach by modeling the time evolution of several hypothetical cell-free metabolic networks. We found that simple effective rules, when integrated with traditional enzyme kinetic expressions, captured complex allosteric patterns such as ultrasensitivity or non-competitive inhibition in the absence of mechanistic information. Second, when integrated into network models, these rules captured classic regulatory patterns such as product-induced feedback inhibition. Lastly, we showed, at least for the network architectures considered here, that we could simultaneously estimate kinetic parameters and allosteric connectivity from synthetic data starting from an unbiased collection of possible allosteric structures using particle swarm optimization. However, when starting with an initial population that was heavily enriched with incorrect structures, our particle swarm approach could converge to an incorrect structure. While only an initial proof-of-concept, the framework presented here could be an important first step toward genome-scale cell-free kinetic modeling of the biosynthetic capacity of industrially important organisms. Full article
(This article belongs to the Special Issue Dynamic Approaches to Metabolic Modeling and Metabolic Engineering)
Open AccessReview Deterministic Performance Assessment and Retuning of Industrial Controllers Based on Routine Operating Data: Applications
Processes 2015, 3(1), 113-137; https://doi.org/10.3390/pr3010113
Received: 30 December 2014 / Revised: 2 February 2015 / Accepted: 10 February 2015 / Published: 17 February 2015
Cited by 1 | Viewed by 2470 | PDF Full-text (619 KB) | HTML Full-text | XML Full-text
Abstract
Performance assessment and retuning techniques for proportional-integral-derivative (PID) controllers are reviewed in this paper. In particular, we focus on techniques that consider deterministic performance and that use routine operating data (that is, set-point and load disturbance step signals). Simulation and experimental results show [...] Read more.
Performance assessment and retuning techniques for proportional-integral-derivative (PID) controllers are reviewed in this paper. In particular, we focus on techniques that consider deterministic performance and that use routine operating data (that is, set-point and load disturbance step signals). Simulation and experimental results show that the use of integrals of predefined signals can be effectively employed for the estimation of the process parameters and, therefore, for the comparison of the current controller with a selected benchmark. Full article
(This article belongs to the Special Issue Process Control: Current Trends and Future Challenges)
Open AccessArticle Ag/SiO2- and Ag/Co3O4-Based Monolithic Flow Microreactors for Hydrogenation of Dyes: Their Activity and Stability
Processes 2015, 3(1), 98-112; https://doi.org/10.3390/pr3010098
Received: 31 December 2014 / Revised: 6 February 2015 / Accepted: 9 February 2015 / Published: 16 February 2015
Cited by 2 | Viewed by 2573 | PDF Full-text (29622 KB) | HTML Full-text | XML Full-text
Abstract
Silver nanoparticles supported on hierarchically porous silica and cobalt oxide monoliths have previously been shown to be catalytically active for the hydrogenation of common organic dyes in batch studies. This work presents a detailed investigation of the activity and stability of these monoliths [...] Read more.
Silver nanoparticles supported on hierarchically porous silica and cobalt oxide monoliths have previously been shown to be catalytically active for the hydrogenation of common organic dyes in batch studies. This work presents a detailed investigation of the activity and stability of these monoliths during the hydrogenation of eosin-Y in a continuous flow microreactor. The silver-containing monoliths showed excellent catalytic activity that reached a plateau after a period of approximately 6 h. From SEM particle size distribution studies of the catalysts before and after water and hexane were flowed through them, it was determined that under reaction conditions, silver was removed both by washing off of particles and by dissolution of silver. Full article
Figures

Figure 1

Open AccessArticle A Computational Study of the Effects of Syk Activity on B Cell Receptor Signaling Dynamics
Processes 2015, 3(1), 75-97; https://doi.org/10.3390/pr3010075
Received: 14 October 2014 / Revised: 20 January 2015 / Accepted: 28 January 2015 / Published: 11 February 2015
Cited by 2 | Viewed by 2347 | PDF Full-text (423 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The kinase Syk is intricately involved in early signaling events in B cells and isrequired for proper response when antigens bind to B cell receptors (BCRs). Experimentsusing an analog-sensitive version of Syk (Syk-AQL) have better elucidated its role, buthave not completely characterized its [...] Read more.
The kinase Syk is intricately involved in early signaling events in B cells and isrequired for proper response when antigens bind to B cell receptors (BCRs). Experimentsusing an analog-sensitive version of Syk (Syk-AQL) have better elucidated its role, buthave not completely characterized its behavior. We present a computational model for BCRsignaling, using dynamical systems, which incorporates both wild-type Syk and Syk-AQL.Following the use of sensitivity analysis to identify significant reaction parameters, we screenfor parameter vectors that produced graded responses to BCR stimulation as is observedexperimentally. We demonstrate qualitative agreement between the model and dose responsedata for both mutant and wild-type kinases. Analysis of our model suggests that the level of NF-KB activation, which is reduced in Syk-AQL cells relative to wild-type, is more sensitiveto small reductions in kinase activity than Erkp activation, which is essentially unchanged.Since this profile of high Erkp and reduced NF-KB is consistent with anergy, this implies thatanergy is particularly sensitive to small changes in catalytic activity. Also, under a range offorward and reverse ligand binding rates, our model of Erkp and NF-KB activation displaysa dependence on a power law affinity: the ratio of the forward rate to a non-unit power of thereverse rate. This dependence implies that B cells may respond to certain details of bindingand unbinding rates for ligands rather than simple affinity alone. Full article
Open AccessEditorial Special Issue “Feature Papers”
Processes 2015, 3(1), 71-74; https://doi.org/10.3390/pr3010071
Received: 6 February 2015 / Accepted: 9 February 2015 / Published: 11 February 2015
Viewed by 2005 | PDF Full-text (607 KB) | HTML Full-text | XML Full-text
Abstract
The Special Issue “Feature Papers” of the journal Processes aims to establish the scope of this new open access journal in chemical, biological, environmental, pharmaceutical, and material-process engineering, as well as the development of general process engineering methods. The Special Issue is available [...] Read more.
The Special Issue “Feature Papers” of the journal Processes aims to establish the scope of this new open access journal in chemical, biological, environmental, pharmaceutical, and material-process engineering, as well as the development of general process engineering methods. The Special Issue is available online at: https://www.mdpi.com/journal/processes/special_issues/feature-paper.[...] Full article
(This article belongs to the Special Issue Feature Papers) Printed Edition available
Open AccessArticle Modeling the Dynamics of Acute Phase Protein Expression in Human Hepatoma Cells Stimulated by IL-6
Processes 2015, 3(1), 50-70; https://doi.org/10.3390/pr3010050
Received: 22 August 2014 / Accepted: 9 December 2014 / Published: 14 January 2015
Cited by 3 | Viewed by 2972 | PDF Full-text (2825 KB) | HTML Full-text | XML Full-text
Abstract
Interleukin-6 (IL-6) is a systemic inflammatory mediator that triggers the human body’s acute phase response to trauma or inflammation. Although mathematical models for IL-6 signaling pathways have previously been developed, reactions that describe the expression of acute phase proteins were not included. To [...] Read more.
Interleukin-6 (IL-6) is a systemic inflammatory mediator that triggers the human body’s acute phase response to trauma or inflammation. Although mathematical models for IL-6 signaling pathways have previously been developed, reactions that describe the expression of acute phase proteins were not included. To address this deficiency, a recent model of IL-6 signaling was extended to predict the dynamics of acute phase protein expression in IL-6-stimulated HepG2 cells (a human hepatoma cell line). This included reactions that describe the regulation of haptoglobin, fibrinogen, and albumin secretion by nuclear transcription factors STAT3 dimer and C/EBPβ. This new extended model was validated against two different sets of experimental data. Using the validated model, a sensitivity analysis was performed to identify seven potential drug targets to regulate the secretion of haptoglobin, fibrinogen, and albumin. The drug-target binding kinetics for these seven targets was then integrated with the IL-6 kinetic model to rank them based upon the influence of their pairing with drugs on acute phase protein dynamics. It was found that gp80, JAK, and gp130 were the three most promising drug targets and that it was possible to reduce the therapeutic dosage by combining drugs aimed at the top three targets in a cocktail. These findings suggest hypotheses for further experimental investigation. Full article
Figures

Figure 1

Open AccessEditorial Special Issue: Design of Bioreactor Systems for Tissue Engineering
Processes 2015, 3(1), 46-49; https://doi.org/10.3390/pr3010046
Received: 15 December 2014 / Accepted: 23 December 2014 / Published: 12 January 2015
Viewed by 2053 | PDF Full-text (611 KB) | HTML Full-text | XML Full-text
Abstract
Tissue engineering and, more broadly, regenerative medicine is moving into a phase where we are seeing potential therapies moving ‘slowly but surely’ from the laboratory into the clinic, i.e., from research to the clinic and into manufacturing. The numbers of cells required [...] Read more.
Tissue engineering and, more broadly, regenerative medicine is moving into a phase where we are seeing potential therapies moving ‘slowly but surely’ from the laboratory into the clinic, i.e., from research to the clinic and into manufacturing. The numbers of cells required for cell therapy protocols can vary from tens of millions, to billions [1], and it is widely considered that such cell numbers can be produced in bioreactor systems. Thus, the bioreactor is becoming a key tool for culturing clinical numbers of human cells and the regenerative medicine industry will become increasingly reliant on such systems at the centre of cell therapy production and tissue engineering.[...] Full article
(This article belongs to the Special Issue Design of Bioreactor Systems for Tissue Engineering)
Open AccessArticle The Effect of Coincidence Horizon on Predictive Functional Control
Processes 2015, 3(1), 25-45; https://doi.org/10.3390/pr3010025
Received: 15 October 2014 / Accepted: 12 December 2014 / Published: 8 January 2015
Cited by 12 | Viewed by 1975 | PDF Full-text (223 KB) | HTML Full-text | XML Full-text
Abstract
This paper gives an analysis of the efficacy of PFC strategies. PFC is widely used in industry for simple loops with constraint handling, as it is very simple and cheap to implement. However, the algorithm has had very little exposure in the mainstream [...] Read more.
This paper gives an analysis of the efficacy of PFC strategies. PFC is widely used in industry for simple loops with constraint handling, as it is very simple and cheap to implement. However, the algorithm has had very little exposure in the mainstream literature. This paper gives some insight into when a PFC approach is expected to be successful and, conversely, when one should deploy with caution. Full article
(This article belongs to the Special Issue Process Control: Current Trends and Future Challenges)
Open AccessEditorial Acknowledgement to Reviewers of Processes in 2014
Processes 2015, 3(1), 23-24; https://doi.org/10.3390/pr3010023
Received: 8 January 2015 / Accepted: 8 January 2015 / Published: 8 January 2015
Viewed by 1378 | PDF Full-text (594 KB) | HTML Full-text | XML Full-text
Abstract
The editors of Processes would like to express their sincere gratitude to the following reviewers for assessing manuscripts in 2014:[...] Full article
Open AccessEditorial Special Issue: Design and Engineering of Microreactor and Smart-Scaled Flow Processes
Processes 2015, 3(1), 19-22; https://doi.org/10.3390/pr3010019
Received: 30 November 2014 / Accepted: 22 December 2014 / Published: 26 December 2014
Cited by 1 | Viewed by 2006 | PDF Full-text (608 KB) | HTML Full-text | XML Full-text
Abstract
Reaction-oriented research in flow chemistry and microreactor has been extensively focused upon in special journal issues and books. On a process level, this resembled the “drop-in” (retrofit) concept with the microreactor replacing a conventional (batch) reactor. Meanwhile, with the introduction of the mobile, [...] Read more.
Reaction-oriented research in flow chemistry and microreactor has been extensively focused upon in special journal issues and books. On a process level, this resembled the “drop-in” (retrofit) concept with the microreactor replacing a conventional (batch) reactor. Meanwhile, with the introduction of the mobile, compact, modular container technology, the focus is more on the process side, including also providing an end-to-end vision of intensified process design. Exactly this is the focus of the current special issue “Design and Engineering of Microreactor and Smart-Scaled Flow Processes” of the journal “Processes”. This special issue comprises three review papers, five research articles and two communications. [...] Full article
Open AccessArticle Mathematical Modeling of Pro- and Anti-Inflammatory Signaling in Macrophages
Processes 2015, 3(1), 1-18; https://doi.org/10.3390/pr3010001
Received: 30 September 2014 / Accepted: 25 November 2014 / Published: 26 December 2014
Cited by 6 | Viewed by 4483 | PDF Full-text (1753 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Inflammation is a beneficial mechanism that is usually triggered by injury or infection and is designed to return the body to homeostasis. However, uncontrolled or sustained inflammation can be deleterious and has been shown to be involved in the etiology of several diseases, [...] Read more.
Inflammation is a beneficial mechanism that is usually triggered by injury or infection and is designed to return the body to homeostasis. However, uncontrolled or sustained inflammation can be deleterious and has been shown to be involved in the etiology of several diseases, including inflammatory bowel disorder and asthma. Therefore, effective anti-inflammatory signaling is important in the maintenance of homeostasis in the body. However, the inter-play between pro- and anti-inflammatory signaling is not fully understood. In the present study, we develop a mathematical model to describe integrated pro- and anti-inflammatory signaling in macrophages. The model incorporates the feedback effects of de novo synthesized pro-inflammatory (tumor necrosis factor α; TNF-α) and anti-inflammatory (interleukin-10; IL-10) cytokines on the activation of the transcription factor nuclear factor κB (NF-κB) under continuous lipopolysaccharide (LPS) stimulation (mimicking bacterial infection). In the model, IL-10 upregulates its own production (positive feedback) and also downregulates TNF-α production through NF-κB (negative feedback). In addition, TNF-α upregulates its own production through NF-κB (positive feedback). Eight model parameters are selected for estimation involving sensitivity analysis and clustering techniques. We validate the mathematical model predictions by measuring phosphorylated NF-κB, de novo synthesized TNF-α and IL-10 in RAW 264.7 macrophages exposed to LPS. This integrated model represents a first step towards modeling the interaction between pro- and anti-inflammatory signaling. Full article
Figures

Figure 1

Processes EISSN 2227-9717 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top