Low cost and convenient method for off-gas flowrate determination in industrial fermenters

Summary Analysis of fermenter off-gas requires that the flowrate be accurately determined. We present an alternative to conventional methods which periodically spikes the off-gas flow with an accurately determined flow of argon. The resulting mol fraction of argon is determined by an existing mass spectrometer which in turn is used with a mol balance on argon to determine the total off-gas flowrate. For multiple fermenters this technique replaces expensive and maintenance intensive equipment with a single accurately controlled argon stream.     

Blunt Traumatic Aortic Injury of Right Aortic Arch in a Patient with an Aberrant Left Subclavian Artery

Right-sided aortic arch (RAA) is a rare congenital developmental variant present in about 0.1 percent of the population. This anatomical anomaly is commonly associated with congenital heart disease and complications from compression of mediastinal structures. However, it is unknown if patients are at a higher risk of blunt thoracic aortic injury (BTAI). We report a case of a 20-year-old man admitted to the hospital after being hit by an automobile. Computed tomographic scan revealed an RAA with an aberrant left subclavian artery originating from a Kommerell’s diverticulum. A pseudo-aneurysm was also seen along the aortic arch. A diagnosis of blunt traumatic aortic injury was made. The patient was successfully treated with a 26mm Vascutek hybrid stentgraft using the frozen elephant trunk technique.A literature review of the pathophysiology of BTAI was performed to investigate if patients with right-sided aortic arch are at a higher risk of suffering from BTAI. Results from the review suggest that although theoretically there may be a higher risk of BTAI in RAA patients, the rarity of this condition has prevented large studies to be conducted. Previously reported cases of BTAI in RAA have highlighted the possibility that the aortic isthmus may be anatomically weak and therefore prone to injury. We have explored this possibility by reviewing current literature of the embryological origins of the aortic arch and descending aorta.     

Computational genomics of noncoding RNA genes

The number of known noncoding RNA genes is expanding rapidly. Computational analysis of genome sequences, which has been revolutionary for protein gene analysis, should also be able to address questions of the number and diversity of noncoding RNA genes. However, noncoding RNAs present computational genomics with a new set of challenges.     

Non-Newtonian flow patterns associated with an arterial stenosis.

A non-Newtonian constitutive equation for blood has been introduced in this paper. Using this equation, blood flow attributes such as velocity profiles, flowrate, pressure gradient, and wall shear stress in both straight and stenotic (constricted) tubes have been examined. Results showed that compared with Newtonian flow at the same flowrate, the non-Newtonian normally features larger pressure gradient, higher wall shear stress, and different velocity profile, especially in stenotic tube. In addition, the non-Newtonian stenotic flow appears to be more stable than Newtonian flow.     

A Mathematical model for ethanol production by extractive fermentation in a continuous stirred tank fermentor

Extractive fermentation is a technique that can be used to reduce the effect of end product inhibition through the use of a water-immiscible phase that removes fermentation products in situ. This has the beneficial effect of not only removing inhibitory products as they are formed (thus keeping reaction rates high) but also has the potential for reducing product recovery costs. We have chosen to examine the ethanol fermentation as a model system for end product inhibition and extractive fermentation and have developed a computer model predicting the productivity enhancement possible with this technique together with other key parameters such as extraction efficiency and residual glucose concentration. The model accommodates variable liquid flowrates entering and leaving the system, since it was found that the aqueous outlet flowrate could be up to 35% lower than the inlet flowrate during extractive fermentation of concentrated glucose feeds due to the continuous removal of ethanol from the fermentation broth by solvent extraction. The model predicts a total ethanol productivity of 82.6 g/L h if a glucose feed of 750 g/L is fermented with a solvent having a distribution coefficient of 0.5 at a solvent dilution rate of 5.0 h(-1). This is more than 10 times higher than for a conventional chemostat fermentation of a 250 g/L glucose feed. The model has furthermore illustrated the possible trade-offs that exist between obtaining a high extraction efficiency and a low residual glucose concentration.     

New targets for an old drug

Methotrexate has been a clinical agent used in cancer, immunosuppression, rheumatoid arthritis and other highly proliferative diseases for many years, yet its underlying molecular mechanism of action in these therapeutic areas is still unclear. We present a chemical proteomics approach that uses ultra-sensitive mass spectrometry coupled to an inverse protein-ligand docking computational technique to unravel the mechanism of action of this drug. Using methotrexate tethered to a solid support we were able to isolate a signficant number of proteins. We effectively captured a large portion of the de novo purine metaolome and propose a pathway architecture similar to that seen in signaling pathways and consistent with substrate channeling. More importantly, we were able to capture protein targets that could potentially provide new insights into the mechanism of action of methotrexate in rheumatoid arthritis and immunosuppression. The application of this approach to other drugs and drug candidates may facilitate the prediction of unknown and secondary therapeutic target proteins and those related to the side effects and toxicity. These results demonstrate that this proteomics technology could play an important role in drug discovery and development since it allows monitoring of the interactions between a drug and the protein content of a cell.     

A communication-efficient linear system solver for large eddy simulation of jet engine noise

High-fidelity computational fluid dynamics (CFD) tools, such as the large eddy simulation technique, have become feasible in aiding the field of computational aeroacoustics (CAA) to compute noise on petascale computing platforms. CAA poses significant challenges for researchers because the computational schemes used in the CFD tools should have high accuracy, good spectral resolution, and low dispersion and diffusion errors. A high-order compact finite difference scheme, which is implicit in space, can be used for such simulations because it fulfills the requirements for CAA. Usually, this method is parallelized using a transposition scheme; however, that approach has a high communication overhead. In this paper, we discuss the use of a parallel tridiagonal linear system solver based on the truncated SPIKE algorithm for reducing the communication overhead in our large eddy simulations. We present theoretical performance analysis and report experimental results collected on two parallel computing platforms.     

Design and implementation of an introductory course for computer applications in molecular genetics

Formal training in computational biology was initiated at Wayne State University in 1990 to meet the needs of the faculty. This was still at a time when the molecular databases and analysis tools could be housed in what is now equivalent to a modern but dated desktop computer. In 1995 the course was expanded to include graduate students to provide these senior students with a foundation in computational biology. This course has armed our students with a requisite set of basic skills that are necessary for a successful career in molecular genetics. It is now an integral component of the graduate program of the Center for Molecular Medicine and Genetics and our experiences in course delivery have been detailed (BioInformatics Methods and Protocols, S. Misener and S. A. Krawetz, eds., Humana Press, Totowa, NJ, 2000.). The course was expanded to a campus-wide unlimited enrollment program for the summer of 2000 to address the needs of our student body. In this review we present our experience with delivering a multidisciplinary campuswide computational biology course to a new and widely diverse student body.     

PSysCal: a parallel tool for calibration of ecosystem models

The methods used for ecosystem modelling are generally based on differential equations. Nowadays, new computational models based on concurrent processing of multiple agents (multi-agents) or the simulation of biological processes with the Population Dynamic P-System models (PDPs) are gaining importance. These models have significant advantages over traditional models, such as high computational efficiency, modularity and its ability to model the interaction between different biological processes which operate concurrently. By this, they are becoming useful for simulating complex dynamic ecosystems, untreatable with classical techniques. On the other hand, the main counterpart of P-System models is the need for calibration. The model parameters represent the field measurements taken by experts. However, the exact values of some of these parameters are unknown and experts define a numerical interval of possible values. Therefore, it is necessary to perform a calibration process to fit the best value of each interval. When the number of unknown parameters increases, the calibration process becomes computationally complex and storage requirements increase significantly. In this paper, we present a parallel tool (PSysCal) for calibrating next generation PDP models. The results shown that the calibration time is reduced exponentially with the amount of computational resources. However, the complexity of the calibration process and a limitation in the number of available computational resources make the calibration process intractable for large models. To solve this, we propose a heuristic technique (PSysCal+H). The results show that this technique significantly reduces the computational cost, it being practical for solving large model instances even with limited computational resources.     

Computational model for simulation of vascular adaptation following vascular access surgery in haemodialysis patients

An important number of surgical procedures for creation of vascular access (VA) in haemodialysis patients still results in non-adequate increase in blood flow (non-maturation). The rise in blood flow in arteriovenous shunts depends on vascular remodelling. Computational tools to predict the outcome of VA surgery would be important in this clinical context. The aim of our investigation was then to develop a 0D/1D computational model of arm vasculature able to simulate vessel wall remodelling and related changes in blood flow. We assumed that blood vessel remodelling is driven by peak wall shear stress. The model was calibrated with previously reported values of radial artery diameter and blood flow after end-to-end distal fistula creation. Good agreement was obtained between predicted changes in VA flow and in arterial diameter after surgery and corresponding measured values. The use of this computational model may allow accurate vascular surgery planning and ameliorate VA surgery outcomes.     

Model reduction using a posteriori analysis

Mathematical models in biology and physiology are often represented by large systems of non-linear ordinary differential equations. In many cases, an observed behaviour may be written as a linear functional of the solution of this system of equations. A technique is presented in this study for automatically identifying key terms in the system of equations that are responsible for a given linear functional of the solution. This technique is underpinned by ideas drawn from a posteriori error analysis. This concept has been used in finite element analysis to identify regions of the computational domain and components of the solution where a fine computational mesh should be used to ensure accuracy of the numerical solution. We use this concept to identify regions of the computational domain and components of the solution where accurate representation of the mathematical model is required for accuracy of the functional of interest. The technique presented is demonstrated by application to a model problem, and then to automatically deduce known results from a cell-level cardiac electrophysiology model.     

A novel Markov chain monte carlo approach for constructing accurate meiotic maps

Mapping markers from linkage data continues to be a task performed in many genetic epidemiological studies. Data collected in a study may be used to refine published map estimates and a study may use markers that do not appear in any published map. Furthermore, inaccuracies in meiotic maps can seriously bias linkage findings. To make best use of the available marker information, multilocus linkage analyses are performed. However, two computational issues greatly limit the number of markers currently mapped jointly; the number of candidate marker orders increases exponentially with marker number and computing exact multilocus likelihoods on general pedigrees is computationally demanding. In this article, a new Markov chain Monte Carlo (MCMC) approach that solves both these computational problems is presented. The MCMC approach allows many markers to be mapped jointly, using data observed on general pedigrees with unobserved individuals. The performance of the new mapping procedure is demonstrated through the analysis of simulated and real data. The MCMC procedure performs extremely well, even when there are millions of candidate orders, and gives results superior to those of CRI-MAP.     

Exploring the conformational space of membrane protein folds matching distance constraints

Herein we present a computational technique for generating helix-membrane protein folds matching a predefined set of distance constraints, such as those obtained from NMR NOE, chemical cross-linking, dipolar EPR, and FRET experiments. The purpose of the technique is to provide initial structures for local conformational searches based on either energetic considerations or ad-hoc scoring criteria. In order to properly screen the conformational space, the technique generates an exhaustive list of conformations within a specified root-mean-square deviation (RMSD) where the helices are positioned in order to match the provided distances. Our results indicate that the number of structures decreases exponentially as the number of distances increases, and increases exponentially as the errors associated with the distances increases. We also found the number of solutions to be smaller when all the distances share one helix in common, compared to the case where the distances connect helices in a daisy-chain manner. We found that for 7 helices, at least 15 distances with errors up to 8 A are needed to produce a number of solutions that is not too large to be processed by local search refinement procedures. Finally, without energetic considerations, our enumeration technique retrieved the transmembrane domains of Bacteriorhodopsin (PDB entry1c3w), Halorhodopsin (1e12), Rhodopsin (1f88), Aquaporin-1 (1fqy), Glycerol uptake facilitator protein (1fx8), Sensory Rhodopsin (1jgj), and a subunit of Fumarate reductase flavoprotein (1qlaC) with Calpha level RMSDs of 3.0 A, 2.3 A, 3.2 A, 4.6 A, 6.0 A, 3.7 A, and 4.4 A, respectively.     

Rise and Demise of Bioinformatics? Promise and Progress

The field of bioinformatics and computational biology has gone through a number of transformations during the past 15 years, establishing itself as a key component of new biology. This spectacular growth has been challenged by a number of disruptive changes in science and technology. Despite the apparent fatigue of the linguistic use of the term itself, bioinformatics has grown perhaps to a point beyond recognition. We explore both historical aspects and future trends and argue that as the field expands, key questions remain unanswered and acquire new meaning while at the same time the range of applications is widening to cover an ever increasing number of biological disciplines. These trends appear to be pointing to a redefinition of certain objectives, milestones, and possibly the field itself.     

The impact of process stress on suspended anchorage-dependent mammalian cells as an indicator of likely challenges for regenerative medicines

To quantify the engineering shear constraint on processing, the effect of capillary shear stress (pipe flow) on suspended anchorage-dependent mammalian cells has been investigated. Exposure of cultured rat aortic smooth muscle cells to repeated capillary shear stress (2-120 N m(-2)) causes a decrease in total number of cells, number of intact cells and number of cells able to grow. The optimum wall shear stress for cell survival was found to be 10-50 N m(-2) (flowrate 4-20 mL/min, I.D. 0.45 mm). Cell populations which are able to grow after exposure to shear stress do not exhibit reduced growth rate or altered metabolism.     

Comparison of an exact and a simulation method for calculating gene extinction probabilities in pedigrees

A comparison is made between a much used simulation method, commonly called gene dropping, and the exact computational technique of peeling. These methods are illustrated using the problem of finding the distribution of the number of distinct ancestral genes surviving at an autosomal locus. Each method is used on several real zoo pedigrees, of varying size and complexity, and the results are compared. Gene dropping is found to be a good approximation to peeling, but for all but the most complex pedigrees surveyed, peeling is preferable. The relationship between heterozygosity and allelic variability is investigated.     

Enumeration of rhizobia by enzyme-linked immunosorbent assay (ELISA)

The use of the enzyme-linked immunosorbent assay (ELISA) to enumerate rhizobia in peat carrier and in soil has been investigated. The ELISA technique takes less time than the conventional plant infection technique often used to enumerate rhizobia present in the presence of other micro-organisms. A minimum of 10₂–10₃ cells are required for a detectable ELISA reaction, limiting the use of this technique when the number of rhizobia is low.