Pilot-scale verification of a computer-based simulation for fractional protein precipitation

The development and experimental verification at pilot scale of a suite of models for the batch precipitation by two-cut ammonium sulphate salting-out of total protein and alcohol dehydrogenase from yeast homogenate is presented. The model consists of two elements: protein and enzyme solubility prediction and precipitate phase particle property prediction. An isotherm-based approach has been used successfully to describe solubility behaviour for a range of operating conditions typical of those obtained at a process scale. Estimation of the precipitate phase particle size distributions has been achieved through a discretized population balance approach using simplified terms to account for particle breakage and aggregation. The developed model accounts for the effects of average shear rate and residence time in the precipitation vessel across a two orders of magnitude range of scale. The size-density relationship for the precipitate phase has been defined. Results of simulations are compared with pilot scale verification data to confirm the validity of the models developed.     

Resource limited and equilibrium models of populations

Summary The logistic equation has been used as the basis of two distinct models of population dynamics, a resource limited model and an equilibrium model. It is argued that although the two models are very different, the distinction between them has been obscured by the use of the same terminology for the parameters of both. It is further argued that the simple equilibrium model developed from the logistic equation has inconsistencies which make it untenable as a population model.     

The development of an EMG-assisted model to assess spine loading during whole-body free-dynamic lifting

Low back disorders (LBDs) are the most common and costly occupationally-related compensable conditions facing employers today. Over the years several biomechanical assessment models have been developed that intended to assess the load profile imposed upon the spine during lifting and, thus, intended to facilitate the control of LBD risk in the workplace. Many of these biomechanical models have evolved based upon assumptions about how the trunk musculature respond to loads imposed upon the body during lifting. However, few of these models have been able to accurately predict the co-contraction of the trunk musculature which has been shown to have a major influence on the development of spinal loads. Thus, our understanding of how the spine is loaded under realistic dynamic lifting conditions has been deficient. A biologically-assisted or EMG-assisted model has been developed in our laboratory over the past 15 years which endeavours to overcome these traditional problems. The model has been assessed in the sagittal, coronal, and torsional planes of the body. The model development and performance will be reviewed as well as the benefits for controlling occupationally-related LBDs.     

How should pathogen transmission be modelled?

Host-pathogen models are essential for designing strategies for managing disease threats to humans, wild animals and domestic animals. The behaviour of these models is greatly affected by the way in which transmission between infected and susceptible hosts is modelled. Since host-pathogen models were first developed at the beginning of the 20th century, the 'mass action' assumption has almost always been used for transmission. Recently, however, it has been suggested that mass action has often been modelled wrongly. Alternative models of transmission are beginning to appear, as are empirical tests of transmission dynamics.     

The hematopoietic system during chronic irradiation with high dose rates (mathematical modeling)]

Mathematical models have been developed to describe dynamics of some haemopoietic compartments in mammals subjected to long-term irradiation. Within the framework of the models developed an equation has been obtained for a critical dose-rate (Ncr) of chronic irradiation, leading to complete depletion of certain haemopoietic compartments, that helps to prognose the dangerous Ncr values without preliminary experiments.     

A genetic algorithm based molecular modeling technique for RNA stem-loop structures.

A new modeling technique for arriving at the three dimensional (3-D) structure of an RNA stem-loop has been developed based on a conformational search by a genetic algorithm and the following refinement by energy minimization. The genetic algorithm simultaneously optimizes a population of conformations in the predefined conformational space and generates 3-D models of RNA. The fitness function to be optimized by the algorithm has been defined to reflect the satisfaction of known conformational constraints. In addition to a term for distance constraints, the fitness function contains a term to constrain each local conformation near to a prepared template conformation. The technique has been applied to the two loops of tRNA, the anticodon loop and the T-loop, and has found good models with small root mean square deviations from the crystal structure. Slightly different models have also been found for the anticodon loop. The analysis of a collection of alternative models obtained has revealed statistical features of local variations at each base position.     

Java Web Simulation (JWS); a web based database of kinetic models

Software to make a database of kinetic models accessible via the internet has been developed and a core database has been set up at http://jjj.biochem.sun.ac.za/. This repository of models, available to everyone with internet access, opens a whole new way in which we can make our models public. Via the database, a user can change enzyme parameters and run time simulations or steady state analyses. The interface is user friendly and no additional software is necessary. The database currently contains 10 models, but since the generation of the program code to include new models has largely been automated the addition of new models is straightforward and people are invited to submit their models to be included in the database.     

In‐line monitoring of amino acids in mammalian cell cultures using raman spectroscopy and multivariate chemometrics models

The application of PAT for in‐line monitoring of biopharmaceutical manufacturing operations has a central role in developing more robust and consistent processes. Various spectroscopic techniques have been applied for collecting real‐time data from cell culture processes. Among these, Raman spectroscopy has been shown to have advantages over other spectroscopic techniques, especially in aqueous culture solutions. Measurements of several process parameters such as glucose, lactate, glutamine, glutamate, ammonium, osmolality and VCD using Raman‐based chemometrics models have been reported in literature. The application of Raman spectroscopy, coupled with calibration models for amino acid measurement in cell cultures, has been assessed. The developed models cover four amino acids important for cell growth and production: tyrosine, tryptophan, phenylalanine and methionine. The chemometrics models based on Raman spectroscopy data demonstrate the significant potential for the quantification of tyrosine, tryptophan and phenylalanine. The model for methionine would have to be further refined to improve quantification.     

Relations Between Bacterial Biomass and Carbon Cycle in Marine Sediments: An Early Diagenetic Model

A new model for early diagenetic processes has been developed through a new formula explicitly accounting for microbial population dynamics. Following a mechanistic approach based on enzymatic reactions, a new model has been proposed for oxic mineralisation and denitrification. It incorporates the dynamics of bacterial metabolism. We find a general formula for inhibition processes of which some other mathematical expressions are particular cases. Moreover a fast numerical algorithm has been developed. It allows us to perform simulations of different diagenetic models in non-steady states. We use this algorithm to compare our model to a classical one (Soetaert et al., 1996). Dynamical evolutions of a perturbation of particulate organic carbon (POC) input are studied for both models. The results are very similar for stationary cases. But with variable inputs, the bacterial biomass dynamics brings about noticeable differences, and these are discussed.     

Designing of highly effective complementary and mismatch siRNAs for silencing a gene

In past, numerous methods have been developed for predicting efficacy of short interfering RNA (siRNA). However these methods have been developed for predicting efficacy of fully complementary siRNA against a gene. Best of author's knowledge no method has been developed for predicting efficacy of mismatch siRNA against a gene. In this study, a systematic attempt has been made to identify highly effective complementary as well as mismatch siRNAs for silencing a gene.Support vector machine (SVM) based models have been developed for predicting efficacy of siRNAs using composition, binary and hybrid pattern siRNAs. We achieved maximum correlation 0.67 between predicted and actual efficacy of siRNAs using hybrid model. All models were trained and tested on a dataset of 2182 siRNAs and performance was evaluated using five-fold cross validation techniques. The performance of our method desiRm is comparable to other well-known methods. In this study, first time attempt has been made to design mutant siRNAs (mismatch siRNAs). In this approach we mutated a given siRNA on all possible sites/positions with all possible nucleotides. Efficacy of each mutated siRNA is predicted using our method desiRm. It is well known from literature that mismatches between siRNA and target affects the silencing efficacy. Thus we have incorporated the rules derived from base mismatches experimental data to find out over all efficacy of mutated or mismatch siRNAs. Finally we developed a webserver, desiRm (http://www.imtech.res.in/raghava/desirm/) for designing highly effective siRNA for silencing a gene. This tool will be helpful to design siRNA to degrade disease isoform of heterozygous single nucleotide polymorphism gene without depleting the wild type protein.     

Phylogenomic analysis of the Chlamydomonas genome unmasks proteins potentially involved in photosynthetic function and regulation

Chlamydomonas reinhardtii, a unicellular green alga, has been exploited as a reference organism for identifying proteins and activities associated with the photosynthetic apparatus and the functioning of chloroplasts. Recently, the full genome sequence of Chlamydomonas was generated and a set of gene models, representing all genes on the genome, was developed. Using these gene models, and gene models developed for the genomes of other organisms, a phylogenomic, comparative analysis was performed to identify proteins encoded on the Chlamydomonas genome which were likely involved in chloroplast functions (or specifically associated with the green algal lineage); this set of proteins has been designated the GreenCut. Further analyses of those GreenCut proteins with uncharacterized functions and the generation of mutant strains aberrant for these proteins are beginning to unmask new layers of functionality/regulation that are integrated into the workings of the photosynthetic apparatus.     

Mathematical modeling of ovarian cancer treatments: sequencing of surgery and chemotherapy

Ovarian cancer has long been one of the most common forms of cancer in women. The main treatment for ovarian cancer comprises a combination of surgery and chemotherapy. In an effort to improve treatment strategies, a variety of mathematical models have been developed in the literature. In this paper, we consider a simple mathematical model that incorporates tumor growth as well as the effects of chemotherapeutic and surgical treatments in ovarian cancer. We consider several growth models and combine them with different cell-kill hypotheses. Surgery is assumed to eliminate a fixed fraction of tumor cells instantaneously. We discuss how different models predict the optimal sequencing of chemotherapeutic and surgical treatments. This work has been carried out in the context of ovarian cancer; however, the results may also be useful for other kind of cancers.     

Finite element models of the thigh-buttock complex for assessing static sitting discomfort and pressure sore risk: a literature review

Being seated for long periods, while part of many leisure or occupational activities, can lead to discomfort, pain and sometimes health issues. The impact of prolonged sitting on the body has been widely studied in the literature, with a large number of human-body finite element models developed to simulate sitting and assess seat-induced discomfort or to investigate the biomechanical factors involved. Here, we review the finite element models developed to investigate sitting discomfort or risk of pressure sores. Our study examines finite element models from twenty-seven papers, seventeen dedicated to assessing seating discomfort and ten dedicated to investigating pressure ulcers caused by prolonged sitting. The models’ mesh composition and material properties are found to differ widely. These models share a lack of validation and generally make little allowance for anthropometric diversity.     

Measurement and modelling of x-direction apparent mass of the seated human body-cushioned seat system

For modelling purposes and for evaluation of driver's seat performance in the vertical direction various mechano-mathematical models of the seated human body have been developed and standardized by the ISO. No such models exist hitherto for human body sitting in an upright position in a cushioned seat upper part, used in industrial environment, where the fore-and-aft vibrations play an important role. The interaction with the steering wheel has to be taken into consideration, as well as, the position of the human body upper torso with respect to the cushioned seat back as observed in real driving conditions. This complex problem has to be simplified first to arrive at manageable simpler models, which still reflect the main problem features. In a laboratory study accelerations and forces in x-direction were measured at the seat base during whole-body vibration in the fore-and-aft direction (random signal in the frequency range between 0.3 and 30 Hz, vibration magnitudes 0.28, 0.96, and 2.03 ms(-2) unweighted rms). Thirteen male subjects with body masses between 62.2 and 103.6 kg were chosen for the tests. They sat on a cushioned driver seat with hands on a support and backrest contact in the lumbar region only. Based on these laboratory measurements a linear model of the system-seated human body and cushioned seat in the fore-and-aft direction has been developed. The model accounts for the reaction from the steering wheel. Model parameters have been identified for each subject-measured apparent mass values (modulus and phase). The developed model structure and the averaged parameters can be used for further bio-dynamical research in this field.     

北京中医医院医疗联盟模式探讨

在新医改背景下,北京中医医院积极探索“医疗联盟”的新模式,在全国范围内相继与三十多家医院建立了协作与对口支援、院际合作、托管等合作关系,并制定了具体措施来深化和落实合作,取得了不少成效。对医疗联盟的模式和成果作出总结,为完善工作模式提供参考。     

Prediction of enteric methane emissions from cattle

Agriculture has a key role in food production worldwide and it is a major component of the gross domestic product of several countries. Livestock production is essential for the generation of high quality protein foods and the delivery of foods in regions where animal products are the main food source. Environmental impacts of livestock production have been examined for decades, but recently emission of methane from enteric fermentation has been targeted as a substantial greenhouse gas source. The quantification of methane emissions from livestock on a global scale relies on prediction models because measurements require specialized equipment and may be expensive. The predictive ability of current methane emission models remains poor. Moreover, the availability of information on livestock production systems has increased substantially over the years enabling the development of more detailed methane prediction models. In this study, we have developed and evaluated prediction models based on a large database of enteric methane emissions from North American dairy and beef cattle. Most probable models of various complexity levels were identified using a Bayesian model selection procedure and were fitted under a hierarchical setting. Energy intake, dietary fiber and lipid proportions, animal body weight and milk fat proportion were identified as key explanatory variables for predicting emissions. Models here developed substantially outperformed models currently used in national greenhouse gas inventories. Additionally, estimates of repeatability of methane emissions were lower than the ones from the literature and multicollinearity diagnostics suggested that prediction models are stable. In this context, we propose various enteric methane prediction models which require different levels of information availability and can be readily implemented in national greenhouse gas inventories of different complexity levels. The utilization of such models may reduce errors associated with prediction of methane and allow a better examination and representation of policies regulating emissions from cattle.     

The simple construction of protein alpha-carbon models

A method has been developed for the rapid construction of protein alpha-carbon models from a continuous length of metal rod. Selected side groups can be attached, and the scale is continuously variable from 20mm/Å to 4mm/Å. At the smaller scales, models are self-supporting.     

The power of comparative and developmental studies for mouse models of Down syndrome

Since the genetic basis for Down syndrome (DS) was described, understanding the causative relationship between genes at dosage imbalance and phenotypes associated with DS has been a principal goal of researchers studying trisomy 21 (Ts21). Though inferences to the gene-phenotype relationship in humans have been made, evidence linking a specific gene or region to a particular congenital phenotype has been limited. To further understand the genetic basis for DS phenotypes, mouse models with three copies of human chromosome 21 (Hsa21) orthologs have been developed. Mouse models offer access to every tissue at each stage of development, opportunity to manipulate genetic content, and ability to precisely quantify phenotypes. Numerous approaches to recreate trisomic composition and analyze phenotypes similar to DS have resulted in diverse trisomic mouse models. A murine intraspecies comparative analysis of different genetic models of Ts21 and specific DS phenotypes reveals the complexity of trisomy and important considerations to understand the etiology of and strategies for amelioration or prevention of trisomic phenotypes. By analyzing individual phenotypes in different mouse models throughout development, such as neurologic, craniofacial, and cardiovascular abnormalities, greater insight into the gene-phenotype relationship has been demonstrated. In this review we discuss how phenotype-based comparisons between DS mouse models have been useful in analyzing the relationship of trisomy and DS phenotypes.