Modeling of rotating biological contactor systems

An investigation of the rotating biological contractor (RBC) process variables to determine the efficiency of biological oxygen demand (BOD) removal is presented. Operating parameters including influent BOD content (<355 mg/liter), flow rate, disk surface area, hydraulic loading, disk rotational speed, liquid retention time, stage number, and wastewater temperature were evaluated. The BOD predictive model was developed using literature data with multiple regression analysis. This study shows that influent BOD concentration, hydraulic loading, stage number, and wastewater temperature are the most significant variables in predicting the RBC system performance. The model presently developed was verified by field data concerned with the treatment of both domestic and low-strength industrial wastewaters. Also, the results calculated by this model were compared to those obtained from Weng's model.     

Variance-based sensitivity analysis of biological uncertainties in carbon ion therapy

PurposeBiological models to estimate the relative biological effectiveness (RBE) or the equivalent dose in 2 Gy fractions (EQD2) are needed for treatment planning and plan evaluation in carbon ion therapy. We present a model-independent, Monte Carlo based sensitivity analysis (SA) approach to quantify the impact of different uncertainties on the biological models.Methods and materialsThe Monte Carlo based SA is used for the evaluation of variations in biological parameters. The key property of this SA is the high number of simulation runs, each with randomized input parameters, allowing for a statistical variance-based ranking of the input variations. The potential of this SA is shown in a simplified one-dimensional treatment plan optimization. Physical properties of carbon ion beams (e.g. fragmentation) are simulated using the Monte Carlo code FLUKA. To estimate biological effects of ion beams compared to X-rays, we use the Local Effect Model (LEM) in the framework of the linear-quadratic (LQ) model. Currently, only uncertainties in the output of the biological models are taken into account.Results/conclusionsThe presented SA is suitable for evaluation of the impact of variations in biological parameters. Major advantages are the possibility to access and display the sensitivity of the evaluated quantity on several parameter variations at the same time. Main challenges for later use in three-dimensional treatment plan evaluation are computational time and memory usage. The presented SA can be performed with any analytical or numerical function and hence be applied to any biological model used in carbon ion therapy.     

Kinetic Instability of Zero Steady State As a Fundamental Cause of Low Efficiency of Chemotherapy of Cancer

Using mathematical modeling of the process of cancer treatment by the classical chemotherapy methods and therapy with biological agents, the effect of the kinetic parameters of the model on the final outcome of treatment was studied. It is established that the complete cure (i.e., the formation of a stable steady state with a zero number of cancer cells) cannot be reached by means of only classical chemotherapy.     

Dependence of biological treatment rate on species composition in activated sludge or biofilm. II: From models to theory

Traditional biological treatment models are "deduced" from formal chemical kinetics or dynamics of pure microorganism cultures growth. The best formal models give reasonable approximations of the biological treatment model with an ecosystem adaptation (ESA model). The model presented here explains some features of the biological treatment mechanism that cannot be described by formal models.     

Tumor therapy and track structure

The elevated relative biological effectiveness (RBE) of heavy ions like carbon is the main reason for their use in radiotherapy and is due to the microscopic distribution of dose inside each particle track. High local doses produce lesions that are expected to have a diminished possibility of repair. Thus, RBE depends on track structure and on the biological repair capacity of the tissue that is affected by the irradiation. For tumor treatment planning with heavy ions, the beam quality and the tissue sensitivity have to be taken into account. Using the dependence of radial dose distribution on particle energy and atomic number on the physical side and x-ray dose response for the repair capacity on the biological side, the response to particle irradiation can be calculated in the local effect model (LEM) and used for treatment planning. This article traces the route from electron emission as the basis of track structure to the RBE calculation and the application in treatment planning. Received: 21 April 1999 / Accepted in revised form: 1 September 1999     

Mathematical modeling of fungal infection in immune compromised individuals: implications for drug treatment

We present a mathematical model that describes treatment of a fungal infection in an immune compromised patient in which both susceptible and resistant strains are present. The resulting nonlinear differential equations model the biological outcome, in terms of strain growth and cell number, when an individual, who has both a susceptible and a resistant population of fungus, is treated with a fungicidal or fungistatic drug. The model demonstrates that when the drug is only successful at treating the susceptible strain, low levels of the drug cause both strains to be in stable co-existence and high levels eradicate the susceptible strain while allowing the resistant strain to persist or to multiply unchecked. A modified model is then described in which the drug is changed to one in which both strains are susceptible, and subsequently, at the appropriate level of treatment, complete eradication of both fungal strains ensues. We discuss the model and implications for treatment options within the context of an immune compromised patient.     

Studies on the toxicity and binding kinetics of abrin in normal and Epstein Barr virus-transformed lymphocyte culture-I: experimental results - 3

The effects of treatment with varying doses of abrin, a D-galactose binding lectin, on DNA and protein synthesis of normal and Epstein Barr virus-transformed lymphocytes have been investigated. Using data on EBV-transformed lymphocyte cell density as a function of time and dose of abrin, one can demonstrate that the mean number of sites bound/EBV-lymphocyte needed to exert a biological influence upon the cell DNA synthesis lies between 59,264 and 370,000 sites/cell. Using a simple packing model, one can demonstrate that a theoretical estimate places the number of binding sites between 57,600 and 360,000 sites/cells.     

The possible role of information technology in radiotherapy II. The development of a biological dose distribution model in the 3-dimensional treatment planning of brain tumours

OBJECTIVE: Developing a new medical software based on the utilisation of information technology required in 3-dimensional treatment planning and modern radiotherapy. METHODS: The physical dose distribution programs were converted into biological meaning with the insertion of biological equivalence equations based on LQ model. Biological dose distributions and biological dose-volume histograms were generated. The treatment plans of a brain tumour patient were investigated to determine the dose burdening of the normal central nervous system tissues. RESULTS: Employing 3D conformal method, the dose of the vital mid-line structures decreased significantly, which possesses a more meaningful biological importance. Different treatment plans and different fractionation regimens could be compared to each other by utilising this kind of biological model. CONCLUSION: By employing information technology we succeeded in establishing a theoretical biological dose distribution system that could be visualised. The advantages of 3D treatment planning proved unambiguous. In the future this method will probably be suitable to choose the best therapeutic regimens.     

Proteomic analysis of differential protein expression in neuropathic pain and electroacupuncture treatment models

Acupuncture has long been used for pain relief. Although recent studies have shown that acupuncture can reduce neuropathic pain, the mechanism of this effect is not clear and little information is available regarding proteins that are involved in the development of neuropathic pain and the effects of acupuncture. We have developed an animal model for neuropathic pain using young adult male Sprague-Dawley rats. The model was confirmed by behavioral tests. Electroacupuncture (EA) treatment was applied to Zusanli (ST36) of neuropathic pain model to examine the analgesic effect of EA. The protein expression profile of the hypothalamus in both neuropathic pain and EA treatment models was analyzed using two-dimensional electrophoresis-based proteomics. We detected thirty-six proteins that were differentially expressed in the neuropathic pain model compared with normal rats and that restored to normal expression levels after EA treatment. Twenty-one of these proteins were identified in the MS-FiT database and are involved in a number of biological processes, including inflammation, enzyme metabolism and signal transduction. Potential applications of our results include the identification and characterization of signaling pathways involved in EA treatment and further exploration of the role of selected identified proteins in the animal model.     

Online nonlinear sequential Bayesian estimation of a biological wastewater treatment process

Online estimation of unknown state variables is a key component in the accurate modelling of biological wastewater treatment processes due to a lack of reliable online measurement systems. The extended Kalman filter (EKF) algorithm has been widely applied for wastewater treatment processes. However, the series approximations in the EKF algorithm are not valid, because biological wastewater treatment processes are highly nonlinear with a time-varying characteristic. This work proposes an alternative online estimation approach using the sequential Monte Carlo (SMC) methods for recursive online state estimation of a biological sequencing batch reactor for wastewater treatment. SMC is an algorithm that makes it possible to recursively construct the posterior probability density of the state variables, with respect to all available measurements, through a random exploration of the states by entities called ‘particle’. In this work, the simplified and modified Activated Sludge Model No. 3 with nonlinear biological kinetic models is used as a process model and formulated in a dynamic state-space model applied to the SMC method. The performance of the SMC method for online state estimation applied to a biological sequencing batch reactor with online and offline measured data is encouraging. The results indicate that the SMC method could emerge as a powerful tool for solving online state and parameter estimation problems without any model linearization or restrictive assumptions pertaining to the type of nonlinear models for biological wastewater treatment processes.     

A general framework for analyzing the genetic architecture of developmental characteristics

The genetic architecture of growth traits plays a central role in shaping the growth, development, and evolution of organisms. While a limited number of models have been devised to estimate genetic effects on complex phenotypes, no model has been available to examine how gene actions and interactions alter the ontogenetic development of an organism and transform the altered ontogeny into descendants. In this article, we present a novel statistical model for mapping quantitative trait loci (QTL) determining the developmental process of complex traits. Our model is constructed within the traditional maximum-likelihood framework implemented with the EM algorithm. We employ biologically meaningful growth curve equations to model time-specific expected genetic values and the AR(1) model to structure the residual variance-covariance matrix among different time points. Because of a reduced number of parameters being estimated and the incorporation of biological principles, the new model displays increased statistical power to detect QTL exerting an effect on the shape of ontogenetic growth and development. The model allows for the tests of a number of biological hypotheses regarding the role of epistasis in determining biological growth, form, and shape and for the resolution of developmental problems at the interface with evolution. Using our newly developed model, we have successfully detected significant additive x additive epistatic effects on stem height growth trajectories in a forest tree.     

Estimation of Human Biological Age Based on the Parameters of Heart Rhythmic Activity

A linear regression model has been constructed for estimating human biological age, with the parameters of heart rhythmic activity being used as biological markers. One of the advantages of using these parameters as biological markers of aging is the possibility to measure a number of parameters for an individual subject in a brief (6–7 min) procedure of rhythmogram recording. This makes the collection of data for a statistically reliable sample much easier, increases the accuracy of the model, and permits its use along with other methods for mass examinations of a population and for control of the effects of drugs and food additives. The model may be extended and supplemented with other biological markers in order to improve the approximation of biological age.     

A cooperative model for ligand binding to biological macromolecules as applied to oxygen carriers

This paper presents a model describing the thermodynamics of cooperative ligand binding to multimeric biological macromolecules and integrating some of the features of the two-state and induced-fit models. The protein is taken to be partitioned into a number of noninteracting functional constellations, each one existing in two possible quaternary conformations. Furthermore, the model postulates that a functional constellation is organized in several subsets of sites (called cooperons), in which subunits interact according to an induced-fit mechanism. In the present version the number of subunits forming a cooperon has been limited to two and the total number of parameters used for fitting experimental data is four, all having a precise physical meaning. Although the present application is limited to oxygen-carrying proteins (hemoglobins, hemocyanins, erythrocruorins), the model appears suitable to describe other biological macromolecules with functional interactions.     

Treatment and survival study in the C57BL/6J-APC(Min)/+(Min) mouse with R-flurbiprofen

Our previous studies with the mouse model of familial adenomatous polyposis (FAP), C57BL/6J-APC(Min)/+ or Min mouse, demonstrated the optimal dose for adenoma reduction with R-flurbiprofen was 10 mg/kg/day as an undivided dose. Divided doses exhibited no increased efficaciousness. This study examines 10 mg/kg R-flurbiprofen daily (qd) on survival as well as a second daily (q.o.d.) schedule and compares it with sulindac sulfone. The q.o.d. schedule at 10 mg/kg was equally efficacious as qd treatment at the same dose. For the q.o.d. group, tumor number decreased similarly (p<0.01); while body weight gain (p<0.01), hematocrit and average tumor area (both, p<0.05) were improved compared with qd treatment. Treatment with R-flurbiprofen (10 mg/kg/day) increased survival significantly (p=0.0004, log-rank) compared to vehicle treated animals. Major biological endpoints (hematocrit, weight gain, tumor number, average and total area [99% reduction]) were significantly improved in treated animals (p<0.01). Sulindac sulfone treatment (50 mg/kg/day) of the Min mouse produced no significant biological benefit. The dose schedule study suggests that for tumor reduction it is necessary to attain a threshold drug-level but not necessarily sustain it over 24 hrs (pharmacodynamic t1/2 > pharmacokinetic t1/2). During the period of administration R-flurbiprofen dramatically prolongs survival for the mouse model of the human disease, FAP.     

A stochastic model for the sigmoidal behaviour of cooperative biological systems

A stochastic model for cooperative transitions in biological systems based on a Markov chain is proposed. This model requires only two parameters, the mean probability, p, and the coupling capacity, Deltap, which measure the probability of forming a new weak bond depending on the number of similar bonds already formed and it is also responsible for the transition. In this paper we show how the model works for a large number of identical molecules and how it can be useful for studying the noise around the centre of the transition where, increasing the degree of cooperativity, i.e. the number n in the well-known Hill equation, the width of the noise increases along with its fractal dimension. A simple relationship between the degree of cooperativity and the parameter Deltap is proposed, suggesting that the cooperativity of real biological transitions is related to the coupling capacity Deltap of the present model.     

基于SVM和MPC的数字蚯蚓生物反应器温度及相对湿度动态预测控制

为实现自动控制蚯蚓生物处理反应器处理城市污泥过程中温度和相对湿度, 采用SVM(support vector machine)技术结合MPC(model predictive control)模型控制技术建立自动控制模型,准确调节蚯蚓反应器内强耦合的温度和相对湿度,在预定时间有效地控制实际温度和相对湿度达到预设目标。     

Review of operative considerations in spinal cord stem cell therapy

Spinal cord injury (SCI) can permanently impair motor and sensory function and has a devastating cost to patients and the United States healthcare system. Stem cell transplantation for treatment of SCI is a new technique aimed at creating biological functional recovery. Operative techniques in stem cell transplantation for SCI are varied. We review various clinical treatment paradigms, surgical techniques and technical considerations important in SCI treatment. The NCBI PubMed database was queried for “SCI” and “stem cell” with a filter placed for “clinical trials”. Thirty-nine articles resulted from the search and 29 were included and evaluated by study authors. A total of 10 articles were excluded (9 not SCI focused or transplantation focused, 1 canine model). Key considerations for stem cell transplantation include method of delivery (intravenous, intrathecal, intramedullary, or excision and engraftment), time course of treatment, number of treatments and time from injury until treatment. There are no phase III clinical trials yet, but decreased time from injury to treatment and a greater number of stem cell injections both seem to increase the chance of functional recovery.     

Chemometric analysis of Hymenoptera toxins and defensins: A model for predicting the biological activity of novel peptides from venoms and hemolymph

When searching for prospective novel peptides, it is difficult to determine the biological activity of a peptide based only on its sequence. The “trial and error” approach is generally laborious, expensive and time consuming due to the large number of different experimental setups required to cover a reasonable number of biological assays. To simulate a virtual model for Hymenoptera insects, 166 peptides were selected from the venoms and hemolymphs of wasps, bees and ants and applied to a mathematical model of multivariate analysis, with nine different chemometric components: GRAVY, aliphaticity index, number of disulfide bonds, total residues, net charge, pI value, Boman index, percentage of alpha helix, and flexibility prediction. Principal component analysis (PCA) with non-linear iterative projections by alternating least-squares (NIPALS) algorithm was performed, without including any information about the biological activity of the peptides. This analysis permitted the grouping of peptides in a way that strongly correlated to the biological function of the peptides. Six different groupings were observed, which seemed to correspond to the following groups: chemotactic peptides, mastoparans, tachykinins, kinins, antibiotic peptides, and a group of long peptides with one or two disulfide bonds and with biological activities that are not yet clearly defined. The partial overlap between the mastoparans group and the chemotactic peptides, tachykinins, kinins and antibiotic peptides in the PCA score plot may be used to explain the frequent reports in the literature about the multifunctionality of some of these peptides. The mathematical model used in the present investigation can be used to predict the biological activities of novel peptides in this system, and it may also be easily applied to other biological systems.