Cyclic stretch enhances reorientation and differentiation of 3-D culture model of human airway smooth muscle

Activation of airway smooth muscle (ASM) cells plays a central role in the pathophysiology of asthma. Because ASM is an important therapeutic target in asthma, it is beneficial to develop bioengineered ASM models available for assessing physiological and biophysical properties of ASM cells. In the physiological condition in vivo, ASM cells are surrounded by extracellular matrix (ECM) and exposed to mechanical stresses such as cyclic stretch. We utilized a 3-D culture model of human ASM cells embedded in type-I collagen gel. We further examined the effects of cyclic mechanical stretch, which mimics tidal breathing, on cell orientation and expression of contractile proteins of ASM cells within the 3-D gel. ASM cells in type-I collagen exhibited a tissue-like structure with actin stress fiber formation and intracellular Ca²⁺ mobilization in response to methacholine. Uniaxial cyclic stretching enhanced alignment of nuclei and actin stress fibers of ASM cells. Moreover, expression of mRNAs for contractile proteins such as α-smooth muscle actin, calponin, myosin heavy chain 11, and transgelin of stretched ASM cells was significantly higher than that under the static condition. Our findings suggest that mechanical force and interaction with ECM affects development of the ASM tissue-like construct and differentiation to the contractile phenotype in a 3-D culture model.     

Mathematical Model for the Contribution of Individual Organs to Non-Zero Y-Intercepts in Single and Multi-Compartment Linear Models of Whole-Body Energy Expenditure

Mathematical models for the dependence of energy expenditure (EE) on body mass and composition are essential tools in metabolic phenotyping. EE scales over broad ranges of body mass as a non-linear allometric function. When considered within restricted ranges of body mass, however, allometric EE curves exhibit ‘local linearity.’ Indeed, modern EE analysis makes extensive use of linear models. Such models typically involve one or two body mass compartments (e.g., fat free mass and fat mass). Importantly, linear EE models typically involve a non-zero (usually positive) y-intercept term of uncertain origin, a recurring theme in discussions of EE analysis and a source of confounding in traditional ratio-based EE normalization. Emerging linear model approaches quantify whole-body resting EE (REE) in terms of individual organ masses (e.g., liver, kidneys, heart, brain). Proponents of individual organ REE modeling hypothesize that multi-organ linear models may eliminate non-zero y-intercepts. This could have advantages in adjusting REE for body mass and composition. Studies reveal that individual organ REE is an allometric function of total body mass. I exploit first-order Taylor linearization of individual organ REEs to model the manner in which individual organs contribute to whole-body REE and to the non-zero y-intercept in linear REE models. The model predicts that REE analysis at the individual organ-tissue level will not eliminate intercept terms. I demonstrate that the parameters of a linear EE equation can be transformed into the parameters of the underlying ‘latent’ allometric equation. This permits estimates of the allometric scaling of EE in a diverse variety of physiological states that are not represented in the allometric EE literature but are well represented by published linear EE analyses.     

Prediction of function divergence in protein families using the substitution rate variation parameter alpha

Protein families typically embody a range of related functions and may thus be decomposed into subfamilies with, for example, distinct substrate specificities. Detection of functionally divergent subfamilies is possible by methods for recognizing branches of adaptive evolution in a gene tree. As the number of genome sequences is growing rapidly, it is highly desirable to automatically detect subfamily function divergence. To this end, we here introduce a method for large-scale prediction of function divergence within protein families. It is called the alpha shift measure (ASM) as it is based on detecting a shift in the shape parameter (alpha [alpha]) of the substitution rate gamma distribution. Four different methods for estimating alpha were investigated. We benchmarked the accuracy of ASM using function annotation from Enzyme Commission numbers within Pfam protein families divided into subfamilies by the automatic tree-based method BETE. In a test using 563 subfamily pairs in 162 families, ASM outperformed functional site-based methods using rate or conservation shifting (rate shift measure [RSM] and conservation shift measure [CSM]). The best results were obtained using the "GZ-Gamma" method for estimating alpha. By combining ASM with RSM and CSM using linear discriminant analysis, the prediction accuracy was further improved.     

A novel model of early type 1 diabetes mellitus: The chick embryo air sack model

Diabetes Mellitus (DM) is a metabolic disease characterized by hyperglycemia. Chronic hyperglycemia is associated with long-term dysfunction such as retinopathy, nephropathy, neuropathy and cardiovascular diseases. These complications increase rates of death and disability worldwide. Due to the negative effects of DM on the quality of life, the mechanism and treatments of the disease should be investigated in more detail. Most of the research in diabetes is performed in experimental animals. Experimental animal models contributed to the advancement of clinical research, the development of new therapeutic approaches, the discovery of insulin and the purification of insulin. There are many animal models of DM in the literature. But there are a few DM model studies created with chick embryos. In these studies, it was seen that there were differences in STZ doses and STZ administration techniques. The objective of this study was to create a more acceptable and easier DM model. 180 specific pathogen free (SPF) fertilized chicken eggs (White Leghorn chicken) were used in this study. STZ was administered to 160 SPF eggs for an induced DM model. The remaining 20 SPF eggs were separated as a control group. We used two different DM models (Air sack model (ASM) and Chorioallantoic membrane model (CAMM)) and blood sampling technique in our study. 160 SPF eggs were divided into two groups with 80 eggs in each group, according to the model in which STZ was administered. When the relationship between blood glucose and blood insulin levels were examined, it was determined that there was a significantly strong negative correlation in the control group and ASM 1 group; and a significantly very strong negative correlation was found in the ASM 2 group and ASM 3 group. Our data indicate that the optimal STZ dose to create a DM model was 0.45 mg/egg and the best DM model was ASM. The second technique to be the best blood sampling technique for determining blood glucose levels. We believe that ASM can be used in DM studies and anti-DM drug studies in terms of its easebly, applicability, reproducibility and low cost.     

Development of mechanistically based model for simulating soluble microbial products generation in an aerated/non-aerated SBR

Soluble microbial products (SMPs) are considered as the main organic components in wastewater treatment plant effluent from biological wastewater treatment systems. To investigate and explore SMP metabolism pathway for further treatment and control, two innovative mechanistically based activated sludge models were developed by extension of activated sludge model no.3 (ASM3). One was the model by combining SMP formation and degradation (ASM3-SMP model) processes with ASM3, and the other by combining both SMP and simultaneous substrate storage and growth (SSSG) mechanisms with ASM3 (SSSG-ASM3-SMP model). The detailed schematic modification and process supplements were introduced for comprehensively understanding all the mechanisms involved in the activated sludge process. The evaluations of these two models were demonstrated by a laboratory-scale sequencing batch reactor (SBR) operated under aerated/non-aerated conditions. The simulated and measured results indicated that SMP comprised about 83% of total soluble chemical oxygen demand (SCOD) in which biomass-associated products (BAPs) were predominant compared with utilization-associated products (UAPs). It also elucidated that there should be a minimum SMP value as the reactive time increases continuously and this conclusion could be used to optimize effluent SCOD in activated sludge processes. The comparative results among ASM3, ASM3-SMP and SSSG-ASM3-SMP models and the experimental measurements (SCOD, ammonia and nitrate nitrogen) showed clearly the best agreement with SSSG-ASM3-SMP simulation values (R = 0.993), strongly suggesting that both SMP formation and degradation and SSSG mechanisms are necessary in biologically activated sludge modeling for municipal wastewater treatment.     

Critical review of activated sludge modeling: State of process knowledge,modeling concepts,and limitations

This work critically reviews modeling concepts for standard activated sludge wastewater treatment processes (e.g., hydrolysis, growth and decay of organisms, etc.) for some of the most commonly used models. Based on a short overview on the theoretical biochemistry knowledge this review should help model users to better understand (i) the model concepts used; (ii) the differences between models, and (iii) the limits of the models. The seven analyzed models are: (1) ASM1; (2) ASM2d; (3) ASM3; (4) ASM3 + BioP; (5) ASM2d + TUD; (6) Barker & Dold model; and (7) UCTPHO+. Nine standard processes are distinguished and discussed in the present work: hydrolysis; fermentation; ordinary heterotrophic organisms (OHO) growth; autotrophic nitrifying organisms (ANO) growth; OHO & ANO decay; poly‐hydroxyalkanoates (PHA) storage; polyphosphate (polyP) storage; phosphorus accumulating organisms PAO) growth; and PAO decay. For a structured comparison, a new schematic representation of these processes is proposed. Each process is represented as a reaction with consumed components on the left of the figure and produced components on the right. Standardized icons, based on shapes and color codes, enable the representation of the stoichiometric modeling concepts and kinetics. This representation allows highlighting the conceptual differences of the models, and the level of simplification between the concepts and the theoretical knowledge. The model selection depending on their theoretical limitations and the main research needs to increase the model quality are finally discussed. Biotechnol. Bioeng. 2013; 110: 24–46. © 2012 Wiley Periodicals, Inc.     

Effect of pH on biological phosphorus uptake

An anaerobic aerobic laboratory scale sequencing batch reactor (SBR) was operated to study the effect of pH on enhanced biological phosphorus removal. Seven steady states were achieved under different operating conditions. In all of them, a slight variation in the pH value was observed during anaerobic phase. However, pH rose significantly during aerobic phase. The increase observed was due to phosphorus uptake and carbon dioxide stripping. When pH was higher than 8.2-8.25 the phosphorus uptake rate clearly decreased. The capability of Activated Sludge Model No. 2d (ASM2d) and Biological Nutrient Removal Model No. 1 (BNRM1) to simulate experimental results was evaluated. Both models successfully characterized the enhanced biological phosphorus removal performance of the SBR. Furthermore, BNRM1 also reproduced the pH variations observed and the decrease in the phosphorus uptake rate. This model includes a switch function in the kinetic expressions to represent the pH inhibition in biological processes. The pH inhibition constants related to polyphosphate storage process were obtained by adjusting model predictions to measured phosphorus concentrations. On the other hand, pH inhibition should be included in ASM2d to accurately simulate experimental phosphorus evolution observed in an A/O SBR.     

Pattern formation in discrete cell lattices

In recent years, models for lattices of discrete cells have been attracting increased attention due to their greater flexibility to represent signalling and contact-dependent cell-cell interaction than conventional reaction-diffusion models. Using the almost forgotten method of Othmer and Scriven (1971) to calculate eigenvalues and eigenvectors for the Jacobian of the homogeneous state, a Turing-like linear stability analysis is carried out for diffusion-driven (DD) and signalling-driven (SD) discrete models. The method is a generalisation of the original method of Turing (1952). For two-species models it is found that there are profound differences between the two types of model when the size of the lattice increases. For DD models, the homogeneous state is typically either always stable, always unstable, or becomes unstable when the lattice gets suffficiently large. For SD models, the homogeneous state is typically unstable independent of lattice size, and stable only in a minor part of parameter space. Thus, SD models seem in general more pattern-prone than DD models. The conjecture that the linear analysis predicts the final pattern is investigated for a DD system with Thomas internal dynamics. Commonly the final pattern resembles the pattern of the initial perturbation of the homogeneous state, but this is by no means a general feature. When applied to a recent model for Delta-Notch lateral inhibition, linear analysis must be supplemented by various non-linear techniques to get a deeper insight into the patterning mechanisms. The overall conclusion is that a linear Turing analysis may be useful for predicting pattern, but when it comes to explaining patterns, non-linear analysis cannot be ignored. Received: 1 March 2000 / Revised version: 23 April 2000 / Published online: 12 October 2001     

Periodicities of open linear systems with positive steady states

Systems of two, three, and four linear non-homogeneous differential equations are examined with a view toward determining whether they can possibly serve as mathematical models to describe periodicities in the concentrations of substances which enhance or inhibit each other's rate of production (or dissipation). The nature of the model demands that the solutions of the differential equations be non-negative at all times, i.e., that all the steady states be positive. Conditions for periodicity and for positive steady states are derived, and it is shown that these conditions are not always compatible with each other. In particular it is shown that certain three- and four-hormone models proposed to account for the periodicities observed in the menstrual cycle cannot satisfy the above conditions for any values of the parameters and hence are inadequate.     

Robust control of the activated sludge process

In this work, a robust control strategy is proposed for maintaining the oxygen concentration in the aerobic tank and the pollutant, i.e., ammonium, nitrate, nitrite, concentrations at acceptable levels in the effluent water at the outlet of the activated sludge process. To this end, the Activated Sludge Model no. 1 (ASM1) is first reduced using biological arguments and a singular perturbation method, and a simplified model of the secondary settler is included. In contrast with previous studies that make use of piecewise linear models, an average operating point is evaluated using available data (here data from the COST Action 624) and the reduced‐order model is linearized around it using standard techniques. Finally, a H₂ robust control strategy acting on the oxygen injection and the recirculated flow rate is designed and tested in simulation. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2009     

A review towards finding a simplified approach for modelling the kinetics of the soluble microbial products (SMP) in an integrated mathematical model of membrane bioreactor (MBR)

Soluble microbial products (SMPs) tend to accumulate in the membrane bioreactor (MBR) systems as a consequence of high membrane rejection and apparently low biodegradability within the wastewater treatment system. The extension of the activated sludge models (ASMs) with SMPs, therefore, has received crucial importance in recent days, particularly considering their potential use as indicators of the membrane fouling propensity. This paper presents a critical review of the formation and degradation kinetics of SMP subdivisions that have so far been used for the mathematical modelling of MBR. The paper identified a simplified approach to incorporate the kinetics of the SMP formation and degradation in the general mathematical models of MBR. It suggested that the inclusion of only four additional linear differential equations in the ASM1-SMP integrated mathematical model could simulate well the effluent quality and membrane fouling prediction. The model would also serve as a useful tool in optimizing operation conditions for better treatability and fouling control.     

Interpretable machine learning for high-dimensional trajectories of aging health

We have built a computational model for individual aging trajectories of health and survival, which contains physical, functional, and biological variables, and is conditioned on demographic, lifestyle, and medical background information. We combine techniques of modern machine learning with an interpretable interaction network, where health variables are coupled by explicit pair-wise interactions within a stochastic dynamical system. Our dynamic joint interpretable network (DJIN) model is scalable to large longitudinal data sets, is predictive of individual high-dimensional health trajectories and survival from baseline health states, and infers an interpretable network of directed interactions between the health variables. The network identifies plausible physiological connections between health variables as well as clusters of strongly connected health variables. We use English Longitudinal Study of Aging (ELSA) data to train our model and show that it performs better than multiple dedicated linear models for health outcomes and survival. We compare our model with flexible lower-dimensional latent-space models to explore the dimensionality required to accurately model aging health outcomes. Our DJIN model can be used to generate synthetic individuals that age realistically, to impute missing data, and to simulate future aging outcomes given arbitrary initial health states.     

Monotone dependence of the spectral bound on the transition rates in linear compartment models

For linear compartment models or Leslie-type staged population models with quasi-positive matrix the spectral bound of the matrix (the eigenvalue determining stability) is studied in the situation where particles or individuals leave a compartment or stage with some rate and enter another with the same rate. Then the matrix carries the rate with a positive sign in some off-diagonal entry and with a negative sign in the corresponding diagonal entry. Hence the matrix does not depend on the rate in a monotone way. It is shown, however, that the spectral bound is a monotone function of the rate. It is all the time strictly increasing or strictly decreasing or it is constant. A simple algebraic criterion distinguishes between the three cases. The results can be applied to linear systems and to the stability of stationary states in non-linear systems, in particular to models for the transmission of infectious diseases, and in population dynamics.     

Human airway smooth muscle promotes human lung mast cell survival, proliferation, and constitutive activation: cooperative roles for CADM1, stem cell factor, and IL-6

The microlocalization of mast cells within specific tissue compartments is thought to be critical for the pathophysiology of many diverse diseases. This is particularly evident in asthma where they localize to the airway smooth muscle (ASM) bundles. Mast cells are recruited to the ASM by numerous chemoattractants and adhere through CADM1, but the functional consequences of this are unknown. In this study, we show that human ASM maintains human lung mast cell (HLMC) survival in vitro and induces rapid HLMC proliferation. This required cell-cell contact and occurred through a cooperative interaction between membrane-bound stem cell factor (SCF) expressed on ASM, soluble IL-6, and CADM1 expressed on HLMC. There was a physical interaction in HLMC between CADM1 and the SCF receptor (CD117), suggesting that CADM1-dependent adhesion facilitates the interaction of membrane-bound SCF with its receptor. HLMC-ASM coculture also enhanced constitutive HLMC degranulation, revealing a novel smooth muscle-driven allergen-independent mechanism of chronic mast cell activation. Targeting these interactions in asthma might offer a new strategy for the treatment of this common disease.     

Controllability of non-linear biochemical systems

Mathematical methods of biochemical pathway analysis are rapidly maturing to a point where it is possible to provide objective rationale for the natural design of metabolic systems and where it is becoming feasible to manipulate these systems based on model predictions, for instance, with the goal of optimizing the yield of a desired microbial product. So far, theory-based metabolic optimization techniques have mostly been applied to steady-state conditions or the minimization of transition time, using either linear stoichiometric models or fully kinetic models within biochemical systems theory (BST). This article addresses the related problem of controllability, where the task is to steer a non-linear biochemical system, within a given time period, from an initial state to some target state, which may or may not be a steady state. For this purpose, BST models in S-system form are transformed into affine non-linear control systems, which are subjected to an exact feedback linearization that permits controllability through independent variables. The method is exemplified with a small glycolytic-glycogenolytic pathway that had been analyzed previously by several other authors in different contexts.     

A maturational model for the study of airway smooth muscle adaptation to mechanical oscillation

It has been shown that mechanical stretches imposed on airway smooth muscle (ASM) by deep inspiration reduce the subsequent contractile response of the ASM. This passive maneuver of lengthening and retraction of the muscle is beneficial in normal subjects to counteract bronchospasm. However, it is detrimental to hyperresponsive airways because it triggers further bronchoconstriction. Although the exact mechanisms for this contrary response by normal and hyperresponsive airways are unclear, it has been suggested that the phenomenon is related to changes in ASM adaptability to mechanical oscillation. Healthy immature airways of both human and animal exhibit hyperresponsiveness, but whether the adaptative properties of hyperresponsive airway differ from normal is still unknown. In this article, we review the phenomenon of ASM adaptation to mechanical oscillation and its relevance and implication to airway hyperresponsiveness. We demonstrate that the age-specific expression of ASM adaptation is prominent using an established maturational animal model developed in our laboratory. Our data on immature ASM showed potentiated contractile force shortly after a length oscillation compared with the maximum force generated before oscillation. Several potential mechanisms such as myogenic response, changes in actin polymerization, or changes in the quantity of the cytoskeletal regulatory proteins plectin and vimentin, which may underlie this age-specific force potentiation, are discussed. We suggest a working model of the structure of smooth muscle associated with force transmission, which may help to elucidate the mechanisms responsible for the age-specific expression of smooth muscle adaptation. It is important to study the maturational profile of ASM adaptation as it could contribute to juvenile hyperresponsiveness.     

Reaction rate constants and mean population percentage for nitrifiers in an alternating oxidation ditch system

This paper presents a methodology for the determination of reaction rate constants for nitrifying bacteria and their mean population percentage in biomass in an alternating oxidation ditch system. The method used is based on the growth rate equations of the ASM1 model (IWA) (Henze et al. in Activated sludge models ASM1, ASM2, ASM2d, and ASM3. IWA Scientific and Technical Report no. 9, IWA Publishing, London, UK, 2000) and the application of mass balance equations for nitrifiers and ammonium nitrogen in an operational cycle of the ditch system. The system consists of two ditches operating in four phases. Data from a large-scale oxidation ditch pilot plant with a total volume of 120 m³ within an experimental period of 8 months was used. Maximum specific growth rate for autotrophs (μ _A) and the half-saturation constant for ammonium nitrogen (K _NH) were found to be 0.36 day⁻¹ and 0.65 mgNH₄–N/l, respectively. Additionally, the average population percentage of the nitrifiers in the biomass was estimated to be around 3%.     

Could an increase in airway smooth muscle shortening velocity cause airway hyperresponsiveness?

Airway hyperresponsiveness (AHR) is a characteristic feature of asthma. It has been proposed that an increase in the shortening velocity of airway smooth muscle (ASM) could contribute to AHR. To address this possibility, we tested whether an increase in the isotonic shortening velocity of ASM is associated with an increase in the rate and total amount of shortening when ASM is subjected to an oscillating load, as occurs during breathing. Experiments were performed in vitro using 27 rat tracheal ASM strips supramaximally stimulated with methacholine. Isotonic velocity at 20% isometric force (Fiso) was measured, and then the load on the muscle was varied sinusoidally (0.33 ± 0.25 Fiso, 1.2 Hz) for 20 min, while muscle length was measured. A large amplitude oscillation was applied every 4 min to simulate a deep breath. We found that: 1) ASM strips with a higher isotonic velocity shortened more quickly during the force oscillations, both initially (P < 0.001) and after the simulated deep breaths (P = 0.002); 2) ASM strips with a higher isotonic velocity exhibited a greater total shortening during the force oscillation protocol (P < 0.005); and 3) the effect of an increase in isotonic velocity was at least comparable in magnitude to the effect of a proportional increase in ASM force-generating capacity. A cross-bridge model showed that an increase in the total amount of shortening with increased isotonic velocity could be explained by a change in either the cycling rate of phosphorylated cross bridges or the rate of myosin light chain phosphorylation. We conclude that, if asthma involves an increase in ASM velocity, this could be an important factor in the associated AHR.     

The Importance of Synergy between Deep Inspirations and Fluidization in Reversing Airway Closure

Deep inspirations (DIs) and airway smooth muscle fluidization are two widely studied phenomena in asthma research, particularly for their ability (or inability) to counteract severe airway constriction. For example, DIs have been shown effectively to reverse airway constriction in normal subjects, but this is impaired in asthmatics. Fluidization is a connected phenomenon, wherein the ability of airway smooth muscle (ASM, which surrounds and constricts the airways) to exert force is decreased by applied strain. A maneuver which sufficiently strains the ASM, then, such as a DI, is thought to reduce the force generating capacity of the muscle via fluidization and hence reverse or prevent airway constriction. Understanding these two phenomena is considered key to understanding the pathophysiology of asthma and airway hyper-responsiveness, and while both have been extensively studied, the mechanism by which DIs fail in asthmatics remains elusive. Here we show for the first time the synergistic interaction between DIs and fluidization which allows the combination to provide near complete reversal of airway closure where neither is effective alone. This relies not just on the traditional model of airway bistability between open and closed states, but also the critical addition of previously-unknown oscillatory and chaotic dynamics. It also allows us to explore the types of subtle change which can cause this interaction to fail, and thus could provide the missing link to explain DI failure in asthmatics.     

Effect of Loading History on Airway Smooth Muscle Cell-Matrix Adhesions

Integrin-mediated adhesions between airway smooth muscle (ASM) cells and the extracellular matrix (ECM) regulate how contractile forces generated within the cell are transmitted to its external environment. Environmental cues are known to influence the formation, size, and survival of cell-matrix adhesions, but it is not yet known how they are affected by dynamic fluctuations associated with tidal breathing in the intact airway. Here, we develop two closely related theoretical models to study adhesion dynamics in response to oscillatory loading of the ECM, representing the dynamic environment of ASM cells in vivo. Using a discrete stochastic-elastic model, we simulate individual integrin binding and rupture events and observe two stable regimes in which either bond formation or bond rupture dominate, depending on the amplitude of the oscillatory loading. These regimes have either a high or low fraction of persistent adhesions, which could affect the level of strain transmission between contracted ASM cells and the airway tissue. For intermediate loading, we observe a region of bistability and hysteresis due to shared loading between existing bonds; the level of adhesion depends on the loading history. These findings are replicated in a related continuum model, which we use to investigate the effect of perturbations mimicking deep inspirations (DIs). Because of the bistability, a DI applied to the high adhesion state could either induce a permanent switch to a lower adhesion state or allow a return of the system to the high adhesion state. Transitions between states are further influenced by the frequency of oscillations, cytoskeletal or ECM stiffnesses, and binding affinities, which modify the magnitudes of the stable adhesion states as well as the region of bistability. These findings could explain (in part) the transient bronchodilatory effect of a DI observed in asthmatics compared to a more sustained effect in normal subjects.