Whole-genome DNA methylation status associated with clinical PTSD measures of OIF/OEF veterans.

Emerging knowledge suggests that post-traumatic stress disorder (PTSD) pathophysiology is linked to the patients' epigenetic changes, but comprehensive studies examining genome-wide methylation have not been performed. In this study, we examined genome-wide DNA methylation in peripheral whole blood in combat veterans with and without PTSD to ascertain differentially methylated probes. Discovery was initially made in a training sample comprising 48 male Operation Enduring Freedom (OEF)/Operation Iraqi Freedom (OIF) veterans with PTSD and 51 age/ethnicity/gender-matched combat-exposed PTSD-negative controls. Agilent whole-genome array detected ~5600 differentially methylated CpG islands (CpGI) annotated to ~2800 differently methylated genes (DMGs). The majority (84.5%) of these CpGIs were hypermethylated in the PTSD cases. Functional analysis was performed using the DMGs encoding the promoter-bound CpGIs to identify networks related to PTSD. The identified networks were further validated by an independent test set comprising 31 PTSD+/29 PTSD- veterans. Targeted bisulfite sequencing was also used to confirm the methylation status of 20 DMGs shown to be highly perturbed in the training set. To improve the statistical power and mitigate the assay bias and batch effects, a union set combining both training and test set was assayed using a different platform from Illumina. The pathways curated from this analysis confirmed 65% of the pool of pathways mined from training and test sets. The results highlight the importance of assay methodology and use of independent samples for discovery and validation of differentially methylated genes mined from whole blood. Nonetheless, the current study demonstrates that several important epigenetically altered networks may distinguish combat-exposed veterans with and without PTSD.

Note: Parameter-independent bounding of the stochastic Michaelis-Menten steady-state intrinsic noise variance.

Using the (slow-scale) linear noise approximation, we give parameter-independent bounds to the substrate and product intrinsic noise variance for the stochastic Michaelis-Menten approximation at steady state.

Modular closed-loop control of diabetes.

Modularity plays a key role in many engineering systems, allowing for plug-and-play integration of components, enhancing flexibility and adaptability, and facilitating standardization. In the control of diabetes, i.e., the so-called "artificial pancreas," modularity allows for the step-wise introduction of (and regulatory approval for) algorithmic components, starting with subsystems for assured patient safety and followed by higher layer components that serve to modify the patient's basal rate in real time. In this paper, we introduce a three-layer modular architecture for the control of diabetes, consisting in a sensor/pump interface module (IM), a continuous safety module (CSM), and a real-time control module (RTCM), which separates the functions of insulin recommendation (postmeal insulin for mitigating hyperglycemia) and safety (prevention of hypoglycemia). In addition, we provide details of instances of all three layers of the architecture: the APS© serving as the IM, the safety supervision module (SSM) serving as the CSM, and the range correction module (RCM) serving as the RTCM. We evaluate the performance of the integrated system via in silico preclinical trials, demonstrating 1) the ability of the SSM to reduce the incidence of hypoglycemia under nonideal operating conditions and 2) the ability of the RCM to reduce glycemic variability.

Cell population modelling describes intrinsic heterogeneity: a case study for hematopoietic stem cells.

The control of stem cell properties during in vitro expansion is of paramount importance for their clinical use. According to Food and Drug Administration (FDA) guidelines, phenotypic heterogeneity is a critical aspect influencing therapeutic response. Even if the authors ability to reduce heterogeneity were limited, the sources from which it arises should be well understood for safe clinical applications. The aim of this work was to describe theoretically the intrinsic cell population heterogeneity that is present even when cells are cultured in a perfectly homogeneous environment. A bivariate population balance model is developed to account for the heterogeneity in the number of receptors and receptor-ligand complexes per cell, and is coupled with a ligand conservation equation. As a case study, the model is applied to the hematopoietic stem cell expansion, considering the c-Kit receptor and stem cell factor pair. Results show the dependence of intrinsic heterogeneity from ligand concentration and the kinetics of its administration. By tracking the cell generations within the total population, the authors highlight intra- and an inter-generational contributions to total population heterogeneity. In terms of dimensionless variables, intrinsic heterogeneity is dependent on the ratio of the characteristic time of cell division to that needed by a newborn cell to reach its single-cell steady state. [Includes supplementary material].

Development of a multi-parametric model predictive control algorithm for insulin delivery in type 1 diabetes mellitus using clinical parameters.

A multi-parametric model predictive control (mpMPC) algorithm for subcutaneous insulin delivery for individuals with type 1 diabetes mellitus (T1DM) that is computationally efficient, robust to variations in insulin sensitivity, and involves minimal burden for the user is proposed. System identification was achieved through impulse response tests feasible for ambulatory conditions on the UVa/Padova simulator adult subjects with T1DM. An alternative means of system identification using readily available clinical parameters was also investigated. A safety constraint was included explicitly in the algorithm formulation using clinical parameters typical of those available to an attending physician. Closed-loop simulations were carried out with daily consumption of 200 g carbohydrate. Controller robustness was assessed by subject/model mismatch scenarios addressing daily, simultaneous variation in insulin sensitivity and meal size with the addition of Gaussian white noise with a standard deviation of 10%. A second-order-plus-time-delay transfer function model fit the validation data with a mean (coefficient of variation) root-mean-square-error (RMSE) of 26 mg/dL (19%) for a 3 h prediction horizon. The resulting control law maintained a low risk Low Blood Glucose Index without any information about carbohydrate consumption for 90% of the subjects. Low-order linear models with clinically meaningful parameters thus provided sufficient information for a model predictive control algorithm to control glycemia. The use of clinical knowledge as a safety constraint can reduce hypoglycemic events, and this same knowledge can further improve glycemic control when used explicitly as the controller model. The resulting mpMPC algorithm was sufficiently compact to be implemented on a simple electronic device.

Distribution-based sensitivity metric for highly variable biochemical systems.

Classical sensitivity analysis is routinely used to identify points of fragility or robustness in biochemical networks. However, intracellular systems often contain components that number in the thousands to tens or less and consequently motivate a stochastic treatment. Although methodologies exist to quantify sensitivities in stochastic models, they differ substantially from those used in deterministic regimes. Therefore it is not possible to tell whether observed differences in sensitivity measured in deterministic and stochastic elaborations of the same network are the result of methodology or model form. The authors introduce here a distribution-based methodology to measure sensitivity that is equally applicable in both regimes, and demonstrate its use and applicability on a sophisticated mathematical model of the mouse circadian clock that is available in both deterministic and stochastic variants. The authors use the method to produce sensitivity measurements on both variants. They note that the rank-order sensitivity of the clock to parametric perturbations is extremely well conserved across several orders of magnitude. The data show that the clock is fragile to perturbations in parameters common to the cellular machinery ('global' parameters) and robust to perturbations in parameters that are clock-specific ('local' parameters). The sensitivity measure can be used to reduce the model from its original 73 ordinary differential equations (ODEs) to 18 ODEs and to predict the degree to which parametric perturbation can distort the phase response curve of the clock. Finally, the method is employed to evaluate the effect of transcriptional and translational noise on clock function. [Includes supplementary material].

Simultaneous high gain and wide dynamic range in a model of bacterial chemotaxis.

Mathematical modelling and sensitivity analysis of the signal transduction pathway underlying chemotaxis in Escherichia coli suggests a mechanism for high sensitivity over a dynamic range of five orders of magnitude. The analysis reveals that the enhancement in sensing ability occurs in the signal receiving module that is comprised of ligand binding, change of occupancy and change of receptor activities. The clustering of receptors contributes to the signal capability by exploiting interactions between receptors for the activity change. The role of the autophosphorylation of the histidine kinase CheA and the phosphotransfer to the response regulator protein CheY is to relay the signal to the cell's motor apparatus at little expense to the sensitivity at low stimuli. The results also provide insight on the values of kinetic parameters that maximise the efficiency of the signalling pathway.

Model identification of signal transduction networks from data using a state regulator problem.

Advances in molecular biology provide an opportunity to develop detailed models of biological processes that can be used to obtain an integrated understanding of the system. However, development of useful models from the available knowledge of the system and experimental observations still remains a daunting task. In this work, a model identification strategy for complex biological networks is proposed. The approach includes a state regulator problem (SRP) that provides estimates of all the component concentrations and the reaction rates of the network using the available measurements. The full set of the estimates is utilised for model parameter identification for the network of known topology. An a priori model complexity test that indicates the feasibility of performance of the proposed algorithm is developed. Fisher information matrix (FIM) theory is used to address model identifiability issues. Two signalling pathway case studies, the caspase function in apoptosis and the MAP kinase cascade system, are considered. The MAP kinase cascade, with measurements restricted to protein complex concentrations, fails the a priori test and the SRP estimates are poor as expected. The apoptosis network structure used in this work has moderate complexity and is suitable for application of the proposed tools. Using a measurement set of seven protein concentrations, accurate estimates for all unknowns are obtained. Furthermore, the effects of measurement sampling frequency and quality of information in the measurement set on the performance of the identified model are described.

Analysis of cellular response to protein overexpression.

The overexpression of secreted proteins is of critical importance to the biotechnology and biomedical fields. A common roadblock to high yields of proteins is in the endoplasmic reticulum (ER) where proofreading for properly folded proteins is often rate limiting. Heterologous expression of secreted proteins can saturate the cell's capacity to properly fold protein, initiating the unfolded protein response (UPR), and resulting in a loss of protein expression. An obvious method for overcoming this block would be to increase the capacity of the folding process (overexpressing chaperones) or decreasing the proofreading process (blocking the down-regulation by the UPR). Unfortunately, these processes are tightly interlinked, whereby modification of one mechanism has unknown effects on the other. Although some success has been achieved in improving expression via co-overexpressing ER chaperones, the results have not lead to a global method for increasing all heterologously overexpressed proteins. Further, many diseases have been linked to extended periods of stress and are not treatable by these approaches. This work utilises both experimental analysis of the interactions within the ER and modelling in order to understand how these interactions affect early secretory pathway dynamics. This study shows that overexpression of the ER chaperone binding protein does not regulate Ire1p and the UPR as predicted by a model based on the published understanding of the molecular mechanism. A new model is proposed for Ire1p regulation and the UPR that better fits the experimental data and recent studies on Ire1p.

Analysis and neuronal modeling of the nonlinear characteristics of a local cardiac reflex in the rat.

Previous experimental results have suggested the existence of a local cardiac reflex in the rat. In this study, the putative role of such a local reflex in cardiovascular regulation is quantitatively analyzed. A model for the local reflex is developed from anatomical experimental results and physiological data in the literature. Using this model, a systems-level analysis is conducted. Simulation results indicate that the neuromodulatory mechanism of the local reflex attenuates the nonlinearity of the relationship between cardiac vagal drive and arterial pressure. This behavior is characterized through coherence analysis. Furthermore, the modulation of phase-related characteristics of the cardiovascular system is suggested as a plausible mechanism for the nonlinear attenuation. Based on these results, it is plausible that the functional role of the local reflex is highly robust nonlinear compensation at the heart, which results in less complex dynamics in other parts of the reflex.

Control-relevant modeling in drug delivery.

The development of control-relevant models for a variety of biomedical engineering drug delivery problems is reviewed in this paper. A summary of each control problem is followed by a review of relevant patient models from literature, an examination of the control approaches taken to solve the problem, and a discussion of the control-relevance of the models used in each case. The areas examined are regulating the depth of anesthesia, blood pressure control, optimal cancer chemotherapy, regulation of cardiac assist devices, and insulin delivery to diabetic patients.

Dynamic behavior of glucose oxidase-containing microparticles of poly(ethylene glycol)-grafted cationic hydrogels in an environment of changing pH.

Poly(diethylaminoethyl-g-ethylene glycol) microparticles were prepared by suspension polymerization of diethylaminoethyl methacrylate, poly(ethylene glycol) monomethacrylate and the crosslinking agent tetra(ethylene glycol) dimethacrylate in silicone oil using redox initiators. Particles of different sizes, crosslinking ratios and graft molecular weights were prepared. The changes in the swelling of the particles were studied as the pH was changed between 3.0 and 7.4. The particles showed rapid swelling/deswelling dynamics in response to changes in pH. It was evident that faster response could be obtained from smaller particles. Changing the crosslinking ratio resulted in changes in the extent of swelling, as well as the speed of response. It was also found that longer graft lengths were responsible for increasing the effect of relaxation of the swelling of the network.

Glucose-sensitivity of glucose oxidase-containing cationic copolymer hydrogels having poly(ethylene glycol) grafts.

Glucose oxidase and catalase were immobilized on poly(diethylaminoethyl methacrylate-g-ethylene glycol) gels by copolymerization of the constituent monomers and the functionalized enzyme solutions. The hydrogels were prepared in the form of discs and microparticles. The amount and the activity of enzymes immobilized in the matrix were determined. The hydrogels were tested for their response to glucose by exposing microparticles to varying concentrations of glucose. The generation of gluconic acid as a result of the reaction of glucose with oxygen was investigated as a function of polymer parameters, such as crosslinking ratio and enzyme loading. Pulsatile variation of the glucose concentration was used to confirm the glucose-dependent swelling properties of these hydrogels.

Projections of the dorsal motor nucleus of the vagus to cardiac ganglia of rat atria: an anterograde tracing study.

We injected the anterograde fluorescent tracer 1,1'-dioleyl-3,3,3',3'-tetramethylindocarbocyanine methanesulfonate (DiI) into the dorsal motor nucleus of the vagus (DmnX), counterstained the cardiac ganglia with Fluorogold (FG), and used confocal microscopy to examine the distributions and different types of DmnX fibers in wholemounts of the atria. We also quantified the number of DmnX cardiac axons and the number of innervated cardiac principal neurons (PNs). Rats with unilateral DiI injections were used in three different experiments, including unilateral FG soaking of cervical vagal trunks, intracranially rhizotomizing the vagal afferent roots, or contralaterally sectioning the cervical vagus. These manipulations indicated that DiI-labeled cardiac fibers were exclusively from the DmnX. Our observations established that: (1) three major ganglionic plexuses were localized in the epicardium; (2) both sides of the DmnX supplied significant fibers to each of the plexuses; (3) these cardiac efferents formed dense basket terminals around individual PNs; (4) collaterals of individual DmnX fibers diverged, producing calyx endings on multiple PNs; (5) small intensely fluorescent (SIF) cells in the cardiac plexuses were innervated pericellularly; (6) individual axons could innervate both PNs and SIF cells; (7) the total number of DmnX fibers were in the range of [68, 96; left] and [67, 115; right]; (8) these fibers innervated 709 (left) and 494 (right), or at least 18% and 12%, of the PNs, respectively; and (9) vagal preganglionics exhibited a degree of lateralization: Significantly more PNs were contacted by fiber varicosities in the sinoatrial plexus than in the atrioventricular plexus after right DmnX injections. In summary, the present observations suggest that the DmnX plays a significant role(s) in controlling the heart.

A model-based algorithm for blood glucose control in type I diabetic patients.

A model-based predictive control algorithm is developed to maintain normoglycemia in the Type I diabetic patient using a closed-loop insulin infusion pump. Utilizing compartmental modeling techniques, a fundamental model of the diabetic patient is constructed. The resulting nineteenth-order nonlinear pharmacokinetic-pharmacodynamic representation is used in controller synthesis. Linear identification of an input-output model from noisy patient data is performed by filtering the impulse-response coefficients via projection onto the Laguerre basis. A linear model predictive controller is developed using the identified step response model. Controller performance for unmeasured disturbance rejection (50 g oral glucose tolerance test) is examined. Glucose setpoint tracking performance is improved by designing a second controller which substitutes a more detailed internal model including state-estimation and a Kalman filter for the input-output representation. The state-estimating controller maintains glucose within 15 mg/dl of the setpoint in the presence of measurement noise. Under noise-free conditions, the model-based predictive controller using state estimation outperforms an internal model controller from literature (49.4% reduction in undershoot and 45.7% reduction in settling time). These results demonstrate the potential use of predictive algorithms for blood glucose control in an insulin infusion pump.

Vagal afferent innervation of the atria of the rat heart reconstructed with confocal microscopy.

We have used confocal microscopy to analyze the vagal afferent innervation of the rat heart. Afferents were labeled by injecting 1,1'-dioleyl-3,3,3',3'-tetramethylindocarbocyanine methanesulfonate (DiI) into the nodose ganglia of animals with prior supranodose de-efferentations, autonomic ganglia were stained with Fluoro-gold, and tissues were examined in whole mounts. Distinctively different fiber specializations were observed in the epi-, myo-, and endocardium: Afferents to the epicardium formed complexes associated with cardiac ganglia. These ganglia consisted of four major ganglionated plexuses, two on each atrium, at junctions of the major vessels with the atria. Ganglionic locations and sizes (left > right) were consistent across animals. In addition to principal neurons (PNs), significant numbers of small intensely fluorescent (SIF) cells were located in each of these plexuses, and vagal afferents provided dense pericellular varicose endings around the SIF cells in each ganglionic plexus, with few if any terminations on PNs. In the myocardium, vagal afferents formed close contacts with cardiac muscles, including conduction fibers. In the endocardium, vagal fibers formed "flower-spray" and "end-net" terminals in connective tissue. With three-dimensional reconstruction of confocal optical sections, a novel polymorphism was seen: Some fibers had one or more collaterals ending as endocardial flower sprays and other collaterals ending as myocardial intramuscular endings. Some unipolar or pseudounipolar neurons within each cardiac ganglionic plexus were retrogradely labeled from the nodose ganglia. In conclusion, vagal afferents form a heterogeneity of differentiated endings in the heart, including structured elements which may mediate chemoreceptor function, stretch reception, and local cardiac reflexes.

A neuro-mimetic dynamic scheduling algorithm for control: analysis and applications.

A simple neuronal network model of the baroreceptor reflex is analyzed. From a control perspective, the analysis suggests a dynamic scheduled control mechanisms by which the baroreflex may perform regulation of the blood pressure. The main objectives of this work are to investigate the static and dynamic response characteristics of the single neurons and the network, to analyze the neuromimetic dynamic scheduled control function of the model, and to apply the algorithm to nonlinear process control problems. The dynamic scheduling activity of the network is exploited in two control architectures. Control structure I is drawn directly from the present model of the baroreceptor reflex. An application of this structure for level control in a conical tank is described. Control structure II employs an explicit set point to determine the feedback error. The performance of this control structure is illustrated on a nonlinear continuous stirred tank reactor with van de Vusse kinetics. The two case studies validate the dynamic scheduled control approach for nonlinear process control applications.

A laser confocal microscopic study of vagal afferent innervation of rat aortic arch: chemoreceptors as well as baroreceptors.

Although the aortic nerves contain vagal afferents that terminate in both the wall of the aortic arch (putative baroreceptors) and its associated glomus tissue (putative chemoreceptors) in most mammalian species, the aortic nerves of the rat have been widely assumed to contain only baro- or pressor afferents. The present study reconsidered this anomaly by characterizing vagal afferent endings and their targets in the aortic arch region of the rat, both qualitatively and quantitatively. Eight Sprague-Dawley rats received intracranial vagal motor rhizotomy unilaterally to eliminate efferents in the nerve and then, two weeks later, injections of the tracer DiI (1,1'-dioleyl-3,3,3',3'-tetramethylindocarbocyanine methanesulfonate) into the ipsilateral nodose ganglion. The aortic arch and its surrounding tissue, with the common carotid and subclavian arteries attached, were examined with both conventional epifluorescence and confocal microscopes. Consistent with earlier observations, vagal afferents formed both flower-spray and end-net terminals rather diffusely within the wall of the aortic arch. More interestingly, vagal afferents also innervated glomus or SIF (i.e., small intensely fluorescent) cell bodies at the junction areas of the common carotid and subclavian arteries. To identify the course of these fibers, six additional animals received DiI injection into the nodose unilaterally after a complete cervical vagotomy caudal to the nodose; in these animals, the aortic nerve had been separated from the vagal trunk and kept intact. There were no marked differences in innervation patterns between the nonvagotomized and the cervically vagotomized animals, indicating that the vagal axons innervating the walls of the blood vessels and the SIF cells in the aortic arch region travel through the aortic nerves. Using a stereological method, we estimated the relative number of chemo- and baroreceptor afferents innervating the aortic arch. About 16.4% (left) and 13.1% (right) of fibers in the aortic nerves innervate SIF cells. These findings challenge the general consensus that the aortic nerves of rats contain exclusively baroreceptor fibers.