Dynamics of a minimal model of interlocked positive and negative feedback loops of transcriptional regulation by cAMP-response element binding proteins.

cAMP-response element binding (CREB) proteins are involved in transcriptional regulation in a number of cellular processes (e.g., neural plasticity and circadian rhythms). The CREB family contains activators and repressors that may interact through positive and negative feedback loops. These loops can be generated by auto- and cross-regulation of expression of CREB proteins, via CRE elements in or near their genes. Experiments suggest that such feedback loops may operate in several systems (e.g., Aplysia and rat). To understand the functional implications of such feedback loops, which are interlocked via cross-regulation of transcription, a minimal model with a positive and negative loop was developed and investigated using bifurcation analysis. Bifurcation analysis revealed diverse nonlinear dynamics (e.g., bistability and oscillations). The stability of steady states or oscillations could be changed by time delays in the synthesis of the activator (CREB1) or the repressor (CREB2). Investigation of stochastic fluctuations due to small numbers of molecules of CREB1 and CREB2 revealed a bimodal distribution of CREB molecules in the bistability region. The robustness of the stable HIGH and LOW states of CREB expression to stochastic noise differs, and a critical number of molecules was required to sustain the HIGH state for days or longer. Increasing positive feedback or decreasing negative feedback also increased the lifetime of the HIGH state, and persistence of this state may correlate with long-term memory formation. A critical number of molecules was also required to sustain robust oscillations of CREB expression. If a steady state was near a deterministic Hopf bifurcation point, stochastic resonance could induce oscillations. This comparative analysis of deterministic and stochastic dynamics not only provides insights into the possible dynamics of CREB regulatory motifs, but also demonstrates a framework for understanding other regulatory processes with similar network architecture.

Differential dynamic properties of scleroderma fibroblasts in response to perturbation of environmental stimuli.

Diseases are believed to arise from dysregulation of biological systems (pathways) perturbed by environmental triggers. Biological systems as a whole are not just the sum of their components, rather ever-changing, complex and dynamic systems over time in response to internal and external perturbation. In the past, biologists have mainly focused on studying either functions of isolated genes or steady-states of small biological pathways. However, it is systems dynamics that play an essential role in giving rise to cellular function/dysfunction which cause diseases, such as growth, differentiation, division and apoptosis. Biological phenomena of the entire organism are not only determined by steady-state characteristics of the biological systems, but also by intrinsic dynamic properties of biological systems, including stability, transient-response, and controllability, which determine how the systems maintain their functions and performance under a broad range of random internal and external perturbations. As a proof of principle, we examine signal transduction pathways and genetic regulatory pathways as biological systems. We employ widely used state-space equations in systems science to model biological systems, and use expectation-maximization (EM) algorithms and Kalman filter to estimate the parameters in the models. We apply the developed state-space models to human fibroblasts obtained from the autoimmune fibrosing disease, scleroderma, and then perform dynamic analysis of partial TGF-beta pathway in both normal and scleroderma fibroblasts stimulated by silica. We find that TGF-beta pathway under perturbation of silica shows significant differences in dynamic properties between normal and scleroderma fibroblasts. Our findings may open a new avenue in exploring the functions of cells and mechanism operative in disease development.

Extended kalman filter for estimation of parameters in nonlinear state-space models of biochemical networks.

It is system dynamics that determines the function of cells, tissues and organisms. To develop mathematical models and estimate their parameters are an essential issue for studying dynamic behaviors of biological systems which include metabolic networks, genetic regulatory networks and signal transduction pathways, under perturbation of external stimuli. In general, biological dynamic systems are partially observed. Therefore, a natural way to model dynamic biological systems is to employ nonlinear state-space equations. Although statistical methods for parameter estimation of linear models in biological dynamic systems have been developed intensively in the recent years, the estimation of both states and parameters of nonlinear dynamic systems remains a challenging task. In this report, we apply extended Kalman Filter (EKF) to the estimation of both states and parameters of nonlinear state-space models. To evaluate the performance of the EKF for parameter estimation, we apply the EKF to a simulation dataset and two real datasets: JAK-STAT signal transduction pathway and Ras/Raf/MEK/ERK signaling transduction pathways datasets. The preliminary results show that EKF can accurately estimate the parameters and predict states in nonlinear state-space equations for modeling dynamic biochemical networks.

Active water in protein-protein communication within the membrane: the case of SRII-HtrII signal relay.

We detect internal water molecules in a membrane-embedded receptor-transducer complex and demonstrate water structure changes during formation of the signaling state. Time-resolved FTIR spectroscopy reveals stimulus-induced repositioning of one or more structurally active water molecules to a significantly more hydrophobic environment in the signaling state of the sensory rhodopsin II (SRII)-transducer (HtrII) complex. These waters, distinct from bound water molecules within the SRII receptor, appear to be in the middle of the transmembrane interface region near the Tyr199(SRII)-Asn74(HtrII) hydrogen bond. We conclude that water potentially plays an important role in the SRII --> HtrII signal transfer mechanism in the membrane's hydrophobic core.

Differential dynamic properties of scleroderma fibroblasts in response to perturbation of environmental stimuli.

Diseases are believed to arise from dysregulation of biological systems (pathways) perturbed by environmental triggers. Biological systems as a whole are not just the sum of their components, rather ever-changing, complex and dynamic systems over time in response to internal and external perturbation. In the past, biologists have mainly focused on studying either functions of isolated genes or steady-states of small biological pathways. However, it is systems dynamics that play an essential role in giving rise to cellular function/dysfunction which cause diseases, such as growth, differentiation, division and apoptosis. Biological phenomena of the entire organism are not only determined by steady-state characteristics of the biological systems, but also by intrinsic dynamic properties of biological systems, including stability, transient-response, and controllability, which determine how the systems maintain their functions and performance under a broad range of random internal and external perturbations. As a proof of principle, we examine signal transduction pathways and genetic regulatory pathways as biological systems. We employ widely used state-space equations in systems science to model biological systems, and use expectation-maximization (EM) algorithms and Kalman filter to estimate the parameters in the models. We apply the developed state-space models to human fibroblasts obtained from the autoimmune fibrosing disease, scleroderma, and then perform dynamic analysis of partial TGF-beta pathway in both normal and scleroderma fibroblasts stimulated by silica. We find that TGF-beta pathway under perturbation of silica shows significant differences in dynamic properties between normal and scleroderma fibroblasts. Our findings may open a new avenue in exploring the functions of cells and mechanism operative in disease development.

Dynamics of a minimal model of interlocked positive and negative feedback loops of transcriptional regulation by cAMP-response element binding proteins.

cAMP-response element binding (CREB) proteins are involved in transcriptional regulation in a number of cellular processes (e.g., neural plasticity and circadian rhythms). The CREB family contains activators and repressors that may interact through positive and negative feedback loops. These loops can be generated by auto- and cross-regulation of expression of CREB proteins, via CRE elements in or near their genes. Experiments suggest that such feedback loops may operate in several systems (e.g., Aplysia and rat). To understand the functional implications of such feedback loops, which are interlocked via cross-regulation of transcription, a minimal model with a positive and negative loop was developed and investigated using bifurcation analysis. Bifurcation analysis revealed diverse nonlinear dynamics (e.g., bistability and oscillations). The stability of steady states or oscillations could be changed by time delays in the synthesis of the activator (CREB1) or the repressor (CREB2). Investigation of stochastic fluctuations due to small numbers of molecules of CREB1 and CREB2 revealed a bimodal distribution of CREB molecules in the bistability region. The robustness of the stable HIGH and LOW states of CREB expression to stochastic noise differs, and a critical number of molecules was required to sustain the HIGH state for days or longer. Increasing positive feedback or decreasing negative feedback also increased the lifetime of the HIGH state, and persistence of this state may correlate with long-term memory formation. A critical number of molecules was also required to sustain robust oscillations of CREB expression. If a steady state was near a deterministic Hopf bifurcation point, stochastic resonance could induce oscillations. This comparative analysis of deterministic and stochastic dynamics not only provides insights into the possible dynamics of CREB regulatory motifs, but also demonstrates a framework for understanding other regulatory processes with similar network architecture.

Temporal analysis of PI-3kinase and MAPK signal transduction during skeletal muscle overload

Skeletal muscles can adapt to increased mechanical forces (or loading) by increasing the size and strength of the muscle. Knowledge of the molecular mechanisms by which muscle responds to increased loading may lead to the discovery of novel treatment strategies for muscle wasting and frailty. The objective of this research was to examine the temporal associations between the activation of specific signaling pathway intermediates and their potential upstream regulator(s) in response to increased muscle loading. Previous work has demonstrated that focal adhesion kinase (FAK) activity is increased in overloaded hypertrophying skeletal muscle. Thus FAK is a candidate for transducing the loading stimulus in skeletal muscle, potentially by activating phosphatidylinositol 3-kinase (PI3K) and members of the mitogen-activated protein kinase (MAPK) family. However, it was unknown if muscle overload would result in activation of PI3K or the MAPKs. Thus, this work seeks to characterized the temporal response of (1) MAPK phosphorylation (including Erk 2, p38 MAPK and JNK), (2) PI3K activity, and (3) FAK tyrosine phosphorylation in response to 24 hours of compensatory overload in the rat soleus and plantaris muscles. In both muscles, overload resulted in transient Increases in the phosphorylation state of Erk2 and JNK, which peaked within the first hour of overload and returned to baseline thereafter. In contrast, p38 MAPK phosphorylation remained elevated throughout the entire 24-hour overload period. Moreover, overload increased PI3K activity only, in the plantaris and only at 12 hours. Moreover, 24 hours of overload induced a significant increase in total protein content in the plantaris but not the soleus. Thus an increase in total muscle protein content within the 24-hour loading period was observed only in muscle exhibiting increased PI3K activity. Surprisingly, FAK tyrosine phosphorylation was not increased during the overload period in either muscle, indicating that PI3K activation and increased MAPK phosphorylation were independent of increased FAK tyrosine phosphorylation. In summary, increased PI3K activity and sustained elevation of p38 MAPK phosphorylation were associated with muscle overload, identifying these pathways as potential mediators of the early hypertrophic response to skeletal muscle overload. This suggests that stimuli or mechanisms that activate these pathways may reduce/minimize muscle wasting and frailty. ^

Blood-oxygen-level-dependent (BOLD) signal changes in total cortex and subcortex, pain, reward, and vigilance regions during mechanical pressure pain after morphine administration

Morphine is the most common clinical choice in the management of severe pain. Although the molecular mechanisms of morphine have already been characterized, the cerebral circuits by which it attenuates the sensation of pain have not yet been studied in humans. The objective of this two-arm (morphine versus placebo), between-subjects study was to examine whether morphine affects pain via pain-related cortical circuits, but also via reward regions that relate to the motivational state, as well as prefrontal regions that relate to vigilance as a result of morphine's sedative effects. Cortical activity was measured by the blood-oxygen-level-dependent (BOLD) signal changes using functional magnetic resonance imaging (fMRI). ^ The novelty of this study is at three levels: (i) to develop a methodology that will assess the average BOLD signal across subjects for the pain, reward, and vigilance cortical systems; (ii) to examine whether the reward and/or sedative effects of morphine are contributing factors to cortical regions associated with the motivational state and vigilance; and (iii) to propose a neuroanatomical model related to the opioid-sensitive effects of reward and sedation as a function of cortical activity related to pain in an effort to assess future analgesics. ^ Consistent with our hypotheses, our findings showed that the decrease in total pain-related volume activated between the post- and the pre-treatment morphine group was about 78%, while the post-treatment placebo group displayed only a 5% decrease when compared to pre-treatment levels of activation. The volume increase in reward regions was 451% in the post-treatment compared to the pre-treatment morphine condition. Finally, the volumetric decrease in vigilance regions was 63% in the posttreatment compared to the pre-treatment morphine condition. ^ These findings imply that changes in the blood flow of the reward and vigilance regions may be contributing factors in producing the analgesic effect under morphine administration. Future studies need to replicate this study in a higher resolution fMRI environment and to assess the proposed neuroanatomical model in patient populations. The necessity of pain research is apparent, since pain cuts across different diseases especially chronic ones, and thus, is recognized as a vital public health developing area. ^

Molecular interactions and signal transfer between sensory rhodopsin-I and its cognate transducer

SRI is unique among known photoreceptors in that it produces opposite signals depending on the color of light stimuli. Absorption of orange light (587 nm) triggers an attractant response by the cell, whereas absorption of orange light followed by near-UV light (373 run) triggers a repellent response. Using behavioral mutants that exhibit aberrant color-sensing ability, we tested a two-conformation equilibrium model, using FRET and EPR spectroscopy. The essence of the model applied to SRI-HtrI is that the complex exists in a metastable two-conformer equilibrium which is shifted in one direction by orange light absorption (producing an attractant signal) and in the opposite direction by a second UV-violet photon (producing a repellent signal). First, by FRET we found that the E-F cytoplasmic loop of SRI moves toward the RAMP domain of the HtrI transducer during the formation of the orange-light activated signaling state of the complex. This is the first localization of a change in the physical relationship between the receptor and transducer subunits of the complex and provides a structural property of the two proposed conformers that we can monitor. Second, EPR spectra of a spin label probe at this cytoplasmic position showed shifts in the dark in the mutants toward shorter or longer EF loop-RAMP distances, explaining their behavior in terms of their mutations causing pre-stimulus shifts into one or the other conformer. ^ Next, we applied a novel electrophysiological method for monitoring the directionality of proton movement during photoactivation of SRI, to investigate the process of proton transfer in the photoactive site from the chromophore to proton acceptors on both the wildtype and aberrant color-response mutants. We observed an unexpected and critical difference in the two signaling conformations of the SRI-HtrI complex. The finding is that the vectoriality (i.e. movement away or toward the cytoplasm) of the light-induced proton transfer from the chromophore to the protein is opposite in formation of the two conformations. Retinylidene proton transfer is a common critical process in rhodopsins and these results are the first to show differences in vectoriality in a rhodopsin receptor, and to demonstrate functional importance of the direction of proton transfer. ^

Using small area estimation and geographic information systems technology to target health services for the uninsured

The three articles that comprise this dissertation describe how small area estimation and geographic information systems (GIS) technologies can be integrated to provide useful information about the number of uninsured and where they are located. Comprehensive data about the numbers and characteristics of the uninsured are typically only available from surveys. Utilization and administrative data are poor proxies from which to develop this information. Those who cannot access services are unlikely to be fully captured, either by health care provider utilization data or by state and local administrative data. In the absence of direct measures, a well-developed estimation of the local uninsured count or rate can prove valuable when assessing the unmet health service needs of this population. However, the fact that these are “estimates” increases the chances that results will be rejected or, at best, treated with suspicion. The visual impact and spatial analysis capabilities afforded by geographic information systems (GIS) technology can strengthen the likelihood of acceptance of area estimates by those most likely to benefit from the information, including health planners and policy makers. ^ The first article describes how uninsured estimates are currently being performed in the Houston metropolitan region. It details the synthetic model used to calculate numbers and percentages of uninsured, and how the resulting estimates are integrated into a GIS. The second article compares the estimation method of the first article with one currently used by the Texas State Data Center to estimate numbers of uninsured for all Texas counties. Estimates are developed for census tracts in Harris County, using both models with the same data sets. The results are statistically compared. The third article describes a new, revised synthetic method that is being tested to provide uninsured estimates at sub-county levels for eight counties in the Houston metropolitan area. It is being designed to replicate the same categorical results provided by a current U.S. Census Bureau estimation method. The estimates calculated by this revised model are compared to the most recent U.S. Census Bureau estimates, using the same areas and population categories. ^

HPV vaccine coverage in Texas counties: An application of multilevel, small area estimation

Health departments, research institutions, policy-makers, and healthcare providers are often interested in knowing the health status of their clients/constituents. Without the resources, financially or administratively, to go out into the community and conduct health assessments directly, these entities frequently rely on data from population-based surveys to supply the information they need. Unfortunately, these surveys are ill-equipped for the job due to sample size and privacy concerns. Small area estimation (SAE) techniques have excellent potential in such circumstances, but have been underutilized in public health due to lack of awareness and confidence in applying its methods. The goal of this research is to make model-based SAE accessible to a broad readership using clear, example-based learning. Specifically, we applied the principles of multilevel, unit-level SAE to describe the geographic distribution of HPV vaccine coverage among females aged 11-26 in Texas.^ Multilevel (3 level: individual, county, public health region) random-intercept logit models of HPV vaccination (receipt of ≥ 1 dose Gardasil® ) were fit to data from the 2008 Behavioral Risk Factor Surveillance System (outcome and level 1 covariates) and a number of secondary sources (group-level covariates). Sampling weights were scaled (level 1) or constructed (levels 2 & 3), and incorporated at every level. Using the regression coefficients (and standard errors) from the final models, I simulated 10,000 datasets for each regression coefficient from the normal distribution and applied them to the logit model to estimate HPV vaccine coverage in each county and respective demographic subgroup. For simplicity, I only provide coverage estimates (and 95% confidence intervals) for counties.^ County-level coverage among females aged 11-17 varied from 6.8-29.0%. For females aged 18-26, coverage varied from 1.9%-23.8%. Aggregated to the state level, these values translate to indirect state estimates of 15.5% and 11.4%, respectively; both of which fall within the confidence intervals for the direct estimates of HPV vaccine coverage in Texas (Females 11-17: 17.7%, 95% CI: 13.6, 21.9; Females 18-26: 12.0%, 95% CI: 6.2, 17.7).^ Small area estimation has great potential for informing policy, program development and evaluation, and the provision of health services. Harnessing the flexibility of multilevel, unit-level SAE to estimate HPV vaccine coverage among females aged 11-26 in Texas counties, I have provided (1) practical guidance on how to conceptualize and conduct modelbased SAE, (2) a robust framework that can be applied to other health outcomes or geographic levels of aggregation, and (3) HPV vaccine coverage data that may inform the development of health education programs, the provision of health services, the planning of additional research studies, and the creation of local health policies.^

Design, Calibration, and Evaluation of Depth-of-Interaction-Capable PET Detector Modules

High-resolution, small-bore PET systems suffer from a tradeoff between system sensitivity, and image quality degradation. In these systems long crystals allow mispositioning of the line of response due to parallax error and this mispositioning causes resolution blurring, but long crystals are necessary for high system sensitivity. One means to allow long crystals without introducing parallax errors is to determine the depth of interaction (DOI) of the gamma ray interaction within the detector module. While DOI has been investigated previously, newly available solid state photomultipliers (SSPMs) well-suited to PET applications and allow new modules for investigation. Depth of interaction in full modules is a relatively new field, and so even if high performance DOI capable modules were available, the appropriate means to characterize and calibrate the modules are not. This work presents an investigation of DOI capable arrays and techniques for characterizing and calibrating those modules. The methods introduced here accurately and reliably characterize and calibrate energy, timing, and event interaction positioning. Additionally presented is a characterization of the spatial resolution of DOI capable modules and a measurement of DOI effects for different angles between detector modules. These arrays have been built into a prototype PET system that delivers better than 2.0 mm resolution with a single-sided-stopping-power in excess of 95% for 511 keV g's. The noise properties of SSPMs scale with the active area of the detector face, and so the best signal-to-noise ratio is possible with parallel readout of each SSPM photodetector pixel rather than multiplexing signals together. This work additionally investigates several algorithms for improving timing performance using timing information from multiple SSPM pixels when light is distributed among several photodetectors.

Associations between ambient levels of combustion pollutants and small for gestational age infants in Texas

There is scant evidence regarding the associations between ambient levels of combustion pollutants and small for gestational age (SGA) infants. No studies of this type have been completed in the Southern United States. The main objective of the project presented was to determine associations between combustion pollutants and SGA infants in Texas using three different exposure assessments. ^ Birth certificate data that contained information on maternal and infant characteristics were obtained from the Texas Department of State Health Services (TX DSHS). Exposure assessment data for the three aims came from: (1) U.S. Environmental Protection Agency (EPA) National Air Toxics Assessment (NATA), (2) U.S. EPA Air Quality System (AQS), and (3) TX Department of Transportation (DOT), respectively. Multiple logistic regression models were used to determine the associations between combustion pollutants and SGA. ^ For the first study looked at annual estimates of four air toxics at the census tract level in the Greater Houston Area. After controlling for maternal race, maternal education, tobacco use, maternal age, number of prenatal visits, marital status, maternal weight gain, and median census tract income level, adjusted ORs and 95% confidence intervals (CI) for exposure to PAHs (per 10 ng/m3), naphthalene (per 10 ng/m3), benzene (per 1 µg/m3), and diesel engine emissions (per 10 µg/m3) were 1.01 (0.97–1.05), 1.00 (0.99–1.01), 1.01 (0.97–1.05), and 1.08 (0.95–1.23) respectively. For the second study looking at Hispanics in El Paso County, AORs and 95% confidence intervals (CI) for increases of 5 ng/m3 for the sum of carcinogenic PAHs (Σ c-PAHs), 1 ng/m3 of benzo[a]pyrene, and 100 ng/m3 in naphthalene during the third trimester of pregnancy were 1.02 (0.97–1.07), 1.03 (0.96–1.11), and 1.01 (0.97–1.06), respectively. For the third study using maternal proximity to major roadways as the exposure metric, there was a negative association with increasing distance from a maternal residence to the nearest major roadway (Odds Ratio (OR) = 0.96; 95% CI = 0.94–0.97) per 1000 m); however, once adjusted for covariates this effect was no longer significant (AOR = 0.98; 95% CI = 0.96–1.00). There was no association with distance weighted traffic density (DWTD). ^ This project is the first to look at SGA and combustion pollutants in the Southern United States with three different exposure metrics. Although there was no evidence of associations found between SGA and the air pollutants mentioned in these studies, the results contribute to the body of literature assessing maternal exposure to ambient air pollution and adverse birth outcomes. ^