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.

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.

DISCHARGE PLANNING: A PROCESS MODEL

As the requirements for health care hospitalization have become more demanding, so has the discharge planning process become a more important part of the health services system. A thorough understanding of hospital discharge planning can, then, contribute to our understanding of the health services system. This study involved the development of a process model of discharge planning from hospitals. Model building involved the identification of factors used by discharge planners to develop aftercare plans, and the specification of the roles of these factors in the development of the discharge plan. The factors in the model were concatenated in 16 discrete decision sequences, each of which produced an aftercare plan.^ The sample for this study comprised 407 inpatients admitted to the M. D. Anderson Hospital and Tumor Institution at Houston, Texas, who were discharged to any site within Texas during a 15 day period. Allogeneic bone marrow donors were excluded from the sample. The factors considered in the development of discharge plans were recorded by discharge planners and were used to develop the model. Data analysis consisted of sorting the discharge plans using the plan development factors until for some combination and sequence of factors all patients were discharged to a single site. The arrangement of factors that led to that aftercare plan became a decision sequence in the model.^ The model constructs the same discharge plans as those developed by hospital staff for every patient in the study. Tests of the validity of the model should be extended to other patients at the MDAH, to other cancer hospitals, and to other inpatient services. Revisions of the model based on these tests should be of value in the management of discharge planning services and in the design and development of comprehensive community health services.^

Mixture modeling for joint analysis of survival, discrete, and continuous data

Mixture modeling is commonly used to model categorical latent variables that represent subpopulations in which population membership is unknown but can be inferred from the data. In relatively recent years, the potential of finite mixture models has been applied in time-to-event data. However, the commonly used survival mixture model assumes that the effects of the covariates involved in failure times differ across latent classes, but the covariate distribution is homogeneous. The aim of this dissertation is to develop a method to examine time-to-event data in the presence of unobserved heterogeneity under a framework of mixture modeling. A joint model is developed to incorporate the latent survival trajectory along with the observed information for the joint analysis of a time-to-event variable, its discrete and continuous covariates, and a latent class variable. It is assumed that the effects of covariates on survival times and the distribution of covariates vary across different latent classes. The unobservable survival trajectories are identified through estimating the probability that a subject belongs to a particular class based on observed information. We applied this method to a Hodgkin lymphoma study with long-term follow-up and observed four distinct latent classes in terms of long-term survival and distributions of prognostic factors. Our results from simulation studies and from the Hodgkin lymphoma study demonstrated the superiority of our joint model compared with the conventional survival model. This flexible inference method provides more accurate estimation and accommodates unobservable heterogeneity among individuals while taking involved interactions between covariates into consideration.^

Characterization of the MLC box: A conserved {\it cis\/}-acting DNA element present in the chicken MLC1s/1c gene

The slow/cardiac alkali myosin light chain (MLC1s/1c) is a member of a multigene family whose protein products are essential for activation of the myosin ATPase. In the adult, the MLC1s/1c isoform is expressed in both cardiac and slow-twitch skeletal muscles, while it is expressed by all skeletal muscles during development.^ To elucidate the molecular mechanisms that underlie the transcriptional regulation of MLC1s/1c gene expression, the immediate 5$\sp\prime$ flanking region of the gene was isolated and shown to be capable of directing reporter gene expression. Analysis of this region revealed a 110 bp muscle-specific enhancer that includes a myocyte-specific enhancer-binding factor 2 (MEF-2) site, E-boxes, which are potential binding sites for the basic-helix-loop-helix proteins such as MyoD, and a MLC box. The focus of the thesis was to identify the role of the MLC box in expression of the MLC1s/1c gene.^ The MLC box is a member of the family of CArG box containing cis-acting DNA elements. Mutagenesis showed that the MLC box is necessary, but not sufficient, for the expression of a reporter gene linked to the 5$\sp\prime$ flanking region of the MLC1s/1c gene. Linker scanner and site-directed mutagenesis identified a number of potential sites within the 110 bp muscle-specific enhancer that may cooperate with the MLC box. These are the MEF-2 site, the E-box site, and a 10 bp element located upstream of the MEF-2 site that does not have sequence similarity with any known cis-acting element. The MLC box is capable of binding to factors present in muscle nuclear extracts, as well as to human recombinant serum response factor (SRF). Binding of SRF to the MLC box was correlated with the ability of the 5$\sp\prime$ flanking region of the MLC1s/1c gene to drive reporter gene expression. Results suggest a model in which binding of SRF to the MLC box activates expression of the MLC1s/1c gene while binding of the factors present in the nuclear extracts suppresses the expression of the gene. (Abstract shortened with permission of author.) ^

A distinct element involved in the lipopolysaccharide activation of the tumor necrosis factor -alpha promoter in a promonocytic cell line, THP-1

TNF-α is a pleiotropic cytokine involved in normal homeostasis and plays a key role in defending the host from infection and malignancy. However when deregulated, TNF-α can lead to various disease states. Therefore, understanding the mechanisms by which TNF-α is regulated may aid in its control. In spite of the knowledge gained regarding the transcriptional regulation of TNF-α further characterization of specific TNF-α promoter elements remains to be elucidated. In particular, the T&barbelow;NF-α A&barbelow;P-1/C&barbelow;RE-like (TAC) element of the TNF-α promoter has been shown to be important in the regulation of TNF-α in lymphocytes. Activating transcription factor-2 (ATF-2) and c-Jun were shown to bind to and transactivate the TAC element However, the role of TAC and transcription factors ATF-2 and c-Jun in the regulation of TNF-α in monocytes is not as well characterized. Lipopolysaccharide (LPS), a potent activator of TNF-α in monocytes, provides a good model to study the involvement of TAC in TNF-α regulation. On the other hand, all-tram retinoic acid (ATRA), a physiological monocyte-differentiation agent, is unable to induce TNF-α protein release. ^ To delineate the functional role of TAC, we transfected the wildtype or the TAC deleted TNF-α promoter-CAT construct into THP-1 promonocytic cells before stimulating them with LPS. CAT activity was induced 17-fold with the wildtype TNF-α promoter, whereas the CAT activity was uninducible when the TAC deletion mutant was used. This daft suggests that TAC is vital for LPS to activate the TNF-α promoter. Electrophoretic mobility shift assays using the TAC element as a probe showed a unique pattern for LPS-activated cells: the disappearance of the upper band of a doublet seen in untreated and ATRA treated cells. Supershift analysis identified c-Jun and ATF-2 as components of the LPS-stimulated binding complex. Transient transfection studies using dominant negative mutants of JNK, c-Jun, or ATF-2 suggest that these proteins we important for LPS to activate the TNF-α promoter. Furthermore, an increase in phosphorylated or activated c-Jun was bound to the TAC element in LPS-stimulated cells. Increased c-Jun activation was correlated with increased activity of Jun N-terminal kinase (JNK), a known upstream stimulator of c-Jun and ATF-2, in LPS-stimulated monocytes. On the other hand, ATRA did not induce TNF-α protein release nor changes in the phosphorylation of c-Jun or JNK activity, suggesting that pathways leading to ATRA differentiation of monocytic cells are independent of TNF-α activation. Together, the induction of TNF-α gene expression seems to require JNK activation, and activated c-Jun binding to the TAC element of the TNF-α promoter in THP-1 promonocytic cells. ^