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.

Evaluating minimal important differences for the FACT-Melanoma quality of life questionnaire

Objectives. Minimal Important Differences (MIDs) establish benchmarks for interpreting mean differences in clinical trials involving quality of life outcomes and inform discussions of clinically meaningful change in patient status. As such, the purpose of this study was to assess MIDs for the Functional Assessment of Cancer Therapy–Melanoma (FACT-M). ^ Methods. A prospective validation study of the FACT-M was performed with 273 patients with stage I to IV melanoma. FACT-M, Karnofsky Performance Status (KPS), and Eastern Cooperative Oncology Group Performance Status (ECOG-PS) scores were obtained at baseline and 3 months following enrollment. Anchor- and distribution-based methods were used to assess MIDs, and the correspondence between MID ranges derived from each method was evaluated. ^ Results. This study indicates that an approximate range for MIDs of the FACT-M subscales is between 5 to 8 points for the Trial Outcome Index, 4 to 5 points for the Melanoma Combined Subscale, 2 to 4 points for the Melanoma Subscale, and 1 to 2 points for the Melanoma Surgery Subscale. Each method produced similar but not identical ranges of MIDs. ^ Conclusions. The properties of the anchor instrument employed to derive MIDs directly affect resulting MID ranges and point values. When MIDs are offered as supportive evidence of a clinically meaningful change, the anchor instrument used to derive thresholds should be clearly stated along with evidence supporting the choice of anchor instrument as the most appropriate for the domain of interest. In this analysis, the KPS was a more appropriate measure than the ECOG-PS for assessing MIDs. ^

Supplemental Nutrition Assistance Program: A policy analysis of restricting foods with minimal nutritional value

In 2011, expenditures for the Supplemental Nutrition Assistance Program (SNAP) reached an all-time high of $72 billion. The goal of SNAP is " to alleviate hunger and malnutrition…by increasing food purchasing power for all eligible households who apply for participation." It has been well established that proper nutrition is essential to good health, making SNAP an important program to public health consumers. Thus, this analysis examined whether SNAP is meeting its stated goal and whether the goal would be reduced if the purchase of foods of minimal nutritional value (FMNV) were restricted. ^ A review of existing literature found that SNAP has been shown to alleviate hunger, but the studies on the nutritional impact of the program were not sufficient to assert whether change is needed. When considering whether limiting FMNV would reduce or improve the effectiveness of SNAP at alleviating hunger and malnutrition, there is very little information on which to base a policy change, particular one that singles out a low income group to restrict purchases. ^ Several states have attempted to restrict the purchase of FMNV but, to date, no such change has been implemented or tested. Conducting pilot studies on the restriction of FMNV, along with better data collection on SNAP purchases, would guide policy changes to the program. Although there are many potential public health benefits to restricting FMNV purchase using SNAP dollars, research is needed to quantify the cost impact of these benefits.^

BIOMEDICAL LANGUAGE UNDERSTANDING AND EXTRACTION (BLUE-TEXT): A MINIMAL SYNTACTIC, SEMANTIC METHOD

Clinical text understanding (CTU) is of interest to health informatics because critical clinical information frequently represented as unconstrained text in electronic health records are extensively used by human experts to guide clinical practice, decision making, and to document delivery of care, but are largely unusable by information systems for queries and computations. Recent initiatives advocating for translational research call for generation of technologies that can integrate structured clinical data with unstructured data, provide a unified interface to all data, and contextualize clinical information for reuse in multidisciplinary and collaborative environment envisioned by CTSA program. This implies that technologies for the processing and interpretation of clinical text should be evaluated not only in terms of their validity and reliability in their intended environment, but also in light of their interoperability, and ability to support information integration and contextualization in a distributed and dynamic environment. This vision adds a new layer of information representation requirements that needs to be accounted for when conceptualizing implementation or acquisition of clinical text processing tools and technologies for multidisciplinary research. On the other hand, electronic health records frequently contain unconstrained clinical text with high variability in use of terms and documentation practices, and without commitmentto grammatical or syntactic structure of the language (e.g. Triage notes, physician and nurse notes, chief complaints, etc). This hinders performance of natural language processing technologies which typically rely heavily on the syntax of language and grammatical structure of the text. This document introduces our method to transform unconstrained clinical text found in electronic health information systems to a formal (computationally understandable) representation that is suitable for querying, integration, contextualization and reuse, and is resilient to the grammatical and syntactic irregularities of the clinical text. We present our design rationale, method, and results of evaluation in processing chief complaints and triage notes from 8 different emergency departments in Houston Texas. At the end, we will discuss significance of our contribution in enabling use of clinical text in a practical bio-surveillance setting.

Minimal DNA sequences that control the cell lineage-specific expression of the pro$\alpha$2(I) collagen promoter in transgenic mice

The pattern of expression of the pro$\alpha$2(I) collagen gene is highly tissue-specific in adult mice and shows its strongest expression in bones, tendons, and skin. Transgenic mice were generated harboring promoter fragments of the mouse pro$\alpha$2(I) collagen gene linked to the Escherichia coli $\beta$-galactosidase or firefly luciferase genes to examine the activity of these promoters during development. A region of the mouse pro$\alpha$2(I) collagen promoter between $-$2000 and +54 exhibited a pattern of $\beta$-galactosidase activity during embryonic development that corresponded to the expression pattern of the endogenous pro$\alpha$2(I) collagen gene as determined by in situ hybridization. A similar pattern of activity was also observed with much smaller promoter fragments containing either 500 or 350 bp of upstream sequence relative to the start of transcription. Embryonic regions expressing high levels of $\beta$-galactosidase activity included the valves of the developing heart, sclerotomes, meninges, limb buds, connective tissue fascia between muscle fibers, osteoblasts, tendon, periosteum, dermis, and peritoneal membranes. The pattern of $\beta$-galactosidase activity was similar to the extracellular immunohistochemical localization of transforming growth factor-$\beta$1 (TGF-$\beta$1). The $-$315 to $-$284 region of the pro$\alpha$2(I) collagen promoter was previously shown to mediate the stimulatory effects of TGF-$\beta$1 on the pro$\alpha$2(I) collagen promoter in DNA transfection experiments with cultured fibroblasts. A construct containing this sequence tandemly repeated 5$\sp\prime$ to both a very short $\alpha$2(I) collagen promoter ($-$40 to +54) and a heterologous minimal promoter showed preferential activity in tail and skin of 4-week old transgenic mice. The pattern of expression mimics that of the $-$350 to +54 pro$\alpha$2(I) collagen promoter linked to a luciferase reporter gene in transgenic mice. ^