13 resultados para Minimal-complexity classifier

em DigitalCommons@The Texas Medical Center


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Purpose: Respiratory motion causes substantial uncertainty in radiotherapy treatment planning. Four-dimensional computed tomography (4D-CT) is a useful tool to image tumor motion during normal respiration. Treatment margins can be reduced by targeting the motion path of the tumor. The expense and complexity of 4D-CT, however, may be cost-prohibitive at some facilities. We developed an image processing technique to produce images from cine CT that contain significant motion information without 4D-CT. The purpose of this work was to compare cine CT and 4D-CT for the purposes of target delineation and dose calculation, and to explore the role of PET in target delineation of lung cancer. Methods: To determine whether cine CT could substitute 4D-CT for small mobile lung tumors, we compared target volumes delineated by a physician on cine CT and 4D-CT for 27 tumors with intrafractional motion greater than 1 cm. We assessed dose calculation by comparing dose distributions calculated on respiratory-averaged cine CT and respiratory-averaged 4D-CT using the gamma index. A threshold-based PET segmentation model of size, motion, and source-to-background was developed from phantom scans and validated with 24 lung tumors. Finally, feasibility of integrating cine CT and PET for contouring was assessed on a small group of larger tumors. Results: Cine CT to 4D-CT target volume ratios were (1.05±0.14) and (0.97±0.13) for high-contrast and low-contrast tumors respectively which was within intraobserver variation. Dose distributions on cine CT produced good agreement (< 2%/1 mm) with 4D-CT for 71 of 73 patients. The segmentation model fit the phantom data with R2 = 0.96 and produced PET target volumes that matched CT better than 6 published methods (-5.15%). Application of the model to more complex tumors produced mixed results and further research is necessary to adequately integrate PET and cine CT for delineation. Conclusions: Cine CT can be used for target delineation of small mobile lesions with minimal differences to 4D-CT. PET, utilizing the segmentation model, can provide additional contrast. Additional research is required to assess the efficacy of complex tumor delineation with cine CT and PET. Respiratory-averaged cine CT can substitute respiratory-averaged 4D-CT for dose calculation with negligible differences.

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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.

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Although several detailed models of molecular processes essential for circadian oscillations have been developed, their complexity makes intuitive understanding of the oscillation mechanism difficult. The goal of the present study was to reduce a previously developed, detailed model to a minimal representation of the transcriptional regulation essential for circadian rhythmicity in Drosophila. The reduced model contains only two differential equations, each with time delays. A negative feedback loop is included, in which PER protein represses per transcription by binding the dCLOCK transcription factor. A positive feedback loop is also included, in which dCLOCK indirectly enhances its own formation. The model simulated circadian oscillations, light entrainment, and a phase-response curve with qualitative similarities to experiment. Time delays were found to be essential for simulation of circadian oscillations with this model. To examine the robustness of the simplified model to fluctuations in molecule numbers, a stochastic variant was constructed. Robust circadian oscillations and entrainment to light pulses were simulated with fewer than 80 molecules of each gene product present on average. Circadian oscillations persisted when the positive feedback loop was removed. Moreover, elimination of positive feedback did not decrease the robustness of oscillations to stochastic fluctuations or to variations in parameter values. Such reduced models can aid understanding of the oscillation mechanisms in Drosophila and in other organisms in which feedback regulation of transcription may play an important role.

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Myxobacteria are single-celled, but social, eubacterial predators. Upon starvation they build multicellular fruiting bodies using a developmental program that progressively changes the pattern of cell movement and the repertoire of genes expressed. Development terminates with spore differentiation and is coordinated by both diffusible and cell-bound signals. The growth and development of Myxococcus xanthus is regulated by the integration of multiple signals from outside the cells with physiological signals from within. A collection of M. xanthus cells behaves, in many respects, like a multicellular organism. For these reasons M. xanthus offers unparalleled access to a regulatory network that controls development and that organizes cell movement on surfaces. The genome of M. xanthus is large (9.14 Mb), considerably larger than the other sequenced delta-proteobacteria. We suggest that gene duplication and divergence were major contributors to genomic expansion from its progenitor. More than 1,500 duplications specific to the myxobacterial lineage were identified, representing >15% of the total genes. Genes were not duplicated at random; rather, genes for cell-cell signaling, small molecule sensing, and integrative transcription control were amplified selectively. Families of genes encoding the production of secondary metabolites are overrepresented in the genome but may have been received by horizontal gene transfer and are likely to be important for predation.

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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.

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Intensity modulated radiation therapy (IMRT) is a technique that delivers a highly conformal dose distribution to a target volume while attempting to maximally spare the surrounding normal tissues. IMRT is a common treatment modality used for treating head and neck (H&N) cancers, and the presence of many critical structures in this region requires accurate treatment delivery. The Radiological Physics Center (RPC) acts as both a remote and on-site quality assurance agency that credentials institutions participating in clinical trials. To date, about 30% of all IMRT participants have failed the RPC’s remote audit using the IMRT H&N phantom. The purpose of this project is to evaluate possible causes of H&N IMRT delivery errors observed by the RPC, specifically IMRT treatment plan complexity and the use of improper dosimetry data from machines that were thought to be matched but in reality were not. Eight H&N IMRT plans with a range of complexity defined by total MU (1460-3466), number of segments (54-225), and modulation complexity scores (MCS) (0.181-0.609) were created in Pinnacle v.8m. These plans were delivered to the RPC’s H&N phantom on a single Varian Clinac. One of the IMRT plans (1851 MU, 88 segments, and MCS=0.469) was equivalent to the median H&N plan from 130 previous RPC H&N phantom irradiations. This average IMRT plan was also delivered on four matched Varian Clinac machines and the dose distribution calculated using a different 6MV beam model. Radiochromic film and TLD within the phantom were used to analyze the dose profiles and absolute doses, respectively. The measured and calculated were compared to evaluate the dosimetric accuracy. All deliveries met the RPC acceptance criteria of ±7% absolute dose difference and 4 mm distance-to-agreement (DTA). Additionally, gamma index analysis was performed for all deliveries using a ±7%/4mm and ±5%/3mm criteria. Increasing the treatment plan complexity by varying the MU, number of segments, or varying the MCS resulted in no clear trend toward an increase in dosimetric error determined by the absolute dose difference, DTA, or gamma index. Varying the delivery machines as well as the beam model (use of a Clinac 6EX 6MV beam model vs. Clinac 21EX 6MV model), also did not show any clear trend towards an increased dosimetric error using the same criteria indicated above.

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mRNA 3′ polyadenylation is central to mRNA biogenesis in prokaryotes and eukaryotes, and is implicated in numerous aspects of mRNA metabolism, including efficiency of mRNA export from the nucleus, message stability, and initiation of translation. However, due to the great complexity of the eukaryotic polyadenylation apparatus, the mechanisms of RNA 3 ′ end processing have remained elusive. Although the RNA processing reactions leading to polyadenylated messenger RNA have been studied in many systems, and much progress has been made, a complete understanding of the biochemistry of the poly(A) polymerase enzyme is still lacking. My research uses Vaccinia virus as a model system to gain a better understanding of this complicated polyadenylation process, which consist of RNA binding, catalysis and polymerase translocation. ^ Vaccinia virus replicates in the cytoplasm of its host cell, so it must employ its own poly(A) polymerase (PAP), a heterodimer of two virus encoded proteins, VP55 and VP39. VP55 is the catalytic subunit, adding 30 adenylates to a non-polyadenylated RNA in a rapid processive manner before abruptly changing to a slow, non-processive mode of adenylate addition and dissociating from the RNA. VP39 is the stimulatory subunit. It has no polyadenylation catalytic activity by itself, but when associated with VP55 it facilitates the semi-processive synthesis of tails several hundred adenylates in length. ^ Oligonucleotide selection and competition studies have shown that the heterodimer binds a minimal motif of (rU)2 (N)25 U, the “heterodimer binding motif”, within an oligonucleotide, and its primer selection for polyadenylation is base-type specific. ^ Crosslinking studies using photosensitive uridylate analogs show that within a VP55-VP39-primer ternary complex, VP55 comes into contact with all three required uridylates, while VP39 only contacts the downstream uridylate. Further studies, using a backbone-anchored photosensitive crosslinker show that both PAP subunits are in close proximity to the downstream −10 to −21 region of 50mer model primers containing the heterodimer binding motif. This equal crosslinking to both subunits suggests that the dimerization of VP55 and VP39 creates either a cleft or a channel between the two subunits through which this region of RNA passes. ^ Peptide mapping studies of VP39 covalently crosslinked to the oligonucleotide have identified residue R107 as the amino acid in close proximity to the −10 uridylate. This helps us project a conceptual model onto the known physical surface of this subunit. In the absence of any tertiary structural data for VP55, we have used a series of oligonucleotide selection assays, as well as crosslinking, nucleotide transfer assays, and gel shift assays to gain insight into the requirements for binding, polyadenylation and translocation. Collectively, these data allow us to put together a comprehensive model of the structure and function of the polyadenylation ternary complex consisting of VP39, VP55 and RNA. ^

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Random Forests™ is reported to be one of the most accurate classification algorithms in complex data analysis. It shows excellent performance even when most predictors are noisy and the number of variables is much larger than the number of observations. In this thesis Random Forests was applied to a large-scale lung cancer case-control study. A novel way of automatically selecting prognostic factors was proposed. Also, synthetic positive control was used to validate Random Forests method. Throughout this study we showed that Random Forests can deal with large number of weak input variables without overfitting. It can account for non-additive interactions between these input variables. Random Forests can also be used for variable selection without being adversely affected by collinearities. ^ Random Forests can deal with the large-scale data sets without rigorous data preprocessing. It has robust variable importance ranking measure. Proposed is a novel variable selection method in context of Random Forests that uses the data noise level as the cut-off value to determine the subset of the important predictors. This new approach enhanced the ability of the Random Forests algorithm to automatically identify important predictors for complex data. The cut-off value can also be adjusted based on the results of the synthetic positive control experiments. ^ When the data set had high variables to observations ratio, Random Forests complemented the established logistic regression. This study suggested that Random Forests is recommended for such high dimensionality data. One can use Random Forests to select the important variables and then use logistic regression or Random Forests itself to estimate the effect size of the predictors and to classify new observations. ^ We also found that the mean decrease of accuracy is a more reliable variable ranking measurement than mean decrease of Gini. ^

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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. ^

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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.^

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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.

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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. ^