6 resultados para closing

em DigitalCommons@The Texas Medical Center


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Clinical medical librarianship is entering its second decade, but little evaluative data has accrued in the literature. Variations from the original programs and novel new approaches have insured the survival of the program so far. The clinical librarian (CL) forms a vital link between the library and the health care professional, operating as an important information transfer agent. However, to further insure the survival of these vital programs, hard evaluative evidence is needed. The University of Texas Medical Branch (UTMB) at Galveston began a CL Program in 1978/79. An extensive three-year pre/post evaluation study was conducted using a specifically developed evaluation model, which, if adopted by others, will provide the needed comparative data. Both a pilot study, or formative evaluation, and a summative evaluation were conducted. The results of this evaluation confirmed many of the conclusions reported by other CL programs. Eight hypotheses were proposed at the beginning of this study. Data were collected and used to support acceptance or rejection of the null hypotheses, and conclusions were drawn according to the results. Implications relevant to the study conclusions and future trends in medical librarianship are also discussed in the closing chapter.

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Brain tumor is one of the most aggressive types of cancer in humans, with an estimated median survival time of 12 months and only 4% of the patients surviving more than 5 years after disease diagnosis. Until recently, brain tumor prognosis has been based only on clinical information such as tumor grade and patient age, but there are reports indicating that molecular profiling of gliomas can reveal subgroups of patients with distinct survival rates. We hypothesize that coupling molecular profiling of brain tumors with clinical information might improve predictions of patient survival time and, consequently, better guide future treatment decisions. In order to evaluate this hypothesis, the general goal of this research is to build models for survival prediction of glioma patients using DNA molecular profiles (U133 Affymetrix gene expression microarrays) along with clinical information. First, a predictive Random Forest model is built for binary outcomes (i.e. short vs. long-term survival) and a small subset of genes whose expression values can be used to predict survival time is selected. Following, a new statistical methodology is developed for predicting time-to-death outcomes using Bayesian ensemble trees. Due to a large heterogeneity observed within prognostic classes obtained by the Random Forest model, prediction can be improved by relating time-to-death with gene expression profile directly. We propose a Bayesian ensemble model for survival prediction which is appropriate for high-dimensional data such as gene expression data. Our approach is based on the ensemble "sum-of-trees" model which is flexible to incorporate additive and interaction effects between genes. We specify a fully Bayesian hierarchical approach and illustrate our methodology for the CPH, Weibull, and AFT survival models. We overcome the lack of conjugacy using a latent variable formulation to model the covariate effects which decreases computation time for model fitting. Also, our proposed models provides a model-free way to select important predictive prognostic markers based on controlling false discovery rates. We compare the performance of our methods with baseline reference survival methods and apply our methodology to an unpublished data set of brain tumor survival times and gene expression data, selecting genes potentially related to the development of the disease under study. A closing discussion compares results obtained by Random Forest and Bayesian ensemble methods under the biological/clinical perspectives and highlights the statistical advantages and disadvantages of the new methodology in the context of DNA microarray data analysis.

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Withdrawal reflexes of the mollusk Aplysia exhibit sensitization, a simple form of long-term memory (LTM). Sensitization is due, in part, to long-term facilitation (LTF) of sensorimotor neuron synapses. LTF is induced by the modulatory actions of serotonin (5-HT). Pettigrew et al. developed a computational model of the nonlinear intracellular signaling and gene network that underlies the induction of 5-HT-induced LTF. The model simulated empirical observations that repeated applications of 5-HT induce persistent activation of protein kinase A (PKA) and that this persistent activation requires a suprathreshold exposure of 5-HT. This study extends the analysis of the Pettigrew model by applying bifurcation analysis, singularity theory, and numerical simulation. Using singularity theory, classification diagrams of parameter space were constructed, identifying regions with qualitatively different steady-state behaviors. The graphical representation of these regions illustrates the robustness of these regions to changes in model parameters. Because persistent protein kinase A (PKA) activity correlates with Aplysia LTM, the analysis focuses on a positive feedback loop in the model that tends to maintain PKA activity. In this loop, PKA phosphorylates a transcription factor (TF-1), thereby increasing the expression of an ubiquitin hydrolase (Ap-Uch). Ap-Uch then acts to increase PKA activity, closing the loop. This positive feedback loop manifests multiple, coexisting steady states, or multiplicity, which provides a mechanism for a bistable switch in PKA activity. After the removal of 5-HT, the PKA activity either returns to its basal level (reversible switch) or remains at a high level (irreversible switch). Such an irreversible switch might be a mechanism that contributes to the persistence of LTM. The classification diagrams also identify parameters and processes that might be manipulated, perhaps pharmacologically, to enhance the induction of memory. Rational drug design, to affect complex processes such as memory formation, can benefit from this type of analysis.

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This article describes a study of the outcomes of home-based family preservation services for abusive and neglectful families in Los Angeles County. It focuses on changes in family functioning during the 3 month service period and one year after case closing. Families known to the public child welfare agency were referred to the project based on caseworker judgement of the need for services rather than on the criteria of imminent risk of placement. Two hundred forty families were randomly assigned to either the service group receiving family preservation services from two non-profit agencies or to the comparison group receiving regular public agency services. Both caseworkers and families reported small but significant improvements in family functioning for the service group families, but not for the comparison group families. Study findings also suggest the aspects of family functioning most changed by services, the characteristics of families most affected by services, and variables which predicted service success.

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Involvement of E. coli 23S ribosomal RNA (rRNA) in decoding of termination codons was first indicated by the characterization of a 23S rRNA mutant that causes UGA-specific nonsense suppression. The work described here was begun to test the hypothesis that more 23S rRNA suppressors of specific nonsense mutations can be isolated and that they would occur non-randomly in the rRNA genes and be clustered in specific, functionally significant regions of rRNA.^ Approximately 2 kilobases of the gene for 23S rRNA were subjected to PCR random mutagenesis and the amplified products screened for suppression of nonsense mutations in trpA. All of the suppressor mutations obtained were located in a thirty-nucleotide part of the GTPase center, a conserved rRNA sequence and structure, and they and others made in that region by site-directed mutagenesis were shown to be UGA-specific in their suppression of termination codon mutations. These results proved the initial hypothesis and demonstrated that a group of nucleotides in this region are involved in decoding of the UGA termination codon. Further, it was shown that limitation of cellular availability or synthesis of L11, a ribosomal protein that binds to the GTPase center rRNA, resulted in suppression of termination codon mutations, suggesting the direct involvement of L11 in termination in vivo.^ Finally, in vivo analysis of certain site-specific mutations made in the GTPase center RNA demonstrated that (a) the G$\cdot$A base pair closing the hexanucleotide hairpin loop was not essential for normal termination, (b) the "U-turn" structure in the 1093 to 1098 hexaloop is critical for normal termination, (c) nucleotides A1095 and A1067, necessary for the binding to ribosomes of thiostrepton, an antibiotic that inhibits polypeptide release factor binding to ribosomes in vitro, are also necessary for normal peptide chain termination in vivo, and (d) involvement of this region of rRNA in termination is determined by some unique subset structure that includes particular nucleotides rather than merely by a general structural feature of the GTPase center.^ This work advances the understanding of peptide chain termination by demonstrating that the GTPase region of 23S rRNA participates in recognition of termination codons, through an associated ribosomal protein and specific conserved nucleotides and structural motifs in its RNA. ^

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Effective communication; whether from an interpersonal, mass media, or global perspective, is a critical component in public health. It is an essential conduit in increasing public awareness of available health resources, potential health hazards and related disease prevention strategies, and in delivering better health care. Within this context, available literature asserts doctor-patient communication as central to healthcare delivery. It has been shown to affect patient health outcomes, satisfaction with care, adherence to treatment recommendations, and even understanding of medical information. While research supports the essential imperative of interventions aimed at teaching doctors and patients the communication skills necessary for a successful and meaningful medical interaction, most interventions to date, focus on teaching these communication skills to doctors and seem to rely, largely, on mass media for providing patients with the information needed to increase communication efficacy. This study sought to fill a significant gap in the doctor-patient communication literature by reviewing the context of the doctor-patient exchange in the medical interaction, the implications of this exchange in resulting care of the patient, and the potential improvements to practice through interventions aimed at improving the communication exchange. Closing with an evaluation of a patient-centered communication intervention, the “How to Talk to Your Doctor” (HTTTYD) program that combines previously identified optimal strategies for improving communication between doctors and patients, this study examined the patients’ perspective of their potential as better communicators in the medical interaction. ^ Specific Aims, Hypotheses or Questions (Aim I) To examine the context of health communication within a public health framework and its relation to health care delivery. (Aim II) To review doctor-patient communication as a central focus within health care delivery and the resulting implications to patient care. (Aim III) To assess the utility of interventions to improve doctor-patient communication. Specifically, to evaluate the effectiveness of a patient-centered community education intervention, the “How to Talk to Your Doctor” (HTTTYD) program, aimed at improving patient communication efficacy.^