3 resultados para Shifting Interior
em DigitalCommons@The Texas Medical Center
Resumo:
Subfields of the hippocampus display differential dynamics in processing a spatial environment, especially when changes are introduced to the environment. Specifically, when familiar cues in the environment are spatially rearranged, place cells in the CA3 subfield tend to rotate with a particular set of cues (e.g., proximal cues), maintaining a coherent spatial representation. Place cells in CA1, in contrast, display discordant behaviors (e.g., rotating with different sets of cues or remapping) in the same condition. In addition, on average, CA3 place cells shift their firing locations (measured by the center of mass, or COM) backward over time when the animal encounters the changed environment for the first time, but not after that first experience. However, CA1 displays an opposite pattern, in which place cells exhibit the backward COM-shift only from the second day of experience, but not on the first day. Here, we examined the relationship between the environment-representing behavior (i.e., rotation vs. remapping) and the COM-shift of place fields in CA1 and CA3. Both in CA1 and CA3, the backward (as well as forward) COM-shift phenomena occurred regardless of the rotating versus remapping of the place cell. The differential, daily time course of the onset/offset of backward COM-shift in the cue-altered environment in CA1 and CA3 (on day 1 in CA1 and from day 2 onward in CA3) stems from different population dynamics between the subfields. The results suggest that heterogeneous, complex plasticity mechanisms underlie the environment-representating behavior (i.e., rotate/remap) and the COM-shifting behavior of the place cell.
Resumo:
During the 82nd Texas legislature, state leaders passed a provision stating that healthcare providers, who perform, promote, or affiliate with providers who perform or promote elective abortion services may not be eligible to participate in the Texas Medicaid Women's Health Program (WHP). The federal government reacted to this new provision by vowing to eliminate its 90% share of program support on the grounds that the provision violated a patient's freedom to choose a provider; a right protected by the Social Security Act. Texas leaders stated that the Women's Health Program would continue without federal support, financed exclusively with state funds.^ The following policy analysis compares the projected impact of the current Medicaid Women's Health Program to the proposed state-run program using the criteria-alternative matrix framework. The criteria used to evaluate the program alternatives include population affected, unintended pregnancy and abortion impact, impact on cervical cancer rate, and state-level government expenditures. Each criterion was defined by selected measures. The population affected was measured by the number of women served in the programs. Government expenditures were measured in terms of payments for program costs, Medicaid delivery costs, and cervical cancer diagnostic costs. Unintended pregnancy impact was measured by the number of projected unplanned pregnancies and abortions under each alternative. The impact on cervical cancer was projected in terms of the number of new cervical cancer cases under each alternative. Differences in the projections with respect to each criterion were compared to assess the impact of shifting to the state-only policy.^ After examining program alternatives, it is highly recommended that Texas retain the Medicaid WHP. If the state does decide to move forward with the state-run WHP, it is recommended that the program run at its previous capacity. Furthermore, for the purpose of addressing the relatively high cervical cancer incidence rate in Texas, incorporating HPV vaccination coverage for women ages 18-26 as part of the Women's Health Program is recommended.^
Resumo:
The purpose of this study was to understand the scope of breast cancer disparities within the Texas Medical Center. The goal was to increase the awareness of breast cancer disparities at the health care organization level, and to foster the development of organizational interventions to reduce breast cancer disparities. The study seeks to answer the following questions: 1. Are hospitals in the Texas Medical Center implementing interventions to reduce breast cancer disparities? 2. What are their interventions for reducing the effects of non clinical factors on breast cancer treatment disparities? 3. What are their measures for monitoring, continuously improving, and evaluating the success of their interventions? ^ This research project was designed as a mixed methods case study. Quantitative breast cancer data for the years 2000-2009 was obtained from the Texas Cancer Registry (TCR). Qualitative data collection and analysis was done by conducting a total of 20 semi-structured interviews of administrators, physicians and nurses at five hospitals (A, B, C, D and E) in the Texas Medical Center (TMC). For quantitative analysis, the study was limited to early stage breast cancer patients: local and regional. The dependent variable was receipt of standard treatment: Surgery (Yes/No), BCS vs Mastectomy, Chemotherapy (Yes/No) and Radiation after BCS (Yes/No). The main independent variable was race: non-Hispanic White (NHW) , non-Hispanic Black (NHB), and Hispanic. Other covariates included age at diagnosis, diagnosis date, percent poverty, grade, stage, and regional nodes. Multivariate logistic regression was used to test the adjusted association between receipt of standard care and race. Qualitative data was analyzed with the Atlas.ti7 software (ATLAS.ti GmbH, Berlin). ^ Though there were significant differences by race for all dependent variables when the data was analyzed as a single group of all hospitals; at the level of the individual hospitals the results were not consistent by race/ethnicity across all dependent variables for hospitals A, B, and E. There were no racial differences in adjusted analysis for receipt of chemotherapy for the individual hospitals of interest in this study. For hospitals C and D, no racial disparities in treatment was observed in adjusted multivariable analysis. All organizations in this study were aware of the body of research which shows that there are disparities in breast cancer outcomes for patient population groups. However, qualitative data analysis found that there were differences in interest among hospitals in addressing breast cancer disparities in their patient population groups. Some organizations were actively implementing directed measures to reduce the breast cancer disparity gap in outcomes for patients, and others were not. Despite the differences in levels of interest, quantitative data analysis showed that organizations in the Texas Medical Center were making progress in reducing the burden of breast cancer disparities in the patient populations being served.^