Comparison of medical and forensic profiling potential of volatile biomarkers from different biological specimens from individuals and across populations

There is limited scientific knowledge on the composition of human odor from different biological specimens and the effect that physiological and psychological health conditions could have on them. There is currently no direct comparison of the volatile organic compounds (VOCs) emanating from different biological specimens collected from healthy individuals as well as individuals with certain diagnosed medical conditions. Therefore the question of matching VOCs present in human odor across various biological samples and across health statuses remains unanswered. The main purpose of this study was to use analytical instrumental methods to compare the VOCs from different biological specimens from the same individual and to compare the populations evaluated in this project. The goals of this study were to utilize headspace solid-phase microextraction gas chromatography mass spectrometry (HS-SPME-GC/MS) to evaluate its potential for profiling VOCs from specimens collected using standard forensic and medical methods over three different populations: healthy group with no diagnosed medical or psychological condition, one group with diagnosed type 2 diabetes, and one group with diagnosed major depressive disorder. The pre-treatment methods of collection materials developed for the study allowed for the removal of targeted VOCs from the sampling kits prior to sampling, extraction and analysis. Optimized SPME-GC/MS conditions has been demonstrated to be capable of sampling, identifying and differentiating the VOCs present in the five biological specimens collected from different subjects and yielded excellent detection limits for the VOCs from buccal swab, breath, blood, and urine with average limits of detection of 8.3 ng. Visual, Spearman rank correlation, and PCA comparisons of the most abundant and frequent VOCs from each specimen demonstrated that each specimen has characteristic VOCs that allow them to be differentiated for both healthy and diseased individuals. Preliminary comparisons of VOC profiles of healthy individuals, patients with type 2 diabetes, and patients with major depressive disorder revealed compounds that could be used as potential biomarkers to differentiate between healthy and diseased individuals. Finally, a human biological specimen compound database has been created compiling the volatile compounds present in the emanations of human hand odor, oral fluids, breath, blood, and urine.

Hospital discharge planning in the provision of food and nutrition services for older adults post discharge

This descriptive study examined whether discharge planning ensures that food and nutrition services are provided to older adults following hospital discharge. The questionnaire was distributed to discharge planning professionals in 11 South Florida hospitals. Of the 84 respondents (88% response rate), most were female nurse case managers. Almost all reported job barriers including excessive patient loads, too many responsibilities, and limited community services. While physicians, registered nurses, social workers, physical therapists, were deemed "very important" in discharge planning,registered dietitians were not, and almost half consulted them infrequently, if at all. Over 84% said nutrition-related medical conditions/factors, "strongly influenced" discharge planning. Many did not have adequate information about nutrition-related community resources, eg, home delivered meals, food stamps, outpatient registered dietitians. Therewere no universal approaches in meeting the nutrition needs in 6 case scenarios. More communication among community services and hospitals is needed.

Managerial work roles of health care executives in the changing environment of academic medical centers

The current U.S. health care system faces numerous environmental challenges. To compete and survive, health care organizations are developing strategies to lower costs and increase efficiency and quality. All of these strategies require rapid and precise decision making by top level managers. The purpose of this study is to determine the relationship between the environment, made up of unfavorable market conditions and limited resources, and the work roles of top level managers, specifically in the settings of academic medical centers. Managerial work roles are based on the ten work roles developed by Henry Mintzberg, in his book, The Nature of Managerial Work (1973). ^ This research utilized an integrated conceptual framework made up of systems theory in conjunction with role, attribution and contingency theories to illustrate that four most frequently performed Mintzberg's work roles are affected by the two environment dimensions. The study sample consisted of 108 chief executive officers in academic medical centers throughout the United States. The methods included qualitative methods in the form of key informants and case studies and quantitative in the form of a survey questionnaire. Research analysis involved descriptive statistics, reliability tests, correlation, principal component and multivariate analyses. ^ Results indicated that under the market condition of increased revenue based on capitation, the work roles increased. In addition, under the environment dimension of limited resources, the work roles increased when uncompensated care increased while Medicare and non-government funding decreased. ^ Based on these results, a typology of health care managers in academic medical centers was created. Managers could be typed as a strategy-formulator, relationship-builder or task delegator. Therefore, managers who ascertained their types would be able to use this knowledge to build their strengths and develop their weaknesses. Furthermore, organizations could use the typology to identify appropriate roles and responsibilities of managers for their specific needs. Consequently, this research is a valuable tool for understanding health care managerial behaviors that lead to improved decision making. At the same time, this could enhance satisfaction and performance and enable organizations to gain the competitive edge . ^

Rigid and non-rigid point-based medical image registration

The primary goal of this dissertation is to develop point-based rigid and non-rigid image registration methods that have better accuracy than existing methods. We first present point-based PoIRe, which provides the framework for point-based global rigid registrations. It allows a choice of different search strategies including (a) branch-and-bound, (b) probabilistic hill-climbing, and (c) a novel hybrid method that takes advantage of the best characteristics of the other two methods. We use a robust similarity measure that is insensitive to noise, which is often introduced during feature extraction. We show the robustness of PoIRe using it to register images obtained with an electronic portal imaging device (EPID), which have large amounts of scatter and low contrast. To evaluate PoIRe we used (a) simulated images and (b) images with fiducial markers; PoIRe was extensively tested with 2D EPID images and images generated by 3D Computer Tomography (CT) and Magnetic Resonance (MR) images. PoIRe was also evaluated using benchmark data sets from the blind retrospective evaluation project (RIRE). We show that PoIRe is better than existing methods such as Iterative Closest Point (ICP) and methods based on mutual information. We also present a novel point-based local non-rigid shape registration algorithm. We extend the robust similarity measure used in PoIRe to non-rigid registrations adapting it to a free form deformation (FFD) model and making it robust to local minima, which is a drawback common to existing non-rigid point-based methods. For non-rigid registrations we show that it performs better than existing methods and that is less sensitive to starting conditions. We test our non-rigid registration method using available benchmark data sets for shape registration. Finally, we also explore the extraction of features invariant to changes in perspective and illumination, and explore how they can help improve the accuracy of multi-modal registration. For multimodal registration of EPID-DRR images we present a method based on a local descriptor defined by a vector of complex responses to a circular Gabor filter.

Rigid and Non-rigid Point-based Medical Image Registration

The primary goal of this dissertation is to develop point-based rigid and non-rigid image registration methods that have better accuracy than existing methods. We first present point-based PoIRe, which provides the framework for point-based global rigid registrations. It allows a choice of different search strategies including (a) branch-and-bound, (b) probabilistic hill-climbing, and (c) a novel hybrid method that takes advantage of the best characteristics of the other two methods. We use a robust similarity measure that is insensitive to noise, which is often introduced during feature extraction. We show the robustness of PoIRe using it to register images obtained with an electronic portal imaging device (EPID), which have large amounts of scatter and low contrast. To evaluate PoIRe we used (a) simulated images and (b) images with fiducial markers; PoIRe was extensively tested with 2D EPID images and images generated by 3D Computer Tomography (CT) and Magnetic Resonance (MR) images. PoIRe was also evaluated using benchmark data sets from the blind retrospective evaluation project (RIRE). We show that PoIRe is better than existing methods such as Iterative Closest Point (ICP) and methods based on mutual information. We also present a novel point-based local non-rigid shape registration algorithm. We extend the robust similarity measure used in PoIRe to non-rigid registrations adapting it to a free form deformation (FFD) model and making it robust to local minima, which is a drawback common to existing non-rigid point-based methods. For non-rigid registrations we show that it performs better than existing methods and that is less sensitive to starting conditions. We test our non-rigid registration method using available benchmark data sets for shape registration. Finally, we also explore the extraction of features invariant to changes in perspective and illumination, and explore how they can help improve the accuracy of multi-modal registration. For multimodal registration of EPID-DRR images we present a method based on a local descriptor defined by a vector of complex responses to a circular Gabor filter.