Annexin A5-Conjugated Polymeric Micelles For Dual SPECT and Optical Detection of Apoptosis

Apoptosis, a form of programmed cell death, is critical to homoeostasis, normal development, and physiology. Dysregulation of apoptosis can lead to the accumulation of unwanted cells, such as occurs in cancer, and the removal of needed cells or disorders of normal tissues, such as heart, neurodegenerative, and autoimmune diseases. Noninvasive detection of apoptosis may play an important role in the evaluation of disease states and response to therapeutic intervention for a variety of diseases. It is desirable to have an imaging method to accurately detect and monitor this process in patients. In this study, we developed annexin A5-conjugated polymeric micellar nanoparticles dual-labeled with a near-infrared fluorescence fluorophores (Cy7) and a radioisotope (111In), named as 111In-labeled annexin A5-CCPM. In vitro studies demonstrated that annexin A5-CCPM could strongly and specifically bind to apoptotic cells. In vivo studies showed that apoptotic tissues could be clearly visualized by both single photon emission computed tomography (SPECT) and fluorescence molecular tomography (FMT) after intravenous injection of 111In-labeled Annexin A5-CCPM in 6 different apoptosis models. In contrast, there was little signal in respective healthy tissues. All the biodistribution data confirmed imaging results. Moreover, histological analysis revealed that radioactivity count correlated with fluorescence signal from the nanoparticles, and both signals co-localized with the region of apoptosis. In sum, 111In-labeled annexin A5-CCPM allowed visualization of apoptosis by both nuclear and optical imaging techniques. The complementary information acquired with multiple imaging techniques should be advantageous in improving diagnostics and management of patients.

'Reform' of the British national health service after the election of a labour government: Understanding the policy development process

The policy development process leading to the Labour government's white paper of December 1997—The new NHS: Modern, Dependable—is the focus of this project and the public policy development literature is used to aid in the understanding of this process. Policy makers who had been involved in the development of the white paper were interviewed in order to acquire a thorough understanding of who was involved in this process and how they produced the white paper. A theoretical framework is used that sorts policy development models into those that focus on knowledge and experience, and those which focus on politics and influence. This framework is central to understanding the evidence gathered from the individuals and associations that participated in this policy development process. The main research question to be asked in this project is to what extent do either of these sets of policy development models aid in understanding and explicating the process by which the Labour government's policies were developed. The interview evidence, along with published evidence, show that a clear pattern of policy change emerged from this policy development process, and the Knowledge-Experience and Politics-Influence policy making models both assist in understanding this process. The early stages of the policy development process were characterized as hierarchical and iterative, yet also very collaborative among those participating, with knowledge and experience being quite prevalent. At every point in the process, however, informal networks of political influence were used and noted to be quite prevalent by all of the individuals interviewed. The later stages of the process then became increasingly noninclusive, with decisions made by a select group of internal and external policy makers. These policy making models became an important tool with which to understand the policy development process. This Knowledge-Experience and Politics-Influence dichotomy of policy development models could therefore be useful in analyzing other types of policy development. ^

The functions of pitx2 and Bmp signaling in craniofacial development

The formation of the vertebrate face is an extremely complex developmental process, which needs to coordinate the outgrowth of several facial primordia. Facial primordia are small buds made up of mesenchymal masses enclosed by an epithelial layer that surrounds the primitive mouth. The upper jaw is formed by the maxillary process, the lateral nasal process, and the frontonasal process while the mandibular process forms the lower jaw. Recent experiments using genetics in mice and bead implantation approaches have shown that the pitx2 homeobox gene and Bmp signaling play important roles in this complex developmental process. However, the molecular mechanisms underlying the function of pitx2 and Bmp in these events are still unclear. Here, we show that pitx2 is required for oral epithelium maintenance, and branchial arch signaling is pitx2 dosage sensitive by using pitx2 allelic combinations that encode varying levels of pitx2. Maintenance of fgf8 signaling requires only low pitx2 dosage while repression of Bmp signaling requires high pitx2 levels. Different incisor and molar phenotypes in low level pitx2 mutant embryos suggest a distinct requirement for pitx2 in tooth-type development. The results show that pitx2 is required for craniofacial muscle formation and expanded Bmp signaling results in excess bone formation in pitx2 mutant embryos. Fate-mapping studies show that ectopic bone results from excessive bone growth, instead of muscle transformation. Moreover, by using cre/loxp system we show that partial loss of Bmpr-IA in the facial primordia results in cleft lip/palate, abnormal teeth, ectopic teeth and tooth transformation. These phenotypes suggest that Bmp signaling has multiple functions during craniofacial development. The mutant palate shelves can fuse with each other when cultured in vitro, suggesting that cleft palate is secondary to the partial loss of Bmpr-IA. Furthermore, we prove that Bmp4, one of the ligands of Bmpr-IA, plays a role during lip fusion developmental process and partial loss of Bmp4 in the facial primordia results in the lip fusion delay. These results have provided insight to understand the complex signaling cascades that regulate craniofacial development. ^

Receptor tyrosine kinase HER2-mediated signaling pathways in metastasis and angiogenesis

Metastasis, the major cause of morbidity and mortality in most cancers, is a highly organized and organ-selective process. The receptor tyrosine kinase HER2 enhances tumor metastasis, however, its role in homing to metastatic organs is poorly understood. The chemokine receptor CXCR4 has recently been shown to mediate the malignant cancer cells to specific organs. Here we show that HER2 enhances the expression of CXCR4 by increasing CXCR4 protein synthesis and inhibiting its degradation. We also observed significant correlation between HER2 and CXCR4 expression in human breast tumor tissues, and an association between CXCR4 expression and a poor overall survival rate in patients with breast cancer. Furthermore, we found that CXCR4 is required for HER2-induced invasion, migration, and adhesion activities in vitro . Finally we established stable transfectants using retroviral RNA interference to inhibit CXCR4 expression and showed that the CXCR4 is required for HER2-mediated lung metastasis in vivo. These results provide a plausible mechanism for HER2-mediated breast tumor metastasis and homing to metastatic organs, and establish a functional link between the receptor tyrosine kinase HER2 and the chemokine receptor CXCR4 signaling pathways. ^ The HER2 overexpression activates PI-3K/Akt pathways and plays an important role in mediating cell survival and tumor development. Hypoxia inducible factors (HIF) are the key regulator for angiogenesis and energy metabolism, and thereby enhance tumor growth and metastasis. HIF activation occurs in the majority of human cancers, including the HER2 overexpressing cancer cells. Previous reports suggested that increased PI-3K/Akt may activate HIF pathway in various tumors, but the detail mechanism is still not completely understood. Here we found that HER2/PI-3K/Akt pathway induces HIF-1α activation, which is independent of hypoxia, but relatively weaker than hypoxic stimulation. This phenomenon was further observed in Akt knock out mouse embryonic fibroblast cells. The PI-3K/Akt pathway does not affect HIF-1α binding with its E3 ligase VHL, but enhances the binding affinity between HIF-1α and β unit. Furthermore, we found Akt phosphorylates HIF-1β at serine 271 and further regulated HIF transcriptional activity. Our findings provided one mechanism that HER2 induce HIF activation via Akt to promote angiogenesis, and this process is independent on hypoxia, which may have implications in the oncogenic activity of HER2 and PI-3K/Akt pathway. ^

The association of internet use and depression among spinal cord injury population

The purpose of this study was to exam the relationship between internet use and depression among a population of individuals who have sustained spinal cord injury. This was cross-sectional survey design conducted among spinal cord injury (SCI) patients in the Model Spinal Cord Injury System. We included a total of 1,011 SCI-patients who were interviewed face-to-face or by telephone interview over approximately a three year time period (2004–2006). All data were collected through a telephone survey which included the Patient Health Questionnaire-9 (PHQ-9) to assess depression. We examined various scales of this survey, included a reduced 3-item scale (items 1, 2 and 6) to avoid the presence of somatic symptoms among SCI patients from influencing classification of depression. The frequency of internet usage was grouped as daily/weekly/monthly/non user. Covariates examined as possible confounders included demographic characteristics, occupational status, educational level, injury type, daily function of living, pain level, self-perceived health status and satisfaction with life. We observed a negative association between the frequency of internet use and the level of depression. Daily use of internet was associated with lower PHQ-9 score and depression; however this association did not reach statistical significance after for the mentioned covariates. In conclusion, the factors related to lower depression in SCI patients who use the internet are complicated. Daily internet usage was associated with lower levels of depression. The accuracy of 3-item scale needs further validation and investigation. Further study of internet usage pattern in SCI patient is recommended. ^

HIV disclosure decisions and social support among African-American women in Houston, Texas

African Americans make up 12.3% of the population but account for over half of the new HIV cases and 39% of the AIDS cases in 2003 (Centers for Disease Control and Prevention [CDC], 2003). African American women in particular accounted for 64% of these cases of HIV and 60% of the AIDS cases (Leigh & Huff, 2003). This study contributed to the knowledge about the disclosure process of women living with HIV/AIDS by documenting the relationship between social support and the disclosure process in the African American HIV/AIDS population.^ The study aims were to: (1) discuss the participants' self concept of support; (2) describe the common characteristics of the disclosure process; and (3) evaluate the common characteristics of support sought in a potential disclosure source. The ethnographic qualitative methodology was utilized to elicit participant narratives of HIV disclosure and social support. The researcher utilized a key informant interview methodology building on existing social and organizational relationships (Krueger, 1994) to gain access to the population. ^ Semi-structured interviews are a widely used and accepted qualitative research method for use with hard to reach populations and sensitive topics. Ten participants completed a 45 to 60 minute, one on one semi-structured interview covering social support and disclosure variables. Inclusion and exclusion criteria included: (1) self identified as a person living with HIV/AIDS; (2) African American); (3) female; (4) age 18-64 years old, (5) residence in Houston or surrounding counties.^ Themes generated from the interviews were (1) nondisclosure, (2) experiences with disclosure, (3) timing, (4) disclosure sources, and (5) coping. The themes suggest African American women living with HIV/AIDS come from different lifestyles but share similar experiences. Women utilize different strategies such as deciphering whom to trust and determining how much information to divulge in order to protect themselves or others.^ Although the sample group was small for this study, the results inform us about the various experiences each woman goes through as it relates to social support and disclosure and that each woman has to customize her response to the type of support she is receiving and her personal attitude about her disease.^

Process to develop a State Model Law to reduce prescription drug trafficking while protecting pain management

This paper will discuss the intersection of pill mills and the under-treatment of pain, while addressing the unintended consequence that cracking down on pill mills actually has on medical professionals' treatment of legitimate pain in clinical settings. Moreover, the impact each issue has on the spectrum of related policy, regulatory issues and legislation will be analyzed while addressing the national impact on medical care. Lastly, this paper will outline a process to develop a State Model Law on this subject. This process will include suggestions for the future and how we can move forward to adequately address public safety needs and how we can attempt to mitigate the unintended impact prescription drug trafficking has had on a patient's right to appropriate pain management. This balance is achievable and this paper will address ways we can find this elusive balancing point through the development of a State Model Law. ^

Funding the utilization of community health workers in Texas

Community health workers (CHWs) are volunteers or paid members of communities that perform outreach, patient assistance, health education, and assist in navigation of healthcare system amongst other duties. The utilization of CHWs in hospital and community setting provides health benefits to their communities while reducing cost to the overall healthcare system. ^ The general population of Texas lacks adequate access to primary care. An important indicator of such a crisis is excessive usage of emergency department services in Texas, especially by the large minority population within the state. Also, unmanaged chronic diseases have been shown to be correlated with the excessive usage of emergency services. According to a recent survey of 25 Houston metropolitan area hospitals, almost 54% of the ER visits could have been resolved in primary care settings. A Galveston based study also indicated that the ER usage was higher amongst African-Americans and Latinos. Meanwhile, 28.5% of the total ER visits were made by Latinos from the surrounding areas (Begley et al., 2007). There is substantial evidence present which indicates enormous cost-savings that CHWs have produced in Texas and nationwide through reduction in unnecessary ER visits along with better management of chronic diseases (Fedder et al, 2003). ^ This paper provides an analysis regarding the need and importance for sustainable and stable sources of funding for Community health workers (CHWs) in Texas utilizing Kingdon's model of Agenda Setting as framework. The policy analysis is also aimed at reporting on the policy process and actions taken by Children at Risk to address this critical issue. Children at Risk, a Houston based advocacy organization, has created a legislative proposal that calls on the Texas Health and Human Commission to apply for a Medicaid §§1115 waiver to provide sustainable sources of funding for CHWs, Rep. John Zerwas sponsored HB 2244 bill and it was filed on March 3, 2011. The bill would affect the use of CHWs in Texas in two ways: 1) through the establishment and operation of a program designed to train and educate CHWs 2) by creating a statewide training and certification advisory committee. The advisory committee is required in the bill to submit recommendations for providing sustainable funding and employment for CHWs. The HB 2244 failed to move out of the House Public Health committee. However, HB2244 was amended into HB 2610 introduced by Representative Guillen. The House Bill 2610 is geared towards establishing a community-based navigator program in order to assist individuals applying for public assistance through the Internet. The House Bill 2610 was signed by the Governor and will be effective September 1, 2011.^

Radiomics of NSCLC: Quantitative CT Image Feature Characterization and Tumor Shrinkage Prediction

Radiomics is the high-throughput extraction and analysis of quantitative image features. For non-small cell lung cancer (NSCLC) patients, radiomics can be applied to standard of care computed tomography (CT) images to improve tumor diagnosis, staging, and response assessment. The first objective of this work was to show that CT image features extracted from pre-treatment NSCLC tumors could be used to predict tumor shrinkage in response to therapy. This is important since tumor shrinkage is an important cancer treatment endpoint that is correlated with probability of disease progression and overall survival. Accurate prediction of tumor shrinkage could also lead to individually customized treatment plans. To accomplish this objective, 64 stage NSCLC patients with similar treatments were all imaged using the same CT scanner and protocol. Quantitative image features were extracted and principal component regression with simulated annealing subset selection was used to predict shrinkage. Cross validation and permutation tests were used to validate the results. The optimal model gave a strong correlation between the observed and predicted shrinkages with . The second objective of this work was to identify sets of NSCLC CT image features that are reproducible, non-redundant, and informative across multiple machines. Feature sets with these qualities are needed for NSCLC radiomics models to be robust to machine variation and spurious correlation. To accomplish this objective, test-retest CT image pairs were obtained from 56 NSCLC patients imaged on three CT machines from two institutions. For each machine, quantitative image features with concordance correlation coefficient values greater than 0.90 were considered reproducible. Multi-machine reproducible feature sets were created by taking the intersection of individual machine reproducible feature sets. Redundant features were removed through hierarchical clustering. The findings showed that image feature reproducibility and redundancy depended on both the CT machine and the CT image type (average cine 4D-CT imaging vs. end-exhale cine 4D-CT imaging vs. helical inspiratory breath-hold 3D CT). For each image type, a set of cross-machine reproducible, non-redundant, and informative image features was identified. Compared to end-exhale 4D-CT and breath-hold 3D-CT, average 4D-CT derived image features showed superior multi-machine reproducibility and are the best candidates for clinical correlation.

Understanding and Characterizing Shared Decision-Making and Behavioral Intent in Medical Uncertainty

Applying Theoretical Constructs to Address Medical Uncertainty Situations involving medical reasoning usually include some level of medical uncertainty. Despite the identification of shared decision-making (SDM) as an effective technique, it has been observed that the likelihood of physicians and patients engaging in shared decision making is lower in those situations where it is most needed; specifically in circumstances of medical uncertainty. Having identified shared decision making as an effective, yet often a neglected approach to resolving a lack of information exchange in situations involving medical uncertainty, the next step is to determine the way(s) in which SDM can be integrated and the supplemental processes that may facilitate its integration. SDM involves unique types of communication and relationships between patients and physicians. Therefore, it is necessary to further understand and incorporate human behavioral elements - in particular, behavioral intent - in order to successfully identify and realize the potential benefits of SDM. This paper discusses the background and potential interaction between the theories of shared decision-making, medical uncertainty, and behavioral intent. Identifying Shared Decision-Making Elements in Medical Encounters Dealing with Uncertainty A recent summary of the state of medical knowledge in the U.S. reported that nearly half (47%) of all treatments were of unknown effectiveness, and an additional 7% involved an uncertain tradeoff between benefits and harms. Shared decision-making (SDM) was identified as an effective technique for managing uncertainty when two or more parties were involved. In order to understand which of the elements of SDM are used most frequently and effectively, it is necessary to identify these key elements, and understand how these elements related to each other and the SDM process. The elements identified through the course of the present research were selected from basic principles of the SDM model and the “Data, Information, Knowledge, Wisdom” (DIKW) Hierarchy. The goal of this ethnographic research was to identify which common elements of shared decision-making patients are most often observed applying in the medical encounter. The results of the present study facilitated the understanding of which elements patients were more likely to exhibit during a primary care medical encounter, as well as determining variables of interest leading to more successful shared decision-making practices between patients and their physicians. Understanding Behavioral Intent to Participate in Shared Decision-Making in Medically Uncertain Situations Objective: This article describes the process undertaken to identify and validate behavioral and normative beliefs and behavioral intent of men between the ages of 45-70 with regard to participating in shared decision-making in medically uncertain situations. This article also discusses the preliminary results of the aforementioned processes and explores potential future uses of this information which may facilitate greater understanding, efficiency and effectiveness of doctor-patient consultations.Design: Qualitative Study using deductive content analysisSetting: Individual semi-structure patient interviews were conducted until data saturation was reached. Researchers read the transcripts and developed a list of codes.Subjects: 25 subjects drawn from the Philadelphia community.Measurements: Qualitative indicators were developed to measure respondents’ experiences and beliefs related to behavioral intent to participate in shared decision-making during medical uncertainty. Subjects were also asked to complete the Krantz Health Opinion Survey as a method of triangulation.Results: Several factors were repeatedly described by respondents as being essential to participate in shared decision-making in medical uncertainty. These factors included past experience with medical uncertainty, an individual’s personality, and the relationship between the patient and his physician.Conclusions: The findings of this study led to the development of a category framework that helped understand an individual’s needs and motivational factors in their intent to participate in shared decision-making. The three main categories include 1) an individual’s representation of medically uncertainty, 2) how the individual copes with medical uncertainty, and 3) the individual’s behavioral intent to seek information and participate in shared decision-making during times of medically uncertain situations.

Attitudes and other barriers to the utilization of clinical research findings by American physicians: A systematic review

Background: The Institute of Medicine estimates that only a maximum of 25% of clinical research findings are incorporated into practice by physicians. To improve clinical practice, efforts have been made to promote evidence-based medicine and the use of clinical guidelines. Despite these efforts, the gap between research and clinical practice remains wide.^ Objective: To systematically review the literature describing the factors which influence the use of clinical research recommendations by American physicians.^ Hypothesis: Barriers exist in the application of clinical research into clinical practice, and are multifactorial. The establishment of the Clinical and Translational Awards (CTSA; special federal grants awarded to selected institutions to support clinical and translational research) has reduced the effect of these barriers and improved the process of clinical research translation into practice among American physicians.^ Aims: Identify barriers and facilitators of the use of research findings in clinical practice by American physicians. Contrast studies published six years before and after the creation of the CTSA.^ Methods: The sources of data include published literature from Medline, PubMed and PsycINFO. Selected studies must be qualitative, a survey of American clinicians, based on evidence-based medicine practice, clinical guidelines or treatment pathways. Systematic reviews and reports were excluded, as well as studies with less than 100 respondents.^ Results: In total, 1036 abstracts were reviewed; 115 full text potential articles were identified and reviewed, and a total of 31 studies met all criteria for inclusion in the final review.^ Conclusions: The barriers against the application of clinical research findings, in the forms of clinical guidelines, evidence-based medicine guides and clinical pathways, can be divided broadly into physician barriers, practice/system barriers and patient barriers. Physician barriers are the most common barriers, especially the lack of familiarity with guidelines and the lack of time. Of the factors which improve the use of research based guidelines, physician factors such as younger age, lower duration of clinical practice, specialty training, and practice in large group Health Maintenance Organization (HMO) settings with fewer patients seen were the most commonly cited.^

Comparison of machine learning approaches and statistical methods for estimation of airborne chemical exposures

Accurate quantitative estimation of exposure using retrospective data has been one of the most challenging tasks in the exposure assessment field. To improve these estimates, some models have been developed using published exposure databases with their corresponding exposure determinants. These models are designed to be applied to reported exposure determinants obtained from study subjects or exposure levels assigned by an industrial hygienist, so quantitative exposure estimates can be obtained. ^ In an effort to improve the prediction accuracy and generalizability of these models, and taking into account that the limitations encountered in previous studies might be due to limitations in the applicability of traditional statistical methods and concepts, the use of computer science- derived data analysis methods, predominantly machine learning approaches, were proposed and explored in this study. ^ The goal of this study was to develop a set of models using decision trees/ensemble and neural networks methods to predict occupational outcomes based on literature-derived databases, and compare, using cross-validation and data splitting techniques, the resulting prediction capacity to that of traditional regression models. Two cases were addressed: the categorical case, where the exposure level was measured as an exposure rating following the American Industrial Hygiene Association guidelines and the continuous case, where the result of the exposure is expressed as a concentration value. Previously developed literature-based exposure databases for 1,1,1 trichloroethane, methylene dichloride and, trichloroethylene were used. ^ When compared to regression estimations, results showed better accuracy of decision trees/ensemble techniques for the categorical case while neural networks were better for estimation of continuous exposure values. Overrepresentation of classes and overfitting were the main causes for poor neural network performance and accuracy. Estimations based on literature-based databases using machine learning techniques might provide an advantage when they are applied to other methodologies that combine `expert inputs' with current exposure measurements, like the Bayesian Decision Analysis tool. The use of machine learning techniques to more accurately estimate exposures from literature-based exposure databases might represent the starting point for the independence from the expert judgment.^