Targeted cancer diagnosis with radiolabeled endostatin

Nuclear imaging is used for non-invasive detection, staging and therapeutic monitoring of tumors through the use of radiolabeled probes. Generally, these probes are used for applications in which they provide passive, non-specific information about the target. Therefore, there is a significant need for actively-targeted radioactive probes to provide functional information about the site of interest. This study examined endostatin, an endogenous inhibitor of tumor angiogenesis, which has affinity for tumor vasculature. The major objective of this study was to develop radiolabeled analogues of endostatin through novel chemical and radiochemical syntheses, and to determine their usefulness for tumor imaging using in vitro and in vivo models of vascular, mammary and prostate tumor cells. I hypothesize that this binding will allow for a non-invasive approach to detection of tumor angiogenesis, and such detection can be used for therapeutic monitoring to determine the efficacy of anti-angiogenic therapy. ^ The data showed that endostatin could be successfully conjugated to the bifunctional chelator ethylenedicysteine (EC), and radiolabeled with technetium-99m and gallium-68, providing a unique opportunity to use a single precursor for both nuclear imaging modalities: 99mTc for single photon emission computed tomography and 68Ga for positron emission tomography, respectively. Both radiolabeled analogues showed increased binding as a function of time in human umbilical vein endothelial cells and mammary and prostate tumor cells. Binding could be blocked in a dose-dependent manner by unlabeled endostatin implying the presence of endostatin receptors on both vascular and tumor cells. Animal biodistribution studies demonstrated that both analogues were stable in vivo, showed typical reticuloendothelial and renal excretion and produced favorable absorbed organ doses for application in humans. The imaging data provide evidence that the compounds quantitate tumor volumes with clinically-useful tumor-to-nontumor ratios, and can be used for treatment follow-up to depict changes occurring at the vascular and cellular levels. ^ Two novel endostatin analogues were developed and demonstrated interaction with vascular and tumor cells. Both can be incorporated into existing nuclear imaging platforms allowing for potential wide-spread clinical benefit as well as serving as a diagnostic tool for elucidation of the mechanism of action of endostatin. ^

Team: Bee Me. A formulative evaluation of a negative eating attitudes and behaviors primary prevention curriculum targeted at 5 th grade elementary school girls

Objective. To evaluate a school-based intervention aimed at the primary prevention of negative eating attitudes and behaviors among preadolescent girls, and to revise curriculum lessons based on quantitative and qualitative findings. ^ Intervention Design. A formative evaluation was conducted on four Team: Bee Me curriculum lessons at a Houston elementary school. Evaluation focused on program satisfaction and short-term effect on knowledge and eating attitudes and behaviors. ^ Results. Sixteen girls participated in the five-day project. Statistically significant improvements in overall knowledge were observed (p<0.05), however only modest changes were observed in eating attitudes and behaviors. Program satisfaction was high among student participants and the teacher who implemented it. Insight for future modifications to this program and for similar interventions was provided by the students and teacher. ^ Conclusions. This program led to positive trends in outcome variables; however longer and more intensive testing of this program is needed to better evaluate its effectiveness.^

Application of cell line based genomic predictors to predict response to targeted therapies in breast cancer

Cancer cell lines can be treated with a drug and the molecular comparison of responders and non-responders may yield potential predictors that could be tested in the clinic. It is a bioinformatics challenge to apply the cell line-derived multivariable response predictors to patients who respond to therapy. Using the gene expression data from 23 breast cancer cell lines, I developed three predictors of dasatinib sensitivity by selecting differentially expressed genes and applying different classification algorithms. The performance of these predictors on independent cell lines with known dasatinib response was tested. The predictor based on weighted voting method has the best overall performance. It correctly predicted dasatinib sensitivity in 11 out of 12 (92%) breast and 17 out of 23 (74%) lung cancer cell lines. These predictors were then applied to the gene expression data from 133 breast cancer patients in an attempt to predict how the patients might respond to dasatinib therapy. Two predictors identified 13 patients in common to be dasatinib sensitive. Sixty two percent of these cases are triple negative (ER-negative, HER2-negative and PR-negative) and 76% are double negative. The result is consistent with the findings from other studies, which identified a target population for dasatinib treatment to be triple negative or basal breast cancer subtype. In conclusion, we think that the cell line-derived dasatinib classifiers can be applied to the human patients. ^

Targeted immunization to protect infants against pertussis in the United States

Pertussis is an infectious disease caused by the bacteria Bordetella pertussis, and is associated with a serious respiratory infection, a prolonged cough, and can require hospitalization. A vaccine for adolescents and adults has been available since 2005. This paper examines one recommended immunization strategy to prevent pertussis among infants, called “cocooning.” The strategy focuses on creating immunity among adult caregivers so they serve as a protective cocoon to the newborns, who are too young to be vaccinated. This paper looks at relevant studies summarizing implementation of cocooning strategies and addresses the question – Does the research literature support the view of using cocooning as an effective strategy to prevent pertussis in infants? After exclusions, 8 studies remained for synthesis. The evidence shows that cocooning is complex strategy and the evidence is mixed when it comes to ensuring an increase in immunization of caregivers. ^

Increasing awareness of colorectal cancer screening through targeted exam room based video messages

Colorectal cancer (CRC) is the third largest cause of cancer death in the United States. While the disease burden is high, there are proven methods to screen for CRC and detect it at a stage that is amenable to cure. Patients with low health literacy have difficulty navigating the health care system and are at increased risk to not receive preventive care services such as colorectal cancer screening (CRCS). To address this need, an exam-room based video was developed to be played for patients in the privacy of the exam room, while they are waiting to be seen by their medical provider. In roughly 2 minutes, the video informs the patient about CRC and CRCS and how they can successfully complete CRCS. One of the key barriers to completing CRCS is the need to increase patients' knowledge and improve attitudes surrounding CRCS. This study examines the impact of the video on patients' knowledge and attitudes about CRC and CRCS in a medically underserved patient population in Houston, Texas. ^ Sixty-one patients presenting for routine medical care were enrolled in the study. Depending on their randomization, the patients either received routine information about CRC and CRCS or they watched the video. We found that the patients who did watch the video did have improvements in their knowledge and improved attitudes about CRC and CRCS. Future studies will be needed to examine whether the video improves the patients' completion of CRCS.^

Predictive validity of the personal background and preparation survey and effectiveness of targeted interventions among health science community college students

Existing data, collected from 1st-year students enrolled in a major Health Science Community College in the south central United States, for Fall 2010, Spring 2011, Fall 2011 and Spring 2012 semesters as part of the "Online Navigational Assessment Vehicle, Intervention Guidance, and Targeting of Risks (NAVIGATOR) for Undergraduate Minority Student Success" with CPHS approval number HSC-GEN-07-0158, was used for this thesis. The Personal Background and Preparation Survey (PBPS) and a two-question risk self-assessment subscale were administered to students during their 1st-year orientation. The PBPS total risk score, risk self-assessment total and overall scores, and Under Representative Minority Student (URMS) status were recorded. The purpose of this study is to evaluate and report the predictive validity of the indicators identified above for Adverse Academic Status Events (AASE) and Nonadvancement Adverse Academic Status Events (NAASE) as well as the effectiveness of interventions targeted using the PBPS among a diverse population of health science community college students. The predictive validity of the PBPS for AASE has previously been demonstrated among health science professions and graduate students (Johnson, Johnson, Kim, & McKee, 2009a; Johnson, Johnson, McKee, & Kim, 2009b). Data will be analyzed using binary logistic regression and correlation using SPSS 19 statistical package. Independent variables will include baseline- versus intervention-year treatments, PBPS, risk self-assessment, and URMS status. The dependent variables will be binary AASE and NAASE status. ^ The PBPS was the first reliable diagnostic and prescriptive instrument to establish documented predictive validity for student Adverse Academic Status Events (AASE) among students attending health science professional schools. These results extend the documented validity for the PBPS in predicting AASE to a health science community college student population. Results further demonstrated that interventions introduced using the PBPS were followed by approximately one-third reduction in the odds of Nonadvancement Adverse Academic Status Events (NAASE), controlling for URMS status and risk self-assessment scores. These results indicate interventions introduced using the PBPS may have potential to reduce AASE or attrition among URMS and nonURMS attending health science community colleges on a broader scale; positively impacting costs, shortages, and diversity of health science professionals.^

Adaptive clinical trial design for targeted therapy development

The development of targeted therapy involve many challenges. Our study will address some of the key issues involved in biomarker identification and clinical trial design. In our study, we propose two biomarker selection methods, and then apply them in two different clinical trial designs for targeted therapy development. In particular, we propose a Bayesian two-step lasso procedure for biomarker selection in the proportional hazards model in Chapter 2. In the first step of this strategy, we use the Bayesian group lasso to identify the important marker groups, wherein each group contains the main effect of a single marker and its interactions with treatments. In the second step, we zoom in to select each individual marker and the interactions between markers and treatments in order to identify prognostic or predictive markers using the Bayesian adaptive lasso. In Chapter 3, we propose a Bayesian two-stage adaptive design for targeted therapy development while implementing the variable selection method given in Chapter 2. In Chapter 4, we proposed an alternate frequentist adaptive randomization strategy for situations where a large number of biomarkers need to be incorporated in the study design. We also propose a new adaptive randomization rule, which takes into account the variations associated with the point estimates of survival times. In all of our designs, we seek to identify the key markers that are either prognostic or predictive with respect to treatment. We are going to use extensive simulation to evaluate the operating characteristics of our methods.^

Targeted Deletion Of Functionally Validated Enhancers Defines Their Role in Mouse Limb Development

Transcriptional enhancers are genomic DNA sequences that contain clustered transcription factor (TF) binding sites. When combinations of TFs bind to enhancer sequences they act together with basal transcriptional machinery to regulate the timing, location and quantity of gene transcription. Elucidating the genetic mechanisms responsible for differential gene expression, including the role of enhancers, during embryological and postnatal development is essential to an understanding of evolutionary processes and disease etiology. Numerous methods are in use to identify and characterize enhancers. Several high-throughput methods generate large datasets of enhancer sequences with putative roles in embryonic development. However, few enhancers have been deleted from the genome to determine their roles in the development of specific structures, such as the limb. Manipulation of enhancers at their endogenous loci, such as the deletion of such elements, leads to a better understanding of the regulatory interactions, rules and complexities that contribute to faithful and variant gene transcription – the molecular genetic substrate of evolution and disease. To understand the endogenous roles of two distinct enhancers known to be active in the mouse embryo limb bud we deleted them from the mouse genome. I hypothesized that deletion of these enhancers would lead to aberrant limb development. The enhancers were selected because of their association with p300, a protein associated with active transcription, and because the human enhancer sequences drive distinct lacZ expression patterns in limb buds of embryonic day (E) 11.5 transgenic mice. To confirm that the orthologous mouse enhancers, mouse 280 and 1442 (M280 and M1442, respectively), regulate expression in the developing limb we generated stable transgenic lines, and examined lacZ expression. In M280-lacZ mice, expression was detected in E11.5 fore- and hindlimbs in a region that corresponds to digits II-IV. M1442-lacZ mice exhibited lacZ expression in posterior and anterior margins of the fore- and hindlimbs that overlapped with digits I and V and several wrist bones. We generated mice lacking the M280 and M1442 enhancers by gene targeting. Intercrosses between M280 -/+ and M1442 -/+, respectively, generated M280 and M1442 null mice, which are born at expected Mendelian ratios and manifest no gross limb malformations. Quantitative real-time PCR of mutant E11.5 limb buds indicated that significant changes in transcriptional output of enhancer-proximal genes accompanied the deletion of both M280 and M1442. In neonatal null mice we observed that all limb bones are present in their expected positions, an observation also confirmed by histology of E18.5 distal limbs. Fine-scale measurement of E18.5 digit bone lengths found no differences between mutant and control embryos. Furthermore, when the developmental progression of cartilaginous elements was analyzed in M280 and M1442 embryos from E13.5-E15.5, transient development defects were not detected. These results demonstrate that M280 and M1442 are not required for mouse limb development. Though M280 is not required for embryonic limb development it is required for the development and/or maintenance of body size – adult M280 mice are significantly smaller than control littermates. These studies highlight the importance of experiments that manipulate enhancers in situ to understand their contribution to development.

Functional analysis of SOX9 in chondrogenesis by targeted gene inactivation

Sox9 is a Sry-related HMG-domain containing transcription factor. Lines of evidence suggest that Sox9 has a potential role in skeletal development. During mouse development, Sox9 is predominantly expressed in all chondroprogenitors and differentiated chondrocytes, throughout the deposition of cartilage matrix. Mutations in one allele of SOX9 in humans result in campomelic dysplasia (CD), a skeletal dysplasia. syndrome characterized by the bowing of long bones. Moreover, Sox9 binds to and activates chondrocyte-specific enhancers in Col2a1 and Col11a2 genes. To further investigate the function of Sox9 in chondrogenesis, we analyzed chimeras derived from Sox9 heterozygous and homozygous null embryonic stem (ES) cells. In mouse chimeras, Sox9 −/− cells were excluded from all cartilages and did not express chondrocyte-specific genes. The segregation occurred during mesenchymal condensation. No cartilages developed in teratocarcinomas derived from Sox9 −/− ES cells. Mice heterozygous for the Sox9 mutation died neonatally and exhibited skeletal abnormalities resembling those of the CD patients. The Sox9 +/− mutants had a cleft palate and hypoplasia of scapula, pelvis and other skeletal structures derived by endochondral ossification. Bending of the radius, ulna and tibia cartilage was prominent at embryonic day 14.5 (E14.5). At E12.5 many pre-cartilaginous condensations were already defective. Advanced ossification was observed and the hypertrophic zone was enlarged in the growth plates, suggesting that Sox9 also regulates hypertrophic chondrocyte differentiation. Our results identify Sox9 as the first essential regulator of chondrocyte differentiation, which plays multiple roles in chondrogenesis. ^

Counting, scoring and classifying hunger to allocate resources targeted to solve the problem

A proper allocation of resources targeted to solve hunger is essential to optimize the efficacy of actions and maximize results. This requires an adequate measurement and formulation of the problem as, paraphrasing Einstein, the formulation of a problem is essential to reach a solution. Different measurement methods have been designed to count, score, classify and compare hunger at local level and to allow comparisons between different places. However, the alternative methods produce significantly reach different results. These discrepancies make decisions on the targeting of resource allocations difficult. To assist decision makers, a new method taking into account the dimension of hunger and the coping capacities of countries, is proposed enabling to establish both geographical and sectoral priorities for the allocation of resources.

Counting, scoring and classifying hunger to allocate resources targeted to solve the problem

A proper allocation of resources targeted to solve hunger is essential to optimize the efficacy of actions and maximize results. This requires an adequate measurement and formulation of the problem as, paraphrasing Einstein, the formulation of a problem is essential to reach a solution. Different measurement methods have been designed to count, score, classify and compare hunger at local level and to allow comparisons between different places. However, the alternative methods reach significantly different results. These discrepancies make decisions on the targeting of resource allocations difficult. To assist decision makers, a new method taking into account the dimension of hunger and the coping capacities of countries is proposed enabling to establish both geographical and sectoral priorities for the allocation of resources

Disruption of abscisic acid signaling constitutively activates Arabidopsis resistance to the necrotrophic fungus Plectosphaerella cucumerina.

Plant resistance to necrotrophic fungi is regulated by a complex set of signaling pathways that includes those mediated by the hormones salicylic acid (SA), ethylene (ET), jasmonic acid (JA), and abscisic acid (ABA). The role of ABA in plant resistance remains controversial, as positive and negative regulatory functions have been described depending on the plant-pathogen interaction analyzed. Here, we show that ABA signaling negatively regulates Arabidopsis (Arabidopsis thaliana) resistance to the necrotrophic fungus Plectosphaerella cucumerina. Arabidopsis plants impaired in ABA biosynthesis, such as the aba1-6 mutant, or in ABA signaling, like the quadruple pyr/pyl mutant (pyr1pyl1pyl2pyl4), were more resistant to P. cucumerina than wild-type plants. In contrast, the hab1-1abi1-2abi2-2 mutant impaired in three phosphatases that negatively regulate ABA signaling displayed an enhanced susceptibility phenotype to this fungus. Comparative transcriptomic analyses of aba1-6 and wild-type plants revealed that the ABA pathway negatively regulates defense genes, many of which are controlled by the SA, JA, or ET pathway. In line with these data, we found that aba1-6 resistance to P. cucumerina was partially compromised when the SA, JA, or ET pathway was disrupted in this mutant. Additionally, in the aba1-6 plants, some genes encoding cell wall-related proteins were misregulated. Fourier transform infrared spectroscopy and biochemical analyses of cell walls from aba1-6 and wild-type plants revealed significant differences in their Fourier transform infrared spectratypes and uronic acid and cellulose contents. All these data suggest that ABA signaling has a complex function in Arabidopsis basal resistance, negatively regulating SA/JA/ET-mediated resistance to necrotrophic fungi.

Simulator of the JET real-time disruption predictor

A disruption predictor based on support vector machines (SVM) has been developed to be used in JET. The training process uses thousands of discharges and, therefore, high performance computing has been necessary to obtain the models. To this respect, several models have been generated with data from different JET campaigns. In addition, various kernels (mainly linear and RBF) and parameters have been tested. The main objective of this work has been the implementation of the predictor model under real-time constraints. A “C-code” software application has been developed to simulate the real-time behavior of the predictor. The application reads the signals from the JET database and simulates the real-time data processing, in particular, the specific data hold method to be developed when reading data from the JET ATM real time network. The simulator is fully configurable by means of text files to select models, signal thresholds, sampling rates, etc. Results with data between campaigns C23and C28 will be shown.

Results of the JET real-time disruption predictor in the ITER-like wall campaigns

The impact of disruptions in JET became even more important with the replacement of the previous Carbon Fiber Composite (CFC) wall with a more fragile full metal ITER-like wall (ILW). The development of robust disruption mitigation systems is crucial for JET (and also for ITER). Moreover, a reliable real-time (RT) disruption predictor is a pre-requisite to any mitigation method. The Advance Predictor Of DISruptions (APODIS) has been installed in the JET Real-Time Data Network (RTDN) for the RT recognition of disruptions. The predictor operates with the new ILW but it has been trained only with discharges belonging to campaigns with the CFC wall. 7 realtime signals are used to characterize the plasma status (disruptive or non-disruptive) at regular intervals of 1 ms. After the first 3 JET ILW campaigns (991 discharges), the success rate of the predictor is 98.36% (alarms are triggered in average 426 ms before the disruptions). The false alarm and missed alarm rates are 0.92% and 1.64%.

Latest developments in data analysis tools for disruption prediction and for the exploration of multimachine operational spaces.

In the last years significant efforts have been devoted to the development of advanced data analysis tools to both predict the occurrence of disruptions and to investigate the operational spaces of devices, with the long term goal of advancing the understanding of the physics of these events and to prepare for ITER. On JET the latest generation of the disruption predictor called APODIS has been deployed in the real time network during the last campaigns with the new metallic wall. Even if it was trained only with discharges with the carbon wall, it has reached very good performance, with both missed alarms and false alarms in the order of a few percent (and strategies to improve the performance have already been identified). Since for the optimisation of the mitigation measures, predicting also the type of disruption is considered to be also very important, a new clustering method, based on the geodesic distance on a probabilistic manifold, has been developed. This technique allows automatic classification of an incoming disruption with a success rate of better than 85%. Various other manifold learning tools, particularly Principal Component Analysis and Self Organised Maps, are also producing very interesting results in the comparative analysis of JET and ASDEX Upgrade (AUG) operational spaces, on the route to developing predictors capable of extrapolating from one device to another.