20 resultados para Multiple Antigen Peptide System

em Duke University


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The generation of recombinant antibodies (Abs) using phage display is a proven method to obtain a large variety of Abs that bind with high affinity to a given antigen. Traditionally, the generation of single-chain Abs depends on the use of recombinant proteins in several stages of the procedure. This can be a problem, especially in the case of cell-surface receptors, because Abs generated and selected against recombinant proteins may not bind the same protein expressed on a cell surface in its native form and because the expression of some receptors as recombinant proteins is problematic. To overcome these difficulties, we developed a strategy to generate single-chain Abs that does not require the use of recombinant protein at any stage of the procedure. In this strategy, stably transfected cells are used for the immunization of mice, measuring Ab responses to immunization, panning the phage library, high-throughput screening of arrayed phage clones, and characterization of recombinant single-chain variable regions. This strategy was used to generate a panel of single-chain Abs specific for the innate immunity receptor Toll-like receptor 2. Once generated, individual single-chain variable regions were subcloned into an expression vector allowing the production of recombinant Abs in insect cells, thus avoiding the contamination of recombinant Abs with microbial products. This cell-based system efficiently generates Abs that bind to native molecules on the cell surface, bypasses the requirement of recombinant protein production, and avoids risks of microbial component contamination.

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We demonstrate a scalable approach to addressing multiple atomic qubits for use in quantum information processing. Individually trapped 87Rb atoms in a linear array are selectively manipulated with a single laser guided by a microelectromechanical beam steering system. Single qubit oscillations are shown on multiple sites at frequencies of ≃3.5 MHz with negligible crosstalk to neighboring sites. Switching times between the central atom and its closest neighbor were measured to be 6-7 μs while moving between the central atom and an atom two trap sites away took 10-14 μs. © 2010 American Institute of Physics.

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Systemic challenges within child welfare have prompted many states to explore new strategies aimed at protecting children while meeting the needs of families, but doing so within the confines of shrinking budgets. Differential Response has emerged as a promising practice for low or moderate risk cases of child maltreatment. This mixed methods evaluation explored various aspects of North Carolina's differential response system, known as the Multiple Response System (MRS), including: child safety, timeliness of response and case decision, frontloading of services, case distribution, implementation of Child and Family Teams, collaboration with community-based service providers and Shared Parenting. Utilizing Child Protective Services (CPS) administrative data, researchers found that compared to matched control counties, MRS: had a positive impact on child safety evidenced by a decline in the rates of substantiations and re-assessments; temporarily disrupted timeliness of response in pilot counties but had no effect on time to case decision; and increased the number of upfront services provided to families during assessment. Qualitative data collected through focus groups with providers and phone interviews with families provided important information on key MRS strategies, highlighting aspects that families and social workers like as well as identifying areas for improvement. This information is useful for continuous quality improvement efforts, particularly related to the development of training and technical assistance programs at the state and local level.

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BACKGROUND: Blocking leukocyte function-associated antigen (LFA)-1 in organ transplant recipients prolongs allograft survival. However, the precise mechanisms underlying the therapeutic potential of LFA-1 blockade in preventing chronic rejection are not fully elucidated. Cardiac allograft vasculopathy (CAV) is the preeminent cause of late cardiac allograft failure characterized histologically by concentric intimal hyperplasia. METHODS: Anti-LFA-1 monoclonal antibody was used in a multiple minor antigen-mismatched, BALB.B (H-2B) to C57BL/6 (H-2B), cardiac allograft model. Endogenous donor-specific CD8 T cells were tracked down using major histocompatibility complex multimers against the immunodominant H4, H7, H13, H28, and H60 minor Ags. RESULTS: The LFA-1 blockade prevented acute rejection and preserved palpable beating quality with reduced CD8 T-cell graft infiltration. Interestingly, less CD8 T cell infiltration was secondary to reduction of T-cell expansion rather than less trafficking. The LFA-1 blockade significantly suppressed the clonal expansion of minor histocompatibility antigen-specific CD8 T cells during the expansion and contraction phase. The CAV development was evaluated with morphometric analysis at postoperation day 100. The LFA-1 blockade profoundly attenuated neointimal hyperplasia (61.6 vs 23.8%; P < 0.05), CAV-affected vessel number (55.3 vs 15.9%; P < 0.05), and myocardial fibrosis (grade 3.29 vs 1.8; P < 0.05). Finally, short-term LFA-1 blockade promoted long-term donor-specific regulation, which resulted in attenuated transplant arteriosclerosis. CONCLUSIONS: Taken together, LFA-1 blockade inhibits initial endogenous alloreactive T-cell expansion and induces more regulation. Such a mechanism supports a pulse tolerance induction strategy with anti-LFA-1 rather than long-term treatment.

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Increasing atmospheric carbon dioxide (CO2) from anthropogenic sources is acidifying marine environments resulting in potentially dramatic consequences for the physical, chemical and biological functioning of these ecosystems. If current trends continue, mean ocean pH is expected to decrease by ~0.2 units over the next ~50 years. Yet, there is also substantial temporal variability in pH and other carbon system parameters in the ocean resulting in regions that already experience change that exceeds long-term projected trends in pH. This points to short-term dynamics as an important layer of complexity on top of long-term trends. Thus, in order to predict future climate change impacts, there is a critical need to characterize the natural range and dynamics of the marine carbonate system and the mechanisms responsible for observed variability. Here, we present pH and dissolved inorganic carbon (DIC) at time intervals spanning 1 hour to >1 year from a dynamic, coastal, temperate marine system (Beaufort Inlet, Beaufort NC USA) to characterize the carbonate system at multiple time scales. Daily and seasonal variation of the carbonate system is largely driven by temperature, alkalinity and the balance between primary production and respiration, but high frequency change (hours to days) is further influenced by water mass movement (e.g. tides) and stochastic events (e.g. storms). Both annual (~0.3 units) and diurnal (~0.1 units) variability in coastal ocean acidity are similar in magnitude to 50 year projections of ocean acidity associated with increasing atmospheric CO2. The environmental variables driving these changes highlight the importance of characterizing the complete carbonate system rather than just pH. Short-term dynamics of ocean carbon parameters may already exert significant pressure on some coastal marine ecosystems with implications for ecology, biogeochemistry and evolution and this shorter term variability layers additive effects and complexity, including extreme values, on top of long-term trends in ocean acidification.

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B cells mediate immune responses via the secretion of antibody and interactions with other immune cell populations through antigen presentation, costimulation, and cytokine secretion. Although B cells are primarily believed to promote immune responses using the mechanisms described above, some unique regulatory B cell populations that negatively influence inflammation have also been described. Among these is a rare interleukin (IL)-10-producing B lymphocyte subset termed “B10 cells.” B cell-derived IL-10 can inhibit various arms of the immune system, including polarization of Th1/Th2 cell subsets, antigen presentation and cytokine production by monocytes and macrophages, and activation of regulatory T cells. Further studies in numerous autoimmune and inflammatory models of disease have confirmed the ability of B10 cells to negatively regulate inflammation in an IL-10-dependent manner. Although IL-10 is indispensable to the effector functions of B10 cells, how this specialized B cell population is selected in vivo to produce IL-10 is unknown. Some studies have demonstrated a link between B cell receptor (BCR)-derived signals and the acquisition of IL-10 competence. Additionally, whether antigen-BCR interactions are required for B cell IL-10 production during homeostasis as well as active immune responses is a matter of debate. Therefore, the goal of this thesis is to determine the importance of antigen-driven signals during B10 cell development in vivo and during B10 cell-mediated immunosuppression.

Chapter 3 of the dissertation explored the BCR repertoire of spleen and peritoneal cavity B10 cells using single-cell sequencing to lay the foundation for studies to understand the full range of antigens that may be involved in B10 cell selection. In both the spleen and peritoneal cavity B10 cells studied, BCR gene utilization was diverse, and the expressed BCR transcripts were largely unmutated. Thus, B10 cells are likely capable of responding to a wide range of foreign and self-antigens in vivo.

Studies in Chapter 4 determined the predominant antigens that drive B cell IL-10 secretion during homeostasis. A novel in vitro B cell expansion system was used to isolate B cells actively expressing IL-10 in vivo and probe the reactivities of their secreted monoclonal antibodies. B10 cells were found to produce polyreactive antibodies that bound multiple self-antigens. Therefore, in the absence of overarching active immune responses, B cell IL-10 is secreted following interactions with self-antigens.

Chapter 5 of this dissertation investigated whether foreign antigens are capable of driving B10 cell expansion and effector activity during an active immune response. In a model of contact-induced hypersensitivity, in vitro B cell expansion was again used to isolate antigen-specific B10 clones, which were required for optimal immunosuppression.

The studies described in this dissertation shed light on the relative contributions of BCR-derived signals during B10 cell development and effector function. Furthermore, these investigations demonstrate that B10 cells respond to both foreign and self-antigens, which has important implications for the potential manipulation of B10 cells for human therapy. Therefore, B10 cells represent a polyreactive B cell population that provides antigen-specific regulation of immune responses via the production of IL-10.

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BACKGROUND: Sensor-augmented pump therapy (SAPT) integrates real-time continuous glucose monitoring (RT-CGM) with continuous subcutaneous insulin infusion (CSII) and offers an alternative to multiple daily injections (MDI). Previous studies provide evidence that SAPT may improve clinical outcomes among people with type 1 diabetes. Sensor-Augmented Pump Therapy for A1c Reduction (STAR) 3 is a multicenter randomized controlled trial comparing the efficacy of SAPT to that of MDI in subjects with type 1 diabetes. METHODS: Subjects were randomized to either continue with MDI or transition to SAPT for 1 year. Subjects in the MDI cohort were allowed to transition to SAPT for 6 months after completion of the study. SAPT subjects who completed the study were also allowed to continue for 6 months. The primary end point was the difference between treatment groups in change in hemoglobin A1c (HbA1c) percentage from baseline to 1 year of treatment. Secondary end points included percentage of subjects with HbA1c < or =7% and without severe hypoglycemia, as well as area under the curve of time spent in normal glycemic ranges. Tertiary end points include percentage of subjects with HbA1c < or =7%, key safety end points, user satisfaction, and responses on standardized assessments. RESULTS: A total of 495 subjects were enrolled, and the baseline characteristics similar between the SAPT and MDI groups. Study completion is anticipated in June 2010. CONCLUSIONS: Results of this randomized controlled trial should help establish whether an integrated RT-CGM and CSII system benefits patients with type 1 diabetes more than MDI.

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A recent quantum computing paper (G. S. Uhrig, Phys. Rev. Lett. 98, 100504 (2007)) analytically derived optimal pulse spacings for a multiple spin echo sequence designed to remove decoherence in a two-level system coupled to a bath. The spacings in what has been called a "Uhrig dynamic decoupling (UDD) sequence" differ dramatically from the conventional, equal pulse spacing of a Carr-Purcell-Meiboom-Gill (CPMG) multiple spin echo sequence. The UDD sequence was derived for a model that is unrelated to magnetic resonance, but was recently shown theoretically to be more general. Here we show that the UDD sequence has theoretical advantages for magnetic resonance imaging of structured materials such as tissue, where diffusion in compartmentalized and microstructured environments leads to fluctuating fields on a range of different time scales. We also show experimentally, both in excised tissue and in a live mouse tumor model, that optimal UDD sequences produce different T(2)-weighted contrast than do CPMG sequences with the same number of pulses and total delay, with substantial enhancements in most regions. This permits improved characterization of low-frequency spectral density functions in a wide range of applications.

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Alternative splicing is a general mechanism for regulating gene expression that affects the RNA products of more than 90% of human genes. Not surprisingly, alternative splicing is observed among gene products of metazoan immune systems, which have evolved to efficiently recognize pathogens and discriminate between "self" and "non-self", and thus need to be both diverse and flexible. In this review we focus on the specific interface between alternative splicing and autoimmune diseases, which result from a malfunctioning of the immune system and are characterized by the inappropriate reaction to self-antigens. Despite the widespread recognition of alternative splicing as one of the major regulators of gene expression, the connections between alternative splicing and autoimmunity have not been apparent. We summarize recent findings connecting splicing and autoimmune disease, and attempt to find common patterns of splicing regulation that may advance our understanding of autoimmune diseases and open new avenues for therapy.

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As many as 20-70% of patients undergoing breast conserving surgery require repeat surgeries due to a close or positive surgical margin diagnosed post-operatively [1]. Currently there are no widely accepted tools for intra-operative margin assessment which is a significant unmet clinical need. Our group has developed a first-generation optical visible spectral imaging platform to image the molecular composition of breast tumor margins and has tested it clinically in 48 patients in a previously published study [2]. The goal of this paper is to report on the performance metrics of the system and compare it to clinical criteria for intra-operative tumor margin assessment. The system was found to have an average signal to noise ratio (SNR) >100 and <15% error in the extraction of optical properties indicating that there is sufficient SNR to leverage the differences in optical properties between negative and close/positive margins. The probe had a sensing depth of 0.5-2.2 mm over the wavelength range of 450-600 nm which is consistent with the pathologic criterion for clear margins of 0-2 mm. There was <1% cross-talk between adjacent channels of the multi-channel probe which shows that multiple sites can be measured simultaneously with negligible cross-talk between adjacent sites. Lastly, the system and measurement procedure were found to be reproducible when evaluated with repeated measures, with a low coefficient of variation (<0.11). The only aspect of the system not optimized for intra-operative use was the imaging time. The manuscript includes a discussion of how the speed of the system can be improved to work within the time constraints of an intra-operative setting.

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Long term, high quality estimates of burned area are needed for improving both prognostic and diagnostic fire emissions models and for assessing feedbacks between fire and the climate system. We developed global, monthly burned area estimates aggregated to 0.5° spatial resolution for the time period July 1996 through mid-2009 using four satellite data sets. From 2001ĝ€ "2009, our primary data source was 500-m burned area maps produced using Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance imagery; more than 90% of the global area burned during this time period was mapped in this fashion. During times when the 500-m MODIS data were not available, we used a combination of local regression and regional regression trees developed over periods when burned area and Terra MODIS active fire data were available to indirectly estimate burned area. Cross-calibration with fire observations from the Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner (VIRS) and the Along-Track Scanning Radiometer (ATSR) allowed the data set to be extended prior to the MODIS era. With our data set we estimated that the global annual area burned for the years 1997ĝ€ "2008 varied between 330 and 431 Mha, with the maximum occurring in 1998. We compared our data set to the recent GFED2, L3JRC, GLOBCARBON, and MODIS MCD45A1 global burned area products and found substantial differences in many regions. Lastly, we assessed the interannual variability and long-term trends in global burned area over the past 13 years. This burned area time series serves as the basis for the third version of the Global Fire Emissions Database (GFED3) estimates of trace gas and aerosol emissions.

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Recently, we identified a GTPase-activating protein for the ADP ribosylation factor family of small GTP-binding proteins that we call GIT1. This protein initially was identified as an interacting partner for the G protein-coupled receptor kinases, and its overexpression was found to affect signaling and internalization of the prototypical beta(2)-adrenergic receptor. Here, we report that GIT1 overexpression regulates internalization of numerous, but not all, G protein-coupled receptors. The specificity of the GIT1 effect is not related to the type of G protein to which a receptor couples, but rather to the endocytic route it uses. GIT1 only affects the function of G protein-coupled receptors that are internalized through the clathrin-coated pit pathway in a beta-arrestin- and dynamin-sensitive manner. Furthermore, the GIT1 effect is not limited to G protein-coupled receptors because overexpression of this protein also affects internalization of the epidermal growth factor receptor. However, constitutive agonist-independent internalization is not regulated by GIT1, because transferrin uptake is not affected by GIT1 overexpression. Thus, GIT1 is a protein involved in regulating the function of signaling receptors internalized through the clathrin pathway and can be used as a diagnostic tool for defining the endocytic pathway of a receptor.

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Understanding immune tolerance mechanisms is a major goal of immunology research, but mechanistic studies have generally required the use of mouse models carrying untargeted or targeted antigen receptor transgenes, which distort lymphocyte development and therefore preclude analysis of a truly normal immune system. Here we demonstrate an advance in in vivo analysis of immune tolerance that overcomes these shortcomings. We show that custom superantigens generated by single chain antibody technology permit the study of tolerance in a normal, polyclonal immune system. In the present study we generated a membrane-tethered anti-Igkappa-reactive single chain antibody chimeric gene and expressed it as a transgene in mice. B cell tolerance was directly characterized in the transgenic mice and in radiation bone marrow chimeras in which ligand-bearing mice served as recipients of nontransgenic cells. We find that the ubiquitously expressed, Igkappa-reactive ligand induces efficient B cell tolerance primarily or exclusively by receptor editing. We also demonstrate the unique advantages of our model in the genetic and cellular analysis of immune tolerance.

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On-board image guidance, such as cone-beam CT (CBCT) and kV/MV 2D imaging, is essential in many radiation therapy procedures, such as intensity modulated radiotherapy (IMRT) and stereotactic body radiation therapy (SBRT). These imaging techniques provide predominantly anatomical information for treatment planning and target localization. Recently, studies have shown that treatment planning based on functional and molecular information about the tumor and surrounding tissue could potentially improve the effectiveness of radiation therapy. However, current on-board imaging systems are limited in their functional and molecular imaging capability. Single Photon Emission Computed Tomography (SPECT) is a candidate to achieve on-board functional and molecular imaging. Traditional SPECT systems typically take 20 minutes or more for a scan, which is too long for on-board imaging. A robotic multi-pinhole SPECT system was proposed in this dissertation to provide shorter imaging time by using a robotic arm to maneuver the multi-pinhole SPECT system around the patient in position for radiation therapy.

A 49-pinhole collimated SPECT detector and its shielding were designed and simulated in this work using the computer-aided design (CAD) software. The trajectories of robotic arm about the patient, treatment table and gantry in the radiation therapy room and several detector assemblies such as parallel holes, single pinhole and 49 pinholes collimated detector were investigated. The rail mounted system was designed to enable a full range of detector positions and orientations to various crucial treatment sites including head and torso, while avoiding collision with linear accelerator (LINAC), patient table and patient.

An alignment method was developed in this work to calibrate the on-board robotic SPECT to the LINAC coordinate frame and to the coordinate frames of other on-board imaging systems such as CBCT. This alignment method utilizes line sources and one pinhole projection of these line sources. The model consists of multiple alignment parameters which maps line sources in 3-dimensional (3D) space to their 2-dimensional (2D) projections on the SPECT detector. Computer-simulation studies and experimental evaluations were performed as a function of number of line sources, Radon transform accuracy, finite line-source width, intrinsic camera resolution, Poisson noise and acquisition geometry. In computer-simulation studies, when there was no error in determining angles (α) and offsets (ρ) of the measured projections, the six alignment parameters (3 translational and 3 rotational) were estimated perfectly using three line sources. When angles (α) and offsets (ρ) were provided by Radon transform, the estimation accuracy was reduced. The estimation error was associated with rounding errors of Radon transform, finite line-source width, Poisson noise, number of line sources, intrinsic camera resolution and detector acquisition geometry. The estimation accuracy was significantly improved by using 4 line sources rather than 3 and also by using thinner line-source projections (obtained by better intrinsic detector resolution). With 5 line sources, median errors were 0.2 mm for the detector translations, 0.7 mm for the detector radius of rotation, and less than 0.5° for detector rotation, tilt and twist. In experimental evaluations, average errors relative to a different, independent registration technique were about 1.8 mm for detector translations, 1.1 mm for the detector radius of rotation (ROR), 0.5° and 0.4° for detector rotation and tilt, respectively, and 1.2° for detector twist.

Simulation studies were performed to investigate the improvement of imaging sensitivity and accuracy of hot sphere localization for breast imaging of patients in prone position. A 3D XCAT phantom was simulated in the prone position with nine hot spheres of 10 mm diameter added in the left breast. A no-treatment-table case and two commercial prone breast boards, 7 and 24 cm thick, were simulated. Different pinhole focal lengths were assessed for root-mean-square-error (RMSE). The pinhole focal lengths resulting in the lowest RMSE values were 12 cm, 18 cm and 21 cm for no table, thin board, and thick board, respectively. In both no table and thin board cases, all 9 hot spheres were easily visualized above background with 4-minute scans utilizing the 49-pinhole SPECT system while seven of nine hot spheres were visible with the thick board. In comparison with parallel-hole system, our 49-pinhole system shows reduction in noise and bias under these simulation cases. These results correspond to smaller radii of rotation for no-table case and thinner prone board. Similarly, localization accuracy with the 49-pinhole system was significantly better than with the parallel-hole system for both the thin and thick prone boards. Median localization errors for the 49-pinhole system with the thin board were less than 3 mm for 5 of 9 hot spheres, and less than 6 mm for the other 4 hot spheres. Median localization errors of 49-pinhole system with the thick board were less than 4 mm for 5 of 9 hot spheres, and less than 8 mm for the other 4 hot spheres.

Besides prone breast imaging, respiratory-gated region-of-interest (ROI) imaging of lung tumor was also investigated. A simulation study was conducted on the potential of multi-pinhole, region-of-interest (ROI) SPECT to alleviate noise effects associated with respiratory-gated SPECT imaging of the thorax. Two 4D XCAT digital phantoms were constructed, with either a 10 mm or 20 mm diameter tumor added in the right lung. The maximum diaphragm motion was 2 cm (for 10 mm tumor) or 4 cm (for 20 mm tumor) in superior-inferior direction and 1.2 cm in anterior-posterior direction. Projections were simulated with a 4-minute acquisition time (40 seconds per each of 6 gates) using either the ROI SPECT system (49-pinhole) or reference single and dual conventional broad cross-section, parallel-hole collimated SPECT. The SPECT images were reconstructed using OSEM with up to 6 iterations. Images were evaluated as a function of gate by profiles, noise versus bias curves, and a numerical observer performing a forced-choice localization task. Even for the 20 mm tumor, the 49-pinhole imaging ROI was found sufficient to encompass fully usual clinical ranges of diaphragm motion. Averaged over the 6 gates, noise at iteration 6 of 49-pinhole ROI imaging (10.9 µCi/ml) was approximately comparable to noise at iteration 2 of the two dual and single parallel-hole, broad cross-section systems (12.4 µCi/ml and 13.8 µCi/ml, respectively). Corresponding biases were much lower for the 49-pinhole ROI system (3.8 µCi/ml), versus 6.2 µCi/ml and 6.5 µCi/ml for the dual and single parallel-hole systems, respectively. Median localization errors averaged over 6 gates, for the 10 mm and 20 mm tumors respectively, were 1.6 mm and 0.5 mm using the ROI imaging system and 6.6 mm and 2.3 mm using the dual parallel-hole, broad cross-section system. The results demonstrate substantially improved imaging via ROI methods. One important application may be gated imaging of patients in position for radiation therapy.

A robotic SPECT imaging system was constructed utilizing a gamma camera detector (Digirad 2020tc) and a robot (KUKA KR150-L110 robot). An imaging study was performed with a phantom (PET CT PhantomTM), which includes 5 spheres of 10, 13, 17, 22 and 28 mm in diameter. The phantom was placed on a flat-top couch. SPECT projections were acquired with a parallel-hole collimator and a single-pinhole collimator both without background in the phantom, and with background at 1/10th the sphere activity concentration. The imaging trajectories of parallel-hole and pinhole collimated detectors spanned 180 degrees and 228 degrees respectively. The pinhole detector viewed a 14.7 cm-diameter common volume which encompassed the 28 mm and 22 mm spheres. The common volume for parallel-hole was a 20.8-cm-diameter cylinder which encompassed all five spheres in the phantom. The maneuverability of the robotic system was tested by navigating the detector to trace the flat-top table while avoiding collision with the table and maintaining the closest possible proximity to the common volume. For image reconstruction, detector trajectories were described by radius-of-rotation and detector rotation angle θ. These reconstruction parameters were obtained from the robot base and tool coordinates. The robotic SPECT system was able to maneuver the parallel-hole and pinhole collimated SPECT detectors in close proximity to the phantom, minimizing impact of the flat-top couch on detector to center-of-rotation (COR) distance. In no background case, all five spheres were visible in the reconstructed parallel-hole and pinhole images. In with background case, three spheres of 17, 22 and 28 mm diameter were readily observed with the parallel-hole imaging, and the targeted spheres (22 and 28 mm diameter) were readily observed in the pinhole ROI imaging.

In conclusion, the proposed on-board robotic SPECT can be aligned to LINAC/CBCT with a single pinhole projection of the line-source phantom. Alignment parameters can be estimated using one pinhole projection of line sources. This alignment method may be important for multi-pinhole SPECT, where relative pinhole alignment may vary during rotation. For single pinhole and multi-pinhole SPECT imaging onboard radiation therapy machines, the method could provide alignment of SPECT coordinates with those of CBCT and the LINAC. In simulation studies of prone breast imaging and respiratory-gated lung imaging, the 49-pinhole detector showed better tumor contrast recovery and localization in a 4-minute scan compared to parallel-hole detector. On-board SPECT could be achieved by a robot maneuvering a SPECT detector about patients in position for radiation therapy on a flat-top couch. The robot inherent coordinate frames could be an effective means to estimate detector pose for use in SPECT image reconstruction.

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An enterprise information system (EIS) is an integrated data-applications platform characterized by diverse, heterogeneous, and distributed data sources. For many enterprises, a number of business processes still depend heavily on static rule-based methods and extensive human expertise. Enterprises are faced with the need for optimizing operation scheduling, improving resource utilization, discovering useful knowledge, and making data-driven decisions.

This thesis research is focused on real-time optimization and knowledge discovery that addresses workflow optimization, resource allocation, as well as data-driven predictions of process-execution times, order fulfillment, and enterprise service-level performance. In contrast to prior work on data analytics techniques for enterprise performance optimization, the emphasis here is on realizing scalable and real-time enterprise intelligence based on a combination of heterogeneous system simulation, combinatorial optimization, machine-learning algorithms, and statistical methods.

On-demand digital-print service is a representative enterprise requiring a powerful EIS.We use real-life data from Reischling Press, Inc. (RPI), a digit-print-service provider (PSP), to evaluate our optimization algorithms.

In order to handle the increase in volume and diversity of demands, we first present a high-performance, scalable, and real-time production scheduling algorithm for production automation based on an incremental genetic algorithm (IGA). The objective of this algorithm is to optimize the order dispatching sequence and balance resource utilization. Compared to prior work, this solution is scalable for a high volume of orders and it provides fast scheduling solutions for orders that require complex fulfillment procedures. Experimental results highlight its potential benefit in reducing production inefficiencies and enhancing the productivity of an enterprise.

We next discuss analysis and prediction of different attributes involved in hierarchical components of an enterprise. We start from a study of the fundamental processes related to real-time prediction. Our process-execution time and process status prediction models integrate statistical methods with machine-learning algorithms. In addition to improved prediction accuracy compared to stand-alone machine-learning algorithms, it also performs a probabilistic estimation of the predicted status. An order generally consists of multiple series and parallel processes. We next introduce an order-fulfillment prediction model that combines advantages of multiple classification models by incorporating flexible decision-integration mechanisms. Experimental results show that adopting due dates recommended by the model can significantly reduce enterprise late-delivery ratio. Finally, we investigate service-level attributes that reflect the overall performance of an enterprise. We analyze and decompose time-series data into different components according to their hierarchical periodic nature, perform correlation analysis,

and develop univariate prediction models for each component as well as multivariate models for correlated components. Predictions for the original time series are aggregated from the predictions of its components. In addition to a significant increase in mid-term prediction accuracy, this distributed modeling strategy also improves short-term time-series prediction accuracy.

In summary, this thesis research has led to a set of characterization, optimization, and prediction tools for an EIS to derive insightful knowledge from data and use them as guidance for production management. It is expected to provide solutions for enterprises to increase reconfigurability, accomplish more automated procedures, and obtain data-driven recommendations or effective decisions.