Enhancement of cardiac function after adenoviral-mediated in vivo intracoronary beta2-adrenergic receptor gene delivery.

Exogenous gene delivery to alter the function of the heart is a potential novel therapeutic strategy for treatment of cardiovascular diseases such as heart failure (HF). Before gene therapy approaches to alter cardiac function can be realized, efficient and reproducible in vivo gene techniques must be established to efficiently transfer transgenes globally to the myocardium. We have been testing the hypothesis that genetic manipulation of the myocardial beta-adrenergic receptor (beta-AR) system, which is impaired in HF, can enhance cardiac function. We have delivered adenoviral transgenes, including the human beta2-AR (Adeno-beta2AR), to the myocardium of rabbits using an intracoronary approach. Catheter-mediated Adeno-beta2AR delivery produced diffuse multichamber myocardial expression, peaking 1 week after gene transfer. A total of 5 x 10(11) viral particles of Adeno-beta2AR reproducibly produced 5- to 10-fold beta-AR overexpression in the heart, which, at 7 and 21 days after delivery, resulted in increased in vivo hemodynamic function compared with control rabbits that received an empty adenovirus. Several physiological parameters, including dP/dtmax as a measure of contractility, were significantly enhanced basally and showed increased responsiveness to the beta-agonist isoproterenol. Our results demonstrate that global myocardial in vivo gene delivery is possible and that genetic manipulation of beta-AR density can result in enhanced cardiac performance. Thus, replacement of lost receptors seen in HF may represent novel inotropic therapy.

Real-Time and Data-Driven Operation Optimization and Knowledge Discovery for an Enterprise Information System

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.

Caring for Alaska Native prostate cancer survivors in primary care: a survey of Alaska Tribal Health System providers.

BACKGROUND: Little is known about the constraints of optimizing health care for prostate cancer survivors in Alaska primary care. OBJECTIVE: To describe the experiences and attitudes of primary care providers within the Alaska Tribal Health System (ATHS) regarding the care of prostate cancer survivors. DESIGN: In late October 2011, we emailed a 22-item electronic survey to 268 ATHS primary care providers regarding the frequency of Prostate Specific Antigen (PSA) monitoring for a hypothetical prostate cancer survivor; who should be responsible for the patient's life-long prostate cancer surveillance; who should support the patient's emotional and medical needs as a survivor; and providers' level of comfort addressing recurrence monitoring, erectile dysfunction, urinary incontinence, androgen deprivation therapy, and emotional needs. We used simple logistic regression to examine the association between provider characteristics and their responses to the survivorship survey items. RESULTS: Of 221 individuals who were successfully contacted, a total of 114 responded (52% response rate). Most ATHS providers indicated they would order a PSA test every 12 months (69%) and believed that, ideally, the hypothetical patient's primary care provider should be responsible for his life-long prostate cancer surveillance (60%). Most providers reported feeling either "moderately" or "very" comfortable addressing topics such as prostate cancer recurrence (59%), erectile dysfunction (64%), urinary incontinence (63%), and emotional needs (61%) with prostate cancer survivors. These results varied somewhat by provider characteristics including female sex, years in practice, and the number of prostate cancer survivors seen in their practice. CONCLUSIONS: These data suggest that most primary care providers in Alaska are poised to assume the care of prostate cancer survivors locally. However, we also found that large minorities of providers do not feel confident in their ability to manage common issues in prostate cancer survivorship, implying that continued access to specialists with more expert knowledge would be beneficial.

Delivery and Scavenging of Nucleic Acids by Polycationic Polymers

Electrostatic interaction is a strong force that attracts positively and negatively charged molecules to each other. Such an interaction is formed between positively charged polycationic polymers and negatively charged nucleic acids. In this dissertation, the electrostatic attraction between polycationic polymers and nucleic acids is exploited for applications in oral gene delivery and nucleic acid scavenging. An enhanced nanoparticle for oral gene delivery of a human Factor IX (hFIX) plasmid is developed using the polycationic polysaccharide, chitosan (Ch), in combination with protamine sulfate (PS) to treat hemophilia B. For nucleic acid scavenging purposes, the development of an effective nucleic acid scavenging nanofiber platform is described for dampening hyper-inflammation and reducing the formation of biofilms.

Non-viral gene therapy may be an attractive alternative to chronic protein replacement therapy. Orally administered non-viral gene vectors have been investigated for more than one decade with little progress made beyond the initial studies. Oral administration has many benefits over intravenous injection including patient compliance and overall cost; however, effective oral gene delivery systems remain elusive. To date, only chitosan carriers have demonstrated successful oral gene delivery due to chitosan’s stability via the oral route. In this study, we increase the transfection efficiency of the chitosan gene carrier by adding protamine sulfate to the nanoparticle formulation. The addition of protamine sulfate to the chitosan nanoparticles results in up to 42x higher in vitro transfection efficiency than chitosan nanoparticles without protamine sulfate. Therapeutic levels of hFIX protein are detected after oral delivery of Ch/PS/phFIX nanoparticles in 5/12 mice in vivo, ranging from 3 -132 ng/mL, as compared to levels below 4 ng/mL in 1/12 mice given Ch/phFIX nanoparticles. These results indicate the protamine sulfate enhances the transfection efficiency of chitosan and should be considered as an effective ternary component for applications in oral gene delivery.

Dying cells release nucleic acids (NA) and NA-complexes that activate the inflammatory pathways of immune cells. Sustained activation of these pathways contributes to chronic inflammation related to autoimmune diseases including systemic lupus erythematosus, rheumatoid arthritis, and inflammatory bowel disease. Studies have shown that certain soluble, cationic polymers can scavenge extracellular nucleic acids and inhibit RNA-and DNA-mediated activation of Toll-like receptors (TLRs) and inflammation. In this study, the cationic polymers are incorporated onto insoluble nanofibers, enabling local scavenging of negatively charged pro-inflammatory species such as damage-associated molecular pattern (DAMP) molecules in the extracellular space, reducing cytotoxicity related to unwanted internalization of soluble cationic polymers. In vitro data show that electrospun nanofibers grafted with cationic polymers, termed nucleic acid scavenging nanofibers (NASFs), can scavenge nucleic acid-based agonists of TLR 3 and TLR 9 directly from serum and prevent the production of NF-ĸB, an immune system activating transcription factor while also demonstrating low cytotoxicity. NASFs formed from poly (styrene-alt-maleic anhydride) conjugated with 1.8 kDa branched polyethylenimine (bPEI) resulted in randomly aligned fibers with diameters of 486±9 nm. NASFs effectively eliminate the immune stimulating response of NA based agonists CpG (TLR 9) and poly (I:C) (TLR 3) while not affecting the activation caused by the non-nucleic acid TLR agonist pam3CSK4. Results in a more biologically relevant context of doxorubicin-induced cell death in RAW cells demonstrates that NASFs block ~25-40% of NF-ĸβ response in Ramos-Blue cells treated with RAW extracellular debris, ie DAMPs, following doxorubicin treatment. Together, these data demonstrate that the formation of cationic NASFs by a simple, replicable, modular technique is effective and that such NASFs are capable of modulating localized inflammatory responses.

An understandable way to clinically apply the NASF is as a wound bandage. Chronic wounds are a serious clinical problem that is attributed to an extended period of inflammation as well as the presence of biofilms. An NASF bandage can potentially have two benefits in the treatment of chronic wounds by reducing the inflammation and preventing biofilm formation. NASF can prevent biofilm formation by reducing the NA present in the wound bed, therefore removing large components of what the bacteria use to develop their biofilm matrix, the extracellular polymeric substance, without which the biofilm cannot develop. The NASF described above is used to show the effect of the nucleic acid scavenging technology on in vitro and in vivo biofilm formation of P. aeruginosa, S. aureus, and S. epidermidis biofilms. The in vitro studies demonstrated that the NASFs were able to significantly reduce the biofilm formation in all three bacterial strains. In vivo studies of the NASF on mouse wounds infected with biofilm show that the NASF retain their functionality and are able to scavenge DNA, RNA, and protein from the wound bed. The NASF remove DNA that are maintaining the inflammatory state of the open wound and contributing to the extracellular polymeric substance (EPS), such as mtDNA, and also removing proteins that are required for bacteria/biofilm formation and maintenance such as chaperonin, ribosomal proteins, succinyl CoA-ligase, and polymerases. However, the NASF are not successful at decreasing the wound healing time because their repeated application and removal disrupts the wound bed and removes proteins required for wound healing such as fibronectin, vibronectin, keratin, and plasminogen. Further optimization of NASF treatment duration and potential combination treatments should be tested to reduce the unwanted side effects of increased wound healing time.

Biologically Inspired Design of Protein-Silica Hybrid Nanoparticles for Drug Delivery Applications

The design and application of effective drug carriers is a fundamental concern in the delivery of therapeutics for the treatment of cancer and other vexing health problems. Traditionally utilized chemotherapeutics are limited in efficacy due to poor bioavailability as a result of their size and solubility as well as significant deleterious effects to healthy tissue through their inability to preferentially target pathological cells and tissues, especially in treatment of cancer. Thus, a major effort in the development of nanoscopic drug delivery vehicles for cancer treatment has focused on exploiting the inherent differences in tumor physiology and limiting the exposure of drugs to non-tumorous tissue, which is commonly achieved by encapsulation of chemotherapeutics within macromolecular or supramolecular carriers that incorporate targeting ligands and that enable controlled release. The overall aim of this work is to engineer a hybrid nanomaterial system comprised of protein and silica and to characterize its potential as an encapsulating drug carrier. The synthesis of silica, an attractive nanomaterial component because it is both biocompatible as well as structurally and chemically stable, within this system is catalyzed by self-assembled elastin-like polypeptide (ELP) micelles that incorporate of a class of biologically-inspired, silica-promoting peptides, silaffins. Furthermore, this methodology produces near-monodisperse, hybrid inorganic/micellar materials under mild reaction conditions such as temperature, pH and solvent. This work studies this material system along three avenues: 1) proof-of-concept silicification (i.e. the formation and deposition of silica upon organic materials) of ELP micellar templates, 2) encapsulation and pH-triggered release of small, hydrophobic chemotherapeutics, and 3) selective silicification of templates to potentiate retention of peptide targeting ability.