10 resultados para Enzyme optimization

em Duke University


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BACKGROUND: Ganglioside biosynthesis occurs through a multi-enzymatic pathway which at the lactosylceramide step is branched into several biosynthetic series. Lc3 synthase utilizes a variety of galactose-terminated glycolipids as acceptors by establishing a glycosidic bond in the beta-1,3-linkage to GlcNaAc to extend the lacto- and neolacto-series gangliosides. In order to examine the lacto-series ganglioside functions in mice, we used gene knockout technology to generate Lc3 synthase gene B3gnt5-deficient mice by two different strategies and compared the phenotypes of the two null mouse groups with each other and with their wild-type counterparts. RESULTS: B3gnt5 gene knockout mutant mice appeared normal in the embryonic stage and, if they survived delivery, remained normal during early life. However, about 9% developed early-stage growth retardation, 11% died postnatally in less than 2 months, and adults tended to die in 5-15 months, demonstrating splenomegaly and notably enlarged lymph nodes. Without lacto-neolacto series gangliosides, both homozygous and heterozygous mice gradually displayed fur loss or obesity, and breeding mice demonstrated reproductive defects. Furthermore, B3gnt5 gene knockout disrupted the functional integrity of B cells, as manifested by a decrease in B-cell numbers in the spleen, germinal center disappearance, and less efficiency to proliferate in hybridoma fusion. CONCLUSIONS: These novel results demonstrate unequivocally that lacto-neolacto series gangliosides are essential to multiple physiological functions, especially the control of reproductive output, and spleen B-cell abnormality. We also report the generation of anti-IgG response against the lacto-series gangliosides 3'-isoLM1 and 3',6'-isoLD1.

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In this paper, we propose a framework for robust optimization that relaxes the standard notion of robustness by allowing the decision maker to vary the protection level in a smooth way across the uncertainty set. We apply our approach to the problem of maximizing the expected value of a payoff function when the underlying distribution is ambiguous and therefore robustness is relevant. Our primary objective is to develop this framework and relate it to the standard notion of robustness, which deals with only a single guarantee across one uncertainty set. First, we show that our approach connects closely to the theory of convex risk measures. We show that the complexity of this approach is equivalent to that of solving a small number of standard robust problems. We then investigate the conservatism benefits and downside probability guarantees implied by this approach and compare to the standard robust approach. Finally, we illustrate theme thodology on an asset allocation example consisting of historical market data over a 25-year investment horizon and find in every case we explore that relaxing standard robustness with soft robustness yields a seemingly favorable risk-return trade-off: each case results in a higher out-of-sample expected return for a relatively minor degradation of out-of-sample downside performance. © 2010 INFORMS.

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BACKGROUND AND PURPOSE: Previous studies have demonstrated that treatment strategy plays a critical role in ensuring maximum stone fragmentation during shockwave lithotripsy (SWL). We aimed to develop an optimal treatment strategy in SWL to produce maximum stone fragmentation. MATERIALS AND METHODS: Four treatment strategies were evaluated using an in-vitro experimental setup that mimics stone fragmentation in the renal pelvis. Spherical stone phantoms were exposed to 2100 shocks using the Siemens Modularis (electromagnetic) lithotripter. The treatment strategies included increasing output voltage with 100 shocks at 12.3 kV, 400 shocks at 14.8 kV, and 1600 shocks at 15.8 kV, and decreasing output voltage with 1600 shocks at 15.8 kV, 400 shocks at 14.8 kV, and 100 shocks at 12.3 kV. Both increasing and decreasing voltages models were run at a pulse repetition frequency (PRF) of 1 and 2 Hz. Fragmentation efficiency was determined using a sequential sieving method to isolate fragments less than 2 mm. A fiberoptic probe hydrophone was used to characterize the pressure waveforms at different output voltage and frequency settings. In addition, a high-speed camera was used to assess cavitation activity in the lithotripter field that was produced by different treatment strategies. RESULTS: The increasing output voltage strategy at 1 Hz PRF produced the best stone fragmentation efficiency. This result was significantly better than the decreasing voltage strategy at 1 Hz PFR (85.8% vs 80.8%, P=0.017) and over the same strategy at 2 Hz PRF (85.8% vs 79.59%, P=0.0078). CONCLUSIONS: A pretreatment dose of 100 low-voltage output shockwaves (SWs) at 60 SWs/min before increasing to a higher voltage output produces the best overall stone fragmentation in vitro. These findings could lead to increased fragmentation efficiency in vivo and higher success rates clinically.

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We have previously shown that second-messenger-dependent kinases (cAMP-dependent kinase, protein kinase C) in the olfactory system are essential in terminating second-messenger signaling in response to odorants. We now document that subtype 2 of the beta-adrenergic receptor kinase (beta ARK) is also involved in this process. By using subtype-specific antibodies to beta ARK-1 and beta ARK-2, we show that beta ARK-2 is preferentially expressed in the olfactory epithelium in contrast to findings in most other tissues. Heparin, an inhibitor of beta ARK, as well as anti-beta ARK-2 antibodies, (i) completely prevents the rapid decline of second-messenger signals (desensitization) that follows odorant stimulation and (ii) strongly inhibits odorant-induced phosphorylation of olfactory ciliary proteins. In contrast, beta ARK-1 antibodies are without effect. Inhibitors of protein kinase A and protein kinase C also block odorant-induced desensitization and phosphorylation. These data suggest that a sequential interplay of second-messenger-dependent and receptor-specific kinases is functionally involved in olfactory desensitization.

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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.

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Effective dosages for enzyme replacement therapy (ERT) in Pompe disease are much higher than for other lysosomal storage disorders, which has been attributed to low cation-independent mannose-6-phosphate receptor (CI-MPR) in skeletal muscle. We have previously demonstrated the benefit of increased CI-MPR-mediated uptake of recombinant human acid-α-glucosidase during ERT in mice with Pompe disease following addition of albuterol therapy. Currently we have completed a pilot study of albuterol in patients with late-onset Pompe disease already on ERT for >2 yr, who were not improving further. The 6-min walk test (6MWT) distance increased in all 7 subjects at wk 6 (30±13 m; P=0.002), wk 12 (34±14 m; P=0.004), and wk 24 (42±37 m; P=0.02), in comparison with baseline. Grip strength was improved significantly for both hands at wk 12. Furthermore, individual subjects reported benefits; e.g., a female patient could stand up from sitting on the floor much more easily (time for supine to standing position decreased from 30 to 11 s), and a male patient could readily swing his legs out of his van seat (hip abduction increased from 1 to 2+ on manual muscle testing). Finally, analysis of the quadriceps biopsies suggested increased CI-MPR at wk 12 (P=0.08), compared with baseline. With the exception of 1 patient who succumbed to respiratory complications of Pompe disease in the first week, only mild adverse events have been reported, including tremor, transient difficulty falling asleep, and mild urinary retention (requiring early morning voiding). Therefore, this pilot study revealed initial safety and efficacy in an open label study of adjunctive albuterol therapy in patients with late-onset Pompe disease who had been stable on ERT with no improvements noted over the previous several years.

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CONCLUSION Radiation dose reduction, while saving image quality could be easily implemented with this approach. Furthermore, the availability of a dosimetric data archive provides immediate feedbacks, related to the implemented optimization strategies. Background JCI Standards and European Legislation (EURATOM 59/2013) require the implementation of patient radiation protection programs in diagnostic radiology. Aim of this study is to demonstrate the possibility to reduce patients radiation exposure without decreasing image quality, through a multidisciplinary team (MT), which analyzes dosimetric data of diagnostic examinations. Evaluation Data from CT examinations performed with two different scanners (Siemens DefinitionTM and GE LightSpeed UltraTM) between November and December 2013 are considered. CT scanners are configured to automatically send images to DoseWatch© software, which is able to store output parameters (e.g. kVp, mAs, pitch ) and exposure data (e.g. CTDIvol, DLP, SSDE). Data are analyzed and discussed by a MT composed by Medical Physicists and Radiologists, to identify protocols which show critical dosimetric values, then suggest possible improvement actions to be implemented. Furthermore, the large amount of data available allows to monitor diagnostic protocols currently in use and to identify different statistic populations for each of them. Discussion We identified critical values of average CTDIvol for head and facial bones examinations (respectively 61.8 mGy, 151 scans; 61.6 mGy, 72 scans), performed with the GE LightSpeed CTTM. Statistic analysis allowed us to identify the presence of two different populations for head scan, one of which was only 10% of the total number of scans and corresponded to lower exposure values. The MT adopted this protocol as standard. Moreover, the constant output parameters monitoring allowed us to identify unusual values in facial bones exams, due to changes during maintenance service, which the team promptly suggested to correct. This resulted in a substantial dose saving in CTDIvol average values of approximately 15% and 50% for head and facial bones exams, respectively. Diagnostic image quality was deemed suitable for clinical use by radiologists.

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Few epidemiologic studies describe longitudinal liver chemistry (LC) elevations in cancer patients. A population-based retrospective cohort was identified from 31 Phase 2-3 oncology trials (excluding targeted therapies) conducted from 1985 to 2005 to evaluate background rates of LC elevations in patients (n = 3998) with or without liver metastases. Patients with baseline liver metastases (29% of patients) presented with a 3% prevalence of alanine transaminase (ALT) ≥ 3x upper limits normal (ULN) and 0.2% prevalence of bilirubin ≥ 3xULN. During follow-up, the incidence (per 1000 person-months) of new onset ALT elevations ≥3xULN was 6.1 (95% CI: 4.5, 8.0) and 2.2 (95% CI: 0.9, 4.5) in patients without and with liver metastases, respectively. No new incident cases of ALT and bilirubin elevations suggestive of severe liver injury occurred among those with liver metastases; a single case occurred among those without metastasis. Regardless of the presence of liver metastases, LC elevations were rare in cancer patients during oncology trials, which may be due to enrollment criteria. Our study validates uniform thresholds for detection of LC elevations in oncology studies and serves as an empirical referent point for comparing liver enzyme abnormalities in oncology trials of novel targeted therapies. These data support uniform LC stopping criteria in oncology trials.

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INTRODUCTION: Malignant gliomas frequently harbor mutations in the isocitrate dehydrogenase 1 (IDH1) gene. Studies suggest that IDH mutation contributes to tumor pathogenesis through mechanisms that are mediated by the neomorphic metabolite of the mutant IDH1 enzyme, 2-hydroxyglutarate (2-HG). The aim of this work was to synthesize and evaluate radiolabeled compounds that bind to the mutant IDH1 enzyme with the goal of enabling noninvasive imaging of mutant IDH1 expression in gliomas by positron emission tomography (PET). METHODS: A small library of nonradioactive analogs were designed and synthesized based on the chemical structure of reported butyl-phenyl sulfonamide inhibitors of mutant IDH1. Enzyme inhibition assays were conducted using purified mutant IDH1 enzyme, IDH1-R132H, to determine the IC50 and the maximal inhibitory efficiency of the synthesized compounds. Selected compounds, 1 and 4, were labeled with radioiodine ((125)I) and/or (18)F using bromo- and phenol precursors, respectively. In vivo behavior of the labeled inhibitors was studied by conducting tissue distribution studies with [(125)I]1 in normal mice. Cell uptake studies were conducted using an isogenic astrocytoma cell line that carried a native IDH1-R132H mutation to evaluate the potential uptake of the labeled inhibitors in IDH1-mutated tumor cells. RESULTS: Enzyme inhibition assays showed good inhibitory potency for compounds that have iodine or a fluoroethoxy substituent at the ortho position of the phenyl ring in compounds 1 and 4 with IC50 values of 1.7 μM and 2.3 μM, respectively. Compounds 1 and 4 inhibited mutant IDH1 activity and decreased the production of 2-HG in an IDH1-mutated astrocytoma cell line. Radiolabeling of 1 and 4 was achieved with an average radiochemical yield of 56.6 ± 20.1% for [(125)I]1 (n = 4) and 67.5 ± 6.6% for [(18)F]4 (n = 3). [(125)I]1 exhibited favorable biodistribution characteristics in normal mice, with rapid clearance from the blood and elimination via the hepatobiliary system by 4 h after injection. The uptake of [(125)I]1 in tumor cells positive for IDH1-R132H was significantly higher compared to isogenic WT-IDH1 controls, with a maximal uptake ratio of 1.67 at 3 h post injection. Co-incubation of the labeled inhibitors with the corresponding nonradioactive analogs, and decreasing the normal concentrations of FBS (10%) in the incubation media substantially increased the uptake of the labeled inhibitors in both the IDH1-mutant and WT-IDH1 tumor cell lines, suggesting significant non-specific binding of the synthesized labeled butyl-phenyl sulfonamide inhibitors. CONCLUSIONS: These data demonstrate the feasibility of developing radiolabeled probes for the mutant IDH1 enzyme based on enzyme inhibitors. Further optimization of the labeled inhibitors by modifying the chemical structure to decrease the lipophilicity and to increase potency may yield compounds with improved characteristics as probes for imaging mutant IDH1 expression in tumors.