Prediction of individual genetic risk to prostate cancer using a polygenic score

BACKGROUND Polygenic risk scores comprising established susceptibility variants have shown to be informative classifiers for several complex diseases including prostate cancer. For prostate cancer it is unknown if inclusion of genetic markers that have so far not been associated with prostate cancer risk at a genome-wide significant level will improve disease prediction. METHODS We built polygenic risk scores in a large training set comprising over 25,000 individuals. Initially 65 established prostate cancer susceptibility variants were selected. After LD pruning additional variants were prioritized based on their association with prostate cancer. Six-fold cross validation was performed to assess genetic risk scores and optimize the number of additional variants to be included. The final model was evaluated in an independent study population including 1,370 cases and 1,239 controls. RESULTS The polygenic risk score with 65 established susceptibility variants provided an area under the curve (AUC) of 0.67. Adding an additional 68 novel variants significantly increased the AUC to 0.68 (P = 0.0012) and the net reclassification index with 0.21 (P = 8.5E-08). All novel variants were located in genomic regions established as associated with prostate cancer risk. CONCLUSIONS Inclusion of additional genetic variants from established prostate cancer susceptibility regions improves disease prediction. Prostate 75:1467–1474, 2015. © 2015 Wiley Periodicals, Inc.

Channelled porous TiO2 synthesized with a water-in-oil microemulsion

Porous titanium dioxide synthesized with a bicontinuous surfactant template is a promising method that leads to a high active surface area electrode. The template used is based on a water/isooctane/dioctyl sodium sulfosuccinate salt together with lecithin. Several parameters were varied during the synthesis to understand and optimize channel formation mechanisms. The material is patterned in stacked conical channels, widening towards the centre of the grains. The active surface area increased by 116% when the concentration of alkoxide precursors was decreased and increased by 241% when the template formation temperature was decreased to 10C. Increasing the oil phase viscosity tends to widen the pore aperture, thus decreasing the overall active surface area. Changing the phase proportions alters the microemulsion integrity and disrupts channel formation.

Design Optimization of Field Emission From A Stacked Carbon Nanotube Array

Fluctuation of field emission in carbon nanotubes (CNTs) is riot desirable in many applications and the design of biomedical x-ray devices is one of them. In these applications, it is of great importance to have precise control of electron beams over multiple spatio-temporal scales. In this paper, a new design is proposed in order to optimize the field emission performance of CNT arrays. A diode configuration is used for analysis, where arrays of CNTs act as cathode. The results indicate that the linear height distribution of CNTs, as proposed in this study, shows more stable performance than the conventionally used unifrom distribution.

Optimized Policies for the Retransmission Probabilities in Slotted Aloha

In this paper, we study the behaviour of the slotted Aloha multiple access scheme with a finite number of users under different traffic loads and optimize the retransmission probability q(r) for various settings, cost objectives and policies. First, we formulate the problem as a parameter optimization problem and use certain efficient smoothed functional algorithms for finding the optimal retransmission probability parameter. Next, we propose two classes of multi-level closed-loop feedback policies (for finding in each case the retransmission probability qr that now depends on the current system state) and apply the above algorithms for finding an optimal policy within each class of policies. While one of the policy classes depends on the number of backlogged nodes in the system, the other depends on the number of time slots since the last successful transmission. The latter policies are more realistic as it is difficult to keep track of the number of backlogged nodes at each instant. We investigate the effect of increasing the number of levels in the feedback policies. Wen also investigate the effects of using different cost functions (withn and without penalization) in our algorithms and the corresponding change in the throughput and delay using these. Both of our algorithms use two-timescale stochastic approximation. One of the algorithms uses one simulation while the other uses two simulations of the system. The two-simulation algorithm is seen to perform better than the other algorithm. Optimal multi-level closed-loop policies are seen to perform better than optimal open-loop policies. The performance further improves when more levels are used in the feedback policies.

Splitting Algorithms for Fast Relay Selection: Generalizations, Analysis, and a Unified View

Relay selection for cooperative communications promises significant performance improvements, and is, therefore, attracting considerable attention. While several criteria have been proposed for selecting one or more relays, distributed mechanisms that perform the selection have received relatively less attention. In this paper, we develop a novel, yet simple, asymptotic analysis of a splitting-based multiple access selection algorithm to find the single best relay. The analysis leads to simpler and alternate expressions for the average number of slots required to find the best user. By introducing a new contention load' parameter, the analysis shows that the parameter settings used in the existing literature can be improved upon. New and simple bounds are also derived. Furthermore, we propose a new algorithm that addresses the general problem of selecting the best Q >= 1 relays, and analyze and optimize it. Even for a large number of relays, the scalable algorithm selects the best two relays within 4.406 slots and the best three within 6.491 slots, on average. We also propose a new and simple scheme for the practically relevant case of discrete metrics. Altogether, our results develop a unifying perspective about the general problem of distributed selection in cooperative systems and several other multi-node systems.

A genetic algorithm with characteristic amplification through multiple geographically isolated populations and varied fitness landscapes

This paper proposes a new approach, wherein multiple populations are evolved on different landscapes. The problem statement is broken down, to describe discrete characteristics. Each landscape, described by its fitness landscape is used to optimize or amplify a certain characteristic or set of characteristics. Individuals from each of these populations are kept geographically isolated from each other Each population is evolved individually. After a predetermined number of evolutions, the system of populations is analysed against a normalized fitness function. Depending on this score and a predefined merging scheme, the populations are merged, one at a time, while continuing evolution. Merging continues until only one final population remains. This population is then evolved, following which the resulting population will contain the optimal solution. The final resulting population will contain individuals which have been optimized against all characteristics as desired by the problem statement. Each individual population is optimized for a local maxima. Thus when populations are merged, the effect is to produce a new population which is closer to the global maxima.

A genetic algorithm with characteristic amplification through multiple geographically isolated populations and varied fitness landscapes

This paper proposes a new approach, wherein multiple populations are evolved on different landscapes. The problem statement is broken down, to describe discrete characteristics. Each landscape, described by its fitness landscape is used to optimize or amplify a certain characteristic or set of characteristics. Individuals from each of these populations are kept geographically isolated from each other Each population is evolved individually. After a predetermined number of evolutions, the system of populations is analysed against a normalized fitness function. Depending on this score and a predefined merging scheme, the populations are merged, one at a time, while continuing evolution. Merging continues until only one final population remains. This population is then evolved, following which the resulting population will contain the optimal solution. The final resulting population will contain individuals which have been optimized against all characteristics as desired by the problem statement. Each individual population is optimized for a local maxima. Thus when populations are merged, the effect is to produce a new population which is closer to the global maxima.

Vector Evaluated Particle Swarm Optimization (VEPSO) of Supersonic Ejector for Hydrogen Fuel Cells

Fuel cells are emerging as alternate green power producers for both large power production and for use in automobiles. Hydrogen is seen as the best option as a fuel; however, hydrogen fuel cells require recirculation of unspent hydrogen. A supersonic ejector is an apt device for recirculation in the operating regimes of a hydrogen fuel cell. Optimal ejectors have to be designed to achieve best performances. The use of the vector evaluated particle swarm optimization technique to optimize supersonic ejectors with a focus on its application for hydrogen recirculation in fuel cells is presented here. Two parameters, compression ratio and efficiency, have been identified as the objective functions to be optimized. Their relation to operating and design parameters of ejector is obtained by control volume based analysis using a constant area mixing approximation. The independent parameters considered are the area ratio and the exit Mach number of the nozzle. The optimization is carried out at a particularentrainment ratio and results in a set of nondominated solutions, the Pareto front. A set of such curves can be used for choosing the optimal design parameters of the ejector.

Two ex situ fungal technologies to treat contaminated soil

Wood-degrading fungi are able to degrade a large range of recalcitrant pollutants which resemble the lignin biopolymer. This ability is attributed to the production of lignin-modifying enzymes, which are extracellular and non-specific. Despite the potential of fungi in bioremediation, there is still an understanding gap in terms of the technology. In this thesis, the feasibility of two ex situ fungal bioremediation methods to treat contaminated soil was evaluated. Treatment of polycyclic aromatic hydrocarbons (PAHs)-contaminated marsh soil was studied in a stirred slurry-phase reactor. Due to the salt content in marsh soil, fungi were screened for their halotolerance, and the white-rot fungi Lentinus tigrinus, Irpex lacteus and Bjerkandera adusta were selected for further studies. These fungi degraded 40 - 60% of a PAH mixture (phenanthrene, fluoranthene, pyrene and chrysene) in a slurry-phase reactor (100 ml) during 30 days of incubation. Thereafter, B. adusta was selected to scale-up and optimize the process in a 5 L reactor. Maximum degradation of dibenzothiophene (93%), fluoranthene (82%), pyrene (81%) and chrysene (83%) was achieved with the free mycelium inoculum of the highest initial biomass (2.2 g/l). In autoclaved soil, MnP was the most important enzyme involved in PAH degradation. In non-sterile soil, endogenous soil microbes together with B. adusta also degraded the PAHs extensively, suggesting a synergic action between soil microbes and the fungus. A fungal solid-phase cultivation method to pretreat contaminated sawmill soil with high organic matter content was developed to enhance the effectiveness of the subsequent soil combustion. In a preliminary screening of 146 fungal strains, 28 out of 52 fungi, which extensively colonized non-sterile contaminated soil, were litter-decomposing fungi. The 18 strains further selected were characterized by their production of lignin-modifying and hydrolytic enzymes, of which MnP and endo-1,4-β-glucanase were the main enzymes during cultivation on Scots pine (Pinus sylvestris) bark. Of the six fungi selected for further tests, Gymnopilus luteofolius, Phanerochaete velutina, and Stropharia rugosoannulata were the most active soil organic matter degraders. The results showed that a six-month pretreatment of sawmill soil would result in a 3.5 - 9.5% loss of organic matter, depending on the fungus applied. The pretreatment process was scaled-up for a 0.56 m3 reactor, in which perforated plastic tubes filled with S. rugosoannulata growing on pine bark were introduced into the soil. The fungal pretreatment resulted in a soil mass loss of 30.5 kg, which represents 10% of the original soil mass (308 kg). Despite the fact that Scots pine bark contains several antimicrobial compounds, it was a suitable substrate for fungal growth and promoter of the production of oxidative enzymes, as well as an excellent and cheap natural carrier of fungal mycelium. This thesis successfully developed two novel fungal ex situ bioremediation technologies and introduce new insights for their further full-scale application. Ex situ slurry-phase fungal reactors might be applied in cases when the soil has a high water content or when the contaminant bioavailability is low; for example, in wastewater treatment plants to remove pharmaceutical residues. Fungal solid-phase bioremediation is a promising remediation technology to ex situ or in situ treat contaminated soil.

Updated search for the flavor-changing neutral-current decay D0→μ+μ- in pp̅ collisions at √s=1.96 TeV

We report on a search for the flavor-changing neutral-current decay D0 \to {\mu}+ {\mu}- in pp collisions at \surd s = 1.96 TeV using 360 pb-1 of integrated luminosity collected by the CDF II detector at the Fermilab Tevatron collider. A displaced vertex trigger selects long-lived D0 candidates in the {\mu}+ {\mu}-, {\pi}+{\pi}-, and K-{\pi}+ decay modes. We use the Cabibbo-favored D0 \to K-{\pi}+ channel to optimize the selection criteria in an unbiased manner, and the kinematically similar D0 \to{\pi}+ {\pi}- channel for normalization. We set an upper limit on the branching fraction (D0 --> {\mu}+ {\mu}-)

Adhesion of Acidithiobacillus ferrooxidans to mineral surfaces

Direct contact mechanism in bioleaching implies prior mineral adhesion of Acidithiobacillus ferrooxidans and subsequent enzymatic attack.Prior bacterial adaptation to sulfide mineral substrates influences bacterial ferrous ion oxidation rates. It is highly beneficial to understand major biooxidation mechanisms with reference to solution- and mineral-grown cells in order to optimize bioleaching reactions. For A. ferrooxidans grown in the presence of solid substrates such as sulfur, pyrite and chalcopyrite, bacterial adhesion is required for its enzymatic machinery to come into close contact for mineral dissolution.But when grown in solution substrate such as ferrous ions and thiosulfate, such an adhesion machinery is not required for substrate utilization. Proteinaceous compounds were observed on the surface of sulfur-grown cells. Such an induction of relatively hydrophobic proteins and down regulation of exposed polysaccharides leads to changes in cell surface chemistry. Sulfur-grown and pyrite- and chalcopyrite-grown bacterial cells were found to be more efficient in the bioleaching of chalcopyrite than those grown in the presence of ferrous ions and thiosulfate. (C) 2010 Elsevier B.V. All rights reserved.

Kirjallisuuskatsaus: Eturauhassyövän androgeeniresponsiiviset in vivo -mallit; Kokeellinen osa: Bioluminesenssiin perustuvan ortotooppisen eturauhassyöpämallin optimointi

Eturauhassyöpä on yksi yleisimmistä syövistä länsimaissa. Eturauhassyöpä on yleensä hitaasti kehittyvä tauti. Edetessään se voi kuitenkin muuntua aggressiivisemmaksi ja aiheuttaa metastaaseja, jotka ovat pääasiallisena syynä taudin kuolleisuuteen. Androgeenit ovat merkittäviä tekijöitä eturauhassyövän patogeneesissä ja eturauhassyöpäkudos on useimmiten riippuvainen androgeeneista. Tämän vuoksi hoidon tavoitteena on estää niiden eritys kirurgisella tai kemiallisella kastraatiolla ja/tai estää androgeenien vaikutus antiandrogeeneilla. Eturauhassyöpää sekä sen hoitoon tarkoitettuja uusia lääkehoitomahdollisuuksia tutkitaan kiivaasti. Eturauhassyövän tutkimiseen on kehitetty lukematon määrä erilaisia in vivo -malleja. Koska eturauhassyöpä on yleensä androgeeneille herkkä, kuvaavat androgeeniresponsiiviset eläinmallit ihmisen tautia parhaiten. Eturauhassyövän mallintamiseen in vivo voidaan käyttää eri eläinlajeja, mutta hiiri on ylivoimaisesti käytetyin mallieläin. Immuunipuutteisiin hiiriin voidaan aiheuttaa kasvaimia inokuloimalla ihmisen kasvainsoluja tai osia ihmisen kasvaimista. Ortotooppisesti eturauhaseen inokuloitavat kasvainmallit mallintavat eturauhassyövässä esiintyvää syöpäsolujen ja stroomasolujen välistä epänormaalia vuorovaikutusta. Muuntogeeniset hiirimallit ovat yhä yleisempiä eturauhassyövän tutkimuksessa. Muuntogeenisilla malleilla voidaan mallintaa taudin kehittymistä ja sen etenemistä kokonaisuudessaan parhaiten. Eturauhasessa olevaa kasvainta ja sen kasvua on vaikea seurata ilman prostataspesifisen antigeenin (PSA) pitoisuuden mittausta tai erityisiä kuvantamistekniikoita. Tällaisia menetelmiä, kuten optista kuvantamista, käytetään yhä enemmän hyödyksi erilaisissa eturauhassyövän in vivo -malleissa. Tutkielman kokeellisen osan tavoitteena oli optimoida bioluminesenssiin perustuva optinen kuvantamismenetelmä androgeeniresponsiivisessa LNCaP-luc2-solulinjassa ortotooppisessa eturauhassyöpämallissa. Bioluminesenssikuvantaminen perustuu kasvainsolujen ilmentämän lusiferaasin katalysoimaan reaktioon, jossa entsyymin substraatti, lusiferiini, hapettuu ja tuottaa näkyvää valoa. Lisäksi tavoitteena oli tutkia lääkehoitojen ja kastraation vasteita mallissa. Bioluminesenssiin perustuvalla kuvantamisella oli mahdollista seurata eturauhaskasvainten kasvua noninvasiivisesti, reaaliaikaisesti ja toistuvasti. Bioluminesenssikuvantamisen avulla kasvainten kvantitointi oli nopeampaa kuin ultraäänikuvantamisen avulla, ja kasvainten kasvua oli myös mahdollista seurata useammin kuin seerumin PSA-mittausten avulla. Bioluminesenssikuvantamisen todettiin korreloivan paremmin PSA-pitoisuuden kanssa kuin kasvaimen todelliseen kokoon lopetushetkellä. Seerumin PSA-pitoisuus korreloi kuitenkin bioluminesenssimittausta paremmin eturauhaskasvaimen kokoon tässä kokeessa. Kasvainten oletettua suurempaa kokoa voidaan pitää todennäköisimpänä syynä sille, ettei lääkehoitojen tai kastraation todettu vaikuttavan kasvainten kasvuun bioluminesenssikuvantamisella mitattuna. Bioluminesenssikuvantaminen ei sovellu suurille eikä nekroottisille kasvaimille, sillä kuvantamismenetelmä toimii vain elävillä soluilla. Bioluminesenssikuvantamisen hyödyntämisen kannalta oleellista tässä mallissa on myös lusiferiini-injektion onnistuminen. Jatkotutkimuksia tarvitaan edelleen mallin validoimiseksi mm. lääkehoitojen vasteiden osoittamiseksi.

A four-timescale algorithm for constrained stochastic optimization of RED

The overall performance of random early detection (RED) routers in the Internet is determined by the settings of their associated parameters. The non-availability of a functional relationship between the RED performance and its parameters makes it difficult to implement optimization techniques directly in order to optimize the RED parameters. In this paper, we formulate a generic optimization framework using a stochastically bounded delay metric to dynamically adapt the RED parameters. The constrained optimization problem thus formulated is solved using traditional nonlinear programming techniques. Here, we implement the barrier and penalty function approaches, respectively. We adopt a second-order nonlinear optimization framework and propose a novel four-timescale stochastic approximation algorithm to estimate the gradient and Hessian of the barrier and penalty objectives and update the RED parameters. A convergence analysis of the proposed algorithm is briefly sketched. We perform simulations to evaluate the performance of our algorithm with both barrier and penalty objectives and compare these with RED and a variant of it in the literature. We observe an improvement in performance using our proposed algorithm over RED, and the above variant of it.

Customer asset management in action: using customers portfolio for allocating resources across business-to-business relationships for improved shareholder value

Suvi Nenonen Customer asset management in action: using customer portfolios for allocating resources across business-to-business relationships for improved shareholder value Customers are crucial assets to all firms as customers are the ultimate source of all cash flows. Regardless this financial importance of customer relationships, for decades there has been a lack of suitable frameworks explaining how customer relationships contribute to the firm financial performance and how this contribution can be actively managed. In order to facilitate a better understanding of the customer asset, contemporary marketing has investigated the use of financial theories and asset management practices in the customer relationship context. Building on this, marketing academics have promoted the customer lifetime value concept as a solution for valuating and managing customer relationships for optimal financial outcomes. However, the empirical investigation of customer asset management lags behind the conceptual development steps taken. Additionally, the practitioners have not embraced the use of customer lifetime value in guiding managerial decisions - especially in the business-to-business context. The thesis points out that there are fundamental differences between customer relationships and investment instruments as investment targets, effectively eliminating the possibility to use financial theories in a customer relationships context or to optimize the customer base as a single investment portfolio. As an alternative, the thesis proposes the use of customer portfolio approach for allocating resources across the customer base for improved shareholder value. In the customer portfolio approach, the customer base of a firm is divided into multiple portfolios based on customer relationships’ potential to contribute to the shareholder value creation. After this, customer management concepts are tailored to each customer portfolio, designed to improve the shareholder value in their own respect. Therefore, effective customer asset management with the customer portfolio approach necessitates that firms are able to manage multiple parallel customer management concepts, or business models, simultaneously. The thesis is one of the first empirical studies on customer asset management, bringing empirical evidence from multiple business-to-business case studies on how customer portfolio models can be formed, how customer portfolios can be managed, and how customer asset management has contributed to the firm financial performance.

Customer asset management in action: using customers portfolio for allocating resources across business-to-business relationships for improved shareholder value

Suvi Nenonen Customer asset management in action: using customer portfolios for allocating resources across business-to-business relationships for improved shareholder value Customers are crucial assets to all firms as customers are the ultimate source of all cash flows. Regardless this financial importance of customer relationships, for decades there has been a lack of suitable frameworks explaining how customer relationships contribute to the firm financial performance and how this contribution can be actively managed. In order to facilitate a better understanding of the customer asset, contemporary marketing has investigated the use of financial theories and asset management practices in the customer relationship context. Building on this, marketing academics have promoted the customer lifetime value concept as a solution for valuating and managing customer relationships for optimal financial outcomes. However, the empirical investigation of customer asset management lags behind the conceptual development steps taken. Additionally, the practitioners have not embraced the use of customer lifetime value in guiding managerial decisions - especially in the business-to-business context. The thesis points out that there are fundamental differences between customer relationships and investment instruments as investment targets, effectively eliminating the possibility to use financial theories in a customer relationships context or to optimize the customer base as a single investment portfolio. As an alternative, the thesis proposes the use of customer portfolio approach for allocating resources across the customer base for improved shareholder value. In the customer portfolio approach, the customer base of a firm is divided into multiple portfolios based on customer relationships’ potential to contribute to the shareholder value creation. After this, customer management concepts are tailored to each customer portfolio, designed to improve the shareholder value in their own respect. Therefore, effective customer asset management with the customer portfolio approach necessitates that firms are able to manage multiple parallel customer management concepts, or business models, simultaneously. The thesis is one of the first empirical studies on customer asset management, bringing empirical evidence from multiple business-to-business case studies on how customer portfolio models can be formed, how customer portfolios can be managed, and how customer asset management has contributed to the firm financial performance.