Evaluation of polymeric nanomedicines targeted to PSMA: Effect of ligand on targeting efficiency

Targeted nanomedicines offer a strategy for greatly enhancing accumulation of a therapeutic within a specific tissue in animals. In this study, we report on the comparative targeting efficiency toward prostate-specific membrane antigen (PSMA) of a number of different ligands that are covalently attached by the same chemistry to a polymeric nanocarrier. The targeting ligands included a small molecule (glutamate urea), a peptide ligand, and a monoclonal antibody (J591). A hyperbranched polymer (HBP) was utilized as the nanocarrier and contained a fluorophore for tracking/analysis, whereas the pendant functional chain-ends provided a handle for ligand conjugation. Targeting efficiency of each ligand was assessed in vitro using flow cytometry and confocal microscopy to compare degree of binding and internalization of the HBPs by human prostate cancer (PCa) cell lines with different PSMA expression status (PC3-PIP (PSMA+) and PC3-FLU (PSMA−). The peptide ligand was further investigated in vivo, in which BALB/c nude mice bearing subcutaneous PC3-PIP and PC3-FLU PCa tumors were injected intravenously with the HBP-peptide conjugate and assessed by fluorescence imaging. Enhanced accumulation in the tumor tissue of PC3-PIP compared to PC3-FLU highlighted the applicability of this system as a future imaging and therapeutic delivery vehicle.

The impact of service failure on brand credibility

Recent studies have examined the consequences of brand credibility, with the majority of works embedded in physical goods. Despite the growing attention service branding receives, little is known about how service failure and recovery efforts impact on brand credibility in service organisations. The purpose of this study is to examine how brand credibility is affected by service failure and an organisations recovery efforts. An online self-completion survey of airline consumers (n=875) was employed to test the relationships between the focal constructs. The results show that a service firm’s effective complaint handling positively impacts satisfaction with complaining, overall satisfaction and service brand credibility. The study also finds that the higher the perceived magnitude of failure, the more difficult it is to satisfy a customer. These results demonstrate that it is possible to maintain service brand credibility during a service failure, provided brand managers develop and implement effective complain handling procedures.

Clinical application of biomarkers in prostate cancer in men with metabolic syndrome project: Prostate Specific Membrane Antigen (PSMA) Positron Emission Tomography (PET) in diagnosing localised prostate cancer

Localised prostate cancer is a heterogenous disease and a multi-modal approach is required to accurately diagnose and stage the disease. Whilst the use of magnetic resonance imaging (MRI) has become more common, small volume and multi-focal disease are oft en diffi cult to characterise. Prostate specifi c membrane antigen is a cell surface protein, which is expressed in nearly all prostate cancer cells. Its expression is signifi cantly higher in high grade prostate cancer cells. In this study, we compare multi-parametric magnetic resonance imaging and 68-Gallinium-PSMA PET with whole-mount pathology of the prostate to evaluate the applicability of multiparameteric (MP) MRI and 68Ga-PSMA PET in detecting and locating tumour foci in patients with localised prostate cancer.

Extracellular vesicles mediate paracrine signalling in androgen deprived prostate cancer

The androgen receptor (AR) is the main therapeutic target for advanced prostate cancer (PCa). Current treatments have focused on inhibiting the transcriptional activity of the AR, however androgens can also induce non-genomic effects by facilitating the initiation of kinase signaling cascades in PCa. Cells, including PCa, secrete extracellular vesicles (EV), which are able to mediate communication between cells and can also contribute towards these processes.

Targeting neuropilin-1 to inhibit prostate cancer invasion and metastasis

Recent reports provide evidence that the epithelial-to-mesenchymal transition (EMT) plays a key role in prostate cancer (PCa) metastasis and therapy resistance. We have recently identified the cell surface receptor, Neuropilin-1 (NRP1) to be increased during epithelial-mesenchymal transition (EMT) and this study aims to determine whether the inhibition of NRP1 will be a feasible therapeutic strategy for blocking PCa metastasis and therapy resistance.

Neck length and mean arterial pressure in the sauropod dinosaurs

How blood was able to reach the heads of the long-necked sauropod dinosaurs has long been a matter of debate and several hypotheses have been presented. For example, it has been proposed that sauropods had exceptionally large hearts, multiple ‘normal’ sized hearts spaced at regular intervals up the neck or held their necks horizontal, or that the siphon effect was in operation. By means of an experimental model, we demonstrate that the siphon principle is able to explain how blood was able to adequately perfuse the sauropod brain. The return venous circulation may have been protected from complete collapse by a structure akin to the vertebral venous plexus. We derive an equation relating neck height and mean arterial pressure, which indicates that with a mean arterial pressure similar to that of the giraffe, the maximum safe vertical distance between heart and head would have been about 12 m. A hypothesis is presented that the maximum neck length in the fossil record is due to the siphon height limit. The equation indicates that to migrate over high ground, sauropods would have had to either significantly increase their mean arterial pressure or keep their necks below a certain height dependent on altitude.

Automated Discovery of Structured Process Models: Discover Structured vs. Discover and Structure

This paper addresses the problem of discovering business process models from event logs. Existing approaches to this problem strike various tradeoffs between accuracy and understandability of the discovered models. With respect to the second criterion, empirical studies have shown that block-structured process models are generally more understandable and less error-prone than unstructured ones. Accordingly, several automated process discovery methods generate block-structured models by construction. These approaches however intertwine the concern of producing accurate models with that of ensuring their structuredness, sometimes sacrificing the former to ensure the latter. In this paper we propose an alternative approach that separates these two concerns. Instead of directly discovering a structured process model, we first apply a well-known heuristic technique that discovers more accurate but sometimes unstructured (and even unsound) process models, and then transform the resulting model into a structured one. An experimental evaluation shows that our “discover and structure” approach outperforms traditional “discover structured” approaches with respect to a range of accuracy and complexity measures.

Modeling and Forecasting Implied Volatility: Implications for Trading, Pricing, and Risk Management

Modeling and forecasting of implied volatility (IV) is important to both practitioners and academics, especially in trading, pricing, hedging, and risk management activities, all of which require an accurate volatility. However, it has become challenging since the 1987 stock market crash, as implied volatilities (IVs) recovered from stock index options present two patterns: volatility smirk(skew) and volatility term-structure, if the two are examined at the same time, presents a rich implied volatility surface (IVS). This implies that the assumptions behind the Black-Scholes (1973) model do not hold empirically, as asset prices are mostly influenced by many underlying risk factors. This thesis, consists of four essays, is modeling and forecasting implied volatility in the presence of options markets’ empirical regularities. The first essay is modeling the dynamics IVS, it extends the Dumas, Fleming and Whaley (DFW) (1998) framework; for instance, using moneyness in the implied forward price and OTM put-call options on the FTSE100 index, a nonlinear optimization is used to estimate different models and thereby produce rich, smooth IVSs. Here, the constant-volatility model fails to explain the variations in the rich IVS. Next, it is found that three factors can explain about 69-88% of the variance in the IVS. Of this, on average, 56% is explained by the level factor, 15% by the term-structure factor, and the additional 7% by the jump-fear factor. The second essay proposes a quantile regression model for modeling contemporaneous asymmetric return-volatility relationship, which is the generalization of Hibbert et al. (2008) model. The results show strong negative asymmetric return-volatility relationship at various quantiles of IV distributions, it is monotonically increasing when moving from the median quantile to the uppermost quantile (i.e., 95%); therefore, OLS underestimates this relationship at upper quantiles. Additionally, the asymmetric relationship is more pronounced with the smirk (skew) adjusted volatility index measure in comparison to the old volatility index measure. Nonetheless, the volatility indices are ranked in terms of asymmetric volatility as follows: VIX, VSTOXX, VDAX, and VXN. The third essay examines the information content of the new-VDAX volatility index to forecast daily Value-at-Risk (VaR) estimates and compares its VaR forecasts with the forecasts of the Filtered Historical Simulation and RiskMetrics. All daily VaR models are then backtested from 1992-2009 using unconditional, independence, conditional coverage, and quadratic-score tests. It is found that the VDAX subsumes almost all information required for the volatility of daily VaR forecasts for a portfolio of the DAX30 index; implied-VaR models outperform all other VaR models. The fourth essay models the risk factors driving the swaption IVs. It is found that three factors can explain 94-97% of the variation in each of the EUR, USD, and GBP swaption IVs. There are significant linkages across factors, and bi-directional causality is at work between the factors implied by EUR and USD swaption IVs. Furthermore, the factors implied by EUR and USD IVs respond to each others’ shocks; however, surprisingly, GBP does not affect them. Second, the string market model calibration results show it can efficiently reproduce (or forecast) the volatility surface for each of the swaptions markets.

Penetration of hydromagnetic energy deep into the magnetosphere

Magnetometer data, acquired on spacecraft and simultaneously at high and low latitudes on the ground, are compared in order to study the propagation characteristics of hydromagnetic energy deep into the magnetosphere. Single events provide evidence that wave energy at L ∼ 3 can at times be only one order of magnitude lower than at L ∼ 13. In addition, statistical analyses of the H-component groundbased data obtained during local daytime hours of 17 July-3 August 1985 show that wave amplitudes at L ∼ 3 are generally 10-30 times lower than at L ∼ 13. The L-dependence of near-equator magnetic field fluctuations measured on ISEE-2 show a sharp drop in energy near the magnetopause and a more gradual fall-off of energy deeper inside the magnetosphere. Such high levels of wave power deep in the magnetosphere have not been quantitatively understood previously. Our initial attempt is to calculate the decay length of an evanescent wave generated at a thick magnetopause boundary. Numerical calculations show that fast magnetosonic modes (called magnetopause and inner mode) can be generated under very restrictive conditions for the field and plasma parameters. These fast compressional modes may have their energy reduced by only one order of magnitude over a penetration depth of about 8RE. More realistic numerical simulations need to be carried out to see whether better agreement with the data can be attained.

Test of the Clustering Hypothesis in the Helsinki Exchanges

This paper investigates the clustering pattern in the Finnish stock market. Using trading volume and time as factors capturing the clustering pattern in the market, the Keim and Madhavan (1996) and the Engle and Russell (1998) model provide the framework for the analysis. The descriptive and the parametric analysis provide evidences that an important determinant of the famous U-shape pattern in the market is the rate of information arrivals as measured by large trading volumes and durations at the market open and close. Precisely, 1) the larger the trading volume, the greater the impact on prices both in the short and the long run, thus prices will differ across quantities. 2) Large trading volume is a non-linear function of price changes in the long run. 3) Arrival times are positively autocorrelated, indicating a clustering pattern and 4) Information arrivals as approximated by durations are negatively related to trading flow.

An Empirical Study of the Mixture of Time and Movements in Prices

This paper investigates the persistent pattern in the Helsinki Exchanges. The persistent pattern is analyzed using a time and a price approach. It is hypothesized that arrival times are related to movements in prices. Thus, the arrival times are defined as durations and formulated as an Autoregressive Conditional Duration (ACD) model as in Engle and Russell (1998). The prices are defined as price changes and formulated as a GARCH process including duration measures. The research question follows from market microstructure predictions about price intensities defined as time between price changes. The microstructure theory states that long transaction durations might be associated with both no news and bad news. Accordingly, short durations would be related to high volatility and long durations to low volatility. As a result, the spread will tend to be larger under intensive moments. The main findings of this study are 1) arrival times are positively autocorrelated and 2) long durations are associated with low volatility in the market.

Kymmenen koirarodun perinnöllinen monimuotoisuus

Tämän tutkimuksen tavoitteena oli selvittää koirarotujen sisäistä ja välistä perinnöllistä muuntelua ja populaatioiden rakenteita. Tutkimuksessa käytettiin Finnzymes Oy:ltä saatua koirien mikrosatelliittimerkkeihin perustuvaa genotyypitysaineistoa. Lopullisessa aineistossa oli 395 koiraa kymmenestä keskenään varsin erilaisesta rodusta. Koirien määrä rotua kohti vaihteli 31:stä 53:een. Tutkimuksessa käytettiin 18 mikrosatelliittilokusta. Alleelirikkaus vaihteli mikrosatelliittilokuksissa välillä 2,0 – 9,9. Kaikkein muuntelevin lokus oli AHT137 ja vähiten muunteleva AHTk211. Jackrussellinterrierin alleelirikkaus oli yli kaikkien lokusten tarkasteltuna suurinta ja cavalier kingcharlesinspanielin pienintä. Eniten Hardy-Weinbergin tasapainosta poikkeavia mikrosatelliittilokuksia oli schipperke- rodulla. Coton de tulearin, saksanpaimenkoiran ja suomenlapinkoiran kaikki mikrosatelliittilokukset olivat Hardy-Weinbergin tasapainossa. Cavalier kingcharlesinspanielin havaittu heterotsygotia-aste oli matalin kaikkien lokusten yli tarkasteltuna (0,50) ja suomenlapinkoiran korkein (0,73). Ainoat tilastollisesti merkitsevät FIS-arvot olivat schipperken lokuksessa INU030 (0,39) ja kaikkien lokusten yli tarkasteltuna (0,11). Eniten populaatioiden välisiin eroihin perustuvaa muuntelua oli cavalier kingcharlesinspanielin ja pitkäkarvaisen collien välillä (FST = 0,34) ja vähiten chihuahuan ja coton de tulearin välillä (FST = 0,07). Koko aineistossa noin 17,7 % populaatioiden välisestä geneettisestä muuntelusta johtui populaatioiden välisistä eroista. Rodut ovat tulosten perusteella selvästi erillisiä populaatioita. Coton de tulearin alleeliparit olivat selvästi eniten kytkentäepätasapainossa keskenään (94) ja tiibetinspanielin vähiten (15). Pitkäkarvaisen collien tehollinen populaatiokoko oli pienin (35) ja chihuahuan suurin (86). U seiden populaatiogeneettisten tunnuslukujen perusteella nousivat esiin cavalier kingcharlesinspanieli, pitkäkarvainen collie ja schipperke perinnöllisen muuntelun vähäisyyden perusteella ja chihuahua, jackrussellinterrieri ja suomenlapinkoira keskimääräistä suuremman perinnöllisen muuntelun perusteella. Selityksiä geneettisen monimuotoisuuden vaihteluun näillä roduilla löytyy rotujen historiasta.