Rare genetic variant burden in DPYD predicts severe fluoropyrimidine-related toxicity risk

Preemptive targeted pharmacogenetic testing of candidate variations in DPYD is currently being used to limit toxicity associated with fluoropyrimidines. The use of innovative next generation sequencing (NGS) approaches could unveil additional rare (minor allele frequency <1%) genetic risk variants. However, their predictive value and management in clinical practice are still controversial, at least partly due to the challenges associated with functional analyses of rare variants. The aim of this study was to define the predictive power of rare DPYD variants burden on the risk of severe fluoropyrimidine-related toxicity. The DPYD coding sequence and untranslated regions were analyzed by NGS in 120 patients developing grade 3–5 (NCI-CTC vs3.0) fluoropyrimidine-related toxicity and 104 matched controls (no-toxicity). The functional impact of rare variants was assessed using two different in silico predictive tools (i.e., Predict2SNP and ADME Prediction Framework) and structural modeling. Plasma concentrations of uracil (U) and dihydrouracil (UH2) were quantified in carriers of the novel variants. Here, we demonstrate that the burden of rare variants was significantly higher in patients with toxicity compared to controls (p = 0.007, Mann-Whitney test). Carriers of at least one rare missense DPYD variant had a 16-fold increased risk in the first cycle and an 11-fold increased risk during the entire course of chemotherapy of developing a severe adverse event compared to controls (p = 0.013 and p = 0.0250, respectively by multinomial regression model). Quantification of plasmatic U/UH2 metabolites and in silico visualization of the encoded protein were consistent with the predicted functional effect for the novel variations. Analysis and consideration of rare variants by DPYD-sequencing could improve prevention of severe toxicity of fluoropyrimidines and improve patients’ quality of life

Applications of Genetic Programming to Finance and Economics: Past, Present, Future

While the origins of Genetic Programming (GP) stretch back over fifty years, the field of GP was invigorated by John Koza’s popularisation of the methodology in the 1990s. A particular feature of the GP literature since then has been a strong interest in the application of GP to real-world problem domains. One application domain which has attracted significant attention is that of finance and economics, with several hundred papers from this subfield being listed in the Genetic Programming Bibliography. In this article we outline why finance and economics has been a popular application area for GP and briefly indicate the wide span of this work. However, despite this research effort there is relatively scant evidence of the usage of GP by the mainstream finance community in academia or industry. We speculate why this may be the case, describe what is needed to make this research more relevant from a finance perspective, and suggest some future directions for the application of GP in finance and economics

Modeling and Simulation of an Artificial Stock Option Market

Since their introduction in 1973, options have become an important and very popular financial instrument. However, despite much research performed on the subject, the effects of option trading on the underlying asset market are still debated. Both empirical and theoretical studies have failed to point out how price volatility and volumes of the underlying asset are affected. In this paper we present the first study on the effects of an option market related to an underlying stock market, using an artificial financial market based on heterogeneous agents. We modeled a realistic European option using two market models. The microstructure of the first model is kept as simple as possible, being composed only of random traders. The second model is more complex and realistic, involving the presence of various kinds of trading strategies (random, fundamentalist and chartist). We show that the introduction of options, in the proposed models, tends to decrease the volatility of the underlying stock price. Moreover, the traders’ wealth can be strongly affected by the use of option hedging

Clonal Evolution of TP53 c.375+1G>A Mutation in Pre- and Post- Neo-Adjuvant Chemotherapy (NACT) Tumor Samples in High-Grade Serous Ovarian Cancer (HGSOC)

Carboplatin/paclitaxel is the reference regimen in the treatment of advanced high-grade serous ovarian cancer (HGSOC) in neo-adjuvant chemotherapy (NACT) before interval debulking surgery (IDS). To identify new genetic markers of platinum-resistance, next-generation sequencing (NGS) analysis of 26 cancer-genes was performed on paired matched pre- and post-NACT tumor and blood samples in a patient with stage IV HGSOC treated with NACT-IDS, showing platinum-refractory/resistance and poor prognosis. Only the TP53 c.375+1G>A somatic mutation was identified in both tumor samples. This variant, associated with aberrant splicing, was in trans configuration with the 72Arg allele of the known germline polymorphism TP53 c.215C>G (p. Pro72Arg). In the post-NACT tumor sample we observed the complete expansion of the TP53 c.375+1G>A driver mutant clone with somatic loss of the treatment-sensitive 72Arg allele. NGS results were confirmed with Sanger method and immunostaining for p53, BRCA1, p16, WT1, and Ki-67 markers were evaluated. This study showed that (i) the splice mutation in TP53 was present as an early driver mutation at diagnosis; (ii) the mutational profile was shared in pre- and post-NACT tumor samples; (iii) the complete expansion of a single dominant mutant clone through loss of heterozygosity (LOH) had occurred, suggesting a possible mechanism of platinum-resistance in HGSOC under the pressure of NACT

FOCOLAI DI BLUE TONGUE: OSSERVAZIONI SULLE TIPOLOGIE DI SUOLI, NUMEROSIT\uc0 DEGLI INSETTI VETTORI E DANNI CORRELATI

In Sudafrica esistono zone di quarantena per i cavalli al fine di poterli movimentare verso paesi esteri senza esportare la African Horse Sickness (Peste Equina), patologia che prevede lo stesso vettore della febbre catarrale degli ovini. Tali zone sono caratterizzate da abbondanza di terreni prevalentemente salmastri. Questo dato, nonch\ue8 le osservazioni raccolte in Sardegna durante le diverse ondate epidemiche susseguitesi nel periodo 2000- 2007, che hanno fatto rilevare come alcuni allevamenti di specifici territori (penisola del Sinis, Giara di Gesturi, ecc.) mostravano una morbilit\ue0 - mortalit\ue0 estremamente ridotta rispetto agli allevamenti circostanti - se non addirittura rappresentano una sorta di enclave circoscritta -, hanno suggerito di effettuare specifici sopralluoghi finalizzati alla valutazione geologica dei suoli. \uc8 stata anche valutata la compatibilit\ue0 di questi territori con l\u92habitat ideale per l\u92insetto vettore e contemporaneamente con gli altri fattori di rischio noti, correlati allo sviluppo di Culicoides imicola e, di conseguenza, all\u92ingresso del virus e al possibile sviluppo di focolai di Blue Tongue. Dalla verifica dei suoli e dalla sovrapposizione delle mappe della mortalit\ue0 osservata nel corso della prima epidemia di Blue Tongue (2000-2001), si \ue8 rilevato che il danno osservato nei focolai non era distribuito omogeneamente nel territorio. Al fine di validare il presupposto scientifico citato in premessa (terreni salmastri), si \ue8 verificato puntualmente quanto accaduto durante la prima epidemia in alcuni comuni della Sardegna, per i quali si era in possesso della georeferenziazione degli allevamenti sede di focolaio, verificando il tipo di suolo nel quale tali allevamenti insistevano. Dall\u92analisi dei dati \ue8 emerso che esistono forti correlazioni tra la tipologia di pH del suolo, unito alla granulometria e al drenaggio dello stesso. I tipi di suolo sono individuabili in Acidi o sub acidi (AC) e Neutri, Subalcalini o Alcalini (AK). Si sono individuate in funzione del tipo di suolo due categorie di allevamenti sede di focolaio ed \ue8 stata verificata la differenza esistente tra le somme dei danni totali osservate negli allevamenti appartenenti ai due gruppi (AC vs AK), che si \ue8 mostrata statisticamente significativa. Questo dato di estremo interesse pare confermare l\u92assunto teorico basato sulla ipotesi che certi terreni sono meno favorenti lo sviluppo di C. imicola, con una forte correlazione con il pH del terreno stesso. L\u92applicazione pratica di tale osservazione \ue8 quella che si sta cercando di attuare in Sardegna ovvero quella di \u93alcalinizzare\u94 i siti considerati di massimo rischio per la riproduzione dell\u92insetto vettore situati in prossimit\ue0 di allevamenti ovicaprini, attraverso l\u92utilizzo di alcune sostanze (es. latte di calce), in quantit\ue0 e modalit\ue0 valutate in funzione della tipologia di suolo e della relativa permeabilit\ue0 dello stesso. Viene descritta l\u92esperienza in un sito pilota e i risultati preliminari ottenuti

Natural computing in finance : a review

The field of Natural Computing (NC) has advanced rapidly over the past decade. One significant offshoot of this progress has been the application of NC methods in finance. This chapter provides an introduction to a wide range of financial problems to which NC methods have been usefully applied. The chapter also identifies open issues and suggests future directions for the application of NC methods in finance.Science Foundation IrelandDue to be published June 2012 http://www.springer.com/computer/theoretical+computer+science/book/978-3-540-92911-6 - OR 10/01/2012 Not yet published : on publication, 12 months embargo, add link to published article and text "The final publication is available at springerlink.com" in Rights field - AV 20/01/201