The effect of multisensory stimuli on path selection in virtual reality environments

Virtual Reality (VR) has as a key feature, the users’ interaction with a virtual environment. Depending on the purpose of a given VR application, it can be essential to use multisensory stimulus without biasing users towards specific actions or decisions in the virtual environment (VE). The goal of the present work is to study if the choice of paths can be influenced by the addition of multisensory stimulus when navigating in a VE using an immersive setup. The awareness of having to take such decisions was also considered. For the purpose, we used a VR game-like application contemplating three levels. Each level was symmetrical and had two possible paths to move to the next level (left or right). For each level, there was a multisensory stimulus on the right path (from a subject orientation): wind, vibration, scent respectively. The sample of the study consisted of 50 participants, and the results showed that none of the multisensory stimuli had a significant impact users’ decision. The users’ awareness of having to decide also did not affect their path. We conclude that multisensory stimuli can be used to raise the credibility of the virtual environments without compromising the users’ decisions.This work is financed by the ERDF – European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 Programme and by National Funds through the Portuguese funding agency, FCT - Fundação para a Ciência e a Tecnologia within project POCI-01-0145-FEDER-028618 entitled PERFECT - Perceptual Equivalence in virtual Reality For authEntiC Training.info:eu-repo/semantics/publishedVersio

Bookselling online: an examination of consumer behaviour patterns.

Based upon empirical research, and using a range of methods, this paper examines the behaviour and experiences of consumers in online bookselling settings and offers comparison between online and offline (traditional) bookselling. The research finds that while the convenience of online bookshops is important, the key factors enticing consumers online are a combination of breadth of range, ease of access to obscure titles, as well as personalised recommendations and customer reviews. The research is of value to the book trade, highlighting consumer responses to widely adopted online marketing approaches. The research also contributes to scholarly knowledge in the fields of consumer behaviour, e-marketing and e-commerce in online bookselling, as well as providing findings which can be tested in other online settings, informing future theoretical research

A quantitative systems pharmacology approach, incorporating a novel liver model, for predicting pharmacokinetic drug-drug interactions

All pharmaceutical companies are required to assess pharmacokinetic drug-drug interactions (DDIs) of new chemical entities (NCEs) and mathematical prediction helps to select the best NCE candidate with regard to adverse effects resulting from a DDI before any costly clinical studies. Most current models assume that the liver is a homogeneous organ where the majority of the metabolism occurs. However, the circulatory system of the liver has a complex hierarchical geometry which distributes xenobiotics throughout the organ. Nevertheless, the lobule (liver unit), located at the end of each branch, is composed of many sinusoids where the blood flow can vary and therefore creates heterogeneity (e.g. drug concentration, enzyme level). A liver model was constructed by describing the geometry of a lobule, where the blood velocity increases toward the central vein, and by modeling the exchange mechanisms between the blood and hepatocytes. Moreover, the three major DDI mechanisms of metabolic enzymes; competitive inhibition, mechanism based inhibition and induction, were accounted for with an undefined number of drugs and/or enzymes. The liver model was incorporated into a physiological-based pharmacokinetic (PBPK) model and simulations produced, that in turn were compared to ten clinical results. The liver model generated a hierarchy of 5 sinusoidal levels and estimated a blood volume of 283 mL and a cell density of 193 × 106 cells/g in the liver. The overall PBPK model predicted the pharmacokinetics of midazolam and the magnitude of the clinical DDI with perpetrator drug(s) including spatial and temporal enzyme levels changes. The model presented herein may reduce costs and the use of laboratory animals and give the opportunity to explore different clinical scenarios, which reduce the risk of adverse events, prior to costly human clinical studies

Towards a modular language curriculum for using tasks

Task-based language teaching (TBLT) and task-supported language teaching (TSLT) are often seen as incompatible as they draw on different theories of language learning and language teaching. The position adopted in this article, however, is that both approaches are needed especially in instructional contexts where ‘pure’ task-based teaching may be problematic for various reasons. The article makes a case for a modular curriculum consisting of separate (i.e. non-integrated) task-based and structure-based components. Different curriculum models are considered in the light of what is known about how a second language is learned. The model that is proposed assumes the importance of developing fluency first. It consists of a primary task-based module implemented with focus-on-form (Long, 1991) and, once a basic fluency has been achieved, supported by a secondary structural module to provide for explicit accuracy-oriented work to counteract learned selective attention (N. Ellis, 2006): one of the main sources of persistent error. The article also addresses the content and grading of the task-based and structural modules. It considers the factors that need to be considered in the vertical and horizontal grading of tasks but also points out that, for the time being, syllabus designers will have to draw on their experience and intuition as much as on research to make decisions about how to sequence tasks. An argument is presented for treating the structural component as a checklist rather than as a syllabus so as to allow teachers to address selectively those features that are found to be problematic for their students when they perform tasks

Metabolic inactivation of estrogens in breast tissue by UDP-glucuronosyltransferase enzymes: an overview

The breast tissue is the site of major metabolic conversions of estradiol (E(2)) mediated by specific cytochromes P450 hydroxylations and methylation by catechol-O-methytransferase. In addition to E(2 )itself, recent findings highlight the significance of 4-hydroxylated estrogen metabolites as chemical mediators and their link to breast cancer development and progression, whereas, in opposition, 2-methoxylated estrogens appear to be protective. Recent data also indicate that breast tissue possesses enzymatic machinery to inactivate and eliminate E(2 )and its oxidized and methoxylated metabolites through conjugation catalyzed by UDP-glucuronosyltransferases (UGTs), which involves the covalent addition of glucuronic acid. In opposition to other metabolic pathways of estrogen, the UGT-mediated process leads to the formation of glucuronides that are devoid of biologic activity and are readily excreted from the tissue into the circulation. This review addresses the most recent findings on the identification of UGT enzymes that are responsible for the glucuronidation of E(2 )and its metabolites, and evidence regarding their potential role in breast cancer

Physiologically Based Pharmacokinetic Modelling of Cytochrome P450 2C9-Related Tolbutamide Drug Interactions with Sulfaphenazole and Tasisulam

Background and Objectives: Cytochrome P450 2C9 (CYP2C9) is involved in the biotransformation of many commonly used drugs, and significant drug interactions have been reported for CYP2C9 substrates. Previously published physiologically based pharmacokinetic (PBPK) models of tolbutamide are based on an assumption that its metabolic clearance is exclusively through CYP2C9; however, many studies indicate that CYP2C9 metabolism is only responsible for 80–90% of the total clearance. Therefore, these models are not useful for predicting the magnitude of CYP2C9 drug–drug interactions (DDIs). This paper describes the development and verification of SimCYP-based PBPK models that accurately describe the human pharmacokinetics of tolbutamide when dosed alone or in combination with the CYP2C9 inhibitors sulfaphenazole and tasisulam. Methods: A PBPK model was optimized in SimCYP for tolbutamide as a CYP2C9 substrate, based on published in vitro and clinical data. This model was verified to replicate the magnitude of DDI reported with sulfaphenazole and was further applied to simulate the DDI with tasisulam, a small molecule investigated for the treatment of cancer. A clinical study (CT registration # NCT01185548) was conducted in patients with cancer to assess the pharmacokinetic interaction of tasisulum with tolbutamide. A PBPK model was built for tasisulam, and the clinical study design was replicated using the optimized tolbutamide model. Results: The optimized tolbutamide model accurately predicted the magnitude of tolbutamide AUC increase (5.3–6.2-fold) reported for sulfaphenazole. Furthermore, the PBPK simulations in a healthy volunteer population adequately predicted the increase in plasma exposure of tolbutamide in patients with cancer (predicted AUC ratio = 4.7–5.4; measured mean AUC ratio = 5.7). Conclusions: This optimized tolbutamide PBPK model was verified with two strong CYP2C9 inhibitors and can be applied to the prediction of CYP2C9 interactions for novel inhibitors. Furthermore, this work highlights the utility of mechanistic models in navigating the challenges in conducting clinical pharmacology studies in cancer patients