In Vivo Imaging-Based Mathematical Modeling Techniques That Enhance the Understanding of Oncogene Addiction in Relation to Tumor Growth.

In Vivo Imaging-Based Mathematical Modeling Techniques That Enhance the Understanding of Oncogene Addiction in relation to Tumor Growth.

Comput Math Methods Med. 2013; 2013: 802512
Nwabugwu C, Rakhra K, Felsher D, Paik D

The dependence on the overexpression of a single oncogene constitutes an exploitable weakness for molecular targeted therapy. These drugs can produce dramatic tumor regression by targeting the driving oncogene, but relapse often follows. Understanding the complex interactions of the tumor’s multifaceted response to oncogene inactivation is key to tumor regression. It has become clear that a collection of cellular responses lead to regression and that immune-mediated steps are vital to preventing relapse. Our integrative mathematical model includes a variety of cellular response mechanisms of tumors to oncogene inactivation. It allows for correct predictions of the time course of events following oncogene inactivation and their impact on tumor burden. A number of aspects of our mathematical model have proven to be necessary for recapitulating our experimental results. These include a number of heterogeneous tumor cell states since cells following different cellular programs have vastly different fates. Stochastic transitions between these states are necessary to capture the effect of escape from oncogene addiction (i.e., resistance). Finally, delay differential equations were used to accurately model the tumor growth kinetics that we have observed. We use this to model oncogene addiction in MYC-induced lymphoma, osteosarcoma, and hepatocellular carcinoma. HubMed – addiction


Quality of persian addiction websites: a survey based on silberg, discern and wqet instruments (2011).

Acta Inform Med. 2013 Mar; 21(1): 46-50
Zahedi R, Taheri B, Shahrzadi L, Tazhibi M, Ashrafi-Rizi H

Nowadays, World Wide Web is an accessible and widespread resource to attain medical information. So physicians and health institutions try to inform patients about different domains of medicine through Web. Addiction is a noteworthy subject in medicine and a controversial issue among them. However, quality of health information on the internet is doubtful. The objective of this study is to determine the quality of Persian addiction websites to offer recommendation for their improvement.This was survey and an applied study that the study population was all Persian addiction websites. Sample of this study was 28 Persian addiction website which were chosen by searching Persian equivalences of 7 key terms (addiction, addict, addiction center, drug, treatment of addiction, recovery of addiction, addiction withdrawal) into the Google and Yahoo search engines. Finally, the websites were ranked based on the Silberg, DISCERN and WQET instruments. Data were analyzed with Excel software using descriptive statistics.The overall mean of websites in Silberg, DISCERN and WQET instruments were 1.42, 41.89, 64.57. Also the results showed that “Unit of Substance Abuse Treatment” belonging to Mashhad University of Medical Sciences was ranked first based on the Silberg, DISCERN and WQET instruments. 5 (from total of 9), 60 (from total of 80) and 82 (from total of normalized grade 82) were grades for this website for these instruments respectively.It showed that the quality of Persian websites according to Silberg, DISCERN and WQET instruments was “low”, “more than half” and “very good” respectively. Not assigning date of entering data, author names, and references of information (authority) were most important missing characteristics of these websites. In addition, lack of interactive opportunities like chat rooms was another problem that leads to dissatisfaction of users. HubMed – addiction


Smoking and Opioid Detoxification: Behavioral Changes and Response to Treatment.

Nicotine Tob Res. 2013 Apr 9;
Mannelli P, Wu LT, Peindl KS, Gorelick DA

INTRODUCTION: The relevance of tobacco use in opioid addiction (OA) has generated a demand for available and more effective interventions. Thus, further analysis of less explored nicotine-opioid clinical interactions is warranted. METHODS: A post-hoc analysis of OA participants in a double-blind, randomized very low dose naltrexone (VLNTX) inpatient detoxification trial evaluated measures of opioid withdrawal and tobacco use. Intreatment smokers were compared with nonsmokers, or smokers who were not allowed to smoke. RESULTS: A total of 141 (81%) of 174 OA participants were smokers, all nicotine-dependent. Inpatient smoking was a predictor of opioid withdrawal discomfort. Intreatment smokers (n = 96) showed significantly higher opioid craving (F = 3.7, p < .001) and lower detoxification completion rate (?(2) = 7.9, p < .02) compared with smokers who were not allowed to smoke (n = 45) or nonsmokers (n = 33). Smoking during treatment was associated with more elevated cigarette craving during detoxification (F = 4.1, p < .001) and a higher number of cigarettes smoked at follow-up (F = 3.6, p < .02). Among intreatment smokers, VLNTX addition to methadone taper was effective in easing opioid withdrawal and craving more than other treatments, whereas the combination VLNTX-clonidine was associated with significantly reduced cigarette craving and smoking during detoxification. CONCLUSIONS: Failure to address tobacco use may negatively affect pharmacologically managed opioid discontinuation. Opioid detoxification may offer a window of opportunity to expand smoking cessation treatment, hence improving OA outcomes. The observed effects support testing of VLNTX-clonidine in smoking cessation trials among individuals with or without substance abuse. HubMed – addiction


Gambling among youths in Switzerland and its association with other addictive behaviours: a population-based study.

Swiss Med Wkly. 2013; 143: 0
Tozzi L, Akre C, Fleury-Schubert A, Suris JC

To assess the prevalence of problem gambling in a population of youths in Switzerland and to determine its association with other potentially addictive behaviours.Cross-sectional survey including 1,102 participants in the first and second year of post-compulsory education, reporting gambling, socio-demographics, internet use and substance use. For three categories of gambling (nongambler; nonproblem gambler and at-risk/problem gambler). socio-demographic and addiction data were compared using a bivariate analysis. All significant variables were included in a multinominal logistic regression using nongamblers as the reference category.The prevalence of gamblers was 37.48% (n = 413), with nonproblem gamblers being 31.94% (n = 352) and at-risk/problem gamblers 5.54% (n = 61). At the bivariate level, severity of gambling increased among adults (over 18 years) and among males, vocational students, participants not living with both parents and youths having a low socio-economic status. Gambling was also associated to the four addictive behaviours studied. At the multivariate level, risk of nonproblem gambling was increased in males, older youths, vocational students, participants of Swiss origin and alcohol misusers. Risk of at-risk/problem gambling was higher for males, older youths, alcohol misusers, participants not living with both parents and problem internet users.One-third of youths in our sample had gambled in the previous year and gambling is associated with other addictive behaviours. Clinicians should screen their adolescent patients for gambling habits, especially if other addictive behaviours are present. Additionally, gambling should be included in prevention campaigns together with other addictive behaviours. HubMed – addiction



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