Stationary density profiles in the Alcator C-mod tokamak

In the absence of an internal particle source, plasma turbulence will impose an intrinsic relationship between an inwards pinch and an outwards diffusion resulting in a stationary density profile. The Alcator C-mod tokamak utilizes RF heating and current drive so that fueling only occurs in the vicinity of the separatrix. Discharges that transition from L-mode to I-mode are seen to maintain a self-similar stationary density profile as measured by Thomson scattering. For discharges with negative magnetic shear, an observed rise of the safety factor in the vicinity of the magnetic axis appears to be accompanied by a decrease of electron density, qualitatively consistent with the theoretical expectations. © 2012 American Institute of Physics.United States. Department of Energy. Office of Fusion Energy Science

Tissue-scale, personalized modeling and simulation of prostate cancer growth

Recently, mathematical modeling and simulation of diseases and their treatments have enabled the prediction of clinical outcomes and the design of optimal therapies on a personalized (i.e., patient-specific) basis. This new trend in medical research has been termed “predictive medicine.” Prostate cancer (PCa) is a major health problem and an ideal candidate to explore tissue-scale, personalized modeling of cancer growth for two main reasons: First, it is a small organ, and, second, tumor growth can be estimated by measuring serum prostate-specific antigen (PSA, a PCa biomarker in blood), which may enable in vivo validation. In this paper, we present a simple continuous model that reproduces the growth patterns of PCa. We use the phase-field method to account for the transformation of healthy cells to cancer cells and use diffusion-reaction equations to compute nutrient consumption and PSA production. To accurately and efficiently compute tumor growth, our simulations leverage isogeometric analysis (IGA). Our model is shown to reproduce a known shape instability from a spheroidal pattern to fingered growth. Results of our computations indicate that such shift is a tumor response to escape starvation, hypoxia, and, eventually, necrosis. Thus, branching enables the tumor to minimize the distance from inner cells to external nutrients, contributing to cancer survival and further development. We have also used our model to perform tissue-scale, personalized simulation of a PCa patient, based on prostatic anatomy extracted from computed tomography images. This simulation shows tumor progression similar to that seen in clinical practice.Peer ReviewedPostprint (published version

Suicidal Behavior and Depression in Smoking Cessation Treatments

BACKGROUND: Two treatments for smoking cessation--varenicline and bupropion--carry Boxed Warnings from the U.S. Food and Drug Administration (FDA) about suicidal/self-injurious behavior and depression. However, some epidemiological studies report an increased risk in smoking or smoking cessation independent of treatment, and differences between drugs are unknown. METHODOLOGY: From the FDA's Adverse Event Reporting System (AERS) database from 1998 through September 2010 we selected domestic, serious case reports for varenicline (n = 9,575), bupropion for smoking cessation (n = 1,751), and nicotine replacement products (n = 1,917). A composite endpoint of suicidal/self-injurious behavior or depression was defined as a case with one or more Preferred Terms in Standardized MedDRA Query (SMQ) for those adverse effects. The main outcome measure was the ratio of reported suicide/self-injury or depression cases for each drug compared to all other serious events for that drug. RESULTS: Overall we identified 3,249 reported cases of suicidal/self-injurious behavior or depression, 2,925 (90%) for varenicline, 229 (7%) for bupropion, and 95 (3%) for nicotine replacement. Compared to nicotine replacement, the disproportionality results (OR (95% CI)) were varenicline 8.4 (6.8-10.4), and bupropion 2.9 (2.3-3.7). The disproportionality persisted after excluding reports indicating concomitant therapy with any of 58 drugs with suicidal behavior warnings or precautions in the prescribing information. An additional antibiotic comparison group showed that adverse event reports of suicidal/self-injurious behavior or depression were otherwise rare in a healthy population receiving short-term drug treatment. CONCLUSIONS: Varenicline shows a substantial, statistically significant increased risk of reported depression and suicidal/self-injurious behavior. Bupropion for smoking cessation had smaller increased risks. The findings for varenicline, combined with other problems with its safety profile, render it unsuitable for first-line use in smoking cessation

Computational medicine, present and the future: obstetrics and gynecology perspective.

Medicine is, in its essence, decision making under uncertainty; the decisions are made about tests to be performed and treatments to be administered. Traditionally, the uncertainty in decision making was handled using expertise collected by individual providers and, more recently, systematic appraisal of research in the form of evidence-based medicine. The traditional approach has been used successfully in medicine for a very long time. However, it has substantial limitations because of the complexity of the system of the human body and healthcare. The complex systems are a network of highly coupled components intensely interacting with each other. These interactions give those systems redundancy and thus robustness to failure and, at the same time, equifinality, that is, many different causative pathways leading to the same outcome. The equifinality of the complex systems of the human body and healthcare system demand the individualization of medical care, medicine, and medical decision making. Computational models excel in modeling complex systems and, consequently, enabling individualization of medical decision making and medicine. Computational models are theory- or knowledge-based models, data-driven models, or models that combine both approaches. Data are essential, although to a different degree, for computational models to successfully represent complex systems. The individualized decision making, made possible by the computational modeling of complex systems, has the potential to revolutionize the entire spectrum of medicine from individual patient care to policymaking. This approach allows applying tests and treatments to individuals who receive a net benefit from them, for whom benefits outweigh the risk, rather than treating all individuals in a population because, on average, the population benefits. Thus, the computational modeling-enabled individualization of medical decision making has the potential to both improve health outcomes and decrease the costs of healthcare

Correlation ECE diagnostic in Alcator C-Mod

Correlation ECE (CECE) is a diagnostic technique that allows measurement of small amplitude electron temperature, T[subscript e], fluctuations through standard cross-correlation analysis methods. In Alcator C-Mod, a new CECE diagnostic has been installed[Sung RSI 2012], and interesting phenomena have been observed in various plasma conditions. We find that local T[subscript e] fluctuations near the edge (ρ ~ 0:8) decrease across the linearto- saturated ohmic confinement transition, with fluctuations decreasing with increasing plasma density[Sung NF 2013], which occurs simultaneously with rotation reversals[Rice NF 2011]. T[subscript e] fluctuations are also reduced across core rotation reversals with an increase of plasma density in RF heated L-mode plasmas, which implies that the same physics related to the reduction of T[subscript e] fluctuations may be applied to both ohmic and RF heated L-mode plasmas. In I-mode plasmas, we observe the reduction of core T[subscript e] fluctuations, which indicates changes of turbulence occur not only in the pedestal region but also in the core across the L/I transition[White NF 2014]. The present CECE diagnostic system in C-Mod and these experimental results are described in this paper

Protocol for the Smoking, Nicotine and Pregnancy (SNAP) trial: double-blind, placebo-randomised, controlled trial of nicotine replacement therapy in pregnancy

Background: Smoking in pregnancy remains a public health challenge. Nicotine replacement therapy (NRT) is effective for smoking cessation in non-pregnant people, but because women metabolise nicotine and cotinine much faster in pregnancy, it is unclear whether this will be effective for smoking cessation in pregnancy. The NHS Health Technology Assessment Programme (HTA)-funded smoking, nicotine and pregnancy ( SNAP) trial will investigate whether or not nicotine replacement therapy ( NRT) is effective, cost-effective and safe when used for smoking cessation by pregnant women. Methods/Design: Over two years, in 5 trial centres, 1050 pregnant women who are between 12 and 24 weeks pregnant will be randomised as they attend hospital for ante-natal ultrasound scans. Women will receive either nicotine or placebo transdermal patches with behavioural support. The primary outcome measure is biochemically-validated, self-reported, prolonged and total abstinence from smoking between a quit date ( defined before randomisation and set within two weeks of this) and delivery. At six months after childbirth self-reported maternal smoking status will be ascertained and two years after childbirth, self-reported maternal smoking status and the behaviour, cognitive development and respiratory symptoms of children born in the trial will be compared in both groups. Discussion: This trial is designed to ascertain whether or not standard doses of NRT ( as transdermal patches) are effective and safe when used for smoking cessation during pregnancy

Explaining Cold-Pulse Dynamics in Tokamak Plasmas Using Local Turbulent Transport Models

A long-standing enigma in plasma transport has been resolved by modeling of cold-pulse experiments conducted on the Alcator C-Mod tokamak. Controlled edge cooling of fusion plasmas triggers core electron heating on time scales faster than an energy confinement time, which has long been interpreted as strong evidence of nonlocal transport. This Letter shows that the steady-state profiles, the cold-pulse rise time, and disappearance at higher density as measured in these experiments are successfully captured by a recent local quasilinear turbulent transport model, demonstrating that the existence of nonlocal transport phenomena is not necessary for explaining the behavior and time scales of cold-pulse experiments in tokamak plasmas.United States. Department of Energy (Award DE-FC02-99ER54512)United States. Department of Energy (Grant DESC0014264