Using geospatial mapping to predict and compare gambling harm hotspots in urban, rural and coastal areas of a large county in England.

BACKGROUND: Disordered gambling is a public health problem with interconnections with health and social inequality, and adverse impacts on physical and mental health. Mapping technologies have been used to explore gambling in the UK, though most were based in urban locations. METHODS: We used routine data sources and geospatial mapping software to predict where gambling related harm would be most prevalent within a large English county, host to urban, rural and coastal communities. RESULTS: Licensed gambling premises were most concentrated in areas of deprivation, and in urban and coastal areas. The aggregate prevalence of disordered gambling associated characteristics was also greatest in these areas. CONCLUSIONS: This mapping study links the number of gambling premises, deprivation, and risk factors for disordered gambling, and highlights that coastal areas see particularly high density of gambling premises. Findings can be applied to target resources to where they are most needed.

Ambulance attendance for substance and/or alcohol use in a pandemic: Interrupted time series analysis of incidents.

INTRODUCTION: The ambulance attendance for substance and/or alcohol use in a pandemic (ASAP) study explores incidents during the COVID-19 lockdown in the East Midlands region of the United Kingdom (23 March-4 July 2020). METHOD: Retrospective cross-sectional count per day of ambulance attendances from the East Midlands Ambulance Service Trust. Ambulance attendances relating to alcohol or other drug use in the year prior, during lockdown and weeks following, were examined using interrupted time series analysis by patient demographics and geographical location. RESULTS: A total of 36 104 records were identified (53.7% male, 84.5% ethnicity classified as White, mean age 38.4 years). A significant drop in the number of attendances per day at the start of lockdown (-25.24, confidence interval - 38.16, -12.32) was observed, followed by a gradual increase during the ongoing lockdown period (0.36, confidence interval 0.23, 0.46). Similar patterns were found across genders, age groups 16-64 and urban/rural locations. DISCUSSION AND CONCLUSION: The pattern of ambulance attendances for alcohol or other drug use changed during the COVID-19 lockdown period. Lockdown significantly affected the use of ambulances for incidents involving alcohol or other drug use, impacting on health-care services. Further research into hazardous use of alcohol or other drugs during the lockdown periods is needed to inform policy, planning and public health initiatives.

Alcohol and other substance use during the COVID-19 pandemic: A systematic review.

BACKGROUND: Although evidence suggests substance and alcohol use may change during the Covid-19 pandemic there has been no full review of the evidence around this. METHODS: A systematic review of all available evidence was carried out to document and interpret the frequency and severity of alcohol and other substance use during the Covid-19 pandemic and their relationship to demographic and mental health variables that may suggest further clinical implications. Peer reviewed articles in MEDLINE, Embase, PsycINFO, CINAHL complete and Sociological Abstracts were searched from December 2019 until November 2020. RESULTS: The search and screening identified 45 articles from 513 deduplicated records. The evidence suggests a mixed picture for alcohol use. Overall, there was a trend towards increased alcohol consumption. The proportion of people consuming alcohol during the pandemic ranged from 21.7% to 72.9% in general population samples. Unlike alcohol use, there was a clear trend towards increased use of other substances use during the COVID-19 pandemic. The proportion of people consuming other substances during the pandemic ranged from 3.6% to 17.5% in the general population. Mental health factors were the most common correlates or triggers for increased use of both alcohol and other substances. CONCLUSION: There is an increased need for treatment for alcohol and other substance use related problems during the pandemic. Increased targeting and evidence-based interventions will also be important in the period which follows this pandemic, to improve the quality of life for individuals and families, but also to prevent additional costs to society and health systems.

Self-monitoring for recurrence of secondary atrial fibrillation following non-cardiac surgery or acute illness: A pilot study.

BACKGROUND: Atrial fibrillation (AF) secondary to non-cardiac surgery and medical illness is common and, although often transient, is associated with an increased risk of stroke and mortality. This pilot study tested the feasibility of self-monitoring to detect recurrent AF in this setting and the frequency with which it occurred. METHODS: Patients with new secondary AF after non-cardiac surgery or medical illness that reverted to sinus rhythm before discharge were recruited in three tertiary hospitals in Australia. Participants performed self-monitoring for AF recurrence using a Handheld single-lead ECG device 3-4 times/day for 4-weeks. RESULTS: From 16,454 admissions, 224 (1.4%) secondary AF cases were identified. Of these, 94 were eligible, and 29 agreed to participate in self-monitoring (66% male; median age 67 years). Self-monitoring was feasible and acceptable to participants in this setting. Self-monitoring identified AF recurrence in 10 participants (34%; 95% CI, 18% -54%), with recurrence occurring ≤ 9 days following discharge in 9/10 participants. Only 4 participants (40%) reported associated palpitations with recurrence. Six participants (60%) with recurrence had a CHA2DS2-VA score ≥ 2, suggesting a potential indication for oral anticoagulation. CONCLUSIONS: Approximately 1 in 3 patients with transient secondary AF will have recurrent AF within nine days of discharge. These recurrent episodes are often asymptomatic but can be detected promptly using patient self-monitoring, which was feasible and acceptable. Future research is warranted to further investigate the incidence of secondary AF, the rate of recurrence after discharge and its prognosis, and whether use of oral anticoagulation can reduce stroke in this setting.

Integrating interactive computational modeling in biology curricula.

While the use of computer tools to simulate complex processes such as computer circuits is normal practice in fields like engineering, the majority of life sciences/biological sciences courses continue to rely on the traditional textbook and memorization approach. To address this issue, we explored the use of the Cell Collective platform as a novel, interactive, and evolving pedagogical tool to foster student engagement, creativity, and higher-level thinking. Cell Collective is a Web-based platform used to create and simulate dynamical models of various biological processes. Students can create models of cells, diseases, or pathways themselves or explore existing models. This technology was implemented in both undergraduate and graduate courses as a pilot study to determine the feasibility of such software at the university level. First, a new (In Silico Biology) class was developed to enable students to learn biology by "building and breaking it" via computer models and their simulations. This class and technology also provide a non-intimidating way to incorporate mathematical and computational concepts into a class with students who have a limited mathematical background. Second, we used the technology to mediate the use of simulations and modeling modules as a learning tool for traditional biological concepts, such as T cell differentiation or cell cycle regulation, in existing biology courses. Results of this pilot application suggest that there is promise in the use of computational modeling and software tools such as Cell Collective to provide new teaching methods in biology and contribute to the implementation of the "Vision and Change" call to action in undergraduate biology education by providing a hands-on approach to biology.

Modeling and simulation of the exposure-response and dropout pattern of guanfacine extended-release in pediatric patients with ADHD.

Guanfacine extended-release (GXR) is a selective α2A-adrenergic receptor agonist approved in the United States for once-daily administration for the treatment of attention-deficit hyperactivity disorder (ADHD) in children and adolescents ages 6-17 years old either as monotherapy or adjunctive to stimulant medications. This analysis integrates exposure-response, placebo, and dropout data from 10 clinical trials that used GXR in adolescents and children with ADHD. In these trials, the ADHD Rating Scale-IV (ADHD RS-IV) score was collected longitudinally within patients over the course of 6-13 weeks. Non-linear mixed effects models were developed and used to describe the exposure-response of the GXR and placebo time course. The OpenBUGS program was utilized to describe the dropout time course across the trials. Placebo time course was best described by an inverse Bateman function with a 3-group mixture model that allowed for the onset and offset of the placebo response. Dropout time modeling indicated a missing at random mechanism for dropouts which was best described by a Weibull distribution with an estimated percentage of non-dropout patients. A linear exposure-response model with an adolescent effect on maximum slope (SLPmax), and a time delay for reaching SLPmax, provided the best description of the GXR exposure-response time course. The GXR exposure-response model indicated that the typical (95 % confidence interval) decrease in ADHD RS-IV score from the placebo-response trajectory would be 37.1 % (32.2, 42.0 %) per 0.1 mg/kg of GXR exposure. There was little noticeable difference between the exposure-response in adolescents and children or across ADHD subtypes.

Sensitivity analysis of biological Boolean networks using information fusion based on nonadditive set functions.

BACKGROUND: An algebraic method for information fusion based on nonadditive set functions is used to assess the joint contribution of Boolean network attributes to the sensitivity of the network to individual node mutations. The node attributes or characteristics under consideration are: in-degree, out-degree, minimum and average path lengths, bias, average sensitivity of Boolean functions, and canalizing degrees. The impact of node mutations is assessed using as target measure the average Hamming distance between a non-mutated/wild-type network and a mutated network. RESULTS: We find that for a biochemical signal transduction network consisting of several main signaling pathways whose nodes represent signaling molecules (mainly proteins), the algebraic method provides a robust classification of attribute contributions. This method indicates that for the biochemical network, the most significant impact is generated mainly by the combined effects of two attributes: out-degree, and average sensitivity of nodes. CONCLUSIONS: The results support the idea that both topological and dynamical properties of the nodes need to be under consideration. The algebraic method is robust against the choice of initial conditions and partition of data sets in training and testing sets for estimation of the nonadditive set functions of the information fusion procedure.

A comprehensive, multi-scale dynamical model of ErbB receptor signal transduction in human mammary epithelial cells.

The non-receptor tyrosine kinase Src and receptor tyrosine kinase epidermal growth factor receptor (EGFR/ErbB1) have been established as collaborators in cellular signaling and their combined dysregulation plays key roles in human cancers, including breast cancer. In part due to the complexity of the biochemical network associated with the regulation of these proteins as well as their cellular functions, the role of Src in EGFR regulation remains unclear. Herein we present a new comprehensive, multi-scale dynamical model of ErbB receptor signal transduction in human mammary epithelial cells. This model, constructed manually from published biochemical literature, consists of 245 nodes representing proteins and their post-translational modifications sites, and over 1,000 biochemical interactions. Using computer simulations of the model, we find it is able to reproduce a number of cellular phenomena. Furthermore, the model predicts that overexpression of Src results in increased endocytosis of EGFR in the absence/low amount of the epidermal growth factor (EGF). Our subsequent laboratory experiments also suggest increased internalization of EGFR upon Src overexpression under EGF-deprived conditions, further supporting this model-generated hypothesis.

Dynamics of influenza virus and human host interactions during infection and replication cycle.

The replication and life cycle of the influenza virus is governed by an intricate network of intracellular regulatory events during infection, including interactions with an even more complex system of biochemical interactions of the host cell. Computational modeling and systems biology have been successfully employed to further the understanding of various biological systems, however, computational studies of the complexity of intracellular interactions during influenza infection is lacking. In this work, we present the first large-scale dynamical model of the infection and replication cycle of influenza, as well as some of its interactions with the host's signaling machinery. Specifically, we focus on and visualize the dynamics of the internalization and endocytosis of the virus, replication and translation of its genomic components, as well as the assembly of progeny virions. Simulations and analyses of the models dynamics qualitatively reproduced numerous biological phenomena discovered in the laboratory. Finally, comparisons of the dynamics of existing and proposed drugs, our results suggest that a drug targeting PB1:PA would be more efficient than existing Amantadin/Rimantaine or Zanamivir/Oseltamivir.

Bio-logic builder: a non-technical tool for building dynamical, qualitative models.

Computational modeling of biological processes is a promising tool in biomedical research. While a large part of its potential lies in the ability to integrate it with laboratory research, modeling currently generally requires a high degree of training in mathematics and/or computer science. To help address this issue, we have developed a web-based tool, Bio-Logic Builder, that enables laboratory scientists to define mathematical representations (based on a discrete formalism) of biological regulatory mechanisms in a modular and non-technical fashion. As part of the user interface, generalized "bio-logic" modules have been defined to provide users with the building blocks for many biological processes. To build/modify computational models, experimentalists provide purely qualitative information about a particular regulatory mechanisms as is generally found in the laboratory. The Bio-Logic Builder subsequently converts the provided information into a mathematical representation described with Boolean expressions/rules. We used this tool to build a number of dynamical models, including a 130-protein large-scale model of signal transduction with over 800 interactions, influenza A replication cycle with 127 species and 200+ interactions, and mammalian and budding yeast cell cycles. We also show that any and all qualitative regulatory mechanisms can be built using this tool.

The Cell Collective: toward an open and collaborative approach to systems biology.

BACKGROUND: Despite decades of new discoveries in biomedical research, the overwhelming complexity of cells has been a significant barrier to a fundamental understanding of how cells work as a whole. As such, the holistic study of biochemical pathways requires computer modeling. Due to the complexity of cells, it is not feasible for one person or group to model the cell in its entirety. RESULTS: The Cell Collective is a platform that allows the world-wide scientific community to create these models collectively. Its interface enables users to build and use models without specifying any mathematical equations or computer code - addressing one of the major hurdles with computational research. In addition, this platform allows scientists to simulate and analyze the models in real-time on the web, including the ability to simulate loss/gain of function and test what-if scenarios in real time. CONCLUSIONS: The Cell Collective is a web-based platform that enables laboratory scientists from across the globe to collaboratively build large-scale models of various biological processes, and simulate/analyze them in real time. In this manuscript, we show examples of its application to a large-scale model of signal transduction.

Personal health budgets: a new way of accessing complementary therapies?

The popularity and use of complementary and alternative therapies and medicines (CAM) has remained high in the UK and many other countries over at least the last two decades. Access to such modalities via publicly funded health and welfare systems has remained very limited over the same period. Personal health budgets, designed to offer significant control and personal choice over health care, offer a potential mechanism for some individuals to access publicly funded CAM treatments more directly. This development brings into sharp focus debates about evidence based health care and conflicts between public policy which is geared towards consumer choice and public policy which is based on certain forms of scientific evidence. This paper will examine some of the arguments for allowing access to CAM via personal health budgets, and potential objections and obstacles to this.

Hahnemann and the methodology of pathogenetic trials in healthy volunteers: a reappraisal / Hahnemann e a metodologia de ensaios patogenéticos em voluntários saudáveis: uma reavaliação / Hahnemann y la metodología de ensayos patogenéticos en voluntarios sanos: una reevaluación

This article assesses the guidelines and protocols that Hahnemann developed for homeopathic pathogenetic trials (HPTs) - often referred to as proving - and reappraise them in the light of more recent knowledge and protocols for clinical trials involving human subjects. Innovative features and methods introduced by Hahnemann and aimed at reducing bias are noted. A number of features which are now known to lead to bias in trials and which may be included in the reporting of symptoms are discussed in relation to HPTs. These features include: absence of control groups, absence of random allocation, absence of blinding, the inclusion of trivial and pre-existing symptoms, the inclusion of well-known acquaintances as trial participants, and the lack of definition of the healthy state. Advice from experts and papers published in recent decades related to the design of HPTs are discussed. The importance of developing methods to screen participants in HPTs for susceptibility to the tested medicine is discussed. The absence of trials meeting high quality standards in their design is highlighted. The article concludes with a plea for researchers to show the same desire for rigour and innovation that Hahnemann did in the development of HPTs, whilst fully recognising the requirements and protocols necessary for any trial of medicines on human beings, so that, as Hahnemann wanted, only reliable symptoms from HPTs will be admitted in the materia medica and clinical practice.(AU)

Este artigo discute as orientações e protocolos desenvolvidos por Hahnemann, para a realização de ensaios homeopáticos patogenésicos e reavalia-os com base no conhecimento e protocolos atuais, usados em pesquisas clínicas envolvendo humanos. Técnicas e métodos inovadores foram introduzidos por Hahnemann objetivando a redução de viéses estatísticos. Alguns aspectos metodológicos que podem induzir viéses em ensaios patogenésicos e que podem levar a inclusão incorreta de sintomas são discutidos. Dentre vários, podemos citar: ausência de grupo controle, ausência de randomização, ausência de protocolo cego, inclusão de sintomas triviais e pré-existentes, inclusão de conhecidos como participantes no estudo e a falta de definição do estado saudável. Recomendações de especialistas e de trabalhos publicados recentemente, relacionados aos ensaios patogenésicos são discutidos. A importância do desenvolvimento de métodos capazes de identificar a susceptibilidade dos participantes, aos medicamentos testados, é discutida. A ausência de ensaios desenhados com alto padrão metodológico é destacada. Este artigo termina com um apelo para que pesquisadores mantenham o mesmo desejo pela inovação e rigor metodológico, como Hahnemann, no desenvolvimento dos ensaios patogenésicos, não obstante atendendo plenamente os protocolos e requerimentos necessários para qualquer ensaio de medicamentos, com humanos, de forma que, como Hahnemann queria, somente sintomas confiáveis possam ser admitidos na matéria medica e na prática clínica.(AU)

Este artículo reevalúa las orientaciones y protocolos que Hahnemann formuló para los ensayos patogenéticos homeopáticos (HPTs) a la luz de conocimientos y protocolos recientes para la investigación en seres humanos. Son mencionados algunos aspectos y métodos innovadores formulados por Hahnemann, en particular aquellos destinados a reducir sesgos. Un número de aspectos actualmente conocidos que llevan a sesgos en ensayos y que pueden aparecer en el reporte de síntomas son discutidos en el contexto de los HPTs. Entre estos aspectos se menciona: ausencia de grupos-controle, ausencia de distribución aleatoria, falta de cegamiento, inclusión de síntomas triviales y pre-existentes, inclusión de personas conocidas como participantes del estudio y la falta de definición del concepto de estado de salud. Se discute la opinión de expertos así como la literatura especializada publicada en las últimas décadas sobre el diseño de HPTs. También es abordad la importancia de formular métodos para seleccionar participantes en HPTs en función de su susceptibilidad a la droga estudiada. Es resaltada la falta de estudios de alta calidad metodológica. O artículo concluye con una convocatoria para que los investigadores utilicen el mismo rigor e espíritu innovador que Hahnemann en el desarrollo de HPTs, y que al mismo tiempo reconozcan plenamente los requisitos y protocolos necesarios en cualquier ensayo de drogas en seres humanos de modo a cumplir el desiderátum de Hahnemann: admitir solamente síntomas confiables en la materia médica y la práctica clínica.(AU)

Hahnemann and the methodology of pathogenetic trials in healthy volunteers: a reappraisal / Hahnemann e a metodologia de ensaios patogenéticos em voluntários saudáveis: uma reavaliação / Hahnemann y la metodología de ensayos patogenéticos en voluntarios sanos: una reevaluación

This article assesses the guidelines and protocols that Hahnemann developed for homeopathic pathogenetic trials (HPTs) - often referred to as proving - and reappraise them in the light of more recent knowledge and protocols for clinical trials involving human subjects. Innovative features and methods introduced by Hahnemann and aimed at reducing bias are noted. A number of features which are now known to lead to bias in trials and which may be included in the reporting of symptoms are discussed in relation to HPTs. These features include: absence of control groups, absence of random allocation, absence of blinding, the inclusion of trivial and pre-existing symptoms, the inclusion of well-known acquaintances as trial participants, and the lack of definition of the healthy state. Advice from experts and papers published in recent decades related to the design of HPTs are discussed. The importance of developing methods to screen participants in HPTs for susceptibility to the tested medicine is discussed. The absence of trials meeting high quality standards in their design is highlighted. The article concludes with a plea for researchers to show the same desire for rigour and innovation that Hahnemann did in the development of HPTs, whilst fully recognising the requirements and protocols necessary for any trial of medicines on human beings, so that, as Hahnemann wanted, only reliable symptoms from HPTs will be admitted in the materia medica and clinical practice.

Este artigo discute as orientações e protocolos desenvolvidos por Hahnemann, para a realização de ensaios homeopáticos patogenésicos e reavalia-os com base no conhecimento e protocolos atuais, usados em pesquisas clínicas envolvendo humanos. Técnicas e métodos inovadores foram introduzidos por Hahnemann objetivando a redução de viéses estatísticos. Alguns aspectos metodológicos que podem induzir viéses em ensaios patogenésicos e que podem levar a inclusão incorreta de sintomas são discutidos. Dentre vários, podemos citar: ausência de grupo controle, ausência de randomização, ausência de protocolo cego, inclusão de sintomas triviais e pré-existentes, inclusão de conhecidos como participantes no estudo e a falta de definição do estado saudável. Recomendações de especialistas e de trabalhos publicados recentemente, relacionados aos ensaios patogenésicos são discutidos. A importância do desenvolvimento de métodos capazes de identificar a susceptibilidade dos participantes, aos medicamentos testados, é discutida. A ausência de ensaios desenhados com alto padrão metodológico é destacada. Este artigo termina com um apelo para que pesquisadores mantenham o mesmo desejo pela inovação e rigor metodológico, como Hahnemann, no desenvolvimento dos ensaios patogenésicos, não obstante atendendo plenamente os protocolos e requerimentos necessários para qualquer ensaio de medicamentos, com humanos, de forma que, como Hahnemann queria, somente sintomas confiáveis possam ser admitidos na matéria medica e na prática clínica.

Este artículo reevalúa las orientaciones y protocolos que Hahnemann formuló para los ensayos patogenéticos homeopáticos (HPTs) a la luz de conocimientos y protocolos recientes para la investigación en seres humanos. Son mencionados algunos aspectos y métodos innovadores formulados por Hahnemann, en particular aquellos destinados a reducir sesgos. Un número de aspectos actualmente conocidos que llevan a sesgos en ensayos y que pueden aparecer en el reporte de síntomas son discutidos en el contexto de los HPTs. Entre estos aspectos se menciona: ausencia de grupos-controle, ausencia de distribución aleatoria, falta de cegamiento, inclusión de síntomas triviales y pre-existentes, inclusión de personas conocidas como participantes del estudio y la falta de definición del concepto de estado de salud. Se discute la opinión de expertos así como la literatura especializada publicada en las últimas décadas sobre el diseño de HPTs. También es abordad la importancia de formular métodos para seleccionar participantes en HPTs en función de su susceptibilidad a la droga estudiada. Es resaltada la falta de estudios de alta calidad metodológica. O artículo concluye con una convocatoria para que los investigadores utilicen el mismo rigor e espíritu innovador que Hahnemann en el desarrollo de HPTs, y que al mismo tiempo reconozcan plenamente los requisitos y protocolos necesarios en cualquier ensayo de drogas en seres humanos de modo a cumplir el desiderátum de Hahnemann: admitir solamente síntomas confiables en la materia médica y la práctica clínica.

ChemChains: a platform for simulation and analysis of biochemical networks aimed to laboratory scientists.

BACKGROUND: New mathematical models of complex biological structures and computer simulation software allow modelers to simulate and analyze biochemical systems in silico and form mathematical predictions. Due to this potential predictive ability, the use of these models and software has the possibility to compliment laboratory investigations and help refine, or even develop, new hypotheses. However, the existing mathematical modeling techniques and simulation tools are often difficult to use by laboratory biologists without training in high-level mathematics, limiting their use to trained modelers. RESULTS: We have developed a Boolean network-based simulation and analysis software tool, ChemChains, which combines the advantages of the parameter-free nature of logical models while providing the ability for users to interact with their models in a continuous manner, similar to the way laboratory biologists interact with laboratory data. ChemChains allows users to simulate models in an automatic fashion under tens of thousands of different external environments, as well as perform various mutational studies. CONCLUSION: ChemChains combines the advantages of logical and continuous modeling and provides a way for laboratory biologists to perform in silico experiments on mathematical models easily, a necessary component of laboratory research in the systems biology era.

Emergent decision-making in biological signal transduction networks.

The complexity of biochemical intracellular signal transduction networks has led to speculation that the high degree of interconnectivity that exists in these networks transforms them into an information processing network. To test this hypothesis directly, a large scale model was created with the logical mechanism of each node described completely to allow simulation and dynamical analysis. Exposing the network to tens of thousands of random combinations of inputs and analyzing the combined dynamics of multiple outputs revealed a robust system capable of clustering widely varying input combinations into equivalence classes of biologically relevant cellular responses. This capability was nontrivial in that the network performed sharp, nonfuzzy classifications even in the face of added noise, a hallmark of real-world decision-making.

Double-blind, randomized, placebo-controlled study of high-dose HMG CoA reductase inhibitor therapy on ventricular remodeling, pro-inflammatory cytokines and neurohormonal parameters in patients with chronic systolic heart failure.

BACKGROUND: Statins decrease mortality in patients with coronary artery disease. However, chronic heart failure (CHF) patients were often excluded in such trials. Statins possess pharmacologic properties (independent of cholesterol lowering) that may be beneficial on ventricular remodeling in such patients. METHODS AND RESULTS: We conducted a 6-month randomized placebo (PBO)-controlled study of rosuvastatin (ROS) in patients with systolic (left ventricular ejection fraction [LVEF] <40%) CHF of ischemic or nonischemic etiology. The primary end point was change in LVEF by radionuclide ventriculogram. Secondary end points included change in echocardiographic parameters, neurohormonal and inflammatory markers, Packer composite score, death, and heart failure hospitalization. Patients were well matched for baseline values. Compared with PBO (n = 46), ROS patients (n = 40) had a decrease in low-density lipoprotein cholesterol (PBO +3, ROS -54%, P < .001). There was no significant change in LVEF by radionuclide ventriculogram (PBO +5.3, ROS +3.2%), fractional shortening by echocardiographic (PBO +2.7, ROS +1.8%), left ventricular end-diastolic diameter (PBO -1.7, ROS +0.8 mm), left ventricular end-systolic diameter (PBO -1.9, ROS +0.1 mm). Plasma norepinephrine, endothelin-1, brain natriuretic peptide, hsCRP, tumor necrosis factor-alpha and interleukin-6, patient global assessment, Packer composite, death/heart failure hospitalization, and adverse events were similar between PBO and ROS. CONCLUSIONS: Despite being safe and effective at decreasing plasma cholesterol, high-dose ROS did not beneficially alter parameters of LV remodeling. Reasons for absence of benefit are uncertain, but may include patient population studied, high dose of ROS used or high use of effective background CHF medications.

Scalar equations for synchronous Boolean networks with biological applications.

One way of coping with the complexity of biological systems is to use the simplest possible models which are able to reproduce at least some nontrivial features of reality. Although two value Boolean models have a long history in technology, it is perhaps a little bit surprising that they can also represent important features of living organizms. In this paper, the scalar equation approach to Boolean network models is further developed and then applied to two interesting biological models. In particular, a linear reduced scalar equation is derived from a more rudimentary nonlinear scalar equation. This simpler, but higher order, two term equation gives immediate information about both cycle and transient structure of the network.