bluuebunny/crossref_metadata_2025_split huggingface dataset:
The size and mix of government spending on illicit drug policy in Australia
Authors: MOORE TIMOTHY J. 
Published: June 2008

AbstractAim. To estimate how much governments in Australia spend on reducing and dealing with illicit drug problems. Methods. Government documents and supplementary information sources were used to estimate drug‐related expenditure for the financial year 2002–03, in Australian dollars. Public sector expenditure on reducing drug problems (‘proactive expenditure’) was classified into four policy functions: prevention, treatment, harm reduction and enforcement. Expenditure related to the consequences of drug use (‘reactive expenditure’) was included as a separate category. Results. Spending by Australian governments in financial year 2002–03 on all drug‐related activities was estimated to be $3.2 billion. Proactive expenditure was estimated to be $1.3 billion, comprising 55% on enforcement, 23% on prevention, 17% on treatment, 3% on harm reduction and 1% on activities that span several of these functions. Expenditure on dealing with the consequences of drug use was estimated to be $1.9 billion, with the majority the result of crime‐related consequences. Conclusion. Several insights result from estimating these expenditures. First, law enforcement is the largest drug policy component, with Australian governments also spending significant amounts on treatment and prevention programmes. Secondly, apart from the prevention component, Australia's drug policy mix is strikingly similar to recent international estimates. Finally, expenditures associated with dealing with the consequences of illicit drugs are large and important for assessing drug‐related public sector expenditure.
Screening and brief interventions for alcohol: attitudes, knowledge and experience of community pharmacists in Auckland, New Zealand
Authors: SHERIDAN JANIE , WHEELER AMANDA , CHEN LUCY JU‐HSING , HUANG ANNIE CHEN‐YUN , LEUNG IRIS NGA‐YEE , TIEN KAREN YOW‐CHYI 
Published: June 2008

AbstractIntroduction. Screening and brief intervention (SBI) for alcohol consumption in primary care have been shown to be effective in reducing drinking. This role has not been taken up by community pharmacists. This study aimed to explore attitudes, knowledge, barriers and incentives towards involvement of community pharmacists in New Zealand with problem drinkers. Method. A postal survey (three mailshots) of community pharmacies was undertaken in Auckland, New Zealand, followed by a 10% random sample non‐responder‐follow‐up. Results. A response rate of 39.1% to the postal survey was obtained. In general, knowledge of alcohol content of drinks and recommended safe drinking limits was poor. Respondents were generally well motivated towards undertaking this role, but lacked knowledge, skills and confidence. On follow‐up, non‐responders were found to be less knowledgeable, but had similar attitudes to respondents, indicating potential for extrapolation with regard to beliefs and views on this subject. Discussion. This novel study has found that there is potential for involvement of community pharmacists in New Zealand in SBI for problem drinkers. Lack of knowledge can be remedied relatively easily; greater hurdles such as lack of skills, and lack of confidence may be offset by the high level of motivation of this group. This is an area where community pharmacists can further their professional scope of practice by being in an essential position to provide this service.
Ready to drinks are associated with heavier drinking patterns among young females
Authors: HUCKLE TAISIA , SWEETSUR PAUL , MOYES SIMON , CASSWELL SALLY 
Published: June 2008

AbstractAim. To report patterns of use of ready to drinks (RTDs) and to assess if RTD consumers have heavier drinking patterns. RTDs were introduced in 1995. Method. Data from a general population sample of 7201 respondents aged 14–65 years, in New Zealand in 2004, were modelled. Results. Nineteen per cent of respondents consumed RTDs. Respondents aged 14–17 and 18–24 years and females were the largest consumers of RTDs. Compared to beer, wine or spirits, being an RTD consumer predicted (1) higher typical occasion quantities for respondents aged 14–17, 18–24 and 25+ years and (2) heavier drinking for those aged 14–17 and 18–24 years. When amounts of beverages consumed were modelled, quantity of RTDs predicted higher typical occasion quantities among females of all ages. Among males beer was more predictive. Similar results were found for the heavier drinking measure. For 14–17‐year‐old females, RTDs consumption predicted higher annual frequency, but for the other females and males the amount of wine or beer consumed predicted higher frequency. Conclusion. RTDs were most popular among young people aged 14–17 years, and females. RTDs predicted higher typical occasion alcohol consumption and heavier drinking better than any other beverage for females aged 14–17 years. For the other age and gender groups, other beverages predicted higher quantity and frequency consumption.
Role of Thromboxane A2 Receptor on the Effects of Oxidized LDL on Microvascular Endothelium Nitric Oxide, Endothelin‐1, and IL‐6 Production
Authors: LUBRANO VALTER , BALDI SIMONA , FERRANNINI ELE , L'ABBATE ANTONIO , NATALI ANDREA 
Published: June 2008

ABSTRACTObjective: The aim of this study was to determine to what extent thromboxane A2 (TP) receptor mediates the effect of oxidated low‐density lipoprotein (LDL) on nitric oxide (NO), interleukin (IL)‐6, and endothelin‐1 (ET‐1) release by microvascular endothelial cells.Methods: Endothelial nitric oxide synthase (eNOS), nitrites and nitrates (NO2/NO3), ET‐1, and IL‐6 production were measured following human microvascular endothelial cell 1 exposure to isoprostane‐8‐epi‐PGF2α (F2IP), a natural agonist of the TP receptor present in oxidized LDL, or native, low‐, or medium‐oxidized LDL either with the TP‐receptor blocker, SQ29.548, or its vehicle.Results: F2IP and both native and oxidized LDL enhanced NO2/NO3. F2IP through the TP receptor stimulated eNOS (eight‐fold), while the oxidized LDL effect (two‐to five‐fold) was only partially prevented by SQ29.548. While LDL concentration and degree of oxidation synergistically and independent of SQ29.548 stimulated IL‐6, F2IP had no effect. F2IP induced a modest (+50%) increase in ET‐1. LDL, independent of concentration or degree of oxidation, stimulated (+120%) ET‐1 production, and this effect was only partially attenuated by SQ29.548.Conclusions: In microvascular endothelial cells, LDL concentration and degree of oxidation synergistically stimulate NO and IL‐6 production, but only NO release is largely mediated by the TP receptor. LDL facilitates ET‐1 release independent of concentration and degree of oxidation; TP‐receptor stimulation is only partially responsible for this effect.
Modeling of Cellular Metabolism and Microcirculatory Transport
Authors: BEARD DANIEL A. , WU FAN , CABRERA MARCO E. , DASH RANJAN K. 
Published: June 2008

ABSTRACTOxygen and other substrates, waste products, hormone messengers, and cells and other particles of the immune system are all transported in a closed‐loop circulatory system in vertebrates, within which pumped blood travels to within diffusion distances of practically every cell in the body. Exchange of oxygen and carbon dioxide in the pulmonary capillaries and absorption of nutrients in the gut provide the circulating blood with biochemical reactants to sustain bioenergetic processes throughout the body. Inputs and outputs transported by the microcirculation are necessary to drive the open‐system nonequilibrium chemical reactions of metabolism that are essential for cellular function. In turn, metabolically derived signals influence microcirculatory dynamics. Indeed, the microcirculation is the key system that ties processes at the whole‐body level of the cardiovascular system to subcellular phenomena. This tight integration between cellular metabolism and microcirculatory transport begs for integrative simulations that span the cell, tissue, and organ scales.
Energetic particles in magnetic confinement systems
Authors: Günter S. 
Published: June 2008

Dominating α-particle heating will be the qualitatively new physics element of ITER. As it constitutes both a conceptually challenging as well as a practically highly relevant field, it has attracted the attention of a large and growing scientific community. Theoretical and diagnostic tools should be fully developed at the commencement of the thermonuclear operation of ITER. Fortunately effective methods exist to produce significant fractions of energetic ions already in present experiments. Although these populations differ qualitatively in their energy and pitch-angle spectra from those of fusion-alphas, they offer an excellent opportunity to test theoretical models and codes and to develop and benchmark diagnostic techniques. ITER itself will not mark the last stage in the development of fusion heating, and a comprehensive ab initio understanding of fast particle results on this device will be a necessary prerequisite for bridging the gap to DEMO. The study of the confinement properties of energetic particles, and in particular their interaction with the background plasma, is therefore a key element in the preparation for ITER and DEMO operation.
The papers contained in this special section are based on invited presentations at the 10th IAEA Technical Meeting on Energetic Particles in Magnetic Confinement Systems held in Kloster Seeon, Germany, 8–10 October 2007, hosted by the Max-Planck-Institut für Plasmaphysik, Garching. The main topics of the presentations at this meeting were experimental observations and theoretical results on instabilities driven by energetic ions in tokamaks and stellarators, recent diagnostic developments, runaway electrons, heating and current drive.
The papers presented here are devoted to the most challenging topics in energetic particle physics: the drive of instabilities via resonant interaction between energetic particles and plasma waves and the non-linear back-reaction on the confinement of the fast ions. Experimental observations in various magnetic confinement devices (tokamaks, spherical tokamaks, stellarators) are presented as well as theoretical investigations based on true ab initio physics models.
Damping and drive of low-frequency modes in tokamak plasmas
Authors: Lauber Ph. , Günter S. 
Published: June 2008

The ability to predict the stability of fast-particle-driven Alfvén eigenmodes in burning fusion plasmas requires a detailed understanding of the dissipative mechanisms that damp these modes. In order to address this question, the linear gyro-kinetic, electromagnetic code LIGKA (Lauber 2003 Linear gyrokinetic description of fast particle effects on the MHD stability in tokamaks PhD Thesis Technical University München, Lauber et al 2007 J. Comp. Phys.
226 447) is employed to investigate their behaviour in realistic tokamak geometry.
Recently, the model and the implementation of LIGKA were extended in order to capture rigorously the coupling of the shear Alfvén wave to the drift and sound waves. This coupling becomes important for the investigation of low-frequency modes such as the Alfvén cascade modes (AC), the beta-induced Alfvén eigenmodes (BAEs), the geodesic acoustic modes (GAMs), the energetic particle modes (EPMs) and—at even lower frequencies—the resistive wall modes (RWMs).
The authors report on an effort to close the gap between high-n micro-scale turbulence codes (in their linear phase) and low-n global MHD codes. More precisely, the aim is to describe both regimes within the same framework of equations and with the same numerical implementation by improving the range of applicability and validity of LIGKA: an eigenvalue code allows one to explore both the local complex dispersion relations, e.g. kinetic Alfvén waves (electromagnetic), ion acoustic waves (electrostatic) or drift waves in realistic geometry and also their global eigenfunctions.
As an application of this extension, an investigation of the kinetic RWM damping mechanisms is carried out.
MHD induced neutral beam ion loss from NSTX plasmas
Authors: Darrow D.S. , Fredrickson E.D. , Gorelenkov N.N. , Roquemore A.L. , Shinohara K. 
Published: June 2008

Bursts of ∼60 kHz activity on Mirnov coils, identified as energetic particle modes, occur frequently in NSTX plasmas and these are accompanied by bursts of neutral beam ion loss over a range in pitch angles. These losses have been measured with a scintillator type loss probe imaged with a high speed (> 10 000 frames s−1) video camera, giving the evolution of the energy and pitch angle distributions of the lost neutral beam ions over the course of the events. The instability occurs below the TAE frequency in NSTX (∼100 kHz) in high beta plasmas and may also be identified as a beta-induced Alfvén acoustic (BAAE) mode.
The data from one burst that causes a 13% reduction in the neutron rate have been studied extensively and have several interesting features. First, the burst begins with the mode having a purely n = 1 character, sweeping downwards in frequency. However, there is no change to the underlying loss signal during this time interval. This indicates there is no phase space transport of fast (80 keV D) ions into the loss cone seen by the probe from the frequency sweeping. As the burst evolves further in time, a concurrent n = 2 mode arises, followed quickly by a concurrent n = 3 mode. During this period when multiple modes are present, loss over a wide range of pitch angles is seen simultaneously, suggesting stochastization of the beam ion phase space. There is no evidence of any sweeping in pitch angle of the loss in either phase of the burst, at least not on the 100 µs time scale.
Assessment and improvement of the Plasmodium yoelii yoelii genome annotation through comparative analysis
Authors: Vaughan Ashley , Chiu Sum-Ying , Ramasamy Gowthaman , Li Ling , Gardner Malcolm J. , Tarun Alice S. , Kappe Stefan H.I. , Peng Xinxia 
Published: June 2008

Abstract
Motivation: The sequencing of the Plasmodium yoelii genome, a model rodent malaria parasite, has greatly facilitated research for the development of new drug and vaccine candidates against malaria. Unfortunately, only preliminary gene models were annotated on the partially sequenced genome, mostly by in silico gene prediction, and there has been no major improvement of the annotation since 2002.
Results: Here we report on a systematic assessment of the accuracy of the genome annotation based on a detailed analysis of a comprehensive set of cDNA sequences and proteomics data. We found that the coverage of the current annotation tends to be biased toward genes expressed in the blood stages of the parasite life cycle. Based on our proteomic analysis, we estimate that about 15% of the liver stage proteome data we have generated is absent from the current annotation. Through comparative analysis we identified and manually curated a further 510 P. yoelii genes which have clear orthologs in the P. falciparum genome, but were not present or incorrectly annotated in the current annotation. This study suggests that improvements of the current P. yoelii genome annotation should focus on genes expressed in stages other than blood stages. Comparative analysis will be critically helpful for this re-annotation. The addition of newly annotated genes will facilitate the use of P. yoelii as a model system for studying human malaria.
Contact: xinxia.peng@sbri.org; stefan.kappe@sbri.org
Supplementary information: Supplementary data are available at Bioinformatics online.
Differential variability analysis of gene expression and its application to human diseases
Authors: Ho Joshua W.K. , Stefani Maurizio , dos Remedios Cristobal G. , Charleston Michael A. 
Published: June 2008

AbstractMotivation: Current microarray analyses focus on identifying sets of genes that are differentially expressed (DE) or differentially coexpressed (DC) in different biological states (e.g. diseased versus non-diseased). We observed that in many human diseases, some genes have a significantincrease or decrease in expression variability (variance). Asthese observed changes in expression variability may be caused by alteration of the underlying expression dynamics, such differential variability (DV) patterns are also biologically interesting.Results: Here we propose a novel analysis for changes in gene expression variability between groups of amples, which we call differential variability analysis. We introduce the concept of differential variability (DV), and present a simple procedure for identifying DV genes from microarray data. Our procedure is evaluated with simulated and real microarray datasets. The effect of data preprocessing methods on identification of DV gene is investigated. The biological significance of DV analysis is demonstrated with four human disease datasets. The relationships among DV, DE and DC genes are investigated. The results suggest that changes in expression variability are associated with changes in coexpression pattern, which imply that DV is not merely stochastic noise, but informative signal.Availability: The R source code for differential variability analysis is available from the contact authors upon request.Contact: joshua@it.usyd.edu.au; mcharleston@it.usyd.edu.au
Classification and feature selection algorithms for multi-class CGH data
Authors: Liu Jun , Ranka Sanjay , Kahveci Tamer 
Published: June 2008

Abstract
Recurrent chromosomal alterations provide cytological and molecular positions for the diagnosis and prognosis of cancer. Comparative genomic hybridization (CGH) has been useful in understanding these alterations in cancerous cells. CGH datasets consist of samples that are represented by large dimensional arrays of intervals. Each sample consists of long runs of intervals with losses and gains.
In this article, we develop novel SVM-based methods for classification and feature selection of CGH data. For classification, we developed a novel similarity kernel that is shown to be more effective than the standard linear kernel used in SVM. For feature selection, we propose a novel method based on the new kernel that iteratively selects features that provides the maximum benefit for classification. We compared our methods against the best wrapper-based and filter-based approaches that have been used for feature selection of large dimensional biological data. Our results on datasets generated from the Progenetix database, suggests that our methods are considerably superior to existing methods.
Availability: All software developed in this article can be downloaded from http://plaza.ufl.edu/junliu/feature.tar.gz
Contact: juliu@cise.ufl.edu
A model of higher accuracy for the individual haplotyping problem based on weighted SNP fragments and genotype with errors
Authors: Xie Minzhu , Wang Jianxin , Chen Jianer 
Published: June 2008

Abstract
Motivation: In genetic studies of complex diseases, haplotypes provide more information than genotypes. However, haplotyping is much more difficult than genotyping using biological techniques. Therefore effective computational techniques have been in demand. The individual haplotyping problem is the computational problem of inducing a pair of haplotypes from an individual's aligned SNP fragments. Based on various optimal criteria and including different extra information, many models for the problem have been proposed. Higher accuracy of the models has been an important issue in the study of haplotype reconstruction.
Results: The current article proposes a highly accurate model for the single individual haplotyping problem based on weighted fragments and genotypes with errors. The model is proved to be NP-hard even with gapless fragments. Based on the characteristics of Single Nucleotide Polymorphism (SNP) fragments, a parameterized algorithm of time complexity O(nk22k2 + m log m + mk1) is developed, where m is the number of fragments, n is the number of SNP sites, k1 is the maximum number of SNP sites that a fragment covers (no more than n and usually smaller than 10) and k2 is the maximum number of the fragments covering a SNP site (usually no more than 19). Extensive experiments show that this model is more accurate in haplotype reconstruction than other models.
Availability: The program of the parameterized algorithm can be obtained by sending an email to the corresponding author.
Contact: jxwang@mail.csu.edu.cn
Efficient inference of bacterial strain trees from genome-scale multilocus data
Authors: Than C. , Sugino R. , Innan H. , Nakhleh L. 
Published: June 2008

AbstractMotivation: In bacterial evolution, inferring a strain tree, which is the evolutionary history of different strains of the same bacterium, plays a major role in analyzing and understanding the evolution of strongly isolated populations, population divergence and various evolutionary events, such as horizontal gene transfer and homologous recombination. Inferring a strain tree from multilocus data of these strains is exceptionally hard since, at this scale of evolution, processes such as homologous recombination result in a very high degree of gene tree incongruence.Results: In this article we present a novel computational method for inferring the strain tree despite massive gene tree incongruence caused by homologous recombination. Our method operates in three phases, where in phase I a set of candidate strain-tree topologies is computed using the maximal cliques concept, in phase II divergence times for each of the topologies are estimated using mixed integer linear programming (MILP) and in phase III the optimal tree (or trees) is selected based on an optimality criterion. We have analyzed 1898 genes from nine strains of the Staphylococcus aureus bacteria, and identified a fully resolved (binary) strain tree with estimated divergence times, despite the high degrees of sequence identity at the nucleotide level and gene tree incongruence. Our method's efficiency makes it particularly suitable for analysis of genome-scale datasets, including those of strongly isolated populations which are usually very challenging to analyze.Availability: We have implemented the algorithms in the PhyloNet software package, which is available publicly at http://bioinfo.cs.rice.edu/phylonet/Contact: nakhleh@cs.rice.edu
Inferring differentiation pathways from gene expression
Authors: Costa Ivan G. , Roepcke Stefan , Hafemeister Christoph , Schliep Alexander 
Published: June 2008

AbstractMotivation: The regulation of proliferation and differentiation of embryonic and adult stem cells into mature cells is central to developmental biology. Gene expression measured in distinguishable developmental stages helps to elucidate underlying molecular processes. In previous work we showed that functional gene modules, which act distinctly in the course of development, can be represented by a mixture of trees. In general, the similarities in the gene expression programs of cell populations reflect the similarities in the differentiation path.Results: We propose a novel model for gene expression profiles and an unsupervised learning method to estimate developmental similarity and infer differentiation pathways. We assess the performance of our model on simulated data and compare it with favorable results to related methods. We also infer differentiation pathways and predict functional modules in gene expression data of lymphoid development.Conclusions: We demonstrate for the first time how, in principal, the incorporation of structural knowledge about the dependence structure helps to reveal differentiation pathways and potentially relevant functional gene modules from microarray datasets. Our method applies in any area of developmental biology where it is possible to obtain cells of distinguishable differentiation stages.Availability: The implementation of our method (GPL license), data and additional results are available at http://algorithmics.molgen.mpg.de/Supplements/InfDif/Contact: filho@molgen.mpg.de, schliep@molgen.mpg.deSupplementary information: Supplementary data is available at Bioinformatics online.