Efficiently Reasoning with Interval Constraints in Forward Search Planning

In this paper we present techniques for reasoning natively with quantitative/qualitative interval constraints in statebased PDDL planners. While these are considered important in modeling and solving problems in timeline based planners; reasoning with these in PDDL planners has seen relatively little attention, yet is a crucial step towards making PDDL planners applicable in real-world scenarios, such as space missions. Our main contribution is to extend the planner OPTIC to reason natively with Allen interval constraints. We show that our approach outperforms both MTP, the only PDDL planner capable of handling similar constraints and a compilation to PDDL 2.1, by an order of magnitude. We go on to present initial results indicating that our approach is competitive with a timeline based planner on a Mars rover domain, showing the potential of PDDL planners in this setting

Knowledge, attitudes and anxiety towards influenza A/H1N1 vaccination of healthcare workers in Turkey

<p>Abstract</p> <p>Background</p> <p>This study aimed to analyze the factors associated with knowledge and attitudes about influenza A (H1N1) and vaccination, and possible relations of these factors with anxiety among healthcare workers (HCW).</p> <p>Methods</p> <p>The study used a cross-sectional descriptive design, and it was carried out between 23 November and 4 December 2009. A total of 300 HCW from two hospitals completed a questionnaire. Data collection tools comprised a questionnaire and the State-Trait Anxiety Inventory (STAI).</p> <p>Results</p> <p>Vaccination rate for 2009 pandemic influenza A(H1N1) among HCW was low (12.7%). Most of the respondents believed the vaccine was not safe and protective. Vaccination refusal was mostly related to the vaccine's side effects, disbelief to vaccine's protectiveness, negative news about the vaccine and the perceived negative attitude of the Prime Minister to the vaccine. State anxiety was found to be high in respondents who felt the vaccine was unsafe.</p> <p>Conclusions</p> <p>HCW considered the seriousness of the outbreak, their vaccination rate was low. In vaccination campaigns, governments have to aim at providing trust, and media campaigns should be used to reinforce this trust as well. Accurate reporting by the media of the safety and efficacy of influenza vaccines and the importance of vaccines for the public health would likely have a positive influence on vaccine uptake. Uncertain or negative reporting about the vaccine is detrimental to vaccination efforts.</p

Bioinformatic analyses identifies novel protein-coding pharmacogenomic markers associated with paclitaxel sensitivity in NCI60 cancer cell lines

<p>Abstract</p> <p>Background</p> <p>Paclitaxel is a microtubule-stabilizing drug that has been commonly used in treating cancer. Due to genetic heterogeneity within patient populations, therapeutic response rates often vary. Here we used the NCI60 panel to identify SNPs associated with paclitaxel sensitivity. Using the panel's GI50 response data available from Developmental Therapeutics Program, cell lines were categorized as either sensitive or resistant. PLINK software was used to perform a genome-wide association analysis of the cellular response to paclitaxel with the panel's SNP-genotype data on the Affymetrix 125 k SNP array. FastSNP software helped predict each SNP's potential impact on their gene product. mRNA expression differences between sensitive and resistant cell lines was examined using data from BioGPS. Using Haploview software, we investigated for haplotypes that were more strongly associated with the cellular response to paclitaxel. Ingenuity Pathway Analysis software helped us understand how our identified genes may alter the cellular response to paclitaxel.</p> <p>Results</p> <p>43 SNPs were found significantly associated (FDR < 0.005) with paclitaxel response, with 10 belonging to protein-coding genes (<it>CFTR</it>, <it>ROBO1</it>, <it>PTPRD</it>, <it>BTBD12</it>, <it>DCT</it>, <it>SNTG1</it>, <it>SGCD</it>, <it>LPHN2</it>, <it>GRIK1</it>, <it>ZNF607</it>). SNPs in <it>GRIK1</it>, <it>DCT</it>, <it>SGCD </it>and <it>CFTR </it>were predicted to be intronic enhancers, altering gene expression, while SNPs in <it>ZNF607 </it>and <it>BTBD12 </it>cause conservative missense mutations. mRNA expression analysis supported these findings as <it>GRIK1</it>, <it>DCT</it>, <it>SNTG1</it>, <it>SGCD </it>and <it>CFTR </it>showed significantly (p < 0.05) increased expression among sensitive cell lines. Haplotypes found in <it>GRIK1, SGCD, ROBO1, LPHN2</it>, and <it>PTPRD </it>were more strongly associated with response than their individual SNPs.</p> <p>Conclusions</p> <p>Our study has taken advantage of available genotypic data and its integration with drug response data obtained from the NCI60 panel. We identified 10 SNPs located within protein-coding genes that were not previously shown to be associated with paclitaxel response. As only five genes showed differential mRNA expression, the remainder would not have been detected solely based on expression data. The identified haplotypes highlight the role of utilizing SNP combinations within genomic loci of interest to improve the risk determination associated with drug response. These genetic variants represent promising biomarkers for predicting paclitaxel response and may play a significant role in the cellular response to paclitaxel.</p

NCI60 Cancer Cell Line Panel Data and RNAi Analysis Help Identify EAF2 as a Modulator of Simvastatin and Lovastatin Response in HCT-116 Cells

Simvastatin and lovastatin are statins traditionally used for lowering serum cholesterol levels. However, there exists evidence indicating their potential chemotherapeutic characteristics in cancer. In this study, we used bioinformatic analysis of publicly available data in order to systematically identify the genes involved in resistance to cytotoxic effects of these two drugs in the NCI60 cell line panel. We used the pharmacological data available for all the NCI60 cell lines to classify simvastatin or lovastatin resistant and sensitive cell lines, respectively. Next, we performed whole-genome single marker case-control association tests for the lovastatin and simvastatin resistant and sensitive cells using their publicly available Affymetrix 125K SNP genomic data. The results were then evaluated using RNAi methodology. After correction of the p-values for multiple testing using False Discovery Rate, our results identified three genes (NRP1, COL13A1, MRPS31) and six genes (EAF2, ANK2, AKAP7, STEAP2, LPIN2, PARVB) associated with resistance to simvastatin and lovastatin, respectively. Functional validation using RNAi confirmed that silencing of EAF2 expression modulated the response of HCT-116 colon cancer cells to both statins. In summary, we have successfully utilized the publicly available data on the NCI60 cell lines to perform whole-genome association studies for simvastatin and lovastatin. Our results indicated genes involved in the cellular response to these statins and siRNA studies confirmed the role of the EAF2 in response to these drugs in HCT-116 colon cancer cells

Neuropathology in Mouse Models of Mucopolysaccharidosis Type I, IIIA and IIIB

Mucopolysaccharide diseases (MPS) are caused by deficiency of glycosaminoglycan (GAG) degrading enzymes, leading to GAG accumulation. Neurodegenerative MPS diseases exhibit cognitive decline, behavioural problems and shortened lifespan. We have characterised neuropathological changes in mouse models of MPSI, IIIA and IIIB to provide a better understanding of these events

A Pathogenic Mechanism in Huntington's Disease Involves Small CAG-Repeated RNAs with Neurotoxic Activity

Huntington's disease (HD) is an autosomal dominantly inherited disorder caused by the expansion of CAG repeats in the Huntingtin (HTT) gene. The abnormally extended polyglutamine in the HTT protein encoded by the CAG repeats has toxic effects. Here, we provide evidence to support that the mutant HTT CAG repeats interfere with cell viability at the RNA level. In human neuronal cells, expanded HTT exon-1 mRNA with CAG repeat lengths above the threshold for complete penetrance (40 or greater) induced cell death and increased levels of small CAG-repeated RNAs (sCAGs), of ≈21 nucleotides in a Dicer-dependent manner. The severity of the toxic effect of HTT mRNA and sCAG generation correlated with CAG expansion length. Small RNAs obtained from cells expressing mutant HTT and from HD human brains significantly decreased neuronal viability, in an Ago2-dependent mechanism. In both cases, the use of anti-miRs specific for sCAGs efficiently blocked the toxic effect, supporting a key role of sCAGs in HTT-mediated toxicity. Luciferase-reporter assays showed that expanded HTT silences the expression of CTG-containing genes that are down-regulated in HD. These results suggest a possible link between HD and sCAG expression with an aberrant activation of the siRNA/miRNA gene silencing machinery, which may trigger a detrimental response. The identification of the specific cellular processes affected by sCAGs may provide insights into the pathogenic mechanisms underlying HD, offering opportunities to develop new therapeutic approaches

A Whole-Genome SNP Association Study of NCI60 Cell Line Panel Indicates a Role of Ca2+ Signaling in Selenium Resistance

Epidemiological studies have suggested an association between selenium intake and protection from a variety of cancer. Considering this clinical importance of selenium, we aimed to identify the genes associated with resistance to selenium treatment. We have applied a previous methodology developed by our group, which is based on the genetic and pharmacological data publicly available for the NCI60 cancer cell line panel. In short, we have categorized the NCI60 cell lines as selenium resistant and sensitive based on their growth inhibition (GI50) data. Then, we have utilized the Affymetrix 125K SNP chip data available and carried out a genome-wide case-control association study for the selenium sensitive and resistant NCI60 cell lines. Our results showed statistically significant association of four SNPs in 5q33–34, 10q11.2, 10q22.3 and 14q13.1 with selenium resistance. These SNPs were located in introns of the genes encoding for a kinase-scaffolding protein (AKAP6), a membrane protein (SGCD), a channel protein (KCNMA1), and a protein kinase (PRKG1). The knock-down of KCNMA1 by siRNA showed increased sensitivity to selenium in both LNCaP and PC3 cell lines. Furthermore, SNP-SNP interaction (epistasis) analysis indicated the interactions of the SNPs in AKAP6 with SGCD as well as SNPs in AKAP6 with KCNMA1 with each other, assuming additive genetic model. These genes were also all involved in the Ca2+ signaling, which has a direct role in induction of apoptosis and induction of apoptosis in tumor cells is consistent with the chemopreventive action of selenium. Once our findings are further validated, this knowledge can be translated into clinics where individuals who can benefit from the chemopreventive characteristics of the selenium supplementation will be easily identified using a simple DNA analysis

Stochastic variation of transcript abundance in C57BL/6J mice

<p>Abstract</p> <p>Background</p> <p>Transcripts can exhibit significant variation in tissue samples from inbred laboratory mice. We have designed and carried out a microarray experiment to examine transcript variation across samples from adipose, heart, kidney, and liver tissues of C57BL/6J mice and to partition variation into within-mouse and between-mouse components. Within-mouse variance captures variation due to heterogeneity of gene expression within tissues, RNA-extraction, and array processing. Between-mouse variance reflects differences in transcript abundance between genetically identical mice.</p> <p>Results</p> <p>The nature and extent of transcript variation differs across tissues. Adipose has the largest total variance and the largest within-mouse variance. Liver has the smallest total variance, but it has the most between-mouse variance. Genes with high variability can be classified into groups with correlated patterns of expression that are enriched for specific biological functions. Variation between mice is associated with circadian rhythm, growth hormone signaling, immune response, androgen regulation, lipid metabolism, and the extracellular matrix. Genes showing correlated patterns of within-mouse variation are also associated with biological functions that largely reflect heterogeneity of cell types within tissues.</p> <p>Conclusions</p> <p>Genetically identical mice can experience different individual outcomes for medically important traits. Variation in gene expression observed between genetically identical mice can identify functional classes of genes that are likely to vary in the absence of experimental perturbations, can inform experimental design decisions, and provides a baseline for the interpretation of gene expression data in interventional studies. The extent of transcript variation among genetically identical mice underscores the importance of stochastic and micro-environmental factors and their phenotypic consequences.</p

Comparison of active treatments for impaired glucose regulation : a Salford Royal Foundation Trust and Hitachi collaboration (CATFISH): study protocol for a randomized controlled trial

BACKGROUND: Diabetes is highly prevalent and contributes to significant morbidity and mortality worldwide. Behaviour change interventions that target health and lifestyle factors associated with the onset of diabetes can delay progression to diabetes, but many approaches rely on intensive one-to-one contact by specialists. Health coaching is an approach based on motivational interviewing that can potentially deliver behaviour change interventions by non-specialists at a larger scale. This trial protocol describes a randomized controlled trial (CATFISH) that tests whether a web-enhanced telephone health coaching intervention (IGR3) is more acceptable and efficient than a telephone-only health coaching intervention (IGR2) for people with prediabetes (impaired glucose regulation). METHODS: CATFISH is a two-parallel group, single-centre individually randomized controlled trial. Eligible participants are patients aged ≥18 years with impaired glucose regulation (HbA1c concentration between 42 and 47 mmol/mol), have access to a telephone and home internet and have been referred to an existing telephone health coaching service at Salford Royal NHS Foundation Trust, Salford, UK. Participants who give written informed consent will be randomized remotely (via a clinical trials unit) to either the existing pathway (IGR2) or the new web-enhanced pathway (IGR3) for 9 months. The primary outcome measure is patient acceptability at 9 months, determined using the Client Satisfaction Questionnaire. Secondary outcome measures at 9 months are: cost of delivery of IGR2 and IGR3, mental health, quality of life, patient activation, self-management, weight (kg), HbA1c concentration, and body mass index. All outcome measures will be analyzed on an intention-to-treat basis. A qualitative process evaluation will explore the experiences of participants and providers with a focus on understanding usability of interventions, mechanisms of behaviour change, and impact of context on delivery and user acceptability. Qualitative data will be analyzed using Framework. DISCUSSION: The CATFISH trial will provide a pragmatic assessment of whether a web-based information technology platform can enhance acceptability of a telephone health coaching intervention for people with prediabetes. The data will prove critical in understanding the role of web applications to improve engagement with evidence-based approaches to preventing diabetes. TRIAL REGISTRATION: ISRCTN16534814 . Registered on 7 February 2016