Meta-Analysis of Genome-Wide Linkage Studies in Celiac Disease.

OBJECTIVE: A meta-analysis of genome-wide linkage studies allows us to summarize the extensive information available from family-based studies, as the field moves into genome-wide association studies. METHODS: Here we apply the genome scan meta-analysis (GSMA) method, a rank-based, model-free approach, to combine results across eight independent genome-wide linkages performed on celiac disease (CD), including 554 families with over 1,500 affected individuals. We also investigate the agreement between signals we identified from this meta-analysis of linkage studies and those identified from genome-wide association analysis using a hypergeometric distribution. RESULTS: Not surprisingly, the most significant result was obtained in the HLA region. Outside the HLA region, suggestive evidence for linkage was obtained at the telomeric region of chromosome 10 (10q26.12-qter; p = 0.00366), and on chromosome 8 (8q22.2-q24.21; p = 0.00491). Testing signals of association and linkage within bins showed no significant evidence for co-localization of results. CONCLUSION: This meta-analysis allowed us to pool the results from available genome-wide linkage studies and to identify novel regions potentially harboring predisposing genetic variation contributing to CD. This study also shows that linkage and association studies may identify different types of disease-predisposing variants

Test–retest stability of patient experience items derived from the national GP patient survey

PURPOSE: The validity and reliability of various items on the GP Patient Survey (GPPS) survey have been reported, however stability of patient responses over time has not been tested. The purpose of this study was to determine the test-retest reliability of the core items from the GPPS. METHODS: Patients who had recently consulted participating GPs in five general practices across the South West England were sent a postal questionnaire comprising of 54 items concerning their experience of their consultation and the care they received from the GP practice. Patients returning the questionnaire within 3 weeks of mail-out were sent a second identical (retest) questionnaire. Stability of responses was assessed by raw agreement rates and Cohen's kappa (for categorical response items) and intraclass correlation coefficients and means (for ordinal response items). RESULTS: 348 of 597 Patients returned a retest questionnaire (58.3 % response rate). In comparison to the test phase, patients responding to the retest phase were older and more likely to have white British ethnicity. Raw agreement rates for the 33 categorical items ranged from 66 to 100 % (mean 88 %) while the kappa coefficients ranged from 0.00 to 1.00 (mean 0.53). Intraclass correlation coefficients for the 21 ordinal items averaged 0.67 (range 0.44-0.77). CONCLUSIONS: Formal testing of items from the national GP patient survey examining patient experience in primary care highlighted their acceptable temporal stability several weeks following a GP consultation.Funding was provided by Health Services and Delivery Research Programme (Grant No. RP-PG-0608-10050)

A SAT-based System for Consistent Query Answering

An inconsistent database is a database that violates one or more integrity constraints, such as functional dependencies. Consistent Query Answering is a rigorous and principled approach to the semantics of queries posed against inconsistent databases. The consistent answers to a query on an inconsistent database is the intersection of the answers to the query on every repair, i.e., on every consistent database that differs from the given inconsistent one in a minimal way. Computing the consistent answers of a fixed conjunctive query on a given inconsistent database can be a coNP-hard problem, even though every fixed conjunctive query is efficiently computable on a given consistent database. We designed, implemented, and evaluated CAvSAT, a SAT-based system for consistent query answering. CAvSAT leverages a set of natural reductions from the complement of consistent query answering to SAT and to Weighted MaxSAT. The system is capable of handling unions of conjunctive queries and arbitrary denial constraints, which include functional dependencies as a special case. We report results from experiments evaluating CAvSAT on both synthetic and real-world databases. These results provide evidence that a SAT-based approach can give rise to a comprehensive and scalable system for consistent query answering.Comment: 25 pages including appendix, to appear in the 22nd International Conference on Theory and Applications of Satisfiability Testin

Systems and technologies for objective evaluation of technical skills in laparoscopic surgery

Minimally invasive surgery is a highly demanding surgical approach regarding technical requirements for the surgeon, who must be trained in order to perform a safe surgical intervention. Traditional surgical education in minimally invasive surgery is commonly based on subjective criteria to quantify and evaluate surgical abilities, which could be potentially unsafe for the patient. Authors, surgeons and associations are increasingly demanding the development of more objective assessment tools that can accredit surgeons as technically competent. This paper describes the state of the art in objective assessment methods of surgical skills. It gives an overview on assessment systems based on structured checklists and rating scales, surgical simulators, and instrument motion analysis. As a future work, an objective and automatic assessment method of surgical skills should be standardized as a means towards proficiency-based curricula for training in laparoscopic surgery and its certification

Illness beliefs and the sociocultural context of diabetes self-management in British South Asians: a mixed methods study

Background: British South Asians have a higher incidence of diabetes and poorer health outcomes compared to the general UK population. Beliefs about diabetes are known to play an important role in self-management, yet little is known about the sociocultural context in shaping beliefs. This study aimed to explore the influence of sociocultural context on illness beliefs and diabetes self-management in British South Asians. Methods: A mixed methods approach was used. 67 participants recruited using random and purposive sampling, completed a questionnaire measuring illness beliefs, fatalism, health outcomes and demographics; 37 participants completed a social network survey interview and semi-structured interviews. Results were analysed using SPSS and thematic analysis. Results: Quantitative data found certain social network characteristics (emotional and illness work) were related to perceived concern, emotional distress and health outcomes (p < 0.05). After multivariate analysis, emotional work remained a significant predictor of perceived concern and emotional distress related to diabetes (p < 0.05). Analysis of the qualitative data suggest that fatalistic attitudes and beliefs influences self-management practices and alternative food ‘therapies’ are used which are often recommended by social networks. Conclusions: Diabetes-related illness beliefs and self-management appear to be shaped by the sociocultural context. Better understanding of the contextual determinants of behaviour could facilitate the development of culturally appropriate interventions to modify beliefs and support self-management in this population

Informational entropy : a failure tolerance and reliability surrogate for water distribution networks

Evolutionary algorithms are used widely in optimization studies on water distribution networks. The optimization algorithms use simulation models that analyse the networks under various operating conditions. The solution process typically involves cost minimization along with reliability constraints that ensure reasonably satisfactory performance under abnormal operating conditions also. Flow entropy has been employed previously as a surrogate reliability measure. While a body of work exists for a single operating condition under steady state conditions, the effectiveness of flow entropy for systems with multiple operating conditions has received very little attention. This paper describes a multi-objective genetic algorithm that maximizes the flow entropy under multiple operating conditions for any given network. The new methodology proposed is consistent with the maximum entropy formalism that requires active consideration of all the relevant information. Furthermore, an alternative but equivalent flow entropy model that emphasizes the relative uniformity of the nodal demands is described. The flow entropy of water distribution networks under multiple operating conditions is discussed with reference to the joint entropy of multiple probability spaces, which provides the theoretical foundation for the optimization methodology proposed. Besides the rationale, results are included that show that the most robust or failure-tolerant solutions are achieved by maximizing the sum of the entropies

Mixtures of four organochlorines enhance human breast cancer cell proliferation.

In view of the large differences between the concentrations of estrogenic chemicals needed to elicit effects in in vitro assays and their levels in human tissues, it is hard to explain possible health risks in terms of exposure to individual compounds. Human populations, however, are exposed to mixtures of estrogenic and estrogen-like agents and it is necessary to consider the impact of combined effects. We assessed the combined effects of 1-(o-chlorophenyl)-1-(p-chlorophenyl)-2,2,2-trichloroethane (o,p'-DDT), 2,2-bis(p-chlorophenyl)-1,1-dichloroethylene (p,p'-DDE), beta-hexachlorocyclohexane (beta-HCH), and 1,1-bis(p-chlorophenyl)-2,2,2-trichloroethane (p,p'-DDT) on the induction of cell proliferation in MCF-7 cells. All four compounds are persistent organochlorines that can be found in human tissues. We performed extensive concentration-response analyses with the single agents to predict the effects of two mixtures of all four compounds with different mixture ratios. We calculated the predictions by using the pharmacologically well-founded models of concentration addition and independent action and then tested them experimentally. o,p'-DDT, p,p'-DDE, beta-HCH, and p,p'-DDT acted together to produce proliferative effects in MCF-7 cells. The combined effect of the four agents could be predicted on the basis of data about single agent concentration-response relationships. Regression analysis demonstrated that there were combination effects even when each mixture component was present at levels at or below its individual no-observed-effect-concentration. We assessed combination effects in two ways: First, evaluations in relation to the proliferative responses induced by single mixture components revealed that the combination effects were stronger than the effects of the most potent constituent. Thus, according to this method of evaluation, the combined effects may be termed synergistic. Second, comparisons with the expected effects, as predicted by concentration addition and independent action, showed excellent agreement between prediction and observation. With this approach, the combined effect of all four compounds can be termed additive

Ten Years of Mixing Cocktails: A Review of Combination Effects of Endocrine-Disrupting Chemicals

In the last 10 years, good evidence has become available to show that the combined effects of endocrine disruptors (EDs) belonging to the same category (e.g., estrogenic, antiandrogenic, or thyroid-disrupting agents) can be predicted by using dose addition. This is true for a variety of end points representing a wide range of organizational levels and biological complexity. Combinations of EDs are able to produce significant effect, even when each chemical is present at low doses that individually do not induce observable effects. However, comparatively little is known about mixtures composed of chemicals from different classes of EDs. Nevertheless, I argue that the accumulated evidence seriously undermines continuation with the customary chemical-by-chemical approach to risk assessment for EDs. Instead, we should seriously consider group-wise regulation of classes of EDs. Great care should be taken to define such classes by using suitable similarity criteria. Criteria should focus on common effects, rather than common mechanisms. In this review I also highlight research needs and identify the lack of information about exposure scenarios as a knowledge gap that seriously hampers progress with ED risk assessment. Future research should focus on investigating the effects of combinations of EDs from different categories, with considerable emphasis on elucidating mechanisms. This strategy may lead to better-defined criteria for grouping EDs for regulatory purposes. Also, steps should be taken to develop dedicated mixtures exposure assessment for EDs

Optimal Drug Synergy in Antimicrobial Treatments

The rapid proliferation of antibiotic-resistant pathogens has spurred the use of drug combinations to maintain clinical efficacy and combat the evolution of resistance. Drug pairs can interact synergistically or antagonistically, yielding inhibitory effects larger or smaller than expected from the drugs' individual potencies. Clinical strategies often favor synergistic interactions because they maximize the rate at which the infection is cleared from an individual, but it is unclear how such interactions affect the evolution of multi-drug resistance. We used a mathematical model of in vivo infection dynamics to determine the optimal treatment strategy for preventing the evolution of multi-drug resistance. We found that synergy has two conflicting effects: it clears the infection faster and thereby decreases the time during which resistant mutants can arise, but increases the selective advantage of these mutants over wild-type cells. When competition for resources is weak, the former effect is dominant and greater synergy more effectively prevents multi-drug resistance. However, under conditions of strong resource competition, a tradeoff emerges in which greater synergy increases the rate of infection clearance, but also increases the risk of multi-drug resistance. This tradeoff breaks down at a critical level of drug interaction, above which greater synergy has no effect on infection clearance, but still increases the risk of multi-drug resistance. These results suggest that the optimal strategy for suppressing multi-drug resistance is not always to maximize synergy, and that in some cases drug antagonism, despite its weaker efficacy, may better suppress the evolution of multi-drug resistance.Molecular and Cellular Biolog

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac