971 resultados para Meta heuristic algorithm


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Research on regulation has crossed paths with the literature on policy instruments, showing that regulatory policy instruments contain cognitive and normative beliefs about policy. Thus, their usage stacks the deck in favor of one type of actor or one type of regulatory solution. In this article, we challenge the assumption that there is a predetermined relationship between ideas, regulatory policy instruments, and outcomes. We argue that different combinations of conditions lead to different outcomes, depending on how actors use the instrument. Empirically, we analyze 31 EU and UK case studies of regulatory impact assessment (RIA) - a regulatory policy instrument that has been pivotal in the so-called better regulation movement. We distinguish four main usages of RIA, that is, political, instrumental, communicative, and perfunctory. We find that in our sample instrumental usage is not so rare and that the contrast between communicative and political usages is less stark than is commonly thought. In terms of policy recommendations, our analysis suggests that there may be different paths to desirable outcomes. Policymakers should therefore explore different combinations of conditions leading to the usages they deem desirable rather than arguing for a fixed menu of variables.

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Several epidemiological studies have reported an association between complications of pregnancy and delivery and schizophrenia, but none have had sufficient power to examine specific complications that, individually, are of low prevalence. We, therefore, performed an individual patient meta-analysis using the raw data from case control studies that used the Lewis-Murray scale. Data were obtained from 12 studies on 700 schizophrenia subjects and 835 controls. There were significant associations between schizophrenia and premature rupture of membranes, gestational age shorter than 37 weeks, and use of resuscitation or incubator. There were associations of borderline significance between schizophrenia and birthweight lower than 2,500 g and forceps delivery. There was no significant interaction between these complications and sex. We conclude that some abnormalities of pregnancy and delivery may be associated with development of schizophrenia. The pathophysiology may involve hypoxia and so future studies should focus on the accurate measurement of this exposure.

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Aims: Recently, several clinical trials analyzed if extended duration of treatment with pegylated interferon-alfa and ribavirin over 48 weeks can improve sustained virologic response (SVR) rates in HCV genotype 1-infected patients with slow virologic response. Because results of these clinical trials are conflicting, we performed a metaanalysis to determine the overall impact of extended treatment compared to standard treatment on virologic response rates in treatment-naive HCV genotype 1 slow responders. Methods: Literature search was performed independently by two observers using Pub Med, EMBASE, CENTRAL and abstracts presented in English at international liver and gastroenterology meetings. Randomized controlled clinical trials (RCTs; but studies that re-analyzed data retrospectively RCTs were also allowed) were considered if they included monoinfected treatment-naive HCV genotype 1 patients and compared treatment with pegIFN-alfa 2a or 2b in combination with ribavirin for 48 weeks versus extended treatment (up to 72 weeks) in slow responders. Primary and secondary end points were SVR rates and end-of-treatment (EOT) and relapse rates, respectively. In the present meta-analysis, study endpoints were summarized with a DerSimonian-Laird estimate for binary outcome basing on a random effects model. Results: Literature search yielded seven RTCs addressing the benefit of extended treatment with pegylated interferon-alfa and ribavirin in treatment-naive HCV genotype 1 slow responders. In total, 1330 slow responders were included in our meta-analysis. We show that extended treatment duration compared to the standard of care significantly improves SVR rates in HCV genotype 1 slow responders (12.4% improvement of overall SVR rate, 95% CI 0.055- 0.193, P = 0.0005). In addition, we show that rates of viral relapse were significantly reduced by extended treatment (24.1% reduction of relapse, 95% CI −0.3332 to −0.1487, P < 0.0001), whereas no significant impact of extended treatment on EOT response rates was found. Though extended treatment was burdened with an enhanced rate of premature treatment discontinuation due to interferonalfa- and ribavirin-related side effects, the frequency of serious adverse events was not increased. Conclusions: Treatment extension in HCV genotype 1 slow responders can improve SVR rates in difficult to treat patients and should be considered in patients who need to be treated before specific antivirals will be approved.

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BACKGROUND: Pharmacotherapy may represent a potential means to limit the expansion rate of abdominal aortic aneurysms (AAAs). Studies evaluating the efficacy of different pharmacological agents to slow down human AAA-expansion rates have been performed, but they have never been systematically reviewed or summarized. METHODS AND FINDINGS: Two independent reviewers identified studies and selected randomized trials and prospective cohort studies comparing the growth rate of AAA in patients with pharmacotherapy vs. no pharmacotherapy. We extracted information on study interventions, baseline characteristics, methodological quality, and AAA growth rate differences (in mm/year). Fourteen prospective studies met eligibility criteria. Five cohort studies raised the possibility of benefit of beta-blockers [pooled growth rate difference: -0.62 mm/year, (95%CI, -1.00 to -0.24)], but this was not confirmed in three beta-blocker RCTs [pooled RCT growth rate difference: -0.05 mm/year (-0.16 to 0.05)]. Statins have been evaluated in two cohort studies that yield a pooled growth rate difference of -2.97 (-5.83 to -0.11). Doxycycline and roxithromycin have been evaluated in two RCTs that suggest possible benefit [pooled RCT growth rate difference: -1.32 mm/year (-2.89 to 0.25)]. Studies assessing NSAIDs, diuretics, calcium channel blockers and ACE inhibitors, meanwhile, did not find statistically significant differences. CONCLUSIONS: Beta-blockers do not appear to significantly reduce the growth rate of AAAs. Statins and other anti-inflammatory agents appear to hold promise for decreasing the expansion rate of AAA, but need further evaluation before definitive recommendations can be made.

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The progression of liver fibrosis in chronic hepatitis C has long been considered to be independent from viral genotypes. However, recent studies suggest an association between Hepatitis C virus (HCV) genotype 3 and accelerated liver disease progression. We completed a systematic review and meta-analysis of studies evaluating the association between HCV genotypes and fibrosis progression. PubMed, Embase and ISI Web of Knowledge databases were searched for cohort, cross-sectional and case-control studies on treatment-naïve HCV-infected adults in which liver fibrosis progression rate (FPR) was assessed by the ratio of fibrosis stage in one single biopsy to the duration of infection (single-biopsy studies) or from the change in fibrosis stage between two biopsies (paired biopsies studies). A random effect model was used to derive FPR among different HCV genotypes. Eight single-biopsy studies (3182 patients, mean/median duration of infection ranging from 9 to 21 years) and eight paired biopsies studies (mean interval between biopsies 2-12 years) met the selection criteria. The odds ratio for the association of genotype 3 with accelerated fibrosis progression was 1.52 (95% CI 1.12-2.07, P = 0.007) in single-biopsy studies and 1.37 (95% CI 0.87-2.17, P = 0.17) in paired biopsy studies. In conclusion, viral genotype 3 was associated with faster fibrosis progression in single-biopsy studies. This observation may have important consequences on the clinical management of genotype 3-infected patients. The association was not significant in paired biopsies studies, although the latter may be limited by important indication bias, short observation time and small sample size.

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We present a heuristic method for learning error correcting output codes matrices based on a hierarchical partition of the class space that maximizes a discriminative criterion. To achieve this goal, the optimal codeword separation is sacrificed in favor of a maximum class discrimination in the partitions. The creation of the hierarchical partition set is performed using a binary tree. As a result, a compact matrix with high discrimination power is obtained. Our method is validated using the UCI database and applied to a real problem, the classification of traffic sign images.

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For the last 2 decades, supertree reconstruction has been an active field of research and has seen the development of a large number of major algorithms. Because of the growing popularity of the supertree methods, it has become necessary to evaluate the performance of these algorithms to determine which are the best options (especially with regard to the supermatrix approach that is widely used). In this study, seven of the most commonly used supertree methods are investigated by using a large empirical data set (in terms of number of taxa and molecular markers) from the worldwide flowering plant family Sapindaceae. Supertree methods were evaluated using several criteria: similarity of the supertrees with the input trees, similarity between the supertrees and the total evidence tree, level of resolution of the supertree and computational time required by the algorithm. Additional analyses were also conducted on a reduced data set to test if the performance levels were affected by the heuristic searches rather than the algorithms themselves. Based on our results, two main groups of supertree methods were identified: on one hand, the matrix representation with parsimony (MRP), MinFlip, and MinCut methods performed well according to our criteria, whereas the average consensus, split fit, and most similar supertree methods showed a poorer performance or at least did not behave the same way as the total evidence tree. Results for the super distance matrix, that is, the most recent approach tested here, were promising with at least one derived method performing as well as MRP, MinFlip, and MinCut. The output of each method was only slightly improved when applied to the reduced data set, suggesting a correct behavior of the heuristic searches and a relatively low sensitivity of the algorithms to data set sizes and missing data. Results also showed that the MRP analyses could reach a high level of quality even when using a simple heuristic search strategy, with the exception of MRP with Purvis coding scheme and reversible parsimony. The future of supertrees lies in the implementation of a standardized heuristic search for all methods and the increase in computing power to handle large data sets. The latter would prove to be particularly useful for promising approaches such as the maximum quartet fit method that yet requires substantial computing power.

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BACKGROUND: Results from cohort studies evaluating the severity of respiratory viral co-infections are conflicting. We conducted a systematic review and meta-analysis to assess the clinical severity of viral co-infections as compared to single viral respiratory infections. METHODS: We searched electronic databases and other sources for studies published up to January 28, 2013. We included observational studies on inpatients with respiratory illnesses comparing the clinical severity of viral co-infections to single viral infections as detected by molecular assays. The primary outcome reflecting clinical disease severity was length of hospital stay (LOS). A random-effects model was used to conduct the meta-analyses. RESULTS: Twenty-one studies involving 4,280 patients were included. The overall quality of evidence applying the GRADE approach ranged from moderate for oxygen requirements to low for all other outcomes. No significant differences in length of hospital stay (LOS) (mean difference (MD) -0.20 days, 95% CI -0.94, 0.53, p = 0.59), or mortality (RR 2.44, 95% CI 0.86, 6.91, p = 0.09) were documented in subjects with viral co-infections compared to those with a single viral infection. There was no evidence for differences in effects across age subgroups in post hoc analyses with the exception of the higher mortality in preschool children (RR 9.82, 95% CI 3.09, 31.20, p<0.001) with viral co-infection as compared to other age groups (I2 for subgroup analysis 64%, p = 0.04). CONCLUSIONS: No differences in clinical disease severity between viral co-infections and single respiratory infections were documented. The suggested increased risk of mortality observed amongst children with viral co-infections requires further investigation.

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Molecular chaperones are central to cellular protein homeostasis. In mammals, protein misfolding diseases and aging cause inflammation and progressive tissue loss, in correlation with the accumulation of toxic protein aggregates and the defective expression of chaperone genes. Bacteria and non-diseased, non-aged eukaryotic cells effectively respond to heat shock by inducing the accumulation of heat-shock proteins (HSPs), many of which molecular chaperones involved in protein homeostasis, in reducing stress damages and promoting cellular recovery and thermotolerance. We performed a meta-analysis of published microarray data and compared expression profiles of HSP genes from mammalian and plant cells in response to heat or isothermal treatments with drugs. The differences and overlaps between HSP and chaperone genes were analyzed, and expression patterns were clustered and organized in a network. HSPs and chaperones only partly overlapped. Heat-shock induced a subset of chaperones primarily targeted to the cytoplasm and organelles but not to the endoplasmic reticulum, which organized into a network with a central core of Hsp90s, Hsp70s, and sHSPs. Heat was best mimicked by isothermal treatments with Hsp90 inhibitors, whereas less toxic drugs, some of which non-steroidal anti-inflammatory drugs, weakly expressed different subsets of Hsp chaperones. This type of analysis may uncover new HSP-inducing drugs to improve protein homeostasis in misfolding and aging diseases.

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The primary goal of this project is to demonstrate the accuracy and utility of a freezing drizzle algorithm that can be implemented on roadway environmental sensing systems (ESSs). The types of problems related to the occurrence of freezing precipitation range from simple traffic delays to major accidents that involve fatalities. Freezing drizzle can also lead to economic impacts in communities with lost work hours, vehicular damage, and downed power lines. There are means for transportation agencies to perform preventive and reactive treatments to roadways, but freezing drizzle can be difficult to forecast accurately or even detect as weather radar and surface observation networks poorly observe these conditions. The detection of freezing precipitation is problematic and requires special instrumentation and analysis. The Federal Aviation Administration (FAA) development of aircraft anti-icing and deicing technologies has led to the development of a freezing drizzle algorithm that utilizes air temperature data and a specialized sensor capable of detecting ice accretion. However, at present, roadway ESSs are not capable of reporting freezing drizzle. This study investigates the use of the methods developed for the FAA and the National Weather Service (NWS) within a roadway environment to detect the occurrence of freezing drizzle using a combination of icing detection equipment and available ESS sensors. The work performed in this study incorporated the algorithm developed initially and further modified for work with the FAA for aircraft icing. The freezing drizzle algorithm developed for the FAA was applied using data from standard roadway ESSs. The work performed in this study lays the foundation for addressing the central question of interest to winter maintenance professionals as to whether it is possible to use roadside freezing precipitation detection (e.g., icing detection) sensors to determine the occurrence of pavement icing during freezing precipitation events and the rates at which this occurs.

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INTRODUCTION: Breast cancer subtyping and prognosis have been studied extensively by gene expression profiling, resulting in disparate signatures with little overlap in their constituent genes. Although a previous study demonstrated a prognostic concordance among gene expression signatures, it was limited to only one dataset and did not fully elucidate how the different genes were related to one another nor did it examine the contribution of well-known biological processes of breast cancer tumorigenesis to their prognostic performance. METHOD: To address the above issues and to further validate these initial findings, we performed the largest meta-analysis of publicly available breast cancer gene expression and clinical data, which are comprised of 2,833 breast tumors. Gene coexpression modules of three key biological processes in breast cancer (namely, proliferation, estrogen receptor [ER], and HER2 signaling) were used to dissect the role of constituent genes of nine prognostic signatures. RESULTS: Using a meta-analytical approach, we consolidated the signatures associated with ER signaling, ERBB2 amplification, and proliferation. Previously published expression-based nomenclature of breast cancer 'intrinsic' subtypes can be mapped to the three modules, namely, the ER-/HER2- (basal-like), the HER2+ (HER2-like), and the low- and high-proliferation ER+/HER2- subtypes (luminal A and B). We showed that all nine prognostic signatures exhibited a similar prognostic performance in the entire dataset. Their prognostic abilities are due mostly to the detection of proliferation activity. Although ER- status (basal-like) and ERBB2+ expression status correspond to bad outcome, they seem to act through elevated expression of proliferation genes and thus contain only indirect information about prognosis. Clinical variables measuring the extent of tumor progression, such as tumor size and nodal status, still add independent prognostic information to proliferation genes. CONCLUSION: This meta-analysis unifies various results of previous gene expression studies in breast cancer. It reveals connections between traditional prognostic factors, expression-based subtyping, and prognostic signatures, highlighting the important role of proliferation in breast cancer prognosis.