572 resultados para multiple objective programming


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Common diseases such as endometriosis (ED), Alzheimer's disease (AD) and multiple sclerosis (MS) account for a significant proportion of the health care burden in many countries. Genome-wide association studies (GWASs) for these diseases have identified a number of individual genetic variants contributing to the risk of those diseases. However, the effect size for most variants is small and collectively the known variants explain only a small proportion of the estimated heritability. We used a linear mixed model to fit all single nucleotide polymorphisms (SNPs) simultaneously, and estimated genetic variances on the liability scale using SNPs from GWASs in unrelated individuals for these three diseases. For each of the three diseases, case and control samples were not all genotyped in the same laboratory. We demonstrate that a careful analysis can obtain robust estimates, but also that insufficient quality control (QC) of SNPs can lead to spurious results and that too stringent QC is likely to remove real genetic signals. Our estimates show that common SNPs on commercially available genotyping chips capture significant variation contributing to liability for all three diseases. The estimated proportion of total variation tagged by all SNPs was 0.26 (SE 0.04) for ED, 0.24 (SE 0.03) for AD and 0.30 (SE 0.03) for MS. Further, we partitioned the genetic variance explained into five categories by a minor allele frequency (MAF), by chromosomes and gene annotation. We provide strong evidence that a substantial proportion of variation in liability is explained by common SNPs, and thereby give insights into the genetic architecture of the diseases.

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Objective: In Australian residential aged care facilities (RACFs), the use of certain classes of high-risk medication such as antipsychotics, potent analgesics, and sedatives is high. Here, we examined the prescribed medications and subsequent changes recommended by geriatricians during comprehensive geriatric consultations provided to residents of RACFs via videoconference. Design: This is a prospective observational study. Setting: Four RACFs in Queensland, Australia, are included. Participants: A total of 153 residents referred by general practitioners for comprehensive assessment by geriatricians delivered by video-consultation. Results: Residents’ mean (standard deviation, SD) age was 83.0 (8.1) years and 64.1% were female. They had multiple comorbidities (mean 6), high levels of dependency, and were prescribed a mean (SD) of 9.6 (4.2) regular medications. Ninety-one percent of patients were taking five or more medications daily. Of total medications prescribed (n=1,469), geriatricians recommended withdrawal of 9.8% (n=145) and dose alteration of 3.5% (n=51). New medications were initiated in 47.7% (n=73) patients. Of the 10.3% (n=151) medications considered as high risk, 17.2% were stopped and dose altered in 2.6%. Conclusion: There was a moderate prevalence of potentially inappropriate high-risk medications. However, geriatricians made relatively few changes, suggesting either that, on balance, prescription of these medications was appropriate or, because of other factors, there was a reluctance to adjust medications. A structured medication review using an algorithm for withdrawing medications of high disutility might help optimize medications in frail patients. Further research, including a broader survey, is required to understand these dynamics.

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Objective To understand differences in the managerial ethical decision-making styles of Australian healthcare managers through the exploratory use of the Managerial Ethical Profiles (MEP) Scale. Background Healthcare managers (doctors, nurses, allied health practitioners and non-clinically trained professionals) are faced with a raft of variables when making decisions within the workplace. In the absence of clear protocols and policies healthcare managers rely on a range of personal experiences, personal ethical philosophies, personal factors and organizational factors to arrive at a decision. Understanding the dominant approaches to managerial ethical decision-making, particularly for clinically trained healthcare managers, is a fundamental step in both increasing awareness of the importance of how managers make decisions, but also as a basis for ongoing development of healthcare managers. Design Cross-sectional. Methods The study adopts a taxonomic approach that simultaneously considers multiple ethical factors that potentially influence managerial ethical decision-making. These factors are used as inputs into cluster analysis to identify distinct patterns of influence on managerial ethical decision-making. Results Data analysis from the participants (n=441) showed a similar spread of the five managerial ethical profiles (Knights, Guardian Angels, Duty Followers, Defenders and Chameleons) across clinically trained and non-clinically trained healthcare managers. There was no substantial statistical difference between the two manager types (clinical and non-clinical) across the five profiles. Conclusion This paper demonstrated that managers that came from clinical backgrounds have similar ethical decision-making profiles to non-clinically trained managers. This is an important finding in terms of manager development and how organisations understand the various approaches of managerial decision-making across the different ethical profiles.

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OBJECTIVE: The study of ethnically homogeneous populations may help to identify schizophrenia risk loci. The authors conducted a genomewide linkage scan for schizophrenia in an Indian population. METHOD: Participants were 441 individuals (262 affected probands and siblings) who were recruited primarily from one ethnically homogeneous group, the Tamil Brahmin caste, although individuals from other geographically proximal castes also participated. Genotyping of 124 affected sibling pair pedigrees was performed with 402 short tandem repeat polymorphisms. Linkage analyses were conducted using nonparametric exponential LOD (logarithm of the odds ratio for linkage) scores and parametric heterogeneity LOD scores. Parametric heterogeneity scores were calculated using simple dominant and recessive models, correcting for multiple statistics. The data were examined for evidence of consanguinity. Genomewide significance levels were determined using 10,000 gene dropping simulations. RESULTS: These findings revealed genomewide significant linkage to chromosome 1p31.1, through the use of both exponential and heterogeneity LOD scores, incorporating correction for multiple statistics and mild consanguinity. The estimated sibling recurrence risk associated with this putative locus was 1.95. Analysis for heterogeneity LOD scores also detected suggestive linkage to chromosomes 13q22.1 and 16q12.2. Using 117 tag single nucleotide polymorphisms (SNPs), family-based association analyses of phosphodiesterase 4B (PDE4B), the closest schizophrenia candidate gene, detected no convincing evidence of association, suggesting that the chromosome 1 peak represents a novel risk locus. CONCLUSIONS: This is the first study-to the authors' knowledge-to report significant linkage of schizophrenia to chromosome 1p31.1. Further investigation of this chromosome region in diverse populations is warranted to identify underlying sequence variants.

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Context: Identifying susceptibility genes for schizophrenia may be complicated by phenotypic heterogeneity, with some evidence suggesting that phenotypic heterogeneity reflects genetic heterogeneity. Objective: To evaluate the heritability and conduct genetic linkage analyses of empirically derived, clinically homogeneous schizophrenia subtypes. Design: Latent class and linkage analysis. Setting: Taiwanese field research centers. Participants: The latent class analysis included 1236 Han Chinese individuals with DSM-IV schizophrenia. These individuals were members of a large affected-sibling-pair sample of schizophrenia (606 ascertained families), original linkage analyses of which detected a maximum logarithm of odds (LOD) of 1.8 (z = 2.88) on chromosome 10q22.3. Main Outcome Measures: Multipoint exponential LOD scores by latent class assignment and parametric heterogeneity LOD scores. Results: Latent class analyses identified 4 classes, with 2 demonstrating familial aggregation. The first (LC2) described a group with severe negative symptoms, disorganization, and pronounced functional impairment, resembling “deficit schizophrenia.” The second (LC3) described a group with minimal functional impairment, mild or absent negative symptoms, and low disorganization. Using the negative/deficit subtype, we detected genome-wide significant linkage to 1q23-25 (LOD = 3.78, empiric genome-wide P = .01). This region was not detected using the DSM-IV schizophrenia diagnosis, but has been strongly implicated in schizophrenia pathogenesis by previous linkage and association studies.Variants in the 1q region may specifically increase risk for a negative/deficit schizophrenia subtype. Alternatively, these results may reflect increased familiality/heritability of the negative class, the presence of multiple 1q schizophrenia risk genes, or a pleiotropic 1q risk locus or loci, with stronger genotype-phenotype correlation with negative/deficit symptoms. Using the second familial latent class, we identified nominally significant linkage to the original 10q peak region. Conclusion: Genetic analyses of heritable, homogeneous phenotypes may improve the power of linkage and association studies of schizophrenia and thus have relevance to the design and analysis of genome-wide association studies.

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CONTEXT People meeting diagnostic criteria for anxiety or depressive disorders tend to score high on the personality scale of neuroticism. Studying this personality dimension can give insights into the etiology of these important psychiatric disorders. OBJECTIVES To undertake a comprehensive genome-wide linkage study of neuroticism using large study samples that have been measured multiple times and to compare the results between countries for replication and across time within countries for consistency. DESIGN Genome-wide linkage scan. SETTING Twin individuals and their family members from Australia and the Netherlands. PARTICIPANTS Nineteen thousand six hundred thirty-five sibling pairs completed self-report questionnaires for neuroticism up to 5 times over a period of up to 22 years. Five thousand sixty-nine sibling pairs were genotyped with microsatellite markers. METHODS Nonparametric linkage analyses were conducted in MERLIN-REGRESS for the mean neuroticism scores averaged across time. Additional analyses were conducted for the time-specific measures of neuroticism from each country to investigate consistency of linkage results. RESULTS Three chromosomal regions exceeded empirically derived thresholds for suggestive linkage using mean neuroticism scores: 10p 5 Kosambi cM (cM) (Dutch study sample), 14q 103 cM (Dutch study sample), and 18q 117 cM (combined Australian and Dutch study sample), but only 14q retained significance after correction for multiple testing. These regions all showed evidence for linkage in individual time-specific measures of neuroticism and 1 (18q) showed some evidence for replication between countries. Linkage intervals for these regions all overlap with regions identified in other studies of neuroticism or related traits and/or in studies of anxiety in mice. CONCLUSIONS Our results demonstrate the value of the availability of multiple measures over time and add to the optimism reported in recent reviews for replication of linkage regions for neuroticism. These regions are likely to harbor causal variants for neuroticism and its related psychiatric disorders and can inform prioritization of results from genome-wide association studies.

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Accurate determination of same-sex twin zygosity is important for medical, scientific and personal reasons. Determination may be based upon questionnaire data, blood group, enzyme isoforms and fetal membrane examination, but assignment of zygosity must ultimately be confirmed by genotypic data. Here methods are reviewed for calculating average probabilities of correctly concluding a twin pair is monozygotic, given they share the same genotypes across all loci for commonly utilized multiplex short tandem repeat (STR) kits.

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In this report, we describe a simple correction for multiple testing of single-nucleotide polymorphisms (SNPs) in linkage disequilibrium (LD) with each other, on the basis of the spectral decomposition (SpD) of matrices of pairwise LD between SNPs. This method provides a useful alternative to more computationally intensive permutation tests. Additionally, output from SNPSpD includes eigenvalues, principal-component coefficients, and factor "loadings" after varimax rotation, enabling the selection of a subset of SNPs that optimize the information in a genomic region.

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Working on the serotonin (5-hydroxytryptamine, 5-HT) 5-HT2B receptor since several years, we have read with high interest the review by Hertz et al. (2015). Previous studies from our group demonstrated that a direct injection in mouse raphe nucleus of the 5-HT2B agonist BW723C86 has the ability to increase extracellular levels of serotonin, which can be blocked by the selective 5-HT2B receptor antagonist RS127445 (Doly et al., 2008, 2009). We also reported that an acute injection of paroxetine 2 mg/kg in mice knocked out for the 5-HT2B receptor gene or in wild type mice injected with RS127445 (0.5 mg/kg) triggers a strong reduction in extracellular accumulation of 5-HT in hippocampus (Diaz et al., 2012). Following these observations, we showed that acute and chronic BW723C86 injection (3 mg/kg) can mimic the fluoxetine (3 mg/kg) and paroxetine (1 mg/kg) behavioral and biochemical antidepressant effects in mice (Diaz and Maroteaux, 2011; Diaz et al., 2012)...

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Age estimation from facial images is increasingly receiving attention to solve age-based access control, age-adaptive targeted marketing, amongst other applications. Since even humans can be induced in error due to the complex biological processes involved, finding a robust method remains a research challenge today. In this paper, we propose a new framework for the integration of Active Appearance Models (AAM), Local Binary Patterns (LBP), Gabor wavelets (GW) and Local Phase Quantization (LPQ) in order to obtain a highly discriminative feature representation which is able to model shape, appearance, wrinkles and skin spots. In addition, this paper proposes a novel flexible hierarchical age estimation approach consisting of a multi-class Support Vector Machine (SVM) to classify a subject into an age group followed by a Support Vector Regression (SVR) to estimate a specific age. The errors that may happen in the classification step, caused by the hard boundaries between age classes, are compensated in the specific age estimation by a flexible overlapping of the age ranges. The performance of the proposed approach was evaluated on FG-NET Aging and MORPH Album 2 datasets and a mean absolute error (MAE) of 4.50 and 5.86 years was achieved respectively. The robustness of the proposed approach was also evaluated on a merge of both datasets and a MAE of 5.20 years was achieved. Furthermore, we have also compared the age estimation made by humans with the proposed approach and it has shown that the machine outperforms humans. The proposed approach is competitive with current state-of-the-art and it provides an additional robustness to blur, lighting and expression variance brought about by the local phase features.

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BACKGROUND Physical therapy for youth with cerebral palsy (CP) who are ambulatory includes interventions to increase functional mobility and participation in physical activity (PA). Thus, reliable and valid measures are needed to document PA in youth with CP. OBJECTIVE The purpose of this study was to evaluate the inter-instrument reliability and concurrent validity of 3 accelerometer-based motion sensors with indirect calorimetry as the criterion for measuring PA intensity in youth with CP. METHODS Fifty-seven youth with CP (mean age=12.5 years, SD=3.3; 51% female; 49.1% with spastic hemiplegia) participated. Inclusion criteria were: aged 6 to 20 years, ambulatory, Gross Motor Function Classification System (GMFCS) levels I through III, able to follow directions, and able to complete the full PA protocol. Protocol activities included standardized activity trials with increasing PA intensity (resting, writing, household chores, active video games, and walking at 3 self-selected speeds), as measured by weight-relative oxygen uptake (in mL/kg/min). During each trial, participants wore bilateral accelerometers on the upper arms, waist/hip, and ankle and a portable indirect calorimeter. Intraclass coefficient correlations (ICCs) were calculated to evaluate inter-instrument reliability (left-to-right accelerometer placement). Spearman correlations were used to examine concurrent validity between accelerometer output (activity and step counts) and indirect calorimetry. Friedman analyses of variance with post hoc pair-wise analyses were conducted to examine the validity of accelerometers to discriminate PA intensity across activity trials. RESULTS All accelerometers exhibited excellent inter-instrument reliability (ICC=.94-.99) and good concurrent validity (rho=.70-.85). All accelerometers discriminated PA intensity across most activity trials. LIMITATIONS This PA protocol consisted of controlled activity trials. CONCLUSIONS Accelerometers provide valid and reliable measures of PA intensity among youth with CP.

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The built environment is a major contributor to the world’s carbon dioxide emissions, with a considerable amount of energy being consumed in buildings due to heating, ventilation and air-conditioning, space illumination, use of electrical appliances, etc., to facilitate various anthropogenic activities. The development of sustainable buildings seeks to ameliorate this situation mainly by reducing energy consumption. Sustainable building design, however, is a complicated process involving a large number of design variables, each with a range of feasible values. There are also multiple, often conflicting, objectives involved such as the life cycle costs and occupant satisfaction. One approach to dealing with this is through the use of optimization models. In this paper, a new multi-objective optimization model is developed for sustainable building design by considering the design objectives of cost and energy consumption minimization and occupant comfort level maximization. In a case study demonstration, it is shown that the model can derive a set of suitable design solutions in terms of life cycle cost, energy consumption and indoor environmental quality so as to help the client and design team gain a better understanding of the design space and trade-off patterns between different design objectives. The model can very useful in the conceptual design stages to determine appropriate operational settings to achieve the optimal building performance in terms of minimizing energy consumption and maximizing occupant comfort level.

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This paper presents an effective feature representation method in the context of activity recognition. Efficient and effective feature representation plays a crucial role not only in activity recognition, but also in a wide range of applications such as motion analysis, tracking, 3D scene understanding etc. In the context of activity recognition, local features are increasingly popular for representing videos because of their simplicity and efficiency. While they achieve state-of-the-art performance with low computational requirements, their performance is still limited for real world applications due to a lack of contextual information and models not being tailored to specific activities. We propose a new activity representation framework to address the shortcomings of the popular, but simple bag-of-words approach. In our framework, first multiple instance SVM (mi-SVM) is used to identify positive features for each action category and the k-means algorithm is used to generate a codebook. Then locality-constrained linear coding is used to encode the features into the generated codebook, followed by spatio-temporal pyramid pooling to convey the spatio-temporal statistics. Finally, an SVM is used to classify the videos. Experiments carried out on two popular datasets with varying complexity demonstrate significant performance improvement over the base-line bag-of-feature method.