937 resultados para PREDICTOR


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Background: Primary chemotherapy is being given in the treatment of large and locally advanced breast cancers, but a major concern is local relapse after therapy. This paper has examined patients treated with primary chemotherapy and surgery (either breast-conserving surgery or mastectomy) and has examined the role of factors which may indicate those patients who are subsequently more likely to experience local recurrence of,disease.

Methods: A consecutive series of 173 women, with data available for 166 of these, presenting with large and locally advanced breast cancer (T2 >4 cm, T3, T4, or N2) were treated with primary chemotherapy comprising cyclophosphamide, vincristine, doxorubicin, and prednisolone and then surgery (either conservation or mastectomy with axillary surgery) followed by radiotherapy were examined.

Results: The clinical response rate of these patients was 75% (21% complete and 54% partial), with a complete pathological response rate of 15%. A total of 10 patients (6%) experienced local disease relapse, and the median time to relapse was 14 months (ranging from 3 to 40). The median survival in this group was 27 months (ranging from 13 to 78). In patients having breast conservation surgery, local recurrence occurred in 2%, and in those undergoing mastectomy 7% experience local relapse of disease. Factors predicting patients most likely to experience local recurrence were poor clinical response and residual axillary nodal disease after chemotherapy.

Conclusions: Excellent local control of disease can be achieved in patients with large and locally advanced breast cancers using a combination of primary chemotherapy, surgery and radiotherapy. However, the presence of residual tumor in the axillary lymph nodes after chemotherapy is a predictor of local recurrence and patients with a better clinical response were also less likely to experience local disease recurrence. The size and degree of pathological response did not predict patients most likely to experience recurrence of disease. (C) 2003 Excerpta Medica, Inc. All rights reserved.

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This paper considers the potential for improving the reputation of the Irish accountancy profession by exploring undergraduate accounting students’ intolerance of academic cheating as a predictor of future attitudes to unethical workplace practices. The study reports that females are significantly more intolerant of cheating than males. Further, with regard to ethical ideology, idealism was found to have a significant positive association with intolerance of cheating while relativism reported no association. It is anticipated that the growing admission of women to professional accountancy membership together with educational intervention to increase idealism may improve ethical attitudes and help restore the profession's reputation.

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Background: The majority of research examining the influence of social environment on early child development suggests benefits to two-parent households, but contradictory evidence for the effects of siblings. The aims of the present study were to examine the influence of the child's proximal social environment, and the effects of interactions between socioeconomic status and social environment on developmental outcomes.

Methods: Primary caregivers of a representative sample of 10,748 nine-month-old infants in Ireland completed the Ages and Stages Questionnaire and provided information on social environment. Adjustment was made for infant and maternal characteristics, household income, and area where the child was living at the time of the study. Further analyses tested for interactions between social environment and household income.

Results: Binary logistic regressions indicated no effects for number of parents in the household. However, the presence of siblings in the household was a consistent predictor of failing to reach milestones in communication, gross motor, problem-solving, and personal-social development. Furthermore, there was a gradient of increasing likelihood of failing in gross motor, problem-solving, and personal-social development with increasing numbers of siblings. Care by a grandparent decreased the likelihood of failing in communication and personal-social development.

Conclusions:These findings do not support the majority of research that finds positive benefits for two-parent households. Similarly, the findings suggest limited effects for non-parental care. However, the observed negative effects of siblings support both the confluence and resource dilution models of sibling effect. Examination of follow-up data may elucidate current findings.

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Background
When asked to solve mathematical problems, some people experience anxiety and threat, which can lead to impaired mathematical performance (Curr Dir Psychol Sci 11:181–185, 2002). The present studies investigated the link between mathematical anxiety and performance on the cognitive reflection test (CRT; J Econ Perspect 19:25–42, 2005). The CRT is a measure of a person’s ability to resist intuitive response tendencies, and it correlates strongly with important real-life outcomes, such as time preferences, risk-taking, and rational thinking.

Methods
In Experiments 1 and 2 the relationships between maths anxiety, mathematical knowledge/mathematical achievement, test anxiety and cognitive reflection were analysed using mediation analyses. Experiment 3 included a manipulation of working memory load. The effects of anxiety and working memory load were analysed using ANOVAs.

Results
Our experiments with university students (Experiments 1 and 3) and secondary school students (Experiment 2) demonstrated that mathematical anxiety was a significant predictor of cognitive reflection, even after controlling for the effects of general mathematical knowledge (in Experiment 1), school mathematical achievement (in Experiment 2) and test anxiety (in Experiments 1–3). Furthermore, Experiment 3 showed that mathematical anxiety and burdening working memory resources with a secondary task had similar effects on cognitive reflection.

Conclusions
Given earlier findings that showed a close link between cognitive reflection, unbiased decisions and rationality, our results suggest that mathematical anxiety might be negatively related to individuals’ ability to make advantageous choices and good decisions.

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This study investigates the trading activity in options and stock markets around informed events with extreme daily stock price movements. We find that informed agents are more likely to trade options prior to negative news and stocks ahead of positive news. We also show that optioned stocks overreact to the arrival of negative news, but react efficiently to positive news. However, the overreaction patterns are unique to the subsample of stocks with the lowest pre-event abnormal option/stock volume ratio (O/S). This finding suggests that the incremental benefit of option listing is related to the level of option trading activity, over and beyond the presence of an options market on the firm's stock. Finally, we find that the pre-event abnormal O/S is a better predictor of stock price patterns following a negative shock than is the pre-event O/S, implying that the former may contain more information about the future value of stocks than the latter.

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Aim: This paper is a report of a study to examine the role of personality and self-efficacy in predicting academic performance and attrition in nursing students.

Background: Despite a considerable amount of research investigating attrition in nursing students and new nurses, concerns remain. This particular issue highlights the need for a more effective selection process whereby those selected are more likely to complete their preregistration programme successfully, and remain employed as Registered Nurses.

Method: A longitudinal design was adopted. A questionnaire, which included measures of personality and occupational and academic self-efficacy, was administered to 384 students early in the first year of the study. At the end of the programme, final marks and attrition rates were obtained from university records for a total of 350 students. The data were collected from 1999 to 2002.

Findings: Individuals who scored higher on a psychoticism scale were more likely to withdraw from the programme. Occupational self-efficacy was revealed to be a statistically significant predictor of final mark obtained, in that those with higher self-efficacy beliefs were more likely to achieve better final marks. Extraversion was also shown to negatively predict academic performance in that those with higher extraversion scores were more likely to achieve lower marks.

Conclusion: More research is needed to explore the attributes of successful nursing students and the potential contribution of psychological profiling to a more effective selection process.

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Conventional wisdom on party systems in advanced industrial democracies holds that modern electorates are dealigned and that social cleavages no longer structure party politics. Recent work on class cleavages has challenged this stylized fact. The analysis performed here extends this criticism to the religious-secular cleavage. Using path analysis and comparing the current electorates of the United States, Germany, and Great Britain with the early 1960s, this paper demonstrates that the religious-secular cleavage remains or has become a significant predictor of conservative vote choice. While the effects of the religious-secular cleavage on vote choice have become largely indirect, the total of the direct and indirect effects is substantial and equivalent to the effects of class and status.

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Many modeling problems require to estimate a scalar output from one or more time series. Such problems are usually tackled by extracting a fixed number of features from the time series (like their statistical moments), with a consequent loss in information that leads to suboptimal predictive models. Moreover, feature extraction techniques usually make assumptions that are not met by real world settings (e.g. uniformly sampled time series of constant length), and fail to deliver a thorough methodology to deal with noisy data. In this paper a methodology based on functional learning is proposed to overcome the aforementioned problems; the proposed Supervised Aggregative Feature Extraction (SAFE) approach allows to derive continuous, smooth estimates of time series data (yielding aggregate local information), while simultaneously estimating a continuous shape function yielding optimal predictions. The SAFE paradigm enjoys several properties like closed form solution, incorporation of first and second order derivative information into the regressor matrix, interpretability of the generated functional predictor and the possibility to exploit Reproducing Kernel Hilbert Spaces setting to yield nonlinear predictive models. Simulation studies are provided to highlight the strengths of the new methodology w.r.t. standard unsupervised feature selection approaches. © 2012 IEEE.

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Summary

1.While plant–fungal interactions are important determinants of plant community assembly and ecosystem functioning, the processes underlying fungal community composition are poorly understood.
2.Here, we studied for the first time the root-associated eumycotan communities in a set of co-occurring plant species of varying relatedness in a species-rich, semi-arid grassland in Germany. The study system provides an opportunity to evaluate the importance of host plants and gradients in soil type and landscape structure as drivers of fungal community structure on a relevant spatial scale. We used 454 pyrosequencing of the fungal internal transcribed spacer region to analyse root-associated eumycotan communities of 25 species within the Asteraceae, which were sampled at different locations within a soil type gradient. We partitioned the variance accounted for by three predictors (host plant phylogeny, spatial distribution and soil type) to quantify their relative roles in determining fungal community composition and used null model analyses to determine whether community composition was influenced by biotic interactions among the fungi.
3.We found a high fungal diversity (156 816 sequences clustered in 1100 operational taxonomic units (OTUs)). Most OTUs belonged to the phylum Ascomycota (35.8%); the most abundant phylotype best-matched Phialophora mustea. Basidiomycota were represented by 18.3%, with Sebacina as most abundant genus. The three predictors explained 30% of variation in the community structure of root-associated fungi, with host plant phylogeny being the most important variance component. Null model analysis suggested that many fungal taxa co-occurred less often than expected by chance, which demonstrates spatial segregation and indicates that negative interactions may prevail in the assembly of fungal communities.
4.Synthesis. The results show that the phylogenetic relationship of host plants is the most important predictor of root-associated fungal community assembly, indicating that fungal colonization of host plants might be facilitated by certain plant traits that may be shared among closely related plant species.

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Pattern and process are inextricably linked in biogeographic analyses, though we can observe pattern, we must infer process. Inferences of process are often based on ad hoc comparisons using a single spatial predictor. Here, we present an alternative approach that uses mixed-spatial models to measure the predictive potential of combinations of hypotheses. Biodiversity patterns are estimated from 8,362 occurrence records from 745 species of Malagasy amphibians and reptiles. By incorporating 18 spatially explicit predictions of 12 major biogeographic hypotheses, we show that mixed models greatly improve our ability to explain the observed biodiversity patterns. We conclude that patterns are influenced by a combination of diversification processes rather than by a single predominant mechanism. A ‘one-size-fits-all’ model does not exist. By developing a novel method for examining and synthesizing spatial parameters such as species richness, endemism and community similarity, we demonstrate the potential of these analyses for understanding the diversification history of Madagascar’s biota.

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Virtual metrology (VM) aims to predict metrology values using sensor data from production equipment and physical metrology values of preceding samples. VM is a promising technology for the semiconductor manufacturing industry as it can reduce the frequency of in-line metrology operations and provide supportive information for other operations such as fault detection, predictive maintenance and run-to-run control. The prediction models for VM can be from a large variety of linear and nonlinear regression methods and the selection of a proper regression method for a specific VM problem is not straightforward, especially when the candidate predictor set is of high dimension, correlated and noisy. Using process data from a benchmark semiconductor manufacturing process, this paper evaluates the performance of four typical regression methods for VM: multiple linear regression (MLR), least absolute shrinkage and selection operator (LASSO), neural networks (NN) and Gaussian process regression (GPR). It is observed that GPR performs the best among the four methods and that, remarkably, the performance of linear regression approaches that of GPR as the subset of selected input variables is increased. The observed competitiveness of high-dimensional linear regression models, which does not hold true in general, is explained in the context of extreme learning machines and functional link neural networks.

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There is increasing appreciation that hosts in natural populations are subject to infection by multiple parasite species. Yet the epidemiological and ecological processes determining the outcome of mixed infections are poorly understood. Here, we use two intracellular gut parasites (Microsporidia), one exotic and one co-evolved in the western honeybee (Apis mellifera), in an experiment in which either one or both parasites were administered either simultaneously or sequentially. We provide clear evidence of within-host competition; order of infection was an important determinant of the competitive outcome between parasites, with the first parasite significantly inhibiting the growth of the second, regardless of species. However, the strength of this ‘priority effect’ was highly asymmetric, with the exotic Nosema ceranae exhibiting stronger inhibition of Nosema apis than vice versa. Our results reveal an unusual asymmetry in parasite competition that is dependent on order of infection. When incorporated into a mathematical model of disease prevalence, we find asymmetric competition to be an important predictor of the patterns of parasite prevalence found in nature. Our findings demonstrate the wider significance of complex multi-host–multi-parasite interactions as drivers of host–pathogen community structure

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Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.

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OBJECTIVES: Sphingosine kinase 1 (SphK1) phosphorylates the membrane sphingolipid, sphingosine, to sphingosine-1-phosphate (S1P), an oncogenic mediator, which drives tumor cell growth and survival. Although SphK1 has gained increasing prominence as an oncogenic determinant in several cancers, its potential as a therapeutic target in colon cancer remains uncertain. We investigated the clinical relevance of SphK1 expression in colon cancer as well as its inhibitory effects in vitro.

METHODS: SphK1 expression in human colon tumor tissues was determined by immunohistochemistry and its clinicopathological significance was ascertained in 303 colon cancer cases. The effects of SphK1 inhibition on colon cancer cell viability and the phosphoinositide 3-kinase (PI3K)/Akt cell survival pathway were investigated using a SphK1-selective inhibitor-compound 5c (5c). The cytotoxicity of a novel combination using SphK1 inhibition with the chemotherapeutic drug, 5-fluorouracil (5-FU), was also determined.

RESULTS: High SphK1 expression correlated with advanced tumor stages (AJCC classification). Using a competing risk analysis model to take into account disease recurrence, we found that SphK1 is a significant independent predictor for mortality in colon cancer patients. In vitro, the inhibition of SphK1 induced cell death in colon cancer cell lines and attenuated the serum-dependent PI3K/Akt signaling. Inhibition of SphK1 also enhanced the sensitivity of colon cancer cells to 5-FU.

CONCLUSION: Our findings highlight the impact of SphK1 in colon cancer progression and patient survival, and provide evidence supportive of further development in combination strategies that incorporate SphK1 inhibition with current chemotherapeutic agents to improve colon cancer outcomes.

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Few pain studies have made community-dwelling people with dementia (PWD) their focus. The aim of this study was to determine the prevalence of pain among this patient population and to explore medication use. Moreover, we sought to investigate patient and caregiver variables associated with the presence of pain. Community-dwelling PWD and their caregivers were recruited between May 2009 and July 2012 from outpatient memory clinics in Northern Ireland to take part in a face-to-face structured interview with a researcher. Patients' cognitive status and presence of depression were established. A full medication history was taken. Both patients and caregivers were asked to rate patients' pain, at the time of the interview and on an average day, using a 7-point verbal descriptor scale. From the 206 patients who were eligible to take part, 75 patient-caregiver dyads participated in the study (participation rate = 36.4%). The majority of patients (92.0%) had dementia classed as mild or moderate. Pain was commonly reported among the sample, with 57.3% of patients and 70.7% of caregivers reporting patient pain on an average day. Significant differences were found between patients' and caregivers' reports of pain. Two-fifths of patients (40.0%) were prescribed analgesia. Antipsychotic, hypnotic and anxiolytic drug use was low, whereas antidepressant drugs were prescribed more commonly. Presence of pain was unaffected by dementia severity; however, the use of prescribed analgesic medication was a significant predictor of the presence of pain in these patients, whether reported by the patient or their caregiver 'right now' or 'on an average day' (P < 0.001). Patient and caregiver recruitment was challenging, and remains a barrier to research in this area in the future.