Pearl hunter : an inspired hyper-heuristic

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Towards a learning-based heuristic searching reform scheme

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A hyper-heuristic inspired by pearl hunting

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Pearl hunter: a cross-domain hyper-heuristic that compiles iterated local search algorithms

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IL8 polymorphisms and overall survival in pazopanib- or sunitinib-treated patients with renal cell carcinoma.

BACKGROUND: We evaluated germline single nucleotide polymorphisms (SNPs) for association with overall survival (OS) in pazopanib- or sunitinib-treated patients with advanced renal cell carcinoma (aRCC). METHODS: The discovery analysis tested 27 SNPs within 13 genes from a phase III pazopanib trial (N=241, study 1). Suggestive associations were then pursued in two independent datasets: a phase III trial (COMPARZ) comparing pazopanib vs sunitinib (N=729, study 2) and an observational study of sunitinib-treated patients (N=89, study 3). RESULTS: In study 1, four SNPs showed nominally significant association (P≤0.05) with OS; two of these SNPs (rs1126647, rs4073) in IL8 were associated (P≤0.05) with OS in study 2. Because rs1126647 and rs4073 were highly correlated, only rs1126647 was evaluated in study 3, which also showed association (P≤0.05). In the combined data, rs1126647 was associated with OS after conservative multiple-test adjustment (P=8.8 × 10(-5); variant vs reference allele hazard ratio 1.32, 95% confidence interval: 1.15-1.52), without evidence for heterogeneity of effects between studies or between pazopanib- and sunitinib-treated patients. CONCLUSIONS: Variant alleles of IL8 polymorphisms are associated with poorer survival outcomes in pazopanib- or sunitinib-treated patients with aRCC. These findings provide insight in aRCC prognosis and may advance our thinking in development of new therapies

Expression and DNA methylation of TNF, IFNG and FOXP3 in colorectal cancer and their prognostic significance.

BACKGROUND: Colorectal cancer (CRC) progression is associated with suppression of host cell-mediated immunity and local immune escape mechanisms. Our aim was to assess the immune function in terms of expression of TNF, IFNG and FOXP3 in CRC. METHODS: Sixty patients with CRC and 15 matched controls were recruited. TaqMan quantitative PCR and methylation-specific PCR was performed for expression and DNA methylation analysis of TNF, IFNG and FOXP3. Survival analysis was performed over a median follow-up of 48 months. RESULTS: TNF was suppressed in tumour and IFNG was suppressed in peripheral blood mononuclear cells (PBMCs) of patients with CRC. Tumours showed enhanced expression of FOXP3 and was significantly higher when tumour size was >38 mm (median tumour size; P=0.006, Mann-Whitney U-test). Peripheral blood mononuclear cell IFNG was suppressed in recurrent CRC (P=0.01). Methylated TNFpromoter (P=0.003) and TNFexon1 (P=0.001) were associated with significant suppression of TNF in tumours. Methylated FOXP3cpg was associated with significant suppression of FOXP3 in both PBMC (P=0.018) and tumours (P=0.010). Reduced PBMC FOXP3 expression was associated with significantly worse overall survival (HR=8.319, P=0.019). CONCLUSIONS: We have detected changes in the expression of immunomodulatory genes that could act as biomarkers for prognosis and future immunotherapeutic strategies

Interleukin-1β sequesters hypoxia inducible factor 2α to the primary cilium.

BACKGROUND: The primary cilium coordinates signalling in development, health and disease. Previously we have shown that the cilium is essential for the anabolic response to loading and the inflammatory response to interleukin-1β (IL-1β). We have also shown the primary cilium elongates in response to IL-1β exposure. Both anabolic phenotype and inflammatory pathology are proposed to be dependent on hypoxia-inducible factor 2 alpha (HIF-2α). The present study tests the hypothesis that an association exists between the primary cilium and HIFs in inflammatory signalling. RESULTS: Here we show, in articular chondrocytes, that IL-1β-induces primary cilia elongation with alterations to cilia trafficking of arl13b. This elongation is associated with a transient increase in HIF-2α expression and accumulation in the primary cilium. Prolyl hydroxylase inhibition results in primary cilia elongation also associated with accumulation of HIF-2α in the ciliary base and axoneme. This recruitment and the associated cilia elongation is not inhibited by blockade of HIFα transcription activity or rescue of basal HIF-2α expression. Hypomorphic mutation to intraflagellar transport protein IFT88 results in limited ciliogenesis. This is associated with increased HIF-2α expression and inhibited response to prolyl hydroxylase inhibition. CONCLUSIONS: These findings suggest that ciliary sequestration of HIF-2α provides negative regulation of HIF-2α expression and potentially activity. This study indicates, for the first time, that the primary cilium regulates HIF signalling during inflammation

Multi-Target Prediction: A Unifying View on Problems and Methods

Multi-target prediction (MTP) is concerned with the simultaneous prediction of multiple target variables of diverse type. Due to its enormous application potential, it has developed into an active and rapidly expanding research field that combines several subfields of machine learning, including multivariate regression, multi-label classification, multi-task learning, dyadic prediction, zero-shot learning, network inference, and matrix completion. In this paper, we present a unifying view on MTP problems and methods. First, we formally discuss commonalities and differences between existing MTP problems. To this end, we introduce a general framework that covers the above subfields as special cases. As a second contribution, we provide a structured overview of MTP methods. This is accomplished by identifying a number of key properties, which distinguish such methods and determine their suitability for different types of problems. Finally, we also discuss a few challenges for future research

Choosing Organic Pesticides over Synthetic Pesticides May Not Effectively Mitigate Environmental Risk in Soybeans

Background: Selection of pesticides with small ecological footprints is a key factor in developing sustainable agricultural systems. Policy guiding the selection of pesticides often emphasizes natural products and organic-certified pesticides to increase sustainability, because of the prevailing public opinion that natural products are uniformly safer, and thus more environmentally friendly, than synthetic chemicals. Methodology/Principal Findings: We report the results of a study examining the environmental impact of several new synthetic and certified organic insecticides under consideration as reduced-risk insecticides for soybean aphid (Aphis glycines) control, using established and novel methodologies to directly quantify pesticide impact in terms of biocontrol services. We found that in addition to reduced efficacy against aphids compared to novel synthetic insecticides, organic approved insecticides had a similar or even greater negative impact on several natural enemy species in lab studies, were more detrimental to biological control organisms in field experiments, and had higher Environmental Impact Quotients at field use rates. Conclusions/Significance: These data bring into caution the widely held assumption that organic pesticides are more environmentally benign than synthetic ones. All pesticides must be evaluated using an empirically-based risk assessment

Multi-agent modeling and analysis of EV users’ travel willingness based on an integrated causal/statistical/behavioral model

An electric vehicle (EV) centred ecosystem has not yet been formed, the existing limited statistic data are far from enough for the analysis of EV users’ travel and charge behaviors, which however tends to be affected by many certain and uncertain factors. An experimental economics (EE) based simulation method can be used to analyze the behaviors of key participants in a system. However, it is restricted by the system size, experimental site and the number of qualified human participants. Therefore, this method is hard to be adopted for the behavioral analysis of a large number of human participants. In this paper, a new method combining a questionnaire statistics and the EE-based simulation is proposed. The causal relationship is considered in the design of the questionnaires and data extraction, then a multi-agent modeling integration method is introduced in the EE-based simulation, which enables the integration of causal/statistical/behavioral models into the multi-agent framework to reflect the EV users’ travel willingness statistically. The generated multi-agents are used to replace human participants in the EE-based simulation in order to evaluate EV users’ travel demands in different scenarios, and compare the differences of simulated or measured travel behaviors between potential EV users and internal combustion engine (ICE) vehicle users