A savings based method for real-life vehicle routing problems

This paper describes a Savings Based algorithm for the Extended Vehicle Routing Problem. This algorithm is compared with a Sequential Insertion algorithm on real-life data. Besides the traditional quality measures such as total distance traveled and total workload, we compare the routing plans of both algorithms according to non-standard quality measures that h

Genetic variants for head size share genes and pathways with cancer

The size of the human head is highly heritable, but genetic drivers of its variation within the general population remain unmapped. We perform a genome-wide association study on head size (N = 80,890) and identify 67 genetic loci, of which 50 are novel. Neuroimaging studies show that 17 variants affect specific brain areas, but most have widespread effects. Gene set enrichment is observed for various cancers and the p53, Wnt, and ErbB signaling pathways. Genes harboring lead variants are enriched for macrocephaly syndrome genes (37-fold) and high-fidelity cancer genes (9-fold), which is not seen for human height variants. Head size variants are also near genes preferentially expressed in intermediate progenitor cells, neural cells linked to evolutionary brain expansion. Our results indicate that genes regulating early brain and cranial growth incline to neoplasia later in life, irrespective of height. This warrants investigation of clinical implications of the link between head size and cancer.</p

The BAF complex interacts with Pax6 in adult neural progenitors to establish a neurogenic cross-regulatory transcriptional network

Numerous transcriptional regulators of neurogenesis have been identified in the developing and adult brain, but how neurogenic fate is programmed at the epigenetic level remains poorly defined. Here, we report that the transcription factor Pax6 directly interacts with the Brg1-containing BAF complex in adult neural progenitor

Genetic Variants For Head Size Share Genes and Pathways With Cancer

The size of the human head is highly heritable, but genetic drivers of its variation within the general population remain unmapped. We perform a genome-wide association study on head size (N = 80,890) and identify 67 genetic loci, of which 50 are novel. Neuroimaging studies show that 17 variants affect specific brain areas, but most have widespread effects. Gene set enrichment is observed for various cancers and the p53, Wnt, and ErbB signaling pathways. Genes harboring lead variants are enriched for macrocephaly syndrome genes (37-fold) and high-fidelity cancer genes (9-fold), which is not seen for human height variants. Head size variants are also near genes preferentially expressed in intermediate progenitor cells, neural cells linked to evolutionary brain expansion. Our results indicate that genes regulating early brain and cranial growth incline to neoplasia later in life, irrespective of height. This warrants investigation of clinical implications of the link between head size and cancer

Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals

We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of ~3 million individuals and identify 3,952 approximately uncorrelated genome-wide-significant single-nucleotide polymorphisms (SNPs). A genome-wide polygenic predictor, or polygenic index (PGI), explains 12-16% of EA variance and contributes to risk prediction for ten diseases. Direct effects (i.e., controlling for parental PGIs) explain roughly half the PGI's magnitude of association with EA and other phenotypes. The correlation between mate-pair PGIs is far too large to be consistent with phenotypic assortment alone, implying additional assortment on PGI-associated factors. In an additional GWAS of dominance deviations from the additive model, we identify no genome-wide-significant SNPs, and a separate X-chromosome additive GWAS identifies 57

Genome-wide association study identifies 74 loci associated with educational attainment

Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals1. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample1,2 of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases

Diffusion MRI microstructure models with in vivo human brain Connectome data: results from a multi-group comparison

A large number of mathematical models have been proposed to describe the measured signal in diffusion-weighted (DW) magnetic resonance imaging (MRI). However, model comparison to date focuses only on specific subclasses, e.g. compartment models or signal models, and little or no information is available in the literature on how performance varies among the different types of models. To address this deficiency, we organized the ‘White Matter Modeling Challenge’ during the International Symposium on Biomedical Imaging (ISBI) 2015 conference. This competition aimed to compare a range of different kinds of models in their ability to explain a large range of measurable in vivo DW human brain data. Specifically, we assessed the ability of models to predict the DW signal accurately for new diffusion gradients and b values. We did not evaluate the accuracy of estimated model parameters, as a ground truth is hard to obtain. We used the Connectome scanner at the Massachusetts General Hospital, using gradient strengths of up to 300 mT/m and a broad set of diffusion times. We focused on assessing the DW signal prediction in two regions: the genu in the corpus callosum, where the fibres are relatively straight and parallel, and the fornix, where the configuration of fibres is more complex. The challenge participants had access to three-quarters of the dataset and their models were ranked on their ability to predict the remaining unseen quarter of the data. The challenge provided a unique opportunity for a quantitative comparison of diverse methods from multiple groups worldwide. The comparison of the challenge entries reveals interesting trends that could potentially influence the next generation of diffusion-based quantitative MRI techniques. The first is that signal models do not necessarily outperform tissue models; in fact, of those tested, tissue models rank highest on average. The second is that assuming a non-Gaussian (rather than purely Gaussian) noise model provides little improvement in prediction of unseen data, although it is possible that this may still have a beneficial effect on estimated parameter values. The third is that preprocessing the training data, here by omitting signal outliers, and using signal-predicting strategies, such as bootstrapping or cross-validation, could benefit the model fitting. The analysis in this study provides a benchmark for other models and the data remain available to build up a more complete comparison in the future

Heterogeneous clinical phenotypes and cerebral malformations reflected by rotatin cellular dynamics

Recessive mutations in RTTN, encoding the protein rotatin, were originally identified as cause of polymicrogyria, a cortical malformation. With time, a wide variety of other brain malformations has been ascribed to RTTN mutations, including primary microcephaly. Rotatin is a centrosomal protein possibly involved in centriolar elongation and ciliogenesis. However, the function of rotatin in brain development is largely unknown and the molecular disease mechanism underlying cortical malformations has not yet been elucidated. We performed both clinical and cell biological studies, aimed at clarifying rotatin function and pathogenesis. Review of the 23 published and five unpublished clinical cases and genomic mutations, including the effect of novel deep intronic pathogenic mutations on RTTN transcripts, allowed us to extrapolate the core phenotype, consisting of intellectual disability, short stature, microcephaly, lissencephaly, periventricular heterotopia, polymicrogyria and other malformations. We show that the severity of the phenotype is related to residual function of the protein, not only the level of mRNA expression. Skin fibroblasts from eight affected individuals were studied by high resolution immunomicroscopy and flow cytometry, in parallel with in vitro expression of RTTN in HEK293T cells. We demonstrate that rotatin regulates different phases of the cell cycle and is mislocalized in affected individuals. Mutant cells showed consistent and severe mitotic failure with centrosome amplification and multipolar spindle formation, leading to aneuploidy and apoptosis, which could relate to depletion of neuronal progenitors often observed in microcephaly. We confirmed the role of rotatin in functional and structural maintenance of primary cilia and determined that the protein localized not only to the basal body, but also to the axoneme, proving the functional interconnectivity between ciliogenesis and cell cycle progression. Proteomics analysis of both native and exogenous rotatin uncovered that rotatin interacts with the neuronal (non-muscle) myosin heavy chain subunits, motors of nucleokinesis during neuronal migration, and in human induced pluripotent stem cell-derived bipolar mature neurons rotatin localizes at the centrosome in the leading edge. This illustrates the role of rotatin in neuronal migration. These different functions of rotatin explain why RTTN mutations can lead to heterogeneous cerebral malformations, both related to proliferation and migration defects