Sex-specific incidence and temporal trends in solid tumours in young people from Northern England, 1968–2005

<p>Abstract</p> <p>Background</p> <p>This study examined sex-specific patterns and temporal trends in the incidence of solid tumours in the Northern Region of England from 1968 to 2005. This updates earlier analyses from the region where sex was not considered in depth. Sex-specific analyses were carried out to determine whether sex differences might provide clues to aetiology.</p> <p>Methods</p> <p>Details of 3576 cases, aged 0–24 years, were obtained from a specialist population-based cancer registry. There were 1843 males (886 aged 0–14 years and 957 aged 15–24 years) and 1733 females (791 aged 0–14 years and 942 aged 15–24 years). Age-standardized incidence rates (per million population) were calculated. Linear regression was used to analyze temporal trends in incidence and annual percentage changes were estimated. Analyses were stratified by sex and by age-group.</p> <p>Results</p> <p>There were marked differences in incidence patterns and trends between males and females and also between age-groups. For males central nervous system (CNS) tumours formed the largest proportion of under-15 cases and germ cell tumours was the largest group in the 15–24's, whilst for females CNS tumours dominated in the under-15's and carcinomas in the older group. For 0–14 year olds there were male-specific increases in the incidence of rhabdomyosarcoma (2.4% per annum; 95% CI: 0.2%–4.5%) and non-melanotic skin cancer (9.6%; 95% CI: 0.0%–19.2%) and female-specific increases for sympathetic nervous system tumours (2.2%; 95% CI: 0.4%–3.9%), gonadal germ cell tumours (8.6%; 95% CI: 4.3%–12.9%) and non-gonadal germ cell tumours (5.4%; 95% CI: 2.8%–7.9%). For 15–24 year olds, there were male-specific increases in gonadal germ cell tumours (1.9%; 95% CI: 0.3%–3.4%), non-gonadal germ cell tumours (4.4%; 95% CI: 1.1%–7.7%) and non-melanotic skin cancer (4.7%; 95% CI: 0.5%–8.9%) and female-specific increases for osteosarcoma (3.5%; 95% CI: 0.5%–6.5%), thyroid cancer (2.8%; 95% CI: 0.1%–5.6%) and melanoma (4.6%; 95% CI: 2.2%–7.1%).</p> <p>Conclusion</p> <p>This study has highlighted notable differences between the sexes in incidence patterns and trends for solid tumours. Some of these sex-specific differences could have been obscured if males and females had been analysed together. Furthermore, they suggest aetiological differences or differential susceptibility to environmental factors between males and females.</p

Space-time clustering of childhood central nervous system tumours in Yorkshire, UK

<p>Abstract</p> <p>Background</p> <p>We specifically tested the aetiological hypothesis that a factor influencing geographical or temporal heterogeneity of childhood central nervous system (CNS) tumour incidence was related to exposure to a transient environmental agent.</p> <p>Methods</p> <p>Information was extracted on individuals aged 0-14 years, diagnosed with a CNS tumour between the 1st January 1974 and 31st December 2006 from the Yorkshire Specialist Register of Cancer in Children and Young People. Ordnance Survey eight-digit grid references were allocated to each case with respect to addresses at the time of birth and the time of diagnosis, locating each address to within 0.1 km. The following diagnostic groups were specified <it>a priori </it>for analysis: ependymoma; astrocytoma; primitive neuroectodermal tumours (PNETs); other gliomas; total CNS tumours. We applied the <it>K</it>-function method for testing global space-time clustering using fixed geographical distance thresholds. Tests were repeated using variable nearest neighbour (NN) thresholds.</p> <p>Results</p> <p>There was statistically significant global space-time clustering for PNETs only, based on time and place of diagnosis (<it>P </it>= 0.03 and 0.01 using the fixed geographical distance and the variable NN threshold versions of the <it>K</it>-function method respectively).</p> <p>Conclusions</p> <p>There was some evidence for a transient environmental component to the aetiology of PNETs. However, a possible role for chance cannot be excluded.</p

Reinforcement Learning Tutor Better Supported Lower Performers in a Math Task

Resource limitations make it hard to provide all students with one of the most effective educational interventions: personalized instruction. Reinforcement learning could be a key tool to reduce the development cost and improve the effectiveness of, intelligent tutoring software that aims to provide the right support, at the right time, to a student. Here we illustrate that deep reinforcement learning can be used to provide adaptive pedagogical support to students learning about the concept of volume in a narrative storyline software. Using explainable artificial intelligence tools, we also extracted interpretable insights about the pedagogical policy learned, and we demonstrate that the resulting policy had similar performance in a different student population. Most importantly, in both studies the reinforcement-learning narrative system had the largest benefit for those students with the lowest initial pretest scores, suggesting the opportunity for AI to adapt and provide support for those most in need.Comment: 23 pages. Under revie

Insulin resistance in type 1 diabetes: what is ‘double diabetes’ and what are the risks?

In this review, we explore the concept of ‘double diabetes’, a combination of type 1 diabetes with features of insulin resistance and type 2 diabetes. After considering whether double diabetes is a useful concept, we discuss potential mechanisms of increased insulin resistance in type 1 diabetes before examining the extent to which double diabetes might increase the risk of cardiovascular disease (CVD). We then go on to consider the proposal that weight gain from intensive insulin regimens may be associated with increased CV risk factors in some patients with type 1 diabetes, and explore the complex relationships between weight gain, insulin resistance, glycaemic control and CV outcome. Important comparisons and contrasts between type 1 diabetes and type 2 diabetes are highlighted in terms of hepatic fat, fat partitioning and lipid profile, and how these may differ between type 1 diabetic patients with and without double diabetes. In so doing, we hope this work will stimulate much-needed research in this area and an improvement in clinical practice

Chronic excitotoxin-induced axon degeneration in a compartmented neuronal culture model

Glutamate excitotoxicity is a major pathogenic process implicated in many neurodegenerative conditions, including AD (Alzheimer's disease) and following traumatic brain injury. Occurring predominantly from over-stimulation of ionotropic glutamate receptors located along dendrites, excitotoxic axonal degeneration may also occur in white matter tracts. Recent identification of axonal glutamate receptor subunits within axonal nanocomplexes raises the possibility of direct excitotoxic effects on axons. Individual neuronal responses to excitotoxicity are highly dependent on the complement of glutamate receptors expressed by the cell, and the localization of the functional receptors. To enable isolation of distal axons and targeted excitotoxicity, murine cortical neuron cultures were prepared in compartmented microfluidic devices, such that distal axons were isolated from neuronal cell bodies. Within the compartmented culture system, cortical neurons developed to relative maturity at 11 DIV (days in vitro) as demonstrated by the formation of dendritic spines and clustering of the presynaptic protein synaptophysin. The isolated distal axons retained growth cone structures in the absence of synaptic targets, and expressed glutamate receptor subunits. Glutamate treatment (100 μM) to the cell body chamber resulted in widespread degeneration within this chamber and degeneration of distal axons in the other chamber. Glutamate application to the distal axon chamber triggered a lesser degree of axonal degeneration without degenerative changes in the untreated somal chamber. These data indicate that in addition to current mechanisms of indirect axonal excitotoxicity, the distal axon may be a primary target for excitotoxicity in neurodegenerative conditions

Effects of Thyroxine Exposure on Osteogenesis in Mouse Calvarial Pre-Osteoblasts

The incidence of craniosynostosis is one in every 1,800-2500 births. The gene-environment model proposes that if a genetic predisposition is coupled with environmental exposures, the effects can be multiplicative resulting in severely abnormal phenotypes. At present, very little is known about the role of gene-environment interactions in modulating craniosynostosis phenotypes, but prior evidence suggests a role for endocrine factors. Here we provide a report of the effects of thyroid hormone exposure on murine calvaria cells. Murine derived calvaria cells were exposed to critical doses of pharmaceutical thyroxine and analyzed after 3 and 7 days of treatment. Endpoint assays were designed to determine the effects of the hormone exposure on markers of osteogenesis and included, proliferation assay, quantitative ALP activity assay, targeted qPCR for mRNA expression of Runx2, Alp, Ocn, and Twist1, genechip array for 28,853 targets, and targeted osteogenic microarray with qPCR confirmations. Exposure to thyroxine stimulated the cells to express ALP in a dose dependent manner. There were no patterns of difference observed for proliferation. Targeted RNA expression data confirmed expression increases for Alp and Ocn at 7 days in culture. The genechip array suggests substantive expression differences for 46 gene targets and the targeted osteogenesis microarray indicated 23 targets with substantive differences. 11 gene targets were chosen for qPCR confirmation because of their known association with bone or craniosynostosis (Col2a1, Dmp1, Fgf1, 2, Igf1, Mmp9, Phex, Tnf, Htra1, Por, and Dcn). We confirmed substantive increases in mRNA for Phex, FGF1, 2, Tnf, Dmp1, Htra1, Por, Igf1 and Mmp9, and substantive decreases for Dcn. It appears thyroid hormone may exert its effects through increasing osteogenesis. Targets isolated suggest a possible interaction for those gene products associated with calvarial suture growth and homeostasis as well as craniosynostosis. © 2013 Cray et al

Porcine dentin matrix protein 1: gene structure, cDNA sequence, and expression in teeth

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73278/1/j.1600-0722.2006.00284.x.pd

Detailed Mitochondrial Phenotyping by High Resolution Metabolomics

Mitochondrial phenotype is complex and difficult to define at the level of individual cell types. Newer metabolic profiling methods provide information on dozens of metabolic pathways from a relatively small sample. This pilot study used “top-down” metabolic profiling to determine the spectrum of metabolites present in liver mitochondria. High resolution mass spectral analyses and multivariate statistical tests provided global metabolic information about mitochondria and showed that liver mitochondria possess a significant phenotype based on gender and genotype. The data also show that mitochondria contain a large number of unidentified chemicals

Predicting Landscape-Genetic Consequences of Habitat Loss, Fragmentation and Mobility for Multiple Species of Woodland Birds

Inference concerning the impact of habitat fragmentation on dispersal and gene flow is a key theme in landscape genetics. Recently, the ability of established approaches to identify reliably the differential effects of landscape structure (e.g. land-cover composition, remnant vegetation configuration and extent) on the mobility of organisms has been questioned. More explicit methods of predicting and testing for such effects must move beyond post hoc explanations for single landscapes and species. Here, we document a process for making a priori predictions, using existing spatial and ecological data and expert opinion, of the effects of landscape structure on genetic structure of multiple species across replicated landscape blocks. We compare the results of two common methods for estimating the influence of landscape structure on effective distance: least-cost path analysis and isolation-by-resistance. We present a series of alternative models of genetic connectivity in the study area, represented by different landscape resistance surfaces for calculating effective distance, and identify appropriate null models. The process is applied to ten species of sympatric woodland-dependant birds. For each species, we rank a priori the expectation of fit of genetic response to the models according to the expected response of birds to loss of structural connectivity and landscape-scale tree-cover. These rankings (our hypotheses) are presented for testing with empirical genetic data in a subsequent contribution. We propose that this replicated landscape, multi-species approach offers a robust method for identifying the likely effects of landscape fragmentation on dispersal