Hirschsprung's disease prevalence in Europe: A register based study

Background: Hirschsprung's disease is a congenital gut motility disorder, characterised by the absence of the enteric ganglion cells along the distal gut. The aim of this study was to describe the epidemiology of Hirschsprung's disease, including additional congenital anomalies, total prevalence, trends, and association with maternal age. Methods: Cases of Hirschsprung's disease delivered during 1980 to 2009 notified to 31 European Surveillance of Congenital Anomaly registers formed the population-based case-series. Prevalence rates and 95% confidence intervals were calculated as the number of cases per 10,000 births. Multilevel Poisson regression was performed to investigate trends in prevalence, geographical variation and the association with maternal age. Results: There were 1,322 cases of Hirschsprung's disease among 12,146,210 births. The total prevalence was 1.09 (95% confidence interval, 1.03–1.15) per 10,000 births and there was a small but significant increase in prevalence over time (relative risk = 1.01; 95% credible interval, 1.00–1.02; p = 0.004). There was evidence of geographical heterogeneity in prevalence (p < 0.001). Excluding 146 (11.0%) cases with chromosomal anomalies or genetic syndromes, there were 1,176 cases (prevalence = 0.97; 95% confidence interval, 0.91–1.03 per 10,000 births), of which 137 (11.6%) had major structural anomalies. There was no evidence of a significant increased risk of Hirschsprung's disease in cases born to women aged ≥35 years compared with those aged 25 to 29 (relative risk = 1.09; 95% credible interval, 0.91–1.31; p = 0.355). Conclusion: This large population-based study found evidence of a small increasing trend in Hirschsprung's disease and differences in prevalence by geographic location. There was also no evidence of an association with maternal age.

Prognostic significance of minichromosome maintenance proteins in breast cancer

A role for the minichromosome maintenance (MCM) proteins in cancer initiation and progression is slowly emerging. Functioning as a complex to ensure a single chromosomal replication per cell cycle, the six family members have been implicated in several neoplastic disease states, including breast cancer. Our study aim to investigate the prognostic significance of these proteins in breast cancer. We studied the expression of MCMs in various datasets and the associations of the expression with clinicopathological parameters. When considered alone, high level MCM4 overexpression was only weakly associated with shorter survival in the combined breast cancer patient cohort (n = 1441, Hazard Ratio = 1.31; 95% Confidence Interval = 1.11-1.55; p = 0.001). On the other hand, when we studied all six components of the MCM complex, we found that overexpression of all MCMs was strongly associated with shorter survival in the same cohort (n = 1441, Hazard Ratio = 1.75; 95% Confidence Interval = 1.31-2.34; p <0.001), suggesting these MCM proteins may cooperate to promote breast cancer progression. Indeed, their expressions were significantly correlated with each other in these cohorts. In addition, we found that increasing number of overexpressed MCMs was associated with negative ER status as well as treatment response. Together, our findings are reproducible in seven independent breast cancer cohorts, with 1441 patients, and suggest that MCM profiling could potentially be used to predict response to treatment and prognosis in breast cancer patients.

Discovering subgroups of patients from DNA copy number data using NMF on compacted matrices

In the study of complex genetic diseases, the identification of subgroups of patients sharing similar genetic characteristics represents a challenging task, for example, to improve treatment decision. One type of genetic lesion, frequently investigated in such disorders, is the change of the DNA copy number (CN) at specific genomic traits. Non-negative Matrix Factorization (NMF) is a standard technique to reduce the dimensionality of a data set and to cluster data samples, while keeping its most relevant information in meaningful components. Thus, it can be used to discover subgroups of patients from CN profiles. It is however computationally impractical for very high dimensional data, such as CN microarray data. Deciding the most suitable number of subgroups is also a challenging problem. The aim of this work is to derive a procedure to compact high dimensional data, in order to improve NMF applicability without compromising the quality of the clustering. This is particularly important for analyzing high-resolution microarray data. Many commonly used quality measures, as well as our own measures, are employed to decide the number of subgroups and to assess the quality of the results. Our measures are based on the idea of identifying robust subgroups, inspired by biologically/clinically relevance instead of simply aiming at well-separated clusters. We evaluate our procedure using four real independent data sets. In these data sets, our method was able to find accurate subgroups with individual molecular and clinical features and outperformed the standard NMF in terms of accuracy in the factorization fitness function. Hence, it can be useful for the discovery of subgroups of patients with similar CN profiles in the study of heterogeneous diseases.

Power and Energy Implications of the Number of Threads Used on the Intel Xeon Phi

Energy consumption has become an important area of research of late. With the advent of new manycore processors, situations have arisen where not all the processors need to be active to reach an optimal relation between performance and energy usage. In this paper a study of the power and energy usage of a series of benchmarks, the PARSEC and the SPLASH- 2X Benchmark Suites, on the Intel Xeon Phi for different threads configurations, is presented. To carry out this study, a tool was designed to monitor and record the power usage in real time during execution time and afterwards to compare the r

Mapping neutral, ion and electron number densities within laser ablated plasma plumes

Spatially and temporally varying neutral, ion and electron number densities have been mapped out within laser ablated plasma plumes expanding into vacuum. Ablation of a magnesium target was performed using a KrF laser, 30 ns pulse duration and 248 nm wavelength. During the initial stage of plasma expansion (t <EQ 100 ns) interferometry has been used to obtain line averaged electron number densities, for laser power densities on target in the range 1.3 - 3.0 X 108 W/cm2. Later in the plasma expansion (t equals 1 microsecond(s) ) simultaneous absorption and laser induced fluorescence spectroscopy has been used to determine 3D neutral and ion number densities, for a power density equal to 6.7 X 107 W/cm2. Two distinct regions within the plume were identified. One is a fast component (approximately 106 cm-1) consisting of ions and neutrals with maximum number densities observed to be approximately 30 and 4 X 1012 cm-3 respectively, and the second consists of slow moving neutral material at a number density of up to 1015 cm-3. Additionally a Langmuir probe has been used to obtain ion and electron number densities at very late times in the plasma expansion (1 microsecond(s) <EQ t <EQ 15 microsecond(s) ). A copper target was ablated using a Nd:YAG laser, 7.5 ns duration and 532 nm (2 (omega) ) wavelength, with a power density on target equal to 6 X 108 W/cm2. Two regions within the plume with different velocities were observed. Within a fast component (approximately 3 X 106 cms-1) electron and ion number densities of the order 5 X 1012 cm-3 were observed and within the second slower component (approximately 106 cms-1) electron and ion number densities of the order 1 - 2 X 1013 cm-3 were determined.

Distributed Massive MIMO in Cellular Networks: Impact of Imperfect Hardware and Number of Oscillators

Distributed massive multiple-input multiple-output (MIMO) combines the array gain of coherent MIMO processing with the proximity gains of distributed antenna setups. In this paper, we analyze how transceiver hardware impairments affect the downlink with maximum ratio transmission. We derive closed-form spectral efficiencies expressions and study their asymptotic behavior as the number of the antennas increases. We prove a scaling law on the hardware quality, which reveals that massive MIMO is resilient to additive distortions, while multiplicative phase noise is a limiting factor. It is also better to have separate oscillators at each antenna than one per BS.

The paradox of invasion: Reeves’ muntjac deer invade the British Isles from a limited number of founding females

High levels of genetic diversity and high propagule pressure are favoured by conservation biologists as the basis for successful reintroductions and ensuring the persistence of populations. However, invasion ecologists recognize the ‘paradox of invasion’, as successful species introductions may often be characterized by limited numbers of individuals and associated genetic bottlenecks. In the present study, we used a combination of high-resolution nuclear and mitochondrial genetic markers to investigate the invasion history of Reeves' muntjac deer in the British Isles. This invasion has caused severe economic and ecological damage, with secondary spread currently a concern throughout Europe and potentially globally. Microsatellite analysis based on eight loci grouped all 176 introduced individuals studied from across the species' range in the UK into one genetic cluster, and seven mitochondrial D-loop haplotypes were recovered, two of which were present at very low frequency and were related to more common haplotypes. Our results indicate that the entire invasion can be traced to a single founding event involving a low number of females. These findings highlight the fact that even small releases of species may, if ignored, result in irreversible and costly invasion, regardless of initial genetic diversity or continual genetic influx.

Magnetic Characteristics of a High-layer-number NiFe/FeMn Multilayer

We report the static & dynamic magnetic characteristics of a high-layer-number NiFe/FeMn multilayer test structure with potential applications in broadband absorber and filter devices. To allow fine control over the absorption linewidths and to understand the mechanisms governing the resonances in a tailored structure similar to that expected to be used in real world applications, the multilayer was intentionally designed to have layer thickness and interface roughness variations. Magnetometry measurements show the sample has complex hysteresis loops with features consistent with single ferromagnetic film reversals. Structural characterisation by transmission electron microscopy allows us to correlate the magnetic properties with structural features. Analysis of resonance frequencies from broadband ferromagnetic resonance measurements as a function of field magnitude and orientation provide values of the local exchange bias, rotatable anisotropy, and uniaxial anisotropy fields for specific layers in the stack and explain the observed mode softening. The linewidths of the multilayer are adjustable around the bias field, approaching twice that seen at larger fields, allowing control over the bandwidth of devices formed from the structure.

Evaluation of mixed chimerism by in vitro amplification of dinucleotide repeat sequences using the polymerase chain reaction

The influence of mixed hematopoietic chimerism (MC) after allogeneic bone marrow transplantation remains unknown. Increasingly sensitive detection methods have shown that MC occurs frequently. We report a highly sensitive novel method to assess MC based on the polymerase chain reaction (PCR). Simple dinucleotide repeat sequences called microsatellites have been found to vary in their repeat number between individuals. We use this variation to type donor-recipient pairs following allogeneic BMT. A panel of seven microsatellites was used to distinguish between donor and recipient cells of 32 transplants. Informative microsatellites were subsequently used to assess MC after BMT in this group of patients. Seventeen of the 32 transplants involved a donor of opposite sex; hence, cytogenetics and Y chromosome-specific PCR were also used as an index of chimerism in these patients. MC was detected in bone marrow aspirates and peripheral blood in 18 of 32 patients (56%) by PCR. In several cases, only stored slide material was available for analysis but PCR of microsatellites or Y chromosomal material could be used successfully to assess the origin of cells in this archival material. Cytogenetic analysis was possible in 17 patients and MC was detected in three patients. Twelve patients received T-cell-depleted marrow and showed a high incidence of MC as revealed by PCR (greater than 80%). Twenty patients received unmanipulated marrow, and while the incidence of MC was lower (44%), this was a high percentage when compared with other studies. Once MC was detected, the percentages of recipient cells tended to increase. However, in patients exhibiting MC who subsequently relapsed, this increase was relatively sudden. The overall level of recipient cells in the group of MC patients who subsequently relapsed was higher than in those who exhibited stable MC. Thus, while the occurrence of MC was not indicative of a poor prognosis per se, sudden increases in the proportions of recipient cells may be a prelude to graft rejection or relapse.

The mitochondrial and autosomal mutation landscapes of prostate cancer

BACKGROUND: Prostate cancer (PCa) is the most common cancer in men. PCa is strongly age associated; low death rates in surveillance cohorts call into question the widespread use of surgery, which leads to overtreatment and a reduction in quality of life. There is a great need to increase the understanding of tumor characteristics in the context of disease progression.

OBJECTIVE: To perform the first multigenome investigation of PCa through analysis of both autosomal and mitochondrial DNA, and to integrate exome sequencing data, and RNA sequencing and copy-number alteration (CNA) data to investigate how various different tumor characteristics, commonly analyzed separately, are interconnected.

DESIGN, SETTING, AND PARTICIPANTS: Exome sequencing was applied to 64 tumor samples from 55 PCa patients with varying stage and grade. Integrated analysis was performed on a core set of 50 tumors from which exome sequencing, CNA, and RNA sequencing data were available.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Genes, mutated at a significantly higher rate relative to a genomic background, were identified. In addition, mitochondrial and autosomal mutation rates were correlated to CNAs and proliferation, assessed as a cell cycle gene expression signature.

RESULTS AND LIMITATIONS: Genes not previously reported to be significantly mutated in PCa, such as cell division cycle 27 homolog (Saccharomyces cerevisiae) (CDC27), myeloid/lymphoid or mixed-lineage leukemia 3 (MLL3), lysine (K)-specific demethylase 6A (KDM6A), and kinesin family member 5A (KIF5A) were identified. The mutation rate in the mitochondrial genome was 55 times higher than that of the autosomes. Multilevel analysis demonstrated a tight correlation between high reactive-oxygen exposure, chromosomal damage, high proliferation, and in parallel, a transition from multiclonal indolent primary PCa to monoclonal aggressive disease. As we only performed targeted sequence analysis; copy-number neutral rearrangements recently described for PCa were not accounted for.

CONCLUSIONS: The mitochondrial genome displays an elevated mutation rate compared to the autosomal chromosomes. By integrated analysis, we demonstrated that different tumor characteristics are interconnected, providing an increased understanding of PCa etiology.

AURKA overexpression accompanies dysregulation of DNA-damage response genes in invasive urothelial cell carcinoma

Invasive urothelial cell carcinoma (UCC) is characterized by increased chromosomal instability and follows an aggressive clinical course in contrast to non-invasive disease. To identify molecular processes that confer and maintain an aggressive malignant phenotype, we used a high-throughput genome-wide approach to interrogate a cohort of high and low clinical risk UCC tumors. Differential expression analyses highlighted cohesive dysregulation of critical genes involved in the G(2)/M checkpoint in aggressive UCC. Hierarchical clustering based on DNA Damage Response (DDR) genes separated tumors according to a pre-defined clinical risk phenotype. Using array-comparative genomic hybridization, we confirmed that the DDR was disrupted in tumors displaying high genomic instability. We identified DNA copy number gains at 20q13.2-q13.3 (AURKA locus) and determined that overexpression of AURKA accompanied dysregulation of DDR genes in high risk tumors. We postulated that DDR-deficient UCC tumors are advantaged by a selective pressure for AURKA associated override of M phase barriers and confirmed this in an independent tissue microarray series. This mechanism that enables cancer cells to maintain an aggressive phenotype forms a rationale for targeting AURKA as a therapeutic strategy in advanced stage UCC.

A new look towards BAC-based array CGH through a comprehensive comparison with oligo-based array CGH

BACKGROUND: Currently, two main technologies are used for screening of DNA copy number; the BAC (Bacterial Artificial Chromosome) and the recently developed oligonucleotide-based CGH (Chromosomal Comparative Genomic Hybridization) arrays which are capable of detecting small genomic regions with amplification or deletion. The correlation as well as the discriminative power of these platforms has never been compared statistically on a significant set of human patient samples.

RESULTS: In this paper, we present an exhaustive comparison between the two CGH platforms, undertaken at two independent sites using the same batch of DNA from 19 advanced prostate cancers. The comparison was performed directly on the raw data and a significant correlation was found between the two platforms. The correlation was greatly improved when the data were averaged over large chromosomic regions using a segmentation algorithm. In addition, this analysis has enabled the development of a statistical model to discriminate BAC outliers that might indicate microevents. These microevents were validated by the oligo platform results.

CONCLUSION: This article presents a genome-wide statistical validation of the oligo array platform on a large set of patient samples and demonstrates statistically its superiority over the BAC platform for the Identification of chromosomic events. Taking advantage of a large set of human samples treated by the two technologies, a statistical model has been developed to show that the BAC platform could also detect microevents.

Low alanine aminotransferase levels and higher number of cardiovascular events in people with Type 2 diabetes: analysis of the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) study.

AIMS: To determine whether alanine aminotransferase or gamma-glutamyltransferase levels, as markers of liver health and non-alcoholic fatty liver disease, might predict cardiovascular events in people with Type 2 diabetes.

METHODS: Data from the Fenofibrate Intervention and Event Lowering in Diabetes study were analysed to examine the relationship between liver enzymes and incident cardiovascular events (non-fatal myocardial infarction, stroke, coronary and other cardiovascular death, coronary or carotid revascularization) over 5 years.

RESULTS: Alanine aminotransferase level had a linear inverse relationship with the first cardiovascular event occurring in participants during the study period. After adjustment, for every 1 sd higher baseline alanine aminotransferase value (13.2 U/l), the risk of a cardiovascular event was 7% lower (95% CI 4-13; P=0.02). Participants with alanine aminotransferase levels below and above the reference range 8-41 U/l for women and 9-59 U/l for men, had hazard ratios for a cardiovascular event of 1.86 (95% CI 1.12-3.09) and 0.65 (95% CI 0.49-0.87), respectively (P=0.001). No relationship was found for gamma-glutamyltransferase.

CONCLUSIONS: The data may indicate that in people with Type 2 diabetes, which is associated with higher alanine aminotransferase levels because of prevalent non-alcoholic fatty liver disease, a low alanine aminotransferase level is a marker of hepatic or systemic frailty rather than health. This article is protected by copyright. All rights reserved.