A feature selection approach for identification of signature genes from SAGE data

Abstract Background One goal of gene expression profiling is to identify signature genes that robustly distinguish different types or grades of tumors. Several tumor classifiers based on expression profiling have been proposed using microarray technique. Due to important differences in the probabilistic models of microarray and SAGE technologies, it is important to develop suitable techniques to select specific genes from SAGE measurements. Results A new framework to select specific genes that distinguish different biological states based on the analysis of SAGE data is proposed. The new framework applies the bolstered error for the identification of strong genes that separate the biological states in a feature space defined by the gene expression of a training set. Credibility intervals defined from a probabilistic model of SAGE measurements are used to identify the genes that distinguish the different states with more reliability among all gene groups selected by the strong genes method. A score taking into account the credibility and the bolstered error values in order to rank the groups of considered genes is proposed. Results obtained using SAGE data from gliomas are presented, thus corroborating the introduced methodology. Conclusion The model representing counting data, such as SAGE, provides additional statistical information that allows a more robust analysis. The additional statistical information provided by the probabilistic model is incorporated in the methodology described in the paper. The introduced method is suitable to identify signature genes that lead to a good separation of the biological states using SAGE and may be adapted for other counting methods such as Massive Parallel Signature Sequencing (MPSS) or the recent Sequencing-By-Synthesis (SBS) technique. Some of such genes identified by the proposed method may be useful to generate classifiers.

In situ and remote sensing signature of meddies east of the mid-Atlantic ridge

[EN] Mediterranean Water eddies (meddies) are thought to play an important climatic role. Nevertheless, their dynamics are not sufficiently known because of difficulties encountered in their observation. Though propagating below the main thermocline, a number of pieces of evidence of sea surface manifestation of meddies are collected. The present work is based on joint in situ and altimetry data analyses to prove that the meddies can be followed with remote sensing data for long periods of time. The in situ observations are based on data from an oceanographic cruise, which crossed three meddies, and reanalysis of historical data sets, including RAFOS floats paths. Suggested methodology permitted us to obtain uninterrupted tracks for several meddies for a period from several months to more than 2 years. It was found that the dynamically calm region to the north of the Azores current presents favorable conditions for meddy tracking. The meddy surface signal may become shattered and difficult to follow during interaction with a strong dynamic structures (the Azores current/surface vortexes) or peaking topography. Theoretical considerations support the observations and lead to the conclusion that the dynamic signature of meddies at the sea surface is an intrinsic property of meddy dynamics

The genetic signature of Neolithic in Greece

The Neolithic is characterized by the transition from a subsistence economy, based on hunting and gathering, to one based on food producing. This important change was paralleled by one of the most significant demographic increase in the recent history of European populations. The earliest Neolithic sites in Europe are located in Greece. However, the debate regarding the colonization route followed by the Middle-eastern farmers is still open. Based on archaeological, archaeobotanical, craniometric and genetic data, two main hypotheses have been proposed. The first implies the maritime colonization of North-eastern Peloponnesus from Crete, whereas the second points to an island hopping route that finally brought migrants to Central Greece. To test these hypotheses using a genetic approach, 206 samples were collected from the two Greek regions proposed as the arrival point of the two routes (Korinthian district and Euboea). Expectations for each hypothesis were compared with empirical observations based on the analysis of 60 SNPs and 26 microsatellite loci of Y-chromosome and mitochondrial DNA hypervariable region I. The analysis of Y-chromosome haplogroups revealed a strong genetic affinity of Euboea with Anatolian and Middle-eastern populations. The inferences of the time since population expansion suggests an earlier usage of agriculture in Euboea. Moreover, the haplogroup J2a-M410, supposed to be associated with the Neolithic transition, was observed at higher frequency and variance in Euboea showing, for both these parameters, a decreasing gradient moving from this area. The time since expansion estimates for J2a-M410 was found to be compatible with the Neolithic and slightly older in Euboea. The analysis of mtDNA resulted less informative. However, a higher genetic affinity of Euboea with Anatolian and Middle-eastern populations was confirmed. These results taken as a whole suggests that the most probable route followed by Neolithic farmers during the colonization of Greece was the island hopping route.

Diagnosis and Fault detection in Electrical Machines and Drives based on Advanced Signal Processing Techniques

In the present thesis, a new methodology of diagnosis based on advanced use of time-frequency technique analysis is presented. More precisely, a new fault index that allows tracking individual fault components in a single frequency band is defined. More in detail, a frequency sliding is applied to the signals being analyzed (currents, voltages, vibration signals), so that each single fault frequency component is shifted into a prefixed single frequency band. Then, the discrete Wavelet Transform is applied to the resulting signal to extract the fault signature in the frequency band that has been chosen. Once the state of the machine has been qualitatively diagnosed, a quantitative evaluation of the fault degree is necessary. For this purpose, a fault index based on the energy calculation of approximation and/or detail signals resulting from wavelet decomposition has been introduced to quantify the fault extend. The main advantages of the developed new method over existing Diagnosis techniques are the following: - Capability of monitoring the fault evolution continuously over time under any transient operating condition; - Speed/slip measurement or estimation is not required; - Higher accuracy in filtering frequency components around the fundamental in case of rotor faults; - Reduction in the likelihood of false indications by avoiding confusion with other fault harmonics (the contribution of the most relevant fault frequency components under speed-varying conditions are clamped in a single frequency band); - Low memory requirement due to low sampling frequency; - Reduction in the latency of time processing (no requirement of repeated sampling operation).

Epigenetic signature in persons with Down Syndrome

Persons affected by Down Syndrome show a heterogeneous phenotype that includes developmental defects and cognitive and haematological disorders. Premature accelerated aging and the consequent development of age associated diseases like Alzheimer Disease (AD) seem to be the cause of higher mortality late in life of DS persons. Down Syndrome is caused by the complete or partial trisomy of chromosome 21, but it is not clear if the molecular alterations of the disease are triggered by the specific functions of a limited number of genes on chromosome 21 or by the disruption of genetic homeostasis due the presence of a trisomic chromosome. As epigenomic studies can help to shed light on this issue, here we used the Infinium HumanMethilation450 BeadChip to analyse blood DNA methylation patterns of 29 persons affected by Down syndrome (DSP), using their healthy siblings (DSS) and mothers (DSM) as controls. In this way we obtained a family-based model that allowed us to monitor possible confounding effects on DNA methylation patterns deriving from genetic and environmental factors. We showed that defects in DNA methylation map in genes involved in developmental, neurological and haematological pathways. These genes are enriched on chromosome 21 but localize also in the rest of the genome, suggesting that the trisomy of specific genes on chromosome 21 induces a cascade of events that engages many genes on other chromosomes and results in a global alteration of genomic function. We also analysed the methylation status of three target regions localized at the promoter (Ribo) and at the 5’ sequences of 18S and 28S regions of the rDNA, identifying differently methylated CpG sites. In conclusion, we identified an epigenetic signature of Down Syndrome in blood cells that sustains a link between developmental defects and disease phenotype, including segmental premature aging.

Antiepileptic drugs and pregnancy. Population based pharmaco-epidemiological study on prescription patterns, pregnancy outcome and foetal health

Aims of the study: To assess the prevalence of Antiepileptic Drug (AED) exposure in pregnant women with or without epilepsy and the comparative risk of terminations of pregnancy (TOPs), spontaneous abortions, stillbirth, major congenital malformations (MCMs) and foetal growth retardation (FGR) following intrauterine AED exposure in the Emilia Romagna region (RER), Northern Italy (4 million inhabitants). Methods: Data were obtained from official regional registries: Certificate of Delivery Assistance, Hospital Discharge Card, reimbursed prescription databases and Registry of Congenital Malformations. We identified all the deliveries, hospitalized abortions and MCMs occurred between January 2009 and December 2011. Results: We identified 145,243 pregnancies: 111,284 deliveries (112,845 live births and 279 stillbirths), 16408 spontaneous abortions and 17551 TOPs. Six hundred and eleven pregnancies (0.42% 95% Cl: 0.39-0.46) were exposed to AEDs. Twenty-one per cent of pregnancies ended in TOP in the AED group vs 12% in the non-exposed (OR:2.24; CI 1.41-3.56). The rate of spontaneous abortions and stillbirth was comparable in the two groups. Three hundred fifty-three babies (0.31%, 95% CI: 0.28-0.35) were exposed to AEDs during the first trimester. The rate of MCMs was 2.3% in the AED group (2.2% in babies exposed to monotherapy and 3.1% in babies exposed to polytherapy) vs 2.0% in the non-exposed. The risk of FGR was 12.7 % in the exposed group compared to 10% in the non-exposed. Discussion and Conclusion: The prevalence of AED exposure in pregnancy in the RER was 0.42%. The rate of MCMs in children exposed to AEDs in utero was almost superimposable to the one of the non-exposed, however polytherapy carried a slightly increased risk . The rate of TOPs was significantly higher in the exposed women. Further studies are needed to clarify whether this high rate reflects a higher rate of MCMs detected prenatally or other more elusive reasons.

UPLC-MS-based urine metabolomics reveals indole-3-lactic acid and phenyllactic acid as conserved biomarkers for alcohol-induced liver disease in the Ppara-null mouse model

Since the development and prognosis of alcohol-induced liver disease (ALD) vary significantly with genetic background, identification of a genetic background-independent noninvasive ALD biomarker would significantly improve screening and diagnosis. This study explored the effect of genetic background on the ALD-associated urinary metabolome using the Ppara-null mouse model on two different backgrounds, C57BL/6 (B6) and 129/SvJ (129S), along with their wild-type counterparts. Reversed-phase gradient UPLC-ESI-QTOF-MS analysis revealed that urinary excretion of a number of metabolites, such as ethylsulfate, 4-hydroxyphenylacetic acid, 4-hydroxyphenylacetic acid sulfate, adipic acid, pimelic acid, xanthurenic acid, and taurine, were background-dependent. Elevation of ethyl-β-d-glucuronide and N-acetylglycine was found to be a common signature of the metabolomic response to alcohol exposure in wild-type as well as in Ppara-null mice of both strains. However, increased excretion of indole-3-lactic acid and phenyllactic acid was found to be a conserved feature exclusively associated with the alcohol-treated Ppara-null mouse on both backgrounds that develop liver pathologies similar to the early stages of human ALD. These markers reflected the biochemical events associated with early stages of ALD pathogenesis. The results suggest that indole-3-lactic acid and phenyllactic acid are potential candidates for conserved and pathology-specific high-throughput noninvasive biomarkers for early stages of ALD.

Expression profiling of stem cell-related genes in neoadjuvant-treated gastric cancer: a NOTCH2, GSK3B and β-catenin gene signature predicts survival

Cancer stem cell (CSC) based gene expression signatures are associated with prognosis in various tumour types and CSCs are suggested to be particularly drug resistant. The aim of our study was first, to determine the prognostic significance of CSC-related gene expression in residual tumour cells of neoadjuvant-treated gastric cancer (GC) patients. Second, we wished to examine, whether expression alterations between pre- and post-therapeutic tumour samples exist, consistent with an enrichment of drug resistant tumour cells. The expression of 44 genes was analysed in 63 formalin-fixed, paraffin embedded tumour specimens with partial tumour regression (10-50% residual tumour) after neoadjuvant chemotherapy by quantitative real time PCR low-density arrays. A signature of combined GSK3B(high), β-catenin (CTNNB1)(high) and NOTCH2(low) expression was strongly correlated with better patient survival (p<0.001). A prognostic relevance of these genes was also found analysing publically available gene expression data. The expression of 9 genes was compared between pre-therapeutic biopsies and post-therapeutic resected specimens. A significant post-therapeutic increase in NOTCH2, LGR5 and POU5F1 expression was found in tumours with different tumour regression grades. No significant alterations were observed for GSK3B and CTNNB1. Immunohistochemical analysis demonstrated a chemotherapy-associated increase in the intensity of NOTCH2 staining, but not in the percentage of NOTCH2. Taken together, the GSK3B, CTNNB1 and NOTCH2 expression signature is a novel, promising prognostic parameter for GC. The results of the differential expression analysis indicate a prominent role for NOTCH2 and chemotherapy resistance in GC, which seems to be related to an effect of the drugs on NOTCH2 expression rather than to an enrichment of NOTCH2 expressing tumour cells.

Synchronisation of the EDML and EDC ice cores for the last 52 kyr by volcanic signature matching

A common time scale for the EPICA ice cores from Dome C (EDC) and Dronning Maud Land (EDML) has been established. Since the EDML core was not drilled on a dome, the development of the EDML1 time scale for the EPICA ice core drilled in Dronning Maud Land was based on the creation of a detailed stratigraphic link between EDML and EDC, which was dated by a simpler 1D ice-flow model. The synchronisation between the two EPICA ice cores was done through the identification of several common volcanic signatures. This paper describes the rigorous method, using the signature of volcanic sulfate, which was employed for the last 52 kyr of the record. We estimated the discrepancies between the modelled EDC and EDML glaciological age scales during the studied period, by evaluating the ratio R of the apparent duration of temporal intervals between pairs of isochrones. On average R ranges between 0.8 and 1.2 corresponding to an uncertainty of up to 20% in the estimate of the time duration in at least one of the two ice cores. Significant deviations of R up to 1.4–1.5 are observed between 18 and 28 kyr before present (BP), where present is defined as 1950. At this stage our approach does not allow us unequivocally to find out which of the models is affected by errors, but assuming that the thinning function at both sites and accumulation history at Dome C (which was drilled on a dome) are correct, this anomaly can be ascribed to a complex spatial accumulation variability (which may be different in the past compared to the present day) upstream of the EDML core.

Toward an early diagnosis of lung cancer: an autoantibody signature for squamous cell lung carcinoma

Serum-based diagnosis offers the prospect of early lung carcinoma detection and of differentiation between benign and malignant nodules identified by CT. One major challenge toward a future blood-based diagnostic consists in showing that seroreactivity patterns allow for discriminating lung cancer patients not only from normal controls but also from patients with non-tumor lung pathologies. We addressed this question for squamous cell lung cancer, one of the most common lung tumor types. Using a panel of 82 phage-peptide clones, which express potential autoantigens, we performed serological spot assay. We screened 108 sera, including 39 sera from squamous cell lung cancer patients, 29 sera from patients with other non-tumor lung pathologies, and 40 sera from volunteers without known disease. To classify the serum groups, we employed the standard Naïve Bayesian method combined with a subset selection approach. We were able to separate squamous cell lung carcinoma and normal sera with an accuracy of 93%. Low-grade squamous cell lung carcinoma were separated from normal sera with an accuracy of 92.9%. We were able to distinguish squamous cell lung carcinoma from non-tumor lung pathologies with an accuracy of 83%. Three phage-peptide clones with sequence homology to ROCK1, PRKCB1 and KIAA0376 reacted with more than 15% of the cancer sera, but neither with normal nor with non-tumor lung pathology sera. Our study demonstrates that seroreactivity profiles combined with statistical classification methods have great potential for discriminating patients with squamous cell lung carcinoma not only from normal controls but also from patients with non-tumor lung pathologies.

Wireless and passive pressure sensor system based on the magnetic higher-order harmonic field

The goal of this work is to develop a magnetic-based passive and wireless pressure sensor for use in biomedical applications. Structurally, the pressure sensor, referred to as the magneto-harmonic pressure sensor, is composed of two magnetic elements: a magnetically-soft material acts as a sensing element, and a magnetically hard material acts as a biasing element. Both elements are embedded within a rigid sensor body and sealed with an elastomer pressure membrane. Upon excitation of an externally applied AC magnetic field, the sensing element is capable of producing higher-order magnetic signature that is able to be remotely detected with an external receiving coil. When exposed to environment with changing ambient pressure, the elastomer pressure membrane of pressure sensor is deflected depending on the surrounding pressure. The deflection of elastomer membrane changes the separation distance between the sensing and biasing elements. As a result, the higher-order harmonic signal emitted by the magnetically-soft sensing element is shifted, allowing detection of pressure change by determining the extent of the harmonic shifting. The passive and wireless nature of the sensor is enabled with an external excitation and receiving system consisting of an excitation coil and a receiving coil. These unique characteristics made the sensor suitable to be used for continuous and long-term pressure monitoring, particularly useful for biomedical applications which often require frequent surveillance. In this work, abdominal aortic aneurysm is selected as the disease model for evaluation the performance of pressure sensor and system. Animal model, with subcutaneous sensor implantation in mice, was conducted to demonstrate the efficacy and feasibility of pressure sensor in biological environment.

Analysis of independent microarray datasets of renal biopsies identifies a robust transcript signature of acute allograft rejection

Transcriptomics could contribute significantly to the early and specific diagnosis of rejection episodes by defining 'molecular Banff' signatures. Recently, the description of pathogenesis-based transcript sets offered a new opportunity for objective and quantitative diagnosis. Generating high-quality transcript panels is thus critical to define high-performance diagnostic classifier. In this study, a comparative analysis was performed across four different microarray datasets of heterogeneous sample collections from two published clinical datasets and two own datasets including biopsies for clinical indication, and samples from nonhuman primates. We characterized a common transcriptional profile of 70 genes, defined as acute rejection transcript set (ARTS). ARTS expression is significantly up-regulated in all AR samples as compared with stable allografts or healthy kidneys, and strongly correlates with the severity of Banff AR types. Similarly, ARTS were tested as a classifier in a large collection of 143 independent biopsies recently published by the University of Alberta. Results demonstrate that the 'in silico' approach applied in this study is able to identify a robust and reliable molecular signature for AR, supporting a specific and sensitive molecular diagnostic approach for renal transplant monitoring.

Circulating microRNA profiling in patients with advanced non-squamous NSCLC receiving bevacizumab/erlotinib followed by platinum-based chemotherapy at progression (SAKK 19/05).

OBJECTIVES Molecular subclassification of non small-cell lung cancer (NSCLC) is essential to improve clinical outcome. This study assessed the prognostic and predictive value of circulating micro-RNA (miRNA) in patients with non-squamous NSCLC enrolled in the phase II SAKK (Swiss Group for Clinical Cancer Research) trial 19/05, receiving uniform treatment with first-line bevacizumab and erlotinib followed by platinum-based chemotherapy at progression. MATERIALS AND METHODS Fifty patients with baseline and 24 h blood samples were included from SAKK 19/05. The primary study endpoint was to identify prognostic (overall survival, OS) miRNA's. Patient samples were analyzed with Agilent human miRNA 8x60K microarrays, each glass slide formatted with eight high-definition 60K arrays. Each array contained 40 probes targeting each of the 1347 miRNA. Data preprocessing included quantile normalization using robust multi-array average (RMA) algorithm. Prognostic and predictive miRNA expression profiles were identified by Spearman's rank correlation test (percentage tumor shrinkage) or log-rank testing (for time-to-event endpoints). RESULTS Data preprocessing kept 49 patients and 424 miRNA for further analysis. Ten miRNA's were significantly associated with OS, with hsa-miR-29a being the strongest prognostic marker (HR=6.44, 95%-CI 2.39-17.33). Patients with high has-miR-29a expression had a significantly lower survival at 10 months compared to patients with a low expression (54% versus 83%). Six out of the 10 miRNA's (hsa-miRN-29a, hsa-miR-542-5p, hsa-miR-502-3p, hsa-miR-376a, hsa-miR-500a, hsa-miR-424) were insensitive to perturbations according to jackknife cross-validation on their HR for OS. The respective principal component analysis (PCA) defined a meta-miRNA signature including the same 6 miRNA's, resulting in a HR of 0.66 (95%-CI 0.53-0.82). CONCLUSION Cell-free circulating miRNA-profiling successfully identified a highly prognostic 6-gene signature in patients with advanced non-squamous NSCLC. Circulating miRNA profiling should further be validated in external cohorts for the selection and monitoring of systemic treatment in patients with advanced NSCLC.

Zeeman effect in atmospheric O₂ measured by ground-based microwave radiometry

In this work we study the Zeeman effect on stratospheric O₂ using ground-based microwave radiometer measurements. The interaction of the Earth magnetic field with the oxygen dipole leads to a splitting of O₂ energy states, which polarizes the emission spectra. A special campaign was carried out in order to measure this effect in the oxygen emission line centered at 53.07 GHz. Both a fixed and a rotating mirror were incorporated into the TEMPERA (TEMPERature RAdiometer) in order to be able to measure under different observational angles. This new configuration allowed us to change the angle between the observational path and the Earth magnetic field direction. Moreover, a high-resolution spectrometer (1 kHz) was used in order to measure for the first time the polarization state of the radiation due to the Zeeman effect in the main isotopologue of oxygen from ground-based microwave measurements. The measured spectra showed a clear polarized signature when the observational angles were changed, evidencing the Zeeman effect in the oxygen molecule. In addition, simulations carried out with the Atmospheric Radiative Transfer Simulator (ARTS) allowed us to verify the microwave measurements showing a very good agreement between model and measurements. The results suggest some interesting new aspects for research of the upper atmosphere.

Detecting the signature of natural selection with microsatellites

Natural selection is one of the major factors in the evolution of all organisms. Detecting the signature of natural selection has been a central theme in evolutionary genetics. With the availability of microsatellite data, it is of interest to study how natural selection can be detected with microsatellites. ^ The overall aim of this research is to detect signatures of natural selection with data on genetic variation at microsatellite loci. The null hypothesis to be tested is the neutral mutation theory of molecular evolution, which states that different alleles at a locus have equivalent effects on fitness. Currently used tests of this hypothesis based on data on genetic polymorphism in natural populations presume that mutations at the loci follow the infinite allele/site models (IAM, ISM), in the sense that at each site at most only one mutation event is recorded, and each mutation leads to an allele not seen before in the population. Microsatellite loci, which are abundant in the genome, do not obey these mutation models, since the new alleles at such loci can be created either by contraction or expansion of tandem repeat sizes of core motifs. Since the current genome map is mainly composed of microsatellite loci and this class of loci is still most commonly studied in the context of human genome diversity, this research explores how the current test procedures for testing the neutral mutation hypothesis should be modified to take into account a generalized model of forward-backward stepwise mutations. In addition, recent literature also suggested that past demographic history of populations, presence of population substructure, and varying rates of mutations across loci all have confounding effects for detecting signatures of natural selection. ^ The effects of the stepwise mutation model and other confounding factors on detecting signature of natural selection are the main results of the research. ^