Multiple Independent Data Research Articles

Performance analysis of relay‐multiplexing scheme in cellular systems employing massive multiple‐input multiple‐output antennas

This study presents the symbol error probability (SEP) analysis of relay-multiplexing scheme in relay-assisted cellular systems such as the IEEE 802.16j and upcoming fifth generation (5G) systems. The availability of multiple relay paths in these systems motivates two relay configurations: (i) relay diversity and (ii) relay multiplexing. Available works in the literature have focused on the relay diversity methods. In this study, we explore the relay-multiplexing alternative whereby relay stations (RSs) act as independent data pipes for transmitting multiple independent data streams from the base station (BS) to the mobile station (MS). We examine the case when the BS is equipped with massive multiple-input multiple-output (MIMO) antennas, transmitting independent data streams to several MS simultaneously via different relay paths. We derive analytical expressions for the SEP performance of the proposed scheme, and also complement the analysis with simulations. The results show that parallel relaying of independent data streams via different RSs has acceptable SEP performance while boosting the capacity of the system linearly with the number of parallel RSs available in the system. The results also show that when this relaying approach is combined with the emerging massive MIMO techniques, a tremendous boost in data rate can be achieved.

A 6-gene signature for outcome prediction of grade II/III glioma.

2002 Background: Grade II and III gliomas are very heterogeneous in their outcome, leaving some uncertainty as to what the best treatment is for the individual patient. Methods: We used multiple datasets totaling 756 glioma patients to develop a prognostic 6-gene signature for grade II and III gliomas. Three risk groups were defined (low, medium, and high risk). This 6-gene classifier was then validated in multiple independent glioma data sets totaling over 500 patients and translated into a PCR-based assay. Results: The classifier was validated in a 214 grade II/III glioma patient independent validation set (TCGA, HR=4.03; 95% CI, 1.82-8.92; p= 0.001, for low vs high risk group) and a 287 patient grade IV glioblastoma set (updated TCGA, HR, 2.42; 95% CI, 1.69-3.47; p< 0.001, for low vs high risk group). The classifier was then translated into a PCR based assay in an independent 32 grade II/III glioma patient pilot cohort (multi-institutional, HR=6.3; 95% CI, 1.7-23.6; p= 0.006, for low vs high risk group...

Meta-Analysis of Pathway Enrichment: Combining Independent and Dependent Omics Data Sets

A major challenge in current systems biology is the combination and integrative analysis of large data sets obtained from different high-throughput omics platforms, such as mass spectrometry based Metabolomics and Proteomics or DNA microarray or RNA-seq-based Transcriptomics. Especially in the case of non-targeted Metabolomics experiments, where it is often impossible to unambiguously map ion features from mass spectrometry analysis to metabolites, the integration of more reliable omics technologies is highly desirable. A popular method for the knowledge-based interpretation of single data sets is the (Gene) Set Enrichment Analysis. In order to combine the results from different analyses, we introduce a methodical framework for the meta-analysis of p-values obtained from Pathway Enrichment Analysis (Set Enrichment Analysis based on pathways) of multiple dependent or independent data sets from different omics platforms. For dependent data sets, e.g. obtained from the same biological samples, the framework utilizes a covariance estimation procedure based on the nonsignificant pathways in single data set enrichment analysis. The framework is evaluated and applied in the joint analysis of Metabolomics mass spectrometry and Transcriptomics DNA microarray data in the context of plant wounding. In extensive studies of simulated data set dependence, the introduced correlation could be fully reconstructed by means of the covariance estimation based on pathway enrichment. By restricting the range of p-values of pathways considered in the estimation, the overestimation of correlation, which is introduced by the significant pathways, could be reduced. When applying the proposed methods to the real data sets, the meta-analysis was shown not only to be a powerful tool to investigate the correlation between different data sets and summarize the results of multiple analyses but also to distinguish experiment-specific key pathways.

Converging genetic and functional brain imaging evidence links neuronal excitability to working memory, psychiatric disease, and brain activity.

Working memory, the capacity of actively maintaining task-relevant information during a cognitive task, is a heritable trait. Working memory deficits are characteristic for many psychiatric disorders. We performed genome-wide gene set enrichment analyses in multiple independent data sets of young and aged cognitively healthy subjects (n= 2,824) and in a large schizophrenia case-control sample (n= 32,143). The voltage-gated cation channel activity gene set, consisting of genes related to neuronal excitability, was robustly linked to performance in working memory-related tasks across ages and toschizophrenia. Functional brain imaging in 707 healthy participants linked this gene setalso to working memory-related activity in the parietal cortex and the cerebellum. Gene set analyses may help to dissect the molecular underpinnings of cognitive dimensions, brain activity, and psychopathology.

Comparison of direct costs of type 2 diabetes care: Different care models with different outcomes

Backgrounds and aimsTo compare direct costs of four different care models and health outcomes in adults with type 2 diabetes. Methods and resultsWe used multiple independent data sources to identify 25,570 adults with type 2 diabetes residing in Turin, Italy, as of 1 July 2003. Data extracted from administrative data databases were used to create four care models ranging in organization from highly structured care (integrated primary and specialist care) to progressively less structured care (unstructured care). Regression analyses, adjusted for main confounders, were applied to examine the differences between the models in direct costs, mortality, and diabetes-related hospitalizations rates over a 4-year period. In patients managed according to the unstructured care model (i.e., usual care by a primary care provider and without strict guidelines adherence), excess of all-cause mortality was 84% and 4-year direct cost was 8% higher than in those managed according to the highly structured care model. Cost ratio analysis revealed that the major cost driver in the unstructured care model was hospital admissions, which were 31% higher than the rate calculated for the more structured care models. In contrast, spending on prescription medications and specialist consultations was higher in the highly structured care model. ConclusionA diabetes care model that integrates primary and specialty care, together with practices that adhere to guideline recommendations, was associated with a reduction in all-cause mortality and hospitalizations, as compared with less structured models, without increasing direct health costs.

Distributed Transceiver Design and Power Control for Wireless MIMO Interference Networks

This paper considers distributed transceiver design and power control for K-user multiple-input-multiple-output interference networks. Each source intends to send multiple independent data streams to its corresponding destination where the number of data streams coincides with the degrees of freedom of the network. Each data stream is encoded at a fixed data rate, whereas different streams can be encoded at possibly different rates. We assume that only local channel side information (i.e., knowledge related to channels directly connected to a terminal) can be acquired by each terminal. We propose iterative algorithms to perform both power control and transceiver design. Transmitter beamforming matrices and receiver filtering matrices are designed to maximize signal-to-interference-plus-noise ratio corresponding to each stream, and a power control scheme is performed to assign the minimum power to each encoded data stream such that successful communication can be guaranteed. The proposed algorithms exhibit a substantial performance improvement compared with the conventional orthogonal transmission schemes.

Optimal Beam-Forming Design in Cognitive Relay Networks under Interference Threshold

Recently, a new model for cognitive radio networks appears, in which a cognitive user (CU) can relay the primary data stream to improve the performance of the primary user s communication. Traditionally, the transmitter of the cognitive users will send data to the receiver of the cognitive users and relay the data sent from the primary user (PU) in different time slots. However, Multiple Input Multiple Output (MIMO) provides a remarkable increase in the spectral efficiency, which can transmit multiple independent data streams in a time slot with MIMO antenna. Based on the MIMO technique, we propose a novel framework, in which the cognitive user near by the primary user is equipped with MIMO antenna. In this paper, we search for the maximum sum-rate of the cognitive user, limiting the interference to the primary users. Simulation results show that the proposed method can really improve the performance of the cognitive relay networks.

EYA4 is inactivated biallelically at a high frequency in sporadic lung cancer and is associated with familial lung cancer risk

In an effort to identify novel biallelically inactivated tumor suppressor genes (TSG) in sporadic invasive and pre-invasive non-small cell lung cancer (NSCLC) genomes, we applied a comprehensive integrated multi-‘omics approach to investigate patient matched, paired NSCLC tumor and non-malignant parenchymal tissues. By surveying lung tumor genomes for genes concomitantly inactivated within individual tumors by multiple mechanisms, and by the frequency of disruption in tumors across multiple cohorts, we have identified a putative lung cancer TSG, Eyes Absent 4 (EYA4). EYA4 is frequently and concomitantly deleted, hypermethylated and underexpressed in multiple independent lung tumor data sets, in both major NSCLC subtypes, and in the earliest stages of lung cancer. We find not only that decreased EYA4 expression is associated with poor survival in sporadic lung cancers, but EYA4 SNPs are associated with increased familial cancer risk, consistent with EYA4’s proximity to the previously reported lung cancer susceptibility locus on 6q. Functionally, we find that EYA4 displays TSG-like properties with a role in modulating apoptosis and DNA repair. Cross examination of EYA4 expression across multiple tumor types suggests a cell type-specific tumorigenic role for EYA4, consistent with a tumor suppressor function in cancers of epithelial origin. This work shows a clear role for EYA4 as a putative TSG in NSCLC.

Optimal Cooperative Jamming for Multiuser Broadcast Channel with Multiple Eavesdroppers

Cooperative jamming for multiuser multiple input multiple output (MIMO) broadcast channel is studied to enhance the physical layer security with the help of a friendly jammer. We assume the base station transmits multiple independent data streams to multiple legitimate users. During the transmission, however, there are multiple eavesdroppers with multiple antennas that have interests in the streams from the base station. In order to wiretap the desired streams, the eavesdroppers may collude or not, and maximize the signal-to-interference-plus-noise ratio (SINR) of the desired streams using receive beamforming. The optimal cooperative jammer is designed to keep the achieved SINR at eavesdroppers below a threshold to guarantee that the transmission from the base station to legitimate users is confidential. One main advantage of the proposed cooperative jamming scheme is that no modification is needed for the existing precoding schemes at the base station and decoding schemes at legitimate users. Thus, any existing practical precoding/decoding schemes for multiuser MIMO broadcast channel can be applied directly with the help of a friendly jammer using the proposed cooperative jamming.

The integration of multiple independent data reveals an unusual response toPleistocene climatic changes in the hard tickIxodes ricinus

In the last few years, improved analytical tools and the integration of genetic data with multiple sources of information have shown that temperate species exhibited more complex responses to ice ages than previously thought. In this study, we investigated how Pleistocene climatic changes affected the current distribution and genetic diversity of European populations of the tick Ixodes ricinus, an ectoparasite with high ecological plasticity. We first used mitochondrial and nuclear genetic markers to investigate the phylogeographic structure of the species and its Pleistocene history using coalescent-based methods; then we used species distribution modelling to infer the climatic niche of the species at last glacial maximum; finally, we reviewed the literature on the I.ricinus hosts to identify the locations of their glacial refugia. Our results support the scenario that during the last glacial phase, I.ricinus never experienced a prolonged allopatric divergence in separate glacial refugia, but persisted with interconnected populations across Southern and Central Europe. The generalist behaviour in host choice of I.ricinus would have played a major role in maintaining connections between its populations. Although most of the hosts persisted in separate refugia, from the point of view of I.ricinus, they represented a continuity of 'bridges' among populations. Our study highlights the importance of species-specific ecology in affecting responses to Pleistocene glacial-interglacial cycles. Together with other cases in Europe and elsewhere, it contributes to setting new hypotheses on how species with wide ecological plasticity coped with Pleistocene climatic changes.

A robust prognostic signature for hormone-positive node-negative breast cancer

BackgroundSystemic chemotherapy in the adjuvant setting can cure breast cancer in some patients that would otherwise recur with incurable, metastatic disease. However, since only a fraction of patients would have recurrence after surgery alone, the challenge is to stratify high-risk patients (who stand to benefit from systemic chemotherapy) from low-risk patients (who can safely be spared treatment related toxicities and costs).MethodsWe focus here on risk stratification in node-negative, ER-positive, HER2-negative breast cancer. We use a large database of publicly available microarray datasets to build a random forests classifier and develop a robust multi-gene mRNA transcription-based predictor of relapse free survival at 10 years, which we call the Random Forests Relapse Score (RFRS). Performance was assessed by internal cross-validation, multiple independent data sets, and comparison to existing algorithms using receiver-operating characteristic and Kaplan-Meier survival analysis. Internal redundancy of features was determined using k-means clustering to define optimal signatures with smaller numbers of primary genes, each with multiple alternates.ResultsInternal OOB cross-validation for the initial (full-gene-set) model on training data reported an ROC AUC of 0.704, which was comparable to or better than those reported previously or obtained by applying existing methods to our dataset. Three risk groups with probability cutoffs for low, intermediate, and high-risk were defined. Survival analysis determined a highly significant difference in relapse rate between these risk groups. Validation of the models against independent test datasets showed highly similar results. Smaller 17-gene and 8-gene optimized models were also developed with minimal reduction in performance. Furthermore, the signature was shown to be almost equally effective on both hormone-treated and untreated patients.ConclusionsRFRS allows flexibility in both the number and identity of genes utilized from thousands to as few as 17 or eight genes, each with multiple alternatives. The RFRS reports a probability score strongly correlated with risk of relapse. This score could therefore be used to assign systemic chemotherapy specifically to those high-risk patients most likely to benefit from further treatment.

5-hmC in the brain is abundant in synaptic genes and shows differences at the exon-intron boundary

5-hydroxymethylcytosine (5-hmC), a derivative of 5-methylcytosine (5-mC), is abundant in the brain for unknown reasons. Our goal was to characterize the genomic distribution of 5-hmC and 5-mC in human and mouse tissues. We assayed 5-hmC using glucosylation coupled with restriction enzyme digestion, and interrogation on microarrays. We detected 5-hmC enrichment in genes with synapse-related functions in both human and mouse brain. We also identified substantial tissue-specific differential distributions of these DNA modifications at the exon-intron boundary, in both human and mouse. This boundary change was mainly due to 5-hmC in the brain, but due to 5-mC in non-neural contexts. This pattern was replicated in multiple independent datasets and with single molecule sequencing. Moreover, in human frontal cortex, constitutive exons contained higher levels of 5-hmC, relative to alternatively-spliced exons. Our study suggests a novel role for 5-hmC in RNA splicing and synaptic function in the brain.

Development and Validation of a Prognostic Gene-Expression Signature for Lung Adenocarcinoma

Although several prognostic signatures have been developed in lung cancer, their application in clinical practice has been limited because they have not been validated in multiple independent data sets. Moreover, the lack of common genes between the signatures makes it difficult to know what biological process may be reflected or measured by the signature. By using classical data exploration approach with gene expression data from patients with lung adenocarcinoma (n = 186), we uncovered two distinct subgroups of lung adenocarcinoma and identified prognostic 193-gene gene expression signature associated with two subgroups. The signature was validated in 4 independent lung adenocarcinoma cohorts, including 556 patients. In multivariate analysis, the signature was an independent predictor of overall survival (hazard ratio, 2.4; 95% confidence interval, 1.2 to 4.8; p = 0.01). An integrated analysis of the signature revealed that E2F1 plays key roles in regulating genes in the signature. Subset analysis demonstrated that the gene signature could identify high-risk patients in early stage (stage I disease), and patients who would have benefit of adjuvant chemotherapy. Thus, our study provided evidence for molecular basis of clinically relevant two distinct two subtypes of lung adenocarcinoma.

Multi-criteria parameter estimation for the Unified Land Model

Abstract. We describe a parameter estimation framework for the Unified Land Model (ULM) that utilizes multiple independent data sets over the continental United States. These include a satellite-based evapotranspiration (ET) product based on MODerate resolution Imaging Spectroradiometer (MODIS) and Geostationary Operational Environmental Satellites (GOES) imagery, an atmospheric-water balance based ET estimate that utilizes North American Regional Reanalysis (NARR) atmospheric fields, terrestrial water storage content (TWSC) data from the Gravity Recovery and Climate Experiment (GRACE), and streamflow (Q) primarily from the United States Geological Survey (USGS) stream gauges. The study domain includes 10 large-scale (≥105 km2) river basins and 250 smaller-scale (&lt;104 km2) tributary basins. ULM, which is essentially a merger of the Noah Land Surface Model and Sacramento Soil Moisture Accounting Model, is the basis for these experiments. Calibrations were made using each of the data sets individually, in addition to combinations of multiple criteria, with multi-criteria skill scores computed for all cases. At large scales, calibration to Q resulted in the best overall performance, whereas certain combinations of ET and TWSC calibrations lead to large errors in other criteria. At small scales, about one-third of the basins had their highest Q performance from multi-criteria calibrations (to Q and ET) suggesting that traditional calibration to Q may benefit by supplementing observed Q with remote sensing estimates of ET. Model streamflow errors using optimized parameters were mostly due to over (under) estimation of low (high) flows. Overall, uncertainties in remote-sensing data proved to be a limiting factor in the utility of multi-criteria parameter estimation.

Vertically averaged velocities in the North Atlantic Current from field trials of a Lagrangian electric-field float

A subsurface Lagrangian float that utilizes motional induction to calculate vertically averaged velocities was tested in the North Atlantic Current (NAC), taking advantage of existing cruises and infrastructure. The Electric Field Float (EFF) is a RAFOS float with horizontal electrodes that measures its own velocity by RAFOS tracking and calculates vertically averaged velocities when merged with the electrode system. The observations showed depth-averaged velocities that were fast in the core of the NAC (0.6–0.9ms −1) and moderate in adjacent recirculations and eddies (0.3–0.4ms−1). A float at 850dbar moved at close to the depth-averaged velocity, while shallower floats followed surface intensified flow on top of the depth-averaged motion. Integral time scales of depth-averaged velocity (1.3–1.6±0.4d) are slightly shorter than time scales of float velocity (1.6–2.0±0.3d), while integral length scales of depth-averaged water velocity (35±10km for u, 18±6km for v) are slightly shorter than length scales of float motion (53±12km for u, 28±6km for v). Velocity spectra of depth-averaged velocity show significant variance at inertial periods. Quantitative and qualitative validation with multiple independent data sets confirms the accuracy of the instrument and sampling strategy in the NAC, advancing the limited observational knowledge of depth-averaged circulation in subpolar regions.

Abstract 3388: Progression of ductal carcinoma in situ to invasive breast cancer is associated with gene expression programs of EMT and myoepithelia

Abstract Ductal carcinoma in situ (DCIS) is a precursor lesion that can give rise to invasive breast cancer (IBC). It has been proposed that both the nature of the lesion and the tumor microenvironment play key roles in progression to IBC. Here laser capture microdissected tissue from pure DCIS and pure IBC were employed to define key gene expression profiles in either the epithelial or stromal compartment associated with disease progression. Each tissue had distinct gene expression profiles, and a DCIS/IBC classifier accurately distinguished DCIS versus IBC in multiple independent data sets. However, contrary to other studies that profiled DCIS associated with IBC, we found that the most significant alterations in gene expression were observed in the epithelial compartment rather than in the stroma. In particular, genes associated with epithelial to mesenchymal transition (EMT) and myoepithelial cell specific genes were enriched in invasive cancer relative to pure DCIS. Such alterations in transcript levels were associated with all subtypes of breast cancer, but were particularly indicative of poor outcome in ER-negative breast cancer. Together, these studies indicate that lesion specific differences in gene expression associated with invasive phenotype are particularly relevant in the progression of DCIS to IBC. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 3388. doi:1538-7445.AM2012-3388

A Novel Multiuser SISO-BOFDM Systems with Group Fractional Fourier Transforms Scheme

Existing multiuser (MU) schemes are mainly accomplished by MIMO techniques. In this letter, we propose a novel group fractional Fourier transform based MU SISO Biorthogonal Frequency Division Multiplexing system, in which multiple independent data streams from co-channel mobile stations (MSs) can be transmitted in the same frequency and time slot. Because the chirp bases generated by different orders based fractional Fourier transform (FrFTs), at same subchannel, are mutually approximately orthogonal, when FrFT orders are effectively allocated to different co-channel MSs, the co-channel interference can be perfectly suppressed by simple correlative detection in FrFT domain with respective optimal order, at the receiver of each MS. Finally, system simulations show the essential advantages over conventional MU schemes.

The impact of adherence to screening guidelines and of diabetes clinics referral on morbidity and mortality in diabetes.

Despite the heightened awareness of diabetes as a major health problem, evidence on the impact of assistance and organizational factors, as well as of adherence to recommended care guidelines, on morbidity and mortality in diabetes is scanty. We identified diabetic residents in Torino, Italy, as of 1st January 2002, using multiple independent data sources. We collected data on several laboratory tests and specialist medical examinations to compare primary versus specialty care management of diabetes and the fulfillment of a quality-of-care indicator based on existing screening guidelines (GCI). Then, we performed regression analyses to identify associations of these factors with mortality and cardiovascular morbidity over a 4 year- follow-up. Patients with the lowest degree of quality of care (i.e. only cared for by primary care and with no fulfillment of GCI) had worse RRs for all-cause (1.72 [95% CI 1.57–1.89]), cardiovascular (1.74 [95% CI 1.50–2.01]) and cancer (1.35 [95% CI 1.14–1.61]) mortality, compared with those with the highest quality of care. They also showed increased RRs for incidence of major cardiovascular events up to 2.03 (95% CI 1.26–3.28) for lower extremity amputations. Receiving specialist care itself increased survival, but was far more effective when combined with the fulfillment of GCI. Throughout the whole set of analysis, implementation of guidelines emerged as a strong modifier of prognosis. We conclude that management of diabetic patients with a pathway based on both primary and specialist care is associated with a favorable impact on all-cause mortality and CV incidence, provided that guidelines are implemented.

Building trust in climate science: data products for the 21st century

Climate science has a key role to play in informing strategies for adapting to and mitigating the effects of climate change. However, given the magnitude of the issues involved and their implications, it is imperative that the scientific process is–and is seen to be—rigorous, defensible, and transparent so as to ensure trust in the results. A key element in building such trust is to provide access to underlying data, so that interested parties can check published results and compare with their own analyses. A further priority is to provide data at the fine space and time scales that are relevant for user needs. Until recently, the ability to meet these requirements has been constrained by data‐sharing agreements and limitations on digital storage and processing. This is now changing however, thanks to improved global collaboration, communication and computing capability. This article describes current efforts to exploit these opportunities via the International Surface Temperature Initiative, an international and multidisciplinary effort that aims: firstly, to create a single comprehensive global databank of surface meteorological observations at monthly, daily, and sub‐daily resolutions; and secondly, to encourage the contribution of multiple independent data products, subject to common performance assessment and benchmarking criteria, thus providing the opportunity for a detailed assessment of uncertainties. The rationale for the initiative is discussed, along with logistical and technical challenges, as well as opportunities for involvement from the statistical and wider scientific and user communities. Copyright © 2012 John Wiley &amp; Sons, Ltd.

Combination of a Novel Gene Expression Signature with a Clinical Nomogram Improves the Prediction of Survival in High-Risk Bladder Cancer

We aimed to validate and improve prognostic signatures for high-risk urothelial carcinoma of the bladder. We evaluated microarray data from 93 patients with bladder cancer managed by radical cystectomy to determine gene expression patterns associated with clinical and prognostic variables. We compared our results with published bladder cancer microarray data sets comprising 578 additional patients and with 49 published gene signatures from multiple cancer types. Hierarchical clustering was utilized to identify subtypes associated with differences in survival. We then investigated whether the addition of survival-associated gene expression information to a validated postcystectomy nomogram utilizing clinical and pathologic variables improves prediction of recurrence. Multiple markers for muscle invasive disease with highly significant expression differences in multiple data sets were identified, such as fibronectin 1 (FN1), NNMT, POSTN, and SMAD6. We identified signatures associated with pathologic stage and the likelihood of developing metastasis and death from bladder cancer, as well as with two distinct clustering subtypes of bladder cancer. Our novel signature correlated with overall survival in multiple independent data sets, significantly improving the prediction concordance of standard staging in all data sets [mean ΔC-statistic: 0.14; 95% confidence interval (CI), 0.01-0.27; P < 0.001]. Tested in our patient cohort, it significantly enhanced the performance of a postoperative survival nomogram (ΔC-statistic: 0.08, 95% CI, -0.04-0.20; P < 0.005). Prognostic information obtained from gene expression data can aid in posttreatment prediction of bladder cancer recurrence. Our findings require further validation in external cohorts and prospectively in a clinical trial setting.