A summarization approach for Affymetrix GeneChip data using a reference training set from a large, biologically diverse database

BACKGROUND: Many of the most popular pre-processing methods for Affymetrix expression arrays, such as RMA, gcRMA, and PLIER, simultaneously analyze data across a set of predetermined arrays to improve precision of the final measures of expression. One problem associated with these algorithms is that expression measurements for a particular sample are highly dependent on the set of samples used for normalization and results obtained by normalization with a different set may not be comparable. A related problem is that an organization producing and/or storing large amounts of data in a sequential fashion will need to either re-run the pre-processing algorithm every time an array is added or store them in batches that are pre-processed together. Furthermore, pre-processing of large numbers of arrays requires loading all the feature-level data into memory which is a difficult task even with modern computers. We utilize a scheme that produces all the information necessary for pre-processing using a very large training set that can be used for summarization of samples outside of the training set. All subsequent pre-processing tasks can be done on an individual array basis. We demonstrate the utility of this approach by defining a new version of the Robust Multi-chip Averaging (RMA) algorithm which we refer to as refRMA. RESULTS: We assess performance based on multiple sets of samples processed over HG U133A Affymetrix GeneChip(® )arrays. We show that the refRMA workflow, when used in conjunction with a large, biologically diverse training set, results in the same general characteristics as that of RMA in its classic form when comparing overall data structure, sample-to-sample correlation, and variation. Further, we demonstrate that the refRMA workflow and reference set can be robustly applied to naïve organ types and to benchmark data where its performance indicates respectable results. CONCLUSION: Our results indicate that a biologically diverse reference database can be used to train a model for estimating probe set intensities of exclusive test sets, while retaining the overall characteristics of the base algorithm. Although the results we present are specific for RMA, similar versions of other multi-array normalization and summarization schemes can be developed

Nonsolar astronomy with the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI)

The Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI) is a NASA Small Explorer satellite designed to study hard x-ray and gamma-ray emission from solar flares. In addition, its high-resolution array of germanium detectors can see photons from high-energy sources throughout the Universe. Here we discuss the various algorithms necessary to extract spectra, lightcurves, and other information about cosmic gamma-ray bursts, pulsars, and other astrophysical phenomena using an unpointed, spinning array of detectors. We show some preliminary results and discuss our plans for future analyses. All RHESSI data are public, and scientists interested in participating should contact the principal author

Integrating biological knowledge into variable selection : an empirical Bayes approach with an application in cancer biology

Background: An important question in the analysis of biochemical data is that of identifying subsets of molecular variables that may jointly influence a biological response. Statistical variable selection methods have been widely used for this purpose. In many settings, it may be important to incorporate ancillary biological information concerning the variables of interest. Pathway and network maps are one example of a source of such information. However, although ancillary information is increasingly available, it is not always clear how it should be used nor how it should be weighted in relation to primary data. Results: We put forward an approach in which biological knowledge is incorporated using informative prior distributions over variable subsets, with prior information selected and weighted in an automated, objective manner using an empirical Bayes formulation. We employ continuous, linear models with interaction terms and exploit biochemically-motivated sparsity constraints to permit exact inference. We show an example of priors for pathway- and network-based information and illustrate our proposed method on both synthetic response data and by an application to cancer drug response data. Comparisons are also made to alternative Bayesian and frequentist penalised-likelihood methods for incorporating network-based information. Conclusions: The empirical Bayes method proposed here can aid prior elicitation for Bayesian variable selection studies and help to guard against mis-specification of priors. Empirical Bayes, together with the proposed pathway-based priors, results in an approach with a competitive variable selection performance. In addition, the overall procedure is fast, deterministic, and has very few user-set parameters, yet is capable of capturing interplay between molecular players. The approach presented is general and readily applicable in any setting with multiple sources of biological prior knowledge

Receptive Field Block Net for Accurate and Fast Object Detection

Current top-performing object detectors depend on deep CNN backbones, such as ResNet-101 and Inception, benefiting from their powerful feature representations but suffering from high computational costs. Conversely, some lightweight model based detectors fulfil real time processing, while their accuracies are often criticized. In this paper, we explore an alternative to build a fast and accurate detector by strengthening lightweight features using a hand-crafted mechanism. Inspired by the structure of Receptive Fields (RFs) in human visual systems, we propose a novel RF Block (RFB) module, which takes the relationship between the size and eccentricity of RFs into account, to enhance the feature discriminability and robustness. We further assemble RFB to the top of SSD, constructing the RFB Net detector. To evaluate its effectiveness, experiments are conducted on two major benchmarks and the results show that RFB Net is able to reach the performance of advanced very deep detectors while keeping the real-time speed. Code is available at https://github.com/ruinmessi/RFBNet.Comment: Accepted by ECCV 201

O-GlcNAc modification blocks the aggregation and toxicity of the protein α-synuclein associated with Parkinson's disease.

Several aggregation-prone proteins associated with neurodegenerative diseases can be modified by O-linked N-acetyl-glucosamine (O-GlcNAc) in vivo. One of these proteins, α-synuclein, is a toxic aggregating protein associated with synucleinopathies, including Parkinson's disease. However, the effect of O-GlcNAcylation on α-synuclein is not clear. Here, we use synthetic protein chemistry to generate both unmodified α-synuclein and α-synuclein bearing a site-specific O-GlcNAc modification at the physiologically relevant threonine residue 72. We show that this single modification has a notable and substoichiometric inhibitory effect on α-synuclein aggregation, while not affecting the membrane binding or bending properties of α-synuclein. O-GlcNAcylation is also shown to affect the phosphorylation of α-synuclein in vitro and block the toxicity of α-synuclein that was exogenously added to cells in culture. These results suggest that increasing O-GlcNAcylation may slow the progression of synucleinopathies and further support a general function for O-GlcNAc in preventing protein aggregation

Complex responses of spring vegetation growth to climate in a moisture-limited alpine meadow.

Since 2000, the phenology has advanced in some years and at some locations on the Qinghai-Tibetan Plateau, whereas it has been delayed in others. To understand the variations in spring vegetation growth in response to climate, we conducted both regional and experimental studies on the central Qinghai-Tibetan Plateau. We used the normalized difference vegetation index to identify correlations between climate and phenological greening, and found that greening correlated negatively with winter-spring time precipitation, but not with temperature. We used open top chambers to induce warming in an alpine meadow ecosystem from 2012 to 2014. Our results showed that in the early growing season, plant growth (represented by the net ecosystem CO2 exchange, NEE) was lower in the warmed plots than in the control plots. Late-season plant growth increased with warming relative to that under control conditions. These data suggest that the response of plant growth to warming is complex and non-intuitive in this system. Our results are consistent with the hypothesis that moisture limitation increases in early spring as temperature increases. The effects of moisture limitation on plant growth with increasing temperatures will have important ramifications for grazers in this system

Differential Validity and Utility of Successive and Simultaneous Approaches to the Development of Equivalent Achievement Tests in French and English

Described in this article are the first three activities of a research program designed to assess the differential validity and utility of successive and simultaneous approaches to the development of equivalent achievement tests in the French and English languages. Two teams of multilingual/multicultural French-English teachers used the simultaneous approach to develop 70 items respectively for mathematics and social studies at the grade 9 level. The evidence gained from the pilot study suggests that the issue of differential item performance attributable to translation differences appears to be confounded by the presence of socioeconomic differences between the two groups of students. Consequently, the next activities of this research will be directed toward disentangling these two issues to obtain a clearer view of the efficacy of the simultaneous method in reducing differential group performance and enhancing linguistic and cultural decentering

Monovalent Ion Condensation at the Electrified Liquid/Liquid Interface

X-ray reflectivity studies demonstrate the condensation of a monovalent ion at the electrified interface between electrolyte solutions of water and 1,2-dichloroethane. Predictions of the ion distributions by standard Poisson-Boltzmann (Gouy-Chapman) theory are inconsistent with these data at higher applied interfacial electric potentials. Calculations from a Poisson-Boltzmann equation that incorporates a non-monotonic ion-specific potential of mean force are in good agreement with the data.Comment: 4 pages, 4 figure

Assembly of long error-prone reads using de Bruijn graphs

The recent breakthroughs in assembling long error-prone reads were based on the overlap-layout-consensus (OLC) approach and did not utilize the strengths of the alternative de Bruijn graph approach to genome assembly. Moreover, these studies often assume that applications of the de Bruijn graph approach are limited to short and accurate reads and that the OLC approach is the only practical paradigm for assembling long error-prone reads. We show how to generalize de Bruijn graphs for assembling long error-prone reads and describe the ABruijn assembler, which combines the de Bruijn graph and the OLC approaches and results in accurate genome reconstructions

Outcomes and prognostic factors in parotid gland malignancies: A 10-year single center experience.

Objectives:To describe a 10-year single center experience with parotid gland malignancies and to determine factors affecting outcomes. Study Design:Retrospective review. Methods:The institutional cancer registry was used to identify patients treated surgically for malignancies of the parotid gland between January 2005 and December 2014. Clinical and pathologic data were collected retrospectively from patient charts and analyzed for their association with overall survival (OS) and disease-free survival (DFS). Results:Two hundred patients were identified. Mean age at surgery was 57.8 years, and mean follow-up time was 52 months. One hundred two patients underwent total parotidectomy, while 77 underwent superficial parotidectomy, and 21 underwent deep lobe resection. Seventy patients (35%) required facial nerve (FN) sacrifice. Acinic cell carcinoma was the most common histologic type (22%), followed by mucoepidermoid carcinoma (21.5%) and adenoid cystic carcinoma (12.5%). Twenty-nine patients (14.5%) experienced recurrences, with mean time to recurrence of 23.6 months (range: 1-82 months). Five- and 10-year OS were 81% and 73%, respectively. Five- and 10-year DFS were 80% and 73%, respectively. In univariate analyses, age > 60, histologic type, positive margins, high grade, T-stage, node positivity, perineural invasion, and FN involvement were predictors of OS and DFS. In the multivariate analysis, histology, positive margins, node positivity, and FN involvement were independent predictors of OS and DFS. Conclusions:Our single-center experience of 200 patients suggests that histology, positive margins, node positivity, and FN involvement are independently associated with outcomes in parotid malignancies. Level of Evidence:4