Using iterative cluster merging with improved gap statistics to perform online phenotype discovery in the context of high-throughput RNAi screens

<p>Abstract</p> <p>Background</p> <p>The recent emergence of high-throughput automated image acquisition technologies has forever changed how cell biologists collect and analyze data. Historically, the interpretation of cellular phenotypes in different experimental conditions has been dependent upon the expert opinions of well-trained biologists. Such qualitative analysis is particularly effective in detecting subtle, but important, deviations in phenotypes. However, while the rapid and continuing development of automated microscope-based technologies now facilitates the acquisition of trillions of cells in thousands of diverse experimental conditions, such as in the context of RNA interference (RNAi) or small-molecule screens, the massive size of these datasets precludes human analysis. Thus, the development of automated methods which aim to identify novel and biological relevant phenotypes online is one of the major challenges in high-throughput image-based screening. Ideally, phenotype discovery methods should be designed to utilize prior/existing information and tackle three challenging tasks, i.e. restoring pre-defined biological meaningful phenotypes, differentiating novel phenotypes from known ones and clarifying novel phenotypes from each other. Arbitrarily extracted information causes biased analysis, while combining the complete existing datasets with each new image is intractable in high-throughput screens.</p> <p>Results</p> <p>Here we present the design and implementation of a novel and robust online phenotype discovery method with broad applicability that can be used in diverse experimental contexts, especially high-throughput RNAi screens. This method features phenotype modelling and iterative cluster merging using improved gap statistics. A Gaussian Mixture Model (GMM) is employed to estimate the distribution of each existing phenotype, and then used as reference distribution in gap statistics. This method is broadly applicable to a number of different types of image-based datasets derived from a wide spectrum of experimental conditions and is suitable to adaptively process new images which are continuously added to existing datasets. Validations were carried out on different dataset, including published RNAi screening using <it>Drosophila </it>embryos [Additional files <supplr sid="S1">1</supplr>, <supplr sid="S2">2</supplr>], dataset for cell cycle phase identification using HeLa cells [Additional files <supplr sid="S1">1</supplr>, <supplr sid="S3">3</supplr>, <supplr sid="S4">4</supplr>] and synthetic dataset using polygons, our methods tackled three aforementioned tasks effectively with an accuracy range of 85%–90%. When our method is implemented in the context of a <it>Drosophila </it>genome-scale RNAi image-based screening of cultured cells aimed to identifying the contribution of individual genes towards the regulation of cell-shape, it efficiently discovers meaningful new phenotypes and provides novel biological insight. We also propose a two-step procedure to modify the novelty detection method based on one-class SVM, so that it can be used to online phenotype discovery. In different conditions, we compared the SVM based method with our method using various datasets and our methods consistently outperformed SVM based method in at least two of three tasks by 2% to 5%. These results demonstrate that our methods can be used to better identify novel phenotypes in image-based datasets from a wide range of conditions and organisms.</p> <p>Conclusion</p> <p>We demonstrate that our method can detect various novel phenotypes effectively in complex datasets. Experiment results also validate that our method performs consistently under different order of image input, variation of starting conditions including the number and composition of existing phenotypes, and dataset from different screens. In our findings, the proposed method is suitable for online phenotype discovery in diverse high-throughput image-based genetic and chemical screens.</p

Photonics - An atomic dimmer switch

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62775/1/396217a0.pd

Computer-Aided Design and Analysis of Spectrally Aligned Hybrid Plasmonic Nanojunctions for SERS Detection of Nucleobases

Hybrid plasmonic nanojunctions with optimal surface-enhanced Raman scattering (SERS) activity are designed via a computer-aided approach, and fabricated via time-controlled aqueous self-assembly of core@shell gold@silver nanoparticles (Au@Ag NPs) with cucurbit[7]uril (CB7) upon simple mixing. The authors showed that SERS signals can be significantly boosted by the incorporation of a strong plasmonic metal and the spectral alignment between the maximal localized surface plasmon resonance (LSPR) and a laser wavelength used for SERS excitation. In a proof-of-concept application, SERS detection of nucleobases with a 633-nm laser has been demonstrated by positioning them within the nanojunctions via formation of host–guest complexes with CB7, achieving rapid response with a detection limit down to sub-nanomolar concentration and an enhancement factor (EF) up to ≈109–1010, i.e., the minimum required EF for single-molecule detection. Furthermore, machine-learning-driven multiplexing of nucleobases is demonstrated, which shows promise in point-of-care diagnosis of diseases related to oxidative damage of DNA and wastewater-based epidemiology

Diversity and Distribution of Symbiodinium Associated with Seven Common Coral Species in the Chagos Archipelago, Central Indian Ocean

The Chagos Archipelago designated as a no-take marine protected area in 2010, lying about 500 km south of the Maldives in the Indian Ocean, has a high conservation priority, particularly because of its fast recovery from the ocean-wide massive coral mortality following the 1998 coral bleaching event. The aims of this study were to examine Symbiodinium diversity and distribution associated with scleractinian corals in five atolls of the Chagos Archipelago, spread over 10,000 km 2. Symbiodinium clade diversity in 262 samples of seven common coral species, Acropora muricata, Isopora palifera, Pocillopora damicornis, P. verrucosa, P. eydouxi, Seriatopora hystrix, and Stylophora pistillata were determined using PCR-SSCP of the ribosomal internal transcribed spacer 1 (ITS1), PCR-DDGE of ITS2, and phylogenetic analyses. The results indicated that Symbiodinium in clade C were the dominant symbiont group in the seven coral species. Our analysis revealed types of Symbiodinium clade C specific to coral species. Types C1 and C3 (with C3z and C3i variants) were dominant in Acroporidae and C1 and C1c were the dominant types in Pocilloporidae. We also found 2 novel ITS2 types in S. hystrix and 1 novel ITS2 type of Symbiodinium in A. muricata. Some colonies of A. muricata and I. palifera were also associated with Symbiodinium A1. These results suggest that corals in the Chagos Archipelago host different assemblages of Symbiodinium types then their conspecifics from other locations in the Indian Ocean; and that future research will show whether these patterns in Symbiodinium genotypes may be due to local adaptation to specific conditions in the Chagos

Natural coagulates for wastewater treatment; a review for application and mechanism

The increase of water demand and wastewater generation is among the global concerns in the world. The less effective management of water sources leads to serious consequences, the direct disposal of untreated wastewater is associated with the environmental pollution, elimination of aquatic life and the spread of deadly epidemics. The flocculation process is one of the most important stages in water and wastewater treatment plants, wherein this phase the plankton, colloidal particles, and pollutants are precipitated and removed. Two major types of coagulants are used in the flocculation process included the chemical and natural coagulants. Many studies have been performed to optimize the flocculation process while most of these studies have confirmed the hazardous effects of chemical coagulants utilization on the ecosystem. This chapter reviews a summary of the coagulation/flocculation processes using natural coagulants as well as reviews one of the most effective natural methods of water and wastewater treatment

An assessment of the quality of randomised controlled trials conducted in China

Background: Despite the rapid increase in research in China, little is known about the quality of clinical trials conducted there.Methods: A systematic review and critical appraisal of randomised controlled trials (RCTs) conducted in China and published in 2004 was undertaken to describe their characteristics, assess the quality of their reporting, and where possible, the quality of their conduct. Randomised controlled trials in all disease areas and types of interventions, which took place in China and included Chinese citizens were identified using PubMed and hand searching the Journal Series of the Chinese Medical Association. Quality was assessed against a subset of criteria adapted from the CONSORT statement.Results: Three hundred and seven RCTs were included. One hundred and ninety-nine (64.8%) failed to report methods of randomization and 254 (82.4%) did not mention blinding of either participants or investigators. Reporting of baseline characteristics, primary outcome and length of follow-up was inadequate in a substantial proportion of studies. Fewer than 11% of RCTs mentioned ethical approval and only 18.0% adequately discussed informed consent. However, dropout rates were very favourable with nearly 44% of trials reporting a zero dropout rate.Conclusion: Reporting of RCTs in China requires substantial improvement to meet the targets of the CONSORT statement. The conduct of Chinese RCTs cannot be directly inferred from the standard of reporting; however without good reporting the methods of the trials cannot be clearly ascertained

A process pattern model for tackling and improving big data quality

Data seldom create value by themselves. They need to be linked and combined from multiple sources, which can often come with variable data quality. The task of improving data quality is a recurring challenge. In this paper, we use a case study of a large telecom company to develop a generic process pattern model for improving data quality. The process pattern model is defined as a proven series of activities, aimed at improving the data quality given a certain context, a particular objective, and a specific set of initial conditions. Four different patterns are derived to deal with the variations in data quality of datasets. Instead of having to find the way to improve the quality of big data for each situation, the process model provides data users with generic patterns, which can be used as a reference model to improve big data quality

The Association among Literacy, Numeracy, HIV Knowledge and Health-Seeking Behavior: A Population-Based Survey of Women in Rural Mozambique

BACKGROUND: Limited literacy skills are common in the United States (US) and are related to lower HIV knowledge and worse health behaviors and outcomes. The extent of these associations is unknown in countries like Mozambique, where no rigorously validated literacy and numeracy measures exist. METHODS: A validated measure of literacy and numeracy, the Wide Range Achievement Test, version 3 (WRAT-3) was translated into Portuguese, adapted for a Mozambican context, and administered to a cross-section of female heads-of-household during a provincially representative survey conducted from August 8 to September 25, 2010. Construct validity of each subscale was examined by testing associations with education, income, and possession of socioeconomic assets, stratified by Portuguese speaking ability. Multivariable regression models estimated the association among literacy/numeracy and HIV knowledge, self-reported HIV testing, and utilization of prenatal care. RESULTS: Data from 3,557 women were analyzed; 1,110 (37.9%) reported speaking Portuguese. Respondents' mean age was 31.2; 44.6% lacked formal education, and 34.3% reported no income. Illiteracy was common (50.4% of Portuguese speakers, 93.7% of non-Portuguese speakers) and the mean numeracy score (10.4) corresponded to US kindergarten-level skills. Literacy or numeracy was associated (p<0.01) with education, income, age, and other socioeconomic assets. Literacy and numeracy skills were associated with HIV knowledge in adjusted models, but not with HIV testing or receipt of clinic-based prenatal care. CONCLUSION: The adapted literacy and numeracy subscales are valid for use with rural Mozambican women. Limited literacy and numeracy skills were common and associated with lower HIV knowledge. Further study is needed to determine the extent to which addressing literacy/numeracy will lead to improved health outcomes

Upregulation of the cell-cycle regulator RGC-32 in Epstein-Barr virus-immortalized cells

Epstein-Barr virus (EBV) is implicated in the pathogenesis of multiple human tumours of lymphoid and epithelial origin. The virus infects and immortalizes B cells establishing a persistent latent infection characterized by varying patterns of EBV latent gene expression (latency 0, I, II and III). The CDK1 activator, Response Gene to Complement-32 (RGC-32, C13ORF15), is overexpressed in colon, breast and ovarian cancer tissues and we have detected selective high-level RGC-32 protein expression in EBV-immortalized latency III cells. Significantly, we show that overexpression of RGC-32 in B cells is sufficient to disrupt G2 cell-cycle arrest consistent with activation of CDK1, implicating RGC-32 in the EBV transformation process. Surprisingly, RGC-32 mRNA is expressed at high levels in latency I Burkitt's lymphoma (BL) cells and in some EBV-negative BL cell-lines, although RGC-32 protein expression is not detectable. We show that RGC-32 mRNA expression is elevated in latency I cells due to transcriptional activation by high levels of the differentially expressed RUNX1c transcription factor. We found that proteosomal degradation or blocked cytoplasmic export of the RGC-32 message were not responsible for the lack of RGC-32 protein expression in latency I cells. Significantly, analysis of the ribosomal association of the RGC-32 mRNA in latency I and latency III cells revealed that RGC-32 transcripts were associated with multiple ribosomes in both cell-types implicating post-initiation translational repression mechanisms in the block to RGC-32 protein production in latency I cells. In summary, our results are the first to demonstrate RGC-32 protein upregulation in cells transformed by a human tumour virus and to identify post-initiation translational mechanisms as an expression control point for this key cell-cycle regulator

Frequency-Invariant Representation of Interaural Time Differences in Mammals

Interaural time differences (ITDs) are the major cue for localizing low-frequency sounds. The activity of neuronal populations in the brainstem encodes ITDs with an exquisite temporal acuity of about . The response of single neurons, however, also changes with other stimulus properties like the spectral composition of sound. The influence of stimulus frequency is very different across neurons and thus it is unclear how ITDs are encoded independently of stimulus frequency by populations of neurons. Here we fitted a statistical model to single-cell rate responses of the dorsal nucleus of the lateral lemniscus. The model was used to evaluate the impact of single-cell response characteristics on the frequency-invariant mutual information between rate response and ITD. We found a rough correspondence between the measured cell characteristics and those predicted by computing mutual information. Furthermore, we studied two readout mechanisms, a linear classifier and a two-channel rate difference decoder. The latter turned out to be better suited to decode the population patterns obtained from the fitted model