SMCKAT, a Sequential Multi-Dimensional CNV Kernel-Based Association Test.

Copy number variants (CNVs) are the most common form of structural genetic variation, reflecting the gain or loss of DNA segments compared with a reference genome. Studies have identified CNV association with different diseases. However, the association between the sequential order of CNVs and disease-related traits has not been studied, to our knowledge, and it is still unclear that CNVs function individually or whether they work in coordination with other CNVs to manifest a disease or trait. Consequently, we propose the first such method to test the association between the sequential order of CNVs and diseases. Our sequential multi-dimensional CNV kernel-based association test (SMCKAT) consists of three parts: (1) a single CNV group kernel measuring the similarity between two groups of CNVs; (2) a whole genome group kernel that aggregates several single group kernels to summarize the similarity between CNV groups in a single chromosome or the whole genome; and (3) an association test between the CNV sequential order and disease-related traits using a random effect model. We evaluate SMCKAT on CNV data sets exhibiting rare or common CNVs, demonstrating that it can detect specific biologically relevant chromosomal regions supported by the biomedical literature. We compare the performance of SMCKAT with MCKAT, a multi-dimensional kernel association test. Based on the results, SMCKAT can detect more specific chromosomal regions compared with MCKAT that not only have CNV characteristics, but the CNV order on them are significantly associated with the disease-related trait

DancingLines: An Analytical Scheme to Depict Cross-Platform Event Popularity

Nowadays, events usually burst and are propagated online through multiple modern media like social networks and search engines. There exists various research discussing the event dissemination trends on individual medium, while few studies focus on event popularity analysis from a cross-platform perspective. Challenges come from the vast diversity of events and media, limited access to aligned datasets across different media and a great deal of noise in the datasets. In this paper, we design DancingLines, an innovative scheme that captures and quantitatively analyzes event popularity between pairwise text media. It contains two models: TF-SW, a semantic-aware popularity quantification model, based on an integrated weight coefficient leveraging Word2Vec and TextRank; and wDTW-CD, a pairwise event popularity time series alignment model matching different event phases adapted from Dynamic Time Warping. We also propose three metrics to interpret event popularity trends between pairwise social platforms. Experimental results on eighteen real-world event datasets from an influential social network and a popular search engine validate the effectiveness and applicability of our scheme. DancingLines is demonstrated to possess broad application potentials for discovering the knowledge of various aspects related to events and different media

MCKAT: a multi-dimensional copy number variant kernel association test.

BACKGROUND: Copy number variants (CNVs) are the gain or loss of DNA segments in the genome. Studies have shown that CNVs are linked to various disorders, including autism, intellectual disability, and schizophrenia. Consequently, the interest in studying a possible association of CNVs to specific disease traits is growing. However, due to the specific multi-dimensional characteristics of the CNVs, methods for testing the association between CNVs and the disease-related traits are still underdeveloped. We propose a novel multi-dimensional CNV kernel association test (MCKAT) in this paper. We aim to find significant associations between CNVs and disease-related traits using kernel-based methods. RESULTS: We address the multi-dimensionality in CNV characteristics. We first design a single pair CNV kernel, which contains three sub-kernels to summarize the similarity between two CNVs considering all CNV characteristics. Then, aggregate single pair CNV kernel to the whole chromosome CNV kernel, which summarizes the similarity between CNVs in two or more chromosomes. Finally, the association between the CNVs and disease-related traits is evaluated by comparing the similarity in the trait with kernel-based similarity using a score test in a random effect model. We apply MCKAT on genome-wide CNV datasets to examine the association between CNVs and disease-related traits, which demonstrates the potential usefulness the proposed method has for the CNV association tests. We compare the performance of MCKAT with CKAT, a uni-dimensional kernel method. Based on the results, MCKAT indicates stronger evidence, smaller p-value, in detecting significant associations between CNVs and disease-related traits in both rare and common CNV datasets. CONCLUSION: A multi-dimensional copy number variant kernel association test can detect statistically significant associated CNV regions with any disease-related trait. MCKAT can provide biologists with CNV hot spots at the cytogenetic band level that CNVs on them may have a significant association with disease-related traits. Using MCKAT, biologists can narrow their investigation from the whole genome, including many genes and CNVs, to more specific cytogenetic bands that MCKAT identifies. Furthermore, MCKAT can help biologists detect significantly associated CNVs with disease-related traits across a patient group instead of examining each subject's CNVs case by case

Tidal signals in ocean-bottom magnetic measurements of the Northwestern Pacific: observation versus prediction

Motional induction in the ocean by tides has long been observed by both land and satellite measurements of magnetic fields. While these signals are weak (∼10 nT) when compared to the main magnetic field, their persistent nature makes them important for consideration during geomagnetic field modelling. Previous studies have reported several discrepancies between observations and numerical predictions of the tidal magnetic signals and those studies were inconclusive of the source of the error. We address this issue by (1) analysing magnetometer data from ocean-bottom stations, where the low-noise and high-signal environment is most suitable for detecting the weak tidal magnetic signals, (2) by numerically predicting the magnetic field with a spatial resolution that is 16times higher than the previous studies and (3) by using four different models of upper-mantle conductivity. We use vector magnetic data from six ocean-bottom electromagnetic (OBEM) stations located in the Northwestern Pacific Ocean. The OBEM tidal amplitudes were derived using an iteratively re-weighted least-squares (IRLS) method and by limiting the analysis of lunar semidiurnal (M2), lunar elliptic semidinurnal (N2) and diurnal (O1) tidal modes to the night-time. Using a 3-D electromagnetic induction solver and the TPX07.2 tidal model, we predict the tidal magnetic signal. We use earth models with non-uniform oceans and four 1-D mantle sections underneath taken from Kuvshinov and Olsen, Shimizu etal. and Baba etal. to compare the effect of upper-mantle conductivity. We find that in general, the predictions and observations match within 10-70 per cent across all the stations for each of the tidal modes. The median normalized percent difference (NPD) between observed and predicted amplitudes for the tidal modes M2, N2 and O1 were 15 per cent, 47 per cent and 98 per cent, respectively, for all the stations and models. At the majority of stations, and for each of the tidal modes, the higher resolution (0.25°×0.25°) modelling gave amplitudes consistently closer to the observations than the lower resolution (1°×1°) modelling. The difference in lithospheric resistance east and west of the Izu-Bonin trench system seems to be affecting the model response and observations in the O1 tidal mode. This response is not seen in the M2 and N2 modes, thereby indicating that the O1 mode is more sensitive to lithospheric resistanc

Growth in brine, at low temperature and different organic acids, of yeasts from table olives

The evolution of the main yeast species related to table olives (Pichia anomala, Pichia membranaefaciens, Pichia minuta, Saccharomyces cerevisiae, Candida diddensii, Candida famata, and Debaryomyces hansenii) at low temperature (7ºC) and different physico-chemical brine conditions was studied, using the log of the relative growth as response. In general, the NaCl concentration had a reduced effect, which was slightly greater at pH 3.5, although it was never significant. The effects of pH and type of acid were significant: the presence of acetic acid always diminished the yeast population with time; however the population was maintained, or even slightly increased, in the presence of lactic acid. Such effects were higher at pH 3.5 than at pH 4.0. The behavior of the yeast species was diverse. Sacch. cerevisiae, P. membranaefaciens, C. famata y Deb. hansenii disminished with time in 8% NaCl. The yeast population markedly decreased at pH 3.5, mainly in the case of Sacch. cerevisiae and C. famata. The presence of acetic acid decreased the yeast population in most species and always lead to a progressive diminution of it with time. No differences between species due to lactic acid was observed. These results can be of interest for the development of commercial presentations of table olives to be preserved at low temperature and with a reduced level of sodium.Se ha estudiado la evolución de las principales especies de levaduras relacionadas con las aceitunas de mesa (Pichia anomala, Pichia membranaefaciens, Pichia minuta, Saccharomyces cerevisiae, Candida diddensii, Candida famata , y Debaryomyces hansenii) a baja temperara (7ºC) y en diversas condiciones físico-químicas en las salmueras, utilizando el log del crecimiento relativo como respuesta. En general, la concentración de sal tiene un efecto muy limitado, que se aprecia algo más a pH 4, pero sin llegar a ser significativo. Los efectos del tipo de ácido y pH fueron significativos; la presencia de acético disminuye la población con el tiempo, mientras que con el láctico se mantiene e, incluso, se eleva ligeramente. Estos efectos se acentúan a pH 3,5. El comportamiento de cada levadura frente a las diferentes variables ha sido diverso. La población relativa de las especies Sacch. cerevisiae , P. membranaefaciens , C. famata y Deb. hansenii disminuyó con el tiempo en presencia del 8 % de NaCl. A pH 3,5 disminuye muy sensiblemente la población inicial en todos los casos, siendo tal influencia más destacada en Sacch. cerevisiae y C. famata. La presencia de acético disminuye de forma importante la población inicial inoculada en la mayoría de los casos y provocó siempre un descenso paulatino en las mismas. No se observó diferencias entre las especies debido al ácido láctico. Estos estudios pueden ser de interés para el desarrollo de presentaciones comerciales de aceitunas de mesa refrigeradas y con reducido nivel de sodio.Los autores desean expresar su gratitud a la CICYT (AGL2000-1539-CO2-01) y a la Unión Europea (FAIR-97-9526) por la financiación parcial de esta investigación.Peer reviewe

The dose makes the poison: have “field realistic” rates of exposure of bees to neonicotinoid insecticides been overestimated in laboratory studies?

Recent laboratory based studies have demonstrated adverse sub-lethal effects of neonicotinoid insecticides on honey bees and bumble bees, and these studies have been influential in leading to a European Union moratorium on the use of three neonicotinoids, clothianidin, imidacloprid, and thiamethoxam on “bee attractive” crops. Yet so far, these same effects have not been observed in field studies. Here we review the three key dosage factors (concentration, duration and choice) relevant to field conditions, and conclude that these have probably been over estimated in many laboratory based studies