Detecting Differential Expression from RNA-seq Data with Expression Measurement Uncertainty

High-throughput RNA sequencing (RNA-seq) has emerged as a revolutionary and powerful technology for expression profiling. Most proposed methods for detecting differentially expressed (DE) genes from RNA-seq are based on statistics that compare normalized read counts between conditions. However, there are few methods considering the expression measurement uncertainty into DE detection. Moreover, most methods are only capable of detecting DE genes, and few methods are available for detecting DE isoforms. In this paper, a Bayesian framework (BDSeq) is proposed to detect DE genes and isoforms with consideration of expression measurement uncertainty. This expression measurement uncertainty provides useful information which can help to improve the performance of DE detection. Three real RAN-seq data sets are used to evaluate the performance of BDSeq and results show that the inclusion of expression measurement uncertainty improves accuracy in detection of DE genes and isoforms. Finally, we develop a GamSeq-BDSeq RNA-seq analysis pipeline to facilitate users, which is freely available at the website http://parnec.nuaa.edu.cn/liux/GSBD/GamSeq-BDSeq.html.Comment: 20 pages, 9 figure

Representing Image Matrices: Eigenimages Versus Eigenvectors. Lect

Abstract. We consider the problem of representing image matrices with a set of basis functions. One common solution for that problem is to first transform the 2D image matrices into 1D image vectors and then to represent those 1D image vectors with eigenvectors, as done in classical principal component analysis. In this paper, we adopt a natural representation for the 2D image matrices using eigenimages, which are 2D matrices with the same size of original images and can be directly computed from original 2D image matrices. We discuss how to compute those eigenimages effectively. Experimental result on ORL image database shows the advantages of eigenimages method in representing the 2D images

Metabolic Interaction of the Active Constituents of Coptis chinensis

Coptis chinensis is commonly used in traditional Chinese medicine. The study investigated metabolic interaction of the active constituents (berberine, coptisine, palmatine, and jatrorrhizine) of Coptis chinensis in human liver microsomes. After incubation of the four constituents of Coptis chinensis in HLMs, the metabolism of the four constituents was observed by HPLC. The in vitro inhibition experiment between the active constituents was conducted, and IC50 value was estimated. Coptisine exhibited inhibitions against the formation of the two metabolites of berberine with IC50 values of 6.5 and 8.3 μM, respectively. Palmatine and jatrorrhizine showed the weaker inhibitory effect on the formation of the metabolites of berberine. Berberine showed a weak inhibitory effect on the production of coptisine metabolite with an IC50 value of 115 μM, and palmatine and jatrorrhizine had little inhibitory effect on the formation of coptisine metabolite. Berberine, coptisine, and jatrorrhizine showed no inhibitory effect on the generation of palmatine metabolite (IC50 > 200 μM). The findings suggested that there are different degrees of metabolic interaction between the four components. Coptisine showed the strongest inhibition toward berberine metabolism

Label-aligned multi-task feature learning for multimodal classification of Alzheimer’s disease and mild cognitive impairment

Multimodal classification methods using different modalities of imaging and non-imaging data have recently shown great advantages over traditional single-modality-based ones for diagnosis and prognosis of Alzheimer’s disease (AD), as well as its prodromal stage, i.e., mild cognitive impairment (MCI). However, to the best of our knowledge, most existing methods focus on mining the relationship across multiple modalities of the same subjects, while ignoring the potentially useful relationship across different subjects. Accordingly, in this paper, we propose a novel learning method for multimodal classification of AD/MCI, by fully exploring the relationships across both modalities and subjects. Specifically, our proposed method includes two subsequent components, i.e., label-aligned multi-task feature selection and multimodal classification. In the first step, the feature selection learning from multiple modalities are treated as different learning tasks and a group sparsity regularizer is imposed to jointly select a subset of relevant features. Furthermore, to utilize the discriminative information among labeled subjects, a new label-aligned regularization term is added into the objective function of standard multi-task feature selection, where label-alignment means that all multi-modality subjects with the same class labels should be closer in the new feature-reduced space. In the second step, a multi-kernel support vector machine (SVM) is adopted to fuse the selected features from multi-modality data for final classification. To validate our method, we perform experiments on the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database using baseline MRI and FDG-PET imaging data. The experimental results demonstrate that our proposed method achieves better classification performance compared with several state-of-the-art methods for multimodal classification of AD/MCI

Multiple resolution seismic attenuation imaging at Mt. Vesuvius

A three-dimensional S wave attenuation tomography of Mt. Vesuvius has been ob- tained with multiple measurements of coda-normalized S-wave spectra of local small magnitude earthquakes. We used 6609 waveforms, relative to 826 volcano-tectonic earthquakes, located close to the crater axis in a depth range between 1 and 4 km (below the sea level), recorded at seven 3-component digital seismic stations. We adopted a two-point ray-tracing; rays were traced in an high resolution 3-D velocity model. The spatial resolution achieved in the attenuation tomography is comparable with that of the velocity tomography (we resolve 300 m side cubic cells). We statisti- cally tested that the results are almost independent from the radiation pattern. We also applied an improvement of the ordinary spectral-slope method to both P- and S-waves, assuming that the di¤erences between the theoretical and the experimental high frequency spectral-slope are only due to the attenuation e¤ects.We could check the coda-normalization method comparing the S attenuation image obtained with the two methods. The images were obtained with a multiple resolution approach. Results show the general coincidence of low attenuation with high velocity zones. The joint interpretation of velocity and attenuation images allows us to interpret the low attenuation zone intruding toward the surface until a depth of 500 meters below the sea level as related to the residual part of solidi ed magma from the last eruption. In the depth range between -700 and -2300 meters above sea level, the images are consistent with the presence of multiple acquifer layers. No evidence of magma patches greater than the minimum cell dimension (300m) has been found. A shallow P wave attenuation anomaly (beneath the southern ank of the volcano) is consitent with the presence of gas saturated rocks. The zone characterized by the maximum seismic energy release cohincides with a high attenuation and low velocity volume, interpreted as a cracked medium

Effects of Danshen Ethanol Extract on the Pharmacokinetics of Fexofenadine in Healthy Volunteers

This study investigated the effect of multidose administration of danshen ethanol extract on fexofenadine pharmacokinetics in healthy volunteers. A sequential, open-label, two-period pharmacokinetic interaction design was used. 12 healthy male volunteers received a single oral dose of fexofenadine (60 mg) followed by danshen ethanol extract (1 g orally, three times a day) for 10 days, after which they received 1 g of the danshen extract with fexofenadine (60 mg) on the last day. The plasma concentrations of fexofenadine was measured by LC-MS/MS. After 10 days of the danshen extract administration, the mean AUC and max of the fexofenadine was decreased by 37.2% and 27.4% compared with the control, respectively. The mean clearance of fexofenadine was increased by 104.9%. The in vitro study showed that tanshinone IIA and cryptotanshinone could induce MDR1 mRNA. This study showed that multidose administration of danshen ethanol extract could increase oral clearance of fexofenadine. The increased oral clearance of fexofenadine is attributable to induction of intestinal P-glycoprotein

Opposite effects of single-dose and multidose administration of the ethanol extract of danshen on

The aim of this study was to investigate the effect of single-and multidose administration of the ethanol extract of danshen on in vivo CYP3A activity in healthy volunteers. A sequential, open-label, and three-period pharmacokinetic interaction study design was used based on 12 healthy male individuals. The plasma concentrations of midazolam and its metabolite 1-hydroxymidazolam were measured. Treatment with single dose of the extract caused the mean max of midazolam to increase by 87% compared with control. After 10 days of the danshen extract intake, the mean AUC 0-12 , max , and 1/2 of midazolam were decreased by 79.9%, 66.6%, and 43.8%, respectively. The mean clearance of midazolam was increased by 501.6% compared with control. The in vitro study showed that dihydrotanshinone I in the extract could inhibit CYP3A, while tanshinone IIA and cryptotanshinone could induce CYP3A. In conclusion, a single-dose administration of the danshen extract can inhibit intestinal CYP3A, but multidose administration can induce intestinal and hepatic CYP3A

Abstract: As an extension to 2DPCA, Generalized Low Rank Approximation of Matrices (GLRAM)

applies two-sided (i.e., the left and right) rather than single-sided (i.e., the left or the right alone) linear projecting transform(s) to each 2D image for compression and feature extraction. Its advantages over 2DPCA include higher compression ratio and superior classification performance etc. However, GLRAM can only adopt an iterative rather than analytical approach to get the left and right projecting transforms and lacks a criterion to automatically determine the dimensionality of the projected matrix. In this paper, a novel non-iterative GLRAM (NIGLRAM) is proposed to overcome the above shortcomings. Experimental results on ORL and AR face datasets and COIL-20 object dataset show that NIGLRAM can get not only so-needed closed-form transforms but also comparable performance to GLRAM

Crystal facet engineering of photoelectrodes for photoelectrochemical water splitting

Photoelectrochemical (PEC) water splitting is a promising approach for solar-driven hydrogen production with zero emissions, and it has been intensively studied over the past decades. However, the solar-to-hydrogen (STH) efficiencies of the current PEC systems are still far from the 10% target needed for practical application. The development of efficient photoelectrodes in PEC systems holds the key to achieving high STH efficiencies. In recent years, crystal facet engineering has emerged as an important strategy in designing efficient photoelectrodes for PEC water splitting, which has yet to be comprehensively reviewed and is the main focus of this article. After the Introduction, the second section of this review concisely introduces the mechanisms of crystal facet engineering. The subsequent section provides a snapshot of the unique facet-dependent properties of some semiconductor crystals including surface electronic structures, redox reaction sites, surface built-in electric fields, molecular adsorption, photoreaction activity, photocorrosion resistance, and electrical conductivity. Then, the methods for fabricating photoelectrodes with faceted semiconductor crystals are reviewed, with a focus on the preparation processes. In addition, the notable advantages of the crystal facet engineering of photoelectrodes in terms of light harvesting, charge separation and transfer, and surface reactions are critically discussed. This is followed by a systematic overview of the modification strategies of faceted photoelectrodes to further enhance the PEC performance. The last section summarizes the major challenges and some invigorating perspectives for future research on crystal facet engineered photoelectrodes, which are believed to play a vital role in promoting the development of this important research field