Accurate reconstruction of viral quasispecies spectra through improved estimation of strain richness

Background Estimating the number of different species (richness) in a mixed microbial population has been a main focus in metagenomic research. Existing methods of species richness estimation ride on the assumption that the reads in each assembled contig correspond to only one of the microbial genomes in the population. This assumption and the underlying probabilistic formulations of existing methods are not useful for quasispecies populations where the strains are highly genetically related. The lack of knowledge on the number of different strains in a quasispecies population is observed to hinder the precision of existing Viral Quasispecies Spectrum Reconstruction (QSR) methods due to the uncontrolled reconstruction of a large number of in silico false positives. In this work, we formulated a novel probabilistic method for strain richness estimation specifically targeting viral quasispecies. By using this approach we improved our recently proposed spectrum reconstruction pipeline ViQuaS to achieve higher levels of precision in reconstructed quasispecies spectra without compromising the recall rates. We also discuss how one other existing popular QSR method named ShoRAH can be improved using this new approach. Results On benchmark data sets, our estimation method provided accurate richness estimates (< 0.2 median estimation error) and improved the precision of ViQuaS by 2%-13% and F-score by 1%-9% without compromising the recall rates. We also demonstrate that our estimation method can be used to improve the precision and F-score of ShoRAH by 0%-7% and 0%-5% respectively. Conclusions The proposed probabilistic estimation method can be used to estimate the richness of viral populations with a quasispecies behavior and to improve the accuracy of the quasispecies spectra reconstructed by the existing methods ViQuaS and ShoRAH in the presence of a moderate level of technical sequencing errors

Hip fracture risk assessment: Artificial neural network outperforms conditional logistic regression in an age- and sex-matched case control study

Copyright @ 2013 Tseng et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background - Osteoporotic hip fractures with a significant morbidity and excess mortality among the elderly have imposed huge health and economic burdens on societies worldwide. In this age- and sex-matched case control study, we examined the risk factors of hip fractures and assessed the fracture risk by conditional logistic regression (CLR) and ensemble artificial neural network (ANN). The performances of these two classifiers were compared. Methods - The study population consisted of 217 pairs (149 women and 68 men) of fractures and controls with an age older than 60 years. All the participants were interviewed with the same standardized questionnaire including questions on 66 risk factors in 12 categories. Univariate CLR analysis was initially conducted to examine the unadjusted odds ratio of all potential risk factors. The significant risk factors were then tested by multivariate analyses. For fracture risk assessment, the participants were randomly divided into modeling and testing datasets for 10-fold cross validation analyses. The predicting models built by CLR and ANN in modeling datasets were applied to testing datasets for generalization study. The performances, including discrimination and calibration, were compared with non-parametric Wilcoxon tests. Results - In univariate CLR analyses, 16 variables achieved significant level, and six of them remained significant in multivariate analyses, including low T score, low BMI, low MMSE score, milk intake, walking difficulty, and significant fall at home. For discrimination, ANN outperformed CLR in both 16- and 6-variable analyses in modeling and testing datasets (p?<?0.005). For calibration, ANN outperformed CLR only in 16-variable analyses in modeling and testing datasets (p?=?0.013 and 0.047, respectively). Conclusions - The risk factors of hip fracture are more personal than environmental. With adequate model construction, ANN may outperform CLR in both discrimination and calibration. ANN seems to have not been developed to its full potential and efforts should be made to improve its performance.National Health Research Institutes in Taiwa

Evidence for Anthropogenic Surface Loading as Trigger Mechanism of the 2008 Wenchuan Earthquake

Two and a half years prior to China's M7.9 Wenchuan earthquake of May 2008, at least 300 million metric tons of water accumulated with additional seasonal water level changes in the Minjiang River Valley at the eastern margin of the Longmen Shan. This article shows that static surface loading in the Zipingpu water reservoir induced Coulomb failure stresses on the nearby Beichuan thrust fault system at <17km depth. Triggering stresses exceeded levels of daily lunar and solar tides and perturbed a fault area measuring 416+/-96km^2. These stress perturbations, in turn, likely advanced the clock of the mainshock and directed the initial rupture propagation upward towards the reservoir on the "Coulomb-like" Beichuan fault with rate-and-state dependent frictional behavior. Static triggering perturbations produced up to 60 years (0.6%) of equivalent tectonic loading, and show strong correlations to the coseismic slip. Moreover, correlations between clock advancement and coseismic slip, observed during the mainshock beneath the reservoir, are strongest for a longer seismic cycle (10kyr) of M>7 earthquakes. Finally, the daily event rate of the micro-seismicity (M>0.5) correlates well with the static stress perturbations, indicating destabilization.Comment: 22 pages, 4 figures, 3 table

A microchip optomechanical accelerometer

The monitoring of accelerations is essential for a variety of applications ranging from inertial navigation to consumer electronics. The basic operation principle of an accelerometer is to measure the displacement of a flexibly mounted test mass; sensitive displacement measurement can be realized using capacitive, piezo-electric, tunnel-current, or optical methods. While optical readout provides superior displacement resolution and resilience to electromagnetic interference, current optical accelerometers either do not allow for chip-scale integration or require bulky test masses. Here we demonstrate an optomechanical accelerometer that employs ultra-sensitive all-optical displacement read-out using a planar photonic crystal cavity monolithically integrated with a nano-tethered test mass of high mechanical Q-factor. This device architecture allows for full on-chip integration and achieves a broadband acceleration resolution of 10 \mu g/rt-Hz, a bandwidth greater than 20 kHz, and a dynamic range of 50 dB with sub-milliwatt optical power requirements. Moreover, the nano-gram test masses used here allow for optomechanical back-action in the form of cooling or the optical spring effect, setting the stage for a new class of motional sensors.Comment: 16 pages, 9 figure

The ALMaQUEST Survey: The Molecular Gas Main Sequence and the Origin of the Star-forming Main Sequence

The origin of the star forming main sequence ( i.e., the relation between star formation rate and stellar mass, globally or on kpc-scales; hereafter SFMS) remains a hotly debated topic in galaxy evolution. Using the ALMA-MaNGA QUEnching and STar formation (ALMaQUEST) survey, we show that for star forming spaxels in the main sequence galaxies, the three local quantities, star-formation rate surface density (\sigsfr), stellar mass surface density (\sigsm), and the \h2~mass surface density (\sigh2), are strongly correlated with one another and form a 3D linear (in log) relation with dispersion. In addition to the two well known scaling relations, the resolved SFMS (\sigsfr~ vs. \sigsm) and the Schmidt-Kennicutt relation (\sigsfr~ vs. \sigh2; SK relation), there is a third scaling relation between \sigh2~ and \sigsm, which we refer to as the `molecular gas main sequence' (MGMS). The latter indicates that either the local gas mass traces the gravitational potential set by the local stellar mass or both quantities follow the underlying total mass distributions. The scatter of the resolved SFMS ($\sigma \sim 0.25$ dex) is the largest compared to those of the SK and MGMS relations ($\sigma \sim$ 0.2 dex). A Pearson correlation test also indicates that the SK and MGMS relations are more strongly correlated than the resolved SFMS. Our result suggests a scenario in which the resolved SFMS is the least physically fundamental and is the consequence of the combination of the SK and the MGMS relations

KCa1.1, a calcium-activated potassium channel subunit alpha 1, is targeted by miR-17-5p and modulates cell migration in malignant pleural mesothelioma

© 2016 Lin et al. Background: Malignant pleural mesothelioma (MPM) is an aggressive, locally invasive, cancer elicited by asbestos exposure and almost invariably a fatal diagnosis. To date, we are one of the leading laboratory that compared microRNA expression profiles in MPM and normal mesothelium samples in order to identify dysregulated microRNAs with functional roles in mesothelioma. We interrogated a significant collection of MPM tumors and normal pleural samples in our biobank in search for novel therapeutic targets. Methods: Utilizing mRNA-microRNA correlations based on differential gene expression using Gene Set Enrichment Analysis (GSEA), we systematically combined publicly available gene expression datasets with our own MPM data in order to identify candidate targets for MPM therapy. Results: We identified enrichment of target binding sites for the miR-17 and miR-30 families in both MPM tumors and cell lines. RT-qPCR revealed that members of both families were significantly downregulated in MPM tumors and cell lines. Interestingly, lower expression of miR-17-5p (P = 0.022) and miR-20a-5p (P = 0.026) was clearly associated with epithelioid histology. We interrogated the predicted targets of these differentially expressed microRNA families in MPM cell lines, and identified KCa1.1, a calcium-activated potassium channel subunit alpha 1 encoded by the KCNMA1 gene, as a target of miR-17-5p. KCa1.1 was overexpressed in MPM cells compared to the (normal) mesothelial line MeT-5A, and was also upregulated in patient tumor samples compared to normal mesothelium. Transfection of MPM cells with a miR-17-5p mimic or KCNMA1-specific siRNAs reduced mRNA expression of KCa1.1 and inhibited MPM cell migration. Similarly, treatment with paxilline, a small molecule inhibitor of KCa1.1, resulted in suppression of MPM cell migration. Conclusion: These functional data implicating KCa1.1 in MPM cell migration support our integrative approach using MPM gene expression datasets to identify novel and potentially druggable targets

The specificity and patterns of staining in human cells and tissues of p16INK4a antibodies demonstrate variant antigen binding

The validity of the identification and classification of human cancer using antibodies to detect biomarker proteins depends upon antibody specificity. Antibodies that bind to the tumour-suppressor protein p16INK4a are widely used for cancer diagnosis and research. In this study we examined the specificity of four commercially available anti-p16INK4a antibodies in four immunological applications. The antibodies H-156 and JC8 detected the same 16 kDa protein in western blot and immunoprecipitation tests, whereas the antibody F-12 did not detect any protein in western blot analysis or capture a protein that could be recognised by the H-156 antibody. In immunocytochemistry tests, the antibodies JC8 and H-156 detected a predominately cytoplasmic localised antigen, whose signal was depleted in p16INK4a siRNA experiments. F-12, in contrast, detected a predominately nuclear located antigen and there was no noticeable reduction in this signal after siRNA knockdown. Furthermore in immunohistochemistry tests, F-12 generated a different pattern of staining compared to the JC8 and E6H4 antibodies. These results demonstrate that three out of four commercially available p16INK4a antibodies are specific to, and indicate a mainly cytoplasmic localisation for, the p16INK4a protein. The F-12 antibody, which has been widely used in previous studies, gave different results to the other antibodies and did not demonstrate specificity to human p16INK4a. This work emphasizes the importance of the validation of commercial antibodies, aside to the previously reported use, for the full verification of immunoreaction specificity