MsatAllele_1.0: An R package to visualize the binning of microsatellite Alleles

MsatAllele is a computer package built on R to visualize and bin the raw microsatellite allele size distributions. The method is based on the creation of an R database with exported files from the open-source electropherogram peak-reading program STRAND. Contrary to other binning programs, in this program, the bin limits are not fixed and are automatically defined by the data stored in the database. Data manipulation and graphical functions allow to 1) visualize raw allele size variation, allowing the detection of potential scoring errors, strange bin distributions, and unexpected spacing between the bins; 2) bin raw fragment sizes and write bin summary statistics for each locus; and 3) export genotype files with the resulting binned data.Fundacao para a Ciencia e Tecnologia [SFRH/BPD/14945/2004]; MEGIKELP [PTDC/MAR/65461/2006]info:eu-repo/semantics/publishedVersio

Research Collaborations and Scientific productivity among the Research Universities in South Africa

This study presents the share of 5 most productive South African institutions for the main stream scientific out put covering the 10 year periods of 1995-2004. This paper discusses the distribution of publications by institutions, Index of specialization, collaboration and pattern of co-authorship. The result shows that South African authors collaborate more frequently with international authors with a percentage of (73.99%) than did so for national collaboration which amount to (26.01%). This was confirmed statistically at the confidence level of P-value 0.025. A further non-parametric chi-square statistical analysis illustrated that there are significant differences in the proportion of co-authorship among the 5 institutions (p-value0.005)

Direct comparison of distinct naive pluripotent states in human embryonic stem cells

Until recently, human embryonic stem cells (hESCs) were shown to exist in a state of primed pluripotency, while mouse embryonic stem cells (mESCs) display a naive or primed pluripotent state. Here we show the rapid conversion of in-house-derived primed hESCs on mouse embryonic feeder layer (MEF) to a naive state within 5-6 days in naive conversion media (NCM-MEF), 6-10 days in naive human stem cell media (NHSM-MEF) and 14-20 days using the reverse-toggle protocol (RT-MEF). We further observe enhanced unbiased lineage-specific differentiation potential of naive hESCs converted in NCM-MEF, however, all naive hESCs fail to differentiate towards functional cell types. RNA-seq analysis reveals a divergent role of PI3K/AKT/mTORC signalling, specifically of the mTORC2 subunit, in the different naive hESCs. Overall, we demonstrate a direct evaluation of several naive culture conditions performed in the same laboratory, thereby contributing to an unbiased, more in-depth understanding of different naive hESCs

Non spontaneous saccadic movements identification in clinical electrooculography using machine learning

In this paper we evaluate the use of the machine learning algorithms Support Vector Machines, K-Nearest Neighbors, CART decision trees and Naive Bayes to identify non spontaneous saccades in clinical electrooculography tests. Our approach tries to solve problems like the use of manually established thresholds present in classical methods like identification by velocity threshold (I-VT) or identification by dispersion threshold (I-DT). We propose a modification to an adaptive threshold estimation algorithm for detecting signal impulses without the need of any user input. Also, a set of features were selected to take advantage of intrinsic characteristics of clinical electrooculography tests. The models were evaluated with signals recorded to subjects affected by Spinocerebellar Ataxia type 2 (SCA2). Results obtained by the algorithm shows accuracies over 97%, recalls over 97% and precisions over 91% for the four models evaluated.Universidad de Málaga, Campus de excelencia de Andalucía Tec

Disease activity and cognition in rheumatoid arthritis : an open label pilot study

Acknowledgements This work was supported in part by NIHR Newcastle Biomedical Research Centre. Funding for this study was provided by Abbott Laboratories. Abbott Laboratories were not involved in study design; in the collection, analysis and interpretation of data; or in the writing of the report.Peer reviewedPublisher PD

A temporally-constrained convolutive probabilistic model for pitch detection

A method for pitch detection which models the temporal evolution of musical sounds is presented in this paper. The proposed model is based on shift-invariant probabilistic latent component analysis, constrained by a hidden Markov model. The time-frequency representation of a produced musical note can be expressed by the model as a temporal sequence of spectral templates which can also be shifted over log-frequency. Thus, this approach can be effectively used for pitch detection in music signals that contain amplitude and frequency modulations. Experiments were performed using extracted sequences of spectral templates on monophonic music excerpts, where the proposed model outperforms a non-temporally constrained convolutive model for pitch detection. Finally, future directions are given for multipitch extensions of the proposed model

The big five: Discovering linguistic characteristics that typify distinct personality traits across Yahoo! answers members

Indexación: Scopus.This work was partially supported by the project FONDECYT “Bridging the Gap between Askers and Answers in Community Question Answering Services” (11130094) funded by the Chilean Government.In psychology, it is widely believed that there are five big factors that determine the different personality traits: Extraversion, Agreeableness, Conscientiousness and Neuroticism as well as Openness. In the last years, researchers have started to examine how these factors are manifested across several social networks like Facebook and Twitter. However, to the best of our knowledge, other kinds of social networks such as social/informational question-answering communities (e.g., Yahoo! Answers) have been left unexplored. Therefore, this work explores several predictive models to automatically recognize these factors across Yahoo! Answers members. As a means of devising powerful generalizations, these models were combined with assorted linguistic features. Since we do not have access to ask community members to volunteer for taking the personality test, we built a study corpus by conducting a discourse analysis based on deconstructing the test into 112 adjectives. Our results reveal that it is plausible to lessen the dependency upon answered tests and that effective models across distinct factors are sharply different. Also, sentiment analysis and dependency parsing proven to be fundamental to deal with extraversion, agreeableness and conscientiousness. Furthermore, medium and low levels of neuroticism were found to be related to initial stages of depression and anxiety disorders. © 2018 Lithuanian Institute of Philosophy and Sociology. All rights reserved.https://www.cys.cic.ipn.mx/ojs/index.php/CyS/article/view/275

Performance analysis with network-enhanced complexities: On fading measurements, event-triggered mechanisms, and cyber attacks

Copyright © 2014 Derui Ding et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Nowadays, the real-world systems are usually subject to various complexities such as parameter uncertainties, time-delays, and nonlinear disturbances. For networked systems, especially large-scale systems such as multiagent systems and systems over sensor networks, the complexities are inevitably enhanced in terms of their degrees or intensities because of the usage of the communication networks. Therefore, it would be interesting to (1) examine how this kind of network-enhanced complexities affects the control or filtering performance; and (2) develop some suitable approaches for controller/filter design problems. In this paper, we aim to survey some recent advances on the performance analysis and synthesis with three sorts of fashionable network-enhanced complexities, namely, fading measurements, event-triggered mechanisms, and attack behaviors of adversaries. First, these three kinds of complexities are introduced in detail according to their engineering backgrounds, dynamical characteristic, and modelling techniques. Then, the developments of the performance analysis and synthesis issues for various networked systems are systematically reviewed. Furthermore, some challenges are illustrated by using a thorough literature review and some possible future research directions are highlighted.This work was supported in part by the National Natural Science Foundation of China under Grants 61134009, 61329301, 61203139, 61374127, and 61374010, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany

A Laser-Guided Spinal Cord Displacement Injury in Adult Mice

Mouse models are unique for studying molecular mechanisms of neurotrauma because of the availability of various genetic modified mouse lines. For spinal cord injury (SCI) research, producing an accurate injury is essential, but it is challenging because of the small size of the mouse cord and the inconsistency of injury production. The Louisville Injury System Apparatus (LISA) impactor has been shown to produce precise contusive SCI in adult rats. Here, we examined whether the LISA impactor could be used to create accurate and graded contusive SCIs in mice. Adult C57BL/6 mice received a T10 laminectomy followed by 0.2, 0.5, and 0.8 mm displacement injuries, guided by a laser, from the dorsal surface of the spinal cord using the LISA impactor. Basso Mouse Scale (BMS), grid-walking, TreadScan, and Hargreaves analyses were performed for up to 6 weeks post-injury. All mice were euthanized at the 7th week, and the spinal cords were collected for histological analysis. Our results showed that the LISA impactor produced accurate and consistent contusive SCIs corresponding to mild, moderate, and severe injuries to the cord. The degree of injury severities could be readily determined by the BMS locomotor, grid-walking, and TreadScan gait assessments. The cutaneous hyperalgesia threshold was also significantly increased as the injury severity increased. The terminal lesion area and the spared white matter of the injury epicenter were strongly correlated with the injury severities. We conclude that the LISA device, guided by a laser, can produce reliable graded contusive SCIs in mice, resulting in severity-dependent behavioral and histopathological deficits