bluuebunny/crossref_metadata_2025_split huggingface dataset:
Caenorhabditis elegans exhibit a coupling between the defecation motor program and directed locomotion
Authors: Nagy Stanislav , Huang Yung-Chi , Alkema Mark J. , Biron David 
Published: November 2015

AbstractDistinct motor programs can be coupled to refine the repertoire of behavior dynamics. However, mechanisms underlying such coupling are poorly understood. The defecation motor program (DMP) of C. elegans is composed of a succession of body contraction and expulsion steps, performed repeatedly with a period of 50–60 sec. We show that recurring patterns of directed locomotion are executed in tandem with, co-reset and co-terminate with the DMP cycle. Calcium waves in the intestine and proton signaling were shown to regulate the DMP. We found that genetic manipulations affecting these calcium dynamics regulated the corresponding patterns of directed locomotion. Moreover, we observed the initiation of a recurring locomotion pattern 10 seconds prior to the posterior body contraction, suggesting that the synchronized motor program may initiate prior to the DMP. This study links two multi-step motor programs executed by C. elegans in synchrony, utilizing non-neuronal tissue to drive directed locomotion.
Local false discovery rate estimation using feature reliability in LC/MS metabolomics data
Authors: Chong Elizabeth Y. , Huang Yijian , Wu Hao , Ghasemzadeh Nima , Uppal Karan , Quyyumi Arshed A. , Jones Dean P. , Yu Tianwei 
Published: November 2015

AbstractFalse discovery rate (FDR) control is an important tool of statistical inference in feature selection. In mass spectrometry-based metabolomics data, features can be measured at different levels of reliability and false features are often detected in untargeted metabolite profiling as chemical and/or bioinformatics noise. The traditional false discovery rate methods treat all features equally, which can cause substantial loss of statistical power to detect differentially expressed features. We propose a reliability index for mass spectrometry-based metabolomics data with repeated measurements, which is quantified using a composite measure. We then present a new method to estimate the local false discovery rate (lfdr) that incorporates feature reliability. In simulations, our proposed method achieved better balance between sensitivity and controlling false discovery, as compared to traditional lfdr estimation. We applied our method to a real metabolomics dataset and were able to detect more differentially expressed metabolites that were biologically meaningful.
Mitochondrial dysfunction in fatty acid oxidation disorders: insights from human and animal studies
Authors: Wajner Moacir , Amaral Alexandre Umpierrez 
Published: November 2015

Mitochondrial fatty acid oxidation (FAO) plays a pivotal role in maintaining body energy homoeostasis mainly during catabolic states. Oxidation of fatty acids requires approximately 25 proteins. Inherited defects of FAO have been identified in the majority of these proteins and constitute an important group of inborn errors of metabolism. Affected patients usually present with severe hepatopathy, cardiomyopathy and skeletal myopathy, whereas some patients may suffer acute and/or progressive encephalopathy whose pathogenesis is poorly known. In recent years growing evidence has emerged indicating that energy deficiency/disruption of mitochondrial homoeostasis is involved in the pathophysiology of some fatty acid oxidation defects (FAOD), although the exact underlying mechanisms are not yet established. Characteristic fatty acids and carnitine derivatives are found at high concentrations in these patients and more markedly during episodes of metabolic decompensation that are associated with worsening of clinical symptoms. Therefore, it is conceivable that these compounds may be toxic. We will briefly summarize the current knowledge obtained from patients and genetic mouse models with these disorders indicating that disruption of mitochondrial energy, redox and calcium homoeostasis is involved in the pathophysiology of the tissue damage in the more common FAOD, including medium-chain acyl-CoA dehydrogenase (MCAD), long-chain 3-hydroxyacyl-CoA dehydrogenase (LCHAD) and very long-chain acyl-CoA dehydrogenase (VLCAD) deficiencies. We will also provide evidence that the fatty acids and derivatives that accumulate in these diseases disrupt mitochondrial homoeostasis. The elucidation of the toxic mechanisms of these compounds may offer new perspectives for potential novel adjuvant therapeutic strategies in selected disorders of this group.
iPQF: a new peptide-to-protein summarization method using peptide spectra characteristics to improve protein quantification
Authors: Fischer Martina , Renard Bernhard Y. 
Published: November 2015

Abstract
Motivation: Isobaric labelling techniques such as iTRAQ and TMT are popular methods for relative protein abundance estimation in proteomic studies. However, measurements are assessed at the peptide spectrum level and exhibit substantial heterogeneity per protein. Hence, clever summarization strategies are required to infer protein ratios. So far, current methods rely exclusively on quantitative values, while additional information on peptides is available, yet it is not considered in these methods.
Methods: We present iPQF (isobaric Protein Quantification based on Features) as a novel peptide-to-protein summarization method, which integrates peptide spectra characteristics as well as quantitative values for protein ratio estimation. We investigate diverse features characterizing spectra reliability and reveal significant correlations to ratio accuracy in spectra. As a result, we developed a feature-based weighting of peptide spectra.
Results: A performance evaluation of iPQF in comparison to nine different protein ratio inference methods is conducted on five published MS2 and MS3 datasets with predefined ground truth. We demonstrate the benefit of using peptide feature information to improve protein ratio estimation. Compared to purely quantitative approaches, our proposed strategy achieves increased accuracy by addressing peptide spectra reliability.
Availability and implementation: The iPQF algorithm is available within the established R/Bioconductor package MSnbase (version ≥ 1.17.8).
Contact: renardB@rki.de
Supplementary information: Supplementary data are available at Bioinformatics online.
CDSfold: an algorithm for designing a protein-coding sequence with the most stable secondary structure
Authors: Terai Goro , Kamegai Satoshi , Asai Kiyoshi 
Published: November 2015

Abstract
Motivation: An important problem in synthetic biology is to design a nucleotide sequence of an mRNA that confers a desirable expression level of a target protein. The secondary structure of protein-coding sequences (CDSs) is one potential factor that could have both positive and negative effects on protein production. To elucidate the role of secondary structure in CDSs, algorithms for manipulating secondary structure should be developed.
Results: We developed an algorithm for designing a CDS with the most stable secondary structure among all possible ones translated into the same protein, and implemented it as the program CDSfold. The algorithm runs the Zuker algorithm under the constraint of a given amino acid sequence. The time and space complexity is O(L3) and O(L2), respectively, where L is the length of the CDS to be designed. Although our algorithm is slower than the original Zuker algorithm, it could design a relatively long (2.7-kb) CDS in approximately 1 h.
Availability and implementation: The CDSfold program is freely available for non-commercial users as stand-alone and web-based software from http://cdsfold.trahed.jp/cdsfold/.
Contacts: terai-goro@aist.go.jp or asai@k.u-tokyo.ac.jp
Supplementary information: Supplementary data are available at Bioinformatics online.
AccessFold: predicting RNA–RNA interactions with consideration for competing self-structure
Authors: DiChiacchio Laura , Sloma Michael F. , Mathews David H. 
Published: November 2015

AbstractMotivation: There are numerous examples of RNA–RNA complexes, including microRNA–mRNA and small RNA–mRNA duplexes for regulation of translation, guide RNA interactions with target RNA for post-transcriptional modification and small nuclear RNA duplexes for splicing. Predicting the base pairs formed between two interacting sequences remains difficult, at least in part because of the competition between unimolecular and bimolecular structure.Results: Two algorithms were developed for improved prediction of bimolecular RNA structure that consider the competition between self-structure and bimolecular structure. These algorithms utilize two novel approaches to evaluate accessibility: free energy density minimization and pseudo-energy minimization. Free energy density minimization minimizes the folding free energy change per nucleotide involved in an intermolecular secondary structure. Pseudo-energy minimization (called AccessFold) minimizes the sum of free energy change and a pseudo-free energy penalty for bimolecular pairing of nucleotides that are unlikely to be accessible for bimolecular structure. The pseudo-free energy, derived from unimolecular pairing probabilities, is applied per nucleotide in bimolecular pairs, and this approach is able to predict binding sites that are split by unimolecular structures. A benchmark set of 17 bimolecular RNA structures was assembled to assess structure prediction. Pseudo-energy minimization provides a statistically significant improvement in sensitivity over the method that was found in a benchmark to be the most accurate previously available method, with an improvement from 36.8% to 57.8% in mean sensitivity for base pair prediction.Availability and implementation: Pseudo-energy minimization is available for download as AccessFold, under an open-source license and as part of the RNAstructure package, at: http://rna.urmc.rochester.edu/RNAstructure.html.Contact: david_mathews@urmc.rochester.eduSupplementary information: Supplementary data are available at Bioinformatics online.
Large-scale machine learning for metagenomics sequence classification
Authors: Vervier Kévin , Mahé Pierre , Tournoud Maud , Veyrieras Jean-Baptiste , Vert Jean-Philippe 
Published: November 2015

Abstract
Motivation: Metagenomics characterizes the taxonomic diversity of microbial communities by sequencing DNA directly from an environmental sample. One of the main challenges in metagenomics data analysis is the binning step, where each sequenced read is assigned to a taxonomic clade. Because of the large volume of metagenomics datasets, binning methods need fast and accurate algorithms that can operate with reasonable computing requirements. While standard alignment-based methods provide state-of-the-art performance, compositional approaches that assign a taxonomic class to a DNA read based on the k-mers it contains have the potential to provide faster solutions.
Results: We propose a new rank-flexible machine learning-based compositional approach for taxonomic assignment of metagenomics reads and show that it benefits from increasing the number of fragments sampled from reference genome to tune its parameters, up to a coverage of about 10, and from increasing the k-mer size to about 12. Tuning the method involves training machine learning models on about 108 samples in 107 dimensions, which is out of reach of standard softwares but can be done efficiently with modern implementations for large-scale machine learning. The resulting method is competitive in terms of accuracy with well-established alignment and composition-based tools for problems involving a small to moderate number of candidate species and for reasonable amounts of sequencing errors. We show, however, that machine learning-based compositional approaches are still limited in their ability to deal with problems involving a greater number of species and more sensitive to sequencing errors. We finally show that the new method outperforms the state-of-the-art in its ability to classify reads from species of lineage absent from the reference database and confirm that compositional approaches achieve faster prediction times, with a gain of 2–17 times with respect to the BWA-MEM short read mapper, depending on the number of candidate species and the level of sequencing noise.
Availability and implementation: Data and codes are available at http://cbio.ensmp.fr/largescalemetagenomics.
Contact: pierre.mahe@biomerieux.com
Supplementary information: Supplementary data are available at Bioinformatics online.
SomVarIUS: somatic variant identification from unpaired tissue samples
Authors: Smith Kyle S. , Yadav Vinod K. , Pei Shanshan , Pollyea Daniel A. , Jordan Craig T. , De Subhajyoti 
Published: November 2015

Abstract
Motivation: Somatic variant calling typically requires paired tumor-normal tissue samples. Yet, paired normal tissues are not always available in clinical settings or for archival samples.
Results: We present SomVarIUS, a computational method for detecting somatic variants using high throughput sequencing data from unpaired tissue samples. We evaluate the performance of the method using genomic data from synthetic and real tumor samples. SomVarIUS identifies somatic variants in exome-seq data of  ∼150 ×  coverage with at least 67.7% precision and 64.6% recall rates, when compared with paired-tissue somatic variant calls in real tumor samples. We demonstrate the utility of SomVarIUS by identifying somatic mutations in formalin-fixed samples, and tracking clonal dynamics of oncogenic mutations in targeted deep sequencing data from pre- and post-treatment leukemia samples.
Availability and implementation: SomVarIUS is written in Python 2.7 and available at http://www.sjdlab.org/resources/
Contact: subhajyoti.de@ucdenver.edu
Supplementary information: Supplementary data are available at Bioinformatics online.
CellTracker (not only) for dummies
Authors: Piccinini Filippo , Kiss Alexa , Horvath Peter 
Published: November 2015

Abstract
Motivation: Time-lapse experiments play a key role in studying the dynamic behavior of cells. Single-cell tracking is one of the fundamental tools for such analyses. The vast majority of the recently introduced cell tracking methods are limited to fluorescently labeled cells. An equally important limitation is that most software cannot be effectively used by biologists without reasonable expertise in image processing. Here we present CellTracker, a user-friendly open-source software tool for tracking cells imaged with various imaging modalities, including fluorescent, phase contrast and differential interference contrast (DIC) techniques.
Availability and implementation: CellTracker is written in MATLAB (The MathWorks, Inc., USA). It works with Windows, Macintosh and UNIX-based systems. Source code and graphical user interface (GUI) are freely available at: http://celltracker.website/.
Contact: horvath.peter@brc.mta.hu
Supplementary information: Supplementary data are available at Bioinformatics online.
FoCuS-point: software for STED fluorescence correlation and time-gated single photon counting
Authors: Waithe Dominic , Clausen Mathias P. , Sezgin Erdinc , Eggeling Christian 
Published: November 2015

Abstract
Motivation: Fluorescence Correlation Spectroscopy (FCS) is a popular tool for measuring molecular mobility and how mobility relates to molecular interaction dynamics and bioactivity in living cells. The FCS technique has been significantly advanced by its combination with super-resolution STED microscopy (STED-FCS). Specifically, the use of gated detection has shown great potential for enhancing STED-FCS, but has also created a demand for software which is efficient and also implements the latest algorithms. Prior to this study, no open software has been available which would allow practical time-gating and correlation of point data derived from STED-FCS experiments.
Results: The product of this study is a piece of stand-alone software called FoCuS-point. FoCuS-point utilizes advanced time-correlated single-photon counting (TCSPC) correlation algorithms along with time-gated filtering and innovative data visualization. The software has been designed to be highly user-friendly and is tailored to handle batches of data with tools designed to process files in bulk. FoCuS-point also includes advanced fitting algorithms which allow the parameters of the correlation curves and thus the kinetics of diffusion to be established quickly and efficiently.
Availability and implementation: FoCuS-point is written in python and is available through the github repository: https://github.com/dwaithe/FCS_point_correlator. Furthermore, compiled versions of the code are available as executables which can be run directly in Linux, Windows and Mac OSX operating systems.
Contact: dominic.waithe@imm.ox.ac.uk
LocusExplorer: a user-friendly tool for integrated visualization of human genetic association data and biological annotations
Authors: Dadaev Tokhir , Leongamornlert Daniel A. , Saunders Edward J. , Eeles Rosalind , Kote-Jarai Zsofia 
Published: November 2015

Abstract
Summary: In this article, we present LocusExplorer, a data visualization and exploration tool for genetic association data. LocusExplorer is written in R using the Shiny library, providing access to powerful R-based functions through a simple user interface. LocusExplorer allows users to simultaneously display genetic, statistical and biological data for humans in a single image and allows dynamic zooming and customization of the plot features. Publication quality plots may then be produced in a variety of file formats.
Availability and implementation: LocusExplorer is open source and runs through R and a web browser. It is available at www.oncogenetics.icr.ac.uk/LocusExplorer/ or can be installed locally and the source code accessed from https://github.com/oncogenetics/LocusExplorer.
Contact: tokhir.dadaev@icr.ac.uk
The Northern
récit paysan
: Regional Variations of the Modern Peasant Novel in Haiti
Authors: Stieber Chelsea 
Published: November 2015

Abstract

In a revisionist reading of the Haitian peasant novel, this article addresses the short shrift given to Haiti's regionalism in scholarship, a lacuna that social geographer Georges Anglade attributes to ‘les effets d'occultation propre à la structure dominante centralisée’. Contrary to Port-au-Prince-centric renderings of Haitian literary history, which locate the elaboration of the modern peasant novel in the elite (read: Port-au-Princean) intelligentsia's quest for a more authentic national identity, I show that the modern peasant novel emerged in the pages of the northern literary magazine
Stella
(Cap-Haïtien, 1926–30) out of a primarily regional context. Through a close reading of several short and virtually unstudied
récits paysans
published in
Stella
, I argue that northern writers deployed the peasant novel genre as a regional response to the process of centralization and regional ‘occultation’ by the centralized nation-state apparatus. In particular, I examine how the lived experience of dramatic demographic and economic decline in the north informed the specific contours of this new literary expression.
Mountain lion (
Puma concolor
) feeding behavior in the Little Missouri Badlands of North Dakota
Authors: Wilckens David T. , Smith Joshua B. , Tucker Stephanie A. , Thompson Daniel J. , Jenks Jonathan A. 
Published: November 2015

Abstract
Recent recolonization of mountain lions ( Puma concolor ) into the Little Missouri Badlands of North Dakota has led to questions regarding the potential impacts of predation on prey populations in the region. From 2012 to 2013, we deployed 9 real-time GPS collars to investigate mountain lion feeding habits. We monitored mountain lions for 1,845 telemetry-days, investigated 506 GPS clusters, and identified 292 feeding events. Deer ( Odocoileus spp.) were the most prevalent item in mountain lion diets (76.9%). We used logistic regression to predict feeding events and size of prey consumed at an additional 535 clusters. Our top model for predicting presence of prey items produced a receiver operating characteristic score of 0.90 and an overall accuracy of 81.4%. Application of our models to all GPS clusters resulted in an estimated ungulate kill rate of 1.09 ungulates/week (95% confidence interval [ CI ] = 0.83–1.36) in summer (15 May‒15 November) and 0.90 ungulates/week (95% CI = 0.69–1.12) in winter (16 November‒14 May). Estimates of total biomass consumed were 5.8kg/day (95% CI = 4.7–6.9) in summer and 7.2kg/day (95% CI = 5.3–9.2) in winter. Overall scavenge rates were 3.7% in summer and 11.9% in winter. Prey composition included higher proportions of nonungulates in summer (female = 21.5%; male = 24.8%) than in winter (female = 4.8%; male = 7.5%). Proportion of juvenile ungulates in mountain lion diets increased during the fawning season (June‒August) following the ungulate birth pulse in June (June–August = 60.7%, 95% CI = 43.0–78.3; September–May = 37.2%, 95% CI = 30.8–43.7), resulting in an ungulate kill rate 1.61 times higher (1.41 ungulates/week, 95% CI = 1.12–1.71) than during the remainder of the year (0.88 ungulates/week, 95% CI = 0.62–1.13). Quantifying these feeding characteristics is essential to assessing the potential impacts of mountain lions on prey populations in the North Dakota Badlands, where deer dominate the available prey base and mountain lions represent the lone apex predator.
Tuberculosis Incidence and Risk Factors Among Human Immunodeficiency Virus (HIV)-Infected Adults Receiving Antiretroviral Therapy in a Large HIV Program in Nigeria
Authors: Chang Charlotte A. , Meloni Seema Thakore , Eisen Geoffrey , Chaplin Beth , Akande Patrick , Okonkwo Prosper , Rawizza Holly E. , Tchetgen Tchetgen Eric , Kanki Phyllis J. 
Published: November 2015

Abstract
Background.  Despite the benefits of antiretroviral therapy (ART), tuberculosis (TB) is the leading cause of mortality among human immunodeficiency virus (HIV)-infected persons in Africa. Nigeria bears the highest TB burden in Africa and second highest HIV burden globally. This long-term multicenter study aimed to determine the incidence rate and predictors of TB in adults in the Harvard/AIDS Prevention Initiative in Nigeria (APIN) and President's Emergency Plan for AIDS Relief (PEPFAR) Nigeria ART program.
Methods.  This retrospective evaluation used data collected from 2004 to 2012 through the Harvard/APIN PEPFAR program. Risk factors for incident TB were determined using multivariate Cox proportional hazards regression with time-dependent covariates.
Results.  Of 50 320 adults enrolled from 2005 to 2010, 11 092 (22%) had laboratory-confirmed active TB disease at ART initiation, and 2021 (4%) developed active TB after commencing ART. During 78 228 total person-years (PY) of follow-up, the TB incidence rate was 25.8 cases per 1000 PY (95% confidence interval [CI], 24.7–27.0) overall, and it decreased significantly both with duration on ART and calendar year. Risk factors at ART initiation for incident TB included the following: earlier ART enrollment year, tenofovir-containing initial ART regimen, and World Health Organization clinical stage above 1. Time-updated risk factors included the following: low body mass index, low CD4+ cell count, unsuppressed viral load, anemia, and ART adherence below 80%.
Conclusions.  The rate of incident TB decreased with longer duration on ART and over the program years. The strongest TB risk factors were time-updated clinical markers, reinforcing the importance of consistent clinical and laboratory monitoring of ART patients in prompt diagnosis and treatment of TB and other coinfections.