bluuebunny/crossref_metadata_2025_split huggingface dataset:
When the Injury's Healing Process Meets the Needs of a Top-Level Volleyball Player
Authors: Checcarelli Daniele , Zampolini Mauro , Berloco Michele , Fusco Claudia , Özçakar Levent 
Published: June 2018

Abstract
Managing top-level athlete's recovery after an injury is very complicated because it requires a challenging combination of clinical and social/professional aspects with the need to return as soon as possible to sports play. Herein, we report a top-level volleyball player for whom a finger splint combined with a custom made thermoplastic protection was used for the conservative management of a Mallet fracture reinjury. This way our player continued training and competitions in contrast to conventional rehabilitation protocols, which suggest to avoid new traumas until the healing phase is completed. After 8 wks, we obtained the fracture healing and a complete functional recovery without major medical complications. From our results, we suggest that novel treatment strategies or modification of conventional rehabilitation protocols are worth consideration for the management of high-level sports players' injuries. However, new clinical studies with a larger sample can compare these results with those resulting from both surgical procedures and from immobilization and rest as well.
Sex Education and HIV Testing Among Young Men Who Have Sex With Men: Findings From the 2006–2010 and 2011–2015 National Survey of Family Growth
Authors: Pierce Jace D. , Ylitalo Kelly R. , Lanning Beth A. , Limbers Christine C. 
Published: June 2018

Background:
Young men who have sex with men (YMSM) are disproportionally affected by HIV and exhibit low levels of HIV testing. The purpose of this study was to examine the relationship between sex education and subsequent HIV testing among YMSM.

Methods:
Data from sexually active men aged 15–24 years at interview in the 2006–2010 or 2011–2015 National Survey of Family Growth. Sex education included 3 contexts [formal institutions (eg, schools), parents, and health care providers] and specific topics. Outcome variables were ever- and recent-HIV testing. Multivariate models were adjusted for sociodemographics, and data were weighted to account for the complex survey sampling design.

Results:
A total of 323 sexually active YMSM met inclusion criteria. Overall, 42.4% had ever-tested for HIV and 16.9% tested in the previous 12 months. YMSM were more likely to have ever-tested for HIV if they talked with a parent/guardian about how to prevent HIV/AIDS [adjusted prevalence ratio (aPR) = 1.48; 95% confidence interval (CI): 1.07 to 2.06], talked with a health care provider about how HIV/AIDs is transmitted (aPR = 1.64; 95% CI: 1.13 to 2.38), sexually transmitted diseases (aPR = 1.49; 95% CI: 1.02 to 2.19), condom use (aPR = 1.61; 95% CI: 1.13 to 2.30), and the importance of HIV testing (aPR = 1.83; 95% CI: 1.22 to 2.73).

Conclusions:
Tailored sex education by parent(s) and health care providers related to HIV/AIDS seems to significantly increase the likelihood of HIV testing among YMSM.
Torticollis Caused by Nontraumatic Craniovertebral Junction Abnormalities
Authors: Park Sunghoon , Woo Ji-Eun , Kim Sanghyun , Yim Shin-Young 
Published: June 2018

Abstract
Torticollis could be the only symptom and sign of craniovertebral junction (CVJ) abnormality. It could be difficult to identify CVJ abnormality as a cause of torticollis due to their rarity, especially for the subjects with torticollis caused by nontraumatic CVJ abnormalities. There has been no report to focus on nontraumatic CVJ abnormalities as a cause of torticollis. The objective of this study was to report 27 patients of torticollis caused by nontraumatic CVJ abnormalities, with the aim of helping clinicians to identify nontraumatic CVJ abnormalities as a cause of torticollis. This is a retrospective cohort study including 27 subjects who had torticollis caused by nontraumatic CVJ abnormalities. The CVJ was examined in terms of atlanto-occipital angle, atlanto-axial angle, and lateral and anterior atlanto-dens intervals for the evaluation of occipital condylar hypoplasia, rotation of atlanto-axial joint, and lateral and anterior shift of the dens, respectively. Abnormalities of the lower cervical or thoracic spine were also evaluated. Occipital condylar hypoplasia, rotation of atlanto-axial joint, and lateral shift of the dens were the most common CVJ abnormalities. The 18.5% of the subjects had concurrent anomalies of lower cervical or thoracic vertebrae along with CVJ abnormalities. Each subject had 2.22 ± 1.10 types of CVJ abnormalities on average. In conclusion, comprehensive evaluation of CVJ abnormalities is recommended for differential diagnosis of subjects with unexplained torticollis. Once CVJ abnormalities are identified, concurrent abnormalities of other vertebrae need to be evaluated.
Influence of activation pattern estimates and statistical significance tests in fMRI decoding analysis
Authors: Arco Juan E. , González-García Carlos , Díaz-Gutiérrez Paloma , Ramírez Javier , Ruz María 
Published: June 2018

AbstractThe use of Multi-Voxel Pattern Analysis (MVPA) has increased considerably in recent functional magnetic resonance imaging studies. A crucial step consists in the choice of methods for the estimation of responses and their statistical significance. However, a systematic comparison of these and their adequacy to predominant experimental design is missing.In the current study, we compared three pattern estimation methods: Least-Squares Unitary (LSU), based on run-wise estimation, Least-Squares All (LSA) and Least-Squares Separate (LSS), which rely on trial-wise estimation. We compared the efficiency of these methods in an experiment where sustained activity had to be isolated from zero-duration events as well as in a block-design approach and in an event-related design. We evaluated the sensitivity of the t-test in comparison with two non-parametric methods based on permutation testing: one proposed in Stelzer et al. (2013), equivalent to performing a permutation in each voxel separately and the Threshold-Free Cluster Enhancement (Smith and Nichols, 2009).LSS resulted the most accurate approach to address the large overlap of signal among close events in the event-related designs. We found a larger sensitivity of Stelzer’s method in all settings, especially in the event-related designs, where voxels close to surpass the statistical threshold with the other approaches were now marked as informative regions.Our results provide evidence that LSS is the most accurate approach for unmixing events with different duration and large overlap of signal, consistent with previous studies showing better handling of collinearity in LSS. Moreover, Stelzer’s potentiates this better estimation with its larger sensitivity.
An unexpectedly effective Monte Carlo technique for the RNA inverse folding problem
Authors: Portela Fernando 
Published: June 2018

AbstractSolving the RNA inverse folding problem, also known as the RNA design problem, is critical to advance several scientific fields like bioengineering, yet existing approaches have had limited success. The problem has several features that resist traditional computational techniques, such as its exponential complexity and the chaotic behavior of its cost function. Although some state-of-the-art AI approaches have reported promising results, all existing computational methods substantially underperform expert human designers. I combine a different technique, Nested Monte Carlo Search (NMCS), with domain-specific knowledge to create an algorithm that outperforms all prior published methods by wide margins and solves 95 of the 100 puzzles listed in a recently proposed RNA solving difficulty benchmark.
Quantification of nuclear protein dynamics reveals chromatin remodeling during acute protein degradation
Authors: Federation Alexander J. , Nandakumar Vivek , Wang Hao , Searle Brian C. , Pino Lindsay K. , Merrihew Gennifer , Ting Ying S. , Howard Nicholas , Kutyavin Tanya , MacCoss Michael J. , Stamatoyannopoulos John A. 
Published: June 2018

AbstractSequencing-based technologies cannot measure post-transcriptional dynamics of the nuclear proteome, but unbiased mass-spectrometry measurements of chromatin-associated proteins remain difficult. In this work, we have combined facile nuclear sub-fractionation approaches with data-independent acquisition mass spectrometry to improve detection and quantification of nuclear proteins in human cells and tissues. Nuclei are isolated and subjected to a series of extraction conditions that enrich for nucleoplasm, euchromatin, heterochromatin and nuclear-membrane associated proteins. Using this approach, we can measure peptides from over 70% of the expressed nuclear proteome. As we are physically separating chromatin compartments prior to analysis, proteins can be assigned into functional chromatin environments to illuminate systems-wide nuclear protein dynamics. The integrity of nuclear sub-compartments were validated with immunofluorescence, which confirms the presence of key markers during chromatin extraction. We then apply this method to study the nuclear proteome-wide response to pharmacological degradation of the BET bromodomain proteins. BET degradation leads to widespread changes in chromatin composition, and we discover global HDAC1/2-mediated remodeling of chromatin previously bound by BET bromodomains. In summary, we have developed a technology for reproducible, comprehensive characterization of the nuclear proteome to observe the systems-wide nuclear protein dynamics.
Transfer learning with deep convolutional neural networks for classifying cellular morphological changes
Authors: Kensert Alexander , Harrison Philip J , Spjuth Ola 
Published: June 2018

AbstractQuantification and identification of cellular phenotypes from high content microscopy images have proven to be very useful for understanding biological activity in response to different drug treatments. The traditional approach has been to use classical image analysis to quantify changes in cell morphology, which requires several non-trivial and independent analysis steps. Recently convolutional neural networks have emerged as a compelling alternative, offering good predictive performance and the possibility to replace traditional workflows with a single network architecture. In this study we applied the pre-trained deep convolutional neural networks ResNet50, InceptionV3 and InceptionResnetV2 to predict cell mechanisms of action in response to chemical perturbations for two cell profiling datasets from the Broad Bioimage Benchmark Collection. These networks were pre-trained on ImageNet enabling much quicker model training. We obtain higher predictive accuracy than previously reported, between 95 and 97% based on “leave-one-compound-out” cross-validation. The ability to quickly and accurately distinguish between different cell morphologies from a scarce amount of labelled data illustrates the combined benefit of transfer learning and deep convolutional neural networks for interrogating cell-based images.
The radial expression of dorsal-ventral patterning genes in placozoans,Trichoplax adhaerens,argues for an oral-aboral axis
Authors: DuBuc Timothy Q. , Bobkov Yuriy , Ryan Joseph , Martindale Mark Q. 
Published: June 2018

AbstractThe placozoans are a morphologically simplistic group of marine animals found globally in tropical and subtropical environments. They consist of a single named species,Trichoplax adhaerensand have roughly six morphologically distinct cell types. With a sequenced genome, a limited number of cell-types and a simple flattened morphology,Trichoplaxis an ideal model organism to understand cellular dynamics and tissue patterning in the first animals. Using new approaches for identification of gene expression patterns this research looks at the relationship of Chordin/TgfB signaling and the axial patterning system of Placozoa. Our results suggest that placozoans have an oral-aboral axis similar to cnidarians and that the parahoxozoan ancestor (common ancestor of Placozoa and Cnidaria) was likely radially symmetric.
Holistic optimization of an RNA-seq workflow for multi-threaded environments
Authors: Hung Ling-Hong , Lloyd Wes , Agumbe Sridhar Radhika , Athmalingam Ravishankar Saranya Devi , Xiong Yuguang , Sobie Eric , Yeung Ka Yee 
Published: June 2018

AbstractSummaryFor many next-generation sequencing pipelines, the most computationally intensive step is the alignment of reads to a reference sequence. As a result, alignment software such as the Burrows-Wheeler Aligner (BWA) is optimized for speed and and is often executed in parallel on the cloud. However, there are other less demanding steps that can also be optimized and significantly increase the speed especially when using many threads. We demonstrate this using a Unique-molecular-identifier (UMI) RNA sequencing pipeline consisting of 3 steps: split, align, and merge. Optimization of all three steps yields a 40% increase in speed when executed using a single thread. However, when executed using 16 threads, we observe a 4-fold improvement over the original parallel imple-mentation and more than an 8-fold improvement over the original single-threaded implementation. In contrast, optimizing only the alignment step results in just a 13% improvement over the original parallel workflow using 16 threads.
Stress-responsive and metabolic gene regulation are altered in low S-adenosylmethionine
Authors: Ding Wei , Higgins Daniel P , Yadav Dilip K. , Pukklia-Worley Read , Walker Amy K 
Published: June 2018

AbstractS-adenosylmethionine (SAM) is the methyl donor that modifies proteins such as histones, nucleic acids and produces phosphatidylcholine. Thus variations in SAM levels could affect processes from lipogenesis to epigenetic gene regulation. SAM is hypothesized to link metabolism and chromatin modification, however, its role in acute gene regulation is poorly understood. We recently found that Caenorhabditis elegans with reduced SAM had deficiencies in bacterial-induced H3K4 trimethylation at selected pathogen-response genes, decreasing their expression and limiting survival on the pathogen Pseudomonas aeruginosa. This led us to the hypothesis that SAM may be generally required stress-responsive transcription. Here we show that C. elegans with low SAM fail to activate genome-wide transcriptional programs when exposed to bacterial or xenotoxic stress. However, heat shock responses were unaffected. We also investigated the role of two H3K4 methyltransferases that use SAM, set-2/SET1, and set-16/MLL and found that set-2/SET1 has a specific requirement in bacterial stress responses, whereas set-16/MLL was required for survival in all three stresses. These results define a role for SAM and H3K4 methyltransferases in the acute genome-wide remodeling of gene expression in response to stress. Finally, we find that the ability to modify metabolic gene expression correlates with enhanced survival in stress conditions.
Scalable methods for analyzing and visualizing phylogenetic placement of metagenomic samples
Authors: Czech Lucas , Stamatakis Alexandros 
Published: June 2018

1AbstractThe exponential decrease in molecular sequencing cost generates unprecedented amounts of data. Hence, scalable methods to analyze these data are required. Phylogenetic (or Evolutionary) Placement methods identify the evolutionary provenance of anonymous sequences with respect to a given reference phylogeny. This increasingly popular method is deployed for scrutinizing metagenomic samples from environments such as water, soil, or the human gut.Here, we present novel and, more importantly, highly scalable methods for analyzing phylogenetic placements of metagenomic samples. More specifically, we introduce methods for (a) visualizing differences between samples and their correlation with associated meta-data on the reference phylogeny, (b) clustering similar samples using a variant of the fc-means method, and (c) finding phylogenetic factors using an adaptation of the Phylofactorization method. These methods enable to interpret metagenomic data in a phylogenetic context, to find patterns in the data, and to identify branches of the phylogeny that are driving these patterns.To demonstrate the scalability and utility of our methods, as well as to provide exemplary interpretations of our methods, we applied them to 3 publicly available datasets comprising 9782 samples with a total of approximately 168 million sequences. The results indicate that new biological insights can be attained via our methods.
Haplotype assembly of autotetraploid potato using integer linear programming
Authors: Siragusa Enrico , Finkers Richard , Parida Laxmi 
Published: June 2018

AbstractHaplotype assembly of polyploids is an open issue in plant genomics. Recent experimental studies on highly heterozygous autotetraploid potato have shown that available methods are not delivering satisfying results in practice. We propose an optimal method to assemble haplotypes of highly heterozygous polyploids from Illumina short sequencing reads. Our method is based on a generalization of the existing minimum fragment removal (MFR) model to the polyploid case and on new integer linear programs (ILPs) to reconstruct optimal haplotypes. We validate our methods experimentally by means of a combined evaluation on simulated and real data based on 83 previously sequenced autotetraploid potato cultivars. Results on simulated data show that our methods produce highly accurate haplotype assemblies, while results on real data confirm a sensible improvement over the state of the art. Binaries for Linux are available at: http://github.com/ComputationalGenomics/HaplotypeAssembler.
A new method for detecting autocorrelation of evolutionary rates in large phylogenies
Authors: Tao Qiqing , Tamura Koichiro , Battistuzzi Fabia , Kumar Sudhir 
Published: June 2018

AbstractNew species arise from pre-existing species and inherit similar genomes and environments. This predicts greater similarity of mutation rates and the tempo of molecular evolution between direct ancestors and descendants, resulting in autocorrelation of evolutionary rates within lineages in the tree of life. Surprisingly, molecular sequence data have not confirmed this expectation, possibly because available methods lack power to detect autocorrelated rates. Here we present a machine learning method to detect the presence evolutionary rate autocorrelation in large phylogenies. The new method is computationally efficient and performs better than the available state-of-the-art methods. Application of the new method reveals extensive rate autocorrelation in DNA and amino acid sequence evolution of mammals, birds, insects, metazoans, plants, fungi, and prokaryotes. Therefore, rate autocorrelation is a common phenomenon throughout the tree of life. These findings suggest concordance between molecular and non-molecular evolutionary patterns and will foster unbiased and precise dating of the tree of life.
Computation of history-dependent mechanical damage of axonal fiber tracts in the brain: towards tracking sub-concussive and occupational damage to the brain
Authors: Gerber Jesse I. , Garimella Harsha T. , Kraft Reuben H. 
Published: June 2018

ABSTRACTFinite element models are frequently used to simulate traumatic brain injuries. However, current models are unable to capture the progressive damage caused by repeated head trauma. In this work, we propose a method for computing the history-dependent mechanical damage of axonal fiber bundle tracts in the brain. Through the introduction of multiple damage models, we provide the ability to link consecutive head impact simulations, so that potential injury to the brain can be tracked over time. In addition, internal damage variables are used to degrade the mechanical response of each axonal fiber bundle element. As a result, the stiffness of the aggregate tissue decreases as damage evolves. To counteract this degenerative process, we have also introduced a preliminary healing model that reverses the accumulated damage, based on a user-specified healing duration. Using two detailed examples, we demonstrate that damage produces a significant decrease in fiber stress, which ultimately propagates to the tissue level and produces a measurable decrease in overall stiffness. These results suggest that damage modeling has the potential to enhance current brain simulation techniques and lead to new insights, especially in the study of repetitive head injuries.
Local-community network automata modelling based on length-three-paths for prediction of complex network structures in protein interactomes, food webs and more
Authors: Muscoloni Alessandro , Abdelhamid Ilyes , Cannistraci Carlo Vittorio 
Published: June 2018

AbstractFrom nests to nets intricate wiring diagrams surround the birth and the death of life. Here we show that the same rule of complex network self-organization is valid across different physical scales and allows to predict protein interactions, food web trophic relations and world trade network transitions. This rule, which we named CH2-L3, is a network automaton that is based on paths of length-three and that maximizes internal links in local communities and minimizes external ones, according to a mechanistic model essentially driven by topological neighbourhood information.
A Combined Numerical and Experimental Investigation of Localized Electroporation-based Transfection and Sampling
Authors: Mukherjee Prithvijit , Nathamgari S. Shiva P. , Kessler John A. , Espinosa Horacio D. 
Published: June 2018

AbstractLocalized electroporation has evolved as an effective technology for the delivery of foreign molecules into adherent cells, and more recently, for the sampling of cytosolic content from a small population of cells. Unlike bulk electroporation, where the electric field is poorly controlled, localized electroporation benefits from the spatial localization of the electric field on a small areal fraction of the cell membrane, resulting in efficient molecular transport and high cell-viability. Although there have been numerous experimental reports, a mechanistic understanding of the different parameters involved in localized electroporation is lacking. In this work, we developed a multiphysics model that a) predicts the electro-pore distribution in response to the local transmembrane potential and b) calculates the molecular transport into and out of the cell based on the predicted pore-sizes. Using the model, we identify that cell membrane tension plays a crucial role in enhancing both the amount and the uniformity of molecular transport, particularly for large proteins and plasmids. We qualitatively validate the model predictions by delivering large molecules (fluorescent-tagged bovine serum albumin and mCherry encoding plasmid) and by sampling an exogeneous protein (tdTomato) in an engineered cell line. The findings presented here should inform the future design of microfluidic devices for localized electroporation based sampling, eventually paving the way for temporal, single-cell analysis.