bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development and Prospective Validation of Tools to Accurately Identify Neurosurgical and Critical Care Events in Children With Traumatic Brain Injury*
Authors: Bennett Tellen D. , DeWitt Peter E. , Dixon Rebecca R. , Kartchner Cory , Sierra Yamila , Ladell Diane , Srivastava Rajendu , Riva-Cambrin Jay , Kempe Allison , Runyan Desmond K. , Keenan Heather T. , Dean J. Michael 
Published: March 2017

Objective:To develop and validate case definitions (computable phenotypes) to accurately identify neurosurgical and critical care events in children with traumatic brain injury.Design:Prospective observational cohort study, May 2013 to September 2015.Setting:Two large U.S. children’s hospitals with level 1 Pediatric Trauma Centers.Patients:One hundred seventy-four children less than 18 years old admitted to an ICU after traumatic brain injury.Measurements and Main Results:Prospective data were linked to database codes for each patient. The outcomes were prospectively identified acute traumatic brain injury, intracranial pressure monitor placement, craniotomy or craniectomy, vascular catheter placement, invasive mechanical ventilation, and new gastrostomy tube or tracheostomy placement. Candidate predictors were database codes present in administrative, billing, or trauma registry data. For each clinical event, we developed and validated penalized regression and Boolean classifiers (models to identify clinical events that take database codes as predictors). We externally validated the best model for each clinical event. The primary model performance measure was accuracy, the percent of test patients correctly classified. The cohort included 174 children who required ICU admission after traumatic brain injury. Simple Boolean classifiers were greater than or equal to 94% accurate for seven of nine clinical diagnoses and events. For central venous catheter placement, no classifier achieved 90% accuracy. Classifier accuracy was dependent on available data fields. Five of nine classifiers were acceptably accurate using only administrative data but three required trauma registry fields and two required billing data.Conclusions:In children with traumatic brain injury, computable phenotypes based on simple Boolean classifiers were highly accurate for most neurosurgical and critical care diagnoses and events. The computable phenotypes we developed and validated can be used in any observational study of children with traumatic brain injury and can reasonably be applied in studies of these interventions in other patient populations.
Altering lipid droplet homeostasis affectsCoxiella burnetiiintracellular growth
Authors: Mulye Minal , Zapata Brianne , Gilk Stacey D. 
Published: March 2017

ABSTRACTCoxiella burnetiiis an obligate intracellular bacterial pathogen and a causative agent of culture-negative endocarditis. WhileC. burnetiiinitially infects alveolar macrophages, it has also been found in lipid droplet (LD)-containing foamy macrophages in the cardiac valves of endocarditis patients. In addition, transcriptional studies ofC. burnetii-infected macrophages reported differential regulation of the LD coat protein-encoding gene perilipin 2(plin-2). To further investigate the relationship between LDs andC. burnetii, we compared LD numbers using fluorescence microscopy in mock-infected andC. burnetii-infected alveolar macrophages. On average,C. burnetii-infected macrophages contained twice as many LDs as mock-infected macrophages. LD numbers increased as early as 24 hours post-infection, an effect reversed by blockingC. burnetiiprotein synthesis. The observed LD accumulation was dependent on theC. burnetiiType 4B Secretion System (T4BSS), a major virulence factor that manipulates host cellular processes by secreting bacterial effector proteins into the host cell cytoplasm. To determine the importance of LDs duringC. burnetiiinfection, we manipulated LD homeostasis and assessedC. burnetiiintracellular growth. Surprisingly, blocking LD formation with the pharmacological inhibitors triacsin C or T863, or knocking out acyl-CoA transferase-1 (acat-1) in alveolar macrophages, increasedC. burnetiigrowth at least 2-fold. Conversely, preventing LD lipolysis by inhibiting adipose triglyceride lipase (ATGL) with atglistatin almost completely blocked bacterial growth, suggesting LD breakdown is essential forC. burnetii.Together these data suggest that maintenance of LD homeostasis, possibly via theC. burnetiiT4BSS, is critical for bacterial growth.IMPORTANCEHost neutral lipid storage organelles known as lipid droplets (LDs) serve as a source of energy, nutrients, and signaling lipids. LDs are associated with infection of the intracellular bacterial pathogenCoxiella burnetii, a significant cause of culture-negative endocarditis. WhileC. burnetiiwas found in LD-rich foamy macrophages in endocarditis patients, little is known about the host LD-C. burnetiirelationship. We demonstratedC. burnetiiType 4B Secretion System (T4BSS)-dependent LD accumulation in macrophages, suggesting a T4BSS-mediated regulation of host LD homeostasis. Further, manipulating LD homeostasis significantly affected bacterial growth, indicating LDs play an important role duringC. burnetiiinfection. AsC. burnetiiendocarditis has a 19% mortality rate even in treated patients, exploring the LD-C. burnetiiassociation might identify novel therapeutic targets.
Systematic identification of pleiotropic genes from genetic interactions
Authors: Koch Elizabeth N. , Costanzo Michael , Deshpande Raamesh , Andrews Brenda , Boone Charles , Myers Chad L. 
Published: March 2017

SummaryModular structures in biological networks are ubiquitous and well-described, yet this organization does not capture the complexity of genes individually influencing many modules. Pleiotropy, the phenomenon of a single genetic locus with multiple phenotypic effects, has previously been measured according to many definitions, which typically count phenotypes associated with genes. We take the perspective that, because genes work in complex and interconnected modules, pleiotropy can be treated as a network-derived characteristic. Here, we use the complete network of yeast genetic interactions (GI) to measure pleiotropy of nearly 2700 essential and nonessential genes. Our method uses frequent item set mining to discover GI modules, annotates them with high-level processes, and uses entropy to measure the functional spread of each gene’s set of containing modules. We classify genes whose modules indicate broad functional influence as having high pleiotropy, while genes with focused functional influence have low pleiotropy. These pleiotropy classes differed in a number of ways: high-pleiotropy genes have comparatively higher expression variance, higher protein abundance, more domains, and higher copy number, while low pleiotropy genes are more likely to be in protein complexes and have many curated phenotypes. We discuss the implications of these results regarding the nature and evolution of pleiotropy.
HiCPlus: Resolution Enhancement of Hi-C interaction heatmap
Authors: Zhang Yan , An Lin , Hu Ming , Tang Jijun , Yue Feng 
Published: March 2017

AbstractMotivationThe Hi-C technology has become an efficient tool to measure the spatial organization of the genome. With the recent advance of 1Kb resolution Hi-C experiment, some of the essential regulatory features have been uncovered. However, most available Hi-C datasets are in coarse-resolution due to the extremely high cost for generating high-resolution data. Therefore, a computational method to maximum the usage of the current available Hi-C data is urgently desired.ResultsInspired by the super-resolution image technique, we develop a computational approach to impute the high-resolution Hi-C data from low-resolution Hi-C data using the deep convolutional neural network. We hypothesize that the Hi-C interaction heatmap contains the repeating features, and develop an end-to-end framework to map these features from low-resolution Hi-C heatmap to high-resolution Hi-C heatmap at the feature level. Our approach successfully reconstructs the high-resolution Hi-C interaction map from the low-resolution counterpart, which also proves that the Hi-C interaction matrix is a combination of the regional features. Besides, our approach is highly expandable, and we can also increase prediction accuracy by incorporating ChIA-PET data.AvailabilitySource code is publicly available athttps://github.com/zhangyan32/HiCPlusContactjtang@cse.sc.edu,fyue@hmc.psu.edu
Comparative genomics of the tardigrades Hypsibius dujardini and Ramazzottius varieornatus
Authors: Yoshida Yuki , Koutsovoulos Georgios , Laetsch Dominik R. , Stevens Lewis , Kumar Sujai , Horikawa Daiki D. , Ishino Kyoko , Komine Shiori , Kunieda Takekazu , Tomita Masaru , Blaxter Mark , Arakawa Kazuharu 
Published: March 2017

ABSTRACTTardigrada, a phylum of meiofaunal organisms, have been at the center of discussions of the evolution of Metazoa, the biology of survival in extreme environments, and the role of horizontal gene transfer in animal evolution. Tardigrada are placed as sisters to Arthropoda and Onychophora (velvet worms) in the superphylum Ecdysozoa by morphological analyses, but many molecular phylogenies fail to recover this relationship. This tension between molecular and morphological understanding may be very revealing of the mode and patterns of evolution of major groups. Similar to bdelloid rotifers, nematodes and other animals of the water film, limno-terrestrial tardigrades display extreme cryptobiotic abilities, including anhydrobiosis and cryobiosis. These extremophile behaviors challenge understanding of normal, aqueous physiology: how does a multicellular organism avoid lethal cellular collapse in the absence of liquid water? Meiofaunal species have been reported to have elevated levels of HGT events, but how important this is in evolution, and in particular in the evolution of extremophile physiology, is unclear. To address these questions, we resequenced and reassembled the genome of Hypsibius dujardini, a limno-terrestrial tardigrade that can undergo anhydrobiosis only after extensive pre-exposure to drying conditions, and compared it to the genome of Ramazzottius varieornatus, a related species with tolerance to rapid desiccation. The two species had contrasting gene expression responses to anhydrobiosis, with major transcriptional change in H. dujardini but limited regulation in R. varieornatus. We identified few horizontally transferred genes, but some of these were shown to be involved in entry into anhydrobiosis. Whole-genome molecular phylogenies supported a Tardigrada+Nematoda relationship over Tardigrada+Arthropoda, but rare genomic changes tended to support Tardigrada+Arthropoda.
Improving prediction of compound function from chemical structure using chemical-genetic networks
Authors: Safizadeh Hamid , Simpkins Scott W. , Nelson Justin , Myers Chad L. 
Published: March 2017

ABSTRACTThe drug discovery process can be significantly improved through understanding how the structure of chemical compounds relates to their function. A common paradigm that has been used to filter and prioritize compounds is ligand-based virtual screening, where large libraries of compounds are queried for high structural similarity to a target molecule, with the assumption that structural similarity is predictive of similar biological activity. Although the chemical informatics community has already proposed a wide range of structure descriptors and similarity coefficients, a major challenge has been the lack of systematic and unbiased benchmarks for biological activity that covers a broad range of targets to definitively assess the performance of the alternative approaches.We leveraged a large set of chemical-genetic interaction data from the yeastSaccharomyces cerevisiaethat our labs have recently generated, covering more than 13,000 compounds from the RIKEN NPDepo and several NCI, NIH, and GlaxoSmithKline (GSK) compound collections. Supportive of the idea that chemical-genetic interaction data provide an unbiased proxy for biological functions, we found that many commonly used structural similarity measures were able to predict the compounds that exhibited similar chemical-genetic interaction profiles, although these measures did exhibit significant differences in performance. Using the chemical-genetic interaction profiles as a basis for our evaluation, we performed a systematic benchmarking of 10 different structure descriptors, each combined with 12 different similarity coefficients. We found that the All-Shortest Path (ASP) structure descriptor paired with the Braun-Blanquet similarity coefficient provided superior performance that was robust across several different compound collections.We further describe a machine learning approach that improves the ability of the ASP metric to capture biological activity. We used the ASP fingerprints as input for several supervised machine learning models and the chemical-genetic interaction profiles as the standard for learning. We found that the predictive power of the ASP fingerprints (as well as several other descriptors) could be substantially improved by using support vector machines. For example, on held-out data, we measured a 5-fold improvement in the recall of biologically similar compounds at a precision of 50% based upon the ASP fingerprints. Our results generally suggest that using high-dimensional chemical-genetic data as a basis for refining chemical structure descriptors can be a powerful approach to improving prediction of biological function from structure.
Evolution of ribosomal internal transcribed spacers in Deuterostomia
Authors: Dyomin Alexandr , Volodkina Valeria , Koshel Elena , Galkina Svetlana , Saifitdinova Alsu , Gaginskaya Elena 
Published: March 2017

AbstractSequences of ribosomal internal transcribed spacers (ITSs) are of great importance to molecular phylogenetics and DNA barcoding, but remain unstudied in some large taxa of Deuterostomia. We have analyzed completeITS1andITS2sequences in 62 species from 16 Deuterostomia classes, withITSssequences in 24 species from 11 classes initially obtained using unannotated contigs and raw read sequences. A general tendency for bothITSlength and GC-content increase from interior to superior Deuterostomia taxa, a uniform GC-content in bothITSswithin the same species, thymine content decrease in sense DNA sequences of bothITSsare shown. A possible role of GC-based gene conversion in DeuterostomiaITSsevolutionary changes is hypothesized. The first example of non-LTR retrotransposon insertion intoITSsequence in Deuterostomia is described in turtleGeochelone nigra.The roles of mobile genetic element insertions in the evolution ofITSsequences in some Sauropsida taxa are discussed as well.
Learning Complex Representations from Spatial Phase Statistics of Natural Scenes
Authors: MaBouDi HaDi , Subramani Krishna , Soltanian-Zadeh Hamid , Amari Shun-ichi , Shimazaki Hideaki 
Published: March 2017

AbstractNatural scenes contain higher-order statistical structures that can be encoded in their spatial phase information. Nevertheless, little progress has been made in modeling phase information of images, and understanding efficient representation of the image phases in the brain. In order to capture spatial phase structure under the efficient coding hypothesis, here we introduce a generative model of natural scenes by assuming independent source signals in a complex domain and non-uniform phase priors for the complex signals. Parameters of the proposed model are then estimated under the maximum-likelihood principle. This approach extends existing methods of independent component analysis for complex-valued signals to the one that utilizes phase information. Using simulated data, we demonstrate that the proposed model outperforms conventional models with a uniform phase prior in blind source separation of complex-valued signals. We then apply the proposed model to natural scenes in the Fourier domain. Real and imaginary parts of the learned complex features exhibit a pair of Gabor-like filters in quadratic phase structure with a similar shape. The proposed model significantly improved the goodness-of-the-fit from the model with a uniform phase prior, indicating that the structured spatial phases are important for removing redundancy in natural scenes. These results predict the presence of phase sensitive complex cells in the visual cortex.
The research and development of seamless knitted shapewears made of PTT filament
Authors: Yan Yuxiu , Feng Yanna , Jin Zimin , Tao Jianwei 
Published: March 2017

Purpose
The purpose of this paper is to improve the comfort and shaping function of seamless shapewear on the material and structure and develop new seamless shapewear products. The shaping figure effect will be verified as well.

Design/methodology/approach
The performance of the knitted fabrics made of Polytrimethylene terephthalate (PTT) filament was analyzed by orthogonal experiment and fuzzy mathematical methods analysis, in order to get the optimal conditions for the best performance. The new products were designed and made based on the results of the material research with the consideration of the aesthetic requirements. The shaping effect of seamless shapewears on local and global figure was tested by the methods of the combination of subjective and objective evaluation.

Findings
The sample which renders the optimal performance for shapewear is the one with PTT filament as face yarn, nylon core-spun yarn as ground yarn and 3+1 simulate rib knit structure. The material of face yarn, mixed proportion and structure can influence the shape retention, appearance and comfort of PTT fabric in various degrees. Three shapewears which were developed according to the results of material research have different shaping effect. And women with different figures put different satisfaction degrees on each shapewear’s shaping effect.

Practical implications
This paper provides scientific basis and reference for enterprise to design good tight seamless shapewear as well as for consumer to buy suitable products.

Originality/value
In the view of the problems of present shapewears, this paper completed the development of the shapewears and verified the shaping effect of them on women with different figures. The shapewears can be put into production directly.
A socioecological view toward an understanding of how to prevent overweight in children
Authors: Carrete Lorena , Arroyo Pilar , Villaseñor Roberto 
Published: March 2017

PurposeThis study aims to contribute to the understanding of how elements of the socioecological system shape individual behaviors. The problem of childhood overweight and obesity is analyzed as existing within a complex system of relationships at different levels by means of system dynamics (SD).Design/methodology/approachSecondary sources and primary information collected from an elementary school were used to analyze the influences of several social environmental factors on the dietary habits and physical activity of children. The major elements that influence these behaviors were identified via a socioecological framework (SEF), and the interrelationships among these elements were described using an SD model. Then, several scenarios corresponding to social marketing actions oriented toward modifying the influence of specific elements in the socioecological system were proposed to evaluate how effective they are at reducing the percentages of overweight and obesity among children.FindingsThe current research shows the existence of counteracting efforts at the micro (family) and macro (governmental policies) levels that need to be aligned to reduce rates of obesity and overweight.Practical implicationsThe systems perspective supports decision makers in defining social marketing strategies to modify alimentary behaviors based on the understanding of what elements of the SEF influence behavior and how they interrelate. To the authors’ knowledge, a detailed analysis of the influences of the socioecological environment has not been performed based on Latin American countries to seek solutions to the public health problems of overweight and obesity.Originality/valueThe application of SD enhances the value of the SEF suggested by Collinset al.(2010) for modeling individual behaviors. Moreover, the use of the systems approach for framing and understanding how the interrelationships of socioecological elements derive in synergic or antagonistic effects helps to predict the long-term effect of governmental actions and school interventions.
Life after death? Study of goods multiple lives practices
Authors: Ertz Myriam , Durif Fabien , Arcand Manon 
Published: March 2017

Purpose
Marketing scholars have devoted little attention to the study of practices which grant multiple lives to goods. However, these practices can considerably extend products lifecycles with far-reaching implications for traditional retailers and the economy. Accordingly, this paper aims to provide scales for perceived impact and motivations of goods multiple lives practices and to investigate the influence of impacts on motivations.

Design/methodology/approach
A qualitative phase (three discussion groups and 15 in-depth interviews) identified consumers’ motivations and perceived impacts of goods multiple lives practices. Two online surveys were then conducted on online panels, involving more than 2,200 consumers, to develop the measurement scales and test the structural model.

Findings
Results show that impacts measured only marginally influence economic motives but account significantly for a broad range of other motivations (ecological, protester and social contact motives).

Research limitations/implications
The study design is cross-sectional, therefore lacking causality. Replication studies could cross-validate the findings by means of experimental research.

Practical implications
The findings may prove of specific interest to marketers and organizations in the goods multiple lives sector seeking to harness consumer interest in these types of practices for reasons above and beyond lone economic incentives.

Originality/value
This study is innovative in two regards: it explores a relatively under-theorized field in marketing, namely, goods multiple lives practices; and it proposes a challenging theoretical perspective which supposes that consumers’ perceived impact of their practices plays a significant role in motivating them to engage in practices of the like.
Impact of point-of-purchase olfactory cues on purchase behavior
Authors: Kivioja Kaisa 
Published: March 2017

Purpose
This study aims to examine the impact of olfactory cues at the point of purchase on consumers’ purchase behavior in terms of sales.

Design/methodology/approach
The theory of semantic congruence and sensory marketing on consumer behavior is tested using data collected through an experiment and analyzed using quantitative methods.

Findings
The presence of an olfactory cue has a positive impact on purchase behavior, as measured by product and product-category sales. Results indicate that a more common, category-congruent scent is optimal, as opposed to product-congruent, differentiating scent, even for a single product.

Practical implications
The findings encourage retailers to implement scents at the point of purchase as a sales promotion tool. Targeting a product category, instead of a single product, would seem the most feasible target scope.

Originality/value
This paper studies sensory marketing and cue congruence in a real-life retail setting, measuring the impact in terms of sales, and not only in relation to purchase intentions or brand image. Addressing a precisely defined target that suits retailing, namely, a single product and product category, is also novel, contrasting with earlier studies focused on ambient scents in large environments.