bluuebunny/crossref_metadata_2025_split huggingface dataset:
A LDA-based approach to promoting ranking diversity for genomics information retrieval
Authors: Chen Yan , Yin Xiaoshi , Li Zhoujun , Hu Xiaohua , Huang Jimmy Xiangji 
Published: December 2019

Abstract

Background
In the biomedical domain, there are immense data and tremendous increase of genomics and biomedical relevant publications. The wealth of information has led to an increasing amount of interest in and need for applying information retrieval techniques to access the scientific literature in genomics and related biomedical disciplines. In many cases, the desired information of a query asked by biologists is a list of a certain type of entities covering different aspects that are related to the question, such as cells, genes, diseases, proteins, mutations, etc. Hence, it is important of a biomedical IR system to be able to provide relevant and diverse answers to fulfill biologists' information needs. However traditional IR model only concerns with the relevance between retrieved documents and user query, but does not take redundancy between retrieved documents into account. This will lead to high redundancy and low diversity in the retrieval ranked lists.

Results
In this paper, we propose an approach which employs a topic generative model called Latent Dirichlet Allocation (LDA) to promoting ranking diversity for biomedical information retrieval. Different from other approaches or models which consider aspects on word level, our approach assumes that aspects should be identified by the topics of retrieved documents. We present LDA model to discover topic distribution of retrieval passages and word distribution of each topic dimension, and then re-rank retrieval results with topic distribution similarity between passages based on N-size slide window. We perform our approach on TREC 2007 Genomics collection and two distinctive IR baseline runs, which can achieve 8% improvement over the highest Aspect MAP reported in TREC 2007 Genomics track.

Conclusions
The proposed method is the first study of adopting topic model to genomics information retrieval, and demonstrates its effectiveness in promoting ranking diversity as well as in improving relevance of ranked lists of genomics search. Moreover, we proposes a distance measure to quantify how much a passage can increase topical diversity by considering both topical importance and topical coefficient by LDA, and the distance measure is a modified Euclidean distance.
A UML profile for the OBO relation ontology
Authors: Guardia Gabriela DA , Vêncio Ricardo ZN , de Farias Cléver RG 
Published: December 2019

Abstract

Background
Ontologies have increasingly been used in the biomedical domain, which has prompted the emergence of different initiatives to facilitate their development and integration. The Open Biological and Biomedical Ontologies (OBO) Foundry consortium provides a repository of life-science ontologies, which are developed according to a set of shared principles. This consortium has developed an ontology called OBO Relation Ontology aiming at standardizing the different types of biological entity classes and associated relationships. Since ontologies are primarily intended to be used by humans, the use of graphical notations for ontology development facilitates the capture, comprehension and communication of knowledge between its users. However, OBO Foundry ontologies are captured and represented basically using text-based notations. The Unified Modeling Language (UML) provides a standard and widely-used graphical notation for modeling computer systems. UML provides a well-defined set of modeling elements, which can be extended using a built-in extension mechanism named Profile. Thus, this work aims at developing a UML profile for the OBO Relation Ontology to provide a domain-specific set of modeling elements that can be used to create standard UML-based ontologies in the biomedical domain.

Results
We have studied the OBO Relation Ontology, the UML metamodel and the UML profiling mechanism. Based on these studies, we have proposed an extension to the UML metamodel in conformance with the OBO Relation Ontology and we have defined a profile that implements the extended metamodel. Finally, we have applied the proposed UML profile in the development of a number of fragments from different ontologies. Particularly, we have considered the Gene Ontology (GO), the PRotein Ontology (PRO) and the Xenopus Anatomy and Development Ontology (XAO).

Conclusions
The use of an established and well-known graphical language in the development of biomedical ontologies provides a more intuitive form of capturing and representing knowledge than using only text-based notations. The use of the profile requires the domain expert to reason about the underlying semantics of the concepts and relationships being modeled, which helps preventing the introduction of inconsistencies in an ontology under development and facilitates the identification and correction of errors in an already defined ontology.
Efficient calculation of steady state probability distribution for stochastic biochemical reaction network
Authors: Karim Shahriar , Buzzard Gregery T , Umulis David M 
Published: December 2019

Abstract
The Steady State (SS) probability distribution is an important quantity needed to characterize the steady state behavior of many stochastic biochemical networks. In this paper, we propose an efficient and accurate approach to calculating an approximate SS probability distribution from solution of the Chemical Master Equation (CME) under the assumption of the existence of a unique deterministic SS of the system. To find the approximate solution to the CME, a truncated state-space representation is used to reduce the state-space of the system and translate it to a finite dimension. The subsequent ill-posed eigenvalue problem of a linear system for the finite state-space can be converted to a well-posed system of linear equations and solved. The proposed strategy yields efficient and accurate estimation of noise in stochastic biochemical systems. To demonstrate the approach, we applied the method to characterize the noise behavior of a set of biochemical networks of ligand-receptor interactions for Bone Morphogenetic Protein (BMP) signaling. We found that recruitment of type II receptors during the receptor oligomerization by itself doesn't not tend to lower noise in receptor signaling, but regulation by a secreted co-factor may provide a substantial improvement in signaling relative to noise. The steady state probability approximation method shortened the time necessary to calculate the probability distributions compared to earlier approaches, such as Gillespie's Stochastic Simulation Algorithm (SSA) while maintaining high accuracy.
Species-level classification of the vaginal microbiome
Authors: Fettweis Jennifer M , Serrano Myrna G , Sheth Nihar U , Mayer Carly M , Glascock Abigail L , Brooks J Paul , Jefferson Kimberly K ,   Vaginal Microbiome Consortium (additional members), Buck Gregory A 
Published: December 2019

Abstract

Background
The application of next-generation sequencing to the study of the vaginal microbiome is revealing the spectrum of microbial communities that inhabit the human vagina. High-resolution identification of bacterial taxa, minimally to the species level, is necessary to fully understand the association of the vaginal microbiome with bacterial vaginosis, sexually transmitted infections, pregnancy complications, menopause, and other physiological and infectious conditions. However, most current taxonomic assignment strategies based on metagenomic 16S rDNA sequence analysis provide at best a genus-level resolution. While surveys of 16S rRNA gene sequences are common in microbiome studies, few well-curated, body-site-specific reference databases of 16S rRNA gene sequences are available, and no such resource is available for vaginal microbiome studies.

Results
We constructed the Vaginal 16S rDNA Reference Database, a comprehensive and non-redundant database of 16S rDNA reference sequences for bacterial taxa likely to be associated with vaginal health, and we developed STIRRUPS, a new method that employs the USEARCH algorithm with a curated reference database for rapid species-level classification of 16S rDNA partial sequences. The method was applied to two datasets of V1-V3 16S rDNA reads: one generated from a mock community containing DNA from six bacterial strains associated with vaginal health, and a second generated from over 1,000 mid-vaginal samples collected as part of the Vaginal Human Microbiome Project at Virginia Commonwealth University. In both datasets, STIRRUPS, used in conjunction with the Vaginal 16S rDNA Reference Database, classified more than 95% of processed reads to a species-level taxon using a 97% global identity threshold for assignment.

Conclusions
This database and method provide accurate species-level classifications of metagenomic 16S rDNA sequence reads that will be useful for analysis and comparison of microbiome profiles from vaginal samples. STIRRUPS can be used to classify 16S rDNA sequence reads from other ecological niches if an appropriate reference database of 16S rDNA sequences is available.
Accelerating read mapping with FastHASH
Authors: Xin Hongyi , Lee Donghyuk , Hormozdiari Farhad , Yedkar Samihan , Mutlu Onur , Alkan Can 
Published: December 2019

Abstract
With the introduction of next-generation sequencing (NGS) technologies, we are facing an exponential increase in the amount of genomic sequence data. The success of all medical and genetic applications of next-generation sequencing critically depends on the existence of computational techniques that can process and analyze the enormous amount of sequence data quickly and accurately. Unfortunately, the current read mapping algorithms have difficulties in coping with the massive amounts of data generated by NGS.
We propose a new algorithm, FastHASH, which drastically improves the performance of the seed-and-extend type hash table based read mapping algorithms, while maintaining the high sensitivity and comprehensiveness of such methods. FastHASH is a generic algorithm compatible with all seed-and-extend class read mapping algorithms. It introduces two main techniques, namely Adjacency Filtering, and Cheap K-mer Selection.
We implemented FastHASH and merged it into the codebase of the popular read mapping program, mrFAST. Depending on the edit distance cutoffs, we observed up to 19-fold speedup while still maintaining 100% sensitivity and high comprehensiveness.
Immunogenicity and cross-reactivity against Mycobacterium tuberculosis of proteoliposomes derived from Mycobacterium bovis BCG
Authors: Reyes Fátima , Tirado Yanely , Puig Alina , Borrero Reinier , Reyes Giselle , Fernández Sonsire , Pérez José Luis , Kadir Ramlah , Zayas Caridad , Norazmi Mohd Nor , Sarmiento María E , Acosta Armando 
Published: December 2019

Abstract
The only currently available vaccine against tuberculosis (TB) is Mycobacterium bovis Bacille Calmette-Guerin (BCG), which has inconsistent efficacy to protect against the disease in adults. M. tuberculosis (MTB) cell wall components have been implicated in the pathogenicity of TB and therefore have been a prime target for the identification and characterization of cell wall proteins with potential application in vaccine development. In this regard, proteoliposomes (PLs) derived from mycobacteria containing lipids and cell wall proteins could be potential vaccine candidates against TB. In the present study PLs derived from BCG were prepared. These homogeneous population of spherical microparticles was then immunized into Balb/c mice. Sera of immunized animals showed high IgG response and strong cross-reactivity against different MTB antigens.These results showed that BCG PLs could be potential vaccine candidates against TB.
Excision dynamics of Vibrio pathogenicity island-2 from Vibrio cholerae: role of a recombination directionality factor VefA
Authors: Almagro-Moreno Salvador , Napolitano Michael G , Boyd E Fidelma 
Published: December 2019

Abstract

Background

Vibrio Pathogenicity Island-2 (VPI-2) is a 57 kb region present in choleragenic V. cholerae isolates that is required for growth on sialic acid as a sole carbon source. V. cholerae non-O1/O139 pathogenic strains also contain VPI-2, which in addition to sialic acid catabolism genes also encodes a type 3 secretion system in these strains. VPI-2 integrates into chromosome 1 at a tRNA-serine site and encodes an integrase intV2 (VC1758) that belongs to the tyrosine recombinase family. IntV2 is required for VPI-2 excision from chromosome 1, which occurs at very low levels, and formation of a non-replicative circular intermediate.

Results
We determined the conditions and the factors that affect excision of VPI-2 in V. cholerae N16961. We demonstrate that excision from chromosome 1 is induced at low temperature and after sublethal UV-light irradiation treatment. In addition, after UV-light irradiation compared to untreated cells, cells showed increased expression of three genes, intV2 (VC1758) , and two putative recombination directionality factors (RDFs), vefA (VC1785) and vefB (VC1809) encoded within VPI-2. We demonstrate that along with IntV2, the RDF VefA is essential for excision. We constructed a knockout mutant of vefA in V. cholerae N16961, and found that no excision of VPI-2 occurred, indicating that a functional vefA gene is required for excision. Deletion of the second RDF encoded by vefB did not result in a loss of excision. Among Vibrio species in the genome database, we identified 27 putative RDFs within regions that also encoded IntV2 homologues. Within each species the RDFs and their cognate IntV2 proteins were associated with different island regions suggesting that this pairing is widespread.

Conclusions
We demonstrate that excision of VPI-2 is induced under some environmental stress conditions and we show for the first time that an RDF encoded within a pathogenicity island in V. cholerae is required for excision of the region.
CSF from Parkinson disease Patients Differentially Affects Cultured Microglia and Astrocytes
Authors: Schiess Mya C , Barnes Jennifer L , Ellmore Timothy M , Poindexter Brian J , Dinh Kha , Bick Roger J 
Published: December 2019

Abstract

Background
Excessive and abnormal accumulation of alpha-synuclein (α-synuclein) is a factor contributing to pathogenic cell death in Parkinson's disease. The purpose of this study, based on earlier observations of Parkinson's disease cerebrospinal fluid (PD-CSF) initiated cell death, was to determine the effects of CSF from PD patients on the functionally different microglia and astrocyte glial cell lines. Microglia cells from human glioblastoma and astrocytes from fetal brain tissue were cultured, grown to confluence, treated with fixed concentrations of PD-CSF, non-PD disease control CSF, or control no-CSF medium, then photographed and fluorescently probed for α-synuclein content by deconvolution fluorescence microscopy. Outcome measures included manually counted cell growth patterns from day 1-8; α-synuclein density and distribution by antibody tagged 3D model stacked deconvoluted fluorescent imaging.

Results
After PD-CSF treatment, microglia growth was reduced extensively, and a non-confluent pattern with morphological changes developed, that was not evident in disease control CSF and no-CSF treated cultures. Astrocyte growth rates were similarly reduced by exposure to PD-CSF, but morphological changes were not consistently noted. PD-CSF treated microglia showed a significant increase in α-synuclein content by day 4 compared to other treatments (p ≤ 0.02). In microglia only, α-synuclein aggregated and redistributed to peri-nuclear locations.

Conclusions
Cultured microglia and astrocytes are differentially affected by PD-CSF exposure compared to non-PD-CSF controls. PD-CSF dramatically impacts microglia cell growth, morphology, and α-synuclein deposition compared to astrocytes, supporting the hypothesis of cell specific susceptibility to PD-CSF toxicity.
Comparing CenteringPregnancy® to standard prenatal care plus prenatal education
Authors: Benediktsson Ingunn , McDonald Sheila W , Vekved Monica , McNeil Deborah A , Dolan Siobhan M , Tough Suzanne C 
Published: December 2019

BackgroundThere is significant evidence to support the importance of prenatal care in preventing adverse outcomes such as preterm birth and low infant birth weight. Previous studies have indicated that the benefits of prenatal care are not evenly distributed throughout the social strata. In addition, emerging evidence suggests that among particular populations, rates of preterm birth are unchanged or increasing. This suggests that an alternate care model is necessary, one that seeks to addresses some of the myriad of social factors that also contribute to adverse birth outcomes. In previous studies, the group prenatal care model CenteringPregnancy® had been shown to reduce adverse birth outcomes, but to date, no comparison had been made with a model that included prenatal education. This study sought to investigate whether any significant difference remained within the comparison groups when both models accounted for social factors.MethodsThis analysis was based on survey data collected from a prospective cohort of pregnant women through the All Our Babies Study in Calgary, Alberta.ResultsAt baseline, there were significant differences between the comparison groups in their psychosocial health, with the women in the CenteringPregnancy® group scoring higher levels of depressive symptoms, stress and anxiety. At four months postpartum, the differences between the groups were no longer significant. Conclusions: These results suggest that CenteringPregnancy® can recruit and retain a demographically vulnerable group of women with a constellation of risk factors for poor pregnancy and birth outcomes, including poverty, language barriers and poor mental health. Post program, the rates of stress, anxiety and depression were similar to other women with more social and financial advantage. These findings suggest that CenteringPregnancy® may be a community based care strategy that contributes to improved mental health, knowledge, and behaviours to optimize outcomes for mothers and children.
Efficient protein structure search using indexing methods
Authors: Kim Sungchul , Sael Lee , Yu Hwanjo 
Published: December 2019

Abstract
Understanding functions of proteins is one of the most important challenges in many studies of biological processes. The function of a protein can be predicted by analyzing the functions of structurally similar proteins, thus finding structurally similar proteins accurately and efficiently from a large set of proteins is crucial. A protein structure can be represented as a vector by 3D-Zernike Descriptor (3DZD) which compactly represents the surface shape of the protein tertiary structure. This simplified representation accelerates the searching process. However, computing the similarity of two protein structures is still computationally expensive, thus it is hard to efficiently process many simultaneous requests of structurally similar protein search. This paper proposes indexing techniques which substantially reduce the search time to find structurally similar proteins. In particular, we first exploit two indexing techniques, i.e., iDistance and iKernel, on the 3DZDs. After that, we extend the techniques to further improve the search speed for protein structures. The extended indexing techniques build and utilize an reduced index constructed from the first few attributes of 3DZDs of protein structures. To retrieve top-k similar structures, top-10 × k similar structures are first found using the reduced index, and top-k structures are selected among them. We also modify the indexing techniques to support θ-based nearest neighbor search, which returns data points less than θ to the query point. The results show that both iDistance and iKernel significantly enhance the searching speed. In top-k nearest neighbor search, the searching time is reduced 69.6%, 77%, 77.4% and 87.9%, respectively using iDistance, iKernel, the extended iDistance, and the extended iKernel. In θ-based nearest neighbor serach, the searching time is reduced 80%, 81%, 95.6% and 95.6% using iDistance, iKernel, the extended iDistance, and the extended iKernel, respectively.
Single cell oils of the cold-adapted oleaginous yeast Rhodotorula glacialis DBVPG 4785
Authors: Amaretti Alberto , Raimondi Stefano , Sala Maurizio , Roncaglia Lucia , De Lucia Marzia , Leonardi Alan , Rossi Maddalena 
Published: December 2019

Abstract

Background
The production of microbial lipids has attracted considerable interest during the past decade since they can be successfully used to produce biodiesel by catalyzed transesterification with short chain alcohols. Certain yeast species, including several psychrophilic isolates, are oleaginous and accumulate lipids from 20 to 70% of biomass under appropriate cultivation conditions. Among them, Rhodotorula glacialis is a psychrophilic basidiomycetous species capable to accumulate intracellular lipids.

Results

Rhodotorula glacialis DBVPG 4785 is an oleaginous psychrophilic yeast isolated from a glacial environment. Despite its origin, the strain abundantly grew and accumulated lipids between -3 to 20°C. The temperature did not influence the yield coefficients of both biomass and lipids production, but had positive effect on the growth rate and thus on volumetric productivity of lipid. In glucose-based media, cellular multiplication occurred first, while the lipogenic phase followed whenever the culture was limited by a nutrient other than glucose. The extent of the carbon excess had positive effects on triacylglycerols production, that was maximum with 120 g L-1 glucose, in terms of lipid concentration (19 g L-1), lipid/biomass (68%) and lipid/glucose yields (16%). Both glucose concentration and growth temperature influenced the composition of fatty acids, whose unsaturation degree decreased when the temperature or glucose excess increased.

Conclusions
This study is the first proposed biotechnological application for Rhodotorula glacialis species, whose oleaginous biomass accumulates high amounts of lipids within a wide range of temperatures through appropriate cultivation C:N ratio. Although R. glacialis DBVPG 4785 is a cold adapted yeast, lipid production occurs over a broad range of temperatures and it can be considered an interesting microorganism for the production of single cell oils.