bluuebunny/crossref_metadata_2025 huggingface dataset:
Ultrastructural Characteristics of Gallbladder Epithelial Inclusions Mimicking Cystoisospora
Authors: Gopinath Arun , Mubeen Aysha , Baskovich Brett , Ginn Amber , Shukri Amal , Menes Manual , Kenneth Keyler , Makary Raafat , Herrera Guillermo A , Masood Shahla , Alkhasawneh Ahmad
Published: July 2019

Objectives

There is recently reported increased prevalence of Isospora organisms in cholecystectomy specimens from immunocompetent patients, especially in acalculous cholecystectomies. We performed an ultrastructural and molecular evaluation of these specimens.

Methods

From 28 gallbladders with intraepithelial inclusions, two specimens with diffuse involvement of the gallbladder epithelium were analyzed by electron microscopy. Polymerase chain reaction was performed on five samples for the ITS2 region of C belli and eukaryotic 18S region. The 18S products were sequenced by next-generation sequencing.

Results

Electron microscopic analysis showed cytoplasmic condensations leading to vacuole formation. In contrast with true C belli, there were no identifiable organelles or organization. None of these cases showed amplified products other than human on molecular analysis.

Conclusions

Electron microscopic analysis demonstrates that the inclusions are condensed cytoplasmic material and not true organisms.
Metabolome-Wide Association Study of the Relationship Between Habitual Physical Activity and Plasma Metabolite Levels
Authors: Ding Ming , Zeleznik Oana A , Guasch-Ferre Marta , Hu Jie , Lasky-Su Jessica , Lee I-Min , Jackson Rebecca D , Shadyab Aladdin H , LaMonte Michael J , Clish Clary , Eliassen A Heather , Sacks Frank , Willett Walter C , Hu Frank B , Rexrode Kathryn M , Kraft Peter
Published: July 2019

We identified plasma metabolites associated with habitual physical activity among 5,197 US participants from the Nurses’ Health Study (NHS), Nurses’ Health Study II (NHS II), and the Health Professionals Follow-up Study (HPFS). Physical activity was assessed every 2–4 years via self-report questionnaires. Blood was collected in the NHS in 1989–1990, in NHS II during 1996–1999, and in the HPFS during 1993–1995. Metabolic profiling was conducted by liquid chromatography–mass spectrometry. Our study included 337 known metabolites, with 256 of them classified as lipids. We corrected for multiple testing by controlling the tail probability of the proportion of false positives (TPPFP) and accounted for correlated tests using bootstrapping. Physical activity was significantly associated with 20 metabolites after correction for multiple testing (TPPFP < 0.05), and positive associations were found for most of the metabolites, including 2 amino acids (citrulline and glycine), 4 cholesteryl esters (C18:2, C18:1, C16:0, C18:3), 8 phosphocholines (PCs) (C36:4 PC-A, C34:3 PC plasmalogen, C36:3 PC plasmalogen, C34:2 PC plasmalogen, C36:2 PC) and lysophosphatidylcholines (C18:2, C20:5, C18:1), and 3 phosphatidylethanolamines (PEs) (C38:3 PE plasmalogen) and lysophosphatidylethanolamines (C18:2, C18:1). We independently replicated the 20 metabolites among 2,305 women in the Women’s Health Initiative using 1993 data, and half of the metabolites were replicated. Our study may help identify biomarkers of physical activity and provide insight into biological mechanisms underlying the beneficial effect of being physically active on cardiometabolic health.
The costs and benefits of decentralization and centralization of ant colonies
Authors: Burns Dominic D R , Pitchford Jon W , Parr Catherine L , Franks Daniel W , Robinson Elva J H
Published: July 2019

A challenge faced by individuals and groups of many species is determining how resources and activities should be spatially distributed: centralized or decentralized. This distribution problem is hard to understand due to the many costs and benefits of each strategy in different settings. Ant colonies are faced by this problem and demonstrate two solutions: 1) centralizing resources in a single nest (monodomy) and 2) decentralizing by spreading resources across many nests (polydomy). Despite the possibilities for using this system to study the centralization/decentralization problem, the trade-offs associated with using either polydomy or monodomy are poorly understood due to a lack of empirical data and cohesive theory. Here, we present a dynamic network model of a population of ant nests which is based on observations of a facultatively polydomous ant species (Formica lugubris). We use the model to test several key hypotheses for costs and benefits of polydomy and monodomy and show that decentralization is advantageous when resource acquisition costs are high, nest size is limited, resources are clustered, and there is a risk of nest destruction, but centralization prevails when resource availability fluctuates and nest size is limited. Our model explains the phylogenetic and ecological diversity of polydomous ants, demonstrates several trade-offs of decentralization and centralization, and provides testable predictions for empirical work on ants and in other systems.
Flexible polyandry in female flies is an adaptive response to infertile males
Authors: Sutter Andreas , Travers Laura M , Oku Keiko , L. Delaney Kynan , J. Store Stefan , Price Tom A R , Wedell Nina
Published: July 2019

Infertility is common in nature despite its obvious cost to individual fitness. Rising global temperatures are predicted to decrease fertility, and male sterility is frequently used in attempts to regulate pest or disease vector populations. When males are infertile, females may mate with multiple males to ensure fertilization, and changes in female mating behavior in turn could intensify selection on male fertility. Fertility assurance is a potentially wide-spread explanation for polyandry, but whether and how it actually contributes to the evolution of polyandry is not clear. Moreover, whether a drop in male fertility would lead to a genetic increase in polyandry depends on whether females respond genetically or through behavioral plasticity to male infertility. Here, we experimentally manipulate male fertility through heat-exposure in Drosophila pseudoobscura, and test female discrimination against infertile males before and after mating. Using isogenic lines, we compare the roles of behaviorally plastic versus genetically fixed polyandry. We find that heat-exposed males are less active and attractive, and that females are more likely to remate after mating with these males. Remating rate increases with reduced reproductive output, indicating that females use current sperm storage threshold to make dynamic remating decisions. After remating with fertile males, females restore normal fecundity levels. Our results suggest that male infertility could explain the evolution of adaptively flexible polyandry, but is less likely to cause an increase in genetic polyandry.
Towards accurate high-throughput ligand affinity prediction by exploiting structural ensembles, docking metrics and ligand similarity
Authors: Schneider Melanie , Pons Jean-Luc , Bourguet William , Labesse Gilles
Published: July 2019

Motivation

Nowadays, virtual screening (VS) plays a major role in the process of drug development. Nonetheless, an accurate estimation of binding affinities, which is crucial at all stages, is not trivial and may require target-specific fine-tuning. Furthermore, drug design also requires improved predictions for putative secondary targets among which is Estrogen Receptor alpha (ERα).

Results

VS based on combinations of Structure-Based VS (SBVS) and Ligand-Based VS (LBVS) is gaining momentum to improve VS performances. In this study, we propose an integrated approach using ligand docking on multiple structural ensembles to reflect receptor flexibility. Then, we investigate the impact of the two different types of features (structure-based and ligand molecular descriptors) on affinity predictions using a random forest algorithm. We find that ligand-based features have lower predictive power (rP = 0.69, R2 = 0.47) than structure-based features (rP = 0.78, R2 = 0.60). Their combination maintains high accuracy (rP = 0.73, R2 = 0.50) on the internal test set, but it shows superior robustness on external datasets. Further improvement and extending the training dataset to include xenobiotics, leads to a novel high-throughput affinity prediction method for ERα ligands (rP = 0.85, R2 = 0.71). The presented prediction tool is provided to the community as a dedicated satellite of the @TOME server in which one can upload a ligand dataset in mol2 format and get ligand docked and affinity predicted.

Availability and implementation

http://edmon.cbs.cnrs.fr.

Supplementary information

Supplementary data are available at Bioinformatics online.
BioNorm: deep learning-based event normalization for the curation of reaction databases
Authors: Lou Peiliang , Jimeno Yepes Antonio , Zhang Zai , Zheng Qinghua , Zhang Xiangrong , Li Chen
Published: July 2019

Motivation

A biochemical reaction, bio-event, depicts the relationships between participating entities. Current text mining research has been focusing on identifying bio-events from scientific literature. However, rare efforts have been dedicated to normalize bio-events extracted from scientific literature with the entries in the curated reaction databases, which could disambiguate the events and further support interconnecting events into biologically meaningful and complete networks.

Results

In this paper, we propose BioNorm, a novel method of normalizing bio-events extracted from scientific literature to entries in the bio-molecular reaction database, e.g. IntAct. BioNorm considers event normalization as a paraphrase identification problem. It represents an entry as a natural language statement by combining multiple types of information contained in it. Then, it predicts the semantic similarity between the natural language statement and the statements mentioning events in scientific literature using a long short-term memory recurrent neural network (LSTM). An event will be normalized to the entry if the two statements are paraphrase. To the best of our knowledge, this is the first attempt of event normalization in the biomedical text mining. The experiments have been conducted using the molecular interaction data from IntAct. The results demonstrate that the method could achieve F-score of 0.87 in normalizing event-containing statements.

Availability and implementation

The source code is available at the gitlab repository https://gitlab.com/BioAI/leen and BioASQvec Plus is available on figshare https://figshare.com/s/45896c31d10c3f6d857a.
Haplotype-aware graph indexes
Authors: Sirén Jouni , Garrison Erik , Novak Adam M , Paten Benedict , Durbin Richard
Published: July 2019

Motivation

The variation graph toolkit (VG) represents genetic variation as a graph. Although each path in the graph is a potential haplotype, most paths are non-biological, unlikely recombinations of true haplotypes.

Results

We augment the VG model with haplotype information to identify which paths are more likely to exist in nature. For this purpose, we develop a scalable implementation of the graph extension of the positional Burrows–Wheeler transform. We demonstrate the scalability of the new implementation by building a whole-genome index of the 5008 haplotypes of the 1000 Genomes Project, and an index of all 108 070 Trans-Omics for Precision Medicine Freeze 5 chromosome 17 haplotypes. We also develop an algorithm for simplifying variation graphs for k-mer indexing without losing any k-mers in the haplotypes.

Availability and implementation

Our software is available at https://github.com/vgteam/vg, https://github.com/jltsiren/gbwt and https://github.com/jltsiren/gcsa2.

Supplementary information

Supplementary data are available at Bioinformatics online.
MetaBMF: a scalable binning algorithm for large-scale reference-free metagenomic studies
Authors: Ma Terry , Xiao Di , Xing Xin
Published: July 2019

Motivation

Metagenomics studies microbial genomes in an ecosystem such as the gastrointestinal tract of a human. Identification of novel microbial species and quantification of their distributional variations among different samples that are sequenced using next-generation-sequencing technology hold the key to the success of most metagenomic studies. To achieve these goals, we propose a simple yet powerful metagenomic binning method, MetaBMF. The method does not require prior knowledge of reference genomes and produces highly accurate results, even at a strain level. Thus, it can be broadly used to identify disease-related microbial organisms that are not well-studied.

Results

Mathematically, we count the number of mapped reads on each assembled genomic fragment cross different samples as our input matrix and propose a scalable stratified angle regression algorithm to factorize this count matrix into a product of a binary matrix and a nonnegative matrix. The binary matrix can be used to separate microbial species and the nonnegative matrix quantifies the species distributions in different samples. In simulation and empirical studies, we demonstrate that MetaBMF has a high binning accuracy. It can not only bin DNA fragments accurately at a species level but also at a strain level. As shown in our example, we can accurately identify the Shiga-toxigenic Escherichia coli O104: H4 strain which led to the 2011 German E.coli outbreak. Our efforts in these areas should lead to (i) fundamental advances in metagenomic binning, (ii) development and refinement of technology for the rapid identification and quantification of microbial distributions and (iii) finding of potential probiotics or reliable pathogenic bacterial strains.

Availability and implementation

The software is available at https://github.com/didi10384/MetaBMF.
DR-SIP: protocols for higher order structure modeling with distance restraints- and cyclic symmetry-imposed packing
Authors: Chan Justin , Zou Jinhao , Ortiz Christopher Llynard , Chang Chien Chi-Hong , Pan Rong-Long , Yang Lee-Wei
Published: July 2019

Motivation

Quaternary structure determination for transmembrane/soluble proteins requires a reliable computational protocol that leverages observed distance restraints and/or cyclic symmetry (Cn symmetry) found in most homo-oligomeric transmembrane proteins.

Results

We survey 118 X-ray crystallographically solved structures of homo-oligomeric transmembrane proteins (HoTPs) and find that ∼97% are Cn symmetric. Given the prevalence of Cn symmetric HoTPs and the benefits of incorporating geometry restraints in aiding quaternary structure determination, we introduce two new filters, the distance-restraints (DR) and the Symmetry-Imposed Packing (SIP) filters. SIP relies on a new method that can rebuild the closest ideal Cn symmetric complex from docking poses containing a homo-dimer without prior knowledge of the number (n) of monomers. Using only the geometrical filter, SIP, near-native poses of 7 HoTPs in their monomeric states can be correctly identified in the top-10 for 71% of all cases, or 29% among 31 HoTP structures obtained through homology modeling, while ZDOCK alone returns 14 and 3%, respectively. When the n is given, the optional n-mer filter is applied with SIP and returns the near-native poses for 76% of the test set within the top-10, outperforming M-ZDOCK’s 55% and Sam’s 47%. While applying only SIP to three HoTPs that comes with distance restraints, we found the near-native poses were ranked 1st, 1st and 10th among 54 000 possible decoys. The results are further improved to 1st, 1st and 3rd when both DR and SIP filters are used. By applying only DR, a soluble system with distance restraints is recovered at the 1st-ranked pose.

Availability and implementation

https://github.com/capslockwizard/drsip.

Supplementary information

Supplementary data are available at Bioinformatics online.
Efficient parameterization of large-scale dynamic models based on relative measurements
Authors: Schmiester Leonard , Schälte Yannik , Fröhlich Fabian , Hasenauer Jan , Weindl Daniel
Published: July 2019

Motivation

Mechanistic models of biochemical reaction networks facilitate the quantitative understanding of biological processes and the integration of heterogeneous datasets. However, some biological processes require the consideration of comprehensive reaction networks and therefore large-scale models. Parameter estimation for such models poses great challenges, in particular when the data are on a relative scale.

Results

Here, we propose a novel hierarchical approach combining (i) the efficient analytic evaluation of optimal scaling, offset and error model parameters with (ii) the scalable evaluation of objective function gradients using adjoint sensitivity analysis. We evaluate the properties of the methods by parameterizing a pan-cancer ordinary differential equation model (>1000 state variables, >4000 parameters) using relative protein, phosphoprotein and viability measurements. The hierarchical formulation improves optimizer performance considerably. Furthermore, we show that this approach allows estimating error model parameters with negligible computational overhead when no experimental estimates are available, providing an unbiased way to weight heterogeneous data. Overall, our hierarchical formulation is applicable to a wide range of models, and allows for the efficient parameterization of large-scale models based on heterogeneous relative measurements.

Availability and implementation

Supplementary code and data are available online at http://doi.org/10.5281/zenodo.3254429 and http://doi.org/10.5281/zenodo.3254441.

Supplementary information

Supplementary data are available at Bioinformatics online.
pourRNA—a time- and memory-efficient approach for the guided exploration of RNA energy landscapes
Authors: Entzian Gregor , Raden Martin
Published: July 2019

Motivation

The folding dynamics of ribonucleic acids (RNAs) are typically studied via coarse-grained models of the underlying energy landscape to face the exponential growths of the RNA secondary structure space. Still, studies of exact folding kinetics based on gradient basin abstractions are currently limited to short sequence lengths due to vast memory requirements. In order to compute exact transition rates between gradient basins, state-of-the-art approaches apply global flooding schemes that require to memorize the whole structure space at once. pourRNA tackles this problem via local flooding techniques where memorization is limited to the structure ensembles of individual gradient basins.

Results

Compared to the only available tool for exact gradient basin-based macro-state transition rates (namely barriers), pourRNA computes the same exact transition rates up to 10 times faster and requires two orders of magnitude less memory for sequences that are still computationally accessible for exhaustive enumeration. Parallelized computation as well as additional heuristics further speed up computations while still producing high-quality transition model approximations. The introduced heuristics enable a guided trade-off between model quality and required computational resources. We introduce and evaluate a macroscopic direct path heuristics to efficiently compute refolding energy barrier estimations for the co-transcriptionally trapped RNA sv11 of length 115 nt. Finally, we also show how pourRNA can be used to identify folding funnels and their respective energetically lowest minima.

Availability and implementation

pourRNA is freely available at https://github.com/ViennaRNA/pourRNA.

Supplementary information

Supplementary data are available at Bioinformatics online.
DISPOT: a simple knowledge-based protein domain interaction statistical potential
Authors: Narykov Oleksandr , Bogatov Dmytro , Korkin Dmitry
Published: July 2019

Motivation

The complexity of protein–protein interactions (PPIs) is further compounded by the fact that an average protein consists of two or more domains, structurally and evolutionary independent subunits. Experimental studies have demonstrated that an interaction between a pair of proteins is not carried out by all domains constituting each protein, but rather by a select subset. However, determining which domains from each protein mediate the corresponding PPI is a challenging task.

Results

Here, we present domain interaction statistical potential (DISPOT), a simple knowledge-based statistical potential that estimates the propensity of an interaction between a pair of protein domains, given their structural classification of protein (SCOP) family annotations. The statistical potential is derived based on the analysis of >352 000 structurally resolved PPIs obtained from DOMMINO, a comprehensive database of structurally resolved macromolecular interactions.

Availability and implementation

DISPOT is implemented in Python 2.7 and packaged as an open-source tool. DISPOT is implemented in two modes, basic and auto-extraction. The source code for both modes is available on GitHub: https://github.com/korkinlab/dispot and standalone docker images on DockerHub: https://hub.docker.com/r/korkinlab/dispot. The web server is freely available at http://dispot.korkinlab.org/.

Supplementary information

Supplementary data are available at Bioinformatics online.
P-value evaluation, variability index and biomarker categorization for adaptively weighted Fisher’s meta-analysis method in omics applications
Authors: Huo Zhiguang , Tang Shaowu , Park Yongseok , Tseng George
Published: July 2019

Motivation

Meta-analysis methods have been widely used to combine results from multiple clinical or genomic studies to increase statistical powers and ensure robust and accurate conclusions. The adaptively weighted Fisher’s method (AW-Fisher), initially developed for omics applications but applicable for general meta-analysis, is an effective approach to combine P-values from K independent studies and to provide better biological interpretability by characterizing which studies contribute to the meta-analysis. Currently, AW-Fisher suffers from the lack of fast P-value computation and variability estimate of AW weights. When the number of studies K is large, the 3K − 1 possible differential expression pattern categories generated by AW-Fisher can become intractable. In this paper, we develop an importance sampling scheme with spline interpolation to increase the accuracy and speed of the P-value calculation. We also apply bootstrapping to construct a variability index for the AW-Fisher weight estimator and a co-membership matrix to categorize (cluster) differentially expressed genes based on their meta-patterns for intuitive biological investigations.

Results

The superior performance of the proposed methods is shown in simulations as well as two real omics meta-analysis applications to demonstrate its insightful biological findings.

Availability and implementation

An R package AWFisher (calling C++) is available at Bioconductor and GitHub (https://github.com/Caleb-Huo/AWFisher), and all datasets and programing codes for this paper are available in the Supplementary Material.

Supplementary information

Supplementary data are available at Bioinformatics online.
Identifying small-effect genetic associations overlooked by the conventional fixed-effect model in a large-scale meta-analysis of coronary artery disease
Authors: Magosi Lerato E , Goel Anuj , Hopewell Jemma C , Farrall Martin
Published: July 2019

Motivation

Common small-effect genetic variants that contribute to human complex traits and disease are typically identified using traditional fixed-effect (FE) meta-analysis methods. However, the power to detect genetic associations under FE models deteriorates with increasing heterogeneity, so that some small-effect heterogeneous loci might go undetected. A modified random-effects meta-analysis approach (RE2) was previously developed that is more powerful than traditional fixed and random-effects methods at detecting small-effect heterogeneous genetic associations, the method was updated (RE2C) to identify small-effect heterogeneous variants overlooked by traditional fixed-effect meta-analysis. Here, we re-appraise a large-scale meta-analysis of coronary disease with RE2C to search for small-effect genetic signals potentially masked by heterogeneity in a FE meta-analysis.

Results

Our application of RE2C suggests a high sensitivity but low specificity of this approach for discovering small-effect heterogeneous genetic associations. We recommend that reports of small-effect heterogeneous loci discovered with RE2C are accompanied by forest plots and standardized predicted random-effects statistics to reveal the distribution of genetic effect estimates across component studies of meta-analyses, highlighting overly influential outlier studies with the potential to inflate genetic signals.

Availability and implementation

Scripts to calculate standardized predicted random-effects statistics and generate forest plots are available in the getspres R package entitled from https://magosil86.github.io/getspres/.

Supplementary information

Supplementary data are available at Bioinformatics online.
Homelessness in a Post-Soviet City: Weak Social Support and Institutional Alienation
Authors: Negură Petru
Published: July 2019

Research has shown that most homeless people suffer from weak support from family, relatives and friends. Based on a descriptive statistical analysis with biographical records of 810 subjects, and a thematic analysis of interviews with homeless people (N = 65), people at risk of homelessness (N = 5) and professionals (N = 20), the article explores the social support system of homeless people from Chisinau (Moldova). Only 18.6 per cent of all users of the Shelter for homeless in Chisinau were in a couple relationship (and only 5.6 per cent registered officially). For former detainees (23 per cent of the Shelter users) and care leavers (11 per cent), it is even more difficult to create a couple and to strengthen their social support network, as the institutions they come from did not foster their social support. As homelessness becomes chronic, people build social support networks with other homeless people. This social support helps homeless people to cope with stressful living conditions. The article suggests, in the case of Moldova, that social support relations with family, friends, acquaintances and other homeless people are affected negatively in the absence of policies and institutional measures targeted to encourage and strengthen such relationships.
The phylogeography of Vellozia auriculata (Velloziaceae) supports low zygotic gene flow and local population persistence in the campo rupestre, a Neotropical OCBIL
Authors: Fiorini Cecilia F , Miranda Marina Dutra , Silva-Pereira Viviane , Barbosa Ariane Raquel , Oliveira Ubirajara De , Kamino Luciana Hiromi Yoshino , Mota Nara Furtado De Oliveira , Viana Pedro Lage , Borba Eduardo Leite
Published: July 2019

The campo rupestre is a Neotropical azonal vegetation. Its disjoint distribution and the fact that it is an old climatic buffered infertile landscape (OCBIL) have been associated with the high diversity and endemism observed in this environment. Here, we tested whether a micro-endemic species from campo rupestre shows: (1) limited zygotic gene flow; (2) lower gametic than zygotic gene flow structure; (3) substrate-driven genetic structure and (4) no evidence of Pleistocene local extinction or recolonization. By sequencing intergenic plastid regions, phenotyping inter simple sequence repeats (ISSR) and modelling present and past species suitability distributions for Vellozia auriculata we conclude that (1) zygotic gene flow is limited; (2) gametic gene flow is recurrent, but limited by elevation and distance; (3) there is no support for genetic structure driven by substrate and (4) Pleistocene climatic changes did not restrict the species to refugia, with local persistence. As long-term gene flow restrictions may lead to differentiation and speciation, our data helps to corroborate that the campo rupestre is both a cradle (due to low zygotic gene flow, prolonged isolation and consequent differentiation) and a lineage museum (due to local survival during climate oscillations). We highlight two distinct evolutionarily significant units (ESU), providing information for better conservation practice.
Deep brain stimulation induced normalization of the human functional connectome in Parkinson’s disease
Authors: Horn Andreas , Wenzel Gregor , Irmen Friederike , Huebl Julius , Li Ningfei , Neumann Wolf-Julian , Krause Patricia , Bohner Georg , Scheel Michael , Kühn Andrea A
Published: July 2019

Deep brain stimulation has local effects on the target structure, but also global effects via distributed brain networks. Horn et al. show that modulating the activity of the subthalamic nucleus in patients with Parkinson’s disease normalizes signatures of widespread network connectivity towards those found in healthy controls.
Functional Integration of Neuronal Precursors in the Adult Murine Piriform Cortex
Authors: Benedetti Bruno , Dannehl Dominik , König Richard , Coviello Simona , Kreutzer Christina , Zaunmair Pia , Jakubecova Dominika , Weiger Thomas M , Aigner Ludwig , Nacher Juan , Engelhardt Maren , Couillard-Després Sébastien
Published: July 2019

The extent of functional maturation and integration of nonproliferative neuronal precursors, becoming neurons in the adult murine piriform cortex, is largely unexplored. We thus questioned whether precursors eventually become equivalent to neighboring principal neurons or whether they represent a novel functional network element. Adult brain neuronal precursors and immature neurons (complex cells) were labeled in transgenic mice (DCX-DsRed and DCX-CreERT2 /flox-EGFP), and their cell fate was characterized with patch clamp experiments and morphometric analysis of axon initial segments. Young (DCX+) complex cells in the piriform cortex of 2- to 4-month-old mice received sparse synaptic input and fired action potentials at low maximal frequency, resembling neonatal principal neurons. Following maturation, the synaptic input detected on older (DCX−) complex cells was larger, but predominantly GABAergic, despite evidence of glutamatergic synaptic contacts. Furthermore, the rheobase current of old complex cells was larger and the maximal firing frequency was lower than those measured in neighboring age-matched principal neurons. The striking differences between principal neurons and complex cells suggest that the latter are a novel type of neuron and new coding element in the adult brain rather than simple addition or replacement for preexisting network components.
Development and Validation of HPLC and HPTLC Methods for Therapeutic Drug Monitoring of Capecitabine in Colorectal Cancer Patients
Authors: Thorat Sonali G , Chikhale Rupesh V , Tajne Madhukar R
Published: July 2019

Capecitabine is a prodrug of 5-fluorouracil, employed as a monotherapy or combination chemotherapy agent for treatment of colorectal cancer. Combination therapy of capecitabine consists of oxaliplatin, and hence, it becomes essential to determine that co-administration does not affect its metabolism. High-performance liquid chromatography and high-performance thin-layer chromatography methods were developed and validated to determine the plasma concentration of capecitabine. In this study, blood samples from 12 patients with colorectal cancer were collected and analyzed by both methods with a reference internal standard. Two groups consisting of six patients each were formed: the first group was treated with capecitabine monotherapy, the second group with capecitabine + oxaliplatin combination therapy. The results of analysis from both the methods indicated that there is no significant drug–drug interaction. The co-administration of oxaliplatin did not affect the metabolism of capecitabine. Both assay methods were compared for their sensitivity, robustness and specificity. It was found that both the assay methods were suitable for therapeutic drug monitoring of capecitabine.
Development and validation of a HPLC-UV method for the simultaneous detection and quantification of paclitaxel and sulforaphane in lipid based self-microemulsifying formulation
Authors: Kamal Mohammad M , Nazzal Sami
Published: July 2019

Paclitaxel (PTX) and sulforaphane (SFN) are known anticancer molecules. Their activity was found to be potentiated when tested concurrently. Only recently, however, a novel SFN enabled PTX self-microemulsifying formulation (SMEDDS) was developed for their simultaneous delivery. This necessitated the development of an analytical method for the simultaneous detection and quantitation of PTX and SFN. In this study, a simple and sensitive isocratic high performance liquid chromatography-ultraviolet (HPLC-UV) analytical method was developed and validated per International Conference on Harmonization guidelines to satisfy this objective. Its application was demonstrated when quantifying the amount of PTX and SFN released from the SMEDDS in various dissolution media. The separation of the analytes was performed with the aid of a reversed phase C18 column at ambient temperature using a 60:40 mixture of acetonitrile and KH2PO4 buffer (pH 5.0) as the mobile phase. PTX and SFN peaks were detected at 202 nm with high resolution without interference from excipients. This method showed linearity within 2.5–100 μg/mL range with r2 > 0.999. The limit of detection and lower limit of quantitation were 0.1638 and 0.4964 μg/mL for PTX and 0.4419 and 1.3389 μg/mL for SFN, respectively. A total of 98–101% of the injected samples was recovered with RSD of 0.06–0.68% indicating the suitability of the method for the simultaneous detection and quantitation of the molecules in dissolution media.
Generating the Evidence for Typhoid Vaccine Introduction: Considerations for Global Disease Burden Estimates and Vaccine Testing Through Human Challenge
Authors: Meiring James E , Giubilini Alberto , Savulescu Julian , Pitzer Virginia E , Pollard Andrew J
Published: July 2019

Typhoid fever has had a major impact on human populations, with the causative pathogen Salmonella enterica serovar Typhi implicated in many outbreaks through history. The current burden of disease is estimated at 11–18 million infections annually, with the majority of infections located in Africa and South Asia. Data that have been used to estimate burden are limited to a small number of blood-culture surveillance studies, largely from densely populated urban centers. Extrapolating these data to estimate disease burden within and across countries highlights the lack of precision in global figures. A number of approaches have been developed, characterizing different geographical areas by water-based risk factors for typhoid infection or broader measures of health and development to more accurately extrapolate incidence. Recognition of the substantial disease burden is essential for policy-makers considering vaccine introduction. Typhoid vaccines have been in development for >100 years. The Vi polysaccharide (ViPS) and Ty21a vaccines have had a World Health Organization (WHO) recommendation for programmatic use in countries with high burden for 10 years, with 1 ViPS vaccine also having WHO prequalification. Despite this, uptake and introduction of these vaccines has been minimal. The development of a controlled human infection model (CHIM) enabled the accelerated testing of the newly WHO-prequalified ViPS–tetanus toxoid protein conjugate vaccine, providing efficacy estimates for the vaccine, prior to larger field trials. There is an urgency to the global control of enteric fever due to the escalating problem of antimicrobial resistance. With more accurate burden of disease estimates and a vaccine showing efficacy in CHIM, that control is now a possibility.
Methylation in Predicting Progression of Untreated High-grade Cervical Intraepithelial Neoplasia
Authors: Louvanto Karolina , Aro Karoliina , Nedjai Belinda , Bützow Ralf , Jakobsson Maija , Kalliala Ilkka , Dillner Joakim , Nieminen Pekka , Lorincz Attila
Published: July 2019

Background

There is no prognostic test to ascertain whether cervical intraepithelial neoplasias (CINs) regress or progress. The majority of CINs regress in young women, and treatments increase the risk of adverse pregnancy outcomes. We investigated the ability of a DNA methylation panel (the S5 classifier) to discriminate between outcomes among young women with untreated CIN grade 2 (CIN2).

Methods

Baseline pyrosequencing methylation and human papillomavirus (HPV) genotyping assays were performed on cervical cells from 149 women with CIN2 in a 2-year cohort study of active surveillance.

Results

Twenty-five lesions progressed to CIN grade 3 or worse, 88 regressed to less than CIN grade 1, and 36 persisted as CIN1/2. When cytology, HPV16/18 and HPV16/18/31/33 genotyping, and the S5 classifier were compared to outcomes, the S5 classifier was the strongest biomarker associated with regression vs progression. The S5 classifier alone or in combination with HPV16/18/31/33 genotyping also showed significantly increased sensitivity vs cytology when comparing regression vs persistence/progression. With both the S5 classifier and cytology set at a specificity of 38.6% (95% confidence interval [CI], 28.4–49.6), the sensitivity of the S5 classifier was significantly higher (83.6%; 95% CI, 71.9–91.8) than of cytology (62.3%; 95% CI, 49.0–74.4; P = 0.005). The highest area under the curve was 0.735 (95% CI, 0.621–0.849) in comparing regression vs progression with a combination of the S5 classifier and cytology, whereas HPV genotyping did not provide additional information.

Conclusions

The S5 classifier shows high potential as a prognostic biomarker to identify progressive CIN2.
Low Hepatitis C Reinfection Following Direct-acting Antiviral Therapy Among People Who Inject Drugs on Opioid Agonist Therapy
Authors: Akiyama Matthew J , Lipsey Daniel , Heo Moonseong , Agyemang Linda , Norton Brianna L , Hidalgo Jennifer , Lora Kiara , Litwin Alain H
Published: July 2019

Background

Direct-acting antiviral (DAA) therapy is highly effective in people who inject drugs (PWID); however, rates, specific injection behaviors, and social determinants associated with hepatitis C virus (HCV) reinfection following DAA therapy among PWID on opioid agonist therapy (OAT) are poorly understood.

Methods

PREVAIL was a randomized controlled trial that assessed models of HCV care for 150 PWID on OAT. Those who achieved sustained virologic response (SVR) (n = 141; 94%) were eligible for this extension study. Interviews and assessments of recurrent HCV viremia occurred at 6-month intervals for up to 24 months following PREVAIL. We used survival analysis to analyze variables associated with time to reinfection.

Results

Of 141 who achieved SVR, 114 had a least 1 visit in the extension study (62% male; mean age, 52 years). Injection drug use (IDU) was reported by 19% (n = 22) in the extension study. HCV reinfection was observed in 3 participants. Over 246 person-years of follow-up, the incidence of reinfection was 1.22/100 person-years (95% CI, 0.25–3.57). All reinfections occurred among participants reporting ongoing IDU. The incidence of reinfection in participants reporting ongoing IDU (41 person-years of follow-up) was 7.4/100 person-years (95% CI, 1.5–21.6). Reinfection was associated with reporting ongoing IDU in the follow-up period (P < .001), a lack confidence in the ability to avoid contracting HCV (P < .001), homelessness (P = .002), and living with a PWID (P = .007).

Conclusions

HCV reinfection was low overall, but more common among people with ongoing IDU following DAA therapy on OAT, as well as those who were not confident in the ability to avoid contracting HCV, homeless, or living with a PWID. Interventions to mediate these risk factors following HCV therapy are warranted.
Cranial Imaging and Lumbar Puncture in Patients With Suspected Central Nervous System Infection
Authors: Costerus Joost M , Lemmens Cynthia M C , van de Beek Diederik , Brouwer Matthijs C
Published: July 2019

Background

Performing cranial imaging prior to lumbar punctures (LPs) in patients with suspected central nervous system (CNS) infections has been associated with delayed treatments and poor outcomes. Various guidelines provide different criteria for cranial imaging prior to LP.

Methods

We describe the use of cranial imaging in a cohort of adult patients with suspected CNS infections, and evaluated adherence to the recommendations made in the Infectious Disease Society of America (IDSA), European Society of Clinical Microbiology and Infectious Diseases (ESCMID), Swedish, and Dutch guidelines. We also analyzed the association between cranial imaging and the time between emergency department entrance and intravenous antibiotic administration.

Results

From 2012–2015, 203 patients with suspected CNS infections were included, of whom 56 (27%) were diagnosed with CNS infections and 16 were diagnosed with bacterial meningitis (8%). Cranial imaging, in all cases computed tomography (CT), was performed in 130 patients (64%) and led to the deferral of LPs in 7 (5%). Criteria by the IDSA, ESCMID, Swedish, and Dutch guidelines showed indications for imaging in 64%, 39%, 39%, and 40% of patients, respectively. The times between emergency department arrivals and the start of antibiotic therapy between patients with and without CT before LP were similar (median 134 [interquartile range (IQR) 58–292] vs. 141 minutes [IQR 52–227], respectively; Mann-Whitney U P = .74).

Conclusions

A cranial CT prior to LP was done in the majority of patients with a suspected CNS infection, irrespective of guideline indications. The ESCMID, Swedish, and Dutch guidelines were more restrictive in advising imaging, compared to the IDSA guidelines. Performing cranial imaging prior to LP was not associated with treatment delays in this Dutch cohort study.
Power Saving Proxies for Web Servers
Authors: O’Dwyer Karl J , Creedon Eoin , Purcell Mark , Malone David
Published: July 2019

Electricity is a major cost in running a data centre, and servers are responsible for a significant percentage of the power consumption. Given the widespread use of HTTP, both as a service and a component of other services, it is worthwhile reducing the power consumption of web servers. In this paper we consider how reverse proxies, commonly used to improve the performance of web servers, might be used to improve energy efficiency. We suggest that when demand on a server is low, it may be possible to switch off servers. In their absence, an embedded system with a small energy footprint could act as a reverse proxy serving commonly-requested content. When new content is required, the reverse proxy can power on the servers to meet this new load. Our results indicate that even with a modest server, we can get a 25% power saving while maintaining acceptable performance.
Building a Fuzzy Logic-Based Artificial Neural Network to Uplift Recommendation Accuracy
Authors: Sinha Bam Bahadur , Dhanalakshmi R
Published: July 2019

With the advent of the internet, the recommender system escorts the users in a customized way to nominate items from a massive set of possible alternatives. The emergence of overspecification in recommender system has emphasized negative effects on the context of prediction. The drift of user interest over time is one of the challenging affairs in present personalized recommender system. In this paper, we present a neural network model to improve the recommendation performance along with usage of fuzzy-based clustering to decide membership value of users and matching imputation to cutback sparsity to some extent. We evaluate our model on the MovieLens dataset and show that our model not only elevates accuracy, but also considers the order in which recommendation should be given. We compare the proposed model with a number of state-of-the-art personalization methods and show the dominance of our model using accuracy metrics such as root-mean-square error and mean absolute error.
Localization and non-ergodicity in clustered random networks
Authors: Avetisov V , Gorsky A , Nechaev S , Valba O
Published: July 2019

We consider clustering in rewired Erdős–Rényi networks with conserved vertex degree and in random regular graphs from the localization perspective. It has been found in Avetisov et al. (2016, Phys. Rev. E, 94, 062313) that at some critical value of chemical potential $\mu_{\rm cr}$ of closed triad of bonds, the evolving networks decay into the maximally possible number of dense subgraphs. The adjacency matrix acquires above $\mu_{\rm cr}$ the two-zonal support with the triangle-shaped main (perturbative) zone separated by a wide gap from the side (non-perturbative) zone. Studying the distribution of gaps between neighbouring eigenvalues (the level spacing), we demonstrate that in the main zone the level spacing matches the Wigner–Dyson law and is delocalized, however it shares the Poisson statistics in the side zone, which is the signature of localization. In parallel with the evolutionary designed networks, we consider ‘instantly’ ad hoc prepared networks with in- and cross-cluster probabilities exactly as at the final stage of the evolutionary designed network. For such ‘instant’ networks the eigenvalues are delocalized in both zones. We speculate about the difference in eigenvalue statistics between ‘evolutionary’ and ‘instant’ networks from the perspective of a possible phase transition between ergodic and non-ergodic network patterns with a strong ‘memory dependence’, thus advocating possible existence of non-ergodic delocalized states in the clustered random networks at least at finite network sizes.
Lower bound for the cost of connecting tree with given vertex degree sequence
Authors: Goubko Mikhail , Kuznetsov Alexander
Published: July 2019

The optimal connecting network problem generalizes many models of structure optimization known from the literature, including communication and transport network topology design, graph cut and graph clustering, etc. For the case of connecting trees with the given sequence of vertex degrees the cost of the optimal tree is shown to be bounded from below by the solution of a semidefinite optimization program with bilinear matrix inequality constraints, which is reduced to the solution of a series of convex programs with linear matrix inequality constraints. The proposed lower-bound estimate is used to construct several heuristic algorithms and to evaluate their quality on a variety of generated and real-life datasets.
Electrophysiological and Behavioral Responses of Drosophila suzukii (Diptera: Drosophilidae) Towards the Leaf Volatile β-cyclocitral and Selected Fruit-Ripening Volatiles
Authors: Bolton L Grant , Piñero Jaime C , Barrett Bruce A
Published: July 2019

The spotted-wing drosophila, Drosophila suzukii Matsumura (Diptera: Drosophilidae), is attracted to numerous volatile organic compounds (VOCs) emitted from several ripening, small fruit crops. However, the strawberry leaf terpenoid, β-cyclocitral, is reportedly very attractive to D. suzukii (but not to all Drosophila spp.). This suggests that leaf and fruit VOCs may be critical sources needed to further develop a more species-specific D. suzukii monitoring lure, or semiochemically based attract-and-kill systems. This study investigated the electrophysiological responses of male and female D. suzukii towards selected host fruit-ripening VOCs and β-cyclocitral, along with behavioral responses toward combined fruit VOCs with β-cyclocitral. Electroantennogram (EAG) results revealed a positive dose–response, for both sexes, as concentrations increased for all VOCs tested. For β-cyclocitral, hexyl acetate and methyl butyrate, the mean male EAG responses were significantly greater than the female responses at lower doses. In caged behavioral bioassays, only in the β-cyclocitral treatments were the mean number of flies captured (sexes combined) significantly greater than that captured in solvent (mineral oil) controls. Our study has demonstrated that while single fruit-based VOCs alone are not enough to cause a strong behavioral attraction by both male and female D. suzukii, the addition of β-cyclocitral did produce a significant attraction response from both sexes. In both bioassays, males had higher responses to β-cyclocitral than females, which suggest a greater sensitivity to this compound. Further studies are needed to ascertain the role β-cyclocitral may play in the development of a more species-specific D. suzukii monitoring lure.