bluuebunny/crossref_metadata_2025_split huggingface dataset:
An untargeted metabolomics strategy to measure differences in metabolite uptake and excretion by mammalian cell lines
Authors: Muelas Marina Wright , Roberts Ivayla , Mughal Farah , O’Hagan Steve , Day Philip J. , Kell Douglas B. 
Published: June 2020

AbstractIntroductionIt is widely but erroneously believed that drugs get into cells by passing through the phospholipid bilayer portion of the plasma and other membranes. Much evidence shows, however, that this is not the case, and that drugs cross biomembranes by hitchhiking on transporters for other natural molecules to which these drugs are structurally similar. Untargeted metabolomics can provide a method for determining the differential uptake of such metabolites.ObjectivesBlood serum contains many thousands of molecules and provides a convenient source of biologically relevant metabolites. Our objective was to measure them.MethodsWe develop an untargeted LC-MS/MS method to detect a broad range of compounds present in human serum. We apply this to the analysis of the time course of the uptake and secretion of metabolites in serum by several human cell lines, by analysing changes in the serum that represents the extracellular phase (the ‘exometabolome’ or metabolic footprint).ResultsOur method measures some 4,000-5,000 metabolic features in both ES+and ES−modes. We show that the metabolic footprints of different cell lines differ greatly from each other.ConclusionOur new, 15-minute untargeted metabolome method allows for the robust and convenient measurement of differences in the uptake of serum compounds by cell lines following incubation in serum, and its relation to differences in transporter expression.
Calmodulin binds to the N-terminal domain of the cardiac sodium channel Nav1.5
Authors: Wang Zizun , Vermij Sarah H. , Sottas Valentin , Shestak Anna , Ross-Kaschitza Daniela , Zaklyazminskaya Elena V. , Hudmon Andy , Pitt Geoffrey S. , Rougier Jean-Sébastien , Abriel Hugues 
Published: June 2020

ABSTRACTThe cardiac voltage-gated sodium channel Nav1.5 conducts the rapid inward sodium current crucial for cardiomyocyte excitability. Loss-of-function mutations in its geneSCN5Aare linked to cardiac arrhythmias such as Brugada Syndrome (BrS). Several BrS-associated mutations in the Nav1.5 N-terminal domain exert a dominant-negative effect (DNE) on wild-type channel function, for which mechanisms remain poorly understood. We aim to contribute to the understanding of BrS pathophysiology by characterizing three mutations in the Nav1.5 N-terminal domain (NTD): Y87C–here newly identified–, R104W and R121W. In addition, we hypothesize that the calcium sensor protein calmodulin is a new NTD binding partner.Recordings of whole-cell sodium currents in TsA-201 cells expressing WT and variant Nav1.5 showed that Y87C and R104W but not R121W exert a DNE on WT channels. Biotinylation assays revealed reduction in fully glycosylated Nav1.5 at the cell surface and in whole-cell lysates. Localization of Nav1.5 WT channel with the ER however did not change in the presence of variants, shown by transfected and stained rat neonatal cardiomyocytes. We next demonstrated that calmodulin binds Nav1.5 N-terminus usingin silicomodeling, SPOTS, pull-down and proximity ligation assays. This binding is impaired in the R121W variant and in a Nav1.5 construct missing residues 80-105, a predicted calmodulin binding site.In conclusion, we present the first evidence that calmodulin binds to the Nav1.5 NTD, which seems to be a determinant for the DNE.
Analysis of costs and strategies for using academic research in a private dental college to develop commercially viable products
Authors: Chandra Rampalli Viswa , Raju Devaraju Rama 
Published: June 2020

ABSTRACTBackground & objectivesThe study had two aims. 1) Analysis of research projects done in our institution from 2014-2019 to identify products with a potential for commercialization and 2) To understand the effect of product-development variables on research projects to improve the quality of future commercialization-oriented trials.Methods338 clinical trials were grouped into 188 projects under the headings irrigants, diagnostic devices, surgical devices, biomaterials and gels. Trials per project, capital, material costs, labour and the cycle timespertrial were calculated. To understand the effect these variables, five hypotheses were generated to test whether greater number of trials, successes, higher capital, more investigators per trial and a longer trial duration will result in a product worthy of commercialization.Results22 projects had products with a potential for commercialization. Except labour and cycle time (p>0.05), all variables showed significant differences across all projects. Three products were identified as having potential for actual commercialization. It was observed that greater number of trials (χ2=4.6793; p=0.030528) and successes (χ2=20.8134; p<0.00001) in a project along with a higher capital (χ2=12.2662; p=0.000461) will generate a product worthy of commercialization.Interpretation & conclusionsThe results seem to suggest that in trials for commercialization, emphasis must be placed on implementing multiple, well-designed clinical trials on a device or product to successfully identify whether it is commercialization-worthy or not. Due attention must be given to the financial aspects of the projects as deficiencies may result in negative impact on the flow and outcomes of a clinical trial.
Environmental rhythms orchestrate neural activity at multiple stages of processing during memory encoding: Evidence from event-related potentials
Authors: Hickey Paige , Barnett-Young Annie , Patel Aniruddh D. , Race Elizabeth 
Published: June 2020

AbstractAccumulating evidence suggests that rhythmic temporal structures in the environment influence memory formation. For example, stimuli that appear in synchrony with the beat of background, environmental rhythms are better remembered than stimuli that appear out-of-synchrony with the beat. This rhythmic modulation of memory has been linked to entrained neural oscillations which are proposed to act as a mechanism of selective attention by amplifying early sensory responses to events that coincide with the beat. The current study aimed to further test this hypothesis by using event-related potentials (ERPs) to investigate the locus of stimulus processing at which rhythm temporal cues operate in the service of memory formation. Participants incidentally encoded a series of visual objects while passively listening to background, instrumental music with a steady beat. Objects either appeared in-synchrony or out-of-synchrony with the background beat. Participants were then given a surprise subsequent memory test (in silence). The timing of stimulus presentation during encoding (in-synchrony or out-of-synchrony with the background beat) influenced canonical ERPs associated with post-perceptual selection and orienting attention in time. Importantly, post-perceptual ERPs also differed according to whether or not participants demonstrated a mnemonic benefit for in-synchrony compared to out-of-synchrony stimuli, and were related to the magnitude of the rhythmic modulation of memory across participants. These results support two prominent theories in the field, the Dynamic Attending Theory and the Oscillation Selection Hypothesis, which propose that neural responses to rhythm act as a core mechanism of selective attention that optimize processing at specific moments in time. Furthermore, they reveal that in addition to acting as a mechanism of early attentional selection, rhythm influences later, post-perceptual cognitive processes as events are transformed into memory.
NetBoxR: Automated Discovery of Biological Process Modules by Network Analysis in R
Authors: Liu Eric Minwei , Luna Augustin , Dong Guanlan , Sander Chris 
Published: June 2020

AbstractSummaryLarge-scale sequencing projects, such as The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC), have accumulated a variety of high throughput sequencing and molecular profiling data, but it is still challenging to identify potentially causal genetic mutations in cancer as well as in other diseases in an automated fashion. We developed the NetBoxR package written in the R programming language, that makes use of the NetBox algorithm to identify candidate cancer-related processes. The algorithm makes use of a networkbased approach that combines prior knowledge with a network clustering algorithm, obviating the need for and the limitation of functionally curated gene sets. A key aspect of this approach is its ability to combine multiple data types, such as mutations and copy number alterations, leading to more reliable identification of functional modules. We make the tool available in the Bioconductor R ecosystem for applications in cancer research and cell biology.Availability and implementationThe NetBoxR package is free and open-sourced under the GNU GPL-3 license R package available athttps://www.bioconductor.org/packages/release/bioc/html/netboxr.htmlContactlium2@mskcc.org;aluna@jimmy.harvard.edu;sander.research@gmail.comSupplementary informationNone
Real-time tracking of Tomato brown rugose fruit virus (ToBRFV) outbreaks in the Netherlands using Nextstrain
Authors: van de Vossenberg Bart T.L.H. , Visser Michael , Bruinsma Maaike , Koenraadt Harrie M.S. , Westenberg Marcel , Botermans Marleen 
Published: June 2020

AbstractTomato brown rugose fruit virus (ToBRFV) is a Tobamovirus that was first observed in 2014 and 2015 on tomato plants in Israel and Jordan causing discolorations and deformation of leaves and fruits. Apart from tomato, damage in pepper fruits has been reported. Since the first description, the virus has been found on all continents except Oceania and Antarctica.In October 2019, the Dutch National Plant Protection Organization received a tomato sample suspected to be infected with ToBRFV as part of an official specific survey of tomato fruit growers in the Netherlands carried out July to October 2019. During the survey 124 companies were visited and inspected for possible ToBRFV symptoms. Of the 47 samples tested, one sample tested positive with ELISA and test plants, which was verified using real-time RT-PCR and Illumina RNAseq data. A follow-up survey was initiated to determine the extent of ToBRFV presence in the Dutch tomato horticulture and identify possible linkages between ToBRFV genotypes, companies and epidemiological traits. We used Nextstrain to visualize these potential connections.Genomic diversity of ToBRFV isolates found in the Netherlands group in three main clusters which are hypothesized to represent three sources. No correlation was found between genotypes, companies and epidemiological traits such as rootstock and scion varieties, seed batches and nurseries, and the source(s) of the Dutch outbreak remain unknown.This paper describes a Nextstrain build containing ToBRFV genomes up to and including November 2019. The NPPO-NL has committed itself to maintain and improve the build. Sharing data with this interactive online tool will enable the regulatory plant virology field to better understand and communicate the diversity and spread of this new virus. Other organizations are stimulated to share data or materials for inclusion in the Nextstrain build, which can be accessed at //40.91.255.14/ToBRFV/20191231.
Analysis of opticin binding to collagen fibrils identifies a single binding site in the gap region and a high specificity towards thin heterotypic fibrils containing collagens II, and XI or V/XI
Authors: Hansen Uwe , Holmes David F. , Bruckner Peter , Bishop Paul N. 
Published: June 2020

AbstractOpticin is a class III member of the extracellular matrix small leucine-rich repeat protein/proteoglycan (SLRP) family found in vitreous humour and cartilage. It was first identified associated with the surface of vitreous collagen fibrils and several other SLRPs are also known to bind collagen fibrils and it some cases alter fibril morphology. The purpose of this study was to investigate the binding of opticin to the collagen II-containing fibrils found in vitreous and cartilage. Electron microscopic studies using gold labelling demonstrated that opticin binds vitreous and thin cartilage collagen fibrils specifically at a single site in the gap region of the collagen D-period corresponding to the e2 stain band; this is the first demonstration of the binding site of a class III SLRP on collagen fibrils. Opticin did not bind thick cartilage collagen fibrils from cartilage or tactoids formedin vitrofrom collagen II, but shows high specificity for thin, heterotypic collagen fibrils containing collagens II, and XI or V/XI. Vitreous collagen fibrils from opticin null and wild-type mice were compared and no difference in fibril morphology or diameter was observed. Similarly,in vitrofibrillogenesis experiments showed that opticin did not affect fibril formation. We propose that when opticin is bound to collagen fibrils, rather than influencing their morphology it instead hinders the binding of other molecules to the fibril surfaces and/or act as an intermediary bridge linking the collagen fibrils to other non-collagenous molecules.
GuidingNet: revealing transcriptional cofactor and predicting binding for DNA methyltransferase by network regularization
Authors: Ren Lixin , Gao Caixia , Duren Zhana , Wang Yong 
Published: June 2020

AbstractThe DNA methyltransferases (DNMTs) (DNMT3A, DNMT3B, and DNMT3L) are primarily responsible for the establishment of genomic locus-specific DNA methylation patterns, which play an important role in gene regulation and animal development. However, this important protein family’s binding mechanism, i.e., how and where the DNMTs bind to genome, is still missing in most tissues and cell lines. This motivates us to explore DNMTs and TF’s cooperation and develop a network regularized logistic regression model, GuidingNet, to predict DNMTs’ genome-wide binding by integrating gene expression, chromatin accessibility, sequence, and protein-protein interaction data. GuidingNet accurately predicted methylation experimental data validated DNMTs’ binding, outperformed single data source based method and sparsity regularized methods, and performed well in within and across tissue prediction for several DNMTs in both human and mouse. Importantly, GuidingNet can reveal transcription co-factors assisting DNMTs for methylation establishment. This provides biological understanding in the DNMTs’ binding specificity in different tissues and demonstrate the advantage of network regularization. In addition, GuidingNet achieves good performance for chromatin regulators’ binding other than DNMTs and serves as a useful method for studying chromatin regulator binding and function. The GuidingNet is freely available athttps://github.com/AMSSwanglab/GuidingNet.Author summaryDNA methyltransferases (DNMTs) are in charge of the addition of methyl groups to cytosine residues by binding to DNA specific region. However, DNMTs do not have DNA binding domains to recognize specific DNA sequences and an urging question is how DNMTs recognize their binding sites in the genome in different tissues. Here, we propose a network regularized logistic regression model, GuidingNet, for predicting DNMT’ genome-wide binding by integrating gene expression, chromatin accessibility, sequence, and protein-protein interaction data. The main contribution is to hypothesize that DNMTs interact with transcription factors and are guided by the TF network to bind to DNA, and methylate DNA GuidingNet captures the mechanism of DNMT binding in different tissue contexts and predict DNMTs’ binding well.
Species composition and risk of transmission ofAedes-borne arboviruses around some Yellow hotspot areas in Northern Ghana
Authors: Joannides Joannitta , Dzodzomenyo Mawuli , Azerigyik Faustus , Agbosu Eudocia Esinam , Pratt Deborah , Osei Nyarkoh Joseph , Pwalia Rebecca , Kwame Amlalo Godwin , Appawu Maxwell A. , Takashi Hayashi , Iwanaga Shiroh , Buchwald Andrea , Rochford Rosemary , Boakye Daniel , Koram Kwadwo , Bonney Kofi , Dadzie Samuel Kweku 
Published: June 2020

AbstractAedes-borne viral diseases mainly Yellow Fever (YF), Dengue (DEN), Zika (ZIK) and Chikungunya (CHK) have contributed to many deaths’ in the world especially in Africa. There have been major outbreaks of these diseases in West Africa. YF outbreaks have occurred in Ghana. Although Ghana has not recorded any outbreak of DEN, ZIK and CHK, the risk is high due to its proximity to West African countries where outbreaks have been recently been recorded. This study assessed the risk of transmission of Yellow fever (YFV), Dengue (DENV), Chikungunya (CHKV) and Zika (ZIKV) viruses in Larabanga and Mole Game Reserve areas in Northern Ghana. The immature and adult stages ofAedesmosquitoes were collected from Larabanga and Mole Game Reserve area. There was a significant (P>0.001) number of mosquitoes collected during the rainy season than the dry season. A total of 1,930Aedesmosquitoes were collected during the rainy season and morphologically identified. Of these, 1,915 (99.22%) wereAedes aegyptiand 15 (0.22%) wereAedes vittatus. During the dry season, 27Aedes aegyptimosquitoes were collected. A total of 415Ae. aegyptimosquitoes were molecularly identified to subspecies level of whichAedes (Ae) aegypti aegyptiwas the predominant subspecies. BothAe. aegypti aegypti and Ae aegypti formosusexist in sympatry in the area. AllAedespools (75) were negative for DENV, ZIKV and CHKV when examined by RT-PCR. Three Larval indices namely House Index, HI (percentage of houses positive forAedeslarvae or pupae), Container Index, CI (the percentage of containers positive forAedeslarvae or pupae) and Breteau Index, BI (the number of positive containers (with larvae and/or pupae per 100 inspected houses) were assessed as a measure for risk of transmission. The HI, CI and BI for both sites were as follows; Mole game reserve (HI, 42.1%, CI, 23.5% and BI, 100 for rainy season and 0 for all indices for dry season) and Larabanga (39%, 15.5% and 61 for rainy season and 2.3%, 1.3% and 2.3 for dry season). The spatial distribution ofAedesbreeding sites in both areas indicated thatAedeslarvae were breeding in areas with close proximity to humans. Lorry tires were the main source ofAedeslarvae in all the study areas. Information about the species composition and the potential role ofAedesmosquitoes in future outbreaks of the diseases that they transmit is needed to design efficient surveillance and vector control tools.
Target tracking behaviour of the praying mantisSphrodromantis lineola(Linnaeus) is driven by looming-type motion-detectors
Authors: Rind F. Claire , Jones Lisa , Tarawneh Ghaith , Read Jenny F. M. 
Published: June 2020

AbstractWe designed visual stimuli to characterise the motion-detectors that underlie target tracking behaviour in the mantis. The first was a small, moving, stripy, bug-like target, made by opening a moving, Gabor-filtered window onto an extended, moving, sinewave pattern. The mantis tracked this bug-like target, but the likelihood of tracking the bug depended only on the temporal frequency of its motion. In contrast, optomotor responses to the extended moving sinewave pattern alone depended on both spatial and temporal frequency of the pattern, as expected from classical, correlation-based motion-detectors. In another experiment, we used small moving objects that were made up of chequerboard patterns of randomly arranged dark squares, and found objects with smaller sized chequers were tracked relatively less. Response suppression like this, when the internal detail of an object increases, suggests the presence of lateral inhibition between inputs to the motion-detectors for target tracking. Finally, wide-field motion of a chequerboard background near the target, balanced so no optomotor responses were evoked, suppressed tracking proportionally both to the nearness of the background to the target and to the size its dark chequered squares. Backgrounds with smaller sized squares produced more suppression. This effect has been used as a demonstration of lateral inhibition in detectors for looming-motion and makes their response greatest to an expanding outer edge, an image produced by an approaching object. Our findings point to a new role for a looming-type motion-detector in mantis target tracking. We also discuss the suitability of several large lobula-complex neurons for this role.Summary StatementLateral inhibition shown by motion-detectors underlying target tracking by the praying mantisSphrodromantis lineola(Linnaeus).
Online milk composition analysis with an on-farm near-infrared sensor
Authors: Diaz-Olivares Jose A. , Adriaens Ines , Stevens Els , Saeys Wouter , Aernouts Ben 
Published: June 2020

AbstractOn-farm monitoring of milk composition can support close control of the udder and metabolic health of individual dairy cows. In previous studies, near-infrared (NIR) spectroscopy applied to milk analysis has proven useful for predicting the main components of raw milk (fat, protein, and lactose). In this contribution, we present and evaluate a precise tool for online milk composition analysis on the farm. For each milking, the online analyzer automatically collects and analyses a representative milk sample. The system acquires the NIR transmission spectra of the milk samples in the wavelength range from 960 to 1690 nm and performs a milk composition prediction afterward.Over a testing period of 8 weeks, the sensor collected 1165 NIR transmittance spectra of raw milk samples originating from 36 cows for which reference chemical analyses were performed for fat, protein, and lactose. For the same online sensor system, two calibration scenarios were evaluated: training post-hoc prediction models based on a representative set of calibration samples (n= 319) acquired over the entire testing period, and training real-time prediction models exclusively on the samples acquired in the first week of the testing period (n= 308).The obtained prediction models were thoroughly tested on all the remaining samples not included in the calibration sets (nrespectively 846 and 857). For the post-hoc prediction models, this resulted in an overall prediction error (root-mean-squared error of prediction, RMSEP) smaller than 0.08% (all % are inw/w) for milk fat (range 1.5-6.3%), protein (2.6-4.3%) and lactose (4-5.1%), while for the real-time prediction models the RMSEP was smaller than 0.09% for milk fat and lactose, and smaller than 0.11% for protein. The milk lactose predictions could be further improved by taking into account a cow-specific bias. The presented online sensor system using the real-time prediction approach can thus be used for detailed and autonomous on-farm monitoring of milk composition after each individual milking, as its accuracy is well within the ICAR requirements for on-farm milk analyzers and even meet the ICAR standards for laboratory analysis systems for fat and lactose. For this real-time prediction approach, a drift was observed in the predictions, especially for protein. Therefore, further research on the development of online calibration maintenance techniques is required to correct for this model drift and further improve the performance of this sensor system.