bluuebunny/crossref_metadata_2025_split huggingface dataset:
Metabolic changes of the host-pathogen environment in aCryptosporidiuminfection
Authors: Miller Christopher N. , Panagos Charalampos G. , Kváč Martin , Howard Mark J. , Tsaousis Anastasios D. 
Published: June 2017

AbstractCryptosporidiumis an important gut microbe whose contributions towards infant and immunocompromise patient mortality rates are steadily increasing. Current techniques for diagnosing, curing or simply understanding the biology of the parasite are few and far between, relying on a combination ofin-silicopredictions modelled on a varied and unique group of organisms and medical reports. The development of anin-vitroculture system, using COLO-680N cells, has provided theCryptosporidiumcommunity with the opportunity to expand its toolkit for investigating this disease. One area in particular that is sorely overlooked is the metabolic alterations upon infection. Existing research is extremely limited and has already shown that significant variation can be found between the metabolome of different infected host species. Using a1H Nuclear Magnetic Resonance approach to metabolomics, we have explored the nature of the mouse gut metabolome as well as providing the first insight into the metabolome of an infected cell line. Through a combination of Partial Least Squares Discriminant Analysis and predictive modelling, we exhibit new and potentially game changing insights into the effects of aCryptosporidium parvuminfection, while verifying the presence of known metabolic changes. Of particular note is the potential contribution of host derived taurine to the diuretic aspects of the disease previously attributed to a solely parasite based alteration of the gut environment. This practical and informative approach can spearhead our understanding of theCryptosporidium-host metabolic exchange and thus provide novel targets for tackling this deadly parasite.
The importance of Chargaff’s second parity rule for genomic signatures in metagenomics
Authors: Gori Fabio , Mavroeidis Dimitrios , Jetten Mike SM , Marchiori Elena 
Published: June 2017

AbstractAn important problem in metagenomic data analysis is to identify the source organism, or at least taxon, of each sequence. Most methods tackle this problem in two steps by using an alignment-free approach: first the DNA sequences are represented as points of a real n-dimensional space via a mapping function then either clustering or classification algorithms are applied. Those mapping functions require to be genomic signatures: the dissimilarity between the mapped points must reflect the degree of phylogenetic similarity of the source species. Designing good signatures for metagenomics can be challenging due to the special characteristics of metagenomic sequences; most of the existing signatures were not designed accordingly and they were tested only on error-free sequences sampled from a few dozens of species.In this work we analyze comparatively the goodness of existing and novel signatures based on tetranu-cleotide frequencies via statistical models and computational experiments; we also study how they are affected by the generalized Chargaff’s second parity rule (GCSPR), which states that in a given sequence longer than 50kbp, inverse oligonucleotides are approximately equally frequent. We analyze 38 million sequences of 150 bp-1,000 bp with 1% base-calling error, sampled from 1,284 microbes. Our models indicate that GCSPR reduces strand-dependence of signatures, that is, their values are less affected by the source strand; GCSPR is further exploited by some signatures to reduce the intra-species dispersion. Two novel signatures stand out both in the models and in the experiments: the combination signature and the operation signature. The former achieves strand-independence without grouping oligonucleotides; this could be valuable for alignment-free sequence comparison methods when distinguishing inverse oligonucleotides matters. Operation signature sums the frequencies of reverse, complement, and inverse tetranucleotides; having 72 features it reduces the computational intensity of the analysis.
Emerging patterns of plasmid-host coevolution that stabilize antibiotic resistance
Authors: Stalder Thibault , Rogers Linda M. , Renfrow Chris , Yano Hirokazu , Smith Zachary , Top Eva M. 
Published: June 2017

ABSTRACTMultidrug resistant bacterial pathogens have become a serious global human health threat, and conjugative plasmids are important drivers of the rapid spread of resistance to last-resort antibiotics. Whereas antibiotics have been shown to select for adaptation of resistance plasmids to their new bacterial hosts, orvice versa, a general evolutionary mechanism has not yet emerged. Here we conducted an experimental evolution study aimed at determining general patterns of plasmid-bacteria evolution. Specifically, we found that a large conjugative resistance plasmid follows the same evolutionary trajectories as its non-conjugative mini-replicon in the same and other species. Furthermore, within a single host–plasmid pair three distinct patterns of adaptive evolution led to increased plasmid persistence: i) mutations in the replication protein gene (trfA1); ii) the acquisition by the resistance plasmid of a transposon from a co-residing plasmid encoding a putative toxin-antitoxin system; iii) a mutation in the host’s global transcriptional regulator genefur. Since each of these evolutionary solutions individually have been shown to increase plasmid persistence in other plasmid-host pairs, our work points towards common mechanisms of plasmid stabilization. These could become the targets of future alternative drug therapies to slow down the spread of antibiotic resistance.
Compartmental and spatial rule-based modeling withVirtual Cell(VCell)
Authors: Blinov M. L. , Schaff J. C. , Vasilescu D. , Moraru I. I. , Bloom J. E. , Loew L. M. 
Published: June 2017

AbstractIn rule-based modeling, molecular interactions are systematically specified in the form of reaction rules that serve as generators of reactions. This provides a way to account for all the potential molecular complexes and interactions among multivalent or multistate molecules. Recently, we introduced rule-based modeling into the Virtual Cell (VCell) modeling framework, permitting graphical specification of rules and merger of networks generated automatically (using the BioNetGen modeling engine) with hand-specified reaction networks. VCell provides a number of ordinary differential equation (ODE) and stochastic numerical solvers for single-compartment simulations of the kinetic systems derived from these networks, and agent-based network-free simulation of the rules. In this work, compartmental and spatial modeling of rule-based models has been implemented within VCell. To enable rule-based deterministic and stochastic spatial simulations and network-free agent-based compartmental simulations, the BioNetGen and NFSim engines were each modified to support compartments. In the new rule-based formalism, every reactant and product pattern and every reaction rule are assigned locations. We also introduce the novel rule-based concept of molecular anchors. This assures that any species that has a molecule anchored to a predefined compartment will remain in this compartment. Importantly, in addition to formulation of compartmental models, this now permits VCell users to seamlessly connect reaction networks derived from rules to explicit geometries to automatically generate a system of reaction-diffusion equations. These may then be simulated using either the VCell partial differential equations (PDE) deterministic solvers or the Smoldyn stochastic simulator.
Separable Fully Connected Layers Improve Deep Learning Models For Genomics
Authors: Alexandari Amr Mohamed , Shrikumar Avanti , Kundaje Anshul 
Published: June 2017

ABSTRACTConvolutional neural networks are rapidly gaining popularity in regulatory genomics. Typically, these networks have a stack of convolutional and pooling layers, followed by one or more fully connected layers. In genomics, the same positional patterns are often present across multiple convolutional channels. Therefore, in current state-of-the-art networks, there exists significant redundancy in the representations learned by standard fully connected layers. We present a new separable fully connected layer that learns a weights tensor that is the outer product of positional weights and cross-channel weights, thereby allowing the same positional patterns to be applied across multiple convolutional channels. Decomposing positional and cross-channel weights further enables us to readily impose biologically-inspired constraints on positional weights, such as symmetry. We also propose a novel regularizer and constraint that act on curvature in the positional weights. Using experiments on simulated andin vivodatasets, we show that networks that incorporate our separable fully connected layer outperform conventional models with analogous architectures and the same number of parameters. Additionally, our networks are more robust to hyperparameter tuning, have more informative gradients, and produce importance scores that are more consistent with known biology than conventional deep neural networks.AvailabilityImplementation:https://github.com/kundajelab/keras/tree/keras_1A gist illustrating model setup is at:goo.gl/gYooaa
Analytical Fingerprint of Wolframite Ore Concentrates
Authors: Gäbler Hans‐Eike , Schink Wilhelm , Goldmann Simon , Bahr Andreas , Gawronski Timo 
Published: June 2017

AbstractOngoing violent conflicts in Central Africa are fueled by illegal mining and trading of tantalum, tin, and tungsten ores. The credibility of document‐based traceability systems can be improved by an analytical fingerprint applied as an independent method to confirm or doubt the documented origin of ore minerals. Wolframite (Fe,Mn)WO4 is the most important ore mineral for tungsten and is subject to artisanal mining in Central Africa. Element concentrations of wolframite grains analyzed by laser ablation‐inductively coupled plasma‐mass spectrometry are used to establish the analytical fingerprint. The data from ore concentrate samples are multivariate, not normal or log‐normal distributed. The samples cannot be regarded as representative aliquots of a population. Based on the Kolmogorov–Smirnov distance, a measure of similarity between a sample in question and reference samples from a database is determined. A decision criterion is deduced to recognize samples which do not originate from the declared mine site.
Facial Age Synthesis Using Sparse Partial Least Squares (The Case of Ben Needham)
Authors: Bukar Ali M. , Ugail Hassan 
Published: June 2017

AbstractAutomatic facial age progression (AFAP) has been an active area of research in recent years. This is due to its numerous applications which include searching for missing. This study presents a new method of AFAP. Here, we use an active appearance model (AAM) to extract facial features from available images. An aging function is then modelled using sparse partial least squares regression (sPLS). Thereafter, the aging function is used to render new faces at different ages. To test the accuracy of our algorithm, extensive evaluation is conducted using a database of 500 face images with known ages. Furthermore, the algorithm is used to progress Ben Needham's facial image that was taken when he was 21 months old to the ages of 6, 14, and 22 years. The algorithm presented in this study could potentially be used to enhance the search for missing people worldwide.
Morphological characterization and biological control of Alitropus typus (Isopoda: Aegidae)
Authors: Shah Syed Aizaz Ali , Ashraf Asma , Qureshi Naveeda Akhtar 
Published: June 2017

AbstractThe Alitropus typus infestation has a serious influence on fish farming in Pakistan. The present study focuses on the external morphology and control of highly infested ectoparasitic isopod Alitropus typus. Sixteen morphological parameters of the whole body were measured and statistically analyzed for mean, standard error and coefficient of variation by using the student t test. Non‐significant variations were observed in the size of pereopods which depict the significance of swimming and attached to its host. For biological control, different concentrations (1000, 5000 and 10 000 ppm) of a leaf extract of four plants (i.e. Euphorbia helioscopia, Ajuga bracteosa, Cannabis sativa and Callistemon citrinus) were tested against A. typus, and the mortality rates were recorded after 12, 24 and 36 h. One way Anova and Tukey tests were used to analyze the results. The recorded percentage mortality was in the order of E. helioscopia > A. bracteosa > C. sativa, whereas C. citrinus did not showed any toxicity. Concentrations of biochemical components like carbohydrates (mg/g), proteins (mg/g), and lipids (mg/dL) of treated isopods were estimated by the phenol‐sulfuric acid process, Lowry's method and biochemistry analyzer, respectively. The protein contents of the insects tested had decreased markedly as compared to control rates, and this might be due to insecticidal stress caused by the extracts. In another biocontrol experiment, crabs were introduced along with isopods into an aquarium. It was then noted that one crab consumes an average of seven isopods/week and can act as a scavenger for dead organisms.
Improved sample preparation for direct quantitative detection of Escherichia coli O157 in soil using qPCR without pre‐enrichment
Authors: Highmore Callum J. , Rothwell Steve D. , Keevil Charles W. 
Published: June 2017

SummaryThe prominence of fresh produce as a vehicle for foodborne pathogens such as enterohaemorrhagic Escherichia coli (EHEC) O157 is rising, where disease cases can cause hospitalization and in some cases death. This rise emphasises the necessity for accurate and sensitive methods for detection of pathogens in soil, potential sources of contamination of fresh produce. The complexity of the soil matrix has previously proven prohibitive to pathogen detection via molecular methods without the use of a culture enrichment step, thereby excluding the detection of viable but non‐culturable cells. Here, a sample preparation procedure to facilitate a direct qPCR assay is developed for the detection of E. coli O157 in soil, bypassing culture steps in favour of sample separation through pulsification release and filtration. In sand and peat‐based compost, the method is sensitive to 10 CFU g−1 soil. When testing soils from agricultural sites, it was found that several were qPCR positive for E. coli O157 while being culture‐negative, with peat‐based compost possessing a concentration of 200 tir gene copies per gram. This procedure offers a rapid, quantitative assessment of the potential presence of E. coli O157 in soils which can act as a prescreen of their suitability to grow fresh produce safely.
Thermal sensitivity of bacteriocytes constrains the persistence of intracellular bacteria in whitefly symbiosis under heat stress
Authors: Shan Hong‐Wei , Deng Wen‐Hao , Luan Jun‐Bo , Zhang Min‐Jing , Zhang Zhen , Liu Shu‐Sheng , Liu Yin‐Quan 
Published: June 2017

SummaryTemperature affects the persistence of diverse symbionts of insects. Our previous study indicates that the whitefly symbionts confined within bacteriocytes or scattered throughout the body cavity outside bacteriocytes may have differential thermal sensitivity. However, the underlying mechanisms remain largely unknown. Here, we report that following continuous heat stress, Portiera and Hamiltonella were almost completely depleted in two species of Middle East‐Asia Minor 1 (MEAM1) and Mediterranean (MED) of the Bemisia tabaci whitefly cryptic species complex. Meanwhile, proliferation of bacteriocytes was severely inhibited and approximately 50% of the nymphs had lost one of the two bacteriomes. While cell size of bacteriocytes was increased, cell number was severely decreased leading to reduction of total volume of bacteriocytes. Moreover, bacteriocyte organelles and associated symbionts were lysed, and huge amount of electron‐dense inclusions accumulated. Eventually, Portiera and Hamiltonella failed to be transmitted to the next generation. In contrast, Rickettsia could be detected although at a reduced level, and successfully transmitted to eggs. The results suggest that the thermal sensitivity of bacteriocytes may limit thermal tolerance and vertical transmission of the associated symbionts, and consequently different patterns of distribution of symbionts may affect their capacity to tolerate unfavourable temperatures and persistence in the host.
A discussion on disease severity index values. Part I: warning on inherent errors and suggestions to maximise accuracy
Authors: Chiang K.S. , Liu H.I. , Bock C.H. 
Published: June 2017

AbstractA special type of ordinal scale comprising a number of intervals of known numeric ranges can be used when estimating severity of a plant disease. The interval ranges are most often based on the percent area with symptoms [e.g. the Horsfall–Barratt (H–B) scale]. Studies in plant pathology and plant breeding often use this type of ordinal scale. The disease severity is estimated by a rater as a value on the scale and has been used to determine a disease severity index (DSI) on a percentage basis, where DSI (%) = [sum (class frequency × score of rating class)]/[(total number of plants) × (maximal disease index)] × 100. However, very few studies have investigated the effects of different scales on accuracy of the DSI. Therefore, the objectives of this study were to investigate the process of calculating a DSI on a percentage basis from ordinal scale data, and to use simulation approaches to explore the effect of using different methods for calculation of the interval range and the nature of the ordinal scales used on the DSI estimates (%). We found that the DSI is particularly prone to overestimation when using the above formula if the midpoint values of the rating class are not considered. Moreover, the results of the simulation studies show that, if rater estimates are unbiased, compared with other methods tested in this study, the most accurate method for estimation of a DSI is to use the midpoint of the severity range for each class with an amended 10% ordinal scale (an ordinal scale based on a 10% linear scale emphasising severities ≤50% disease, with additional grades at low severities). As for biased conditions, the accuracy for calculating DSI estimates (%) will depend mainly on the degree and direction of the rater bias relative to the actual mean value.
Advances in Therapeutic Approaches to Extend Healthspan: a perspective from the 2nd Scripps Symposium on the Biology of Aging
Authors: Robbins Paul D. , Niedernhofer Laura J. 
Published: June 2017

SummaryThe 2nd Scripps Florida Symposium on The Biology of Aging entitled ‘Advances in Therapeutic Approaches to Extend Healthspan’ was held on January 22nd–25th, 2017 at The Scripps Research Institute in Jupiter, Florida. The meeting highlighted a variety of therapeutic approaches in animal models of aging that either are or soon will be in clinic trials. For example, drugs targeting senescent cells, metformin, rapalogs, NAD precursors, young plasma, mitochondrial‐targeted free radical scavengers, stem cells, and stem cell factors all have shown significant preclinical efficacy. This perspective, based on presentations and discussions at the symposium, outlines the current and future state of development of therapeutic approaches to extend human healthspan.
Psychometric evaluation of a 6‐item Chinese version of the Hamilton Depression Rating Scale: Mokken scaling and item analysis
Authors: Lee Chin‐Pang , Liu Chia‐Yih , Hung Ching‐I 
Published: June 2017

AbstractBackgroundIt is unclear whether the 6‐item Melancholia subscale of the Hamilton Depression Rating Scale (HAM‐D6) has better psychometric properties than the parental 17‐item version (HAM‐D17) in the Chinese populations.MethodsThe study was to check the Chinese HAM‐D17 and HAM‐D6 for reliability and validity with Mokken scale analysis and item analysis. We reanalyzed a clinical sample of adult psychiatric outpatients (N = 214; age, mean (SD) = 38.3 (10.5) years; 63.1% female) in Taiwan.ResultsOur Mokken scale analysis showed that the HAM‐D6 was a moderate unidimensional scale (Hs = 0.44) while the HAM‐D17 was not (Hs = 0.26). The 5 items of the HAM‐D6 had strong invariant item ordering (HT = 0.58). The HAM‐D17 and HAM‐D6 had comparable reliability (α = 0.79) and validity (r = 0.91), and the HAM‐D6 was more homogenous than the HAM‐D17. To predict depression in remission (HAM‐D17 ≤ 7), the best cutoff of the HAM‐D6 was 4 (specificity, 87.5%; sensitivity, 100%; positive predictive value, 56.0%; negative predictive value, 100%).DiscussionThe Chinese HAM‐D6 was a reliable, valid, and unidimensional scale of depression.
Combined interventional sialendoscopy and intraductal steroid therapy for recurrent sialadenitis in Sjögren's syndrome: Results of a pilot monocentric trial
Authors: Capaccio P. , Canzi P. , Torretta S. , Rossi V. , Benazzo M. , Bossi A. , Vitali C. , Cavagna L. , Pignataro L. 
Published: June 2017

AbstractObjectivesTo evaluate the effectiveness of interventional sialendoscopy alone or combined with outpatient intraductal steroid irrigations in patients with sialadenitis due to Sjögren's syndrome (SS).DesignA pilot therapeutic study.SettingENT Clinics, Universities of Milan and Pavia.Study PopulationWe included 22 patients with SS of whom 12 underwent interventional sialendoscopy followed by intraductal steroid irrigations (group A), and 10 interventional sialendoscopy alone (group B).Outcomes MeasuresThe following outcome measures were considered and recorded before and after the therapeutic intervention: (i) number of episodes of glandular swelling, (ii) cumulative prevalence of patients with glandular swelling assessed by the specific domain, the EULAR SS Disease Activity Index (ESSDAI), (iii) severity of pain by means of a 0‐10 pain visual analogue scale (VAS), (iv) severity of xerostomia and other disease symptoms assessed by the EULAR SS Patient Reported Index (ESSPRI) and the Xerostomia Inventory questionnaire.ResultsThe postoperative reduction in the mean number of episodes of glandular swelling was 87% (95% CI: 77‐93) and 75% (95% CI: 47%‐88%) in the groups A and B, respectively. The percentage of patients with glandular swelling decreased from 41.7% to 0.0% in the group A and from 30.0% to 0.0% in the group B, respectively. Most of the patients experienced a subjective clinical improvement documented by the statistically significant reductions in the postoperative mean pain VAS (group A P<.001; group B P=.004), Xerostomia Inventory (P<.001 and P=.003) and ESSPRI scores (P<.001 and P=.008). Interventional sialendoscopy followed by outpatient intraductal steroid irrigations was more effective than interventional sialendoscopy alone, when pain VAS, Xerostomia Inventory and ESSPRI scores before and after treatment were analysed together using the multivariate Hotelling T2 test (P=.0173).ConclusionsThis pilot study confirms that interventional sialendoscopy with steroid duct irrigation significantly reduces the number of painful episodes of sialadenitis and improves the subjective sensation of oral dryness and other disease symptoms in patients with SS. The study results also suggest that the improvement is greater when interventional sialendoscopy is combined with a cycle of outpatient steroid ductal irrigations. Larger controlled randomised studies are certainly needed to confirm these preliminary data.