bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Molecular Clock in the Evolution of Protein Structures
Authors: Pascual-García Alberto , Arenas Miguel , Bastolla Ugo 
Published: April 2019

AbstractThe molecular clock hypothesis, which states that substitutions accumulate in protein sequences at a constant rate, plays a fundamental role in molecular evolution but it is violated when selective or mutational processes vary with time. Such violations of the molecular clock have been widely investigated for protein sequences, but not yet for protein structures. Here, we introduce a novel statistical test (Significant Clock Violations) and perform a large scale assessment of the molecular clock in the evolution of both protein sequences and structures in three large superfamilies. After validating our method with computer simulations, we find that clock violations are generally consistent in sequence and structure evolution, but they tend to be larger and more significant in structure evolution. Moreover, changes of function assessed through Gene Ontology and InterPro terms are associated with large and significant clock violations in structure evolution. We found that almost one third of significant clock violations are significant in structure evolution but not in sequence evolution, highlighting the advantage to use structure information for assessing accelerated evolution and gathering hints of positive selection. Clock violations between closely related pairs are frequently significant in sequence evolution, consistent with the observed time dependence of the substitution rate attributed to segregation of neutral and slightly deleterious polymorphisms, but not in structure evolution, suggesting that these substitutions do not affect protein structure although they may affect stability. These results are consistent with the view that natural selection, both negative and positive, constrains more strongly protein structures than protein sequences. Our code for computing clock violations is freely available at https://github.com/ugobas/Molecular_clock.
A Novel Open Access Web Portal for Integrating Mechanistic and Toxicogenomic Study Results
Authors: Sutherland Jeffrey J , Stevens James L , Johnson Kamin , Elango Navin , Webster Yue W , Mills Bradley J , Robertson Daniel H 
Published: April 2019

Abstract
Applying toxicogenomics to improving the safety profile of drug candidates and crop protection molecules is most useful when it identifies relevant biological and mechanistic information that highlights risks and informs risk mitigation strategies. Pathway-based approaches, such as gene set enrichment analysis, integrate toxicogenomic data with known biological process and pathways. Network methods help define unknown biological processes and offer data reduction advantages. Integrating the 2 approaches would improve interpretation of toxicogenomic information. Barriers to the routine application of these methods in genome-wide transcriptomic studies include a need for “hands-on” computer programming experience, the selection of 1 or more analysis methods (eg pathway analysis methods), the sensitivity of results to algorithm parameters, and challenges in linking differential gene expression to variation in safety outcomes. To facilitate adoption and reproducibility of gene expression analysis in safety studies, we have developed Collaborative Toxicogeomics, an open-access integrated web portal using the Django web framework. The software, developed with the Python programming language, is modular, extensible and implements “best-practice” methods in computational biology. New study results are compared with over 4000 rodent liver experiments from Drug Matrix and open TG-GATEs. A unique feature of the software is the ability to integrate clinical chemistry and histopathology-derived outcomes with results from gene expression studies, leading to relevant mechanistic conclusions. We describe its application by analyzing the effects of several toxicants on liver gene expression and exemplify application to predicting toxicity study outcomes upon chronic treatment from expression changes in acute-duration studies.
Stem cell delivery to kidney via minimally invasive ultrasound-guided renal artery injection in mice
Authors: Thin May Zaw , Ogunldade Olumide , Comenge Joan , Patrick P. Stephen , Stuckey Daniel J. , L.David Anna , Lévy Raphaël , Lythgoe Mark F. , Beard Paul , Kalber Tammy L. 
Published: April 2019

AbstractCell-based therapies are promising treatments for various kidney diseases. However, the major hurdle in initiating therapeutic responses is the inefficiency of injection routes to deliver cells to the kidney parenchyma. Systemic injection, such as intravenous injection only delivers a small proportion of cells to the kidney. Whereas direct delivery, such as renal artery injection require surgical procedures. A minimally invasive renal artery injection was therefore developed to enhance cell delivery to kidney. In this study, luciferase expressing human adipocyte derived stem cells (ADSC) were labelled with gold nanorods (GNR) and injected into the renal artery using ultrasound guidance. The ADSCs were tracked using bioluminescence and photoacoustic imaging serially over 7 days. Imaging confirmed that the majority of signal was within the kidney, indicative of successful injection and that signal remained stable for 3 days. Histology showed co-localization of GNRs with ADSC staining throughout the kidney with no indication of injury caused by injection. These findings demonstrate that ultrasound-guided renal artery injection is feasible in mice and can successfully deliver a large proportion of cells which are retained within the kidney for 3 days. Therefore, the techniques developed here will be useful for optimising cell therapy in kidney diseases.
Predicting the short-term success of human influenza A variants with machine learning
Authors: Hayati Maryam , Biller Priscila , Colijn Caroline 
Published: April 2019

AbstractSeasonal influenza viruses are constantly changing, and produce a different set of circulating strains each season. Small genetic changes can accumulate over time and result in antigenically different viruses; this may prevent the body’s immune system from recognizing those viruses. Due to rapid mutations, in particular in the hemagglutinin gene, seasonal influenza vaccines must be updated frequently. This requires choosing strains to include in the updates to maximize the vaccines’ benefits, according to estimates of which strains will be circulating in upcoming seasons. This is a challenging prediction task. In this paper we use longitudinally sampled phylogenetic trees based on hemagglutinin sequences from human influenza viruses, together with counts of epitope site polymorphisms in hemagglutinin, to predict which influenza virus strains are likely to be successful. We extract small groups of taxa (subtrees) and use a suite of features of these subtrees as key inputs to the machine learning tools. Using a range of training and testing strategies, including training on H3N2 and testing on H1N1, we find that successful prediction of future expansion of small subtrees is possible from these data, with accuracies of 0.71-0.85 and a classifier ‘area under the curve’ (AUC) 0.75-0.9.
Simulation of multiple microenvironments shows a putative role of RPTPs on the control of Epithelial-to-Mesenchymal Transition
Authors: Pais Ricardo Jorge 
Published: April 2019

AbstractEpithelial-to-Mesenchymal Transition (EMT) together with Mesenchymal-to-Epithelial Transition (MET) are two natural processes thought to participate in the process of metastasis. Multiple signals from the microenvironment have been reported to drive EMT. However, microenvironment signals that control EMT and promote MET are still unknown. Here, we analysed a regulatory network of EMT involving 8 microenvironment signals to evaluate the role of cell contact signals on the switching between Epithelial and Mesenchymal-like phenotypes. The results demonstrated that RPTP activation by cell contacts have the potential to control EMT and promote MET in the presence of 5 EMT driving signals under physiological scenarios. These simulations also showed that hypoxia inhibits the RPTPs capacity of controlling EMT. In this case, FAT4 activation by cell contacts functions as an alternative control mechanism of EMT except under chronic inflammation, providing a theoretical explanation for the observed correlation between hypoxia and metastasis under chronic inflammation. Taken together, we propose here a natural control mechanism of EMT that supports the idea that this process is tightly regulated by the microenvironment.HighlightsCell contact dependent RPTP inhibit EMT and triggers MET in the presence of 5 EMT driving signals in silico.A proposed molecular mechanism for the control of EMT by cell contact dependent RPTPs.A proposed explanation for the observed MET in vitro and the correlation between hypoxia and metastasis in vivo.
The number sense is an emergent property of a deep convolutional neural network trained for object recognition
Authors: DeWind Nicholas K. 
Published: April 2019

SummaryHumans and many non-human animals have the “number sense,” an ability to estimate the number of items in a set without counting. This innate sense of number is hypothesized to provide a foundation for more complex numerical and mathematical concepts. Here I investigated whether we also share the number sense with a deep convolutional neural network (DCNN) trained for object recognition. These in silico networks have revolutionized machine learning over the last seven years, allowing computers to reach human-level performance on object recognition tasks for the first time. Their architecture is based on the structure of mammalian visual cortex, and after they are trained, they provide a highly predictive model of responses in primate visual cortex, suggesting deep homologies. I found that the DCNN demonstrates three key hallmarks of the number sense: numerosity-selective units (analogous to biological neurons), the behavioral ratio effect, and ordinality over representational space. Because the DCNN was not trained to enumerate, I conclude that the number sense is an emergent property of the network, the result of some combination of the network architecture and the constraint to develop the complex representational structure necessary for object recognition. By analogy I conclude that the number sense in animals was not necessarily the result of direct selective pressure to enumerate but might have “come for free” with the evolution of a complex visual system that evolved to identify objects and scenes in the real world.
PyRanges: efficient comparison of genomic intervals in Python
Authors: Stovner Endre Bakken , Sætrom Pål 
Published: April 2019

AbstractSummaryComplex genomic analyses often use sequences of simple set operations like intersection, overlap, and nearest on genomic intervals. These operations, coupled with some custom programming, allow a wide range of analyses to be performed. To this end, we have written PyRanges, a data structure for representing and manipulating genomic intervals and their associated data in Python. Run single-threaded on binary set operations, PyRanges is in median 2.3-9.6 times faster than the popular R GenomicRanges library and is equally memory efficient; run multi-threaded on 8 cores, our library is up to 123 times faster. PyRanges is therefore ideally suited both for individual analyses and as a foundation for future genomic libraries in Python.AvailabilityPyRanges is available open-source under the MIT license at https://github.com/biocore-NTNU/pyranges and documentation exists at https://biocore-NTNU.github.io/pyranges/Contactendrebak85@gmail.comSupplementary informationSupplementary data are available.
The pace of life: Time, temperature, and a biological theory of relativity
Authors: Neuheimer Anna B. 
Published: April 2019

AbstractFor living things, time proceeds relative to body temperature. In this contribution, I describe the biochemical underpinnings of this “biological time” and formalize the Biological Theory of Relativity (BTR). Paralleling Einstein’s Special Theory of Relativity, the BTR describes how time progresses across temporal frames of reference, contrasting temperature-scaled biological time with our more familiar (and constant) “calendar” time measures. By characterizing the relationship between these two time frames, the BTR allows us to position observed biological variability on a relevant time-scale. In so doing, we are better able to explain observed variation (both temperature-dependent and -independent), make predictions about the timing of biological phenomena, and even manipulate the biological world around us. The BTR presents a theoretical framework to direct future work regarding an entire landscape of fundamental biological questions across space, time and species.
Presynaptic MAST Kinase Controls Bidirectional Post-Synaptic Responses to Convey Stimulus Valence in C. elegans
Authors: Nakano Shunji , Ikeda Muneki , Tsukada Yuki , Fei Xianfeng , Suzuki Takamasa , Ahluwalia Rhea , Sano Ayana , Kondo Rumi , Ihara Kunio , Hashimoto Koichi , Higashiyama Tetsuya , Mori Ikue 
Published: April 2019

AbstractPresynaptic plasticity is known to modulate the strength of synaptic transmission. However, it remains unknown whether regulation in presynaptic neurons alters the directionality –positive or negative-of postsynaptic responses. We report here that the C. elegans homologs of MAST kinase, Stomatin and Diacylglycerol kinase act in a thermosensory neuron to elicit in its postsynaptic neuron an excitatory or inhibitory response that correlates with the valence of thermal stimuli. By monitoring neural activity of the valence-coding interneuron in freely behaving animals, we show that the alteration between excitatory and inhibitory responses of the interneuron is mediated by controlling the balance of two opposing signals released from the presynaptic neuron. These alternative transmissions further generate opposing behavioral outputs necessary for the navigation on thermal gradients. Our findings reveal the previously unrecognized capability of presynaptic regulation to evoke bidirectional postsynaptic responses and suggest a molecular mechanism of determining stimulus valence.
Understanding requires tracking: noise and knowledge interact in bilingual comprehension
Authors: Blanco-Elorrieta Esti , Ding Nai , Pylkkänen Liina , Poeppel David 
Published: April 2019

AbstractUnderstanding speech in noise is a fundamental challenge for speech comprehension. This perceptual demand is amplified in a second language: it is a common experience in bars, train stations, and other noisy environments that degraded signal quality severely compromises second language comprehension. Through a novel design, paired with a carefully selected participant profile, we independently assessed signal-driven and knowledge-driven contributions to the brain bases of first versus second language processing. We were able to dissociate the neural processes driven by the speech signal from the processes that come from speakers’ knowledge of their first versus second languages. The neurophysiological data show that in combination with impaired access to top-down linguistic information in the second language, the locus of bilinguals’ difficulty in understanding second language speech in noisy conditions arises from a failure to successfully perform a basic, low-level process: cortical entrainment to speech signals above the syllabic level.Significance statementOver half of the world’s population is multilingual. Although proficiency in a second language improves over time, even to the point of reaching native-like proficiency, one persistent difficulty is understanding a second language in noisy environments (e.g. in crowds, train stations, etc.). We examined this processing impairment using a novel frequency-tagging paradigm with magnetoencephalography (MEG). We found that the reason underlying bilinguals’ difficulty in understanding second language speech in noisy conditions is induced by a failure to neurally track the operations reflecting structure (i.e., phrase) building.
Optimizing genomic prediction of host resistance to koi herpesvirus disease in carp
Authors: Palaiokostas Christos , Vesely Tomas , Kocour Martin , Prchal Martin , Pokorova Dagmar , Piackova Veronika , Pojezdal Lubomir , Houston Ross D. 
Published: April 2019

AbstractGenomic selection (GS) is increasingly applied in breeding programmes of major aquaculture species, enabling improved prediction accuracy and genetic gain compared to pedigree-based approaches. Koi Herpesvirus disease (KHVD) is notifiable by the World Organisation for Animal Health and the European Union, causing major economic losses to carp production. Genomic selection has potential to breed carp with improved resistance to KHVD, thereby contributing to disease control. In the current study, Restriction-site Associated DNA sequencing (RAD-seq) was applied on a population of 1,425 common carp juveniles which had been challenged with Koi herpes virus, followed by sampling of survivors and mortalities. Genomic selection (GS) was tested on a wide range of scenarios by varying both SNP densities and the genetic relationships between training and validation sets. The accuracy of correctly identifying KHVD resistant animals using genomic selection was between 8 and 18 % higher than pedigree best linear unbiased predictor (pBLUP) depending on the tested scenario. Furthermore, minor decreases in prediction accuracy were observed with decreased SNP density. However, the genetic relationship between the training and validation sets was a key factor in the efficacy of genomic prediction of KHVD resistance in carp, with substantially lower prediction accuracy when the relationships between the training and validation sets did not contain close relatives.
Upscaling of Microbial Electrolysis Cell Integrating Microbial Electrosynthesis: Insights, Challenges and Perspectives
Authors: Tian Jiang-Hao , Lacroix Rémy , Quéméner Elie Desmond-Le , Bureau Chrystelle , Midoux Cédric , Bouchez Théodore 
Published: April 2019

AbstractRecent development of microbial electrochemical technologies has allowed microbial electrosynthesis (MES) of organic molecules with microbial electrolysis cell treating waste organic matter. An electrolytic cell with a MES cathode (ME-ME cell) can produce soluble organic molecules with higher market price than biomethane, and thus satisfy both economic and environmental interest. However, the sustainability of bioanode activity could become a major concern. In this work, a 15-liter ME-ME reactor was designed with specific electrode configurations. An electrochemical model was established to assess the feasibility and possible performance of the design, considering the “aging” effect of the bioanode. The reactor was then built and operated for performance evaluation as well as bioanode regeneration assay. Biowaste from an industrial deconditioning platform was used as substrate for bioanode. The COD removal rate in the anodic chamber reached 0.83 g day-1 L-1 of anolyte and the anodic coulombic efficiency reached 98.6%. Acetate was produced with a rate of 0.53 g day-1 L-1 of catholyte, reaching a maximum concentration of 8.3 g L-1. A potential difference was applied between the bioanode and biocathode independent of reference electrodes. The active biocathode was dominated by members of the Genus Pseudomonas, rarely reported so far for MES activity.
Developmentally regulated Shh expression is robust to TAD perturbations
Authors: Williamson Iain , Kane Lauren , Devenney Paul S. , Anderson Eve , Kilanowski Fiona , Hill Robert E. , Bickmore Wendy A. , Lettice Laura A. 
Published: April 2019

AbstractTopologically Associating Domains (TADs) have been proposed to both guide and constrain enhancer activity. Shh is located within a TAD known to contain all its enhancers. To investigate the importance of chromatin conformation and TAD integrity on developmental gene regulation, we have manipulated the Shh TAD – creating internal deletions, deleting CTCF sites including those at TAD boundaries, as well as larger deletions and inversions of TAD boundaries. Chromosome conformation capture and fluorescence in situ hybridisation assays were used the investigate changes in chromatin conformation that result from these manipulations. Our data suggest that the substantial alteration of TAD structure has no readily detectable effect on Shh expression patterns during development – except where enhancers are deleted - and results in no detectable phenotypes. Only in the case of a larger deletion of one TAD boundary could some ectopic influence of the Shh limb enhancer be detected on a gene - Mnx1 in the neighbouring TAD. Our data suggests that, contrary to expectations, the developmental regulation of Shh expression is remarkably robust to TAD perturbations.
Progress toward the identification and stacking of crucial domestication traits in pennycress
Authors: Chopra Ratan , Johnson Evan B. , Emenecker Ryan , Cahoon Edgar B. , Lyons Joe , Kliebenstein Daniel J. , Daniels Erin , Dorn Kevin M. , Esfahanian Maliheh , Folstad Nicole , Frels Katherine , McGinn Michaela , Ott Matthew , Gallaher Cynthia , Altendorf Kayla , Berroyer Alexandra , Ismail Baraem , Anderson James A. , Wyse Donald L. , Umaslov Tim , Sedbrook John C. , Marks M. David 
Published: April 2019

AbstractThe oilseed speciesThlaspi arvense(pennycress) is being domesticated as a new crop that can provide both important ecosystem services and intensify farmland output. Through the use of high throughput sequencing and phenotyping, along with classical mutagenesis key traits needed for pennycress domestication have been identified. Domestication traits identified herein include reduced pod shatter, early maturity, reduced seed glucosinolate levels, and improved oil fatty acid content. By taking advantage of pennycress’ close genetic relationship withArabidopsis thaliana, the causative mutations responsible for each of these traits have been identified. These mutations have been used to develop molecular markers to begin to stack the traits into individual lines.