bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multicellular tumor spheroids- an effectivein vitromodel for understanding drug resistance in head and neck cancer
Authors: Azharuddin Mohammad , Roberg Karin , Dhara Ashis Kumar , Jain Mayur Vilas , D’arcy Padraig , Hinkula Jorma , Slater Nigel K H , Patra Hirak K 
Published: July 2019

AbstractA hallmark of cancer is the ability to develop resistance against therapeutic agents. Therefore, developing effectivein vitrostrategies to identify drug resistance remains of paramount importance for treatment success. A way cancer cells achieve drug resistance is through the expression of efflux pumps that actively pump drugs out of the cells. To date, several studies have investigated the potential of using 3D multicellular tumor spheroids (MCSs) to assess drug resistance; however, a unified system that uses MCSs to differentiate between multi drug resistant (MDR) and non-MDR cells does not exist. In the present report, we have used MCSs obtained from post-diagnosed, pre-treated (PDPT) patient derived head and neck squamous cancer cells that often become treatment resistant, to develop an integrated approach combining clinical drug response and cytotoxicity screening, real-time drug uptake monitoring, and drug transporter activity assessment using flow cytometry in the presence and absence of their respective specific inhibitors. The present report shows a comparative response to MDR, drug efflux capability, and reactive oxygen species (ROS) activity to assess the resistance profile of PDPT patient-derived MCSs and two-dimensional cultures of the same set of cells. We show that MCSs serve as robust and reliable models for the clinical evaluation of drug resistance. Our proposed strategy can thus have potential clinical applicability for profiling drug resistance in cancers with unknown resistance profiles, which consequentially can indicate benefit from downstream therapy.
Histone code dictates fate biasing of neural crest cells to melanocyte lineage
Authors: Raja Desingu Ayyappa , Subramaniam Yogaspoorthi , Gotherwal Vishvabandhu , Tanwar Jyoti , Motiani Rajender , Sivasubbu Sridhar , Gokhale Rajesh S , Natarajan Vivek T 
Published: July 2019

AbstractIn the neural crest lineage, progressive fate-restriction and stem cell assignment are critical for both development and regeneration. While the fate-commitment events have distinct transcriptional footprints, fate-biasing is often transitory and metastable, and is thought to be moulded by epigenetic programs. Hence molecular basis of specification is difficult to define. In this study, we establish a role of a histone variantH2a.z.2in specification of melanocyte lineage from multipotent neural crest cells. Silencing ofH2a.z.2reduces the number of melanocyte precursors in developing zebrafish embryos, and from mouse embryonic stem cellsin vitro. We demonstrate that this histone variant occupies nucleosomes in the promoter of key melanocyte determinantMitf, and enhances its induction. CRISPR-Cas9 based targeted mutagenesis of this gene in zebrafish drastically reduces adult melanocytes, as well as their regeneration. Thereby our study establishes a histone based specification code upstream to the core gene regulatory network in the neural crest lineage of melanocytes. This epigenetic code renders a poised state to the promoter of key determinant and enhances activation by external instructive signals thereby establishing melanocyte fate identity.
The relative impact of evolving pleiotropy and mutational correlation on trait divergence
Authors: Chebib Jobran , Guillaume Frédéric 
Published: July 2019

AbstractBoth pleiotropic connectivity and mutational correlations can restrict the decoupling of traits under divergent selection, but it is unknown which is more important in trait evolution. In order to address this question, we create a model that permits within-population variation in both pleiotropic connectivity and mutational correlation, and compare their relative importance to trait evolution. Specifically, we developed an individual-based, stochastic model where mutations can affect whether a locus affects a trait and the extent of mutational correlations in a population. We find that traits can decouple whether there is evolution in pleiotropic connectivity or mutational correlation but when both can evolve then evolution in pleiotropic connectivity is more likely to allow for decoupling to occur. The most common genotype found in this case is characterized by having one locus that maintains connectivity to all traits and another that loses connectivity to the traits under stabilizing selection (subfunctionalization). This genotype is favoured because it allows the subfunctionalized locus to accumulate greater effect size alleles, contributing to increasingly divergent trait values in the traits under divergent selection without changing the trait values of the other traits (genetic modularization). These results provide evidence that partial subfunctionalization of pleiotropic loci may be a common mechanism of trait decoupling under regimes of corridor selection.
GenEPi: Piezo1-based fluorescent reporter for visualizing mechanical stimuli with high spatiotemporal resolution
Authors: Yaganoglu Sine , Helassa Nordine , Gaub Benjamin M. , Welling Maaike , Shi Jian , Müller Daniel J. , Török Katalin , Pantazis Periklis 
Published: July 2019

AbstractMechanosensing is a ubiquitous process to translate external mechanical stimuli into biological responses during development, homeostasis, and disease. However, non-invasive investigation of cellular mechanosensing in complex and intact live tissue remains challenging. Here, we developed GenEPi, a genetically-encoded fluorescent intensiometric reporter for mechanical stimuli based on Piezo1, an essential mechanosensitive ion channel found in vertebrates. We show that GenEPi has high specificity and spatiotemporal resolution for Piezo1-dependent mechanical stimuli, exemplified by resolving repetitive mechanical stimuli of spontaneously contracting cardiomyocytes within microtissues, in a non-invasive manner.
Potential for transmission ofElizabethkingia anophelisbyAedes albopictusand the role of microbial interactions in Zika virus competence
Authors: Onyango MG , Payne AF , Stout J , Dieme C , Kuo L , Kramer LD , Ciota AT 
Published: July 2019

AbstractElizabethkingia anophelishas been the cause of four outbreaks with significant morbidity and mortality. Its transmission routes remain unknown and no point source of infection has been identified. Here we show thatE. anopheliscan be found in the saliva ofAedesmosquitoes, suggesting the novel possibility of vector-borne transmission of this bacterium. We additionally characterized diverse microbial communities inAedesmidguts, salivary glands and saliva. To the best of our knowledge, this represents the first description of the microbiome ofAedessaliva. Further, we demonstrate that increased abundance ofE. anophelisis associated with decreased susceptibility and replication of Zika virus (ZIKV) in the midgut ofAedesmosquitoes, suggesting a novel transmission barrier for arboviruses transmitted byAedesmosquitoes. Together, these results demonstrate the complex relationships between the mosquito, the midgut microbial community and arboviruses and offer insights into the epidemiology and control of emerging bacterial and viral pathogens.Author SummaryElizabethkingia anophelishas in the recent past caused outbreaks different parts of the world resulting both in morbidity and mortality. Until now, to the best of our knowledge, no study has been able to demonstrate that this bacterium can be transmitted by mosquitoes. We have demonstrated for the first time thatElizabethkingia anophelisis present in the saliva of both infected and non-infectedAedesmosquitoes. Further, we have shown that it confers an inhibitory effect on Zika virus establishment in the midguts ofAedesmosquitoes. Together, these results potentially display the potential for vector borne transmission ofE. anophelisas well as a novel transmission barrier of ZIKV. Lastly, we have for the first time characterized salivary microbes ofAedesmosquitoes necessitating the investigation of the impact of salivary microbes in severity of disease in vertebrate hosts.
Dynamic Ins2 gene activity defines β-cell maturity states
Authors: Chu Chieh Min Jamie , Modi Honey , Skovsø Søs , Ellis Cara , Krentz Nicole A.J. , Zhao Yiwei Bernie , Cen Haoning , Noursadeghi N , Panzhinskiy Evgeniy , Hu Xiaoke , Dionne Derek A. , Xia Yi Han , Xuan Shouhong , Huising Mark O. , Kieffer Timothy J. , Lynn Francis C. , Johnson James D. 
Published: July 2019

AbstractTranscriptional and functional cellular specialization has been described for insulin-secreting β-cells of the endocrine pancreas. However, it is not clear whether β-cell heterogeneity is stable or reflects dynamic cellular states. We investigated the temporal kinetics of endogenous insulin gene activity using live cell imaging, with complementary experiments employing FACS and single cell RNA sequencing, in β-cells from Ins2GFP knock-in mice. In vivo staining and FACS analysis of islets from Ins2GFP mice confirmed that at a given moment, ~25% of β-cells exhibited significantly higher activity at the conserved insulin gene Ins2. Live cell imaging captured Ins2 gene activity dynamics in single β-cells over days. Autocorrelation analysis revealed a subset of cells with oscillating behavior, with mean oscillation periods of 17 hours. Increased glucose concentrations stimulated more cells to oscillate and resulted in higher average Ins2 gene activity per cell. Single cell RNA sequencing showed that Ins2(GFP)HIGH β-cells were enriched for markers of β-cell maturity. Ins2(GFP)HIGH β-cells were also significantly less viable at all glucose concentrations and in the context of ER stress. Collectively, our results demonstrate that the heterogeneity of insulin production, observed in mouse and human β-cells, can be accounted for by dynamic states of insulin gene activity.BlurbPreviously reported pancreatic β-cell heterogeneity reflects β-cell state transitions.
A Comparison of Deep Neural Networks for Seizure Detection in EEG Signals
Authors: Boonyakitanont Poomipat , Lek-uthai Apiwat , Chomtho Krisnachai , Songsiri Jitkomut 
Published: July 2019

AbstractThis paper aims to apply machine learning techniques to an automated epileptic seizure detection using EEG signals to help neurologists in a time-consuming diagnostic process. We employ two approaches based on convolution neural networks (CNNs) and artificial neural networks (ANNs) to provide a probability of seizure occurrence in a windowed EEG recording of 18 channels. In order to extract relevant features based on time, frequency, and time-frequency domains for these networks, we consider an improvement of the Bayesian error rate from a baseline. Features of which the improvement rates are higher than the significant level are considered. These dominant features extracted from all EEG channels are concatenated as the input for ANN with 7 hidden layers, while the input of CNN is taken as raw multi-channel EEG signals. Using multi-concept of deep CNN in image processing, we exploit 2D-filter decomposition to handle the signal in spatial and temporal domains. Our experiments based on CHB-MIT Scalp EEG Database showed that both ANN and CNN were able to perform with the overall accuracy of up to 99.07% and F1-score of up to 77.04%. ANN with dominant features is more capable of detecting seizure events than CNN whereas CNN requiring no feature extraction is slightly better than ANN in classification accuracy.
The role of recombination on genome-wide patterns of local ancestry exemplified by supplemented Brook Charr populations
Authors: Leitwein Maeva , Cayuela Hugo , Ferchaud Anne-Laure , Normandeau Éric , Gagnaire Pierre-Alexandre , Bernatchez Louis 
Published: July 2019

AbstractAssessing the immediate and long-term evolutionary consequences of human-mediated hybridization is of major concern for conservation biology. Several studies have documented how selection in interaction with recombination modulates introgression at a genome-wide scale, but few have considered the dynamics of this process within and between chromosomes. Here, we used an exploited freshwater fish, the Brook Charr (Salvelinus fontinalis) for which decades of stocking practices have resulted in admixture between wild populations and an introduced domestic strain to assess both the temporal dynamics and local chromosomal variation in domestic ancestry. We provide a detailed picture of the domestic ancestry patterns across the genome using about 33,000 mapped SNPs genotyped in 611 individuals from 24 supplemented populations. For each lake, we distinguished early and late-generation hybrids using admixture tracts information. To assess the selective outcomes following admixture we then evaluated the relationship between recombination and admixture proportions at three different scales: the whole genome, chromosomes and within 2Mb windows. This allowed us to detect the signature of varied evolutionary mechanisms, as reflected by the finding of genomic regions where the introgression of domestic haplotypes are favored or disfavored. Among these, the main factor modulating local ancestry was likely the presence of deleterious recessive mutations in the wild populations, which can be efficiently hidden to selection in the presence of long admixture tracts. Overall, our results emphasize the relevance of taking into consideration local ancestry information to assess both the temporal and chromosomal variation in local ancestry toward better understanding post-hybridization evolutionary outcomes.
Adult-born hippocampal neurons undergo extended development and are morphologically distinct from neonatally-born neurons
Authors: Cole John Darby , Espinueva Delane , Seib Désirée R. , Ash Alyssa M. , Cooke Matthew B. , Cahill Shaina P. , O’Leary Timothy , Kwan Sharon S. , Snyder Jason S. 
Published: July 2019

ABSTRACTDuring immature stages, adult-born neurons pass through critical periods for survival and plasticity. It is generally assumed that by 2 months of age adult-born neurons are mature and equivalent to the broader neuronal population, raising questions of how they might contribute to hippocampal function in old age when neurogenesis has declined. However, few have examined adult-born neurons beyond the critical period, or directly compared them to neurons born in infancy. Here, we used a retrovirus to visualize functionally-relevant morphological features of 2- to 24-week-old adult-born neurons in male rats. From 2-7 weeks neurons grew and attained a relatively mature phenotype. However, several features of 7-week-old neurons suggested a later wave of growth: these neurons had larger nuclei, thicker dendrites and more dendritic filopodia than all other groups. Indeed, between 7-24 weeks, adult-born neurons gained additional dendritic branches, grew a 2ndprimary dendrite, acquired more mushroom spines and had enlarged mossy fiber presynaptic terminals. Compared to neonatally-born neurons, old adult-born neurons had greater spine density, larger presynaptic terminals, and more putative efferent filopodial contacts onto inhibitory neurons. By integrating rates of cell birth and growth across the lifespan, we estimate that adult neurogenesis ultimately produces half of the cells and the majority of spines in the dentate gyrus. Critically, protracted development contributes to the plasticity of the hippocampus through to the end of life, even after cell production declines. Persistent differences from neonatally-born neurons may additionally endow adult-born neurons with unique functions even after they have matured.SIGNIFICANCE STATEMENTNeurogenesis occurs in the hippocampus throughout adult life and contributes to memory and emotion. It is generally assumed that new neurons have the greatest impact on behavior when they are immature and plastic. However, since neurogenesis declines dramatically with age, it is unclear how they might contribute to behavior later in life when cell proliferation has slowed. Here we find that newborn neurons mature over many months in rats, and end up with distinct morphological features compared to neurons born in infancy. Using a mathematical model, we estimate that a large fraction of neurons is added in adulthood. Moreover, their extended growth produces a reserve of plasticity that persists even after neurogenesis has declined to low rates.
A Comprehensive Evaluation of Methods for Mendelian Randomization Using Realistic Simulations and an Analysis of 38 Biomarkers for Risk of Type-2 Diabetes
Authors: Qi Guanghao , Chatterjee Nilanjan 
Published: July 2019

AbstractBackgroundMendelian randomization (MR) has provided major opportunities for understanding the causal relationship among complex traits. Previous studies have often evaluated MR methods based on simulations that do not adequately reflect the data-generating mechanism in GWAS and there are often discrepancies in performance of MR methods in simulations and real datasets.MethodsWe use a simulation framework that generates data on full GWAS for two traits under realistic model for effect-size distribution coherent with heritability, co-heritability and polygenicity typically observed for complex traits. We further use recent data generated from GWAS of 38 biomarkers in the UK Biobank to investigate their causal effects on risk of type-2 diabetes using externally available GWAS summary-statistics.ResultsSimulation studies show that weighted mode and MRMix are the only two methods which maintain correct type-I error rate in a diverse set of scenarios. Between the two methods, MRMix tends to be more powerful for larger GWAS while the opposite being true for smaller sample sizes. Among the other methods, random-effect IVW, MR-Robust and MR-RAPS tend to perform best in maintaining low mean squared error when the InSIDE assumption is satisfied, but can produce large bias when InSIDE is violated. In real data analysis, some biomarkers showed major heterogeneity in estimates of their causal effects on risk of type-2 diabetes across the different methods, with patterns similar to those observed in simulation studies.ConclusionsRelative performance of different MR methods depends heavily on sample sizes of underlying GWAS, proportion of valid instruments and validity of the InSIDE assumption.Key MessagesMany previous simulations studies to evaluate Mendelian randomization methods do not adequately reflect the data-generating mechanism of genome-wide association studies (GWAS).We use a simulation framework that generates data on full GWASs under realistic model informed by recent studies on effect-size distribution. We also used very recent GWAS data available on a large number of biomarkers to evaluate their causal effect on type-2 diabetes using alternative methods.Among the 10 methods that were compared, relative performance of different methods depends heavily on sample sizes of underlying GWAS, proportion of valid instruments and validity of the InSIDE assumption.Weighted mode and MRMix are the only two methods that maintain correct type I error rate in a diverse set of scenarios.
An implicit lipid model for efficient reaction-diffusion simulations of protein binding to surfaces of arbitrary topology
Authors: Fu Yiben , Yogurtcu Osman N. , Kothari Ruchita , Thorkelsdottir Gudrun , Sodt Alexander J. , Johnson Margaret E. 
Published: July 2019

AbstractLocalization of proteins to a membrane is an essential step in a broad range of biological processes such as signaling, virion formation, and clathrin-mediated endocytosis. The strength and specificity of proteins binding to a membrane depend on the lipid composition. Single-particle reaction-diffusion methods offer a powerful tool for capturing lipid-specific binding to membrane surfaces by treating lipids explicitly as individual diffusible binding sites. However, modeling lipid particle populations is expensive. Here we present an algorithm for reversible binding of proteins to continuum surfaces with implicit lipids, providing dramatic speed-ups to many body simulations. Our algorithm can be readily integrated into most reaction-diffusion software packages. We characterize changes to kinetics that emerge from explicit versus implicit lipids as well as surface adsorption models, showing excellent agreement between our method and the full explicit lipid model. Compared to models of surface adsorption, which couple together binding affinity and lipid concentration, our implicit lipid model decouples them to provide more flexibility for controlling surface binding properties and lipid inhomogeneity, and thus reproducing binding kinetics and equilibria. Crucially, we demonstrate our method’s application to membranes of arbitrary curvature and topology, modeled via a subdivision limit surface, again showing excellent agreement with explicit lipid simulations. Unlike adsorption models, our method retains the ability to bind lipids after proteins are localized to the surface (through e.g. a protein-protein interaction), which can greatly increase stability of multi-protein complexes on the surface. Our method will enable efficient cell-scale simulations involving proteins localizing to realistic membrane models, which is a critical step for predictive modeling and quantification of in vitro and in vivo dynamics.
Improved identification and differentiation from epileptiform activity of human hippocampal sharpwave-ripples during NREM sleep
Authors: Jiang Xi , Gonzalez-Martinez Jorge , Cash Sydney S. , Chauvel Patrick , Gale John , Halgren Eric 
Published: July 2019

AbstractIn rodents, pyramidal cell firing patterns from waking may be replayed in NREM sleep during hippocampal sharpwave-ripples (HC-SWR). In humans, HC-SWR have only been recorded with electrodes implanted to localize epileptogenesis. Here, we characterize human HC-SWR with rigorous rejection of epileptiform activity, requiring multiple oscillations and coordinated sharpwaves. We demonstrated typical SWR in those rare HC recordings which lack interictal epileptiform spikes (IIS), and with no or minimal seizure involvement. These HC-SWR have a similar rate (~12/min) and apparent intra-HC topography (ripple maximum in putative stratum pyramidale, slow wave in radiatum) as rodents, though with lower frequency (~85Hz compared to ~140Hz in rodents). Similar SWR are found in HC with IIS, but no significant seizure involvement. These SWR were modulated by behavior, being largely absent (<2/min) except during NREM sleep in both stage 2 (~9/min) and stage 3 (~15/min), distinguishing them from IIS. This study quantifies the basic characteristics of a strictly selected sample of SWR recorded in relatively healthy human hippocampi.