bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exposure to fruit-flavoring during adolescence increases nicotine consumption and promotes dose escalation
Authors: Patten Theresa , Dreier Allison , Herman Rae J. , Kimball Bruce A. , De Biasi Mariella 
Published: January 2021

AbstractThe rise of e-cigarette popularity has sparked interest in the role of palatable flavors on nicotine use. Despite growing evidence that sweet flavorants enhance nicotine reward, their influence on nicotine consumption has not been studied extensively. In addition, the impact that flavored nicotine use in adolescence could have on nicotine reward and dependence in adulthood remains unclear. This study examined the role of flavored nicotine access on nicotine preference and consumption longitudinally, from adolescence to adulthood. Male and female adolescent mice preferred a fruit-flavored nicotine solution. However, only adolescent female mice with access to flavored nicotine consumed higher doses. Furthermore, while adolescent male mice escalated consumption of both flavored and unflavored nicotine, female mice only escalated when given access to flavored nicotine. As mice matured into adulthood, there was no evidence that a history of flavored-nicotine access altered preference for unflavored nicotine. However, when the nicotine concentration was reduced, mice that had consumed strawberry-flavored nicotine in adolescence maintained baseline nicotine consumption levels longer than mice that initiated nicotine use without flavor in adolescence. Finally, addition of fruit-flavorants into the nicotine solution during adulthood led to increased levels of nicotine consumption, regardless of previous flavored-nicotine access or of familiarity with the selected flavorant. These results indicate that flavorants increase nicotine consumption independent of life stage, possibly posing a disproportionate risk to adolescent females. Our results also point to an effect of adolescent flavored-nicotine use on nicotine dose maintenance in adulthood, which could have implications for the success of future quit attempts.
Does the punishment fit the crime? Consequences and diagnosis of misspecified detection functions in Bayesian spatial capture-recapture modelling
Authors: Dey Soumen , Bischof Richard , Dupont Pierre P. A. , Milleret Cyril 
Published: January 2021

AbstractSpatial capture-recapture (SCR) is now used widely to estimate wildlife densities. At the core of SCR models lies the detection function, linking individual detection probability to the distance from its latent activity center. The most common function (half-normal) assumes a bivariate normal space use and consequently detection pattern. This is likely an oversimplification and misrepresentation of real-life animal space use patterns, but studies have reported that density estimates are relatively robust to misspecified detection functions. However, information about consequences of such misspecification on space use parameters (e.g. home range area), as well as diagnostic tools to reveal it are lacking.We simulated SCR data under six different detection functions, including the half-normal, to represent a wide range of space use patterns. We then fit three different SCR models, with the three simplest detection functions (half-normal, exponential and half-normal plateau) to each simulated data set. We evaluated the consequences of misspecification in terms of bias, precision and coverage probability of density and home range area estimates. We also calculated Bayesian p-values with respect to different discrepancy metrics to assess whether these can help identify misspecifications of the detection function.We corroborate previous findings that density estimates are robust to misspecifications of the detection function. However, estimates of home range area are prone to bias when the detection function is misspecified. When fitted with the half-normal model, average relative bias of 95% kernel home range area estimates ranged between −25% and 26% depending on the misspecification. In contrast, the half-normal plateau model (an extension of the half-normal) returned average relative bias that ranged between −26% and −4%. Additionally, we found useful heuristic patterns in Bayesianp-values to diagnose the misspecification in detection function.Our analytical framework and diagnostic tools may help users select a detection function when analyzing empirical data, especially when space use parameters (such as home range area) are of interest. We urge development of additional custom goodness of fit diagnostics for Bayesian SCR models to help practitioners identify a wider range of model misspecifications.
High-throughput Identification of Eukaryotic Parasites and Arboviruses in Mosquitoes
Authors: Cannon Matthew V. , Bogale Haikel N. , Bhalerao Devika , Keita Kalil , Camara Denka , Barry Yaya , Keita Moussa , Coulibaly Drissa , Kone Abdoulaye K. , Doumbo Ogobara K. , Thera Mahamadou A. , Plowe Christopher V. , Travassos Mark A. , Irish Seth R. , Yeroshefsky Joshua , Dorothy Jeannine , Prendergast Brian , Laurent Brandyce St. , Fritz Megan L. , Serre David 
Published: January 2021

AbstractVector-borne pathogens cause many human infectious diseases and are responsible for high mortality and morbidity throughout the world. They can also cause livestock epidemics with dramatic social and economic consequences. Due to the high costs, vector-borne disease surveillance is often limited to current threats, and the investigation of emerging pathogens typically occur after the reports of clinical cases. Here, we use high-throughput sequencing to detect and identify a wide range of parasites and viruses carried by mosquitoes from Cambodia, Guinea, Mali and Maryland. We apply this approach to individualAnophelesmosquitoes as well as pools of mosquitoes captured in traps; and compare the outcomes of this assay when applied to DNA or RNA. We identified known human and animal pathogens and mosquito parasites belonging to a wide range of taxa, insect Flaviviruses, and novel DNA sequences from previously uncharacterized organisms. Our results also revealed that analysis of the content of an entire trap is an efficient approach to monitor and identify potential vector-borne pathogens in large surveillance studies, and that analyses of RNA extracted from mosquitoes is preferable, when possible, over DNA-based analyses. Overall, we describe a flexible and easy-to-customize assay that can provide important information for vector-borne disease surveillance and research studies to efficiently complement current approaches.
Hydration-induced structural transitions in biomimetic tandem repeat proteins
Authors: Dubini Romeo C. A. , Jung Huihun , Demirel Melik C. , Rovó Petra 
Published: January 2021

AbstractA major challenge in developing biomimetic, high-performance, and sustainable products is the accurate replication of the biological materials’ striking properties, such as high strength, self-repair, and stimuli-responsiveness. The rationalization of such features on the microscopic scale, together with the rational design of synthetic materials, is currently hindered by our limited understanding of the sequence-structure-property relationship. Here, employing state-of-the-art nuclear magnetic resonance (NMR) spectroscopy, we link the atomistic structural and dynamic properties of an artificial bioinspired tandem repeat protein TR(1,11) to its stunning macroscopic properties including high elasticity, self-healing capabilities, and recordholding proton conductivity amongst biological materials. We show that the hydration-induced structural rearrangement of the amorphous Gly-rich soft segment and the ordered Ala-rich hard segment is the key to the material’s outstanding physical properties. We found that in the hydrated state both the Ala-rich ordered and Gly-rich disordered parts contribute to the formation of the nanoconfinedβ-sheets, thereby enhancing the strength and toughness of the material. This restructuring is accompanied by fast proline ring puckering and backbonecis-transisomerization at the water-protein interface, which in turn enhances the elasticity and the thermal conductivity of the hydrated films. Our in-depth characterization provides a solid ground for the development of next-generation materials with improved properties.
Reticulate Evolutionary History in a Recent Radiation of Montane Grasshoppers Revealed by Genomic Data
Authors: Tonzo Vanina , Bellvert AdriÀ , Ortego Joaquín 
Published: January 2021

AbstractInferring the ecological and evolutionary processes underlying lineage and phenotypic diversification is of paramount importance to shed light on the origin of contemporary patterns of biological diversity. However, reconstructing phylogenetic relationships in recent evolutionary radiations represents a major challenge due to the frequent co-occurrence of incomplete lineage sorting and introgression. In this study, we combined high throughput sequence data (ddRADseq), geometric morphometric information, and novel phylogenetic inference methods that explicitly account for gene flow to infer the evolutionary relationships and the timing and mode of diversification in a complex of Ibero-Maghrebian montane grasshoppers of the subgenusDreuxius(genusOmocestus). Our analyses supported the phenotypic distinctiveness of most sister taxa, two events of historical introgression involving lineages at different stages of the diversification continuum, and the recent Pleistocene origin (< 1 Ma) of the complex. Phylogenetic analyses did not recover the reciprocal monophyly of taxa from Iberia and northwestern Africa, supporting overseas migration between the two continents during the Pleistocene. Collectively, these results indicate that periods of isolation and secondary contact linked to Pleistocene glacial cycles likely contributed to both allopatric speciation and post divergence gene flow in the complex. This study exemplifies how the integration of multiple lines of evidence can help to reconstruct complex histories of reticulated evolution and highlights the important role of Quaternary climatic oscillations as a diversification engine in the Ibero-Maghrebian biodiversity hotspot.
The long-term dynamics of the CA1 spatial code preserve the relative structure of contextual representation
Authors: Keinath Alexandra T. , Mosser Coralie-Anne , Brandon Mark P. 
Published: January 2021

AbstractThe hippocampus is thought to mediate episodic memory through the instantiation and reinstatement of context-specific cognitive maps. However, recent longitudinal experiments have challenged this view, reporting that most hippocampal cells change their tuning properties over days even in the same environment. Often referred to asrepresentational drift, these dynamics raise multiple questions about the representational capacity and content of the hippocampal code. One such question is whether and how these dynamics impact the contextual code. To address this, here we imaged large CA1 populations over more than a month of daily experience as freely behaving mice participated in an extended geometric morph paradigm. We find that long-timescale changes in population activity occurred orthogonally to the representation of context in network space, allowing for consistent readout of contextual information across weeks. Together, these results demonstrate that long-timescale changes to the CA1 spatial code preserve the relative structure of contextual representation.
Protein-Free ribosomal RNA scaffolds can assemble poly-lysine oligos from charged tRNA fragments
Authors: Xu Doris , Wang Yuhong 
Published: January 2021

AbstractRibosomal protein synthesis is a central process of the modern biological world. Because the ribosome contains proteins itself, it is very important to understand its precursor and evolution. Small ribozymes have demonstrated the principle of “RNA world” hypothesis, but protein free peptide ligase remains elusive. In this report, we have identified two fragments in the peptidyl transfer center that can synthesize a 9-mer poly-lysine in a solution contains Mg2+. This result is deduced from isotope-shifting in high resolution MS. To our best knowledge, this is the longest peptide oligo that can be synthesized by a pure ribozyme. Via single molecule FRET experiments, we have demonstrated the ligase mechanism was probably by substrate proximity via dimerization. We prospect that these RNA fragments can be useful to synthesize template free natural and non-natural peptides, to be model system for peptidyl transfer reaction mechanism and can shed light to the evolution of ribosome.Table of Content Graph
The landscape of transcriptional and translational changes over 22 years of bacterial adaptation
Authors: Favate John S. , Liang Shun , Yadavalli Srujana S. , Shah Premal 
Published: January 2021

AbstractOrganisms can adapt to an environment by taking multiple mutational paths. This redundancy at the genetic level, where many mutations have similar phenotypic and fitness effects, can make untangling the molecular mechanisms of complex adaptations difficult. Here we use theE. colilong-term evolution experiment (LTEE) as a model to address this challenge. To bridge the gap between disparate genomic changes and parallel fitness gains, we characterize the landscape of transcriptional and translational changes across 11 replicate populations evolving in parallel for 50,000 generations. By quantifying absolute changes in mRNA abundances, we show that not only do all evolved lines have more mRNAs but that this increase in mRNA abundance scales with cell size. We also find that despite few shared mutations at the genetic level, clones from replicate populations in the LTEE are remarkably similar to each other in their gene expression patterns at both the transcriptional and translational levels. Furthermore, we show that the bulk of the expression changes are due to changes at the transcriptional level with very few translational changes. Finally, we show how mutations in transcriptional regulators lead to consistent and parallel changes in the expression levels of downstream genes, thereby linking genomic changes to parallel fitness gains in the LTEE. These results deepen our understanding of the molecular mechanisms underlying complex adaptations and provide insights into the repeatability of evolution.
A Unified Probabilistic Modeling Framework for Eukaryotic Transcription Based on Nascent RNA Sequencing Data
Authors: Siepel Adam 
Published: January 2021

AbstractNascent RNA sequencing protocols, such as PRO-seq and NET-seq, are now widely used in the study of eukaryotic transcription, and these experimental techniques have given rise to a variety of statistical and machine-learning methods for data analysis. These computational methods, however, are generally designed to address specialized signal-processing or prediction tasks, rather than directly describing the dynamics of RNA polymerases as they move along the DNA template. Here, I introduce a general probabilistic model that describes the kinetics of transcription initiation, elongation, pause release, and termination, as well as the generation of sequencing read counts. I show that this generative model enables estimation of separate pause-release rates, termination rates, and the initiation/elongation rate ratio up to a proportionality constant. Furthermore, if applied to time-course data in a nonequilibrium setting, the model can be used to estimate elongation rates. This model leads naturally to likelihood ratio tests for differences between genes, conditions, or species in various rates of interest. If read counts are assumed to be Poisson-distributed, convenient, closed-form solutions are available for both parameter estimates and likelihood-ratio-test statistics. Straightforward extensions of the model accommodate variability in the pause site and steric hindrance of initiation by paused polymerases. Additional extensions address Bayesian inference under the Poisson model and a generalized linear model that can be used to discover genomic features associated with rates of elongation. Finally, I address technicalities concerning estimation of library size, normalization and sequencing replicates. Altogether, this modeling framework enables a unified treatment of many common tasks in the analysis of nascent RNA sequencing data.
DNA looping by protamine follows a nonuniform spatial distribution
Authors: McMillan Ryan B. , Kuntz Victoria D. , Devenica Luka M. , Bediako Hilary , Carter Ashley R. 
Published: January 2021

ABSTRACTDNA looping plays an important role in cells in both regulating and protecting the genome. Often, studies of looping focus on looping by prokaryotic transcription factors likelacrepressor or by structural maintenance of chromosomes (SMC) proteins such as condensin. Here, however, we are interested in a different looping method whereby multivalent cations (charge≥+3), such as protamine proteins, neutralize the DNA, causing it to form loops and toroids. We considered two previously proposed mechanisms for DNA looping by protamine. In the first mechanism, protamine stabilizes spontaneous DNA fluctuations, forming randomly distributed loops along the DNA. In the second mechanism, protamine binds and bends the DNA to form a loop, creating a distribution of loops that is biased by protamine binding. To differentiate between these mechanisms, we imaged both spontaneous and protamine-induced loops on short-length (≤ 1μm) DNA fragments using atomic force microscopy (AFM). We then compared the spatial distribution of the loops to several model distributions. A random looping model, which describes the mechanism of spontaneous DNA folding, fit the distribution of spontaneous loops, but it did not fit the distribution of protamine-induced loops. Specifically, it overestimated the number of loops that form at the ends of the molecule and failed to predict a peak in the spatial distribution of loops at an intermediate location along the DNA. An electrostatic multibinding model, which was created to mimic the bind-and-bend mechanism of protamine, was a better fit of the distribution of protamine-induced loops. In this model, multiple protamines bind to the DNA electrostatically within a particular region along the DNA to coordinate the formation of a loop. We speculate that these findings will impact our understanding of protamine’sin vivorole for looping DNA into toroids and the mechanism of DNA condensation by multivalent cations more broadly.SIGNIFICANCEDNA looping is important in a variety of bothin vivofunctions (e.g. gene regulation) andin vitroapplications (e.g. DNA origami). Here, we sought a mechanistic understanding of DNA looping by multivalent cations (≥+3), which condense DNA into loops and toroids. One such multivalent cation is the protein protamine, which condenses DNA in sperm. We investigated the mechanism for loop formation by protamine and found that the experimental data was consistent with an electrostatic multibinding model in which two protamines bind electrostatically to the DNA within a 50-nm region to form a loop. This model is likely general to all multivalent cations and may be helpful in applications involving toroid formation or DNA nanoengineering.
An Open-Source Pipeline for Analyzing Changes In Microglial Morphology
Authors: Clarke Devin , Crombag Hans S. , Hall Catherine N. 
Published: January 2021

ABSTRACTChanges in microglial morphology are powerful indicators of the inflammatory state of the brain. Here we provide an open-source microglia morphology analysis pipeline that first cleans and registers images of microglia, before extracting 62 parameters describing microglial morphology. It then compares control and “inflammation” training data and uses dimensionality reduction to generate a single metric of morphological change (an ‘inflammation index’). This index can then be calculated for test data to assess inflammation, as we demonstrate by investigating the effect of short-term high fat diet consumption in heterozygous Cx3CR1-GFP mice, finding no significant effects of diet. Our pipeline represents the first open-source microglia morphology pipeline combining semi-automated image processing and dimensionality reduction. It uses free software (ImageJ and R) and can be applied to a wide variety of experimental paradigms. We anticipate it will enable others to more easily take advantage of the powerful insights microglial morphology analysis provides.
NeurotoxKb: compilation, curation and exploration of a knowledgebase of environmental neurotoxicants specific to mammals
Authors: Ravichandran Janani , Karthikeyan Bagavathy Shanmugam , Singla Palak , Aparna S. R. , Samal Areejit 
Published: January 2021

AbstractExposure to environmental neurotoxicants is a significant concern due to their potential to cause permanent or irreversible damage to the human nervous system. Here, we present the first dedicated knowledgebase, NeurotoxKb, on environmental neurotoxicants specific to mammals. Using a detailed workflow, we have compiled 475 potential non-biogenic neurotoxicants from 835 published studies with evidence of neurotoxicity specific to mammals. A unique feature of NeurotoxKb is the manual curation effort to compile and standardize the observed neurotoxic effects for the potential neurotoxicants from 835 published studies. For the 475 potential neurotoxicants, we have compiled diverse information such as chemical structures, environmental sources, chemical classification, physicochemical properties, molecular descriptors, predicted ADMET properties, and target human genes. To better understand the prospect of human exposure, we have explored the presence of potential neurotoxicants in external exposomes via two different analyses. By analyzing 55 chemical lists representing global regulations and guidelines, we reveal potential neurotoxicants both in regular use and produced in high volume. By analyzing human biospecimens, we reveal potential neurotoxicants detected in them. Lastly, a construction of the chemical similarity network and ensuing analysis revealed the diversity of the toxicological space of 475 potential neurotoxicants. NeurotoxKb is accessible online at:https://cb.imsc.res.in/neurotoxkb/.
DISMIR: a deep learning-based cancer-detection method by integrating DNA sequence and methylation information of individual cell-free DNA reads
Authors: Li Jiaqi , Wei Lei , Zhang Xianglin , Zhang Wei , Wang Haochen , Zhong Bixi , Xie Zhen , Lv Hairong , Wang Xiaowo 
Published: January 2021

ABSTRACTDetecting cancer signals in cell-free DNA (cfDNA) high-throughput sequencing data is emerging as a novel non-invasive cancer detection method. Due to the high cost of sequencing, it is crucial to make robust and precise prediction with low-depth cfDNA sequencing data. Here we propose a novel approach named DISMIR, which can provide ultrasensitive and robust cancer detection by integrating DNA sequence and methylation information in plasma cfDNA whole genome bisulfite sequencing (WGBS) data. DISMIR introduces a new feature termed as “switching region” to define cancer-specific differentially methylated regions, which can enrich the cancer-related signal at read-resolution. DISMIR applies a deep learning model to predict the source of every single read based on its DNA sequence and methylation state, and then predicts the risk that the plasma donor is suffering from cancer. DISMIR exhibited high accuracy and robustness on hepatocellular carcinoma detection by plasma cfDNA WGBS data even at ultra-low sequencing depths. Analysis showed that DISMIR tends to be insensitive to alterations of single CpG sites’ methylation states, which suggests DISMIR could resist to technical noise of WGBS. All these results showed DISMIR with the potential to be a precise and robust method for low-cost early cancer detection.