bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predicting Environmental Chemical Carcinogenicity using a Hybrid Machine-Learning Approach
Authors: Limbu Sarita , Dakshanamurthy Sivanesan 
Published: May 2021

ABSTRACTDetermining environmental chemical carcinogenicity is an urgent need as humans are increasingly exposed to these chemicals. In this study, we determined the carcinogenicity of wide variety real-life exposure chemicals in large scale. To determine chemical carcinogenicity, we have developed carcinogenicity prediction models based on the hybrid neural network (HNN) architecture. In the HNN model, we included new SMILES feature representation method, by modifying our previous 3D array representation of 1D SMILES simulated by the convolutional neural network (CNN). We used 653 molecular descriptors modeled by feed forward neural network (FFNN), and SMILES as chemical features to train the models. We have developed three types of machine learning models: binary classification models to predict chemical is a carcinogenic or non-carcinogenic, multiclass classification models to predict severity of the chemical carcinogenicity, and regression models to predict median toxic dose of the chemicals. Along with the hybrid neural network (HNN) model that we developed, Random Forest (RF), Bootstrap Aggregating (Bagging) and Adaptive Boosting (AdaBoost) methods were also used for binary and multiclass classification. Regression models were developed using HNN, RF, Support Vector Regressor (SVR), Gradient Boosting (GB), Kernel Ridge (KR), Decision Tree with AdaBoost (DT), KNeighbors (KN), and a consensus method. For binary classification, our HNN model predicted with an average accuracy of 74.33% and an average AUC of 0.806, for multiclass classification, the HNN model predicted with an average accuracy of 50.58% and an average micro-AUC of 0.68, and for regression model, the consensus method achieved R2of 0.40. The predictive performance of our models based on a highly diverse chemicals is comparable to the literature reported models that included the similar and less diverse molecules. Our models can be used in identifying the potentially carcinogenic chemicals for a wide variety of chemical classes.
Digital 3D Brain MRI Arterial Territories Atlas
Authors: Liu Chin-Fu , Hsu Johnny , Xu Xin , Kim Ganghyun , Sheppard Shannon M. , Meier Erin L. , Miller Michael I. , Hillis Argye E. , Faria Andreia V. 
Published: May 2021

ABSTRACTThe locus and extent of brain damage in the event of vascular insult can be quantitatively established quickly and easily with vascular atlases. Although highly anticipated by clinicians and clinical researchers, no digital MRI arterial atlas is readily available for automated data analyses. We created a digital arterial territory atlas based on lesion distributions in 1,298 patients with acute stroke. The lesions were manually traced in the diffusion-weighted MRIs, binary stroke masks were mapped to a common space, probability maps of lesions were generated and the boundaries for each arterial territory was defined based on the ratio between probabilistic maps. The atlas contains the definition of four major supra- and infra-tentorial arterial territories: Anterior, Middle, Posterior Cerebral Arteries and Vertebro-Basilar, and sub-territories (thalamoperforating, lenticulostriate, basilar and cerebellar arterial territories), in two hierarchical levels. This study provides the first publicly-available, digital, 3D deformable atlas of arterial brain territories, which may serve as a valuable resource for large-scale, reproducible processing and analysis of brain MRIs of patients with stroke and other conditions.
Gain control by sparse, ultra-slow glycinergic synapses
Authors: Jain Varsha , Hanson Laura , Sethuramanujam Santhosh , Gregg Ronald G. , Zhang Chi , Smith Robert G. , Berson David , McCall Maureen A. , Awatramani Gautam B. 
Published: May 2021

SummaryRetinal ON starburst amacrine cells (SACs) play a critical role in computing stimulus direction, partly in service of image stabilization by optokinetic nystagmus. ON SAC responses are sculpted by rich GABAergic innervation, mostly from neighbouring SACs. Surprisingly, however, we find that glycinergic narrow field amacrine cells (NACs) serve as their dominant source of inhibition during sustained activity. Although NAC inputs constitute only ∼5% of inhibitory synapses to ON SACs, their distinct input patterns enable them to drive glycine inhibition during the both light increments and decrements. NAC-to-ON-SAC inhibition appears to be mediated by ultra-slow non-canonical glycine receptors containing the α4 subunit, which effectively summate during repetitive stimulation. Glycinergic inhibition strongly decreases the output gain of the SACs, ensuring that their direction-selective output is maintained over their operating range. These results reveal an unexpected role for glycinergic pathways and receptor kinetics in modulating direction selectivity in the retina.
Recovering mixtures of fast diffusing states from short single particle trajectories
Authors: Heckert Alec , Dahal Liza , Tjian Robert , Darzacq Xavier 
Published: May 2021

AbstractSingle particle tracking (SPT) directly measures the dynamics of proteins in living cells and is a powerful tool to dissect molecular mechanisms of cellular regulation. Interpretation of SPT with fast-diffusing proteins in mammalian cells, however, is complicated by technical limitations imposed by fast image acquisition. These limitations include short trajectory length due to photobleaching and shallow depth of field, high localization error due to the low photon budget imposed by short integration times, and cell-to-cell variability. To address these issues, we developed methods to infer distributions of diffusion coefficients from SPT data with short trajectories, variable localization accuracy, and absence of prior knowledge about the number of underlying states. We discuss advantages and disadvantages of these approaches relative to other frameworks for SPT analysis.Significance statementSingle particle tracking (SPT) uses fluorescent probes to track the motions of individual molecules inside living cells, providing biologists with a close view of the cell’s inner machinery at work. Commonly used SPT imaging approaches, however, result in fragmentation of trajectories into small pieces as the probes move through the microscope’s plane of focus. This makes it challenging to extract usable biological information. This paper describes a method to reconstruct an SPT target’s dynamic profile from these trajectory fragments. The method builds on previous approaches to provide information about challenging SPT targets without discrete dynamic states while accounting for some known biases, enabling observation of previously hidden features in mammalian SPT experiments.
Benchmark of data processing methods and machine learning models for gut microbiome-based diagnosis of inflammatory bowel disease
Authors: Kubinski Ryszard , Djamen-Kepaou Jean-Yves , Zhanabaev Timur , Hernandez-Garcia Alex , Bauer Stefan , Hildebrand Falk , Korcsmaros Tamas , Karam Sani , Jantchou Prévost , Kafi Kamran , Martin Ryan D. 
Published: May 2021

AbstractBackgroundInflammatory bowel disease (IBD) patients wait months and undergo numerous invasive procedures between the initial appearance of symptoms and receiving a diagnosis. In order to reduce time until diagnosis and improve patient wellbeing, machine learning algorithms capable of diagnosing IBD from the gut microbiome’s composition are currently being explored. To date, these models have had limited clinical application due to decreased performance when applied to a new cohort of patient samples. Various methods have been developed to analyze microbiome data which may improve the generalizability of machine learning IBD diagnostic tests. With an abundance of methods, there is a need to benchmark the performance and generalizability of various machine learning pipelines (from data processing to training a machine learning model) for microbiome-based IBD diagnostic tools.ResultsWe collected fifteen 16S rRNA microbiome datasets (7707 samples) from North America to benchmark combinations of gut microbiome features, data normalization methods, batch effect reduction methods, and machine learning models. Pipeline generalizability to new cohorts of patients was evaluated with four binary classification metrics following leave-one dataset-out cross validation, where all samples from one study were left out of the training set and tested upon. We demonstrate that taxonomic features obtained from QIIME2 lead to better classification of samples from IBD patients than inferred functional features obtained from PICRUSt2. In addition, machine learning models that identify non-linear decision boundaries between labels are more generalizable than those that are linearly constrained. Prior to training a non-linear machine learning model on taxonomic features, it is important to apply a compositional normalization method and remove batch effects with the naive zero-centering method. Lastly, we illustrate the importance of generating a curated training dataset to ensure similar performance across patient demographics.ConclusionsThese findings will help improve the generalizability of machine learning models as we move towards non-invasive diagnostic and disease management tools for patients with IBD.
Ablation ofmpeg+ macrophages exacerbatesmfrp-related hyperopia
Authors: Brandt Zachary J. , Collery Ross F , Besharse Joseph C , Link Brian A. 
Published: May 2021

ABSTRACTPURPOSEProper refractive development of the eye, termed emmetropization, is critical for focused vision and impacted by both genetic determinants and several visual environment factors. Improper emmetropization caused by genetic variants can lead to congenital hyperopia, which is characterized by small eyes and relatively short ocular axial length. To date variants in only four genes have been firmly associated with human hyperopia, one of which isMFRP. Zebrafishmfrpmutants also have hyperopia and similar to reports in mice, exhibit increased macrophage recruitment to the retina. The goal of this research was to examine the effects of macrophage ablation on emmetropization andmfrp-related hyperopia.METHODSWe utilized a chemically inducible, cell-specific ablation system to deplete macrophages in both wild-type andmfrpmutant zebrafish. Spectral-domain optical coherence tomography (SD-OCT) was used to measure components of the eye and determine relative refractive state. Histology, immunohistochemistry, and transmission electron microscopy was used to further study the eyes.RESULTSWhile macrophage ablation does not cause significant changes to the relative refractive state of wild-type zebrafish, macrophage ablation inmfrpmutants significantly exacerbates their hyperopic phenotype.CONCLUSIONSGenetic inactivation ofmfrpleads to hyperopia as well as abnormal accumulation of macrophages in the retina. Ablation of the mpeg1-positive macrophage population exacerbates the hyperopia, suggesting that macrophages are recruited in an effort help preserve emmetropization and ameliorate hyperopia.
Epigenetic Programming during thymic development sets the stage for optimal function in effector T cells via DNA demethylation
Authors: Teghanemt Athmane , Pulipati Priyanjali , Day Kenneth , Yorek Matt , Yi Ren , Misel-Wuchter Kara , Keen Henry L , Au Christy , Maretzky Thorsten , Gurung Prajwal , Littman Dan R. , Issuree Priya D. 
Published: May 2021

ABSTRACTThe repressive effect of DNA methylation at promoters is well-known. However, its role within conserved sequences in intragenic and intergenic regions is less clear. UsingCd4as a model gene, here we show that DNA methylation regulates the function of stimulus-responsive regulatory elements in effector T cells. Twocis-elements orchestrate intra-and intergenic DNA demethylation of theCd4gene during thymic development, which in turn licenses a stimulus-responsive element, E4a, for its later function in effector cells. Deficiency in DNA demethylation leads to impaired E4a function, reduced H3K4me3 promoter levels and an inability to repelde novoDNA methylation during replication, ultimately leading to gene silencing. This physiological reduction in CD4 expression leads to a defect in Th1 polarization during cutaneous Leishmaniasis. Similar patterns of regulation were observed in a broad number of genes, highlighting an essential role for DNA demethylation during thymic development in modulating the function of stimulus-responsive elements.
Automation Assisted Anaerobic Phenotyping For Metabolic Engineering
Authors: Raj Kaushik , Venayak Naveen , Diep Patrick , Golla Sai Akhil , Yakunin Alexander F. , Mahadevan Radhakrishnan 
Published: May 2021

AbstractMicroorganisms can be metabolically engineered to produce a wide range of commercially important chemicals. Advancements in computational strategies for strain design and synthetic biological techniques to construct the designed strains have facilitated the generation of large libraries of potential candidates for chemical production. Consequently, there is a need for a high-throughput, laboratory scale techniques to characterize and screen these candidates to select strains for further investigation in large scale fermentation processes. Several small-scale fermentation techniques, in conjunction with laboratory automation have enhanced the throughput of enzyme and strain phenotyping experiments. However, such high throughput experimentation typically entails large operational costs and generate massive amounts of laboratory plastic waste. In this work, we develop an eco-friendly automation workflow that effectively calibrates and decontaminates fixed-tip liquid handling systems to reduce tip waste. We also investigate inexpensive methods to establish anaerobic conditions in microplates for high-throughput anaerobic phenotyping. To validate our phenotyping platform, we perform two case studies - an anaerobic enzyme screen, and a microbial phenotypic screen. We used our automation platform to investigate conditions under which several strains ofE. coliexhibit the same phenotypes in 0.5 L bioreactors and in our scaled-down fermentation platform. Further, we propose the use of dimensionality reduction through t-distributed stochastic neighbours embedding in conjunction with our phenotyping platform to serve as an effective scale-down model for bioreactor phenotypes. By integrating an in-house data-analysis pipeline, we were able to accelerate the ‘test’ phase of the design-build-test-learn cycle of metabolic engineering.
Semantic object-scene inconsistencies affect eye movements, but not in the way predicted by contextualized meaning maps
Authors: Pedziwiatr Marek A. , Kümmerer Matthias , Wallis Thomas S.A. , Bethge Matthias , Teufel Christoph 
Published: May 2021

AbstractSemantic information is important in eye-movement control. An important semantic influence on gaze guidance relates to object-scene relationships: objects that are semantically inconsistent with the scene attract more fixations than consistent objects. One interpretation of this effect is that fixations are driven towards inconsistent objects because they are semantically more informative. We tested this explanation using contextualized meaning maps, a method that is based on crowd-sourced ratings to quantify the spatial distribution of context-sensitive ‘meaning’ in images. In Experiment 1, we compared gaze data and contextualized meaning maps for images, in which objects-scene consistency was manipulated. Observers fixated more on inconsistent vs. consistent objects. However, contextualized meaning maps did not assigned higher meaning to image regions that contained semantic inconsistencies. In Experiment 2, a large number of raters evaluated the meaningfulness of a set of carefully selected image-regions. The results suggest that the same scene locations were experienced as slightlylessmeaningful when they contained inconsistent compared to consistent objects. In summary, we demonstrated that – in the context of our rating task – semantically inconsistent objects are experienced as less meaningful than their consistent counterparts, and that contextualized meaning maps do not capture prototypical influences of image meaning on gaze guidance.
Discrete mechanical model of lamellipodial actin network implements molecular clutch mechanism and generates arcs and microspikes
Authors: Rutkowski David M. , Vavylonis Dimitrios 
Published: May 2021

AbstractMechanical forces, actin filament turnover, and adhesion to the extracellular environment regulate lamellipodial protrusions. Computational and mathematical models at the continuum level have been used to investigate the molecular clutch mechanism, calculating the stress profile through the lamellipodium and around focal adhesions. However, the forces and deformations of individual actin filaments have not been considered while interactions between actin networks and actin bundles is not easily accounted with such methods. We develop a filament-level model of a lamellipodial actin network undergoing retrograde flow using 3D Brownian dynamics. Retrograde flow is promoted in simulations by pushing forces from the leading edge (due to actin polymerization), pulling forces (due to molecular motors), and opposed by viscous drag in cytoplasm and focal adhesions. Simulated networks have densities similar to measurements in prior electron micrographs. Connectivity between individual actin segments is maintained by permanent and dynamic crosslinkers. Remodeling of the network occurs via the addition of single actin filaments near the leading edge and via filament bond severing. We investigated how several parameters affect the stress distribution, network deformation and retrograde flow speed. The model captures the decrease in retrograde flow upon increase of focal adhesion strength. The stress profile changes from compression to extension across the leading edge, with regions of filament bending around focal adhesions. The model reproduces the observed reduction in retrograde flow speed upon exposure to cytochalasin D, which halts actin polymerization. Changes in crosslinker concentration and dynamics, as well as in the orientation pattern of newly added filaments demonstrate the model’s ability to generate bundles of filaments perpendicular (actin arcs) or parallel (microspikes) to the protruding direction.
Tropism, susceptibility, infectivity, and cytokine releases of differentiated human tonsillar epithelial cells by different Influenza viruses
Authors: Okda Faten , Sakr Ahmed , Webster Robert , Webby Richard 
Published: May 2021

ABSTRACTHuman tonsil epithelium cells (HTEC) are a heterogeneous group of actively differentiating cells comprising stratified squamous epithelial and reticulated crypt cells with abundant keratin expression. We hypothesized that the tonsils are a primary site for influenza infection and sustained viral replication. Primary HTEC were grown using an air-liquid culture and infected apically with different influenza viruses (IVs) to measure viral growth kinetics. These cultures were highly differentiated, with subpopulations of heterogenous surface stratified squamous cells rich with both cilia and microvilli; these cells contained more α2,6-linked sialic acids, those preferentially bound by human IVs, than α2,3-linked avian like sialic acids. The stratified squamous cells were interrupted by patches of reticular epithelial cells rich in α2,3-linked sialic acids. The HTEC were permissive for influenza A and B virus replication. Following infection, a subset of cells, mostly ciliated cells, underwent apoptosis while others remained intact despite being positive for IV nucleoprotein. H3N2 virus antigen colocalized with non-ciliated cells while H1N1 virus antigen was mostly associated with ciliated cells. Exposure of HTECs to IVs triggers an early proinflammatory response that fluctuates between viruses. The H3N2 IV induces an early response that persists, whereas pH1N1 induces a primarily late response in HTECs. Our results implicated HTEC as a site for IV replication. The HTEC differentiated system provides a valuable in vitro model for studying cellular tropism, infectivity, cytokine responses and the pathogenesis of IVs.IMPORTANCETo develop an effective intervention against influenza, it is important to identify host factors affecting transmission, pathogenesis, and immune response. Tonsils are lymphoepithelial organs characterized by infiltration of B and T lymphocytes into the squamous epithelium of tonsillar crypts, beneath which germinal centers play key roles in antigen processing and immune response. The heterogenicity of HTECs as well as the sialic acid distributions supports the replication of IVs and may play a role in IV adaptation. Furthermore, Tonsillectomy is a surgical procedure in which tonsils are fully removed from the human throat and may contribute to the diverse outcomes among infected individuals.
A temperateSiphoviridaebacteriophage isolate from Siberian tiger enhances the virulence of Methicillin-resistantStaphylococcusaureus through distinct mechanisms
Authors: Yang Dan , Wang Shuang , Sun Erchao , Chen Yibao , Hua Lin , Zhou Rui , Chen Huanchun , Peng Zhong , Wu Bin 
Published: May 2021

AbstractThe emergence and worldwide spread of Methicillin-resistantStaphylococcus aureus(MRSA) poses a threat to human health. While bacteriophages are recognized as an effective alternative to treat infections caused by drug resistant pathogens, some bacteriophages in particular the temperate bacteriophage may also influence the virulence of the host bacteria in distinct ways. In this study, we isolated a bacteriophage vB_Saus_PHB21 from an epidermal sample of Siberian tiger (Panthera tigris altaica) using a MRSA strain SA14 as the indicator. Our following laboratory tests and whole genome sequencing analyses revealed that vB_Saus_PHB21 was a temperate bacteriophage belonging to theSiphoviridaefamily, and this bacteriophage did not contain any virulence genes. However, the integration of PHB21 genome into the host MRSA increased the bacterial capacities of cell adhesion, cell invasion, anti-phagocytosis and biofilm formation. Challenge of the lysogenic strain (SA14+) caused severer mortalities in bothGalleria mellonellaand mouse models. Mice challenged with SA14+showed more serious organ lesions and produced higher inflammatory cytokines (IL-8, IFN-γ and TNF-α) compared to those challenged with SA14. In mechanism, we found the integration of PHB21 genome caused the upregulated expression of many genes encoding products involved in bacterial biofilm formation, adherence and invasion to host cells, anti-phagocytosis, and virulence. This study may provide novel knowledge of “bacteria-phage-interactions” in MRSA.IMPORTANCEThe interaction between bacteriophage and bacteria is like a “double-edged sword”: phages can either kill bacteria, or they may contribute to the bacterial fitness and virulence. In general, phages have positive impacts on bacterial fitness and virulence mainly because they carry antimicrobial resistance genes (ARGs) and/or virulence factors encoding genes (VFGs) and they can spread these harmful genes to the host bacteria. However, we found those phages which do not harbor ARGs and/or VFGs may also enhance the bacterial fitness and virulence. In addition, we also found the integration of phage genomes may lead to the upregulated expression of virulence associated genes in bacteria. Our study may provide new insights to redefine the relationship between phage and bacteria, and the results may also remind a cautious way to set phage-therapy for bacterial infections, before which the safety of a phage intends to be used should be fully evaluated.