bluuebunny/crossref_metadata_2025_split huggingface dataset:
Amino acid variability, tradeoffs and optimality in human diet
Authors: Dai Ziwei , Locasale Jason W. 
Published: June 2021

AbstractWhile the quality of fat (e.g. saturated/unsaturated) and carbohydrate (e.g. whole grain/simple sugars) intake has been of great interest, less attention has been made to the type of protein and resulting amino acid intake profiles in human diets. Studies at the molecular level however demonstrate that dietary amino acid intake produces substantial effects on health and disease such as cancer by modulating metabolism. How these effects may manifest in human food consumption and dietary patterns is unknown. We developed a series of algorithms to map, characterize and model the landscape of amino acid content in human food, dietary patterns, and individual consumption including relations to health status, covering over 2,000 foods, ten dietary patterns, and over 30,000 dietary records. We found that the type of amino acids contained in foods and human consumption is highly dynamic with variability far exceeding that of fat and carbohydrate. Some amino acids positively associate with diseases such as obesity while others contained in the same food negatively link to disease. Using linear programming and machine learning, we show that these health trade-offs among can be accounted to satisfy biochemical constraints in food and human eating patterns to construct a Pareto front in dietary practice, a means of achieving optimality in the face of tradeoffs that are commonly considered in economic and evolutionary theories. Thus this study may enable the design of human protein quality intake guidelines based on a quantitative framework.
Effects of tDCS on the attentional blink revisited: A statistical evaluation of a replication attempt
Authors: Reteig Leon C. , Newman Lionel A. , Richard Ridderinkhof K. , Slagter Heleen A. 
Published: June 2021

AbstractThe attentional blink (AB) phenomenon reveals a bottleneck of human information processing: the second of two targets is often missed when they are presented in rapid succession among distractors. In our previous work, we showed that the size of the AB can be changed by applying transcranial direct current stimulation (tDCS) over the left dorsolateral prefrontal cortex (lDLPFC) (London & Slagter, Journal of Cognitive Neuroscience, 33, 756–68, 2021). Although AB size at the group level remained unchanged, the effects of anodal and cathodal tDCS were negatively correlated: if a given individual’s AB size decreased from baseline during anodal tDCS, their AB size would increase during cathodal tDCS, and vice versa. Here, we attempted to replicate this finding. We found no group effects of tDCS, as in the original study, but we no longer found a significant negative correlation. We present a series of statistical measures of replication success, all of which confirm that both studies are not in agreement. First, the correlation here is significantly smaller than a conservative estimate of the original correlation. Second, the difference between the correlations is greater than expected due to sampling error, and our data are more consistent with a zero-effect than with the original estimate. Finally, the overall effect when combining both studies is small and not significant. Our findings thus indicate that the effects of lDPLFC-tDCS on the AB are less substantial than observed in our initial study. Although this should be quite a common scenario, null findings can be difficult to interpret and are still under-represented in the brain stimulation and cognitive neuroscience literatures. An important auxiliary goal of this paper is therefore to provide a tutorial for other researchers, to maximize the evidential value from null findings.
A hierarchy in clusters of cephalopod mRNA editing sites
Authors: Moldovan Mikhail A. , Chervontseva Zoe S. , Nogina Daria S. , Gelfand Mikhail S. 
Published: June 2021

AbstractRNA editing in the form of substituting adenine to inosine (A-to-I editing) is the most frequent type of RNA editing, observed in many metazoan species. A-to-I editing sites form clusters in most studied species, and editing at clustered sites depends on editing of the adjacent sites. Although functionally important in some specific cases, A-to-I editing in most considered species is rare, the exception being soft-bodied cephalopods (coleoids), where tens of thousands of potentially important A-to-I editing sites have been identified, making coleoids an ideal object for studying of general properties and evolution of A-to-I editing sites. Here, we apply several diverse techniques to demonstrate a strong tendency of coleoid RNA editing sites to cluster along the transcript. We identify three distinct types of editing site clusters, varying in size, and describe RNA structural features and mechanisms likely underlying formation of these clusters. In particular, these observations may resolve the paradox of sequence conservation at large distances around editing sites.
ACES: Analysis of Conservation with Expansive Species
Authors: Padhi Evin M. , Mehinovic Elvisa , Sams Eleanor I. , Ng Jeffrey K. , Turner Tychele N. 
Published: June 2021

AbstractMotivationAn abundance of new reference genomes are becoming available through large-scale sequencing efforts. While the reference FASTA for each genome is available, there is currently no automated mechanism to query a specific sequence across all new reference genomes.ResultsWe developed ACES (Analysis of Conservation with Expansive Species) as a computational workflow to query specific sequences of interest (e.g., enhancers, promoters, exons) against reference genomes with an available reference FASTA. This automated workflow generates BLAST hits against each of the reference genomes, a multiple sequence alignment file, a graphical fragment assembly file, and a phylogenetic tree file. These data files can then be used by the researcher in several ways to provide key insights into conservation of the query sequence.AvailabilityACES is available at https://github.com/TNTurnerLab/ACESContacttychele@wustl.eduSupplementary informationSupplementary Figure 1 is available on bioRxiv.
Concurrent contextual and time-distant mnemonic information co-exist as feedback in human visual cortex
Authors: Ortiz-Tudela Javier , Bergmann Johanna , Bennett Matthew , Ehrlich Isabelle , Muckli Lars , Shing Yee Lee 
Published: June 2021

AbstractEfficient processing of visual environment necessitates the integration of incoming sensory evidence with concurrent contextual inputs and mnemonic content from our past experiences. To delineate how this integration takes place in the brain, we studied modulations of feedback neural patterns in non-stimulated areas of the early visual cortex in humans (i.e., V1 and V2). Using functional magnetic resonance imaging and multivariate pattern analysis, we show that both, concurrent contextual and time-distant mnemonic information, coexist in V1/V2 as feedback signals. The extent to which mnemonic information is reinstated in V1/V2 depends on whether the information is retrieved episodically or semantically. These results demonstrate that our stream of visual experience contains not just information from the visual surrounding, but also memory-based predictions internally generated in the brain.One-Sentence SummaryFeedback activity in human early visual cortex contains concurrent contextual and time-distant mnemonic information.
Proteomic changes induced by harmine in human brain organoids reveal signaling pathways related to neuroprotection
Authors: Karmirian Karina , Goto-Silva Lívia , Nascimento Juliana Minardi , Costa Marcelo N. , Salerno José Alexandre , Ornelas Isis Moraes , Vanderborght Bart , Martins-de-Souza Daniel , Rehen Stevens 
Published: June 2021

AbstractHarmine is a β-carboline found in Banisteriopsis caapi, a constituent of ayahuasca brew. Ayahuasca is consumed as a beverage in native Americans’ sacred rituals and in religious ceremonies in Brazil. Throughout the years, the beneficial effects of ayahuasca to improve mental health and life quality have been reported, which propelled the investigation of its therapeutic potential to target neurological disorders such as depression and anxiety. Indeed, antidepressant effects of ayahuasca have been described, raising the question of which cellular mechanisms might underlie those effects. Previous animal studies describe potential neuroprotective mechanisms of harmine, including anti-inflammatory and antioxidant activities, and neurotrophin signaling activation. However, the cellular and molecular mechanisms modulated by harmine in human models remain less investigated. Here we analyzed the short-term changes in the proteome of human brain organoids treated with harmine using shotgun mass spectrometry. Harmine upregulates proteins related to synaptic vesicle cycle, cytoskeleton-dependent intracellular transport, cell cycle, glucose transporter-4 translocation, and neurotrophin signaling pathway. In addition, protein expression levels of Akt and phosphorylated CREB were increased after 24 hour-treatment. Our results shed light on the potential mechanisms that may underlie harmine-induced neuroprotective effects.
Arabidopsis ABIG1 Functions in Laminar Growth and Polarity Formation through Regulation by REVOLUTA and KANADI
Authors: Preciado Jesus , Begcy Kevin , Liu Tie 
Published: June 2021

AbstractLeaf laminar growth and adaxial-abaxial boundary formation are fundamental outcomes of plant development. Boundary and laminar growth coordinate the further patterning and growth of the leaf, directing the differentiation of cell types within the top and bottom domains and promoting initiation of lateral organs along their adaxial/abaxial axis. Leaf adaxial-abaxial polarity specification and laminar out-growth are regulated by two transcription factors, REVOLUTA (REV) and KANADI (KAN). ABA INSENSITIVE TO GROWTH 1 (ABIG1) is a HOMEODOMAIN-LEUCINE ZIPPER (HD-ZIP) Class II transcription factor and is a direct target of the adaxial-abaxial regulators REV and KAN. To investigate the role of ABIG1 in the leaf development and establishment of polarity, we examined the phenotypes of both gain-of-function and loss-of-function mutants. Through genetic interaction analysis with REV and KAN mutants, we have determined that ABIG1 plays a role in leaf laminar-growth as well as in adaxial-abaxial polarity establishment. Genetic and physical interaction assays showed that ABIG1 interacts with the transcriptional corepressor TOPLESS (TPL). This study provides new evidence that another HD-ZIP II gene, ABIG1, facilitates growth through the corepressor TPL.HighlightABIG1, a HD-ZIP Class II transcription factor, promotes laminar growth and adaxial-abaxial polarity through the regulation of REV and KAN.
YAPP-CD: Yet another protein-peptide complex database
Authors: Park Joon-Sang 
Published: June 2021

AbstractProtein-peptide interactions are of great interest to the research community not only because they serve as mediators in many protein-protein interactions but also because of the increasing demand for peptide-based pharmaceutical products. Protein-peptide docking is a major tool for studying protein-peptide interactions, and several docking methods are currently available. Among various protein-peptide docking algorithms, template-based approaches, which utilize known protein-peptide complexes or templates to predict a new one, have been shown to yield more reliable results than template-free methods in recent comparative research. To obtain reliable results with a template-based docking method, the template database must be comprehensive enough; that is, there must be similar templates of protein-peptide complexes to the protein and peptide being investigated. Thus, the template database must be updated to leverage recent advances in structural biology. However, the template database distributed with GalaxyPepDock, one of the most widely used peptide docking programs, is outdated, limiting the prediction quality of the method. Here, we present an up-to-date protein-peptide complex database called YAPP-CD, which can be directly plugged into the GalaxyPepDock binary package to improve GalaxyPepDock’s prediction quality by drawing on recent discoveries in structural biology. Experimental results show that YAPP-CD significantly improves GalaxyPepDock’s prediction quality, e.g., the average Ligand/Interface RMSD of a benchmark set is reduced from 7.60 Å/3.62 Å to 3.47 Å/1.71 Å.
Evaluation of RNAlater™ as a field-compatible preservation method for metaproteomic analyses of bacteria-animal symbioses
Authors: Jensen Marlene , Wippler Juliane , Kleiner Manuel 
Published: June 2021

AbstractField studies are central to environmental microbiology and microbial ecology as they enable studies of natural microbial communities. Metaproteomics, the study of protein abundances in microbial communities, allows to study these communities ‘in situ’ which requires protein preservation directly in the field as protein abundance patterns can change rapidly after sampling. Ideally, a protein preservative for field deployment works rapidly and preserves the whole proteome, is stable in long-term storage, is non-hazardous and easy to transport, and is available at low cost. Although these requirements might be met by several protein preservatives, an assessment of their suitability in field conditions when targeted for metaproteomics is currently lacking. Here, we compared the protein preservation performance of flash freezing and the preservation solution RNAlater™ using the marine gutless oligochaete Olavius algarvensis and its symbiotic microbes as a test case. In addition, we evaluated long-term RNAlater™ storage after 1 day, 1 week and 4 weeks at room temperature (22-23 °C). We evaluated protein preservation using one dimensional liquid chromatography tandem mass spectrometry (1D-LC-MS/MS). We found that RNAlater™ and flash freezing preserved proteins equally well in terms of total number of identified proteins or relative abundances of individual proteins and none of the test time points were altered compared to t0. Moreover, we did not find biases against specific taxonomic groups or proteins with particular biochemical properties. Based on our metaproteomics data and the logistical requirements for field deployment we recommend RNAlater™ for protein preservation of field-collected samples when targeted for metaproteomcis.ImportanceMetaproteomics, the large-scale identification and quantification of proteins from microbial communities, provides direct insights into the phenotypes of microorganisms on the molecular level. To ensure the integrity of the metaproteomic data, samples need to be preserved immediately after sampling to avoid changes in protein abundance patterns. In laboratory set-ups samples for proteomic analyses are most commonly preserved by flash freezing; however, liquid nitrogen or dry ice is often unavailable at remote field locations due to its hazardous nature and transport restrictions. Our study shows that RNAlater™ can serve as a low hazard, easy to transport alternative to flash freezing for field preservation of samples for metaproteomics. We show that RNAlater™ preserves the metaproteome equally well as compared to flash freezing and protein abundance patterns remain stable during long-term storage for at least 4 weeks at room temperature.
Natian and Ryabhatta—graphical user interfaces to create, analyze and visualize single-cell transcriptomic datasets
Authors: Manivannan Sathiya N. , Garg Vidu 
Published: June 2021

AbstractSingle-cell transcriptomic analyses permit a high-resolution investigation of biological processes at the individual cell level. Single-cell transcriptomics technologies such as Drop-seq, Smart-seq, MARS-seq, sci-RNA-seq, and CELL-seq produce large volumes of data in the form of sequence reads. In general, the alignment of the reads to genomes and the enumeration of reads mapping to a specific gene results in a gene-count matrix. These gene-count matrix data require robust quality control and statistical analytical pipelines before data mining and interpretation. Among these post-alignment pipelines, the ‘Seurat’ package in ‘R’ is the most popular analytical pipeline for the analysis of single-cell data. This package provides quality control, normalization, principal component analysis, dimensional reduction, clustering, and marker identification among other functions needed to process and mine the single-cell transcriptomic data. While the Seurat package is continuously updated and includes a variety of functionalities, the user is still required to be proficient in the ‘R’ programming language and its data structures to be able to execute the Seurat functions. Hence, there is a demand for a graphical user interface (GUI) that takes in relevant input information and processes the single-cell data using the Seurat pipeline. A GUI will also highly improve the access to single-cell data for life sciences researchers who are not trained in the command-line operation of the ‘R’ platform. To meet this demand, we present R Shiny apps ‘Natian’ and ‘Ryabhatta’ to assist in the generation and analysis of Seurat files from a variety of different sources. The apps and example data can be downloaded from https://singlecelltranscriptomics.org. Natian allows users to create Seurat files from the output of multiple pipelines, integrate existing Seurat files, add metadata information, perform dimensional reduction analysis or upload dimensional reduction data, resume partially processed Seurat files and find cluster markers. Ryabhatta allows users to visualize gene expression using a variety of plotting options, analyze cluster markers, rename clusters, select cells from a graph or based on expression levels of markers, perform differential expression, count the number of cells in each condition, and perform pseudotime analysis using Monocle. We found that the use of these apps substantially improved the analytical and processing time and remove needless troubleshooting due to incompatible commands, typographical errors in scripts, and cluttering of the R environment with variables. We hope the use of these apps improves the use of single-cell data for life sciences research while also providing a tool to learn the functionalities of Seurat and R functions available for single-cell data analysis.
Novel LOTUS-domain proteins are organizational hubs that recruit C. elegans Vasa to germ granules
Authors: Cipriani P. Giselle , Bay Olivia , Zinno John , Gutwein Michelle , Gan Hin Hark , Mayya Vinay K. , Chung George , Chen Jia-Xuan , Fahs Hala , Guan Yu , Duchaine Thomas F. , Selbach Matthias , Piano Fabio , Gunsalus Kristin C. 
Published: June 2021

AbstractWe describe MIP-1 and MIP-2, novel paralogous C. elegans germ granule components that interact with the intrinsically disordered MEG-3 protein. These proteins promote P granule condensation, form granules independently of MEG-3 in the postembryonic germ line, and balance each other in regulating P granule growth and localization. MIP-1 and MIP-2 each contain two LOTUS domains and intrinsically disordered regions and form homo- and heterodimers. They bind and anchor the Vasa homolog GLH-1 within P granules and are jointly required for coalescence of MEG-3, GLH-1, and PGL proteins. Animals lacking MIP-1 and MIP-2 show temperature-sensitive embryonic lethality, sterility, and mortal germ lines. Germline phenotypes include defects in stem cell self-renewal, meiotic progression, and gamete differentiation. We propose that these proteins serve as scaffolds and organizing centers for ribonucleoprotein networks within P granules that help recruit and balance essential RNA processing machinery to regulate key developmental transitions in the germ line.
Teaching Python for Data Science: Collaborative development of a modular & interactive curriculum
Authors: Duda Marlena , Sovacool Kelly L. , Farzaneh Negar , Nguyen Vy Kim , Haynes Sarah E. , Falk Hayley , Furman Katherine L. , Walker Logan A. , Diao Rucheng , Oneka Morgan , Drotos Audrey C. , Woloshin Alana , Dotson Gabrielle A. , Kriebel April , Meng Lucy , Thiede Stephanie N. , Lapp Zena , Wolford Brooke N. 
Published: June 2021

SummaryWe are bioinformatics trainees at the University of Michigan who started a local chapter of Girls Who Code to provide a fun and supportive environment for high school women to learn the power of coding. Our goal was to cover basic coding topics and data science concepts through live coding and hands-on practice. However, we could not find a resource that exactly met our needs. Therefore, over the past three years, we have developed a curriculum and instructional format using Jupyter notebooks to effectively teach introductory Python for data science. This method, inspired by The Carpentries organization, uses bite-sized lessons followed by independent practice time to reinforce coding concepts, and culminates in a data science capstone project using real-world data. We believe our open curriculum is a valuable resource to the wider education community and hope that educators will use and improve our lessons, practice problems, and teaching best practices. Anyone can contribute to our educational materials on GitHub.
Incorporation of data from multiple hypervariable regions when analyzing bacterial 16S rRNA sequencing data
Authors: Jones Carli B. , White James R. , Ernst Sarah E. , Sfanos Karen S. , Peiffer Lauren B. 
Published: June 2021

AbstractShort read 16S rRNA amplicon sequencing is a common technique used in microbiome research. However, inaccuracies in estimated bacterial community composition can occur due to amplification bias of the targeted hypervariable region. A potential solution is to sequence and assess multiple hypervariable regions in tandem, yet there is currently no consensus as to the appropriate method for analyzing this data. Additionally, there are many sequence analysis resources for data produced from the Illumina platform, but fewer open-source options available for data from the Ion Torrent platform. Herein, we present an analysis pipeline using an open-source analysis platform that integrates data from multiple hypervariable regions and is compatible with data produced from the Ion Torrent platform. We used the ThermoFisher Ion 16S™ Metagenomics Kit and a mock community of 20 bacterial strains to assess taxonomic classification of amplicons from 6 separate hypervariable regions (V2, V3, V4, V6-7, V8, V9) using our analysis pipeline. We report that different hypervariable regions have different specificities for taxonomic classification, which also had implications for global level analyses such as alpha and beta diversity. Finally, we utilize a generalized linear modeling approach to statistically integrate the results from multiple hypervariable regions and apply this methodology to data from a small clinical cohort. We conclude that scrutinizing sequencing results separately by hypervariable region provides a more granular view of the taxonomic classification achieved by each primer set as well as the concordance of results across hypervariable regions. However, the data across all hypervariable regions can be combined using generalized linear models to statistically evaluate overall differences in community structure and relatedness among sample groups.