bluuebunny/crossref_metadata_2025_split huggingface dataset:
Updating urinary microbiome analyses to enhance biologic interpretation
Authors: Siddiqui Nazema Y. , Ma Li , Brubaker Linda , Mao Jialiang , Hoffman Carter , Karstens Lisa 
Published: October 2021

AbstractObjectiveAn approach for assessing the urinary microbiome is 16S rRNA gene sequencing, where a segment of the bacterial genome is amplified and sequenced. Methods used to analyze these data are rapidly evolving, although the research implications are not known. This re-analysis of an existing dataset aimed to determine the impact of updated bioinformatic and statistical techniques.MethodsA prior Pelvic Floor Disorders Network (PFDN) study compared the urinary microbiome in 123 women with mixed urinary incontinence (MUI) and 84 controls. We used the PFDN’s unprocessed sequencing data of V1-V3 and V4-V6 16S variable regions, processed operational taxonomic unit (OTU) tables, and de-identified clinical data. We processed sequencing data with an updated bioinformatic pipeline, which used DADA2 to generate amplicon sequence variant (ASV) tables. Taxa from ASV tables were compared to OTU tables generated from the original processing; taxa from different variable regions (e.g., V1-V3 versus V4-V6) after updated processing were also compared. After updated processing, data were analyzed with multiple filtering thresholds. Several techniques were tested to cluster samples into microbial communities. Multivariable regression was used to test for associations between microbial communities and MUI, while controlling for potentially confounding variables.ResultsOf taxa identified through updated bioinformatic processing, only 40% were identified originally, though taxa identified through both methods represented >99% of sequencing data in terms of relative abundance. When different 16S rRNA gene regions were sequenced from the same samples, there were differences noted in recovered taxa. When the original clustering methods were applied to reprocessed sequencing data, we confirmed differences in microbial communities associated with MUI. However, when samples were clustered with a different methodology, microbial communities were no longer associated with MUI.ConclusionsUpdated bioinformatic processing techniques recover many different taxa compared to prior techniques, though most of these differences exist in low abundance taxa that occupy a small proportion of the overall microbiome. Detection of high abundance taxa are not significantly impacted by bioinformatic strategy. However, there are different biases for less abundant taxa; these differences as well as downstream clustering methodology and filtering thresholds may affect interpretation of overall results.
ModelMatcher: A scientist-centric online platform to facilitate collaborations between stakeholders of rare and undiagnosed disease research
Authors: Harnish J. Michael , Li Lucian , Rogic Sanja , Poirier-Morency Guillaume , Kim Seon-Young ,   Undiagnosed Diseases Network, Boycott Kym M. , Wangler Michael F. , Bellen Hugo J. , Hieter Philip , Pavlidis Paul , Liu Zhandong , Yamamoto Shinya 
Published: October 2021

AbstractNext-generation sequencing is a prevalent diagnostic tool for undiagnosed diseases, and has played a significant role in rare disease gene discovery. While this technology resolves some cases, others are given a list of possibly damaging genetic variants necessitating functional studies. Productive collaborations between scientists, clinicians, and patients can help resolve such medical mysteries, and provide insights into in vivo function of human genes. Furthermore, facilitating interactions between scientists and research funders, including non-profit organizations or commercial entities, can dramatically reduce the time to translate discoveries from bench to bedside. Several systems designed to connect clinicians and researchers with a shared gene of interest have been successful. However, these platforms exclude some stakeholders based on their role or geography. Here we describe ModelMatcher, a global online matchmaking tool designed to facilitate cross-disciplinary collaborations, especially between scientists and other stakeholders of rare and undiagnosed disease research. ModelMatcher is integrated into the Rare Diseases Models and Mechanisms Network and Matchmaker Exchange, allowing users to identify potential collaborators in other registries. This living database decreases the time from when a scientist or clinician is making discoveries regarding their genes of interest, to when they identify collaborators and sponsors to facilitate translational and therapeutic research.
Hippocampus does not appear to be a major target of thalamic nucleus reuniens
Authors: Andrianova Lilya , Brady Erica S , Margetts-Smith Gabriella , Kohli Shivali , Cavanagh Jonathan , McBain Chris J , Craig Michael T 
Published: October 2021

AbstractThe prefrontal – hippocampal – entorhinal system is perhaps the most widely-studied circuit in cognitive and systems neuroscience, due to its role in supporting cognitive functions such as working memory and decision-making. Disrupted communication within this circuit is a key feature of disorders such as schizophrenia and dementia. Nucleus reuniens (NRe) is a midline thalamic nucleus that sits at the nexus of this circuit, linking these regions together. As there are no direct projections from prefrontal cortex to hippocampus, the accepted model is that the NRe mediates prefrontal drive of hippocampal activity, although these connections are poorly defined at the cellular and synaptic level. Usingex vivooptogenetics and electrophysiology, alongside monosynaptic circuit-tracing, we sought to test the mechanisms through which NRe could drive hippocampal activity. Unexpectedly, we found no evidence that pyramidal cells in CA1 receive input from NRe, with midline thalamic input to hippocampus proper appearing selective for GABAergic interneurons. In other regions targeted by NRe, we found that pyramidal cells in prosubiculum and subiculum received synaptic inputs from NRe that were at least an order of magnitude weaker than those in prefrontal or entorhinal cortices. We conclude that, contrary to widely-held assumptions in the field, the hippocampus is not a major target of nucleus reuniens.
A spike-sorting method based on hierarchical clustering to discriminate extracellularly recorded simple spikes and complex spikes from cerebellar Purkinje cells
Authors: Michikawa Takayuki , Isobe Keisuke , Itohara Shigeyoshi 
Published: October 2021

AbstractBackgroundIn the cerebellar cortex, Purkinje cells are the only output neurons and exhibit two types of discharge. Most Purkinje cell discharges are simple spikes, which are commonly appearing action potentials exhibiting a rich variety of firing patterns with a rate of up to 400 Hz. More infrequent discharges are complex spikes, which consist of a short burst of impulses accompanied by a massive increase in dendritic Ca2+ with a firing rate of around 1 Hz. The discrimination of these spikes in extracellular single-unit recordings is not always straightforward, as their waveforms vary depending on recording conditions and intrinsic fluctuations.New MethodTo discriminate complex spikes from simple spikes in the extracellular single-unit data, we developed a semiautomatic spike-sorting method based on divisive hierarchical clustering.ResultsQuantitative evaluation using parallel in vivo two-photon Ca2+ imaging of Purkinje cell dendrites indicated that 96.6% of the complex spikes were detected using our spike-sorting method from extracellular single-unit recordings obtained from anesthetized mice.Comparison with Existing Method(s)No reports have conducted a quantitative evaluation of spike-sorting algorithms used for the classification of extracellular spikes recorded from cerebellar Purkinje cells.ConclusionsOur method could be expected to contribute to research in information processing in the cerebellar cortex and the development of a fully automatic spike-sorting algorithm by providing ground-truth data useful for deep learning.HighlightsA spike-sorting algorithm on hierarchical clustering was developed.It was applied to extracellular recordings from cerebellar Purkinje cells.Complex and simple spikes were discriminated based on their waveforms.Spike-sorting performance was quantified using in vivo Ca2+ imaging data.The algorithm isolated over 96.6% of complex spikes.
interpolatedXY: a two-step strategy to normalise DNA methylation microarray data avoiding sex bias
Authors: Wang Yucheng , Gorrie-Stone Tyler J. , Grant Olivia A. , Andrayas Alexandria D. , Zhai Xiaojun , McDonald-Maier Klaus D. , Schalkwyk Leonard C. 
Published: October 2021

AbstractMotivationData normalization is an essential step to reduce technical variation within and between arrays. Due to the different karyotypes and the effects of X chromosome inactivation, females and males exhibit distinct methylation patterns on sex chromosomes, thus it poses a significant challenge to normalise sex chromosome data without introducing bias. Currently, existing methods do not provide unbiased solutions to normalise sex chromosome data, usually, they just process autosomal and sex chromosomes indiscriminately.ResultsHere, we demonstrate that ignoring this sex difference will lead to introducing artificial sex bias, especially for thousands of autosomal CpGs. We present a novel two-step strategy (interpolatedXY) to address this issue, which is applicable to all quantile-based normalisation methods. By this new strategy, the autosomal CpGs are first normalised independently by conventional methods, such as funnorm or dasen; then the corrected methylation values of sex chromosome linked CpGs are estimated as the weighted average of their nearest neighbours on autosomes. The proposed two-step strategy can also be applied to other non-quantile-based normalisation methods, as well as other array-based data types. Moreover, we propose a useful concept: the sex explained fraction of variance, to quantitatively measure the normalisation effect.AvailabilityThe proposed methods are available by calling the function ‘adjustedDasen’ or ‘adjustedFunnorm’ in the latest wateRmelon package (https://github.com/schalkwyk/wateRmelon), with methods compatible with all the major workflows, including minfi.Contactxzhai@essex.ac.uk; lschal@essex.ac.ukSupplementary informationSupplementary data are available at...
Cx43 carboxyl terminal domain determines AQP4 and Cx30 endfoot organization and blood brain barrier permeability
Authors: Cibelli Antonio , Stout Randy , Timmermann Aline , de Menezes Laura , Guo Peng , Maass Karen , Seifert Gerald , Steinhäuser Christian , Spray David C. , Scemes Eliana 
Published: October 2021

ABSTRACTThe neurovascular unit (NVU) consists of cells intrinsic to the vessel wall, the endothelial cells and pericytes, and astrocyte endfeet that surround the vessel but are separated from it by basement membrane. Endothelial cells are primarily responsible for creating and maintaining blood-brain-barrier (BBB) tightness, but astrocytes contribute to the barrier through paracrine signaling to the endothelial cells and by forming the glia limitans. Gap junctions (GJs) between astrocyte endfeet are composed of connexin 43 (Cx43) and Cx30, which form plaques between cells. GJ plaques formed of Cx43 do not diffuse laterally in the plasma membrane and thus potentially provide stable organizational features to the endfoot domain, whereas GJ plaques formed of other connexins and of Cx43 lacking a large portion of its cytoplasmic carboxyl terminus are quite mobile. In order to examine the organizational features that immobile GJs impose on the endfoot, we have used super-resolution confocal microscopy to map number and sizes of GJ plaques and aquaporin (AQP)-4 channel clusters in the perivascular endfeet of mice in which astrocyte GJs (Cx30, Cx43) were deleted or the carboxyl terminus of Cx43 was truncated. To determine if blood-brain-barrier integrity was compromised in these transgenic mice, we conducted perfusion studies under elevated hydrostatic pressure using horseradish peroxide as a molecular probe enabling detection of micro-hemorrhages in brain sections. These studies revealed that microhemorrhages were more numerous in mice lacking Cx43 or its carboxyl terminus. In perivascular domains of cerebral vessels, we found that density of Cx43 GJs was higher in the truncation mutant, while GJ size was smaller. Density of perivascular particles formed by AQP4 and its extended isoform AQP4ex was inversely related to the presence of full length Cx43, whereas the ratio of sizes of the particles of the AQP4ex isoform to total AQP4 was directly related to the presence of full length Cx43. Confocal analysis showed that Cx43 and Cx30 were substantially colocalized in astrocyte domains near vasculature of truncation mutant mice. These results showing altered distribution of some astrocyte nexus components (AQP4 and Cx30) in Cx43 null mice and in a truncation mutant, together with leakier cerebral vasculature, support the hypothesis that localization and mobility of gap junction proteins and their binding partners influences organization of astrocyte endfeet which in turn impacts BBB integrity of the NVU.
Multivariate pattern analysis reveals location specific aftereffects of 10Hz motor cortex transcranial alternating current stimulation
Authors: Tzvi Elinor , Alizadeh Jalal , Schubert Christine , Classen Joseph 
Published: October 2021

AbstractBackgroundTranscranial alternating current stimulation (tACS) may induce frequency-specific aftereffects on brain oscillations in the stimulated location, which could serve as evidence for region-specific neuroplasticity. Aftereffects of tACS on the motor system remain unknown.ObjectiveTo find evidence for aftereffects in short EEG segments following tACS to two critical nodes of the motor network, namely, left motor cortex (lMC) and right cerebellum (rCB). We hypothesized that aftereffects of lMC will be stronger in and around lMC compared to both active stimulation of rCB, as well as inactive (“sham”) control conditions.MethodsTo this end, we employed multivariate pattern analysis (MVPA), and trained a classifier to distinguish between EEG signals following each of the three stimulation protocols. This method accounts for the multitude facets of the EEG signal and thus is more sensitive to subtle modulation of the EEG signal.ResultsEEG signals in both theta (θ, 4-8Hz) and alpha (α, 8-13Hz) were better classified to lMC-tACS compared to rCB-tACS/sham, in and around lMC-tACS stimulation locations (electrodes FC3 and CP3). This effect was associated with a decrease in power following tACS. Source reconstruction revealed significant differences in premotor cortex but not in primary motor cortex as the computational model suggested. Correlation between classification accuracies in θ and α in lMC-tACS was stronger compared to rCB-tACS/sham, suggesting cross-frequency effects of tACS. Nonetheless, θ/α phase-coupling did not differ between stimulation protocols.ConclusionsSuccessful classification of EEG signals to left motor cortex using MVPA revealed focal tACS aftereffects on the motor cortex, indicative of region-specific neuroplasticity.
Microevolution of Pieris butterfly genes involved in host-plant adaptation along a host-plant community cline
Authors: Okamura Yu , Sato Ai , Kawaguchi Lina , Nagano Atsushi J. , Murakami Masashi , Vogel Heiko , Kroymann Juergen 
Published: October 2021

AbstractHerbivorous insects have evolved counteradaptations to overcome the chemical defenses of their host plants. Several of these counteradaptations have been elucidated at the molecular level, in particular for insects specialized on cruciferous host plants. While the importance of these counteradaptations for host plant colonization is well established,little is known about their microevolutionary dynamics in the field. In this study, we examine patterns of host plant use and insect counteradaptation in three Pieris butterfly species across Japan. The larvae of these butterflies express nitrile-specifier protein (NSP) and its paralog major allergen (MA) in their gut to overcome the highly diversified glucosinolate-myrosinase defense system of their cruciferous host plants. Pieris napi and Pieris melete colonize wild Brassicaceae whereas Pieris rapae typically uses cultivated Brassica as a host, regardless of the local composition of wild crucifers. As expected, NSP and MA diversity was independent of the local composition of wild Brassicaceae in P. rapae. In contrast, NSP diversity correlated with local host plant diversity in both species that preferred wild Brassicaceae. P. melete and P. napi both revealed two distinct major NSP alleles, which shaped diversity among local populations, albeit with different evolutionary trajectories. In comparison, MA showed no indication for local adaptation. Altogether, MA appeared to be evolutionary more conserved than NSP, suggesting that both genes play different roles in diverting host plant chemical defense.
Isotopic evidence for population dynamics in the Central Italian Copper Age and Bronze Age
Authors: Romboni Marco , Arienzo Ilenia , Di Vito Mauro Antonio , Lubritto Carmine , Piochi Monica , Di Cicco Maria Rosa , Rickards Olga , Rolfo Mario Federico , Sevink Jan , De Angelis Flavio , Alessandri Luca 
Published: October 2021

AbstractThe mobility patterns in the Italian peninsula during prehistory are still relatively unknown. The excavation of the Copper Age and Bronze Age deposits in La Sassa cave (Sonnino, Italy) allowed to broaden the knowledge about some local and regional dynamics. We employed a multi-disciplinary approach, including stable (carbon and nitrogen – C and N, respectively) and radiogenic (strontium-Sr) isotopes analyses and the identification of the cultural traits in the material culture to identify mobility patterns that took place in the region. The Sr isotopic analyses on the human bones show that in the Copper Age and at the beginning of the Bronze Age, the cave was used as a burial place by different villages, perhaps spread in a radius of no more than 5 km. Stable isotopes analyses suggest the introduction of C4 plants in the diet of the Middle Bronze Age (MBA) communities in the area. Remarkably, in the same period, the material culture shows increasing influxes coming from the North. This evidence is consistent with the recent genomic findings tracing the arrival of people carrying a Steppe-related ancestry in Central Italy in MBA.
Knockout of a singleSoxgene resurrects an ancestral cell type in the sea anemoneNematostella vectensis
Authors: Babonis Leslie S. , Enjolras Camille , Reft Abigail J. , Foster Brent M. , Hugosson Fredrik , Ryan Joseph F. , Daly Marymegan , Martindale Mark Q. 
Published: October 2021

AbstractCnidocytes are the explosive stinging cells found only in cnidarians (corals, jellyfish, etc). Specialized for prey capture and defense, cnidocytes are morphologically complex and vary widely in form and function across taxa; how such diversity evolved is unknown. Using CRISPR/Cas9-mediated genome editing in the burrowing sea anemoneNematostella vectensis, we show that a single transcription factor (NvSox2) acts as a binary switch between two alternative cnidocyte fates. Knockout ofNvSox2caused a complete transformation of nematocytes (piercing cells) into spirocytes (ensnaring cells). The type of spirocyte induced byNvSox2knockout (robust spirocyte) is not normally found inN. vectensisbut is common in sea anemones from other habitats. Homeotic control of cell fate provides a mechanistic explanation for the discontinuous distribution of cnidocyte types across cnidarians and demonstrates how simple counts of cell types can underestimate biodiversity.
MoSBi: Automated signature mining for molecular stratification and subtyping
Authors: Rose Tim Daniel , Bechtler Thibault , Ciora Octavia-Andreea , Lilian Le Kim Anh , Molnar Florian , Koehler Nikolai , Baumbach Jan , Röttger Richard , Pauling Josch Konstantin 
Published: October 2021

AbstractThe improving access to increasing amounts of biomedical data provides completely new chances for advanced patient stratification and disease subtyping strategies. This requires computational tools that produce uniformly robust results across highly heterogeneous molecular data. Unsupervised machine learning methodologies are able to discover de-novo patterns in such data. Biclustering is especially suited by simultaneously identifying sample groups and corresponding feature sets across heterogeneous omics data. The performance of available biclustering algorithms heavily depends on individual parameterization and varies with their application. Here, we developed MoSBi (Molecular Signature identification using Biclustering), an automated multi-algorithm ensemble approach that integrates results utilizing an error model-supported similarity network. We evaluated the performance of MoSBi on transcriptomics, proteomics and metabolomics data, as well as synthetic datasets covering various data properties. Profiting from multi-algorithm integration, MoSBi identified robust group and disease specific signatures across all scenarios overcoming single algorithm specificities. Furthermore, we developed a scalable network-based visualization of bicluster communities that support biological hypothesis generation. MoSBi is available as an R package and web-service to make automated biclustering analysis accessible for application in molecular sample stratification.
Climatic clustering and longitudinal analysis with impacts on food, bioenergy, and pandemics
Authors: Lagergren John , Cashman Mikaela , Melesse Vergara Verónica G. , Eller Paul R. , Gazolla Joao Gabriel Felipe Machado , Chhetri Hari B. , Streich Jared , Climer Sharlee , Thornton Peter , Joubert Wayne , Jacobson Daniel 
Published: October 2021

AbstractPredicted growth in world population will put unparalleled stress on the need for sustainable energy and global food production, as well as increase the likelihood of future pandemics. In this work, we identify high-resolution environmental zones in the context of a changing climate and predict longitudinal processes relevant to these challenges. We do this using exhaustive vector comparison methods that measure the climatic similarity between all locations on earth at high geospatial resolution. The results are captured as networks, in which edges between geolocations are defined if their historical climates exceed a similarity threshold. We then apply Markov clustering and our novel Correlation of Correlations method to the resulting climatic networks, which provides unprecedented agglomerative and longitudinal views of climatic relationships across the globe. The methods performed here resulted in the fastest (9.37 × 1018 operations/sec) and one of the largest (168.7 × 1021 operations) scientific computations ever performed, with more than 100 quadrillion edges considered for a single climatic network. Correlation and network analysis methods of this kind are widely applicable across computational and predictive biology domains, including systems biology, ecology, carbon cycles, biogeochemistry, and zoonosis research.