bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dynamic neural reconstructions of attended object location and features using EEG
Authors: Chen Jiageng , Golomb Julie D. 
Published: April 2022

AbstractAttention allows us to select relevant and ignore irrelevant information from our complex environments. What happens when attention shifts from one item to another? To answer this question, it is critical to have tools that accurately recover neural representations of both feature and location information with high temporal resolution. In the current study, we used human electroencephalography (EEG) and machine learning to explore how neural representations of object features and locations update across dynamic shifts of attention. We demonstrate that EEG can be used to create simultaneous timecourses of neural representations of attended features (timepoint-by-timepoint inverted encoding model reconstructions) and attended location (timepoint-by-timepoint decoding) during both stable periods and across dynamic shifts of attention. Each trial presented two oriented gratings that flickered at the same frequency but had different orientations; participants were cued to attend one of them, and on half of trials received a shift cue mid-trial. We trained models on a stable period from Hold attention trials, and then reconstructed/decoded the attended orientation/location at each timepoint on Shift attention trials. Our results showed that both feature reconstruction and location decoding dynamically track the shift of attention, and that there may be timepoints during the shifting of attention when (1) feature and location representations become uncoupled, and (2) both the previously-attended and currently-attended orientations are represented with roughly equal strength. The results offer insight into our understanding of attentional shifts, and the noninvasive techniques developed in the current study lend themselves well to a wide variety of future applications.Open Practice StatementThe data and analysis code will be made publicly available on the Open Science Framework (link to be updated upon publication).New & NoteworthyWe used human EEG and machine learning to reconstruct neural response profiles during dynamic shifts of attention. Specifically, we demonstrated that we could simultaneously read out both location and feature information from an attended item in a multi-stimulus display. Moreover, we examined how that readout evolves over time during the dynamic process of attentional shifts. These results provide insight into our understanding of attention, and this technique carries substantial potential for versatile extensions and applications.
BioNE: Integration of network embeddings for supervised learning
Authors: Parvizi Poorya , Azuaje Francisco , Theodoratou Evropi , Luz Saturnino 
Published: April 2022

SummaryA network embedding approach reduces the analysis complexity of large biological networks by converting them to lowdimensional vector representations (features/embeddings). These lower-dimensional vectors can then be used in machine learning prediction tasks with a wide range of applications in computational biology and bioinformatics. Several network embedding approaches have been proposed with different methods of generating vector representations. These network embedding approaches can be quite diverse in terms of data representation and implementation. Moreover, most were not originally developed for biological networks. Therefore comparing and assessing the performance of these diverse models in practice, in biological contexts, can be challenging. To facilitate such comparisons, we have developed the BioNE framework for integration of different embedding methods in prediction tasks. Using this framework one can easily assess, for instance, whether combined vector representations from multiple embedding methods offer complementary information with regards to the network features and thus better performance on prediction tasks. In this paper, we present the BioNE software suite for embedding integration, which applies network embedding methods following standardised network preparation steps, and integrates the vector representations achieved by these methods using three different techniques. BioNE enables selection of prediction models, oversampling methods, feature selection methods, cross-validation type and cross-validation parameters.Availability and implementationBioNE pipeline and detailed explanation of implementation is freely available on GitHub, athttps://github.com/pooryaparvizi/BioNE
Inflammation as a Silent Partner in Opioid Addiction: A Regulatory Logic Model
Authors: Toole J. Tory , Morris Matthew , Lyman Cole A. , Spink Garry , Broderick Gordon 
Published: April 2022

AbstractThe brain and body consist of complex networks of interconnected feedback and feed forward loops. Because these networks are capable of supporting multiple homeostatic states, a stressor or combination of stressors may cause the network to become “stuck” in a persistent maladaptive state, for example, chronic pain and the potentiation of opioid dependency. The current research uses automated text mining of over 14,000 publications to assemble a regulatory circuit consisting of 44 immune and neurotransmission mediators linked by 188 documented regulatory interactions. Decisional logic parameters dictating the regulatory dynamics available to each network model were estimated such that predicted behavior would adhere to observed pathologies. Analysis of this psycho-neuroimmune network confirmed that a broad family of behavioral kinetics may be equally capable of supporting dynamically stable conditions of chronic pain, persistent depression and addiction behaviors. Despite differences in the predicted course of onset, these models typically point to characteristic patterns of increased inflammatory activity in the brain for each of these pathologies, specifically increased expression of the protein complex NF-kB and inflammatory signaling proteins IL1-B, IL6, and TNF. Potential treatments targeting both addiction and chronic pain may therefore benefit from the use of anti-inflammatory drugs as pharmacological potentiators of current behavioral interventions.Clinical RelevanceThis work establishes a methodology for understanding both illness-specific and shared mechanisms underlying addiction, chronic pain, and depression, and the corresponding expression profiles of psychoneuroimmune markers that might facilitate screening and treatment design.
Improved imaging and preservation of lysosome dynamics using silver nanoparticle-enhanced fluorescence
Authors: Soha Sumaiya A. , Santhireswaran Araniy , Huq Saaimatul , Casimir-Powell Jayde , Jenkins Nicala , Hodgson Gregory K. , Sugiyama Michael , Antonescu Costin N. , Impellizzeri Stefania , Botelho Roberto J. 
Published: April 2022

SummaryThe dynamics of living cells can be studied by live-cell fluorescence microscopy. However, this requires the use of excessive light energy to obtain good signal-to-noise ratio, which can then photobleach fluorochromes, and more worrisomely, lead to photo-toxicity. Upon light excitation, noble metal nanoparticles such as silver nanoparticles (AgNP) generate plasmons, which can then amplify excitation in direct proximity of the nanoparticle’s surface and couple to the oscillating dipole of nearby radiating fluorophores, modifying their rate of emission and thus, enhancing their fluorescence. Here, we show that AgNP fed to cells to accumulate within lysosomes enhanced the fluorescence of lysosome-targeted Alexa488-conjugated dextran, BODIPY-cholesterol, and DQ-BSA. Moreover, AgNP increased the fluorescence of GFP fused to the cytosolic tail of LAMP1, showing that metal enhanced fluorescence can occur across the lysosomal membrane. The inclusion of AgNPs in lysosomes did not disturb lysosomal properties such as lysosomal pH, degradative capacity, autophagy and autophagic flux, and membrane integrity, though AgNP seemed to increase basal lysosome tubulation. Importantly, by using AgNP, we could track lysosome motility with reduced laser power without damaging and altering lysosome dynamics. Overall, AgNP-enhanced fluorescence may be a useful tool to study the dynamics of the endo-lysosomal pathway while minimizing photo-toxicity.eTOCSilver nanoparticles enhance fluorescence via surface plasmons. Here, we show that loading lysosomes with silver nanoparticles enhances the fluorescence of fluorochrome- and GFP-based molecular probes for lysosomes. This affords reduced excitation and exposure, diminishing photobleaching and phototoxicity, and preserving lysosome dynamics.
Truncated suPAR simultaneously causes kidney disease and autoimmune diabetes mellitus
Authors: Zhu Ke , Mukherjee Kamalika , Wei Changli , Hayek Salim S. , Collins Agnieszka , Gu Changkyu , Corapi Kristin , Altintas Mehmet M. , Wang Yong , Waikar Sushrut S. , Bianco Antonio C. , Reiser Jochen , Sever Sanja 
Published: April 2022

AbstractSoluble urokinase-type plasminogen activator receptor (suPAR) is a risk factor for kidney diseases. Here we report the presence of C-terminal suPAR fragment, D2D3, in patients with diabetic nephropathy. D2D3-positive human sera inhibited glucose-stimulated insulin release in human islets and were associated with patients requiring insulin therapy. D2D3 transgenic mice presented kidney disease and diabetes marked by decreased levels of insulin and C-peptide, impaired glucose-stimulated insulin secretion, decreased pancreatic β-cell mass, and high fasting glucose. D2D3 fragment dysregulated glucose-induced cytoskeletal dynamics, impaired maturation and trafficking of insulin granules, and inhibited bioenergetics of β-cells in culture. An anti-uPAR antibody restored β-cell function in D2D3 transgenic mice. We show that the D2D3 fragment injures the kidney and pancreas, offering a unique dual therapeutic approach for kidney diseases and insulin-dependent diabetes.SummaryProteolytic suPAR fragment, D2D3, simultaneously injures two organs, the kidney and pancreas, thus causing a dual organ disease.
happi: a Hierarchical Approach to Pangenomics Inference
Authors: Trinh Pauline , Clausen David S. , Willis Amy D. 
Published: April 2022

AbstractRecovering metagenome-assembled genomes (MAGs) from shotgun sequencing data is an increasingly common task in microbiome studies, as MAGs provide deeper insight into the functional potential of both culturable and non-culturable microorganisms. However, metagenome-assembled genomes vary in quality, and may contain omissions and contamination. These errors present challenges for detecting genes and comparing gene enrichment across sample types. To address this, we propose happi, an approach to testing hypotheses about gene enrichment that accounts for genome quality. We illustrate the advantages of happi over existing approaches using published Saccharibacteria MAGs and via simulation.
Genome-wide CRISPRi screening reveals regulators of Alzheimer’s tau pathology shared between exosomal and vesicle-free tau seeds
Authors: Polanco Juan Carlos , Akimov Yevhen , Fernandes Avinash , Hand Gabriel Rhys , Briner Adam , van Roijen Marloes , Balistreri Giuseppe , Götz Jürgen 
Published: April 2022

AbstractAggregation of the microtubule-associated protein tau is a defining feature of Alzheimer’s disease and other tauopathies. Tau pathology is believed to be driven by both free tau aggregates and tau carried within exosomes, which propagate trans-synaptically and induce tau pathology in recipient neurons by a corrupting process of seeding. Here, we performed a genome-wide CRISPRi screen in tau biosensor cells and identified cellular regulators shared by both mechanisms of tau seeding. The top validated regulators are ANKLE2, BANF1, NUSAP1, EIF1AD, and VPS18, which work as factors that restrict tau aggregation initiated by both exosomal and vesicle-free tau seeds. Interestingly, ANKLE2 and BANF1 more robustly affected exosomal tau seeding than free aggregates. Lastly, validation studies revealed that several of the identified protein hits are downregulated in the brains of Alzheimer’s patients, suggesting that their decreased activity may be required for the emergence or progression of tau pathology in the human brain.
How to measure response diversity
Authors: Ross Samuel R.P-J. , Petchey Owen L. , Sasaki Takehiro , Armitage David W. 
Published: April 2022

AbstractThe insurance effect of biodiversity—that diversity stabilises aggregate ecosystem properties—is mechanistically underlain by inter- and intraspecific trait variation in organismal responses to the environment. This variation, termedresponse diversity, is therefore a potentially critical determinant of ecological stability. However, response diversity has yet to be widely quantified, possibly due to difficulties in its measurement. Even when it has been measured, approaches have varied.Here, we review methods for measuring response diversity and from them distil a methodological framework for quantifying response diversity from experimental and/or observational data, which can be practically applied in lab and field settings across a range of taxa.Previous empirical studies on response diversity most commonly invoke response traits as proxies aimed at capturing species’ ecological responses to the environment. Our approach, which is based on environment-dependent ecological responses to any biotic or abiotic environmental variable, is conceptually simple and robust to any form of environmental response, including nonlinear responses. Given its derivation from empirical data on species’ ecological responses, this approach should more directly reflect response diversity than the trait-based approach dominant in the literature.By capturing even subtle inter- or intraspecific variation in environmental responses, and environment-dependencies in response diversity, we hope this framework will motivate tests of the diversity-stability relationship from a new perspective, and provide an approach for mapping, monitoring, and conserving this critical dimension of biodiversity.
P681 mutations within the polybasic motif of spike dictate fusogenicity and syncytia formation of SARS CoV-2 variants
Authors: Kuzmina Alona , Atari Nofar , Ottolenghi Aner , Korovin Dina , lass Ido Cohen , Rosental Benyamin , Rosenberg Elli , Mandelboim Michal , Taube Ran 
Published: April 2022

AbstractThe rapid spread and dominance of the Omicron SARS-CoV-2 over its Delta variant has posed severe global challenges. While extensive research on the role of the Receptor Binding Domain on viral infectivity and vaccine sensitivity has been documented, the role of the spike681PRRAR/SV687polybasic motif is less clear. Here we monitored infectivity and vaccine sensitivity of Omicron SARS-CoV-2 pseudovirus against sera samples that were drawn four months post administration of the third dose of BNT162b2 mRNA vaccine. Our findings show that relative to Wuhan-Hu and Delta SARS-CoV-2, Omicron displayed enhanced infectivity and a sharp decline in its sensitivity to vaccine-induced neutralizing antibodies. Furthermore, while the spike proteins form Wuhan-Hu (P681), Omicron (H681) and BA.2 (H681) pseudoviruses modestly promoted cell fusion and syncytia formation, Delta spike (P681R) displayed enhanced fusogenic activity and syncytia formation capability. Live-viruses plaque formation assays confirmed these findings and demonstrated that relatively to the Wuhan-Hu and Omicron SARS-CoV-2, Delta formed more plaques that were smaller in size. Introducing a single P681R point mutation within the Wuhan-Hu spike, or H681R within Omicron spike, restored fusion potential to similar levels observed for Delta spike. Conversely, a R681P point mutation within Delta spike efficiency abolished fusion potential. We conclude that over time, the efficiency of the third dose of the Pfizer vaccine against SARS CoV-2 is waned, and cannot neutralize Omicron. We further verify that the P681 position of the viral spike dictates fusogenicity and syncytia formation.
Multi-level analysis of adipose tissue reveals the relevance of perivascular subpopulations and an increased endothelial permeability in early-stage lipedema
Authors: Strohmeier Karin , Hofmann Martina , Jacak Jaroslaw , Narzt Marie-Sophie , Wahlmueller Marlene , Mairhofer Mario , Schaedl Barbara , Holnthoner Wolfgang , Barsch Martin , Sandhofer Matthias , Wolbank Susanne , Priglinger Eleni 
Published: April 2022

AbstractLipedema is a chronic, progressive disease of adipose tissue with unknown etiology. Based on the relevance of the stromal vascular fraction (SVF) cell population in lipedema, we performed a thorough characterization of subcutaneous adipose tissue, SVF isolated thereof and the sorted populations of endothelial cells (EC), pericytes and cultured adipose-derived stromal/stem cells (ASC) of early-stage lipedema patients. We employed histological and gene expression analysis and investigated the endothelial barrier by immunofluorescence and analysis of endothelial permeability in vitro. Although there were no significant differences in histological stainings, we found altered gene expression of factors relevant for local estrogen metabolism (aromatase), preadipocyte commitment (ZNF423) and immune cell infiltration (CD11c) in lipedema on tissue level as well as in distinct cellular subpopulations. Machine learning analysis of immunofluorescence images of CD31 and ZO-1 revealed a morphological difference in the cellular junctions of EC cultures derived from healthy and lipedema individuals. Furthermore, the secretome of lipedema-derived SVF cells was sufficient to significantly increase leakiness of healthy human primary EC, which was also reflected by decreased mRNA expression of VE-cadherin. Here we showed for the first time, that the secretome of SVF cells creates an environment that triggers endothelial barrier dysfunction in early-stage lipedema. Moreover, since alterations in gene expression were detected on the cellular and/or tissue level, the choice of sample material is of high importance in elucidating this complex disease.
Preclinical interstitial lung disease in relatives of familial pulmonary fibrosis patients
Authors: Lucas Sionne EM , Raspin Kelsie , Mackintosh John , Glaspole Ian , Reynolds Paul N , Chia Collin , Grainge Christopher , Kendall Peter , Troy Lauren , Schwartz David A , Wood-Baker Richard , Walsh Simon LF , Moodley Yuben , Robertson James , Macansh Sacha , Walters Eugene H , Chambers Daniel , Corte Tamera J , Dickinson Joanne L 
Published: April 2022

ABSTRACTFamily history is amongst the strongest risk factors for interstitial lung disease (ILD), with emerging evidence for a shared genetic aetiology across ILD subtypes. Recruited families comprised at least two first-degree relatives who had been previously diagnosed with an ILD. All living cases and available unaffected first-degree relatives underwent a clinical examination for evidence of ILD. Preclinical ILD was diagnosed in 47.7% of first-degree relatives who had previously self-reported as unaffected. This study highlights the strong genetic predisposition in family members of ILD cases, and supports the call for routine screening of individuals with a family history of ILD.
Urban greenspace and anxiety symptoms during the COVID-19 pandemic: A 20-month follow up of 19,848 participants in England
Authors: Bu Feifei , Mak Hei Wan , Steptoe Andrew , Wheeler Benedict W , Fancourt Daisy 
Published: April 2022

AbstractThis study examined the association between greenspace and the growth trajectories of anxiety symptoms during the COVID-19 pandemic. Using data from 19,848 urban residents in England who were followed for 20 months between March 2020 and October 2021, we found that living in an area with higher greenspace coverage was associated with fewer anxiety symptoms over time independent of population density, area deprivation levels, socio-demographics, and health profiles. There was limited evidence that greenspace was related to the change of anxiety symptoms over time. No association with anxiety trajectories was found when using greenspace proximity.
Removal of Clinically Relevant SARS-CoV-2 Variants by An Affinity Resin Containing Galanthus nivalis Agglutinin
Authors: Gooldy Melanie , Roux Christelle M. , LaRosa Steven P. , Spaulding Nicole , Fisher Charles J. 
Published: April 2022

AbstractThe Coronavirus-19 (COVID-19) pandemic due to the SARS-CoV-2 virus has now exceeded two years in duration. The pandemic has been characterized by the development of a succession of variants containing mutations in the spike protein affecting infectiousness, virulence and efficacy of vaccines and monoclonal antibodies. Resistance to vaccination and limitations in the current treatments available require the ongoing development of therapies especially for those with severe disease. The plant lectin Galanthus nivalis binds to mannose structures in the viral envelope. We hypothesized that viral binding should be unaffected by spike protein mutations. Known concentrations of seven clinically relevant SARS-CoV-2 variants were spiked in medium and passed three times over columns containing 1 gm of GNA affinity resin. Percent decrease in viral titer was compared with a control sample. Viral capture efficiency was found to range from 53 to 89% for all variants. Extrapolation indicated that an adult Aethlon Hemopurifier® would have more than sufficient binding capacity for viral loads observed in adult patients with severe COVID-19 infection.
Coordination between ECM and cell-cell adhesion regulates the development of islet aggregation, architecture, and functional maturation
Authors: Tixi Wilma , Maldonado Maricela , Chang Ya-Ting , Chiu Amy , Yeung Wilson , Parveen Nazia , Nelson Michael , Hart Ryan , Wang Shihao , Hsu Wu Jih , Fueger Patrick , Kopp Janel L. , Huising Mark O. , Dhawan Sangeeta , Shih Hung-Ping 
Published: April 2022

SUMMARYPancreatic islets are 3-dimensional cell aggregates consisting of unique cellular composition, cell-to-cell contacts, and interactions with blood vessels. Cell aggregation is essential for islet endocrine function; however, it remains unclear how developing islets establish aggregation. By combining genetic animal models, imaging tools, and gene expression profiling, we demonstrate that islet aggregation is regulated by extracellular matrix signaling and cell-cell adhesion. Islet endocrine cell-specific inactivation of extracellular matrix receptor Integrin β1 disrupted blood vessel interactions but promoted cell-cell adhesion and the formation of larger islets. In contrast, ablation of cell-cell adhesion molecule α-Catenin promoted blood vessel interactions yet compromised islet clustering. Simultaneous removal of Integrin β1 and α-Catenin disrupts islet aggregation and the endocrine cell maturation process, demonstrating that establishment of islet aggregates is essential for functional maturation. Our study provides new insights into understanding the fundamental self-organizing mechanism for islet aggregation, architecture, and functional maturation.HIGHLIGHTSIslet vascularization and aggregation are regulated via ECM-Itgb1 signalingECM-Itgb1 signaling negatively controls islet aggregation via regulation of cell-cell adhesion during developmentCell-cell adhesion negatively regulates the interaction of endocrine cell-vasculature in isletsDifferential cell adhesion regulates the establishment of islet architectureEndocrine functional maturation depends on islet aggregation regulated by the coordination of ECM-Itgb1 signaling and cell-cell adhesion