bluuebunny/crossref_metadata_2025_split huggingface dataset:
Imaging synaptic microstructure and synaptic loss in vivo in early Alzheimer’s Disease
Authors: Venkataraman Ashwin V , Bishop Courtney , Mansur Ayla , Rizzo Gaia , Lewis Yvonne , Kocagoncu Ece , Lingford-Hughes Anne , Huiban Mickael , Passchier Jan , Rowe James B , Tsukada Hideo , Brooks David J. , Martarello Laurent , Comley Robert A. , Chen Laigao , Hargreaves Richard , Schwarz Adam J. , Gunn Roger N. , Rabiner Eugenii A. , Matthews Paul M 
Published: November 2021

1.ABSTRACTBackgroundSynaptic loss and neurite dystrophy are early events in Alzheimer’s Disease (AD). We aimed to characterise early synaptic microstructural changes in vivo.MethodsMRI neurite orientation dispersion and density imaging (NODDI) and diffusion tensor imaging (DTI) were used to image cortical microstructure in both sporadic, late onset, amyloid PET positive AD patients and healthy controls (total n = 28). We derived NODDI measures of grey matter extracellular free water (FISO), neurite density (NDI) and orientation dispersion (ODI), which provides an index of neurite branching and orientation, as well as more conventional DTI measures of fractional anisotropy (FA), mean/axial/radial diffusivity (MD, AD, RD, respectively). We also performed [11C]UCB-J PET, which provides a specific measure of the density of pre-synaptic vesicular protein SV2A. Both sets of measures were compared to regional brain volumes.ResultsThe AD patients showed expected relative decreases in regional brain volumes (range, -6 to - 23%) and regional [11C]UCB-J densities (range, -2 to -25%). Differences between AD and controls were greatest in the hippocampus. NODDI microstructural measures showed greater FISO (range, +26 to +44%) in AD, with little difference in NDI (range, -1 to +7%) and mild focal changes in ODI (range, -4 to +3%). Regionally greater FISO and lower [11C]UCB-J binding were correlated across grey matter in patients (most strongly in the caudate, r2 = 0.37, p = 0.001). FISO and DTI RD were strongly positively associated, particularly in the hippocampus (r2 = 0.98, p < 7.4 × 10−9). After 12-18 months we found a 5% increase in FISO in the temporal lobe, but little change across all ROIs in NDI and ODI. An exploratory analysis showed higher parietal lobe FISO was associated with lower language scores in people with AD.ConclusionsWe interpreted the increased extracellular free water as a possible consequence of glial activation. The dynamic range of disease-associated differences and the feasibility of measuring FISO on commercially available imaging systems makes it a potential surrogate for pathology related to synapse loss that could be used to support early-stage evaluations of novel therapeutics for AD.
Recurring Spatiotemporal Patterns of COVID-19 in the United States
Authors: Jalal Hawre , Lee Kyueun , Burke Donald S. 
Published: November 2021

AbstractWe analyzed the waxing and waning patterns (“surges”) of reported SARS-CoV-2 cases from January 1, 2020 through Oct 31, 2021 in all states and provinces (n = 93) in the USA, Mexico, and Canada, and across all counties (N = 3142) in the USA. A correlation matrix of the 576 × 576 daily case incidence rates in the 50 US states generates a distinctive “checkerboard” pattern showing that the epidemic has consisted of seven distinct internally coherent spatiotemporal wave patterns, four in the first year of the epidemic, and three thus far in the second year. Geoclustering of state case rate trajectories reveals three dominant co-varying spatial clusters of similar case rate trajectories, in the northeastern, southeastern and central/western regions of the USA. The spatiotemporal patterns of epidemic year 1 have thus far been repeated (p<.001) in epidemic year 2. The “checkerboard” pattern of the correlation matrix of case trajectories can be closely simulated as three sets of interacting sine waves with annual frequencies of 1:1:2 major cycles per year, corresponding to the northeastern, central/western, and southeastern state clusters. Case incidence patterns in Mexico and Canada have been similar to nearby regions in the southern US and the northern US, respectively. Time lapse videos allow visualization of the wave patterns. These highly structured geographical and temporal patterns, coupled with emerging evidence of annual repetition of these same patterns, show that SARS-CoV-2 case rates are driven at least in part by predictable seasonal factors.Significance StatementLocal COVID-19 rates wax and wane. Often these epidemic changes are attributed to localized human behavioral factors. Our finding of highly structured continental scale spatiotemporal patterns that cross state and national boundaries, coupled with emerging evidence of annual repetition of these same patterns, shows that COVID-19 transmission is driven at least in part by seasonal factors. Other epidemic factors such as vaccine coverage rates, or emergence of new strains like the Delta variant of SARS-CoV-2 appear to modify, but not totally eclipse, these underlying seasonal patterns. COVID-19 seasonal transmission patterns are associated with, and may be driven by, seasonal weather patterns. Predictability of these patterns can provide opportunities for forecasting the epidemic and for guiding public health preparedness and control efforts.
Phylogeny of the ingoid clade (Caesalpinioideae, Fabaceae), based on nuclear and plastid data
Authors: Ferm Julia , Ståhl Bertil , Wikström Niklas , Rydin Catarina 
Published: November 2021

AbstractWe investigated generic relationships in the ingoid clade (Fabaceae) (sensu Koenen & al. 2020a), with main focus on genera with a taxonomic history inCalliandras.l. of the tribe Ingeae (i.e.Afrocalliandra, Calliandras.s.,Sanjappa, Thailentadopsis, Viguieranthus, Zapoteca), and three genera of the tribe Acacieae (i.e.,Acacia, Acaciella, Senegalia). The nuclear ribosomal ETS and ITS, and the plastidmatK, trnL-trnFandycf1DNA-regions were analysed for 246 representatives from 36 genera using maximum likelihood as implemented in IQ-tree. The results show an Ingeae–Acaciaclade within the ingoid clade, resolved in three major clades. Clade 1 (Calliandras.s. andAfrocalliandra) is sister to clades 2 and 3. Clade 2 comprisesFaidherbia, Sanjappa, Thailentadopsis, ViguieranthusandZapoteca. Clade 3 comprises the remaining genera of the Ingeae, plusAcacia. The ingoid genusSenegaliais excluded from the Ingeae–Acaciaclade.Acaciellais sister to the remaining ingoid clade when nuclear ribosomal data is included in the analyses, but included in the Ingeae–Acaciaclade based on plastid data.Acaciaand perhaps alsoAcaciellaare thus nested within Ingeae. Species traditionally referred toCalliandra(Calliandras.l.) are resolved in two clades, and the “Calliandra-pod” has apparently evolved independently several times.
SARS-CoV-2 Delta Spike Protein Enhances the Viral Fusogenicity and Inflammatory Cytokine Production
Authors: Ao Zhujun , Ouyang Maggie Jing , Olukitibi Titus Abiola , Yao Xiaojian 
Published: November 2021

SUMMARYThe Delta variant is now the most dominant and virulent SARS-CoV-2 variant of concern (VOC). In this study, we investigated several virological features of Delta spike protein (SPDelta), including protein maturation and its impact on viral entry of cell-free pseudotyped virus, cell-cell fusion ability and its induction of inflammatory cytokine production in human macrophages and dendritic cells. The results showed that SPΔCDelta exhibited enhanced S1/S2 cleavage in cells and pseudotyped virus-like particles (PVLPs). We further showed that SPΔCDelta elevated pseudovirus infection in human lung cell lines and mediated significantly enhanced syncytia formation. Furthermore, we revealed that SPΔCDelta-PVLPs had stronger effects on stimulating NF-κB and AP-1 signaling in human monocytic THP1 cells and induced significantly higher levels of pro-inflammatory cytokine, such as TNF-α, IL-1β and IL-6, released from human macrophages and dendritic cells. Overall, these studies provide evidence to support the important role of SPΔCDelta during virus infection, transmission and pathogenesis.
Learning the Rules of Cell Competition without Prior Scientific Knowledge
Authors: Soelistyo Christopher J. , Vallardi Giulia , Charras Guillaume , Lowe Alan R. 
Published: November 2021

AbstractDeep learning is now a powerful tool in microscopy data analysis, and is routinely used for image processing applications such as segmentation and denoising. However, it has rarely been used to directly learn mechanistic models of a biological system, owing to the complexity of the internal representations. Here, we develop an end-to-end machine learning model capable of learning the rules of a complex biological phenomenon, cell competition, directly from a large corpus of time-lapse microscopy data. Cell competition is a quality control mechanism that eliminates unfit cells from a tissue and during which cell fate is thought to be determined by the local cellular neighborhood over time. To investigate this, we developed a new approach (τ-VAE) by coupling a probabilistic encoder to a temporal convolution network to predict the fate of each cell in an epithelium. Using the τ-VAE’s latent representation of the local tissue organization and the flow of information in the network, we decode the physical parameters responsible for correct prediction of fate in cell competition. Remarkably, the model autonomously learns that cell density is the single most important factor in predicting cell fate – a conclusion that is in agreement with our current understanding from over a decade of scientific research. Finally, to test the learned internal representation, we challenge the network with experiments performed in the presence of drugs that block signalling pathways involved in competition. We present a novel discriminator network that, using the predictions of the τ-VAE, can identify conditions which deviate from the normal behaviour, paving the way for automated, mechanism-aware drug screening.
Fluidic Circuit Board with Modular Sensor and Valves Enables Stand-Alone, Tubeless Microfluidic Flow Control in Organs-on-Chips
Authors: Vivas Aisen , van den Berg Albert , Passier Robert , Odijk Mathieu , van der Meer Andries D. 
Published: November 2021

AbstractOrgans-on-chips are a unique class of microfluidic in vitro cell culture models, in which the in vivo tissue microenvironment is mimicked. Unfortunately, its widespread use is hampered by their operation complexity and incompatibility with end-user research settings. To address these issues, many commercial and non-commercial platforms have been developed for semi-automated culture of organs-on-chips. However, these organ-on-chip culture platforms each represent a closed ecosystem, with very little opportunity to interchange and integrate components from different platforms or to develop new ones. The Translational Organ-on-Chip Platform (TOP) is a multi-institutional effort to develop an open platform for automated organ-on-chip culture and integration of components from various developers. Central to TOP is the fluidic circuit board (FCB), a microfluidic plate with the form factor of a typical well plate. The FCB enables microfluidic control of multiple components like sensors or organ-on-chip devices through an interface based on openly available standards. Here, we report an FCB to integrate commercial and in-house developed components forming a stand-alone flow control system for organs-on-chips. The control system is able to achieve constant and pulsatile flow recirculation through a connected organ-on-chip device. We demonstrate that this system is able to automatically perfuse a heart-on-chip device containing co-cultures of cardiac tissues derived from human pluripotent stem cell-derived cardiomyocytes and monolayers of endothelial cells for five days. Altogether, we conclude that open technology platforms allow the integration of components from different sources to form functional and fit-for-purpose organ-on-chip systems. We anticipate that open platforms will play a central role in catalysing and maturing further technological development of organ-on-chip culture systems.
ECLIPSER: identifying causal cell types and genes for complex traits through single cell enrichment of e/sQTL-mapped genes in GWAS loci
Authors: Rouhana John M. , Wang Jiali , Eraslan Gokcen , Anand Shankara , Hamel Andrew R. , Cole Brian , Regev Aviv , Aguet François , Ardlie Kristin G. , Segrè Ayellet V. 
Published: November 2021

AbstractSummaryECLIPSER was developed to identify pathogenic cell types and cell type-specific genes that may affect complex disease susceptibility and trait variation by integrating single cell data with known GWAS loci. ECLIPSER maps genes to GWAS loci for a given complex trait based on expression and splicing quantitative trait loci (e/sQTLs) and other functional data, and tests whether the mapped genes are enriched for cell type-specific expression in particular cell types using single-cell/nucleus RNA-seq data from one or more tissues of interest. A Bayesian Fisher’s exact test is used to compute fold-enrichment significance. We demonstrate the application of ECLIPSER on various skin diseases and traits using snRNA-seq of healthy human skin samples.Availability and ImplementationThe source code and documentation for ECLIPSER and a Jupyter notebook for generating output tables and figures are available at https://github.com/segrelabgenomics/ECLIPSER. The source code for GWASvar2gene that maps genes to GWAS loci based on e/sQTLs is available at https://github.com/segrelabgenomics/GWASvar2gene. The analysis presented here used data from GTEx (https://gtexportal.org/home/datasets) and Open Targets Genetics (https://genetics-docs.opentargets.org/data-access/graphql-api), but can also be applied to other GWAS variant lists and QTL studies. Data used to reproduce the results of the paper are available in Supplementary data.
Spread of pathological human Tau from neurons to oligodendrocytes and loss of high-firing pyramidal neurons in ageing mice
Authors: Viney Tim J. , Sarkany Barbara , Ozdemir A. Tugrul , Hartwich Katja , Schweimer Judith , Bannerman David , Somogyi Peter 
Published: November 2021

AbstractIntracellular aggregation of hyperphosphorylated Tau (pTau) in the brain is associated with cognitive and motor impairments, and ultimately neurodegeneration. We investigate how human pTau affects cells and network activity in the hippocampal formation of THY-Tau22 tauopathy model micein vivo. We find that pTau preferentially accumulates in deep-layer pyramidal neurons, leading to neurodegeneration, and we establish that pTau spreads to oligodendrocytes. During goal-directed virtual navigation in aged transgenic mice, we detect fewer high-firing prosubicular pyramidal cells but the firing population retains its coupling to theta oscillations. Analysis of network oscillations and firing patterns of pyramidal and GABAergic neurons recorded in head-fixed and freely-moving mice suggests preserved neuronal coordination. In spatial memory tests, transgenic mice have reduced short-term familiarity but spatial working and reference memory are surprisingly normal. We hypothesize that unimpaired subcortical network mechanisms maintain cortical neuronal coordination, counteracting the widespread pTau aggregation, loss of high-firing cells, and neurodegeneration.
High diversity in the regulatory region of Stx-converting bacteriophage genomes
Authors: Fagerlund Annette , Aspholm Marina , Węgrzyn Grzegorz , Lindbäck Toril 
Published: November 2021

ABSTRACTShiga toxin (Stx) is the major virulence factor of enterohemorrhagic Escherichia coli (EHEC), and the stx genes are carried by temperate bacteriophages (Stx phages). The switch between lysogenic and lytic life cycle of the phage, which is crucial for Stx production and for severity of the disease, is regulated by the CI repressor. CI maintain latency by preventing transcription of the replication proteins. Three EHEC phage replication units (Eru1-3) in addition to the classical lambdoid replication region have been described previously, and Stx phages carrying the Eru1 replication region were associated with highly virulent EHEC strains. In this study, we have classified the Eru replication region of 419 Stx phages. In addition to the lambdoid replication region and the three already described Erus, ten novel Erus (named Eru4 to Eru13) were detected. The lambdoid type, Eru1, Eru4 and Eru7 seem to be widely distributed in Western Europe. Notably, EHEC strains involved in severe outbreaks in England and Norway carry Stx phages with Eru1, Eru2, Eru5 and Eru7 replication regions. Phylogenetic analysis of CI repressors from Stx phages revealed eight major clades that largely separate according to Eru type. The classification of replication regions and CI proteins of Stx phages provides an important platform for further studies aimed to assess how characteristics of the replication region influence the regulation of phage life cycle and, consequently, the virulence potential of the host EHEC strain.IMPORTANCEEHEC is an emerging health challenge worldwide and outbreaks caused by this pathogen tend to be more frequent and severe. Increased knowledge on how characteristics of the replication region influence the virulence of E. coli may be used for more precise identification of high-risk EHEC strains.
High prevalence ofKlebsiella pneumoniaein European food products: a multicentric study comparing culture and molecular detection methods
Authors: Rodrigues Carla , Hauser Kathrin , Cahill Niamh , Ligowska-Marzęta Małgorzata , Centorotola Gabriella , Cornacchia Alessandra , Garcia Fierro Raquel , Haenni Marisa , Møller Nielsen Eva , Piveteau Pascal , Barbier Elodie , Morris Dearbháile , Pomilio Francesco , Brisse Sylvain 
Published: November 2021

AbstractKlebsiella pneumoniaespecies complex (KpSC) is a leading cause of multidrug-resistant human infections. To better understand the potential contribution of food as a vehicle of KpSC, we conducted a multicentric study to define an optimal culture method for its recovery from food matrices, and to characterize food isolates phenotypically and genotypically. Chicken meat (n=160) and salad (n=145) samples were collected in five European countries and screened for KpSC presence using culture-based and ZKIR qPCR methods. Enrichment using buffered peptone water followed by streaking on Simmons citrate agar with inositol (44°C/48h) was defined as the most suitable selective culture method for KpSC recovery. High prevalence of KpSC was found in chicken meat (60% and 52% by ZKIR qPCR and culture approach, respectively) and salad (30% and 21%, respectively) samples. Genomic analyses revealed high genetic diversity with the dominance of phylogroups Kp1 (91%) and Kp3 (6%). 82% of isolates presented a natural antimicrobial susceptibility phenotype and genotype, with only four CTX-M-15-producing isolates detected. Notably, identical genotypes were found across samples: same food type and same country (15 cases); different food types and same country (1); same food type and two countries (1), suggesting high rates of transmission of KpSC within the food sector. Our study provides a novel isolation strategy for KpSC from food matrices and reinforces the view of food as a potential source of KpSC colonization in humans.ImportanceBacteria of theKlebsiella pneumoniaespecies complex (KpSC) are ubiquitous andK. pneumoniae(Kp) is a leading cause of antibiotic-resistant infections in humans and animals. Despite the urgent public health threat represented by Kp, there is a lack of knowledge on the contribution of food sources to colonization and subsequent infection in humans. This is partly due to the absence of standardized methods for characterizing KpSC presence in food matrices. Our multicentric study provides and implements a novel isolation strategy for KpSC from food matrices and shows that KpSC members are highly prevalent in salads and chicken meat, reinforcing the view of food as a potential source of KpSC colonization in humans. Despite the large genetic diversity and the low-levels of resistance detected, the occurrence of identical genotypes across samples suggests high rates of transmission of KpSC within the food sector, which need to be further explored to define possible control strategies.
Identification of differentially expressed genes and signaling pathways in gestational diabetes mellitus by integrated bioinformatics analysis
Authors: Vastrad Basavaraj , Vastrad Chanabasayya 
Published: November 2021

AbstractGestational diabetes mellitus (GDM) is a metabolic disorder during pregnancy. Numerous biomarkers have been identified that are linked with the occurrence and development of GDM. The aim of this investigation was to identify differentially expressed genes (DEGs) in GDM using a bioinformatics approach to elucidate their molecular pathogenesis. GDM associated expression profiling by high throughput sequencing dataset (GSE154377) was obtained from Gene Expression Omnibus (GEO) database including 28 normal pregnancy samples and 33 GDM samples. DEGs were identified using DESeq2. The gene ontology (GO) and REACTOME pathway enrichments of DEGs were performed by g:Profiler. Protein-protein interaction (PPI) networks were assembled with Cytoscape software and separated into modules using the PEWCC1 algorithm. MiRNA-hub gene regulatory network and TF-hub gene regulatory network were performed with the miRNet database and NetworkAnalyst database. Receiver Operating Characteristic (ROC) analyses was conducted to validate the hub genes. A total of 953 DEGs were identified, of which 478 DEGs were up regulated and 475 DEGs were down regulated. Furthermore, GO and REACTOME pathway enrichment analysis demonstrated that these DEGs were mainly enriched in multicellular organismal process, cell activation, formation of the cornified envelope and hemostasis. TRIM54, ELAVL2, PTN, KIT, BMPR1B, APP, SRC, ITGA4, RPA1 and ACTB were identified as key genes in the PPI network, miRNA-hub gene regulatory network and TF-hub gene regulatory network. TRIM54, ELAVL2, PTN, KIT, BMPR1B, APP, SRC, ITGA4, RPA1 and ACTB in GDM were validated using ROC analysis. This investigation provides further insights into the molecular pathogenesis of GDM, which might facilitate the diagnosis and treatment of GDM.
Correspondence analysis for dimension reduction, batch integration, and visualization of single-cell RNA-seq data
Authors: Hsu Lauren L. , Culhane Aedín C. 
Published: November 2021

AbstractEffective dimension reduction is essential for single cell RNA-seq (scRNAseq) analysis. Principal component analysis (PCA) is widely used, but requires continuous, normally-distributed data; therefore, it is often coupled with log-transformation in scRNAseq applications, which can distort the data and obscure meaningful variation. We describe correspondence analysis (CA), a count-based alternative to PCA. CA is based on decomposition of a chi-squared residual matrix, avoiding distortive logtransformation. To address overdispersion and high sparsity in scRNAseq data, we propose five adaptations of CA, which are fast, scalable, and outperform standard CA and glmPCA, to compute cell embeddings with more performant or comparable clustering accuracy in 8 out of 9 datasets. In particular, we find that CA with Freeman-Tukey residuals (CA-FT) performs especially well across diverse datasets. Other advantages of the CA framework include visualization of associations between genes and cell populations in a “CA biplot,” and extension to multi-table analysis; we introducecorralmfor integrative multi-table dimension reduction of scRNAseq data. We implement CA for scRNAseq data incorral, an R/Bioconductor package which interfaces directly with single cell classes in Bioconductor. Switching from PCA to CA is achieved through a simple pipeline substitution and improves dimension reduction of scRNAseq datasets.