bluuebunny/crossref_metadata_2025_split huggingface dataset:
Latent anxiety and depression dimensions differ among eating disorders: a Swedish nationwide investigation
Authors: Hübel Christopher , Birgegård Andreas , Johansson Therese , Petersen Liselotte V. , Isomaa Rasmus , Herle Moritz 
Published: May 2022

AbstractObjectiveAnxiety and depression symptoms are common in eating disorders. To study these, we need high-quality self-report questionnaires. The 19-item self-rated Comprehensive Psychopathological Rating Scale for Affective Syndromes (CPRS-S-A) is not validated in eating disorders. We tested its factor structure, invariance, and differences its latent dimensions.MethodPatients were registered by 45 treatment units in the Swedish nationwide Stepwise quality assurance database for specialised eating disorder care (n= 9,509). Patients self-reported their anxiety and depression symptoms on the CPRS-S-A. Analyses included exploratory and confirmatory factor analysis in a split samples and invariance difference testing in subscales across eating disorders.ResultsResults suggested a four-factor solution: Depression, Somatic & fear symptoms, Disinterest, and Worry. Multigroup confirmatory factor analysis indicated an invariant factor structure. We detected the following differences: Patients with anorexia nervosa binge-eating/purging subtype scored the highest and patients with unspecified feeding and eating disorders the lowest on all subscales. Patients with anorexia nervosa or purging disorder show more somatic & fear symptoms than individuals with either bulimia nervosa or binge-eating disorder.ConclusionOur four-factor solution of the CPRS-S-A is suitable for patients with eating disorders and may help to identify differences in anxiety and depression dimensions amongst eating disorders.Significant Outcomes⍰Symptoms of anxiety and depression in eating disorder patients load on four dimensions: Depression, Somatic & fear symptoms, Disinterest, and Worry.⍰Patients with anorexia nervosa binge-eating/purging subtype show the largest depression and anxiety symptom burden while patients with subsyndromal forms of eating disorders show the lowest.⍰Instead of calculating total scores of anxiety and depression, a dimensional approach delivers more fine-grained association results.Limitations⍰Our sample consisted of eating disorder patients only and there was no healthy control group or data from patients with other psychiatric disorders for comparison.⍰The sample consisted predominantly of women which limits the ability to identify sex differences.⍰The sample included Swedish treatment seeking patients of mostly white European ancestry limiting the generalisability of our findings.
A repeat pattern of founder events for SARS-CoV-2 variants in Alaska
Authors: Haan Tracie J. , Smith Lisa K. , DeRonde Stephanie , House Elva , Zidek Jacob , Puhak Diana , Mullen Logan , Redlinger Matthew , Parker Jayme , Barnes Brian M. , Burkhead Jason L. , Knall Cindy , Bortz Eric , Chen Jack , Drown Devin M. 
Published: May 2022

AbstractAlaska is a unique US state because of its large size, geographically disparate population density, and physical distance from the contiguous United States. Here, we describe a pattern of SARS-CoV-2 variant emergence across Alaska reflective of these differences. Using genomic data, we found that in Alaska the Omicron sublineage BA.2.3 overtook BA.1.1 by the week of 2022-02-27, reaching 48.5% of sequenced cases. On the contrary in the contiguous United States, BA.1.1 dominated cases for longer, eventually being displaced by BA.2 sublineages other than BA.2.3. BA.2.3 only reached a prevalence of 10.9% in the contiguous United States. Using phylogenetics, we found evidence of potential origins of the two major clades of BA.2.3 in Alaska and with logistic regression estimated how it emerged and spread throughout the state. The combined evidence is suggestive of founder events in Alaska and is reflective of how Alaska’s unique dynamics influence the emergence of SARS-CoV-2 variants.
Genetic diversity of Staphylococcus aureus wall teichoic acid glycosyltransferases affects immune recognition
Authors: Tamminga Sara M. , Völpel Simon L. , Schipper Kim , Stehle Thilo , Pannekoek Yvonne , van Sorge Nina M. 
Published: May 2022

AbstractStaphylococcus aureus (S. aureus) is a leading cause of skin and soft tissue infections and (hospital-acquired) systemic infections. Wall teichoic acids (WTAs) are cell wall-anchored glycopolymers that are important for S. aureus nasal colonization, endocarditis, and antibiotic resistance. WTAs consist of a polymerized ribitol phosphate (RboP) chain that can be glycosylated with N-acetylglucosamine (GlcNAc) by three glycosyltransferases: TarS, TarM, and TarP. TarS and TarP modify WTA with β-linked GlcNAc on the C-4 (β1,4-GlcNAc) and the C-3 position (β1,3-GlcNAc) of the RboP subunit, respectively, whereas TarM modifies WTA with α-linked GlcNAc at the C-4 position (α1,4-GlcNAc). Importantly, these WTA glycosylation patterns impact immune recognition and clearance of S. aureus. Previous studies suggest that tarS is near-universally expressed within the S. aureus population, whereas a smaller proportion co-express either tarM or tarP. To gain more insight in the presence and genetic variation of tarS, tarM, and tarP in the S. aureus population, we analyzed a collection of 25,652 S. aureus genomes within the PubMLST database. Over 99% of isolates contained tarS. Co-expression of tarS/tarM or tarS/tarP occurred in 37% and 7% of isolates, respectively, and was associated to specific S. aureus clonal complexes. We also identified 26 isolates (0.1%) that contained all three glycosyltransferase genes. At sequence level, we identified tar alleles with amino acid substitutions in critical enzymatic residues or with premature stop codons. Several tar variants were expressed in a S. aureus tar-negative strain. Analysis using specific monoclonal antibodies and human langerin showed that WTA glycosylation was severely attenuated or absent. Overall, our data provide a broad overview of the genetic diversity of the three WTA glycosyltransferases in the S. aureus population and the functional consequences for immune recognition.
A generalizable brain extraction net (BEN) for multimodal MRI data from rodents, nonhuman primates, and humans
Authors: Yu Ziqi , Han Xiaoyang , Xu Wenjing , Zhang Jie , Marr Carsten , Shen Dinggang , Peng Tingying , Zhang Xiao-Yong , Feng Jianfeng 
Published: May 2022

AbstractAccurate brain tissue extraction on magnetic resonance imaging (MRI) data is crucial for analyzing brain structure and function. While several conventional tools have been optimized to handle human brain data, there have been no generalizable methods to extract brain tissues for multimodal MRI data from rodents, nonhuman primates, and humans. Therefore, developing a flexible and generalizable method for extracting whole brain tissue across species would allow researchers to analyze and compare experiment results more efficiently. Here, we propose a domain-adaptive and semi-supervised deep neural network, named the Brain Extraction Net (BEN), to extract brain tissues across species, MRI modalities, and MR scanners. We have evaluated BEN on 18 independent datasets, including 783 rodent MRI scans, 246 nonhuman primate MRI scans, and 4,601 human MRI scans, covering five species, four modalities, and six MR scanners with various magnetic field strengths. Compared to conventional toolboxes, the superiority of BEN is illustrated by its robustness, accuracy, and generalizability. Our proposed method not only provides a generalized solution for extracting brain tissue across species but also significantly improves the accuracy of atlas registration, thereby benefiting the downstream processing tasks. As a novel fully automated deep-learning method, BEN is designed as an open-source software to enable high-throughput processing of neuroimaging data across species in preclinical and clinical applications.
Programmable RNA Sensing for Cell Monitoring and Manipulation
Authors: Qian Yongjun , Li Jiayun , Zhao Shengli , Matthews Elizabeth , Adoff Michael , Zhong Weixin , An Xu , Yeo Michele , Park Christine , Wang Bor-Shuen , Southwell Derek , Huang Z. Josh 
Published: May 2022

ABSTRACTRNAs are the central and universal mediator of genetic information underlying the diversity of cell types and cell states, which together shape tissue organization and organismal function across species and life spans. Despite advances in RNA sequencing and massive accumulation of transcriptome datasets across life sciences, the dearth of technologies that leverage RNAs to observe and manipulate cell types remains a prohibitive bottleneck in biology and medicine. Here, we describe CellREADR (Cell access through RNA sensing by Endogenous ADAR), a programmable RNA sensing technology that leverages RNA editing mediated by ADAR (adenosine deaminase acting on RNA) for coupling the detection of cell-defining RNAs with translation of effector proteins. Viral delivery of CellREADR conferred specific cell type access in mouse and rat brains and in ex vivo human brain tissues. Furthermore, CellREADR enabled recording and control of neuron types in behaving mice. CellREADR thus highlights the potential for RNA-based monitoring and editing of animal cells in ways that are specific, versatile, easy, and generalizable across organ systems and species, with broad applications in biology, biotechnology, and programmable RNA medicine.
Integration of imaging modalities with lipidomic characterization to investigate MSCs potency metrics
Authors: Priyadarshani Priyanka , Van Grouw Alexandria , Liversage Adrian Ross , Nikitina Arina , Tehrani Kayvan Forouhesh , Kemp Melissa , Fernandez Facundo , Mortensen Luke J. 
Published: May 2022

AbstractMesenchymal stem cells (MSCs) are widely used as therapeutics targets for numerous autoimmune diseases. However, MSC therapies have had limited success so far in clinical trials, mainly being heterogenous population it is difficult to determine MSCs efficiencies. It is critical to understand internal signaling of individual MSCs population that directly affect the cell phenotype. Lipid signaling is closely associated with cell shape so, a holistic approach to understand how changes in lipid metabolites trickles all the way to single cell phenotype could reveal deeper understanding of MSCs functional regulation. So, we aim to evaluate lipid metabolic profiles of single cell MSCs with known variability in immune regulation and explore the phenotypic changes that occur because of differences in lipid signaling. We use longitudinal label free phase imaging strategies to obtain cell phenotypic features which are directly correlated with single cell lipid metabolome obtained using advanced MALDI-MSI technique. Correlation maps indicate associations between lipid signaling and phenotypic changes in MSCs.Moreover, a novel machine learning clustering approach detects the heterogeneity in the MSCs subpopulation then methodically see how each heterogenous population is being impacted by the changes in lipid profiles which could be linked to the functional behaviors of the cell.
Fast and accurate out-of-core PCA framework for large scale biobank data
Authors: Li Zilong , Meisner Jonas , Albrechtsen Anders 
Published: May 2022

AbstractPrincipal Component Analysis (PCA) is widely utilized in statistics, machine learning, and genomics for dimensionality reduction and uncovering low-dimensional latent structure. To address the challenges posed by ever-growing data size, fast and memory-efficient PCA methods have gained prominence. In this paper, we propose a novel Randomized Singular Value Decomposition (RSVD) algorithm implemented in PCAone, featuring a window-based optimization scheme that enables accelerated convergence while improving the accuracy. Additionally, PCAone incorporates out-of-core and multithreaded implementations for the existing Implicitly Restarted Arnoldi Method (IRAM) and RSVD. Through comprehensive evaluations using multiple large-scale real-world datasets in different fields, we demonstrate the advantage of PCAone over existing methods. The new algorithm achieves significantly faster computation time while maintaining accuracy comparable to the slower IRAM method. Notably, our analyses of UK Biobank, comprising around 0.5 million individuals and 6.1 million common SNPs, demonstrate that PCAone accurately computes the top 40 principal components within a 9 hours. This analysis effectively captures population structure, signals of selection, structural variants, and low recombination regions, utilizing less than 20 GB of memory and 20 CPU threads. Furthermore, when applied to single-cell RNA sequencing data featuring 1.3 million cells, PCAone, accurately capturing the top 40 principal components in 49 minutes. This performance represents a 10-fold improvement over state-of-the-art tools.
Accumulation of copy-back viral genomes during respiratory syncytial virus infection is preceded by diversification of the copy-back viral genome population followed by selection
Authors: Felt Sébastien A. , Achouri Emna , Faber Sydney R. , López Carolina B. 
Published: May 2022

AbstractRNA viruses generate non-standard viral genomes during their replication, including viral genomes of the copy-back (cbVG) type that cannot replicate in the absence of a standard virus. cbVGs play a crucial role in shaping virus infection outcomes due to their ability to interfere with virus replication and induce strong immune responses. However, despite their critical role during infection, the principles that drive the selection and evolution of cbVGs within a virus population are poorly understood. As cbVGs are dependent on the virus replication machinery to be generated and replicated, we hypothesized that host factors that affect virus replication exert selective pressure on cbVGs and drive their evolution within a virus population. To test this hypothesis, we used respiratory syncytial virus (RSV) as model and took an experimental evolution approach by serially passaging RSV in immune competent A549 control and immune deficient A549 STAT1 KO cells which allow higher levels of virus replication. As predicted, we observed that virus populations accumulated higher amounts of cbVGs in the more permissive A549 STAT1 KO cells over time but, unexpectedly, the predominant cbVG species after passages in the two conditions were different. While A549 STAT1 KO cells accumulated relatively short cbVGs, A549 control cells mainly contained cbVGs of much longer predicted size that have not been described previously. These long cbVGs were predominant at first in both cell linesin vitroand the predominant ones observed in samples from RSV infected patients. Although sustained high replication levels are associated with cbVG generation and accumulation, our data show that sustained high levels of virus replication are critical for cbVG population diversification, a process that preceded the generation of shorter cbVGs that selectively accumulated over time. Taken together, we show that selection and evolution of cbVGs within a virus population is shaped by how resistant or permissive a host is to RSV.
Using Extracellular Vesicles Released by GDNF-transfected Macrophages for Therapy of Parkinson’s Disease
Authors: Zhao Yuling , Haney Matthew J. , Fallon John K. , Rodriguez Myosotys , Swain Carson J. , Arzt Camryn J. , Smith Philip C. , Loop Matthew Shane , Harrison Emily B. , El-Hage Nazira , Batrakova Elena V. 
Published: May 2022

AbstractExtracellular vesicles (EVs) are cell-derived nanoparticles that facilitate transport of proteins, lipids and genetic material playing important roles in intracellular communication. They have a remarkable potential as non-toxic and non-immunogenic nanocarriers for drug delivery to unreachable organs and tissues, in particular, the central nervous system (CNS). Herein, we developed a novel platform based on macrophage derived EVs to treat Parkinson’s disease (PD). Specifically, we evaluated the therapeutic potential of EVs secreted by autologous macrophages that were transfectedex vivoto express glial cell line-derived neurotrophic factor (GDNF). EV-GDNF were collected from conditioned media of GDNF-transfected macrophages and characterized for GDNF content, size, charge, and expression of EV-specific proteins. The data revealed that along with the encoded neurotrophic factor, EVs released by pre-transfected macrophages carry GDNF-encoding DNA. Four months-old transgenic Parkin Q311(X)A mice were treated with EV-GDNFviaintranasal administration, and the effect of this therapeutic intervention on locomotor functions was assessed over a year. Significant improvements in mobility, increase in neuronal survival, and decrease in neuroinflammation were found in PD mice treated with EV-GDNF. No offsite toxicity caused by EV-GDNF administrations was detected. Overall, EV-based approach can provide a versatile and potent therapeutic intervention for PD.
Non-invasive monitoring of microbiota and host metabolism using Secondary electrospray ionization-Mass spectrometry
Authors: Lan Jiayi , Greter Giorgia , Streckenbach Bettina , Arnoldini Markus , Zenobi Renato , Slack Emma 
Published: May 2022

AbstractThe metabolic “handshake” between the microbiota and its mammalian host is a complex, dynamic process with potentially major influences on health. Dissecting the interaction between microbial species/strains and metabolites found in host tissues has been a challenge due to the high diversity of a complete micro-biota and the requirement for invasive sampling, which precludes high-resolution longitudinal analysis. Here we demonstrate that secondary electrospray ionization mass spectrometry can be used to non-invasively monitor metabolic activity of the intestinal microbiome of a live, awake mouse. This was achieved via analysis of the headspace volatile and semi-volatile metabolome of individual gut microbiota bacterial species growing in pure culture, as well as from live gnotobiotic mice specifically colonized with these microbes (i.e. metabolites released to the atmosphere via breath, the skin and from the gut). The microbial origin of these compounds was confirmed by feeding of heavy-isotope labeled microbiota-accessible sugars. This reveals that the microbiota is a major contributor to the released metabolites of a whole live mouse, and that it is possible to capture the catabolism of sugars and cross-feeding within the gut microbiota of a living animal using volatile/semi-volatile metabolite monitoring.
A system for generating reversible knockout cell lines
Authors: DiTacchio Kacee A. , DiTacchio Luciano 
Published: May 2022

AbstractA powerful use of gene editing technology is the generation of genetic-null (knockout) mutants of human immortalized cell lines. However, a problem that arises in the process of generating such edited lines is that to ensure edit homogeneity, clonal selection must often be performed and, given the genomic instability of immortalized cell lines and the high division number inherent to the clonal selection process, the resulting clone can exhibit genotypic and phenotypic differences from the parental line. Here, we present a system that allows for the generation of genetic null cell lines with an excisable cassette. This system allows for the generation of suitable controls without the need of further rounds of clonal selection.
A Versatile Nanoluciferase Reporter Reveals Structural Properties Associated With a Highly Efficient, N-Terminal Legionella pneumophila type IV Secretion Translocation Signal
Authors: Kang Yoon-Suk , Kirby James E. 
Published: May 2022

AbstractMany gram-negative pathogens rely on type IV secretion systems (T4SS) for infection. One limitation in the field has been the lack of ideal reporters to identify T4SS translocated effectors and study T4SS function. Most existing reporter systems make use of fusions to reporter proteins, for example, β-lactamase, to detect translocated enzymatic activity inside the host cell. However, these systems require costly substrates, complex procedures to separate eukaryotic cytoplasm for analysis, and/or are insensitive. Here, we developed and characterized a novel reporter system using nanoluciferase (NLuc) fusions to address these limitations. Serendipitously, we discovered that Nluc itself is efficiently translocated by L. pneumophila T4SS in an IcmSW chaperone-dependent manner via an N-terminal translocation signal. Extensive directed and random mutagenesis in the NLuc N-terminus revealed a critical α-helical domain spanning D5 to V9, as mutations that are predicted to disrupt this α-helix were translocation defective. Notably, NLuc was capable of translocating several proteins examined when fused to the N or C-terminus, while maintaining robust luciferase activity. In particular, it delivered the split GFP11 fragment into J774 macrophages permanently transfected with GFPopt, thereby resulting in in vivo assembly of superfolder GFP. This provided a bifunctional assay in which translocation could be assayed in by fluorescence microplate, confocal microscopy, and/or luciferase assay. We further identified an optimal NLuc substrate, which allowed a robust, inexpensive, one-step, high throughput screening assay to identify T4SS translocation substrates and inhibitors. Taken, together NLuc provides both new insight into and tools for studying T4SS biology.ImportanceType IV secretion systems (T4SS) are used by gram-negative pathogens to coopt host cell function. However, the translocation signals recognized by T4SS are not fully explained by primary amino acid sequence, suggesting yet to be defined contributions of secondary and tertiary structure. Here, we unexpectedly identify nanoluciferase (NLuc) as an efficient IcmSW-dependent translocated T4SS substrate and provide extensive mutagenesis data suggesting that the first N-terminal, alpha helix domain is a critical translocation recognition motif. Notably, most existing reporter systems for studying translocated proteins make use of fusions to reporters to permit detection of translocated enzymatic activity inside the host cell. However, existing systems require extremely costly substrates, complex technical procedures to isolate eukaryotic cytoplasm for analysis, and/or are insensitive. Importantly, we find that NLuc provides a powerful, cost-effective new tool to address these limitations and facilitate high throughput exploration of secretion system biology.