bluuebunny/crossref_metadata_2025_split huggingface dataset:
The transmembrane domain of DWORF activates SERCA directly; P15 and W22 residues are essential
Authors: Li Ang , Stroik Daniel R. , Yuen Samantha L. , Kleinboehl Evan , Cornea Razvan L. , Thomas David D. 
Published: September 2020

AbstractThe Ca-ATPase isoform 2a (SERCA2a) re-sequesters cytosolic Ca2+into the sarcoplasmic reticulum (SR) of cardiac myocytes, enabling muscle relaxation during diastole. A central factor in heart failure is abnormally high cytosolic [Ca2+], resulting in pathophysiology and decreased cardiac performance. Therefore, augmentation of the SERCA2a Ca2+transport activity is a promising therapeutic approach. A novel transmembrane peptide, dwarf open reading frame (DWORF), is proposed to enhance SR Ca2+uptake and myocyte contractility by displacing the protein phospholamban (PLB) from its inhibitory site on SERCA2a. In the present study, we have developed several cell-based FRET biosensor systems for time-resolved FRET (TR-FRET) measurements of the protein-protein interactions and structural changes in SERCA2a complexes with PLB and/or DWORF. To test the hypothesis that DWORF competes with PLB to occupy the putative SERCA2a binding site, we transiently transfected DWORF into a stable cell line expressing SERCA2a labeled with green fluorescent protein (GFP, the FRET donor) and PLB labeled with red fluorescent protein (RFP, the FRET acceptor). We observed a significant decrease in FRET efficiency, consistent with a decrease in the fraction of SERCA2a bound to PLB. Functional analysis demonstrates that DWORF activates SERCA in both the presence and absence of PLB. Furthermore, using site-directed mutagenesis, we generated DWORF variants that do not activate SERCA, thus identifying residues that are necessary for functional SERCA2a-DWORF interactions. This work advances our mechanistic understanding of the regulation of SERCA2a by small transmembrane proteins and sets the stage for future therapeutic development in heart failure research.
Inferring intestinal mucosal immune cell associated microbiome species and microbiota-derived metabolites in inflammatory bowel disease
Authors: Narasimhan Rajagopalan Lakshmi , Throm Allison A. , Koshy Jesvin Joy , Saldanha Keith Metelo Raul , Chandranpillai Harikrishnan , Lal Rahul Deva , Kumravat Mausam , Kumar K M Ajaya , Batra Aneesh , Zhong Fei , Liu Jiajian 
Published: September 2020

AbstractInflammatory bowel disease (IBD) is a complex, chronic inflammatory disease of the gastrointestinal tract with subtypes Crohn’s disease (CD) and ulcerative colitis (UC). While evidence indicates IBD is characterized by alterations in the composition and abundance of the intestinal microbiome, the challenge remains to specify bacterial species and their metabolites associated with IBD pathogenesis. By the integration of microbiome multi-omics data and computational methods, we provide analyses and methods for the first time to identify microbiome species and their metabolites that are associated with the human intestine mucosal immune response in patients with CD and UC at a systems level. First, we identified seven gut bacterial species and seventeen metabolites that are significantly associated with Th17 cellular differentiation and immunity in patients with active CD by comparing with those obtained in inactive CD and non-IBD controls. The seven species areRuminococcus gnavus, Escherichia coli, Lachnospiraceae bacterium, Clostridium hathewayi, Bacteroides faecis, Bacteroides vulgatus, andAkkermansia muciniphila, and a few associated metabolites include the secondary bile acid lithocholate and three short-chain fatty acids (SCFAs): propionate, butyrate, and caproate. We next systematically characterized potential mechanistic relationships between the Th17-involved metabolites and bacterial species and further performed differential abundance analysis for both microbiome species and their metabolites in CD and UC relative to non-IBD controls with their metagenomic and metabolomic data. Based on the deconvolution of immune cell compositions from host intestinal bulk RNA-seq, we investigated changes in immune cell composition and abundance in CD and UC in comparison to non-IBD controls. Finally, we further extended our species and metabolite associations with immune cells from Th17 and Th2 cells to B cells, plasma B cells, plasmablasts, CD4+ T cells, and CD8+ T cells. While a set of associations of immune cells with bacterial species and metabolites was supported by published evidence, the new findings in this work will help to furthering our understanding of immune responses and pathogenesis in IBD.
JSTA: joint cell segmentation and cell type annotation for spatial transcriptomics
Authors: Littman Russell , Hemminger Zachary , Foreman Robert , Arneson Douglas , Zhang Guanglin , Gómez-Pinilla Fernando , Yang Xia , Wollman Roy 
Published: September 2020

AbstractRNA hybridization based spatial transcriptomics provides unparalleled detection sensitivity. However, inaccuracies in segmentation of image volumes into cells cause misassignment of mRNAs which is a major source of errors. Here we develop JSTA, a computational framework for Joint cell Segmentation and cell Type Annotation that utilizes prior knowledge of cell-type specific gene expression. Simulation results show that leveraging existing cell type taxonomy increases RNA assignment accuracy by more than 45%. Using JSTA we were able to classify cells in the mouse hippocampus into 133 (sub)types revealing the spatial organization of CA1, CA3, and Sst neuron subtypes. Analysis of within cell subtype spatial differential gene expression of 80 candidate genes identified 43 with statistically significant spatial differential gene expression across 61 (sub)types. Overall, our work demonstrates that known cell type expression patterns can be leveraged to improve the accuracy of RNA hybridization based spatial transcriptomics while providing highly granular cell (sub)type information. The large number of newly discovered spatial gene expression patterns substantiates the need for accurate spatial transcriptomics measurements that can provide information beyond cell (sub)type labels.
DeepPPPred: An Ensemble of BERT, CNN, and RNN for Classifying Co-mentions of Proteins and Phenotypes
Authors: Shahri Morteza Pourreza , Lyon Katrina , Schearer Julia , Kahanda Indika 
Published: September 2020

AbstractThe biomedical literature provides an extensive source of information in the form of unstructured text. One of the most important types of information hidden in biomedical literature is the relationships between human proteins and their phenotypes, which, due to the exponential growth of publications, can remain hidden. This provides a range of opportunities for the development of computational methods to extract the biomedical relationships from the unstructured text. In our previous work, we developed a supervised machine learning approach, called PPPred, for classifying the validity of a given sentence-level human protein-phenotype co-mention. In this work, we propose DeepPPPred, an ensemble classifier composed of PPPred and three deep neural network models: RNN, CNN, and BERT. Using an expanded gold-standard co-mention dataset, we demonstrate that the proposed ensemble method significantly outperforms its constituent components and provides a new state-of-the-art performance on classifying the co-mentions of human proteins and phenotype terms.
Proliferation of lung epithelial cells is regulated by the mechanisms of autophagy upon exposure of soots
Authors: Niranjan Rituraj , Mishra Kaushal Prasad , Thakur Ashwani Kumar 
Published: September 2020

AbstractSoots are known to cause many diseases in humans but their underlying mechanisms of toxicity are still not known. Here, we report that, soots induce cell proliferation of lung epithelial cells via modulating autophagic pathways. Fullerene soot and diesel exhaust particles (DEP) induced cell proliferation of lung epithelial, A549 cells, via distinct autophagic mechanisms and did not cause cell death. Exposure of fullerene soot protected cell death of A549 cells, caused by hydrogen peroxide and inhibited LPS-induced autophagy. Fullerene soot co-localize with the autophagic proteins and inhibited starvation-induced autophagy (downregulated ATG-5, beclin-1, p62 and LC3 expressions) independent of its antioxidant properties. Similarly, it decreased expression profile of autophagic genes and upregulated proliferation responsive gene, Ki-67, in mice. We observed that, expressions of fullerene soot responsive genes (Beclin-1, ATG-5 and p62) were reverted by Akt Inhibitor X, indicating an important role of Akt pathway. On the other hand, DEP up-regulated expressions of autophagy genes. Akt Inhibitor X and Etoricoxib, did not attenuate DEP-induced cell proliferation and autophagic response. However, autophagic inhibiter 3-MA and chloroquine has significantly inhibited DEP-induced cell roliferation. In conclusion, distinct autophagic mechanisms are operational in cell proliferation of lung epithelial cells in response to soots and may have implication in diseases. The proliferation inducing potential of fullerene soot may be utilized as a regenerative agent in autophagy-associated disorders.
An Overview of the Application of Deep Learning in Short Read Sequence Classification
Authors: Bebris Kristaps , Polaka Inese 
Published: September 2020

AbstractAdvances in sequencing technology have led to an ever increasing amount of available short read sequencing data. This has, consequently, exacerbated the need for efficient and precise classification tools that can be used in the analysis of this data. As it stands, recent years have shown that massive leaps in performance can be achieved when it comes to approaches that are based in heuristics, and alongside these improvements there has been an ever increasing interest in applying deep learning techniques to revolutionize this classification task. We attempt to gather up these approaches and to evaluate their performance in a reproducible fashion to get a better perspective on the current state of deep learning based methods when it comes to the classification of short read sequencing data.
Childhood location correlates with epigenetic age and methylation stability in British-Bangladeshi migrants
Authors: Stöger Reinhard , Choi Minseung , Leeman Gregory , Emes Richard D. , Begum Khurshida , Melamed Philippa , Bentley Gillian R. 
Published: September 2020

AbstractBackgroundMigration from one environment to another often causes marked changes in developmental conditions. Here we compare epigenetic ageing and stability of the epigenetic maintenance system among British-Bangladeshi women who grew up in Bangladesh (adult migrants), where there are higher pathogen loads and poorer health care, to second-generation Bangladeshis who grew up in the UK. In our previous studies of these migrants, those who spent their childhoods in Bangladesh also had lower levels of reproductive hormones and a shorter reproductive lifespan compared to those who grew up in the UK, suggesting life history trade-offs during development. In the present study, we hypothesised that women who grew up in Bangladesh would havei)an older epigenetic/biological age compared to the women with a childhood in the UK andii)that differences in the pace of epigenetic ageing might also be reflected by altered stability of DNA methylation marks.ResultsIllumina EPIC array methylation data from buccal tissue was used to establish epigenetic age estimates from 15 adult migrants and 11 second-generation migrants, aged 18-35 years. Using residuals from linear regression of DNA methylation-based biological age (DNAm age) on the chronological age, the results showed significant differences (p=0.016) in epigenetic age estimates: women whose childhood was in Bangladesh are on average 6.02 (± 2.34) years older, than those who grew up in London. We further investigated the efficiency of the epigenetic maintenance system which purportedly is reflected by epigenetic clocks. Methylation states of CpGs at theLHCGR/LHRlocus, which contributes to Horvath’s multi tissue epigenetic clock were evaluated. Based on the Ratio of Concordance Preference (RCP) approach that uses double-stranded methylation data, we find that maintenance of epigenetic information is more stable in women who grew up in Bangladesh.ConclusionsThe work supports earlier findings that adverse childhood environments lead to phenotypic life history trade-offs. The data indicate that childhood environments can induce subtle changes to the epigenetic maintenance system that are detectable long after exposure occurred. The implication of such a finding warrants further investigation as it implies that a less flexible epigenetic memory system established early in life could reduce the capacity to respond to different environmental conditions in adult life.
Auditory Target Detection Enhances Visual Processing and Hippocampal Functional Connectivity
Authors: Moyal Roy , Turker Hamid B. , Luh Wen-Ming , Swallow Khena M. 
Published: September 2020

AbstractThough dividing one’s attention between two input streams typically impairs performance, detecting a behaviorally relevant stimulus can sometimes enhance the encoding of unrelated information presented at the same time. Previous research has shown that selection of this kind boosts visual cortical activity and memory for concurrent items. An important unanswered question is whether such effects are reflected in processing quality and functional connectivity in visual regions and in the hippocampus. In this fMRI study, participants were asked to memorize a stream of naturalistic images and press a button only when they heard a predefined target tone (400 or 1200 Hz, counterbalanced). Images could be presented with a target tone, with a distractor tone, or without a tone. Auditory target detection increased activity throughout the ventral visual cortex but lowered it in the hippocampus. Enhancements in functional connectivity between the ventral visual cortex and the hippocampus were also observed following auditory targets. Multi-voxel pattern classification of image category was more accurate on target tone trials than on distractor and no tone trials in the fusiform gyrus and parahippocampal gyrus. This effect was stronger in visual cortical clusters whose activity was more correlated with the hippocampus on target tone than on distractor tone trials. In agreement with accounts suggesting that subcortical noradrenergic influences play a role in the attentional boost effect, auditory target detection also caused an increase in locus coeruleus activity and phasic pupil responses. These findings outline a network of cortical and subcortical regions that are involved in the selection and processing of information presented at behaviorally relevant moments.
Gaining confidence in inferred networks
Authors: Diaz Léo P.M. , Stumpf Michael P.H. 
Published: September 2020

AbstractNetwork inference is a notoriously challenging problem. Inferred networks are associated with high uncertainty and likely riddled with false positive and false negative interactions. Especially for biological networks we do not have good ways of judging the performance of inference methods against real networks, and instead we often rely solely on the performance against simulated data. Gaining confidence in networks inferred from real data nevertheless thus requires establishing reliable validation methods. Here, we argue that the expectation of mixing patterns in biological networks such as gene regulatory networks offers a reasonable starting point: interactions are more likely to occur between nodes with similar biological functions. We can quantify this behaviour using the assortativity coefficient, and here we show that the resulting heuristic,functional assortativity, offers a reliable and informative route for comparing different inference algorithms.
Lymph flow directs rapid neutrophil positioning in the lymph node in infection
Authors: Xue Jingna , Lin Yujia , Oo Darellynn , Zhang Jianbo , Jesus Flavia , Zardynezhad Ava , de Almeida Luiz G. N. , Young Daniel , Dufour Antoine , Liao Shan 
Published: September 2020

AbstractSoon afterStaphylococcus aureus(S. aureus) skin infection, neutrophils infiltrate the LN via the high endothelial venules (HEVs) to restrain and kill the invading microbes to prevent systemic spread of microbes. In this study, we found that rapid neutrophil migration depends on lymph flow, through which inflammatory chemokines/cytokines produced in the infected tissue are transported to the LN. Without lymph flow, bacteria accumulation in the LN was insufficient to stimulate chemokine production or neutrophil migration. Oxazolone (OX)-induced skin inflammation impaired lymphatic function, and reduced chemokines in the LN after a secondary infection withS. aureus. Due to LN reconstruction and impaired conduit-mediated lymph flow, neutrophil preferentially transmigrated in HEVs located in the medullary sinus, where the HEVs remained exposed to lymph-borne chemokines. Altered neutrophil migration resulted in persistent infection in the LN. Our studies showed that lymph flow directed chemokine dispersal in the LN and ensured rapid neutrophil migration for timely immune protection in infection. The impaired lymph flow and neutrophil migration may contribute to the frequent infection in skin inflammation, such as atopic dermatitis.
Improved cortical surface reconstruction using sub-millimeter resolution MPRAGE by image denoising
Authors: Tian Qiyuan , Zaretskaya Natalia , Fan Qiuyun , Ngamsombat Chanon , Bilgic Berkin , Polimeni Jonathan R. , Huang Susie Y. 
Published: September 2020

AbstractAutomatic cerebral cortical surface reconstruction is a useful tool for cortical anatomy quantification, analysis and visualization. Recently, the Human Connectome Project and several studies have shown the advantages of using T1-weighted magnetic resonance (MR) images with sub-millimeter isotropic spatial resolution instead of the standard 1-millimeter isotropic resolution for improved accuracy of cortical surface positioning and thickness estimation. Nonetheless, sub-millimeter resolution images are noisy by nature and require averaging multiple repetitions to increase the signal-to-noise ratio for precisely delineating the cortical boundary. The prolonged acquisition time and potential motion artifacts pose significant barriers to the wide adoption of cortical surface reconstruction at sub-millimeter resolution for a broad range of neuroscientific and clinical applications. We address this challenge by evaluating the cortical surface reconstruction resulting from denoised single-repetition sub-millimeter T1-weighted images. We systematically characterized the effects of image denoising on empirical data acquired at 0.6 mm isotropic resolution using three classical denoising methods, including denoising convolutional neural network (DnCNN), block-matching and 4-dimensional filtering (BM4D) and adaptive optimized non-local means (AONLM). The denoised single-repetition images were found to be highly similar to 6-repetition averaged images, with a low whole-brain averaged mean absolute difference of ∼0.016, high whole-brain averaged peak signal-to-noise ratio of ∼33.5 dB and structural similarity index of 0.92, and minimal gray matter–white matter contrast loss (2% to 9%). The whole-brain mean absolute discrepancies in gray–white surface placement, gray–CSF surface placement and cortical thickness estimation were lower than 165 μm, 155 μm and 145 μm—sufficiently accurate for most applications. The denoising performance is equivalent to averaging ∼2.5 repetitions of the data in terms of image similarity, and 1.6–2.2 repetitions in terms of the cortical surface placement accuracy. The scan-rescan precision of the cortical surface positioning and thickness estimation was lower than 170 μm. Our unique dataset and systematic characterization support the use of denoising methods for improved cortical surface reconstruction sub-millimeter resolution.
Identifying Cancer-Relevant Mutations in the DLC START Domain using Evolutionary and Structure-Function Analyses
Authors: Holub Ashton S. , Bouley Renee A. , Petreaca Ruben C. , Husbands Aman Y. 
Published: September 2020

AbstractRho GTPase signaling promotes proliferation, invasion, and metastasis in a broad spectrum of cancers. Rho GTPase activity is regulated by the Deleted in Liver Cancer (DLC) family of bonafide tumor suppressors which directly inactivate Rho GTPases by stimulating GTP hydrolysis. In addition to a RhoGAP domain, DLC proteins contain a StAR-related lipid transfer (START) domain. START domains in other organisms bind hydrophobic small molecules and can regulate interacting partners or co-occurring domains through a variety of mechanisms. In the case of DLC proteins, their START domain appears to contribute to tumor suppressive activity. However, the nature of this START-directed mechanism, as well as the identities of relevant functional residues, remain virtually unknown. Using the Catalogue of Somatic Mutations in Cancer (COSMIC) dataset, and evolutionary and structure-function analyses, we identify several conserved residues likely to be required for START-directed regulation of DLC-1 and DLC-2 tumor suppressive capability. This pan-cancer analysis shows that conserved residues of both START domains are highly-overrepresented in cancer cells from a wide range tissues. Interestingly, in DLC-1 and DLC-2, three of these residues form multiple interactions at the tertiary structural level. Further, mutation of any of these residues is predicted to disrupt interactions and thus destabilize the START domain. As such, these mutations would not have emerged from traditional hotspot scans of COSMIC. We propose that evolutionary and structure-function analyses are an underutilized strategy which could be used to unmask cancer-relevant mutations within COSMIC. Our data also suggest DLC-1 and DLC-2 as high- priority candidates for development of novel therapeutics targeting their START domain.Simple SummaryDeleted in Liver Cancer (DLC) proteins are tumor suppressors that contain a StAR-related lipid transfer (START) domain. Little is known about the DLC START domain including the residues that mediate its activation. Using the Catalogue of Somatic Mutations in Cancer (COSMIC) dataset, evolutionary, and structure-function analyses, we identify key functional residues of DLC START domains. Mutations in these residues are significantly overrepresented in numerous cancers in multiple tissue types. In other contexts, START domains bind hydrophobic small molecules and stimulate regulatory outputs of interacting partners or co-occurring domains. The identification of functional residues in the DLC START domain may thus have implications for targeted manipulation of DLC tumor suppressive activity. Critically, these residues would not have been identified using traditional queries of COSMIC. Thus, we propose tandem evolutionary and structure-function approaches are an underutilized strategy to unmask cancer-relevant mutations within COSMIC.