bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hypothalamic Overexpression of Neurosecretory Protein GL Leads to Obesity in Mice
Authors: Narimatsu Yuki , Fukumura Keisuke , Shikano Kenshiro , Iwakoshi-Ukena Eiko , Furumitsu Megumi , Bentley George E. , Kriegsfeld Lance J. , Ukena Kazuyoshi 
Published: March 2021

AbstractIntroductionThe mechanisms underlying obesity are not fully understood, necessitating the creation of novel animal models for investigation of metabolic disorders from the cellular-molecular to behavioral levels of analysis. We have previously found that neurosecretory protein GL (NPGL), a newly-identified hypothalamic neuropeptide, is involved in feeding behavior and fat accumulation in rats. Given the broad availability of genetic tools in mice, the present investigation sought to establish a mouse model of NPGL-induced obesity.MethodsWe overexpressed the NPGL-precursor gene (Npgl) in the hypothalamus using adeno-associated virus in C57BL/6J mice fed normal chow (NC) or a high-calorie diet (HCD). After 9 weeks ofNpgloverexpression, we measured adipose tissues, muscle, and several organ masses in addition to food intake and body mass. To assess the effects ofNpgloverexpression on peripheral tissues, we analyzed mRNA expression of lipid metabolism-related genes by quantitative RT-PCR.ResultsNpgloverexpression increased food intake, body mass, adipose tissues and liver masses, food efficiency, and circulating insulin levels under both NC and HCD, resulting in obesity observable within 8 weeks. Furthermore, we observed fat accumulation in adipose tissues and liver. Additionally, mRNA expression of lipid metabolism-related factors was increased in white adipose tissue and the liver afterNpgloverexpression.ConclusionTaken together, the present study suggests that NPGL is an endogenous obesogenic factor that acts within a short period of time in mice. As a result, this animal model can be widely applied to study the etiology of obesity from genes to behavior.
Day by day symptoms following positive and negative PCR tests for SARS-CoV-2 in non-hospitalised health-care workers: a 90-day follow-up study
Authors: Nielsen Kent J. , Vestergaard Jesper Medom , Schlünssen Vivi , Bonde Jens Peter , Kaspersen Kathrine Agergård , Biering Karin , Carstensen Ole , Greve Thomas , Hansen Karoline Kærgaard , Dalbøge Annett , Flachs Esben Meulengracht , Jespersen Sanne , Hansen Mette Lausten , Mikkelsen Susan , Thomsen Marianne Kragh , Redder Jacob Dvinge , Würtz Else Toft , Østergaard Lars , Erikstrup Christian , Kolstad Henrik Albert 
Published: March 2021

AbstractBackgroundLittle is known about the long-term course of symptoms for mild coronavirus disease 2019 (COVID-19) when accounting for symptoms due to other causes. We aimed to compare symptoms day by day for non-hospitalised individuals who tested positive and negative with polymerase chain reaction for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).MethodsWe followed 210 test-positive and 630 individually matched test-negative health-care workers of the Central Denmark Region up to 90 days after the test, April-June 2020. They daily reported seven COVID-19 related symptoms. Symptom courses were compared graphically and by conditional multivariable logistic regression.ResultsThirty % of test-positive and close to zero of test-negative participants reported a reduced sense of taste and smell during all 90 days of follow-up (adjusted odds ratio [aOR] 86.07, 95% CI 22.86-323). Dyspnoea was reported by an initial 20% of test-positive with a gradual decline to about 5% after 30 days without ever reaching the level of the test-negative participants (aOR 6.88, 95% CI 2.41-19.63). Cough, headache, sore throat, muscle aches, and fever were temporarily more prevalent among the test positive participants, but after 30 days, no increases were seen. Women and participants aged 45 years or older tended to be more susceptible to SARS-CoV-2 infection.ConclusionPrevalence of long-lasting reduced sense of taste and smell is highly increased after being diagnosed with mild COVID-19. This pattern is also seen for dyspnoea at a low level but not for cough, sore throat, headache, muscle ache or pain, or fever.Key messagesReduced sense of taste and smell is present at a highly increased level of 30% during 90 days after testing positive for severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2).Test-positive participants experience dyspnoea persistently more often than test-negative participants but affect only few.The prevalence of cough, sore throat, headache, muscle ache or pain, and fever following a positive test reach the level seen after a negative test within 30 days.Women and participants aged 45 years or older tend to be more susceptible to symptoms following SARS-CoV-2 infection.
Relation of severe COVID-19 in Scotland to transmission-related factors and risk conditions eligible for shielding support: REACT-SCOT case-control study
Authors: McKeigue Paul M , McAllister David A , Caldwell David , Gribben Ciara , Bishop Jen , McGurnaghan Stuart , Armstrong Matthew , Delvaux Joke , Colville Sam , Hutchinson Sharon , Robertson Chris , Lone Nazir , McMenamin Jim , Goldberg David , Colhoun Helen M 
Published: March 2021

AbstractBackgroundClinically vulnerable individuals have been advised to shield themselves during the COVID-19 epidemic. The objectives of this study were to investigate: (1) the risk of severe COVID-19 in those eligible for shielding, and (2) the relation of severe COVID-19 to transmission-related factors in those in shielding and the general population.MethodsAll 178578 diagnosed cases of COVID-19 in Scotland from 1 March 2020 to 18 February 2021 were matched for age, sex and primary care practice to 1744283 controls from the general population. This dataset (REACT-SCOT) was linked to the list of 212702 individuals identified as eligible for shielding. Severe COVID-19 was defined as cases that entered critical care or were fatal.ResultsWith those without risk conditions as reference category, the univariate rate ratio for severe COVID-19 was 3.21 (95% CI 3.01 to 3.41) in those with moderate risk conditions and 6.3 (95% CI 5.8 to 6.8) in those eligible for shielding. The highest rate was in solid organ transplant recipients: rate ratio 13.4 (95% CI 9.6 to 18.8). Risk of severe COVID-19 increased with the number of adults but decreased with the number of school-age children in the household. Severe COVID-19 was strongly associated with recent exposure to hospital (defined as 5 to 14 days before presentation date): rate ratio 12.3 (95% CI 11.5 to 13.2) overall. To test for causality, a case-crossover analysis was undertaken; with less recent exposure only (15 to 24 days before first testing positive) as reference category, the rate ratio associated with recent exposure only was 5.9 (95% CI 3.6 to 9.7). The population attributable risk fraction for recent exposure to hospital peaked at 50% in May 2020 and again at 65% in December 2020.ConclusionsThe effectiveness of shielding vulnerable individuals was limited by the inability to control transmission in hospital and from other adults in the household. For solid organ transplant recipients, in whom the efficacy of vaccines is uncertain, these results support a policy of offering vaccination to household contacts. Mitigating the impact of the epidemic requires control of nosocomial transmission.
Inter-tissue convergence of gene expression during ageing suggests age-related loss of tissue and cellular identity
Authors: Izgi Hamit , Han DingDing , Isildak Ulas , Huang Shuyun , Kocabiyik Ece , Khaitovich Philipp , Somel Mehmet , Dönertaş Handan Melike 
Published: March 2021

AbstractDevelopmental trajectories of gene expression may reverse in their direction during ageing, a phenomenon previously linked to cellular identity loss. Our analysis of cerebral cortex, lung, liver and muscle transcriptomes of 16 mice, covering development and ageing intervals, revealed widespread but tissue-specific ageing-associated expression reversals. Cumulatively, these reversals create a unique phenomenon: mammalian tissue transcriptomes diverge from each other during postnatal development, but during ageing, they tend to converge towards similar expression levels, a process we termDivergence followed byConvergence, or DiCo. We found that DiCo was most prevalent among tissue-specific genes and associated with loss of tissue identity, which is confirmed using data from independent mouse and human datasets. Further, using publicly available single-cell transcriptome data, we showed that DiCo could be driven both by alterations in tissue cell type composition and also by cell-autonomous expression changes within particular cell types.
Neutralizing IFNL3 Autoantibodies in Severe COVID-19 Identified Using Molecular Indexing of Proteins by Self-Assembly
Authors: Credle Joel J. , Gunn Jonathan , Sangkhapreecha Puwanat , Monaco Daniel R. , Zheng Xuwen Alice , Tsai Hung-Ji , Wilbon Azaan , Morgenlander William R. , Dong Yi , Jayaraman Sahana , Tosi Lorenzo , Parekkadan Biju , Baer Alan N. , Roederer Mario , Bloch Evan M. , Tobian Aaron A. R. , Zyskind Israel , Silverberg Jonathan I. , Rosenberg Avi Z. , Cox Andrea L. , Lloyd Tom , Mammen Andrew L. , Larman H. Benjamin 
Published: March 2021

AbstractUnbiased antibody profiling can identify the targets of an immune reaction. A number of likely pathogenic autoreactive antibodies have been associated with life-threatening SARS-CoV-2 infection; yet, many additional autoantibodies likely remain unknown. Here we present Molecular Indexing of Proteins by Self Assembly (MIPSA), a technique that produces ORFeome-scale libraries of proteins covalently coupled to uniquely identifying DNA barcodes for analysis by sequencing. We used MIPSA to profile circulating autoantibodies from 55 patients with severe COVID-19 against 11,076 DNA-barcoded proteins of the human ORFeome library. MIPSA identified previously known autoreactivities, and also detected undescribed neutralizing interferon lambda 3 (IFN-λ3) autoantibodies. At-risk individuals with anti-IFN-λ3 antibodies may benefit from interferon supplementation therapies, such as those currently undergoing clinical evaluation.One-Sentence SummaryMolecular Indexing of Proteins by Self Assembly (MIPSA) identifies neutralizing IFNL3 autoantibodies in patients with severe COVID-19.Graphical Abstract
Body mass, temperature, and depth shape the maximum intrinsic rate of population increase in sharks and rays
Authors: A. Pardo Sebastián , Dulvy Nicholas K. 
Published: March 2021

AbstractAn important challenge in ecology is to understand variation in species’ maximum intrinsic rate of population increase,rmax, not least becausermaxunderpins our understanding of the limits of fishing, recovery potential, and ultimately extinction risk. Across many vertebrates, terrestrial and aquatic, body mass and environmental temperature across important correlatesrmaxacross species. In sharks and rays, specifically,rmaxis known be lower in larger species, but also in deep-sea ones. We use an information-theoretic approach that accounts for phylogenetic relatedness to evaluate the relative importance of body mass, temperature and depth onrmax. We show that both temperature and depth have separate effects on shark and rayrmaxestimates, such that species living in deeper waters have lowerrmax. Furthermore, temperature also correlates with changes in the mass scaling coefficient, suggesting that as body size increases, decreases inrmaxare much steeper for species in warmer waters. These findings suggest that there (as-yet understood) depth-related processes that limit the maximum rate at which populations can grow in deep sea sharks and rays. While the deep ocean is associated with colder temperatures, other factors that are independent of temperature, such as food availability and physiological constraints, may influence the lowrmaxobserved in deep sea sharks and rays. Our study lays the foundation for predicting the intrinsic limit of fishing, recovery potential, and extinction risk species based on easily accessible environmental information such as temperature and depth, particularly for data-poor species.
Genome-wide screens identify calcium signaling as a key regulator of IgE+plasma cell differentiation and survival
Authors: Newman Rebecca , Tolar Pavel 
Published: March 2021

SummaryIgE antibodies protect against toxins and parasites, however, they also mediate allergic reactions. In contrast to other antibody isotypes, B cells switched to IgE respond transiently and do not give rise to long-lived plasma cells (PCs) or memory B cells. Although the intrinsic differences of IgE+B cells have been linked to signaling by the IgE-B cell receptor (BCR), the molecular pathways controlling their behavior remain poorly understood. Here we employ whole-genome CRISPR screening to identify genes regulating IgE+B cell proliferation, survival and differentiation into PCs. We show that IgE+B cells are selectively suppressed by the IgE-BCR signaling to intracellular calcium, which inhibits PC differentiation and limits their lifespan after differentiation. Consequently, manipulation of calcium signalingin vivoenhances IgE+PC responses. Insights from this pathway shed new light on the self-limiting character of IgE responses and open new avenues to eliminate IgE+PCs in allergy.
A study of the neuronal injury biomarkers pNF-H and UCHL1 in serum, CSF and urine in a cohort of thoracic endovascular aortic repair (TEVAR) patients
Authors: Beck Adam , Marin Vedrana , Deng Jay , Madorsky Irina , Ren Bin , Guo Yichen , Neal Dan , Shaw Gerry 
Published: March 2021

AbstractA collection of longitudinal serum, cerebrospinal fluid (CSF) and urine samples were collected from a cohort of 50 patients undergoing thoracic endovascular aortic repairs (TEVAR). Samples were taken multiple time per day out to 5 days post operation and were probed with novel electrochemiluminescent assays specific for the phosphorylated axonal form of the major neurofilament subunit NF-H (pNF-H) and for ubiquitin C-terminal hydrolase 1 (UCHL1). Control blood samples showed small signals for pNF-H and in some cases rather larger signals for UCHL1. The presence of UCHL1 in these control blood samples was convincingly verified by western blotting with multiple well characterized UCHL1 antibodies and by mass spectroscopy. Elevated levels of both pNF-H and UCHL1 in blood and CSF in recovering TEVAR patients were associated with poorer outcomes. In particular release of UCHL1 into blood over several hours following TEVAR and peaking at any time over 1 ng/ml was a very strong predictor of patient death and was associated with renal failure and spinal cord ischemia (SCI). An unexpected finding was that high levels of UCHL1 were detected in certain urine samples, again in association with SCI, renal failure and poor patient outcome. We also present epitope mapping data on the UCHL1 monoclonal antibodies used including data on the widely used commercially available MCA-BH7. These studies suggest that measurement of the levels of both proteins in the blood, CSF and urine of TEVAR patients may be of clinical utility. However this study also raises questions about the origin and significance of UCHL1 both in control blood, in patient blood samples and in urine.
A New Straightforward Method for Automated Segmentation of Trabecular Bone from Cortical Bone in Diverse and Challenging Morphologies
Authors: Herbst Eva C. , Felder Alessandro A. , Evans Lucinda A. E. , Ajami Sara , Javaheri Behzad , Pitsillides Andrew A. 
Published: March 2021

AbstractMany physiological, biomechanical, evolutionary and clinical studies that explore skeletal structure and function require successful separation of trabecular from cortical compartments of a bone that has been imaged by X-ray micro-computed tomography (microCT) prior to analysis. Separation is often time-consuming, involves user bias and needs manual sub-division of these two similarly radio-opaque compartments. We have developed an objective, automated protocol which reduces user bias and enables straightforward, user-friendly segmentation of trabecular from cortical bone without requiring sophisticated programming expertise. This method can conveniently be used as a “recipe” in commercial programmes (Avizo herein) and applied to a variety of datasets. Here, we characterise and share this recipe, and demonstrate its application to a range of murine and human bone types, including normal and osteoarthritic specimens, and bones with distinct embryonic origins and spanning a range of ages. We validate the method by testing inter-user bias during the scan preparation steps and confirm utility in the architecturally challenging analysis of growing murine epiphyses. We also report details of the recipe, so that other groups can readily re-create a similar method in open access programs. Our aim is that this method will be adopted widely to create a more standardized and time efficient method of segmenting trabecular and cortical bone.
High-content screening of coronavirus genes for innate immune suppression reveals enhanced potency of SARS-CoV-2 proteins
Authors: Olson Erika J. , Brown David M. , Chang Timothy Z. , Ding Lin , Ng Tai L. , Weiss H. Sloane , Koide Yukiye , Koch Peter , Rollins Nathan , Mach Pia , Meisinger Tobias , Bricken Trenton , Rollins Joshua , Zhang Yun , Molloy Colin , Zhang Yun , Queenan Bridget N. , Mitchison Timothy , Marks Debora , Way Jeffrey C. , Glass John I. , Silver Pamela A. 
Published: March 2021

SummarySuppression of the host intracellular innate immune system is an essential aspect of viral replication. Here, we developed a suite of medium-throughput high-content cell-based assays to reveal the effect of individual coronavirus proteins on antiviral innate immune pathways. Using these assays, we screened the 196 protein products of seven coronaviruses (SARS-CoV-2, SARS-CoV-1, 229E, NL63, OC43, HKU1 and MERS). This includes a previously unidentified gene in SARS-CoV-2 encoded within the Spike gene. We observe immune-suppressing activity in both known host-suppressing genes (e.g., NSP1, Orf6, NSP3, and NSP5) as well as other coronavirus genes, including the newly identified SARS-CoV-2 protein. Moreover, the genes encoded by SARS-CoV-2 are generally more potent immune suppressors than their homologues from the other coronaviruses. This suite of pathway-based and mechanism-agnostic assays could serve as the basis for rapid in vitro prediction of the pathogenicity of novel viruses based on provision of sequence information alone.
DeepMOCCA: A pan-cancer prognostic model identifies personalized prognostic markers through graph attention and multi-omics data integration
Authors: Althubaiti Sara , Kulmanov Maxat , Liu Yang , Gkoutos Georgios V , Schofield Paul , Hoehndorf Robert 
Published: March 2021

AbstractCombining multiple types of genomic, transcriptional, proteomic, and epigenetic datasets has the potential to reveal biological mechanisms across multiple scales, and may lead to more accurate models for clinical decision support. Developing efficient models that can derive clinical outcomes from high-dimensional data remains problematical; challenges include the integration of multiple types of omics data, inclusion of biological background knowledge, and developing machine learning models that are able to deal with this high dimensionality while having only few samples from which to derive a model. We developed DeepMOCCA, a framework for multi-omics cancer analysis. We combine different types of omics data using biological relations between genes, transcripts, and proteins, combine the multi-omics data with background knowledge in the form of protein–protein interaction networks, and use graph convolution neural networks to exploit this combination of multi-omics data and background knowledge. DeepMOCCA predicts survival time for individual patient samples for 33 cancer types and outperforms most existing survival prediction methods. Moreover, DeepMOCCA includes a graph attention mechanism which prioritizes driver genes and prognostic markers in a patient-specific manner; the attention mechanism can be used to identify drivers and prognostic markers within cohorts and individual patients.Author summaryLinking the features of tumors to a prognosis for the patient is a critical part of managing cancer. Many methods have been applied to this problem but we still lack accurate prognostic markers for many cancers. We now have more information than ever before on the state of the cancer genome, the epigenetic changes in tumors, and gene expression at both RNA and protein levels. Here, we address the question of how this data can be used to predict cancer survival and discover which tumor genes make the greatest contribution to the prognosis in individual tumor samples. We have developed a computational model, DeepMOCCA, that uses artificial neural networks underpinned by a large graph constructed from background knowledge concerning the functional interactions between genes and their products. We show that with our method, DeepMOCCA can predict cancer survival time based entirely on features of the tumor at a cellular and molecular level. The method confirms many existing genes that affect survival but for some cancers suggests new genes, either not implicated in survival before or not known to be important in that particular cancer. The ability to predict the important features in individual tumors provided by our method raises the possibility of personalized therapy based on the gene or network dominating the prognosis for that patient.
Predicting biological pathways of chemical compounds with a profile-inspired aproach
Authors: Lopez-Ibañez Javier , Pazos Florencio , Chagoyen Monica 
Published: March 2021

AbstractAssignment of chemical compounds to biological pathways is a crucial step to understand the relationship between the chemical repertory of an organism and its biology. Protein sequence profiles are very successful in capturing the main structural and functional features of a protein family, and can be used to assign new members to it based on matching of their sequences against these profiles. In this work, we extend this idea to chemical compounds, constructing a profile-inspired model for a set of related metabolites (those in the same biological pathway), based on a fragment-based vectorial representation of their chemical structures. We use this representation to predict the biological pathway of a chemical compound with good overall accuracy (AUC 0.74-0.90 depending on the database tested), and analyzed some factors that affect performance. The approach, which is compared with equivalent methods, can in addition detect those molecular fragments characteristic of a pathway. The method is available as a graphical interactive web serverhttp://csbg.cnb.csic.es/iFragMent
Decline in large-seeded species in Danish grasslands over an eight-year period
Authors: Damgaard Christian 
Published: March 2021

AbstractA time-series analysis of cover data from 236 Danish grassland sites demonstrated community selection on seed mass. Across four grassland habitat types and during an eight-year period there was a significant decline in large-seeded species. In the analysis, the continuous seed size variable was used to group plant species into functional types. This method was chosen in order to account for the sampling process of the abundance data, and is in contrast to most other analyses of trait selection, where the community weighted mean of the traits is used as the dependent variable. Generally, little is known on the causes for seed size community selection in semi-natural grasslands that are not subjected to successional processes.