bluuebunny/crossref_metadata_2025_split huggingface dataset:
Systematic benchmark of state-of-the-art variant calling pipelines identifies major factors affecting accuracy of coding sequence variant discovery
Authors: Abasov Ruslan , Tvorogova Varvara E. , Glotov Andrey S. , Predeus Alexander V. , Barbitoff Yury A. 
Published: April 2021

AbstractAccurate variant detection in the coding regions of the human genome is a key requirement for molecular diagnostics of Mendelian disorders. Efficiency of variant discovery from nextgeneration sequencing (NGS) data depends on multiple factors, including reproducible coverage biases of NGS methods and the performance of read alignment and variant calling software. In this work, we systematically evaluated the performance of 4 popular short read aligners (Bowtie2, BWA, Isaac, and Novoalign) and 6 variant calling and filtering methods (based on DeepVariant, Genome Analysis ToolKit (GATK), FreeBayes, and Strelka2) using a set of 10 “gold standard” WES and WGS datasets. Our results suggest that Bowtie2 performs significantly worse than other aligners and should not be used for medical variant calling. When other aligners were used, the accuracy of variant discovery mostly depended on the variant caller and not the read aligner. Among the tested variant callers, DeepVariant consistently showed the best performance and the highest robustness, with other state-of-the-art tools, i.e. Strelka2 and GATK with 1D convolutional neural network variant scoring, also showing high performance on both WES and WGS data. The results show surprisingly large differences in the performance of cutting-edge tools even on high confidence regions of the coding genome. This highlights the importance of regular benchmarking of quickly evolving tools and pipelines. Finally, we discuss the need for a more diverse set of gold standard genomes (e.g. of African, Hispanic, or mixed ancestry) that would allow to control for deep learning model overfitting. For similar reasons there is a need for better variant caller assessment in the repetitive regions of the coding genome.
TNFα increases Tyrosine Hydroxylase expression in human monocytes
Authors: Gopinath Adithya , Badova Martin , Francisa Madison , Shaw Gerry , Collins Anthony , Miller Douglas R. , Hansen Carissa A. , Mackie Phillip , Tansey Malú Gámez , Dagra Abeer , Madorsky Irina , Ramirez-Zamora Adolfo , Okun Michael S. , Streit Wolfgang J. , Khoshbouei Habibeh 
Published: April 2021

AbstractMost, if not all, peripheral immune cells in humans and animals express tyrosine hydroxylase (TH), the rate limiting enzyme in catecholamine synthesis. Since TH is typically studied in the context of brain catecholamine signaling, little is known about changes in TH production and function in peripheral immune cells. This knowledge gap is due, in part, to the lack of an adequately sensitive assay to measure TH in immune cells expressing lower TH levels compared to other TH expressing cells. Here, we report the development of a highly sensitive and reproducible Bio-ELISA to quantify picogram levels of TH in multiple model systems. We have applied this assay to monocytes isolated from blood of persons with Parkinson’s disease (PD) and to age-matched, healthy controls. Our study unexpectedly revealed that PD patients’ monocytes express significantly higher levels of TH protein in peripheral monocytes relative to healthy controls. Tumor necrosis factor (TNFδ), a pro-inflammatory cytokine, has also been shown to be increased in the brains and peripheral circulation in human PD, as well as in animal models of PD. Therefore, we investigated a possible connection between higher levels of TH protein and the known increase in circulating TNFδ in PD. Monocytes isolated from healthy donors were treated with TNFδ or with TNFδ in the presence of an inhibitor. Tissue plasminogen activator (TPA) was used as a positive control. We observed that TNFδ stimulation increased both the number of TH+ monocytes and the quantity of TH per monocyte, without increasing the total numbers of monocytes. These results revealed that TNFδ could potentially modify monocytic TH production and serve a regulatory role in peripheral immune function. The development and application of a highly sensitive assay to quantify TH in both human and animal cells will provide a novel tool for further investigating possible PD immune regulatory pathways between brain and periphery.
Variant calling from scRNA-seq data allows the assessment of cellular identity in patient-derived cell lines
Authors: Ramazzotti Daniele , Angaroni Fabrizio , Maspero Davide , Ascolani Gianluca , Castiglioni Isabella , Piazza Rocco , Antoniotti Marco , Graudenzi Alex 
Published: April 2021

AbstractMatters Arising from:Sharma, A., Cao, E.Y., Kumar, V. et al. Longitudinal single-cell RNA sequencing of patient-derived primary cells reveals drug-induced infidelity in stem cell hierarchy.Nat Commun9, 4931 (2018).https://doi.org/10.1038/s41467-018-07261-3.In Sharma, A. et al.Nat Commun9, 4931 (2018) the authors employ longitudinal single-cell transcriptomic data from patient-derived primary and metastatic oral squamous cell carcinomas cell lines, to investigate possible divergent modes of chemo-resistance in tumor cell subpopulations. We integrated the analyses presented in the manuscript, by performing variant calling from scRNA-seq data via GATK Best Practices. As a main result, we show that an extremely high number of singlenucleotide variants representative of the identity of a specific patient is unexpectedly found in the scRNA-seq data of the cell line derived from a second patient, and vice versa. This finding likely suggests the existence of a sample swap, thus jeopardizing some of the translational conclusions of the article. Our results prove the efficacy of a joint analysis of the genotypic and transcriptomic identity of single-cells.
pUL21 is a viral phosphatase adaptor that promotes herpes simplex virus replication and spread
Authors: Benedyk Tomasz H. , Muenzner Julia , Connor Viv , Han Yue , Brown Katherine , Wijesinghe Kaveesha J. , Zhuang Yunhui , Colaco Susanna , Stoll Guido A. , Tutt Owen S. , Svobodova Stanislava , Svergun Dmitri I. , Bryant Neil A. , Deane Janet E. , Firth Andrew E. , Jeffries Cy M. , Crump Colin M. , Graham Stephen C. 
Published: April 2021

AbstractThe herpes simplex virus (HSV)-1 protein pUL21 is essential for efficient virus replication and dissemination. While pUL21 has been shown to promote multiple steps of virus assembly and spread, the molecular basis of its function remained unclear. Here we identify that pUL21 is a virus-encoded adaptor of protein phosphatase 1 (PP1). pUL21 directs the dephosphorylation of cellular and virus proteins, including components of the viral nuclear egress complex, and we define a conserved non-canonical linear motif in pUL21 that is essential for PP1 recruitment.In vitroevolution experiments reveal that pUL21 directly antagonises the activity of the virus-encoded kinase pUS3, with growth and spread of pUL21 PP1-binding mutant viruses being restored when pUS3 activity is disrupted. This study shows that virus-directed phosphatase activity is essential for efficient herpesvirus assembly and spread, highlighting the fine balance between kinase and phosphatase activity required for optimal virus replication.
RAREsim: A simulation method for very rare genetic variants
Authors: Null Megan , Dupuis Josée , Gignoux Christopher R. , Hendricks Audrey E. 
Published: April 2021

AbstractIdentification of rare variant associations is crucial to fully characterize the genetic architecture of complex traits and diseases. Essential in this process is the evaluation of novel methods in simulated data that mirrors the distribution of rare variants and haplotype structure in real data. Additionally, importing real variant annotation enables in silico comparison of methods that focus on putative causal variants, such as rare variant association tests, and polygenic scoring methods. Existing simulation methods are either unable to employ real variant annotation or severely under- or over-estimate the number of singletons and doubletons reducing the ability to generalize simulation results to real studies. We present RAREsim, a flexible and accurate rare variant simulation algorithm. Using parameters and haplotypes derived from real sequencing data, RAREsim efficiently simulates the expected variant distribution and enables real variant annotations. We highlight RAREsim’s utility across various genetic regions, sample sizes, ancestries, and variant classes.
Characteristic changes in EEG spectral powers of patients with opioid-use disorder as compared with those with methamphetamine- and alcohol-use disorders
Authors: Minnerly Christopher , Shokry Ibrahim M. , To William , Callanan John J , Tao Rui 
Published: April 2021

AbstractElectroencephalography (EEG) likely reflects activity of cortical neurocircuits, making it an insightful estimation for mental health in patients with substance use disorder (SUD). EEG signals are recorded as sinusoidal waves, containing spectral amplitudes across several frequency bands with high spatio-temporal resolution. Prior work on EEG signal analysis has been made mainly at individual electrodes. These signals can be evaluated from advanced aspects, including sub-regional and hemispheric analyses. Due to limitation of computational techniques, few studies in earlier work could conduct data analyses from these aspects. Therefore, EEG in patients with SUD is not fully understood. In the present retrospective study, spectral powers from a data house containing opioid (OUD), methamphetamine/stimulants (MUD), and alcohol use disorder (AUD) were extracted, and then converted into five distinct topographic data (i.e., electrode-based, cortical subregion-based, left-right hemispheric, anterior-posterior based, and total cortex-based analyses). We found that EEG spectral powers in patients with OUD were significantly different from those with MUD or AUD. Differential changes were observed from multiple perspectives, including individual electrodes, subregions, hemispheres, anterior-posterior cortices, and across the cortex as a whole. Understanding the differential changes in EEG signals may be useful for future work with machine learning and artificial intelligence (AI), not only for diagnostic but also for prognostic purposes in patients with SUD.
Training Data Distribution Significantly Impacts the Estimation of Tissue Microstructure with Machine Learning
Authors: Gyori Noemi G. , Palombo Marco , Clark Christopher A. , Zhang Hui , Alexander Daniel C. 
Published: April 2021

AbstractPurposeSupervised machine learning (ML) provides a compelling alternative to traditional model fitting for parameter mapping in quantitative MRI. The aim of this work is to demonstrate and quantify the effect of different training strategies on the accuracy and precision of parameter estimates when supervised ML is used for fitting.MethodsWe fit a two-compartment biophysical model to diffusion measurements from in-vivo human brain, as well as simulated diffusion data, using both traditional model fitting and supervised ML. For supervised ML, we train several artificial neural networks, as well as random forest regressors, on different distributions of ground truth parameters. We compare the accuracy and precision of parameter estimates obtained from the different estimation approaches using synthetic test data.ResultsWhen the distribution of parameter combinations in the training set matches those observed in similar data sets, we observe high precision, but inaccurate estimates for atypical parameter combinations. In contrast, when training data is sampled uniformly from the entire plausible parameter space, estimates tend to be more accurate for atypical parameter combinations but may have lower precision for typical parameter combinations.ConclusionThis work highlights the need to consider the choice of training data when deploying supervised ML for estimating microstructural metrics, as performance depends strongly on the training-set distribution. We show that high precision obtained using ML may mask strong bias, and visual assessment of the parameter maps is not sufficient for evaluating the quality of the estimates.
Intercalated Disk Nanoscale Structure Regulates Cardiac Conduction
Authors: Moise Nicolae , Struckman Heather L. , Dagher Celine , Veeraraghavan Rengasayee , Weinberg Seth H. 
Published: April 2021

AbstractThe intercalated disk (ID) is a specialized subcellular region that provides electrical and mechanical connections between myocytes in the heart. The ID has a clearly defined passive role in cardiac tissue, transmitting mechanical forces and electrical currents between cells. Recent studies have shown that Na+channels, the primary current responsible for cardiac excitation, are preferentially localized at the ID, particularly within nanodomains around mechanical and gap junctions, and that perturbations of ID structure alter cardiac conduction. This suggests that the ID may play an important, active role in regulating conduction. However, the structure of the ID and intercellular cleft are not well characterized, and to date, no models have incorporated the influence of ID structure on conduction in cardiac tissue. In this study, we developed an approach to generate realistic finite element model (FEM) meshes replicating ID nanoscale structure, based on experimental measurements from transmission electron microscopy (TEM) images. We then integrated measurements of the intercellular cleft electrical conductivity, derived from the FEM meshes, into a novel cardiac tissue model formulation. FEM-based calculations predict that the distribution of cleft conductances are sensitive to regional changes in ID structure, specifically the intermembrane separation and gap junction distribution. Tissue-scale simulations demonstrated that ID structural heterogeneity leads to significant spatial variation in electrical polarization within the intercellular cleft. Importantly, we find that this heterogeneous cleft polarization regulates conduction by desynchronizing the activation of post-junctional Na+currents. Additionally, these heterogeneities lead to a weaker dependence of conduction velocity on gap junctional coupling, compared with prior modeling formulations that neglect or simplify ID structure. Further, we find that disruption of local ID nanodomains can lead to either conduction slowing or enhancing, depending on gap junctional coupling strength. Overall, our study demonstrates that ID nanoscale structure can play a significant role in regulating cardiac conduction.
Dynamics ofSalmonellainoculated during rearing of black soldier fly larvae (Hermetia illucens) on chicken feed
Authors: De Smet J. , Vandeweyer D. , Van Moll L. , Lachi D. , Van Campenhout L. 
Published: April 2021

AbstractThe black soldier fly is currently the most produced edible insect on industrial scale, with its larval stage being processed into animal feed as the main application. As this insect species enters the feed and food chain, good hygiene and monitoring practices are needed to avoid the entrance of foodborne pathogens via the larvae. However, insufficient data on the risk of such introductions via industrial larvae production are available. To address this gap, a range of rearing trials were conducted in which the substrate, chicken feed, was inoculated with different levels ofSalmonellaand in which total viable counts andSalmonellacounts were determined during the following days. The outgrowth ofSalmonellawas slower in those experiments with a lower initial contamination level than in experiments with a higher level. No significant reducing effect originating from the larvae on the substrateSalmonellacounts was observed, in contrast to previous studies using other substrates. Our study also revealed that airborne transmission ofSalmonellais possible under rearing conditions corresponding to those applied at industrial production sites. Based on our results, we recommend insect producers to use substrate ingredients free ofSalmonella, and not to count on the antimicrobial activities that BSFL may exert in some situations towards food pathogens. More inoculation studies using otherSalmonellaserotypes, other zoonotic bacteria, other substrates, larvae of other ages and including variations on rearing protocols are needed in order to obtain a general view on the dynamics of food pathogens in this insect species and to support comprehensive risk assessments.
A Platform for Oncogenomic Reporting and Interpretation
Authors: Reisle Caralyn , Williamson Laura , Pleasance Erin , Davies Anna , Pellegrini Brayden , Bleile Dustin W , Mungall Karen L , Chuah Eric , Jones Martin R , Ma Yussanne , Beckie Isaac , Pham David , Pletz Raphael Matiello , Muhammadzadeh Amir , Pierce Brandon M , Li Jacky , Stevenson Ross , Wong Hansen , Bailey Lance , Reisle Abbey , Douglas Matthew , Bonakdar Melika , Nelson Jessica M T , Grisdale Cameron J , Krzywinski Martin , Fisic Ana , Mitchell Teresa , Renouf Daniel J , Yip Stephen , Laskin Janessa , Marra Marco A , Jones Steven J M 
Published: April 2021

AbstractManual interpretation of variants remains rate limiting in precision oncology. The increasing scale and complexity of molecular data generated from comprehensive sequencing of cancer samples requires advanced interpretative platforms as precision oncology expands beyond individual patients to entire populations. To address this unmet need, we created the Platform for Oncogenomic Reporting and Interpretation (PORI), comprising an analytic framework created to facilitate the interpretation and reporting of somatic variants in cancer. PORI is unique in its integration of reporting and graph knowledge base tools combined with support for manual curation at the reporting stage. PORI represents one of the first open-source platform alternatives to commercial reporting solutions suitable for comprehensive genomic data sets in precision oncology. We demonstrate the utility of PORI by matching 9,961 TCGA tumours to the graph knowledge base, revealing that 88.2% have at least one potentially targetable alteration, and making available reports describing select individual samples.
UCell: robust and scalable single-cell gene signature scoring
Authors: Andreatta Massimo , Carmona Santiago J. 
Published: April 2021

AbstractUCell is an R package for evaluating gene signatures in single-cell datasets. UCell signature scores, based on the Mann-Whitney U statistic, are robust to dataset size and heterogeneity, and their calculation demands less computing time and memory than other available methods, enabling the processing of large datasets in a few minutes even on machines with limited computing power. UCell can be applied to any single-cell data matrix, and includes functions to directly interact with Seurat objects. The UCell package and documentation are available on GitHub athttps://github.com/carmonalab/UCell
Sex differences and risk factors for bleeding in Alagille syndrome
Authors: Hankeova Simona , Van Hul Noemi , Laznovsky Jakub , Mangold Katrin , Hensens Naomi , Verhoef Elvira , Zikmund Tomas , Dawit Feven , Kavkova Michaela , Salplachta Jakub , Sjöqvist Marika , Johansson Bengt R. , Hassan Mohamed , Fredriksson Linda , Bryja Vitezslav , Lendahl Urban , Jheon Andrew , Alten Florian , Fahnehjelm Kristina Teär , Fischler Björn , Kaiser Jozef , Andersson Emma R. 
Published: April 2021

AbstractSpontaneous lethal bleeds are major cause of death in the pediatric liver disease Alagille syndrome (ALGS), yet risk factors and screening methods have not been established. We performed a systematic review and identified significantly more female than male patients with idiopathic intracranial hemorrhage (10:1). We investigated bleeding and vasculature in patients and a mouse model for ALGS (Jag1Ndr/Ndrmice) and asked whether phenotypes identified in mice could be detected in patients non-invasively.Jag1Ndr/Ndrmice bled spontaneously, exhibiting a thin skull and vascular defects including artery-vein crossings, tortuous vessels, capillary breakdown and CADASIL-like sparse vascular smooth muscle cell coverage which was aggravated by hypertension. Retinographs from patients confirmed tortuous blood vessels and artery-vein crossings in ALGS. In conclusion,Jag1Ndr/Ndrmice could be used to develop interventions for vascular defects in ALGS, and retinography could provide a non-invasive method for vascular analysis in these pediatric patients.
Visualization of reactive astrocytes in living brain of Alzheimer’s disease patient
Authors: Nam Min-Ho , Ko Hae Young , Lee Sangwon , Park Yongmin Mason , Hyeon Seung Jae , Won Woojin , Kim Seon Yoo , Jo Han Hee , Chung Jee-In , Han Young-Eun , Lee Gwan-Ho , Ju Yeonha , Stein Thor D. , Kong Mingyu , Lee Hyunbeom , Lee Seung Eun , Oh Soo-Jin , Chun Joong-Hyun , Park Ki Duk , Ryu Hoon , Yun Mijin , Lee C. Justin 
Published: April 2021

AbstractAn early appearance of reactive astrocytes is a hallmark of Alzheimer’s disease (AD)1,2, providing a substrate for early diagnostic neuroimaging targets. However, there is no clinically validated neuroimaging probe to visualize the reactive astrogliosis in the human brainin vivo. Here, we report that PET/CT imaging with11C-acetate and18F-fluorodeoxyglucose (18F-FDG) functionally visualizes the reactive astrocyte-mediated neuronal hypometabolism in the brains with neuroinflammation and AD. We demonstrate that reactive astrocytes excessively absorb acetate through elevated monocarboxylate transporter-1 (MCT1), leading to aberrant GABA synthesis and release which suppresses neuronal glucose uptake through decreased glucose transporter-3 (GLUT3) in both animal and human brains. We propose the non-invasive functional PET/CT imaging for astrocytic acetate-hypermetabolism and neuronal glucose-hypometabolism as an advanced diagnostic strategy for early stages of AD.
Visualizing cancer-originated acetate uptake through MCT1 in reactive astrocytes demarcates tumor border and extends survival in glioblastoma patients
Authors: Ko Hae Young , Chung Jee-In , Kim Dongwoo , Park Yongmin Mason , Jo Han Hee , Lee Sangwon , Kim Seon Yoo , Kim Jisu , Chun Joong-Hyun , Han Kyung-Seok , Lee Misu , Ju Yeonha , Park Sun Jun , Park Ki Duk , Nam Min-Ho , Park Youngjoo , Kim Se Hoon , Shim Jin-Kyoung , Kang Seok-Gu , Chang Jong Hee , Lee C. Justin , Yun Mijin 
Published: April 2021

SummaryGlioblastoma multiforme (GBM) is a devastating brain tumor with dismal prognosis of only 15-month survival regardless of surgical resection. Here, we report an advanced neuroimaging technique combining11C-acetate PET and MRI (AcePET), visualizing the boundary beyond the MRI-defined tumor. Targeted biopsy of the regions with increased11C-acetate uptake revealed the presence of reactive astrocytes with enhanced acetate-transporter MCT1, along with cancer stem cells. Reactive astrogliosis and MCT1-dependent11C-acetate-uptake were recapitulated in U87MG-orthotopic models. Mechanistically, glycolytic tumor cells release excessive acetate causing reactive astrogliosis, leading to the release of aberrant astrocytic GABA and H2O2, which further down-regulate the neuronal glucose uptake through GLUT3. Clincally, AcePET-guided surgery allows complete tumor resection of infiltrating cancer stem cells and extends the overall survival of patients by 5.25 months compared to conventional MRI-guided surgery. We established a new concept of the metabolic interactions between GBM cells and neighboring neurons through reactive astrocytes and developed AcePET-guided surgery to fight against GBM.