bluuebunny/crossref_metadata_2025_split huggingface dataset:
Transcriptome-Wide Off-Target Effects of Steric-Blocking Oligonucleotides
Authors: Holgersen Erle M. , Gandhi Shreshth , Zhou Yongchao , Kim Jinkuk , Vaz Brandon , Bogojeski Jovanka , Bugno Magdalena , Shalev Zvi , Cheung-Ong Kahlin , Gonçalves João , O’Hara Matthew , Sun Mark , Kakaradov Boyko , Delong Andrew , Merico Daniele , Deshwar Amit G. 
Published: September 2020

AbstractSteric-blocking oligonucleotides (SBOs) are short, single-stranded nucleic acids designed to modulate gene expression by binding to mRNA and blocking access from cellular machinery such as splicing factors. SBOs have the potential to bind to near-complementary sites in the transcriptome, causing off-target effects. In this study, we used RNA-seq to evaluate the off-target differential splicing events of 81 SBOs and differential expression events of 46 SBOs. Our results suggest that differential splicing events are predominantly hybridization-driven, while differential expression events are more common and driven by other mechanisms. We further evaluated the performance of in silico screens for off-target events, and found an edit distance cutoff of three to result in a sensitivity of 14% and false discovery rate of 99%. A machine learning model incorporating splicing predictions substantially improved the ability to prioritize low edit distance hits, increasing sensitivity from 4% to 26% at a fixed FDR. Despite these large improvements in performance, the approach does not detect the majority of events at a false discovery rate below 99%. Our results suggest that in silico methods are currently of limited use for predicting the off-target effects of SBOs.
Oxidized Lipids and CD36-Mediated Lipid Peroxidation in CD8 T Cells Suppress Anti-Tumor Immune Responses
Authors: Xu Shihao , Chaudhary Omkar , Rodríguez-Morales Patricia , Sun Xiaoli , Zappasodi Roberta , Xu Ziyan , Pinto Antonio F. M. , Williams April , Chen Dan , Low Jun Siong , Farsakoglu Yagmur , Tang Wenxi , Wang Haiping , Varanasi Siva Karthik , McDonald Bryan , Tripple Victoria , Downes Michael , Evans Ronald M. , Abumrad Nada A. , Merghoub Taha , Wolchok Jedd D. , Shokhirev Maxim N. , Ho Ping-Chih , Witztum Joseph L. , Emu Brinda , Cui Guoliang , Kaech Susan M. 
Published: September 2020

SummaryT cell metabolic fitness plays a pivotal role in anti-tumor immunity and metabolic deregulation causes T cell dysfunction (i.e., ‘exhaustion’) in cancer. We identify that the scavenger receptor CD36 limits anti-tumor CD8+T cell effector functions through lipid peroxidation. In murine tumors, oxidized phospholipids (OxPLs) were highly abundant and CD8+TILs increased uptake and accumulation of lipids and lipid peroxidation. Functionally ‘exhausted’ CD8+TILs substantially increased CD36 expression and CD36-deficient CD8+TILs had more robust anti-tumor activity and cytokine production than wild-type cells. We further show that CD36 promotes uptake of oxidized low-density lipoproteins (OxLDL) and induces lipid peroxidation in CD8+TILs, and OxLDL inhibits CD8+T cell functions in a CD36-dependent manner. Moreover, glutathione peroxidase 4 (GPX4) over-expression lowers lipid peroxidation and restores functionalities in CD8+TILs. These results define a key role for an oxidized lipid-CD36 axis in promoting intratumoral CD8+T cell dysfunction.
A vapor exposure method for delivering heroin alters nociception, body temperature and spontaneous activity in female and male rats
Authors: Gutierrez Arnold , Creehan Kevin M. , Taffe Michael A. 
Published: September 2020

AbstractBackgroundThe ongoing crisis related to non-medical use of opioids makes it of continued importance to understand the risk factors for opioid addiction, the behavioral and neurobiological consequences of opioid exposure and to seek potential avenues for therapy. Pre-clinical rodent models have been critical to advancing understanding of opioid consequences for decades, but have been mostly limited to drug delivery by injection or by oral dosing. Inhalation, a significant route for many human users, has not been as well-established.MethodWe adapted an e-cigarette based exposure system, previously shown efficacious for delivery of other drugs to rats, to deliver heroin vapor. Effectsin vivowere assessed in male and female Sprague-Dawley rats using a warm-water assay for anti-nociception and an implanted radiotelemetry system for evaluating changes in body temperature and spontaneous activity rate.ResultsInhalation of vapor created by heroin 100 mg/mL in the propylene glycol (PG) vehicle significantly slowed tail-withdrawal from a 52°C water bath, bi-phasically altered activity, and increased temperature in male and female rats. Inhalation of heroin 50 mg/mL for 15 minutes produced significant effects, as the lower bound on efficacy, whereas inhalation of heroin 100 mg/mL for 30 minutes produced robust effects across all endpoints and groups.ConclusionsThis work shows that e-cigarette devices deliver psychoactive doses of heroin to rats, using concentrations of ∼50-100 mg/mL and inhalation durations of 15-30 minutes. This technique may be useful to assess the health consequences of inhaled heroin and other opioid drugs.
Combinatorial native MS and LC-MS/MS approach reveals high intrinsic phosphorylation of human Tau but minimal levels of other key modifications
Authors: Drepper Friedel , Biernat Jacek , Kaniyappan Senthillvelrajan , Meyer Helmut E. , Mandelkow Eva Maria , Warscheid Bettina , Mandelkow Eckhard 
Published: September 2020

AbstractAbnormal changes in the neuronal microtubule-associated protein Tau, such as hyperphosphorylation and aggregation, are considered hallmarks of cognitive deficits in Alzheimer disease. Hyperphosphorylation is thought to take place before aggregation, and therefore it is often assumed that phosphorylation predisposes Tau towards aggregation. However, the nature and extent of phosphorylation has remained ill-defined. Tau protein contains up to 85 potential phosphorylation sites (80 Ser/Thr, and 5 Tyr P-sites), many of which can be phosphorylated by various kinases because the unfolded structure of Tau makes them accessible. However, limitations in methods (e.g. in mass spectrometry of phosphorylated peptides, or antibodies against phospho-epitopes) have led to conflicting results regarding the overall degree of phosphorylation of Tau in cells. Here we present results from a new approach, that is based on native mass spectrometry analysis of intact Tau expressed in a eukaryotic cell system (Sf9) which reveals Tau in different phosphorylation states. The extent of phosphorylation is remarkably heterogeneous with up to ∼20 phosphates (Pi) per molecule and distributed over 51 sites (including all P-sites published so far and additional 18 P-sites). The medium phosphorylated fraction Pmshowed overall occupancies centered at 8 Pi(± 5 Pi) with a bell-shaped distribution, the highly phosphorylated fraction Phhad 14 Pi(± 6 Pi). The distribution of sites was remarkably asymmetric (with 71% of all P-sites located in the C-terminal half of Tau). All phosphorylation sites were on Ser or Thr residues, but none on Tyr. Other known posttranslational modifications of Tau were near or below our detection limit (e.g. acetylation, ubiquitination). None of the Tau fractions self-assemble readily, arguing that Tau aggregation is not promoted by phosphorylation per se but requires additional factors.
Subcutaneous nanotherapy repurposes the immunosuppressive mechanism of rapamycin to enhance allogeneic islet graft viability
Authors: Burke Jacqueline A. , Zhang Xiaomin , Reddy Bobbala Sharan Kumar , Frey Molly A. , Fuentes Carolina Bohorquez , Haddad Helena Freire , Allen Sean D. , Richardson Reese A.K. , Ameer Guillermo A. , Scott Evan A. 
Published: September 2020

AbstractOral rapamycin administration rapamycin is plagued by poor bioavailability and wide biodistribution. Thus, this pleotropic mTOR inhibitor has a narrow therapeutic window, numerous side effects and provides inadequate transplantation protection. Parental formulation was not possible due to rapamycin’s hydrophobicity (log P 4.3). Here, we demonstrate that subcutaneous rapamycin delivery via poly(ethylene glycol)-b-poly(propylene sulfide)(PEG-b-PPS) polymersome (PS) nanocarriers modulates cellular biodistribution of rapamycin to change its immunosuppressive mechanism for enhanced efficacy while minimizing side effects. While oral rapamycin inhibits naïve T cell proliferation directly, subcutaneously administered rapamycin-loaded polymersomes (rPS) instead modulated Ly-6Clowmonocytes and tolerogenic semi-mature dendritic cells, with immunosuppression mediated by CD8+ Tregs and rare CD4+ CD8+ double-positive T cells. As PEG-b-PPS PS are uniquely non-inflammatory, background immunostimulation from the vehicle was avoided, allowing immunomodulation to be primarily attributed to rapamycin’s cellular biodistribution. Repurposing mTOR inhibition significantly improved maintenance of normoglycemia in a clinically relevant, MHC-mismatched, allogeneic, intraportal (liver) islet transplantation model. These results demonstrate the ability of engineered nanocarriers to repurpose drugs for alternate routes of administration by rationally controlling cellular biodistribution.
NHR-49/PPAR-α and HLH-30/TFEB promoteC. eleganshost defense via a flavin-containing monooxygenase
Authors: Wani Khursheed A. , Goswamy Debanjan , Taubert Stefan , Ratnappan Ramesh , Ghazi Arjumand , Irazoqui Javier E. 
Published: September 2020

SUMMARYDuring bacterial infection, the host is confronted with multiple overlapping signals that are integrated at the organismal level to produce defensive host responses. How multiple infection signals are sensed by the host and how they elicit the transcription of host defense genes is much less understood at the whole-animal level than at the cellular level. The model organismCaenorhabditis elegansis known to mount transcriptional defense responses against intestinal bacterial infections that elicit overlapping starvation and infection responses, but the regulation of such responses is not well understood. Direct comparison ofC. elegansthat were starved or infected withStaphylococcus aureusrevealed a large infection-specific transcriptional signature. This signature was almost completely abrogated by deletion of transcription factorhlh-30/TFEB, except for six genes including a flavin-containing monooxygenase (FMO) gene,fmo-2/FMO5. Deletion offmo-2/FMO5severely compromised infection survival, thus identifying the first FMO with innate immunity functions in animals. Moreover, the mechanism offmo-2/FMO5induction required the nuclear hormone receptor, NHR-49/PPAR-α, which inducedfmo-2/FMO5and host defense cell non-autonomously. These findings for the first time reveal an infection-specific host response toS. aureus, identify HLH-30/TFEB as its main regulator, reveal that FMOs are important innate immunity effectors in animals, and identify the mechanism of FMO regulation through NHR-49/PPAR-α inC. elegans, with important implications for innate host defense in higher organisms.
Correlation imputation in single cell RNA-seq using auxiliary information and ensemble learning
Authors: Gan Luqin , Vinci Giuseppe , Allen Genevera I. 
Published: September 2020

AbstractSingle cell RNA sequencing is a powerful technique that measures the gene expression of individual cells in a high throughput fashion. However, due to sequencing inefficiency, the data is unreliable due to dropout events, or technical artifacts where genes erroneously appear to have zero expression. Many data imputation methods have been proposed to alleviate this issue. Yet, effective imputation can be difficult and biased because the data is sparse and high-dimensional, resulting in major distortions in downstream analyses. In this paper, we propose a completely novel approach that imputes the gene-by-gene correlations rather than the data itself. We call this method SCENA: Single cell RNA-seq Correlation completion by ENsemble learning and Auxiliary information. The SCENA gene-by-gene correlation matrix estimate is obtained by model stacking of multiple imputed correlation matrices based on known auxiliary information about gene connections. In an extensive simulation study based on real scRNA-seq data, we demonstrate that SCENA not only accurately imputes gene correlations but also outperforms existing imputation approaches in downstream analyses such as dimension reduction, cell clustering, graphical model estimation.
SS-Detect: Development and Validation of a New Strategy for Source-Based Morphometry in Multi-Scanner Studies
Authors: Ge Ruiyang , Ding Shiqing , Keeling Tyler , Honer William G. , Frangou Sophia , Vila-Rodriguez Fidel 
Published: September 2020

ABSTRACTBackground and PurposeSource-based morphometry (SBM) has been used in multi-centre studies pooling magnetic resonance imaging (MRI) data across different scanners to advance the reproducibility of neuroscience research. In the present study, we developed an analysis strategy forScanner-SpecificDetection (SS-Detect) of SBPs in multi-scanner studies, and evaluated its performance relative to a conventional strategy.MethodsIn the first experiment, the SimTB toolbox was used to generate simulated datasets mimicking twenty different scanners with common and scanner-specific SBPs. In the second experiment, we generated one simulated SBP from empirical gray matter volume (GMV) datasets from two different scanners. Moreover, we applied two strategies to compare SBPs between schizophrenia patients’ and healthy controls’ GMV from two different scanners.ResultsThe outputs of the conventional strategy were limited to whole-sample-level results across all scanners; the outputs of SS-Detect included whole-sample-level and scanner-specific results. In the first simulation experiment, SS-Detect successfully estimated all simulated SBPs, including the common and scanner-specific SBPs whereas the conventional strategy detected only some of the whole-sample SBPs. The second simulation experiment showed that both strategies could detect the simulated SBP. Quantitative evaluations of both experiments demonstrated greater accuracy of the SS-Detect in estimating spatial SBPs and subject-specific loading parameters. In the third experiment, SS-Detect detected more significant between-group SBPs, and these SBPs corresponded with the results from voxel-based morphometry analysis, suggesting that SS-Detect has higher sensitivity in detecting between-group differences.ConclusionsSS-Detect outperformed the conventional strategy and can be considered advantageous when SBM is applied to a multi-scanner study.
Inferring number of populations and changes in connectivity under the n-island model
Authors: Arredondo Armando , Mourato Beatriz , Nguyen Khoa , Boitard Simon , Rodríguez Willy , Noûs Camille , Mazet Olivier , Chikhi Lounès 
Published: September 2020

AbstractInferring the demographic history of species is one of the greatest challenges in populations genetics. This history is often represented as a history of size changes, thus ignoring population structure. Alternatively, structure is defined a priori as a population tree and not inferred. Here we propose a framework based on the IICR (Inverse Instantaneous Coalescence Rate), which can be estimated using the PSMC method of Li and Durbin (2011) for a single diploid individual. For an isolated population, the IICR matches the population size history, which is how the PSMC outputs are generally interpreted. However, it is increasingly acknowledged that the IICR is a function of the demographic model and sampling scheme. Our automated method fits observed IICR curves of diploid individuals with IICR curves obtained under piecewise-stationary symmetrical island models, in which we assume a fixed number of time periods during which gene flow is constant. We infer the number of islands, their sizes, the periods at which connectivity changes and the corresponding rates of connectivity. Validation with simulated data showed that the method can accurately recover most of the scenario parameters. Our application to a set of five human PSMCs yielded demographic histories that are in agreement with previous studies using similar methods and with recent research suggesting ancient human structure. They are in contrast with the widely accepted view of human evolution consisting of one ancestral population branching into three large continental and panmictic populations with varying degrees of connectivity and no population structure within each continent.
Mammalian ANP32A and ANP32B proteins drive alternative avian influenza virus polymerase adaptations
Authors: Peacock Thomas. P. , Sheppard Carol M. , Staller Ecco , Frise Rebecca , Swann Olivia C. , Goldhill Daniel H. , Long Jason S. , Barclay Wendy S. 
Published: September 2020

AbstractANP32 proteins, which act as influenza polymerase co-factors, vary between birds and mammals. The well-known mammalian adaptation, PB2-E627K, enables influenza polymerase to use mammalian ANP32 proteins. However, some mammalian-adapted influenza viruses do not harbour this adaptation. Here, we show that alternative PB2 adaptations, Q591R and D701N also allow influenza polymerase to use mammalian ANP32 proteins. PB2-E627K strongly favours use of mammalian ANP32B proteins, whereas D701N shows no such bias. Accordingly, PB2-E627K adaptation emerges in species with strong pro-viral ANP32B proteins, such as humans and mice, while D701N is more commonly seen in isolates from swine, dogs and horses where ANP32A proteins are more strongly pro-viral. In an experimental evolution approach, passage of avian viruses in human cells drives acquisition of PB2-E627K, but not when ANP32B is ablated. The strong pro-viral support of ANP32B for PB2-E627K maps to the LCAR region of ANP32B.
Inferring metabolic rewiring in embryonic neural development using single cell data
Authors: Jatav Shashank , Malhotra Saksham , Miller Freda D , Jha Abhishek , Goyal Sidhartha 
Published: September 2020

AbstractMetabolism is intricately linked with cell fate changes. Much of this understanding comes from detailed metabolomics studies averaged across a population of cells which may be composed of multiple cell types. Currently, there are no quantitative techniques sensitive enough to assess metabolomics broadly at the single cell level. Here we presentscMetNet, a technique that interrogates metabolic rewiring at the single cell resolution and we apply it to murine embryonic development. Our method first confirms the key metabolic pathways, categorized into bioenergetic, epigenetic and biosynthetic, that change as embryonic neural stem cells differentiate and age. It then goes beyond to identify specific sub-networks, such as the cholesterol and mevalonate biosynthesis pathway, that drive the global metabolic changes during neural cortical development. Having such contextual information about metabolic rewiring provides putative mechanisms driving stem cell differentiation and identifies potential targets for regulating neural stem cell and neuronal biology.
Thermodynamic constraints are sufficient for the emergence of flux sensors in metabolism
Authors: Euler Christian Karl , Mahadevan Radhakrishnan 
Published: September 2020

AbstractMetabolism is a precisely coordinated phenomenon, the apparent goal of which is to balance fluxes to maintain robust growth. However, coordinating fluxes requires information aboutrates, which is not obviously reconcilable with known regulatory mechanisms in whichconcentrationsare sensed through metabolite binding. While flux sensor examples have been characterized, the fundamental principles underlying the phenomenon in general are not well understood. Specifically, the questions of which fluxes can be sensed, and the mechanism by which they are remain open. We address this by showing that the concentrations of substrates of thermodynamically constrained reactions reflect upstream flux and therefore carry information about rates which can be propagated through regulatory interactions to control other fluxes in the network. Using fluxomic, metabolomic, and thermodynamic data inE coli, we show that the concentrations of a few metabolites in central carbon metabolism reflect their producing fluxes and demonstrate that they can transmit information about these rates because of their positions in the network and their roles as effectors.
SILAC-Based Quantitative Proteomics Identifies Multifactorial Mechanism of Oxaliplatin Resistance in Pancreatic Cancer Cells
Authors: Kim Young Eun , Kim Eun-Kyung , Song Min-Jeong , Kim Tae-Young , Jang Ho Hee , Kang Dukjin 
Published: September 2020

AbstractOxaliplatin is a commonly used chemotherapeutic drug for the treatment of pancreatic cancer. Understanding the cellular mechanisms of oxaliplatin resistance is important for developing new strategies to overcome drug resistance in pancreatic cancer. In this study, we performed a stable isotope labelling by amino acids in cell culture (SILAC)-based quantitative proteomic analysis of oxaliplatin-resistant and sensitive pancreatic cancer PANC-1 cells. We identified 107 proteins whose expression levels changed between oxaliplatin-resistant and sensitive cells, which were involved in multiple biological processes, including DNA repair, drug response, apoptotic signalling, and the type 1 interferon signalling pathway. Notably, myristoylated alanine-rich C-kinase substrate (MARCKS) and wntless homolog protein (WLS) were upregulated in oxaliplatin-resistant cells compared to sensitive cells, as confirmed by qRT-PCR and Western blot analysis. We further demonstrated the activation of AKT and β-catenin signalling (downstream targets of MARCKS and WLS, respectively) in oxaliplatin-resistant PANC-1 cells. Additionally, we show that the siRNA-mediated suppression of both MARCKS and WLS enhanced oxaliplatin sensitivity in oxaliplatin-resistant PANC-1 cells. Taken together, our results provide insights into multiple mechanisms of oxaliplatin resistance in pancreatic cancer cells and reveal that MARCKS and WLS might be involved in the chemotherapeutic resistance in pancreatic cancer.
Brazilian Natura & Co: creating cosmetic powerhouse. Empirical evidence of competence-based synergies in M&A processes
Authors: čirjevskis Andrejs 
Published: September 2020

PurposeThis paper aims to operationalize and to test the ARCTIC (A – Advantage, R – Relatedness, C – Complexity of Competence, T – Time of Integration, I – Implementation Plan, C – Cultural Fit) framework to assess the prerequisites of competence-based synergy in the acquisition process. The current research provides new analyses of recent acquisitions in the global beauty industry where the ARCTIC framework was satisfied and where the ARCTIC model was NOT satisfied by decisive factors to get the acquisition's synergies. It allows readers to contrast two case studies and grasp how the framework works in greater detail.Design/methodology/approachThe current research relies on an extensive archival search that included financial statements, annual reports, internal documents, industry publications and CEO statements to get at a micro-level understanding. This boosts research data and the operationalization of the ARCTIC framework.FindingsThe research identified four steps for investigating whether core competence transfer in an acquisition process would be a source of competence-based synergies. The incorporation of real options into the synergy valuation measures market value-added arising from M&A deals.Originality/valueThe current paper contributes to theoretical and practical issues of global M&As as part of the existing literature of international business and strategic management. The impact on reciprocal synergies of agency problems, external interaction between CEOs in M&A deals, corporate governance systems and an executive compensation theory are promising areas of future research.