bluuebunny/crossref_metadata_2025_split huggingface dataset:
PARP and PI3K inhibitor combination therapy eradicates c-MYC-driven murine prostate cancers via cGAS/STING pathway activation within tumor-associated macrophages
Authors: Gupta Priyanka Dutta , Chaudagar Kiranj , Sharma-Saha Sweta , Bynoe Kaela , Maillat Lea , Heiss Brian , Stadler Walter M , Patnaik Akash 
Published: July 2020

ABSTRACTThe majority of metastatic, castrate-resistant prostate cancer (mCRPC) patients arede novoresistant to immune checkpoint blockade (ICB), so therapeutic strategies to enhance immune-responsiveness are urgently needed. Here we performed a co-clinical trial of PARP inhibitor (PARPi) in combination with PD-1 or PDL-1 antibody in genomically unselected mCRPC patients or homologous-recombination proficient murine models, respectively, which demonstrated lack of efficacy. In contrast, PARPi in combination with PI3K inhibitor (PI3Ki), induced tumor regression via macrophage STING-dependent innate immune activationin vivo, and enhanced T-cell infiltration/activation in c-myc driven murine prostate cancer models, which was augmented by PD-L1 blockade.Ex vivomechanistic studies revealed that PARPi-induced DNA double strand break-associated microvesicles released from tumor cells, coupled with PI3Ki-mediated c-GAS de-repression, were both required for macrophage cGAS/STING pathway activation. These data demonstrate that PARPi/PI3Ki combination triggers macrophage STING-mediated anti-cancer innate immunity, which is sufficient to induce tumor regression in ICB-refractory c-myc-driven prostate cancer.STATEMENT OF SIGNIFICANCECo-targeting of PARP and PI3K signaling pathways activates c-GAS/STING pathway within tumor-associated macrophages, thereby enhancing T cell recruitment/activation and cancer clearance in c-myc-driven murine prostate cancer models. PARPi/PI3Ki combination therapy could markedly increase the fraction of mCRPC patients responsive to ICB, independent of germline or tumor homologous recombination status.
Preparing For the Next Pandemic: Learning Wild Mutational Patterns At Scale For Analyzing Sequence Divergence In Novel Pathogens
Authors: Li Jin , Li Timmy , Chattopadhyay Ishanu 
Published: July 2020

AbstractAs we begin to recover from the COVID-19 pandemic, a key question is if we can avert such disasters in future. Current surveillance protocols generally focus on qualitative impact assessments of viral diversity 1. These efforts are primarliy aimed at ecosystem and human impact monitoring, and do not help to precisely quantify emergence. Currently, the similarity of biological strains is measured by the edit distance or the number of mutations that separate their genomic sequences 2–6, e.g. the number of mutations that make an avian flu strain human-adapted. However, ignoring the odds of those mutations in the wild keeps us blind to the true jump risk, and gives us little indication of which strains are more risky. In this study, we develop a more meaningful metric for comparison of genomic sequences. Our metric, the q-distance, precisely quantifies the probability of spontaneous jump by random chance. Learning from patterns of mutations from large sequence databases, the q-distance adapts to the specific organism, the background population, and realistic selection pressures; demonstrably improving inference of ancestral relationships and future trajectories. As important application, we show that the q-distance predicts future strains for seasonal Influenza, outperforming World Health Organization (WHO) recommended flu-shot composition almost consistently over two decades. Such performance is demonstrated separately for Northern and Southern hemisphere for different subtypes, and key capsidic proteins. Additionally, we investigate the SARS-CoV-2 origin problem, and precisely quantify the likelihood of different animal species that hosted an immediate progenitor, producing a list of related species of bats that have a quantifiably high likelihood of being the source. Additionally, we identify specific rodents with a credible likelihood of hosting a SARS-CoV-2 ancestor. Combining machine learning and large deviation theory, the analysis reported here may open the door to actionable predictions of future pandemics.
Sample Adequacy Controls for Infectious Disease Diagnosis by Oral Swabbing
Authors: Deviaene Meagan , Weigel Kris M. , Wood Rachel C. , Luabeya Angelique K. K. , Jones-Engel Lisa , Hatherill Mark , Cangelosi Gerard A. 
Published: July 2020

ABSTRACTOral swabs are emerging as a non-invasive sample type for diagnosing infectious diseases including Ebola, tuberculosis (TB), and COVID-19. To assure proper sample collection, sample adequacy controls (SACs) are needed that detect substances indicative of samples collected within the oral cavity. This study evaluated two candidate SACs for this purpose. One detected representative oral microbiota (Streptococcus species DNA) and the other, human cells (human mitochondrial DNA, mtDNA). Quantitative PCR (qPCR) assays for the two target cell types were applied to buccal swabs (representing samples collected within the oral cavity) and hand swabs (representing improperly collected samples) obtained from 51 healthy U.S. volunteers. Quantification cycle (Cq) cutoffs that maximized Youden’s index were established for each assay. The streptococcal target at a Cq cutoff of ≤34.9 had 99.0% sensitivity and specificity for oral swab samples, whereas human mtDNA perfectly distinguished between hand and mouth swabs with a Cq cutoff of 31.3. The human mtDNA test was then applied to buccal, tongue, and gum swabs that had previously been collected from TB patients and controls in South Africa, along with “air swabs” collected as negative controls (total N = 292 swabs from 71 subjects). Of these swabs, 287/292 (98%) exhibited the expected Cq values. In a paired analysis the three oral sites yielded indistinguishable amounts of human mtDNA, however PurFlock™ swabs collected slightly more human mtDNA than did OmniSwabs™ (p = 0.012). The results indicate that quantification of human mtDNA cannot distinguish swabs collected from different sites within the mouth. However, it can reliably distinguish oral swabs from swabs that were not used orally., which makes it a useful SAC for oral swab-based diagnosis.
Geographic access to COVID-19 healthcare in Brazil using a balanced float catchment area approach
Authors: Pereira Rafael H. M. , Braga Carlos Kauê Vieira , Servo Luciana Mendes , Serra Bernardo , Amaral Pedro , Gouveia Nelson , Paez Antonio 
Published: July 2020

AbstractThe rapid spread of the new coronavirus across the world has raised concerns about the responsiveness of cities and healthcare systems during pandemics. Recent studies try to model how the number of COVID-19 infections will likely grow and impact the demand for hospitalization services at national and regional levels. However, less attention has been paid to the geographic access to COVID-19 healthcare services and to the response capacity of hospitals at the local level, particularly in urban areas in the Global South. This paper shows how transport accessibility analysis can provide actionable information to help improve healthcare coverage and responsiveness. It analyzes accessibility to COVID-19 healthcare at high spatial resolution in the 20 largest cities of Brazil. Using network-distance metrics, we estimate the vulnerable population living in areas with poor access to healthcare facilities that could either screen or hospitalize COVID-19 patients. We then use a new balanced floating catchment area (BFCA) indicator to estimate spatial, income and racial inequalities in access to hospitals with intensive care unit (ICU) beds and mechanical ventilators while taking into account congestion effects. Based on this analysis, we identify substantial social and spatial inequalities in access to health services during the pandemic. The availability of ICU equipment varies considerably between cities and it is substantially lower among black and poor communities. The study maps territorial inequalities in healthcare access and reflects on different policy lessons that can be learned for other countries based on the Brazilian case.
Large-scale Multi-omic Analysis of COVID-19 Severity
Authors: Overmyer Katherine A. , Shishkova Evgenia , Miller Ian J. , Balnis Joseph , Bernstein Matthew N. , Peters-Clarke Trenton M. , Meyer Jesse G. , Quan Qiuwen , Muehlbauer Laura K. , Trujillo Edna A. , He Yuchen , Chopra Amit , Chieng Hau C. , Tiwari Anupama , Judson Marc A. , Paulson Brett , Brademan Dain R. , Zhu Yunyun , Serrano Lia R. , Linke Vanessa , Drake Lisa A. , Adam Alejandro P. , Schwartz Bradford S. , Singer Harold A. , Swanson Scott , Mosher Deane F. , Stewart Ron , Coon Joshua J. , Jaitovich Ariel 
Published: July 2020

SUMMARYWe performed RNA-Seq and high-resolution mass spectrometry on 128 blood samples from COVID-19 positive and negative patients with diverse disease severities. Over 17,000 transcripts, proteins, metabolites, and lipids were quantified and associated with clinical outcomes in a curated relational database, uniquely enabling systems analysis and cross-ome correlations to molecules and patient prognoses. We mapped 219 molecular features with high significance to COVID-19 status and severity, many involved in complement activation, dysregulated lipid transport, and neutrophil activation. We identified sets of covarying molecules, e.g., protein gelsolin and metabolite citrate or plasmalogens and apolipoproteins, offering pathophysiological insights and therapeutic suggestions. The observed dysregulation of platelet function, blood coagulation, acute phase response, and endotheliopathy further illuminated the unique COVID-19 phenotype. We present a web-based tool (covid-omics.app) enabling interactive exploration of our compendium and illustrate its utility through a comparative analysis with published data and a machine learning approach for prediction of COVID-19 severity.
Quantifying SARS-CoV-2 infection risk within the Google/Apple exposure notification framework to inform quarantine recommendations
Authors: Wilson Amanda M. , Aviles Nathan , Petrie James I. , Beamer Paloma I. , Szabo Zsombor , Xie Michelle , McIllece Janet , Chen Yijie , Son Young-Jun , Halai Sameer , White Tina , Ernst Kacey C. , Masel Joanna 
Published: July 2020

ABSTRACTMost Bluetooth-based exposure notification apps use three binary classifications to recommend quarantine following SARS-CoV-2 exposure: a window of infectiousness in the transmitter, ≥15 minutes duration, and Bluetooth attenuation below a threshold. However, Bluetooth attenuation is not a reliable measure of distance, and infection risk is not a binary function of distance, nor duration, nor timing. We model uncertainty in the shape and orientation of an exhaled virus-containing plume and in inhalation parameters, and measure uncertainty in distance as a function of Bluetooth attenuation. We calculate expected dose by combining this with estimated infectiousness based on timing relative to symptom onset. We calibrate an exponential dose-response curve based on infection probabilities of household contacts. The probability of current or future infectiousness, conditioned on how long post-exposure an exposed individual has been symptom-free, decreases during quarantine, with shape determined by incubation periods, proportion of asymptomatic cases, and asymptomatic shedding durations. It can be adjusted for negative test results using Bayes Theorem. We capture a 10-fold range of risk using 6 infectiousness values, 11-fold range using 3 Bluetooth attenuation bins, ∼6-fold range from exposure duration given the 30 minute duration cap imposed by the Google/Apple v1.1, and ∼11-fold between the beginning and end of 14 day quarantine. Public health authorities can either set a threshold on initial infection risk to determine 14-day quarantine onset, or on the conditional probability of current and future infectiousness conditions to determine both quarantine and duration.
Novel features of centriole polarity and cartwheel stacking revealed by cryo-tomography
Authors: Nazarov Sergey , Bezler Alexandra , Hatzopoulos Georgios N , Villímová Veronika Nemčíková , Demurtas Davide , Le Guennec Maeva , Guichard Paul , Gönczy Pierre 
Published: July 2020

SummaryCentrioles are polarized microtubule-based organelles that seed the formation of cilia, and which assemble from a cartwheel containing stacked ring oligomers of SAS-6 proteins. A cryo-tomography map of centrioles from the termite flagellateTrichonymphaspp. was obtained previously, but higher resolution analysis is likely to reveal novel features. Using sub-tomogram averaging (STA) inT.spp. andTrichonympha agilis, we delineate the architecture of centriolar microtubules, pinhead and A-C-linker. Moreover, we report ∼25 Å resolution maps of the central cartwheel, revealing notably polarized cartwheel inner densities (CID). Furthermore, STA of centrioles from the distant flagellateTeranympha mirabilisuncovers similar cartwheel architecture and a distinct filamentous CID. Fitting the CrSAS-6 crystal structure into the flagellate maps and analyzing cartwheels generatedin vitroindicates that SAS-6 rings can directly stack onto one another in two alternating configurations: with a slight rotational offset and in register. Overall, improved STA maps in three flagellates enabled us to unravel novel architectural features, including of centriole polarity and cartwheel stacking, thus setting the stage for an accelerated elucidation of underlying assembly mechanisms.
Assessing the impact of grassland management on landscape multifunctionality
Authors: Neyret M. , Fischer M. , Allan E. , Hölzel N. , Klaus V.H. , Kleinebecker T. , Krauss J. , Le Provost G. , Peter S. , Schenk N. , Simons N.K. , van der Plas F. , Binkenstein J. , Börschig C. , Jung K. , Prati D. , Schäfer D. , Schäfer M. , Schöning I. , Schrumpf M. , Tschapka M. , Westphal C. , Manning P. 
Published: July 2020

AbstractLand-use intensification has contrasting effects on different ecosystem services, often leading to land-use conflicts. While multiple studies have demonstrated how landscape-scale strategies can minimise the trade-off between agricultural production and biodiversity conservation, little is known about which land-use strategies maximise the landscape-level supply of multiple ecosystem services (landscape multifunctionality), a common goal of stakeholder communities.We combine comprehensive data collected from 150 German grassland sites with a simulation approach to identify landscape compositions, with differing proportions of low-, medium-, and high-intensity grasslands, that minimise trade-offs between the six main grassland ecosystem services prioritised by local stakeholders: biodiversity conservation, aesthetic value, productivity, carbon storage, foraging, and regional identity. Results are made accessible through an online tool that provides information on which compositions best meet any combination of user-defined priorities (https://neyret.shinyapps.io/landscape_composition_for_multifunctionality/).Results show that an optimal landscape composition can be identified for any pattern of ecosystem service priorities. However, multifunctionality was similar and low for all landscape compositions in cases where there are strong trade-offs between services (e.g. aesthetic value and fodder production), where many services were prioritised, and where drivers other than land use played an important role. We also found that if moderate service levels are deemed acceptable, then strategies in which both high and low intensity grasslands are present can deliver landscape multifunctionality. The tool presented can aid informed decision-making by predicting the impact of future changes in landscape composition, and by allowing for the relative roles of stakeholder priorities and biophysical trade-offs to be understood by scientists and practitioners alike.HighlightsAn online tool identifies optimal landscape compositions for desired ecosystem servicesWhen the desired services are synergic, the optimum is their common best landscape compositionWhen the desired services trade-off, a mix of grassland intensity is most multifunctionalSuch tools could support decision-making processes and aid conflict resolutionGraphical abstract
Comparative genomics analyses of lifestyle transitions at the origin of an invasive fungal pathogen in the genusCryphonectria
Authors: Stauber Lea , Prospero Simone , Croll Daniel 
Published: July 2020

AbstractEmerging fungal pathogens are a threat to forest and agroecosystems, as well as animal and human health. How pathogens evolve from non-pathogenic ancestors is still poorly understood making the prediction of future outbreaks challenging. Most pathogens have evolved lifestyle adaptations, which were enabled by specific changes in the gene content of the species. Hence, understanding transitions in the functions encoded by genomes gives valuable insight into the evolution of pathogenicity. Here, we studied lifestyle evolution in the genusCryphonectria, including the prominent invasive pathogenC. parasitica, the causal agent of chestnut blight onCastaneaspecies. We assembled and compared the genomes of pathogenic and putatively non-pathogenicCryphonectriaspecies, as well as sister group pathogens in the family Cryphonectriaceae (Diaporthales, Ascomycetes) to investigate the evolution of genome size and gene content. We found a striking loss of genes associated with carbohydrate metabolism (CAZymes) inC. parasiticacompared to other Cryphonectriaceae. Despite substantial CAZyme gene loss, experimental data suggests thatC. parasiticahas retained wood colonization abilities shared with otherCryphonectriaspecies. Putative effectors substantially varied in number, cysteine content and protein length among species. In contrast, secondary metabolite gene clusters show a high degree of conservation within the genus. Overall, our results underpin the recent lifestyle transition ofC. parasiticatowards a more pathogenic lifestyle. Our findings suggest that a CAZyme loss may have promoted pathogenicity ofC. parasiticaon chestnuts. Analyzing gene complements underlying key nutrition modes can facilitate the detection of species with the potential to emerge as pathogens.
Structural basis for the inhibition of the papain-like protease of SARS-CoV-2 by small molecules
Authors: Fu Ziyang , Huang Bin , Tang Jinle , Liu Shuyan , Liu Ming , Ye Yuxin , Liu Zhihong , Xiong Yuxian , Cao Dan , Li Jihui , Niu Xiaogang , Zhou Huan , Zhao Yong Juan , Zhang Guoliang , Huang Hao 
Published: July 2020

ABSTRACTSARS-CoV-2 is the pathogen responsible for the COVID-19 pandemic. The SARS-CoV-2 papain-like cysteine protease has been implicated in virus maturation, dysregulation of host inflammation and antiviral immune responses. We showed that PLpro preferably cleaves the K48-ubiquitin linkage while also being capable of cleaving ISG15 modification. The multiple functions of PLpro render it a promising drug target. Therefore, we screened an FDA-approved drug library and also examined available inhibitors against PLpro. Inhibitor GRL0617 showed a promising IC50of 2.1 μM. The co-crystal structure of SARS-CoV-2 PLpro-C111S in complex with GRL0617 suggests that GRL0617 is a non-covalent inhibitor. NMR data indicate that GRL0617 blocks the binding of ISG15 to PLpro. The antiviral activity of GRL0617 reveal that PLpro is a promising drug target for therapeutically treating COVID-19.One Sentence SummaryCo-crystal structure of PLpro in complex with GRL0617 reveals the druggability of PLpro for SARS-CoV-2 treatment.
SARS-CoV-2 Spike protein co-opts VEGF-A/Neuropilin-1 receptor signaling to induce analgesia
Authors: Moutal Aubin , Martin Laurent F. , Boinon Lisa , Gomez Kimberly , Ran Dongzhi , Zhou Yuan , Stratton Harrison J. , Cai Song , Luo Shizhen , Gonzalez Kerry Beth , Perez-Miller Samantha , Patwardhan Amol , Ibrahim Mohab M. , Khanna Rajesh 
Published: July 2020

AbstractGlobal spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues unabated. Binding of SARS-CoV-2’s Spike protein to host angiotensin converting enzyme 2 triggers viral entry, but other proteins may participate, including neuropilin-1 receptor (NRP-1). As both Spike protein and vascular endothelial growth factor-A (VEGF-A) – a pro-nociceptive and angiogenic factor, bind NRP-1, we tested if Spike could block VEGF-A/NRP-1 signaling. VEGF-A–triggered sensory neuronal firing was blocked by Spike protein and NRP-1 inhibitor EG00229. Pro-nociceptive behaviors of VEGF-A were similarly blocked via suppression of spontaneous spinal synaptic activity and reduction of electrogenic currents in sensory neurons. Remarkably, preventing VEGF-A/NRP-1 signaling was antiallodynic in a neuropathic pain model. A ‘silencing’ of pain via subversion of VEGF-A/NRP-1 signaling may underlie increased disease transmission in asymptomatic individuals.
Interplay of Monocytes and T Lymphocytes in COVID-19 Severity
Authors: Padgett Lindsey E. , Dinh Huy Q. , Chee Serena J. , Olingy Claire E. , Wu Runpei , Araujo Daniel J. , Vijayanand Pandurangan , Ottensmeier Christian H. , Hedrick Catherine C. 
Published: July 2020

ABSTRACTThe COVID-19 pandemic represents an ongoing global crisis that has already impacted over 13 million people. The responses of specific immune cell populations to the disease remain poorly defined, which hinders improvements in treatment and care management. Here, we utilized mass cytometry (CyTOF) to thoroughly phenotype peripheral myeloid cells and T lymphocytes from 30 convalescent patients with mild, moderate, and severe cases of COVID-19. We identified 10 clusters of monocytes and dendritic cells and 17 clusters of T cells. Examination of these clusters revealed that both CD14+CD16+intermediate and CD14dimCD16+nonclassical monocytes, as well as CD4+stem cell memory T (TSCM) cells, correlated with COVID-19 severity, coagulation factor levels, and/or inflammatory indicators. We also identified two nonclassical monocyte subsets distinguished by expression of the sugar residue 6-Sulfo LacNac (Slan). One of these subsets (Slanlo, nMo1) was depleted in moderately and severely ill patients, while the other (Slanhi, nMo2) increased with disease severity and was linked to CD4+T effector memory (TEM) cell frequencies, coagulation factors, and inflammatory indicators. Intermediate monocytes tightly correlated with loss of naive T cells as well as an increased abundance of effector memory T cells expressing the exhaustion marker PD-1. Our data suggest that both intermediate and non-classical monocyte subsets shape the adaptive immune response to SARS-CoV-2. In summary, our study provides both broad and in-depth characterization of immune cell phenotypes in response to COVID-19 and suggests functional interactions between distinct cell types during the disease.One Sentence SummaryUse of mass cytometry on peripheral blood mononuclear cells from convalescent COVID-19 patients allows correlation of distinct monocyte and T lymphocyte subsets with clinical factors.