bluuebunny/crossref_metadata_2025_split huggingface dataset:
CD16ahigh NK cell infiltration and spatial relationships with T cells and macrophages can predict improved progression-free survival in high grade ovarian cancer
Authors: Nersesian Sarah , Lee Stacey N. , Grantham Stephanie , Meunier Liliane , Communal Laudine , Arnason Thomas , Arnold Dirk , Nelson Brad H. , Mes-Messon Anne-Marie , Boudreau Jeanette E. 
Published: June 2021

ABSTRACTBackgroundHigh grade serous cancer (HGSC) remains a highly fatal malignancy with less than 50% of patients surviving 5 years after diagnosis. Despite its high mutational burden, HGSC is relatively refractory to checkpoint immunotherapy, suggesting that additional features of the cancer and its interactions with the immune system remain to be understood. Natural killer (NK) cells may contribute to HGSC control, but the role(s) of this population or its subsets in this disease are poorly understood.MethodsWe used a TMA containing duplicate treatment-naïve tumors from 1145 patients with HGSC and a custom staining panel to simultaneously measure macrophages, T cells and NK cells, separating NK cells based on CD16a expression. Using pathologist-validated digital pathology, machine learning, computational analysis and Pearson’s correlations, we quantitated infiltrating immune cell density, co-infiltration and co-localization with spatial resolution to tumor region. We compared the prognostic value of innate, general, and adaptive immune cell “neighborhoods” to define characteristics of HGSC tumors predictive for progression-free survival and used flow cytometry to define additional features of the CD16adim NK cell subset.ResultsNK cells were observed in >95% of tumor cores. Intrastromal localization of CD16alow and CD16ahigh NK cells was associated with shorter and longer progression-free survival, respectively. CD16ahigh NK cells most frequently co-localized with T cells and macrophages; their proximity was termed an “adaptive” neighborhood. We find that tumors with more area represented by adaptive immune cell neighborhoods corresponded to superior progression free survival. In contrast, CD16alow NK cells did not co-infiltrate with other immune cell types, and expressed the ectonucleotidases, CD39 and CD73, which have been previously associated with poor prognosis in patients with HGSC.ConclusionsProgression-free survival for patients with HGSC may be predicted by the subset of NK cells within the tumor infiltrate (i.e. CD16ahigh vs. CD16alow). NK cell subtypes were associated predictable co-infiltrating and co-localizing leukocyte subsets, suggesting that their presence and activity may influence, or be influenced by the tumor microenvironment. Our data suggest that immunotherapeutic strategies for HGSC should consider the constitution of NK cell subsets and may benefit from mobilizing and activating CD16high NK cells.
Topological data analysis identifies emerging adaptive mutations in SARS-CoV-2
Authors: Bleher Michael , Hahn Lukas , Neumann Maximilian , Patiño-Galindo Juan Ángel , Carrière Mathieu , Bauer Ulrich , Rabadán Raúl , Ott Andreas 
Published: June 2021

AbstractThe COVID-19 pandemic has initiated an unprecedented worldwide effort to characterize its evolution through the mapping of mutations of the coronavirus SARS-CoV-2. The early identification of mutations that could confer adaptive advantages to the virus, such as higher infectivity or immune evasion, is of paramount importance. However, the large number of currently available genomes precludes the efficient use of phylogeny-based methods. Here we present CoVtRec, a fast and scalable Topological Data Analysis approach for the surveillance of emerging adaptive mutations in large genomic datasets. Our method overcomes limitations of state-of-the-art phylogeny-based approaches by quantifying the potential adaptiveness of mutations merely by their topological footprint in the genome alignment, without resorting to the reconstruction of a single optimal phylogenetic tree. Analyzing millions of SARS-CoV-2 genomes from GISAID, we find a correlation between topological signals and adaptation to the human host. By leveraging the stratification by time in sequence data, our method enables the high-resolution longitudinal analysis of topological signals of adaptation. We characterize the convergent evolution of the coronavirus throughout the whole pandemic to date, report on emerging potentially adaptive mutations, and pinpoint mutations in Variants of Concern that are likely associated with positive selection. Our approach can improve the surveillance of mutations of concern and guide experimental studies.
Cross-neutralizing activity against SARS-CoV-2 variants in COVID-19 patients: Comparison of four waves of the pandemic in Japan
Authors: Furukawa Koichi , Tjan Lidya Handayani , Sutandhio Silvia , Kurahashi Yukiya , Iwata Sachiyo , Tohma Yoshiki , Sano Shigeru , Nakamura Sachiko , Nishimura Mitsuhiro , Arii Jun , Kiriu Tatsunori , Yamamoto Masatsugu , Nagano Tatsuya , Nishimura Yoshihiro , Mori Yasuko 
Published: June 2021

ABSTRACTIn March 2021, Japan is facing a 4th wave of SARS-CoV-2 infection. To prevent further spread of infection, sera cross-neutralizing activity of patients previously infected with conventional SARS-CoV-2 against novel variants is important but is not firmly established. We investigated the neutralizing potency of 81 COVID-19 patients’ sera from 4 waves of pandemic against SARS-CoV-2 variants using their authentic viruses. Most sera had neutralizing activity against all variants, showing similar activity against B.1.1.7 and D614G, but lower activity especially against B.1.351. In the 4th wave, sera-neutralizing activity against B.1.1.7 was significantly higher than that against any other variants, including D614G. The cross-neutralizing activity of convalescent sera was effective against all variants but was potentially weaker for B.1.351.
Early Prediction of In-Hospital Death of COVID-19 Patients: A Machine-Learning Model Based on Age, Blood Analyses, and Chest X-Ray Score
Authors: Garrafa E. , Vezzoli M. , Ravanelli M. , Farina D. , Borghesi A. , Calza S. , Maroldi R. 
Published: June 2021

AbstractBackgroundTo develop and validate an early-warning model to predict in-hospital mortality on admission of COVID-19 patients at an emergency department (ED).MethodsIn total, 2782 patients were enrolled between March 2020 and December 2020, including 2106 patients (first wave) and 676 patients (second wave) in the COVID-19 outbreak in Italy. The first-wave patients were divided into two groups with 1474 patients used to train the model, and 632 to validate it. The 676 patients in the second wave were used to test the model. Age, 17 blood analytes and Brescia chest X-ray score were the variables processed using a Random Forests classification algorithm to build and validate the model. ROC analysis was used to assess the model performances. A web-based death-risk calculator was implemented and integrated within the Laboratory Information System of the hospital.ResultsThe final score was constructed by age (the most powerful predictor), blood analytes (the strongest predictors were lactate dehydrogenase, D-dimer, Neutrophil/Lymphocyte ratio, C-reactive protein, Lymphocyte %, Ferritin std and Monocyte %), and Brescia chest X-ray score. The areas under the receiver operating characteristic curve obtained for the three groups (training, validating and testing) were 0.98, 0.83 and 0.78, respectively.ConclusionsThe model predicts in-hospital mortality on the basis of data that can be obtained in a short time, directly at the ED on admission. It functions as a web-based calculator, providing a risk score which is easy to interpret. It can be used in the triage process to support the decision on patient allocation.
Encapsulated allografts preclude host sensitization and promote ovarian endocrine function in ovariectomized young rhesus monkeys and sensitized mice
Authors: Day James R. , Flanagan Colleen L. , David Anu , Hartigan-O’Connor Dennis J. , Mattos Barbosa Mayara Garcia de , Martinez Michele L. , Lee Charles , Barnes Jenna , Farkash Evan , Zelinski Mary , Tarantal Alice , Cascalho Marilia , Shikanov Ariella 
Published: June 2021

AbstractTransplantation of allogeneic donor ovarian tissue holds great potential for female cancer survivors who often experience premature ovarian insufficiency. To avoid complications associated with immune suppression and to protect transplanted ovarian allografts from immune-mediated injury, we have developed an immuno-isolating hydrogel-based capsule that supports the function of ovarian allografts without triggering an immune response. Encapsulated ovarian allografts implanted in naïve ovariectomized BALB/c mice responded to the circulating gonadotropins without direct revascularization and maintained function for 4 months, as evident by regular estrous cycles and presence of antral follicles in the retrieved grafts. Repeated implantations of encapsulated mouse ovarian allografts did not sensitize naïve BALB/c mice in contrast to non-encapsulated controls, which was confirmed with undetectable levels of allo-antibody. Further, encapsulated allografts implanted in hosts previously sensitized by implantation of non-encapsulated allografts restored estrous cycles similarly to our results in naïve recipients. Next, we tested the translational potential and efficiency of the immune-isolating capsule in a rhesus monkey model by implanting encapsulated ovarian auto- and allografts in young ovariectomized animals. The encapsulated ovarian grafts survived and restored basal levels of urinary estrone conjugate and pregnanediol 3-glucuronide during the approximate 4-5 month observation period. We demonstrate, for the first time, that encapsulation of ovarian allografts prevents sensitization and protects the allograft from rejection in young rhesus monkeys and in sensitized mice.
Supervised learning with word embeddings derived from PubMed captures latent knowledge about protein kinases and cancer
Authors: Ravanmehr Vida , Blau Hannah , Cappelletti Luca , Fontana Tommaso , Carmody Leigh , Coleman Ben , George Joshy , Reese Justin , Joachimiak Marcin , Bocci Giovanni , Bult Carol , Rueter Jens , Casiraghi Elena , Valentini Giorgio , Mungall Christopher , Oprea Tudor , Robinson Peter N. 
Published: June 2021

ABSTRACTInhibiting protein kinases (PKs) that cause cancers has been an important topic in cancer therapy for years. So far, almost 8% of more than 530 PKs have been targeted by FDA-approved medications and around 150 protein kinase inhibitors (PKIs) have been tested in clinical trials. We present an approach based on natural language processing and machine learning to the relations between PKs and cancers, predicting PKs whose inhibition would be efficacious to treat a certain cancer. Our approach represents PKs and cancers as semantically meaningful 100-dimensional vectors based on co-occurrence patterns in PubMed abstracts. We use information about phase I-IV trials inClinicalTrials.govto construct a training set for random forest classification. In historical data, associations between PKs and specific cancers could be predicted years in advance with good accuracy. Our model may be a tool to predict the relevance of inhibiting PKs with specific cancers.
Tools, strains, and strategies to effectively conduct anaerobic and aerobic transcriptional reporter screens and assays in Staphylococcus aureus
Authors: Price Erin E. , Rudra Paulami , Norambuena Javiera , Román-Rodríguez Franklin , Boyd Jeffrey M. 
Published: June 2021

AbstractTranscriptional reporters are reliable and time-tested tools to study gene regulation. In Staphylococcus aureus, β-galactosidase (lacZ)-based genetic screens are not widely used because of the necessity of selectable markers for strain construction and the production of staphyloxanthin pigment which obfuscates results. We describe a series of vectors that allow for markerless insertion of codon-optimized lacZ-based transcriptional reporters. The vectors encode for different ribosomal binding sites allowing for tailored lacZ expression. A ΔcrtM::kanR deletion insertion mutant was constructed that prevents the synthesis of staphyloxanthin, thereby permitting blue-white screening without the interference of carotenoid production. We demonstrate the utility of these vectors to monitor aerobic and anaerobic transcriptional activity. For the latter, we describe the use of a ferrocyanide-ferricyanide redox system (Fe(CN)63–/4–) permitting blue-white screening in the absence of oxygen. We also describe additional reporter systems and methods for monitoring transcriptional activity during anaerobic culture including a FAD-binding fluorescent protein (EcFbFP), alpha-hemolysin (hla), or lipase (geh). The systems and methods described are compatible with vectors utilized to create and screen high-density transposon mutant libraries.ImportanceStaphylococcus aureus is a human pathogen and a leading cause of infectious disease-related illness and death worldwide. For S. aureus to successfully colonize and invade host tissues, it must tightly control the expression of genes encoding for virulence factors. Oxygen tension varies greatly at infection sites and many abscesses are devoid of oxygen. In this study, we have developed novel tools and methods to study how and when S. aureus alters transcription of genes. A key advantage to these methods and tools is that they can be utilized in the presence and absence of oxygen. A better understanding of anaerobic gene expression in S. aureus will provide important insight into the regulation of genes in low oxygen environments.
Metabolomic analysis of diverse mice reveals hepatic arginase-1 as source of plasma arginase in Plasmodium chabaudi infection
Authors: Davis Nicole M. , Lissner Michelle M. , Massis Liliana M. , Richards Crystal L. , Chevée Victoria , Gupta Avni S. , Gherardini Frank C. , Monack Denise M. , Schneider David S. 
Published: June 2021

AbstractInfections disrupt host metabolism, but the factors that dictate the nature and magnitude of metabolic change are incompletely characterized. To determine how host metabolism changes in relation to disease severity in murine malaria, we performed plasma metabolomics on eight Plasmodium chabaudi-infected mouse strains with diverse disease phenotypes. We identified plasma metabolic biomarkers for both the nature and severity of different malarial pathologies. A subset of metabolic changes, including plasma arginine depletion, match the plasma metabolomes of human malaria patients, suggesting new connections between pathology and metabolism in human malaria. In our malarial mice, liver damage, which releases hepatic arginase-1 (Arg1) into circulation, correlated with plasma arginine depletion. We confirmed that hepatic Arg1 was the primary source of increased plasma arginase activity in our model, which motivates further investigation of liver damage in human malaria patients. More broadly, our approach shows how leveraging phenotypic diversity can identify and validate relationships between metabolism and the pathophysiology of infectious disease.ImportanceMalaria is a severe and sometimes fatal infectious disease endemic to tropical and subtropical regions. Effective vaccines against malaria-causing Plasmodium parasites remain elusive, and malaria treatments often fail to prevent severe disease. Small molecules that target host metabolism have recently emerged as candidates for therapeutics in malaria and other diseases. However, our limited understanding of how metabolites affect pathophysiology limits our ability to develop new metabolite therapies. By providing a rich dataset of metabolite-pathology correlations, and by validating one of those correlations, our work is an important step toward harnessing metabolism to mitigate disease. Specifically, we showed that liver damage in P. chabaudi-infected mice releases hepatic arginase-1 into circulation, where it may deplete plasma arginine, a candidate malaria therapeutic that mitigates vascular stress. Our data suggest that liver damage may confound efforts to increase levels of arginine in human malaria patients.
Radiosynthesis and preclinical evaluation of a carbon-11 labeled PDE7 inhibitor for PET neuroimaging
Authors: Xiao Zhiwei , Sun Jiyun , Fujinaga Masayuki , Wei Huiyi , Zhao Chunyu , Haider Ahmed , Van Richard , Yamasaki Tomoteru , Zhang Yiding , Rong Jian , Hu Kuan , Chen Jiahui , Leon Erick Calderon , Hiraishi Atsuto , Wei Junjie , Xu Yi , Shao Yihan , Zhang Han-Ting , Xu Ying , Lloyd KC Kent , Wang Lu , Zhang Ming-Rong , Liang Steven 
Published: June 2021

AbstractBackgroundDysfunction of cyclic nucleotide phosphodiesterase 7 (PDE7) has been associated with excess intracellular cAMP concentrations, fueling pathogenic processes that are implicated in neurodegenerative disorders. The aim of this study was to develop a suitable PDE7-targeted positron emission tomography (PET) probe that allows non-invasive mapping of PDE7 in the mammalian brain.MethodsBased on a spiro cyclohexane-1,4’-quinazolinone scaffold with known inhibitory properties towards PDE7, we designed and synthesized a methoxy analog that was suitable for carbon-11 labeling. Radiosynthesis was conducted with the respective desmethyl precursor using [11C]MeI. The resulting PET probe, codenamed [11C]26, was evaluated by cell uptake studies, ex vivo biodistribution and radiometabolite studies, as well as in vivo PET experiments in rodents and nonhuman primates (NHP).ResultsTarget compound 26 and the corresponding phenolic precursor were synthesized in 2-3 steps with overall yields of 49.5% and 12.4%, respectively. An inhibitory constant (IC50) of 31 nM towards PDE7 was obtained and no significant interaction with other PDE isoforms were observed. [11C]26 was synthesized in high molar activities (170 - 220 GBq/µmol) with radiochemical yields of 34±7%. In vitro cell uptake of [11C]26 was 6-7 folds higher in PDE7 overexpressing cells, as compared to the controls, whereas an in vitro specificity of up to 90% was measured. Ex vivo metabolite studies revealed a high fraction of intact parent in the rat brain (98% at 5 min and 75% at 30 min post injection). Considerable brain penetration was further corroborated by ex vivo biodistribution and PET imaging studies – the latter showing heterogenic brain uptake. While marginal specific binding was observed by PET studies in rodents, a moderate, but dose-dependent, blockade was observed in the NHP brain following pretreatment with non-radioactive 26.ConclusionIn this work, we report on the preclinical evaluation of [11C]26 (codename [11C]P7-2104), a PDE7-targeted PET ligand that is based on a spiroquinazolinone scaffold. [11C]26 displayed promising in vitro performance characteristics, a moderate degree of specific binding in PET studies with NHP. Accordingly, [11C]26 will serve as a valuable lead compound for the development of a new arsenal of PDE7-targeted probes with potentially improved in vivo specificity.
An automated method for precise axon reconstruction from recordings of high-density micro-electrode arrays
Authors: Buccino Alessio Paolo , Yuan Xinyue , Emmenegger Vishalini , Xue Xiaohan , Gänswein Tobias , Hierlemann Andreas 
Published: June 2021

AbstractNeurons communicate with each other by sending action potentials through their axons. The velocity of axonal signal propagation describes how fast electrical action potentials can travel, and can be affected in a human brain by several pathologies, including multiple sclerosis, traumatic brain injury and channelopathies. High-density microelectrode arrays (HD-MEAs) provide unprecedented spatio-temporal resolution to extracellularly record neural electrical activity. The high density of the recording electrodes enables to image the activity of individual neurons down to subcellular resolution, which includes the propagation of axonal signals. However, axon recon-struction, to date, mainly relies on a manual approach to select the electrodes and channels that seemingly record the signals along a specific axon, while an automated approach to track multiple axonal branches in extracellular action-potential recordings is still missing.In this article, we propose a fully automated approach to reconstruct axons from extracellular electrical-potential landscapes, so-called “electrical footprints” of neurons. After an initial electrode and channel selection, the proposed method first constructs a graph, based on the voltage signal amplitudes and latencies. Then, the graph is interrogated to extract possible axonal branches. Finally, the axonal branches are pruned and axonal action-potential propagation velocities are computed.We first validate our method using simulated data from detailed reconstructions of neurons, showing that our approach is capable of accurately reconstructing axonal branches. We then apply the reconstruction algorithm to experimental recordings of HD-MEAs and show that it can be used to determine axonal morphologies and signal-propagation velocities at high throughput.We introduce a fully automated method to reconstruct axonal branches and estimate axonal action-potential propagation velocities using HD-MEA recordings. Our method yields highly reliable and reproducible velocity estimations, which constitute an important electrophysiological feature of neuronal preparations.
Scalability of large neural network simulations via activity tracking with time asynchrony and procedural connectivity
Authors: Mascart Cyrille , Scarella Gilles , Reynaud-Bouret Patricia , Muzy Alexandre 
Published: June 2021

AbstractWe present a new algorithm to efficiently simulate random models of large neural networks satisfying the property of time asynchrony. The model parameters (average firing rate, number of neurons, synaptic connection probability, and postsynaptic duration) are of the order of magnitude of a small mammalian brain, or of human brain areas. Through the use of activity tracking and procedural connectivity (dynamical regeneration of synapses), both computational and memory complexities of this algorithm are proved to be theoretically linear with the number of neurons. These results are experimentally validated by sequential simulations of millions of neurons and billions of synapses running in few minutes using a single thread of an equivalent desktop computer.
Age-related increases in reaction time result from slower preparation, not delayed initiation
Authors: Hardwick Robert M , Forrence Alexander D. , Costello Maria Gabriela , Zackowski Kathy , Haith Adrian M 
Published: June 2021

AbstractRecent work indicates that healthy younger adults can prepare accurate responses faster than their voluntary reaction times indicate, leaving a seemingly unnecessary delay of 80-100ms before responding. Here we examined how the preparation of movements, initiation of movements, and the delay between them are affected by ageing. Participants made planar reaching movements in two conditions. The ‘Free Reaction Time’ condition assessed the voluntary reaction times with which participants responded to the appearance of a stimulus. The ‘Forced Reaction Time’ condition assessed the minimum time actually needed to prepare accurate movements by controlling the time allowed for movement preparation. The time taken to both initiate movements in the Free Reaction Time and to prepare movements in the Forced Response condition increased with age. Notably, the time required to prepare accurate movements was significantly shorter than participants’ self-selected initiation times; however, the delay between movement preparation and initiation remained consistent across the lifespan (~90ms). These results indicate that the slower reaction times of healthy older adults are not due to an increased hesitancy to respond, but can instead be attributed to changes in their ability to process stimuli and prepare movements accordingly, consistent with age-related changes in brain structure and function.