bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dynamic methods for ongoing assessment of site-level risk in risk-based monitoring of clinical trials: a scoping review
Authors: Cragg William J , Hurley Caroline , Yorke-Edwards Victoria , Stenning Sally P 
Published: April 2020

AbstractBackground/AimsIt is increasingly recognised that reliance on frequent site visits for monitoring clinical trials is inefficient. Regulators and trialists have in recent years encouraged more risk-based monitoring. Risk assessment should take place before a trial begins in order to define the overarching monitoring strategy. It can also be done on an ongoing basis, in order to target sites for monitoring activity. Various methods have been proposed for such prioritisation, often using terms like ‘central statistical monitoring’, ‘triggered monitoring’ or, as in ICH Good Clinical Practice guidance, ‘targeted on-site monitoring’. We conducted a scoping review to identify such methods, to establish if any published methods were supported by adequate evidence to allow wider implementation, and to point the way to future developments in this field of research.MethodsWe used 7 publication databases, 2 sets of methodological conference abstracts and an internet search engine to look for methods for using centrally held trial data to assess site conduct during a trial. We included only reports in English, and excluded reports published before 1996 and reports not directly relevant to our research question. We used reference and citation searches to find additional relevant reports. We extracted data using a pre- defined template. We contacted authors to request additional information about included reports and to check whether reports might be eligible.ResultsWe included 30 reports in our final dataset, of which 21 were peer-reviewed publications. 20 reports described central statistical monitoring methods (of which 7 focussed on detection of fraud or misconduct) and 9 described triggered monitoring methods. 21 reports included some assessment of their methods’ effectiveness. Most commonly this involved exploring the methods’ characteristics using real trial data with no known integrity issues. Of the 21 with some effectiveness assessment, most presented limited or no information about whether or not concerns identified through central monitoring constituted meaningful problems. Some reports commented on cost savings from reduced on-site monitoring, but none gave detailed costings for the development and maintenance of central monitoring methods themselves.ConclusionsOur review identified various proposed methods, some of which could be combined within the same trial. The apparent emphasis on fraud detection may not be proportionate in all trial settings. Although some methods have self-justifying benefits for data cleaning activity, many have limitations that may currently prevent their routine use for targeting trial monitoring activity. The implementation costs, or uncertainty about these, may also be a barrier. We make recommendations for how the evidence-base supporting these methods could be improved.
Pre-outbreak determinants of perceived risks of corona infection and preventive measures taken. A prospective population-based study
Authors: van der Velden Peter G. , Marchand Miquelle , Cuelenaere Boukje , Das Marcel 
Published: April 2020

ABSTRACTObjectivesAssess how people perceive the risks of coronavirus infection, whether people take preventive measures, and which (pre-outbreak) factors contribute to the perceived risks and measures taken, such as (pre-outbreak) respiratory problems, heart problems, diabetes, anxiety and depression symptoms, loneliness, age, gender, marital status and education level.MethodsData were collected in the longitudinal LISS panel, based on a random sample of the Dutch population. The coronavirus survey started on March 2, and the data collection ended on March 17 2020. Data were linked with surveys on health and social integration conducted at the end of 2019 (Nstudy sample=3,540).ResultsAbout 15% perceived the risk of infection as high, and 11% the risk becoming ill when infected. Multivariate logistic regression analyses showed the following. Older age-groups perceived the risk for coronavirus infection as lower (all adjusted Odd Ratio’s [aOR] ≤ .058). In total, 43.8% had taken preventive measures, especially females (aOR=1.47, 95% CI=1.27-1.69). Those with lower education levels less often used preventive measures (aOR=0.56, 95% CI=0.46-0.69). Those with pre-outbreak respiratory problems (aOR=2.89, 95% CI=2.24-3.73), heart problems (aOR=2.17, 95% CI=1.49-3.16) and diabetes (aOR=3.10, 95% CI=2.02-4.74) perceived the risk becoming ill when infected as higher than others. However, respondents with pre-outbreak respiratory problems and diabetes did not more often take preventive measures.ConclusionsVulnerable patients more often recognize that they are at risk becoming ill when infected by the coronavirus, but many do not take preventive measures. Interventions to stimulate the use of preventive measures should pay additional attention to physically vulnerable patients, men and those with lower education levels.
Structural basis of RNA recognition by the SARS-CoV-2 nucleocapsid phosphoprotein
Authors: Dinesh Dhurvas Chandrasekaran , Chalupska Dominika , Silhan Jan , Veverka Vaclav , Boura Evzen 
Published: April 2020

AbstractSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the Coronavirus disease 2019 (COVID-19) which is currently negatively affecting the population and disrupting the global economy. SARS-CoV-2 belongs to the +RNA virus family that utilize single-stranded positive-sense RNA molecules as genomes. SARS-CoV-2, like other coronaviruses, has an unusually large genome for a +RNA virus that encodes four structural proteins – the matrix (M), small envelope (E), spike (S) and nucleocapsid phosphoprotein (N) - and sixteen nonstructural proteins (nsp1-16) that together ensure replication of the virus in the host cell. The nucleocapsid phosphoprotein N is essential for linking the viral genome to the viral membrane. Its N-terminal RNA binding domain (N-NTD) captures the RNA genome while the C-terminal domain anchors the ribonucleoprotein complex to the viral membrane via its interaction with the M protein. Here, we characterized the structure of the N-NTD and its interaction with RNA using NMR spectroscopy. We observed a positively charged canyon on the surface of the N-NTD lined with arginine residues suggesting a putative RNA binding site. Next, we performed an NMR titration experiment using an RNA duplex. The observed changes in positions of signals in the N-NTD NMR spectra allowed us to construct a model of the N-NTD in complex with RNA.
Optimal COVID-19 epidemic control until vaccine deployment
Authors: Djidjou-Demasse R. , Michalakis Y. , Choisy M. , Sofonea M. T. , Alizon S. 
Published: April 2020

AbstractSince Dec 2019, the COVID-19 epidemic has spread over the globe creating one of the greatest pandemics ever witnessed. This epidemic wave will only begin to roll back once a critical proportion of the population is immunised, either by mounting natural immunity following infection, or by vaccination. The latter option can minimise the cost in terms of human lives but it requires to wait until a safe and efficient vaccine is developed, a period estimated to last at least 18 months. In this work, we use optimal control theory to explore the best strategy to implement while waiting for the vaccine. We seek a solution minimizing deaths and costs due to the implementation of the control strategy itself. We find that such a solution leads to an increasing level of control with a maximum reached near the 16th month of the epidemics and a steady decrease until vaccine deployment. The average containment level is approximately 50% during the 25-months period for vaccine deployment. This strategy strongly out-performs others with constant or cycling allocations of the same amount of resources to control the outbreak. This work opens new perspectives to mitigate the effects of the ongoing COVID-19 pandemics, and be used as a proof-of-concept in using mathematical modelling techniques to enlighten decision making and public health management in the early times of an outbreak.
Quantifying the demographic vulnerabilities of dry woodlands to climate and competition using range-wide monitoring data
Authors: Shriver Robert K. , Yackulic Charles B. , Bell David M. , Bradford John B. 
Published: April 2020

AbstractClimate change is expected to alter the distribution and abundance of tree species, impacting ecosystem structure and function. Yet, anticipating where this will occur is often hampered by a lack of understanding of how demographic rates, most notably recruitment, vary in response to climate and competition across a species range. Using large-scale monitoring data on two dry woodland tree species (Pinus edulisandJuniperus osteosperma), we develop an approach to infer recruitment, survival, and growth of both species across their range. In doing so, we account for ecological and statistical dependencies inherent in large-scale monitoring data. We find that warming and drying conditions generally lead to declines in recruitment and survival, but there were some idiosyncrasy in the strength of responses across species. Climate conditions lead to vulnerable regions, such asPinus edulisin N. Arizona, where both survival and recruitment are low. Our approach provides a path forward for leveraging emerging large-scale monitoring and remotely sensed data to anticipate the impacts of global change on species distributions.
Stability and individual variability of social attachment in imprinting
Authors: Lemaire Bastien S. , Rucco Daniele , Josserand Mathilde , Vallortigara Giorgio , Versace Elisabetta 
Published: April 2020

AbstractFilial imprinting has become a model for understanding memory, learning and social behaviour in neonate animals. This fast attachment mechanism allows the young of precocial bird species to learn the characteristics of conspicuous visual stimuli and display affiliative response to them. Although more prolonged exposure to an object produces a stronger preference for it afterwards, this relation is not linear. Chicks can even prefer to approach novel rather than familiar objects at some stages of imprinting. The time course and stability of imprinting has just started to be investigated. To date, little is known about how filial preferences develop across time, due to the challenges in assessing individual performance. This study aimed to investigate filial preferences for familiar and novel imprinting objects over time. We have used an automated setup to track the behaviour of chicks continuously for subsequent days. After hatching, chicks were individually placed in an arena where stimuli were displayed on two opposite screens. The duration of exposure and the type of stimuli were manipulated while the time spent at the imprinting stimulus was monitored across six days. We showed that prolonged exposure (3 days vs 1 day) to a stimulus produced robust filial imprinting preferences. Interestingly, with a shorter exposure (1 day), animals re-evaluated their filial preferences in functions of their innate preferences and past experiences. Our study suggests that predispositions influence learning when the imprinting memories are not fully consolidated, driving animal preferences toward more predisposed stimuli.
Can biomass distribution across trophic levels predict trophic cascades?
Authors: Galiana Núria , Arnoldi Jean-François , Barbier Matthieu , Acloque Amandine , de Mazancourt Claire , Loreau Michel 
Published: April 2020

AbstractThe biomass distribution across trophic levels (biomass pyramid), and cascading responses to perturbations (trophic cascades), are archetypal representatives of the interconnected set of static and dynamical properties of food chains. A vast literature has explored their respective ecological drivers, sometimes generating correlations between them. Here we instead reveal a fundamental connection: both pyramids and cascades reflect the dynamical sensitivity of the food chain to changes in species intrinsic rates. We deduce a direct relationship between cascades and pyramids, modulated by what we call trophic dissipation – a synthetic concept that encodes the contribution of top-down propagation of consumer losses in the biomass pyramid. Predictable across-ecosystem patterns emerge when systems are in similar regimes of trophic dissipation. Data from 31 aquatic mesocosm experiments demonstrate how our approach can reveal the causal mechanisms linking trophic cascades and biomass distributions, thus providing a road map to deduce reliable predictions from empirical patterns.
Zebrafish macrophage developmental arrest underlies depletion of microglia and reveals Csf1r-independent metaphocytes
Authors: Kuil Laura E. , Oosterhof Nynke , Ferrero Giuliano , Mikulášová Tereza , Hason Martina , Dekker Jordy , Rovira Mireia , van der Linde Herma C. , van Strien Paulina M.H. , de Pater Emma , Schaaf Gerben , Bindels Eric M.J. , Wittamer Valerie , van Ham Tjakko J. 
Published: April 2020

AbstractMacrophages derive from multiple sources of hematopoietic progenitors. Most macrophages require colony-stimulating factor 1 receptor (CSF1R), but some macrophages persist in the absence of CSF1R. Here, we analyzedmpeg1:GFP–expressing macrophages incsf1r-deficient zebrafish and report that embryonic macrophages emerge followed by their developmental arrest. In larvae,mpeg1+ cell numbers then increased showing two distinct types in the skin: branched, putative Langerhans cells, and amoeboid cells. In contrast, although numbers also increased incsf1r-mutants, exclusively amoeboidmpeg1+cells were present, which we showed by genetic lineage tracing to have a non-hematopoietic origin. They expressed macrophage-associated genes, but also showed decreased phagocytic gene expression and increased epithelial-associated gene expression, characteristic of metaphocytes, recently discovered ectoderm-derived cells. We further demonstrated that juvenilecsf1r-deficient zebrafish exhibit systemic macrophage depletion. Thus, Csf1r deficiency disrupts embryonic to adult macrophage development. Csf1r-deficient zebrafish are viable and permit analyzing the consequences of macrophage loss throughout life.
Elucidation of the signatures of proteasome-catalysed peptide splicing
Authors: Paes Wayne , Leonov German , Partridge Thomas , Nicastri Annalisa , Ternette Nicola , Borrow Persephone 
Published: April 2020

AbstractProteasomes catalyse the degradation of endogenous proteins into oligopeptides, but can concurrently create spliced oligopeptides through ligation of previously non-contiguous peptide fragments. Recent studies have uncovered a formerly unappreciated role for proteasome-catalysed peptide splicing (PCPS) in the generation of non-genomically templated human leukocyte antigen class I (HLA-I)-boundcis-spliced peptides that can be targeted by CD8+T cells in cancer and infection. However, the mechanisms defining PCPS reactions are poorly understood. Here, we experimentally define the biochemical constraints of proteasome-catalysedcis-splicing reactions by examination ofin vitroproteasomal digests of a panel of viral- and self-derived polypeptide substrates using a tailored mass-spectrometry-basedde novosequencing workflow. We show that forward and reverse PCPS reactions display unique splicing signatures, defined by preferential fusion of distinct amino acid residues with stringent peptide length distributions, suggesting sequence- and size-dependent accessibility of splice reactants for proteasomal substrate binding pockets. Our data provide the basis for a more informed mechanistic understanding of PCPS that will facilitate future prediction of spliced peptides from protein sequences.
Abundantly expressed class of non-coding RNAs conserved through the multicellular evolution of dictyostelid social amoebae
Authors: Kjellin Jonas , Avesson Lotta , Reimegård Johan , Liao Zhen , Eichinger Ludwig , Noegel Angelika , Glöckner Gernot , Schaap Pauline , Söderbom Fredrik 
Published: April 2020

AbstractBackgroundAggregative multicellularity has evolved multiple times in diverse groups of eukaryotes. One of the most well-studied examples is the development of dictyostelid social amoebae, e.g.Dictyostelium discoideum. However, it is still poorly understood why multicellularity emerged in these amoebae while the great majority of other members of Amoebozoa are unicellular. Previously a novel type of non-coding RNA, Class I RNAs, was identified inD. discoideumand demonstrated to be important for normal multicellular development. In this study we investigated Class I RNA evolution and its connection to multicellular development.ResultsNew Class I RNA genes were identified by constructing a co-variance model combined with a scoring system based on conserved up-stream sequences. Multiple genes were predicted in representatives of each major group of Dictyostelia and expression analysis validated that our search approach can identify expressed Class I RNA genes with high accuracy and sensitivity. Further studies showed that Class I RNAs are ubiquitous in Dictyostelia and share several highly conserved structure and sequence motifs. Class I RNA genes appear to be unique to dictyostelid social amoebae since they could not be identified in searches in outgroup genomes, including the closest known relatives to Dictyostelia.ConclusionOur results show that Class I RNA is an ancient abundant class of ncRNAs, likely to have been present in the last common ancestor of Dictyostelia dating back at least 600 million years. Taken together, our current knowledge of Class I RNAs suggests that they may have been involved in evolution of multicellularity in Dictyostelia.
Distinct responses of oomycete plant parasites according to their lifestyle in a landscape-scale metabarcoding survey
Authors: Fiore-Donno Anna Maria , Bonkowski Michael 
Published: April 2020

AbstractOomycetes are an ubiquitous protistan lineage including devastating crop parasites. Although their ecology in agrosystems has been widely studied, little is known of their distribution in natural and semi-natural ecosystems. We provide here a baseline of the diversity and distribution of soil oomycetes, classified by lifestyles (biotrophy, hemibiotrophy and saprotrophy), at the landscape scale in temperate grassland and forest. From 600 soil samples, we obtained 1,148 Operational Taxonomy Units representing ∼20 million Illumina reads (region V4, 18S rRNA gene). We found a majority of hemibiotrophic plant pathogens, which are parasites spending part of their life cycle as saprotrophs after the death of the host. Overall both grassland and forest constitute an important reservoir of plant pathogens. In forests, relative abundances of obligate biotrophs and hemibiotrophs differed between regions and showed opposite responses to edaphic conditions and human-induced management intensification, suggesting different ecological requirements for these two functional guilds.
Synchronisation of yeast cell cycle through quorum sensing coupling
Authors: Perrino Giansimone , di Bernardo Diego 
Published: April 2020

AbstractThe cell cycle is present in all cells of all species and it is of fundamental importance in coordinating all the steps required for cell replication, including growth, DNA replication and cell division. Budding yeast is an unicellular organism characterised by a mother cell that buds to generate a daughter cell at each cell cycle. Each cell in a population buds at a different time. Despite its importance in biological applications, such as unravelling cell-cycle machinery mechanisms and production of valuable bioproducts, at present no yeast strain is capable of budding synchronously. To overcome this problem, we used control theory to propose a strategy to modify the yeast cell to endow it with the ability to synchronise its cell cycle across the population. Our strategy relies on a quorum sensing molecule diffusing freely in and out of the cell. The quorum sensing molecule is produced only during a specific phase of the cell cycle and couples the cell-cycle across the cell population. Here we model the proposed strategy with ordinary differential equations and numerically simulate it to demonstrate the feasibility of such an approach.
Molecularly Targeted Magnetic Resonance Imaging and Spectroscopy
Authors: Xin Jia-Xiang , Li Yi , Liu Hui-Xia , Li Jianqi , Yang Guang , Zhang Huojun , Wang Jiachen , Tong Rui , Wei Da-Xiu , Yao Ye-Feng 
Published: April 2020

ABSTRACTMagnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) have tremendous utility in many fields, such as clinical diagnosis, medical research and brain science. MRI provides high resolution anatomic images of tissues/organs, and MRS provides functional molecular information related to specific regions of tissues/organs. However, it is often difficult for conventional MRI/MRS to selectively image/probe a specific metabolite molecule other than water and fat. This greatly limits study of the molecular mechanisms underlying metabolism and disease. Herein, we report a novel method for obtaining an exact molecularly targeted MRI and MRS. This method uses the nuclear spin singlet state to select the signals from a specific molecule. Several endogenous molecules in living organism such as N-acetylaspartate and dopamine have been exemplarily imaged and probed as the targeted molecules in the MRI and MRS experiments, demonstrating the unique molecular selectivity of the developed method.Endogenous-molecule-targeted MRI and MRS can be achieved by using the new pulse sequences
A Lysate Proteome Engineering Strategy for Enhancing Cell-Free Metabolite Production
Authors: Garcia David C. , Dinglasan Jaime Lorenzo N. , Shrestha Him , Abraham Paul E. , Hettich Robert L. , Doktycz Mitchel J. 
Published: April 2020

AbstractCell-free systems present a significant opportunity to harness the metabolic potential of diverse organisms. Removing the cellular context provides the ability to produce biological products without the need to maintain cell viability and enables metabolic engineers to explore novel chemical transformation systems. Crude extracts maintain much of a cell’s capabilities. However, only limited tools are available for engineering the contents of the extracts used for cell-free systems. Thus, our ability to take full advantage of the potential of crude extracts for cell-free metabolic engineering is limited. Here, we employ Multiplex Automated Genomic Engineering (MAGE) to tag proteins for selective removal from crude extracts so as to specifically direct chemical production. Specific edits to central metabolism are possible without significantly impacting cell growth. Selective removal of pyruvate degrading enzymes are demonstrated that result in engineered crude lysates that are capable of 10 to 20-fold increases of pyruvate production when compared to the non-engineered extract. The described approach melds the tools of systems and synthetic biology to develop cell-free metabolic engineering into a practical platform for both bioprototyping and bioproduction.HighlightsA novel method of engineering crude cell lysates for enhancing specific metabolic processes is described.Multiplex Automated Genomic Engineering (MAGE) can be used to engineer donor strains for improving cell-free metabolite production with minimal impact on cell-growth.The described lysate engineering strategy can specifically direct metabolic flux and create metabolic states not possible in living cells.Pooling of the central precursor pyruvate was significantly improved through use of this lysate proteome engineering strategy.