bluuebunny/crossref_metadata_2025_split huggingface dataset:
The effect of a specialist paramedic primary care rotation on appropriate non-conveyance decisions (SPRAINED) study: a controlled interrupted time series analysis
Authors: Pilbery Richard , Young Tracey , Hodge Andrew 
Published: August 2020

AbstractIntroductionNHS ambulance service conveyance rates in the UK are almost 70%, despite an increase in non-emergency cases. This is increasing the demands on crowded emergency departments (ED) and contributes to increased ambulance turnaround times. Yorkshire Ambulance Service introduced a specialist paramedic (SP) role to try and address this, but non-conveyance rates in this group have not been as high as expected.MethodsWe conducted a controlled interrupted time series analysis using data from incidents between June 2017 and December 2019, to study appropriate non-conveyance rates before and after a GP placement. A costing analysis examined the average cost per appropriate non-conveyance achieved for patients receiving care from intervention group SPs pre- and post-placement was also conducted.Results7349 incidents attended by intervention group SPs were eligible for inclusion. Following removal of cases with missing data, 5537/7349 (75.3%) cases remained. Post-placement, the intervention group demonstrated an increase in appropriate non-conveyance rate of 35.0% (95%CI 23.8–46.2%, p<0.001), and a reduction in the trend of appropriate non-conveyance of −1.2% (95%CI −2.8–0.5%, p=0.156), relative to the control group.Post-placement, the cost per appropriate non-conveyance for intervention group SPs was a mean of £509.38 (95% bootstrapped CI £455.32–£564.59) versus £1258.04 (95% bootstrapped CI £1232.64–£1284.04) for the same group in the pre-placement phase. This represents a mean saving of £748.66 per appropriate non-conveyance (95% bootstrapped CI £719.45–£777.32) and a cost-effectiveness ratio of £2141.15 per percentage increase in appropriate non-conveyance (95% bootstrapped CI £2057.62–£2223.12).ConclusionIn this single UK NHS ambulance service study, we found a clinically important and statistically significant increase in appropriate non-conveyance rates by specialist paramedics who had completed a 10-week GP placement. This improvement persisted for the 12-month period following the placement and demonstrated cost savings compared to usual care.What this study addsWhat is known about this subjectUK ambulance service conveyance rates are almost 70% despite an increase in the number of non-emergency casesHealth Education England funded a pilot in 2018 to rotate paramedics into a range of health settings to improve patient care and relieve pressures on primary care services.What this study addsClinically important and statistically significant increases in appropriate non-conveyance rates can be achieved by specialist paramedics who complete a 10-week primary care placement.This improvement is sustained for at least 12-months following the placement cost-effective.
Obtaining prevalence estimates of COVID-19: A model to inform decision-making
Authors: Sahlu Ida , Whittaker Alexander 
Published: August 2020

AbstractObjectivesThe primary aim was to evaluate whether randomly sampling and testing a set number of individuals for active or past COVID-19 while adjusting for misclassification error captures a simulated prevalence. The secondary aim was to quantify the impact of misclassification error bias on publicly reported case data in Maryland.MethodsUsing a stratified random sampling approach, 50,000 individuals were selected from a simulated Maryland population to estimate the prevalence of active and past COVID-19. Data from the 2014-2018 and 2018 American Community Surveys were used. The simulated prevalence was 0.5% and 1.0% for active and past COVID-19, respectively. Bayesian models, informed by published validity estimates, were used to account for misclassification error when estimating the prevalence of active and past COVID-19.ResultsFailure to account for misclassification error overestimated the simulated prevalence for active and past COVID-19. Adjustment for misclassification error decreased the point estimate for active and past COVID-19 prevalence by 55% and 29%, respectively. Adjustment for sampling method and misclassification error only captured the simulated past COVID-19 prevalence. The simulated active COVID-19 prevalence was only captured when set to 0.7% and above. Adjustment for misclassification error for publicly reported Maryland data increased the estimated average daily cases by 8%.ConclusionsRandom sampling and testing of COVID-19 is needed but must be accompanied by adjustment for misclassification error to avoid over- or underestimating the prevalence. This approach bolsters disease control efforts. Implementing random testing for active COVID-19 may be best in a smaller geographic area with highly prevalent cases.
Exometabolomic analysis of decidualizing human endometrial stromal and perivascular cells
Authors: Harden Sarah , Zhou Jieliang , Diniz-da-Costa Maria , Lucas Emma S. , Cui Liang , Murakami Keisuke , Fang Jinling , Chen Qingfeng , Brosens Jan J , Lee Yie Hou 
Published: August 2020

ABSTRACTDifferentiation of endometrial fibroblasts into specialized decidual cells controls embryo implantation and transforms the cycling endometrium into a semi-permanent, immune-protective matrix that accommodates the placenta throughout pregnancy. This process starts during the midluteal phase of the menstrual cycle with decidual transformation of perivascular cells (PVC) surrounding the terminal spiral arterioles and endometrial stromal cells (EnSC) underlying the luminal epithelium. Decidualization involves extensive cellular reprogramming and acquisition of a secretory phenotype, essential for coordinated placental trophoblast invasion. Secreted metabolites are an emerging class of signalling molecules. Here, we used liquid chromatography-mass spectrometry to characterise the dynamic changes in metabolite secretion (exometabolome) of primary PVC and EnSC decidualized over 8 days. We identified 79 annotated metabolites differentially secreted upon decidualization, including prostaglandin, sphingolipid, and hyaluronic acid metabolites. Secreted metabolites encompassed 21 metabolic pathways, most prominently glycerolipid and pyrimidine metabolism. Although temporal exometabolome changes were comparable between decidualizing PVC and EnSC, 32 metabolites were differentially secreted across the decidualization time-course. Further, targeted metabolomics demonstrated a conspicuous difference in xanthine secretion between decidualized PVC and EnSC. Taken together, our findings indicate that the metabolic footprints generated by different decidual subpopulations encode spatiotemporal information that may be important for optimal embryo implantation.
Structure of mycobacterial ATP synthase with the TB drug bedaquiline
Authors: Guo Hui , Courbon Gautier M. , Bueler Stephanie A. , Mai Juntao , Liu Jun , Rubinstein John L. 
Published: August 2020

SummaryTuberculosis (TB), the leading cause of death by infectious disease worldwide, is increasingly resistant to first line antibiotics. Developed from a screen againstMycobacterium smegmatis, bedaquiline can sterilize even latentM. tuberculosisinfections that may otherwise persist for decades and has become a cornerstone of treatment for multidrug resistant and extensively-drug resistant TB. Bedaquiline targets mycobacterial ATP synthase, an essential enzyme in the obligate aerobicMycobacteriumgenus. However, how the drug binds the intact enzyme is unknown. We determined the structure ofM. smegmatisATP synthase with and without bedaquiline. The drug-free structure reveals hook-like extensions from the enzyme’s α subunits that inhibit ATP hydrolysis in low-energy conditions, such as during latent infections. Bedaquiline binding induces global conformational changes in ATP synthase, creating tight binding pockets at the interface of subunits a and c. These binding sites explain the drug’s structure-activity relationship and its potency as an antibiotic for TB.
The R1-weighted connectome: complementing brain networks with a myelin-sensitive measure
Authors: Boshkovski Tommy , Kocarev Ljupco , Cohen-Adad Julien , Mišić Bratislav , Lehéricy Stéphane , Stikov Nikola , Mancini Matteo 
Published: August 2020

AbstractMyelin plays a crucial role in how well information travels between brain regions. Many neurological diseases affect the myelin in the white matter, making myelin-sensitive metrics derived from quantitative MRI of potential interest for early detection and prognosis of those conditions. Complementing the structural connectome, obtained with diffusion MRI tractography, with a myelin sensitive measure could result in a more complete model of structural brain connectivity and give better insight into how the myeloarchitecture relates to brain function. In this work we weight the connectome by the longitudinal relaxation rate (R1) as a measure sensitive to myelin, and then we assess its added value by comparing it with connectomes weighted by the number of streamlines (NOS). Our analysis reveals differences between the two connectomes both in the distribution of their weights and the modular organization. Additionally, the rank-based analysis shows that R1 is able to separate different classes (unimodal and transmodal), following a functional gradient. Overall, the R1-weighted connectome provides a different perspective on structural connectivity taking into account white matter myeloarchitecture.Author summaryIn the present work, we integrate a myelin sensitive MRI metric into the connectome and compare it with a connectome weighted with a standard diffusion-derived metric, number of streamlines (NOS). Our analysis shows that the R1-weighted connectome complements the NOS-weighted connectome. We show that the R1-weighted average distribution does not follow the same trend as the NOS strength distribution, and the two connectomes exhibit different modular organization. We also show that unimodal cortical regions tend to be connected by more streamlines, but the connections exhibit a lower R1-weighted average, while the transmodal regions tend to have a higher R1-weighted average but fewer streamlines. In terms of network communication, this could imply that the unimodal regions require more connections with lower myelination, whereas the transmodal regions take more myelinated, but fewer, connections for a reliable transfer of information.
Site-specific RNA Functionalization via DNA-induced Structure
Authors: Xiao Lu , Habibian Maryam , Kool Eric T. 
Published: August 2020

AbstractSite-specific RNA functionalization is in high demand, but remains a challenge, particularly for RNAs produced by transcription rather than by total synthesis. Recent studies have described acylimidazole reagents that react in high yields at 2’-OH groups in RNAs. To date, the reactions occur stochastically at non-base-paired regions of RNA, covering much of the RNA in scattered acyl esters. Localized reactions, if possible, could prove useful in many applications, providing functional handles at specific sites and sequences of the biopolymer. Here we describe a DNA-directed strategy forin vitrofunctionalization of RNA at site-localized 2’-OH groups. The method, RNA Acylation at Induced Loops (RAIL), utilizes complementary helper DNA oligonucleotides that expose gaps or loops at selected positions while protecting the remainder in DNA-RNA duplexes. Reaction with acylimidazole reagents is then carried out, providing high yields of 2’-OH conjugation at predetermined sites. Subsequent removal of the DNA provides the RNA functionalized as desired. Experiments reveal optimal helper oligodeoxynucleotide designs and conditions for the reaction, and tests of the approach were carried out to control ribozyme activities and to label RNAs with dual-color fluorescent dyes. The RAIL approach offers a simple new strategy for site-specific labeling and controlling RNAs of any length and origin.
Emerging fungal pathogen on an invasive grass differentially affects native species
Authors: Kendig Amy E. , Svahnstrom Vida J. , Adhikari Ashish , Harmon Philip F. , Flory S. Luke 
Published: August 2020

AbstractInfectious diseases and invasive species are strong drivers of biological systems that may interact to shift plant community composition. Disease and invasion can each directly suppress native populations, but variation in responses among native species to disease, invasion, and their combined effects are not well characterized. Here, we quantified the responses of three native North American grass species to experimental inoculation with the fungal pathogenBipolaris gigantea, which has recently emerged in populations of the invasive grassMicrostegium vimineum, causing leaf spot disease. In a greenhouse experiment, we examined the direct effects of disease on the native species and the indirect effects of disease on the native species through altered competition withM. vimineum, which was planted at a range of densities. Pathogen inoculation directly affected each of the three native species in unique ways, by increasing, decreasing, or not changing their biomass relative to mock inoculation. HigherM. vimineumdensities, however, reduced the biomass of all three native species, regardless of inoculation treatment, suggesting that disease had no indirect effects through altered competition. In addition, competition withM. vimineumsuppressed native plant biomass to a greater extent than disease. The differential impacts ofB. giganteaand the consistent impacts ofM. vimineumon native species biomass suggest that disease may modify native plant community composition while plant invasion may suppress multiple native plant species in systems where these drivers co-occur.
Genomic Signature of Sexual Reproduction in the Bdelloid RotiferMacrotrachella quadricornifera
Authors: Laine Veronika N. , Sackton Timothy , Meselson Matthew 
Published: August 2020

AbstractBdelloid rotifers, common freshwater invertebrates of ancient origin and worldwide distribution have long been thought to be entirely asexual, being the principal exception to the view that in eukaryotes the loss of sex leads to early extinction. That bdelloids are facultatively sexual is shown by a study of allele sharing within a group of closely related bdelloids of the speciesMacrotrachella quadricornifera, making it likely that sexual reproduction is essential for long-term success in all eukaryotes.
Identifying reliable fitness proxies for growing animals responding to anthropogenic changes
Authors: Higginson Andrew D. 
Published: August 2020

ABSTRACTAnthropogenic influences on habitats often affect predation on species by introducing novel predators, supporting additional predators, or reducing animals’ ability to detect or avoid predators. Other changes may reduce the ability of animals to feed, or alter their energy use. An increase in predation risk is assumed to reduce prey populations by increasing mortality, reducing foraging and growth. Often animals don’t appear to have been adversely affected, or may even increase growth rate. However, theoretical predictions that may have been overlooked suggest that optimal foraging rate, mortality rate and growth rate may change in counter-intuitive ways, depending on exactly how predation risk or costs have been increased. Increasing predator density may increase mortality rate when foraging, reduce the safety of refuges, or alter the relationship between vigilance and attack likelihood. Increasing temperature may increase metabolic costs in ectotherms and reduce thermogenesis costs in endotherms, which affects the costs of active foraging and inactivity differently. Here, I review the theory on how predation risk and metabolic costs should affect foraging behaviour, mortality and growth in order to explain the great variation in behavioural responses. I show that in some situations animals may not respond behaviourally even though a change severely affects survival, and the mortality may be a poor metric of the impact of a change on population viability. In other situations a fitness proxy may change dramatically whilst fitness is unaffected due to compensatory changes in behaviour or life history. Other measures may change in a positive way whilst fitness declines. I describe how to identify the situations in the field and thereby make reliable measure of fitness in particular study systems. Overall, this work shows how behavioural theory can help understand the impacts of environmental change and highlights promising directions to better understand and mitigate their effects on ecosystems.
When does parasitism maintain sex in the absence of Red Queen Dynamics?
Authors: Ashby Ben 
Published: August 2020

AbstractParasites can select for sexual reproduction in host populations, preventing replacement by faster growing asexual lineages. This is usually attributed to so-called “Red Queen Dynamics” (RQD), where antagonistic coevolution causes fluctuating selection in allele frequencies, which provides sex with an advantage over asex. However, parasitism may also maintain sex in the absence of RQD when sexual populations are more genetically diverse – and hence more resistant, on average – than clonal populations, allowing sex and asex to stably coexist. While the maintenance of sex due to RQD has been studied extensively, the conditions that allow sex and asex to stably coexist have yet to be explored in detail. In particular, we lack an understanding of how host demography and parasite epidemiology affect the maintenance of sex in the absence of RQD. Here, I use an eco-evolutionary model to show that both population density and the type and strength of virulence are important for maintaining sex, which can be understood in terms of their effects on disease prevalence and severity. In addition, I show that even in the absence of heterozygote advantage, asexual heterozygosity affects coexistence with sex due to variation in niche overlap. These results reveal which host and parasite characteristics are most important for the maintenance of sex in the absence of RQD, and provide empirically testable predictions for how demography and epidemiology mediate competition between sex and asex.
Change in social rank and brain dopamine levels: findings from a novel pig model
Authors: Cheng Hui G. , Mohammed Abiy M. , Pease Anthony P. , Gehrke Joshua , Bohart George , Burnett Robert , Nader Michael A. , Anthony James C. 
Published: August 2020

AbstractDopamine (DA) signaling is central in hypothesized causal paths linking the influence of social and environmental variables with cognition, behavior and affective states, including vulnerability to drug dependence. Here, we study whetherchange in one’s social rankinduces DA and norepinephrine (NE) changes using a novel pig model with a social-ranking-and-re-ranking protocol to investigate social context influences on catecholamine concentrations in cerebrospinal fluid (CSF) and blood. For two weeks, 16 recently weaned male piglets were socially housed in four groups, with video-recordings for social rank assessments (α, β, γ, and δ); CSF and blood were obtained from these stable social groups. Next, all four α were housed together, as were all four β, etc., again with video recording for blinded social ranking. CSF and blood samples were collected at three time points: prior to initial social housing, following social housing and following re-organization. Regression analyses disclosed a positive relationship between changes in social rank and post-rank change in CSF levels of DA; one unit increase of social rank predicted a 17.4 pg/ml increase in CSF dopamine concentrations (95% CI= 1.2, 33.7). Compared to piglets with downward shifts in ranks (i.e., high-to-low), piglets with upward shifts (i.e., low-to-high) had a statistically significant greater increase in CSF DA levels. No relationship was observed for CSF NE or blood concentrations of DA or NE at any phase of this experiment. This work, using a novel pig model, adds new evidence on alteration of the brain dopaminergic system induced by social rank change.
Exploration of Chemical Space with Partial Labeled Noisy Student Self-Training for Improving Deep Learning Performance: Application to Drug Metabolism
Authors: Liu Yang , Lim Hansaim , Xie Lei 
Published: August 2020

AbstractMotivationDrug discovery is time-consuming and costly. Machine learning, especially deep learning, shows a great potential in accelerating the drug discovery process and reducing its cost. A big challenge in developing robust and generalizable deep learning models for drug design is the lack of a large amount of data with high quality and balanced labels. To address this challenge, we developed a self-training method PLANS that exploits millions of unlabeled chemical compounds as well as partially labeled pharmacological data to improve the performance of neural network models.ResultWe evaluated the self-training with PLANS for Cytochrome P450 binding activity prediction task, and proved that our method could significantly improve the performance of the neural network model with a large margin. Compared with the baseline deep neural network model, the PLANS-trained neural network model improved accuracy, precision, recall, and F1 score by 13.4%, 12.5%, 8.3%, and 10.3%, respectively. The self-training with PLANS is model agnostic, and can be applied to any deep learning architectures. Thus, PLANS provides a general solution to utilize unlabeled and partially labeled data to improve the predictive modeling for drug discovery.AvailabilityThe code that implements PLANS is available athttps://github.com/XieResearchGroup/PLANS