bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characterization of cyclic alternating pattern during sleep in older men and women using large population studies
Authors: Hartmann Simon , Bruni Oliviero , Ferri Raffaele , Redline Susan , Baumert Mathias 
Published: February 2020

Abstract

Study Objectives
To assess the microstructural architecture of non-rapid eye movement (NREM) sleep known as cyclic alternating pattern (CAP) in relation to the age, gender, self-reported sleep quality, and the degree of sleep disruption in large community-based cohort studies of older people.

Methods
We applied a high-performance automated CAP detection system to characterize CAP in 2,811 men from the Osteoporotic Fractures in Men Sleep Study (MrOS) and 426 women from the Study of Osteoporotic Fractures (SOF). CAP was assessed with respect to age and gender and correlated to obstructive apnea–hypopnea index, arousal index (AI-NREM), and periodic limb movements in sleep index. Further, we evaluated CAP across levels of self-reported sleep quality measures using analysis of covariance.

Results
Age was significantly associated with the number of CAP sequences during NREM sleep (MrOS: p = 0.013, SOF = 0.051). CAP correlated significantly with AI-NREM (MrOS: ρ = 0.30, SOF: ρ = 0.29). CAP rate, especially the A2+A3 index, was inversely related to self-reported quality of sleep, independent of age and sleep disturbance measures. Women experienced significantly fewer A1-phases compared to men, in particular, in slow-wave sleep (N3).

Conclusions
We demonstrate that automated CAP analysis of large-scale databases can lead to new findings on CAP and its subcomponents. We show that sleep disturbance indices are associated with the CAP rate. Further, the CAP rate is significantly linked to subjectively reported sleep quality, independent from traditionally scored markers of sleep fragmentation. Finally, men and women show differences in the microarchitecture of sleep as identified by CAP, despite similar macro-architecture.
Older and Less Deviant Reactions to Abusive Supervision? A Moderated Mediation Model of Age and Cognitive Reappraisal
Authors: Peng Yisheng , Xu Xiaohong , Matthews Russell 
Published: February 2020

AbstractGiven the significant costs of abusive supervision and the broad implications of an increasingly aging workforce, scholars have called for examining the role of employee age in the abusive supervision literature. In response to this call, this study introduced a moderated mediation model of age, abusive supervision, cognitive reappraisal, and workplace deviance based on socioemotional selectivity theory. We tested this model with a sample of 614 working adults. Results suggest that employee age significantly moderated the effect of abusive supervision on cognitive reappraisal such that abusive supervision was negatively related to cognitive reappraisal for younger workers, but not for older workers. Cognitive reappraisal was negatively related to workplace (i.e., interpersonal and organizational) deviance. Furthermore, there was a significant moderated mediation effect where the indirect relationship between abusive supervision and workplace deviance via cognitive reappraisal was significant for younger workers, but not for older workers. Our findings suggest that older workers’ emotional competencies (e.g., use of cognitive reappraisal) may account for age-related advantages in coping with abusive supervision. Theoretical and implications were discussed.
Towards a comparative framework of demographic resilience
Authors: Capdevila Pol , Stott Iain , Beger Maria , Salguero-Gómez Roberto 
Published: February 2020

AbstractIn times of global biodiversity crisis, developing tools to define, quantify, compare and predict ecological resilience is essential for understanding species’ responses to global change. Disparate interpretations of ecological resilience have, however, hampered the development of a common currency to quantify and compare resilience across natural systems. Most frameworks of study have focused on upper levels of biological organisation, especially ecosystems or communities, which adds layers of complication to measuring resilience with empirical data. To overcome such limitations, we suggest quantifying resilience using demographic data. Surprisingly, a quantifiable definition of resilience does not exist at the demographic level. Here, we present a framework of demographic resilience with a set of metrics that are comparable across species, and facilitate cost-effective management decisions.
Machine learning using intrinsic genomic signatures for rapid classification of novel pathogens: COVID-19 case study
Authors: Randhawa Gurjit S. , Soltysiak Maximillian P.M. , Roz Hadi El , de Souza Camila P.E. , Hill Kathleen A. , Kari Lila 
Published: February 2020

AbstractAs of February 20, 2020, the 2019 novel coronavirus (renamed to COVID-19) spread to 30 countries with 2130 deaths and more than 75500 confirmed cases. COVID-19 is being compared to the infamous SARS coronavirus, which resulted, between November 2002 and July 2003, in 8098 confirmed cases worldwide with a 9.6% death rate and 774 deaths. Though COVID-19 has a death rate of 2.8% as of 20 February, the 75752 confirmed cases in a few weeks (December 8, 2019 to February 20, 2020) are alarming, with cases likely being under-reported given the comparatively longer incubation period. Such outbreaks demand elucidation of taxonomic classification and origin of the virus genomic sequence, for strategic planning, containment, and treatment. This paper identifies an intrinsic COVID-19 genomic signature and uses it together with a machine learning-based alignment-free approach for an ultra-fast, scalable, and highly accurate classification of whole COVID-19 genomes. The proposed method combines supervised machine learning with digital signal processing for genome analyses, augmented by a decision tree approach to the machine learning component, and a Spearman’s rank correlation coefficient analysis for result validation. These tools are used to analyze a large dataset of over 5000 unique viral genomic sequences, totalling 61.8 million bp. Our results support a hypothesis of a bat origin and classify COVID-19 asSarbecovirus, withinBetacoronavirus. Our method achieves high levels of classification accuracy and discovers the most relevant relationships among over 5,000 viral genomes within a few minutes,ab initio, using raw DNA sequence data alone, and without any specialized biological knowledge, training, gene or genome annotations. This suggests that, for novel viral and pathogen genome sequences, this alignment-free whole-genome machine-learning approach can provide a reliable real-time option for taxonomic classification.
High contiguity long read assembly ofBrassica nigraallows localization of active centromeres and provides insights into the ancestralBrassicagenome
Authors: Perumal Sampath , Koh Chu Shin , Jin Lingling , Buchwaldt Miles , Higgins Erin , Zheng Chunfang , Sankoff David , Robinson Stephen J. , Kagale Sateesh , Navabi Zahra-Katy , Tang Lily , Horner Kyla N. , He Zhesi , Bancroft Ian , Chalhoub Boulos , Sharpe Andrew G , Parkin Isobel AP 
Published: February 2020

AbstractHigh-quality nanopore genome assemblies were generated for twoBrassica nigragenotypes (Ni100 and CN115125); a member of the agronomically importantBrassicaspecies. The N50 contig length for the two assemblies were 17.1 Mb (58 contigs) and 0.29 Mb (963 contigs), respectively, reflecting recent improvements in the technology. Comparison with ade novoshort read assembly for Ni100 corroborated genome integrity and quantified sequence related error rates (0.002%). The contiguity and coverage allowed unprecedented access to low complexity regions of the genome. Pericentromeric regions and coincidence of hypo-methylation enabled localization of active centromeres and identified a novel centromere-associated ALE class I element which appears to have proliferated through relatively recent nested transposition events (<1 million years ago). Computational abstraction was used to define a post-triplicationBrassicaspecific ancestral genome and to calculate the extensive rearrangements that define the genomic distance separatingB. nigrafrom its diploid relatives.
First report of the Eocene bivalveSchedocardia(Mollusca, Cardiidae) from Cuba
Authors: Orihuela Johanset , Izquierdo Yasmani Ceballos , Portell Roger W. 
Published: February 2020

ABSTRACTHerein we provide the first report of the cardiid bivalveSchedocardiafrom Cuba. The single, partial, valve external mold was derived from the Madruga Formation which is characterized by a richly diverse marine fauna including echinoderms, brachiopods, benthic and planktonic foraminiferans, but from which bivalves were not previously reported. The unit is considered late Paleocene in age (Thanetian), but the presence ofSchedocardiasupports a possible age extension of the formation into the early Eocene (Ypresian). Moreover, we provide a reconsideration of the historical factors that affected the accepted type locality of the outcrop, which allows for an alternative interpretation of the fauna found therein.RESUMENSe reporta por primera vez el género bivalvoSchedocardiade la Formación Madruga, para el registro fósil de Cuba. De esta formación se ha reportado una rica fauna de invertebrados incluyendo equinodermos, braquiópodos y, especialmente de foraminíferos, pero no moluscos bivalvos. Se ha considerado que la Formación Madruga se depositó durante el Paleoceno tardío (Thanetiano), no obstante, la presencia deSchedocardiaapoya la extensión de edad de la formación hasta el Eoceno temprano (Ypresiano). Además, se consideran factores antropogénicos que han afectado la localidad tipo de la formación.
The key to complexity in interacting systems with multiple strains
Authors: Gjini Erida , Madec Sten 
Published: February 2020

AbstractEcological community structure, persistence and stability are shaped by multiple forces, acting on multiple scales. These include patterns of resource use and limitation, spatial heterogeneities, drift and migration. Pathogen strains co-circulating in a host population are a special type of an ecological community. They compete for colonization of susceptible hosts, and sometimes interact via altered susceptibilities to co-colonization. Diversity in such pairwise interaction traits enables the multiple strains to create dynamically their niches for growth and persistence, and ‘engineer’ their common environment. How such a network of interactions with others mediates collective coexistence remains puzzling analytically and computationally difficult to simulate. Furthermore, the gradients modulating stability-complexity regimes in such multi-player systems remain poorly understood. In a recent study, we presented an analytic framework forN-type coexistence in an SIS epidemiological system with co-colonization interactions. The multi-strain complexity was reduced fromO(N2) dimensions of population structure to onlyNequations for strain frequency evolution on a long timescale. Here, we examine the key drivers of coexistence regimes in such a system. We find the ratio of single to co-colonizationμcritically determines the type of equilibrium for multi-strain dynamics. This key quantity in the model encodes a trade-off between overall transmission intensityR0and mean interaction coefficient in strain spacek. Preserving a given coexistence regime, under fixed trait variation, can only be achieved from a balance between higher competition in favourable environments, and higher cooperation in harsher environments, consistent with the stress gradient hypothesis in ecology. Multi-strain coexistence regimes are more stable whenμis small, whereas asμincreases, dynamics tends to increase in complexity. There is an intermediate ratio that maximizes the existence and stability of a unique coexistence equilibrium between strains. This framework provides a foundation for linking invariant principles in collective coexistence across biological systems, and for understanding critical shifts in community dynamics, driven by simple and random pairwise interactions but potentiated by mean-field and environmental gradients.
Differential vulnerability of the cerebellum in healthy ageing and Alzheimer’s disease
Authors: Gellersen Helena M. , Guell Xavier , Sami Saber 
Published: February 2020

AbstractRecent findings challenge the prior notion that the cerebellum remains unaffected by Alzheimer’s disease (AD). Yet, it is unclear whether AD exacerbates age-related cerebellar grey matter decline or engages distinct structural and functional territories. We performed a meta-analysis of cerebellar grey matter loss in normal ageing and AD. We mapped voxels with structural decline onto established brain networks, functional parcellations, and along gradients that govern the functional organisation of the cerebellum. Importantly, these gradients track continuous changes in cerebellar specialisation providing a more nuanced measure of the functional profile of regions vulnerable to ageing and AD. Gradient 1 progresses from motor to cognitive territories; Gradient 2 isolates attentional processing; Gradient 3 captures lateralisation differences in cognitive functions. We identified bilateral and right-lateralised posterior cerebellar atrophy in ageing and AD, respectively. Age- and AD- related structural decline only showed partial spatial overlap in right lobule VI/Crus I. Despite the seemingly distinct patterns of AD- and age-related atrophy, the functional profiles of these regions were similar. Both participate in the same macroscale networks (default mode, frontoparietal, attention), support executive functions and language processing, and did not exhibit a difference in relative positions along Gradients 1 or 2. However, Gradient 3 values were significantly different in ageing vs. AD, suggesting that the roles of left and right atrophied cerebellar regions exhibit subtle functional differences despite their membership in similar macroscale networks. These findings provide an unprecedented characterisation of structural and functional differences and similarities in cerebellar grey matter loss between normal ageing and AD.
A survey to explore new markers of achievement to assess and monitor gender equity in an NIHR Biomedical Research Centre: A two-factor model
Authors: Henderson Lorna R , Shah Syed Ghulam Sarwar , Ovseiko Pavel V , Dam Rinita , Buchan Alastair M , McShane Helen , Kiparoglou Vasiliki 
Published: February 2020

ABSTRACTBackgroundThe underrepresentation of women in academic medicine at senior level and in leadership positions is well documented. In the United Kingdom, the National Institute for Health Research (NIHR) announced that eligibility for funding for Biomedical Research Centres (BRCs) required at least Silver award status of the Athena SWAN Charter. However, the evidence base for monitoring gender equity (GE) in BRCs is underdeveloped.MethodsAn exploratory online survey distributed to an entire population of NIHR Oxford BRC affiliates (N=683) who ranked the importance of 13 markers of GE on a five point Likert scale. Data were summarised using frequencies and descriptive statistics. Interrelationships between the markers and underlying latent dimensions (factors) were determined by exploratory and confirmatory factor analyses. Thematic analysis was used to analyse open-ended comments.ResultsThe response rate was 36% (243 respondents). Respondents were more frequently female (55%, n=133), aged 41-50 years (33%, n=81), investigators (33%, n=81) and had been affiliated with the BRC for 2-7 years (39.5%, n=96). Participants ranked BRC senior leadership roles and organisational policies on gender equity, as very important, 58% (n=141) and 57% (n=139) respectively. The top two markers ranked as very important by female participants were organisational policies (64.7%, n=86/133) and recruitment and retention (60.9%, n=81/133), whereas male participants ranked leadership development (52.1%, n=50/96) and BRC senior leadership roles (50%, n=48/96) as being very important. The factor analyses showed two distinct latent dimensions: organisational markers and individual markers of GE in BRCs. Open ended comments suggested three key areas of actions: monitoring and benchmarking, organisational support for those with childcare responsibilities, and leadership and Institutional support for GE.ConclusionsThe findings suggest a two-factor model of markers of achievement for GE with organisational and individual dimensions. Implementation and sustainability of gender equity requires commitment at senior leadership and organisational policy level.
Tourism-driven ocean science for sustainable use: A case study of sharks in Fiji
Authors: Ward-Paige C A , Brunnschweiler J , Sykes H 
Published: February 2020

AbstractThe oceans are in a state of rapid change – both negatively, due climate destabilization and misuse, and positively, due to strengthening of policies for sustainable use combined with momentum to grow the blue economy. Globally, more than 121 million people enjoy nature-based marine tourism — e.g., recreational fishing, diving, whale watching — making it one of the largest marine sectors. This industry is increasingly threatened by ocean degradation and management has not kept pace to ensure long-term sustainability. In response, individuals within the industry are taking it upon themselves to monitor the oceans and provide the data needed to assist management decisions. Fiji is one such place where the dive tourism industry is motivated to monitor the oceans (e.g., track sharks). In 2012, 39 dive operators in collaboration with eOceans commenced the Great Fiji Shark Count (GFSC) to document sharks (and other species) on 592 dive sites. Here, using 146,304 shark observations from 30,668 dives we document spatial patterns of 11 shark species. High variability demonstrates the value of longitudinal data that include absences for describing mobile megafauna and the capacity of stakeholders to document the oceans. Our results may be used to guide future scientific questions, provide a baseline for future assessments, or to evaluate conservation needs. It also shows the value of scientists collaborating with stakeholders to address questions that are most important to the local community so that they have the information needed to make science-based decisions.
Artemisinin-resistant malaria parasites show enhanced transmission to mosquitoes under drug pressure
Authors: Witmer Kathrin , Dahalan Farah A. , Delves Michael J , Yahiya Sabrina , Watson Oliver J. , Straschil Ursula , Chiwcharoen Darunee , Sornboon Boodtee , Pukrittayakamee Sasithon , Pearson Richard D. , Howick Virginia M. , Lawniczak Mara K. N. , White Nicholas J. , Dondorp Arjen M. , Okell Lucy C. , Ruecker Andrea , Chotivanich Kesinee , Baum Jake 
Published: February 2020

ABSTRACTResistance to artemisinin combination therapy (ACT) in thePlasmodium falciparumparasite is threatening to reverse recent gains in reducing global deaths from malaria. Whilst resistance manifests as delayed asexual parasite clearance in patients following ACT treatment, the phenotype can only spread geographically via the sexual cycle and subsequent transmission through the mosquito. Artemisinin and its derivatives (such as dihydroartemisinin, DHA) as well as killing the asexual parasite form are known to sterilize male, sexual-stage gametes from activation. Whether resistant parasites overcome this artemisinin-dependent sterilizing effect has not, however, been fully tested. Here, we analysed fiveP. falciparumclinical isolates from the Greater Mekong Subregion, each of which demonstrated delayed clinical clearance and carried known resistance-associated polymorphisms in theKelch13gene (PfK13var). As well as demonstrating reduced sensitivity to artemisinin-derivates inin vitroasexual growth assays, certain PfK13varisolates also demonstrated a marked reduction in sensitivity to these drugs in anin vitromale gamete activation assay compared to a sensitive control. Importantly, the same reduction in sensitivity to DHA was observed when the most resistant isolate was assayed by standard membrane feeding assays usingAnopheles stephensimosquitoes. These results indicate that ACT use can favour resistant over sensitive parasite transmission. A selective advantage for resistant parasite transmission could also favour acquisition of further polymorphisms, such as mosquito host-specificity or antimalarial partner–drug resistance in mixed infections. Favoured transmission of resistance under ACT coverage could have profound implications for the spread of multidrug resistant malaria beyond Southeast Asia.ONE SENTENCE SUMMARYArtemisinin-resistant clinical isolates can also demonstrate resistance to the transmission-blocking effects of artemisinin-based drugs, favouring resistance transmission to the mosquito.
EMBER: Multi-label prediction of kinase-substrate phosphorylation events through deep learning
Authors: Kirchoff Kathryn E. , Gomez Shawn M. 
Published: February 2020

AbstractKinase-catalyzed phosphorylation of proteins forms the back-bone of signal transduction within the cell, enabling the coordination of numerous processes such as the cell cycle, apoptosis, and differentiation. While on the order of 105phosphorylation events have been described, we know the specific kinase performing these functions for less than 5% of cases. The ability to predict which kinases initiate specific individual phosphorylation events has the potential to greatly enhance the design of downstream experimental studies, while simultaneously creating a preliminary map of the broader phosphorylation network that controls cellular signaling. To this end, we describe EMBER, a deep learning method that integrates kinase-phylogeny information and motif-dissimilarity information into a multi-label classification model for the prediction of kinase-motif phosphorylation events. Unlike previous deep learning methods that perform single-label classification, we restate the task of kinase-motif phosphorylation prediction as a multi-label problem, allowing us to train a single unified model rather than a separate model for each of the 134 kinase families. We utilize a Siamese network to generate novel vector representations, or an embedding, of motif sequences, and we compare our novel embedding to a previously proposed peptide embedding. Our motif vector representations are used, along with one-hot encoded motif sequences, as input to a classification network while also leveraging kinase phylogenetic relationships into our model via a kinase phylogeny-weighted loss function. Results suggest that this approach holds significant promise for improving our map of phosphorylation relations that underlie kinome signaling.Availabilityhttps://github.com/gomezlab/EMBER
Discriminating changes in protein structure using PTAD conjugation to tyrosine
Authors: Moinpour Mahta , Barker Natalie K. , Guzman Lindsay E. , Jewett John C. , Langlais Paul R. , Schwartz Jacob C. 
Published: February 2020

ABSTRACTChemical modification of proteins has been crucial in engineering protein-based therapies, targeted biopharmaceutics, molecular probes, and biomaterials. Here, we explore the use of a conjugation-based approach to sense alternative conformational states in proteins. Tyrosine has both hydrophobic and hydrophilic qualities, thus allowing it to be positioned at protein surfaces, or binding interfaces, or to be buried within a protein. Tyrosine can be conjugated with 4-phenyl-3H-1,2,4-triazole-3,5(4H)-dione (PTAD). We hypothesized that individual protein conformations could be distinguished by labeling tyrosine residues in the protein with PTAD. We conjugated tyrosine residues in a well-folded protein, bovine serum albumin (BSA), and quantified labeled tyrosine with LC-MS/MS. We applied this approach to alternative conformations of BSA produced in the presence of urea. The amount of PTAD labeling was found to relate to the depth of each tyrosine relative to the protein surface. This study demonstrates a new use of tyrosine conjugation using PTAD as an analytic tool able to distinguish the conformational states of a protein.