bluuebunny/crossref_metadata_2025_split huggingface dataset:
COVID-19 Transmission Dynamics Underlying Epidemic Waves in Kenya
Authors: Brand Samuel P. C. , Ojal John , Aziza Rabia , Were Vincent , Okiro Emelda A , Kombe Ivy K , Mburu Caroline , Ogero Morris , Agweyu Ambrose , Warimwe George M , Nyagwange James , Karanja Henry , Gitonga John N , Mugo Daisy , Uyoga Sophie , Adetifa Ifedayo M O , Scott J Anthony G , Otieno Edward , Murunga Nickson , Otiende Mark , Ochola-Oyier Lynette I , Agoti Charles N , Githinji George , Kasera Kadondi , Amoth Patrick , Mwangangi Mercy , Aman Rashid , Ng’ang’a Wangari , Tsofa Benjamin , Bejon Philip , Keeling Matt. J. , Nokes D. James. , Barasa Edwine 
Published: June 2021

AbstractPolicy decisions on COVID-19 interventions should be informed by a local, regional and national understanding of SARS-CoV-2 transmission. Epidemic waves may result when restrictions are lifted or poorly adhered to, variants with new phenotypic properties successfully invade, or when infection spreads to susceptible sub-populations. Three COVID-19 epidemic waves have been observed in Kenya. Using a mechanistic mathematical model we explain the first two distinct waves by differences in contact rates in high and low social-economic groups, and the third wave by the introduction of a new higher-transmissibility variant. Reopening schools led to a minor increase in transmission between the second and third waves. Our predictions of current population exposure in Kenya (∼75% June 1st) have implications for a fourth wave and future control strategies.One Sentence SummaryCOVID-19 spread in Kenya is explained by mixing heterogeneity and a variant less constrained by high population exposure
Clinician views on best practice community care for people with complex emotional needs and how it can be achieved: a qualitative study
Authors: Foye Una , Stuart Ruth , Trevillion Kylee , Oram Sian , Allen Dawn , Broeckelmann Eva , Jefferies Stephen , Jeynes Tamar , Crawford Mike J , Moran Paul , McNicholas Shirley , Billings Jo , Dale Oliver , Simpson Alan , Johnson Sonia 
Published: June 2021

AbstractBackgroundService provision for people with complex emotional needs (CEN) is recurrently identified as needing to be transformed: there are serious concerns about quality, accessibility, fragmentation of the service system and the stigma and therapeutic pessimism service users say they encounter. We use the term CEN as a working description to refer to the needs experienced by people who may have been diagnosed with a ‘personality disorder’. Understanding clinician perspectives is vital for service transformation, as their views and experiences shed light on potential barriers to achieving good care, and how these might be overcome. In this study, we aimed to explore these views.MethodsWe used a qualitative interview design. A total of fifty participants from a range of professions across specialist and generic community mental health services across England who provide care to people with CEN took part in six focus groups and sixteen one-to-one interviews. We analysed the data using a thematic approach.FindingsMain themes were: 1) Defining Best Practice, 2) Facilitators of Best Care, 3) Barriers to Best Care, 4) Systemic Challenges. Across these themes, staff highlighted in particular the need for care that was person-centred, relational, empathic, and trauma informed. However, major barriers to achieving this are stigmatising attitudes and behaviour towards people with CEN, especially in generic mental health services, lack of development of coherent service systems offering clear long-term pathways and ready access to high quality treatment, and lack of well-developed structures for staff training and support.DiscussionOverall, the findings point towards clinician views as generally congruent with those of service users, reinforcing the need for priorities towards systemwide change to ensure that we can provide the best practice care for these individuals. Particularly prominent is the need to put in place system-wide training and support for clinicians working with CEN, encompassing generic as well as specialist services, and to challenge the stigma still experienced throughout the system.ConclusionsStaff working with this service user group report that delivering best practice care services to be flexible, integrated, and sustainably funded, and for staff to be supported through ongoing training and supervision.
Evaluation of the Access Bio CareStart™ rapid SARS-CoV-2 antigen test in asymptomatic individuals tested at a community mass-testing program in Western Massachusetts
Authors: Suliman Sara , Matias Wilfredo R. , Fulcher Isabel R , Molano Francisco J. , Collins Shannon , Uceta Elizabeth , Zhu Jack , Paxton Ryan M. , Gonsalves Sean F. , Harden Maegan V. , Fisher Marissa , Meldrim Jim , Gabriel Stacey , Franke Molly F. , Hung Deborah T. , Smole Sandra C. , Madoff Lawrence C. , Ivers Louise C. 
Published: June 2021

AbstractBackgroundPoint-of-care antigen-detecting rapid diagnostic tests (RDTs) for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) represent a scalable tool for SARS-CoV-2 infections surveillance. Data on their performance in real-world community settings is paramount for their implementation.MethodWe evaluated the accuracy of CareStart™ COVID-19 Antigen test (CareStart) in a testing site in Holyoke, Massachusetts. We compared CareStart to a SARS-CoV-2 reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) reference, using anterior nasal swab samples. We calculated the sensitivity, specificity, and expected positive and negative predictive values at different SARS-CoV-2 prevalence estimates.ResultsWe performed 666 tests on 591 unique individuals. 573 (86%) were asymptomatic. There were 52 positive tests by RT-qPCR. The sensitivity of CareStart was 49.0% (95% Confidence Interval (CI): 34.8 – 63.4) and specificity was 99.5% (95% CI: 98.5 – 99.9). Among positive RT-qPCR tests, the median cycle threshold (Ct) was significantly lower in samples that tested positive on CareStart. Using a Ct ≤ 30 as a benchmark for positivity increased the sensitivity to 64.9% (95% CI: 47.5 – 79.8).ConclusionsCareStart has a high specificity and moderate sensitivity. The utility of RDTs, such as CareStart, in mass implementation should prioritize use cases in which a higher specificity is more important.
Structural basis for the interaction of SARS-CoV-2 virulence factor nsp1 with Pol α - Primase
Authors: Kilkenny Mairi L. , Veale Charlotte E. , Guppy Amir , Hardwick Steven W. , Chirgadze Dimitri Y. , Rzechorzek Neil J. , Maman Joseph D. , Pellegrini Luca 
Published: June 2021

AbstractThe molecular mechanisms that drive the infection by the SARS-CoV-2 coronavirus – the causative agent of the COVID-19 (Coronavirus disease-2019) pandemic – are under intense current scrutiny, to understand how the virus operates and to uncover ways in which the disease can be prevented or alleviated.Recent cell-based analyses of SARS-CoV-2 protein - protein interactions have mapped the human proteins targeted by the virus. The DNA polymerase α - primase complex or primosome – responsible for initiating DNA synthesis in genomic duplication – was identified as a target of nsp1 (non structural protein 1), a major virulence factor in the SARS-CoV-2 infection.Here, we report the biochemical characterisation of the interaction between nsp1 and the primosome and the cryoEM structure of the primosome - nsp1 complex. Our data provide a structural basis for the reported interaction between the primosome and nsp1. They suggest that Pol α - primase plays a part in the immune response to the viral infection, and that its targeting by SARS-CoV-2 aims to interfere with such function.
WWP1 deficiency protects from cardiac remodeling induced by simulated microgravity
Authors: Zhong Guohui , Zhao Dingsheng , Li Jianwei , Liu Zifan , Pan Junjie , Yuan Xinxin , Xing Wenjuan , Zhao Yinglong , Ling Shukuan , Li Yingxian 
Published: June 2021

AbstractCardiac muscle is extremely sensitive to changes in loading conditions, the microgravity during space flight can cause cardiac remodeling and function decline. At present, the mechanism of microgravity-induced cardiac remodeling remains to be revealed. WW domain-containing E3 ubiquitin protein ligase 1 (WWP1) is an important activator of pressure-overload induced cardiac remodeling by stabilizing disheveled segment polarity proteins 2 (DVL2) and activating CaMKII/HDAC4/MEF2C axis. However, the role of WWP1 in the cardiac remodeling induced by microgravity is unknown. The purpose of this study was to determine whether WWP1 was also involved in the regulation of cardiac remodeling caused by microgravity. Firstly, we detected the expression of WWP1 and DVL2 in the heart from mice and monkeys after simulated microgravity using western blotting and Immunohistochemistry. Secondly, WWP1 knockout (KO) and wild type mice were subjected to hindlimb unloading (HU) to simulate microgravity effect. We assessed the cardiac remodeling in morphology and function through histological analysis and echocardiography. Finally, we detected the phosphorylation level of CaMKII and HDAC4 in the heart from WT and WWP1 KO mice after HU. The results revealed the increased expression of WWP1 and DVL2 in the heart both from mice and monkey after simulated microgravity. WWP1 deficiency protected against simulated microgravity-induced cardiac atrophy and function decline. Histological analysis demonstrated WWP1 KO inhibited the decreases in the size of individual cardiomyocytes of mice after hindlimb unloading. WWP1 KO can inhibit the activation of DVL2/CaMKII/HDAC4 pathway in heart of mice induced by simulated microgravity. These results demonstrated WWP1 as a potential therapeutic target for cardiac remodeling and function decline induced by simulated microgravity.
A method to study extracellular vesicles secretedin vitroby cultured cells with minimum sample processing and extracellular vesicle loss
Authors: Viveiros A , Kadam V , Monyror J , Morales LC , Pink D , Rieger A M , Sipione S , Posse de Chaves E 
Published: June 2021

ABSTRACTExtracellular vesicles (EVs) are involved in a multitude of physiological functions and play important roles in health and disease. The study of EV secretion and EV characterization remains challenging due to the small size of these particles, a lack of universal EV markers, and sample loss or technical artifacts that are often associated with EV separation techniques. We developed a method for in-cell EV labeling with fluorescent lipids (DiI), followed by DiI-labelled EV characterization in the conditioned medium by imaging flow cytometry (IFC). Direct IFC analysis of EVs in the conditioned medium, after removal of apoptotic bodies and cellular debris, significantly reduces sample processing and loss compared to established methods for EV separation, resulting in improved detection of quantitative changes in EV secretion and subpopulations compared to protocols that rely on EV separation by ultracentrifugation. In conclusion, our optimized protocol for EV labeling and analysis reduces EV sample processing and loss, and is well suited for cell biology studies that focus on modulation of EV secretion by cells in culture.
Supervised Capacity Preserving Mapping: A Clustering Guided Visualization Method for scRNAseq data
Authors: Zhai Zhiqian , Lei Yu L. , Wang Rongrong , Xie Yuying 
Published: June 2021

AbstractThe rapid development of scRNA-seq technologies enables us to explore the transcriptome at the cell level in a large scale. Recently, various computational methods have been developed to analyze the scR-NAseq data such as clustering and visualization. However, current visualization methods including t-SNE and UMAP are challenged by the limited accuracy of rendering the geometic relationship of populations with distinct functional states. Most visualization methods are unsupervised, leaving out information from the clustering results or given labels. This leads to the inaccurate depiction of the distances between the bona fide functional states and the variance of clusters. We present supCPM, a robust supervised visualization method, which separates different clusters, preserves global structure, and tracks the cluster variance. Compared with six visualization methods using synthetic and real data sets, supCPM shows improved performance than other methods in preserving the global geometric structure and data variance. Overall, supCPM provides an enhanced visualization pipeline to assist the interpretation of functional transition and accurately depict population segregation.
Dynamical differential covariance recovers directional network structure in multiscale neural systems
Authors: Chen Yusi , Rosen Burke Q. , Sejnowski Terrence J. 
Published: June 2021

Investigating neural interactions is essential to understanding the neural basis of behavior. Many statistical methods have been used for analyzing neural activity, but estimating the direction of network interactions correctly and efficiently remains a difficult problem (1). Here, we derive dynamical differential covariance (DDC), a new method based on dynamical network models that detects directional interactions with low bias and high noise tolerance under nonstationarity conditions. The method was first validated and compared with other methods on networks with false positive motifs and multiscale neural simulations where the ground truth connectivity was known. When applied to recordings of resting-state functional magnetic resonance imaging (rs-fMRI) recordings, DDC consistently detected regional interactions with strong structural connectivity in over 1,000 individual subjects obtained by diffusion MRI (dMRI). DDC is a promising new family of methods for estimating functional connectivity that can be generalized to a wide range of dynamical models and recording techniques and to other applications where system identification from sparse data is needed.Significance StatementThrough dynamical interactions with each other, neurons make it possible for us to sense, move and think. It is now possible to simultaneously record from many individual neurons and brain regions. Methods for analyzing these large-scale recordings are needed that can reveal how the patterns of activity give rise to behavior. We developed an efficient, intuitive and robust way to analyze these recordings and validated it on simulations of model neural networks where the ground truth was known. We called this method dynamical differential covariance (DDC) because it can estimate not only the presence of a connection but also which direction the information is flowing in a network between neurons or cortical areas. We also successfully applied DDC to brain imaging data from functional Magnetic Resonance Imaging.
PTT-quant - a new method for direct identification and absolute quantification of premature transcription termination events, following the example of bacterial riboswitches
Authors: Machtel Piotr , Wasilewska-Burczyk Anna , Zacharjasz Julian , Bąkowska-Żywicka Kamilla 
Published: June 2021

AbstractRegulation of gene expression by premature termination of transcription has been well described in all domains of life, including metazoans, yeast, plants and bacteria. Although methods for identification of such regulatory events by sequencing are available, the focused biochemical studies of the mechanism is hampered by lack of highly sensitive and accurate experimental methods. Here we propose a new method for absolute quantification of premature transcription termination events, PTT-quant. It is based on highly sensitive two-step digital droplet PCR protocol, coupled with normalized cDNA synthesis attained by site-specific pre-cleavage of investigated transcripts with RNase H. As a consequence, our method enables the reliable and sensitive quantification of both, prematurely terminated and full-length transcripts. By application of our method to investigation of transcriptional riboswitches in Bacillus subtilis, we were able to precisely measure the dynamics of SAM riboswitch induction, which turned to be ∼23% higher in comparison the results obtained without cDNA synthesis normalization.
On electrical spiking of Ganoderma resinaceum
Authors: Adamatzky Andrew , Gandia Antoni 
Published: June 2021

AbstractFungi exhibit action-potential like spiking activity. Up to date most electrical activity of oyster fungi has been characterised in sufficient detail. It remains unclear if there are any patterns of electrical activity specific only for a certain set of species or if all fungi share the same ‘language’ of electrical signalling. We use pairs of differential electrodes to record extracellular electrical activity of the antler-like sporocarps of the polypore fungus Ganoderma resinaceum. The patterns of the electrical activity are analysed in terms of frequency of spiking and parameters of the spikes. The indicators of the propagation of electrical activity are also highlighted.
Impact of genomic preselection on subsequent genetic evaluations with ssGBLUP - using real data from pigs
Authors: Jibrila Ibrahim , Vandenplas Jeremie , ten Napel Jan , Bergsma Rob , Veerkamp Roel F , Calus Mario P.L 
Published: June 2021

AbstractBackgroundEmpirically assessing the impact of preselection on subsequent genetic evaluations of preselected animals requires comparison of scenarios taking into account different approaches, including scenarios without preselection. However, preselection almost always takes place in animal breeding programs, so it is difficult to have a dataset without preselection. Hence most studies on preselection used simulated datasets, concluding that genomic estimated breeding values (GEBV) from subsequent single-step genomic best linear unbiased prediction (ssGBLUP) evaluations are unbiased. The aim of this study was to investigate the impact of genomic preselection (GPS) on accuracy and bias in subsequent ssGBLUP evaluations, using data from a commercial pig breeding program.MethodsWe used data on four pig production traits from one sire line and one dam line. The traits are average daily gain during performance testing, average daily gain throughout life, backfat thickness, and loin depth. As these traits had different weights in the breeding goals of the two lines, we analyzed the two lines separately. Per line, we had a reference GPS scenario which kept all available data, against which the next two scenarios were compared. We then implemented two other scenarios with additional layers of GPS by removing all animals without progeny either i) only in the validation generation, or ii) in all generations. We conducted subsequent ssGBLUP evaluations per GPS scenario, utilizing all the data remaining after implementing the GPS scenario. In computing accuracy and bias, we compared GEBV against progeny yield deviations of validation animals.ResultsResults for all traits in both lines showed marginal loss in accuracy due to the additional layers of GPS. Average accuracy across all GPS scenarios in both lines was 0.39, 0.47, 0.56, and 0.60 respectively for the four traits considered in this study. Bias was largely absent, and when present did not differ greatly among corresponding GPS scenarios.ConclusionAs preselection generally has the same effect in animal breeding programs, we concluded that impact of preselection is generally minimal on accuracy and bias in subsequent ssGBLUP evaluations of selection candidates in pigs and in other animal breeding programs.
Do we really understand the role of the prefrontal cortex in placebo analgesia?
Authors: Frangos Eleni , Madian Nicholas , Wang Binquan , Bradson Megan L. , Gracely John L. , Richards Emily A. , Colloca Luana , Schweinhardt Petra , Bushnell M. Catherine , Ceko Marta 
Published: June 2021

ABSTRACTSeveral reviews have strongly implicated prefrontal cortical engagement in expectation-based placebo analgesia. We recently found a robust placebo analgesic response and associated decreases in pain-related cortical activations, without observable prefrontal engagement. We hypothesized our substantial conditioning and weak verbal instructions diminished expectation-related prefrontal activation. To test this, we examined the same subjects during a conditioning procedure, in which expectancy of pain relief was high. In two conditioning sessions, noxious heat was applied to a leg region treated with an “analgesic” cream and another treated with a “moisturizing” cream. In reality, both creams were inert, but the temperature applied to the moisturizing-cream area was 2°C higher than that applied to the analgesic-cream area.Functional MRI was acquired during the second conditioning session. Pain ratings were lower for the low heat than the high heat, with corresponding reduced activations in pain-related regions. Similar to previous studies with strong expectation for pain relief, we observed more prefrontal activations during the “analgesic” than the control condition. Nevertheless, contrary to the idea of active prefrontal engagement, the relative activation was based on differences in negative BOLD signals. A literature review revealed that only a few studies conclusively showed active engagement of prefrontal cortex, i.e. increased positive BOLD signal during high expectation compared to a control, with variable timing and spatial-specificity. We suggest that this variability is due to the heterogeneous influence of cognitive, emotional and motivational factors. Future studies should attempt to unravel the multiple contributions to placebo responsiveness in the prefrontal cortex.
EcoEvoApps: Interactive Apps for Theoretical Models in Ecology and Evolutionary Biology
Authors: McGuire Rosa M. , Hayashi Kenji T. , Yan Xinyi , Caritá Vaz Marcel , Cinoğlu Damla , Cowen Madeline C. , Martínez-Blancas Alejandra , Sullivan Lauren L. , Vazquez-Morales Sheila , Kandlikar Gaurav S. 
Published: June 2021

AbstractThe integration of theory and data drives progress in science, but a persistent barrier to such integration in ecology and evolutionary biology (EEB) is that theory is often developed and expressed in the form of mathematical models that can feel daunting and inaccessible for students and empiricists with variable quantitative training and attitudes towards math.A promising way to make mathematical models more approachable is to embed them into interactive tools with which one can visually evaluate model structures and directly explore model outcomes through simulation.To promote such interactive learning of quantitative models, we developed EcoEvoApps, a collection of free, open-source (R/Shiny) apps that include model overviews, interactive model simulations, and code to implement these models directly in R. The package currently focuses on canonical models of population dynamics, species interaction, and landscape ecology. We also outline a vision and approach for growing the collection to include more models from across EEB.These apps help illustrate fundamental results from theoretical ecology and can serve as valuable teaching tools in classroom settings. We present data from student surveys which show that students rate these apps as useful learning tools, and that using interactive apps leads to substantial gains in students’ interest and confidence in mathematical models. This points to the potential for interactive activities to make theoretical models more accessible to a wider audience, and thus facilitate the feedback between theory and data across ecology and evolutionary biology.