bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reflections on US Psychiatry
Authors: de Leon Jose 
Published: May 2021

Abstract
The medical model in psychiatry and descriptive psychopathology were established in Germany by Krapelin’s textbook and Jaspers’ General Psychopathology. In the United Kingdom, Mayer-Gross’ textbook synthesized both books, influencing US psychiatry. US psychiatrists from the World War II generation defeated the US academic psychoanalytic establishment by building three pillars: biological psychiatry (brought by Wortis), the psychopharmacology revolution, and the Diagnostic and Statistical Manual of Mental Disorders, 3rd Edition (DSM-III). The psychopharmacology revolution included immigrants (e.g., Gershon), Cole’s marketing, and textbooks by Klein and Fink. The “neo-Kraepelinians” introduced the medical model in US psychiatry and defined 15 valid psychiatric disorders. Spitzer supervised DSM-III’s development. Its 1980 publication started the world dominance of US psychiatry and the multiplication of diagnoses. Major contributions by US psychiatrists include a) McHugh’s update of the Jaspersian approach, b) Fink’s inclusion of catatonia as a syndrome in DSM-5 (following Abrams and Taylor’s studies), and c) DSM-III's departure from the Jaspersian hierarchy of schizophrenia and affective symptoms.
Learning to Predict in Networks with Heterogeneous and Dynamic Synapses
Authors: Burnham Daniel , Shea-Brown Eric , Mihalas Stefan 
Published: May 2021

AbstractA salient difference between artificial and biological neural networks is the complexity and diversity of individual units in the latter (Tasic et al., 2018). This remarkable diversity is present in the cellular and synaptic dynamics. In this study we focus on the role in learning of one such dynamical mechanism missing from most artificial neural network models, short-term synaptic plasticity (STSP). Biological synapses have dynamics over at least two time scales: a long time scale, which maps well to synaptic changes in artificial neural networks during learning, and the short time scale of STSP, which is typically ignored. Recent studies have shown the utility of such short-term dynamics in a variety of tasks (Masse et al., 2019; Perez-Nieves et al., 2021), and networks trained with such synapses have been shown to better match recorded neuronal activity and animal behavior (Hu et al., 2020). Here, we allow the timescale of STSP in individual neurons to be learned, simultaneously with standard learning of overall synaptic weights. We study learning performance on two predictive tasks, a simple dynamical system and a more complex MNIST pixel sequence. When the number of computational units is similar to the task dimensionality, RNNs with STSP outperform standard RNN and LSTM models. A potential explanation for this improvement is the encoding of activity history in the short-term synaptic dynamics, a biological form of long short-term memory. Beyond a role for synaptic dynamics themselves, we find a reason and a role for their diversity: learned synaptic time constants become heterogeneous across training and contribute to improved prediction performance in feedforward architectures. These results demonstrate how biologically motivated neural dynamics improve performance on the fundamental task of predicting future inputs with limited computational resources, and how learning such predictions drives neural dynamics towards the diversity found in biological brains.
Genomic reconstruction of the SARS-CoV-2 epidemic in England
Authors: Vöhringer Harald S. , Sanderson Theo , Sinnott Matthew , Maio Nicola De , Nguyen Thuy , Goater Richard , Schwach Frank , Harrison Ian , Hellewell Joel , Ariani Cristina , Gonçalves Sonia , Jackson David , Johnston Ian , Jung Alexander W. , Saint Callum , Sillitoe John , Suciu Maria , Goldman Nick , Panovska-Griffiths Jasmina ,   The Wellcome Sanger Institute Covid-19 Surveillance Team,   The COVID-19 Genomics UK (COG-UK) Consortium, Birney Ewan , Volz Erik , Funk Sebastian , Kwiatkowski Dominic , Chand Meera , Martincorena Inigo , Barrett Jeffrey C. , Gerstung Moritz 
Published: May 2021

AbstractThe evolution of the SARS-CoV-2 pandemic continuously produces new variants, which warrant timely epidemiological characterisation. Here we use the dense genomic surveillance generated by the COVID-19 Genomics UK Consortium to reconstruct the dynamics of 71 different lineages in each of 315 English local authorities between September 2020 and June 2021. This analysis reveals a series of sub-epidemics that peaked in the early autumn of 2020, followed by a jump in transmissibility of the B.1.1.7/Alpha lineage. Alpha grew when other lineages declined during the second national lockdown and regionally tiered restrictions between November and December 2020. A third more stringent national lockdown suppressed Alpha and eliminated nearly all other lineages in early 2021. However, a series of variants (mostly containing the spike E484K mutation) defied these trends and persisted at moderately increasing proportions. Accounting for sustained introductions, however, indicates that their transmissibility is unlikely to have exceeded that of Alpha. Finally, B.1.617.2/Delta was repeatedly introduced to England and grew rapidly in the early summer of 2021, constituting approximately 98% of sampled SARS-CoV-2 genomes on June 26.
Single-cell analysis of the epigenomic and transcriptional landscape of innate immunity to seasonal and adjuvanted pandemic influenza vaccination in humans
Authors: Wimmers Florian , Donato Michele , Kuo Alex , Ashuach Tal , Gupta Shakti , Li Chunfeng , Dvorak Mai , Foecke Mariko Hinton , Chang Sarah E. , De Jong Sanne E. , Maecker Holden T. , van der Most Robbert , Cheung Peggie , Cortese Mario , Hagan Thomas , Bosinger Steven E. , Davis Mark , Rouphael Nadine , Subramaniam Shankar , Yosef Nir , Utz Paul J. , Khatri Purvesh , Pulendran Bali 
Published: May 2021

AbstractEmerging evidence indicates a fundamental role for the epigenome in immunity. Here, we used a systems biology approach to map the epigenomic and transcriptional landscape of immunity to influenza vaccination in humans at the single-cell level. Vaccination against seasonal influenza resulted in persistently reduced H3K27ac in monocytes and myeloid dendritic cells, which was associated with impaired cytokine responses to TLR stimulation. Single cell ATAC-seq analysis of 120,305 single cells revealed an epigenomically distinct subcluster of monocytes with reduced chromatin accessibility at AP-1-targeted loci after vaccination. Similar effects were also observed in response to vaccination with the AS03-adjuvanted H5N1 pandemic influenza vaccine. However, this vaccine also stimulated persistently increased chromatin accessibility at loci targeted by interferon response factors (IRFs). This was associated with elevated expression of antiviral genes and type 1 IFN production and heightened resistance to infection with the heterologous viruses Zika and Dengue. These results demonstrate that influenza vaccines stimulate persistent epigenomic remodeling of the innate immune system. Notably, AS03-adjuvanted vaccination remodeled the epigenome of myeloid cells to confer heightened resistance against heterologous viruses, revealing its potentially unappreciated role as an epigenetic adjuvant.
The LeVe CPAP System for oxygen-efficient CPAP respiratory support: Development and pilot evaluation
Authors: Culmer P. , Birch W. Davis , Waters I. , Keeling A. , Osnes C. , Jones D. , de Boer G. , Hetherington R. , Ashton S. , Latham M. , Beacon T. , Royston T. , Miller R. , Littlejohns A. , Parmar J. , Lawton T. , Murdoch S. , Brettle D. , Musasizi R. , Nampiina G. , Namulema E. , Kapur N. 
Published: May 2021

AbstractBackgroundThe COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has placed a significant demand on healthcare providers (HCPs) to provide respiratory support for patients with moderate to severe symptoms. Continuous Positive Airway Pressure (CPAP) non-invasive ventilation can help patients with moderate symptoms to avoid the need for invasive ventilation in intensive care. However, existing CPAP systems can be complex (and thus expensive) or require high levels of oxygen, limiting their use in resource-stretched environments.Technical Development + TestingThe LeVe (“Light”) CPAP system was developed using principles of frugal innovation to produce a solution of low complexity and high resource efficiency. The LeVe system exploits the air flow dynamics of electric fan blowers which are inherently suited to delivery of positive pressure at appropriate flow rates for CPAP. Laboratory evaluation demonstrated that performance of the LeVe system was equivalent to other commercially available systems used to deliver CPAP.Pilot EvaluationThe LeVe CPAP system was tested to evaluate safety and acceptability in a group of ten healthy volunteers at Mengo Hospital in Kampala, Uganda. The study demonstrated that the system can be used safely without inducing hypoxia or hypercapnia and that its use was well tolerated by users, with no adverse events reported.ConclusionsCPAP ventilation systems provide an important treatment option for COVID-19 patients. To deliver this for the high patient numbers associated with the COVID-19 pandemic, healthcare providers require resource efficient solutions. We have shown that this can be achieved through frugal engineering of a CPAP ventilation system, in a system which is safe for use and well tolerated in healthy volunteers. This approach may also benefit other respiratory conditions which often go unaddressed in LMICs for want of context-appropriate technology.
Modellinggambiensehuman African trypanosomiasis infection in villages of the Democratic Republic of Congo using Kolmogorov forward equations
Authors: Davis Christopher N. , Keeling Matt J. , Rock Kat S. 
Published: May 2021

AbstractStochastic methods for modelling disease dynamics enables the direct computation of the probability of elimination of transmission (EOT). For the low-prevalence disease of human African trypanosomiasis (gHAT), we develop a new mechanistic model for gHAT infection that determines the full probability distribution of the gHAT infection using Kolmogorov forward equations. The methodology allows the analytical investigation of the probabilities of gHAT elimination in the spatially-connected villages of the Kwamouth and Mosango health zones of the Democratic Republic of Congo, and captures the uncertainty using exact methods. We predict that, if current active and passive screening continue at current levels, local elimination of infection will occur in 2029 for Mosango and after 2040 in Kwamouth, respectively. Our method provides a more realistic approach to scaling the probability of elimination of infection between single villages and much larger regions, and provides results comparable to established models without the requirement of detailed infection structure. The novel flexibility allows the interventions in the model to be implemented specific to each village, and this introduces the framework to consider the possible future strategies of test-and-treat or direct treatment of individuals living in villages where cases have been found, using a new drug.
COVID-19 mass testing: harnessing the power of wastewater epidemiology
Authors: Fitzgerald Stephen F. , Rossi Gianluigi , Low Alison S. , McAteer Sean P. , O’Keefe Brian , Findlay David , Cameron Graeme J. , Pollard Peter , Singleton Peter T. R. , Ponton George , Singer Andrew C. , Farkas Kata , Jones Davey , Graham David W , Quintela-Baluja Marcos , Tait-Burkard Christine , Gally David L. , Kao Rowland , Corbishley Alexander 
Published: May 2021

SummaryBackgroundCOVID-19 patients shed SARS-CoV-2 RNA in their faeces. We hypothesised that detection of SARS-CoV-2 RNA in wastewater treatment plant (WWTP) influent could be a valuable tool to assist in public health decision making. We aimed to rapidly develop and validate a scalable methodology for the detection of SARS-CoV-2 RNA in wastewater that could be implemented at a national level and to determine the relationship between the wastewater signal and COVID-19 cases in the community.MethodsWe developed a filtration-based methodology for the concentration of SARS-CoV-2 from WWTP influent and subsequent detection and quantification by RT-qPCR. This methodology was used to monitor 28 WWTPs across Scotland, serving 50% of the population. For each WWTP catchment area, we collected data describing COVID-19 cases and deaths. We quantified spatial and temporal relationships between SARS-CoV-2 RNA in wastewater and COVID-19 cases.FindingsDaily WWTP SARS-CoV-2 influent viral RNA load, calculated using daily influent flow rates, had the strongest correlation (ρ>0.9) with COVID-19 cases within a catchment. As the incidence of COVID-19 cases within a community increased, a linear relationship emerged between cases and influent viral RNA load. There were significant differences between WWTPs in their capacity to predict case numbers based on influent viral RNA load, with the limit of detection ranging from twenty-five cases for larger plants to a single case in smaller plants.InterpretationThe levels of SARS-CoV-2 RNA in WWTP influent provide a cost-effective and unbiased measure of COVID-19 incidence within a community, indicating that national scale wastewater-based epidemiology can play a role in COVID-19 surveillance. In Scotland, wastewater testing has been expanded to cover 75% of the population, with sub-catchment sampling being used to focus surge testing. SARS-CoV-2 variant detection, assessment of vaccination on community transmission and surveillance for other infectious diseases represent promising future applications.FundingThis study was funded by project grants from the Scottish Government via the Centre of Expertise for Waters (CD2019/06) and The Natural Environment Research Council’s COVID-19 Rapid Response grants (NE/V010441/1). The Roslin Institute receives strategic funding from the Biotechnology and Biological Sciences Research Council (BB/P013740/1, BBS/E/D/20002173). Sample collection and supplementary analysis was funded and undertaken by Scottish Water and the majority of the sample analysis was funded and undertaken by the Scottish Environment Protection Agency.
Methylation-derived Inflammatory Measures and Lung Cancer Risk and Survival
Authors: Zhao Naisi , Ruan Mengyuan , Koestler Devin C. , Lu Jiayun , Kelsey Karl T. , Platz Elizabeth A. , Michaud Dominique S. 
Published: May 2021

ABSTRACTBackgroundExamining inflammation-related DNA methylation alterations in blood could help elucidate the role of inflammation in lung cancer etiology and aid discovery of factors that are key to lung cancer development and progression. In a nested case-control study, we estimated the neutrophil-to-lymphocyte ratio using a validated index, methylation-derived NLR (mdNLR), and quantified DNA methylation levels at loci previously linked with circulating concentrations of C-reactive protein (CRP). We examined associations between these measures and lung cancer risk, and among the cases, lung cancer survival, using pre-diagnostic blood samples of cases (median of 14 years before diagnosis) and controls in the CLUE I/II cohorts. Our analyses controlled for self-reported smoking and methylation-predicted cumulative smoking in order to better focus our examinations on the DNA methylation marks that are informative of the immune response profile.ResultsUsing conditional logistic regression and further adjusting for BMI, batch effects, and a smoking-based methylation score, we observed a 47% increased risk of non-small cell lung cancer (NSCLC) for one standard deviation increase in mdNLR (n = 150 pairs; OR: 1.47 [1.08, 2.02]) and found the estimated CRP Scores to be inversely associated with risk of NSCLC risk after additionally adjusting for methylation-predicted pack-years (n = 150 pairs; Score 1 OR: 0.57 [0.40, 0.81]; Score 2 OR: 0.62 [0.45, 0.84]; Score 3 OR: 0.65 [0.44, 0.95]). Using Cox proportional-hazards models and adjusting age, sex, smoking status, methylation-predicted pack-years, BMI, batch effect, and stage, we observed a 27% increased risk of dying from lung cancer for one standard deviation increase in mdNLR (n = 145 deaths in 205 cases; HR: 1.27 [1.08, 1.50]). A 50% increased risk of dying from lung cancer for one standard deviation increase in mdNLR was observed for NSCLC cases (n = 103 deaths in 149 cases; HR: 1.50 [1.19, 1.89]).ConclusionsA better understanding of inflammation-associated methylation-based biomarkers in lung cancer development could provide insight into critical pathways that may help identify new markers of early disease and survival.
Neurotrophin signaling is modulated by specific transmembrane domain interactions
Authors: Franco María L. , Nadezhdin Kirill D. , Light Taylor P. , Goncharuk Sergey A. , Soler-Lopez Andrea , Ahmed Fozia , Mineev Konstantin S. , Hristova Kalina , Arseniev Alexander S. , Vilar Marçal 
Published: May 2021

AbstractThe neurotrophin receptors p75 and TrkA play an important role in the development and survival of the nervous system. Biochemical data suggest that p75 and TrkA regulate the activities of each other. For instance, p75 is able to regulate the response of TrkA to lower concentrations of NGF and TrkA promotes p75 shedding by α-secretases in a ligand-dependent manner. The current model is that p75 and TrkA are regulated by means of a physical direct interaction, however the nature of such interaction has been elusive so far. Here using NMR in micelles, multiscale molecular dynamics (MD), FRET and functional studies we identified and characterized the direct interaction between TrkA and p75 through the transmembrane domains (TMDs). MD of p75-TMD mutants suggests that although the interaction between TrkA and p75 TMDs is maintained, a specific protein interface is required to facilitate TrkA active homodimerization in the presence of NGF. The same mutations in the TMD protein interface of p75 reduced the activation of TrkA by NGF and cell differentiation. In summary we provide a structural model of the p75/TrkA receptor complex stabilized by transmembrane domain interactions.
Pollinator habitat plantings benefit wild, native bees, but do not necessarily favor rare species
Authors: Cariveau Daniel P. , Roswell Michael , Harrison Tina , Genung Mark , Gibbs Jason , Winfree Rachael 
Published: May 2021

ABSTRACTInstalling pollinator habitat is a ubiquitous conservation tool, but little is known about which pollinator taxa require support, or which benefit from habitat installations.We studied the response of rare and common bees to pollinator habitat enhancement. We used independent regional datasets to designate bee species as common or rare based on their rank according to one of three metrics: a) site occurrence frequency, b) local relative abundance, and c) geographic range size. We asked whether the abundance or richness of rare and common bees were greater in pollinator habitat, relative to old-field controls. Because we used an arbitrary, quantile-based cutoff to categorize species rarity, we conducted sensitivity analysis and controlled for rarity classification errors with a null model. With this null model, we determined whether rare and/or common species responded to pollinator habitat disproportionately, compared to the expectation for ‘typical’ bee species.We found that the number of individuals and of species designated as rare based on local relative abundance was greater in pollinator habitat enhancements. The number of individuals from bee species designated as rare based on site occurrence was lower in pollinator habitat enhancements, but the number of species was not clearly different between habitat types. We did not find a clear positive nor negative effect of habitat enhancement for species designated rare based on geographic range size. For all three rarity metrics, common species increased in abundance and richness in pollinator habitat relative to controls. Null models indicated that in most cases, neither rare nor common species disproportionately benefited from pollinator habitat.Synthesis and Applications:Our results suggest that pollinator habitat can lead to an increase in the abundance and richness of bees, including species that are rare and that are common. However, rare species appeared to respond differently than typical species, and depending on how species were classified as rare, could display muted or even negative responses to habitat enhancement. Targeting rare species with specific floral resources or unique habitat types may lead to better outcomes for rare and threatened species.
Fast raster-scan optoacoustic mesoscopy enables assessment of human melanoma microvasculature in vivo
Authors: He Hailong , Schönmann Christine , Schwarz Mathias , Hindelang Benedikt , Bereznhoi Andrei , Steimle-Grauer Annette , Darsow Ulf , Aguirre Juan , Ntziachristos Vasilis 
Published: May 2021

AbstractThe development and progression of melanoma tumors is associated with angiogenesis, manifesting as changes in vessel density, morphology, and architecture that may extend through the entire skin depth. Three-dimensional imaging of vascular characteristics in skin lesions could allow diagnostic insights not available to the conventional visual inspection. Raster-scan optoacoustic mesoscopy (RSOM) has emerged as a unique modality to image microvasculature through the entire skin depth with resolutions of tens of micrometers, offering new possibilities to assess angiogenetic processes. However, current RSOM implementations are slow, exacerbating motion artifacts and reducing image quality, particularly when imaging melanoma lesions that often appear on the upper torso where breathing motion is strongest. To visualize for the first time melanoma vasculature in humans, in high-resolution, we accelerated RSOM scanning using an illumination scheme that is co-axial with a high-sensitivity ultrasound detector path, yielding 15 second single-breath-hold scans that minimize motion artifacts. Applied to 10 melanomas and 10 benign nevi in humans, we demonstrate visualization of microvasculature with performance never before shown in vivo. We show marked differences between malignant and benign lesions, supporting the possibility to use vasculature as a biomarker for lesion characterization. The study points to promising clinical potential for Fast-RSOM (FRSOM) as a three dimensional visualization method that can enable the complete assessment of microvascular parameters of melanoma and improve diagnostics.