bluuebunny/crossref_metadata_2025_split huggingface dataset:
Association between PM2.5 air pollution, temperature, and sunlight during different infectious stages with the case fatality of COVID-19 in the United Kingdom: a modeling study
Authors: Hossain M. Pear , Zhou Wen , Leung Marco Y. T. , Yuan Hsiang-Yu 
Published: April 2023

AbstractAlthough the relationship between the environmental factors such as weather conditions and air pollution and COVID-19 case fatality rate (CFR) has been found, the impacts of these factors to which infected cases are exposed at different infectious stages (e.g., virus exposure time, incubation period, and at or after symptom onset) are still unknown. Understanding this link can help reduce mortality rates. During the first wave of COVID-19 in the United Kingdom (UK), the CFR varied widely between and among the four countries of the UK, allowing such differential impacts to be assessed.We developed a generalized linear mixed-effect model combined with distributed lag nonlinear models to estimate the odds ratio of the weather factors (i.e., temperature, sunlight, relative humidity, and rainfall) and air pollution (i.e., ozone,NO2,SO2,CO, PM10andPM2.5) using data between March 26, 2020 and May 12, 2020 in the UK. After retrospectively time adjusted CFR was estimated using back-projection technique, the stepwise model selection method was used to choose the best model based on Akaike information criteria (AIC) and the closeness between the predicted and observed values of CFR.We found that the low temperature (8-11°C), prolonged sunlight duration (11-13hours) and increasedPM2.5(11-18μg/m3) after the incubation period posed a greater risk of death (measured by odds ratio (OR)) than the earlier infectious stages. The risk reached its maximum level when the low temperature occurred one day after (OR = 1.76; 95% CI: 1.10-2.81), prolonged sunlight duration 2-3 days after (OR = 1.50; 95% CI: 1.03-2.18) and increasedP.M2.5at the onset of symptom (OR =1.72; 95% CI: 1.30-2.26). In contrast, prolonged sunlight duration showed a protective effect during the incubation period or earlier.After reopening, many COVID-19 cases will be identified after their symptoms appear. The findings highlight the importance of designing different preventive measures against severe illness or death considering the time before and after symptom onset.
A resampling-based approach to share reference panels
Authors: Cavinato Théo , Rubinacci Simone , Malaspinas Anna-Sapfo , Delaneau Olivier 
Published: April 2023

AbstractFor many genome-wide association studies, imputing genotypes from a haplotype reference panel is a necessary step. Over the past 15 years, reference panels have become larger and more diverse, leading to improvements in imputation accuracy. However, the latest generation of reference panels is subject to restrictions on data sharing due to concerns about privacy, limiting their usefulness for genotype imputation. In this context, we propose RESHAPE, a method that employs a recombination Poisson process on a reference panel to simulate the genomes of hypothetical descendants after multiple generations. This data transformation helps to protect against re-identification threats and preserves important data attributes, such as linkage disequilibrium (LD) patterns and, to some degree, Identity-By-Descent (IBD) sharing, allowing for genotype imputation. Our experiments on gold standard datasets show that simulated descendants up to eight generations can serve as reference panels without significantly reducing genotype imputation accuracy. We suggest that this specific type of data anonymization could be used to generate synthetic reference panels available under less restrictive data sharing policies.
SARS-CoV-2’s evolutionary capacity is mostly driven by host antiviral molecules
Authors: Lamb Kieran D. , Luka Martha M. , Saathoff Megan , Orton Richard , Phan My , Cotten Matthew , Yuan Ke , Robertson David L. 
Published: April 2023

AbstractThe COVID-19 pandemic has been characterised by sequential variant-specific waves shaped by viral, individual human and population factors. SARS-CoV-2 variants are defined by their unique combinations of mutations and there has been a clear adaptation to human infection since its emergence in 2019. Here we use machine learning models to identify shared signatures, i.e., common underlying mutational processes, and link these to the subset of mutations that define the variants of concern (VOCs). First, we examined the global SARS-CoV-2 genomes and associated metadata to determine how viral properties and public health measures have influenced the magnitude of waves, as measured by the number of infection cases, in different geographic locations using regression models. This analysis showed that, as expected, both public health measures and not virus properties alone are associated with the rise and fall of regional SARS-CoV-2 reported infection numbers. This impact varies geographically. We attribute this to intrinsic differences such as vaccine coverage, testing and sequencing capacity, and the effectiveness of government stringency. In terms of underlying evolutionary change, we used non-negative matrix factorisation to observe three distinct mutational signatures, unique in their substitution patterns and exposures from the SARS-CoV-2 genomes. Signatures 0, 1 and 3 were biased to C→T, T→C/A→G and G→T point mutations as would be expected of host antiviral molecules APOBEC, ADAR and ROS effects, respectively. We also observe a shift amidst the pandemic in relative mutational signature activity from predominantly APOBEC-like changes to an increasingly high proportion of changes consistent with ADAR editing. This could represent changes in how the virus and the host immune response interact, and indicates how SARS-CoV-2 may continue to accumulate mutations in the future. Linkage of the detected mutational signatures to the VOC defining amino acids substitutions indicates the majority of SARS-CoV-2’s evolutionary capacity is likely to be associated with the action of host antiviral molecules rather than virus replication errors.
Supplemental LED lighting improves plant growth without affecting biological control in a tri-trophic greenhouse system
Authors: Fraser Jessica L. , Abram Paul K. , Dorais Martine 
Published: April 2023

AbstractArtificial lighting, including light-emitting diode (LED) illumination, is increasingly being optimized in protected agricultural systems to maximize plant yield and quality. However, it may also cause other top-down and bottom-up effects in these relatively simple ecological communities that also include insect pests and their natural enemies. While some effects of LED lighting on insects have been demonstrated to date, it is not known how they influence biological control of insect pests in practice. To examine potential top-down and bottom-up impacts of LED illumination on greenhouse biological control with parasitoids, we studied the effects of artificially lengthened days on a tri-trophic system in cages and in a greenhouse. We grew plants under a 12-hour photoperiod of white-supplemented light with 6 hours of additional 1) white light or 2) red and blue light, or 3) with no additional light. We exposed the plants to the pest aphidMyzus persicae(Hemiptera : Aphididae) with or without its parasitoid waspAphidius matricariae(Hymenoptera : Braconidae), or to no insects. The 18-hour light treatments increased mean plant dry mass by 127% compared with the 12-hour control without affecting the aphid’s population density or the parasitoid’s biological control efficacy under relatively low light conditions. This suggests that insect communities in protected agriculture can be resilient to even drastic changes in their light environment, and that adjusting crop lighting in a manner that affects plant growth does not necessarily compromise biological control’s effectiveness.
Responses of globally important phytoplankton species to olivine dissolution products and implications for carbon dioxide removal via ocean alkalinity enhancement
Authors: Hutchins David A. , Fu Fei-Xue , Yang Shun-Chung , John Seth G. , Romaniello Stephen J. , Andrews M. Grace , Walworth Nathan G. 
Published: April 2023

AbstractAnthropogenic greenhouse gas emissions are leading to global temperature increases, ocean acidification, and significant ecosystem impacts. Given current emissions trajectories, the IPCC reports indicate that rapid abatement of CO2emissions and development of carbon dioxide removal (CDR) strategies are needed to address legacy and difficult to abate emissions sources. These CDR methods must efficiently and safely sequester gigatons of atmospheric CO2. Coastal Enhanced Weathering (CEW) via the addition of the common mineral olivine to coastal waters is one promising approach to enhance ocean alkalinity for large-scale CDR. As olivine weathers, it releases several biologically active dissolution products, including alkalinity, trace metals, and the nutrient silicate. Released trace metals can serve as micronutrients but may also be toxic at high concentrations to marine biota including phytoplankton that lie at the base of marine food webs. We grew six species representing several globally important phytoplankton species under elevated concentrations of olivine dissolution products via a synthetic olivine leachate (OL) based on olivine elemental composition. We monitored their physiological and biogeochemical responses, which allowed us to determine physiological impacts and thresholds at elevated olivine leachate concentrations, in addition to individual effects of specific constituents. We found both positive and neutral responses but no evident toxic effects for two silicifying diatoms, a calcifying coccolithophore, and three cyanobacteria. In both single and competitive co-cultures, silicifiers and calcifiers benefited from olivine dissolution products like iron and silicate or enhanced alkalinity, respectively. The non-N2-fixing picocyanobacterium could use synthetic olivine-derived iron for growth, while N2-fixing cyanobacteria could not. However, other trace metals like nickel and cobalt supported cyanobacterial growth across both groups. Growth benefits to phytoplankton groupsin situwill depend on species-specific responses and ambient concentrations of other required nutrients. Results suggest olivine dissolution products appear unlikely to cause negative physiological effects for any of the phytoplankton examined, even at high concentrations, and may support growth of particular taxa under some conditions. Future studies can shed light on long-term eco-evolutionary responses to olivine exposure and on the potential effects that marine microbes may in turn have on olivine dissolution rates and regional biogeochemistry.
Alpha and SSVEP power outperform Gamma power in capturing Attentional Modulation in Human EEG
Authors: Das Aritra , Nandi Nilanjana , Ray Supratim 
Published: April 2023

AbstractThe effect of visual attention has been extensively studied using various techniques such as macaque neurophysiology that yields spikes and local field potential (LFP), and human electro/magneto encephalogram (EEG/MEG). Attention typically suppresses power at low frequencies such as alpha band (8-12 Hz) and increases power in gamma band (>30 Hz) in brain signals. In addition, EEG studies often use flickering stimuli that produce a specific measure called steady-state visually evoked potential (SSVEP), whose power also increases with attention. However, effectiveness of these various neural measures in capturing attentional modulation is unknown since the stimuli and task paradigms vary widely across these studies. In a recent macaque neurophysiology study with flickering stimuli, we found that the effect of attention was more salient in the gamma band and beyond of the LFP, compared to alpha or SSVEP. To compare this with human EEG, we designed an orientation change detection task where we presented both static and counterphasing stimuli of matched difficulty levels to male (N=15) and female (N=11) subjects, allowing us to compare attentional modulation of various measures under similar conditions. We report two main results. First, attentional modulation was comparable for SSVEP and alpha. Second, non-foveal stimuli produced weak gamma despite various stimulus optimizations and showed a negligible effect of attention although full-screen gratings showed robust gamma activity. Our results are useful for brain-machine-interfacing studies where suitable features depending on recording modality are used for decoding attention, and also provide clues about the spatial scales of neural mechanisms underlying attention.Significance StatementVarious neural measures such as alpha and gamma band power or SSVEP power capture signatures of visual attention. A systematic comparison of their effectiveness in capturing attentional modulation is important for understanding different neural computations underlying attention and for developing brain-machine-interfaces (BMIs) that can decode the focus of attention. Since stimulus configuration and task paradigms vary widely across visual attention studies, we recorded all the relevant neural signals during an attention task under similar stimulus and behavioral conditions in human EEG. In contrast to invasive recordings in which gamma outperforms other measures, our results show that in human EEG, attentional modulation of alpha and SSVEP are comparable, and non-foveal stimuli produce weak gamma which is not well modulated by attention.
Dynamical BLUP modeling of reaction norm evolution, accommodating changing environments, overlapping generations, and multivariate data
Authors: Ergon Rolf 
Published: April 2023

AbstractFor theoretical studies, reaction norm evolution in a changing environment can be modeled by means of the multivariate breeder’s equation, with the reaction norm parameters treated as traits in their own right. This is, however, not a feasible approach for use of field data, where the intercept and slope values are not available. An alternative approach is to use infinite-dimensional characters and smooth covariance function estimates found by, i.e., random regression. This is difficult because of the need to find for example polynomial basis functions that fit the data reasonably well over time, and because reaction norms in multivariate cases are correlated, such that they cannot be modeled independently.Here, I present an alternative approach based on a multivariate linear mixed model of any order, with dynamical incidence and residual covariance matrices that reflect the changing environment. From such a mixed model follows a dynamical BLUP model for prediction of the individual reaction norm parameter values at any given parent generation, and for updating of the mean reaction norm parameter values from generation to generation by means of Robertson’s secondary theorem of natural selection. This will, e.g., make it possible to disentangle the microevolutionary and plasticity components in climate change responses. The BLUP model incorporates the additive genetic relationship matrix in the usual way, and overlapping generations can easily be accommodated.Parameters are assumed to be known and constant, but it is discussed how they can be estimated by means of a prediction error method. The identifiability by use of field or laboratory data containing environmental, phenotypic, fitness, and additive genetic relationship data, is an important feature of the proposed model.
Multi-scale Effects of Habitat Loss and the Role of Trait Variation
Authors: Bagawade Rishabh , van Benthem Koen J. , Wittmann Meike J. 
Published: April 2023

AbstractHabitat loss (HL) is a major cause of species extinctions. Although effects of HL beyond the directly impacted area have been previously observed, they are not very well understood, especially in an eco-evolutionary context. To start filling this gap, we study a two-patch deterministic consumer-resource model, with one of the patches experiencing loss of resources. Our model allows foraging and mating within a patch as well as between patches. We then introduce heritable variation in consumer traits to investigate eco-evolutionary dynamics and compare results with constant or no trait variation scenarios. Our results show that HL indeed reduces consumer densities in the neighboring patch, but when the resources are overexploited, HL in one patch can increase the consumer densities in the neighbouring patch. Yet at the landscape scale, the effect of HL on consumer densities is consistently negative. In presence of HL, patch isolation has positive effects on consumer density in the patch experiencing HL and mostly negative effects on the neighbouring patch. The landscape level pattern depends on which of these effects are dominant at the local scale. Evolution always increased resistance of consumers in the affected patch to HL, with varied effects at the landscape level. Finally, we also show a possibility of landscape level consumer extinction due to HL in a local patch when the cross-patch dependence is high, and foraging and mating preferences are coupled. Eco-evolutionary dynamics can rescue consumers from such extinction in some cases if their death rates are sufficiently small. Our findings show that HL at a local scale can affect the neighbouring patch and the landscape as a whole, and that heritable trait variation can provide some resistance against HL. We thus suggest joint consideration of multiple spatial scales and trait variation when assessing and predicting the impacts of HL.
Caenorhabditis elegansmodels for striated muscle disorders caused by missense variants of humanLMNA
Authors: Gregory Ellen F. , Kalra Shilpi , Brock Trisha , Bonne Gisèle , Luxton G.W. Gant , Hopkins Christopher , Starr Daniel A. 
Published: April 2023

AbstractStriated muscle laminopathies caused by missense mutations in the nuclear lamin geneLMNAare characterized by cardiac dysfunction and often skeletal muscle defects. Attempts to predict whichLMNAvariants are pathogenic and to understand their physiological effects lags behind variant discovery. We createdCaenorhabditis elegansmodels for striated muscle laminopathies by introducing pathogenic humanLMNAvariants and variants of unknown significance at conserved residues within thelmn-1gene. Severe missense variants reduced fertility and/or motility inC. elegans. Nuclear morphology defects were evident in the hypodermal nuclei of many lamin variant strains, indicating a loss of nuclear envelope integrity. Phenotypic severity varied within the two classes of missense mutations involved in striated muscle disease, but overall, variants associated with both skeletal and cardiac muscle defects in humans lead to more severe phenotypes in our model than variants predicted to disrupt cardiac function alone. We also identified a separation of function allele,lmn-1(R204W), that exhibited normal viability and swimming behavior but had a severe nuclear migration defect. Thus, we establishedC. elegansavatars for striated muscle laminopathies and identifiedLMNAvariants that offer insight into lamin mechanisms during normal development.Author summaryMuscular dystrophy is a progressive muscle-wasting disorder that eventually leads to cardiac disease. Mutations in theLMNAgene, which encodes an intermediate filament protein involved in the structure and organization of the nucleus, is a common but poorly understood cause of this disease. How variants across the breadth ofLMNAcontribute to mechanistic cellular defects that lead to disease is poorly understood, leading to hurdles in diagnosing disease and developing treatments. We found that by introducing amino acid substitutions found in patients with striated muscle disorders caused byLMNAinto the conservedlmn-1gene of the nematodeC. elegans, we could rapidly test the function of these variants to better understand their roles. We found that variants modeling diseases that involve both skeletal and cardiac muscle in humans were the most pathogenic inC. elegans, typically affecting both viability and movement, while those that modeled cardiac disease alone had less deleterious effects inC. elegans. Furthermore, we uncovered molecular mechanisms for how lamins interact with other nuclear envelope proteins to carry out their cellular functions. Thus, our newC. elegansmodels can be used to diagnose and predict the severity of new variants of humanLMNAas well as better understanding the molecular mechanisms of lamins in normal development.
Myelodysplastic syndromes disable support of human hematopoietic stem and progenitor cells by CD271, VCAM- 1 and CD146 expressing marrow niche cells
Authors: Kawano Yuko , Kawano Hiroki , Ghoneim Dalia , Fountaine Thomas J. , Byun Daniel K , LaMere Mark W. , Mendler Jason H. , Ho Tzu-Chieh , Salama Noah A. , Frisch Benjamin J. , Myers Jason R. , Hussein Siba El , Ashton John M. , Azadniv Mitra , Liesveld Jane L. , Kfoury Youmna , Scadden David T. , Becker Michael W. , Calvi Laura M. 
Published: April 2023

SUMMARYMesenchymal stem/stromal cells (MSCs) within the bone marrow microenvironment (BMME) support normal hematopoietic stem and progenitor cells (HSPCs). However, the heterogeneity of human MSCs has limited the understanding of their contribution to clonal dynamics and evolution to myelodysplastic syndromes (MDS). We combined three MSC cell surface markers, CD271, VCAM-1 (Vascular Cell Adhesion Molecule-1) and CD146, to isolate distinct subsets of human MSCs from bone marrow aspirates of healthy controls (Control BM). Based on transcriptional and functional analysis, CD271+CD106+CD146+(NGFR+/VCAM1+/MCAM+/Lin-;NVML) cells display stem cell characteristics, are compatible with murine BM- derived Leptin receptor positive MSCs and provide superior support for normal HSPCs. MSC subsets from 17 patients with MDS demonstrated shared transcriptional changes in spite of mutational heterogeneity in the MDS clones, with loss of preferential support of normal HSPCs by MDS-derived NVML cells. Our data provide a new approach to dissect microenvironment-dependent mechanisms regulating clonal dynamics and progression to MDS.
Adolescent morphine exposure impairs cognitive flexibility in female but not male mice
Authors: Wakhlu Aditii , Engelhardt Annabel , Anderson Eden M. , Grafelman Elaine , Ouimet Abbigail , Hearing Matthew C. 
Published: April 2023

AbstractUse of prescription opioids continues to rise, especially in adolescent individuals. As adolescence is a critical development window for higher order cognitive functions, thus opioid exposure during this period may have significant long-lasting effects on cognitive function and predisposition individuals to be at greater risk of developing opioid use later in life. Here, we examine previously explored effects of opioid exposure during adolescence on affect-related behavior, motivation, and cognitive flexibility. We find that a two-week exposure to non-contingent morphine during adolescence (i.e., post-weaning) does not alter performance in an elevated plus maze, forced swim test, or motivation for appetitive reward in male or female mice when tested during adolescence or adulthood. Examination of how adolescent morphine impacts cognition revealed impairments in visual-based discriminative learning and cognitive flexibility in female but not male mice, as assessed using an operant-based attentional set-shifting task. Unexpectedly, deficits in discriminative learning are observed when testing occurred during adolescence but not adulthood, whereas impaired performance in the extradimensional shift remained impaired into adulthood. The data indicate that opioid exposure during adolescence has a greater impact on cognitive function in female mice and that these deficits may be more widespread during acute withdrawal periods, while deficits in flexibility more enduring.