bluuebunny/crossref_metadata_2025_split huggingface dataset:
Explicit expression of mesophyll conductance in the traditional leaf photosynthesis–transpiration coupled model and its physiological significances
Authors: Luo Hong , Carriquí Marc , Nadal Miquel , Han Tuo , Werner Christiane , Huang Jian-feng , Zhang Jiao-lin , Yu Zhi-guo , Li Feng-min , Fang Xiang-wen , Xue Wei 
Published: September 2021

SummaryAlmost all terrestrial biosphere models (TBMs) still assume infinite mesophyll conductance (gm) to estimate photosynthesis and transpiration. This assumption has caused low accuracy of TBMs to predict leaf gas exchange under certain conditions.In this study, we developed a photosynthesis-transpiration coupled model that explicitly considers gm and designed an optimized parameterization solution through evaluating four different gm estimation methods in 19 C3 species at 31 experimental treatments.Results indicated that temperature responses of the maximum carboxylation rate (Fcmax) and the electron transport rate (Jmax) estimated by fusing the Bayesian retrieval algorithm and the Sharkey online calculator together with gm temperature response estimated by fusing the chlorophyll fluorescence-gas exchange method and anatomy method predicted leaf gas exchange more accurately. The gm temperature response exhibited activation energy (ΔHa) of 63.13 ± 36.89 kJ mol-1 and entropy (ΔS) of 654.49 ± 11.36 J K-1 mol-1. The gm optimal temperature (Topt_gm) explained 58% of variations in photosynthesis optimal temperature (ToptA). The gm explicit expression has equally important effects on photosynthesis and transpiration estimations.Results advanced understandings of better representation of plant photosynthesis and transpiration in TBMs.
Altered synaptic connectivity in anin vitrohuman model of STXBP1 encephalopathy
Authors: McLeod Faye , Dimtsi Anna , Lewis-Smith David , Thomas Rhys , Clowry Gavin J , Trevelyan Andrew J 
Published: September 2021

AbstractEarly infantile developmental and epileptic encephalopathies are devastating conditions, generally of genetic origin, but the pathological mechanisms often remain obscure. A major obstacle in this field of research is the difficulty of studying cortical brain development in humans,in utero. To address this, we established anin vitroassay to study the impact of gene variants on the developing human brain, using living organotypic cultures of the human subplate and neighbouring cortical regions, prepared from ethically sourced, 14-17 post conception week brain tissue (www.hdbr.org). We were able to maintain cultures for several months, during which time, the gross anatomical structures of the cortical plate, subplate and marginal zone persisted, while neurons continued to develop morphologically, and form new synaptic networks. This preparation thus permits the study of genetic manipulations, and their downstream effects upon an intact developing human cortical network. We focused upon STXBP1 haploinsufficiency, which is among the most common genetic causes of developmental and epileptic encephalopathy. This was induced using shRNA interference, leading to impaired synaptic function and a drop in the number of glutamatergic synapses. We thereby provide a critical proof-of-principle for how to study the impact of any gene of interest on the development of the human cortex.
The impact of genetic risk for Alzheimer’s disease on the structural brain networks of young adults
Authors: Mirza-Davies Anastasia , Foley Sonya , Caseras Xavier , Baker Emily , Holmans Peter , Escott-Price Valentina , Jones Derek K. , Harrison Judith R. , Messaritaki Eirini 
Published: September 2021

AbstractWe investigated the structural brain networks of 562 young adults in relation to polygenic risk for Alzheimer’s disease, using magnetic resonance imaging (MRI) and genotype data from the Avon Longitudinal Study of Parents and Children. Diffusion MRI data were used to perform whole-brain tractography and to generate structural brain networks for the whole-brain connectome, and for the default mode, limbic and visual subnetworks. The mean clustering coefficient, mean betweenness centrality, characteristic path length, global efficiency and mean nodal strength were calculated for these networks, for each participant. The connectivity of the rich-club, feeder and local connections was also calculated. Polygenic risk scores (PRS), estimating each participant’s genetic risk, were calculated at genome-wide level and for nine specific disease pathways. Correlations were calculated between the PRS and a) the graph theoretical metrics of the structural networks and b) the rich-club, feeder and local connectivity of the whole-brain networks.In the visual subnetwork, the mean nodal strength was negatively correlated with the genomewide PRS (r=−0.19, p=1.3×10−5), the mean betweenness centrality was positively correlated with the plasma lipoprotein particle assembly PRS (r=0.16, p=9.2×10−4), and the mean clustering coefficient was negatively correlated with the tau protein binding PRS (r=−0.16, p=9.2×10−4). In the default mode network, the mean nodal strength was negatively correlated with the genomewide PRS (r=−0.14, p=1.5×10−3). The rich-club and feeder connectivities were negatively correlated with the genome-wide PRS (r=−0.16, p=3.7×10−4; r=−0.15, p=8.8×10−4). Our results indicate small reductions in brain connectivity in young adults at risk of developing Alzheimer’s disease in later life.
Integrated phylogenomics and fossil data illuminate the evolution of beetles
Authors: Cai Chenyang , Tihelka Erik , Giacomelli Mattia , Lawrence John F. , Ślipiński Adam , Kundrata Robin , Yamamoto Shûhei , Thayer Margaret K. , Newton Alfred F. , Leschen Richard A. B. , Gimmel Matthew L. , Lü Liang , Engel Michael S. , Huang Diying , Pisani Davide , Donoghue Philip C.J. 
Published: September 2021

AbstractWith over 380,000 described species and possibly several million more yet unnamed, beetles represent the most biodiverse animal order. Recent phylogenomic studies have arrived at considerably incongruent topologies and widely varying estimates of divergence dates for major beetle clades. Here we use a dataset of 68 single-copy nuclear protein coding genes sampling 129 out of the 194 recognized extant families as well as the first comprehensive set of fully-justified fossil calibrations to recover a refined timescale of beetle evolution. Using phylogenetic methods that counter the effects of compositional and rate heterogeneity we recover a topology congruent with morphological studies, which we use, combined with other recent phylogenomic studies, to propose several formal changes in the classification of Coleoptera: Scirtiformia and Scirtoideasensu nov., Clambiformiaser. nov.and Clamboideasensu nov., Rhinorhipiformiaser. nov., Byrrhoideasensu nov., Dryopoideastat. res., Nosodendriformiaser. nov., and Staphyliniformiasensu nov., alongside changes below the superfamily level. The heterogeneous former superfamily Cucujoidea is divided into three monophyletic groups: Erotyloideastat. nov., Nitiduloideastat. nov., and Cucujoideasensu nov.Our divergence time analysis recovered an evolutionary timescale congruent with the fossil record: a late Carboniferous origin of Coleoptera, a late Paleozoic origin of all modern beetle suborders, and a Triassic–Jurassic origin of most extant families. While fundamental divergences within beetle phylogeny did not coincide with the hypothesis of a Cretaceous Terrestrial Revolution, many polyphagan superfamilies exhibited increases in richness with Cretaceous flowering plants.
IgMAT: immunoglobulin sequence multi-species annotation tool for any species including those with incomplete antibody annotation or unusual characteristics
Authors: Dorey-Robinson Daniel , Maccari Giuseppe , Borne Richard , Hammond John A. 
Published: September 2021

AbstractThe advent and continual improvement of high-throughput sequencing technologies has made immunoglobulin repertoire sequencing accessible and informative regardless of study species. However, to fully map changes in polyclonal dynamics, precise annotation of these constantly rearranging genes is pivotal. For this reason, data agnostic tools able to learn from presented data are required. Most sequence annotation tools are designed primarily for use with human and mouse antibody sequences which use databases with fixed species lists, applying very specific assumptions which select against unique structural characteristics. We present IgMAT, which utilises a reduced amino acid alphabet, incorporates multiple HMM alignments into a single consensus and enables the incorporation of user defined databases to better represent their species of interest.Availability and implementationIgMAT has been developed as a python module, and is available on GitHub (https://github.com/TPI-Immunogenetics/igmat) for download under GPLv3 license.Supplementary informationModel Breakdowns
Oscillatory calcium release and sustained store-operated oscillatory calcium signaling prevents differentiation of human oligodendrocyte progenitor cells
Authors: Seidman Richard A. , Khattab Heba , Polanco Jessie J. , Broome Jacqueline E. , Sim Fraser J. 
Published: September 2021

ABSTRACTEndogenous remyelination in demyelinating diseases such as multiple sclerosis is contingent upon the successful differentiation of oligodendrocyte progenitor cells (OPCs). Signaling via the Gαq-coupled muscarinic receptor (M1/3R) inhibits human OPC differentiation and impairs endogenous remyelination in experimental models. We hypothesized that calcium release following Gαq-coupled receptor (GqR) activation directly regulates human OPC (hOPC) cell fate. In this study, we show that specific GqR agonists activating muscarinic and metabotropic glutamate receptors induce characteristic oscillatory calcium release in hOPCs and that these agonists similarly block hOPC maturation in vitro. Both agonists induce calcium release from endoplasmic reticulum (ER) stores and store operated calcium entry (SOCE) likely via STIM/ORAI-based channels. siRNA mediated knockdown (KD) of obligate calcium sensors STIM1 and STIM2 decreased the magnitude of muscarinic agonist induced oscillatory calcium release and attenuated SOCE in hOPCs. In addition, STIM2 expression was necessary to maintain the frequency of calcium oscillations and STIM2 KD reduced spontaneous OPC differentiation. Furthermore, STIM2 siRNA prevented the effects of muscarinic agonist treatment on OPC differentiation suggesting that SOCE is necessary for the anti-differentiative action of muscarinic receptor-dependent signaling. Finally, using a gain-of-function approach with an optogenetic STIM lentivirus, we demonstrate that independent activation of SOCE was sufficient to significantly block hOPC differentiation and this occurred in a frequency dependent manner while increasing hOPC proliferation. These findings suggest that intracellular calcium oscillations directly regulate hOPC fate and that modulation of calcium oscillation frequency may overcome inhibitory Gαq-coupled signaling that impairs myelin repair.Significance StatementIn this study, Seidman et al. show that SOCE is a common component of ligand-based Gαq-coupled signaling in hOPCs and that SOCE alone is sufficient to block hOPC differentiation and drive proliferation. Therefore, SOCE blocks differentiation and pathological SOCE could contribute to myelin disease.
Long- and short-term history effects in a spiking network model of statistical learning
Authors: Maes Amadeus , Barahona Mauricio , Clopath Claudia 
Published: September 2021

ABSTRACTThe statistical structure of the environment is often important when making decisions. There are multiple theories of how the brain represents statistical structure. One such theory states that neural activity spontaneously samples from probability distributions. In other words, the network spends more time in states which encode high-probability stimuli. Existing spiking network models implementing sampling lack the ability to learn the statistical structure from observed stimuli and instead often hard-code a dynamics. Here, we focus on how arbitrary prior knowledge about the external world can both be learned and spontaneously recollected. We present a model based upon learning the inverse of the cumulative distribution function. Learning is entirely unsupervised using biophysical neurons and biologically plausible learning rules. We show how this prior knowledge can then be accessed to compute expectations and signal surprise in downstream networks. Sensory history effects emerge from the model as a consequence of ongoing learning.
Idiosyncratic epistasis leads to global fitness-correlated trends
Authors: Bakerlee Christopher W. , Nguyen Ba Alex N. , Shulgina Yekaterina , Rojas Echenique Jose I. , Desai Michael M. 
Published: September 2021

AbstractEpistasis can dramatically affect evolutionary trajectories. In recent decades, protein-level fitness landscapes have revealed extensive idiosyncratic epistasis among specific mutations. In contrast, other work has found ubiquitous and apparently non-specific patterns of global diminishing-returns and increasing-costs epistasis among mutations across the genome. Here, we use a hierarchical CRISPR gene drive system to construct all combinations of 10 missense mutations from across the genome in budding yeast, and measure their fitness in six environments. We show that the resulting fitness landscapes exhibit global fitness-correlated trends, but that these trends emerge from specific idiosyncratic interactions. This provides the first experimental validation of recent theoretical work that has argued that fitness-correlated trends can emerge as the generic consequence of idiosyncratic epistasis.One-Sentence SummaryA genome-spanning fitness landscape reveals how idiosyncratic genetic interactions lead to global epistatic patterns.
DcPAR1 is Required for Development and Carotenoid Synthesis in the Dark-Grown Carrot Taproot
Authors: Arias Daniela , Ortega Angélica , González Christian , Quiroz Luis Felipe , Moreno-Romero Jordi , Martínez-García Jaime F. , Stange Claudia 
Published: September 2021

AbstractLight stimulates carotenoid synthesis in plants during photomorphogenesis through the expression of PHYTOENE SYNTHASE (PSY), a key gene in carotenoid biosynthesis. The orange Daucus carota (carrot) synthesizes and accumulates high amounts of carotenoids in the taproot that grows underground. Contrary to other organs, light impairs carrot taproot development and represses the expression of carotenogenic genes such as DcPSY1 and DcPSY2 reducing carotenoid accumulation. By means of an RNA-seq, in previous analysis we observed that carrot PHYTOCHROME RAPIDLY REGULATED 1 (DcPAR1) is more expressed in the underground grown taproot respect to those grown in light. PAR1 is a transcriptional cofactor with a negative role in the shade avoidance syndrome regulation in Arabidopsis thaliana through the dimerization with PHYTOCHROME INTERACTING FACTORs (PIFs), allowing a moderate synthesis of carotenoids. Here we show that overexpressing AtPAR1 in carrot produces an increment of carotenoids in taproots grown underground as well as higher DcPSY1 expression. The high identity of AtPAR1 and DcPAR1 let us to suggest a functional role of DcPAR1 that was verified through the in vivo binding to AtPIF7 and the overexpression in Arabidopsis, where it increments AtPSY expression and carotenoid accumulation together with a photomorphogenic phenotype. Finally, DcPAR1 antisense carrot lines presented a dramatic decrease in carotenoids levels and in the relative expression of key carotenogenic genes as well as impairment in taproot development. These results let us to propose that DcPAR1 is a key factor for secondary root development, plastid differentiation and carotenoid synthesis in carrot taproot grown underground.One-sentence summaryDcPAR1 is a key factor for secondary root development, plastid differentiation and carotenoid synthesis in carrot taproot grown underground.
Prescribed versus wildfire impacts on exotic plants and soil microbes in California grasslands
Authors: Glassman Sydney I , Randolph James WJ , Saroa Sameer S , Capocchi Joia K , Walters Kendra E , Pulido-Chavez M. Fabiola , Larios Loralee 
Published: September 2021

AbstractPrescribed fire is often used as a management tool to decrease exotic plant cover and increase native plant cover in grasslands. These changes may also be mediated by fire impacts on soil microbial communities, which drive plant productivity and function. Yet, the ecological effects of prescribed burns compared to wildfires on either plant or soil microbial composition remain unclear.Here, we investigated the impacts of a spring prescribed fire versus a fall wildfire on plant cover and community composition and bacterial and fungal richness, abundance, and composition in a California grassland. We used qPCR of 16S and 18S to assess impacts on bacterial and fungal abundance and Illumina MiSeq of 16S and ITS2 to assess impacts on bacterial and fungal richness and composition.Wildfire had stronger impacts than prescribed fire on microbial communities and both fires had similar impacts on plants with both prescribed and wildfire reducing exotic plant cover but neither reducing exotic plant richness. Fungal richness declined after the wildfire but not prescribed fire, but bacterial richness was unaffected by either. Yet increasing char levels in both fire types resulted in reduced bacterial and fungal biomass, and both fire types slightly altered bacterial and fungal composition.Exotic and native plant diversity differentially affected soil microbial diversity, with native plant diversity leading to increased arbuscular mycorrhizal fungal richness while exotic plant diversity better predicted bacterial richness. However, the remainder of the soil microbial communities were more related to aspects of soil chemistry including cation exchange capacity, organic matter, pH and phosphorous.Synthesis and applications. Understanding the different ecological effects of prescribed fires and wildfires on plant and soil communities are key to enhancing a prevalent management action and to guide potential management opportunities post wildfires. Our coupled plant and soil community sampling allowed us to capture the sensitivity of the fungal community to fire and highlights the importance of potentially incorporating management actions such as soil or fungal amendments to promote this critical community that mediates native plant performance.
Fitting the Reproduction number from UK coronavirus case data, and why it is close to 1
Authors: Ackland Graeme J , Ackland James A , Antonioletti Mario , Wallace David J. 
Published: September 2021

AbstractWe present a method for rapid calculation of coronavirus growth rates and R-numbers tailored to the publicly available data in the UK. The R-number is derived from time-series of case data, using bespoke data processing to remove systematic and errors and stochastic fluctuations. In principle, growth rate can be obtained by differentiating the reported case numbers, but in fact daily stochastic fluctuations disqualify this method. We therefore assume that the case data comprises a smooth, underlying trend which is differentiable and a noise term. The approach produces, up-to-date estimates of the R-number throughout the period of data availability. Our method is validated against published consensus R-numbers from the UK government, and shown to produce comparable results. A significant advantage of our method is that it is stable up to the most recent data, this enables us to make R-number estimates available over two weeks ahead of the published consensus. The short-lived peaks observed in the R-number and case data cannot be explained by a well-mixed model and are suggestive of spread on a localised network. Such a localised spread model tends to give an Rt number close to 1, regardless of how large R0 is. The case-driven approach is combined with Weight-Shift-Scale (WSS) methods to monitor trends in the epidemic and for medium term predictions. Using case-fatality ratios, we create a narrative for trends in the UK epidemic increased infectiousness of the alpha and delta variants, and the effectiveness of vaccination in reducing severity of infection.
Tracking the temporal variation of COVID-19 surges through wastewater-based epidemiology during the peak of the pandemic: a six-month long study in Charlotte, North Carolina
Authors: Barua Visva Bharati , Islam Juel Md Ariful , Blackwood A. Denene , Clerkin Thomas , Ciesielski Mark , Sorinolu Adeola Julian , Holcomb David A. , Young Isaiah , Kimble Gina , Sypolt Shannon , Engel Lawrence S. , Noble Rachel T. , Munir Mariya 
Published: September 2021

ABSTRACTThe global spread of SARS-CoV-2 has continued to be a serious concern after WHO declared the virus the causative agent of the coronavirus disease 2019 (COVID-19) a global pandemic. Monitoring of wastewater is a useful tool for assessing community prevalence given that fecal shedding of SARS-CoV-2 occurs in high concentrations by infected individuals, regardless of whether they are asymptomatic or symptomatic. Using tools that are part of the wastewater-based epidemiology (WBE) approach, combined with molecular analyses, wastewater monitoring becomes a key piece of information used to assess trends and quantify the scale and dynamics of COVID-19 infection in a specific community, municipality, or area of service. This study investigates a six-month long SARS-CoV-2 RNA quantification in influent wastewater from four municipal wastewater treatment plants (WWTP) serving the Charlotte region of North Carolina (NC) using both RT-qPCR and RT-ddPCR platforms. Influent wastewater was analyzed for the nucleocapsid (N) genes N1 and N2. Both RT-qPCR and RT-ddPCR performed well for detection and quantification of SARS-CoV-2 using the N1 target, while for the N2 target RT-ddPCR was more sensitive. SARS-CoV-2 concentration ranged from 103 to105 copies/L for all four plants. Both RT-qPCR and RT-ddPCR showed a significant moderate to a strong positive correlation between SARS-CoV-2 concentrations and the 7-day rolling average of clinically reported COVID-19 cases using a lag that ranged from 7 to 12 days. A major finding of this study is that despite small differences, both RT-qPCR and RT-ddPCR performed well for tracking the SARS-CoV-2 virus across WWTP of a range of sizes and metropolitan service functions.