bluuebunny/crossref_metadata_2025_split huggingface dataset:
Revealing the evolutionary history of a reticulate polyploid complex in the genusIsoëtes
Authors: Suissa Jacob S. , Kinosian Sylvia P. , Schafran Peter W. , Bolin Jay F. , Taylor W. Carl , Zimmer Elizabeth A. 
Published: November 2020

SummaryPolyploidy and hybridization are important processes in the evolution of spore-dispersed plants. Few studies, however, focus these dynamics in heterosporous lycophytes, such asIsoëtes, where polyploid hybrids are common and thought to be important in the generation of their extant diversity. We investigate reticulate evolution in a complex of western North American quillworts (Isoëtes) and provide insights into the evolutionary history of hybrids, and the role of polyploidy in maintaining novel diversity.We utilize low copy nuclear markers, whole plastomes, restriction site-associated DNA sequencing, cytology, and reproductive status (fertile or sterile) to investigate the reticulate evolutionary history of western North AmericanIsoëtes.We reconstruct the reticulate evolutionary history and directionality of hybridization events in this complex. The presence of high level polyploids, plus frequent homoploid and interploid hybridization suggests that there are low prezygotic reproductive barriers in this complex, hybridization is common and bidirectional between similar—but not divergent—cytotypes, and that allopolyploidization is important to restore fertility in some hybrid taxa.Our data provide five lines of evidence suggesting that hybridization and polyploidy can occur with frequency in the genus, and these evolutionary processes may be important in shaping extantIsoëtesdiversity.
Cannabidiol Attenuates Pulmonary Arterial Hypertension by Normalizing the Mitochondrial Function in Vascular Smooth Muscle Cells
Authors: Lu Xiaohui , Zhang Jingyuan , Liu Huijiao , Ma Wenqiang , Yu Leo , Tan Xin , Wang Shubin , Ren Fazheng , Li Xiru , Li Xiangdong 
Published: November 2020

AbstractPulmonary artery hypertension (PAH) is a chronic disease associated with enhanced proliferation of pulmonary artery smooth muscle cells (PASMCs) and dysfunctional mitochondria, which was with limited therapeutic options. It has been proved that cannabidiol (CBD) had antioxidant effects in many cardiovascular diseases, whereas the efficacy of CBD in PAH is unknown. To defined the effect of CBD in PAH, we explored the functions of CBD in both PASMCs proliferation test in vitro, and preventive and therapeutic PAH rodent models in vivo. The roles of CBD in mitochondria function and the oxidant stress were assessed in human PASMCs and PAH mice. We found that CBD significantly inhibited hyperproliferation of hypoxia-induced PASMCs, and intragastrically administered CBD could reverse the pathological changes in both Sugen-hypoxia and MCT-induced PAH mice models. Mechanical analysis demonstrated that CBD alleviated PAH by recovering mitochondrial energy metabolism, normalizing the hypoxia-induced oxidant stress, inhibiting abnormal glycolysis and lactate accumulation in cannabinoids receptors-independent manner. Thus, CBD could be a potential drug for PAH.Graphical Abstracts
Challenges in Undergraduate Synthetic Biology Training: Insights from a Canadian iGEM Student Perspective
Authors: Diep Patrick , Boucinha Austin , Yeung Bi-ru Amy , Kell Brayden , Chen Xingyu , Tsyplenkov Daniel , Serra Danielle , Escobar Andres , Gnanapragasam Ansley , Emond Christian A. , Sajtovich Victoria A. , Mahadevan Radhakrishnan , Kilkenny Dawn M. , Gini-Newman Garfield , Kaern Mads , Ingalls Brian 
Published: November 2020

ABSTRACTThe last two decades have seen vigorous activity in synthetic biology research and ever-increasing applications of synthetic biology technologies. However, pedagogical research on synthetic biology is scarce, especially when compared to some scientific and engineering disciplines. Within Canada, there are only three universities that formally teach synthetic biology programs; two of which are at the undergraduate level. Many Canadian undergraduate students are instead introduced to synthetic biology through participation in the annual International Genetically Engineered Machine (iGEM) competition where they work in design teams to conceive of and execute a synthetic biology project that they present at an international jamboree. We surveyed the Canadian landscape of synthetic biology education through the experience of students from the Canadian iGEM teams of 2019. Using a thematic codebook analysis, we gathered insights to generate recommendations that could empower future iGEM team operations and inform educators about best practices in teaching undergraduate synthetic biology.
SGLT2 inhibition by intraperitoneal dapagliflozin mitigates peritoneal fibrosis and ultrafiltration failure in a mouse model of chronic peritoneal exposure to high-glucose dialysate
Authors: Balzer Michael S. , Rong Song , Nordlohne Johannes , Zemtsovski Jan D. , Schmidt Sonja , Stapel Britta , Bartosova Maria , von Vietinghoff Sibylle , Haller Hermann , Schmitt Claus P. , Shushakova Nelli 
Published: November 2020

ABSTRACTPeritoneal dialysis (PD) is limited by glucose-mediated peritoneal membrane (PM) fibrosis, angiogenesis and ultrafiltration failure. Influencing PM integrity by pharmacologically targeting sodium-dependent glucose transporter (SGLT)-mediated glucose uptake has not been studied. In this study wildtype C57Bl/6N mice were treated with high-glucose dialysate via an intraperitoneal catheter, with or without addition of selective SGLT2 inhibitor dapagliflozin. PM structural changes, ultrafiltration capacity and PET status for glucose, urea and creatinine were analyzed. Expression of SGLT and GLUT was analyzed by real-time PCR, immunofluorescence and immunohistochemistry. Peritoneal effluents were analyzed for cellular and cytokine composition. We found that peritoneal SGLT2 was expressed in mesothelial cells and in skeletal muscle. Dapagliflozin significantly reduced effluent TGF-β concentrations, peritoneal thickening and fibrosis as well as microvessel density, resulting in improved ultrafiltration, despite the fact that it did not affect development of high glucose transporter status.In vitro, dapagliflozin reduced monocyte chemoattractant protein-1 release under high glucose conditions in human and murine peritoneal mesothelial cells. Pro-inflammatory cytokine release in macrophages was reduced only when cultured in high glucose conditions with an additional inflammatory stimulus. In summary, dapagliflozin improved structural and functional peritoneal health in the context of high glucose PD.
The Establishment of Transgenerational Epigenetic Inheritance in theC. elegansGermline is Mediated by Lipid Metabolism
Authors: Peng Dan , Wang Chen , Li Kai-Le , Gan Zhi-Xue , Li Yong-Hao , Wang Hao-Wei , Li Qiu-Yu , Liu Xi-Wei , Sun He-Yuan , Jing Yuan-Ya , Fang Qiang , Zhao Qian , Zhang Lei , Chen Huan-Huan , Wei Hui-Min , Sun Jin , Tang Huan-Yin , Yang Xiao-Mei , Chang Jiang-Feng , Sun Feng , Jiang Ci-Zhong , Yuan Hong-Bin , Li Wei , Sun Fang-Lin 
Published: November 2020

SUMMARYEnvironmental stress-induced epigenetic changes are inherited by germlines and profoundly affect the behavior and physiology of subsequent generations. However, the mechanisms by which acquired transgenerational epigenetic imprints are established in the parental germline remain poorly understood. In this study, we usedCaenorhabditis elegansas a model system and demonstrated that a key node of metabolism-Pod-2, an acetyl-CoA carboxylase, together with vitellogenins (Vits), cholesterol-binding/transport proteins, guide establishment of the acquired transgenerational epigenetic modifications H3K27me3 in the parental germline. The loss of function of a Vit; its transporter or receptor; or its binding partner, pod-2, resulted in the loss of acquired epigenetic memory in the germline. Our findings indicate that lipid metabolism is a critical mediator for establishing transgenerational epigenetic imprints in the germline.
A combined flow injection/reversed phase chromatography – high resolution mass spectrometry workflow for accurate absolute lipid quantification with13C- internal standards
Authors: Schoeny Harald , Rampler Evelyn , El Abiead Yasin , Hildebrand Felina , Zach Olivia , Hermann Gerrit , Koellensperger Gunda 
Published: November 2020

ABSTRACTWe propose a fully automated novel workflow for lipidomics based on flow injection-followed by liquid chromatography high resolution mass spectrometry (FI/LC-HRMS). The workflow combined in-depth characterization of the lipidome achieved via reversed phase LC-HRMS with absolute quantification as obtained by a high number of lipid species-specific- and/or retention time (RT) matched/class-specific calibrants. The lipidome of13C labelled yeast (LILY) provided a cost efficient, large panel of internal standards covering triacylglycerols (TG), steryl esters (SE), free fatty acids (FA), diacylglycerols (DG), sterols (ST), ceramides (Cer), hexosyl ceramides (HexCer), phosphatidylglycerols (PG), phosphatidylethanolamines (PE), phosphatidic acids (PA), cardiolipins (CL), phosphatidylinositols (PI), phosphatidylserines (PS), phosphatidylcholines (PC), lysophosphatidylcholines (LPC) and lysophosphatidylethanolamines (LPE). In order to exploit the full potential of isotopically enriched biomass, LILY was absolutely quantified on demand via reversed isotope dilution analysis using FI-HRMS. Subsequent LC-HRMS analysis integrated different calibration strategies including lipid species-specific standards for >90 lipids. Extensive measures on quality control allowed to rank the calibration strategies and to automatically selected the calibration strategy of highest metrological order for the respective lipid species. Overall, the workflow enabled a streamlined analysis pipeline (identification and quantification in separate analytical runs) and provided validation tools together with absolute concentration values for >350 lipids in human plasma on a species level with an analytical run-time of less than 25 min per sample.TOC
Computational identification of splicing phenotypes from single cell transcriptomic experiments
Authors: Huang Yuanhua , Sanguinetti Guido 
Published: November 2020

AbstractRNA splicing is an important driver of heterogeneity in single cells, both through the expression of alternative transcripts and as a major determinant of transcriptional kinetics. However, the intrinsic coverage limitations of scRNA-seq technologies make it challenging to associate specific splicing events to cell-level phenotypes. Here, we present BRIE2, a scalable computational method that resolves these issues by regressing single-cell transcriptomic data against cell-level features. We show that BRIE2 effectively identifies differential alternative splicing events that are associated with a disease. Additionally, BRIE2 allows a principled selection of genes (differential momentum genes) that capture heterogeneity in transcriptional kinetics and improve quantitatively RNA velocity analyses. BRIE2, therefore, extends the scope of single-cell transcriptomic experiments towards the identification of splicing phenotypes associated with biological changes at the single-cell level.
Reproduction of a marine planktonic protist: Individual success versus population survival
Authors: Weinkauf Manuel F. G. , Siccha Michael , Weiner Agnes K. M. 
Published: November 2020

AbstractUnderstanding the biology of reproduction is important for retracing key evolutionary processes in organisms, yet gaining detailed insights often poses major challenges. Planktonic Foraminifera are globally distributed marine microbial eukaryotes and important contributors to the global carbon cycle. Their extant biodiversity shows restricted distribution patterns of some species, whereas others are cosmopolitan in the world ocean. Planktonic Foraminifera cannot be bred under laboratory conditions, and thus details of their life cycle remain incomplete. Solely the production of flagellated gametes has been observed and taken as an indication for an exclusively sexual reproduction. Yet, sexual reproduction by spawning of gametes in the open ocean relies on sufficient gamete encounters to maintain viable populations, which represents a problem for organisms that lack the means of active propulsion and are marked by low population densities. To increase knowledge on the reproductive biology of planktonic Foraminifera, we applied a dynamic, individual-based modelling approach with parameters based on laboratory and field observations to test if random gamete encounters under commonly observed population densities are sufficient for maintaining viable populations. We show that temporal synchronization and potentially spatial concentration of gamete release seems inevitable for maintenance of the population. We argue that planktonic Foraminifera optimized their individual reproductive success at the expense of community-wide gene flow, which may explain their high degree of diversity. Our modelling approach helps to illuminate foraminiferal population dynamics and to predict the existence of necessary reproduction strategies, which may be detected in future field experiments. This study therefore contributes to our understanding of plankton ecology and evolution and their reproductive strategies in the open ocean.
Phosphonate production by marine microbes: exploring new sources and potential function
Authors: Acker Marianne , Hogle Shane L. , Berube Paul M. , Hackl Thomas , Stepanauskas Ramunas , Chisholm Sallie W. , Repeta Daniel J. 
Published: November 2020

AbstractPhosphonates, organic compounds with a C-P bond, constitute 20-25% of phosphorus in high molecular weight dissolved organic matter and are a significant phosphorus source for marine microbes. However, little is known about phosphonate sources, biological function, or biogeochemical cycling. Here, we determine the biogeographic distribution and prevalence of phosphonate biosynthesis potential using thousands of genomes and metagenomes from the upper 250 meters of the global ocean. Potential phosphonate producers are taxonomically diverse, occur in widely distributed and abundant marine lineages (including SAR11 andProchlorococcus) and their abundance increases with depth. Within those lineages, phosphonate biosynthesis and catabolism pathways are mutually exclusive, indicating functional niche partitioning of organic phosphorus cycling in the marine microbiome. Surprisingly, one strain ofProchlorococcus(SB) can allocate more than 40% of its cellular P-quota towards phosphonate production. Chemical analyses and genomic evidence suggest that phosphonates in this strain are incorporated into surface layer glycoproteins that may act to reduce mortality from grazing or viral infection. Although phosphonate production is a low-frequency trait inProchlorococcuspopulations (~ 5% of genomes), experimentally derived production rates suggest thatProchlorococcuscould produce a significant fraction of the total phosphonate in the oligotrophic surface ocean. These results underscore the global biogeochemical impact of even relatively rare functional traits in abundant groups likeProchlorococcusand SAR11.
Lowering the Thermal Noise Barrier in Functional Brain Mapping with Magnetic Resonance Imaging
Authors: Vizioli L. , Moeller S. , Dowdle L. , Akçakaya M. , De Martino F. , Yacoub E. , Ugurbil K. 
Published: November 2020

AbstractFunctional magnetic resonance imaging (fMRI) has become one of the most powerful tools for investigating the human brain. However, virtually all fMRI studies have relatively poor signal-to-noise ratio (SNR). Here we introduce a novel fMRI denoising technique, which suppresses noise that is indistinguishable from zero-mean, Gaussian-distributed noise. Thermal noise, falling in this category, is a major source of noise in fMRI, particularly, but not exclusively, at high spatial and/or temporal resolutions. Using 7-Tesla high-resolution data, we demonstrate improvements in temporal-SNR, the detection of stimulus-induced signal changes, and functional maps, while leaving stimulus-induced signal change amplitudes, image spatial precision, and functional point-spread-function unaltered. We also show that the method is equally applicable when using supra-millimeter resolution 3- and 7-Tesla fMRI data, different cortical regions, stimulation/task paradigms, and acquisition strategies. This denoising approach improves key metrics of functional activation detection while preserving spatial precision.
Obligate cross-feeding expands the metabolic niche of bacteria
Authors: Oña Leonardo , Giri Samir , Avermann Neele , Kreienbaum Maximilian , Thormann Kai M. , Kost Christian 
Published: November 2020

AbstractBacteria frequently engage in obligate metabolic mutualisms with other microorganisms. However, it remains generally unclear how the resulting metabolic dependencies affect the ecological niche space accessible to the whole consortium relative to the niche space available to its constituent individuals. Here we address this issue by systematically cultivating metabolically dependent strains of different bacterial species either individually or as pairwise coculture in a wide range of carbon sources. Our results show that obligate cross-feeding is significantly more likely to expand the metabolic niche space of interacting bacterial populations than to contract it. Moreover, niche expansion occurred predominantly between two specialist taxa and correlated positively with the phylogenetic distance between interaction partners. Together, our results demonstrate that obligate cross-feeding can significantly expand the ecological niche space of interacting bacterial genotypes, thus explaining the widespread occurrence of this type of ecological interaction in natural microbiomes.
Bioarchaeological sex prediction from central Italy using generalized low rank imputation for cross-validated metric craniodental supervised ensemble machine learning with missing data
Authors: Muzzall Evan 
Published: November 2020

AbstractI use a novel supervised ensemble machine learning approach to verify sex estimation of archaeological skeletons from central Italian bioarchaeological contexts with large amounts of missing data present. Eighteen cranial interlandmark distances and five maxillary metric distances were recorded fromn= 240 estimated males andn= 180 estimated females from four locations at Alfedena (600-400 BCE) and two locations at Campovalano (750-200 BCE and 9-11thCentury CE). A generalized low rank model (GLRM) was used to impute missing data and 20-fold external stratified cross-validation was used to fit an ensemble of eight machine learning algorithms to six different subsets of the data: 1) the face, 2) vault, 3) cranial base, 4) combined face/vault/base, 5) dentition, and 6) combined cranianiodental. Area under the receiver operator characteristic curve (AUC) was used to evaluate the predictive performance of six constituent algorithms, the discrete algorithmic winner(s), and the SuperLearner weighted ensemble’s classification of males and females from these six bony regions. This approach is useful for predicting male/female sex from central Italy. AUC for the combined craniodental data was the highest (0.9722), followed by the combined cranial data (0.9644), the face (0.9426), vault (0.9116), base (0.9060), and dentition (0.7421). Cross-validated ensemble machine learning of cranial and dental data shows strong potential for estimating sex in the bioarchaeological record and can contribute additional perspectives to help refine our understanding of human sex estimation. Additionally, GLRMs have the potential to handle missing data in ways previously unexplored in the discipline. The main limitation is that the biological sexes of the individuals estimated in this study are not certain, but were estimated macroscopically using common bioarchaeological methods. However, these methods show great promise for estimation of sex in bioarchaeological and forensic contexts and should be investigated on known-sex reference samples for confirmation.
Phylogenomic conflict coincides with rapid morphological innovation
Authors: Parins-Fukuchi Caroline , Stull Gregory W. , Smith Stephen A. 
Published: November 2020

AbstractEvolutionary biologists have long been fascinated with the episodes of rapid phenotypic innovation that underlie the emergence of major lineages. Although our understanding of the environmental and ecological contexts of such episodes has steadily increased, it has remained unclear how population processes contribute to emergent macroevolutionary patterns. One insight gleaned from phylogenomics is that phylogenomic conflict, frequently caused by population-level processes, is often rampant during the origin of major lineages. With the understanding that phylogenomic conflict is often driven by complex population processes, we hypothesized that there may be a direct correspondence between areas of high conflict and elevated rates of phenotypic innovation if both patterns result from the same processes. We evaluated this hypothesis in six clades spanning vertebrates and plants. We found that the most conflict-rich regions of these six clades also tended to experience the highest rates of phenotypic innovation, suggesting that population processes shaping both phenotypic and genomic evolution may leave signatures at deep timescales. Closer examination of the biological significance of phylogenomic conflict may yield improved connections between micro- and macroevolution and increase our understanding of the processes that shape the origin of major lineages across the Tree of Life.
Performance of deep learning restoration methods for the extraction of particle dynamics in noisy microscopy image sequences
Authors: Kefer Paul , Iqbal Fadil , Locatelli Maelle , Lawrimore Josh , Zhang Mengdi , Bloom Kerry , Bonin Keith , Vidi Pierre-Alexandre , Liu Jing 
Published: November 2020

ABSTRACTImage-based particle tracking is an essential tool to answer research questions in cell biology and beyond. A major challenge of particle tracking in living systems is that low light exposure is required to avoid phototoxicity and photobleaching. In addition, high-speed imaging used to fully capture particle motion dictates fast image acquisition rates. Short exposure times come at the expense of tracking accuracy. This is generally true for quantitative microscopy approaches and particularly relevant to single molecule tracking where the number of photons emitted from a single chromophore is limited. Image restoration methods based on deep learning dramatically improve the signal-to-noise ratio in low-exposure datasets. However, it is not clear whether images generated by these methods yield accurate quantitative measurements such as diffusion parameters in (single) particle tracking experiments. Here, we evaluate the performance of two popular deep learning denoising software packages for particle tracking, using synthetic datasets and movies of diffusing chromatin as biological examples. With synthetic data, both supervised and unsupervised deep learning restored particle motions with high accuracy in two-dimensional datasets, whereas artifacts were introduced by the denoisers in 3D datasets. Experimentally, we found that, while both supervised and unsupervised approaches improved the number of trackable particles and tracking accuracy, supervised learning generally outperformed the unsupervised approach, as expected. We also highlight that with extremely noisy image sequences, deep learning algorithms produce deceiving artifacts, which underscores the need to carefully evaluate the results. Finally, we address the challenge of selecting hyper-parameters to train convolutional neural networks by implementing a frugal Bayesian optimizer that rapidly explores multidimensional parameter spaces, identifying networks yielding optional particle tracking accuracy. Our study provides quantitative outcome measures of image restoration using deep learning. We anticipate broad application of the approaches presented here to critically evaluate artificial intelligence solutions for quantitative microscopy.