bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Remote Assessment of Parkinsonism Supporting Ongoing Development of Interventions in Gaucher Disease – Study Protocol
Authors: Higgins Abigail Louise , Toffoli Marco , Mullin Stephen , Lee Chiao-Yin , Koletsi Sofia , Avenali Micol , Blandini Fabio , Schapira Anthony H V 
Published: July 2021

AbstractMutations in GBA which are causative of Gaucher disease in their biallelic form, are the most common genetic risk factor for Parkinson disease. The diagnosis of Parkinson disease relies upon clinically defined motor features which appear after irreversible neurodegeneration. Prodromal symptoms of Parkinson disease may provide a means to predict latent pathology, years before the onset of motor features. Previous work has reported prodromal features of Parkinson disease in GBA mutation carriers, however this has been insufficiently sensitive to identify those that will develop Parkinson disease. The Remote Assessment of Parkinsonism Supporting Ongoing Development of Interventions in Gaucher Disease (RAPSODI) study assesses a large cohort of GBA mutation carriers, to aid development of procedures for earlier diagnosis of Parkinson disease.Summary PointsThe therapeutic focus for Parkinson disease is currently symptomatic, rather than disease-modifying or neuroprotective.Non-motor prodromal features of Parkinson disease may precede the motor symptoms required for clinical diagnosis by several years.GBAmutations, which are associated with Gaucher disease in their biallelic form, have emerged as the most common genetic risk factor for Parkinson Disease.GBAassociated PD displays a slightly exaggerated phenotype, including earlier age of onset, enhanced cognitive decline, more severe affective disturbances, and a greater likelihood of manifesting REM Sleep Behaviour Disorder, hyposmia and autonomic dysfunction.The RAPSODI GD study is an annual remote assessment which aims to define the clinical prodrome of PD in a large cohort ofGBAmutation carriers, to accurately predict clinical diagnosis.The secondary objectives of RAPSODI GD are to risk stratify homozygote and heterozygoteGBAmutation carriers for PD risk, understand the variable penetrance of theGBAassociated PD phenotype, and create a platform for the future evaluation of biomarkers of disease.The putative implication of the RAPSODI GD study is to contribute towards earlier diagnosis ofGBAassociated PD, to provide a timeframe for delivering neuroprotective interventions.Defining prodromal PD inGBAcarriers may have wider implications for sporadic PD.
Mixed culture metagenomics of the microbes making sour beer
Authors: Araujo Piraine Renan Eugênio , Leivas Leite Fábio Pereira , Bochman Matthew L. 
Published: July 2021

AbstractMixed microbial cultures create sour beers, but many brewers do not know which microbes comprise their cultures. The objective of this work was to use deep sequencing to identify microorganisms in sour beers brewed by spontaneous and non-spontaneous methods. Twenty samples were received from brewers, which were processed for microbiome analysis by next generation sequencing. For bacteria, primers were used to amplify the V3-V4 region of the 16S rRNA gene; fungal DNA detection was performed using primers to amplify the entire internal transcribed spacer region. The sequencing results were then used for taxonomy assignment, sample composition, and diversity analyses, as well as nucleotide BLAST searching. We identified 60 genera and 140 species of bacteria, of which the most prevalent wereLactobacillus acetotolerans, Pediococcus damnosus, andRalstonia picketti/mannitolilytica. In fungal identification, 19 genera and 26 species were found, among which the most common yeasts wereBrettanomyces bruxellensisandSaccharomyces cerevisiae. In some cases, genetic material from more than 60 microorganisms was found in a single sample. In conclusion, we were able to determine the microbiomes of various mixed cultures used to produce beer, providing useful information to better understand the sour beer fermentation process and brewing techniques.
Colistin resistance in Escherichia coli confers protection of the cytoplasmic but not outer membrane from the polymyxin antibiotic
Authors: Humphrey Madeleine , Larrouy-Maumus Gerald J. , Furniss R. Christopher D. , Mavridou Despoina A. I. , Sabnis Akshay , Edwards Andrew M. 
Published: July 2021

AbstractColistin is a polymyxin antibiotic of last resort for the treatment of infections caused by multi-drug resistant Gram-negative bacteria. By targeting lipopolysaccharide (LPS), the antibiotic disrupts both the outer and cytoplasmic membranes, leading to lysis and bacterial death. Colistin resistance in Escherichia coli occurs via mutations in the chromosome or the acquisition of mobilised colistin resistance (mcr) genes. Both these colistin resistance mechanisms result in chemical modifications to the LPS, with positively charged moieties added at the cytoplasmic membrane before the LPS is transported to the outer membrane. We have previously shown that MCR-1-mediated LPS modification protects the cytoplasmic but not the outer membrane from damage caused by colistin, enabling bacterial survival. However, it remains unclear whether this observation extends to colistin resistance conferred by other mcr genes, or resistance due to chromosomal mutations. Using a panel of clinical E. coli that had acquired mcr -1, -1.5, -2, -3, -3.2 or -5, or had acquired polymyxin resistance independently of mcr genes, we found that almost all isolates were susceptible to colistin-mediated permeabilisation of the outer, but not cytoplasmic, membrane. Furthermore, we showed that permeabilisation of the outer membrane of colistin resistant isolates by the polymyxin is in turn sufficient to sensitise bacteria to the antibiotic rifampicin, which normally cannot cross the LPS monolayer. These findings demonstrate that colistin resistance in E. coli is typically due to protection of the cytoplasmic but not outer membrane from colistin-mediated damage, regardless of the mechanism of resistance.
Lineage-specific regulatory changes in the pathological cardiac remodeling of hypertrophy cardiomyopathy unraveled by single-nucleus RNA-seq and spatial transcriptomics
Authors: Liu Xuanyu , Yin Kunlun , Chen Liang , Chen Wen , Li Wenke , Zhang Taojun , Sun Yang , Yuan Meng , Wang Hongyue , Wang Shuiyun , Hu Shengshou , Zhou Zhou 
Published: July 2021

ABSTRACTBACKGROUNDHypertrophy cardiomyopathy (HCM) is the most common cardiac genetic disorder with the histopathological features of cardiomyocyte hypertrophy and cardiac fibrosis. The pathological remodeling that occurs in the myocardium of HCM patients may ultimately progress to heart failure and death. A thorough understanding of the cell type-specific changes in the pathological cardiac remodeling of HCM is crucial for developing successful medical therapies to prevent or mitigate the progression of this disease.METHODSWe performed single-nucleus RNA-seq of the cardiac tissues from 10 HCM patients and 2 healthy donors, and conducted spatial transcriptomic assays of 4 cardiac tissue sections from 3 HCM patients. Comparative analyses were performed to explore the lineage-specific changes in expression profile, subpopulation composition and intercellular communication in the cardiac tissues of HCM patients. Based on the results of independent analyses including pseudotime ordering, differential expression analysis, and differential regulatory network analysis, we prioritized candidate therapeutic targets for mitigating the progression to heart failure or attenuating the cardiac fibrosis in HCM. Using the spatial transcriptomic data, we examined the spatial activity patterns of the key candidate genes, pathways and subpopulations.RESULTSUnbiased clustering of 55,122 nuclei from HCM and healthy conditions revealed 9 cell lineages and 28 clusters. Significant expansion of vascular-related lineages and contraction of cardiomyocytes, fibroblasts and myeloid cells in HCM were observed. The transcriptomic dynamics during the transition towards the failing state of cardiomyocytes in HCM were uncovered. Candidate target genes for mitigating the progression to heart failure in HCM were obtained such asFGF12,IL31RA,BDNF,S100A1,CRYABandPROS1. The transcriptomic dynamics underlying the fibroblast activation were also uncovered, and candidate targets for attenuating the cardiac fibrosis in HCM were obtained such asRUNX1,MEOX1,AEBP1,LEF1andNRXN3.CONCLUSIONSWe provided a comprehensive analysis of the lineage-specific regulatory changes in HCM. Our analysis identified a vast array of candidate therapeutic target genes and pathways to prevent or attenuate the pathological remodeling of HCM. Our datasets constitute a valuable resource to examine the lineage-specific expression changes of HCM at single-nucleus and spatial resolution. We developed a web-based interface (http://snsthcm.fwgenetics.org/) for further exploration.
Fixation probabilities in network structured meta-populations
Authors: Yagoobi Sedigheh , Traulsen Arne 
Published: July 2021

ABSTRACTThe effect of population structure on evolutionary dynamics is a long-lasting research topic in evolutionary ecology and population genetics. Evolutionary graph theory is a popular approach to this problem, where individuals are located on the nodes of a network and can replace each other via the links. We study the effect of complex network structure on the fixation probability, but instead of networks of individuals, we model a network of sub-populations with a probability of migration between them. We ask how the structure of such a meta-population and the rate of migration affect the fixation probability. Many of the known results for networks of individuals carry over to meta-populations, in particular for regular networks or low symmetric migration probabilities. However, when patch sizes differ we find interesting deviations between structured meta-populations and networks of individuals. For example, a two patch structure with unequal population size suppresses selection for low migration probabilities.
Are experiment sample sizes adequate to detect biologically important interactions between multiple stressors?
Authors: Burgess Benjamin J. , Jackson Michelle C. , Murrell David J. 
Published: July 2021

AbstractAs most ecosystems are being challenged by multiple, co-occurring stressors, an important challenge is to understand and predict how stressors interact to affect biological responses. A popular approach is to design factorial experiments that measure biological responses to pairs of stressors and compare the observed response to a null model expectation. Unfortunately, we believe experiment sample sizes are inadequate to detect most non-null stressor interaction responses, greatly hindering progress. Determination of adequate sample size requires (i) knowledge of the detection ability of the inference method being used, and (ii) a consideration of the smallest biologically meaningful deviation from the null expectation. However, (i) has not been investigated and (ii) is yet to be discussed. Using both real and simulated data we show sample sizes typical of many experiments (<10) can only detect very large deviations from the additive null model, implying many important non-null stressor-pair interactions are being missed. We also highlight how only reporting statistically significant results at low samples sizes greatly overestimates the degree of non-additive stressor interactions. Computer code that simulates data under either additive or multiplicative null models is provided to estimate statistical power for user defined responses and sample sizes and we recommend this is used to aid experimental design and interpretation of results. We suspect that most experiments may require 20 or more replicates per treatment to have adequate power to detect non-additive. However, researchers still need to define the smallest interaction of interest, i.e. the lower limit for a biologically important interaction, which is likely to be system specific, meaning a general guide is unavailable. Sample sizes could potentially be increased by focussing on individual-level responses to multiple stressors, or by forming coordinated networks of researchers to repeat experiments in larger-scale studies. Our main analyses relate to the additive null model but we show similar problems occur for the multiplicative null model, and we encourage similar investigations into the statistical power of other null models and inference methods. Without knowledge of the detection abilities of the statistical tools at hand, or definition of the smallest meaningful interaction, we will undoubtedly continue to miss important ecosystem stressor interactions.
Shaping nanoparticle diffusion through biological barriers to drug delivery
Authors: Lee Benjamin J. , Cheema Yahya , Bader Shahed , Duncan Gregg A. 
Published: July 2021

AbstractNanoparticle drug delivery systems encounter many biological barriers, such as the extracellular matrix and mucus gels, that they must bypass to gain access to target cells. A design parameter that has recently gained attention is nanoparticle shape, as it has been shown elongated rod–shaped nanoparticles achieve higher diffusion rates through biological gels. However, the optimal dimensions of rod-shaped nanoparticles to enhance this effect has yet to be established. To systematically approach this, rod-shaped nanoparticles were synthesized by mechanically stretching 100 nm, 200 nm, and 500 nm spherical nanoparticles. Transmission electron microscopy confirmed this procedure yields a significant fraction of elongated rods and remaining spheres could be removed by centrifugation. Fluorescent microscopy and multiple particle tracking analysis was then used to characterize rod-shaped and spherical nanoparticle diffusion in MaxGel®, a model extracellular matrix hydrogel. When dispersed in MaxGel, we found rod-shaped nanoparticles exhibited the greatest enhancement in diffusion rate when their length far exceeds the average hydrogel network size. These results further establish the importance of shape as a design criterion to improve nanoparticle-based drug delivery systems.
The five Urochloa spp. used in development of tropical forage cultivars originate from defined subpopulations with differentiated gene pools
Authors: Higgins J , Tomaszewska P , Pellny TK , Castiblanco V , Arango J , Tohme J , Schwarzacher T , Mitchell RA , Heslop-Harrison JS , De Vega JJ 
Published: July 2021

ABSTRACTBackground and AimsUrochloa (syn. Brachiaria, and including some Panicum and Megathyrus) is a genus of tropical and subtropical grasses widely sown as forage to feed ruminants in the tropics. A better understanding of the diversity among Urochloa spp. allow us to leverage its varying ploidy levels and genome composition to accelerate its improvement, following the example from other crop genera.MethodsWe explored the genetic make-up and population structure in 111 accessions, which comprise the five Urochloa species used for the development of commercial cultivars. These accessions are conserved from wild materials from collection sites at their centre of origin in Africa. We used RNA-seq, averaging 40M reads per accession, to generate 1,167,542 stringently selected SNP markers that tentatively encompassed the complete Urochloa gene pool used in breeding.Key ResultsWe identified ten subpopulations, which had no relation with geographical origin and represented ten independent gene pools, and two groups of admixed accessions. Our results support a division in U. decumbens by ploidy, with a diploid subpopulation closely related to U. ruziziensis, and a tetraploid subpopulation closely related to U. brizantha. We observed highly differentiated gene pools in U. brizantha, which were not related with origin or ploidy. Particularly, one U. brizantha subpopulation clustered distant from the other U. brizantha and U. decumbens subpopulations, so likely containing unexplored alleles. We also identified a well-supported subpopulation containing both polyploid U. decumbens and U. brizantha accessions; this was the only group containing more than one species and tentatively constitutes an independent “mixed” gene pool for both species. We observed two gene pools in U. humidicola. One subpopulation, “humidicola-2”, was much less common but likely includes the only known sexual accession in the species.ConclusionsOur results offered a definitive picture of the available diversity in Urochloa to inform breeding and resolve questions raised by previous studies. It also allowed us identifying prospective founders to enrich the breeding gene pool and to develop genotyping and genotype-phenotype association mapping experiments.HIGHLIGHTWe clarified the genetic make-up and population structure of 111 Urochloa spp. forage grasses to inform cultivar development.
Venous activation of MEK/ERK drives development of arteriovenous malformation and blood flow anomalies with loss of Rasa1
Authors: Greysson-Wong Jasper , Rode Rachael , Ryu Jae-Ryeon , Rinker Kristina D. , Childs Sarah J. 
Published: July 2021

AbstractVascular malformations develop when growth pathway signaling goes awry in the endothelial cells lining blood vessels. Arteriovenous malformations (AVMs) arise where arteries and veins abnormally connect in patients with loss of RASA1, a Ras GTPase activating protein, and, as we show here, in zebrafish rasa1 mutants. Mutant fish develop massively enlarged vessels at the connection between artery and vein in the tail vascular plexus. These AVMs progressively enlarge and become filled with slow-flowing blood and have a greater drop in pulsatility from the artery to the vein. Expression of the flow responsive transcription factor klf2a is diminished in rasa1 mutants, suggesting changes in flow velocity and pattern contribute to the progression of vessel malformations. Migration of endothelial cells is not affected in rasa1 mutants, nor is cell death or proliferation. Early developmental artery-vein patterning is also normal in rasa1 mutants, but we find that MEK/ERK signaling is ectopically activated in the vein as compared to high arterial activation seen in wildtype animals. MEK/ERK signaling inhibition prevents AVM development of rasa1 mutants, demonstrating venous MEK/ERK drives the initiation of rasa1 AVMs. Thus, rasa1 mutants show overactivation of MEK/ERK signaling causes AVM formation, altered blood flow and downstream flow responsive signaling.SummaryThe zebrafish model ofRASA1capillary malformation and arteriovenous malformation (CM-AVM1) develops cavernous vascular malformations driven by ectopic MEK/ERK signaling in the vein, disrupting flow and downstream mechanosensitive signaling.
SyMBac: Synthetic Micrographs for Accurate Segmentation of Bacterial Cells using Deep Neural Networks
Authors: Hardo Georgeos , Noka Maximilian , Bakshi Somenath 
Published: July 2021

AbstractWe present a novel method of bacterial image segmentation using machine learning models trained with Synthetic Micrographs of Bacteria (SyMBac). SyMBac is a tool that allows for rapid, automatic creation of arbitrary amounts of training data, combining detailed models of cell growth, physical interactions, and microscope optics to create synthetic images which closely resemble real micrographs. The major advantages of our approach are: 1) synthetic training data can be generated virtually instantly, and on demand; 2) these synthetic images are accompanied by perfect ground truth positions of cells, meaning no data curation is required; 3) different biological conditions, imaging platforms, and imaging modalities can be rapidly simulated, meaning any change in one’s experimental setup no longer requires the laborious process of manually generating new training data for each change. Our benchmarking results demonstrate that models trained on SyMBac data generate more accurate and precise cell masks than those trained on human annotated data, because the model learns the true position of the cell irrespective of imaging artefacts. Machine-learning models trained with SyMBac data are capable of analysing data from various imaging platforms and are robust to drastic changes in cell size and morphology.
Testing the accuracy of 3D automatic landmarking via genome-wide association studies
Authors: Savriama Yoland , Tautz Diethard 
Published: July 2021

AbstractBackgroundVarious advances in 3D automatic phenotyping and particularly in landmark-based geometric morphometric methods have been made, but only a few studies have tested the reliability of such automatic procedures in morphometric analyses. It is generally accepted that automatic landmarking compromises the capture of the actual biological variation, and this not only affects its performance to effectively detect differences among sample means but also the structure of covariance matrices. However, no studies have directly tested the actual impact of such landmarking approaches in analyses requiring a large number of specimens and for which the precision of phenotyping is crucial to capture an actual biological signal adequately.ResultsHere, we use a recently developed 3D atlas-based automatic landmarking method to test its accuracy in detecting QTLs associated with craniofacial development of the house mouse skull and lower jaws for a large number of specimens (circa 700) that were previously phenotyped via a semiautomatic landmarking method complemented with manual adjustment. We compare both landmarking methods with univariate and multivariate mapping of the skull and the lower jaws. In the univariate mapping, the automatic approach failed to recover the same SNPs and found only 1 out of 17 previously identified QTLs for the skull, but found one new QTL. Similarly, for the lower jaws, the automatic approach failed to recover the same SNPs but found 2 neighbouring SNPs for 1 out of 8 previously identified QTLs. For centroid size, the same general results were recovered by the automatic method for both the skull and lower jaws, with the same peak SNP being found for the lower jaws. In the multivariate mapping, the automatic approach did not detect the same markers nor QTLs having their regions overlapping with the ones identified with the semi-automatic procedure for the skull, while the same marker, which is also the peak SNP and sole QTL, was recovered by the automatic pipeline for lower jaws.ConclusionOur results confirm the notion that information is lost in the automated landmarking procedure but somewhat dependent on the analyzed structure. The automatic method seems to capture certain types of structures slightly better, such as lower jaws whose shape is almost entirely summarized by its outline and could be assimilated as a 2D flat object. By contrast, the more apparent 3D features exhibited by a structure such as the skull are not adequately captured by the automatic method. We conclude that using 3D atlas-based automatic landmarking methods requires careful consideration of the experimental question and the cautious interpretation of their results.