bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pasture age impacts soil fungal composition while bacteria respond to soil chemistry
Authors: Seaton Fiona M. , Griffiths Robert I. , Goodall Tim , Lebron Inma , Norton Lisa R. 
Published: September 2021

AbstractPasture is a globally important managed habitat providing both food and income. The way in which it is managed leads to a wide range of impacts on soil microbial communities and associated soil health. While there have been several studies comparing pasture farming to other forms of land use, we still have limited understanding of how the soil microbial communities vary between pasture farms and according to management practices. Here we present the results of a field survey across 56 UK livestock farms that are managed by members of the Pasture fed Livestock Association, using amplicon sequencing of the 16S and ITS regions to characterise the soil bacterial and fungal community within fields that have been under pasture for differing durations. We show that grazing management intensity has only limited effects upon microbial community structure, while the duration of pasture since ploughing (ranging from 1 year to over 100 years) impacted the fungal community structure. The impact of management duration was conditional upon soil physicochemical properties, particularly pH. Plant community effects on upon soil bacterial and fungal composition appear to also interact with the soil chemistry, highlighting the importance of plant-soil interactions in determining microbial community structure. Analyses of microbial indicators revealed proportionally more fungal taxa that responded to multiple ecosystem health associated properties than bacterial taxa. We also identified several fungal taxa that both acted as indicators of soil health related properties within our dataset and showed differentiation between grassland types in a national survey, indicating the generality of some fungal indicators to the national level. Members of the Agaricomycetes were associated with multiple indicators of soil health. Our results show the importance of maintaining grassland for the development of plant-soil interactions and microbial community structure with concomitant effects on soil and general ecosystem health.HighlightsSoil bacteria and fungi from >50 pastures were analysed using DNA metabarcodingDuration of pasture since ploughing impacted fungal community compositionBacteria were more associated with soil physicochemical properties than fungiPlant effects on soil microbes were through interactions with soil chemistryMicrobial indicators of soil health were disproportionately fungal taxa
Social isolation is linked to classical risk factors of Alzheimer’s disease-related dementias
Authors: Shafighi Kimia , Villeneuve Sylvia , Rosa-Neto Pedro , Badhwar AmanPreet , Poirier Judes , Sharma Vaibhav , Iturria-Medina Yasser , Silveira Patricia P , Dube Laurette , Glahn David , Bzdok Danilo 
Published: September 2021

AbstractAlzheimer’s disease and related dementias is a major public health burden – compounding over upcoming years due to longevity. Recently, clinical evidence hinted at the experience of social isolation in expediting dementia onset. In 502,506 UK Biobank participants and 30,097 participants from the Canadian Longitudinal Study of Aging, we revisited traditional risk factors for developing dementia in the context of loneliness and lacking social support. Across these measures of subjective and objective social deprivation, we have identified strong links between individuals’ social capital and various indicators of Alzheimer’s disease and related dementias risk, which replicated across both population cohorts. The quality and quantity of daily social encounters had deep connections with key aetiopathological factors, which represent 1) personal habits and lifestyle factors, 2) physical health, 3) mental health, and 4) societal and external factors. Our population-scale assessment suggest that social lifestyle determinants are linked to most neurodegeneration risk factors, highlighting them promising targets for preventive clinical action.
Optimizing epitope conformational ensembles usingα-synuclein cyclic peptide “glycindel” scaffolds: A customized immunogen method for generating oligomer-selective antibodies for Parkinson’s disease
Authors: Hsueh Shawn C.C. , Aina Adekunle , Roman Andrei Yu. , Cashman Neil R. , Peng Xubiao , Plotkin Steven S. 
Published: September 2021

AbstractEffectively presenting epitopes on immunogens, in order to raise conformationally selective antibodies through active immunization, is a central problem in treating protein misfolding diseases, particularly neurodegenerative diseases such as Alzheimer’s disease or Parkinson’s disease. We seek to selectively target conformations enriched in toxic, oligomeric propagating species while sparing the healthy forms of the protein that are often more abundant. To this end, we computationally modelled scaffolded epitopes in cyclic peptides by inserting/deleting a variable number of flanking glycines (“glycindels”), to best mimic a misfolding-specific conformation of an epitope ofα-synuclein enriched in the oligomer ensemble, as characterized by a region most readily disordered and solvent-exposed in a stressed, partially denatured protofibril. We screen and rank the cyclic peptide scaffolds ofα-synucleinin silicobased on their ensemble overlap properties with the fibril, oligomer-model, and isolated monomer ensembles. We present experimental data of seeded aggregation that supports nucleation rates consistent with computationally predicted cyclic peptide conformational similarity. We also introduce a method for screening against structured off-pathway targets in the human proteome, by selecting scaffolds with minimal conformational similarity between their epitope and the same solvent-exposed primary sequence in structured human proteins. Different cyclic peptide scaffolds with variable numbers of glycines are predicted computationally to have markedly different conformational ensembles. Ensemble comparison and overlap was quantified by the Jensen-Shannon Divergence, and a new measure introduced here—the embedding depth, which determines the extent to which a given ensemble is subsumed by another ensemble, and which may be a more useful measure in developing immunogens that confer conformational-selectivity to an antibody.Graphical TOC Entry
Embracing imperfection: machine-assisted invertebrate classification in real-world datasets
Authors: Blair Jarrett , Weiser Michael D. , de Beurs Kirsten , Kaspari Michael , Siler Cameron , Marshall Katie E. 
Published: September 2021

AbstractDespite growing concerns over the health of global invertebrate diversity, terrestrial invertebrate monitoring efforts remain poorly geographically distributed. Machine-assisted classification has been proposed as a potential solution to quickly gather large amounts of data; however, previous studies have often used unrealistic or idealized datasets to train their models.In this study, we describe a practical methodology for including machine learning in ecological data acquisition pipelines. Here we train and test machine learning algorithms to classify over 56,000 bulk terrestrial invertebrate specimens from morphometric data and contextual metadata. All vouchered specimens were collected in pitfall traps by the National Ecological Observatory Network (NEON) at 27 locations across the United States in 2016. Specimens were photographed, and morphometric data was extracted as feature vectors using ImageJ. Issues stemming from inconsistent taxonomic label specificity were resolved by making classifications at the lowest identified taxonomic level (LITL). Taxa with too few specimens to be included in the training dataset were classified by the model using zero-shot classification.When classifying specimens that were known and seen by our models, we reached an accuracy of 72.7% using extreme gradient boosting (XGBoost) at the LITL. Models that were trained without contextual metadata underperformed models with contextual metadata by an average of 7.2%. We also classified invertebrate taxa that were unknown to the model using zero-shot classification, with an accuracy of 39.4%, resulting in an overall accuracy of 71.5% across the entire NEON dataset.The general methodology outlined here represents a realistic application of machine learning as a tool for ecological studies. Hierarchical and LITL classifications allow for flexible taxonomic specificity at the input and output layers. These methods also help address the ‘long tail’ problem of underrepresented taxa missed by machine learning models. Finally, we encourage researchers to consider more than just morphometric data when training their models, as we have shown that the inclusion of contextual metadata can provide significant improvements to accuracy.
The Effects of Incline Level on Optimized Lower-Limb Exoskeleton Assistance
Authors: Franks Patrick W. , Bryan Gwendolyn M. , Reyes Ricardo , O’Donovan Meghan P. , Gregorczyk Karen N. , Collins Steven H. 
Published: September 2021

AbstractFor exoskeletons to be successful in real-world settings, they will need to be effective across a variety of terrains, including on inclines. While some single-joint exoskeletons have assisted incline walking, recent successes in level-ground assistance suggest that greater improvements may be possible by optimizing assistance of the whole leg. To understand how exoskeleton assistance should change with incline, we used human-in-the-loop optimization to find whole-leg exoskeleton assistance torques that minimized metabolic cost on a range of grades. We optimized assistance for three expert, able-bodied participants on 5 degree, 10 degree and 15 degree inclines using a hip-knee-ankle exoskeleton emulator. For all assisted conditions, the cost of transport was reduced by at least 50% relative to walking in the device with no assistance, a large improvement to walking that is comparable to the benefits of whole-leg assistance on level-ground. This corresponds to large absolute reductions in metabolic cost, with the most strenuous conditions reduced by 4.9 W/kg, more than twice the entire energy cost of level walking. Optimized extension torque magnitudes and exoskeleton power increased with incline, with hip extension, knee extension and ankle plantarflexion often growing as large as allowed by comfort-based limits. Applied powers on steep inclines were double the powers applied during level-ground walking, indicating that larger exoskeleton power may be optimal in scenarios where biological powers and costs are higher. Future exoskeleton devices can be expected to deliver large improvements in walking performance across a range of inclines, if they have sufficient torque and power capabilities.
Individualized Assays of Temporal Coding in the Ascending Human Auditory System
Authors: Borjigin Agudemu , Hustedt-Mai Alexandra R. , Bharadwaj Hari M. 
Published: September 2021

AbstractNeural phase-locking to temporal fluctuations is a fundamental and unique mechanism by which acoustic information is encoded by the auditory system. The perceptual role of this metabolically expensive mechanism, the neural phase-locking to temporal fine structure (TFS) in particular, is debated. Although hypothesized, it is unclear if auditory perceptual deficits in certain clinical populations are attributable to deficits in TFS coding. Efforts to uncover the role of TFS have been impeded by the fact that there are no established assays for quantifying the fidelity of TFS coding at the individual level. While many candidates have been proposed, for an assay to be useful, it should not only intrinsically depend on TFS coding, but should also have the property that individual differences in the assay reflect TFS coding per se over and beyond other sources of variance. Here, we evaluate a range of behavioral and electroencephalogram (EEG)-based measures as candidate individualized measures of TFS sensitivity. Our comparisons of behavioral and EEG-based metrics suggest that extraneous variables dominate both behavioral scores and EEG amplitude metrics, rendering them ineffective. After adjusting behavioral scores using lapse rates, and extracting latency or percent-growth metrics from EEG, interaural timing sensitivity measures exhibit robust behavior-EEG correlations. Together with the fact that unambiguous theoretical links can be made relating binaural measures and phase-locking to TFS, our results suggest that these “adjusted” binaural assays may be well-suited for quantifying individual TFS processing.
Effect of SFX-01 on proliferation of human glioblastoma cell lines
Authors: Leung Euphemia , Wright Edwina , Baguley Bruce C. 
Published: September 2021

AbstractGlioblastoma (GBM) is the most aggressive and lethal of brain tumours and there is a clear need for novel therapies. SFX-01, a stabilised formu of sulforaphane (SFN) that is complexed with α-cyclodextrin, is being investigated as a potential anticancer drug. And as part of this investigation we have determined its effect on the proliferation of a series of tumour cell lines. Growth-inhibitory concentrations (IC50 values) of SFX-01 and reference SFN were highly correlated but showed a divergence at higher drug concentrations that is likely to reflect drug binding to α-cyclodextrin complexes. Because SFN is redox-sensitive, we also compared the effects of these drugs on four GBM lines that had been derived and cultured under physiological oxygen (5%) conditions. Comparisons were also made using a three-dimensional spheroid model, used to mimic the in vivo state of glioblastomas and to simulate barriers to drug delivery in vivo. SFX-01 and reference SFN and inhibited proliferation of four GBM cell lines in monolayers as well as in spheroids; α-cyclodextrin alone had no significant effect. Our results are consistent with the hypothesis that SFN is liberated from SFX-01 at concentrations sufficient to inhibit cell growth. We envision that SFX-01 will have improved pharmacokinetic properties in vivo, warranting further pre-clinical investigation and clinical development.
The value of genotype-specific reference for transcriptome analyses
Authors: Guo Wenbin , Coulter Max , Waugh Robbie , Zhang Runxuan 
Published: September 2021

AbstractHigh quality transcriptome assembly using short reads from RNA-seq data still heavily relies upon reference-based approaches, of which the primary step is to align RNA-seq reads to a single reference genome of haploid sequence. However, it is increasingly apparent that while different genotypes within a species share “core” genes, they also contain variable numbers of “specific” genes that are only present a subset of individuals. Using a common reference may thus lead to a loss of genotype-specific information in the assembled transcript dataset and the generation of erroneous, incomplete or misleading transcriptomics analysis results. With the recent development of pan-genome information in many species, it is important that we understand the limitations of single genotype references for transcriptomics analysis. In this study, we quantitively evaluated the advantages of using genotype-specific reference genomes for transcriptome assembly and analysis using cultivated barley as a model. We mapped barley cultivar Barke RNA-seq reads to the Barke genome and to the cultivar Morex genome (common barley genome reference) to construct a genotype specific Reference Transcript Dataset (sRTD) and a common Reference Transcript Datasets (cRTD), respectively. We compared the two RTDs according to their transcript diversity, transcript sequence and structure similarity and the accuracy they provided for transcript quantification and differential expression analysis. Our evaluation shows that the sRTD has a significantly higher diversity of transcripts and alternative splicing events. Despite using a high-quality reference genome for assembly of the cRTD, we miss ca. 40% transcripts present in the sRTD and cRTD only has ca. 70% true assemblies. We found that the sRTD is more accurate for transcript quantification as well as differential expression and differential alternative splicing analysis. However, gene level quantification and comparative expression analysis are less affected by the source RTD, which indicates that analysing transcriptomic data at the gene level may be a reasonable compromise when a high-quality genotype-specific reference is not available.
Dinosaur bonebed amber from an original swamp forest soil
Authors: Álvarez-Parra Sergio , la Fuente Ricardo Pérez-de , Peñalver Enrique , Barrón Eduardo , Alcalá Luis , Pérez-Cano Jordi , Martín-Closas Carles , Trabelsi Khaled , Meléndez Nieves , Del Valle Rafael López , Lozano Rafael P , Peris David , Rodrigo Ana , Sarto i Monteys Víctor , Bueno-Cebollada Carlos A , Menor-Salván César , Philippe Marc , Sánchez-García Alba , Peña-Kairath Constanza , Arillo Antonio , Espílez Eduardo , Mampel Luis , Delclòs Xavier 
Published: September 2021

AbstractDinosaur bonebeds with amber content, yet scarce, offer a superior wealth and quality of data on ancient terrestrial ecosystems. However, the preserved palaeodiversity and/or taphonomic characteristics of these exceptional localities had hitherto limited their palaeobiological potential. Here we describe the amber from the Lower Cretaceous dinosaur bonebed of Ariño (Teruel, Spain) using a multidisciplinary approach. Amber is found in both a root layer with amber strictly in situ and a litter layer namely composed of aerial pieces unusually rich in bioinclusions, encompassing 11 insect orders, arachnids, and a few plant and vertebrate remains, including a feather. Additional palaeontological data ‒ charophytes, palynomorphs, ostracods‒ are provided. Ariño arguably represents the most prolific and palaeobiologically diverse locality in which fossiliferous amber and a dinosaur bonebed have been found in association, and the only one known where the vast majority of the palaeontological assemblage suffered no or low-grade pre-burial transport. That has enabled unlocking unprecedentedly complete and reliable palaeoecological data out of two complementary windows of preservation from the same site.
PhosPiR: An automated phospho-proteomic pipeline in R
Authors: Hong Ye , Flinkman Dani , Suomi Tomi , Pietilä Sami , James Peter , Coffey Eleanor , Elo Laura L. 
Published: September 2021

ABSTRACTLarge-scale phospho-proteome profiling using mass spectrometry (MS) provides functional insight that is crucial for disease biology and drug discovery. However, extracting biological understanding from this data is an arduous task requiring multiple analysis platforms that are not adapted for automated high-dimensional data analysis. Here, we introduce an integrated pipeline that combines several R packages to extract high-level biological understanding from largescale phosphoproteomic data by seamless integration with existing databases and knowledge resources. In a single run, PhosPiR provides data clean-up, fast data overview, multiple statistical testing, differential expression analysis, phospho-site annotation and translation across species, multi-level enrichment analyses, proteome-wide kinase activity and substrate mapping and network hub analysis. Data output includes graphical formats such as heatmap, box-, volcano- and circos-plots. This resource is designed to assist proteome-wide data mining of pathophysiological mechanism without a need for programming knowledge.
Control Cell Migration by Engineering Integrin Ligand Assembly
Authors: Hu Xunwu , Roy Sona Rani , Jin Chengzhi , Li Guanying , Zhang Qizheng , Natsuko Asano , Asahina Shunsuke , Kajiwara Tomoko , Feng Bolu , Aoki Kazuhiro , Takahara Atsushi , Zhang Ye 
Published: September 2021

Advances in mechanistic understanding of integrin-mediated adhesion highlight the importance of precise control of ligand presentation in directing cell migration. Top-down nanopatterning limited the spatial presentation to sub-micron. To enhance it to molecular level, we propose a bottom-up nanofabrication strategy. Via self-assembly and co-assembly, precise control of ligand presentation is succeeded by varying the proportions of assembling ligand and nonfunctional peptide. Assembled nanofilaments fulfill multi-functions exerting enhancement to suppression effect on cell migration with tunable amplitudes. Self-assembled nanofilaments possessing super high ligand density selectively suppress cancer cell migration by preventing integrin/actin disassembly at cell rear, which provides new insights to ligand-density-dependent-modulation, revealing valuable inputs to therapeutic innovations in tumor metastasis.One-Sentence SummaryEngineering integrin ligand assembly from bottom-up offers a generalized tool to selectively control cell migration with tunable amplitudes.
Chronic sodium bromide treatment relieves autistic-like behavioral deficits in three mouse models of autism
Authors: Derieux Cécile , Léauté Audrey , Brugoux Agathe , Jacaz Déborah , Pin Jean-Philippe , Kniazeff Julie , Merrer Julie Le , Becker Jerome AJ 
Published: September 2021

AbstractAutism Spectrum Disorders (ASD) are neurodevelopmental disorders whose diagnosis relies on deficient social interaction and communication together with repetitive behavior. To date, no pharmacological treatment has been approved that ameliorates social behavior in patients with ASD. Based on the excitation/inhibition imbalance theory of autism, we hypothesized that bromide ions, long used as an antiepileptic medication, could relieve core symptoms of ASD. We evaluated the effects of chronic sodium bromide (NaBr) administration on autistic-like symptoms in three genetic mouse models of autism: Oprm1-/- , Fmr1-/- and Shank3Δex13-16-/- mice. We showed that chronic NaBr treatment relieved autistic-like behaviors in these three models. In Oprm1-/- mice, these beneficial effects were superior to those of chronic bumetanide administration. At transcriptional level, chronic NaBr in Oprm1 null mice was associated with increased expression of genes coding for chloride ions transporters, GABAA receptor subunits, oxytocin and mGlu4 receptor. Lastly, we uncovered synergistic alleviating effects of chronic NaBr and a positive allosteric modulator (PAM) of mGlu4 receptor on autistic-like behavior in Oprm1-/- mice. We evidenced in heterologous cells that bromide ions behave as PAMs of mGlu4, providing a molecular mechanism for such synergy. Our data reveal the therapeutic potential of bromide ions, alone or in combination with a PAM of mGlu4 receptor, for the treatment of ASDs.
Investigation of a derived adverse outcome pathway (AOP) network for endocrine-mediated perturbations
Authors: Ravichandran Janani , Karthikeyan Bagavathy Shanmugam , Samal Areejit 
Published: September 2021

AbstractAn adverse outcome pathway (AOP) is a compact representation of the available mechanistic information on observed adverse effects upon environmental exposure. Sharing of events across individual AOPs has led to the emergence of AOP networks. Since AOP networks are expected to be functional units of toxicity prediction, there is current interest in their development tailored to specific research question or regulatory problem. To this end, we have developed a detailed workflow to construct a comprehensive endocrine-specific AOP (ED-AOP) network. Connectivity analysis of the ED-AOP network comprising 48 AOPs reveals 7 connected components and 12 isolated AOPs. Subsequently, we apply standard network measures to perform an in-depth analysis of the two largest connected components of the ED-AOP network. Notably, the graph-theoretic analyses led to the identification of important events including points of convergence or divergence in the ED-AOP network. Detailed analysis of the largest component in the ED-AOP network gives insights on the systems-level perturbations caused by endocrine disruption, emergent paths, and stressor-event associations. In sum, the derived ED-AOP network can be used to address the current knowledge gaps in the existing regulatory framework and aid in better risk assessment of environmental chemicals.