bluuebunny/crossref_metadata_2025_split huggingface dataset:
enviLink: A database linking contaminant biotransformation rules to enzyme classes in support of functional association mining
Authors: Schmid Emanuel , Fenner Kathrin 
Published: May 2021

AbstractMotivationThe ability to assess and engineer biotransformation of chemical contaminants present in the environment requires knowledge on which enzymes can catalyze specific contaminant biotransformation reactions. For the majority of over 100’000 chemicals in commerce such knowledge is not available. Enumeration of enzyme classes potentially catalyzing observed orde novopredicted contaminant biotransformation reactions can support research that aims at experimentally uncovering enzymes involved in contaminant biotransformation in complex natural microbial communities.DatabaseenviLink is a new data module integrated into the enviPath database and contains 316 theoretically derived linkages between generalized biotransformation rules used for contaminant biotransformation prediction in enviPath and 3rdlevel EC classes. Rule-EC linkages have been derived using two reaction databases, i.e., Eawag-BBD in enviPath, focused on contaminant biotransformation reactions, and KEGG. 32.6% of identified rule-EC linkages overlap between the two databases, whereas 40.2% and 27.2%, respectively, are originating from Eawag-BBD and KEGG only.Implementation and availabilityenviLink is encoded in RDF triples as part of the enviPath RDF database. enviPath is hosted on a public webserver (envipath.org) and all data is freely available for non-commercial use. enviLink can be searched online for individual transformation rules of interest (https://tinyurl.com/y63ath3k) and is also fully downloadable from the supporting materials (i.e., Jupyter notebook “enviLink” and tsv files provided through GitHub athttps://github.com/emanuel-schmid/enviLink).
Weaning age and its effect on the development of the swine gut microbiome and resistome
Authors: Holman Devin B , Gzyl Katherine E. , Mou Kathy T. , Allen Heather K. 
Published: May 2021

AbstractPiglets are often weaned between 19 and 22 d of age in North America although in some swine operations this may occur at 14 d or less. Piglets are abruptly separated from their sow at weaning and are quickly transitioned from sow’s milk to a plant-based diet. The effect of weaning age on the long-term development of the pig gut microbiome is largely unknown. Here, pigs were weaned at either 14, 21, or 28 d of age and fecal samples collected 20 times from d 4 (neonatal) through to marketing at d 140. The fecal microbiome was characterized using 16S rRNA gene and shotgun metagenomic sequencing. The fecal microbiome of all piglets shifted significantly three to seven days post-weaning with an increase in microbial diversity. SeveralPrevotellaspp. increased in relative abundance immediately after weaning as did butyrate-producing species such asButyricicoccus porcorum, Faecalibacterium prausnitzii, andMegasphaera elsdenii. Within 7 days of weaning, the gut microbiome of pigs weaned at 21 and 28 days of age resembled that of pigs weaned at 14 d. Resistance genes to most antimicrobial classes decreased in relative abundance post-weaning with the exception of those conferring resistance to tetracyclines and macrolides-lincosamides-streptogramin B. The relative abundance of microbial carbohydrate-active enzymes (CAZymes) changed significantly in the post-weaning period with an enrichment of CAZymes involved in degradation of plant-derived polysaccharides. These results demonstrate that the pig gut microbiome tends change in a predictable manner post-weaning and that weaning age has only a temporary effect on this microbiome.ImportancePiglets are abruptly separated from their sow at weaning and are quickly transitioned from sow’s milk to a plant-based diet. This is the most important period in commercial swine production yet the effect of weaning age on the long-term development of the pig gut microbiome is largely unknown. Metagenomic sequencing allows for a higher resolution assessment of the pig gut microbiome and enables characterization of the resistome. Here we used metagenomic sequencing to identify bacterial species that were enriched post-weaning and therefore may provide targets for future manipulation studies. In addition, functional profiling of the microbiome indicated that many carbohydrate and metabolic enzymes decrease in relative abundance of after weaning. This study also highlights the challenges faced in reducing antimicrobial resistance in pigs as genes conferring tetracycline and macrolide resistance remained relatively stable from 7 days of age through to market weight at 140 d despite no exposure to antimicrobials.
Identification ofLagopus muta japonicaplant food resources in the Northern Japan Alps using DNA metabarcoding
Authors: Fujii Taichi , Ueno Kaoru , Shirako Tomoyasu , Nakamura Masatoshi , Minami Motoyasu 
Published: May 2021

AbstractDNA metabarcoding was employed to identify plant-derived food resources of the Japanese rock ptarmigan (Lagopus muta japonica), registered as a natural living monument in Japan, in the Northern Japanese Alps in Toyama Prefecture, Japan, in July to October, 2015-2018. By combined use ofrbcLand ITS2 local databases of 74 alpine plant species found in the study area, a total of 43 plant taxa were identified and could be assigned to 40 species (93.0%), two genera (4.7%), and one family (2.3%). Rarefaction analysis of each sample collection period showed that this study covered more than 90% of the plant food resources found in the study area. Of the 21 plant families identified using the combinedrbcLand ITS2 local databases, the most dominant families were Ericaceae (98.1% of 105 fecal samples), followed by Rosaceae (42.9%), Apiaceae (35.2%), and Poaceae (19.0%). In all fecal samples examined, the most frequently encountered plant species wereVaccinium ovalifoliumvar.ovalifolium(69.5%), followed byEmpetrum nigrumvar.japonicum(68.6%),Vacciniumsp. (54.3%),Kalmia procumbens(42.9%), andTilingia ajanensis(34.3%). Rarefaction analysis of each collection period in the study revealed that this study covered more than 90% (from 91.0% in July to 97.5% in September) of the plant food resources found in the study area, and 98.1% of the plant food taxa were covered throughout the entire study period. Thus, DNA metabarcoding using therbcLand ITS2 local databases of alpine plants in combination and rarefaction analysis are considered to be well suited for estimating the dominant food plants in the diet of Japanese rock ptarmigans. Further, the local database constructed in this study can be used to survey other areas with similar flora.
Mosquito-bacteria interactions during larval development trigger metabolic changes with carry-over effects on adult fitness
Authors: Giraud Émilie , Varet Hugo , Legendre Rachel , Sismeiro Odile , Aubry Fabien , Dabo Stéphanie , Dickson Laura B. , Moro Claire Valiente , Lambrechts Louis 
Published: May 2021

AbstractIn animals with distinct life stages such as holometabolous insects, adult phenotypic variation is often shaped by the environment of immature stages, including their interactions with microbes colonizing larval habitats. Such carry-over effects were previously observed for several adult traits of the mosquito Aedes aegypti after larval exposure to different bacteria, but the mechanistic underpinnings are unknown. Here, we investigated the molecular changes triggered by gnotobiotic larval exposure to different bacteria in Ae. aegypti. We initially screened a panel of 16 bacterial isolates from natural mosquito breeding sites to determine their ability to influence adult life-history traits. We subsequently focused on four bacterial isolates (belonging to Flavobacterium, Lysobacter, Paenibacillus, and Enterobacteriaceae) with significant carry-over effects on adult survival and found that they were associated with distinct transcriptomic profiles throughout mosquito development. Moreover, we detected carry-over effects at the level of gene expression for the Flavobacterium and Paenibacillus isolates. The most prominent transcriptomic changes in gnotobiotic larvae reflected a profound remodeling of lipid metabolism, which translated into phenotypic differences in lipid storage and starvation resistance at the adult stage. Together, our findings indicate that larval exposure to environmental bacteria trigger substantial physiological changes that impact adult fitness, uncovering a mechanism underlying carry-over effects of mosquito-bacteria interactions during larval development.
NMR chemical shift assignments of RNA oligonucleotides to expand the RNA chemical shift database
Authors: Liu Yaping , Kotar Anita , Hodges Tracy L. , Abdallah Kyrillos , Taleb Mallak H. , Bitterman Brayden A. , Jaime Sara , Schaubroeck Kyle J. , Mathew Ethan , Morgenstern Nicholas W. , Lohmeier Anthony , Page Jordan L. , Ratanapanichkich Matt , Arhin Grace , Johnson Breanna L. , Cherepanov Stanislav , Moss Stephen C. , Zuniga Gisselle , Tilson Nicholas J. , Yeoh Zoe C. , Johnson Bruce A. , Keane Sarah C. 
Published: May 2021

AbstractRNAs play myriad functional and regulatory roles in the cell. Despite their significance, three-dimensional structure elucidation of RNA molecules lags significantly behind that of proteins. NMR-based studies are often rate-limited by the assignment of chemical shifts. Automation of the chemical shift assignment process can greatly facilitate structural studies, however, accurate chemical shift predictions rely on a robust and complete chemical shift database for training. We searched the Biological Magnetic Resonance Data Bank (BMRB) to identify sequences that had no (or limited) chemical shift information. Here, we report the chemical shift assignments for 12 RNA hairpins designed specifically to help populate the BMRB.
The role of AUX1 during lateral root development in the domestication of the model C4 grass Setaria italica
Authors: Tang Sha , Shahriari Mojgan , Xiang Jishan , Pasternak Taras , Igolkina Anna , Aminizade Somayeh , Zhi Hui , Gao Yuanzhu , Roodbarkelari Farshad , Sui Yi , Jia Guanqing , Wu Chuanyin , Li Xugang , Meshcheryakov Georgy , Samsonova Maria , Diao Xianmin , Palme Klaus , Teale William 
Published: May 2021

AbstractC4 photosynthesis increases the efficiency of carbon fixation by spatially separating high concentrations of molecular oxygen from rubisco. The specialized leaf anatomy required for this separation evolved independently many times. C4 root systems are highly branched, an adaptation thought to support high rates of photosynthesis; however, little is known about the molecular mechanisms that have driven the evolution of C4 root system architecture (RSA). Using a mutant screen in the C4 model plant Setaria italica, we identify siaux1-1 and siaux1-2 as RSA mutants, and use CRISPR/cas9-mediated genome editing and overexpression to confirm the importance of the locus. As AUX1 is not necessary for lateral root emergence in S. viridis, the species from which S. italica was domesticated, we conducted an analysis of auxin responsive elements in the promoters of auxin-responsive gene families in S. italica, and explore the molecular basis of SiAUX1’s role in seedling development using an RNAseq analysis of wild type and siaux1-1 plants. Finally, we use a root coordinate system to compare cell-by-cell meristem structures in siaux1-1 and wild type Setaria plants, observing changes in the distribution of cell volumes in all cell layers and a dependence in the frequency of protophloem and protoxylem strands on siAUX1.
Functional dissection of human mitotic genes using CRISPR-Cas9 tiling screens
Authors: Herman Jacob A. , Carter Lucas , Arora Sonali , Zhu Jun , Biggins Sue , Paddison Patrick J. 
Published: May 2021

SUMMARYKinetochores are large protein complexes that assemble at the centromere and bind to mitotic spindle microtubules to ensure accurate chromosome segregation. Like most protein-coding genes, the full multifunctional nature of kinetochore factors remains uncharacterized due to the limited experimental tools for unbiased dissection of human protein sequences. We developed a method that leverages CRISPR-Cas9 induced mutations to identify key functional regions within protein sequences required for cellular outgrowth. Our analysis of 48 human mitotic genes revealed hundreds of regions required for cell proliferation, including known domains and uncharacterized ones. We validated the essential nature for 15 of these regions, including amino acids 387-402 of Mad1, which identified an unknown domain that contributes to Mad1 kinetochore localization and chromosome segregation fidelity. Altogether, we demonstrate that CRISPR-Cas9-based tiling mutagenesis identifies key functional domains in protein-coding genesde novo, which elucidates separation of function mutants and allows functional annotation across the human proteome.
Geodesic-based distance reveals non-linear topological features in neural activity from mouse visual cortex
Authors: Beshkov Kosio , Tiesinga Paul 
Published: May 2021

AbstractAn increasingly popular approach to the analysis of neural data is to treat activity patterns as being constrained to and sampled from a manifold, which can be characterized by its topology. The persistent homology method identifies the type and number of holes in the manifold thereby yielding functional information about the coding and dynamic properties of the underlying neural network. In this work we give examples of highly non-linear manifolds in which the persistent homology algorithm fails when it uses the Euclidean distance which does not always yield a good approximation of the true distance distribution of a point cloud sampled from a manifold. To deal with this issue we propose a simple strategy for the estimation of the geodesic distance which is a better approximation of the true distance distribution and can be used to successfully identify highly non-linear features with persistent homology. To document the utility of our method we model a circular manifold, based on orthogonal sinusoidal basis functions and compare how the chosen metric determines the performance of the persistent homology algorithm. Furthermore we discuss the robustness of our method across different manifold properties and point out strategies for interpreting its results as well as some possible pitfalls of its application. Finally we apply this analysis to neural data coming from the Visual Coding - Neuropixels dataset recorded in mouse visual cortex after stimulation with drifting gratings at the Allen Institute. We find that different manifolds with a non-trivial topology can be seen across regions and stimulus properties. Finally, we discuss what these manifolds say about visual computation and how they depend on stimulus parameters.
Dioxidomolybdenum(VI) complex featuring a 2,4-difluoro-substituted amine bis(phenolate) ligand
Authors: Bowen Christina L. , Wile Bradley M. 
Published: May 2021

Synthetic complexes containing a cis-[MoO2]2+ core are well-established models for the molybdenum co-factor (Moco). Here we report the crystal structure of such a model complex bearing a tetradentate amine bis(phenolate) ligand with fluorine substituents on the phenolate rings, namely, [2,2′-({[2-(dimethylamino)ethyl]azanediyl}bis(methylene))bis(4,6-difluorophenolato)]dioxidomolybdenum(VI)), [Mo(C18H18F4N2O2)O2]. Distortion from idealized octahedral symmetry about the Mo center is evident in the large O=Mo=O angle [108.54 (4)°] and the small N–Mo–Ophenolate angles [79.79 (4), 81.21 (3), 77.83 (3), and 84.59 (3)°]. The dihedral angle between the phenolate rings is 60.06 (4)°, and π–π stacking is observed between aromatic rings related by inversion (1 − x, 1 − y, 1 − z). The lower data-collection temperature of 150 K vs room-temperature data collection reported previously [KOWXIF; Cao et al. (2014). Transit. Met. Chem.
39, 933–937] and larger 2θ range for data collection (5.8–66.6° versus 6–54.96°) led to a structure with lower R
1 and ωR
2 values (0.019 and 0.049 vs 0.0310 and 0.0566 for KOWXIF). Comparison of the metrical parameters with KOWXIF suggests that this dataset offers a more realistic depiction of bonding within the MoVI=O moiety.
Revenue diversification and financial sustainability of microfinance institutions
Authors: Githaiga Peter Nderitu 
Published: May 2021

PurposeThis paper aims to investigate whether revenue diversification affects the financial sustainability of microfinance institutions (MFIs).Design/methodology/approachThe study uses a worldwide panel data set of 443 MFIs in 108 countries for the period 2013–2018 and two-step system Generalized Method of Moments estimation model.FindingsThe study finds that revenue diversification has a significant and positive effect on the financial sustainability of MFIs.Practical implicationsThe findings of this study actually offer important managerial and policy lessons on MFIs’ financial sustainability. Microfinance managers and policymakers should consider revenue diversification as a strategy through which MFIs can attain financial sustainability instead of overreliance on donations and government subsidiesOriginality/valueUnlike previous studies that examined revenue diversification in the context of banking firms, this study contributes to literature by examining the impact of revenue diversification of the financial sustainability of MFIs.
Time domain finite element method for metamaterial-based low frequency near field systems
Authors: Gong Zhi , Yang Shiyou 
Published: May 2021

PurposeThe purpose of this work is to develop a computational paradigm for performance analysis of low-frequency electromagnetic devices containing both magnetic metamaterials (MTMs) and natural media.Design/methodology/approachA time domain finite element method (TDFEM) is proposed. The electromagnetic properties of the MTMs are modeled by a nonstandard Lorentz model. The time domain governing equation is derived by converting the one from the frequency domain into the time domain based on the Laplace transform and convolution. The backward difference is used for the temporal discretization. An auxiliary variable is introduced to derive the recursive formula.FindingsThe numerical results show good agreements between the time domain solutions and the frequency domain solutions. The error convergence trajectory of the proposed TDFEM conforms to the first-order accuracy.Originality/valueTo the best knowledge of the authors, the presented work is the first one focusing on TDFEMs for low-frequency near fields computations of MTMs. Consequently, the proposed TDFEM greatly benefits the future explorations and performance evaluations of MTM-based near field devices and systems in low-frequency electrical and electronic engineering.
Are Japanese university students ready for remote language learning?
Authors: Hirata Yoko 
Published: May 2021

Purpose
The purpose of this study is to assess Japanese university students’ readiness for taking e-learning language courses. The focus is placed on students’ self-analysis of their abilities to use their smart devices for remote language learning activities.

Design/methodology/approach
Japanese university students’ readiness for the shift towards remote learning has been measured by a self-reported online survey. The question items are based on three categories of Gay’s e-readiness models (2018). The survey was conducted before and after the fully online five-month English courses to examine to what extent students’ e-readiness had changed through the progress of the courses.

Findings
The results suggest that students have few difficulties using the university e-learning software provided. However, students reported limited enthusiasm and aptitude for the online English language learning components. These levels were approximately the same before and after the courses, with the exception of increased online learning confidence.

Originality/value
This study evaluates to what extent groups of Japanese university students’ e-readiness has changed over time. The survey looks at different perspectives including Web research, time management, enthusiasm for online language learning and their thoughts and opinions about interacting with their classmates. Although the sample size is small, the discussion considers the data in the context of the Japanese learning environment and existing e-readiness research, seeking to provide teaching insights for instructors and suggestions for further research.
A decision support healthcare system based on IoT and neural network technique
Authors: Fahmy Khadeja Al_Sayed , Yahya Ahmed , Zorkany M. 
Published: May 2021

Purpose
The purpose of this paper is to develop e-health and patient monitoring systems remotely to overcome the difficulty of patients going to hospitals especially in times of epidemics such as virus disease (COVID-19). Artificial intelligence (AI) technology will be combined Internet of Things (IoT) in this research to overcome these challenges. The research aims to select the most appropriate, best-hidden layers numbers and the activation function types for the neural network (NN). Then, define the patient data sent through protocols of the IoT. NN checks the patient’s medical sensors data to make the appropriate decision. Then it sends this diagnosis to the doctor. Using the proposed solution, the patients can diagnose and expect the disease automatically and help physicians to discover and analyze the disease remotely without the need for patients to go to the hospital.

Design/methodology/approach
AI technology will be combined with the IoT in this research. The research aims to select the most appropriate’ best-hidden layers numbers’ and the activation function types for the NN.

Findings
Decision support health-care system based on IoT and deep learning techniques was proposed. The authors checked out the ability to integrate the deep learning technique in the automatic diagnosis and IoT abilities for speeding message communication over the internet has been investigated in the proposed system. The authors have chosen the appropriate structure of the NN (best-hidden layers numbers and the activation function types) to build the e-health system is performed in this work. Also, depended on the data from expert physicians to learn the NN in the e-health system. In the verification mode, the overall evaluation of the proposed diagnosis health-care system gives reliability under different patient’s conditions. From evaluation and simulation results, it is clear that the double hidden layer of feed-forward NN and its neurons contain Tanh function preferable than other NN.

Originality/value
AI technology will be combined IoT in this research to overcome challenges. The research aims to select the most appropriate, best-hidden layers numbers and the activation function types for the NN.