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Figure 6 from: Dedic M, Gutic S, Gicevic A, Becic E, Imamovic B, Markovic D, Ziga-Smajic N (2020) Application of membrane filters in determination of the adsorption of tetracycline hydrochloride on graphene oxide. Pharmacia 67(4): 339-345. https://doi.org/10.3897/pharmacia.67.e57242
Figure 6 Raman spectrum of thermally reduced graphene oxide.
Figure 3 from: Dedic M, Gutic S, Gicevic A, Becic E, Imamovic B, Markovic D, Ziga-Smajic N (2020) Application of membrane filters in determination of the adsorption of tetracycline hydrochloride on graphene oxide. Pharmacia 67(4): 339-345. https://doi.org/10.3897/pharmacia.67.e57242
Figure 3 FTIR spectrum of graphene oxide.
Figure 5 from: Dedic M, Gutic S, Gicevic A, Becic E, Imamovic B, Markovic D, Ziga-Smajic N (2020) Application of membrane filters in determination of the adsorption of tetracycline hydrochloride on graphene oxide. Pharmacia 67(4): 339-345. https://doi.org/10.3897/pharmacia.67.e57242
Figure 5 Raman spectrum of graphene oxide.
Figure 4 from: Dedic M, Gutic S, Gicevic A, Becic E, Imamovic B, Markovic D, Ziga-Smajic N (2020) Application of membrane filters in determination of the adsorption of tetracycline hydrochloride on graphene oxide. Pharmacia 67(4): 339-345. https://doi.org/10.3897/pharmacia.67.e57242
Figure 4 FTIR spectrogram of thermally reduced graphene oxide.
Figure 2 from: Dedic M, Gutic S, Gicevic A, Becic E, Imamovic B, Markovic D, Ziga-Smajic N (2020) Application of membrane filters in determination of the adsorption of tetracycline hydrochloride on graphene oxide. Pharmacia 67(4): 339-345. https://doi.org/10.3897/pharmacia.67.e57242
Figure 2 UV-Vis absorption spectrum of tetracycline hydrochloride.
Figure 1 from: Dedic M, Gutic S, Gicevic A, Becic E, Imamovic B, Markovic D, Ziga-Smajic N (2020) Application of membrane filters in determination of the adsorption of tetracycline hydrochloride on graphene oxide. Pharmacia 67(4): 339-345. https://doi.org/10.3897/pharmacia.67.e57242
Figure 1 Structure of graphene in the form of a hexagonal lattice (Garg et al. 2016).
Data from: Genome-wide survey of nuclear protein-coding markers for beetle phylogenetics and their application in resolving both deep and shallow-level divergences
Beetles (Coleoptera) are the most diverse and species-rich insect group, representing an impressive explosive radiation in the evolutionary history of insects, and their evolutionary relationships are often difficult to resolve. The amount of "traditional markers" (e.g., mitochondrial genes and nuclear rDNAs) for beetle phylogenetics is small and these markers often lack sufficient signals in resolving relationships for such a rapidly radiating lineage. Here, based on the available genome data of beetles and other related insect species, we performed a genome-wide survey to search nuclear protein-coding (NPC) genes suitable for research on beetle phylogenetics. As a result, we identified 1470 candidate loci, which provided a valuable data resource to the beetle evolutionary research community for NPC marker development. We randomly chose 180 candidate loci from the database to design primers and successfully developed 95 NPC markers which can be PCR amplified from standard genomic DNA extracts. These new nuclear markers are universally applicable across Coleoptera, with an average amplification success rate of 90%. To test the phylogenetic utility, we used them to investigate the backbone phylogeny of Coleoptera (18 families sampled) and the family Coccinellidae (39 species sampled). Both phylogenies are well resolved (average bootstrap support > 95%), showing that our markers can be used to address phylogenetic questions of various evolutionary depth (from species level to family level). In general, the newly developed nuclear markers are much easier to use and more phylogenetically informative than the "traditional markers", and show great potential to expedite resolution of many parts in the Beetle Tree of Life.
Data from: Genetic identification of Iberian rodent species using both mitochondrial and nuclear loci: application to non-invasive sampling
Species identification through non-invasive sampling is increasingly used in animal conservation genetics, given that it obviates the need to handle free-living individuals. Non-invasive sampling is particularly valuable for elusive and small species such as rodents. Although rodents are not usually assumed to be the most obvious target for conservation, of the 21 species or near-species present in Iberia, three are considered endangered and declining while several others are poorly studied. Here we develop a genetic tool for identifying all rodent species in Iberia by non-invasive genetic sampling. To achieve this purpose we selected one mitochondrial gene (cytochrome b – cyt-b) and one nuclear gene (interphotoreceptor retinoid-binding protein – IRBP), which we first sequenced using tissue samples. Both genes allow for the phylogenetic distinction of all species except the sibling species Microtus lusitanicus and M. duodecimcostatus. Overall, cyt-b showed higher resolution than IRBP, revealing a clear barcoding gap. To allow these markers to be applied to non-invasive samples, we selected a short highly-diagnostic fragment from each gene, which we used to obtain sequences from faeces and bones from owl pellets. Amplification success for the cyt-b and IRBP fragment was 85% and 43% in faecal and 88% and 64% in owl-pellet DNA extractions, respectively. The method allows the unambiguous identification of the great majority of Iberian rodent species from non-invasive samples, with application in studies of distribution, spatial ecology and population dynamics, and for conservation.
Data from: A broadly applicable COI primer pair and an efficient single‐tube amplicon library preparation protocol for metabarcoding
The nucleotide variation in the cytochrome c oxidase subunit I (COI) gene makes it ideal for assigning sequences to species. However, this variability also makes it difficult to design truly universal primers. Here, we present the forward primer "Sauron-S878", specifically designed to facilitate library preparation for metabarcoding. This primer is modified to improve the coverage of terrestrial species compared to the primer mCOIintF, optimized for aquatic systems, which raised the in-silico coverage from 74.4% to 98.3% of available NCBI sequences (perfect match in 3'-region, up to 3 mismatches in remaining primer). When paired with the reverse primer "jgHCO2198" (fragment length ~313 bp) these primers amplified 98.4% of 255 tested DNA extracts from various taxa, which is better than many other common COI barcoding primers. Furthermore, a single tube protocol was developed, wherein these primers amplify the target gene, and attach MIDs and Illumina sequencing adapters in one reaction. This eliminates the need for re-amplification or enzymatic ligation during library preparation while keeping the flexibility to modularly combine primers and MIDs. Using the single tube approach, three replicates of three mock samples were sequenced on a MiSeq platform with no adverse effects compared to commercial Nextera indexing kits. From this run 75% of all included taxa could be recovered, with no considerable bias among taxonomic groups. Despite the fact that 98.4% of the extracts were confirmed to amplify in-vitro, this number was lower than expected. A reason for this discrepancy was a clear link between the relative concentration of a specific DNA type in the template and the number of returned reads for this DNA. We would argue that such a bias may be especially problematic in metabarcoding where samples usually contain trace DNA in unknown amounts. However, how this affects the completeness of metabarcoding results has yet been poorly investigated.
Data from: A nuclear DNA barcode for eastern North American oaks and application to a study of hybridization in an Arboretum setting
DNA barcoding has proved difficult in a number of woody plant genera, including the ecologically important oak genus Quercus. In this study, we utilized restriction-site associated DNA sequencing (RAD-seq) to develop an economical single-nucleotide polymorphism (SNP) DNA barcoding system that suffices to distinguish eight common, sympatric eastern North American white oak species. Two de novo clustering pipelines, PyRAD and Stacks, were used in combination with post-clustering bioinformatic tools to generate a list of 291 potential SNPs, 80 of which were included in a barcoding toolkit that is easily implemented using MassARRAY mass spectrometry technology. As a proof-of-concept, we used the genotyping toolkit to infer potential hybridization between North American white oaks transplanted outside of their native range (Q. michauxii, Q. montana, Q muehlenbergii/ Q. prinoides and Q. stellata) among natural forests of locally native trees (Q. alba and Q. macrocarpa) in the living collection at The Morton Arboretum (Lisle, IL, USA). Phylogenetic and clustering analyses suggested low rates of hybridization between cultivated and native species, with the exception of one Q. michauxii mother tree, the acorns of which exhibited high admixture from either Q. alba or Q. stellata and Q. macrocarpa; and a hybrid between Q. stellata that appears to have backcrossed almost exclusively to Q. alba. Together, RAD-seq and MassARRAY technologies allow for efficient development and implementation of a multispecies barcode for one of the more challenging forest tree genera.
Data from: Integrated analysis and visualization of group differences in structural and functional brain connectivity: applications in typical ageing and schizophrenia
Structural and functional brain connectivity are increasingly used to identify and analyze group differences in studies of brain disease. This study presents methods to analyze uni- and bi-modal brain connectivity and evaluate their ability to identify differences. Novel visualizations of significantly different connections comparing multiple metrics are presented. On the global level, "bi-modal comparison plots" show the distribution of uni- and bi-modal group differences and the relationship between structure and function. Differences between brain lobes are visualized using "worm plots". Group differences in connections are examined with an existing visualization, the "connectogram". These visualizations were evaluated in two proof-of-concept studies: (1) middle-aged versus elderly subjects; and (2) patients with schizophrenia versus controls. Each included two measures derived from diffusion weighted images and two from functional magnetic resonance images. The structural measures were minimum cost path between two anatomical regions according to the "Statistical Analysis of Minimum cost path based Structural Connectivity" method and the average fractional anisotropy along the fiber. The functional measures were Pearson's correlation and partial correlation of mean regional time series. The relationship between structure and function was similar in both studies. Uni-modal group differences varied greatly between connectivity types. Group differences were identified in both studies globally, within brain lobes and between regions. In the aging study, minimum cost path was highly effective in identifying group differences on all levels; fractional anisotropy and mean correlation showed smaller differences on the brain lobe and regional levels. In the schizophrenia study, minimum cost path and fractional anisotropy showed differences on the global level and within brain lobes; mean correlation showed small differences on the lobe level. Only fractional anisotropy and mean correlation showed regional differences. The presented visualizations were helpful in comparing and evaluating connectivity measures on multiple levels in both studies.
Data from: Potential application of the Oryza sativa monodehydroascorbate reductase gene (OsMDHAR) to improve the stress tolerance and fermentative capacity of Saccharomyces cerevisiae
Monodehydroascorbate reductase (MDHAR; EC 1.6.5.4) is an important enzyme for ascorbate recycling. To examine whether heterologous expression of MDHAR from Oryza sativa (OsMDHAR) can prevent the deleterious effects of unfavorable growth conditions, we constructed a transgenic yeast strain harboring a recombinant plasmid carrying OsMDHAR (p426GPD::OsMDHAR). OsMDHAR-expressing yeast cells displayed enhanced tolerance to hydrogen peroxide by maintaining redox homoeostasis, proteostasis, and the ascorbate (AsA)-like pool following the accumulation of antioxidant enzymes and molecules, metabolic enzymes, and molecular chaperones and their cofactors, compared to wild-type (WT) cells carrying vector alone. The addition of exogenous AsA or its analogue isoascorbic acid increased the viability of WT and ara2Δ cells under oxidative stress. Furthermore, the survival of OsMDHAR-expressing cells was greater than that of WT cells when cells at mid-log growth phase were exposed to high concentrations of ethanol. High OsMDHAR expression also improved the fermentative capacity of the yeast during glucose-based batch fermentation at a standard cultivation temperature (30°C). The alcohol yield of OsMDHAR-expressing transgenic yeast during fermentation was approximately 25% (0.18 g·g-1) higher than that of WT yeast. Accordingly, OsMDHAR-expressing transgenic yeast showed prolonged survival during the environmental stresses produced during fermentation. These results suggest that heterologous OsMDHAR expression increases tolerance to reactive oxygen species-induced oxidative stress by improving cellular redox homeostasis and improves survival during fermentation, which enhances fermentative capacity.
Data from: Improved demethylation in ecological epigenetic experiments: testing a simple and harmless foliar demethylation application
1. Experimental demethylation of plant DNA enables testing for epigenetic effects in a simple and straightforward way without the use of expensive and laborious DNA sequencing. Plants are commonly demethylated during their germination with the application of agents such as 5-azacytidine (5-azaC). However, this approach can cause unwanted effects such as underdeveloped root systems and high mortality of treated plants, hindering a full comparison with untreated plants, and can be applied only on plant reproducing by seeds. Here we test a simple alternative method of plant demethylation, designed to overcome the shortcomings of the germinating method. 2. We compared a novel method of demethylating plants, based on periodical spraying of 5-azaC aqueous solution on established seedlings, with the previous method in which seeds were germinated directly in 5-azaC solution. We quantified the amount of methylated DNA and measured various aspects of plant performance. Also, we demonstrated its applicability in ecological epigenetic experiments, by testing transgenerational effects of plant-plant competition. 3. We found that the spray application had similar DNA-demethylating efficiency than the germination method, particularly in the earlier phases of plant development, but without unwanted effects. The spray application method did not reduce plant growth and performance compared to untreated plants, as opposed to the traditional method which showed reduced growth. Also, the spray application method equalized the epigenetically-modified plant features of seedlings coming from plants grown under competition and plants growing without competition, demonstrating its application in ecological epigenetic experiments. 4. We conclude that regular spraying of 5-azaC solution onto established seedlings surpassed the germination-in-solution method in terms of vigor and fitness of treated plants. This novel method could thus be better suited for experimental studies seeking valuable insights into ecological epigenetics. Furthermore, the spray method can be suitable for clonal species reproducing asexually, and, most importantly, it opens the possibility of community-level experimental demethylation of plants.
Data from: Optimized application of the secreted Nano-luciferase reporter system using an affinity purification strategy
Secreted Nano-luciferase (secNluc) is a newly engineered secreted luciferase that possesses advantages of high structural stability, long half-life, and glow-type kinetics together with high light emission intensity, and thus would become one of the most valuable tools for bioluminescence assays. However, like other secreted luciferases, secNluc has to mix with the components in the conditioned medium surrounding test cells, or in the biological samples such as blood or urine after being secreted. These components may interfere with secNluc-catalyzed bioluminescence reactions and thus limit the application of the secNluc reporter system. In this study, we first examined the effects of three factors, pH, serum and residual reagents, on secNluc-catalyzed bioluminescence reactions, finding that these factors could interfere with bioluminescence reactions and result in background signal. To resolve these problems, we applied a simple affinity purification strategy in which secNluc was fused with a FLAG-tag, and anti-FLAG magnetic beads were used to catch and transfer the fusion protein to PBST, an optimal buffer for secNluc-catalyzed bioluminescence reactions that was identified in this study. The results indicated that this strategy could not only negate the interferences from serum or residual reagents and enhance the stability of light emission but also greatly increase signal intensity through enzyme enrichment. This strategy may contribute to biomedical studies that utilize secNluc and other secreted luciferases, especially those requiring superior sensitivity, low background noise and high reproducibility.
Data from: Machine learning to classify animal species in camera trap images: applications in ecology
Motion‐activated cameras ("camera traps") are increasingly used in ecological and management studies for remotely observing wildlife and are amongst the most powerful tools for wildlife research. However, studies involving camera traps result in millions of images that need to be analysed, typically by visually observing each image, in order to extract data that can be used in ecological analyses. We trained machine learning models using convolutional neural networks with the ResNet‐18 architecture and 3,367,383 images to automatically classify wildlife species from camera trap images obtained from five states across the United States. We tested our model on an independent subset of images not seen during training from the United States and on an out‐of‐sample (or "out‐of‐distribution" in the machine learning literature) dataset of ungulate images from Canada. We also tested the ability of our model to distinguish empty images from those with animals in another out‐of‐sample dataset from Tanzania, containing a faunal community that was novel to the model. The trained model classified approximately 2,000 images per minute on a laptop computer with 16 gigabytes of RAM. The trained model achieved 98% accuracy at identifying species in the United States, the highest accuracy of such a model to date. Out‐of‐sample validation from Canada achieved 82% accuracy and correctly identified 94% of images containing an animal in the dataset from Tanzania. We provide an r package (Machine Learning for Wildlife Image Classification) that allows the users to (a) use the trained model presented here and (b) train their own model using classified images of wildlife from their studies. The use of machine learning to rapidly and accurately classify wildlife in camera trap images can facilitate non‐invasive sampling designs in ecological studies by reducing the burden of manually analysing images. Our r package makes these methods accessible to ecologists.
Application of the SAFT- g Mie group contribution equation of state to fluids of relevance to the oil and gas industry
<p>Calculated data for all the figures presented in publication.</p>
Additional Data from ``Developments in Stochastic Coupled Cluster Theory: The initiator approximation and application to the Uniform Electron Gas''
<p>We describe further details of the Stochastic Coupled Cluster method and a diagnostic of such calculations, the shoulder height, akin to the plateau found in Full Configuration Interaction Quantum Monte Carlo. We describe an initiator modification to Stochastic Coupled Cluster Theory and show that initiator calculations can be extrapolated to the unbiased limit. We apply this method to the 3D 14-electron uniform electron gas and present complete basis set limit values of the CCSD and previously unattainable CCSDT correlation energies for up to $r_s=2$, showing a requirement to include triple excitations to accurately calculate energies at high densities.</p>
Feedback results for application to "Fondos de Cultura", Chile in 2017
<p>This dataset shows numeric results to the feedback given to the application of "Fondos de Cultura" in Chile for 2017.</p>
Scalable SAT Solving and its Application | Experimental Data
<p>Experimental data accompanying the doctoral thesis of Dominik P. Schreiber entitled "Scalable SAT Solving and its Application", Karlsruhe Institute of Technology, 2023.</p><p>Upstream URL: <a href="https://github.com/domschrei/sssaia">https://github.com/domschrei/sssaia</a></p><p>--</p><p>Funding notices:</p><p>This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 882500).</p><p>Some of this work was performed on the supercomputer ForHLR funded by the Ministry of Science, Research and the Arts Baden-W ̈urttemberg and by the Federal Ministry of Education and Research.</p><p>Some of this work was performed on the HoreKa supercomputer funded by the Ministry of Science, Research and the Arts Baden-Württemberg and by the Federal Ministry of Education and Research.</p><p>The author gratefully acknowledges the Gauss Centre for Supercomputing e.V. (www.gauss-centre.eu) for funding this project by providing computing time on the GCS Supercomputer SuperMUC-NG at Leibniz Supercomputing Centre (www.lrz.de).</p>
Supplementary material to "SnowPappus v1.0, a blowing-snow model for large-scale applications of Crocus snow scheme" : Pleiades snow depth maps analysis
<p>This Folder contains :</p><p> - necessary codes to reprduce Fig. 5, 12 and 13 of the third version of the submitted manuscript SnowPappus v1.0, a blowing-snow model for large-scale applications of Crocus snow scheme"</p><p> - necessary data to run these codes, including extracts of simulation outputs</p><p> - A readme.txt which explains how to run everything</p><p> </p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.