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1,923 results for “compounding”
Supplementary Data: Fungal biostarter and bacterial occurrence of dry-aged beef: the sensory quality and volatile aroma compounds after 21 days of aging
<p>This dataset contains data generated during realisation of the project Tango-IV-C/0005/2019: Biostarters development for dry aged beef production, funded by National Centre for Research and Development (Poland). These data were used to prepare paper entitled "Fungal biostarter and bacterial occurrence of dry-aged beef: the sensory quality and volatile aroma compounds after 21 days of aging" by Wiesław Przybylski , Danuta Jaworska, Paweł Kresa, Grzegorz Michał Ostrowski, Magdalena Płecha, Dorota Korsak, Dorota Derewiaka, Lech Adamczak, Urszula Siekierko, Julia Pawłowska.</p>
NMR data of all compounds appearing in the study "Visible Light-Mediated Formal Alkylation and [4+1]-Cycloaddition Strategies of Silyl Enol Ethers with Aryldiazoacetates"
<p>FID files of NMR data (<em>e.g.</em> 1H, 13C{1H}, 19F{1H}, COSY, HSQC, DEPT135 and HMBC) associated with all compounds synthesized during the study entitled "Visible Light-Mediated Reactions of Silyl Enol Ethers with Aryldiazoacetates: Formal Alkylation and [4+1]-Cycloaddition Strategies" (a research project in organic synthesis)</p>
A Competing Compound For Remdesivir and Molnupiravir In Inhibiting RdRp Protein of COVID-19
<p>According to a docking study conducted with the online tool [1][2], the compound Nicotinate mononucleotide with the formula C11H15NO9P+ could inhibit RNA-dependent RNA polymerase (RdRp (RTP site)) protein in COVID-19 coronavirus, with a Score Value of -9.4 (kcal / mol). This is better than the amount for the Remdesivir molecule (-9.2 (kcal / mol)) and after MW correction, it is also better than Molnupiravir, to inhibit the same protein. Since inhibition of this protein plays a key role in the inhibitory function of Remdesivir against COVID-19 virus [3], we can see the Nicotinate mononucleotide compound as an alternative to Remdesivir in inhibiting this coronavirus. Since the molecular weight of Nicotinate mononucleotide (336 g / mol) is approximately half that of Remdesivir (603 g / mol) and Molnupiravir-active-form (499.16 g / mol), it is better in terms of both protein adhesion and absorption capacity. Since the main precursor of Nicotinate mononucleotide, Trigonelline alkaloid, is a naturally occurring plant secondary metabolite, and Nicotinate mononucleotide itself is present in mammalian biomolecular pathways, it is likely to be more available, more cost-effective, and more non-toxic and be better than Remdesivir and Molnupiravir. Please see added data.</p>
Anti-inflammatory compounds in probiotic yeast revealed by untargeted metabolomics
<p><strong>Abstract</strong></p> <p>The saccharomyces strain <em>Saccharomyces cerevisiae </em>var.<em> boulardii</em> has exhibited efficacy in ameliorating symptoms of gastrointestinal disorders, including inflammatory diseases. The molecular origin of the anti-inflammatory activity has remained largely elusive to this day. Earlier studies suggest a small, secreted, yet undefined, molecule as the active principle and thus an untargeted metabolomics approach towards its identification was adopted. We used LCMS-analysis to interrogate the secreted metabolome of <em>S. cerevisiae </em>var.<em> boulardii</em> in comparison to a <em>S. cerevisiae </em>reference strain. Statistical analysis of the data revealed several compounds unique to <em>S. cerevisiae </em>var.<em> boulardii</em>, that were partially annotated and confirmed by comparison with authentic standards. Furthermore, anti-inflammatory properties were experimentally assigned to several small molecules, indicating that this property of the yeast variant is due to several factors. Our data suggest that the anti-inflammatory properties of <em>S. cerevisiae </em>var.<em> boulardii</em> can be linked to the activity of small molecules in its secreted metabolome.</p>
Morphological profiles extracted from Human MCF7 cells – compound-profiling experiment BBBC021.
<p>This contains morphological profiles extracted from Human MCF-7 cells from the compound-profiling experiment BBBC021 hosted at the Broad Bioimage Benchmark Collection.</p> <p>The profiles were extracted using the software SCIP.</p>
S99 | ANSESEDC | List of potential endocrine disrupting compounds (EDCs) from ANSES
<p>This is the collection associated with list S99 ANSESEDC List of potential endocrine disrupting compounds (EDCs) from ANSES on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a></p> <p>A list of 908 potential endocrine disrupting compounds (EDCs) from <a href="https://www.anses.fr/en">ANSES, the French Agency for Food, Environmental and Occupational Health & Safety</a> to be assessed for their <a href="http://(https://www.anses.fr/en/content/accelerating-assessment-endocrine-disruptors)">endocrine disrupting properties under France’s Second National Endocrine Disruptor Strategy (SNPE 2)</a>. Endocrine disruptors (EDs) are substances that interfere with the hormonal functions of humans and animals. List kindly provided by Sandrine Andres, INERIS. <br> </p>
Data used in the paper: Heatwaves, droughts, and fires: Exploring compound and cascading dry T hazards at the pan-European scale
<p>These datasets were used to analyze European compound and cascading dry hazards. The scripts are publicly available on GitHub: https://github.com/sjsutanto/Dryhazards.git.</p> <p>File Daily_SM_drought_WB_Converted.nc is for soil moisture drought, fwi_1990_2016_binary_95th_lowThreshold.nc is for wildfires, and datacube_2mtpp_19902016_HW.nc is for heatwaves.</p> <p> </p>
Penta-coordinated or -valent: the nature of the chemical bond of some Ti-C-Al compounds
<p>These folders contain the raw date which were used to prepare the above publication.<br> The zipfiles entitles compound-1.zip, compound-2.zip, and compound-3.zip contain the data for the computed compounds of the main publication. Please refer to that for further details. The zip-file xray.zip contains the original cif-file for convenience.<br> </p>
Joint series underlying the paper " Compound coastal-riverine flooding of St. Lawrence River coasts under sea level rise conditions"
<p>Compound coastal-riverine flooding, known as flooding events caused by the co-occurrence of high streamflow and coast water levels, can have substantial economic and social implications in low-lying coastal regions. Recent studies over Canada’s coasts have shown that neglecting the interdependency between flood drivers can underestimate the risk of flooding by up to 50%. However, to date, such interdependency and its effect on the frequency of compound riverine-coastal flooding has not been investigated for the coasts of the St. Lawrence River, Estuary, and Gulf system (StL), where Sea Level Rise (SLR), along with intensified river peaks, are already threatening communities. In this study, a copula-based bivariate frequency analysis (AND hazard scenario) was applied to quantify the differences between joint return periods computed under dependent and independent assumptions, for 26 sites along the StL. Furthermore, design pairs for 100-year joint events in the historical period (1986-2020) were compared with the 2100 horizon, where the SLR associated with the RCP8.5 emission scenario was incorporated into the water level time series. Results show that 1) the independence assumption can underestimate the frequency of compound flooding in the Fluvial Section of the StL by up to 30 times and 2) the SLR can increase the frequency of compound flooding by up to 50 times in the Estuary and the Gulf and by up to 5 times in the Fluvial Section of the StL. This study highlights the need for explicit consideration of the dependence between flood drivers and of SLR in the delineation of flood maps along all of the coasts of the St. Lawrence.</p>
Emission of volatile organic compounds from residential biomass burning and their rapid chemical transformations.
<p>Volatile Organic Compounds (VOCs) were monitored during the Ioannina 2022/23 winter campaign, in north-east Greece. The campaign was carried out between December 6th, 2021, and January 10th, 2022. Nitrogen oxides, carbon monoxide, carbon dioxide, methane, PM10 and Black carbon were also monitored, as well as meteorological variables. Ioannina is nested within the Dinaric mountains and suffers from intense winter pollution events, due to the topology which traps the pollution over the city. The instruments deployed included a Proton Transfer Time-of-Flight Mass Spectrometry (PTR-ToF-MS 4000 – Ionicon GmbH, Austria), a greenhouse gas monitor (G2301 – Picarro Inc., USA), a suite of carbon monoxide, ozone, nitrogen oxide analyzers (APMA-360, APNA-360 and APOA-360 – Horiba Ltd., Japan), a PM10 monitor (F-701-20 – DURAG, Germany), an aethalometer (AE33 – Magee Scientific, USA) and a weather station. Radiation, historical temperature data from the University of Ioannina, and PMF analysis results are also submitted.</p>
Supplementary datasets for "ARBRE: Computational resource to predict pathways towards industrially important aromatic compounds"
<p>Supplementary datasets accompanying the manuscript "ARBRE: Computational resource to predict pathways towards industrially important aromatic compounds" published in the Metabolic Engineering Journal (<a href="https://doi.org/10.1016/j.ymben.2022.03.013">https://doi.org/10.1016/j.ymben.2022.03.013). </a>In line with the standards of open science, the ARBRE toolbox is freely available to the scientific community on gitHub (<a href="https://github.com/EPFL-LCSB/ARBRE">https://github.com/EPFL-LCSB/ARBRE</a>) and we also provide the web-version at <a href="http://lcsb-databases.epfl.ch/arbre/">http://lcsb-databases.epfl.ch/arbre/</a></p> <p>ARBRE: Aromatic compounds RetroBiosynthesis Repository and Explorer is a new computational resource consisting of a comprehensive biochemical reaction network centered around aromatic amino acid biosynthesis and a computational toolbox for navigating this network. ARBRE encompasses over 33′000 known and 390′000 novel reactions predicted with generalized enzymatic reactions rules and over 74′000 compounds, of which 19′000 are known to biochemical databases and 55′000 only to PubChem. Over 1′000 molecules that were solely part of the PubChem database before and were previously impossible to integrate into a biochemical network are included in the ARBRE reaction network by assigning enzymatic reactions. ARBRE can be applied for pathway search, enzyme annotation, pathway ranking, visualization, and network expansion around known biochemical pathways and products of lignin degradation to predict valuable compound derivations.</p> <p>Supplementary files are organized as follows:</p> <p>- 1-s2.0-S1096717622000490-mmc4.docx contains Supplementary Figures 1-4 and Tables 1, 2, and 4.</p> <p>- 1-s2.0-S1096717622000490-mmc2.xlsx contains Supplementary Table 3.</p> <p>- 1-s2.0-S1096717622000490-mmc1.xlsx contains Supplementary Table 5</p> <p>- 1-s2.0-S1096717622000490-mmc3.xlsx contains Supplementary Table 6</p> <p> </p> <p> </p> <p> </p> <p> </p>
Data on soil compounds, respiration and incorporation of 13C-labeled substrate
<p>Root exudation increases the concentration of readily available carbon (C) compounds in its immediate environment. This creates ‘hotspots’ of microbial activity characterized by accelerated soil organic matter turnover with direct implications for nutrient availability for plants. However, we still lack a deeper understanding of the microbial metabolic processes that occur in the immediate vicinity of the roots during and after a root exudation event. Even though theoretical concepts have been developed, the direct consequences of root exudation on microbial metabolism and nutrient availability have never been measured in their immediate environment in intact soil.</p> <p>Here, we used reverse microdialysis to simulate root exudation by releasing a <sup>13</sup>C-labelled mix of low-molecular-weight organic C compounds at discrete, mm-sized locations in undisturbed soil in combination with <sup>13</sup>C stable isotope tracing. This approach allowed us to investigate the fine-scale temporal and spatial response of microbial metabolism and soil chemistry to root exudation at the mm-scale, and to trace microbial respiration and uptake of exuded compounds.</p> <p>Our results show that a 9-hour simulated root exudation pulse leads to i) a large local respiration event and ii) alteration of the temporal dynamics of soil metabolites over the following twelve days right at the spot of exudate release. Notably, we observed an approximately threefold increase in ammonium concentrations twelve hours after the pulse and increased nitrate concentrations five days after the pulse. We also observed an increase of various short-chain fatty acids, such as acetate, propionate and formate over the following days, indicating altered microbial metabolic pathways and activity. Phospholipid and neutral lipid fatty acids (PLFAs and NLFAs) of all major microbial groups were significantly enriched in <sup>13</sup>C within a radius of 5 mm around the microdialysis probes, but not beyond. The highest relative <sup>13</sup>C enrichment was observed in fungal NLFAs, indicating that a significant proportion of the exuded compounds had been incorporated into fungal storage compounds.</p> <p>Our findings indicate that the punctual release of low-molecular weight organic C compounds into intact soil significantly changes microbial metabolism and activity in its immediate surroundings, which lead to enhanced mineralisation of native organic nitrogen (N). Our observations emphasise the versatility of microbial metabolic pathways that underlie the response of soil microbes to rapidly altered C availability. They furthermore demonstrate the effectiveness of this response, as triggered by root exudation pulses, to increase nutrient availability for plants around the root.</p>
Publication & Supplementary data: Pro-health compounds and antioxidant activity of 65 potato cultivars
<p>Metadata (climatic conditions, list of varieties, field plan, etc.) and data (carotenoid content, vitamin C content, radical scavenging activity DPPH and FRAP, yellow index) related to the paper of Tatarowska et al., "The content of total carotenoids, vitamin C and antioxidant properties of 65 potato cultivars characterised under the European project ECOBREED" published in Int. J. Mol. Sci. 24 (2023), 11716.</p>
QC and WGS data on compound heterozygous PRKN-mutant (R275W/dEx8) PD patient
<p>Primary/raw data for QC on the characterisation of an iPSC line from a PD patient (Stem Cell Research)</p>
Engravings from Los Corros Megalithic compound (Vega de Liébana, Cantabria)
<p>3D model of a decorated slab in the megalithic site of Los Corros (Vega de Liébana, Cantabria). The piece was first studied by the authors back in 1989, now with the help of an iPhone Pro 12 Max and the Scaniverse app and some editings afterwards here and there, the 3D model is published.</p> <p>Díaz Casado, Y., Diez Castillo, A., Robles Fernández, G., & Serna González, M. R. (1989). Una necrópolis megalítica en el Pico Jano. Revista de Arqueología, 99, 62-63</p> <p><a href="https://sketchfab.com/3d-models/los-corros-70a46cba011c457ab55d6f4fa0903856?utm_medium=embed&utm_campaign=share-popup&utm_content=70a46cba011c457ab55d6f4fa0903856">Los Corros </a> by <a href="https://sketchfab.com/gvsigmac?utm_medium=embed&utm_campaign=share-popup&utm_content=70a46cba011c457ab55d6f4fa0903856"> gvsigmac </a> on <a href="https://sketchfab.com?utm_medium=embed&utm_campaign=share-popup&utm_content=70a46cba011c457ab55d6f4fa0903856">Sketchfab</a></p>
Compositionality of Nominal Compounds
<p>Originally published at <a href="https://pageperso.lis-lab.fr/carlos.ramisch/?page=downloads/compounds">https://pageperso.lis-lab.fr/carlos.ramisch/?page=downloads/compounds</a></p> <p><strong>=> comp-datasets-release-v2.tar.gz</strong></p> <p>This package contains numerical judgements by native speakers on the compositionality of 190 nominal compound in English (EN), 180 nominal compounds in French (FR), and 180 nominal compounds in Brazilian Portuguese (PT). The English data is split into two parts. The original 90 English compounds were annotated to complement the 90 compounds in the Reddy dataset (see below). The "extra" 100 English compounds were annotated to perform generalisation experiments in the <a href="https://aclanthology.org/J19-1001/">Computational Linguistics</a> paper (Section 6.3).</p> <p>Judgements were obtained using Amazon Mechanical Turk (EN and FR) and a web interface for volunteers (PT). Every compound has 3 scores: compositionality of head word, compositionality of modifier word and compositionality of the whole. Scores range from 1 (fully idiomatic) to 5 (fully compositonal) and are averaged over several annotators (around 10 to 20 depending on the language). All compounds also have synonyms and similar expressions given by annotators.</p> <p>The datasets are described in detail and used in the experiments of papers below. Please cite one of them if you use this material in your research.</p> <ul> <li><a href="https://aclanthology.org/J19-1001/">Unsupervised Compositionality Prediction of Nominal Compounds</a> <a href="https://aclanthology.org/J19-1001/.bib">[bib]</a></li> <li><a href="http://aclweb.org/anthology/P16-2026">How Naked is the Naked Truth? A Multilingual Lexicon of Nominal Compound Compositionality</a> <a href="http://aclweb.org/anthology/P16-2026.bib">[bib]</a></li> <li><a href="http://aclweb.org/anthology/P16-1187">Predicting the Compositionality of Nominal Compounds: Giving Word Embeddings a Hard Time</a> <a href="http://aclweb.org/anthology/P16-1187.bib">[bib]</a></li> <li><a href="http://aclweb.org/anthology/W16-1804">Filtering and Measuring the Intrinsic Quality of Human Compositionality Judgments</a> <a href="http://aclweb.org/anthology/W16-1804.bib">[bib]</a></li> </ul> <p>Our methodology is inspired from <a href="http://www.aclweb.org/anthology/I/I11/I11-1024.pdf">Reddy, McCarthy and Manandhar (2011)</a>. We include their set of 90 compounds and judgments in our dataset for the analyses and experiments on English in our papers above. However, we do not include their dataset here, though. Please also <a href="http://www.dianamccarthy.co.uk/downloads.html">download their data</a> and cite their paper to obtain a fully comparable English dataset to the one used in our experiments.</p> <p><strong>=> lexsub-nc.tar.gz</strong></p> <p>This package is an extension of the original compositionality datasets and includes more detailed annotation for Portuguese lexical substitution candidates in the original dataset. It contains the same 180 nominal compounds in Portuguese as the compositionality dataset. It additionally contains frequency and PMI from a large Brazilian Portuguese corpos (around 1.2 billion words), as well as lexical substitutes annotated according to the following categories:</p> <ul> <li>Invalid: the substitution candidate is not fit for substitution, either for being too specific for a given context or for simply not being valid for the target MWE.</li> <li>Syn-SW: the substitution candidate is a single-word matching synonym in relation to the target MWE.</li> <li>NearSyn-SW: the substitution candidate is a single-word quasi-synonym in relation to the target MWE.</li> <li>Syn-MWE: the substitution candidate is a multiword matching synonym in relation to the target MWE.</li> <li>NearSyn-MWE: the substitution candidate is a multiword quasi-synonym in relation to the target MWE.</li> <li>Paraphrase: the substitution candidate is a paraphrasis of the target MWE.</li> <li>Definition: the substitution candidate is a definition of the target MWE.</li> <li>Head</li> <li>Modifier</li> </ul> <p>The lexical substitutes were provided by volunteer native speaker annotators, who were requested to provide suggestions of substitution candidates for the compounds in context. The suggestions from all annotators were pooled together and sorted according to their frequency. This pool was then manually categorized by a linguist, who attributed categories to each different substitution candidate.</p>
DMS measurements dataset for manuscript "Classification of Volatile Organic Compounds by Differential Mobility Spectrometry Based on Continuity of Alpha Curves"
<p>Differential mobility spectrometry dispersion plots collected for the manuscrit "Classification of Volatile Organic Compounds by Differential Mobility Spectrometry Based on Continuity of Alpha Curves". The measurement files are located in the folders that represent certain week and day of measurement. The folders containing measurements are named with the following pattern: [chemical abbreviation]_[dilution rate]. For example "2PEtOH_1o10k" means that the folder contains measurement of 2-phenylethanol diluted with propylene glycol in volumetric proportion 1/10 000. Another example is "nBuOH_1o100" - n-Butanol diluted with propylene glycol in volumetric proportion 1/100. Please find the abbreviations in the article referred.</p> <p>For the first five weeks only 1/100 dilutions were measured. The last two weeks (weeks 6 and 7) 1/10 000 dilutions were measured. However, Carvone 1/100 was measured again on week 6 due to suspicion of faulty measurements during the previous weeks. The faulty measurements were not confirmed, and thus there 25 more samples of Carvone with dilution rate 1/100.</p>
USP5 ZnF-UBD Co-Crystal Structure with Compound UBTR012574a
<p>Objective: To grow well-diffracting co-crystals of USP5 zinc finger ubiquitin binding domain (ZnF-UBD) to solve the co-crystal structures to determine ligand interactions in the binding pocket and to determine if the predicted binding pose is similar to the experimental binding pose.</p>
Fig. 2. Relationships concentration x in Anesthesia of tambaqui Colossoma macropomum (Characiformes: Serrasalmidae) with the essential oils of Aniba rosaeodora and Aniba parviflora and their major compound, linalool
Fig. 2. Relationships concentration x anesthesia induction or recovery time in tambaqui, Colossoma macropomum, exposed to the linalools. a. synthetic linalool; light sedation: y=4.4+(4281/x), r2=0.716, deep sedation: y=-22.5+(12252/x), r2=0.773, deep anesthesia:y=15.3+(17878/x), r2=0.669, recovery: y=43.9+0.66x+0.0015x2, r2=0.712. b. linalool extracted from Aniba rosaeodora; deep sedation: y=29.0+(6010/x), r2=0.784, deep anesthesia: y=-151.3+(60541/x), r2=0.873. Light sedation and recovery: no significant relationship. y = time to reach stage or recovery (s) and x = concentration (µL L-1).
Compound flood potential from river discharge and storm surge extremes at the global scale
<p>This dataset presents the results presented in <a href="https://doi.org/10.5194/nhess-20-489-2020">Couasnon et al. (2019) - Measuring compound flood potential from river discharge and storm surge extremes at the global scale</a>. For more information about the methods, please refer to the paper. This dataset was created using as input <a href="https://zenodo.org/record/3552820#.XmIdoVxKhaQ">time series of discharge and maximum storm surge at river mouths globally from 1980 - 2014</a>.</p> <p>If using this data, please cite: </p> <p>Couasnon, A., Eilander, D., Muis, S., Veldkamp, T. I. E., Haigh, I. D., Wahl, T., Winsemius, H. C., and Ward, P. J.: Measuring compound flood potential from river discharge and storm surge extremes at the global scale, Nat. Hazards Earth Syst. Sci., 20, 489–504, https://doi.org/10.5194/nhess-20-489-2020, 2020.</p>
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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)
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DANDI Archive for NWB datasets
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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.