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1,542 results for “Degradation”
Data for the publication "Impact of Enzymatic Degradation on the Material Properties of Poly(ethylene terephthalate)"
<p><strong>Background</strong></p> <p>The data set contains raw data of fatigue crack propagation resistance measurements (da/dN), differential scanning calorimetry (DSC), atomic-force microscopy (AFM), and ultra-high performance liquid chromatography (UHPLC) of PET samples incubated with PETase. The experiments were done in the laboratory at the Department of Polymer Engineering and Department of Biochemistry, University of Bayreuth, Germany in 2020 and 2021.</p> <p>The data set was analysed in the publication: Menzel, T.; Weigert, S.; Gagsteiger, A.; Eich, Y.; Sittl, S.; Papastavrou, G.; Ruckdäschel, H.; Altstädt, V.; Höcker, B. Impact of Enzymatic Degradation on the Material Properties of Poly(Ethylene Terephthalate). <em>Polymers</em> <strong>2021</strong>, 13(22), 3885. https://doi.org/10.3390/polym13223885</p> <p><strong>Disclaimer</strong></p> <p>The data are provided without any warranty. Details on the experimental setup are given in the publication.</p> <p><strong>References</strong></p> <p>Menzel, T.; Weigert, S.; Gagsteiger, A.; Eich, Y.; Sittl, S.; Papastavrou, G.; Ruckdäschel, H.; Altstädt, V.; Höcker, B. Impact of Enzymatic Degradation on the Material Properties of Poly(Ethylene Terephthalate). <em>Polymers</em> <strong>2021</strong>, 13(22), 3885. https://doi.org/10.3390/polym13223885</p> <p> </p> <p> </p> <p> </p> <p> </p>
TGA and LOI measurements within the thermal degradation study of a SRF prepared for an aluminium scrap pre-heating system (REVaMP project)
<p>Underlying data (related to Figure 2) for the publication Acha, E.; Lopez-Urionabarrenechea, A.;Delgado, C.; et al. Combustion of a Solid Recovered Fuel (SRF) Produced from the Polymeric Fraction of Automotive Shredder Residue (ASR). Polymers <strong>2021</strong>, 13, 3807. <a href="https://doi.org/10.3390/polym13213807">https://doi.org/10.3390/polym13213807</a></p> <p>Experimental data generated by the REVaMP project (GA 869882, Horizon 2020, European Union) along the research of the combustion of a SRF, prepared from ASR, to be used as alternative fuel in a scrap pre-heater at an aluminium refinery plant. Research pertaining to Task 1.1 (WP1), Deliverable D1. </p> <p>Subject: Thermal degradation study performed in air to measure the mass loss of SRF samples with time and temperature during a continuous heating process (two TGA measurements and determination of variation of LOI with T). The results indicate the different stages in the thermal decomposition of the prepared SRF and the temperature range of its combustion. Useful information for designing the operation conditions of the SRF combustion chamber of the scrap pre-heater.</p> <p> </p>
Dataset: Consistent release of volatile organic compounds across an actively degrading permafrost peatland
<p>Here, we conducted in situ measurements of soil and pond VOC emissions across an actively degrading permafrost peatland in subarctic Norway. We used a permafrost thaw gradient that covered bare soil and vegetated palsa plateaus, underlain by intact permafrost, and increasingly degraded permafrost landscapes: thaw slumps, thaw ponds, and vegetated thaw ponds.</p> <p>This dataset includes two excel files: 1) the first one "Finnmark_source_data" is the source data for figures in the publication <a href="https://doi.org/10.1016/j.geoderma.2023.116355">https://doi.org/10.1016/j.geoderma.2023.116355</a>. ii) the second one "Rawdata_of_emission_rate" is the emission rate of the 210 VOC species identified in this study.</p> <p>Results showed that every peatland landscape type was an important and consistent source of atmospheric VOCs, with a large variety species, such as methanol, acetone, monoterpenes, sesquiterpenes, isoprene, hydrocarbons, oxygenated VOCs, etc. VOC composition varied considerably across the measurement period and across the permafrost thaw gradient. We observed enhanced terpenoid emissions following thaw slump degradation, highlighting the potential atmospheric impact of permafrost thaw, due to the high chemical reactivities of terpenoid compounds. Overall, our study demonstrates that VOCs are being emitted in significant quantities and with largely similar composition upon permafrost thawing, inundation, and subsequent vegetation development, despite major differences in microclimate, hydrological regime, vegetation, and permafrost occurrence.</p> <p>Should you have any questions regarding the dataset, please free feel to contact Yi jiao at yi.jiao@bio.ku.dk or the PI of this project Prof. Rinnan at riikkar@bio.ku.dk</p>
Data from: Forest degradation limits the complementarity and quality of animal seed dispersal
<p><span>Forest degradation changes the structural heterogeneity of forests and species communities, with potential consequences for ecosystem functions including seed dispersal by frugivorous animals. While the quantity of seed dispersal may be robust towards forest degradation, changes in the effectiveness of seed dispersal through qualitative changes are poorly understood. Here, we carried out extensive field sampling on the structure of forest microhabitats, seed deposition sites, and plant recruitment along three characteristics of forest microhabitats (canopy cover, ground vegetation, deadwood) in Europe's last lowland primeval forest (Białowieża, Poland). We then applied niche modelling to study forest degradation effects on multi-dimensional seed deposition by frugivores and recruitment of fleshy-fruited plants. Forest degradation was shown to (1) reduce the niche volume of forest microhabitat characteristics by half, (2) homogenize the spatial seed deposition within and among frugivore species, and (3) limit the regeneration of plants via changes in seed deposition and recruitment. Our study shows that the loss of frugivores in degraded forests is accompanied by a reduction in the complementarity and quality of seed dispersal by remaining frugivores. In contrast, structure-rich habitats, such as old-growth forests, safeguard the diversity of species interactions, forming the basis for high-quality ecosystem functions.</span></p>
How to quantify factors degrading DNA in the environment and predict degradation for effective sampling design
<p>Extra-organismal DNA (eoDNA) from material left behind by organisms (non-invasive DNA: e.g., faeces, hair) or from environmental samples (eDNA: e.g., water, soil) is a valuable source of genetic information. However, the relatively low quality and quantity of eoDNA, which can be further degraded by environmental factors, results in reduced amplification and sequencing success. This is often compensated for through cost- and time-intensive replications of genotyping/sequencing procedures. Therefore, system- and site-specific quantifications of environmental degradation are needed to maximize sampling efficiency (e.g., fewer replicates, shorter sampling durations), and to improve species detection and abundance estimates. Using ten environmentally diverse bat roosts as a case study, we developed a robust modelling pipeline to quantify the environmental factors degrading eoDNA, predict eoDNA quality, and estimate sampling-site-specific ideal exposure duration. Maximum humidity was the strongest eoDNA-degrading factor, followed by exposure duration and then maximum temperature. We also found a positive effect when hottest days occurred later. The strength of this effect fell between the strength of the effects of exposure duration and maximum temperature. With those predictors and information on sampling period (before or after offspring were born), we reliably predicted mean eoDNA quality per sampling visit at new sites with a mean squared error of 0.0349. Site-specific simulations revealed that reducing exposure duration to 2-8 days could substantially improve eoDNA quality for future sampling. Our pipeline identified high humidity and temperature as strong drivers of eoDNA degradation even in the absence of rain and direct sunlight. Furthermore, we outline the pipeline's utility for other systems and study goals, such as estimating sample age, improving eDNA-based species detection, and increasing the accuracy of abundance estimates.</p>
Forced degradation of five drug substances for meRgeION validation
<p>Drug substance is subjected to acid hydrolysis and oxidative stress against a baseline condition. The goal here is to profile and identify various degradation products of five APIs by setting stress conditions more severe than recommended storage, in order to further understand the underlying chemical mechanisms</p> <p>Non-targeted profiling in DDA mode was conducted for samples at Day 0 (1 sample) and Day 7 (3 samples for 3 conditions) on Orbitrap Fusion Lumos. Converted data files were submitted to MZMine for feature detection. Folder change of each feature under different conditions was calculated in excel. We then built a LC-MS/MS data processing pipeline in meRgeION that enables degradation product annotation by searching the spectral database <em>Drug+</em> (lib_drug_plus_matrix.RData) and mechanism understanding through FBMN. </p> <p> </p>
Fig. 3 in Javan mongoose (Herpestes javanicus) abundance and spatial ecology in a degraded dry dipterocarp forest
Fig. 3. Map of Sakaerat Biosphere Reserve with radio tracked (December 2019 to January 2021) Javan mongoose (Herpestes javanicus) home ranges and prey grids (PG). 95% utilisation contours (U.C) for male (M6, M1) and female (F1) mongooses are labelled in the legend. 50% U.C are solid line circles within each individual's home range. Prey grids collected ground-dwelling invertebrate mass as well as rodent biomass within the DDF (October to December 2020). Stars indicate where only ground-dwelling invertebrates were collected. Triangles indicate areas where sweep netting for invertebrates occurred in addition to sampling for rodent biomass and ground-dwelling invertebrates.
Fig. 1 in Javan mongoose (Herpestes javanicus) abundance and spatial ecology in a degraded dry dipterocarp forest
Fig. 1. Map and location of Sakaerat Biosphere Reserve with camera trap stations used to estimate Javan mongoose (Herpestes javanicus) abundance in 2017. Prey grid stations were used to calculate yearly averaged rodent biomass from January 2017 to November 2017.
Text-fig. 3. Mastixia parva E.REID et M.CHANDLER. a–g: Holotype, V. 22972. a: Ventral view (original illustration from pl. 25, fig. 13 of Reid and Chandler 1933), reflected light. b–g: from micro-CT data. b: Dorsal view of specimen in (a) now suffering from encrustation due to pyrite decay; isosurface rendering. c: Translucent volume rendering, dorsal view showing two limbs of the locule and longitudinal groove. d–g: Digital transverse sections at various positions showing c-shaped locule, longitudinal dorsal infold, endocarp wall, and degradational cracks. h, i: V. 22983(1). h: Dorsal view showing longitudinal infold. i: Physical transverse section showing c-shaped locule and longitudinal dorsal infold. Scale bars 5 mm in (a–h), applies also to (b–g), 2 mm in (i). in Mastixioid Fruits (Cornales) From The Early Eocene London Clay Flora: Morphology, Anatomy And Nomenclatural Revision
Text-fig. 3. Mastixia parva E.REID et M.CHANDLER. a–g: Holotype, V. 22972. a: Ventral view (original illustration from pl. 25, fig. 13 of Reid and Chandler 1933), reflected light. b–g: from micro-CT data. b: Dorsal view of specimen in (a) now suffering from encrustation due to pyrite decay; isosurface rendering. c: Translucent volume rendering, dorsal view showing two limbs of the locule and longitudinal groove. d–g: Digital transverse sections at various positions showing c-shaped locule, longitudinal dorsal infold, endocarp wall, and degradational cracks. h, i: V. 22983(1). h: Dorsal view showing longitudinal infold. i: Physical transverse section showing c-shaped locule and longitudinal dorsal infold. Scale bars 5 mm in (a–h), applies also to (b–g), 2 mm in (i).
Engineering dynamic gates in binding pocket of penicillin G acylase to selectively degrade bacterial signaling molecules
<p>(01-mutants_design.tar.gz) Mutants design:</p> <ol> <li>Input structures of ecPGA from the PDB database (PDB IDs: 1GK9, 1GM7, and 1GM9), processed to resemble wild-type state, repaired by RepairPDB module of FoldX 4</li> <li>Double-point mutants preparation, analysis and filtering: <ol> <li>text files including configuration for FoldX 4</li> <li>inputs and outputs of CAVER 3.02 calculations on FoldX 4 PDB files of ecPGA double-point mutants</li> <li>input configuration file and TransportTools library 0.9.4 calculations outputs generated based on the inputs produced in step 01 and 02 above</li> <li>CSV files containing complete information about FoldX 4 stability prediction and geometrical properties from CAVER 3.02 and TransportTools library version 0.9.4 for ecPGA double-point mutants</li> </ol> </li> <li>Triple-point mutant preparation, analysis and filtering: <ol> <li>text files including configuration for FoldX 4</li> <li>inputs and outputs of CAVER 3.02 calculations on FoldX 4 PDB files of ecPGA triple-point mutants</li> <li>input configuration file and TransportTools library 0.9.4 calculations outputs generated based on the inputs produced in step 01 and 02 above</li> <li>CSV files containing complete information about FoldX 4 stability prediction and geometrical properties from CAVER 3.02 and TransportTools library version 0.9.4 for ecPGA triple-point mutants</li> </ol> </li> </ol> <p>(02-docking.tar.gz) Preparation of protein-ligand complexes using molecular docking for wild-type ecPGA and 6 best designed triple-point mutants with 6 various bacterial signaling molecules:</p> <ol> <li>PDB files of ligand, PDBQT files of the receptor and PDB files of the complexes selected from docking experiment:</li> </ol> <p>Full names of presented protein variants:<br>ecPGA_wt, wild-type Escherichia coli penicillin G acylase<br>LAF, Phe138αLeu & Met142αAla & Ile177βPhe ecPGA variant internally referred as 1GK9_Repair_22<br>LSF, Phe138αLeu & Met142αSer & Ile177βPhe ecPGA variant internally referred as 1GK9_Repair_98<br>MAF, Phe138αMet & Met142αAla & Ile177βPhe ecPGA variant internally referred as 1GK9_Repair_23<br>MSF, Phe138αMet & Met142αSer & Ile177βPhe ecPGA variant internally referred as 1GK9_Repair_99<br>VAF, Phe138αVal & Met142αAla & Ile177βPhe ecPGA variant internally referred as 1GK9_Repair_30<br>YAF, Phe138αTyr & Met142αAla & Ile177βPhe ecPGA variant internally referred as 1GK9_Repair_33<br>Full names of presented AHLs:<br>C06, N-hexanoyl-L-homoserine lactone;<br>C06-3O, N-3-oxo-hexanoyl-L-homoserine lactone;<br>C08, N-octanoyl-L-homoserine lactone;<br>C08-3O, N-3-oxo-octanoyl-L-homoserine lactone;<br>C10, N-decanoyl-L-homoserine lactone;<br>C12-3O, N-3-oxo-dodecanoyl-L-homoserine lactone</p> <p>(03-protein_ligand_MDs.tar.gz) Ligand-enzyme complexes molecular dynamics for wild-type ecPGA and 6 best designed triple-point mutants with 6 various bacterial signaling molecules:</p> <ol> <li>Force field parameters in Amber format</li> <li>Input coordinates *.inpcrd, parameters *.parm7 and *.pdb files for each complex ready for simulation in Amber</li> <li>Amber input files *.in for minimization, equilibration and production runs</li> <li>Restart files for each stage of the minimization, equilibration and production runs in Amber *.rst format</li> <li>Simulation output files for each stage of the minimization, equilibration and production runs in Amber *.mdout format</li> <li>Output files generated during post-processing of production runs trajectories in a form of text files generated by cpptraj</li> </ol> <p>(04-free_enzymes_MDs.tar.gz) Free enzymes molecular dynamics of 3 best triple-point ecPGA (VAF, YAF and MSF) mutants prioritized based on protein-ligand molecular dynamics simulations and experimental assays:</p> <ol> <li>Force field parameters and input coordinates *.inpcrd, parameters *.parm7 and *.pdb files for each complex ready for simulation in Amber format</li> <li>Amber input files *.in for minimization, equilibration and production runs</li> <li>Restart files for each stage of the minimization, equilibration and production runs in Amber *.rst format</li> <li>Simulation output files for each stage of the minimization, equilibration and production runs in Amber *.mdout format</li> <li>Post-processing analysis of generated trajectories: <ol> <li>Text files with distances, CSV files containing result of PCA and clustering, PNG files with clustered PCA results</li> <li>Inputs and outputs of MDpocket analysis and visualization of the pocket frequency grid as an isomesh</li> <li>CAVER input configuration files in text format, CAVER output data including parsed CSV and text files for visualization of entrance opening time evolution and cavity profiles inspection</li> <li>cpptraj generated text files including RMSD, distances and chi1 angles measurements</li> </ol> </li> </ol> <p>All plots were generated using matplotlib or seaborn Python libraries. Figures containing structural representations were generated using PyMOL 2.0.1.</p> <p>(05-ecPGA_VAF_YAF_MSF_penG_MDs.tar.gz) PenG-enzyme complexes molecular dynamics for wild-type ecPGA and 3 best designed triple-point mutants (VAF, YAF, MSF):</p> <ol> <li>PenG force field parameters in Amber (GAFF) format</li> <li>Input coordinates *.inpcrd, parameters *.parm7 and *.pdb files for each complex ready for simulation in Amber</li> <li>Amber input files *.in for minimization, equilibration and production runs</li> <li>Restart files for each stage of the minimization, equilibration and production runs in Amber *.rst format</li> <li>Simulation output files for each stage of the minimization, equilibration and production runs in Amber *.mdout format and analysis output files generated during post-processing of production runs trajectories in a form of text files</li> <li>Reactive Stabilization Score [RSS] statistics summarized in CSV files</li> </ol>
Charge-Selective Photocatalytic Degradation of Organic Dyes using Halloysite Nanotubes
<p>This study explores the use of Halloysite NanoTubes (HNTs) as photocatalysts capable of<br>decomposing organic dyes under exposure to visible or ultraviolet light. We observe that the extent of RhB<br>photocatalytic degradation in 100 min in the presence of the HNTs is ~4 times higher compared to<br>that of bare RhB. Moreover, under optimized conditions, the as-extracted photodegradation rate of<br>RhB (~0.0022 /min) is comparable to that of the previously reported work on the photodegradation<br>of RhB in the presence of tubular nanostructures. A parallel effect is observed for anionic Coumarin<br>photodegradation, albeit less efficiently. By leveraging the unique properties of HNTs, a family of naturally occurring<br>nanotube structures, this research offers valuable insights for optimizing photocatalytic systems in<br>the pursuit of effective and eco-friendly solutions for environmental remediation.</p>
Figure 1 in Amazonian soil fungi are efficient degraders of glyphosate herbicide; novel isolates of Penicillium, Aspergillus, and Trichoderma
Figure 1. Mass spectrum resulting from the HPLC-MS of the isolated Penicillium 4A21 filtered. The filtrate presents possible peaks of glyphosate (170.07), AMPA (112.13) and sarcosine (89).
Fig. 5 in Degradation of a photophilic algal community and its associated fauna from eastern Sicily (Mediterranean Sea) Abstract
Fig. 5: Histograms illustrating species richness (A) and specimen abundance (B) for all investigated taxonomic groups from the examined algal community in the whole area (TOT) and in individual sampling stations (CPA, SM). Relationships between lowrank taxonomic groups are shown for some taxa. For serpulids: dark and light nuances refer to Serpulinae and Spirorbinae, respectively; for molluscs, dark, intermediate and light nuances indicate bivalves, gastropods and polyplacophorans, respectively; for bryozoans dark, intermediate and light nuances indicate cyclostomatids, ctenostomatids and cheilostomatids, respecytively; TOT: data for the area as a whole; CPA: Punta Aguzza station; SM: Santa Maria La Scala station. Numbers on each column indicate the total number of species (A) and specimens (B) for the entire group (high) and for lower taxonomic groups (below, separated by comas).
Fig. 4 in Degradation of a photophilic algal community and its associated fauna from eastern Sicily (Mediterranean Sea) Abstract
Fig. 4: Double-layered algal mat formed by erect Ellisolandia elongata basal portions capped by a thick turf of filamentous soft algae and thin geniculate coralline algae entrapping silt. Few species (depicted in the round inserts) thrive in this algal mat, some showing particular distribution pattern (arrowed) and morphological adaptations. 1: Patinella radiata; 2: Crisia spp.; 3: Janua (Dexiospira) pagenstecheri: 4: Hyatella arctica; 5: Filicrisia geniculata; 6: Amathia delicatula. Scale bar: 1 cm.
Fig. 3 in Degradation of a photophilic algal community and its associated fauna from eastern Sicily (Mediterranean Sea) Abstract
Fig. 3: Floristic richness and relationships between algal taxonomic groups in the examined algal community in the whole study area (TOT) and in individual stations (CPA: Punta Aguzza station; SM: Santa Maria La Scala station). Left columns in each group show present-day situation in comparison with past data (right columns) as reported in Pizzuto (1999). Red: Rhodophyta; brown: Ochrophyta; green: Chlorophyta. Numbers indicate the total number of species for each taxonomic group.
Fig. 2 in Degradation of a photophilic algal community and its associated fauna from eastern Sicily (Mediterranean Sea) Abstract
Fig. 2: Underwater images of the sampling stations. A: CPA station; B: SM station, as appeared in June 2015. In A the quadrat frame and the sorbona gear are shown.
Fig. 1 in Degradation of a photophilic algal community and its associated fauna from eastern Sicily (Mediterranean Sea) Abstract
Fig. 1: Location of the sampling area within the Mediterranean (A), and the eastern coast of Sicily (B). C. Santa Maria La Scala D. Punta Aguzza. Sampling stations are indicated with red dots.
Fig. 7 in Degradation of a photophilic algal community and its associated fauna from eastern Sicily (Mediterranean Sea) Abstract
Fig. 7: Dendrogram restricted to serpulid fauna, showing an almost complete seasonal matching of samples at 60-70% BC similarity. Acronyms as in Figure 6.
Fig. 6 in Degradation of a photophilic algal community and its associated fauna from eastern Sicily (Mediterranean Sea) Abstract
Fig. 6: Dendrogram (A) and MDS ordination (B) obtained from a data matrix of live specimens abundance (cf. Tables 1-3) of macrofauna samples (Z5) collected in the examined community. The horizontal line in the dendrogram and the MDS grouping (40% BC similarity) separate CPA (Punta Aguzza) and SM (Santa Matia La Scala) sites. 1, 2, 3, 4, and 5 refer to subsequent sampling surveys.
Figure 2. Flufenacet degradation 24 h in Flufenacet activity is affected by GST inhibitors in blackgrass (Alopecurus myosuroides) populations with reduced flufenacet sensitivity and higher expression levels of GSTs
Figure 2. Flufenacet degradation 24 h after treatment with different inhibitors in the sensitive Alopecurus myosuroides population Herbiseed-S (A) and population Kehdingen1 with reduced flufenacet efficacy (B). Different letters indicate significant differences in flufenacet degradation between treatments,and asterisks (*) indicate significant differences between the two populations for each treatment (P ≤ 0.05).
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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)
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.