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Fig. 14 in Research history, taphonomy, and age structure of a mass accumulation of the ornithopod dinosaur Dysalotosaurus lettowvorbecki from the Upper Jurassic of Tanzania
Fig. 14. Examples of states of bone preservation of ornithopod dinosaur Dysalotosaurus lettowvorbecki Pompeckj, 1920, from Kimmeridgian, Late Jurassic of Tendaguru, Tanzania. A. Several tibiae originally labelled with low Ig numbers showing multiple breaks perpendicular to their long axis. B. Isolated shaft of the left femur GPIT/RE/3446 in medial view with its proximal and distal ends broken off but with excellent preservation of the bone surface and of the delicate 4th trochanter. C. The right ilium GPIT/RE/6544 with the usual broken off preacetabular process and net-like surface cracks on the otherwise well-preserved lateral bone surface. D. Dorsal vertebra GPIT/RE/5462 of a juvenile individual in anterior view with plastic deformation of the left diapophysis. The deformation of this side is visible in two additional, potentially associated dorsal vertebrae. E. Unlabeled right humerus from the SMNS collections with well-preserved articular ends but with a distorted and compressed midshaft. F. Excellent preservation of the right calcaneum GPIT/RE/5808 in lateral view. G. The left jugal MB.R.1333 in lateral view with numerous diagenetic cracks which were resealed in situ by calcite. H. Right quadrate MB.R.3478 in lateral view with its cotylar head and upper part of the anterolateral wing broken off and slightly displaced forward whereas the surface of the bone and its delicate processes are generally well preserved. Scale bars 10 mm.
Fig. 1 in Research history, taphonomy, and age structure of a mass accumulation of the ornithopod dinosaur Dysalotosaurus lettowvorbecki from the Upper Jurassic of Tanzania
Fig. 1. Location of the Ig/WJ-locality. A. Position of the Tendaguru locality in Tanzania, redrawn from Google Maps and on the basis of locality information of Aberhan et al. (2002). B. Geological map of the Tendaguru area with main stratigraphic units, the position of quarry Jg/WJ is marked with an asterisk, and some other important quarries from the German Tendaguru Expedition (1909–1913) are labelled with their respective letters. Roads are marked by dashed lines. Data are from Janensch (1925b), Heinrich 1999b), and Aberhan et al. (2002). The names of stratigraphic units are from Bussert et al. (2009).
Fig. 3 in Research history, taphonomy, and age structure of a mass accumulation of the ornithopod dinosaur Dysalotosaurus lettowvorbecki from the Upper Jurassic of Tanzania
Fig. 3. Original, unopened bamboo corsets containing bones of ornithopod dinosaur Dysalotosaurus lettowvorbecki Pompeckj, 1920, from Kimmeridgian, Late Jurassic of Tendaguru, Tanzania, which are housed in the collection of fossil reptiles at the MfN. A. Stored as a stack. B. Bamboo corset in lateral view. C. Showing the labelling on the front side. The bamboo corsets are labelled with the quarry numbers and field numbers as assigned to single fossil blocks. Reference to specimens is not possible, because most of them are unprepared sediment blocks. D. CT slice exposing cross-section through bamboo corset Ig 88, bones are in white whereas lighter materials such as clay, cushioning with grass, and bamboo sticks are displaying around.
Fig. 8 in Research history, taphonomy, and age structure of a mass accumulation of the ornithopod dinosaur Dysalotosaurus lettowvorbecki from the Upper Jurassic of Tanzania
Fig. 8. Tentative reconstruction of the spatial relationships of the four bonebeds of the Ig/WJ-quarry according to the available descriptions and dates of Werner Janensch and Hans Reck. The actual shape and absolute sizes of the bonebeds are schematic and speculative. Top (A) and profile (B) views are in relation to the cardinal points. Note that the actual stratigraphic level of BB-1 in relation to BB-2 is uncertain (double headed arrow). The dotted ellipses show the approximate position of the large, possibly sauropod, bones found in September 1912 within the otherwise bone-free layer in between BB-3 and BB-4 including a scapula and a cervical vertebra. BB, bonebed. See Fig. 7 for comparison.
Monthly accumulated sublimation and yearly accumulated surface mass balance (SMB) components RACMO model simulations for Antarctica on 27km grid for 2000-2012
<p>Monthly accumulated (denoted monthlyS) sublimation components and yearly accumulated (denoted yearlyS) surface mass balance (SMB) components for Antarctica (ANT) on 27 km horizontal grid produced by RACMO model are presented in this dataset for the year 2000-2012. The dataset consists of data from three simulations named, NODRIFT, Rp3, and RpNew. NODRIFT represents the run with no blowing snow sublimation, Rp3 corresponds to version of the blowing snow model with simplifications, RpNew corresponds to the advanced version with new updates to the blowing snow model in RACMO. Details of the simulations can be found in the associated paper : <a title="Contribution of blowing snow sublimation to the surface mass balance of Antarctica" href="https://doi.org/10.5194/egusphere-2024-116" target="_blank" rel="noopener">https://doi.org/10.5194/egusphere-2024-116</a>. The data includes yealy accumulated SMB components including SMB, snow melt, refreezing, precipiation, runoff, blowing snow erosion, surface sublimation, and blowing snow sublimation, the data also includes yearly averaged (denoted yearlyA) . Furthermore, the data includes monthly accumulated sublimation components of surface sublimation (subl), and blowing snow sublimation (suds). </p>
Fig. 5 in Species Accumulation Curves And Similarity Traits Of A Species-Rich Fly (Diptera) Community
Fig. 5. Jackknifed NESS indices relating to the kth and (k + 1)th group of 50, k = 1,2,…, 19. In case of k = 8 and k = 14 samples from different years are compared
Fig. 2. Sample-based curve for 2003–2005 in Species Accumulation Curves And Similarity Traits Of A Species-Rich Fly (Diptera) Community
Fig. 2. Sample-based curve for 2003–2005. Two points, corresponding to species numbers after adding the first group of ten to the sample in 2004 and 2005 are denoted by empty symbol
Drosophila serrata mutation accumulation lines: Phenotypic data on survival following infection with Drosophila C virus and reproduction
<p>The impact of selection on host immune function genes has been widely documented. However, it remains essentially unknown how mutation influences the quantitative immune traits that selection acts on. Applying a classical mutation accumulation (MA) experimental design in <em>Drosophila serrata</em>, we found the mutational variation in susceptibility (median time of death, LT50) to Drosophila C virus (DCV) was of similar magnitude to that reported for intrinsic survival traits. Mean LT50 did not change as mutations accumulated, suggesting no directional bias in mutational effects. Maintenance of genetic variance in immune function is hypothesised to be influenced by pleiotropic effects on immunity and other traits that contribute to fitness. To investigate this, we assayed female reproductive output for a subset of MA lines with relatively long or short survival times under DCV infection. Longer survival time tended to be associated with lower reproductive output, suggesting that mutations affecting susceptibility to DCV had pleiotropic effects on investment in reproductive fitness. Further studies are needed to uncover the general patterns of mutational effect on immune responses and other fitness traits, and to determine how selection might typically act on new mutations via their direct and pleiotropic effects.</p>
Fig. 2 in Repeated stressors do not provoke habituation or accumulation of the stress response in the catfish Rhamdia quelen
Fig. 2. Plasma cortisol concentrations of R. quelen (Quoy & Gaimard) fingerlings exposed to sequential acute stressors. Comparison of responses to two similar stressors and a third different stressor in experiment "A" and comparison of responses to three sequential stressors of the same type in experiment "B." Data are expressed in terms of mean ± S.E.M. values. The different small letters above the histograms indicate statistical differences by ANOVA, followed by Tukey's range test. (n = 8-9).
Fig. 1 in Repeated stressors do not provoke habituation or accumulation of the stress response in the catfish Rhamdia quelen
Fig. 1. Schematic representation of the experimental design of both groups of experiments. In experiment "A," Rhamdia quelen (Quoy & Gaimard) fingerlings were sequentially exposed to the same stressors twice and to a different stress the third time. In experiment "B," R. quelen fingerlings were sequentially exposed as the same stressors 3 times.
Fig. 1 in Lipid accumulation in Cyprinus carpio (Linnaeus, 1785) liver induced by thiamethoxam
Fig. 1. Intensity of Sudan III staining in Common Carp liver: A – control group, x200; B – 6.6 mg/L insecticide, x400; C – 10 mg/L insecticide, x400; D – 20 mg/L insecticide, x400.
In situ clamped beam bending of accumulative roll bonded Cu/Nb with 63 nm individual layer thickness
<p>In situ scanning electron microscope (SEM) videos of clamped beam bending of Cu/Nb ARB nanolaminates with 63 nm layer thickness. Each video contains the video captured with SEM and the corresponding measured load vs. displacement curve.</p> <p>The beams were fabricated using focused ion beam (FIB) milling from bulk Cu/Nb sample produced in Los Alamos National Lab, USA. The sample was made using accumulative roll bonding (ARB) process, described in ref. [1]. </p> <p>All the beam lengths are aligned either with rolling direction (RD) of the sample of transfer direction of the sample (TD). RD and TD are used to denote the beam length direction in the videos and the table below. Each beam has a rectangular notch located in the center of the beam length. Each notch spans through the beam width. Owing to limited accuracy of FIB, the notch depth was not always same at the front and rear sides of the beam (typically, smaller at the rear sides)</p> <p>Beam geometries:</p> <p>Id | Length, µm | Width, µm | Thickness, µm | Notch depth (front), nm | Notch width (front), nm</p> <p>RD1 | 42 | 5.4 | 4.4 | 1100 | 100</p> <p>RD2 | 20 | 2.8 | 3.1 | 1200 | 300</p> <p>RD3 | 21 | 3 | 2.2 | 700 | 100</p> <p>TD1 | 40 | 4.8 | 5 | 1000 | 250</p> <p>TD2 | 20 | 3 | 2.5 | 700 | 230 </p> <p>TD3 | 19 | 3.3 | 3 | 900 | 300</p> <p>TD4 | 19 | 3.5 | 2.6 | 750 | 360</p> <p>All the beams were loaded using Hysitron PI85 picoindenter with truncated cone shape (5 µm diameter). The indenter tip was aligned with the notch location and the middle of beam width. RD3 beam had some misalignment along the width.</p> <p>All the beams, except RD3 beam, were loaded under displacement control with displacement rates between 5nm/s to 10nm/s until failure. RD3 beam was loaded under load control with loading rate ~33µN/s. </p> <p>The SEM videos were captured using JEOL JSM-7600F SEM. </p> <p>[1] Irene J Beyerlein et al. “Interface-driven microstructure development and ultra high strength of bulk nanostructured Cu-Nb multilayers fabricated by severe plastic deformation”. In: Journal of materials research 28.13 (2013), pp. 1799–1812</p>
Metabolomic Profiling of Zinc Accumulating Prostate Cancer Cells: dataset of metabolomics and transctiptomics
<p>In this study, we focused on the metabolism of prostate cancer cells forced to accumulate zinc. Because levels of metabolites involved in Krebs and methionine cycle can participate in non-metabolic processes such as changes in gene expression, a panel of 371 genes connected with key steps of carcinogenesis was designed and expression levels of these genes were assessed to determine, which pathways are changed due to the long-term zinc treatment.</p> <p>As a model of prostate cancerogenesis, wild-type and zinc accumulating cell lines PNT1A, 22Rv1, and PC-3 were used. Metabolite profiles were examined using liquid chromatography triple quadrupole mass spectrometry. Quantification of total intracellular zinc was performed by atomic absorption spectrometry and gene expression investigated by cDNA microarray. </p> <p>For description of creation of zinc-resistant cell lines see Holubova et al, Metallomics 2014, DOI 10.1039/C4MT00065J</p> <p> </p> <p><strong>Description of dataset</strong></p> <p>Total 6 files are included:</p> <p><em>Krebs.metabolites.csv</em>: table of metabolomic data (in ppm) of wild type/untreated/zinc-resistant cells.</p> <p><em>Krebs.metabolites.medium.csv</em>: table of metabolomic data (in fold change compared to medium) in cultivation media of abovementioned cells.</p> <p><em>RNA_array_fold_p.csv</em>: processed results of microarray displayed as mean log2 fold change (resistant - WT) and p level</p> <p><em>RNA_array_raw_22Rv1.csv</em>, <em>RNA_array_raw_PC-3.csv, RNA_array_raw_PNT1A.csv</em> raw data from microarray reader for WT and resistant cells.</p>
Snow accumulation patterns in a high mountain Andean catchment from optical tri-stereoscopic remote sensing
<p><strong>1) DBSM_Data_RioYeso'</strong> = Automatic weather station (AWS) data from Yeso Embalse and Termas del Plomo meteorological stations (available from Chilean Water Directorate, 'Dirección General de Aguas' or 'DGA' http://www.arcgis.com/apps/OnePane/basicviewer/index.html?appid=d508beb3a88f43d28c17a8ec9fac5ef0), used to force a distributed blowing snow model of Essery et al. (1999) to derive spatial snow depth of the Rio del Yeso catchment, Chile. The format is as follows:</p> <p><em>{'Year','Month','Day','Hour','Incoming shortwave radiation (Wm2)','Incoming longwave radiation (Wm2)','SnowfallRate(mm/hr)','RainfallRate(mm/hr)','Air temperature (celsius)','Relative humidity (%)','Wind speed (m s-1)','Compass wind direction','Air pressure (hPa)'};</em></p> <p><strong>2) 'snowHeightPleiadesREG' </strong>= A snow depth map (horizontal resolution 4m) derived from triplets of high resoution stereo optical satellite images (Pléiades) following the methodology of Marti et al. (2016). The snow depth map is derived for a high mountain catchment (Rio del Yeso) of the central Chilean Andes (see Burger et al., 2018).</p> <p><strong>3) 'L2_LiDAR_4m'</strong> = A LiDAR (Light detection and Ranging) spatial snow depth map at a horizontal resolution of 4 m. The data were captured by a Reigl VZ-6000 LiDAR scanner and generated from the difference of two constructed digital elevation models (DEMs) between the dates 13th September, 2017 (with snow) and 12th December, 2017 (without snow). </p> <p><strong>4) 'L2_Pleiades_SDLidar_NEW' </strong>= The Pléiades snow depth map as described in <strong>2)</strong>, extracted by the areas of LiDAR scan described in <strong>3)</strong>. </p> <p><strong>5) 'SnowDepthResults'</strong> = A folder containing a corrected and gap-filled Pléiades snow depth map (<strong>'SD_PleiadesCORR'</strong>) and for comparison: <strong>'SD_TOPO'</strong>, a statistical estimation of snow depth using topographic parameters and the regression equation of Grünewald et al. (2013) and; The physically based estimates of snow depth using the DBSM model as in <strong>1)</strong> without snow transport for the 4th September, 2017 (<strong>'SD_EXTP_Sep04'</strong>) and 13th September, 2017 ('<strong>SD_EXTP_Sep13'</strong>) and with snow transport for those dates (<strong>'SD_Wind_Sep04','SD_Wind_Sep13'</strong>).</p> <p><strong>6) 'rdyDEM'</strong> = An independent ASTER GDEM (https://asterweb.jpl.nasa.gov/gdem.asp) cut to the area of the study catchment (horizontal resolution = 30 m). </p> <p><strong>7) '</strong><strong>PlanetScope_20170907_TPK' </strong>= An stitched optical PlanetScope image of the catchment (horizontal resolution of 3.25 m) derived from access under the research and teaching iniative (planet.com). </p> <p><strong>Cited work:</strong></p> <p><strong>Burger, F. et al.</strong> (2018) ‘Interannual variability in glacier contribution to runoff from a high ‐ elevation Andean catchment : understanding the role of debris cover in glacier hydrology’, Hydrological Processes, pp. 1–16. doi: 10.1002/hyp.13354.</p> <p><strong>Essery, R</strong>., Li, L. and Pomeroy, J. (1999) ‘A distributed model of blowing snow over complex terrain’, Hydrological Processes, 13(14–15), pp. 2423–2438. doi: 10.1002/(SICI)1099-1085(199910)13:14/15<2423::AID-HYP853>3.0.CO;2-U.</p> <p><strong>Grünewald, T. et al.</strong> (2013) ‘Statistical modelling of the snow depth distribution in open alpine terrain’, Hydrology and Earth System Sciences, 17(8), pp. 3005–3021. doi: 10.5194/hess-17-3005-2013.</p> <p><strong>Marti, R. et al</strong>. (2016) ‘Mapping snow depth in open alpine terrain from stereo satellite imagery’, The Cryosphere, pp. 1361–1380. doi: 10.5194/tc-10-1361-2016.</p>
Identification of novel genes involved in phosphate accumulation in Lotus japonicus through Genome Wide Association mapping of root system architecture and anion content
<p>130 Lotus japonicus accessions were used. The names and accession numbers are<br> listed in S6 Table. Seeds were scarified with sandpaper and then sterilized 14 minutes in 0.05%<br> sodium hypochlorite. Subsequently, seeds were rinsed and washed 5 times in sterile distilled<br> water. For the germination, seeds were positioned in imbibed filter paper, in sterile Petri dishes,<br> and wrapped in aluminium foil. After 3 days at 21°C, young seedling were transferred to square<br> plates (12 x 12 cm) containing growth medium. Both media used in this<br> study were based on Long-Ashton solution (with two levels of phosphate concentration -20 or<br> 750 μM, LP or HP, respectively) with 0.8% MES buffer (Duchefa Biochemie,<br> Haarlem, The Netherlands), 0.8% agarose (to minimize phosphate contamination), and adjusted<br> to pH 5.7 with 1M KOH. After adding the medium, plates were dried, closed, overnight in a<br> sterile laminar flow hood. Two accessions, with four replicates per each accession, were placed<br> on each plate. Each plate was replicated, with mirrored position of each accession to minimize<br> any positional growth effects. Plates were placed vertically, and plants grown under long-day<br> conditions (21°C, 16 h light/8 h dark cycle) with white light bulbs emitting 50 μmol/m 2 /s and<br> roots were exposed to light. Every day at the same time, the racks were transported to the image<br> acquisition room where images of each plate were acquired with eight Epson V600 CCD flatbed<br> color image scanners (Seiko Epson) and then immediately returned to the growth chamber.</p>
Text-fig. 2. Cracked chrysophycean-cysts and nest-like accumulation of the pennate diatom Gomphonema bohemicum REICHELT et FRICKE 1902 embedded in a bituminous and clayish matrix, SEM-photograph, sample Sf (no number), seam 1 roof. in Siliceous Microfossils From The Oligocene Tripoli-Deposit Of Seifhennersdorf
Text-fig. 2. Cracked chrysophycean-cysts and nest-like accumulation of the pennate diatom Gomphonema bohemicum REICHELT et FRICKE 1902 embedded in a bituminous and clayish matrix, SEM-photograph, sample Sf (no number), seam 1 roof.
Figure 2 in Factors affecting trace element accumulation in livers of avian species from East Poland
Figure 2. RDA results showing the effect of different ecological parameters (the dotted lines) on the concentration of heavy metals in the livers of studied bird species. Monte Carlo permutation test of significance of all canonical axes: P = 0.002. Eigenvalues: axis 1 – 0.197; axis 2 – 0.138. Abbreviations and scales used for analysis: Species: CC - Corvus corax, CF - Corvus frugilegus, CO - Corvus cornix, CM - Corvus monedula, PP - Pica pica, SR - Streptopelia decaocto, AC - Anas platyrhynchos, GA - Garrulus glandarius, SR - Scolopax rusticola, AC - Ardea cinerea, PH - Phalacrocorax carbo, LA - Larus argentatus, LC - Larus canus, CR - Chroicocephalus ridibundus. Food preferences: food F – fish, food I – invertebrates, food O – omnivorous, food P – plants. Foraging area: importance of wetlands for foraging (I wetlands), importance of dumps for foraging (I dumps), importance of urban habitats for foraging (I urban): 0 – none, 1 – small, 2 – medium, 3 – big. Nesting site habitat: nest F – forest, nest U – urban habitat, nest A – aquatic habitat, nest R – rural habitats. Vertebrate carrion importance in food (I carrion): 1 – small, 2 – medium, 3 – big; invertebrate importance in food (I inv): 0 – none, 1 – small, 2 – big. Weight – weight of individuals according to Busse (1990).
Figure 6 in Investigations of the nervous system biomarkers in the brain and muscle of freshwater fish (Oreochromis niloticus) following accumulation of nanoparticles in the tissues
Figure 6. TEM images of brain tissue sample of fish (O. niloticus) exposed to 1 (A and B), 5 (C and D), and 25 (E and F) mg/L of CuO NPs for 14 days of uptake and 14 days of depuration periods, respectively.
Figure 10 in Investigations of the nervous system biomarkers in the brain and muscle of freshwater fish (Oreochromis niloticus) following accumulation of nanoparticles in the tissues
Figure 10. The mean ATPase activity and associated standard errors in the brain of O. niloticus exposed to Al2 O 3 (a), CuO (b), and TiO2 NPs for 14 days (n = 6). See Figure 8 for detail.
Figure 5 in Investigations of the nervous system biomarkers in the brain and muscle of freshwater fish (Oreochromis niloticus) following accumulation of nanoparticles in the tissues
Figure 5. TEM images of brain tissue sample of fish (O. niloticus) exposed to 1 (A and B), 5 (C and D), and 25 (E and F) mg/L of Al2 O 3 NPs for 14 days of uptake and 14 days of depuration periods, respectively.
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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.