Find research datasets worth reusing

opencc-by-4.0May 2018View details →

Sparks et al, Heterogeneity in tumor chromatin-doxorubicin binding revealed by in vivo fluorescence lifetime imaging confocal endomicroscopy: In vitro data

Data is divided into three folders: <ul> <li>Sparks_et_al_FIG2_Histone_vs_free_GFP <ul> <li>data for Sparks et al Figure 2</li> <li>main text section: 'FRET between  chromatin-bound GFP and doxorubicin'</li> </ul> </li> <li>Sparks_et_al_FIG3_in_vitro_dose_response <ul> <li>data for Sparks et al Figure 3#</li> <li>main text section: 'FLIM endomicroscope can monitor doxorubicin cellular uptake'</li> </ul> </li> <li>Sparks_et_al_SuppFIG2_endoscope_spectral_cross_talk <ul> <li>data for Sparks et al Supplementary Figure 2</li> <li>Supplementary information</li> </ul> </li> </ul> Cell lines IGROV-1 cell lines were cultured in CO2 dependent media with 10% fetal bovine serum and 1% Pen Strep at 37 ˚C. Before experiments, cells were grown to 80% confluence. For measuring doxorubicin uptake by fluorescence an IGROV-1 cell line stably expressing GFP fused to Histone-1 (H1) was made using the PiggyBac transposon system. As a control to show that effect of doxorubicin on GFP depends on whether it is fused to H1 or not, a stable whole cell expression of GFP by lentiviral transfection and selection by Geneticin was made. For bioluminescence imaging of xenograft tumors, all IGROV-1 cell lines were made to stably express firefly luciferase. To investigate the effect of doxorubicin on other histones, IGROV-1 cells were transiently transfected with a Histone-2B-GFP plasmid (gift from Kurt Anderson) using the Lipofectamine® 2000 reagent. IGROV-1 cells were obtained from Crick institute cell services and confirmed as IGROV-1 by Short Tandem Repeats (STR) profiling and no mycoplasma was detected. In vitro experiments IGROV-1 cells were grown to 80% confluence in 75 ml flasks before being re-plated in 12 or 24 well plates or 35 ml glass bottomed dishes and allowed to attach to the surface for 24 hours before experiments. To study how the fluorescence of GFP labelled H1 labelled IGROV-1 cells changes with doxorubicin treatment, fluorescence intensity and lifetime distributions were measured from cells after 3 hours of incubation with doxorubicin of varying concentrations (0, 0.18, 0.9, 1.8, 9, 18 µM) by serial dilutions of a stock solution with PBS. After 3 of hours, cells were washed in PBS then fixed for 20 minutes in 4% PFA. Cells were then imaged in PBS.  Doxorubicin hydrochloride (Sigma-Aldrich, D1515-10 mg) was dissolved in PBS to a concentration of 9 mM and stored at -20˚C.

opencc-by-4.0May 2018View details →

Sparks et al, Heterogeneity in tumor chromatin-doxorubicin binding revealed by in vivo fluorescence lifetime imaging confocal endomicroscopy: in vivo data

Data is divided into three folders: <ul> <li>Sparks_et_al_FIG_6_IP_intranodule_heterogeneity <ul> <li>data for Sparks et al Figure 6</li> <li>main text section: 'FRET between  chromatin-bound GFP and doxorubicin'</li> </ul> </li> <li>Sparks_et_al_FIG4_5_6_IP_IV_chemo_comparison <ul> <li>data for Sparks et al Figures 4,5 & 6</li> <li>main text section: 'FLIM endomicroscope can monitor doxorubicin cellular uptake'</li> </ul> </li> <li>Sparks_et_al_FIG6_IP__internodule_heterogeneity <ul> <li>data for Sparks et al Figure 6</li> <li>main text section: 'Intra-tumor heterogeneity'</li> </ul> </li> </ul> In vivo experiments Murine xenografts were prepared by intraperitoneal (IP) injection of IGROV-1 cancer cells. IGROV-1 cells were grown to 80% confluence before being trypsinized and re‑suspended in PBS at a concentration of  cells per ml.  cells were injected into ICRF nude mice. After 14 days post-injection, the presence of intraperitoneal tumors was confirmed by bioluminescence imaging. Briefly, an IVIS bioluminescence imaging system was used to image isoflurane anesthetized mice. 100 µl of D-luciferin (luciferase substrate) at 30mg ml-1 was injected IP 10 minutes before recording of bioluminescence images. The presence of peritoneal tumors was confirmed if bioluminescence signals from the peritoneum were above background noise 10-30 minutes after D‑luciferin injections. Following confirmation of tumors, in vivo fluorescence imaging experiments were carried out after 21 days. To study differences in drug uptake between intravenous or intraperitoneal delivery, prior to imaging mice were subject to IP or IV doxorubicin-based chemotherapy for 1.5, 3 or 24 hours. Imaging involved terminal procedures, mice were anesthetized then peritoneal tumors were exposed by minor surgery and inspected with the CEM. All animal model procedures were approved by The Francis Crick Institute Biological Ethics Committee and UK Home Office authority provided by Project License 70/8380.

opengpl-2.0Jun 2018View details →

Companion for "Design, Implementation and Performance Analysis of a CFD task-based Application for Heterogeneous CPU/GPU Resources"

This is the companion data for the VECPAR2018 submission paper entitled: Design, Implementation and Performance Analysis of a CFD task-based Application for Heterogeneous CPU/GPU Resources by Lucas Leandro Nesi, Lucas Mello Schnorr, and Philippe Olivier Alexandre Navaux. All the data, source code, and images generation scripts used in the paper are present here.

opencc-by-4.0Aug 2018View details →

SPUSPO: Spatially Partitioned Unsupervised Segmentation Parameter Optimization for Efficiently Segmenting Large Heterogeneous Areas

This dataset contains several data, results and processing material from the application of GEOBIA-based, Spatially Partitioned Segmentation Parameter Optimization (SPUSPO) in the city of Ouagadougou. In detail in contains: <ul> <li>A Land Use - Land Cover map of Ouagadougou derived through SPUSPO. The classifier used was Extreme Gradient Boosting (XGBoost).  Labels : 2 : Artificial Ground Surface 0 : Building 5 : Low Vegetation 4 : Tree 1 : Swimming Pool 3 : Bare Ground 7 : Shadow 6 : Inland Water </li> </ul>   <ul> <li>The training and test data used in  the study (SPUSPO and benchmark approach). </li> </ul> The data are given in a csv format. <ul> <li>The Jupyter notebook code which involves Python and GRASS GIS to automatize and efficiently perform SPUSPO in a large dataset.</li> </ul> Python code calling GRASS GIS functions for automatizing the procedure.   <ul> <li>The segmentation layers coming from SPUSPO and the benchmark approaches (in raster formats due to data limitations).</li> </ul> Segmentation rasters for each approach. <ul> <li>The R code for optimization of XGBoost as well as feature selection with VSURF and classification of the whole dataset.</li> </ul>   <ul> <li>Segmentation evaluation metrics.</li> </ul> A csv file with the data sued to compute the Area Fit Index for each approach. <ul> <li>Morphological zones of Ouagadougou as created by Grippa et al. 2017 a shp format.</li> </ul>

opencc-by-4.0Nov 2018View details →

Improvements to stratospheric chemistry scheme in the UM-UKCA (v10.7) model: solar cycle and heterogeneous reactions

These are the data and the Python notebooks required to create the figures from the paper.   Abstract: Improvements are made to two areas of the United Kingdom Chemistry and Aerosol (UKCA) module, which forms part of the Met Office Unified Model (UM) used for weather and climate applications. Firstly, a solar cycle is added to the photolysis scheme. The effect on total column ozone of this addition was found to be around 1-2% in mid-latitude and equatorial regions in phase with the solar cycle. Secondly, reactions occurring on the surfaces of polar stratospheric clouds and sulfate aerosol are updated and extended by modification of the uptake coefficients of five existing reactions and the addition of a further eight reactions involving bromine species. These modifications are shown to reduce the overabundance of modeled total-column ozone in the Arctic during October to February, southern mid-latitudes during August, and the Antarctic during September. Antarctic springtime ozone depletion is shown to be enhanced by 25 DU on average, which now causes the ozone hole to be somewhat too deep compared to observations. We show that this is in part due to a cold bias of the Antarctic polar vortex in the model.

opencc-by-4.0Apr 2015View details →

Figure. Constrained ordination plot as produced from canonical correspondence analysis (CCA). The variability of environmental variables is summarized on Axis 1 and Axis 2 of the constrained biplot, explaining the variability of the trophic groups included in the red fox's diet. Trophic groups are shown with black line (unfilled) pyramids, whereas environmental variables are shown with black filled pyramids. Proximity and distance of response centroids to predictor centroids indicate positive and negative correlations between them, respectively. in Factors affecting the diet of the red fox (Vulpes vulpes) in a heterogeneous Mediterranean landscape

Figure. Constrained ordination plot as produced from canonical correspondence analysis (CCA). The variability of environmental variables is summarized on Axis 1 and Axis 2 of the constrained biplot, explaining the variability of the trophic groups included in the red fox's diet. Trophic groups are shown with black line (unfilled) pyramids, whereas environmental variables are shown with black filled pyramids. Proximity and distance of response centroids to predictor centroids indicate positive and negative correlations between them, respectively.

Fig. 5 in Environmental heterogeneity causes differences in the amphibian assemblage structure of an undisturbed montane cloud forest in southern Mexico

Fig. 5. Canonical Correspondence Analysis of the most common amphibians. The arrow orientation and length represent the association, direction, and strength between the environmental variables and the ordination axis. Species names correspond to: Crm (C. matudai), Plm (Pl. matudai), Pls (Pl. sagorum), Pte (Pt. euthysanota), Bof (B. franklini), Boo (B. occidentalis), and Dex (D. xolocalcae) Environmental acronyms correspond to: Hum (Humidity), Understory_Den (Under story density), Le_Li_depth (leaf litter depth), and Temp (temperature).

Fig. 4 in Environmental heterogeneity causes differences in the amphibian assemblage structure of an undisturbed montane cloud forest in southern Mexico

Fig. 4. (a) Principal Component Analysis, grouping the eight sites present in the core zones according to eight environmental variables taken in each site. Blue triangles: TCZ (El Triunfo core zone) sites; pink circles: QCZ (El Quetzal core zone) site. (b) Eight environmental variables measured in the eight sites (four per core zone). Median (solid line), 25th and 75th percentiles (boundaries of boxes), minimum and maximum (lines).

Fig. 1 in Environmental heterogeneity causes differences in the amphibian assemblage structure of an undisturbed montane cloud forest in southern Mexico

Fig. 1. Location of the two sampled zones, El Triunfo core zone [TCZ] (1) and the El Quetzal core zone [QCZ] (3), in the El Triunfo Biosphere Reserve (ETBR), Sierra Madre de Chiapas, Mexico, and illustration of the sample design (core zones, sites, and plots).

Fig. 3 in Environmental heterogeneity causes differences in the amphibian assemblage structure of an undisturbed montane cloud forest in southern Mexico

Fig. 3. (a) Rank-abundance Curves for the El Triunfo core zone [TCZ] and Quetzal core zone [QCZ] in the El Triunfo Biosphere Reserve. Letters on the Rank-abundance Curves correspond to Crm (C. matudai), Crs (C. stuarti), Pll (Pl. lacertosa), Plh (Pl. hartwegii), Plm (Pl. matudai), Pls (Pl. sagorum), Dus (D. schmidtorum), Pte (Pt. euthysanota), Exs (E. sumichrasti), Lim (L. maculatus), Bof (B. franklini), Boo (B. occidentalis), Bofl (B. flavimembris), and Dex (D. xolocalcae). (b) Nonmetric multidimensional scaling of the eight sites within the core zones in the ETBR. Blue triangles: TCZ sites, pink circles: QCZ sites. (c) Dendrogram of functional groups of the El Triunfo core zone amphibian species, using Euclidian Distance, and tested functional groups by ANOSIM are highlighted in different colors (FG1: green; FG2: brown; FG3: blue; FG4: red, and FG5: yellow).

Fig. 2 in Environmental heterogeneity causes differences in the amphibian assemblage structure of an undisturbed montane cloud forest in southern Mexico

Fig. 2. Box plots of amphibian species diversity in the El Triunfo Biosphere Reserve (ETBR), Chiapas, Mexico, showing the median (solid line), 25th and 75th percentiles (boundaries of boxes), and minimum and maximum (lines). (a) Number of individuals, (b) Species richness (0D), (c) Common species (1D), and (d) Dominant species (2D).

opencc-by-4.0Dec 2016View details →

Fig. 1 in Habitat heterogeneity on feeding habit of two sympatric and congeneric characidae fishes in two tropical reservoirs

Fig. 1. NMDS plot showing relation of food item abundance found in the diet of Astyanax aff. bimaculatus Linnaeus, 1758 and A. parahybae Eigenmann, 1908 in Lajes and Santana reservoirs, state of rio de Janeiro, Brazil (Ap, Astyanax parahybae; Ab, Astyanax aff. bimaculatus; Ljs, Lajes; Snt, Santana).

opencc-by-4.0Mar 2021View details →

FIGURE 2 in Population genetics of three threatened catfish species in heterogeneous environments of the Cauca River, Colombia

FIGURE 2 | Population structure suggested by STRUCTURE (A–C) and the Discriminant Analysis of the Principal Components (D–F) for Pimelodus grosskopfii (A, D), Sorubim cuspicaudus (B, E), and Ageneiosus pardalis (C, F).

opencc-by-4.0Mar 2021View details →

FIGURE 1 in Population genetics of three threatened catfish species in heterogeneous environments of the Cauca River, Colombia

FIGURE 1 | Location of sampling sites of Pimelodus grosskopfii, Sorubim cuspicaudus, and Ageneiosus pardalis in the middle and lower sections of the Cauca River.

FIGURE 4 in Fish assemblage structure related to habitat heterogeneity in rocky reefs in the Mexican Pacific coast

FIGURE 4 | Non-metric multidimensional scaling for fish assemblage data for the California Current (CC) and North Equatorial Current (NEC) in the sample sites: Caleta de chon (CH), Las Gatas (LG), Manzanillo (MZ), and Zacatoso (ZC). Horizontal and vertical scatter bars represent 95% confidence interval.

FIGURE 3 in Fish assemblage structure related to habitat heterogeneity in rocky reefs in the Mexican Pacific coast

FIGURE 3 | Rarefaction curves of species richness for the California Current (CC) and North Equatorial Current (NEC) in the sampled sites: Caleta de chon (CH), Las Gatas (LG), Manzanillo (MZ), and Zacatoso (ZC). Shaded area represents 95% confidence interval.

FIGURE 2 in Fish assemblage structure related to habitat heterogeneity in rocky reefs in the Mexican Pacific coast

FIGURE 2 | Principal component analysis of (A) sea water conditions and (B) heterogeneity components in sampling sites for the California Current (CC) and North Equatorial Current (NEC). Sampled sites: Caleta de chon (CH), Las Gatas (LG), Manzanillo (MZ), and Zacatoso (ZC). Horizontal and vertical scatter bars represent 95% of confidence interval.

FIGURE 1 in Fish assemblage structure related to habitat heterogeneity in rocky reefs in the Mexican Pacific coast

FIGURE 1 | Geographic location of the Ixtapa and Zihuatanejo bays in the Pacific Coast of Mexico and sampling sites.

opencc-by-4.0Oct 2021View details →

FIGURE 6 in Effects of urbanization and environmental heterogeneity on fish assemblages in small streams

FIGURE 6 | Ordination of fish species composition by distance-based redundancy analysis (dbRDA) in relation to environmental heterogeneity (EH; estimated from environmental data and transformed by loge(x) prior to dbRDA) and the proportion of impervious surfaces (ImpSurf). Species codes, 1: Poecilia reticulata; 2: Corydoras aeneus; 3: Phenacogaster jancupa; 4: Astyanax abramis; 5: Hoplias malabaricus; 6: Hypostomus khimaera; 7: Serrapinnus calliurus; 8: S. microdon; 9: Hemigrammus tridens; 10: A. lacustris.