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1,742 results for “activity data”
Data for: Identification of activating mutations in the transmembrane and extracellular domains of EGFR
<p>The epidermal growth factor receptor (EGFR) is frequently mutated in human cancer, most notably non-small-cell lung cancer and glioblastoma. While many frequently occurring EGFR mutations are known to confer constitutive EGFR activation, the situation is less clear for rarely detected variants. In fact, more than 1000 distinct EGFR mutations are listed in the Catalogue of Somatic Mutations in Cancer (COSMIC), but for most of them, the functional consequence is unknown. To identify additional, previously unknown activating mutations in EGFR, we screened a randomly mutated EGFR library for constitutive EGFR phosphorylation using a recently developed high-throughput approach termed PhosphoFlowSeq. Enrichment of the well-known activating mutations S768I, T790M, and L858R validated the experimental approach. Importantly, we also identified the activating mutations S442I and L658Q located in the extracellular and transmembrane domains of EGFR, respectively. To the best of our knowledge, neither S442I nor L658Q has been associated with an activating phenotype before. However, both have been detected in cancer samples. Interestingly, molecular dynamics (MD) simulations suggest that the L658Q mutation located in the hydrophobic transmembrane region forms intermolecular hydrogen bonds, thereby promoting EGFR dimerization and activation. Based on these findings, we screened the COSMIC database for additional hydrophilic mutations in the EGFR transmembrane region and indeed detected moderate constitutive activation of EGFR-G652R. Together, this study demonstrates that unbiased screening for activating mutations in EGFR not only yields well-established substitutions located in the kinase domain but also activating mutations in other regions of EGFR, including the extracellular and transmembrane domains.</p> <p> </p> <p>A. Wagner, E. Galicia-Andrés, M. Teufl, L. Gold, C. Obinger, P. Sykacek, C. Oostenbrink and M.W. Traxlmayr<br>Identification of activating mutations in the transmembrane and extracellular domains of EGFR<br>Biochemistry <strong>61</strong> (2022) 2049 – 2062<br>doi: <a href="https://doi.org/10.1021/acs.biochem.2c00384" target="_blank" rel="noopener">10.1021/acs.biochem.2c00384</a></p>
Data and code for "Preconfigured cortico-thalamic neural dynamics constrain movement-associated thalamic activity"
<p>Data and code for "Preconfigured cortico-thalamic neural dynamics constrain movement-associated thalamic activity"</p> <p>Nature Communications; 2024 Nov 24;15(1):10185. doi: 10.1038/s41467-024-54742-9.</p>
DeepCanola: Phenotyping Brassica Pods Using Semi-Synthetic Data and Active Learning
<p>Dataset accomapnying the publication: <em>DeepCanola: Phenotyping Brassica Pods Using Semi-Synthetic Data and Active Learning </em>by Van Vliet, Atkins et al.</p> <p>We provide model weights, training and vlidation datasets, as well as phenotype outputs. Each file/folder is outlined below:</p> <ul> <li><em>deepcanola.pth - </em>Model weights for the final Model 4, named DeepCanola</li> <li><em>generated_datasets</em> - Datasets generated at each stage of the active learning process, datasets 1-4 <ul> <li>Each folder is an iteration of the active learning process, inside each folder are the generated images and associated annotations stored in the COCO format.</li> </ul> </li> <li><em>real_world_datasets - </em>Real-world datasets used for either creation of the pod pools or validation. Datasets include: <ul> <li><em>br9</em> - Ordered and disordered dataset of images with generated pod length data of the ordered images stored in the `br9_gt_lengths.csv` file</li> <li><em>br11</em> - Ordered and disordered dataset of images only</li> <li><em>br17</em> - Ordered dataset with ground-truth of images with length annotations collected in ImageJ and stored in the `BR017 POD SCAN DATA.csv` file.</li> <li><em>misc</em> - Dataset of m<span>iscellaneous images including Brassica napus from Rothamstead and brassica relatives</span></li> </ul> </li> <li><em>data_generation_pools</em> - Pools used to generate semi-synthetic data at each step of the active learning process. Pools include: <ul> <li><em>background_pool</em> - Created background images to be selected at random by the semi-synthetic data generation script</li> <li><em>pod_pools - </em>Pools of pods used in the semi-synthetic data generation process. Pod pools include: <ul> <li><em>br9 - </em>673 pods with associated masks</li> <li><em>br9 and br17 - </em>673 + 332 pods with associated masks</li> </ul> </li> </ul> </li> <li><em>deepcanola_outputs - </em>Phenotype data outputs generated by DeepCanola. Each output is stored as a .csv file of both length measurements of each pod (with <em>_objects.csv</em> suffix), and average length measurements per image (with <em>_averages.csv</em> suffix). Outputs include: <ul> <li><em>br9_ordered</em></li> <li><em>br9_disordered</em></li> <li><em>br17</em></li> </ul> </li> </ul>
Pose-estimated 3D data of infant spontaneous activity from Helsinki and Pisa
<p>This dataset contains pose-estimated 3D (and 2D proxy) data as well as trained models for generating infant Kinetic Age, collected from research trials in Helsinki and Pisa. The dataset is organized into separate archives for metadata, data streams, trained models, and predictions. Below is a detailed breakdown of the dataset contents:</p> <p><strong>Metadata</strong></p> <ul> <li><em>metadata/combined.csv</em><br> - test_id: Unique identifier for each infant.<br> - corrected_age: Corrected age of the infant in days.<br> - outcome: Neurodevelopmental outcome labels (0 typical, 1 weak impairment, 2 MNI).</li> </ul> <p><strong>Data</strong></p> <ul> <li><em>data/features.csv</em><br> - Handcrafted movement features computed for each, by experts annotated, useful video segment.</li> <li><em>data/streams/combined/*.feather</em><br> - 3D recording segment, with 18 J, B, V, A streams over 600 time steps.</li> <li><em>data/streams_2d/combined/*.feather </em><br> - 2D recording segment, with 18 J, B, V, A streams over 600 time steps.</li> </ul> <p><strong>Results</strong></p> <ul> <li><em>results/model/fold_n/...</em><br> - train_predictions.npy: Predictions made on the training set.<br> - val_predictions.npy: Predictions made on the validation set.<br> - best_model.ckpt: Checkpoint file containing the saved model weights.<br> - metadata.json: Metadata describing the fold, including training parameters and validation segments.<br> - scatter_*.png: Regression results.</li> </ul> <p><strong>Predictions</strong></p> <ul> <li><em>predictions/jb-aagcn-coord-xy_predictions.csv</em><br> - Model predictions for the 2D model on MNI samples.</li> <li><em>predictions/jb-aagcn-coord_predictions.csv</em><br> - Model predictions for the 3D model on MNI samples.</li> </ul>
Dataset: Chromatographic data for publication Exploration and optimisation of structure-activity relationships of newtriazole-based C-terminal Hsp90 inhibitors towards in vivoanticancer potency
<p>Bio-chromoatographic data caming from publication Exploration and optimisation of structure-activity relationships of new triazole-based C-terminal Hsp90 inhibitors towards in vivo anticancer potency</p>
Data for Rapid microwave-assisted hydrothermal in situ synthesis of nano-ZnS/kaolinite nanocomposite: a non-toxic photocatalyst active under UV and sunlight
Open the record for dataset details and reuse information.
Data for "The Massive and Distant Clusters of WISE Survey. XII. Exploring X-ray AGN in Dynamically Active Massive Galaxy Clusters at z~1"
<p>This dataset corresponds to the manuscript titled "The Massive and Distant Clusters of <em>WISE</em> Survey. XII. Exploring X-ray AGN in Dynamically Active Massive Galaxy Clusters at z~1" (<span>DOI: 10.3847/1538-4357/adbae4)</span>, accepted for publication in <em>The Astrophysical Journal</em> on February 24, 2025. To replicate the plots and access the catalogs used in the paper, download and extract all the zip folders along with the Jupyter Notebook "<a href="https://zenodo.org/api/records/14928038/draft/files/madcows_notebook.ipynb/content">madcows_notebook.ipynb</a>" into the same directory. Open the notebook and follow the instructions provided. For any issues, please contact the corresponding author.</p>
Data and code from "Full bandwidth electrophysiology of seizures and epileptiform activity enabled by flexible graphene micro-transistor depth neural probes"
<p>Data and python code for reproducing the main results of the paper "Full bandwidth electrophysiology of seizures and epileptiform activity enabled by flexible graphene micro-transistor depth neural probes."</p>
Predictive utility of task-related functional connectivity vs. voxel activation - Data and code archive
<p>Functional connectivity, both in resting state and task performance, has steadily increased its share of neuroimaging research effort in the last 1.5 decades. In the current study, we investigated the predictive utility regarding behavioral performance and task information for 240 participants, aged 20-77, for both voxel activation and functional connectivity in 12 cognitive tasks, belonging to 4 cognitive reference domains (Episodic Memory, Fluid Reasoning, Perceptual Speed, and Vocabulary). We also added a model only comprising brain-structure information not specifically acquired during performance of a cognitive task. We used a simple brain-behavioral prediction technique based on Principal Component Analysis (PCA) and regression and studied the utility of both modalities in quasi out-of-sample predictions, using split-sample simulations (=5-fold Monte Carlo cross validation) with 1,000 iterations for which a regression model predicting a cognitive outcome was estimated in a training sample, with a subsequent assessment of prediction success in a non-overlapping test sample. The sample assignments were identical for functional connectivity, voxel activation, and brain structure, enabling apples-to-apples comparisons of predictive utility. All 3 models that were investigated included the demographic covariates age, gender, and years of education. A minimal reference model using simple linear regression with just these 3 covariates was included for comparison as well and was evaluated with the same resampling scheme as described above. Results of the comparison between voxel activation and functional connectivity were mixed and showed some dependency on cognitive outcome; however, mean differences in predictive utility between voxel activation and functional connectivity were rather small in terms of within-modality variability or predictive success. More notably, only in the case of Fluid Reasoning did concurrent functional neuroimaging provided compelling about cognitive performance beyond structural brain imaging or the minimal reference model.</p>
Characterization of Site-Specific Vegetation Activity in Alaskan Wet and Dry Tundra as Related to Climate and Soil State DATA
<p>We present discrete (2-hour resolution) multi-year (2008 – 2017) <em>in situ </em>measurements of seasonal vegetation growth and soil biophysical properties from two sites on Alaska’s North Slope, USA, representing dry and wet sedge tundra. We examine measurements of vertical active soil layer temperature and soil moisture profiles (freeze/thaw status), woody shrub vegetation physiological activity, and meteorological site data to assess interrelationships within (and between) these two study sites.</p> <p>Vegetation phenophases (cold de-hardening start, physiological function start, stem growth start, stem growth end, physiological function end, cold hardening completion) were found to have greater inter-annual Day-Of-Year (DOY) occurrence variability at the dry site compared to the wet site. At the dry site, vegetation activity begins on average ~ 7 days earlier and ends ~ 11 days earlier. The mean active stem growth window lasts ~ 54 days for the dry site and ~51 days for the wet site. Vegetation, in both tundra environments, began cold de-hardening functions (warm season prep) prior to atmospheric temperatures warming above 0°C. Similar results were found related to the critical soil freeze/thaw/transition dates; the dry site had a DOY phenophase occurrence range that was 8 days larger than that of the wet site. A longer continuous summer thaw period was captured at the wet site by ~ 26 days throughout the active layer. In addition, the dry site was measured to have longer spring and fall soil isothermal conditions than the wet site by ~ 9 and 5 days throughout the active layer. These results show that the dry site’s willow shrub vegetation physiology and soil condition phenology is more variable than the wet site.</p> <p>Alongside the <em>in situ</em> data, a remote sensing product from NASA’s MEaSUREs program was utilized; our research indicates that the AMSR derived satellite product is more precise over the wet tundra site with critical date alignment between remote sensing observations and <em>in situ</em> measurements ranging from ~ 4 to 11 days. Furthermore, the AMSR product was shown to preemptively estimate land surface condition change during the spring transition for both tundra types while lagging during the fall transition and freeze-up periods.</p>
Data from: The active mouse rests within: Energy management among and within individuals
<p>1. The relationship between daily energy expenditure (DEE) and resting metabolic rate (RMR) provides insight into how organisms allocate energy to maintenance <i>versus</i> energetically expensive activities such as locomotor activity.</p> <p>2. Three models have been devised to describe energy management: the allocation, independent, and performance models, which respectively predict a DEE-RMR slope of <i>b</i><1, <i>b</i>=1, and <i>b</i>>1.</p> <p>3. Here, we took paired repeated metabolic and behavioural measurements in 51 female white-footed mice to 1) evaluate which energy management models apply at the among- and within-individual levels, and to 2) quantify the relationship between metabolic traits and two energetically expensive behaviours.</p> <p>4. The DEE-RMR slope was different at the among- <i>versus</i> within-individual levels, with values supporting the performance and allocation models at the among- and within-individual levels, respectively. Accordingly, the relationship between voluntary wheel running and RMR was positive at the among-individual level (<i>r</i><sub> </sub>= 0.40±0.21), but negative at the within-individual level (<i>r </i>= -0.23±0.10).</p> <p>5. To our knowledge, this is the first study to simultaneously partition the relationship between RMR and behaviour at the among- <i>versus</i> within-individuals levels while determining which energy management models apply at each of these levels. In doing so, we have identified a mechanism through which compensation occurs at the within-individual level.</p>
Data from: Dynamics in brain activation and behaviour in acute and repeated social defensive behaviour
<p>In nature, confrontations between conspecifics are recurrent and related, in general, due to the lack of resources such as food and territory. Adequate defences against a conspecific aggressor are essential for the individual's survival and the group integrity. However, repeated social defeat is a significant stressor promoting several behavioural changes including social defence per se. What would be the neural basis of these behavioural changes? To build new hypotheses about this, we here investigate the effects of repeated social stress on the neural circuitry underlying motivated social defence behaviour in male mice. We observed that animals re-exposed to the aggressor three times spent more time in passive defence during the last exposure than in the first one. These animals also show less activation of the amygdalar and hypothalamic nuclei related to the processing of conspecific cues. In turn, we found no changes in the activation of the hypothalamic dorsal pre-mammillary nucleus (PMD) that is essential for passive defence. Therefore, our data suggest that the balance between the activity of circuits related to conspecific processing and the PMD determines the pattern of social defence behaviour. Changes in this balance may be the basis of the adaptations in social defence after repeated social defeat.</p>
Data from: Geographical variation in ant foraging activity and resource use is driven by climate and net primary productivity
<p><b>Aim: </b>Foraging activity is critical for animal survival. Comprehending how ecological drivers influence foraging behavior would benefit our understanding of the link between animals and ecological processes. Here, we evaluated the influence of ecological drivers on ant foraging activity and relative resource use.</p> <p><b>Location: </b>Six Brazilian biomes: Amazon, Atlantic rainforest, Caatinga, Cerrado, Pampa and Pantanal.</p> <p><b>Taxon: </b>Formicidae.</p> <p><b>Methods: </b>We assessed ant foraging activity and resource use by sampling across 60 sites. We placed baited tubes that contained one of five liquid resources (sugar, lipids, amino acid, sodium and distilled water). We used model selection to assess the influence of ecological drivers (temperature, precipitation, temperature seasonality and net primary productivity) on ant foraging activity and relative resource use.</p> <p><b>Results: </b>Foraging activity was higher in wetter, more productive and less thermally seasonal environments. The relative use of amino acids increased at higher temperatures while the relative use of lipids decreased. The relative use of sugar increased in drier and less productive environments with high temperature seasonality while the relative use of amino acid and sodium decreased in those environments. The relative use of lipids was complex: increasing with increasing temperature seasonality and decreasing with increasing precipitation. Further, the relative use of sodium was greater where the foraging activity was high.</p> <p><b>Main Conclusions: </b>We demonstrate how ecological drivers are correlated to ant foraging activity and resource use in the field across large spatial scales. The search for resources encompasses different interactions involving ants with abiotic and biotic components in the ecosystem. Thus, we suggest that changes in climate and NPP, which influence the intensity and the way that ants search for resources, will result in changes in ant-mediated ecological processes.</p>
Source data for "In-degree centrality in a social network is linked to coordinated neural activity"
<p>The following includes the source data for the manuscript titled "In-degree centrality in a social network is linked to coordinated neural activity". A second version of the source data ("Source Data_updated_011222.xlsx") includes the source data for the figures in the supplementary materials.</p>
β-glucosidase activity data after interaction with different soil minerals
<p>β-glucosidase activity data after interaction with different soil minerals</p>
Absolute measurement of cellular activities using photochromic single-fluorophore biosensors and intermittent quantification: data and code example
<p>Minimal code example, raw and derived data for the publication on 'Absolute measurement of cellular activities using photochromic single-fluorophore biosensors and intermittent quantification'.</p>
Data for the original research article 'Enhanced anaerobic digestion of dairy wastewater in a granular activated carbon amended sequential batch reactor'
<p>All data that support the findings of the study 'Enhanced anaerobic digestion of dairy wastewater in a granular activated carbon amended sequential batch reactor' published in GCB Bioenergy Journal are openly available in the file.</p>
Data from: Responses to artificial selection for locomotor activity: A focus on death feigning in red flour beetle
<p>Whole-organism performance, including locomotor activity, is an important fitness trait in many animals. Locomotor activity is often classified into sprint speed and locomotor endurance and differences in sprint speed and locomotor endurance affect on other traits such as life-history traits. Previous studies found that locomotor endurance, sprint speed, and brain dopamine (DA) levels are correlated with artificial selection for death-feigning (an anti-predator behavior that we refer to as "death-feigning syndrome") in some insect species. Thus, if the syndrome has a genetic basis, death feigning, sprint speed, and brain DA levels may be affected by artificial selection for locomotor endurance. We artificially selected for locomotor endurance over 10 generations in the red flour beetle <em>Tribolium castaneum</em>, and established higher (H) and lower activity (L) strains, then compared their death-feigning behavior, sprint speed, and brain DA levels. H-strain beetles exhibited significantly shorter duration of death-feigning, and significantly higher sprint speed, suggesting variation in death-feigning syndrome. Surprisingly, although brain DA expression affects various animal behaviors, we found no significant differences in the brain DA expressions of H- and L-strain beetles. Thus, our results imply genetic correlations between locomotor endurance, sprint speed, and death feigning, but not with brain DA expression, suggesting that differences in the biogenic amine results of our previous studies may reflect differences in behavioral expression mechanisms.</p>
Data from: Olfactory modulation of barrel cortex activity during active whisking and passive whisker stimulation
<p>Rodents depend on olfaction and touch to meet many of their fundamental needs. The joint significance of these sensory systems is underscored by an intricate coupling between sniffing and whisking. However, the impact of simultaneous olfactory and tactile inputs on sensory representations in the cortex remains elusive. To study these interactions, we recorded large populations of barrel cortex neurons using 2-photon calcium imaging in head-fixed mice during olfactory and tactile stimulation. We find that odors alter barrel cortex activity in at least two ways, first by enhancing whisking, and second by central cross-talk that persists after whisking is abolished by facial nerve sectioning. Odors can either enhance or suppress barrel cortex neuronal responses, and while odor identity can be decoded from population activity, it does not interfere with the tactile representation. Thus, barrel cortex represents olfactory information which, in the absence of learned associations, is coded independently of tactile information.</p>
Data used in "Topographic Modulation of the Wind Stress Impact on Eddy Activity in the Southern Ocean"
<p>These are the data used in the creation of figures (Fig3,4,S2) in Cai et al. 2022: "Topographic Modulation of the Wind Stress Impact on Eddy Activity in the Southern Ocean", including 9 experiments. It is obtained from NEMO output.</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.