Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
1,723
datasets available to search
ShareScore release 0.9.0
Dataset results
1,723 results for “Reactivation”
Effect of an alkaline reactive on the thermochemical process (pyrolytic) of HIPS
Open the record for dataset details and reuse information.
Memory reactivation in rat medial prefrontal cortex occurs in a subtype of cortical UP state during slow-wave sleep
Interaction between hippocampal sharp-wave ripples (SWRs) and UP states, possibly by coordinated reactivation of memory traces, is conjectured to play an important role in memory consolidation. Recently, it was reported that SWRs were differentiated into multiple subtypes. However, whether cortical UP states can also be classified into subtypes is not known. Here, we analysed neural ensemble activity from the medial prefrontal cortex from rats trained to run a spatial sequence-memory task. Application of the hidden Markov model (HMM) with three states to epochs of UP–DOWN oscillations identified DOWN states and two subtypes of UP state (UP-1 and UP-2). The two UP subtypes were distinguished by differences in duration, with UP-1 having a longer duration than UP-2, as well as differences in the speed of population vector (PV) decorrelation, with UP-1 decorrelating more slowly than UP-2. Reactivation of recent memory sequences predominantly occurred in UP-2. Short-duration reactivating UP states were dominated by UP-2 whereas long-duration ones exhibit transitions from UP-1 to UP-2. Thus, recent memory reactivation, if it occurred within long-duration UP states, typically was preceded by a period of slow PV evolution not related to recent experience, and which we speculate may be related to previously encoded information. If that is the case, then the transition from UP-1 to UP-2 subtypes may help gradual integration of recent experience with pre-existing cortical memories by interleaving the two in the same UP state. This article is part of the Theo Murphy meeting issue 'Memory reactivation: replaying events past, present and future'.
Poker: Visual Instrumentation of Reactive Programs With Programmable Probes (video demonstration)
<p>This video is supplementary material for a paper submitted to the 2021 workshop on reactive and event-based languages and systems (REBLS 2021): https://2021.splashcon.org/home/rebls-2021</p> <p>Music: <a href="https://www.bensound.com/royalty-free-music">https://www.bensound.com/royalty-free-music</a> </p> <p> </p>
Dataset for study: The association between reactive strength index and reactive strength index modified with approach jump performance
<p>This is the underlying dataset for study: The association between reactive strength index and reactive strength index modified with approach jump performance. </p>
Reactivity of Multimetallic Thorium Nitrides Generated by Reduction of Thorium Azides
<p>This upload contains raw data (NMR, X-Ray, Elemental Analysis) files for the article</p>
Measurement report: Springtime reactive Volatile Organic Compounds (VOCs) and impacts on ozone in urban areas of Yunnan-Guizhou Plateau, China: a PTR-TOF-MS study
<p>Time-varying sequence and day-to-day concentration after treatment. It includes 18 observed major VOCs [acetaldehyde, 2-acrolein, acetone, methyl ethyl ketone (MEK), methyl vinyl ketone (MVK), methacrolein (MACR), methyl isobutyl ketone (MIK), 2-pentanone, ethyl acetate, isoprene, α-pinene, benzene, toluene, styrene, C8 aromatic hydrocarbons, C9 aromatic hydrocarbons, 1,3-dichlorobenzene, naphthalene, and acetonitrile].</p>
Data for Deep Reactive Ion Etching of Cylindrical Nanopores in Silicon for Photonic Crystals
<p>Data for Deep Reactive Ion Etching of Cylindrical Nanopores in Silicon for Photonic Crystals</p>
Structures for article: "The reactivity of pyridine in cold interstellar environments: The reaction of pyridine with the CN radical"
<p>Set of cartesian structures supporting the article: "The reactivity of pyridine in cold interstellar environments: The reaction of pyridine with the CN radical"</p> <p> </p>
Structural characterization of the protein-material interfacial interactions by using lysine reactivity profiling-mass spectrometry
<p>The exploration of interfacial molecular interactions of protein-material integrations and how material modulate the protein structure and activity are essential to the safety evaluation of biomedical micro/nanomaterials, toxicity estimation and design of nano-drugs, and catalytic activity improvement of bio-inorganic functional hybrids. However, characterizing the interfacial molecular details of protein-micro/nanomaterial hybrids remains a great challenge. Herein, we introduce the protocol of lysine reactivity profiling-mass spectrometry (LRP-MS) strategy for probing the interfacial molecular structures between proteins and micro/nanomaterials. LRP-MS utilizes lysine residues as the endogenous probes to characterize the protein localization orientation, interaction sequence regions, binding sites, and modulated protein structures in the protein-material hybrids, which cannot be achieved by traditional spectroscopy methods. We describe the optimized heavy and light two-step isotope dimethyl labeling strategy for protein-material hybrids under their native and denaturing conditions in sequence. The comparative quantification results of lysine reactivity (referred as NLE) are only dependent on the native microenvironments of lysine local structures. We also highlight other critical steps including protein digestion, elution from materials, data processing, and interfacial structure analysis. The two-step isotope labeling steps need about 5 h, and the whole protocol including digestion, liquid chromatography-tandem mass spectrometry, data processing, and structure analysis needs about 3-5 days.</p>
Phototoxicity and Cell Passage Affect Intracellular Reactive Oxygen Species Levels and Sensitivity Towards Non-Thermal Plasma Treatment in Fluorescently-Labeled Cancer Cells
<p>Raw data for the manuscript "Phototoxicity and Cell Passage Affect Intracellular Reactive Oxygen Species Levels and Sensitivity Towards Non-Thermal Plasma Treatment in Fluorescently-Labeled Cancer Cells".</p>
Digitizing Chemical Discovery with a Bayesian Explorer for Interpreting Reactivity Data
<p>Dataset for the work entitled Digitizing Chemical Discovery with a Bayesian Explorer for Interpreting Reactivity Data</p>
Fast Trajectory End-Point Prediction with Event Cameras for Reactive Robot Control
<p>If you use any of this data, please cite the following publication:</p> <p><span>@inproceedings{monforte2023fast,</span><br><span> title={Fast Trajectory End-Point Prediction with Event Cameras for Reactive Robot Control},</span><br><span> author={Monforte, Marco and Gava, Luna and Iacono, Massimiliano and Glover, Arren and Bartolozzi, Chiara},</span><br><span> booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},</span><br><span> pages={4035--4043},</span><br><span> year={2023}</span><br><span>}</span></p> <p>Event-based datasets of synthetic and real trajectories of a bouncing ball.</p> <p>The synthetic trajectories were obtained converting frames taken using Unreal Engine to events. The ground truth is provided along with objects and camera settings.</p> <p>The real trajectories wer dumped from a real event camera located in front of the robot workspace.</p> <p>To import .log files containing events, we suggest <a href="https://github.com/event-driven-robotics/bimvee">bimvee</a> Python library.</p> <p>Specifically use the functions to import .log files:</p> <p>data = importIitYarpBinaryDataLog(filePathOrName=input_path)<br> </p> <p> </p> <p> </p>
Fig. 5 in Bond reactivity indices approach analysis of the [2+2] cycloaddition of jatrophane skeleton diterpenoids from Euphorbia gaditana Coss to tetracyclic gaditanone
Fig. 5. Selected NOESY correlations exhibited by 4. β-face correlations in red and α-face correlations in blue. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 6 in Bond reactivity indices approach analysis of the [2+2] cycloaddition of jatrophane skeleton diterpenoids from Euphorbia gaditana Coss to tetracyclic gaditanone
Fig. 6. Selected NOESY correlations exhibited by 5. β-face correlations in red and α-face correlations in blue. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 5 in Nerolidol inhibits proliferation of leiomyoma cells via reactive oxygen species-induced DNA damage and downregulation of the ATM/ Akt pathway
Fig. 5. Nerolidol suppressed the protein and mRNA expression of ATM in rat leiomyoma cells. (A, B) ELT3 cells were treated with nerolidol for 48 h and were then harvested for the western blot analysis of phosphorylated ATM and total ATM (A) and for determining ATM mRNA expression using quantitative RT-PCR (B). GAPDH was used as the loading control. The inserted numbers in (A) represent the relative expression level compared to that of the vehicle control (indicated as 0 μM). (C, D, E, F) ELT3 cells were treated with the indicated concentrations of KU-55933, an ATM inhibitor, for 48 h, following which the cells were harvested for further analysis. (C) The expression levels of p-ATMser1981, total ATM, p-Aktser473, total Akt, CDK4, and CDK6 were determined using western blot analysis. β-Actin was used as the loading control. The inserted numbers in (C) represent the relative expression level compared to that of the vehicle control (indicated as 0 μM). (D, E) Cell cycle analysis was performed after propidium iodide staining and FACS, and the results were analyzed using the FlowJo software (D). The percentages of cells in each cell cycle phase are plotted in (E). (F) Cell proliferation was determined using the MTT assay. DMSO (0.1 %) was used as the vehicle control. The data are presented as relative percentage compared to that of the vehicle control. The p-value was calculated using one-way ANOVA with Tukey's multiple post hoc test for each group. *, p <0.05; **, p <0.01, and ***, p <0.001 compared to the control group.
Fig. 3 in Nerolidol inhibits proliferation of leiomyoma cells via reactive oxygen species-induced DNA damage and downregulation of the ATM/ Akt pathway
Fig. 3. Nerolidol treatment led to the generation of intracellular ROS and impaired the mitochondrial membrane potential. (A) ELT3 cells were harvested after trypsin/EDTA treatment and then treated with 20 mM NAC, followed by DCFDA staining for 30 min. The cells were then treated with nerolidol for another additional 30 min, and DCF fluorescence was detected using flow cytometry. H2O2 was used as the positive control. The data were analyzed using the FlowJo software. (B, C) ELT3 cells were harvested and treated with nerolidol for 30 min. The cells were then stained with JC-1 dye for 15 min, followed by flow cytometry analysis. FCCP was used as the positive control. The data were analyzed using the FlowJo software. (B) The gated cells in the graphs indicate the cells with low mitochondrial membrane potential, and the quantitative results are plotted in (C). (D) ELT3 cells were treated with the indicated concentration of nerolidol for 48 h with or without co-treatment with 5 mM NAC. Cell proliferation was determined using the MTT assay. Ethanol (1 %) was used as the vehicle control. The data are presented as relative percentage compared to that of the vehicle control. (E) ELT3 cells were treated with the indicated concentration of nerolidol for 48 h with or without co-treatment with 20 μM ferrostatin-1. Cell proliferation was determined using the MTT assay. Ethanol (1 %) was used as the vehicle control. The data are presented as relative percentage compared to that of the vehicle control. The p-values were calculated using one-way ANOVA with Tukey's multiple post hoc test for each group. *, p <0.05; ***, p <0.001 compared to the vehicle control group (C). ***, p <0.001 compared to the nerolidol single treatment group (D, E).
Fig. 4 in Nerolidol inhibits proliferation of leiomyoma cells via reactive oxygen species-induced DNA damage and downregulation of the ATM/ Akt pathway
Fig. 4. Treatment with nerolidol triggered DNA damage in rat leiomyoma cells. (A, B) ELT3 cells were harvested and treated with 100 μM nerolidol for 30 min, followed by determination of DNA damage using the comet assay. H2O2 (200 μM) was used as the positive control. The tail moments are indicated by red arrows in (A), as quantified using a live video imaging system, and dot plots show the mean ± SD in (B). (C, D, E) ELT3 cells were treated with 100 μM nerolidol for 1 h, followed by incubation with anti-p-γH2AXser139 antibody and FITC-conjugated secondary antibody. Nuclei were visualized using DAPI (blue). (C) P-γH2AXser139 expression was quantified using an automated imaging system. The relative positive cell number and the nuclear p-γH2AXser139 intensities are plotted in (D) and (E), respectively. The p-value was calculated using one-way ANOVA with Tukey's multiple post hoc test for each group. *, p <0.05; **, p <0.01, and ***, p <0.001 compared to the vehicle control group (1 % EtOH). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 2. Nerolidol induced G1 in Nerolidol inhibits proliferation of leiomyoma cells via reactive oxygen species-induced DNA damage and downregulation of the ATM/ Akt pathway
Fig. 2. Nerolidol induced G1 cell cycle arrest by downregulating Akt phosphorylation and cell cycle-related proteins. ELT3 cells were treated with the indicated concentrations of nerolidol for 48 h and were then harvested after trypsin/EDTA treatment. (A, B) For cell cycle analysis, the harvested cells were fixed with 70 % ethanol, followed by propidium iodide staining, and the DNA content was measured using flow cytometry. The results were analyzed using the FlowJo software (A). Blue, olive green, and green represent the G1, S, and G2/M phases, respectively. The percentage of each cell cycle phase was plotted in (B). The p-value was calculated using one-way ANOVA with Tukey's multiple post hoc test for each group.*, p <0.05; **, p <0.01, and ***, p <0.001 compared to the vehicle control group (1 % EtOH). (C) Total cellular protein content was measured, and the expression levels of phosphorylated Akt, total Akt, cyclin D1, CDK4, and CDK6 were determined using western blot analysis. β-Actin was used as the loading control. The inserted numbers in (C) indicate the relative expression level compared to that of the vehicle control (indicated as 0 μM). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 1 in Nerolidol inhibits proliferation of leiomyoma cells via reactive oxygen species-induced DNA damage and downregulation of the ATM/ Akt pathway
Fig. 1. Nerolidol inhibited the proliferation of rat leiomyoma cells. ELT3 cells were seeded in 24-well plates and treated with the indicated concentrations of nerolidol for 48 h. (A) Images were captured under an inverted microscope at 100 × magnification. (B) The cells were trypsinized, and the number of viable (upper panel) or dead (lower panel) cells was counted after staining with trypan blue with a hemocytometer. (C) Cell proliferation was also determined using the MTT assay. Ethanol (1 %) was used as the vehicle control, which is indicated as 0 μM. The data are presented as relative percentage compared to the vehicle control. The p-value was calculated using one way ANOVA with Tukey's multiple post hoc test for each group. *, p <0.05 and ***, p <0.001 compared to the vehicle control group. The IC50 values were calculated using the IC50 Calculator (https://www.aatbio.com/tools/ic50-calculator).
Data Sets for: Are High-Temperature Molten Salts Reactive With Excess Electrons? The Case of ZnCl2
<p>Data Sets for: Are High-Temperature Molten Salts Reactive With Excess Electrons? The Case of ZnCl2 <a href="https://doi.org/10.1021/acs.jpcb.3c04210">https://doi.org/10.1021/acs.jpcb.3c04210 </a></p><p> </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.