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.
80
datasets available to search
ShareScore release 0.7.1
Dataset results
80 results for “acetylcholine”
Simulations of focal and reentrant sources with Acetylcholine regulation in atrial fibrillation
<p><strong>Simulations of focal and reentrant sources with Acetylcholine regulation in atrial fibrillation</strong></p> <p>This contains focal and reentrant sources with Acetylcholine regulation in atrial fibrillation simulations used in the manuscript <strong>Detection of focal source and arrhythmogenic substrate from body surface potentials to guide atrial fibrillation ablation (</strong><a href="https://doi.org/10.1371/journal.pcbi.1009893">https://doi.org/10.1371/journal.pcbi.1009893</a><strong>)</strong>. <strong>Please cite our manuscript if you use our code</strong>.</p> <p>Detailed simulation files for focal and reentrant sources with Acetylcholine regulation in <a href="https://carpentry.medunigraz.at">CARPentry</a>. Tested with CARP GIT commit hash: 2e280733.<br> The formats of .elem, .lon, .pts, .dat and .igb used or produced by carp can be found in <a href="https://carpentry.medunigraz.at/getting-started/file-formats.html">the CARPentry website</a>.</p> <p><strong>Data (<code>data/</code>)</strong></p> <ul> <li><code>Mesh1(.elem, .lon, .pts)</code>: files (elements, fibres, nodes) of a mesh Mesh1 with basic tagging of atrial structures.</li> <li><code>Mesh1_FS_L22.vtx</code>: vertices of a focal site at (αLA=0.2,βLA=0.2\alpha_{LA} = 0.2, \beta_{LA} = 0.2αLA=0.2,βLA=0.2).</li> <li><code>Mesh1_L22_r0(.elem, .lon, .pts)</code>: files (elements, fibres, nodes) of a mesh Mesh1 with basic tagging of atrial structures and tagging of regions (Section 1 - 48) for reentrant sources.</li> <li><code>Mesh1_UAC*.dat</code>: plain text files where each row specifies a Universal Atrial Coordinate ( <code>Mesh1_UAC1.dat</code>: alpha, <code>Mesh1_UAC2.dat</code> : beta, <code>Mesh1_UAC3.dat</code> : LA or RA) of Mesh1 in Roney et al. 2019, which could be used to select vertices and tag elements. We annotated elements with tags of 1-4 and 11-28 for the Universal Atrial Coordinate.</li> <li><code>vest.pts</code>: a <code>.pts</code> file specifying the locations of 252 vest leads.</li> <li><code>Mesh1_ACh_islands.adj</code>: adjustment file specifying the node indices (first column) and concentration of the ACh (second column) for ACh islands.</li> </ul> <p><strong>Par files: parameter files for CARPentry software.</strong></p> <ul> <li><code>Focal_source.par</code>: to simulate a focal source with a CL of 180 ms on the left atrial focal site lasting for 3000 ms.</li> <li><code>Focal_source_ACh.par</code>: to simulate a focal source with a CL of 180 ms lasting for 3000 ms with ACh.</li> <li><code>Reentrant_source.par</code>: to simulate a reentrant source around a left atrial core of (αLA=0.2,βLA=0.2\alpha_{LA} = 0.2, \beta_{LA} = 0.2αLA=0.2,βLA=0.2). To run this file in CARP, the user is advised to compute the initial state files of each segment (<code>init/*.sv</code>) using <code>Reentrant_source_get_init_states.py</code>. This serves as initial states for regions with tags 100 - 147 for the left atral sections of a phase distribution method (Section 100 - 147 refers to the Section 1 - 48 in the main article Fig S1) in <code>Mesh1_L22_r0.elem</code>.</li> </ul> <p><strong>Ionic model</strong></p> <ul> <li><code>CRN_ACH.model</code>: an ionic model file with Acetylcholine introduction of Bayer et al. (2019), with Acetylcholine concentration 0 by default.</li> </ul> <p><strong>Initial conditions for reentrant sources</strong></p> <ul> <li><code>Reentrant_source_get_init_states.py</code>: Python script that output Linux commands to call <code>bench</code> software in CARPentry to initiate the reentrant sources. The produced initial state files <code>init/*.sv</code> are to be used by <code>Reentrant_source.par</code>.</li> </ul> <p><strong>Tags for the atrial structures in the element file (specified in <code>.elem</code>)</strong></p> <ul> <li>1 - Right atrial body</li> <li>2 - Right atrial appendage</li> <li>3 - Sinoatrial node</li> <li>4 - Line of block</li> <li>5 - Coronary sinus</li> <li>6 - Superior vena cava</li> <li>7 - Inferior vena cava</li> <li>8 - Crist terminalis</li> <li>9 - Pectinate muscle</li> <li>10 - Bachman Bundle</li> <li>11- Left atrial body endocardial layer</li> <li>12 - Left atrial body epicardial layer</li> <li>13 - Left atrial appendage endocardial layer</li> <li>14 - Left atrial appendage epicardial layer</li> <li>21, 23, 25 & 27 - endocardial layer of four left atrial PVs</li> <li>22, 24, 26 & 28 - epicardial layer of four left atrial PVs</li> </ul> <p><strong>References</strong></p> <ul> <li>Feng Y, Roney CH, Bayer JD, Niederer SA, Hocini M, Vigmond EJ (2022) Detection of focal source and arrhythmogenic substrate from body surface potentials to guide atrial fibrillation ablation. PLoS Comput Biol 18(3): e1009893.<strong> </strong><a href="https://doi.org/10.1371/journal.pcbi.1009893">https://doi.org/10.1371/journal.pcbi.1009893</a></li> <li>Roney CH, Pashaei A, Meo M, Dubois R, Boyle PM, Trayanova NA, et al. Universal atrial coordinates applied to visualisation, registration and construction of patient specific meshes. Medical Image Analysis. 2019 Jul 1;55:65–75. <a href="https://10.1016/j.media.2019.04.004">https://10.1016/j.media.2019.04.004</a></li> <li>Bayer, et al. (2019). Acetylcholine Delays Atrial Activation to Facilitate Atrial Fibrillation. Frontiers in Physiology, 10, 1105. <a href="https://doi.org/10.3389/fphys.2019.01105">https://doi.org/10.3389/fphys.2019.01105</a></li> </ul>
Acetylcholine receptor based chemogenetics engineered for neuronal inhibition and seizure control assessed in mice
<p>Analysis scripts and underlying data used to produce the figures in our study entitled "Acetylcholine receptor based chemogenetics engineered for neuronal inhibition and seizure control assessed in mice", in Nature Communications. The listed project leaders can be contacted with any questions.</p>
Raw data for: "Vesicular Acetylcholine Transporter Alters Cholinergic Tone and Synaptic Plasticity in DYT1 Dystonia"
<p>Raw data for Supplemental Figure 2 - Patch-Clamp recordings of ChI firing activity after bath application of donepezil (Donep 50 μM, 5 minutes). The inhibition by donepezil was weaker in Tor1a+/− than in Tor1a+/+ neurons.</p>
Acetylcholine is released in the basolateral amygdala in response to predictors of reward and enhances learning of cue-reward contingency
<p>The basolateral amygdala (BLA) is critical for associating initially neutral cues with appetitive and aversive stimuli and receives dense neuromodulatory acetylcholine (ACh) projections. We measured BLA ACh signaling and activity of neurons expressing CaMKIIα (a marker for glutamatergic principal cells) in mice during cue-reward learning using a fluorescent ACh sensor and calcium indicators. We found that ACh levels and nucleus basalis of Meynert (NBM) cholinergic terminal activity in the BLA (NBM-BLA) increased sharply in response to reward-related events and shifted as mice learned the cue-reward contingency. BLA CaMKIIα<sup> </sup>neuron activity followed reward retrieval and moved to the reward-predictive cue after task acquisition. Optical stimulation of cholinergic NBM-BLA terminal fibers led to quicker acquisition of the cue-reward contingency. These results indicate BLA ACh signaling carries important information about salient events in cue-reward learning and provides a framework for understanding how ACh signaling contributes to shaping BLA responses to emotional stimuli.</p>
Assessment of endothelial cell function and physiological microcirculatory reserve by video microscopy using a topical acetylcholine and nitroglycerin challenge - Individual subject data
<p>This dataset contains individual subject data for microcirculatory parameters assessed in the present study. Macrocirculatory parameters are not included at this time due to the present study being part of a larger, partially unpublished project.</p>
Data from: Acetylcholine waves and dopamine release in the striatum
<p>Striatal dopamine encodes reward, with recent work showing that dopamine release occurs in spatiotemporal waves. However, the mechanism of dopamine waves is unknown. Here we report that acetylcholine release in mouse striatum also exhibits wave activity, and that the spatial scale of striatal dopamine release is extended by nicotinic acetylcholine receptors. Based on these findings, and on our demonstration that single cholinergic interneurons can induce dopamine release, we hypothesized that the local reciprocal interaction between cholinergic interneurons and dopamine axons suffices to drive endogenous traveling waves. We show that the morphological and physiological properties of cholinergic interneuron – dopamine axon interactions can be modeled as a reaction-diffusion system that gives rise to traveling waves. Analytically-tractable versions of the model show that the structure and the nature of propagation of acetylcholine and dopamine traveling waves depend on their coupling, and that traveling waves can give rise to empirically observed correlations between these signals. Thus, our study provides evidence for striatal acetylcholine waves <em>in vivo</em>, and proposes a testable theoretical framework that predicts that the observed dopamine and acetylcholine waves are strongly coupled phenomena.</p>
Raw diffraction images of human muscarinic acetylcholine receptor
<p>Raw data for <a href="https://www.rcsb.org/structure/5ZK8">5ZK8</a> (M<sub>2</sub>-BRIL–NMS), <a href="https://www.rcsb.org/structure/5ZKC">5ZKC</a> (S110R-BRIL–NMS), <a href="https://www.rcsb.org/structure/5ZKB">5ZKB</a>(S110R-BRIL–AF-DX 384), and <a href="https://www.rcsb.org/structure/5ZK3">5ZK3</a> (S110R-BRIL–QNB). </p>
Data from: Positive allosteric modulation of the α7 nicotinic acetylcholine receptor as a treatment for cognitive deficits after traumatic brain injury
<p><span>Cognitive impairments are a common consequence of traumatic brain injury (TBI). The hippocampus is a subcortical structure that plays a key role in the formation of declarative memories and is highly vulnerable to TBI. The α7 nicotinic acetylcholine receptor (nAChR) is highly expressed in the hippocampus and reduced expression and function of this receptor are linked with cognitive impairments in Alzheimer's disease and schizophrenia. Positive allosteric modulation of α7 nAChRs with AVL-3288 enhances receptor currents and improves cognitive functioning in naïve animals and healthy human subjects. Therefore, we hypothesized that targeting the α7 nAChR with the positive allosteric modulator AVL-3288 would enhance cognitive functioning in the chronic recovery period of TBI. To test this hypothesis, adult male Sprague Dawley rats received moderate parasagittal fluid-percussion brain injury or sham surgery. At 3 months after recovery, animals were treated with vehicle or AVL-3288 at 30 min prior to cue and contextual fear conditioning and the water maze task. Treatment of TBI animals with AVL-3288 rescued learning and memory deficits in water maze retention and working memory. AVL-3288 treatment also improved cue and contextual fear memory when tested at 24 hr and 1 month after training, when TBI animals were treated acutely just during fear conditioning at 3 months post-TBI. Hippocampal atrophy but not cortical atrophy was reduced with AVL-3288 treatment in the chronic recovery phase of TBI. AVL-3288 application to acute hippocampal slices from animals at 3 months after TBI rescued basal synaptic transmission deficits and long-term potentiation (LTP) in area CA1. Our results demonstrate that AVL-3288 improves hippocampal synaptic plasticity, and learning and memory performance after TBI in the chronic recovery period. Enhancing cholinergic transmission through positive allosteric modulation of the α7 nAChR may be a novel therapeutic to improve cognition after TBI.</span></p>
Acetylcholine is released in the basolateral amygdala in response to predictors of reward and enhances learning of cue-reward contingency
Open the record for dataset details and reuse information.
Data from: Positive allosteric modulation of the α7 nicotinic acetylcholine receptor as a treatment for cognitive deficits after traumatic brain injury
Open the record for dataset details and reuse information.
Data from: Acetylcholine waves and dopamine release in the striatum
Open the record for dataset details and reuse information.
Raw diffraction images of mercury-bound human muscarinic acetylcholine receptor
<p>Raw data for <a href="https://www.rcsb.org/structure/5YC8">5YC8</a> (S110R-BRIL–NMS:Hg).</p>
Fig. 4 in An electrophysiological characterization of naturally occurring tobacco alkaloids and their action on human α4β2 and α7 nicotinic acetylcholine receptors
Fig. 4. Concentration–response curves were obtained by using the whole-cell mode of the patch-clamp technique at a holding potential of −70 mV from CHO cells stably expressing human α4β2 (continuous black lines) or human α7 (dotted grey lines) nAChRs. The lines represent the fits to the Hill equation for nicotine (1) (circles symbols), anabasine (12) (triangles symbols), nornicotine (7) (squared symbols), and S-anatabine (16) (diamonds symbols). The fit parameters are presented (Table 1). The averaged normalized current response is plotted as a function of the maximal current to ACh (ImaxACh). Two backgrounds highlight the concentration range of the tobacco alkaloids levels measured in human plasma (grey background with diagonal lines) and in human cerebrospinal fluid (grey background with horizontal lines). Data are presented as mean ± SD.
Fig. 3 in An electrophysiological characterization of naturally occurring tobacco alkaloids and their action on human α4β2 and α7 nicotinic acetylcholine receptors
Fig. 3. Sequential applications of brief ACh pulses are plotted as a function of time for three ACh concentrations. (a) EC20 = 0.4 μM (circles), EC50 = 1.2 μM (squares), EC90 = 11.1 μM (triangles) for human α4β2 receptors. (b) EC20 = 33.3 μM (circles), EC60 = 300 μM (squares), EC90 = 900 μM (triangles) for human α7 receptors. Experiments were performed by using the whole-cell mode of the patch-clamp technique at a holding potential of −70 mV in CHO cells stably expressing the human α4β2 and α7 nAChRs. EC, effective concentration. Data are presented as mean ± SD.
Fig. 2 in An electrophysiological characterization of naturally occurring tobacco alkaloids and their action on human α4β2 and α7 nicotinic acetylcholine receptors
Fig. 2. Representative traces of currents elicited by using the agonist mode (a and c) and PAM mode (b and d) in the whole-cell mode of the patch-clamp technique at a holding potential of −70 mV in CHO cells stably expressing human α4β2 (a and b) and human α7 (c and d) nAChRs. Agonist mode (a, c): 0.3% DMSO (left); 33.3 μM of the tobacco alkaloid anabasine (middle); 33.3 and 900 μM ACh for α4β2 and α7, respectively (right). PAM mode (b, d): 0.4 and 100 μM ACh for α4β2 and α7, respectively (left); co-application of 33.3 μM of the tobacco alkaloid trans-anatalline (middle); 0.4 or 100 μM ACh for α4β2 and α7, respectively (right). Thick dotted lines represent the pre-application period of the alkaloid (≥2 min). Thin dotted lines represent zero current.; PAM, positive allosteric modulator.
Fig. 1 in An electrophysiological characterization of naturally occurring tobacco alkaloids and their action on human α4β2 and α7 nicotinic acetylcholine receptors
Fig. 1. Representative traces of currents elicited in response to increasing concentrations of ACh. Currents were measured in agonist mode by using the whole-cell mode of the patch-clamp technique at a holding potential of −70 mV in CHO cells stably expressing human α4β2 (a) and human α7 (b) nAChRs. The half-maximal effective concentrations determined by using the Hill equation were 1.02 ± 1.0 μM (a) and 142 ± 16 μM (b) (n = 5–11 cells). Bars indicate (in μM): 0.1 (1), 0.4 (2), 1.2 (3), 3.7 (4), 11.1 (5), 33.3 (6), 100 (7), 300 (8), 900 (9), and 2700 (10). Dotted lines represent zero current.
Fig. 6 in Comparative transcriptome analysis reveals the regulatory effects of acetylcholine on salt tolerance of Nicotiana benthamiana
Fig. 6. Differentially expressed genes related to the plant hormone signal transduction pathway in the comparison (NaCl vs NaCl + ACh). (A) diagram of auxin, gibberellin, brassinosteroid and salicylic acid signalling transduction pathways; (B) information and expression patterns of differentially expressed genes involved in auxin, gibberellin, brassinosteroid and salicylic acid signalling transduction pathways. Red means upregulated expression of genes, and green means downregulated expression of genes. The number in each sample name represents the sample order. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 3 in Comparative transcriptome analysis reveals the regulatory effects of acetylcholine on salt tolerance of Nicotiana benthamiana
Fig. 3. Functional annotation of differentially expressed genes (DEGs) based on gene ontology categorization. The left Y-axis represents the significantly enriched GO terms (p <0.05) pathways. The Xaxis represents the percentage of DEGs belonging to the corresponding pathway. The sizes of bubbles represent the number of DEGs in the corresponding pathway, and the colours of the bubbles represent the enrichment p-value of the corresponding pathway. The left y-axis shows the Gene Ontology terms. Biological process, cellular component and molecular function are indicated by different colours. Only significantly enriched GO terms (p <0.05) are shown. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 8 in Comparative transcriptome analysis reveals the regulatory effects of acetylcholine on salt tolerance of Nicotiana benthamiana
Fig. 8. Quantitative real-time PCR (RT-qPCR) validation of selected differentially expressed genes detected in Nicotiana benthamiana leaves. The expression levels obtained by RT-qPCR are represented in black lines, RT-qPCR data showed the mean values from three replicates, and the error bars represent the SE of the means, while the corresponding expression data for RNA-seq are represented in the white histogram. CN, control; CN + ACh, 10 μM acetylcholine; NaCl, 150 mM NaCl stress; NaCl + ACh, 150 mM NaCl stress plus 10 μM acetylcholine.
Fig. 5 in Comparative transcriptome analysis reveals the regulatory effects of acetylcholine on salt tolerance of Nicotiana benthamiana
Fig. 5. Heatmap representing the differentially expressed genes (DEGs) involved in cell wall extensibility of Nicotiana benthamiana leaves as influenced by NaCl alone or in combination with acetylcholine treatment (NaCl + ACh). Red means upregulated expression of genes, and green means downregulated expression of genes. The number in each sample name represents the sample order. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
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.