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642 results for “Oxytocin”
Dataset of Social buffering switches fear to safety encoding by oxytocin recruitment of central amygdala buffer neurons
<p>Dataset of <span>Hegoburu et al., Social buffering switches fear to safety encoding by oxytocin recruitment of central amygdala buffer neurons, Nature Communications.</span></p> <p><span>ABSTRACT</span></p> <p><span>The presence of a companion can reduce fear, but the precise neural mechanisms underlying this social buffering of fear (SBF) are incompletely known. We studied SBF in male and female rats, and its encoding in the amygdala of males, that were fear-conditioned (FC) to auditory conditioned stimuli (CS). Pharmacological, opto,- and/or chemogenetic interventions showed that oxytocin (OT) signaling from hypothalamus-to-central amygdala (CeA) projections was required for acute fear reduction in the presence, and SBF retention 24h later without the companion. Single-unit recordings with optetrodes revealed fear-encoding CeA neurons (characterized by increased CS-responses after FC) were inhibited by SBF and blue light (BL) stimulation of OTergic projections. Other CeA neurons increased CS responses only after SBF exposure. Their baseline activity was enhanced by BL and exposure to the companion. SBF thus switches the CS from encoding "fear" to "safety" by OT-mediated recruitment of a distinct group of CeA "buffer neurons".</span></p> <p> </p>
Citation network data sets for 'Oxytocin – a social peptide? Deconstructing the evidence'
<p><strong>Introduction</strong></p> <p>This note describes the data sets used for all analyses contained in the manuscript 'Oxytocin - a social peptide?’<a href="#_ftn1">[1]</a> </p> <p><strong>Data Collection</strong></p> <p>The datasets described here were originally retrieved from Web of Science (WoS) Core Collection via the University of Edinburgh’s library subscription <a href="#_ftn2">[2]</a>. The aim of the original study for which these data were gathered was to survey peer-reviewed primary studies on oxytocin and social behaviour. To capture relevant papers, we used the following query:</p> <p><em>TI = (“oxytocin” OR “pitocin” OR “syntocinon”) AND TS = (“social*” OR “pro$social” OR “anti$social”)</em></p> <p>The final search was performed on the 13 September 2021. This returned a total of 2,747 records, of which 2,049 were classified by WoS as ‘articles’. Given our interest in primary studies <em>only</em> – articles reporting original data – we excluded all other document types. We further excluded all articles sub-classified as ‘book chapters’ or as ‘proceeding papers’ in order to limit our analysis to primary studies published in peer-reviewed academic journals. This reduced the set to 1,977 articles. All of these were published in the English language, and no further language refinements were unnecessary.</p> <p>All available metadata on these 1,977 articles was exported as plain text ‘flat’ format files in four batches, which we later merged together via Notepad++. Upon manually examination, we discovered examples of papers classified as ‘articles’ by WoS that were, in fact, reviews. To further filter our results, we searched all available PMIDs in PubMed (1,903 had associated PMIDs - ~96% of set). We then filtered results to identify all records classified as ‘review’, ‘systematic review’, or ‘meta-analysis’, identifying 75 records <a href="#_ftn3">[3]</a> (thus, ~4% of records classified by WoS were classified as reviews in PubMed). After examining a sample and agreeing with the PubMed classification, these were removed these from our dataset - leaving a total of 1,902 articles.</p> <p>From these data, we constructed two datasets via parsing out relevant reference data via the Sci2 Tool <a href="#_ftn4">[4]</a>. First, we constructed a ‘node-attribute-list’ by first linking unique reference strings (‘Cite Me As’ column in WoS data files) to unique identifiers, we then parsed into this dataset information on the identify of a paper, including the title of the article, all authors, journal publication, year of publication, total citations as recorded from WoS, and WoS accession number. Second, we constructed an ‘edge-list’ that records the citations from a <em>citing paper</em> in the ‘Source’ column and identifies the <em>cited paper</em> in the ‘Target’ column, using the unique identifies as described previously to link these data to the node-attribute-list.</p> <p>We then constructed a network in which papers are nodes, and citation links between nodes are directed edges between nodes. We used Gephi Version 0.9.2 <a href="#_ftn5">[5]</a> to manually clean these data by merging duplicate references that are caused by different reference formats or by referencing errors. To do this, we needed to retain both all retrieved records (1,902) as well as including <em>all</em> of their references to papers whether these were included in our original search or not. In total, this produced a network of 46,633 nodes (unique reference strings) and 112,520 edges (citation links). Thus, the average reference list size of these articles is ~59 references. The mean indegree (within network citations) is 2.4 (median is 1) for the entire network reflecting a great diversity in referencing choices among our 1,902 articles.</p> <p>After merging duplicates, we then restricted the network to include <em>only</em> articles fully retrieved (1,902), and retrained <em>only</em> those that were connected together by citations links in a large interconnected network (i.e. the largest component). In total, 1,892 (99.5%) of our initial set were connected together via citation links, meaning a total of ten papers were removed from the following analysis – and these were neither connected to the largest component, nor did they form connections with one another (i.e. these were ‘isolates’).</p> <p>This left us with a network of 1,892 nodes connected together by 26,019 edges. <strong><em>It is this network that is described by the ‘node-attribute-list’ and ‘edge-list’ provided here</em></strong>. This network has a mean in-degree of 13.76 (median in-degree of 4). By restricting our analysis in this way, we lose 44,741 unique references (96%) and 86,501 citations (77%) from the full network, but retain a set of articles tightly knitted together, all of which have been fully retrieved due to possessing certain terms related to oxytocin AND social behaviour in their title, abstract, or associated keywords.</p> <p>Before moving on, we calculated indegree for all nodes in this network – this counts the number of citations to a given paper from other papers within this network – and have included this in the <em>node-attribute-list</em>. We further clustered this network via modularity maximisation via the Leiden algorithm <a href="#_ftn6">[6]</a>. We set the algorithm to resolution 1, and allowed the algorithm to run over 100 iterations and 100 restarts. This gave <em>Q</em>=0.43 and identified seven clusters, which we describe in detail within the body of the paper. We have included cluster membership as an attribute in the node-attribute-list.</p> <p>For additional analysis, we also analysed the full reference list data to examine the most commonly cited references between 2016 and 2021 - the results of this are described in OTSOC_Cited_2016-2021.csv. This takes the reference lists of all retrieved papers within the network and examines their full reference lists (including references to other papers not contained within the network). These data were cleaned by matching DOIs and manual cleansing. </p> <p><strong>Data description</strong></p> <p>We include here two network datasets: (i) ‘OTSOC-node-attribute-list.csv’ consists of the attributes of 1,892 primary articles retrieved from WoS that include terms indicating a focus on oxytocin and social behaviour; (ii) ‘OTSOC-edge-list.csv’ records the citations between these papers. Together, these can be imported into a range of different software for network analysis; however, we have formatted these for ease of upload into Gephi 0.9.2. Finally, we include (iii) 'OTSOC_Cited_2016-2021' that lists all papers cited by >10 papers in the OTSOC network following any analysis of the bibliographies of retrieved papers. Below, we detail their contents:</p> <p><strong>1. ‘OTSOC-node-attribute-list.csv’</strong> is a comma-separate values file that contains all node attributes for the citation network (n=1,892) analysed in the paper. The columns refer to:</p> <p><em>Id</em>, the unique identifier</p> <p><em>Label</em>, the reference string of the paper to which the attributes in this row correspond. This is taken from the ‘Cite Me As’ column from the original WoS download. The reference string is in the following format: last name of first author, publication year, journal, volume, start page, and DOI (if available). </p> <p><em>Wos_id</em>, unique Web of Science (WoS) accession number. These can be used to query WoS to find further data on all papers via the ‘UT= ’ field tag.</p> <p><em>Title</em>, paper title.</p> <p><em>Authors</em>, all named authors.</p> <p><em>Journal, </em>journal of publication.</p> <p><em>Pub_year</em>, year of publication.</p> <p><em>Wos_citations</em>, total number of citations recorded by WoS Core Collection to a given paper as of 13 September 2021</p> <p><em>Indegree</em>, the number of within network citations to a given paper, calculated for the network shown in Figure 1 of the manuscript.</p> <p><em>Cluster</em>, provides the cluster membership number as discussed within the manuscript (Figure 1). This was established via modularity maximisation via the Leiden algorithm (Res 1; Q=0.43|7 clusters)</p> <p><strong>2. ‘OTSOC-edge -list.csv’</strong> is a comma-separated values file that contains all citation links between the 1,892 articles (n=26,019). The columns refer to:</p> <p><em>Source</em>, the unique identifier of the citing paper.</p> <p><em>Target, </em>the unique identifier of the cited paper.</p> <p><em>Type, </em>edges are ‘Directed’, and this column tells Gephi to regard all edges as such.</p> <p><em>Syr_date, </em>this contains the date of publication of the citing paper.</p> <p><em>Tyr_date, </em>this contains the date of publication of the cited paper.</p> <p><strong>3. 'OTSOC_Cited_2016-2021.csv'</strong> is a comma-separated values file that contain citations to all cited references that were cited by at least 10 of the retrieved papers within the OTSOC network published from 2016 onwards. The columns refer to: </p> <p><em>Reference, </em>the cited reference string extracted from the bibliographies of retrieved papers.</p> <p><em>Publication year, </em>the publication year of the cited reference.</p> <p><em>DOI</em>, the DOI of the cited reference. </p> <p><em>indegree_2016, </em>the total number of citations to a cited reference from papers published in 2016 and contained within the OTSOC network. </p> <p><em>indegree_2017, </em>the total number of citations to a cited reference from papers published in 2017 and contained within the OTSOC network. </p> <p><em>indegree_2018, </em>the total number of citations to a cited reference from papers published in 2018 and contained within the OTSOC network. </p> <p><em>indegree_2019, </em>the total number of citations to a cited reference from papers published in 2019 and contained within the OTSOC network. </p> <p><em>indegree_2020, </em>the total number of citations to a cited reference from papers published in 2020 and contained within the OTSOC network. </p> <p><em>indegree_2021, </em>the total number of citations to a cited reference from papers published in 2021 and contained within the OTSOC network. </p> <p><em>total indegree 2016-21</em>, the total number of citation to a cited reference from papers published between 2016-2021 and contained within the OTSOC network. </p> <p><strong>Software recommended for analysis</strong></p> <p>Gephi version 0.9.2 was used for the visualisations within the manuscript, and both files can be read and into Gephi without modification.</p> <p><strong>Notes</strong></p> <p><a href="#_ftnref1">[1]</a> Leng, G., Leng, R. I., Ludwig, M. (Submitted). Oxytocin – a social peptide? Deconstructing the evidence.</p> <p><a href="#_ftnref2">[2]</a> Edinburgh University’s subscription to Web of Science covers the following databases: (i) Science Citation Index Expanded, 1900-present; (ii) Social Sciences Citation Index, 1900-present; (iii) Arts & Humanities Citation Index, 1975-present; (iv) Conference Proceedings Citation Index- Science, 1990-present; (v) Conference Proceedings Citation Index- Social Science & Humanities, 1990-present; (vi) Book Citation Index– Science, 2005-present; (vii) Book Citation Index– Social Sciences & Humanities, 2005-present; (viii) Emerging Sources Citation Index, 2015-present.</p> <p><a href="#_ftnref3">[3]</a> For those interested, the following PMIDs were identified as ‘articles’ by WoS, but as ‘reviews’ by PubMed: ‘34502097’ ‘33400920’ ‘32060678’ ‘31925983’ ‘31734142’ ‘30496762’ ‘30253045’ ‘29660735’ ‘29518698’ ‘29065361’ ‘29048602’ ‘28867943’ ‘28586471’ ‘28301323’ ‘27974283’ ‘27626613’ ‘27603523’ ‘27603327’ ‘27513442’ ‘27273834’ ‘27071789’ ‘26940141’ ‘26932552’ ‘26895254’ ‘26869847’ ‘26788924’ ‘26581735’ ‘26548910’ ‘26317636’ ‘26121678’ ‘26094200’ ‘25997760’ ‘25631363’ ‘25526824’ ‘25446893’ ‘25153535’ ‘25092245’ ‘25086828’ ‘24946432’ ‘24637261’ ‘24588761’ ‘24508579’ ‘24486356’ ‘24462936’ ‘24239932’ ‘24239931’ ‘24231551’ ‘24216134’ ‘23955310’ ‘23856187’ ‘23686025’ ‘23589638’ ‘23575742’ ‘23469841’ ‘23055480’ ‘22981649’ ‘22406388’ ‘22373652’ ‘22141469’ ‘21960250’ ‘21881219’ ‘21802859’ ‘21714746’ ‘21618004’ ‘21150165’ ‘20435805’ ‘20173685’ ‘19840865’ ‘19546570’ ‘19309413’ ‘15288368’ ‘12359512’ ‘9401603’ ‘9213136’ ‘7630585’</p> <p><a href="#_ftnref4">[4]</a> Sci2 Team. (2009). Science of Science (Sci2) Tool. Indiana University and SciTech Strategies. Stable URL: <a href="https://sci2.cns.iu.edu">https://sci2.cns.iu.edu</a></p> <p><a href="#_ftnref5">[5]</a> Bastian, M., Heymann, S., & Jacomy, M. (2009). Gephi: an open source software for exploring and manipulating networks. International AAAI Conference on Weblogs and Social Media. Gephi is available via <a href="https://gephi.org/">https://gephi.org/</a></p> <p><a href="#_ftnref6">[6]</a> Traag, V. A., Waltman, L., & van Eck, N. J. (2019). From Louvain to Leiden: guaranteeing well-connected communities. Scientific reports, 9(1), 5233. <a href="https://doi.org/10.1038/s41598-019-41695-z">https://doi.org/10.1038/s41598-019-41695-z</a></p>
An analgesic pathway from parvocellular oxytocin neurons to the periaqueductal gray in rats
<p>Raw data set related to the publication "An analgesic pathway from parvocellular oxytocin neurons to the periaqueductal gray in rats". It includes ex vivo electrophysiology, ex vivo GRAB recordings, and neuroanatomy data.</p>
Data for: Human endogenous oxytocin and its neural correlates
<p><span>Both oxytocin (OT) and touch are key mediators of social attachment. In rodents, tactile stimulation elicits endogenous release of OT, potentially facilitating attachment and other forms of prosocial behavior, yet the relationship between endogenous OT and neural modulation remains unexplored in humans. Using serial sampling of plasma hormone levels during functional neuroimaging across two successive social interactions, we show that contextual circumstances of social touch influence not only current hormonal and brain responses but also <em>later</em> responses. Namely, touch from a male to his female romantic partner enhanced her subsequent OT release for touch from an unfamiliar stranger, yet females' OT responses to partner touch were dampened following stranger touch. Hypothalamus and dorsal raphe activation reflected plasma OT changes during the initial social interaction. In the subsequent interaction, precuneus and parietal-temporal cortex pathways tracked time- and context-dependent variables in an OT-dependent manner. This OT-dependent cortical modulation included a region of medial prefrontal cortex that also covaried with plasma cortisol, suggesting an influence on stress responses. These findings demonstrate that modulation between hormones and the brain during human social interactions can flexibly adapt to features of social context over time.</span></p>
Data for: An AAV-CRISPR/Cas9-strategy for gene editing across divergent rodent species: Targeting neural oxytocin receptors as a proof of concept
<p>A major issue in neuroscience is the poor translatability of research results from preclinical studies in animals to clinical outcomes. Comparative neuroscience can overcome this barrier by studying multiple species to differentiate between species-specific and general mechanisms of neural circuit functioning. Targeted manipulation of neural circuits often depends on genetic dissection, and use of this technique has been restricted to only a few model species, limiting its application in comparative research. However, ongoing advances in genomics make genetic dissection attainable in a growing number of species. To demonstrate the potential of comparative gene editing approaches, we developed a viral-mediated CRISPR/Cas9 strategy that is predicted to target the oxytocin receptor (<em>Oxtr</em>) gene in >80 rodent species. This strategy specifically reduced OXTR levels in all evaluated species (n=6), without causing gross neuronal toxicity. Thus, we show that CRISPR/Cas9-based tools can function in multiple species simultaneously. Thereby, we hope to encourage comparative gene editing and improve the translatability of neuroscientific research.</p>
Inhaled Oxytocin and HPA Axis Reactivity
ClinicalTrials.gov study NCT03593473. IPD Sharing: YES. Countries: 1. Publications: 1.
Data for: An AAV-CRISPR/Cas9-strategy for gene editing across divergent rodent species: Targeting neural oxytocin receptors as a proof of concept
Open the record for dataset details and reuse information.
Data from: Oxytocin and dopamine receptor expression: Cellular level implications for pair bonding
Open the record for dataset details and reuse information.
Data for: Human endogenous oxytocin and its neural correlates
Open the record for dataset details and reuse information.
The oxytocin-prostaglandins pathways in the horse (Equus caballus) placenta during pregnancy, physiological parturition, and parturition with fetal membrane retention
<p>Despite their importance in mammalian reproduction, substances in the oxytocin-prostaglandins pathways have not been investigated in the horse placenta during most of pregnancy and parturition. Therefore, we quantified placental content of oxytocin (OXT), oxytocin receptor (OXTR), and prostaglandin E2 and F2 alpha during days 90–240 of pregnancy (PREG), physiological parturition (PHYS), and parturition with fetal membrane retention (FMR) in heavy draft horses (PREG = 13, PHYS = 11, FMR = 10). We also quantified <i>OXTR</i> and<i> </i>prostaglandin endoperoxide synthase-2 (<i>PTGS2</i>) mRNA expression and determined the immunolocalization of OXT, OXTR, and PTGS2. For relative quantification of OXT and OXTR, we used western blotting with densitometry. To quantify the prostaglandins, we used enzyme immunoassays. For relative quantification of <i>OXTR</i> and <i>PTGS2</i>, we used RT-qPCR. For immunolocalization of OXT, OXTR, and PTGS2, we used immunohistochemistry. We found that OXT was present in cells of the allantochorion and endometrium in all groups. <i>PTGS2</i> expression in the allantochorion was 14.7-fold lower in FMR than in PHYS (<i>p</i> = 0.007). These results suggest that OXT is synthesized in the horse placenta. As PTGS2 synthesis is induced by inflammation, they also suggest that FMR in heavy draft horses may be associated with dysregulation of inflammatory processes.</p>
Human Placental Lactogen (Human Chorionic Somataomammotropin) and Oxytocin during Pregnancy: Individual Patterns and Association with Maternal-Fetal Attachment, Anxiety, and Depression
<p>Dataset from Human Placental Lactogen (Human Chorionic Somataomammotropin) and Oxytocin during Pregnancy: Individual Patterns and Association with Maternal-Fetal Attachment, Anxiety, and Depression</p>
Intranasal Oxytocin for the Treatment of Autism Spectrum Disorders
ClinicalTrials.gov study NCT01337687. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Association Between Fluid Administration, Oxytocin Administration, and Fetal Heart Rate Changes
ClinicalTrials.gov study NCT02121184. IPD Sharing: NO. Countries: 1. Publications: 12.
Comparison of Low-dose and High-dose Oxytocin Regimens for Labor Augmentation
ClinicalTrials.gov study NCT02487797. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Preventing Postpartum Depression With Intranasal Oxytocin
ClinicalTrials.gov study NCT02505984. IPD Sharing: NO. Countries: 1. Publications: 7.
Brain Dynamics of Oxytocin
ClinicalTrials.gov study NCT01834261. IPD Sharing: Not stated. Countries: 1. Publications: 25.
Comparison of Inhaled Oxytocin (IH) With Intramuscular (IM) Oxytocin in Pregnant Women and With Intravenous (IV) Oxytocin in Healthy Non-pregnant Women
ClinicalTrials.gov study NCT02999100. IPD Sharing: Not stated. Countries: 2. Publications: 2.
The Physiologic Effects of Intranasal Oxytocin on Sarcopenic Obesity
ClinicalTrials.gov study NCT03119610. IPD Sharing: NO. Countries: 1. Publications: 1.
The Effects of Oxytocin in Obese Adults
ClinicalTrials.gov study NCT03043053. IPD Sharing: NO. Countries: 1. Publications: 1.
Oxytocin Regimen to Prevent Atony and Postpartum Hemorrhage During Vaginal Delivery: 3-arm RCT
ClinicalTrials.gov study NCT00790062. IPD Sharing: Not stated. Countries: 1. Publications: 1.
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