Find research datasets worth reusing

opencc-byFeb 2020View details →

News article mentions of 4chan from three weeks in 2017 and posts with links to these articles on 4chan/pol/

This upload includes two dataset. The first comprises articles that mentioning "4chan" in its post body as retreived by Nexis Uni. We identified the three weeks in which the highest spikes in terms of the amount of articles occured in 2017 (see the image mentions_nexis_uni_2017_weeks.png ) and extracted the articles that were published within these. The dataset includes the article source, the article title, and the sentences where they mention 4chan to analyse the framing. We deleted the article bodies for copyright reasons. Two columns indicate the URL to the article if it appeared online. Additionally, we added a column with URLs to archive.is links of the same articles, in case they were archived. The second dataset consists of posts on the imageboard 4chan/pol/ that refer to one of the aforementioned URLs.

Dataset related to article "Poly(I:C) stimulation is superior than Imiquimod to induce the antitumoral functional profile of tumor-conditioned macrophages."

Macrophage plasticity is the ability of mononuclear phagocytes to change phenotype, function, and genetic reprogramming upon encounter of specific local stimuli. In the tumor microenvironment, Tumor-Associated Macrophages (TAMs) acquire an immune-suppressive and tumor-promoting phenotype. With the aim to re-educate TAMs to antitumor effectors, in this study, we used two immunestimulatory compounds: the TLR7 agonist Imiquimod (IMQ) and the TLR3 agonist Poly(I:C). To better mimic in vitro the response of TAMs, we used Tumor-Conditioned Macrophages (TC-Mϕ) differentiated in the presence of tumor cell supernatants. Our results show that TC-Mϕ respond differently from conventional M2-polarized macrophages. Upon stimulation with IMQ, TC-Mϕ did not upregulate major histocompatibility complex (MHC II) molecules and unexpectedly expressed increased CD206. With both compounds, TC-Mϕ produced higher levels of inflammatory cytokines than M2 macrophages. IMQ and Poly(I:C) differed in the types of regulated genes and secreted mediators. Reflecting their signaling pathways, only IMQ significantly induced IL-1β and IL-6, while only Poly(I:C) stimulated CXCL10, and both upregulated CCL5. Of note, using a novel cytotoxicity assay, Poly(I:C), but not IMQ, was effective in triggering the cytotoxic activity of TC-Mϕ against cancer cells. Overall, the results demonstrate that Poly(I:C) stimulation of TC-Mϕ is superior than IMQ in terms of macrophage re-education toward antitumor effectors.

Dataset related to article "Single-Cell Sequencing of Mouse Heart Immune Infiltrate in Pressure Overload-Driven Heart Failure Reveals Extent of Immune Activation."

BACKGROUND: Inflammation is a key component of cardiac disease, with macrophages and T lymphocytes mediating essential roles in the progression to heart failure. Nonetheless, little insight exists on other immune subsets involved in the cardiotoxic response. METHODS: Here, we used single-cell RNA sequencing to map the cardiac immune composition in the standard murine nonischemic, pressure-overload heart failure model. By focusing our analysis on CD45+ cells, we obtained a higher resolution identification of the immune cell subsets in the heart, at early and late stages of disease and in controls. We then integrated our findings using multiparameter flow cytometry, immunohistochemistry, and tissue clarification immunofluorescence in mouse and human. RESULTS: We found that most major immune cell subpopulations, including macrophages, B cells, T cells and regulatory T cells, dendritic cells, Natural Killer cells, neutrophils, and mast cells are present in both healthy and diseased hearts. Most cell subsets are found within the myocardium, whereas mast cells are found also in the epicardium. Upon induction of pressure overload, immune activation occurs across the entire range of immune cell types. Activation led to upregulation of key subset-specific molecules, such as oncostatin M in proinflammatory macrophages and PD-1 in regulatory T cells, that may help explain clinical findings such as the refractivity of patients with heart failure to anti-tumor necrosis factor therapy and cardiac toxicity during anti-PD-1 cancer immunotherapy, respectively. CONCLUSIONS: Despite the absence of infectious agents or an autoimmune trigger, induction of disease leads to immune activation that involves far more cell types than previously thought, including neutrophils, B cells, Natural Killer cells, and mast cells. This opens up the field of cardioimmunology to further investigation by using toolkits that have already been developed to study the aforementioned immune subsets. The subset-specific molecules that mediate their activation may thus become useful targets for the diagnostics or therapy of heart failure.   This dataset is created in .ets form, we attach a pdf with the information about.

Dataset related to article "Intracerebral Injection of Extracellular Vesicles from Mesenchymal Stem Cells Exerts Reduced Aβ Plaque Burden in Early Stages of a Preclinical Model of Alzheimer's Disease."

Bone marrow Mesenchymal Stem Cells (BM-MSCs), due to their strong protective and anti-inflammatory abilities, have been widely investigated in the context of several diseases for their possible therapeutic role, based on the release of a highly proactive secretome composed of soluble factors and Extracellular Vesicles (EVs). BM-MSC-EVs, in particular, convey many of the beneficial features of parental cells, including direct and indirect β-amyloid degrading-activities, immunoregulatory and neurotrophic abilities. Therefore, EVs represent an extremely attractive tool for therapeutic purposes in neurodegenerative diseases, including Alzheimer's disease (AD). We examined the therapeutic potential of BM-MSC-EVs injected intracerebrally into the neocortex of APPswe/PS1dE9 AD mice at 3 and 5 months of age, a time window in which the cognitive behavioral phenotype is not yet detectable or has just started to appear. We demonstrate that BM-MSC-EVs are effective at reducing the Aβ plaque burden and the amount of dystrophic neurites in both the cortex and hippocampus. The presence of Neprilysin on BM-MSC-EVs, opens the possibility of a direct β-amyloid degrading action. Our results indicate a potential role for BM-MSC-EVs already in the early stages of AD, suggesting the possibility of intervening before overt clinical manifestations.

Dataset related to article "Neutrophils Driving Unconventional T Cells Mediate Resistance against Murine Sarcomas and Selected Human Tumors"

Neutrophils are a component of the tumor microenvironment and have been predominantly associated with cancer progression. Using a genetic approach complemented by adoptive transfer, we found that neutrophils are essential for resistance against primary 3-methylcholantrene-induced carcinogenesis. Neutrophils were essential for the activation of an interferon-γ-dependent pathway of immune resistance, associated with polarization of a subset of CD4- CD8- unconventional αβ T cells (UTCαβ). Bulk and single-cell RNA sequencing (scRNA-seq) analyses unveiled the innate-like features and diversity of UTCαβ associated with neutrophil-dependent anti-sarcoma immunity. In selected human tumors, including undifferentiated pleomorphic sarcoma, CSF3R expression, a neutrophil signature and neutrophil infiltration were associated with a type 1 immune response and better clinical outcome. Thus, neutrophils driving UTCαβ polarization and type 1 immunity are essential for resistance against murine sarcomas and selected human tumors.

Dataset related to article "Senescent thyrocytes and thyroid tumor cells induce M2-like macrophage polarization of human monocytes via a PGE2-dependent mechanism."

BACKGROUND: Thyroid carcinoma includes several variants characterized by different biological and clinical features: from indolent microcarcinoma to undifferentiated and aggressive anaplastic carcinoma. Inflammation plays a critical role in thyroid tumors. Conditions predisposing to cancer, as well as oncogene activity, contribute to the construction of an inflammatory microenvironment that facilitates thyroid tumor progression. Moreover, oncogene-induced senescence, a mechanism tightly connected with inflammation, and able to restrain or promote cancer progression, is involved in thyroid cancer. The interactions between thyroid tumor cells and the microenvironment are not completely clarified. METHODS: We characterize in vitro the interplay between macrophages and senescent thyrocytes and tumor-derived cell lines, modeling early and late thyroid tumor stages, respectively. Purified peripheral blood-derived human monocytes were exposed to thyroid cell-derived conditioned medium (CM) and assessed for phenotype by flow cytometry. The factors secreted by thyroid cells and macrophages were identified by gene expression analysis and ELISA. The protumoral effect of macrophages was assessed by wound healing assay on K1 thyroid tumor cells. The expression of PTGS2 and M2 markers in thyroid tumors was investigated in publicly available datasets. RESULTS: Human monocytes exposed to CM from senescent thyrocytes and thyroid tumor cell lines undergo M2-like polarization, showing high CD206 and low MHC II markers, and upregulation of CCL17 secretion. The obtained M2-like macrophages displayed tumor-promoting activity. Among genes overexpressed in polarizing cells, we identified the prostaglandin-endoperoxide synthase enzyme (PTGS2/COX-2), which is involved in the production of prostaglandin E2 (PGE2). By using COX-2 inhibitors we demonstrated that the M2-like polarization ability of thyroid cells is related to the production of PGE2. Co-expression of PTGS2 and M2 markers is observed a significant fraction of human thyroid tumors. CONCLUSIONS: Our results demonstrate that both senescent thyrocytes and thyroid tumor cell lines trigger M2-like macrophage polarization that is related to PGE2 secretion. This suggests that the interaction with the microenvironment occurs at both early and late thyroid tumor stages, and favors tumor progression. The co-expression of PTGS2 gene and M2 markers in human thyroid carcinoma highlights the possibility to counteract tumor growth through COX-2 inhibition.

Link to dataset related to article "Dissection of acute stimulus-inducible nucleosome remodeling in mammalian cells"

Accessibility of the genomic regulatory information is largely controlled by the nucleosome-organizing activity of transcription factors (TFs). While stimulus-induced TFs bind to genomic regions that are maintained accessible by lineage-determining TFs, they also increase accessibility of thousands of cis-regulatory elements. Nucleosome remodeling events underlying such changes and their interplay with basal positioning are unknown. Here, we devised a novel quantitative framework discriminating different types of nucleosome remodeling events in micrococcal nuclease ChIP-seq (chromatin immunoprecipitation [ChIP] combined with high-throughput sequencing) data sets and used it to analyze nucleosome dynamics at stimulus-regulated cis-regulatory elements. At enhancers, remodeling preferentially affected poorly positioned nucleosomes while sparing well-positioned nucleosomes flanking the enhancer core, indicating that inducible TFs do not suffice to overrule basal nucleosomal organization maintained by lineage-determining TFs. Remodeling events appeared to be combinatorially driven by multiple TFs, with distinct TFs showing, however, different remodeling efficiencies. Overall, these data provide a systematic view of the impact of stimulation on nucleosome organization and genome accessibility in mammalian cells.

Dataset related to article "Costimulatory Molecules and Immune Checkpoints Are Differentially Expressed on Different Subsets of Dendritic Cells."

Dendritic cells (DCs) play a crucial role in initiating and shaping immune responses. The effects of DCs on adaptive immune responses depend partly on functional specialization of distinct DC subsets, and partly on the activation state of DCs, which is largely dictated by environmental signals. Fully activated immunostimulatory DCs express high levels of costimulatory molecules, produce pro-inflammatory cytokines, and stimulate T cell proliferation, whereas tolerogenic DCs express low levels of costimulatory molecules, produce immunomodulatory cytokines and impair T cell proliferation. Relevant to the increasing use of immune checkpoint blockade in cancer treatment, signals generated from inhibitory checkpoint molecules on DC surface may also contribute to the inhibitory properties of tolerogenic DCs. Yet, our knowledge on the expression of inhibitory molecules on human DC subsets is fragmentary. Therefore, in this study, we investigated the expression of three immune checkpoints on peripheral blood DC subsets, in basal conditions and upon exposure to pro-inflammatory and anti-inflammatory stimuli, by using a flow cytometric panel that allows a direct comparison of the activatory/inhibitory phenotype of DC-lineage and inflammatory DC subsets. We demonstrated that functionally distinct DC subsets are characterized by differential expression of activatory and inhibitory molecules, and that cDC1s in particular are endowed with a unique immune checkpoint repertoire characterized by high TIM-3 expression, scarce PD-L1 expression and lack of ILT2. Notably, this unique cDC1 repertoire was subverted in a group of patients with myelodysplastic syndromes included in the study. Applied to the characterization of DCs in the tumor microenvironment, this panel has the potential to provide valuable information to be used for investigating the role of DC subsets in cancer, guiding DC-targeting treatments, and possibly identifying predictive biomarkers for clinical response to cancer immunotherapy.

Dataset related to article "Computer-aided assessment of the extra-cellular matrix during pancreatic carcinogenesis: a pilot study."

BACKGROUND: A hallmark of pancreatic ductal adenocarcinoma is the desmoplastic reaction, but its impact on the tumor behavior remains controversial. Our aim was to introduce a computer -aided method to precisely quantify the amount of pancreatic collagenic extra-cellular matrix, its spatial distribution pattern, and the degradation process. METHODS: A series of normal, inflammatory and neoplastic pancreatic ductal adenocarcinoma formalin-fixed and paraffin-embedded Sirius red stained sections were automatically digitized and analyzed using a computer-aided method. RESULTS: We found a progressive increase of pancreatic collagenic extra-cellular matrix from normal to the inflammatory and pancreatic ductal adenocarcinoma. The two-dimensional fractal dimension showed a significant difference in the collagenic extra-cellular matrix spatial complexity between normal versus inflammatory and pancreatic ductal adenocarcinoma. A significant difference when comparing the number of cycles necessary to degrade the pancreatic collagenic extra-cellular matrix in normal versus inflammatory and pancreatic ductal adenocarcinoma was also found. The difference between inflammatory and pancreatic ductal adenocarcinoma was also significant. Furthermore, the mean velocity of collagenic extra-cellular matrix degradation was found to be faster in inflammatory and pancreatic ductal adenocarcinoma than in normal. CONCLUSION: These findings demonstrate that inflammatory and pancreatic ductal adenocarcinomas are characterized by an increased amount of pancreatic collagenic extra-cellular matrix and by changes in their spatial complexity and degradation. Our study defines new features about the pancreatic collagenic extra-cellular matrix, and represents a basis for further investigations into the clinical behavior of pancreatic ductal adenocarcinoma and the development of therapeutic strategies.

opencc-by-4.0Jul 2020View details →

Pairwise Multi-Class Document Classification for Semantic Relations between Wikipedia Articles (Dataset, Models & Code)

Many digital libraries recommend literature to their users considering the similarity between a query document and their repository. However, they often fail to distinguish what is the relationship that makes two documents alike. In this paper, we model the problem of finding the relationship between two documents as a pairwise document classification task. To find the semantic relation between documents, we apply a series of techniques, such as GloVe, Paragraph-Vectors, BERT, and XLNet under different configurations (e.g., sequence length, vector concatenation scheme), including a Siamese architecture for the Transformer-based systems. We perform our experiments on a newly proposed dataset of 32,168 Wikipedia article pairs and Wikidata properties that define the semantic document relations. Our results show vanilla BERT as the best performing system with an F1-score of 0.93, which we manually examine to better understand its applicability to other domains. Our findings suggest that classifying semantic relations between documents is a solvable task and motivates the development of recommender systems based on the evaluated techniques. The discussions in this paper serve as first steps in the exploration of documents through SPARQL-like queries such that one could find documents that are similar in one aspect but dissimilar in another. Additional information can be found on <a href="https://github.com/malteos/semantic-document-relations/">GitHub</a>. The following data is supplemental to the experiments described in our research paper. The data consists of: <ul> <li>Datasets (articles, class labels, cross-validation splits)</li> <li>Pretrained models (Transformers, GloVe, Doc2vec)</li> <li>Model output (prediction) for the best performing models</li> </ul> Dataset The Wikipedia article corpus is available in <code>enwiki-20191101-pages-articles.weighted.10k.jsonl.bz2</code>. The original data have been downloaded as <a href="https://dumps.wikimedia.org/enwiki/">XML dump</a>, and the corresponding articles were extracted as plain-text with <a href="https://radimrehurek.com/gensim/scripts/segment_wiki.html">gensim.scripts.segment_wiki</a>. The archive contains only articles that are available in training or test data. The actual dataset is provided as used in the stratified k-fold with <code>k=4</code> in <code>train_testdata__4folds.tar.gz</code>. <pre><code>├── 1 │ ├── test.csv │ └── train.csv ├── 2 │ ├── test.csv │ └── train.csv ├── 3 │ ├── test.csv │ └── train.csv └── 4 ├── test.csv └── train.csv 4 directories, 8 files </code></pre> Pretrained models PyTorch: vanilla and Siamese BERT + XLNet Pretrained model for each fold is available in the corresponding model archives: <pre><code># Vanilla model_wiki.bert_base__joint__seq512.tar.gz model_wiki.xlnet_base__joint__seq512.tar.gz # Siamese model_wiki.bert_base__siamese__seq512__4d.tar.gz model_wiki.xlnet_base__siamese__seq512__4d.tar.gz </code></pre>

openother-ncMar 2020View details →

The "Last.fm" data set used in the article "Cumulative effects of triadic closure and homophily in social networks"

This is the "Last.fm" network used in the article: A. Asikainen, G. Iñiguez,  J. Ureña-Carrión,  K. Kaski, M. Kivelä. Cumulative effects of triadic closure and homophily in social networks. Science Advances (in press) https://doi.org/10.1126/sciadv.aax7310 The data set is described in the article. Please cite the original article when using this data set. The original data in which this network is based on was donwloaded from audioscrobbler.net where it was licensed under the "Creative Commons Attribution-NonCommercial-ShareAlike 2.0 UK: England & Wales" licese, and accordinly this data set uses the same license. The data contains two files: lastfm.edg This is the network formatted as an edge list, where each row in the file is an edge connecting the two nodes indicated by the two numbers separated by a whitespace. Each node number corresponds to a single account in the website. lastfm_genders.txt This is the list of genders of the nodes. Each row corresponds to one node. The first number is the node id (matching the one in the edge list) and the second number indicates the gender such that 0=male and 1=female.

opencc-by-4.0Apr 2020View details →

Supplementary data for the article "Ayahuasca Users in Estonia: Ceremonial Practices, Subjective Long-Term Effects, Mental Health and Quality of Life"

The dataset contains qualitative data from a study of ayahuasca users in Estonia: Appendix 1 - Appendix 6: free-text answers (shuffled and edited for protection of confidentiality of the respondents), in Estonian. Appendices 7 and 8: study-specific questionnaires, in Estonian. The dataset provides supplementary information for the article "Ayahuasca Users in Estonia: Ceremonial Practices, Subjective Long-Term Effects, Mental Health and Quality of Life" (authors Helle Kaasik and Kairi Kreegipuu from University of Tartu, Estonia), submitted to <a href="https://www.tandfonline.com/loi/ujpd20">the Journal of Psychoactive Drugs</a> on April 30, 2019 and accepted for publication on December 3, 2019. More information about the study is available from Helle Kaasik (<a href="mailto:helle.kaasik@ut.ee">helle.kaasik@ut.ee</a>).   In Estonian: Andmehulk sisaldab kvalitatiivseid andmeid Eesti ayahuasca kasutajate uurimisest. Lisa 1-6: vabatekstilised vastused (juhuslikus järjekorras ja toimetatud vastajate konfidentsiaalsuse tagamiseks); Lisa 7-8: uurimuses kasutatud küsimustikud. Andmestik on täienduseks teadusartiklile "Ayahuasca Users in Estonia: Ceremonial Practices, Subjective Long-Term Effects, Mental Health and Quality of Life", mille autorid on Helle Kaasik ja Kairi Kreegipuu Tartu Ülikoolist. Artikkel on saadetud avaldamiseks ajakirjale <a href="https://www.tandfonline.com/loi/ujpd20">Journal of Psychoactive Drugs</a>. Kommentaarid ja küsimused töö kohta on oodatud Helle Kaasiku e-mailile <a href="mailto:helle.kaasik@ut.ee">helle.kaasik@ut.ee</a>

opencc-by-4.0Apr 2020View details →

Research data supporting article "Recurrent horizontal transfer identifies mitochondrial positive selection in a transmissible cancer"

Gene expression data supporting analyses described in the article "Recurrent horizontal transfer identifies mitochondrial positive selection in a transmissible cancer" (Strakova et al., 2020).

Supplemental Material to Journal Article "Assessment of a rotor blade extension retrofit as a supplement to the lifetime extension of wind turbines"

This set supplements the figure data to the article "Assessment of a rotor blade extension retrofit as a supplement to the lifetime extension of wind turbines", DOI: .

The Supplementary Materials of article "remotesensing-801936" of Journal "Remote sensing"

Figures S1-S3 of  article remotesensing-801936 that the integrated maps of the entire (i.e., nine) stations from 30 days before and 15 days after the Jiuzhaigou earthquake at 0.005-0.01 Hz, 0.001-0.005 Hz and 0.01-0.05 Hz, respectively.

opencc-by-4.0Jun 2020View details →

Lexical complexity of editorial articles 2019: Abc, El Mundo, El País, El Periódico

Dataset on lexical complexity of editorial articles of 2019 of four Spanish newspapers: Abc, El Mundo, El País, El Periódico. Size: 23x2845. The columns are the following: Newspaper, Day, # of article of the day, word types, sophisticated word types, lexical word types, sophisticated lexical word types, word tokens, sophisticatred word tokens, lexical word tokens, sophisticated lexical word tokens,  lexical density, lexical sophistication 1,  lexical sophistication 2,  verb sophistication 1, verb sophistication 2, corrected verb sophistication 1, TTR, CTTR, RTTR, MAAS, MTLD, HD-D

Dataset for article titled "The influence of packing structure and interparticle forces on ultrasound transmission in granular media"

Dataset containing supporting materials for article titled "The influence of packing structure and interparticle forces on ultrasound transmission in granular media". An enclosed PDF file describes the data.

opencc-by-4.0Jun 2020View details →

Relating Wikipedia Article Quality to Edit Behavior and Link Structure

This dataset was analyzed and produced during the study described in the paper "Relating Wikipedia Article Quality to Edit Behavior and Link Structure" (under review, doi and link follows - see references). Its creation process and use cases are described in the dedicated paper. For directions and code to process and evaluate this data, please see the corresponding GitHub repository: https://github.com/ruptho/editlinkquality-wikipedia. We provide three files for 4941 Wikipedia articles (in .pkl format): The "article_revisions_labeled.pkl" file provides the final, semantically labeled revisions for each analyzed article per quality category. The "article_revision_features.zip" file contains processed per-article features, divided into folders for the specific quality categories they belong to. In "article_revision_features_raw.zip", we provide the raw features as retrieved via RevScoring API (https://pythonhosted.org/revscoring/).

Datasets for reproduction of simulation study results presented in article "Network Aggregation to Enhance Results Derived from Multiple Analytics"

The included datasets can be used to reproduce the simulation study results presented in the paper: Duroux D., Climente-González H., Wienbrandt L., Van Steen K. (2020) Network Aggregation to Enhance Results Derived from Multiple Analytics. In: Maglogiannis I., Iliadis L., Pimenidis E. (eds) Artificial Intelligence Applications and Innovations. AIAI 2020. IFIP Advances in Information and Communication Technology, vol 583. Springer, Cham. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 813533.