cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3708897
title: Dataset related to article "TNF-Stimulated Gene-6 Is a Key Regulator in Switching Stemness and Biological Properties of Mesenchymal Stem Cells."

description: Mesenchymal stem cells (MSCs) are well established to have promising therapeutic properties. TNF-stimulated gene-6 (TSG-6), a potent tissue-protective and anti-inflammatory factor, has been demonstrated to be responsible for a significant part of the tissue-protecting properties mediated by MSCs. Nevertheless, current knowledge about the biological function of TSG-6 in MSCs is limited. Here, we demonstrated that TSG-6 is a crucial factor that influences many functional properties of MSCs. The transcriptomic sequencing analysis of wild-type (WT) and TSG-6<sup>-/-</sup> -MSCs shows that the loss of TSG-6 expression leads to the perturbation of several transcription factors, cytokines, and other key biological pathways. TSG-6<sup>-/-</sup> -MSCs appeared morphologically different with dissimilar cytoskeleton organization, significantly reduced size of extracellular vesicles, decreased cell proliferative rate, and loss of differentiation abilities compared with the WT cells. These cellular effects may be due to TSG-6-mediated changes in the extracellular matrix (ECM) environment. The supplementation of ECM with exogenous TSG-6, in fact, rescued cell proliferation and changes in morphology. Importantly, TSG-6-deficient MSCs displayed an increased capacity to release interleukin-6 conferring pro-inflammatory and pro-tumorigenic properties to the MSCs. Overall, our data provide strong evidence that TSG-6 is crucial for the maintenance of stemness and other biological properties of murine MSCs. Some dataset of this research are in prism format, to ensure open access we attach a pdf instruction about this format and a link where downoladed it
DOI: 10.5281/zenodo.3708898
title: Dataset related to article "TNF-Stimulated Gene-6 Is a Key Regulator in Switching Stemness and Biological Properties of Mesenchymal Stem Cells."

description: Mesenchymal stem cells (MSCs) are well established to have promising therapeutic properties. TNF-stimulated gene-6 (TSG-6), a potent tissue-protective and anti-inflammatory factor, has been demonstrated to be responsible for a significant part of the tissue-protecting properties mediated by MSCs. Nevertheless, current knowledge about the biological function of TSG-6 in MSCs is limited. Here, we demonstrated that TSG-6 is a crucial factor that influences many functional properties of MSCs. The transcriptomic sequencing analysis of wild-type (WT) and TSG-6<sup>-/-</sup> -MSCs shows that the loss of TSG-6 expression leads to the perturbation of several transcription factors, cytokines, and other key biological pathways. TSG-6<sup>-/-</sup> -MSCs appeared morphologically different with dissimilar cytoskeleton organization, significantly reduced size of extracellular vesicles, decreased cell proliferative rate, and loss of differentiation abilities compared with the WT cells. These cellular effects may be due to TSG-6-mediated changes in the extracellular matrix (ECM) environment. The supplementation of ECM with exogenous TSG-6, in fact, rescued cell proliferation and changes in morphology. Importantly, TSG-6-deficient MSCs displayed an increased capacity to release interleukin-6 conferring pro-inflammatory and pro-tumorigenic properties to the MSCs. Overall, our data provide strong evidence that TSG-6 is crucial for the maintenance of stemness and other biological properties of murine MSCs. Some dataset of this research are in prism format, to ensure open access we attach a pdf instruction about this format and a link where downoladed it
DOI: 10.5281/zenodo.3708014
title: Wikidata Dump films in English

description: RDF dump of wikidata produced with wdumps. Dump of the films in English.<br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3708015
title: Wikidata Dump films in English

description: RDF dump of wikidata produced with wdumps. Dump of the films in English.<br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3706726
title: Aircraft measurement data obtained within the framework of the 3DO measurement campaign in summer 2018 over Berlin

description: Based on airborne in-situ CO<sub>2</sub>, CH<sub>4</sub> and meteorological measurements from two flights on July 20<sup>th</sup> and 24<sup>th</sup> of 2018 we study the greenhouse gas emissions downwind of the German capital Berlin. Measurement flights were conducted within the Urban Climate Under Change [UC]2 programme (module B: Three-Dimensional Observation of Atmospheric Processes in Cities, 3DO). Results are published in T. Klausner, M. Mertens, H. Huntrieser, M. Galkowski, G. Kuhlmann, R. Baumann, A. Fiehn, P. Jöckel, M. Pühl, and A. Roiger: Urban greenhouse gas emissions from the Berlin area: A case study using airborne CO<sub>2</sub> and CH<sub>4</sub> in situ observations in summer 2018, Elementa: Science of the Anthropocene (Ref.: Ms. No. ELEMENTA-D-19-00074R1), 2019.
description: We thank DLR VO-R for funding the young investigator research group "Greenhouse Gases". The German Federal Ministry of Education and Research (BMBF) funds the 3DO consortium under grant 01LP1602 within the framework of Research for Sustainable Development (FONA; www.fona.de). The German Aerospace Center (DLR) Project Management Agency supports the consortium.
DOI: 10.5281/zenodo.3708931
title: Dataset related to article "Postmastectomy radiation therapy using VMAT technique for breast cancer patients with expander reconstruction."

description: Postmastectomy radiotherapy (PMRT) following immediate breast reconstruction is increasingly adopted in the management of breast cancer patients. We retrospectively evaluate the complication rates of PMRT using VMAT technique to immediate tissue expander-based reconstructions and the possible impact of tissue expander volume on radiotherapy planning. We reviewed the data of patients who underwent immediate expander breast reconstruction and received PMRT with VMAT (50 Gy in 25 fractions) on the reconstructed breast and axillary levels III-IV. Neoadjuvant or adjuvant systemic therapy was administered in most of the patients. Autologous fat grafting was routinely performed at the time of second-stage reconstruction. Between 2015 and 2017, PMRT was delivered to 46 consecutive patients (median age 50 years) with expander reconstruction. Median follow-up was 27 months (range 10-41). Two patients (4.3%) had a reconstruction failure, as expander rupture and infection, following the first- and the second-stage reconstruction, respectively. In most cases expanders were completely inflated before PMRT (65.2%). Median expander volume before PMRT was 425 cm<sup>3</sup> (range 150-700 cm<sup>3</sup>). The amount of expander inflation did not significantly affect dosimetry, except for skin dose, with a surface receiving more than 30 Gy of 36.6 ± 0.9 cm<sup>2</sup> and 47.0 ± 2.5 cm<sup>2</sup> for a volume expander below or above the median, respectively. However, this variable was not predictor for complications. Disease progression was recorded in 15.2% of patients. PMRT using VMAT technique for breast cancer patients with expander reconstruction is associated with a very low complication rate. The expander volume before PMRT does not significantly compromise radiotherapy dose distribution.
DOI: 10.5281/zenodo.3708932
title: Dataset related to article "Postmastectomy radiation therapy using VMAT technique for breast cancer patients with expander reconstruction."

description: Postmastectomy radiotherapy (PMRT) following immediate breast reconstruction is increasingly adopted in the management of breast cancer patients. We retrospectively evaluate the complication rates of PMRT using VMAT technique to immediate tissue expander-based reconstructions and the possible impact of tissue expander volume on radiotherapy planning. We reviewed the data of patients who underwent immediate expander breast reconstruction and received PMRT with VMAT (50 Gy in 25 fractions) on the reconstructed breast and axillary levels III-IV. Neoadjuvant or adjuvant systemic therapy was administered in most of the patients. Autologous fat grafting was routinely performed at the time of second-stage reconstruction. Between 2015 and 2017, PMRT was delivered to 46 consecutive patients (median age 50 years) with expander reconstruction. Median follow-up was 27 months (range 10-41). Two patients (4.3%) had a reconstruction failure, as expander rupture and infection, following the first- and the second-stage reconstruction, respectively. In most cases expanders were completely inflated before PMRT (65.2%). Median expander volume before PMRT was 425 cm<sup>3</sup> (range 150-700 cm<sup>3</sup>). The amount of expander inflation did not significantly affect dosimetry, except for skin dose, with a surface receiving more than 30 Gy of 36.6 ± 0.9 cm<sup>2</sup> and 47.0 ± 2.5 cm<sup>2</sup> for a volume expander below or above the median, respectively. However, this variable was not predictor for complications. Disease progression was recorded in 15.2% of patients. PMRT using VMAT technique for breast cancer patients with expander reconstruction is associated with a very low complication rate. The expander volume before PMRT does not significantly compromise radiotherapy dose distribution.
DOI: 10.5281/zenodo.3708959
title: Evaluation of a mulit-physics snow model in the Tyrolean Alps

description: This dataset presents an ensemble of 66240 simulations of the seasonal snow cover in the catchment of the Längentalbach (Tyrol, Austria) over the course of 5 winter seasons. Simulations are evaluated against point scale observations at the snow monitoring station Kühtai and catchment scale observations such as MODIS derived snow cover fraction as well as the seasonal water balance. Simulations are carried out with various parameter sets and forcing data error scenarios. The dataset splits in ModelSkills.csv where the resulting model performance values are listed, and ParameterAndForingError.csv where the corresponding parameter values and forcing errors are presented. The file header_info.txt provides additional information about each column in the files.
DOI: 10.5281/zenodo.3708958
title: Evaluation of a mulit-physics snow model in the Tyrolean Alps

description: This dataset presents an ensemble of 66240 simulations of the seasonal snow cover in the catchment of the Längentalbach (Tyrol, Austria) over the course of 5 winter seasons. Simulations are evaluated against point scale observations at the snow monitoring station Kühtai and catchment scale observations such as MODIS derived snow cover fraction as well as the seasonal water balance. Simulations are carried out with various parameter sets and forcing data error scenarios. The dataset splits in ModelSkills.csv where the resulting model performance values are listed, and ParameterAndForingError.csv where the corresponding parameter values and forcing errors are presented. The file header_info.txt provides additional information about each column in the files.
DOI: 10.5281/zenodo.3708957
title: 3D time-course iSIM dataset HeLa cells MitoTracker Red CMXRos

description: 2020-03-17 Microscopy dataset: - Type: Fluorescence, 3D, time-course, iSIM Visitech, 100x Silicon NA 1.35 (65 nm x 65 nm x 300 nm xyz pixel sizes), 20s time interval - Cell type: HeLa, labelled with MitoTracker Red CMXRos Romain F. Laine, r.laine@ucl.ac.uk, MRC-LMCB, UCL, London, UK
description: Funded by the Medical Research Council (MRC) of the UK Research and Innovation (UKRI) funding body
DOI: 10.5281/zenodo.3708956
title: 3D time-course iSIM dataset HeLa cells MitoTracker Red CMXRos

description: 2020-03-17 Microscopy dataset: - Type: Fluorescence, 3D, time-course, iSIM Visitech, 100x Silicon NA 1.35 (65 nm x 65 nm x 300 nm xyz pixel sizes), 20s time interval - Cell type: HeLa, labelled with MitoTracker Red CMXRos Romain F. Laine, r.laine@ucl.ac.uk, MRC-LMCB, UCL, London, UK
description: Funded by the Medical Research Council (MRC) of the UK Research and Innovation (UKRI) funding body
DOI: 10.5281/zenodo.3708054
title: Data and code for "Plant community functional composition and diversity drive fine-scale variability in carbon cycling in the tundra"

description: <strong>Paper</strong> See the preprint for more detailed description of the performend analyses here. <strong>Description of subdirectories</strong> The structure of this repository loosely follows that recommended by Wilson et al. 2017. <em>docs</em> Contains data documentation and metadata. <em>data</em> Holds raw, unedited data <em>src</em> Contains analysis scripts. The src/figures.R script generates all the figures for this project. The other scripts prepare the data for analysis, and must be run before src/figures.R <em>results</em> Contains all analysis results, cleaned, analysis-ready data, figures, etc. Some of the figures (such as measurement schematics) have been generated by hand, and are thus not linked to any scripts.
DOI: 10.21227/h0bf-6f71
title: Corona Virus (COVID-19) Tweets Dataset (en)

description: Each database (*.db) contain three columns.First column: date and time of the tweetSecond column: tweetThird column: sentiment score for the particular tweet within the range [-1,1] with -1 being the most negative, 0 being the neutral and +1 being the most positive sentiment.The tweets have been collected by the LSTM model deployed here at sentiment.live.To make it easy for the NLP researchers to get access to the sentiment analysis of each collected tweet, the sentiment score out of TextBlob [2] has been appended as the last column. New databases will be added to this dataset every week. Bookmark this page for further updates. [1] https://sentiment.live/ [2] https://textblob.readthedocs.io/en/dev/
DOI: 10.21227/stwz-2z59
title: Twitter Sentiment Analysis Data

description: Collect Corona Virus related Tweets from here.Each database (*.db) contain three columns. First column: date and time of the tweet, second column: tweet, third column: sentiment score for the particular tweet within the range [-1,1] with -1 being the most negative, 0 being the neutral and +1 being the most positive sentiment.The tweets have been collected by the LSTM model deployed here at sentiment.live[1]. The last column, viz. sentiment score, is not the score estimated by the model. The LSTM model is still in the pre-alpha phase. Therefore, to make it easy for the NLP researchers to get access to the sentiment analysis of each collected tweet, the sentiment score out of TextBlob [2] has been appended as the last column. The sentiment scores produced by our model will be made public after the project is completely open-sourced.####status/latest addition: March 02, 2020####The model has been currently monitoring corona related tweets and can be downloaded from herehttps://ieee-dataport.org/open-access/corona-virus-covid-19-tweets-dataset.Tweets containing the term "republic day": 0.37 million-plusTweets containing the term "samsung": 1.20 million-plusTweets containing the term "facebook": 0.77 million-plusTweets containing the term "android": 0.88 million-plusTweets containing the term "oneplus": 15 thousand-plusTweets containing the term "messi": 225 thousand-plusTweets containing the term "housefull 4": 346 thousand-plusTweets containing the term "the joker": 1 million-plusTweets containing the term "iphone 11": 2 million-plus##################References:[1]https://sentiment.live/ [2]https://textblob.readthedocs.io/en/dev/
DOI: 10.21227/2xv3-pr25
title: Corona Virus (COVID-19) Tweets Dataset

description: Tweets Counter: 3.8 Million plusEach database (*.db) contain three columns.First column: date and time of the tweetSecond column: tweetThird column: sentiment score for the particular tweet within the range [-1,1] with -1 being the most negative, 0 being the neutral and +1 being the most positive sentiment.The tweets have been collected by the LSTM model deployed here at sentiment.live.To make it easy for the NLP researchers to get access to the sentiment analysis of each collected tweet, the sentiment score out of TextBlob [2] has been appended as the last column. New databases will be added to this dataset every week. Bookmark this page for further updates. [1] https://sentiment.live/ [2] https://textblob.readthedocs.io/en/dev/
DOI: 10.5281/zenodo.3708963
title: Sample Multi-Modal BIDS dataset

description: This a sample BIDS dataset created for continous integration of the Connectome Mapper 3. This dataset was acquired at the Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland, using a 3T Siemens Prisma MRI scanner. It adopts the sub-/ses- structure and contains one T1w anatomical MRI (MPRAGE), one diffusion MRI (DSI) , and one resting-state functional MRI as well as additional Freesurfer derivatives. It is distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. (See https://creativecommons.org/licenses/by/4.0/ for more details)
description: Funded by SNF Sinergia Grant #170873 (http://p3.snf.ch/Project-170873)
DOI: 10.15129/94f789c4-cdb5-4013-8f89-dce80c028d3b
title: Data for: "Estimation of initial rate from discontinuous progress data"

description: File Supplementary Info is the Supporting Information for the paper, and contains an index to all the other files, which are Excel spreadsheets
DOI: 10.5281/zenodo.3708985
title: Dataset related to article "IL1R8 Deficiency Drives Autoimmunity-Associated Lymphoma Development."

description: Chronic inflammation, including that driven by autoimmunity, is associated with the development of B-cell lymphomas. IL1R8 is a regulatory receptor belonging to the IL1R family, which negatively regulates NF-κB activation following stimulation of IL1R or Toll-like receptor family members. IL1R8 deficiency is associated with the development of severe autoimmune lupus-like disease in <em>lpr</em> mice. We herein investigated whether concomitant exacerbated inflammation and autoimmunity caused by the deficiency of IL1R8 could recapitulate autoimmunity-associated lymphomagenesis. We thus monitored B-cell lymphoma development during the aging of IL1R8-deficient <em>lpr</em> mice, observing an increased lymphoid cell expansion that evolved to diffuse large B-cell lymphoma (DLBCL). Molecular and gene-expression analyses showed that the NF-κB pathway was constitutively activated in <em>Il1r8</em> <sup>-/-</sup>/<em>lpr</em> B splenocytes. In human DLBCL, <em>IL1R8</em> had reduced expression compared with normal B cells, and higher <em>IL1R8</em> expression was associated with a better outcome. Thus, <em>IL1R8</em> silencing is associated with increased lymphoproliferation and transformation in the pathogenesis of B-cell lymphomas associated with autoimmunity.
DOI: 10.5281/zenodo.3708984
title: Dataset related to article "IL1R8 Deficiency Drives Autoimmunity-Associated Lymphoma Development."

description: Chronic inflammation, including that driven by autoimmunity, is associated with the development of B-cell lymphomas. IL1R8 is a regulatory receptor belonging to the IL1R family, which negatively regulates NF-κB activation following stimulation of IL1R or Toll-like receptor family members. IL1R8 deficiency is associated with the development of severe autoimmune lupus-like disease in <em>lpr</em> mice. We herein investigated whether concomitant exacerbated inflammation and autoimmunity caused by the deficiency of IL1R8 could recapitulate autoimmunity-associated lymphomagenesis. We thus monitored B-cell lymphoma development during the aging of IL1R8-deficient <em>lpr</em> mice, observing an increased lymphoid cell expansion that evolved to diffuse large B-cell lymphoma (DLBCL). Molecular and gene-expression analyses showed that the NF-κB pathway was constitutively activated in <em>Il1r8</em> <sup>-/-</sup>/<em>lpr</em> B splenocytes. In human DLBCL, <em>IL1R8</em> had reduced expression compared with normal B cells, and higher <em>IL1R8</em> expression was associated with a better outcome. Thus, <em>IL1R8</em> silencing is associated with increased lymphoproliferation and transformation in the pathogenesis of B-cell lymphomas associated with autoimmunity.
DOI: 10.5281/zenodo.3709004
title: Dataset related to article "Senescent thyrocytes and thyroid tumor cells induce M2-like macrophage polarization of human monocytes via a PGE2-dependent mechanism."

description: 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.