cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25318/3810016301-fra
title: Étendue et croissance des zones habitées contiguës

description: Mesures de l’étendue et de l’expansion des zones habitées à partir des données sur la couverture terrestre tirées de l’observation de la Terre. Les variables comprennent l’étendue et la croissance de la zone habitée contiguë (ZHC) de même que la croissance des surfaces bâties et artificielles dans les zones tampons environnantes. Les limites des ZHC sont créées pour les centres de population de Statistique Canada comptant plus de 5 000 habitants ou ceux situés dans une région métropolitaine de recensement ou une agglomération de recensement.
DOI: 10.6084/m9.figshare.24512508
title: Supplementary Table 1 from A systems-level analysis of the mutually antagonistic roles of RKIP and BACH1 in dynamics of cancer cell plasticity

description: Epithelial-mesenchymal transition (EMT) is an important axis of phenotypic plasticity – a hallmark of cancer metastasis. Raf kinase-B inhibitor protein (RKIP) and BTB and CNC homology 1 (BACH1) are reported to influence EMT. In breast cancer, they act antagonistically, but the exact nature of their roles in mediating EMT and associated other axes of plasticity remains unclear. Here, analysing transcriptomic data, we reveal their antagonistic trends in a pan-cancer manner in terms of association with EMT, metabolic reprogramming and, immune evasion via PD-L1. Next, we developed and simulated a mechanism-based gene regulatory network that captures how RKIP and BACH1 engage in feedback loops with drivers of EMT and stemness. We found that RKIP and BACH1 belong to two antagonistic ‘teams’ of players – while BACH1 belonged to the one driving pro-EMT, stem-like and therapy-resistant cell-states, RKIP belonged to the one enabling pro-epithelial, less stem-like and therapy-sensitive phenotypes. Finally, we observed that low RKIP levels and upregulated BACH1 levels associated with worse clinical outcomes in many cancer types. Together, our systems-level analysis indicates that the emergent dynamics of underlying regulatory network underlie the antagonistic patterns of RKIP and BACH1 with various axes of cancer cell plasticity, and with patient survival data.
DOI: 10.6084/m9.figshare.24512508.v1
title: Supplementary Table 1 from A systems-level analysis of the mutually antagonistic roles of RKIP and BACH1 in dynamics of cancer cell plasticity

description: Epithelial-mesenchymal transition (EMT) is an important axis of phenotypic plasticity – a hallmark of cancer metastasis. Raf kinase-B inhibitor protein (RKIP) and BTB and CNC homology 1 (BACH1) are reported to influence EMT. In breast cancer, they act antagonistically, but the exact nature of their roles in mediating EMT and associated other axes of plasticity remains unclear. Here, analysing transcriptomic data, we reveal their antagonistic trends in a pan-cancer manner in terms of association with EMT, metabolic reprogramming and, immune evasion via PD-L1. Next, we developed and simulated a mechanism-based gene regulatory network that captures how RKIP and BACH1 engage in feedback loops with drivers of EMT and stemness. We found that RKIP and BACH1 belong to two antagonistic ‘teams’ of players – while BACH1 belonged to the one driving pro-EMT, stem-like and therapy-resistant cell-states, RKIP belonged to the one enabling pro-epithelial, less stem-like and therapy-sensitive phenotypes. Finally, we observed that low RKIP levels and upregulated BACH1 levels associated with worse clinical outcomes in many cancer types. Together, our systems-level analysis indicates that the emergent dynamics of underlying regulatory network underlie the antagonistic patterns of RKIP and BACH1 with various axes of cancer cell plasticity, and with patient survival data.
DOI: 10.6084/m9.figshare.24512514
title: Supplementary Table 2 from A systems-level analysis of the mutually antagonistic roles of RKIP and BACH1 in dynamics of cancer cell plasticity

description: Epithelial-mesenchymal transition (EMT) is an important axis of phenotypic plasticity – a hallmark of cancer metastasis. Raf kinase-B inhibitor protein (RKIP) and BTB and CNC homology 1 (BACH1) are reported to influence EMT. In breast cancer, they act antagonistically, but the exact nature of their roles in mediating EMT and associated other axes of plasticity remains unclear. Here, analysing transcriptomic data, we reveal their antagonistic trends in a pan-cancer manner in terms of association with EMT, metabolic reprogramming and, immune evasion via PD-L1. Next, we developed and simulated a mechanism-based gene regulatory network that captures how RKIP and BACH1 engage in feedback loops with drivers of EMT and stemness. We found that RKIP and BACH1 belong to two antagonistic ‘teams’ of players – while BACH1 belonged to the one driving pro-EMT, stem-like and therapy-resistant cell-states, RKIP belonged to the one enabling pro-epithelial, less stem-like and therapy-sensitive phenotypes. Finally, we observed that low RKIP levels and upregulated BACH1 levels associated with worse clinical outcomes in many cancer types. Together, our systems-level analysis indicates that the emergent dynamics of underlying regulatory network underlie the antagonistic patterns of RKIP and BACH1 with various axes of cancer cell plasticity, and with patient survival data.
DOI: 10.6084/m9.figshare.24512514.v1
title: Supplementary Table 2 from A systems-level analysis of the mutually antagonistic roles of RKIP and BACH1 in dynamics of cancer cell plasticity

description: Epithelial-mesenchymal transition (EMT) is an important axis of phenotypic plasticity – a hallmark of cancer metastasis. Raf kinase-B inhibitor protein (RKIP) and BTB and CNC homology 1 (BACH1) are reported to influence EMT. In breast cancer, they act antagonistically, but the exact nature of their roles in mediating EMT and associated other axes of plasticity remains unclear. Here, analysing transcriptomic data, we reveal their antagonistic trends in a pan-cancer manner in terms of association with EMT, metabolic reprogramming and, immune evasion via PD-L1. Next, we developed and simulated a mechanism-based gene regulatory network that captures how RKIP and BACH1 engage in feedback loops with drivers of EMT and stemness. We found that RKIP and BACH1 belong to two antagonistic ‘teams’ of players – while BACH1 belonged to the one driving pro-EMT, stem-like and therapy-resistant cell-states, RKIP belonged to the one enabling pro-epithelial, less stem-like and therapy-sensitive phenotypes. Finally, we observed that low RKIP levels and upregulated BACH1 levels associated with worse clinical outcomes in many cancer types. Together, our systems-level analysis indicates that the emergent dynamics of underlying regulatory network underlie the antagonistic patterns of RKIP and BACH1 with various axes of cancer cell plasticity, and with patient survival data.
DOI: 10.25318/32100472-eng
title: Use and content of a prevention-focused health program for livestock, by farm production type

description: Agricultural operations and the content of their prevention-focused health programs for livestock, separated by farm production type, and by province, available every 5 years.
DOI: 10.6084/m9.figshare.24512401
title: Targeted metabolomics reveals the association between central carbon metabolism and pulmonary nodules.

description: We supplemented the raw data of the published paper, the information on the baseline data, and the model grouping information
DOI: 10.5281/zenodo.10066455
title: Datasets for "Ultra-narrow inhomogeneous spectral distribution of telecom-wavelength vanadium centres in isotopically-enriched silicon carbide"

description: Datasets supporting the paper: "Ultra-narrow inhomogeneous spectral distribution of telecom-wavelength vanadium centres in isotopically-enriched silicon carbide" by P. Cilibrizzi et al.
 
The files are named as date_time_+"PLE_scan_"+frqInitial_polarisation_frqEnd_signal. For example, the file "2022-12-20_17_07_PLE_scan_234420059_MHz_sigma_P_234419877_MHz_X" is taken on teh 20th of December 2022, starting at 17:07pm. The wavelength of the excitation laser is measured by the wavemeter at the beginning of data acquisition to be 234,420,059 MHz. At the end of the map, the laser wavelength is 234,419,877 MHz. The quantity stored in the file is "X", corresponding to the values of the x-axis for the spatial scan.
Possible quantities areX: values of the x-axis for the spatial scan (in microns)Y: values of the y-axis for the spatial scan (in microns)Z: number of photon counts
DOI: 10.5281/zenodo.10066454
title: Datasets for "Ultra-narrow inhomogeneous spectral distribution of telecom-wavelength vanadium centres in isotopically-enriched silicon carbide"

description: Datasets supporting the paper: "Ultra-narrow inhomogeneous spectral distribution of telecom-wavelength vanadium centres in isotopically-enriched silicon carbide" by P. Cilibrizzi et al.
 
The files are named as date_time_+"PLE_scan_"+frqInitial_polarisation_frqEnd_signal. For example, the file "2022-12-20_17_07_PLE_scan_234420059_MHz_sigma_P_234419877_MHz_X" is taken on teh 20th of December 2022, starting at 17:07pm. The wavelength of the excitation laser is measured by the wavemeter at the beginning of data acquisition to be 234,420,059 MHz. At the end of the map, the laser wavelength is 234,419,877 MHz. The quantity stored in the file is "X", corresponding to the values of the x-axis for the spatial scan.
Possible quantities areX: values of the x-axis for the spatial scan (in microns)Y: values of the y-axis for the spatial scan (in microns)Z: number of photon counts
DOI: 10.34740/kaggle/dsv/6900483
title: Mahanagar Yatayat Transport Dataset
DOI: 10.25318/3210047201-fra
title: Utilisation et contenu d'un programme de santé animale axé sur la prévention, selon le type de production agricole

description: Opérations agricoles et le contenu de leur programme de santé animale axé sur la prévention, séparé selon le type de production agricole et la province, disponible tous les 5 ans.
DOI: 10.5281/zenodo.7596036
title: PHQ-9 QUECHUA BOLIVIA

description: Datos complementarios al artículo de adaptación y validación del PHQ-9 al quechua de Bolivia
DOI: 10.34740/kaggle/dsv/6900505
title: MoviesDatasets
DOI: 10.5281/zenodo.10075806
title: Supplementary documents of the PHQ-9 Bolivian Quechua

description: Complementary documents to the article on adaptation and validation of the PHQ-9 into Bolivian Quechua, such as the procedures carried out and the database
DOI: 10.5281/zenodo.7596035
title: Supplementary documents of the PHQ-9 Bolivian Quechua

description: Complementary documents to the article on adaptation and validation of the PHQ-9 into Bolivian Quechua, such as the procedures carried out and the database
DOI: 10.5281/zenodo.8350639
title: Supplementary documents of the PHQ-9 Bolivian Quechua

description: Complementary documents to the article on adaptation and validation of the PHQ-9 into Bolivian Quechua, such as the procedures carried out and the database
DOI: 10.5281/zenodo.10071637
title: Benchmarking results for iStar

description: These data files contain the benchmarking results for iStar using a Xenium breast cancer dataset and a Xenium mouse brain dataset, as presented in the paper "Inferring super-resolution tissue architecture by integrating spatial transcriptomics with histology" by Daiwei Zhang, Amelia Schroeder, Hanying Yan, Haochen Yang, Jian Hu, Michelle Y. Y. Lee, Kyung S. Cho, Katalin Susztak, George X. Xu, Michael D. Feldman, Edward B. Lee, Emma E. Furth, Linghua Wang, Mingyao Li.
DOI: 10.5281/zenodo.10071636
title: Benchmarking results for iStar

description: These data files contain the benchmarking results for iStar using a Xenium breast cancer dataset and a Xenium mouse brain dataset, as presented in the paper "Inferring super-resolution tissue architecture by integrating spatial transcriptomics with histology" by Daiwei Zhang, Amelia Schroeder, Hanying Yan, Haochen Yang, Jian Hu, Michelle Y. Y. Lee, Kyung S. Cho, Katalin Susztak, George X. Xu, Michael D. Feldman, Edward B. Lee, Emma E. Furth, Linghua Wang, Mingyao Li.
DOI: 10.5281/zenodo.8429850
title: δ88/86Sr and δ44/40Ca variability in multi-depth coastal groundwater and its implications for solute exchange across seawater-inflicted aquifers

description: Dataset used in the manuscript "δ88/86Sr and δ44/40Ca variability in multi-depth coastal groundwater and its implications for solute exchange across seawater-inflicted aquifers".
DOI: 10.5517/ccdc.csd.cc277y1h
title: CCDC 2063206: Experimental Crystal Structure Determination

description: Related Article: Priyanka Manna, Avantika Hasija, Deepak Chopra, Partha Mahata|2023|New J.Chem.|47|19846|doi:10.1039/D3NJ03179A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2br0gl
title: CCDC 2167069: Experimental Crystal Structure Determination

description: Related Article: Michael P. Bubnov, Alexey Zolotukhin, Konstantin A. Kozhanov, Evgeny V. Baranov, Artem S. Bogomyakov, Maxim V. Arsenyev, Sergey Yu. Ketkov, Vladimir K. Cherkasov|2023|Polyhedron|246|116692|doi:10.1016/j.poly.2023.116692
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2br0hm
title: CCDC 2167070: Experimental Crystal Structure Determination

description: Related Article: Michael P. Bubnov, Alexey Zolotukhin, Konstantin A. Kozhanov, Evgeny V. Baranov, Artem S. Bogomyakov, Maxim V. Arsenyev, Sergey Yu. Ketkov, Vladimir K. Cherkasov|2023|Polyhedron|246|116692|doi:10.1016/j.poly.2023.116692
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2brtmk
title: CCDC 2167849: Experimental Crystal Structure Determination

description: Related Article: Michael P. Bubnov, Alexey Zolotukhin, Konstantin A. Kozhanov, Evgeny V. Baranov, Artem S. Bogomyakov, Maxim V. Arsenyev, Sergey Yu. Ketkov, Vladimir K. Cherkasov|2023|Polyhedron|246|116692|doi:10.1016/j.poly.2023.116692
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2cly75
title: CCDC 2192947: Experimental Crystal Structure Determination

description: Related Article: David Reza, Rosalino Balo, José M. Otero, Ai M. Fletcher, Rebeca García-Fandino, Víctor M. Sánchez-Pedregal, Stephen G. Davies, Ramón J. Estévez, Juan C. Estévez|2023|Org.Biomol.Chem.|21|8535|doi:10.1039/D3OB00906H
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2d1mlp
title: CCDC 2206102: Experimental Crystal Structure Determination

description: Related Article: Jingwei Meng, Teng Fei, Jinxiong Cai, Qi Lai, Jinya Zhang, Si-Ping Pang, Chunlin He|2023|CSD Communication|||
description: Related Article: Jingwei Meng, Teng Fei, Jinxiong Cai, Qi Lai, Jinya Zhang, Siping Pang, Chunlin He|2023|Mater. Chem. Front.|7|5891|doi:10.1039/D3QM00724C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2f7rl1
title: CCDC 2241783: Experimental Crystal Structure Determination

description: Related Article: Raffaella Mancuso, Alex De Salvo, Patrizio Russo, Aurelia Falcicchio, Nicola Della Ca’, Leonardo Pantoja Munoz, Bartolo Gabriele|2023|Chin.J.Chem.|41|2801|doi:10.1002/cjoc.202300277
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2f7rn3
title: CCDC 2241785: Experimental Crystal Structure Determination

description: Related Article: Raffaella Mancuso, Alex De Salvo, Patrizio Russo, Aurelia Falcicchio, Nicola Della Ca’, Leonardo Pantoja Munoz, Bartolo Gabriele|2023|Chin.J.Chem.|41|2801|doi:10.1002/cjoc.202300277
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.24504127
title: PMC-Patients Meta Data

description: <pre>## PMC-Patients Meta Data<br><br>Meta data for PMC-Patients that might facilitate reproduction or usage of our dataset, consisting of the following files (most of which can be derived from our main files above).<br><br>### PMIDs.json<br><br>PMIDs of articles from which PMC-Patients are extracted.<br>List of string, length 140,897.<br><br>### train_PMIDs.json & dev_PMIDs.json & test_PMIDs.json & human_PMIDs.json<br><br>PMIDs of articles in training / dev / test split.<br>List of string.<br><br>### train_patient_uids.json & dev_patient_uids.json & test_patient_uids.json & human_patient_uids.json<br><br>Patient_uids of notes in training / dev / test split.<br>List of string.<br><br>### patient2article_relevance.json<br><br>Full patient-to-article dataset.<br>A dict where the keys are `patient_uid` of queries and each entry is a list of `PMID`, representing articles relevant to the query.<br><br>The 3-point relevance can be obtained by checking whether the `PMID` is in `PMIDs.json`.<br><br>### patient2patient_similarity.json<br><br>Full patient-to-patient similarity dataset.<br>A dict where the keys are `patient_uid` of queries and each entry is a list of `patient_uid`, representing similar patients to the query.<br><br>The 3-point similarity can be obtained by checking whether the similar patient share the `PMID` (the string before '-' in `patient_uid`) with the query patient.<br><br><br>### PMID2Mesh.json<br><br>Dict of PMIDs to MeSH terms of the article.<br><br>### MeSH_Humans_patient_uids.json<br><br>`patient_uid` of the patients in PMC-Patients-Humans (extracted from articles with "Humans" MeSH term).<br>List of string.<br><br>### PMC-Patients_citations.json<br><br>Citations for all articles we used to collect our dataset.<br>A dict where the keys are `patient_uid` and each entry is the citation of the source article.<br><br>### human_PMIDs.json<br><br>PMIDs of the 500 randomly sampled articles for human evaluation.<br>List of string.<br><br>### PMC-Patients_human_eval.json<br><br>Expert annotation results of the 500 articles in `human_PMIDs.json`, including manually annotated patient note, demographics, and relations of the top 5 retrieved articles / patients.<br>List of dict, and the keys are almost identical to `PMC-Patients.json`, with the exception of `human_patient_id` and `human_patient_uid`.<br><br>The relational annotations are different from automatic ones. They are strings indicating on which dimension(s) are the patient-article / patient-patient pair relevant / similar. <br>"0", "1", "2", and "3" represent "Irrelevant", "Diagnosis", "Test", "Treatment" in ReCDS-PAR, and represent "Dissimilar", "Features", "Outcomes", "Exposure" in ReCDS-PPR.<br>Note that a pair can be relevant / similar on multiple dimensions at the same time.<br><br>### PAR_PMIDs.json<br><br>PMIDs of the 11.7M articles used as PAR corpus.<br>List of string.<br><br><br></pre>
DOI: 10.6084/m9.figshare.24504115
title: PMC-Patients Dataset

description: <pre>## PMC-Patients Dataset<br><br>The core file of our dataset, containing the patient summaries, demographics, and relational annotations.<br><br>### PMC-Patients.json<br>Patient summaries are presented as a `json` file, which is a list of dictionaries with the following keys:<br>- `patient_id`: string. A continuous id of patients, starting from 0.<br>- `patient_uid`: string. Unique ID for each patient, with format PMID-x, where PMID is the PubMed Identifier of source article of the note and x denotes index of the note in source article.<br>- `PMID`: string. PMID for source article.<br>- `file_path`: string. File path of xml file of source article.<br>- `title`: string. Source article title.<br>- `patient`: string. Patient note.<br>- `age`: list of tuples. Each entry is in format `(value, unit)` where value is a float number and unit is in 'year', 'month', 'week', 'day' and 'hour' indicating age unit. For example, `[[1.0, 'year'], [2.0, 'month']]` indicating the patient is a one-year- and two-month-old infant.<br>- `gender`: 'M' or 'F'. Male or Female.<br>- `relevant_articles`: dict. The key is PMID of the relevant articles and the corresponding value is its relevance score (2 or 1 as defined in the ``Methods'' section).<br>- `similar_patients`: dict. The key is patient_uid of the similar patients and the corresponding value is its similarity score (2 or 1 as defined in the ``Methods'' section).</pre>
DOI: 10.25318/3210047301-eng
title: Time spent grazing during winter and summer for beef farms, by most common type of beef

description: Agricultural operations grazing their cattle during the summer or winter, separated by most common beef type, and by province, available every 5 years.
DOI: 10.25318/3210047301-fra
title: Temps passé en pâturage en hiver et en été pour les fermes de bovins de boucherie, selon le type de bovin le plus commun

description: Opérations agricoles avec des bovins en pâturage durant l'été ou l'hiver, séparé selon le type de bovin le plus commun et la province, disponible tous les 5 ans.