cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.22578352
title: Supplementary Material for: The optimization of outpatient hemodialysis management for AKI-D patients: A quality improvement study

description: Introduction: In 2017, the Centers for Medicare and Medicaid Services allowed survivors of hospitalized acute kidney injury requiring dialysis (AKI-D) who were ambulatory and still dependent on hemodialysis (HD) to receive treatment in outpatient dialysis facilities. This policy change generated the ongoing need to improve AKI-D care in the outpatient setting. Methods: Quality improvement study in adult patients admitted to an outpatient HD unit with the diagnosis of AKI-D. We developed a protocol to manage these patients that included: a) multidisciplinary evaluations; b) personalized 3-tier HD prescription for dose/ultrafiltration rate and frequency; c) weekly assessment of kidney recovery; and d) patient empowerment. Patient- and protocol-specific characteristics were described. We analyzed hourly HD data and protocol adherence, and relevant hemodynamic data were compared according to HD-free survival at 90 days. Results: A total of 457.3 hours of HD from nine patients under the AKI-D protocol were interrogated. Three out of nine patients were alive and liberated from HD within the first 90 days of outpatient HD. Overall protocol adherence was 53.8% and did not differ by HD-free survival (54.5% vs. 53.7% in those that recovered vs. not). Protocol adherence was associated with fewer intradialytic hypotension events (peak to nadir BP, p&lt;0.01), while intradialytic hypotension (pre to post BP) occurred more frequently in patients who did not recover kidney function (p=0.009). Conclusion: We demonstrated the feasibility of implementing a management protocol for AKI-D patients in an outpatient dialysis facility. We found that fewer episodes of intradialytic hypotension occurred when the outpatient HD management was adherent to the protocol. The feasibility of this protocol should be confirmed in other facilities, and importantly, efficacy testing to evaluate its impact on AKI-D outpatient care is necessary.
DOI: 10.4121/ba236ea7-650c-4bde-859b-f6b08b5c22ac
title: Data underlying the publication: Spatial pattern recognition of local high temperature increases in mountain areas based on MODIS land surface temperature images

description: Finding out local high temperature increase (HTI) is significant for exploiting and conserving mountain climatic resources. We proposes an image pattern recognition method to identify the HTI zones by GIS and RS technologies, and used the method to produce HTI fileds, HTI strips and other auxiliary data of Yunnan Province, China. The research paper described the method and these data will be submit to the our objective SCI magazine. Therefore, this dataset contains all available data of our submission manuscript.
DOI: 10.4121/ba236ea7-650c-4bde-859b-f6b08b5c22ac.v2
title: Data underlying the publication: Spatial pattern recognition of local high temperature increases in mountain areas based on MODIS land surface temperature images

description: Finding out local high temperature increase (HTI) is significant for exploiting and conserving mountain climatic resources. We proposes an image pattern recognition method to identify the HTI zones by GIS and RS technologies, and used the method to produce HTI fileds, HTI strips and other auxiliary data of Yunnan Province, China. The research paper described the method and these data will be submit to the our objective SCI magazine. Therefore, this dataset contains all available data of our submission manuscript.
DOI: 10.6084/m9.figshare.22226344
title: Supplementary Material for: Evaluation of MicroRNAs expression pattern (miR-28, miR-181a, miR-34a, and miR-31) in Patients with COVID-19 Admitted to ICU, and Diabetic COVID-19 patients

description: Introduction: MicroRNAs, or miRNAs, with regulatory performance in inflammatory responses and infection are the prevalent manifestations of severe Coronavirus disease (COVID-19). This study aimed to evaluate whether PBMC miRNAs are diagnostic biomarkers to screen the ICU COVID-19 and diabetic-COVID-19 subjects. Methods: Candidate miRNAs were selected through previous studies, and then the PBMC levels of selected miRNAs (miR-28, miR-31, miR-34a, and miR-181a) were measured via quantitative reverse transcription PCR. The diagnostic value of miRNAs was determined by the receiver operating characteristic (ROC) curve. The bioinformatics analysis was utilized to predict the DEMs genes and relevant bio-functions. Results: The COVID-19 patients admitted to the ICU had significantly greater levels of selected miRNAs compared to non-hospitalized COVID-19 and healthy people. Besides, the mean miR-28 and miR-34a expression levels in the diabetic-COVID-19 group were upregulated considerably when compared with the non-diabetic COVID-19 group. ROC analyses demonstrated the role of miR-28, -miR-34a, and -181a as new biomarkers to discriminate the non-hospitalized COVID-19 group from the COVID-19 patients admitted to ICU samples, and also miR-34a can probably act as a useful biomarker for screening diabetic COVID-19 patients. Using bioinformatics analyses, we found the performance of target transcripts in many bio-processes and diverse metabolic routes such as regulating multiple inflammatory parameters. Discussion: The difference in miRNA expression patterns between the studied groups suggested that miR-28, miR-34a, and miR181a could be helpful as potent biomarkers for diagnosing and controlling COVID-19.
DOI: 10.6084/m9.figshare.22226344.v1
title: Supplementary Material for: Evaluation of MicroRNAs expression pattern (miR-28, miR-181a, miR-34a, and miR-31) in Patients with COVID-19 Admitted to ICU, and Diabetic COVID-19 patients

description: Introduction: MicroRNAs, or miRNAs, with regulatory performance in inflammatory responses and infection are the prevalent manifestations of severe Coronavirus disease (COVID-19). This study aimed to evaluate whether PBMC miRNAs are diagnostic biomarkers to screen the ICU COVID-19 and diabetic-COVID-19 subjects. Methods: Candidate miRNAs were selected through previous studies, and then the PBMC levels of selected miRNAs (miR-28, miR-31, miR-34a, and miR-181a) were measured via quantitative reverse transcription PCR. The diagnostic value of miRNAs was determined by the receiver operating characteristic (ROC) curve. The bioinformatics analysis was utilized to predict the DEMs genes and relevant bio-functions. Results: The COVID-19 patients admitted to the ICU had significantly greater levels of selected miRNAs compared to non-hospitalized COVID-19 and healthy people. Besides, the mean miR-28 and miR-34a expression levels in the diabetic-COVID-19 group were upregulated considerably when compared with the non-diabetic COVID-19 group. ROC analyses demonstrated the role of miR-28, -miR-34a, and -181a as new biomarkers to discriminate the non-hospitalized COVID-19 group from the COVID-19 patients admitted to ICU samples, and also miR-34a can probably act as a useful biomarker for screening diabetic COVID-19 patients. Using bioinformatics analyses, we found the performance of target transcripts in many bio-processes and diverse metabolic routes such as regulating multiple inflammatory parameters. Discussion: The difference in miRNA expression patterns between the studied groups suggested that miR-28, miR-34a, and miR181a could be helpful as potent biomarkers for diagnosing and controlling COVID-19.
DOI: 10.6084/m9.figshare.22067051.v1
title: Supplementary Material for: Impact of Intrahepatic External Beam Radiotherapy in Advanced Hepatocellular Carcinoma Patients Treated with Tyrosine Kinase Inhibitors

description: Introduction: We aimed to investigate whether concurrent use of intrahepatic external beam radiotherapy (EBRT) is a viable option for patients with advanced hepatocellular carcinoma (HCC) undergoing tyrosine kinase inhibitor (TKI) therapy. Methods: A total of 453 patients with Barcelona Clinic Liver Cancer-stage C (BCLC-C) HCC, who started first-line treatment with TKI with intrahepatic EBRT (TKI + RT, n = 97) or TKI without intrahepatic EBRT (TKI, n = 356) were analyzed. The overall survival (OS) and progression-free survival (PFS) were compared in the overall cohort, patients who received at least 8 weeks of TKI treatment, and a propensity score-matched cohort. Results: OS and PFS was better in those treated with TKI + RT than TKI (8.6 vs. 4.4 months and 4.5 vs. 2.3 months, respectively, with p &lt; 0.001). Of note, the TKI + RT group demonstrated significant longer time-to-intrahepatic tumor progression. In subgroup analysis, TKI + RT led to better OS than TKI in all subgroups and PFS was significantly improved in patients without extrahepatic metastasis, and those with portal vein invasion. There was no significant difference in treatment discontinuation due to adverse events between the TKI + RT and TKI groups (32.0% vs. 37.9%, p = 0.34). Furthermore, patients treated with TKI + RT showed better liver function preservation over time compared to TKI without intrahepatic EBRT. Comparable treatment outcomes were observed between patients who received at least 8 weeks of TKI treatment and the propensity-score matched cohort. Discussion/Conclusion: Concurrent intrahepatic EBRT targeting liver and/or macrovascular invasion can be a viable option to improve outcomes of BCLC-stage C patients receiving TKI therapy with an aim to control intrahepatic progression and preserving liver function.
DOI: 10.5281/zenodo.7997945
title: Tropical deforestation drivers 2008-2019, 1km, IIASA - accompanying file to https://doi.org/10.3389/fcosc.2022.830248

description: The zip file contains a map to support the publication 'A Continental Assessment of the Drivers of Tropical Deforestation With a Focus on Protected Areas', available at https://doi.org/10.3389/fcosc.2022.830248. This is a first version of the drivers of forest loss map, It is an allocation of crowdsourced data on predominant drivers of forest loss (data available here https://doi.org/10.1038/s41597-022-01227-3) to the Hansen et al (2013) dataset of global tree loss (v 1.7), set to a resolution of 1x1 km. Furthermore, the classes 'Other subsistence agriculture' and 'Shifting cultivation' are parts of the 'Subsistence agriculture' class on the original crowdsourced data, separated by extracting shifting agriculture according to Heinimann et al (2017). The map is in Goode Homolosine projection.
DOI: 10.5517/ccdc.csd.cc2b87kf
title: CCDC 2152874: Experimental Crystal Structure Determination

description: Related Article: Shuang Liu, Si-Rui Ding, Yu-Hu Niu, Pei-Jie Sun, Hao-Dong Qing, Lei-Lei Li, Wen-Zhen Wang|2022|J.Solid State Chem.|312|123169|doi:10.1016/j.jssc.2022.123169
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: 10.5281/zenodo.7997944
title: Tropical deforestation drivers 2008-2019, 1km, IIASA - accompanying file to https://doi.org/10.3389/fcosc.2022.830248

description: The zip file contains a map to support the publication 'A Continental Assessment of the Drivers of Tropical Deforestation With a Focus on Protected Areas', available at https://doi.org/10.3389/fcosc.2022.830248. This is a first version of the drivers of forest loss map, It is an allocation of crowdsourced data on predominant drivers of forest loss (data available here https://doi.org/10.1038/s41597-022-01227-3) to the Hansen et al (2013) dataset of global tree loss (v 1.7), set to a resolution of 1x1 km. Furthermore, the classes 'Other subsistence agriculture' and 'Shifting cultivation' are parts of the 'Subsistence agriculture' class on the original crowdsourced data, separated by extracting shifting agriculture according to Heinimann et al (2017). The map is in Goode Homolosine projection.
DOI: 10.5517/ccdc.csd.cc2b87lg
title: CCDC 2152875: Experimental Crystal Structure Determination

description: Related Article: Shuang Liu, Si-Rui Ding, Yu-Hu Niu, Pei-Jie Sun, Hao-Dong Qing, Lei-Lei Li, Wen-Zhen Wang|2022|J.Solid State Chem.|312|123169|doi:10.1016/j.jssc.2022.123169
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: 10.34740/kaggle/dsv/5831411
title: 2021 World Population (updated daily)
DOI: 10.34740/kaggle/dsv/5831414
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.5281/zenodo.7997885
title: Tropical deforestation drivers 2008-2019, 100m, IIASA - accompanying file to https://doi.org/10.3389/fcosc.2022.830248

description: The zip file contains the map used for the statistics calculated in the publication 'A Continental Assessment of the Drivers of Tropical Deforestation With a Focus on Protected Areas', available at https://doi.org/10.3389/fcosc.2022.830248. This is a first version of the drivers of forest loss map, It is an allocation of crowdsourced data on predominant drivers of forest loss (data available here https://doi.org/10.1038/s41597-022-01227-3) to the Hansen et al (2013) dataset of global tree loss (v 1.7), set to a resolution of 100x100 m. Furthermore, the classes 'Other subsistence agriculture' and 'Shifting cultivation' are parts of the 'Subsistence agriculture' class on the original crowdsourced data, separated by extracting shifting agriculture according to Heinimann et al (2017). The map is in Goode Homolosine projection.
DOI: 10.5281/zenodo.7997884
title: Tropical deforestation drivers 2008-2019, 100m, IIASA - accompanying file to https://doi.org/10.3389/fcosc.2022.830248

description: The zip file contains the map used for the statistics calculated in the publication 'A Continental Assessment of the Drivers of Tropical Deforestation With a Focus on Protected Areas', available at https://doi.org/10.3389/fcosc.2022.830248. This is a first version of the drivers of forest loss map, It is an allocation of crowdsourced data on predominant drivers of forest loss (data available here https://doi.org/10.1038/s41597-022-01227-3) to the Hansen et al (2013) dataset of global tree loss (v 1.7), set to a resolution of 100x100 m. Furthermore, the classes 'Other subsistence agriculture' and 'Shifting cultivation' are parts of the 'Subsistence agriculture' class on the original crowdsourced data, separated by extracting shifting agriculture according to Heinimann et al (2017). The map is in Goode Homolosine projection.
DOI: 10.5517/ccdc.csd.cc2f73f7
title: CCDC 2241158: Experimental Crystal Structure Determination

description: Related Article: Grzegorz Vetter, Agata Białońska, Aneta Jezierska, Jarosław J. Panek, Ewa Pacholska-Dudziak|2023|Chem.Commun.|59|6841|doi:10.1039/D3CC01367G
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.cc2f73g8
title: CCDC 2241159: Experimental Crystal Structure Determination

description: Related Article: Grzegorz Vetter, Agata Białońska, Aneta Jezierska, Jarosław J. Panek, Ewa Pacholska-Dudziak|2023|Chem.Commun.|59|6841|doi:10.1039/D3CC01367G
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.21502728
title: Vital Signs Dataset Acquired with a 5.8 GHz Continuous Wave Radar with Different Human Body Structure

description: The dataset herein presented consists of more than 7 hours of data acquired with a Continuous Wave (CW) radar operating at 5.8 GHz. It contains the respiratory signal of 92 healthy subjects measured according to a predefined protocol. The dataset is balanced in gender and age, encompassing a ranging from 18 to 50 years old. This dataset could be used to test and evaluate the algorithms’ performance using a wide population variety. Moreover, it can lead to a better studying and understanding of the different human body structure impact on the vital signs acquired by radar.
DOI: 10.5517/ccdc.csd.cc2ff647
title: CCDC 2247008: Experimental Crystal Structure Determination

description: Related Article: Freya M. Harvey, Alexandra H. Heidecker, Christian Merten, Thorsten Bach|2023|Org.Biomol.Chem.|21|4422|doi:10.1039/D3OB00598D
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.cc2ffytn
title: CCDC 2247742: Experimental Crystal Structure Determination

description: Related Article: Bodo Felsner, Volodymyr Bon, Christopher Bachetzky, Eike Brunner, Stefan Kaskel|2023|Inorg.Chem.Front.|10|3237|doi:10.1039/D3QI00480E
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.21502728.v1
title: Vital Signs Dataset Acquired with a 5.8 GHz Continuous Wave Radar with Different Human Body Structure

description: The dataset herein presented consists of more than 7 hours of data acquired with a Continuous Wave (CW) radar operating at 5.8 GHz. It contains the respiratory signal of 92 healthy subjects measured according to a predefined protocol. The dataset is balanced in gender and age, encompassing a ranging from 18 to 50 years old. This dataset could be used to test and evaluate the algorithms’ performance using a wide population variety. Moreover, it can lead to a better studying and understanding of the different human body structure impact on the vital signs acquired by radar.
DOI: 10.5281/zenodo.7404573
title: Dataset for: Estimating heating times in periodically driven quantum many-body systems via avoided crossing spectroscopy

description: The dataset includes data and Python scripts for all figures in the corresponding article. The data is organized into self-contained folders for each individual figure (possibly consisting of multiple subplots) and should be accessible using standard libraries for scientific Python. The included scripts can serve as a guide for accessing and plotting the data.
description: This work was supported by the Austrian Science Fund (FWF) within the DK-ALM: W1259-N27.
DOI: 10.5281/zenodo.4058927
title: Dataset for: Estimating heating times in periodically driven quantum many-body systems via avoided crossing spectroscopy

description: The dataset includes data and Python scripts for all figures in the corresponding article. The data is organized into self-contained folders for each individual figure (possibly consisting of multiple subplots) and should be accessible using standard libraries for scientific Python. The included scripts can serve as a guide for accessing and plotting the data.
description: This work was supported by the Austrian Science Fund (FWF) within the DK-ALM: W1259-N27.
DOI: 10.5281/zenodo.7997866
title: charmm2gmx: An Automated Method to Port the CHARMM Additive Force Field to GROMACS

description: Validation dataset for the paper "charmm2gmx: An Automated Method to Port the CHARMM Additive Force Field to GROMACS". The dataset includes molecular dynamics input and output files, as well as scripts for running the simulations and analyzing the results, used for validating the ported CHARMM parameters. CHARMM is one of the most widely used biomolecular force fields. Although developed in close connection with a dedicated molecular simulation engine of the same name, it is also usable with other codes. GROMACS is a well-established, highly optimized and multi-purpose software for molecular dynamics, versatile enough to accommodate many different force field potential functions and the associated algorithms. Due to conceptional differences related to software design and the large amount of numeric data inherent to residue topologies and parameter sets, conversion from one software format to another is not straightforward. Here, we present an automated and validated means to port the CHARMM force field to a format read by the GROMACS engine, harmonizing the different capabilities of the two codes in a self-documenting and reproducible way, with a bare minimum of user interaction required. Being based entirely on the upstream data files, the presented approach does not involve any hard-wired/boilerplate code, in contrast with previous attempts to solve the same problem. The heuristic approach used for perceiving local internal geometry is directly applicable for analogous transformations of other force fields.
DOI: 10.5281/zenodo.7997865
title: charmm2gmx: An Automated Method to Port the CHARMM Additive Force Field to GROMACS

description: Validation dataset for the paper "charmm2gmx: An Automated Method to Port the CHARMM Additive Force Field to GROMACS". The dataset includes molecular dynamics input and output files, as well as scripts for running the simulations and analyzing the results, used for validating the ported CHARMM parameters. CHARMM is one of the most widely used biomolecular force fields. Although developed in close connection with a dedicated molecular simulation engine of the same name, it is also usable with other codes. GROMACS is a well-established, highly optimized and multi-purpose software for molecular dynamics, versatile enough to accommodate many different force field potential functions and the associated algorithms. Due to conceptional differences related to software design and the large amount of numeric data inherent to residue topologies and parameter sets, conversion from one software format to another is not straightforward. Here, we present an automated and validated means to port the CHARMM force field to a format read by the GROMACS engine, harmonizing the different capabilities of the two codes in a self-documenting and reproducible way, with a bare minimum of user interaction required. Being based entirely on the upstream data files, the presented approach does not involve any hard-wired/boilerplate code, in contrast with previous attempts to solve the same problem. The heuristic approach used for perceiving local internal geometry is directly applicable for analogous transformations of other force fields.