cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10706423
title: Longitudinal Analysis of Pole Dance Training Impact on Women's Body Composition and Muscular Strengt

description: The provided database is a rich dataset derived from a 20-week longitudinal study examining the effects of pole dance training on women's body composition and muscular strength. The dataset includes pre- and post-intervention measurements of various physical health parameters such as body mass index (BMI), fat percentage (FATP), muscle mass (PMM), and hand grip strength (both left and right). Participant anonymity has been preserved by using identification codes instead of personal information.

This database is a valuable resource for researchers interested in the quantitative effects of alternative fitness programs on women's health. It provides empirical evidence supporting the role of pole dance as a multifaceted physical activity beneficial for improving muscle strength and body composition.

The dataset can facilitate further research in sports science, public health, and exercise physiology. By making this data openly available, we aim to contribute to the growing body of knowledge on the health impacts of pole dance and encourage the development of diverse fitness practices that promote well-being.
DOI: 10.5281/zenodo.10706424
title: Longitudinal Analysis of Pole Dance Training Impact on Women's Body Composition and Muscular Strengt

description: The provided database is a rich dataset derived from a 20-week longitudinal study examining the effects of pole dance training on women's body composition and muscular strength. The dataset includes pre- and post-intervention measurements of various physical health parameters such as body mass index (BMI), fat percentage (FATP), muscle mass (PMM), and hand grip strength (both left and right). Participant anonymity has been preserved by using identification codes instead of personal information.

This database is a valuable resource for researchers interested in the quantitative effects of alternative fitness programs on women's health. It provides empirical evidence supporting the role of pole dance as a multifaceted physical activity beneficial for improving muscle strength and body composition.

The dataset can facilitate further research in sports science, public health, and exercise physiology. By making this data openly available, we aim to contribute to the growing body of knowledge on the health impacts of pole dance and encourage the development of diverse fitness practices that promote well-being.
DOI: 10.5281/zenodo.10706635
title: Spotter_I

description: Microspotter, Spotter I
DOI: 10.5281/zenodo.10706636
title: Spotter_I

description: Microspotter, Spotter I
DOI: 10.6084/m9.figshare.24548152
title: Additional file 1 of Comparison of temporary external and percutaneous k-wire fixations for treatment of ankle fracture–dislocations

description: Additional file 1.
DOI: 10.6084/m9.figshare.24548152.v1
title: Additional file 1 of Comparison of temporary external and percutaneous k-wire fixations for treatment of ankle fracture–dislocations

description: Additional file 1.
DOI: 10.35003/rxra3s
title: Globally findable planetary data: The interdisciplinary TR170-DB Repository

description: The TRR170-DB data repository (https://planetary-data-portal.org/) manages interdisciplinary research data from the collaborative research center ‘Late Accretion onto Terrestrial Planets’ (TRR 170). The repository provides access to TRR 170 data and planetary science data from other research institutions to researchers. Data in the repository reflect the different methods and approaches applied to investigate planet formation processes, including astromaterials data, experimental studies, remote sensing data, and geophysical modeling data. TRR170-DB aligns its data policy and practice to Open Science (https://www.dfg.de/en/research_funding/programmes/nfdi/index.html) and the FAIR principles (Wilkinson et al., https://doi.org/10.1038/sdata.2016.18). TRR170-DB accepts only research data in digital formats. Data are stored in open electronic formats such as csv (tables), pdf (text), and jpeg and tiff (images). At present, the majority of datasets were provided by TRR 170 authors and are replication data of peer-reviewed articles which appeared in international journals since 2016. These replication datasets are freely available via a digital object identifier (DOI) provided by DataCite (https://datacite.org/). Metadata describe the research data to make it easier to find and to use. The research data are licensed with the Creative Commons license CC0 1.0 to ensure secure public domain use. Recently, the global findability of TRR170-DB’s research data has been increased by mapping its metadata content to Freie Universität Berlin’s electronic library system ‘Refubium’. Refubium offers seamless integration of our published data to be discovered and accessed via internet search machines and a wide range of other interlinked academic libraries and global information services. As such the TRR170-DB repository and its data will remain accessible for the global planetary community on the long-term while providing the setting that amplifies the use of best practices and collaborative and interdisciplinary research work.
DOI: 10.15468/jpf36a
title: Red list of flora and fauna of Chernihiv region of Ukraine

description: The checklist consists of species of animals and plants that are rare or endangered in the territory of the Chernihiv region of Ukraine. The checklist was implemented by the decision of the twelfth session of the Chernihiv Regional Council of the seventh convocation on March 28, 2018 No. 32-12/VII.
DOI: 10.6084/m9.figshare.14062423
title: A Comparison of FIML- versus Multiple-imputation-based methods to test measurement invariance with incomplete ordinal variables

description: To ensure meaningful comparison of test scores across groups or time, measurement invariance (i.e., invariance of the general factor structure and the values of the measurement parameters) across groups or time must be examined. However, many empirical examinations of measurement invariance of psychological/educational questionnaires need to address two issues: Using the appropriate model for ordinal variables (e.g., Likert scale items), and handling missing data. In two Monte Carlo simulations, this study examined the performance of one full-information-maximum-likelihood-based method and five multiple-imputation-based methods to obtain tests of measurement invariance across groups for ordinal variables that have missing data. Our results indicate that the full-information-maximum-likelihood-based method and one of the multiple-imputation-based methods generally have better performance than the other examined methods, though they also have their own limitations.
DOI: 10.35003/bvknan
title: Replication Data for: The Loongana (CL) group of carbonaceous chondrites

description: A coordinated study of the petrology, mineral chemistry, and bulk chemical and isotopic composition of the five ungrouped carbonaceous chondrites Coolidge, Loongana 001, Los Vientos (LoV) 051, Northwest Africa (NWA) 033, and NWA 13400 reveals that these meteorites have a similar set of properties that distinguishes them from the other carbonaceous chondrite groups and allows definition of the new Loongana (CL) group of carbonaceous chondrites.
DOI: 10.6084/m9.figshare.14062423.v1
title: A Comparison of FIML- versus Multiple-imputation-based methods to test measurement invariance with incomplete ordinal variables

description: To ensure meaningful comparison of test scores across groups or time, measurement invariance (i.e., invariance of the general factor structure and the values of the measurement parameters) across groups or time must be examined. However, many empirical examinations of measurement invariance of psychological/educational questionnaires need to address two issues: Using the appropriate model for ordinal variables (e.g., Likert scale items), and handling missing data. In two Monte Carlo simulations, this study examined the performance of one full-information-maximum-likelihood-based method and five multiple-imputation-based methods to obtain tests of measurement invariance across groups for ordinal variables that have missing data. Our results indicate that the full-information-maximum-likelihood-based method and one of the multiple-imputation-based methods generally have better performance than the other examined methods, though they also have their own limitations.
DOI: 10.6084/m9.figshare.6722489
title: Additional file 5: of Single SNP- and pathway-based genome-wide association studies for beak deformity in chickens using high-density 600K SNP arrays

description: Table S1. Raw results of the single SNP-based association study. (XLSX 21782 kb)
DOI: 10.6084/m9.figshare.6722489.v1
title: Additional file 5: of Single SNP- and pathway-based genome-wide association studies for beak deformity in chickens using high-density 600K SNP arrays

description: Table S1. Raw results of the single SNP-based association study. (XLSX 21782 kb)
DOI: 10.6084/m9.figshare.6722501
title: Additional file 6: of Single SNP- and pathway-based genome-wide association studies for beak deformity in chickens using high-density 600K SNP arrays

description: Table S2. Single SNP-based association analysis of the selected SNPs used in the pathway-based association study. (XLSX 5391 kb)
DOI: 10.6084/m9.figshare.6722501.v1
title: Additional file 6: of Single SNP- and pathway-based genome-wide association studies for beak deformity in chickens using high-density 600K SNP arrays

description: Table S2. Single SNP-based association analysis of the selected SNPs used in the pathway-based association study. (XLSX 5391 kb)
DOI: 10.6084/m9.figshare.6722516
title: Additional file 7: of Single SNP- and pathway-based genome-wide association studies for beak deformity in chickens using high-density 600K SNP arrays

description: Table S3. The detailed information of each pathway based on the pathway-based association analysis. (XLSX 15 kb)
DOI: 10.6084/m9.figshare.6722516.v1
title: Additional file 7: of Single SNP- and pathway-based genome-wide association studies for beak deformity in chickens using high-density 600K SNP arrays

description: Table S3. The detailed information of each pathway based on the pathway-based association analysis. (XLSX 15 kb)
DOI: 10.6084/m9.figshare.6722531
title: Additional file 8: of Single SNP- and pathway-based genome-wide association studies for beak deformity in chickens using high-density 600K SNP arrays

description: Table S4. The detailed lists of all the chicken pathways used in the pathway-based association analysis. (XLSX 14 kb)
DOI: 10.6084/m9.figshare.6722531.v1
title: Additional file 8: of Single SNP- and pathway-based genome-wide association studies for beak deformity in chickens using high-density 600K SNP arrays

description: Table S4. The detailed lists of all the chicken pathways used in the pathway-based association analysis. (XLSX 14 kb)
DOI: 10.6084/m9.figshare.6722546
title: Additional file 9: of Single SNP- and pathway-based genome-wide association studies for beak deformity in chickens using high-density 600K SNP arrays

description: Table S5. The detailed lists of pathways and SNPs information used in the pathway-based association analysis. (XLSX 3841 kb)
DOI: 10.6084/m9.figshare.6722546.v1
title: Additional file 9: of Single SNP- and pathway-based genome-wide association studies for beak deformity in chickens using high-density 600K SNP arrays

description: Table S5. The detailed lists of pathways and SNPs information used in the pathway-based association analysis. (XLSX 3841 kb)
DOI: 10.6084/m9.figshare.9776870
title: Additional file 5: of The stereoisomeric Bacillus subtilis HN09 metabolite 3,4-dihydroxy-3-methyl-2-pentanone induces disease resistance in Arabidopsis via different signalling pathways

description: Dataset S2. Enriched GO terms from the B16, B17 and JA treatment sets of DEGs. (XLSX 29 kb)
DOI: 10.6084/m9.figshare.9776870.v1
title: Additional file 5: of The stereoisomeric Bacillus subtilis HN09 metabolite 3,4-dihydroxy-3-methyl-2-pentanone induces disease resistance in Arabidopsis via different signalling pathways

description: Dataset S2. Enriched GO terms from the B16, B17 and JA treatment sets of DEGs. (XLSX 29 kb)
DOI: 10.6084/m9.figshare.13014165
title: High-Dimensional Precision Medicine From Patient-Derived Xenografts

description: The complexity of human cancer often results in significant heterogeneity in response to treatment. Precision medicine offers the potential to improve patient outcomes by leveraging this heterogeneity. Individualized treatment rules (ITRs) formalize precision medicine as maps from the patient covariate space into the space of allowable treatments. The optimal ITR is that which maximizes the mean of a clinical outcome in a population of interest. Patient-derived xenograft (PDX) studies permit the evaluation of multiple treatments within a single tumor, and thus are ideally suited for estimating optimal ITRs. PDX data are characterized by correlated outcomes, a high-dimensional feature space, and a large number of treatments. Here we explore machine learning methods for estimating optimal ITRs from PDX data. We analyze data from a large PDX study to identify biomarkers that are informative for developing personalized treatment recommendations in multiple cancers. We estimate optimal ITRs using regression-based (Q-learning) and direct-search methods (outcome weighted learning). Finally, we implement a superlearner approach to combine multiple estimated ITRs and show that the resulting ITR performs better than any of the input ITRs, mitigating uncertainty regarding user choice. Our results indicate that PDX data are a valuable resource for developing individualized treatment strategies in oncology. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.13014165.v1
title: High dimensional precision medicine from patient-derived xenografts

description: The complexity of human cancer often results in significant heterogeneity in response to treatment. Precision medicine offers the potential to improve patient outcomes by leveraging this heterogeneity. Individualized Treatment Rules (ITRs) formalize precision medicine as maps from the patient covariate space into the space of allowable treatments. The optimal ITR is that which maximizes the mean of a clinical outcome in a population of interest. Patient-derived xenograft (PDX) studies permit the evaluation of multiple treatments within a single tumor, and thus are ideally suited for estimating optimal ITRs. PDX data are characterized by correlated outcomes, a high-dimensional feature space, and a large number of treatments. Here we explore machine learning methods for estimating optimal ITRs from PDX data. We analyze data from a large PDX study to identify biomarkers that are informative for developing personalized treatment recommendations in multiple cancers. We estimate optimal ITRs using regression-based (Q-learning) and direct-search methods (Outcome Weighted Learning). Finally, we implement a superlearner approach to combine multiple estimated ITRs and show that the resulting ITR performs better than any of the input ITRs, mitigating uncertainty regarding user choice. Our results indicate that PDX data are a valuable resource for developing individualized treatment strategies in oncology.
DOI: 10.6084/m9.figshare.13014165.v2
title: High-Dimensional Precision Medicine From Patient-Derived Xenografts

description: The complexity of human cancer often results in significant heterogeneity in response to treatment. Precision medicine offers the potential to improve patient outcomes by leveraging this heterogeneity. Individualized treatment rules (ITRs) formalize precision medicine as maps from the patient covariate space into the space of allowable treatments. The optimal ITR is that which maximizes the mean of a clinical outcome in a population of interest. Patient-derived xenograft (PDX) studies permit the evaluation of multiple treatments within a single tumor, and thus are ideally suited for estimating optimal ITRs. PDX data are characterized by correlated outcomes, a high-dimensional feature space, and a large number of treatments. Here we explore machine learning methods for estimating optimal ITRs from PDX data. We analyze data from a large PDX study to identify biomarkers that are informative for developing personalized treatment recommendations in multiple cancers. We estimate optimal ITRs using regression-based (Q-learning) and direct-search methods (outcome weighted learning). Finally, we implement a superlearner approach to combine multiple estimated ITRs and show that the resulting ITR performs better than any of the input ITRs, mitigating uncertainty regarding user choice. Our results indicate that PDX data are a valuable resource for developing individualized treatment strategies in oncology. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.25272958
title: A yearly gapless 1 km resolution XCO<sub>2</sub> dataset for China

description: This is the yearly gapless column-averaged CO<sub>2</sub> dry air mole fractions (XCO<sub>2</sub>) dataset in China from 2012 to 2019. Due to the satellite revisit period and the limitation of sampling window, the continuous XCO<sub>2</sub> data in space is mostly coarse. Long-term data with high spatial resolution (e.g., 1 × 1 km/ yearly) on CO<sub>2</sub> concentration are always unavailable. We proposed a novel model from the perspective of spatial heterogeneity to reconstruct a fine-resolution (1 km ×1 km) XCO<sub>2</sub> data in China from year of 2012 to 2019 based on the existing Global 1° land mapping XCO<sub>2</sub>.
DOI: 10.6084/m9.figshare.13014299
title: A dataset of remote-sensed Forel-Ule Index for global inland waters during 2000–2018

description: We present the
first time series FUI dataset for large global lakes
from 2000–2018 based on MODIS observations. This dataset provides
significant information on spatial and temporal changes of water colour for global large lakes during the past 19 years. It will be valuable to studies in search of
the drivers of global and regional lake colour
change, and the interaction mechanisms between water colour, hydrological
factors, climate change, and anthropogenic activities.
DOI: 10.5517/ccdc.csd.cc2d03l4
title: CCDC 2204645: Experimental Crystal Structure Determination

description: Related Article: Simin Sheybani, Muhammad Abbas, Hamid R. Firouzi, Zhifeng Xiao, Hong-Cai Zhou, Kenneth J. Balkus, Jr|2023|Inorg.Chem.|62|4314|doi:10.1021/acs.inorgchem.2c04470
description: Related Article: Kenneth J. Balkus, Marie L. Mortensen, Simin Sheybani, Juan P. Vizuet|2023|U.S.Patents|||
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.cc2d03m5
title: CCDC 2204646: Experimental Crystal Structure Determination

description: Related Article: Simin Sheybani, Muhammad Abbas, Hamid R. Firouzi, Zhifeng Xiao, Hong-Cai Zhou, Kenneth J. Balkus, Jr|2023|Inorg.Chem.|62|4314|doi:10.1021/acs.inorgchem.2c04470
description: Related Article: Kenneth J. Balkus, Marie L. Mortensen, Simin Sheybani, Juan P. Vizuet|2023|U.S.Patents|||
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.cc2gp4p0
title: CCDC 2284442: Experimental Crystal Structure Determination

description: Related Article: Hannah B. Wineinger, Benjamin Scheibe, Jacob P. Brannon, Todd N. Poe, Brian M. Rotermund, Joseph M. Sperling, Thomas E. Albrecht-Schönzart|2024|Cryst.Growth Des.|24|1544|doi:10.1021/acs.cgd.3c00878
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.cc2gp4q1
title: CCDC 2284443: Experimental Crystal Structure Determination

description: Related Article: Hannah B. Wineinger, Benjamin Scheibe, Jacob P. Brannon, Todd N. Poe, Brian M. Rotermund, Joseph M. Sperling, Thomas E. Albrecht-Schönzart|2024|Cryst.Growth Des.|24|1544|doi:10.1021/acs.cgd.3c00878
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.6722864
title: MiR-146a promotes the asymmetric division and inhibits the self-renewal ability of breast cancer stem-like cells via indirect upregulation of Let-7

description: MiR-146a could stimulate tumor growth or block tumor proliferation in systemic malignancies, referring to the specific downstream targeted gene. However, its roles in breast cancer stem-like cells (BrCSCs) are barely known. To dig out its mechanistic functions, we explored the indicative roles of miR-146 in preclinical study, regardless of the hormone receptor status, and the positive correlation between miR-146 and better prognosis was proved, as its correlation to Let-7c was. To uncover the implicated mechanisms, we first identified the suppressive role of miR-146a in stem cells’ renewal, which was achieved by promoting the asymmetric division of BrCSCs. Let-7c was previously revealed with its suppressive functions in stem-like cells expansion, and miR-146 was predicated and successfully proved to bind to and degrade the 3’UTR of LIN28, a maturation blocker of Let-7 family. Results further showed that miR-146a increased the Let-7c level through degrading LIN28, and LIN28 inhibition is required for miR-146a induction of asymmetric stem cells’ division. Moreover, Let-7 controlled Wnt signaling pathway activity could be strengthened due to the miR146 inhibition of H19, later of which was often activated in stem cells group with functional existence of Wnt signaling. H19 itself in turn formed the positive feedback regulation with Let-7. Our results suggested the miR-146a/LIN28/Wnt signaling circle in restraining the symmetric cells division, which was specifically referred to the controlling of the small circle of Let-7c and H19, and together, this dual axis could help to prohibit the stem cells expansion.