cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.3511077
title: The Emerging Role of Tyrosine Kinase Inhibitors in Ovarian Cancer Treatment: A Systematic Review

description: The present systematic review summarizes current evidence regarding the mechanisms of action, the efficacy, and the adverse effects of tyrosine kinase inhibitors (TKIs) in ovarian cancer patients. Phase II and III clinical trials were sought in the PubMed database and in the Clinical Trials.gov registry through September 30, 2015. Seventy-five clinical trials regarding TKIs targeting mainly vascular endothelial growth factor receptor, epidermal growth factor receptor, platelet-derived growth factor receptor, and sarcoma tyrosine kinase (Src) were yielded. The most promising results were noted with cediranib, nintedanib, and pazopanib. However, drawing universal conclusions about the potential integration of TKIs in ovarian cancer therapy remains elusive. Furthermore, emerging challenges and directions for the future research are critically discussed.
DOI: 10.6084/m9.figshare.3511077.v1
title: The Emerging Role of Tyrosine Kinase Inhibitors in Ovarian Cancer Treatment: A Systematic Review

description: The present systematic review summarizes current evidence regarding the mechanisms of action, the efficacy, and the adverse effects of tyrosine kinase inhibitors (TKIs) in ovarian cancer patients. Phase II and III clinical trials were sought in the PubMed database and in the Clinical Trials.gov registry through September 30, 2015. Seventy-five clinical trials regarding TKIs targeting mainly vascular endothelial growth factor receptor, epidermal growth factor receptor, platelet-derived growth factor receptor, and sarcoma tyrosine kinase (Src) were yielded. The most promising results were noted with cediranib, nintedanib, and pazopanib. However, drawing universal conclusions about the potential integration of TKIs in ovarian cancer therapy remains elusive. Furthermore, emerging challenges and directions for the future research are critically discussed.
DOI: 10.6084/m9.figshare.3511074
title: Epigenetic and transcriptional regulation of autophagy

description: Macroautophagy (hereafter referred to as autophagy) is an essential self-digestion process to maintain homeostasis and promote survival in response to starvation. Although the components of autophagy in the cytoplasm have been well studied, little has been known about the fine-tuning mechanism of autophagy through epigenetic regulations. Recently, we identified the histone arginine methyltransferase CARM1 as a new component and followed histone H3R17 dimethylation as a critical epigenetic mark in starvation-induced autophagy. Upon nutrient starvation, CARM1 is stabilized in the nucleus, but not in the cytoplasm, whereas it is constantly degraded under nutrient-rich conditions by the SKP2-containing SCF (SKP1-CUL1-F-box protein) E3 ubiquitin ligase. We further showed that nutrient starvation induces the protein levels and activity of AMPK in the nucleus. Activated AMPK then phosphorylates FOXO3, leading to SKP2 downregulation and increased CARM1 protein levels in the nucleus. Stabilized CARM1 in turn functions as an essential co-activator of TFEB and regulates the expression of autophagy and lysosomal genes. Our findings provide a conceptual advance that activation of specific epigenetic programs is indispensable for a sustained autophagic response, and shed light on a potential therapeutic targeting of the newly identified AMPK-SKP2-CARM1 signaling axis in autophagy-related diseases.
DOI: 10.6084/m9.figshare.3511074.v2
title: Epigenetic and transcriptional regulation of autophagy

description: Macroautophagy (hereafter referred to as autophagy) is an essential self-digestion process to maintain homeostasis and promote survival in response to starvation. Although the components of autophagy in the cytoplasm have been well studied, little has been known about the fine-tuning mechanism of autophagy through epigenetic regulations. Recently, we identified the histone arginine methyltransferase CARM1 as a new component and followed histone H3R17 dimethylation as a critical epigenetic mark in starvation-induced autophagy. Upon nutrient starvation, CARM1 is stabilized in the nucleus, but not in the cytoplasm, whereas it is constantly degraded under nutrient-rich conditions by the SKP2-containing SCF (SKP1-CUL1-F-box protein) E3 ubiquitin ligase. We further showed that nutrient starvation induces the protein levels and activity of AMPK in the nucleus. Activated AMPK then phosphorylates FOXO3, leading to SKP2 downregulation and increased CARM1 protein levels in the nucleus. Stabilized CARM1 in turn functions as an essential co-activator of TFEB and regulates the expression of autophagy and lysosomal genes. Our findings provide a conceptual advance that activation of specific epigenetic programs is indispensable for a sustained autophagic response, and shed light on a potential therapeutic targeting of the newly identified AMPK-SKP2-CARM1 signaling axis in autophagy-related diseases.
DOI: 10.6084/m9.figshare.3511074.v1
title: Epigenetic and Transcriptional Regulation of Autophagy

description: Macroautophagy (hereafter referred to as autophagy) is an essential self-digestion process to maintain homeostasis and promote survival in response to starvation. Although the components of autophagy in the cytoplasm have been well-studied, little has been known about the fine-tuning mechanism of autophagy through epigenetic regulations. Recently, we identified the histone arginine methyltransferase CARM1 as a new component and followed histone H3R17 dimethylation as a critical epigenetic mark in starvation-induced autophagy. Upon nutrient starvation, CARM1 is stabilized in the nucleus, but not in the cytoplasm, whereas it is constantly degraded under nutrient-rich conditions by the SKP2-containing SCF (SKP1-CUL1-F-box protein) E3 ubiquitin ligase. We further showed that nutrient starvation induces the proteins levels and activity of AMPK in the nucleus. Activated AMPK then phosphorylates FOXO3, leading to SKP2 downregulation and increased CARM1 protein levels in the nucleus. Stabilized CARM1 in turn functions as an essential co-activator of TFEB and regulates the expression of autophagy and lysosomal genes. Our findings provide a conceptual advance that activation of specific epigenetic programs is indispensable for a sustained autophagic response, and shed light on a potential therapeutic targeting of the newly identified AMPK-SKP2-CARM1 signaling axis in autophagy-related diseases.
DOI: 10.6084/m9.figshare.3511053
title: The Structural Architecture of an Infectious Mammalian Prion using Electron Cryomicroscopy

description: Raw data for the single particle analysis of GPI-anchorless PrP 27-30 amyloid fibrils.This is the data set for the reference-free analysis. The files can be read with the image processing packages EMAN, IMAGIC, and RELION.
DOI: 10.6084/m9.figshare.3511051
title: The Structural Architecture of an Infectious Mammalian Prion using Electron Cryomicroscopy

description: Raw data for the single particle analysis of GPI-anchorless PrP 27-30 amyloid fibrils.This is the data set for the analysis that uses a reference for the alignment and classification process. The files can be read with the image processing packages EMAN, IMAGIC, and RELION.<br>
DOI: 10.6084/m9.figshare.3511051.v1
title: The Structural Architecture of an Infectious Mammalian Prion using Electron Cryomicroscopy

description: Raw data for the single particle analysis of GPI-anchorless PrP 27-30 amyloid fibrils.This is the data set for the analysis that uses a reference for the alignment and classification process. The files can be read with the image processing packages EMAN, IMAGIC, and RELION.<br>
DOI: 10.6084/m9.figshare.3511036
title: Visualization of the diffusion of digital mammography, New York State, 2004-2012

description: A zipped collection of .png files containing smoothed maps of the percentage of mammograms captured digitally in New York State from 2004-2012. Over this period, the percentage of digital mammograms rose from about 5% to about 95%. The maps show 12-month trailing averages, for a total of 97 maps. The maps were constructed in R and the code was written such that substituting alternative medical procedures or geographic locations would not be difficult.<br>Update, February 2017: In response to a reviewer's suggestion, the maps now include both screening and diagnostic mammograms, rather than just screening mammograms.The differences in the maps are negligible.
DOI: 10.6084/m9.figshare.3511036.v2
title: Visualization of the diffusion of digital mammography, New York State, 2004-2012

description: A zipped collection of .png files containing smoothed maps of the percentage of mammograms captured digitally in New York State from 2004-2012. Over this period, the percentage of digital mammograms rose from about 5% to about 95%. The maps show 12-month trailing averages, for a total of 97 maps. The maps were constructed in R and the code was written such that substituting alternative medical procedures or geographic locations would not be difficult.<br>Update, February 2017: In response to a reviewer's suggestion, the maps now include both screening and diagnostic mammograms, rather than just screening mammograms.The differences in the maps are negligible.
DOI: 10.6084/m9.figshare.3511028
title: TBC1D20 mediates autophagy as a key regulator of autophagosome maturation

description: In humans, loss of TBC1D20 (TBC1 domain family, member 20) protein function causes Warburg Micro syndrome 4 (WARBM4), an autosomal recessive disorder characterized by congenital eye, brain, and genital abnormalities. TBC1D20-deficient mice exhibit ocular abnormalities and male infertility. TBC1D20 is a ubiquitously expressed member of the family of GTPase-activating proteins (GAPs) that increase the intrinsically slow GTP-hydrolysis rate of small RAB-GTPases when bound to GTP. Biochemical studies have established TBC1D20 as a GAP for RAB1B and RAB2A. However, the cellular role of TBC1D20 still remains elusive, and there is little information about how the functional loss of TBC1D20 causes clinical manifestations in WARBM4-affected children. Here we evaluate the role of TBC1D20 in cells carrying a null mutant allele, as well as TBC1D20-deficient mice, which display eye and testicular abnormalities. We demonstrate that TBC1D20, via its RAB1B GAP function, is a key regulator of autophagosome maturation, a process required for maintenance of autophagic flux and degradation of autophagic cargo. Our results provide evidence that TBC1D20-mediated autophagosome maturation maintains lens transparency by mediating the removal of damaged proteins and organelles from lens fiber cells. Additionally, our results show that in the testes TBC1D20-mediated maturation of autophagosomes is required for autophagic flux, but is also required for the formation of acrosomes. Furthermore TBC1D20-deficient mice, while not mimicking severe developmental brain abnormalities identified in WARBM4 affected children, display disrupted neuronal autophagic flux resulting in adult-onset motor dysfunction. In summary, we show that TBC1D20 has an essential role in the maturation of autophagosomes and a defect in TBC1D20 function results in eye, testicular, and neuronal abnormalities in mice implicating disrupted autophagy as a mechanism that contributes to WARBM4 pathogenesis.
DOI: 10.6084/m9.figshare.12917126
title: temp_timeseries_box.mat

description: temp_timeseries_box.mat is the weekly time series of NCEP1 surface temperature over the 13 boxed regions of interest spanning from 2006 to 2015.
DOI: 10.6084/m9.figshare.12917126.v2
title: temp_timeseries_box.mat

description: temp_timeseries_box.mat is the weekly time series of NCEP1 surface temperature over the 13 boxed regions of interest spanning from 2006 to 2015.
DOI: 10.6084/m9.figshare.12917126.v1
title: Untitled Item

description: temp_timeseries_box.mat
DOI: 10.6084/m9.figshare.3511024
title: MrPUP (Medicare Referring Provider Utilization for Procedures)

description: The Medicare Referring Provider Utilization for Procedures (MrPUP) dataset details the healthcare procedures that Medicare providers referred in the outpatient setting in 2014, and is particularly useful in understanding how specific doctors use blood tests, CT scans, and MRIs to diagnose patients.The dataset is available at https://careset.com/datasets/
DOI: 10.6084/m9.figshare.3511024.v2
title: MrPUP (Medicare Referring Provider Utilization for Procedures)

description: The Medicare Referring Provider Utilization for Procedures (MrPUP) dataset details the healthcare procedures that Medicare providers referred in the outpatient setting in 2014, and is particularly useful in understanding how specific doctors use blood tests, CT scans, and MRIs to diagnose patients.The dataset is available at https://careset.com/datasets/
DOI: 10.6084/m9.figshare.3511024.v1
title: MrPUP (Medicare Referring Provider Utilization for Procedures)

description: The Medicare Referring Provider Utilization for Procedures (MrPUP) dataset details the healthcare procedures that Medicare providers referred in the outpatient setting in 2014, and is particularly useful in understanding how specific doctors use blood tests, CT scans, and MRIs to diagnose patients.The dataset is available at https://careset.com/datasets/
DOI: 10.6084/m9.figshare.3510756
title: Transformative Learning Networks: insights from four case studies

description: Paper presented at the 60th annual meeting of the International Society for the Systems Sciences, July 28, 2016 in Boulder, Colorado.<br>In this paper, we consider how learning networks build capacity for system transformation. We define learning networks as inter-organizational voluntary collaboratives that nurture professional expertise, and describe their potential to catalyze systemic change by disrupting old habits, fostering new relationships, and providing freedom to experiment. We underscore the complexity of designing, facilitating, and sustaining learning networks, noting four distinct ways learning networks can foster systemic resilience, 1) social-psychological 2) engineering 3) social-ecological, and 4) emancipatory. We then describe our research methods and introduce four learning network case study analyses, in order of their age and relative progress towards transformation:<br>• National Alliance for Broader Impacts (NABI)• 100 Resilient Cities Network (100RC)• Fire Adapted Community Learning Network (FACNet)• START (Global Change SysTem for Analysis, Research & Training)<br>After describing each network’s origins, approach to promoting transformative change, and structure, we apply three exploratory questions across our cases:<br>• How do network facilitators “netweave” within and across participating sites?• Is there evidence of organizational learning taking place in each network over time?• What transformative capacity do we see developing in each network?<br>We conclude by describing the contribution of this analysis to a framework we are developing to explore how learning networks foster resilience within, between, and across scales.<br>
DOI: 10.6084/m9.figshare.3510756.v1
title: Transformative Learning Networks: insights from four case studies

description: Paper presented at the 60th annual meeting of the International Society for the Systems Sciences, July 28, 2016 in Boulder, Colorado.<br>In this paper, we consider how learning networks build capacity for system transformation. We define learning networks as inter-organizational voluntary collaboratives that nurture professional expertise, and describe their potential to catalyze systemic change by disrupting old habits, fostering new relationships, and providing freedom to experiment. We underscore the complexity of designing, facilitating, and sustaining learning networks, noting four distinct ways learning networks can foster systemic resilience, 1) social-psychological 2) engineering 3) social-ecological, and 4) emancipatory. We then describe our research methods and introduce four learning network case study analyses, in order of their age and relative progress towards transformation:<br>• National Alliance for Broader Impacts (NABI)• 100 Resilient Cities Network (100RC)• Fire Adapted Community Learning Network (FACNet)• START (Global Change SysTem for Analysis, Research & Training)<br>After describing each network’s origins, approach to promoting transformative change, and structure, we apply three exploratory questions across our cases:<br>• How do network facilitators “netweave” within and across participating sites?• Is there evidence of organizational learning taking place in each network over time?• What transformative capacity do we see developing in each network?<br>We conclude by describing the contribution of this analysis to a framework we are developing to explore how learning networks foster resilience within, between, and across scales.<br>
DOI: 10.6084/m9.figshare.3510448
title: Appendix A. Summary of the functional trait database used in the study.

description: Summary of the functional trait database used in the study.
DOI: 10.6084/m9.figshare.3510447
title: Appendix B. Alternative phylogenetic community structure analysis using a presence/absence null model.

description: Alternative phylogenetic community structure analysis using a presence/absence null model.
DOI: 10.6084/m9.figshare.3510448.v1
title: Appendix A. Summary of the functional trait database used in the study.

description: Summary of the functional trait database used in the study.
DOI: 10.6084/m9.figshare.3510446
title: Appendix C. Percentage of quadrats where the observed trait metrics were significantly different from the the null expectation.

description: Percentage of quadrats where the observed trait metrics were significantly different from the the null expectation.
DOI: 10.6084/m9.figshare.3510446.v1
title: Appendix C. Percentage of quadrats where the observed trait metrics were significantly different from the the null expectation.

description: Percentage of quadrats where the observed trait metrics were significantly different from the the null expectation.
DOI: 10.6084/m9.figshare.3510445
title: Appendix D. Comparison of the ability of three different metrics of even trait spacing to distinguish between alternative models of community assembly.

description: Comparison of the ability of three different metrics of even trait spacing to distinguish between alternative models of community assembly.
DOI: 10.6084/m9.figshare.3510444
title: Appendix E. Distributions of six trait metrics for leaf nitrogen produced by four community assembly simulation models.

description: Distributions of six trait metrics for leaf nitrogen produced by four community assembly simulation models.
DOI: 10.6084/m9.figshare.3510443
title: Appendix F. Distributions of six trait metrics for leaf size produced by four community assembly simulation models.

description: Distributions of six trait metrics for leaf size produced by four community assembly simulation models.
DOI: 10.6084/m9.figshare.3510443.v1
title: Appendix F. Distributions of six trait metrics for leaf size produced by four community assembly simulation models.

description: Distributions of six trait metrics for leaf size produced by four community assembly simulation models.
DOI: 10.6084/m9.figshare.3510442
title: Appendix G. Distributions of six trait metrics for seed size produced by four community assembly simulation models.

description: Distributions of six trait metrics for seed size produced by four community assembly simulation models.
DOI: 10.6084/m9.figshare.3510441
title: Appendix H. Distributions of six trait metrics for wood density produced by four community assembly simulation models.

description: Distributions of six trait metrics for wood density produced by four community assembly simulation models.
DOI: 10.6084/m9.figshare.3510439
title: Appendix I. Distributions of six trait metrics for maximum dbh produced by four community assembly simulation models.

description: Distributions of six trait metrics for maximum dbh produced by four community assembly simulation models.
DOI: 10.6084/m9.figshare.3510441.v1
title: Appendix H. Distributions of six trait metrics for wood density produced by four community assembly simulation models.

description: Distributions of six trait metrics for wood density produced by four community assembly simulation models.
DOI: 10.6084/m9.figshare.3510439.v1
title: Appendix I. Distributions of six trait metrics for maximum dbh produced by four community assembly simulation models.

description: Distributions of six trait metrics for maximum dbh produced by four community assembly simulation models.
DOI: 10.6084/m9.figshare.3510438
title: Appendix J. Distributions of six trait metrics for the 95th quantile of the diameter distribution of all trees ≥ 0.1 of the maximum distance observed in the species, D950.1 produced by four community assembly simulation models.

description: Distributions of six trait metrics for the 95th quantile of the diameter distribution of all trees ≥ 0.1 of the maximum distance observed in the species, D950.1 produced by four community assembly simulation models.
DOI: 10.6084/m9.figshare.3510436
title: Appendix K. Relationship between SLA estimated from leaf punches and SLA estimated from whole leaves.

description: Relationship between SLA estimated from leaf punches and SLA estimated from whole leaves.
DOI: 10.6084/m9.figshare.3510435
title: Supplement 1. Leaf trait data set from the Yasuni Forest Dynamics plot, Ecuador.

description: File List Yasuni_Leaf_Traits.csv Description Species average leaf trait values from the Yasuni Forest Dynamics, Ecuador. Please refer to the main text and Kraft et al. 2008 <i>Science</i> for details on the trait collection methods and discussions of the limitations of the data. Data are presented as comma separated values (.csv). Missing data is indicated by a 'NA'. <strong>Column headings:</strong><br> Code: Six letter species code used in forest dynamics plot census.<br> Genus: Genus name. Taxa that had been placed in families but not genera at the time the data were made available are indicated by genera names in parentheses, such as '(lauraceae)'.<br> Species: Species name, including variety and subspecies if applicable. <br> Family: Family name. <br> SLA: Average specific leaf area measured from shade-grown whole leaves or leaflets, in units of cm<sup>2</sup>/g. <br> Leaf_N: Average leaf nitrogen content measured from shade-grown whole leaves or leaflets, reported on a mass basis.<br> Leaf_Size: Average leaf size, measured from shade-grown whole leaves or leaflets, reported in units of cm<sup>2</sup>. <b>Checksum values:</b><br> cols 1–4 Checksum is NA (it's all text), no missing values<br> col 5 ("SLA") Checksum is 213356.8, 3 missing values<br> col 6("Leaf_N") Checksum is 2768.51, 1 missing value<br> col 7("leaf_size") Checksum is 156860.7, 3 missing values