cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc28rnnc
title: CCDC 2108113: Experimental Crystal Structure Determination

description: Related Article: Wen-Lin Zou, Yan-Qing Liu, Qing-Zhu Li, Xin-Xin Kou, Hua Huang, Rong-Sheng Tong, Jun-Long Li, Bo Han|2023|Org.Chem.Front.|10|1237|doi:10.1039/D2QO01859D
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.cc26prvj
title: CCDC 2046708: Experimental Crystal Structure Determination

description: Related Article: Vijay S. Parmar, Andreas M. Thiel, Rizwan Nabi, Gemma K. Gransbury, Marie S. Norre, Peter Evans, Sophie C. Corner, Jonathan M. Skelton, Nicholas F. Chilton, David P. Mills, Jacob Overgaard|2023|Chem.Commun.|59|2656|doi:10.1039/D2CC06722F
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.cc2dd78b
title: CCDC 2216291: Experimental Crystal Structure Determination

description: Related Article: Xia Song, Kelin Wang, Xinying Zhang, Xuesen Fan|2023|Org.Chem.Front.|10|1191|doi:10.1039/D2QO01795D
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.cc26prrf
title: CCDC 2046705: Experimental Crystal Structure Determination

description: Related Article: Vijay S. Parmar, Andreas M. Thiel, Rizwan Nabi, Gemma K. Gransbury, Marie S. Norre, Peter Evans, Sophie C. Corner, Jonathan M. Skelton, Nicholas F. Chilton, David P. Mills, Jacob Overgaard|2023|Chem.Commun.|59|2656|doi:10.1039/D2CC06722F
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.cc26prwk
title: CCDC 2046709: Experimental Crystal Structure Determination

description: Related Article: Vijay S. Parmar, Andreas M. Thiel, Rizwan Nabi, Gemma K. Gransbury, Marie S. Norre, Peter Evans, Sophie C. Corner, Jonathan M. Skelton, Nicholas F. Chilton, David P. Mills, Jacob Overgaard|2023|Chem.Commun.|59|2656|doi:10.1039/D2CC06722F
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.7668320
title: FTD-tau S320F mutation stabilizes local structure and allosterically promotes amyloid motif-dependent aggregation

description: Amyloid deposition of the microtubule-associated protein tau is a unifying theme in a multitude of neurodegenerative diseases. Disease-associated missense mutations in tau are associated with frontotemporal dementia (FTD) and enhance tau aggregation propensity. However, the molecular mechanism of how mutations in tau promote tau assembly into amyloids remains obscure. There is a need to understand how tau folds into pathogenic conformations to cause disease. Here we describe the structural mechanism for how an FTD-tau S320F mutation drives spontaneous aggregation. We use recombinant protein and synthetic peptide systems, computational modeling, cross-linking mass spectrometry, and cell models to investigate the mechanism of spontaneous aggregation of the S320F FTD-tau mutant. We discover that the S320F mutation drives the stabilization of a local hydrophobic cluster which allosterically exposes the <sup>306</sup>VQIVYK<sup>311</sup> amyloid motif. We identify a suppressor mutation that reverses the S320F aggregation phenotype through the reduction of S320F-based hydrophobic clustering <em>in vitro</em> and in cells. Finally, we use structure-based computational design to engineer rapidly aggregating tau sequences by optimizing nonpolar clusters in proximity to the S320 site revealing a new principle governing the regulation of tau aggregation. We uncover a mechanism for regulating aggregation that balances transient nonpolar contacts within local protective structures or in longer-range interactions that sequester amyloid motifs. The introduction of a pathogenic mutation redistributes these transient interactions to drive spontaneous aggregation. We anticipate that more profound knowledge of this process will permit control of tau aggregation into discrete structural polymorphs to aid the design of reagents that can detect disease-specific tau conformations.
DOI: 10.5281/zenodo.7668319
title: FTD-tau S320F mutation stabilizes local structure and allosterically promotes amyloid motif-dependent aggregation

description: Amyloid deposition of the microtubule-associated protein tau is a unifying theme in a multitude of neurodegenerative diseases. Disease-associated missense mutations in tau are associated with frontotemporal dementia (FTD) and enhance tau aggregation propensity. However, the molecular mechanism of how mutations in tau promote tau assembly into amyloids remains obscure. There is a need to understand how tau folds into pathogenic conformations to cause disease. Here we describe the structural mechanism for how an FTD-tau S320F mutation drives spontaneous aggregation. We use recombinant protein and synthetic peptide systems, computational modeling, cross-linking mass spectrometry, and cell models to investigate the mechanism of spontaneous aggregation of the S320F FTD-tau mutant. We discover that the S320F mutation drives the stabilization of a local hydrophobic cluster which allosterically exposes the <sup>306</sup>VQIVYK<sup>311</sup> amyloid motif. We identify a suppressor mutation that reverses the S320F aggregation phenotype through the reduction of S320F-based hydrophobic clustering <em>in vitro</em> and in cells. Finally, we use structure-based computational design to engineer rapidly aggregating tau sequences by optimizing nonpolar clusters in proximity to the S320 site revealing a new principle governing the regulation of tau aggregation. We uncover a mechanism for regulating aggregation that balances transient nonpolar contacts within local protective structures or in longer-range interactions that sequester amyloid motifs. The introduction of a pathogenic mutation redistributes these transient interactions to drive spontaneous aggregation. We anticipate that more profound knowledge of this process will permit control of tau aggregation into discrete structural polymorphs to aid the design of reagents that can detect disease-specific tau conformations.
DOI: 10.5281/zenodo.7685759
title: dSTORM imaging of Caulobacter crescentus using WGA-AF647

description: See details in readme file.
DOI: 10.5281/zenodo.7685758
title: dSTORM imaging of Caulobacter crescentus using WGA-AF647

description: See details in readme file.
DOI: 10.6084/m9.figshare.7144289
title: IMMI Waitlist Older Adults with Depression Study

description: This is the dataset for the Internet Mindfulness Meditation Intervention and Waitlist study. https://www.mdpi.com/2305-6320/5/4/119
DOI: 10.6084/m9.figshare.7144289.v3
title: IMMI Waitlist Older Adults with Depression Study

description: This is the dataset for the Internet Mindfulness Meditation Intervention and Waitlist study. https://www.mdpi.com/2305-6320/5/4/119
DOI: 10.6073/pasta/c5557d8e3d3f72681b9797a1e4bf39dc
title: Data Supporting: "Phytoplankton as Indicators of Global Warming?"

description: This data package provides monthly time series of measurements made in San Francisco Bay from 1975-2021 and analyzed in the article "Phytoplankton as Indicators of Global Warming?" submitted to Limnology and Oceanography Letters.
DOI: 10.6084/m9.figshare.22191193
title: Zhang_Zagha_code_data_NatureComm

description: A. What is this? Codes and data in this folder are used in the article titled "Motor Cortex Gates Distractor Stimulus Encoding in Sensory Cortex" by Zhaoran Zhang and Dr. Edward Zagha. Data in this folder are collected by Zhaoran Zhang. Scripts in this folder are written by Zhaoran Zhang. <br> B. What does it include? This folder contains 4 parts: 1.example sessions of original data; 2.preprocessed data; 3.MatLab scripts for plotting figures using original data or preprocessed data, depending on certain plots; 4.MatLab functions needed for running the scripts. <br> C. How to use it? 1. Software: The code in this folder is based on Matlab (R2019b). Certain toolbox might be required to run the code. Other version of Matlab should also be fine, but there might be small errors relating to Matlab functions. 2. Code and data: 2.1 After downloading the folder, please unzip it and save it directly in C drive. (If C drive is not available, data pathways in the code need to be modified accordingly.) 2.2 Open Matlab. Copy and paste "C:\Zhang_Zagha_code_data_NatureComm\functions" in the Current Directory, then press "Enter". 2.3 Right click the blank space in current folder. Click "Add to Path", then click "Current Folder". 2.4 Open any code script in Matlab. 2.5 Use "Run and Advance" to obtain all the figures. No need to make any change in the code.
DOI: 10.6084/m9.figshare.22191199
title: DATA_The Economic Impact of Commercial-Industrial Information Loss.xlsx

description: The raw dataset provides corporate M&A activity to test the effect on stock price and other financial variables.
DOI: 10.6084/m9.figshare.22191199.v1
title: DATA_The Economic Impact of Commercial-Industrial Information Loss.xlsx

description: The raw dataset provides corporate M&A activity to test the effect on stock price and other financial variables.
DOI: 10.5281/zenodo.7686195
title: Tables and Data for "Synthesis of Satellite and Surface Measurements, Model Results, and FRAPPÉ Study Findings to Assess the Impacts of Oil and Gas Emissions Reductions on Maximum Ozone in the Denver Metro and Northern Front Range Region in Colorado"

description: These are data sets and tables used in the paper "Synthesis of Satellite and Surface Measurements, Model Results, and FRAPPÉ Study Findings to Assess the Impacts of Oil and Gas Emissions Reductions on Maximum Ozone in the Denver Metro and Northern Front Range Region in Colorado" to be submitted to Earth and Space Science. The monitor site 2016 and 2017 counts files have gridded HYSPLIT back trajectory counts for the 4 highest ozone concentration days at each site, as described in the manuscript.
DOI: 10.17909/qfnj-yt76
title: Data from a Reexamination of Phosphorus and Chlorine Depletions in the Diffuse Interstellar Medium

description: This dataset comprises all medium and high resolution FUV STIS echelle spectra and all FUSE observations for a sample of 107 sight lines used to study P and Cl abundances and depletions in the local Galactic interstellar medium.
DOI: 10.6084/m9.figshare.14036549
title: Estimated Deaths, Intensive Care Admissions and Hospitalizations Averted in Canada during the COVID-19 Pandemic

description: These datasets explore disparities in COVID-19 mortality observed in the US and Canada between January 2020 and early March 2021. Table 1 provides counts of deaths, hospitalizations, ICU admissions, and cases, by age, for Ontario, Canada (Canada's most populous province). <br> Table 2 estimates deaths averted by Canada's response to the COVID-19 pandemic, relative to that in the United States, by "Canada-standardizing" the US epidemic (i.e., by applying US age-specific mortality to Canadian populations, in order to estimate the deaths that would have occurred in a Canadian pandemic with the same rates of death as have been observed in the US). Observed Canadian deaths are compared to "expected" deaths with a US-like response in order to estimate both deaths averted and SMR (Table 2). <br> As Canadian age groups for purposes of death reporting are slightly different from those used in the US (e.g., 0-17 in the US vs. 0-19 in Canada), we reallocate Canadian deaths based on proportions of deaths occurring in 2-year age categories in Ontario (Table 1). <br> Ontario age-specific case-fatality is used to inflate the deaths averted, in order to estimate cases averted. Ontario age-specific hospitalization and ICU risk (again derived from Table 1) are used to estimate hospitalizations and ICU admissions averted (Table 2). <br> As of August 9, 2022, a new dataset has been added which applies the methodology described above to compare deaths in Canada to those in the United Kingdom, France, and Australia. Estimates of QALY loss, and healthcare costs averted, have also been added. Uncertainty bounds are estimated either as parametric confidence intervals, or as upper and lower bound 95% credible intervals through simulation (implemented using the random draw funding in Microsoft Excel). <br> Errors in confidence intervals for QALY losses in France and Australia corrected February 28, 2023.
DOI: 10.6084/m9.figshare.14036549.v2
title: Estimated Deaths, Intensive Care Admissions and Hospitalizations Averted in Canada during the COVID-19 Pandemic

description: These datasets explore disparities in COVID-19 mortality observed in the US and Canada between January 2020 and early March 2021. Table 1 provides counts of deaths, hospitalizations, ICU admissions, and cases, by age, for Ontario, Canada (Canada's most populous province). <br> Table 2 estimates deaths averted by Canada's response to the COVID-19 pandemic, relative to that in the United States, by "Canada-standardizing" the US epidemic (i.e., by applying US age-specific mortality to Canadian populations, in order to estimate the deaths that would have occurred in a Canadian pandemic with the same rates of death as have been observed in the US). Observed Canadian deaths are compared to "expected" deaths with a US-like response in order to estimate both deaths averted and SMR (Table 2). <br> As Canadian age groups for purposes of death reporting are slightly different from those used in the US (e.g., 0-17 in the US vs. 0-19 in Canada), we reallocate Canadian deaths based on proportions of deaths occurring in 2-year age categories in Ontario (Table 1). <br> Ontario age-specific case-fatality is used to inflate the deaths averted, in order to estimate cases averted. Ontario age-specific hospitalization and ICU risk (again derived from Table 1) are used to estimate hospitalizations and ICU admissions averted (Table 2). <br> As of August 9, 2022, a new dataset has been added which applies the methodology described above to compare deaths in Canada to those in the United Kingdom, France, and Australia. Estimates of QALY loss, and healthcare costs averted, have also been added. Uncertainty bounds are estimated either as parametric confidence intervals, or as upper and lower bound 95% credible intervals through simulation (implemented using the random draw funding in Microsoft Excel).
DOI: 10.6084/m9.figshare.20038184
title: Linoleic Acid Improves PIEZO2 Dysfunction in a mouse model of Angelman Syndrome

description: Manuscript source data file
DOI: 10.6084/m9.figshare.20038184.v1
title: Linoleic Acid Improves PIEZO2 Dysfunction in a mouse model of Angelman Syndrome

description: Manuscript source data file
DOI: 10.25452/figshare.plus.21711245
title: THINGS-data: fMRI PRF AFNI inputs

description: Input files required to run a population receptive field analysis on the THINGS-fMRI localizer data with AFNI. <br> Part of THINGS-data: A multimodal collection of large-scale datasets for investigating object representations in brain and behavior <br> See related materials in Collection at: https://doi.org/10.25452/figshare.plus.c.6161151
DOI: 10.5281/zenodo.7533587
title: Molecular Dynamics Simulations of HADDOCK-predicted Complex Structures of apoE2 and Factor H

description: Input and output data for the molecular dynamics simulations of the FH5–7/ApoE2 complex. Initial structures generated with the HADDOCK v2.4 web server with 3 nm distance restraints for lysine pairs that were experimentally found to be cross-linked with DSS. Five clusters and the four representative structures provided by HADDOCK were then used for atomistic molecular dynamics simulations. These structures were solvated and simulated with both CHARMM36m and Amber FF14SB force fields for 250 ns each using GROMACS 2021. The recommended simulation parameters were used for both force fields, and they are available in the mdp files. For each of these 5 (clusters) x 4 (structures per cluster) x 2 (force fields) = 40 simulations, the outputs and inputs are provided; the trajectory (xtc), energy file (edr), final structure (gro), run parameter file (tpr), and continue point (cpt) are system-specific, whereas a single topology (top) and index file (ndx) is shared among all simulations with the same force field. The molecule definitions (itp) referred to in the topology are provided in the compressed files.
DOI: 10.5281/zenodo.7533586
title: Molecular Dynamics Simulations of HADDOCK-predicted Complex Structures of apoE2 and Factor H

description: Input and output data for the molecular dynamics simulations of the FH5–7/ApoE2 complex. Initial structures generated with the HADDOCK v2.4 web server with 3 nm distance restraints for lysine pairs that were experimentally found to be cross-linked with DSS. Five clusters and the four representative structures provided by HADDOCK were then used for atomistic molecular dynamics simulations. These structures were solvated and simulated with both CHARMM36m and Amber FF14SB force fields for 250 ns each using GROMACS 2021. The recommended simulation parameters were used for both force fields, and they are available in the mdp files. For each of these 5 (clusters) x 4 (structures per cluster) x 2 (force fields) = 40 simulations, the outputs and inputs are provided; the trajectory (xtc), energy file (edr), final structure (gro), run parameter file (tpr), and continue point (cpt) are system-specific, whereas a single topology (top) and index file (ndx) is shared among all simulations with the same force field. The molecule definitions (itp) referred to in the topology are provided in the compressed files.
DOI: 10.6084/m9.figshare.22191265
title: Interview Transcript for Emotional Geographies of Graduate Student Teachers.docx

description: This data provides the interview transcripts of graduate student teachers which talk about their emotional geographies when doing teaching oracticum.
DOI: 10.15139/s3/urdfz0
title: Responsiveness in Text Messaging, 2017

description: This research investigated the role of emoji in the communication of perceived responsiveness—conveying understanding, validation, and care to another person—through text messages. Participants (n= 323 college students) read a text message conversation between two individuals where Person A (the discloser) discussed a negative event with Person B (the responder), who attempted to convey responsiveness to Person A’s situation. Participants were randomly assigned to review one of two versions of the conversation: Person B either used or did not use emoji in their responses. Participants rated the perceived responsiveness of Person B toward Person A in subsections of text exchanges. The sample consisted of 323 college students (72 males, 245 females, 6 not reported; Mean age = 20.77 years, SD = 5.40, Range = 18-56). The sample was fairly diverse: 107 White or Caucasian, 72 Asian or Pacific Islander, 42 Black or African American, 33 Hispanic or Latino, 23 Middle Eastern, 2 West Indian or Caribbean, and 33 Multiracial (11 not reported). The sample almost exclusively consisted of smartphone users (99%; 312 participants) and 72.8% (227 participants) of smartphone users reported having an Apple phone. Most of the sample used emoji with only 4.3% (14 participants) reporting that they do not use emoji. Brooklyn College IRB: 2016-0682
DOI: 10.6073/pasta/72811937cb436a198ec9b10483edc2a4
title: Mountain Lake Chemistry and Physics Profile Data since 2015 at Castle Lake

description: This data set contains long-term limnology data from Castle Lake (located 5440 ft above sea level in Northern California). The data contained can be broadly grouped into two different types: chemical and physical data. This data set contains dissolved oxygen saturation, dissolved oxygen concentration, chlorophyll-a concentration, CDOM, phycocyanin concentration, conductivity, specific conductivity, pH, salinity, water temperature, pressure, turbidity, sea pressure, density anomaly, and speed of sound at various depths. Sampling Frequency: Continuous measurements were made and recorded down to milliseconds. Sampling dates vary from year to year, starting as early as February and as late as November. This data collection is part of an ongoing project funded by the US National Science Foundation, private donors, US AID, and the University of Nevada's Global Water Center. This package was updated in February 2023 with data from 2021 and 2022. Dissolved O2 concentration data in the 2020 data file was updated to values in units of mg/L instead of umol/L and specific conductivity units in all files was revised to be in microSiemens per centimeter and not milliSiemens per centimeter.
DOI: 10.25452/figshare.plus.20563800
title: THINGS-data: MEG BIDS raw dataset

description: MEG raw dataset in BIDS format. <br> Part of THINGS-data: A multimodal collection of large-scale datasets for investigating object representations in brain and behavior. <br> See related materials in Collection at: https://doi.org/10.25452/figshare.plus.c.6161151
DOI: 10.25452/figshare.plus.20590140
title: THINGS-data: fMRI Single Trial Responses (nifti format)

description: Whole-brain single trial beta estimates of the THINGS-fMRI data. <br> Part of THINGS-data: A multimodal collection of large-scale datasets for investigating object representations in brain and behavior. <br> See related materials in Collection at: https://doi.org/10.25452/figshare.plus.c.6161151
DOI: 10.25452/figshare.plus.20590326
title: THINGS-data: fMRI BIDS raw dataset

description: fMRI raw dataset in BIDS format. <br> Part of THINGS-data: A multimodal collection of large-scale datasets for investigating object representations in brain and behavior <br> See related materials in Collection at: https://doi.org/10.25452/figshare.plus.c.6161151
DOI: 10.25452/figshare.plus.20492757
title: THINGS-data: fMRI Brain Masks

description: Brain masks for the fMRI data. <br> Part of THINGS-data: A multimodal collection of large-scale datasets for investigating object representations in brain and behavior. <br> See related materials in Collection at: https://doi.org/10.25452/figshare.plus.c.6161151
DOI: 10.25452/figshare.plus.20492763
title: THINGS-data: fMRI ICA Noise Regressors

description: ICA-based noise regressors for the fMRI data. <br> Part of THINGS-data: A multimodal collection of large-scale datasets for investigating object representations in brain and behavior. <br> See related materials in Collection at: https://doi.org/10.25452/figshare.plus.c.6161151