cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.12043365
title: Diverse homeostatic and immunomodulatory roles of immune cells in the developing mouse lung revealed at single cell resolution

description: At birth, the lungs experience a sudden transition from a pathogen-free, hypoxic, fluid-filled environment to a pathogen-rich, rhythmically distended air-liquid interface. While many studies focus on adult tissue, the heterogeneity of immune cells in the perinatal lung remains unexplored. Here, we combine single cell transcriptomics with <em>in situ</em> hybridization to present an atlas of the murine lung immune compartment during a critical period of lung development. We show that the late embryonic lung is dominated by specialized proliferative macrophages with a surprising physical interaction with the developing vasculature. These macrophages disappear after birth and are replaced by a complex and dynamic mixture of macrophage subtypes, dendritic cells, granulocytes, and lymphocytes. Detailed characterization of macrophage diversity revealed a precise orchestration of five distinct subpopulations across postnatal development to fill context-specific functions in tissue remodeling, angiogenesis, and immunity. These data both broaden the putative roles for immune cells in the developing lung and provide a framework for understanding how external insults alter immune cell phenotype during a period of rapid lung growth and heightened vulnerability.<br>File formats:- <b>tsv</b> (gzipped): separate files for gene expression counts and cell metadata- <b>loom</b>: single file with both cell metadata and gene expression counts<br>Metadata columns (tab-separated):- the first column is cell id<br>- title: same as cell id- source name: distal lung<br>- organism: Mus musculus<br>- Sequencing run: DC20, DC21, DC23, DC25, DC30, DC35, DC36<br>- Gender: F or M<br>- Plate: 1 or 2 (the number of 384 well plate the cell for sorted into)<br>- Well: A1-P24 (the well number within the 384 well plate the cell was sorted into)<br>- Timepoint: E18.5, P1, P7, or P21<br>- Cell Type: immune<br>- Cell Subtype: one of several subtypes<br>- Mousename: mouse id<br>- Coverage: number of read pairs uniquely mapped to the mouse genome<br>- Number of genes: number of genes detected with 1+ reads<br>- tsne_1: t-SNE coordinate 1<br>- tsne_2: t-SNE coordinate 2<br>- molecule: mRNA<br>- description: none- processed data file: none- raw file 1: fastq file for read 1 (on GEO: GSE147668)- raw file 2: fastq file for read 2 (on GEO: GSE147668)
DOI: 10.6084/m9.figshare.12043365.v2
title: Diverse homeostatic and immunomodulatory roles of immune cells in the developing mouse lung revealed at single cell resolution

description: At birth, the lungs experience a sudden transition from a pathogen-free, hypoxic, fluid-filled environment to a pathogen-rich, rhythmically distended air-liquid interface. While many studies focus on adult tissue, the heterogeneity of immune cells in the perinatal lung remains unexplored. Here, we combine single cell transcriptomics with <em>in situ</em> hybridization to present an atlas of the murine lung immune compartment during a critical period of lung development. We show that the late embryonic lung is dominated by specialized proliferative macrophages with a surprising physical interaction with the developing vasculature. These macrophages disappear after birth and are replaced by a complex and dynamic mixture of macrophage subtypes, dendritic cells, granulocytes, and lymphocytes. Detailed characterization of macrophage diversity revealed a precise orchestration of five distinct subpopulations across postnatal development to fill context-specific functions in tissue remodeling, angiogenesis, and immunity. These data both broaden the putative roles for immune cells in the developing lung and provide a framework for understanding how external insults alter immune cell phenotype during a period of rapid lung growth and heightened vulnerability.<br>File formats:- <b>tsv</b> (gzipped): separate files for gene expression counts and cell metadata- <b>loom</b>: single file with both cell metadata and gene expression counts<br>Metadata columns (tab-separated):- the first column is cell id<br>- title: same as cell id- source name: distal lung<br>- organism: Mus musculus<br>- Sequencing run: DC20, DC21, DC23, DC25, DC30, DC35, DC36<br>- Gender: F or M<br>- Plate: 1 or 2 (the number of 384 well plate the cell for sorted into)<br>- Well: A1-P24 (the well number within the 384 well plate the cell was sorted into)<br>- Timepoint: E18.5, P1, P7, or P21<br>- Cell Type: immune<br>- Cell Subtype: one of several subtypes<br>- Mousename: mouse id<br>- Coverage: number of read pairs uniquely mapped to the mouse genome<br>- Number of genes: number of genes detected with 1+ reads<br>- tsne_1: t-SNE coordinate 1<br>- tsne_2: t-SNE coordinate 2<br>- molecule: mRNA<br>- description: none- processed data file: none- raw file 1: fastq file for read 1 (on GEO: GSE147668)- raw file 2: fastq file for read 2 (on GEO: GSE147668)
DOI: 10.6084/m9.figshare.12043365.v1
title: Diverse homeostatic and immunomodulatory roles of immune cells in the developing mouse lung revealed at single cell resolution

description: At birth, the lungs experience a sudden transition from a pathogen-free, hypoxic, fluid-filled environment to a pathogen-rich, rhythmically distended air-liquid interface. While many studies focus on adult tissue, the heterogeneity of immune cells in the perinatal lung remains unexplored. Here, we combine single cell transcriptomics with <em>in situ</em> hybridization to present an atlas of the murine lung immune compartment during a critical period of lung development. We show that the late embryonic lung is dominated by specialized proliferative macrophages with a surprising physical interaction with the developing vasculature. These macrophages disappear after birth and are replaced by a complex and dynamic mixture of macrophage subtypes, dendritic cells, granulocytes, and lymphocytes. Detailed characterization of macrophage diversity revealed a precise orchestration of five distinct subpopulations across postnatal development to fill context-specific functions in tissue remodeling, angiogenesis, and immunity. These data both broaden the putative roles for immune cells in the developing lung and provide a framework for understanding how external insults alter immune cell phenotype during a period of rapid lung growth and heightened vulnerability.<br>Metadata columns (tab-separated):- the first column is cell id<br>- title: same as cell id- source name: distal lung<br>- organism: Mus musculus<br>- Sequencing run: DC20, DC21, DC23, DC25, DC30, DC35, DC36<br>- Gender: F or M<br>- Plate: 1 or 2 (the number of 384 well plate the cell for sorted into)<br>- Well: A1-P24 (the well number within the 384 well plate the cell was sorted into)<br>- Timepoint: E18.5, P1, P7, or P21<br>- Cell Type: immune<br>- Cell Subtype: one of several subtypes<br>- Mousename: mouse id<br>- Coverage: number of read pairs uniquely mapped to the mouse genome<br>- Number of genes: number of genes detected with 1+ reads<br>- tsne_1: t-SNE coordinate 1<br>- tsne_2: t-SNE coordinate 2<br>- molecule: mRNA<br>- description: none- processed data file: none- raw file 1: fastq file for read 1 (on GEO: GSE147668)- raw file 2: fastq file for read 2 (on GEO: GSE147668)
DOI: 10.6084/m9.figshare.12043332
title: 1301_Aligned_Part2

description: See description of the collection containing this dataset.<br>
DOI: 10.6084/m9.figshare.12043332.v1
title: 1301_Aligned_Part2

description: See description of the collection containing this dataset.<br>
DOI: 10.6084/m9.figshare.12043305
title: Raw_reads.zip

description: raw reads for sea cucumber microbiome studies
DOI: 10.6084/m9.figshare.12043305.v1
title: Raw_reads.zip

description: raw reads for sea cucumber microbiome studies
DOI: 10.6084/m9.figshare.12043263
title: 1301_Aligned_Part1

description: See description of the collection containing this dataset.<br>
DOI: 10.6084/m9.figshare.12043263.v1
title: 1301_Aligned_Part1

description: See description of the collection containing this dataset.<br>
DOI: 10.6084/m9.figshare.12043248
title: Molina de Aragón, Guadalajara, Spain : archaeological soil micromorphology data from pilot projects in 2015 and 2017

description: This dataset comprises three tables of archaeological soil and sediment descriptions of archaeological deposits from small scale pilot excavations and sampling within the castle of Molina de Aragón, Guadalajara, Spain. Table 1 shows the micromorphological descriptions. Table 2 shows the abundance of inclusions (% of area of thin section). Table 3 shows the abundance of post-depositional alterations and pedofeatures.
DOI: 10.6084/m9.figshare.12043248.v1
title: Molina de Aragón, Guadalajara, Spain : archaeological soil micromorphology data from pilot projects in 2015 and 2017

description: This dataset comprises three tables of archaeological soil and sediment descriptions of archaeological deposits from small scale pilot excavations and sampling within the castle of Molina de Aragón, Guadalajara, Spain. Table 1 shows the micromorphological descriptions. Table 2 shows the abundance of inclusions (% of area of thin section). Table 3 shows the abundance of post-depositional alterations and pedofeatures.
DOI: 10.6084/m9.figshare.12043245
title: Data from the study 'An exploratory study for Assessment of Multimodal Semantic Memory in Colombian Children'

description: This is the data obtained from the study
DOI: 10.6084/m9.figshare.12043233
title: 1301_Aligned_Downsamplex2_GaussBlurx2_Crop

description: See description of the collection containing this dataset.<br>
DOI: 10.6084/m9.figshare.12043245.v3
title: Data from the study 'An exploratory study for Assessment of Multimodal Semantic Memory in Colombian Children'

description: This is the data obtained from the study
DOI: 10.6084/m9.figshare.12043245.v2
title: Data from the study 'An exploratory study for Assessment of Multimodal Semantic Memory in Colombian'

description: This is the data obtained from the study
DOI: 10.6084/m9.figshare.12043221
title: 1298_Aligned_Downsamplex2_GaussBlurx2_Crop

description: See description of the collection containing this dataset.<br>
DOI: 10.6084/m9.figshare.12043233.v2
title: 1301_Aligned_Downsamplex2_GaussBlurx2_Crop

description: See description of the collection containing this dataset.<br>
DOI: 10.6084/m9.figshare.12043221.v1
title: 1298_Aligned_Downsamplex2_GaussBlurx2_Crop

description: See description of the collection containing this dataset.<br>
DOI: 10.6084/m9.figshare.12043233.v1
title: 1301_Aligned_Downsamplex2_GaussBlurx2_Crop

description: See description of the collection containing this dataset.<br>
DOI: 10.6084/m9.figshare.12043188
title: Soybean RNA-seq atlas

description: Data and code associated with the paper "<b>Systematic analysis of 1,298 RNA-Seq samples and construction of a comprehensive soybean (Glycine max) expression atlas</b>" (DOI: 10.1111/tpj.14850) published on The Plant Journal.
DOI: 10.6084/m9.figshare.12043170
title: Supplementary Table 2.

description: <b>Supplementary Table 2. </b><b>Sleep characteristics and the rest-activity cycle by actigraphy.</b><b></b>All data are presented as means (standard deviations). P values represent group differences from One-Way ANOVA for three conditions (HF, LF and CON). <sup>a</sup>: The difference between the mean activity in the least and most active periods, with theoretical range of 0 to 1, where higher values indicate a higher amplitude.<b><br></b>
DOI: 10.6084/m9.figshare.12043164
title: Supplementary Table 1.

description: <b>Supplementary Table 1. Observed concentration of inflammatory markers. </b><br>All data are presented as means (standard deviations). P values represent group differences from One-Way ANOVA for three conditions (HF, LF and CON)<b><sup>; #</sup></b>: HF significantly different from CON at P &lt; .05.
DOI: 10.6084/m9.figshare.12043188.v1
title: Soybean RNA-seq atlas

description: Data and code associated with the paper "<b>Systematic analysis of 1,298 RNA-Seq samples and construction of a comprehensive soybean (Glycine max) expression atlas</b>" (DOI: 10.1111/tpj.14850) published on The Plant Journal.
DOI: 10.6084/m9.figshare.12043170.v1
title: Supplementary Table 2. Sleep characteristics and the rest-activity cycle by actigraphy.

description: <b>Supplementary Table 2. </b><b>Sleep characteristics and the rest-activity cycle by actigraphy.</b><b></b>All data are presented as means (standard deviations). P values represent group differences from One-Way ANOVA for three conditions (HF, LF and CON). <sup>a</sup>: The difference between the mean activity in the least and most active periods, with theoretical range of 0 to 1, where higher values indicate a higher amplitude.<b><br></b>
DOI: 10.6084/m9.figshare.12043164.v1
title: Observed concentration of inflammatory markers

description: All data are presented as means (standard deviations). P values represent group differences from One-Way ANOVA for three conditions (HF, LF and CON)<b><sup>; #</sup></b>: HF significantly different from CON at P &lt; .05.
DOI: 10.6084/m9.figshare.12043164.v3
title: Supplementary Table 1.

description: <b>Supplementary Table 1. Observed concentration of inflammatory markers. </b><br>All data are presented as means (standard deviations). P values represent group differences from One-Way ANOVA for three conditions (HF, LF and CON)<b><sup>; #</sup></b>: HF significantly different from CON at P &lt; .05.
DOI: 10.6084/m9.figshare.12043170.v2
title: Supplementary Table 2.

description: <b>Supplementary Table 2. </b><b>Sleep characteristics and the rest-activity cycle by actigraphy.</b><b></b>All data are presented as means (standard deviations). P values represent group differences from One-Way ANOVA for three conditions (HF, LF and CON). <sup>a</sup>: The difference between the mean activity in the least and most active periods, with theoretical range of 0 to 1, where higher values indicate a higher amplitude.<b><br></b>
DOI: 10.6084/m9.figshare.12043164.v2
title: Supplementary Table 1.

description: <b>Supplementary Table 1. Observed concentration of inflammatory markers. </b><br>All data are presented as means (standard deviations). P values represent group differences from One-Way ANOVA for three conditions (HF, LF and CON)<b><sup>; #</sup></b>: HF significantly different from CON at P &lt; .05.
DOI: 10.6084/m9.figshare.12043170.v3
title: Supplementary Table 2.

description: <b>Supplementary Table 2. </b><b>Sleep characteristics and the rest-activity cycle by actigraphy.</b><b></b>All data are presented as means (standard deviations). P values represent group differences from One-Way ANOVA for three conditions (HF, LF and CON). <sup>a</sup>: The difference between the mean activity in the least and most active periods, with theoretical range of 0 to 1, where higher values indicate a higher amplitude.<b><br></b>
DOI: 10.6084/m9.figshare.12043116
title: Espinoza 2020

description: Raw data backup for the manuscript Espinoza et al., 2020
DOI: 10.6084/m9.figshare.12043170.v4
title: Supplementary Table 2.

description: <b>Supplementary Table 2. </b><b>Sleep characteristics and the rest-activity cycle by actigraphy.</b><b></b>All data are presented as means (standard deviations). P values represent group differences from One-Way ANOVA for three conditions (HF, LF and CON). <sup>a</sup>: The difference between the mean activity in the least and most active periods, with theoretical range of 0 to 1, where higher values indicate a higher amplitude.<b><br></b>
DOI: 10.6084/m9.figshare.12043170.v5
title: Supplementary Table 2.

description: <b>Supplementary Table 2. </b><b>Sleep characteristics and the rest-activity cycle by actigraphy.</b><b></b>All data are presented as means (standard deviations). P values represent group differences from One-Way ANOVA for three conditions (HF, LF and CON). <sup>a</sup>: The difference between the mean activity in the least and most active periods, with theoretical range of 0 to 1, where higher values indicate a higher amplitude.<b><br></b>
DOI: 10.6084/m9.figshare.12043116.v1
title: Espinoza 2020

description: Raw data backup for the manuscript Espinoza et al., 2020
DOI: 10.6084/m9.figshare.12043074
title: Data inputs and data sources for impact of cigarette tax increase on health and financing outcomes in four Indian states

description: Data inputs for the paper "Impact of cigarette tax increase on health and financing outcomes in four Indian states"
DOI: 10.6084/m9.figshare.12043047
title: 1298_Aligned.tif

description: See description for the collection containing this dataset. <br>
DOI: 10.6084/m9.figshare.12043062
title: Asian Summer Monson

description: Data from Westervelt et al. 2020
DOI: 10.6084/m9.figshare.12043047.v1
title: 1298_Aligned.tif

description: See description for the collection containing this dataset. <br>
DOI: 10.6084/m9.figshare.12043062.v1
title: Asian Summer Monson

description: Data from Westervelt et al. 2020
DOI: 10.6084/m9.figshare.12043044
title: Triggers of Thyroid Cancer Diagnosis

description: this is a supplement of <b>A Systematic Review and Meta-analysis.</b> The incidence of thyroid cancer has increased worldwide<i>.</i> In the United States, for instance, the incidence of thyroid cancer increased from a 4.9 to 14.2 per 100,000 person-years over the last two decades, while in South Korea, on the other hand, thyroid cancer increased by more than seven fold, from 6.3 per 100,000 person year in 1999 to 47.5 per 100,000 population in 2009. Understanding the method of thyroid cancer detection has potential implications on interpreting incidence rates, the diagnosis and management of thyroid cancer. The aim of this study is to summarize the available evidence to assess the frequency of incidental (asymptomatic) and non-incidental TC and examine the triggers that lead to diagnosis with comparison across multiple cohorts.
DOI: 10.6084/m9.figshare.12043074.v1
title: Data inputs and data sources for impact of cigarette tax increase on health and financing outcomes in four Indian states

description: Data inputs for the paper "Impact of cigarette tax increase on health and financing outcomes in four Indian states"
DOI: 10.6084/m9.figshare.12043074.v2
title: Data inputs and data sources for impact of cigarette tax increase on health and financing outcomes in four Indian states

description: Data inputs for the paper "Impact of cigarette tax increase on health and financing outcomes in four Indian states"
DOI: 10.23641/asha.12042678
title: Comparing home and childcare language environment (Larson et al., 2020)

description: <b>Purpose: </b>This study was conducted in a large Midwestern metropolitan area to examine the language environments at home and in center-based childcare for young children who are living in poverty. We compared child language use and exposure in the home and childcare settings using extended observations with automated Language Environment Analysis to gain a deeper understanding of the environmental factors that may affect change in language outcomes for young children.<b>Method: </b>Thirty-eight children, along with parents (<i>n</i> = 38) and childcare providers (<i>n</i> = 14) across five childcare centers, participated in this study. Each child completed a standardized language assessment and two daylong recordings with Language Environment Analysis to determine the number of adult words, conversational turns, and child vocalizations that occurred in each setting. Data were analyzed at 5-min intervals across each recording.<b>Results: </b>Comparisons between home recordings in this sample and a comparison group showed reliably higher rates of adult words and conversational turns in the home setting. Linear mixed-effects regression models showed significant differences in the child language environments, with the home setting providing higher levels of language input and use. These effects were still meaningful after accounting for the time of day, participant demographic characteristics, and child language ability.<b>Conclusions: </b>Practical implications for supporting child language development across settings are discussed, and suggestions for further research are provided.<br><b>Supplemental Material S1.</b> Results of the multilevel regression models for the three outcome variables without outlier.<br>Larson, A. L., Barrett, T. S., & McConnell, S. R. (2020). Exploring early childhood language environments: A comparison of language use, exposure, and interactions in the home and childcare settings. <i>Language, Speech, and Hearing Services in Schools.</i> https://doi.org/10.1044/2019_LSHSS-19-00066<br>
DOI: 10.23641/asha.12042678.v1
title: Comparing home and childcare language environment (Larson et al., 2020)

description: <b>Purpose: </b>This study was conducted in a large Midwestern metropolitan area to examine the language environments at home and in center-based childcare for young children who are living in poverty. We compared child language use and exposure in the home and childcare settings using extended observations with automated Language Environment Analysis to gain a deeper understanding of the environmental factors that may affect change in language outcomes for young children.<b>Method: </b>Thirty-eight children, along with parents (<i>n</i> = 38) and childcare providers (<i>n</i> = 14) across five childcare centers, participated in this study. Each child completed a standardized language assessment and two daylong recordings with Language Environment Analysis to determine the number of adult words, conversational turns, and child vocalizations that occurred in each setting. Data were analyzed at 5-min intervals across each recording.<b>Results: </b>Comparisons between home recordings in this sample and a comparison group showed reliably higher rates of adult words and conversational turns in the home setting. Linear mixed-effects regression models showed significant differences in the child language environments, with the home setting providing higher levels of language input and use. These effects were still meaningful after accounting for the time of day, participant demographic characteristics, and child language ability.<b>Conclusions: </b>Practical implications for supporting child language development across settings are discussed, and suggestions for further research are provided.<br><b>Supplemental Material S1.</b> Results of the multilevel regression models for the three outcome variables without outlier.<br>Larson, A. L., Barrett, T. S., & McConnell, S. R. (2020). Exploring early childhood language environments: A comparison of language use, exposure, and interactions in the home and childcare settings. <i>Language, Speech, and Hearing Services in Schools.</i> https://doi.org/10.1044/2019_LSHSS-19-00066<br>
DOI: 10.6084/m9.figshare.12040755
title: Dystrophin mulitplex ISH: supplementary file 1

description: Supplementary file 1 from the following manuscript:<br><b>Single-transcript multiplex in situ hybridisation reveals unique patterns of dystrophin isoform expression in the developing mammalian embryo</b> John C.W. Hildyard, Abbe H. Crawford, Faye Rawson, Dominique O. Riddell, Rachel C.M. Harron, Richard J. Piercy<br>This file contains full-size images used for several figures.
DOI: 10.6084/m9.figshare.12040746
title: Dystrophin multiplex ISH: Extended data

description: This file contains supplementary figures 1-5 from the extended data of the manuscript<br><b>Single-transcript multiplex in situ hybridisation reveals unique patterns of dystrophin isoform expression in the developing mammalian embryo</b> John C.W. Hildyard, Abbe H. Crawford, Faye Rawson, Dominique O. Riddell, Rachel C.M. Harron, Richard J. Piercy<br>
DOI: 10.6084/m9.figshare.12040746.v1
title: Dystrophin multiplex ISH: Extended data

description: This file contains supplementary figures 1-5 from the extended data of the manuscript<br><b>Single-transcript multiplex in situ hybridisation reveals unique patterns of dystrophin isoform expression in the developing mammalian embryo</b> John C.W. Hildyard, Abbe H. Crawford, Faye Rawson, Dominique O. Riddell, Rachel C.M. Harron, Richard J. Piercy<br>