cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.35092/yhjc.11530218
title: B cell flow cytometry data (FlowJo + FCS files) from the NIH/CHI influenza vaccination study

description: PBMC sample collection and processing are described in Tsang, J. S. et al. Global analyses of human immune variation reveal baseline predictors of postvaccination responses. Cell 157, 499–513 (2014). <br><br>Additional B cell subpopulations were gated for the publication "Broad immune activation underlies shared set point signatures for vaccine responsiveness in healthy individuals and disease activity in patients with lupus". (Kotliarov Y, Sparks R et al. Nature Medicine 2020). These new gates include the CD20+CD38++ cells whose frequency evaluated prior to vaccination was predictive of antibody responses to vaccination.<br><br>This item is a part of the collection: https://doi.org/10.35092/yhjc.c.4753772<br><b>If you use our data (including CITE-seq data) or code for your work please cite the following publication</b>:Kotliarov, Y., Sparks, R. et al. Broad immune activation underlies shared set point signatures for vaccine responsiveness in healthy individuals and disease activity in patients with lupus. Nat. Med. DOI: https://doi.org/10.1038/s41591-020-0769-8 (2020)<br><b>Abstract</b>Responses to vaccination and to diseases vary widely across individuals, which may be partly due to baseline immune variations. Identifying such baseline predictors and their biological basis are of broad interest given their potential importance for cancer immunotherapy, disease outcomes, vaccination and infection responses. Here we uncover baseline blood transcriptional signatures predictive of antibody responses to both influenza and yellow fever vaccinations in healthy subjects. These same signatures evaluated at clinical quiescence are correlated with disease activity in systemic lupus erythematosus patients with plasmablast-associated flares. CITE-seq profiling of 82 surface proteins and transcriptomes of 53,201 single cells from healthy high and low influenza-vaccination responders revealed that our signatures reflect the extent of activation in a plasmacytoid dendritic cell—Type I IFN—T/B lymphocyte network. Our findings raise the prospect that modulating such immune baseline states may improve vaccine responsiveness and mitigate undesirable autoimmune disease activities.<br><br><b>General contact</b>: John Tsang (john.tsang@nih.gov)<b>Questions about software/code</b>: Yuri Kotliarov (yuri.kotliarov@nih.gov)<br>
DOI: 10.35092/yhjc.11783697
title: Dataset for "Concept of a Radiofrequency Device for Osteopenia/Osteoporosis Screening"

description: This repository contains all raw data for the manuscript “Concept of a Radiofrequency Device for Osteopenia/Osteoporosis Screening”. <br><br>The data description is given in the document "dataset_description". This repository also contains MATLAB processing scripts used in the paper.<br><br>Supported by NIH grant NIH SBIR Phase I Grant R43AR071220, National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS).<br><br><br><br><br>
DOI: 10.35092/yhjc.11783697.v1
title: Dataset for "Concept of a Radiofrequency Device for Osteopenia/Osteoporosis Screening"

description: This repository contains all raw data for the manuscript “Concept of a Radiofrequency Device for Osteopenia/Osteoporosis Screening”. <br><br>The data description is given in the document "dataset_description". This repository also contains MATLAB processing scripts used in the paper.<br><br>Supported by NIH grant NIH SBIR Phase I Grant R43AR071220, National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS).<br><br><br><br><br>
DOI: 10.35092/yhjc.11921697
title: Biomarkers of Bone Turnover Identify Subsets of Chronic Kidney Disease Patients at High Risk for Fracture

description: <b>Abstract:</b><b>Background:</b>We sought to identify biomarkers that indicated low turnover on bone histomorphometry in CKD patients, and subsequently determined if this panel identified differential risk for fractures in community-living older adults. <b>Methods:</b>Among CKD patients who underwent iliac crest bone biopsies and histomorphometry, we evaluated candidate biomarkers to differentiate low turnover from other bone disease. We applied this biomarker panel to 676 participants in the Health ABC study with eGFR&lt;60 mL/min/1.73m<sup>2</sup>who were followed for fracture. Cox proportional hazards models evaluated the association of BMD with fracture risk and determined whether biomarker-defined low bone turnover modified fracture risk at any level of BMD. <b>Results: </b>In 58 CKD patients age 66±13 years, 48% female, with mean eGFR 48±10 mL/min/1.73m<sup>2</sup>who underwent bone biopsy, lower fibroblast growth factor (FGF)-23, higher ɑ-klotho, and lower parathyroid hormone (PTH) indicated low bone turnover in accordance with bone histomorphometry parameters (individual AUC=0.7, 0.7, and 0.6, respectively; sensitivity=31%, specificity=100%). In Health ABC, 676 participants with CKD were 75±3 years old, 51% female, with mean eGFR 48±10 mL/min/1.73m<sup>2</sup>. For every standard deviation lower BMD at baseline, there was a 6-fold higher fracture risk in persons with biomarker-defined low turnover (HR 5.72 [95% CI 2.67, 12.25]) vs. a 2-fold higher risk in remaining individuals (HR 2.23 [95% CI 1.67, 2.97]) (p<sub>interaction</sub>=0.053). <b>Conclusions: </b>In CKD patients who underwent bone biopsy, lower FGF-23, higher ɑ-klotho, and lower PTH together had high specificity for identifying low bone turnover. When applied to older individuals with CKD, BMD was more strongly associated with fracture risk in those with biomarker-defined low turnover. <b>Supplemental Table Presented Here: </b>When the bone turnover biomarkers were evaluated individually, none of the interactions were statistically significant, yet the point estimate for fracture risk was consistently higher in the group contributing individuals to the low bone turnover subset.
DOI: 10.15156/bio/sh1229243.08fu
title: SH1229243.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1229244.08fu
title: SH1229244.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/th028939
title: TH028939
title: Telotylenchidae

description: Here we present the novel 'taxon hypothesis' (TH) concept to accommodate fungal 'species hypothesis' (SH) into existing classification frameworks for taxonomic communication. As supplied with Digital Object Identifiers (DOIs), THs are flexible in time and enable direct cross-communication of higher level taxa along with evolving classification schemes. Every TH includes given number of SHs and consequently fixed number of fungal rDNA ITS sequences. DNA sequences generated by High-throughput or Sanger sequencing studies and identified against UNITE SHs will be automatically assigned to THs as well.
DOI: 10.15156/bio/th028940
title: TH028940
title: Trichostrongylidae

description: Here we present the novel 'taxon hypothesis' (TH) concept to accommodate fungal 'species hypothesis' (SH) into existing classification frameworks for taxonomic communication. As supplied with Digital Object Identifiers (DOIs), THs are flexible in time and enable direct cross-communication of higher level taxa along with evolving classification schemes. Every TH includes given number of SHs and consequently fixed number of fungal rDNA ITS sequences. DNA sequences generated by High-throughput or Sanger sequencing studies and identified against UNITE SHs will be automatically assigned to THs as well.
DOI: 10.25549/one-c4-49823
title: Harold F., letters (1966)

description: Harold F., postcard asking about broadminded personal advertising (1966)
DOI: 10.35092/yhjc.11921697.v1
title: Biomarkers of Bone Turnover Identify Subsets of Chronic Kidney Disease Patients at High Risk for Fracture

description: <b>Abstract:</b><b>Background:</b>We sought to identify biomarkers that indicated low turnover on bone histomorphometry in CKD patients, and subsequently determined if this panel identified differential risk for fractures in community-living older adults. <b>Methods:</b>Among CKD patients who underwent iliac crest bone biopsies and histomorphometry, we evaluated candidate biomarkers to differentiate low turnover from other bone disease. We applied this biomarker panel to 676 participants in the Health ABC study with eGFR&lt;60 mL/min/1.73m<sup>2</sup>who were followed for fracture. Cox proportional hazards models evaluated the association of BMD with fracture risk and determined whether biomarker-defined low bone turnover modified fracture risk at any level of BMD. <b>Results: </b>In 58 CKD patients age 66±13 years, 48% female, with mean eGFR 48±10 mL/min/1.73m<sup>2</sup>who underwent bone biopsy, lower fibroblast growth factor (FGF)-23, higher ɑ-klotho, and lower parathyroid hormone (PTH) indicated low bone turnover in accordance with bone histomorphometry parameters (individual AUC=0.7, 0.7, and 0.6, respectively; sensitivity=31%, specificity=100%). In Health ABC, 676 participants with CKD were 75±3 years old, 51% female, with mean eGFR 48±10 mL/min/1.73m<sup>2</sup>. For every standard deviation lower BMD at baseline, there was a 6-fold higher fracture risk in persons with biomarker-defined low turnover (HR 5.72 [95% CI 2.67, 12.25]) vs. a 2-fold higher risk in remaining individuals (HR 2.23 [95% CI 1.67, 2.97]) (p<sub>interaction</sub>=0.053). <b>Conclusions: </b>In CKD patients who underwent bone biopsy, lower FGF-23, higher ɑ-klotho, and lower PTH together had high specificity for identifying low bone turnover. When applied to older individuals with CKD, BMD was more strongly associated with fracture risk in those with biomarker-defined low turnover. <b>Supplemental Table Presented Here: </b>When the bone turnover biomarkers were evaluated individually, none of the interactions were statistically significant, yet the point estimate for fracture risk was consistently higher in the group contributing individuals to the low bone turnover subset.
DOI: 10.35092/yhjc.11991546
title: Data for comparison of automated and manual co-registration for magnetoencephalography

description: De-identified, de-faced structural MRI files for 90 participants, as well as co-registration error data used in the computation of intra-class correlations.<br><br>Dataset supporting publication: Houck JM, Claus ED (2020) A comparison of automated and manual co-registration for magnetoencephalography. PLoS ONE 15(4): e0232100. https://doi.org/10.1371/journal.pone.0232100<br><br>Abstract: Magnetoencephalography (MEG) is a neuroimaging technique that accurately captures the rapid (sub-millisecond) activity of neuronal populations. Interpretation of functional data from MEG relies upon registration to the participant’s anatomical MRI. The key remaining step is to transform the participant’s MRI into the MEG head coordinate space. Although both automated and manual approaches to co-registration are available, the relative accuracy of two approaches has not been systematically evaluated. The goal of the present study was to compare the accuracy of manual and automated co-registration. Resting MEG and T1-weighted MRI data were collected from 90 participants. Automated and manual co-registration were performed on the same subjects, and the inter-method reliability of the two methods assessed using the intra-class correlation. Median co-registration error for both methods was within acceptable limits. Inter-method reliability was in the “good” range for co-registration error, and the “good” to “excellent” range for translation and rotation. These results suggest that the output of the automated co-registration procedure is comparable to that achieved using manual co-registration.
DOI: 10.35092/yhjc.11991546.v1
title: Data for comparison of automated and manual co-registration for magnetoencephalography

description: De-identified, de-faced structural MRI files for 90 participants, as well as co-registration error data used in the computation of intra-class correlations.<br><br>Abstract:Magnetoencephalography (MEG) is a neuroimaging technique that accurately captures the rapid (sub-millisecond) activity of neuronal populations. Interpretation of functional data from MEG relies upon registration to the participant’s anatomical MRI. The key remaining step is to transform the participant’s MRI into the MEG head coordinate space. Although both automated and manual approaches to co-registration are available, the relative accuracy of two approaches has not been systematically evaluated. The goal of the present study was to compare the accuracy of manual and automated co-registration. Resting MEG and T1-weighted MRI data were collected from 90 participants. Automated and manual co-registration were performed on the same subjects, and the inter-method reliability of the two methods assessed using the intra-class correlation. Median co-registration error for both methods was within acceptable limits. Inter-method reliability was in the “good” range for co-registration error, and the “good” to “excellent” range for translation and rotation. These results suggest that the output of the automated co-registration procedure is comparable to that achieved using manual co-registration.<br>
DOI: 10.35092/yhjc.11996931
title: Data from: Noninvasive Electromagnetic Source Imaging of Spatio-temporally Distributed Epileptogenic Brain Sources

description: This database includes the de-identified interictal spike information in 9 focal epilepsy patients who became seizure-free after surgery. All underwent intra-cranial EEG (iEEG) monitoring prior to surgery and information about seizure onset zone (SOZ) based on iEEG study was available in these patients. <br> This dataset was collected under support from the National Institutes of Health via grants<b> </b>R01NS096761 and R01EB021027, to Dr. Bin He and Dr. Greg Worrell. The human data were collected and deidentified as part of NIH funded research at Mayo Clinic, Rochester, overseen by Dr. Greg Worrell, and processed and organized at Dr. Bin He’s lab at Carnegie Mellon University.<br> This dataset has been used and analyzed to study epilepsy networks and the results are reported in: Sohrabpour et al, “Noninvasive Electromagnetic Source Imaging of Spatio-temporally Distributed Epileptogenic Brain Sources,” Nature Communications, 2020 (https://doi.org/10.1038/s41467-020-15781-0). Please cite this paper if you use any data included in this dataset. Codes related to this study are also available from https://github.com/bfinl/FAST-IRES.
DOI: 10.35092/yhjc.11996931.v1
title: Data from: Noninvasive Electromagnetic Source Imaging of Spatio-temporally Distributed Epileptogenic Brain Sources

description: This database includes the de-identified interictal spike information in 9 focal epilepsy patients who became seizure-free after surgery. All underwent intra-cranial EEG (iEEG) monitoring prior to surgery and information about seizure onset zone (SOZ) based on iEEG study was available in these patients. <br> This dataset was collected under support from the National Institutes of Health via grants<b> </b>R01NS096761 and R01EB021027, to Dr. Bin He and Dr. Greg Worrell. The human data were collected and deidentified as part of NIH funded research at Mayo Clinic, Rochester, overseen by Dr. Greg Worrell, and processed and organized at Dr. Bin He’s lab at Carnegie Mellon University.<br> This dataset has been used and analyzed to study epilepsy networks and the results are reported in: Sohrabpour et al, “Noninvasive Electromagnetic Source Imaging of Spatio-temporally Distributed Epileptogenic Brain Sources,” Nature Communications, 2020. Please cite this paper if you use any data included in this dataset. Codes related to this study are also available from https://github.com/bfinl/FAST-IRES.
DOI: 10.35092/yhjc.12026910
title: Respiratory disease and virus shedding in rhesus macaques inoculated with SARS-CoV-2

description: These data are associated with a study on SARS-CoV-2 infection in rhesus macaques and support the following peer-reviewed publication: Munster, V.J., Feldmann, F., Williamson, B.N. et al. Respiratory disease in rhesus macaques inoculated with SARS-CoV-2. Nature (2020). https://doi.org/10.1038/s41586-020-2324-7 <br>This work was previously described in a preprint on bioRxiv: https://doi.org/10.1101/2020.03.21.001628<br><br>An outbreak of a novel coronavirus, now named SARS-CoV-2, causing respiratory disease and a ∼2% case fatality rate started in Wuhan, China in December 2019. Following unprecedented rapid global spread, the World Health Organization declared COVID-19 a pandemic on March 11, 2020. Although data on disease in humans are emerging at a steady pace, certain aspects of the pathogenesis of SARS-CoV-2 can only be studied in detail in animal models, where repeated sampling and tissue collection is possible. Here, we show that SARS-CoV-2 causes respiratory disease in infected rhesus macaques, with disease lasting 8-16 days. Pulmonary infiltrates, a hallmark of human disease, were visible in lung radiographs of all animals. High viral loads were detected in swabs from the nose and throat of all animals as well as in bronchoalveolar lavages; in one animal we observed prolonged rectal shedding. Taken together, the rhesus macaque recapitulates moderate disease observed in the majority of human cases. The establishment of the rhesus macaque as a model of COVID-19 will increase our understanding of the pathogenesis of this disease and will aid development and testing of medical countermeasures.
DOI: 10.35092/yhjc.12026910.v1
title: Respiratory disease and virus shedding in rhesus macaques inoculated with SARS-CoV-2

description: These data are associated with a study on SARS-CoV-2 infection in rhesus macaques and support the following peer-reviewed publication: Munster, V.J., Feldmann, F., Williamson, B.N. et al. Respiratory disease in rhesus macaques inoculated with SARS-CoV-2. Nature (2020). https://doi.org/10.1038/s41586-020-2324-7 <br>This work was previously described in a preprint on bioRxiv: https://doi.org/10.1101/2020.03.21.001628<br><br>An outbreak of a novel coronavirus, now named SARS-CoV-2, causing respiratory disease and a ∼2% case fatality rate started in Wuhan, China in December 2019. Following unprecedented rapid global spread, the World Health Organization declared COVID-19 a pandemic on March 11, 2020. Although data on disease in humans are emerging at a steady pace, certain aspects of the pathogenesis of SARS-CoV-2 can only be studied in detail in animal models, where repeated sampling and tissue collection is possible. Here, we show that SARS-CoV-2 causes respiratory disease in infected rhesus macaques, with disease lasting 8-16 days. Pulmonary infiltrates, a hallmark of human disease, were visible in lung radiographs of all animals. High viral loads were detected in swabs from the nose and throat of all animals as well as in bronchoalveolar lavages; in one animal we observed prolonged rectal shedding. Taken together, the rhesus macaque recapitulates moderate disease observed in the majority of human cases. The establishment of the rhesus macaque as a model of COVID-19 will increase our understanding of the pathogenesis of this disease and will aid development and testing of medical countermeasures.
DOI: 10.35092/yhjc.12033390
title: DIPY Processed Parkinson's Progression Markers Initiative (PPMI) Data Derivatives

description: Original PPMI diffusion MRI data of 64 subjects (32 patients, 32 healthy controls) was processed using DIPY.<br>PPMI data derivatives include white matter tracts in common space (MNI space) and tracts in subject's original space. It includes anatomical measures extracted from diffusion data such as FA, RD, MD, and AD and it also contains CSA peaks file for 32 patient subjects and 32 control subjects.<br>
DOI: 10.35092/yhjc.12084987
title: Supplementary Figure 2 - Endometrial stromal cells - Genomic annotation of GATA2 and PGR ChIPseq

description: Cistromic analysis revealed similar genome-wide binding of GATA2 to promoter regions in both Veh and IVD-treated cells.<br>Supplementary dataset supporting manuscript currently under review.<br>Abstract: The transcription factor GATA2 is important for endometrial stromal cell decidualization in early pregnancy. Progesterone receptor (PGR) is also critical during decidualization but its interaction with GATA2 in regulating genes and pathways necessary for decidualization in human endometrium are unclear. RNA-sequencing (RNA-seq) was performed to compare gene expression profiles (n=3) and chromatin immunoprecipitation followed by sequencing (ChIP-seq) using an antibody against GATA2 (n=2) was performed to examine binding to target genes in human endometrial stromal cells undergoing in vitro decidualization (IVD including estrogen, progestin and cAMP analogue) or vehicle treatment. We identified 1232 differentially expressed genes (DEGs) in IVD vs. vehicle. GATA2 cistrome in IVD-treated cells was enriched with motifs for GATA, ATF, and JUN, and gene ontology analysis of GATA2 cistrome revealed pathways that regulate cholesterol storage, p38 MAPK and the c-Jun N-terminal kinase cascades. Integration of RNA-seq and ChIP-seq data revealed that the PGR motif is highly enriched at GATA2 binding regions surrounding upregulated genes in IVD-treated cells. The integration of a mined public PGR cistrome in IVD-treated human endometrial cells with our GATA2 cistrome showed that GATA2 binding was significantly enhanced at PGR-binding regions in IVD vs. vehicle. Interrogating two separate ChIP-seq datasets together with RNA-seq revealed integration of GATA2 and PGR action to co-regulate biologic processes during decidualization of human endometrial stromal cells, specifically via WNT activation and stem cell differentiation pathways. These findings reveal the key pathways that are co-activated by GATA2 and PGR that may be therapeutic targets for supporting implantation and early pregnancy.