cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17044/scilifelab.26233184
title: <b>VISION — an open-source software for automated multi-dimensional image analysis of cellular biophysics</b>

description: It contains data sets from Weber et al, Journal of Cell Science, 2024 (https://doi.org/10.1242/jcs.262166)
The details for citation provided in the README file.
Please cite this item as:
Florian Weber, Sofiia Iskrak, Franziska Ragaller, Jan Schlegel, Birgit Plochberger, Erdinc Sezgin, Luca A. Andronico
DOI: 10.17044/scilifelab.26233184
It contains microscopy images and excel sheets of the data.
<strong>Abstract</strong>: Environment-sensitive probes are frequently used in spectral/multi-channel microscopy to study alterations in cell homeostasis. However, the few open-source packages available for processing of spectral images are limited in scope. Here, we present VISION, a stand-alone software based on Python for spectral analysis with improved applicability. In addition to classical intensity-based analysis, our software can batch-process multidimensional images with an advanced single-cell segmentation capability and apply user-defined mathematical operations on spectra to calculate biophysical and metabolic parameters of single cells. VISION allows for 3D and temporal mapping of properties such as membrane fluidity and mitochondrial potential. We demonstrate the broad applicability of VISION by applying it to study the effect of various drugs on cellular biophysical properties; the correlation between membrane fluidity and mitochondrial potential; protein distribution in cell-cell contacts; and properties of nanodomains in cell-derived vesicles. Together with the code, we provide a graphical user interface for facile adoption.
<strong>Data usage</strong>
Researchers are welcome to use the data contained in the dataset for any projects. Please cite this item upon use or when published. We encourage reuse using the same CC BY 4.0 License.
<strong>Data Content</strong>
lsm or czi files for confocal and spectral images
tif files for super-resolution images
Excel files for graphs
<br>
<strong>Software to open files</strong>
.xlsx - Microsoft Excel
.tif, .lsm, .czi - Fiji (https://imagej.net/software/fiji/)
DOI: 10.7483/opendata.cms.a7yb.286v
title: /TprimeTprime_M-1400_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.17044/scilifelab.26233184.v1
title: <b>VISION — an open-source software for automated multi-dimensional image analysis of cellular biophysics</b>

description: It contains data sets from Weber et al, Journal of Cell Science, 2024 (https://doi.org/10.1242/jcs.262166)
The details for citation provided in the README file.
Please cite this item as:
Florian Weber, Sofiia Iskrak, Franziska Ragaller, Jan Schlegel, Birgit Plochberger, Erdinc Sezgin, Luca A. Andronico
DOI: 10.17044/scilifelab.26233184
It contains microscopy images and excel sheets of the data.
<strong>Abstract</strong>: Environment-sensitive probes are frequently used in spectral/multi-channel microscopy to study alterations in cell homeostasis. However, the few open-source packages available for processing of spectral images are limited in scope. Here, we present VISION, a stand-alone software based on Python for spectral analysis with improved applicability. In addition to classical intensity-based analysis, our software can batch-process multidimensional images with an advanced single-cell segmentation capability and apply user-defined mathematical operations on spectra to calculate biophysical and metabolic parameters of single cells. VISION allows for 3D and temporal mapping of properties such as membrane fluidity and mitochondrial potential. We demonstrate the broad applicability of VISION by applying it to study the effect of various drugs on cellular biophysical properties; the correlation between membrane fluidity and mitochondrial potential; protein distribution in cell-cell contacts; and properties of nanodomains in cell-derived vesicles. Together with the code, we provide a graphical user interface for facile adoption.
<strong>Data usage</strong>
Researchers are welcome to use the data contained in the dataset for any projects. Please cite this item upon use or when published. We encourage reuse using the same CC BY 4.0 License.
<strong>Data Content</strong>
lsm or czi files for confocal and spectral images
tif files for super-resolution images
Excel files for graphs
<br>
<strong>Software to open files</strong>
.xlsx - Microsoft Excel
.tif, .lsm, .czi - Fiji (https://imagej.net/software/fiji/)
DOI: 10.17044/scilifelab.26318929
title: Prevalent and persistent new-onset autoantibodies in mild to severe COVID-19

description: <b>Note: The DOI of the related paper will be provided upon publication.</b>These datasets contain information on autoantibody and anti-SARS-CoV-2 IgG levels.In this study, 478 healthcare workers and 48 patients were followed prospectively over 5 visits from May 2020 to Sept 2021. SARS-CoV-2 serology and autoantibodies were assessed using planar and bead-based arrays. Detected epitopes were validated in blood and cerebrospinal fluid from two independent cohorts of Neuro-COVID patients (n=25) and pre-pandemic healthy controls (n=29).The datasets contain:<b>SARS-CoV-2 serological profiles</b> measured in all samples (above) using 3-plex bead arrays. The data is reported as raw and normalized MFI (AU) and compound serostatus.<b>Proteome-wide autoantibody profiles</b> measured in 12 sample pools using planar arrays. The data is reported as median fluorescent intensity, in raw and normalized arbitrary units (MFI [AU]), and reactivity classification.<b>Targeted autoantibody profiles</b> measured in 478 healthcare workers and 48 patients across 5 time points using 363-plex bead arrays. The data is reported as raw and normalized MFI (AU), fold change (FC) across infection, and new-onset classification.<b>Peptide epitope mapping autoantibody profiles</b> measured in a 142 healthcare workers and COVID-19 patients across 2 time points, and all Neuro-COVID patients (n=25) and pre-pandemic healthy controls (n=29), using 93-plex bead arrays. The data is reported as raw and normalized MFI (AU), and fold change (FC) across infection.Source data is provided with the paper.Access to this individual-level human data can be granted for <b>non-commercial</b><b> </b><b>v</b><b>alidation purposes</b> and upon reasonable request to the provided contact. A reasonable request should contain the following:Name of PI and host organizationContact detailsThe scientific purpose of the data access requestCommitment to inform when the data has been used in a publicationCommitment not to host or share the data outside the requesting organizationStatement of non-commercial use of data
DOI: 10.17044/scilifelab.26318929.v1
title: Prevalent and persistent new-onset autoantibodies in mild to severe COVID-19

description: <b>Note: The DOI of the related paper will be provided upon publication.</b>These datasets contain information on autoantibody and anti-SARS-CoV-2 IgG levels.In this study, 478 healthcare workers and 48 patients were followed prospectively over 5 visits from May 2020 to Sept 2021. SARS-CoV-2 serology and autoantibodies were assessed using planar and bead-based arrays. Detected epitopes were validated in blood and cerebrospinal fluid from two independent cohorts of Neuro-COVID patients (n=25) and pre-pandemic healthy controls (n=29).The datasets contain:<b>SARS-CoV-2 serological profiles</b> measured in all samples (above) using 3-plex bead arrays. The data is reported as raw and normalized MFI (AU) and compound serostatus.<b>Proteome-wide autoantibody profiles</b> measured in 12 sample pools using planar arrays. The data is reported as median fluorescent intensity, in raw and normalized arbitrary units (MFI [AU]), and reactivity classification.<b>Targeted autoantibody profiles</b> measured in 478 healthcare workers and 48 patients across 5 time points using 363-plex bead arrays. The data is reported as raw and normalized MFI (AU), fold change (FC) across infection, and new-onset classification.<b>Peptide epitope mapping autoantibody profiles</b> measured in a 142 healthcare workers and COVID-19 patients across 2 time points, and all Neuro-COVID patients (n=25) and pre-pandemic healthy controls (n=29), using 93-plex bead arrays. The data is reported as raw and normalized MFI (AU), and fold change (FC) across infection.Source data is provided with the paper.Access to this individual-level human data can be granted for <b>non-commercial</b><b> </b><b>v</b><b>alidation purposes</b> and upon reasonable request to the provided contact. A reasonable request should contain the following:Name of PI and host organizationContact detailsThe scientific purpose of the data access requestCommitment to inform when the data has been used in a publicationCommitment not to host or share the data outside the requesting organizationStatement of non-commercial use of data
DOI: 10.7483/opendata.cms.0rta.vbsz
title: /TprimeTprime_M-1400_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.17044/scilifelab.26425576
title: Microscopy data set of mRNA FISH and Protein gene expression measurements in which repressor binding strength is systematically altered.

description: This dataset contains the raw data, analysis and code needed to generate the figures presented in the paper "Anti-correlation of LacI association and dissociation rates observed in living cells" (see Related Material). The raw data consists of microscopy images and qPCR files. The analysis and code consist of data analysis, output from the analysis, its post-processing, simulations, and which figure the data was used in.Experimental data, and analysis scripts are all organized using unique IDs (UID; seen for example in the filenames of experimental data below). The README.txt file in the Analysis_of_data folder describes which UIDs for data, analysis, code & figure generation to combine for specific figures.For the microscopy experiments (has the prefix Microscopy_Data_ in their filenames) there is information on the growth condition and which figure the data was used in. All experiments were performed at 30 degrees Celsius.Details on the output from microscopy experiments can be found in the file MicroscopyInformation.txt.
DOI: 10.17632/ytb3vyfjtv
title: supplementary material for paper "PEGylated nicotinamide mononucleotide facilitated efficient renal uptake and inhibited ferroptosis in acute kidney injury through ACAA1-PRDX5-mediated connection of peroxisome and mitochondria"

description: supplementary material for paper "PEGylated nicotinamide mononucleotide facilitated efficient renal uptake and inhibited ferroptosis in acute kidney injury through ACAA1-PRDX5-mediated connection of peroxisome and mitochondria"
DOI: 10.17632/ytb3vyfjtv.1
title: supplementary material for paper "PEGylated nicotinamide mononucleotide facilitated efficient renal uptake and inhibited ferroptosis in acute kidney injury through ACAA1-PRDX5-mediated connection of peroxisome and mitochondria"

description: supplementary material for paper "PEGylated nicotinamide mononucleotide facilitated efficient renal uptake and inhibited ferroptosis in acute kidney injury through ACAA1-PRDX5-mediated connection of peroxisome and mitochondria"
DOI: 10.17044/scilifelab.26425576.v1
title: Microscopy data set of mRNA FISH and Protein gene expression measurements in which repressor binding strength is systematically altered.

description: This dataset contains the raw data, analysis and code needed to generate the figures presented in the paper "Anti-correlation of LacI association and dissociation rates observed in living cells" (see Related Material). The raw data consists of microscopy images and qPCR files. The analysis and code consist of data analysis, output from the analysis, its post-processing, simulations, and which figure the data was used in.Experimental data, and analysis scripts are all organized using unique IDs (UID; seen for example in the filenames of experimental data below). The README.txt file in the Analysis_of_data folder describes which UIDs for data, analysis, code & figure generation to combine for specific figures.For the microscopy experiments (has the prefix Microscopy_Data_ in their filenames) there is information on the growth condition and which figure the data was used in. All experiments were performed at 30 degrees Celsius.Details on the output from microscopy experiments can be found in the file MicroscopyInformation.txt.
DOI: 10.17044/scilifelab.26936965
title: <i>Linum trigynum </i>- PI estimates per population

description: Whole genome pi estimates for individuals of all population of <i>L. trigynum</i> per 100 kb windows.It is part of this article: Gutiérrez-Valencia, J., Zervakis, P. I., Postel, Z., Fracassetti, M., Losvik, A., Mehrabi, S., ... & Slotte, T. (2024). Genetic causes and genomic consequences of breakdown of distyly in Linum trigynum. Molecular Biology and Evolution, msae087. https://doi.org/10.1093/molbev/msae087Estimations were done using vcftools v.0.1.16 on a filtered vcf file. File's descriptions:CHROM = the chromosome's nameSTART = the start position of the 100 kb windowEND = the end position of the 100 kb windowPI = the estimated value of pi for that windowList of the populations: population 01population 03population 04population 06population 07population 08population 10population 11
DOI: 10.7483/opendata.cms.crfu.qos6
title: /TprimeTprime_M-1500_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.17044/scilifelab.26936965.v2
title: <i>Linum trigynum </i>- PI estimates per population

description: Whole genome pi estimates for individuals of all population of <i>L. trigynum</i> per 100 kb windows.It is part of this article: Gutiérrez-Valencia, J., Zervakis, P. I., Postel, Z., Fracassetti, M., Losvik, A., Mehrabi, S., ... & Slotte, T. (2024). Genetic causes and genomic consequences of breakdown of distyly in Linum trigynum. Molecular Biology and Evolution, msae087. https://doi.org/10.1093/molbev/msae087Estimations were done using vcftools v.0.1.16 on a filtered vcf file. File's descriptions:CHROM = the chromosome's nameSTART = the start position of the 100 kb windowEND = the end position of the 100 kb windowPI = the estimated value of pi for that windowList of the populations: population 01population 03population 04population 06population 07population 08population 10population 11
DOI: 10.17044/scilifelab.26936965.v1
title: <i>Linum trigynum </i>- PI estimates per population

description: Whole genome pi estimates for individuals of all population of <i>L. trigynum</i> per 100 kb windows.It is part of this article: Gutiérrez-Valencia, J., Zervakis, P. I., Postel, Z., Fracassetti, M., Losvik, A., Mehrabi, S., ... & Slotte, T. (2024). Genetic causes and genomic consequences of breakdown of distyly in Linum trigynum. Molecular Biology and Evolution, msae087. https://doi.org/10.1093/molbev/msae087Estimations were done using vcftools v.0.1.16 on a filtered vcf file. File's descriptions:CHROM = the chromosome's nameSTART = the start position of the 100 kb windowEND = the end position of the 100 kb windowPI = the estimated value of pi for that windowList of the populations: population 01population 03population 04population 06population 07population 08population 10population 11
DOI: 10.7483/opendata.cms.wej0.liwg
title: /TprimeTprime_M-1500_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.17044/scilifelab.26937202
title: <i>Linum trigynum</i> - Tajima's D estimates per population

description: Whole genome Tajima's D estimates for individuals of all population of <em>L. trigynum</em> per 100 kb windows.
It is part of this article: Gutiérrez-Valencia, J., Zervakis, P. I., Postel, Z., Fracassetti, M., Losvik, A., Mehrabi, S., ... & Slotte, T. (2024). Genetic causes and genomic consequences of breakdown of distyly in Linum trigynum. Molecular Biology and Evolution, msae087. https://doi.org/10.1093/molbev/msae087
Estimations were done using vcftools v.0.1.16 on a filtered vcf file.
File's descriptions:

 CHROM = the chromosome's name
 START = the start position of the 100 kb window
 END = the end position of the 100 kb window
 TajimaD = the estimated value of Tajima's D for that window

List of the populations:

 population 01
 population 03
 population 04
 population 06
 population 07
 population 08
 population 10
 population 11
DOI: 10.17044/scilifelab.26937202.v2
title: <i>Linum trigynum</i> - Tajima's D estimates per population

description: Whole genome Tajima's D estimates for individuals of all population of <em>L. trigynum</em> per 100 kb windows.
It is part of this article: Gutiérrez-Valencia, J., Zervakis, P. I., Postel, Z., Fracassetti, M., Losvik, A., Mehrabi, S., ... & Slotte, T. (2024). Genetic causes and genomic consequences of breakdown of distyly in Linum trigynum. Molecular Biology and Evolution, msae087. https://doi.org/10.1093/molbev/msae087
Estimations were done using vcftools v.0.1.16 on a filtered vcf file.
File's descriptions:

 CHROM = the chromosome's name
 START = the start position of the 100 kb window
 END = the end position of the 100 kb window
 TajimaD = the estimated value of Tajima's D for that window

List of the populations:

 population 01
 population 03
 population 04
 population 06
 population 07
 population 08
 population 10
 population 11
DOI: 10.17632/czyftbjx4y.1
title: Gender, employability

description: Relationshib between gender and employability perception.
DOI: 10.17632/jp7rzdjhs7.1
title: Updated Expert Opinion Guidelines Regarding the Effects of Immunosuppressive Agents on Patch Testing

description: Supplemental Material
DOI: 10.17044/scilifelab.26937202.v1
title: <i>Linum trigynum</i> - Tajima's D estimates per population

description: Whole genome Tajima's D estimates for individuals of all population of <em>L. trigynum</em> per 100 kb windows.
It is part of this article: Gutiérrez-Valencia, J., Zervakis, P. I., Postel, Z., Fracassetti, M., Losvik, A., Mehrabi, S., ... & Slotte, T. (2024). Genetic causes and genomic consequences of breakdown of distyly in Linum trigynum. Molecular Biology and Evolution, msae087. https://doi.org/10.1093/molbev/msae087
Estimations were done using vcftools v.0.1.16 on a filtered vcf file.
File's descriptions:

 CHROM = the chromosome's name
 START = the start position of the 100 kb window
 END = the end position of the 100 kb window
 TajimaD = the estimated value of Tajima's D for that window

List of the populations:

 population 01
 population 03
 population 04
 population 06
 population 07
 population 08
 population 10
 population 11
DOI: 10.17632/d62dgjrzvf.1
title: ONLINE MENTAL HEALTH INFORMATION SEEKING BEHAVIOUR AMONG UNDERGRADUATE STUDENTS IN NIGERIAN PRIVATE UNIVERSITIES

description: Mental health disorders among youth have emerged as a significant global health burden, affecting approximately one out of seven individuals worldwide aged between 10 to 19 years. This study seeks to shed light on the online mental health information seeking behavior among undergraduate students in Nigerian private universities. The study addresses the online information seeking behaviors of undergraduates related to mental health. Using a descriptive research design, data was collected through questionnaire from a sample of 400 randomly selected undergraduate students from Covenant and Babcock Universities. The findings reveal that students predominantly seek mental health information online, with search engines and social media being the primary sources accessed. The study also revealed that 65% of undergraduates never sought professional assistance after their exposure to mental health information online. Depression, anxiety, and eating disorders emerged as the most frequently sought-after types of mental health information. Students utilized online mental health information for self-education, self-diagnosis, and to gain a better understanding of mental health. This study concludes that the understanding of undergraduate students' information-seeking behavior has implications on mental health education and support within university settings. The study recommends that online mental health communicators should develop messages that would motivate audiences to seek professional assistance for their respective mental health conditions, and should include communicative strategies like partnership with opinion leaders as well as survivors of mental health conditions that would enhance audience confidence in online mental health information.
DOI: 10.7483/opendata.cms.gzl1.lc0x
title: /TprimeTprime_M-1600_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.17044/scilifelab.26937271
title: <i>Linum tenue </i>- PI estimates per population

description: Whole genome pi estimates for individuals of all population of <i>L. tenue</i> per 100 kb windows.It is part of this article: Gutiérrez-Valencia, J., Zervakis, P. I., Postel, Z., Fracassetti, M., Losvik, A., Mehrabi, S., ... & Slotte, T. (2024). Genetic causes and genomic consequences of breakdown of distyly in Linum trigynum. Molecular Biology and Evolution, msae087. https://doi.org/10.1093/molbev/msae087Estimations were done using vcftools v.0.1.16 on a filtered vcf file.File's descriptions:CHROM = the chromosome's nameSTART = the start position of the 100 kb windowEND = the end position of the 100 kb windowPI = the estimated value of pi for that windowList of the populations:population 06population 08population 17population 21population 23population 26population 32population 34
DOI: 10.15468/dl.6p8dd7
title: Occurrence Download

description: A dataset containing 2214 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Brazil",
 "OccurrenceStatus is Present",
 "StateProvince is one of (São Paulo State, Estado de São Paulo, Campos Do Jordao, Campinas, So Paulo)",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 2214 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071225-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17044/scilifelab.26937271.v1
title: <i>Linum tenue </i>- PI estimates per population

description: Whole genome pi estimates for individuals of all population of <i>L. tenue</i> per 100 kb windows.It is part of this article: Gutiérrez-Valencia, J., Zervakis, P. I., Postel, Z., Fracassetti, M., Losvik, A., Mehrabi, S., ... & Slotte, T. (2024). Genetic causes and genomic consequences of breakdown of distyly in Linum trigynum. Molecular Biology and Evolution, msae087. https://doi.org/10.1093/molbev/msae087Estimations were done using vcftools v.0.1.16 on a filtered vcf file.File's descriptions:CHROM = the chromosome's nameSTART = the start position of the 100 kb windowEND = the end position of the 100 kb windowPI = the estimated value of pi for that windowList of the populations:population 06population 08population 17population 21population 23population 26population 32population 34
DOI: 10.17044/scilifelab.26937271.v2
title: <i>Linum tenue </i>- PI estimates per population

description: Whole genome pi estimates for individuals of all population of <i>L. tenue</i> per 100 kb windows.It is part of this article: Gutiérrez-Valencia, J., Zervakis, P. I., Postel, Z., Fracassetti, M., Losvik, A., Mehrabi, S., ... & Slotte, T. (2024). Genetic causes and genomic consequences of breakdown of distyly in Linum trigynum. Molecular Biology and Evolution, msae087. https://doi.org/10.1093/molbev/msae087Estimations were done using vcftools v.0.1.16 on a filtered vcf file.File's descriptions:CHROM = the chromosome's nameSTART = the start position of the 100 kb windowEND = the end position of the 100 kb windowPI = the estimated value of pi for that windowList of the populations:population 06population 08population 17population 21population 23population 26population 32population 34