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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/

    Funding: This work was supported by CIHR Foundation grant FDN 143312 (DWA), CIHR grant PJT 156167 (LZP), the European Union's Seventh Framework Programme (FP7/2008–2013) under Grant Agreement 627951 (Marie Curie IOF to PM), the German Academic Exchange Service (DAAD) with funds from the German Federal Ministry of Education and Research (57212163 to PM), and in part by the Bundesministerium für Bildung und Forschung, Germany (BMBF, grant no. 16GW0191 to PM). JMP is recipient of the Queen Elizabeth II graduate scholarship in science and technology. PM has been supported by the BIH‐Charité Clinical Scientist Program funded by the Charité – Universitätsmedizin Berlin and the Berlin Institute of Health. DWA holds a Tier 1 Canada Research Chair (CRC) in Membrane Biogenesis. LZP holds a Tier 1 CRC in Molecular Oncology. 3D confocal image stacks of primary cortical neurons under different treatment conditions to test the functionality of Phindr3D. Explanatory .txt file contained in the ZIP file. Please see the manuscript for details and on how to access the full data set: Rapid 3D phenotypic analysis of neurons and organoids using data-driven cell segmentation-free machine learning Philipp Mergenthaler*, Santosh Hariharan*, James M. Pemberton, Corey Lourenco, Linda Z. Penn, David W. Andrews PLOS Computational Biology, DOI: 10.1371/journal.pcbi.1008630 Phindr3D is available on GitHub: GitHub - DWALab/Phindr3D

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/

    Many roles of human platelets in health and disease are linked to their ability to transport and secrete a variety of small molecules and proteins carried in dense (δ-) and α-granules. Determination of granule number and content is important for diagnosis of platelet disorders and for studies of platelet structure, function, and development. We have optimized methods for detection and localization of platelet proteins via antibody and lectin staining, imaging via structured illumination laser fluorescence microscopy (SIM), and three-dimension (3D) image analysis. The methods were validated via comparison with published studies based on electron microscopy and high-resolution fluorescence microscopy. The α-granule cargo proteins thrombospondin-1 (TSP1), osteonectin (SPARC), fibrinogen (FGN), and Von Willebrand factor (VWF) were localized within the granule lumen, as was the proteoglycan serglycin (SRGN). Colocalization analysis indicates that staining with fluorescently labeled wheat germ agglutinin (WGA) allows detection of α-granules as effectively as immunostaining for cargo proteins, with the advantage of not requiring antibodies. RAB27B was observed to be concentrated at dense granules, allowing them to be counted via visual scoring and object analysis. We present a workflow for counting dense and α-granules via object analysis of 3D SIM images of platelets stained for RAB27B and with WGA. Abbreviation: SIM: structured illumination microscopy; WGA: wheat germ agglutinin; FGN: fibrinogen; TSP1: thrombospondin 1; ER: endoplasmic reticulum Platelets support blood clotting, wound healing, and other essential processes. These functions rely on the ability of platelets to transport and release small molecules like serotonin carried in dense granules and a wide range of proteins carried in alpha granules. Several conditions have been linked to abnormalities in one or more of platelet granule number, content, structure, and function. These conditions can be difficult to diagnose because platelet granules are so small they cannot be consistently resolved by conventional light microscopy, while higher power electron microscopy is not widely accessible. The goal of this study was to develop a method for counting and examining platelet dense and alpha granules without the need of electron microscopy. Key to this was the discovery that alpha granules can be reliably stained with the plant lectin wheat germ agglutinin, which has the advantages of being a smaller and less expensive molecule than the antibodies commonly used to detect alpha granule cargo proteins. We also establish that dense granules can be detected with high specificity via antibody staining of the membrane-associated protein RAB27B. We used structured illumination laser fluorescence microscopy to obtain high-resolution images of stained platelets. These were assembled into 3D renders using image analysis software, which was used to validate a protocol for rapidly counting granules within individual platelets. Our method supports the relatively rapid, accurate, and cost-effective assessment of platelet granules. We have already shown that it can confirm dense granule deficiency, and we anticipate that this approach will also prove useful in diagnosing and studying alpha granule abnormalities.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ figsharearrow_drop_down
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    figshare
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    figshare
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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      Dataset . 2022
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      Dataset . 2022
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    Additional file 4. Histological assessments for Figure 4. Shown are the data for each animal at either 1d or 3d post a single mild ischemic insult. Positive staining counts for TNF, Iba1 and EBA in addition to the Lectin scores and IgG gray level measures are presented.

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    figshare
    Dataset . 2016
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Dataset . 2016
    License: CC BY
    Data sources: Datacite
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      Dataset . 2016
      License: CC BY
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      Dataset . 2016
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Im, Doo Soon; Joselin, Alvin; Svoboda, Devon; Takano, Tesuya; +7 Authors

    Additional file 4. Individual data values.

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    Dataset . 2022
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    Data sources: Datacite
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    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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      Dataset . 2022
      License: CC BY
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      Dataset . 2022
      License: CC BY
      Data sources: Datacite
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    Authors: Faheem, Muhammad; Deneault, Eric; Alexandrova, Roumiana; Rodrigues, Deivid C.; +12 Authors

    Additional file 1. Supplementary tables.

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    Dataset . 2023
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      Dataset . 2023
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      Dataset . 2023
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    Additional file 7: Table S6. GEO and ENCODE FASTQ identification numbers per cell line for the data that were used to identify differential TF peaks.

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    Dataset . 2022
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    Dataset . 2022
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      Dataset . 2022
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    Authors: Zhan, Shing Hei; Drori, Michal; Goldberg, Emma E.; Otto, Sarah P.; +1 Authors

    Premise of the study: Polyploidization is a common and recurring phenomenon in plants and is often thought to be a mechanism of "instant speciation." Whether polyploidization is associated with the formation of new species ("cladogenesis") or simply occurs over time within a lineage ("anagenesis") has never, however, been assessed systematically. Methods: Here, we tested this hypothesis using phylogenetic and karyotypic information from 235 plant genera (mostly angiosperms). We first constructed a large database of combined sequence and chromosome number data sets using an automated procedure. We then applied likelihood models (ClaSSE) that estimate the degree of synchronization between polyploidization and speciation events in maximum likelihood and Bayesian frameworks. Key results: Our maximum likelihood analysis indicated that 35 genera supported a model that includes cladogenetic transitions over a model with only anagenetic transitions, whereas three genera supported a model that incorporates anagenetic transitions over one with only cladogenetic transitions. Furthermore, the Bayesian analysis supported a preponderance of cladogenetic change in four genera but did not support a preponderance of anagenetic change in any genus. Conclusions: Overall, these phylogenetic analyses provide the first broad confirmation that polyploidization is temporally associated with speciation events, suggesting that it is indeed a major speciation mechanism in plants, at least in some genera. PloiDBPhylogenetic trees inferred using MrBayes, ploidy estimates using ChromEvol, and TPL-based genus species diversity estimates for 223 genera.ploidb_dryad.tar.gz

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    DANS-EASY
    Dataset . 2016
    Data sources: B2FIND
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    Borealis
    Dataset . 2021
    Data sources: Datacite
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      DANS-EASY
      Dataset . 2016
      Data sources: B2FIND
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      Borealis
      Dataset . 2021
      Data sources: Datacite
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    Authors: Tianyuan Lu; Klein, Kathleen; InĂŠs Colmegna; Lora, Maximilien; +2 Authors

    Additional file 2: Table S2. Summary of CHG-based DMGs.

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    figshare
    Dataset . 2019
    License: CC BY
    Data sources: Datacite
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    figshare
    Dataset . 2019
    License: CC BY
    Data sources: Datacite
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      Dataset . 2019
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      Dataset . 2019
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    Authors: Anuli C. Uzozie; Ergin, Enes K.; Rolf, Nina; Tsui, Janice; +8 Authors

    Additional file 14.

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    Dataset . 2021
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    Dataset . 2021
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      Dataset . 2021
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      Dataset . 2021
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    Authors: Carrasco, Andres; Brown, Trecia A.; Lomber, Stephen G.;

    Assemblies of vertically connected neurons in the cerebral cortex form information processing units (columns) that participate in the distribution and segregation of sensory signals. Despite well-accepted models of columnar architecture, functional mechanisms of inter-laminar communication remain poorly understood. Hence, the purpose of the present investigation was to examine the effects of sensory information features on columnar response properties. Using acute recording techniques, extracellular response activity was collected from the right hemisphere of eight mature cats (felis catus). Recordings were conducted with multichannel electrodes that permitted the simultaneous acquisition of neuronal activity within primary auditory cortex columns. Neuronal responses to simple (pure tones), complex (noise burst and frequency modulated sweeps), and ecologically relevant (con-specific vocalizations) acoustic signals were measured. Collectively, the present investigation demonstrates that despite consistencies in neuronal tuning (characteristic frequency), irregularities in discharge activity between neurons of individual A1 columns increase as a function of spectral (signal complexity) and temporal (duration) acoustic variations. Multi-unit responses to acoustic signals within A1 columnsThe data set consists of eight multi-unit electrophysiology experiments located within a single .zip file. Acoustic feature (signal type and duration) are in subfolders where data rasters for each recording session conducted can be found. Columns represent time and rows trial number. Data is presented as Matlab files.DRYAD.zip

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    DANS-EASY
    Dataset . 2014
    Data sources: B2FIND
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      DANS-EASY
      Dataset . 2014
      Data sources: B2FIND
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/

    Funding: This work was supported by CIHR Foundation grant FDN 143312 (DWA), CIHR grant PJT 156167 (LZP), the European Union's Seventh Framework Programme (FP7/2008–2013) under Grant Agreement 627951 (Marie Curie IOF to PM), the German Academic Exchange Service (DAAD) with funds from the German Federal Ministry of Education and Research (57212163 to PM), and in part by the Bundesministerium für Bildung und Forschung, Germany (BMBF, grant no. 16GW0191 to PM). JMP is recipient of the Queen Elizabeth II graduate scholarship in science and technology. PM has been supported by the BIH‐Charité Clinical Scientist Program funded by the Charité – Universitätsmedizin Berlin and the Berlin Institute of Health. DWA holds a Tier 1 Canada Research Chair (CRC) in Membrane Biogenesis. LZP holds a Tier 1 CRC in Molecular Oncology. 3D confocal image stacks of primary cortical neurons under different treatment conditions to test the functionality of Phindr3D. Explanatory .txt file contained in the ZIP file. Please see the manuscript for details and on how to access the full data set: Rapid 3D phenotypic analysis of neurons and organoids using data-driven cell segmentation-free machine learning Philipp Mergenthaler*, Santosh Hariharan*, James M. Pemberton, Corey Lourenco, Linda Z. Penn, David W. Andrews PLOS Computational Biology, DOI: 10.1371/journal.pcbi.1008630 Phindr3D is available on GitHub: GitHub - DWALab/Phindr3D

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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2021
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      ZENODO
      Dataset . 2021
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    Many roles of human platelets in health and disease are linked to their ability to transport and secrete a variety of small molecules and proteins carried in dense (δ-) and α-granules. Determination of granule number and content is important for diagnosis of platelet disorders and for studies of platelet structure, function, and development. We have optimized methods for detection and localization of platelet proteins via antibody and lectin staining, imaging via structured illumination laser fluorescence microscopy (SIM), and three-dimension (3D) image analysis. The methods were validated via comparison with published studies based on electron microscopy and high-resolution fluorescence microscopy. The α-granule cargo proteins thrombospondin-1 (TSP1), osteonectin (SPARC), fibrinogen (FGN), and Von Willebrand factor (VWF) were localized within the granule lumen, as was the proteoglycan serglycin (SRGN). Colocalization analysis indicates that staining with fluorescently labeled wheat germ agglutinin (WGA) allows detection of α-granules as effectively as immunostaining for cargo proteins, with the advantage of not requiring antibodies. RAB27B was observed to be concentrated at dense granules, allowing them to be counted via visual scoring and object analysis. We present a workflow for counting dense and α-granules via object analysis of 3D SIM images of platelets stained for RAB27B and with WGA. Abbreviation: SIM: structured illumination microscopy; WGA: wheat germ agglutinin; FGN: fibrinogen; TSP1: thrombospondin 1; ER: endoplasmic reticulum Platelets support blood clotting, wound healing, and other essential processes. These functions rely on the ability of platelets to transport and release small molecules like serotonin carried in dense granules and a wide range of proteins carried in alpha granules. Several conditions have been linked to abnormalities in one or more of platelet granule number, content, structure, and function. These conditions can be difficult to diagnose because platelet granules are so small they cannot be consistently resolved by conventional light microscopy, while higher power electron microscopy is not widely accessible. The goal of this study was to develop a method for counting and examining platelet dense and alpha granules without the need of electron microscopy. Key to this was the discovery that alpha granules can be reliably stained with the plant lectin wheat germ agglutinin, which has the advantages of being a smaller and less expensive molecule than the antibodies commonly used to detect alpha granule cargo proteins. We also establish that dense granules can be detected with high specificity via antibody staining of the membrane-associated protein RAB27B. We used structured illumination laser fluorescence microscopy to obtain high-resolution images of stained platelets. These were assembled into 3D renders using image analysis software, which was used to validate a protocol for rapidly counting granules within individual platelets. Our method supports the relatively rapid, accurate, and cost-effective assessment of platelet granules. We have already shown that it can confirm dense granule deficiency, and we anticipate that this approach will also prove useful in diagnosing and studying alpha granule abnormalities.

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    Dataset . 2022
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    Dataset . 2022
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    Additional file 4. Histological assessments for Figure 4. Shown are the data for each animal at either 1d or 3d post a single mild ischemic insult. Positive staining counts for TNF, Iba1 and EBA in addition to the Lectin scores and IgG gray level measures are presented.

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    Dataset . 2016
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    Data sources: Datacite
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      Dataset . 2016
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      Dataset . 2016
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    Authors: Im, Doo Soon; Joselin, Alvin; Svoboda, Devon; Takano, Tesuya; +7 Authors

    Additional file 4. Individual data values.

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    Dataset . 2022
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Dataset . 2022
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      Dataset . 2022
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      Dataset . 2022
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/