Find research datasets worth reusing

opencc-by-4.0Dec 2016View details →

Fig. 2. Multiplex PCR gel showing the 716 in Molecular diagnostics of the honey bee parasites Lotmaria passim and Crithidia spp. (Trypanosomatidae) using multiplex PCR

Fig. 2. Multiplex PCR gel showing the 716 to 724 bp amplicon for Lotmaria passim and Crithidia species, the L. passim specific 499 bp amplicon, and the Crithidia specific 245 bp amplicon.

opencc-by-4.0Dec 2016View details →

Fig. 1 in Molecular diagnostics of the honey bee parasites Lotmaria passim and Crithidia spp. (Trypanosomatidae) using multiplex PCR

Fig. 1. Bayesian molecular phylogenetic tree showing relationship of 2 Hawaiian Lotmaria passim positive samples relative to other trypanosomes from Gen- Bank for a 608 bp region of the rDNA SSU gene.

opencc-by-4.0Jul 2024View details →

Multi-modal image analysis for large scale cancer tissue studies within IMMUcan: multiplex immunofluorescence images

In cancer research, multiplexed imaging has enabled the in-depth characterization of the tumor microenvironment (TME) and how it relates to patient prognosis. However, standardized, multi-modal data from large numbers of patients to identify robust biomarkers is missing. To provide such data across five cancer indications, the IMMUcan consortium performs broad molecular and cellular spatial profiling of thousands of cancer samples. Two reproducible and scalable workflows have been developed for whole slide multiplexed immunofluorescence (mIF) and imaging mass cytometry (IMC) to overcome challenges of reproducibility and scalability. For mIF we developed IFQuant, a web-based tool optimized for user-friendliness and reproducibility. This Zenodo record contains the mIF images and IFQuant settings to reproduce the results presented in the referenced publication. The companion IMC dataset is available as a joint Zenodo record.

opencc-by-4.0Oct 2018View details →

Data and code for figures: Spatial multiplexing of soliton microcombs

This dataset contains the data presented in the Figures of the paper Spatial multiplexing of soliton microcombs (doi:<a href="https://doi.org/10.1038/s41566-018-0256-7">https://doi.org/10.1038/s41566-018-0256-7</a>). The datasets and scripts were generated and tested using Matlab 2017.

opencc-by-4.0May 2024View details →

OMAP-21: Organ Mapping Antibody Panel (OMAP) for Multiplexed Antibody-Based Imaging of Human Palatine Tonsil with MICS on MACSima 1.5

OMAP-21 was designed for MICS  (MACSima imaging cyclic staining) imaging of FFPE human tonsil samples.  Tissue fixation and antigen retrieval is described in (<a href="https://www.biorxiv.org/content/biorxiv/early/2023/11/07/2023.10.27.564191.full.pdf">Spatial protein and RNA analysis on the same tissue section using MICS technology</a>). The MACSima technology is described in detail in the following publication (<a href="https://doi.org/10.1038/s41598-022-05841-4">MACSima imaging cyclic staining (MICS) technology reveals combinatorial target pairs for CAR T cell treatment of solid tumors</a>). Most, but not all, antibodies in this panel are recombinant antibodies with a mutated human IgG1 constant region. The described mutation removes the Fc receptor binding capacity of human IgG1, eliminating the need for additional blocking steps and reducing non-specific binding of human antibodies on human tissues. Highly multiplexed imaging is achieved through cycles of immunolabeling with FITC, PE, and APC conjugated antibodies and photobleaching to eliminate fluorescence signal between imaging cycles. The panel contains 47 antibodies and the nuclear marker DAPI for image alignment and nuclear segmentation. This OMAP provides a spatial context for all anatomical structures and most cell types present in the human palatine tonsil. OMAP-21 follows closely OMAP-1 described for human lymph nodes (<a href="https://cdn.humanatlas.io/hra-releases/v1.4/docs/omap/omap-1-human-lymph-node-ibex.html">omap-1-human-lymph-node-ibex</a>) and OMAP-10 (<a href="https://cdn.humanatlas.io/hra-releases/v1.4/docs/omap/omap-10-palatine-tonsil-macsima.html">omap-10-palatine-tonsil-macsima</a>). All reagents were obtained from Miltenyi Biotec and have been rigorously tested through an internal quality control system to have minimal variation between lots. For this reason, lot information is not included in this table. Analysis was performed by an accompanied software package MACSIQ View Analysis also described in the MACSima publication (<a href="https://doi.org/10.1038/s41598-022-05841-4">https://doi.org/10.1038/s41598-022-05841-4</a>). The result of the analysis is included in the uploaded dataset. In brief, the software processes the raw images of the MACSima run, generates stitched images, and then allows downstream analysis including cell segmentation, cell gating, data normalization, dimension reduction plots (tSNE, UMAP), heat maps, distance analyses and cluster analyses, all of which are interactively linked together. The MACSima system is continuously evolving,  this is the second OMAP for the MACSima system. A representative dataset created using OMAP-21 can be found here:<a href="https://doi.org/10.5281/zenodo.7875937"> </a> 10.5281/zenodo.11281609 .

opencc-by-4.0Sep 2016View details →

Fig. 1 in Molecular identification of Atlantic goliath grouper Epinephelus itajara (Lichtenstein, 1822) (Perciformes: Epinephelidae) and related commercial species applying multiplex PCR

Fig. 1. Phylogrambasedontheamplificationofthesequence of the Cytochrome Oxidase I gene of the commerciallyexploited species of fishes of the families Epinephelidae and Polyprion americanus (Polyprionidae). The samples collected in the present study are underlined and those obtained from the GenBank database appear together with their accession numbers.

opencc-by-4.0Sep 2021View details →

Imaging Mass Cytometry Images (APP1) from: A SIMPLI (Single-cell Identification from MultiPLexed Images) approach for spatially resolved tissue phenotyping at single-cell resolution.

Four µm-thick sections were cut from the APP1 FFPE block with a microtome and used for staining with a panel of 26 antibodies targeting the main immune, stromal and epithelial cell populations of the gastrointestinal tract (Supplementary Table 2). The optimal dilution of each antibody in the panel was identified by staining and ablating FFPE appendix sections. The resulting images were reviewed by a mucosal immunologist (J.S.) and the dilution giving the best signal to background ratio was selected for each antibody (Supplementary Table 2). To perform the staining for IMC, slides were dewaxed after a one-hour incubation at 60°C, rehydrated and heat-induced antigen retrieval was performed with a pressure cooker in Antigen Retrieval Reagent-Basic (R&D Systems). Slides were incubated in a 10% BSA (Sigma), 0.1% Tween (Sigma), and 2% Kiovig (Shire Pharmaceuticals) Superblock Blocking Buffer (Thermo Fisher) blocking solution at room temperature for two hours. Each antibody was added to a primary antibody mix at the selected concentration in blocking solution and incubated overnight at 4°C. After two washes in PBS and PBS-0.1% Tween, the slides were treated with the DNA intercalator Cell-ID™ Intercalator-Ir (Fluidigm) (containing the two iridium isotopes 191Ir and 193Ir) 1.25 mM in a PBS solution. After a 30-minute incubation, the slides were washed once in PBS and once in MilliQ water and air-dried. The stained slides were then loaded in the Hyperion Imaging System (Fluidigm) imaging module to obtain light-contrast high resolution images of approximately four mm2. These images were used to select the ROI in each slide. For APP1, a one mm2 ROI containing a lymphoid follicle in its whole depth alongside a portion of lamina propria and of epithelium was selected. ROIs were ablated at a o µm/pixel resolution and 200 Hz frequency.

opencc-by-4.0Oct 2021View details →

Application of hyperbolic geometry of multiplex networks under layer link-based attacks

As real multilayer networks, we consider four networks. The multilayer networks are converted to multiplex networks by assuming that all layers have the same number of nodes (the maximum number of nodes of all layers). Explanation of these networks is as follow: <ol> <li>CS-Aarhus_multiplex [1] : The first network used in this study is a 5-layer multiplex network, named CS-Aarhus_multiplex, which has 61 nodes and 620 edges. The multiplex social network consists of five kinds of online and offline relationships (Facebook, Leisure, Work, Co-authorship, Lunch) between the employees of the Computer Science department at Aarhus.</li> <li>Data_malaria_PLOSCompBiology_2013 [2]: The second network is a 9-layer multiplex network, which consists of 307 nodes and 35306 edges. Networks of recombinant antigen genes from the human malaria parasite P. falciparum. Each of the 9 networks shares the same set of vertices but has different edges, corresponding to the 9 highly variable regions (HVRs) in the DBLa domain of the var protein. Nodes are var genes, and two genes are connected if they share a substring whose length is statistically significant.</li> <li>VICKERS CHAN 7th-GRADERS [3] : The third network is a 3-layer multiplex network, called VICKERS CHAN 7th-GRADERS, which includes 29 nodes and 740 edges. The data were collected by Vickers from 29 seventh-grade students in a school in Victoria, Australia. Students were asked to nominate their classmates on several relations including the three layers.</li> </ol>        4. FAO MULTIPLEX TRADE NETWORK [4]: The fourth network is a 364-layer multiplex network, which contains 214 nodes and 318346 edges. We consider different types of trade relationships among countries, obtained from FAO (Food and Agriculture Organization of the United Nations)

dryad40/100

Processed single cell data from CODEX multiplexed imaging of the human intestine

We performed CODEX (co-detection by indexing) multiplexed imaging on 64 sections of the human intestine (~16 mm2) from 8 donors (B004, B005, B006, B008, B009, B010, B011, and B012) using a panel of 57 oligonucleotide-barcoded antibodies. Subsequently, images underwent standard CODEX image processing (tile stitching, drift compensation, cycle concatenation, background subtraction, deconvolution, and determination of best focal plane), single cell segmentation, and column marker z-normalization by tissue. The outputs of this process were data frames of 2.6 million cells with 57 antibody fluorescence values quantified from each marker. Each cell has its cell type, cellular neighborhood, community of neighborhooods, and tissue unit defined with x, y coordinates representing pixel location in the original image. This is from a total of 25 cell types, 20 multicellular neighborhoods, 10 communities of neighborhoods, and 3 tissue segments that could be used to understand the cellular interactions, composition, and structure of the human intestine from the duodenum to the sigmoid colon and understand differences between different areas of the intestine. This data could be used as a healthy baseline to compare other single-cell datasets of the human intestine, particularly multiplexed imaging ones. The overall structure of the datasets is individual cells segmented out in each row. Columns MUC2 through CD161 are the markers used for clustering the cell types. These are the columns that are the values of the antibody staining the target protein within the tissue quantified at the single-cell level. This value is the per cell/area averaged fluorescent intensity that has subsequently been z normalized along each column as described above. OLFM4 through MUC6 were captured in the quantification but not used within the clustering of cell types. Other columns are explained in the table in the Usage Notes section below. Along with this main data table, there is also a donor metadata table that links the donor ids to clinical metadata such as: age, sex, race, BMI, history of diabetes, history of cancer, history of hypertension, and history of gastorintestinal disease. The raw imaging data can be found at (<a href="https://portal.hubmapconsortium.org/">https://portal.hubmapconsortium.org/</a>). We have created a landing page with links to all the raw dataset IDs and the HuBMAP ID for this Collection is HBM692.JRZB.356 and the DOI is:10.35079/HBM692.JRZB.356. This can be used to also pair it with the matched snRNAseq and snATACseq for each section of tissue.

opencc-zeroNov 2022View details →

opencc-by-4.0Sep 2022View details →

Multiplexed and scalable cellular phenotyping toward the standardized three-dimensional human neuropathology

The dataset for the publication. Cite the publication if you use the datasets.

opencc-by-4.0Sep 2022View details →

FIG. 33. Male terminalia, A. multiplex. A. Epandrium and cerci. B. Lateral view. C. Aedeagal apodeme. D. Paraphyses, lateral view. E. Posterior view. F in Revision Of The Nearctic Species Of The Genus Amiota Loew (Diptera: Drosophilidae)

FIG. 33. Male terminalia, A. multiplex. A. Epandrium and cerci. B. Lateral view. C. Aedeagal apodeme. D. Paraphyses, lateral view. E. Posterior view. F. Surstylus. (Am 1552, holotype).

Multiplexed histology of COVID-19 post-mortem lung samples - PROLONGED CASE 1 FOV2

Image-based data set of a post-mortem lung sample from a COVID-19 donor (PROLONGED CASE 1 FOV2) Each image shows the same field of view (FOV), sequentially stained with the depicted fluorescence-labelled antibodies, including surface proteins, intracellular proteins and transcription factors. Images contain 2024 x 2024 pixels and are generated using an inverted wide-field fluorescence microscope with a 20x objective, a lateral resolution of 325 nm and an axial resolution above 5 µm. Images have been normalized and intensities adjusted.

Multiplexed histology of COVID-19 post-mortem lung samples - PROLONGED CASE 1 FOV1

Image-based data set of a post-mortem lung sample from a COVID-19 donor (PROLONGED CASE 1 FOV1) Each image shows the same field of view (FOV), sequentially stained with the depicted fluorescence-labelled antibodies, including surface proteins, intracellular proteins and transcription factors. Images contain 2024 x 2024 pixels and are generated using an inverted wide-field fluorescence microscope with a 20x objective, a lateral resolution of 325 nm and an axial resolution above 5 µm. Images have been normalized and intensities adjusted.

Multiplexed histology of COVID-19 post-mortem lung samples - CONTROL CASE 1 FOV2

Image-based data set of a post-mortem lung sample from a non-COVID-related pneumonia donor (CONTROL CASE 1, FOV2) Each image shows the same field of view (FOV), sequentially stained with the depicted fluorescence-labelled antibodies, including surface proteins, intracellular proteins and transcription factors. Images contain 2024 x 2024 pixels and are generated using an inverted wide-field fluorescence microscope with a 20x objective, a lateral resolution of 325 nm and an axial resolution above 5 µm. Images have been normalized and intensities adjusted.

Multiplexed histology of COVID-19 post-mortem lung samples - CHRONIC CASE 2 FOV1

Image-based data set of a post-mortem lung sample from a COVID-19 donor (CHRONIC CASE 2 FOV1) Each image shows the same field of view (FOV), sequentially stained with the depicted fluorescence-labelled antibodies, including surface proteins, intracellular proteins and transcription factors. Images contain 2024 x 2024 pixels and are generated using an inverted wide-field fluorescence microscope with a 20x objective, a lateral resolution of 325 nm and an axial resolution above 5 µm. Images have been normalized and intensities adjusted.

Multiplexed histology of COVID-19 post-mortem lung samples - ACUTE CASE 2 FOV1

Image-based data set of a post-mortem lung sample from a COVID-19 donor (ACUTE CASE 2 FOV1) Each image shows the same field of view (FOV), sequentially stained with the depicted fluorescence-labelled antibodies, including surface proteins, intracellular proteins and transcription factors. Images contain 2024 x 2024 pixels and are generated using an inverted wide-field fluorescence microscope with a 20x objective, a lateral resolution of 325 nm and an axial resolution above 5 µm. Images have been normalized and intensities adjusted.

Multiplexed histology of COVID-19 post-mortem lung samples - PROLONGED CASE 5 FOV1

Image-based data set of a post-mortem lung sample from a COVID-19 donor (PROLONGED CASE 5 FOV1) Each image shows the same field of view (FOV), sequentially stained with the depicted fluorescence-labelled antibodies, including surface proteins, intracellular proteins and transcription factors. Images contain 2024 x 2024 pixels and are generated using an inverted wide-field fluorescence microscope with a 20x objective, a lateral resolution of 325 nm and an axial resolution above 5 µm. Images have been normalized and intensities adjusted.

Multiplexed histology of COVID-19 post-mortem lung samples - ACUTE CASE 3 FOV1

Image-based data set of a post-mortem lung sample from a COVID-19 donor (ACUTE CASE 3 FOV1) Each image shows the same field of view (FOV), sequentially stained with the depicted fluorescence-labelled antibodies, including surface proteins, intracellular proteins and transcription factors. Images contain 2024 x 2024 pixels and are generated using an inverted wide-field fluorescence microscope with a 20x objective, a lateral resolution of 325 nm and an axial resolution above 5 µm. Images have been normalized and intensities adjusted.

Multiplexed histology of COVID-19 post-mortem lung samples - ACUTE CASE 3 FOV2

Image-based data set of a post-mortem lung sample from a COVID-19 donor (ACUTE CASE 3 FOV2) Each image shows the same field of view (FOV), sequentially stained with the depicted fluorescence-labelled antibodies, including surface proteins, intracellular proteins and transcription factors. Images contain 2024 x 2024 pixels and are generated using an inverted wide-field fluorescence microscope with a 20x objective, a lateral resolution of 325 nm and an axial resolution above 5 µm. Images have been normalized and intensities adjusted.

Multiplexed histology of COVID-19 post-mortem lung samples - ACUTE CASE 2 FOV2

Image-based data set of a post-mortem lung sample from a COVID-19 donor (ACUTE CASE 2 FOV2) Each image shows the same field of view (FOV), sequentially stained with the depicted fluorescence-labelled antibodies, including surface proteins, intracellular proteins and transcription factors. Images contain 2024 x 2024 pixels and are generated using an inverted wide-field fluorescence microscope with a 20x objective, a lateral resolution of 325 nm and an axial resolution above 5 µm. Images have been normalized and intensities adjusted.