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nis elements deconvolution software  (Nikon)


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    Structured Review

    Nikon nis elements deconvolution software
    Nis Elements Deconvolution Software, supplied by Nikon, used in various techniques. Bioz Stars score: 99/100, based on 39515 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/nis+elements+deconvolution+software/NIS-Elements/bio_rxiv__64898__2026__03__05__709814-155-4-8
    Average 99 stars, based on 39515 article reviews
    nis elements deconvolution software - by Bioz Stars, 2026-09
    99/100 stars

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    Related Articles

    Software:

    Article Title: A Yeast Two-Hybrid Protein Domain Screening Approach for Ebola Virus-Human Protein Interactions Identifies PABPC1 as a Host Factor Required for Replication
    Article Snippet: Z-stack images were acquired using a Nikon Spatial Array Confocal (NSPARC) Ti2 microscope using a 60 X oil immersion objective equipped with 640, 561, 488, and 405 lasers. .. Images were deconvolved using NIS Elements Deconvolution software (Nikon, Tokyo, Japan) and processed using Imaris software (Oxford Instruments, Concord, MA). .. HeLa cells were seeded, incubated overnight and transfected with 5 nM PABPC1 or AllStars scramble siRNA (Qiagen) using Lipofectamine RNAiMax reagent (Invitrogen).

    Article Title: Phenotype, function, and differentiation potential of human monocyte subsets
    Article Snippet: Cells were fixed in 4% paraformaldehyde, permeabilized with a saponin solution, and stained with Hoescht dye and fluorescently labeled phalloidin (both from Molecular Probes), and mAbs against β-tubulin (BD) and vinculin (Abcam). .. Cell morphology was captured on an Eclipse TiE epifluorescent microscope with NIS Elements deconvolution software (Nikon). .. Sorted monocyte subsets were cultured overnight (18 hours) in RPMI-1640 with each agonist from the Human Toll-like receptor (TLR) 1–9 kit according to protocols supplied by the manufacturer (InvivoGen), with use of the following working concentrations: pam3CSK4 (1μg/mL), HKLM (10 8 cells/mL), poly(I:C) (10 μg/mL), LPS (1 μg/mL), flagellin (10 μg/mL), FSL-1 (1μg/mL), imiquimod (10 μg/mL), ssRNA40 (10 μg/mL), ODN2006 (5 μM).

    Article Title: Phenotype, function, and differentiation potential of human monocyte subsets.
    Article Snippet: Cells were fixed in 4% paraformaldehyde, permeabilized with a saponin solution, and stained with Hoescht dye and fluorescently labeled phalloidin (both from Molecular Probes), PLOS ONE | https://doi.org/10.1371/journal.pone.0176460 April 26, 2017 3 / 20 and mAbs against β-tubulin (BD) and vinculin (Abcam). .. Cell morphology was captured on an Eclipse TiE epifluorescent microscope with NIS Elements deconvolution software (Nikon). .. TLR stimulation and luminex assays of cytokine production Sorted monocyte subsets were cultured overnight (18 hours) in RPMI-1640 with each agonist from the Human Toll-like receptor (TLR) 1–9 kit according to protocols supplied by the manufacturer (InvivoGen), with use of the following working concentrations: pam3CSK4 (1μg/ mL), HKLM (108 cells/mL), poly(I:C) (10 μg/mL), LPS (1 μg/mL), flagellin (10 μg/mL), FSL-1 (1μg/mL), imiquimod (10 μg/mL), ssRNA40 (10 μg/mL), ODN2006 (5 μM).

    Article Title: A protein-proximity screen reveals Ebola virus co-opts the mRNA decapping complex through the scaffold protein EDC4
    Article Snippet: .. For super resolution microscopy experiments examining colocalization between VP35 and decapping components, z-stack images were taken on Nikon Spatial Array Confocal (NSPARC) Ti2 microscope using a 60x oil immersion objective and 561, 488, and 405 lasers, with 0.5 μm separating each z-slice, and deconvolved using NIS Elements Deconvolution software (Nikon, Tokyo, Japan). ..

    Microscopy:

    Article Title: Phenotype, function, and differentiation potential of human monocyte subsets
    Article Snippet: Cells were fixed in 4% paraformaldehyde, permeabilized with a saponin solution, and stained with Hoescht dye and fluorescently labeled phalloidin (both from Molecular Probes), and mAbs against β-tubulin (BD) and vinculin (Abcam). .. Cell morphology was captured on an Eclipse TiE epifluorescent microscope with NIS Elements deconvolution software (Nikon). .. Sorted monocyte subsets were cultured overnight (18 hours) in RPMI-1640 with each agonist from the Human Toll-like receptor (TLR) 1–9 kit according to protocols supplied by the manufacturer (InvivoGen), with use of the following working concentrations: pam3CSK4 (1μg/mL), HKLM (10 8 cells/mL), poly(I:C) (10 μg/mL), LPS (1 μg/mL), flagellin (10 μg/mL), FSL-1 (1μg/mL), imiquimod (10 μg/mL), ssRNA40 (10 μg/mL), ODN2006 (5 μM).

    Article Title: Phenotype, function, and differentiation potential of human monocyte subsets.
    Article Snippet: Cells were fixed in 4% paraformaldehyde, permeabilized with a saponin solution, and stained with Hoescht dye and fluorescently labeled phalloidin (both from Molecular Probes), PLOS ONE | https://doi.org/10.1371/journal.pone.0176460 April 26, 2017 3 / 20 and mAbs against β-tubulin (BD) and vinculin (Abcam). .. Cell morphology was captured on an Eclipse TiE epifluorescent microscope with NIS Elements deconvolution software (Nikon). .. TLR stimulation and luminex assays of cytokine production Sorted monocyte subsets were cultured overnight (18 hours) in RPMI-1640 with each agonist from the Human Toll-like receptor (TLR) 1–9 kit according to protocols supplied by the manufacturer (InvivoGen), with use of the following working concentrations: pam3CSK4 (1μg/ mL), HKLM (108 cells/mL), poly(I:C) (10 μg/mL), LPS (1 μg/mL), flagellin (10 μg/mL), FSL-1 (1μg/mL), imiquimod (10 μg/mL), ssRNA40 (10 μg/mL), ODN2006 (5 μM).

    Article Title: A protein-proximity screen reveals Ebola virus co-opts the mRNA decapping complex through the scaffold protein EDC4
    Article Snippet: .. For super resolution microscopy experiments examining colocalization between VP35 and decapping components, z-stack images were taken on Nikon Spatial Array Confocal (NSPARC) Ti2 microscope using a 60x oil immersion objective and 561, 488, and 405 lasers, with 0.5 μm separating each z-slice, and deconvolved using NIS Elements Deconvolution software (Nikon, Tokyo, Japan). ..

    Super-Resolution Microscopy:

    Article Title: A protein-proximity screen reveals Ebola virus co-opts the mRNA decapping complex through the scaffold protein EDC4
    Article Snippet: .. For super resolution microscopy experiments examining colocalization between VP35 and decapping components, z-stack images were taken on Nikon Spatial Array Confocal (NSPARC) Ti2 microscope using a 60x oil immersion objective and 561, 488, and 405 lasers, with 0.5 μm separating each z-slice, and deconvolved using NIS Elements Deconvolution software (Nikon, Tokyo, Japan). ..



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    Fig. 1 | Implementation and benchmarking of Deconwolf. a, Schematic Deconwolf workflow. WSI, whole-slide image. b,c, In silico generated microtubule images before (ground truth) (b) and after adding artificial noise to simulate a real image (c). Maximum z-projection is shown. d, MSE after deconvolving the image in c using the default Deconwolf mode with scaled heavy ball15 acceleration (DW_SHB), or Deconwolf based on the classic Richardson–Lucy <t>deconvolution</t> method (DW_RL)2,3. The dashed vertical lines indicate the number of iterations needed to reach the minimum MSE. e, As in c after deconvolution with Deconwolf (DW) using default settings. it, number of iterations. t, deconvolution time measured on an 8-Core AMD Ryzen 7 3700X machine. f, As in c using DeconvolutionLab2 (DL2) with default settings at 115 iterations. g, As in
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    Fig. 1 | Implementation and benchmarking of Deconwolf. a, Schematic Deconwolf workflow. WSI, whole-slide image. b,c, In silico generated microtubule images before (ground truth) (b) and after adding artificial noise to simulate a real image (c). Maximum z-projection is shown. d, MSE after deconvolving the image in c using the default Deconwolf mode with scaled heavy ball15 acceleration (DW_SHB), or Deconwolf based on the classic Richardson–Lucy <t>deconvolution</t> method (DW_RL)2,3. The dashed vertical lines indicate the number of iterations needed to reach the minimum MSE. e, As in c after deconvolution with Deconwolf (DW) using default settings. it, number of iterations. t, deconvolution time measured on an 8-Core AMD Ryzen 7 3700X machine. f, As in c using DeconvolutionLab2 (DL2) with default settings at 115 iterations. g, As in
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    Fig. 1 | Implementation and benchmarking of Deconwolf. a, Schematic Deconwolf workflow. WSI, whole-slide image. b,c, In silico generated microtubule images before (ground truth) (b) and after adding artificial noise to simulate a real image (c). Maximum z-projection is shown. d, MSE after deconvolving the image in c using the default Deconwolf mode with scaled heavy ball15 acceleration (DW_SHB), or Deconwolf based on the classic Richardson–Lucy <t>deconvolution</t> method (DW_RL)2,3. The dashed vertical lines indicate the number of iterations needed to reach the minimum MSE. e, As in c after deconvolution with Deconwolf (DW) using default settings. it, number of iterations. t, deconvolution time measured on an 8-Core AMD Ryzen 7 3700X machine. f, As in c using DeconvolutionLab2 (DL2) with default settings at 115 iterations. g, As in
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    Image Search Results


    Fig. 1 | Implementation and benchmarking of Deconwolf. a, Schematic Deconwolf workflow. WSI, whole-slide image. b,c, In silico generated microtubule images before (ground truth) (b) and after adding artificial noise to simulate a real image (c). Maximum z-projection is shown. d, MSE after deconvolving the image in c using the default Deconwolf mode with scaled heavy ball15 acceleration (DW_SHB), or Deconwolf based on the classic Richardson–Lucy deconvolution method (DW_RL)2,3. The dashed vertical lines indicate the number of iterations needed to reach the minimum MSE. e, As in c after deconvolution with Deconwolf (DW) using default settings. it, number of iterations. t, deconvolution time measured on an 8-Core AMD Ryzen 7 3700X machine. f, As in c using DeconvolutionLab2 (DL2) with default settings at 115 iterations. g, As in

    Journal: Nature methods

    Article Title: Deconwolf enables high-performance deconvolution of widefield fluorescence microscopy images.

    doi: 10.1038/s41592-024-02294-7

    Figure Lengend Snippet: Fig. 1 | Implementation and benchmarking of Deconwolf. a, Schematic Deconwolf workflow. WSI, whole-slide image. b,c, In silico generated microtubule images before (ground truth) (b) and after adding artificial noise to simulate a real image (c). Maximum z-projection is shown. d, MSE after deconvolving the image in c using the default Deconwolf mode with scaled heavy ball15 acceleration (DW_SHB), or Deconwolf based on the classic Richardson–Lucy deconvolution method (DW_RL)2,3. The dashed vertical lines indicate the number of iterations needed to reach the minimum MSE. e, As in c after deconvolution with Deconwolf (DW) using default settings. it, number of iterations. t, deconvolution time measured on an 8-Core AMD Ryzen 7 3700X machine. f, As in c using DeconvolutionLab2 (DL2) with default settings at 115 iterations. g, As in

    Article Snippet: Visual inspection of the images in the original dataset showed densely packed clouds of fluorescent dots in different colors inside each nucleus, which could be only partially resolved by applying the commercial deconvolution software (Nikon NIS Elements AR, v5.02.0) incorporated in the OligoFISSEQ image processing pipeline (Fig. 6c).

    Techniques: In Silico, Generated

    Fig. 5 | Deconwolf enables robust detection of individual transcripts in low-magnification smFISH images. a, Breast adenocarcinoma tissue section stained with an smFISH probe targeting MKI67 transcripts (white) and imaged on a widefield microscope using a ×20 air objective, after deconvolution with Deconwolf (DW). Maximum z-projection is shown. Blue, DNA. Scale bars, 200 μm in the large left panel; 10 μm in the two small panels on the right. b,c, Zoom-in of the regions (R1 and R2) marked by the white dashed squares in a. Scale bars, 10 μm. d, Left plot: probability density function (PDF) of smFISH dot fluorescence

    Journal: Nature methods

    Article Title: Deconwolf enables high-performance deconvolution of widefield fluorescence microscopy images.

    doi: 10.1038/s41592-024-02294-7

    Figure Lengend Snippet: Fig. 5 | Deconwolf enables robust detection of individual transcripts in low-magnification smFISH images. a, Breast adenocarcinoma tissue section stained with an smFISH probe targeting MKI67 transcripts (white) and imaged on a widefield microscope using a ×20 air objective, after deconvolution with Deconwolf (DW). Maximum z-projection is shown. Blue, DNA. Scale bars, 200 μm in the large left panel; 10 μm in the two small panels on the right. b,c, Zoom-in of the regions (R1 and R2) marked by the white dashed squares in a. Scale bars, 10 μm. d, Left plot: probability density function (PDF) of smFISH dot fluorescence

    Article Snippet: Visual inspection of the images in the original dataset showed densely packed clouds of fluorescent dots in different colors inside each nucleus, which could be only partially resolved by applying the commercial deconvolution software (Nikon NIS Elements AR, v5.02.0) incorporated in the OligoFISSEQ image processing pipeline (Fig. 6c).

    Techniques: Staining, Microscopy, Fluorescence