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zeiss zen black software  (Carl Zeiss)


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    Structured Review

    Carl Zeiss zeiss zen black software
    Zeiss Zen Black Software, supplied by Carl Zeiss, used in various techniques. Bioz Stars score: 94/100, based on 41 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/deconvolution/ZEN+Module+Deconvolution/pm42869022-999-11-11
    Average 94 stars, based on 41 article reviews
    zeiss zen black software - by Bioz Stars, 2026-10
    94/100 stars

    Images

    Related Articles

    Software:

    Article Title: Defining the minimal structural requirements of DivIVA in filamentous Actinomycetota
    Article Snippet: To enable image deconvolution, point-spread functions (PSF) were determined using beads with excitation/emission wavelengths of 505/515 nm (green) and 633/660 nm (deep red) from the PS-Speck TM Microscope Point Source Kit (Invitrogen). .. The beads were imaged and PSFs calculated using the Deconvolution module in Zen software (Zeiss, ver 3.9). ..

    Article Title: PTPRS mediates invasion of tetanus neurotoxin into the central nervous system.
    Article Snippet: Confocal images were captured by Zeiss LSM 880 with Airyscan using 20X objective. .. Deconvolution was performed and a maximum intensity projection was constructed in Zeiss Zen Black software, and brightness and contrast were adjusted in ImageJ. ..

    Article Title: Essential and dispensable domains of DivIVA for walled growth in filamentous Actinomycetota
    Article Snippet: To enable image deconvolution, point-spread functions (PSF) were determined using beads with excitation/emission wavelengths of 505/515 nm (green) and 633/660 nm (deep red) from the PS-Speck Microscope Point Source Kit (Invitrogen). .. The beads were imaged and PSFs calculated using the Deconvolution module in Zen software (Zeiss, ver 3.9). ..

    Article Title: Essential and dispensable domains of DivIVA for walled growth in filamentous Actinomycetota.
    Article Snippet: To enable image deconvolution, point-spread functions (PSF) were determined using beads with excitation/emission wavelengths of 505/515 nm (green) and 633/660 nm (deep red) from the PS-Speck Microscope Point Source Kit (Invitrogen). .. The beads were imaged and PSFs calculated using the Deconvolution module in Zen software (Zeiss, ver 3.9). ..

    Article Title: Plakoglobin transmits tension across VE-cadherin for vascular leak formation and leukocyte diapedesis.
    Article Snippet: .. Zeiss LSM 980 Airyscan acquisitions were processed with Airyscan Joint Deconvolution processing module in ZEN blue software (Zeiss) to improve signal-to-noise and spatial resolution; LSM 880 images were used without further deconvolution. ..

    Article Title: Dynamic regulation of autophagy during Semliki Forest virus infection of neuroblastoma cells
    Article Snippet: The secondary antibody, anti-rabbit AlexaFluor488, was diluted with blocking buffer and incubated at room temperature for 40 min. Coverslips were mounted using FluoroshieldTM with a DAPI mounting medium (Sigma-Aldrich, UK). .. Imaging of multiple z -axis positions was performed using a Zeiss AxioImager M2 system, and images were deconvoluted using the Zeiss Zen software deconvolution module. .. For quantification of LC3-positive punctae, images of only the DyLight 550 channel were selected at random and spots were counted in ImageJ.

    Article Title: Dynamic regulation of autophagy during Semliki Forest virus infection of neuroblastoma cells.
    Article Snippet: The secondary antibody, anti- rabbit AlexaFluor488, was diluted with blocking buffer and incubated at room temperature for 40 min. Coverslips were mounted using FluoroshieldTM with a DAPI mounting medium (Sigma- Aldrich, UK). .. Imaging of multiple z- axis positions was performed using a Zeiss AxioImager M2 system, and images were deconvoluted using the Zeiss Zen software deconvolution module. ..

    Article Title: Plakoglobin transmits tension across VE-cadherin for vascular leak formation and leukocyte diapedesis
    Article Snippet: .. Zeiss LSM 980 Airyscan acquisitions were processed with Airyscan Joint Deconvolution processing module in ZEN blue software (Zeiss) to improve signal-to-noise and spatial resolution; LSM 880 images were used without further deconvolution. ..

    Construct:

    Article Title: PTPRS mediates invasion of tetanus neurotoxin into the central nervous system.
    Article Snippet: Confocal images were captured by Zeiss LSM 880 with Airyscan using 20X objective. .. Deconvolution was performed and a maximum intensity projection was constructed in Zeiss Zen Black software, and brightness and contrast were adjusted in ImageJ. ..

    Imaging:

    Article Title: Dynamic regulation of autophagy during Semliki Forest virus infection of neuroblastoma cells
    Article Snippet: The secondary antibody, anti-rabbit AlexaFluor488, was diluted with blocking buffer and incubated at room temperature for 40 min. Coverslips were mounted using FluoroshieldTM with a DAPI mounting medium (Sigma-Aldrich, UK). .. Imaging of multiple z -axis positions was performed using a Zeiss AxioImager M2 system, and images were deconvoluted using the Zeiss Zen software deconvolution module. .. For quantification of LC3-positive punctae, images of only the DyLight 550 channel were selected at random and spots were counted in ImageJ.

    Article Title: Dynamic regulation of autophagy during Semliki Forest virus infection of neuroblastoma cells.
    Article Snippet: The secondary antibody, anti- rabbit AlexaFluor488, was diluted with blocking buffer and incubated at room temperature for 40 min. Coverslips were mounted using FluoroshieldTM with a DAPI mounting medium (Sigma- Aldrich, UK). .. Imaging of multiple z- axis positions was performed using a Zeiss AxioImager M2 system, and images were deconvoluted using the Zeiss Zen software deconvolution module. ..



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    Proteostasis Therapeutics cibersort deconvolution
    Immune infiltration analysis. (A) Relative proportions of immune cell subpopulations in the control and sepsis groups. (B) Correlation matrix illustrating the associations between different immune cell types. Red indicates a positive correlation, and blue indicates a negative correlation; the intensity of the color and the size of the circles correspond to the strength of the correlation coefficient. (C) Comparison of immune cell abundance between the control and sepsis groups. Blue represents the control group, while yellow represents the sepsis group. (Note: These results are based on <t>CIBERSORT</t> <t>deconvolution</t> of bulk transcriptomic data). (D–G) Correlation analysis between the identified candidate genes and the infiltration levels of various immune cell types. *: p<0.05, **: P<0.01, ***: P<0.001, ns: not significant.
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    Immune infiltration analysis. (A) Relative proportions of immune cell subpopulations in the control and sepsis groups. (B) Correlation matrix illustrating the associations between different immune cell types. Red indicates a positive correlation, and blue indicates a negative correlation; the intensity of the color and the size of the circles correspond to the strength of the correlation coefficient. (C) Comparison of immune cell abundance between the control and sepsis groups. Blue represents the control group, while yellow represents the sepsis group. (Note: These results are based on <t>CIBERSORT</t> <t>deconvolution</t> of bulk transcriptomic data). (D–G) Correlation analysis between the identified candidate genes and the infiltration levels of various immune cell types. *: p<0.05, **: P<0.01, ***: P<0.001, ns: not significant.
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    Softworx Inc membrane deconvolution target
    a Example of <t>deconvolution</t> prediction with FM2FM. Top, input raw fluorescent membrane images (Raw FM 4-64); middle row, true deconvolved fluorescent membrane images (Deconvolved FM 4-64); bottom, FM2FM-predicted image. White squares mark regions zoomed in at right (Block 1 and Block 2). Diagonal dotted lines indicate profile traces in ( b ). Scale bars: full images, 10 µm; zoomed-in blocks, 5 µm. b Fluorescence profiles across the dotted lines in Block 1 (top) and Block 2 (bottom). Light blue, raw FM 4-64; orange, deconvolved FM 4-64; burgundy, FM2FM prediction. c , Structural similarity index measure (SSIM) between FM2FM predicted images and deconvolved images. The distribution of SSIM values across 74 image crops is shown. d Violin plots of cell width, length, surface area, volume, cross-sectional area, convex hull area, eccentricity and solidity calculated from deconvolved FM 4-64 images (orange) and FM2FM-predicted images (burgundy). The white dots and vertical lines within the violin plots represent the medians and standard deviations. P values from statistical comparisons between distributions (ANOVA or Kruskal test; see methods for details) are indicated in each panel. Twenty images (over 1000 cells) were processed and segmented with FMSeg. See the Methods for size calculation details.
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    a Example of <t>deconvolution</t> prediction with FM2FM. Top, input raw fluorescent membrane images (Raw FM 4-64); middle row, true deconvolved fluorescent membrane images (Deconvolved FM 4-64); bottom, FM2FM-predicted image. White squares mark regions zoomed in at right (Block 1 and Block 2). Diagonal dotted lines indicate profile traces in ( b ). Scale bars: full images, 10 µm; zoomed-in blocks, 5 µm. b Fluorescence profiles across the dotted lines in Block 1 (top) and Block 2 (bottom). Light blue, raw FM 4-64; orange, deconvolved FM 4-64; burgundy, FM2FM prediction. c , Structural similarity index measure (SSIM) between FM2FM predicted images and deconvolved images. The distribution of SSIM values across 74 image crops is shown. d Violin plots of cell width, length, surface area, volume, cross-sectional area, convex hull area, eccentricity and solidity calculated from deconvolved FM 4-64 images (orange) and FM2FM-predicted images (burgundy). The white dots and vertical lines within the violin plots represent the medians and standard deviations. P values from statistical comparisons between distributions (ANOVA or Kruskal test; see methods for details) are indicated in each panel. Twenty images (over 1000 cells) were processed and segmented with FMSeg. See the Methods for size calculation details.
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    Image Search Results


    Immune infiltration analysis. (A) Relative proportions of immune cell subpopulations in the control and sepsis groups. (B) Correlation matrix illustrating the associations between different immune cell types. Red indicates a positive correlation, and blue indicates a negative correlation; the intensity of the color and the size of the circles correspond to the strength of the correlation coefficient. (C) Comparison of immune cell abundance between the control and sepsis groups. Blue represents the control group, while yellow represents the sepsis group. (Note: These results are based on CIBERSORT deconvolution of bulk transcriptomic data). (D–G) Correlation analysis between the identified candidate genes and the infiltration levels of various immune cell types. *: p<0.05, **: P<0.01, ***: P<0.001, ns: not significant.

    Journal: Frontiers in Cellular and Infection Microbiology

    Article Title: A synergistic multi-omics approach: causal sepsis drivers identified in activated CD4 + T cells by single-cell RNA sequencing and Mendelian randomization

    doi: 10.3389/fcimb.2026.1749207

    Figure Lengend Snippet: Immune infiltration analysis. (A) Relative proportions of immune cell subpopulations in the control and sepsis groups. (B) Correlation matrix illustrating the associations between different immune cell types. Red indicates a positive correlation, and blue indicates a negative correlation; the intensity of the color and the size of the circles correspond to the strength of the correlation coefficient. (C) Comparison of immune cell abundance between the control and sepsis groups. Blue represents the control group, while yellow represents the sepsis group. (Note: These results are based on CIBERSORT deconvolution of bulk transcriptomic data). (D–G) Correlation analysis between the identified candidate genes and the infiltration levels of various immune cell types. *: p<0.05, **: P<0.01, ***: P<0.001, ns: not significant.

    Article Snippet: While we partially addressed this via CIBERSORT deconvolution to explore neutrophil-related correlations, their specific contribution to the ‘Metabolism–Proteostasis–Immunity’ axis may not be fully captured at the single-cell level.

    Techniques: Control, Comparison

    a Example of deconvolution prediction with FM2FM. Top, input raw fluorescent membrane images (Raw FM 4-64); middle row, true deconvolved fluorescent membrane images (Deconvolved FM 4-64); bottom, FM2FM-predicted image. White squares mark regions zoomed in at right (Block 1 and Block 2). Diagonal dotted lines indicate profile traces in ( b ). Scale bars: full images, 10 µm; zoomed-in blocks, 5 µm. b Fluorescence profiles across the dotted lines in Block 1 (top) and Block 2 (bottom). Light blue, raw FM 4-64; orange, deconvolved FM 4-64; burgundy, FM2FM prediction. c , Structural similarity index measure (SSIM) between FM2FM predicted images and deconvolved images. The distribution of SSIM values across 74 image crops is shown. d Violin plots of cell width, length, surface area, volume, cross-sectional area, convex hull area, eccentricity and solidity calculated from deconvolved FM 4-64 images (orange) and FM2FM-predicted images (burgundy). The white dots and vertical lines within the violin plots represent the medians and standard deviations. P values from statistical comparisons between distributions (ANOVA or Kruskal test; see methods for details) are indicated in each panel. Twenty images (over 1000 cells) were processed and segmented with FMSeg. See the Methods for size calculation details.

    Journal: Communications Biology

    Article Title: Deep-learning deconvolution and segmentation of fluorescent membranes for high-precision bacterial cell-size profiling

    doi: 10.1038/s42003-026-10303-y

    Figure Lengend Snippet: a Example of deconvolution prediction with FM2FM. Top, input raw fluorescent membrane images (Raw FM 4-64); middle row, true deconvolved fluorescent membrane images (Deconvolved FM 4-64); bottom, FM2FM-predicted image. White squares mark regions zoomed in at right (Block 1 and Block 2). Diagonal dotted lines indicate profile traces in ( b ). Scale bars: full images, 10 µm; zoomed-in blocks, 5 µm. b Fluorescence profiles across the dotted lines in Block 1 (top) and Block 2 (bottom). Light blue, raw FM 4-64; orange, deconvolved FM 4-64; burgundy, FM2FM prediction. c , Structural similarity index measure (SSIM) between FM2FM predicted images and deconvolved images. The distribution of SSIM values across 74 image crops is shown. d Violin plots of cell width, length, surface area, volume, cross-sectional area, convex hull area, eccentricity and solidity calculated from deconvolved FM 4-64 images (orange) and FM2FM-predicted images (burgundy). The white dots and vertical lines within the violin plots represent the medians and standard deviations. P values from statistical comparisons between distributions (ANOVA or Kruskal test; see methods for details) are indicated in each panel. Twenty images (over 1000 cells) were processed and segmented with FMSeg. See the Methods for size calculation details.

    Article Snippet: To compare model performance against the membrane deconvolution target (SoftWorx), we conducted qualitative assessments of output images' intensity profiles.

    Techniques: Membrane, Blocking Assay, Fluorescence