Oxford Instruments drgquant pipeline

<t>DRGquant</t> Validation. A) Shows a z projection of an Iba1 stained image stack, where each individual macrophage was identified by an exert observer. Scale bar is 20 μm. Reconstructions of macrophages from A where each object is depicted with a different color when analyzed with B) Imaris C) Otsu thresholding replacing UNET Model in the DRGquant pipeline and D) DRGquant. E) Correctly identified macrophages shown as percent of total macrophages identified by an expert. F) Incorreclty identified macrophages characterized as objects detected that were not determined to be macrophages or objects identified as macrophages that were not detected and displayed as the count per image stack. G) Under segmented macrophages were characterized as multiple macrophages identified as one object and displayed as count per image stack. H) Over segmented macrophages were multiple objects detected that were identified as a single macrophage by an expert and displayed as count per image stack (one way ANOVA with Tukey correction for multiple comparisons; *P < 0.05, ** P < 0.01, ns=not significant).

Drgquant Pipeline, supplied by Oxford Instruments, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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DRGquant Validation. A) Shows a z projection of an Iba1 stained image stack, where each individual macrophage was identified by an exert observer. Scale bar is 20 μm. Reconstructions of macrophages from A where each object is depicted with a different color when analyzed with B) Imaris C) Otsu thresholding replacing UNET Model in the DRGquant pipeline and D) DRGquant. E) Correctly identified macrophages shown as percent of total macrophages identified by an expert. F) Incorreclty identified macrophages characterized as objects detected that were not determined to be macrophages or objects identified as macrophages that were not detected and displayed as the count per image stack. G) Under segmented macrophages were characterized as multiple macrophages identified as one object and displayed as count per image stack. H) Over segmented macrophages were multiple objects detected that were identified as a single macrophage by an expert and displayed as count per image stack (one way ANOVA with Tukey correction for multiple comparisons; *P < 0.05, ** P < 0.01, ns=not significant).

Journal: Journal of neuroscience methods

Article Title: DRGquant: A new modular AI-based pipeline for 3D analysis of the DRG

doi: 10.1016/j.jneumeth.2022.109497

Figure Lengend Snippet: DRGquant Validation. A) Shows a z projection of an Iba1 stained image stack, where each individual macrophage was identified by an exert observer. Scale bar is 20 μm. Reconstructions of macrophages from A where each object is depicted with a different color when analyzed with B) Imaris C) Otsu thresholding replacing UNET Model in the DRGquant pipeline and D) DRGquant. E) Correctly identified macrophages shown as percent of total macrophages identified by an expert. F) Incorreclty identified macrophages characterized as objects detected that were not determined to be macrophages or objects identified as macrophages that were not detected and displayed as the count per image stack. G) Under segmented macrophages were characterized as multiple macrophages identified as one object and displayed as count per image stack. H) Over segmented macrophages were multiple objects detected that were identified as a single macrophage by an expert and displayed as count per image stack (one way ANOVA with Tukey correction for multiple comparisons; *P < 0.05, ** P < 0.01, ns=not significant).

Article Snippet: The time it took to run the full dataset was 3.87 s for DRGquant with Otsu thresholding, 33 s for the full DRGquant pipeline, and 50 min to analyze using Imaris.

Techniques: Staining

LPS induced macrophage activation in our pipeline comparison. (A) Representative images of macrophages 24 h after intrathecal saline or LPS in wild type C57BL/6 mice and Ccr2 −/− mice. Scale bar 20 μm. (B) LPS induces an increase in the volume over macrophages over total volume of the sample in both wild type and Ccr2 −/− mice, Analysis performed with Imaris. (C) Automated analysis with our pipeline shows consistent results with Imaris. (D) No difference is observed between PV and NPV macrophages in macrophage numbers. (E) Using DRGquant we can see that individual macrophages increase in size following IT-LPS in both wild type and CCR2KO mice (one way ANOVA with Tukey correction for multiple comparisons; *P < 0.05, ** P < 0.01, ***P < 0.001, **** P < 0.0001, ns = not significant, number of mice: Wt_saline=6, Wt_LPS=6, CCR2 −/ _saline=3,CCR2 −/− _LPS=3, 2 DRGs per mouse).

Journal: Journal of neuroscience methods

Article Title: DRGquant: A new modular AI-based pipeline for 3D analysis of the DRG

doi: 10.1016/j.jneumeth.2022.109497

Figure Lengend Snippet: LPS induced macrophage activation in our pipeline comparison. (A) Representative images of macrophages 24 h after intrathecal saline or LPS in wild type C57BL/6 mice and Ccr2 −/− mice. Scale bar 20 μm. (B) LPS induces an increase in the volume over macrophages over total volume of the sample in both wild type and Ccr2 −/− mice, Analysis performed with Imaris. (C) Automated analysis with our pipeline shows consistent results with Imaris. (D) No difference is observed between PV and NPV macrophages in macrophage numbers. (E) Using DRGquant we can see that individual macrophages increase in size following IT-LPS in both wild type and CCR2KO mice (one way ANOVA with Tukey correction for multiple comparisons; *P < 0.05, ** P < 0.01, ***P < 0.001, **** P < 0.0001, ns = not significant, number of mice: Wt_saline=6, Wt_LPS=6, CCR2 −/ _saline=3,CCR2 −/− _LPS=3, 2 DRGs per mouse).

Article Snippet: The time it took to run the full dataset was 3.87 s for DRGquant with Otsu thresholding, 33 s for the full DRGquant pipeline, and 50 min to analyze using Imaris.

Techniques: Activation Assay, Comparison, Saline

Uptake of fluorophore labeled dextran. (A) Representative sum z stack images of naïve (top) and 24 h following IT LPS injected (bottom) whole mount DRGs stained with Iba1 for macrophages, dextran, and CD31 for blood vessels. Scale bar 20 μm (B) Mean intensity of dextran within individual macrophages in the DRGs of naïve or IT LPS injected mice (one way ANOVA with Tukey post hoc test, means and individual macrophages are shown; **** P < 0.0001). (C) 3D reconstruction of single macrophage with 3D ROI of DRGquant output outline in green and dextran in blue, showing subcellular spatial resolution. Scale bar is 5 μm.

Journal: Journal of neuroscience methods

Article Title: DRGquant: A new modular AI-based pipeline for 3D analysis of the DRG

doi: 10.1016/j.jneumeth.2022.109497

Figure Lengend Snippet: Uptake of fluorophore labeled dextran. (A) Representative sum z stack images of naïve (top) and 24 h following IT LPS injected (bottom) whole mount DRGs stained with Iba1 for macrophages, dextran, and CD31 for blood vessels. Scale bar 20 μm (B) Mean intensity of dextran within individual macrophages in the DRGs of naïve or IT LPS injected mice (one way ANOVA with Tukey post hoc test, means and individual macrophages are shown; **** P < 0.0001). (C) 3D reconstruction of single macrophage with 3D ROI of DRGquant output outline in green and dextran in blue, showing subcellular spatial resolution. Scale bar is 5 μm.

Article Snippet: The time it took to run the full dataset was 3.87 s for DRGquant with Otsu thresholding, 33 s for the full DRGquant pipeline, and 50 min to analyze using Imaris.

Techniques: Labeling, Injection, Staining

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