Gebiss: an ImageJ plugin for the specification of ground truth and the performance evaluation of 3D segmentation algorithms.

Background: Image segmentation is a crucial step in quantitative microscopy that helps to define regions of tissues, cells or subcellular compartments. Depending on the degree of user interactions, segmentation methods can be divided into manual, automated or semi-automated approaches. 3D image stacks usually require automated methods due to their large number of optical sections. However, certain applications benefit from manual or semi-automated approaches. Scenarios include the quantification of 3D images with poor signal-to-noise ratios or the generation of so-called ground truth segmentations that are used to evaluate the accuracy of automated segmentation methods. Results: We have developed Gebiss; an ImageJ plugin for the interactive segmentation, visualisation and quantification of 3D microscopic image stacks. We integrated a variety of existing plugins for threshold-based segmentation and volume visualisation. Conclusions: We demonstrate the application of Gebiss to the segmentation of nuclei in live Drosophila embryos and the quantification of neurodegeneration in Drosophila larval brains. Gebiss was developed as a cross-platform ImageJ plugin and is freely available on the web at http://imaging.bii.a-star.edu.sg/projects/gebiss

Effects of Hydrogen Peroxide on Wound Healing in Mice in Relation to Oxidative Damage

10.1371/journal.pone.0049215PLoS ONE711

DEGRADATION AND ANNEALING OF ELECTRICALLY-STRESSED THIN OXIDE IN MOS DEVICES

Master'sMASTER OF ENGINEERIN

Wounding increases ERK1/2 and p38 phosphorylation which can be further increased by 166 mM H₂O₂ treatment.

<p>(A) Representative blots of wound tissues lysate collected 30 min after wounding. Skin denotes skin from non-wounded animals while control refers to wounds treated with PBS. (B) The density of phosphorylated ERK and pan-ERK and (C) phosphorylated p38 and pan p38 were normalized against α-tubulin re-probed from their respective blot. Results shown are mean ± S.E.M. (n = 4). Densitometry results were analyzed by 1-way ANOVA and test of significance between all column was determined using Tukey’s post hoc test. Only the comparison between 166 mM treated wounds and skin was statistically significant for both B and C. ** p<0.01.</p

Wounding increased lipid peroxidation and nitrative damage but not protein carbonylation.

<p>Levels of F₂-isoprostanes levels in skin and wounds were compared by normalizing against arachidonic acid (A) or tissue weight (B). Results shown are mean ± S.E.M, n = 5. Wounds were compared to skin using 1-way ANOVA with Dunnett’s post-hoc test. Asterisks denote level of significance when compared to skin. Control and H₂O₂ wounds were also compared against each other using 2-way ANOVA but the differences was not statistically significant. (C) Levels of arachidonic acid in skin and wound tissues. Results shown are mean ± S.E.M, n = 5. Wounds were compared to skin using 1-way ANOVA with Dunnett’s post-hoc test. Asterisks denote level of significance when compared to skin. Control and H₂O₂ wounds were also compared against each other using 2-way ANOVA but the differences was not statistically significant. (D) Levels of protein carbonyls in wounds were compared to intact skin and expressed as fold change. The results shown are the mean fold change ± S.E.M. No difference in the levels of protein carbonyl was observed in control wounds and 166 mM H₂O₂ treated wounds. (E) Comparison of 3-nitrotyrosine level in skin and wounds. Results shown are mean ± S.E.M., n = 5. The 3-nitrotyrosine levels of skin were compared to control wounds or H₂O₂ treated wounds and analyzed with 1-way ANOVA followed by Dunnett’s post-hoc test. Levels of 3-nitrotyrosine were significantly higher at day 6 after wounding. Levels of 3-nitrotyrosine in control and 166 mM H₂O₂ treated wounds were also compared using 2-way ANOVA and the differences were not statistically significant. *p<0.05, ** p<0.01, ***p<0.001.</p

Low concentrations of H₂O₂ increased wound angiogenesis.

<p>Paraffin sections from day 6 wounds were stained for CD31 using an immunohistochemical method. Representative photomicrograph of (A) control, (B) 166 mM H₂O₂ and (C) 10 mM H₂O₂ treated wounds are shown. (D) The number of brown lumen-like structures within the neodermis was counted in a single blinded fashion and analyzed using 1-way ANOVA followed by Dunnett’s multiple comparison test with control. Graph shown is the mean ± S.E.M, n = 6–7, *** p<0.001.</p

High concentrations of H₂O₂ retard connective tissue formation.

<p>Paraffin sections from day 6 wounds were stained with the Masson-Goldner trichrome stain as described in material and method. Connective tissues are stained green. Fibrin, eschar and cytoplasm are stained red. Nuclei are stained dark brown. Representative images for control (A,D) 10 mM (B, E) and 166 mM (C, F) treated wounds are shown. Images A-C are at 100X magnification while D-F are at 200X magnification. (G) Quantification of the fraction of pixels that are stained green. The number of pixels stained green within the neodermis at 100X magnification was quantified using a custom software. The area quantified is outlined with the dashed line. Results were analyzed using 1-way ANOVA followed by Dunnett’s multiple comparison test with control. Graph shown is the mean ± S.E.M. n = 6–7, *** p<0.001.</p

High concentrations of H₂O₂ increase levels of MMP-8 in wounds.

<p>Western blot analysis of wound tissues lysate collected 6 days after wounding. Each lane represents a sample from a different animal. (A) Representative blot of MMP-8. (B) Densitometry analysis of MMP-8 normalized against α-tubulin re-probed from their respective blot. Results are mean ± S.E.M. (n = 4) and were analyzed using 1-way ANOVA followed by Tukey multiple comparison among all the columns. ** p<0.01 (C) Representative blot of MMP-9. (D) Densitometry analysis of MMP-9 normalized against α-tubulin re-probed from their respective blot. Results are mean ± S.E.M. (n = 4), p values for 1-way ANOVA is p = 0.13.</p