Samples
Specimens were sourced from a wound tissue bank repository, harvested and archived from four mixed breed mares included in a previous controlled and randomized study [21]. The study’s protocol was approved IACUC of the [masked for peer rewiew] and followed the guidelines of the Canadian Council on Animal Care (approval # 15-Rech-1811). Briefly, four full-thickness skin wounds were created, after sedation and local anesthesia, on one lateral mid-thoracic wall (two 15 cm2 wounds) and on the distal extremity of one thoracic limb (two 6 cm2 wounds) per horse (corresponding to the control wounds in the original study). Wounds were left to heal by second intention. Full-thickness wound samples were harvested with an 8 mm diameter biopsy punch from the edge of the 2 wounds on the limb and on the thoracic wall (alternatively) at day 1 (D1), D3, D8 and D17. D0 samples corresponded to normal skin obtained upon wound creation. Wounds and granulation tissue were photographed during the healing process and photographs were visually evaluated at the end of the study for granulation tissue elevation scoring according to the Bigbie et al. scale by a blinded board-certified veterinary surgeon. Elevation scores between 1 and 4 were attributed, score 1 corresponded to an elevation not exceeding the edges of the wound. Score 2 to an elevation at the same level as the wound edge. Score 3 corresponded to an elevation exceeding the edges of the wound. Score 4 corresponded to an elevation exceeding the edges of the wound and covering the epithelium [22]. The experimental model is shown in Fig. 1. A total of 31 specimens were harvested and archived, of which 26 were included in the current study based on inclusion and exclusion criteria (n = 26) (Fig. 1, Additional file 4: Table S1) [22]. Specimens included 3-4 mm of intact skin borders (subepidermal layer and the deep dermal layer) and 3-4 mm of the wound (granulation tissue) and were fixed in 10% formalin, dehydrated, paraffin-embedded and then cut into 4 µm sections [21].
Immunohistochemistry for mast cell staining
A rabbit polyclonal anti-CD117/c-kit antibody (1/87, #RB-9038, Thermo Fisher Scientific, Rockford, IL, USA) was incubated on the sections for one hour at room temperature [23]. An equine mast cell tumor was used as a positive control and rabbit serum replaced the primary antibody for the negative control (Fig. 4). The detailed protocol is presented in Additional file 1.
Image analysis and quantification
Immunostained cells were observed under light microscopy at 200x and scanned with the Panoptiq software program v.1. 4. 3 (ViewsIQ, Richmond, BC, CAN). Mast cell characterization and quantification was performed by 2 blinded observers in the wound samples harvested from a former study [21]. In the intact skin borders of the wound, mast cell quantification was performed in the subepidermal layer (0-296 µm under basal membrane) and in the deep dermal layer (296-1 184 µm) [18]. In the wound, mast cell quantification was performed in the granulation tissue. From each region, 5 high power fields (HPFs) were selected randomly. Mast cells were quantified using the newly-developed computer-based quantification method based on the ImageJ software program (U. S. National Institutes of Health, Bethesda, MD, USA). Mast cells in six of these specimens were also manually counted by an ACVP-certified pathologist and statistically compared to the ImageJ method. For both methods, identification of mast cells was based on CD117+ staining by immunohistochemistry and the presence of a nucleus. Particles non-specifically-stained and small foci of non-specific staining without a nucleus were manually (ImageJ) or visually (pathologist) subtracted and excluded from the count. For the ImageJ method, CD117+ cells with a cell area between 8 to 300 µm² were considered mast cells and were included in the count. For the pathologist-based manual counts, inclusion of mast cells in the counts was based on the following morphological parameters: cell shape, cell size and nucleus/cytoplasm ratio. The computer-based quantification method is shown in Fig. 5 and the complete protocol is described in Additional file 2. Additional file 3 provides details about the chosen area range. Mast cell numbers were then compared between limb and body wounds.
Statistical analysis
Statistical analysis was done with SPSS software program v.25 (IBM, Armonk, NY, USA) to validate the quantification method by calculating ICCs and Wilcoxon signed rank test for paired data, and with SAS software program v.9.3 (SAS Institute Inc, Cary, NC, USA) for mast cell quantification. A linear model for repeated measures was used to detect differences relating to time and to anatomical location of the wound (limb vs body). A p-value < 0.05 was considered statistically significant.