Expression of apoptotic and proliferation factors in gastric mucosa of patients with systemic sclerosis correlates with form of the disease

Connexin 37, 40, 43 and Pannexin 1 Expression in the Gastric Mucosa of Patients with Systemic Sclerosis

Systemic sclerosis (SSc) is an autoimmune disease characterized by fibrosis of the skin and internal organs. Although its pathogenesis is not fully understood, connexins (Cxs) and pannexins (Panx) could be involved in the process of fibrosis. We analyzed the protein expression of Cx37, Cx40, Cx43, and Panx1 in the gastric mucosa of patients with SSc and healthy volunteers, using immunofluorescence staining. Protein levels of Cx37 were slightly increased, while the levels of Cx40 were significantly decreased in the lamina propria of the gastric mucosa of SSc patients compared to the controls. The changes were proportional to SSc severity, with the most prominent changes found in patients with severe diffuse cutaneous SSc. No differences in Cx43 or Panx1 levels were found between the analyzed groups of samples. The lack of changes in Cx43 expression, which has been previously associated with fibrosis, could be due to the weak expression of Cx43 in the gastric mucosa in general. Further studies on full-thickness gastric biopsies containing muscle layers and animal SSc models are needed to fully elucidate the role of Cxs and Panxs in SSc-associated fibrosis.

Novel approach for quantification of multiple immunofluorescent signals using histograms and 2D plot profiling of whole-section panoramic images

We describe a novel approach for quantification and colocalization of immunofluorescence (IF) signals of multiple markers on high-resolution panoramic images of serial histological sections utilizing standard staining techniques and readily available software for image processing and analysis. Human gingiva samples stained with primary antibodies against the common leukocyte antigen CD45 and factors related to heparan sulfate glycosaminoglycans (HS GAG) were used. Expression domains and spatial gradients of IF signals were quantified by histograms and 2D plot profiles, respectively. The importance of histomorphometric profiling of tissue samples and IF signal thresholding is elaborated. This approach to quantification of IF staining utilizes pixel (px) counts and comparison of px grey value (GV) or luminance. No cell counting is applied either to determine the cellular content of a given histological section nor the number of cells positive to the primary antibody of interest. There is no selection of multiple Regions-Of-Interest (ROIs) since the entire histological section is quantified. Although the standard IF staining protocol is applied, the data output enables colocalization of multiple markers (up to 30) from a given histological sample. This can serve as an alternative for colocalization of IF staining of multiple primary antibodies based on repeating cycles of staining of the same histological section since those techniques require non standard staining protocols and sophisticated equipment that can be out of reach for small laboratories in academic settings. Combined with the data from ontological bases, this approach to quantification of IF enables creation of in silico virtual disease models.