Fig 2: Tumor vascular perfusion is improved after vaccination against Gal1. a Representative immunostaining for blood vessels (CD31, red) and quantification of CD31-positive area (% of 10× field). B) FITC-LEL perfused blood vessels (green) and immunostaining for blood vessels (CD31, red). The proportion of FITC-LEL positive blood vessels was determined (FITC+ area/CD31+ area). The graphs illustrate mean values ± SD, and each dot represents an individual. Statistical differences between the groups were determined by Student’s t test (CD31+ cells, p = 0.3754 and FITC+ area/CD31+ area, p = 0.0131). Scale bar: 100 µm

Fig 3: Safranin O/Fast Green (A–D), galectin-1 (E–H), and galectin-3 (I–L) immunostaining of third carpal bone cartilage from sham-operated and osteochondral fragment joints from a representative horse 70 days post-injury. Superficial zone chondrocytes and some middle zone chondrocytes stain positively for galectin-3 (I,J) but not galectin-1 (E,F) in sham-operated joints. Cartilage fibrillation, proteoglycan loss and chondrone (arrow) formation is observed in cartilage from the osteochondral fragment joint (C,D). Chondrones stain positively for galectin-1 (G,H-arrow) and galectin-3 (K,L-arrow).

Fig 4: Dysregulated expression of Gal1 and specific glycosyltransferases in IBD.(A) Bioinformatic analysis of galectin expression (LGALS1, LGALS2, LGALS3, LGALS4, LGALS7, LGALS8, and LGALS9) in IBD datasets. (B) Expression of LGALS1, LGALS3, LGALS4, and LGALS9 analyzed by RT-qPCR in colon biopsies from healthy controls (n = 8), uninflamed (n = 13), and inflamed (n = 11) areas from colon biopsies of a local cohort of patients with IBD. (C) Bioinformatic analysis of glycosyltransferases relevant for Gal1 binding (ST6GAL1, MGAT5, and C2GNT1) in IBD datasets. (D) Expression of ST6GAL1, MGAT5, and C2GNT1 analyzed by RT-qPCR in colon biopsies from healthy controls (n = 6), uninflamed (n = 15), and inflamed (n = 14) areas from colon biopsies of a local cohort of patients with IBD. In (A) and (C), two-way analysis of variance (ANOVA) followed by Tukey’s posttest was used; colors in the heatmap depict the logarithm (base 2) of the fold change (log2FC), comparing uninflamed (U) and inflamed (I) areas of colon biopsies from patients with IBD with healthy controls (HC). In (B) and (D), one-way ANOVA followed by Tukey’s posttest was used. Unless otherwise stated, data are presented as means ± SEM. HC-U, healthy controls vs. uninflamed areas; HC-I, healthy controls vs. inflamed areas; U-I, uninflamed vs. inflamed areas. *P < 0.05 and **P < 0.01.

Fig 5: Modulation of intestinal inflammation via glycosylation-dependent pathways.(A) Intestinal inflammation in TNBS-induced colitis alters the extent of a(2,6) sialylation in CD8+CD69+ T cells. This altered glycophenotype makes these cells more sensitive to the immune inhibitory action of Gal1 and recalibrates T cell responses. (B) Role of T cell glycosylation in potentiating or attenuating intestinal inflammation in an adoptive transfer model of colitis. Compared to WT T cells, C2gnt1-/- T cells increase disease severity, generating an earlier onset and more pronounced weight loss. Thus, the absence of core 2 O-glycans on CD4+ T cells influences the development and severity of intestinal inflammation. On the other hand, St6gal1-/- T cells transferred to Rag2-/- mice induce a milder intestinal inflammation with a delayed onset, higher proportions of Tregs and lower IFN-? production.