Cyclic peptides containing the Arg-Gly-Asp (RGD) sequence have been shown to specifically bind the angiogenesis biomarker α V β 3 integrin. We report the synthesis, chemical characterization, and biological evaluation of two novel dimeric cyclic RGD-based molecular probes for the targeted imaging of α V β 3 activity (a radiolabeled version, 64Cu-NOTA-PEG4-cRGD2, for PET imaging, and a fluorescent version, FITC-PEG4-cRGD2, for in vitro work). We investigated the performance of this probe at the receptor, cell, organ, and whole-body levels, including its use to detect diabetes associated impairment of ischemia-induced myocardial angiogenesis. Both versions of the probe were found to be stable, demonstrated fast receptor association constants, and showed high specificity for α V β 3 in HUVECs (K d ~ 35 nM). Dynamic PET-CT imaging indicated rapid blood clearance via kidney filtration, and accumulation within α V β 3-positive infarcted myocardium. 64Cu-NOTA-PEG4-cRGD2 demonstrated a favorable biodistribution, slow washout, and excellent performance with respect to the quality of the PET-CT images obtained. Importantly, the ratio of probe uptake in infarcted heart tissue compared to normal tissue was significantly higher in non-diabetic rats than in diabetic ones. Overall, our probes are promising agents for non-invasive quantitative imaging of α V β 3 expression, both in vitro and in vivo.

Nearly all studies of angiogenesis have focused on uni-family ligand-receptor binding, e.g., VEGFs bind to VEGF receptors, PDGFs bind to PDGF receptors, etc. The discovery of VEGF-PDGFRs binding challenges this paradigm and calls for investigation of other ligand-receptor binding possibilities. We utilized surface plasmon resonance to identify and measure PDGF-to-VEGFR binding rates, establishing cut-offs for binding and non-binding interactions. We quantified the kinetics of the recent VEGF-A:PDGFRβ interaction for the first time with KD = 340 pM. We discovered new PDGF:VEGFR2 interactions with PDGF-AA:R2 KD = 530 nM, PDGF-AB:R2 KD = 110 pM, PDGF-BB:R2 KD = 40 nM, and PDGF-CC:R2 KD = 70 pM. We computationally predict that cross-family PDGF binding could contribute up to 96% of VEGFR2 ligation in healthy conditions and in cancer. Together the identification, quantification, and simulation of these novel cross-family interactions posits new mechanisms for understanding anti-angiogenic drug resistance and presents an expanded role of growth factor signaling with significance in health and disease.

Vascular endothelial growth factor A (VeGf-A) and its binding to VeGfRs is an important angiogenesis regulator, especially the earliest-known isoform, VeGf-A 165a. Yet several additional splice variants play prominent roles in regulating angiogenesis in health and in vascular disease, including VeGf-A 121 and an anti-angiogenic variant, VeGf-A 165b. few studies have attempted to distinguish these forms from their angiogenic counterparts, experimentally. previous studies of VeGf-A:VeGfR binding have measured binding kinetics for VeGfA 165 and VeGf-A 121 , but binding kinetics of the other two pro-and all anti-angiogenic splice variants are not known. We measured the binding kinetics for VeGf-A 165 ,-A 165b , and-A 121 with VEGFR1 and VEGF-R2 using surface plasmon resonance. We validated our methods by reproducing the known affinities between VEGF-A 165a :VEGFR1 and VEGF-A 165a :VEGFR2, 1.0 pM and 10 pM respectively, and validated the known affinity VEGF-A 121 :VEGFR2 as K D = 0.66 nM. We found that VeGf-A 121 also binds VEGFR1 with an affinity K D = 3.7 nM. We further demonstrated that the anti-angiogenic variant, VeGf-A 165b selectively prefers VEGFR2 binding at an affinity = 0.67 pM while binding VEGFR1 with a weaker affinity-K D = 1.4 nM. These results suggest that the − A 165b anti-angiogenic variant would preferentially bind VEGFR2. These discoveries offer a new paradigm for understanding VEGF-A, while further stressing the need to take care in differentiating the splice variants in all future VeGf-A studies. The vascular endothelial growth factors have been extensively studied as signaling molecules in angiogenesis 1,2 , and their signaling comprises several components. The mammalian VEGF family includes five homodimeric ligands: VEGF-A, VEGF-B, VEGF-C, VEGF-D, and placental growth factor (PlGF) 3. VEGF-A signal transduction unfolds following the pattern common to other tyrosine kinase receptors (RTKs), like the fibroblast growth factor (FGF) and platelet-derived growth factor (PDGF) families: (1) ligands bind a receptor monomer, promoting dimerization with another free receptor; (2) phosphorylation occurs at specific tyrosine residues depending on conformational changes allowed by the ligand-i.e. signaling is not directly coupled to binding, but dependent on ligand structure 4,5 ; (3) adaptor proteins bind these tyrosine residues and undergo phosphorylation 6 , and (4) phosphorylated adaptor proteins initiate effector signaling cascades 7 that can ultimately mediate cell-level responses such as cell migration, proliferation, and cell survival 8. The most well-studied ligand is VEGF-A 9. VEGF-A has a wide array of isoforms produced through alternative mRNA splicing 10,11 , including: VEGF-A 121 , VEGF-A 121 b, VEGF-A 145 , VEGF-A 145 b, VEGF-A 165 , VEGF-A 165 b, VEGF-A 183 , VEGF-A 189 , and VEGF-A 206 (Fig. 1), in addition to VEGF-A 111 , an abnormal splice variant induced by genotoxic stressors 12. Members of the VEGF-A xxx family are pro-angiogenic, whereas those designated as VEGF-A xxx b have been desc...

ZnO nanowires were synthesized on gold-coated glass substrates using the hydrothermal method. The effects of precursor concentration, substrate annealing and seeding on the morphology, dimension, and distribution of resultant nanowires were investigated. We found that the density of nanowires on substrates pre-seeded with ZnO nanoparticles is about two orders of magnitude greater than unseeded ones, while the dimension of ZnO nanowires for pre-seeded samples is much smaller than unseeded samples. In addition, we found that the fraction of substrate area covered by nanowires for unseeded samples is proportional to the precursor concentration, and proposed a simple nucleation model to explain this behavior. For pre-seeded substrates, ZnO nanowire density first increases with concentration and decreases as concentration exceeds 20 mM. We attribute this behavior to the competition for ions among the dense wires of varying length as well as the fusion of neighboring wires into larger ones.

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