Problem#3Mimicking nature by codelivery of stimulant and inhibitor

And djm analyzed data and wwy and djm wrote the paper

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: D.J.M. analyzed data; and W.W.Y. and D.J.M. wrote the paper. The authors declare no conflict of interest. This article is a PNAS Direct Submission. 1 To whom correspondence should be addressed. E-mail: mooneyd@seas.harvard.edu. This article contains supporting information online at www.pnas.org/lookup/suppl/ doi:10.1073/pnas.1001192107/-/DCSupplemental. PNAS ∣ October 19, 2010 ∣ vol. 107 ∣ no. 42 ∣ 17933–17938 APPLIED BIOLOGICAL SCIENCES Nature frequently utilizes opposing factors to create a stable activator gradient to robustly control pattern formation. This study employs a biomimicry approach, by delivery of both angiogenic and antiangiogenic factors from spatially restricted zones of a synthetic polymer to achieve temporally stable and spatially restricted angiogenic zones in vivo. The simultaneous release of the two spatially separated agents leads to a spatially sharp angiogenic region that is sustained over 3 wk. Further, the contradictory action of the two agents leads to a stable level of proangiogenic stimulation in this region, in spite of significant variations in the individual release rates over time. The resulting spatially restrictive and temporally sustained profiles of active signaling allow the creation of a spatially heterogeneous and functional vasculature. radioactivity of each scaffold layer (n ¼ 5) was measured with a WIZARD Automatic Gamma Counter (PerkinElmer) prior to incubation at 37 °C in 2 mL of PBS. At specific measurement time points, release solutions were measured using the Gamma counter and the scaffolds were placed in fresh release solutions. The cumulative protein release from the scaffolds at each time point was normalized as a percentage of total protein incorporated. Mathematical Model. A computational model was generated to depict the concentration profiles of free VEGF, anti-VEGF, and VEGF complexed with anti-VEGF. This model accounted for diffusion, release from scaffolds, binding kinetics, and protein degradation. The governing equations of the VEGF and anti-VEGF concentrations inside the scaffold and underlying muscle were ∂c1 ¼ D1 ∇2 c1 − k1 c1 þ f 1 − kon c1 c2 þ koff c3 ; ∂t ∂c2 ¼ D2 ∇2 c2 − k2 c2 þ f 2 − kon c1 c2 þ koff c3 ; ∂t ∂c3 ¼ D3 ∇2 c3 þ kon c1 c2 − koff c3 ; ∂t where ci ¼ concentration fi ¼  ci ðx;y;z;t ¼ 0Þ ¼ 0; release function; 0; ∀i;x;y;z inside scaffold inside muscle  1 free VEGF i ¼ 2 free anti-VEGF 3 VEGF-anti-VEGF complex −7 D1 ¼ 7 × 10 scm ¼ Effective interstitial diffusion coefficient of VEGF165 (20–22). −9 2 D2 ¼ 3.2 × 10 scm ¼ Effective interstitial diffusion coefficient of IgG Ab (23, 24). −9 2 D3 ¼ 2.9 × 10 scm ¼ Effective interstitial diffusion coefficient of complex (25). k1 ¼ 2.31 × 10−4 s−1 ¼ Degradation rate of VEGF (20). k2 ¼ k3 ¼ 1.34 × 10−6 s−1 ¼ Degradation rate of free anti-VEGF and VEGFanti-VEGF complex (26, 27). kon ¼ 5.5 × 104 M−1 s−1 ¼ VEGF-anti-VEGF complex formation r...
View Full Document

Ask a homework question - tutors are online