Positively charged oligo[poly(ethylene glycol) fumarate] (OPF+) scaffolds loaded with Schwann cells bridge spinal cord injury (SCI) lesions and support axonal regeneration in rat. The regeneration achieved is not sufficient for inducing functional recovery. Attempts to increase regeneration would benefit from understanding the effects of the scaffold and transplanted cells on lesion environment. We conducted morphometric and stereological analysis of lesions in rats implanted with OPF+ scaffolds with or without loaded Schwann cells 1, 2, 3, 4, and 8 weeks after thoracic spinal cord transection. No differences were found in collagen scarring, cyst formation, astrocyte reactivity, myelin debris, or chondroitin sulfate proteoglycan (CSPG) accumulation. However, when scaffold-implanted animals were compared with animals with transection injuries only, these barriers to regeneration were significantly reduced, accompanied by increased activated macrophages/microglia. This distinctive and regeneration permissive tissue reaction to scaffold implantation was independent of Schwann cell transplantation. Although the tissue reaction was beneficial in the short term, we observed a chronic fibrotic host response, resulting in scaffolds surrounded by collagen at 8 weeks. This study demonstrates that an appropriate biomaterial scaffold improves the environment for regeneration. Future targeting of the host fibrotic response may allow increased axonal regeneration and functional recovery.
Positively charged oligo[poly(ethylene glycol) fumarate] (OPF+) scaffolds loaded with Schwann cells bridge spinal cord injury (SCI) lesions and support axonal regeneration in rat. The regeneration achieved is not sufficient for inducing functional recovery. Attempts to increase regeneration would benefit from understanding the effects of the scaffold and transplanted cells on lesion environment. We conducted morphometric and stereological analysis of lesions in rats implanted with OPF+ scaffolds with or without loaded Schwann cells 1, 2, 3, 4, and 8 weeks after thoracic spinal cord transection. No differences were found in collagen scarring, cyst formation, astrocyte reactivity, myelin debris, or chondroitin sulfate proteoglycan (CSPG) accumulation. However, when scaffold-implanted animals were compared with animals with transection injuries only, these barriers to regeneration were significantly reduced, accompanied by increased activated macrophages/microglia. This distinctive and regeneration permissive tissue reaction to scaffold implantation was independent of Schwann cell transplantation. Although the tissue reaction was beneficial in the short term, we observed a chronic fibrotic host response, resulting in scaffolds surrounded by collagen at 8 weeks. This study demonstrates that an appropriate biomaterial scaffold improves the environment for regeneration. Future targeting of the host fibrotic response may allow increased axonal regeneration and functional recovery.
MRS is an analytical approach used for both quantitative and qualitative analysis of human body metabolites. The accurate and robust quantification capability of proton MRS ( H-MRS) enables the accurate estimation of living tissue metabolite concentrations. However, such methods can be efficiently employed for quantification of metabolite concentrations only if the overlapping nature of metabolites, existing static field inhomogeneity and low signal-to-noise ratio (SNR) are taken into consideration. Representation of H-MRS signals in the time-frequency domain enables us to handle the baseline and noise better. This is possible because the MRS signal of each metabolite is sparsely represented, with only a few peaks, in the frequency domain, but still along with specific time-domain features such as distinct decay constant associated with T relaxation rate. The baseline, however, has a smooth behavior in the frequency domain. In this study, we proposed a quantification method using continuous wavelet transformation of H-MRS signals in combination with sparse representation of features in the time-frequency domain. Estimation of the sparse representations of MR spectra is performed according to the dictionaries constructed from metabolite profiles. Results on simulated and phantom data show that the proposed method is able to quantify the concentration of metabolites in H-MRS signals with high accuracy and robustness. This is achieved for both low SNR (5 dB) and low signal-to-baseline ratio (-5 dB) regimes.
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