Галерея 1600502

Галерея 1600502

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1 McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15219, USA.; Department of Surgery, University of Pittsburgh, Pittsburgh, PA 15219, USA.

2 McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15219, USA.; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15219, USA.

3 Department of Cell Biology, University of Pittsburgh, Pittsburgh, PA 15219, USA.; Center of Biologic Imaging, University of Pittsburgh School of Medicine, Pittsburgh, PA 15219, USA.

4 McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15219, USA.; Department of Surgery, University of Pittsburgh, Pittsburgh, PA 15219, USA.; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15219, USA.

Luai Huleihel et al.

Sci Adv .

2016 .

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1 McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15219, USA.; Department of Surgery, University of Pittsburgh, Pittsburgh, PA 15219, USA.

2 McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15219, USA.; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15219, USA.

3 Department of Cell Biology, University of Pittsburgh, Pittsburgh, PA 15219, USA.; Center of Biologic Imaging, University of Pittsburgh School of Medicine, Pittsburgh, PA 15219, USA.

4 McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15219, USA.; Department of Surgery, University of Pittsburgh, Pittsburgh, PA 15219, USA.; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15219, USA.

( A to C ) Concentration of total nucleic acid and dsDNA per milligram dry weight of ECM scaffold from untreated (control) and proteinase K– or collagenase-treated samples of (A) UBM and ACell MatriStem (porcine UBM), (B) SIS and Cook Biotech Biodesign (porcine SIS), and (C) dermis and C.R. Bard XenMatrix (porcine dermis). Total nucleic acid concentration was assessed by UV absorbance at 260 nm. dsDNA concentration was assessed using PicoGreen dsDNA quantification reagent. Variability from isolation to isolation is depicted by SD. Data are means ± SD; n = 3 isolations per sample.
( A ) Nucleic acid extracted from untreated UBM (no digest) and pepsin-, proteinase K–, or collagenase-treated UBM was exposed to RNase A, DNase I, or no-nuclease treatment (control). ( B ) Electropherogram depicting the small RNA pattern of nucleic acid in fluorescence units (FU) before (top panel) and after (bottom panel) DNase I treatment. ( C ) Electropherogram depicting small RNA pattern from the indicated samples in FU. ( D ) A subset of nucleic molecules in biologic scaffolds is protected from nuclease degradation.
( A ) TEM imaging of MBVs identified in a UBM sheet stained positive with osmium (left panel), pepsin-treated UBM (middle panel), or proteinase K–treated UBM (right panel). ( B ) TEM imaging of MBVs identified in proteinase K–treated ECM from three commercial and three laboratory-produced scaffolds. Scale bars, 100 nm. ( C ) Validation of MBV size was measured with NanoSight. ( D ) Western blot analysis was performed on four exosomal surface markers: CD63, CD81, CD9, and Hsp70. Expression levels were not detectable as compared to porcine serum, human serum, and human bone marrow–derived mesenchymal stem cell controls. ( E ) MBV protein cargo signature was different between MBVs and hMSCs as evaluated using SDS-PAGE and silver stain imaging.
MBV small RNA sequencing analysis reveals specific miRNA signature between commercial products and comparable in-house products ( n = 1). ( A ) Numbers in each box represents different miRNAs within each sample. ( B and C ) Molecular and cellular functions (B) and physiological system development and function pathways (C) associated with identified miRNAs were generated using IPA. Each box represents the numbers of different miRNAs involved in each pathway.
MBVs isolated from UBM were labeled with Exo-Glow. ( A ) C2C12 cells were exposed to labeled MBVs for 4 hours. The left panel shows a representative image of successful labeling of MBVs before exposure to cell culture. The right panel represents exposure of labeled MBVs in C2C12 compared to the middle panel image (control). Green fluorescence represents DNA, whereas red fluorescence represents RNA MBV cargo that is successfully integrated with target cells. ( B ) Bone marrow was isolated from C57bl/6 mice and cultured in medium supplemented with macrophage colony-stimulating factor (M-CSF) to derive macrophages. Macrophages were treated with IFN-γ (20 ng/ml) and LPS (100 ng/ml) to derive M1 macrophages, IL-4 (20 ng/ml) to derive M2 macrophages, and isolated MBVs (5 μg/ml) from a UBM source. Macrophages were fixed and immunolabeled for the pan-macrophage marker (F4/80) and markers associated with the M1 (iNOS) and M2 (Fizz-1) phenotype. MBV-treated macrophages are predominantly F4/80 + Fizz-1 + macrophages, indicating an M2-like phenotype. Experiment was conducted with n = 2 samples with four technical replicates. ( C ) N1E-115 neuroblastoma cells were exposed to pepsin-solubilized UBM and MBVs. Five days (solubilized UBM) and three days (MBVs) after exposure, neurite extensions were visible in treated cells compared to control.

Costa A, Naranjo JD, Londono R, Badylak SF.
Costa A, et al.
Cold Spring Harb Perspect Med. 2017 Sep 1;7(9):a025676. doi: 10.1101/cshperspect.a025676.
Cold Spring Harb Perspect Med. 2017.

PMID: 28320826
Free PMC article.

Review.

Huleihel L, Bartolacci JG, Dziki JL, Vorobyov T, Arnold B, Scarritt ME, Pineda Molina C, LoPresti ST, Brown BN, Naranjo JD, Badylak SF.
Huleihel L, et al.
Tissue Eng Part A. 2017 Nov;23(21-22):1283-1294. doi: 10.1089/ten.TEA.2017.0102. Epub 2017 Jun 30.
Tissue Eng Part A. 2017.

PMID: 28580875
Free PMC article.

Dziki JL, Wang DS, Pineda C, Sicari BM, Rausch T, Badylak SF.
Dziki JL, et al.
J Biomed Mater Res A. 2017 Jan;105(1):138-147. doi: 10.1002/jbm.a.35894. Epub 2016 Sep 21.
J Biomed Mater Res A. 2017.

PMID: 27601305

Hussey GS, Pineda Molina C, Cramer MC, Tyurina YY, Tyurin VA, Lee YC, El-Mossier SO, Murdock MH, Timashev PS, Kagan VE, Badylak SF.
Hussey GS, et al.
Sci Adv. 2020 Mar 20;6(12):eaay4361. doi: 10.1126/sciadv.aay4361. eCollection 2020 Mar.
Sci Adv. 2020.

PMID: 32219161
Free PMC article.

Keane TJ, Swinehart IT, Badylak SF.
Keane TJ, et al.
Methods. 2015 Aug;84:25-34. doi: 10.1016/j.ymeth.2015.03.005. Epub 2015 Mar 16.
Methods. 2015.

PMID: 25791470

Review.

Palmulli R, Bresteau E, Raposo G, Montagnac G, van Niel G.
Palmulli R, et al.
Int J Mol Sci. 2023 Feb 12;24(4):3703. doi: 10.3390/ijms24043703.
Int J Mol Sci. 2023.

PMID: 36835115
Free PMC article.

Graça AL, Domingues RMA, Gomez-Florit M, Gomes ME.
Graça AL, et al.
Int J Mol Sci. 2023 Feb 9;24(4):3516. doi: 10.3390/ijms24043516.
Int J Mol Sci. 2023.

PMID: 36834925
Free PMC article.

Patel NJ, Ashraf A, Chung EJ.
Patel NJ, et al.
Bioengineering (Basel). 2023 Jan 19;10(2):136. doi: 10.3390/bioengineering10020136.
Bioengineering (Basel). 2023.

PMID: 36829629
Free PMC article.

Review.

Lu JH, Hsia K, Su CK, Pan YH, Ma H, Chiou SH, Lin CH.
Lu JH, et al.
J Funct Biomater. 2023 Feb 14;14(2):104. doi: 10.3390/jfb14020104.
J Funct Biomater. 2023.

PMID: 36826903
Free PMC article.

Xiang Z, Guan X, Ma Z, Shi Q, Panteleev M, Ataullakhanov FI.
Xiang Z, et al.
Biomater Biosyst. 2022 Jun 14;7:100055. doi: 10.1016/j.bbiosy.2022.100055. eCollection 2022 Aug.
Biomater Biosyst. 2022.

PMID: 36824486
Free PMC article.

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Biologic scaffold materials composed of extracellular matrix (ECM) have been used in a variety of surgical and tissue engineering/regenerative medicine applications and are associated with favorable constructive remodeling properties including angiogenesis, stem cell recruitment, and modulation of macrophage phenotype toward an anti-inflammatory effector cell type. However, the mechanisms by which these events are mediated are largely unknown. Matrix-bound nanovesicles (MBVs) are identified as an integral and functional component of ECM bioscaffolds. Extracellular vesicles (EVs) are potent vehicles of intercellular communication due to their ability to transfer RNA, proteins, enzymes, and lipids, thereby affecting physiologic and pathologic processes. Formerly identified exclusively in biologic fluids, the presence of EVs within the ECM of connective tissue has not been reported. In both laboratory-produced and commercially available biologic scaffolds, MBVs can be separated from the matrix only after enzymatic digestion of the ECM scaffold material, a temporal sequence similar to the functional activity attributed to implanted bioscaffolds during and following their degradation when used in clinical applications. The present study shows that MBVs contain microRNA capable of exerting phenotypical and functional effects on macrophage activation and neuroblastoma cell differentiation. The identification of MBVs embedded within the ECM of biologic scaffolds provides mechanistic insights not only into the inductive properties of ECM bioscaffolds but also into the regulation of tissue homeostasis.

Keywords:

Exosomes; Extracellular Matrix (ECM); Extracellular vesicles (EV); Matrix Bound Nano Vesicles (MBV); Microvesicles (MV).

Fig. 1. Comparison of nucleic acid concentration…
Fig. 1. Comparison of nucleic acid concentration from UBM, SIS, or dermis and their commercially…
Fig. 2. Enzymatic digestion of decellularized ECM…
Fig. 2. Enzymatic digestion of decellularized ECM scaffolds releases small RNA molecules.
Fig. 3. Identification of ECM-embedded MBVs.
Fig. 3. Identification of ECM-embedded MBVs.
( A ) TEM imaging of MBVs identified in…
Fig. 4. Identification of miRNA packaged within…
Fig. 4. Identification of miRNA packaged within MBVs.
MBV small RNA sequencing analysis reveals specific…
Fig. 5. MBVs are biologically active.
Fig. 5. MBVs are biologically active.
MBVs isolated from UBM were labeled with Exo-Glow. (…

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As nanofabrication technology progresses, the emerging metasurface has offered unique opportunities for holography, such as an increased data capacity and the realization of polarization-sensitive functionality. Multicolor three-dimensional (3D) meta-hologram imaging is one of the most pursued applications for meta-hologram not yet realized. How to reduce the cross-talk among different colors in broad bandwidth designs is a critical question. On the basis of the off-axis illumination method, we develop a novel way to overcome the cross-talk limitation and achieve multicolor meta-holography with a single type of plasmonic pixel. With this method, the usable data capacity can also be improved. It not only leads to a remarkable image quality, with a signal-to-noise ratio (SNR) five times better than that of the previous meta-hologram designs, but also paves the way to new meta-hologram devices, which mark an advance in the field of meta-holography. For example, a seven-color meta-hologram can be fabricated with a color gamut 1.39 times larger than that of the red, green, and blue (RGB) design. For the first time, a full-color meta-holographic image in the 3D space is also experimentally demonstrated. Our approach to expanding the information capacity of t
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